TY - JOUR TI - Editorial AU - Rouskas, George AU - Verikoukis, Christos T2 - IEEE Networking Letters AB - We are proud to present this inaugural issue of the IEEE Networking Letters. This issue is the culmination of an effort that started two years ago and introduces a new publication that rounds out the IEEE portfolio of journals in the broad field of communications and networking. Specifically, IEEE Networking Letters is intended to complement its sister publications, IEEE Communications Letters and IEEE Wireless Communications Letters, by providing a forum for letter-style journal papers reporting on research advances in all layers of the networking stack above the physical layer. DA - 2019/3// PY - 2019/3// DO - 10.1109/LNET.2019.2897895 VL - 1 IS - 1 SP - 1-1 UR - https://doi.org/10.1109/LNET.2019.2897895 ER - TY - BOOK TI - Answering queries using views AU - Afrati, Foto AU - Chirkova, Rada DA - 2019/// PY - 2019/// PB - Morgan & Claypool Publishers SN - 1681734648 9781681734644 1681734621 9781681734620 ER - TY - CONF TI - Coordinating Capacity Negotiations in Semiconductor Manufacturing AU - Bansal, A. AU - Uzsoy, R. AU - Kempf, K.G. T2 - CASE 2019 - International Conference on Automation Science and Engineering C2 - 2019/8// C3 - Proceedings of the IEEE Conference on Automation Science and Engineering CY - Vancouver, British Columbia, Canada DA - 2019/8// PY - 2019/8// ER - TY - SOUND TI - Impact of Part Scheduling Policy on Additive Manufacturing Production System Performance AU - Kapadia, M.S. AU - Starly, B. AU - Thomas, A. AU - Uzsoy, R. AU - Warsing, D. DA - 2019/5// PY - 2019/5// ER - TY - SOUND TI - Simulation Optimization For Planning Product Transitions In Semiconductor Manufacturing Facilities AU - Manda, A.B. AU - Uzsoy, R. DA - 2019/5// PY - 2019/5// ER - TY - SOUND TI - Conic Reformulation of Production Planning Models with Clearing Functions AU - Gopalswamy, K. AU - Uzsoy, R. DA - 2019/5// PY - 2019/5// ER - TY - ER - TY - ER - TY - JOUR TI - Iterative combinatorial auctions for managing product transitions in semiconductor manufacturing AU - Bansala, Ankit AU - Uzsoy, Reha AU - Kempf, Karl T2 - IISE TRANSACTIONS AB - Successful management of product transitions in the semiconductor industry requires effective coordination of manufacturing and product development activities. Manufacturing units must meet demand for current products while also allocating capacity to product development units for prototype fabrication that will support timely introduction of new products into high-volume manufacturing. Knowledge of detailed operational constraints and capabilities is only available within each unit, precluding the use of a centralized planning model with complete information of all units. However, the decision support tools used by the individual units offer the possibility of a decentralized decision framework that uses these local models as components to rapidly obtain mutually acceptable, implementable solutions. We develop Iterative Combinatorial Auctions (ICAs) that achieve coordinated decisions for all units to maximize the firm’s profit while motivating all units to share information truthfully. Computational results show that the ICA that uses column generation to update prices outperforms that using subgradient search, obtaining near-optimal corporate profit in low CPU times. DA - 2019/// PY - 2019/// DO - 10.1080/24725854.2019.1651951 KW - Product transitions KW - Lagrangian relaxation KW - column generation KW - iterative combinatorial auctions KW - semiconductor manufacturing ER - TY - ER - TY - JOUR TI - What Makes a Location into a “Favorable Habitat” under Changing Climate and Environmental Conditions? A Pilot Study Focused on Exploring the Differences between Natural and Non-natural Habitats using Airborne LiDAR AU - Mohan, M AU - Catts, G P AU - Vaughan, B AU - Roise, J P AU - Silva, C A AU - McCarter, J B AU - Jat, P. AU - Wan Mohd Jaafar, W S AU - Gopan, G AU - Abdul Maulud, K N T2 - IOP Conference Series: Earth and Environmental Science AB - Recovery plans supported by conservation models are critical for the protection of endangered species. For developing these models, parameters are most commonly extracted via field survey or remote sensing based methods. However, at times, these models get narrowed down to specific habitat features associated with naturally occurring ecosystems, and thereby fail to detect suitable non-natural habitats that the animals have gotten adapted to in recent years - as a survival mechanism to cope up with the dynamic climate and environmental conditions. As a first step to address this issue, we considered the case of Red-cockaded woodpecker (RCW) species and undertook a pilot study to explore the characteristics of non-natural locations that make it favorable for RCW nesting. On exploring the differences in habitat characteristics of natural and non-natural ecosystems - by employing airborne laser scanning data and logistic regression analysis method - we identified new prominent forest attributes and their variations for each habitat types. Based on our findings, we provide fruitful interpretations, recommendations and encourage discussions on less-studied conservation aspects and hope to stretch the horizons of ongoing biodiversity conservation efforts in the wake of global environmental change. DA - 2019/2/15/ PY - 2019/2/15/ DO - 10.1088/1755-1315/228/1/012018 VL - 228 SP - 012018 J2 - IOP Conf. Ser.: Earth Environ. Sci. OP - SN - 1755-1315 UR - http://dx.doi.org/10.1088/1755-1315/228/1/012018 DB - Crossref ER - TY - JOUR TI - Fast computation of global solutions to the single-period unit commitment problem AU - Lu, Cheng AU - Deng, Zhibin AU - Fang, Shu-Cherng AU - Jin, Qingwei AU - Xing, Wenxun T2 - Journal of Combinatorial Optimization DA - 2019/11/29/ PY - 2019/11/29/ DO - 10.1007/s10878-019-00489-9 VL - 11 J2 - J Comb Optim LA - en OP - SN - 1382-6905 1573-2886 UR - http://dx.doi.org/10.1007/s10878-019-00489-9 DB - Crossref KW - Mixed-integer pogramming KW - Quadratic programming KW - Branch-and-bound algorithm ER - TY - JOUR TI - Probabilistic sensitivity analysis on Markov models with uncertain transition probabilities: an application in evaluating treatment decisions for type 2 diabetes AU - Zhang, Yuanhui AU - Wu, Haipeng AU - Denton, Brian T. AU - Wilson, James R. AU - Lobo, Jennifer M. T2 - Health Care Management Science DA - 2019/3// PY - 2019/3// DO - 10.1007/S10729-017-9420-8 VL - 22 IS - 1 SP - 34–52 SN - 1386-9620 1572-9389 UR - http://dx.doi.org/10.1007/S10729-017-9420-8 KW - Robustness and sensitivity analysis KW - Markov model KW - Transition probability matrices KW - Medical decision-making KW - Monte Carlo simulation ER - TY - BOOK TI - Introduction to Partial Differential Equations AU - Li, Z. AU - Norris, L. DA - 2019/// PY - 2019/// DO - 10.1142/12052 SP - 220 PB - World Scientific Publishing Company ER - TY - JOUR TI - DESEN: Specification of Sociotechnical Systems via Patterns of Regulation and Control AU - Kafalı, Özgür AU - Ajmeri, Nirav AU - Singh, Munindar P. T2 - ACM Transactions on Software Engineering and Methodology (TOSEM) AB - We address the problem of engineering a sociotechnical system (STS) with respect to its stakeholders’ requirements. We motivate a two-tier STS conception composed of a technical tier that provides control mechanisms and describes what actions are allowed by the software components, and a social tier that characterizes the stakeholders’ expectations of each other in terms of norms. We adopt agents as computational entities, each representing a different stakeholder. Unlike previous approaches, our framework, D ESEN , incorporates the social dimension into the formal verification process. Thus, D ESEN supports agents potentially violating applicable norms—a consequence of their autonomy. In addition to requirements verification, D ESEN supports refinement of STS specifications via design patterns to meet stated requirements. We evaluate D ESEN at three levels. We illustrate how D ESEN carries out refinement via the application of patterns on a hospital emergency scenario. We show via a human-subject study that a design process based on our patterns is helpful for participants who are inexperienced in conceptual modeling and norms. We provide an agent-based environment to simulate the hospital emergency scenario to compare STS specifications (including participant solutions from the human-subject study) with metrics indicating social welfare and norm compliance, and other domain dependent metrics. DA - 2019/2// PY - 2019/2// DO - 10.1145/3365664 VL - 29 IS - 1 SP - 1–50 KW - Agent-oriented software engineering KW - norms KW - security and privacy requirements KW - design patterns KW - simulation ER - TY - CONF TI - Supple: Multiagent Communication Protocols with Causal Types AU - Günay, Akın AU - Chopra, Amit K. AU - Singh, Munindar P. C2 - 2019/5// C3 - Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) DA - 2019/5// SP - 781–789 PB - IFAAMAS SN - 9781450363099 UR - https://eprints.lancs.ac.uk/id/eprint/131277/ ER - TY - RPRT TI - A Problem from Genetics and the Singular Value Decomposition AU - Campbell, S.L. AU - Campbell, M.A. DA - 2019/1// PY - 2019/1// DO - 10.13140/RG.2.2.29979.92964 M3 - Preprint ER - TY - JOUR TI - Impact of Scheduling Policies on the Performance of an Additive Manufacturing Production System AU - Kapadia, Maaz Saleem AU - Starly, Binil AU - Thomas, Alec AU - Uzsoy, Reha AU - Warsing, Donald T2 - Procedia Manufacturing AB - We study the impact of scheduling policies on the cycle time and throughput of an Additive Manufacturing (AM) facility. Orders for irregularly shaped parts with specified due dates and surface quality requirements arrive randomly at the facility. The parts are fabricated in one of several AM build chambers, followed by post-processing operations based on surface finishing requirements. We combine a part placement heuristic with different scheduling policies (FIFO, Earliest Due Date) to allocate parts to AM build chambers and lay out the parts within the chambers to approximately optimize delivery performance. Simulation experiments using an Iterative Optimization-based Simulation (IOS) model integrating a simulation engine (implemented in SIMIO) with a computational engine (implemented in MATLAB) show that the scheduling policies have a significant impact on cycle time and order lateness. Selection and peer review under the responsibility of ICPR25 International Scientific & Advisory and Organizing Committee members. DA - 2019/// PY - 2019/// DO - 10.1016/j.promfg.2020.01.388 VL - 39 SP - 447-456 J2 - Procedia Manufacturing LA - en OP - SN - 2351-9789 UR - http://dx.doi.org/10.1016/j.promfg.2020.01.388 DB - Crossref KW - Iterative Optimization-based Simulation KW - Additive Manufacturing KW - Genetic Algorithm ER - TY - JOUR TI - Integrated traditional and additive manufacturing production profitability model AU - Nagulpelli, Kimberly S. AU - King, Russell E. AU - Warsing, Donald T2 - 47TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 47) AB - Production decision-makers now have a choice of production technologies. Decision-makers are familiar with “Traditional Manufacturing” (TM) technologies. In favorable circumstances, emerging “Additive Manufacturing” (AM) technology now offers more flexibility to modify the manufacturing environment and improve production logistics efficiency to enhance profits over a production schedule. This paper presents research, process methodologies, and a practical approach to the profit-based economic decision-modelling for production planning in a manufacturing environment resourced with both TM and AM technologies. The research identifies a framework for production leaders and managers to implement efficiency measures while adapting or refining AM production in an existing TM production environment. The paper also outlines opportunities for future research toward the objective of optimizing production technology assignments within a mixed-resource manufacturing environment. DA - 2019/// PY - 2019/// DO - 10.1016/j.promfg.2019.06.121 VL - 34 SP - 619-630 SN - 2351-9789 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85072391087&partnerID=MN8TOARS KW - additive manufacturing KW - traditional manufacturing KW - cost model KW - profit model KW - decision support KW - production planning ER - TY - JOUR TI - The use of Bayesian inference in the characterization of materials and thin films AU - Jones, Jacob L. AU - Broughton, Rachel AU - Iamsasri, Thanakorn AU - Fancher, Chris M. AU - Wilson, Alyson G. AU - Reich, Brian AU - Smith, Ralph C. T2 - ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES DA - 2019/// PY - 2019/// DO - 10.1107/S0108767319097940 VL - 75 SP - A211-A211 SN - 2053-2733 ER - TY - JOUR TI - DERIVATIVE-BASED GLOBAL SENSITIVITY ANALYSIS FOR MODELS WITH HIGH-DIMENSIONAL INPUTS AND FUNCTIONAL OUTPUTS AU - Cleaves, Helen L. AU - Alexanderian, Alen AU - Guy, Hayley AU - Smith, Ralph C. AU - Yu, Meilin T2 - SIAM JOURNAL ON SCIENTIFIC COMPUTING AB - We present a framework for derivative-based global sensitivity analysis (GSA) for models with high-dimensional input parameters and functional outputs. We combine ideas from derivative-based GSA, random field representation via Karhunen--Loève expansions, and adjoint-based gradient computation to provide a scalable computational framework for computing the proposed derivative-based GSA measures. We illustrate the strategy for a nonlinear ODE model of cholera epidemics and for elliptic PDEs with application examples from geosciences and biotransport. DA - 2019/// PY - 2019/// DO - 10.1137/19M1243518 VL - 41 IS - 6 SP - A3524-A3551 SN - 1095-7197 KW - global sensitivity analysis KW - DGSMs KW - functional Sobol' indices KW - Karhunen-Loeve expansions ER - TY - JOUR TI - Clearer than Mud: Extending Manufacturer Usage Description (MUD) for Securing IoT Systems AU - Singh, Simran AU - Atrey, Ashlesha AU - Sichitiu, Mihail L. AU - Viniotis, Yannis T2 - INTERNET OF THINGS - ICIOT 2019 AB - Internet of Things (IoT) devices, expected to increase exponentially over the next several years, are easy targets for attackers. To make these devices more secure, the IETF’s draft of Manufacturer Usage Description (MUD) provides a means for the manufacturer of an IoT device to specify its intended purpose and communication patterns in terms of access control lists (ACLs), thereby defining the device’s normal behaviour. However, MUD may not be sufficient to comprehensively capture the normal behaviour specification, as it cannot incorporate variable operational settings that depend on the environment. Further, MUD only supports limited features. Our approach overcomes these limitations by allowing the administrator to define the normal behaviour by choosing combinations from a wider set of features that includes physical layer parameters, values of packet headers, and flow statistics. We developed and implemented a learning-based system that captures and demodulates wireless packets from IoT devices over a period of time, extracts the features specified in the normal behaviour specification, and uses a learning algorithm to create a normal model of each device. Our implementation also enforces these normal models by detecting violations and taking appropriate actions, in terms of ACLs on an Internet Gateway, against the misbehaving devices. Hence, our framework makes the specification tighter and clearer than what is possible with MUD alone, thereby making IoT systems more secure. DA - 2019/// PY - 2019/// DO - 10.1007/978-3-030-23357-0_4 VL - 11519 SP - 43-57 SN - 1611-3349 KW - Internet of Things KW - Security KW - Manufacturer Usage Description (MUD) KW - Clustering ER - TY - CONF TI - Time series anomaly detection from a markov chain perspective AU - Vasheghani Farahani, I. AU - Chien, A. AU - King, R.E. AU - Kay, M.G. AU - Klenz, B. AB - This paper introduces a new method for the pattern-wise anomaly detection problem, which aims to find segments whose behaviors are different from the rest of the segments in the time series (as opposed to finding a single data-point in classic anomaly detection problems). An important motivation for studying this problem is to find anomalies whose data-points are within the normal range but they create an unusual pattern. To this end, normal characteristics of the data are found by clustering the overlapping subsequences of the training dataset and analyzing their orders by Markov chains. The trained model is used to assess how well the testing dataset suits the baseline behavior. The designed anomaly detection framework is capable of discovering unusual patterns in both streaming data (online) and stored data (offline). The performance of the methodology is evaluated by applying it to three datasets from different fields: a medical dataset (electrocardiogram), a utility usage dataset, and a New York City taxi demand dataset. The detected anomaly in the medical data agrees with the results of the studies in the literature. A domain expert confirmed the accuracy of the results for the utility usage data, and the anomalies of the New York City taxi demand data referred to major US holidays. C2 - 2019/// C3 - Proceedings - 18th IEEE International Conference on Machine Learning and Applications, ICMLA 2019 DA - 2019/// DO - 10.1109/ICMLA.2019.00170 SP - 1000-1007 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85080858601&partnerID=MN8TOARS ER - TY - JOUR TI - An Augmented IB Method & Analysis for Elliptic BVP on Irregular Domains AU - Li, Zhilin AU - Dong, Baiying AU - Tong, Fenghua AU - Wang, Weilong T2 - CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES AB - The immersed boundary method is well-known, popular, and has had vast areas of applications due to its simplicity and robustness even though it is only first order accurate near the interface. In this paper, an immersed boundary-augmented method has been developed for linear elliptic boundary value problems on arbitrary domains (exterior or interior) with a Dirichlet boundary condition. The new method inherits the simplicity, robustness, and first order convergence of the IB method but also provides asymptotic first order convergence of partial derivatives. Numerical examples are provided to confirm the analysis. DA - 2019/// PY - 2019/// DO - 10.32604/cmes.2019.04635 VL - 119 IS - 1 SP - 63-72 SN - 1526-1506 KW - Immersed boundary method KW - augmented approach KW - convergence KW - derivative computing ER - TY - JOUR TI - Iterative-Learning-Control-Based Tracking for Asteroid Close-Proximity Operations AU - Long, Jiateng AU - Wu, Fen T2 - JOURNAL OF GUIDANCE CONTROL AND DYNAMICS AB - No AccessEngineering NotesIterative-Learning-Control-Based Tracking for Asteroid Close-Proximity OperationsJiateng Long and Fen WuJiateng LongBeijing Institute of Technology, 100081 Beijing, People’s Republic of China*Ph.D. Candidate, School of Aerospace Engineering; .Search for more papers by this author and Fen WuNorth Carolina State University, Raleigh, North Carolina 27695†Professor, Department of Mechanical and Aerospace Engineering; (Corresponding Author).Search for more papers by this authorPublished Online:2 Jan 2019https://doi.org/10.2514/1.G003884SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations ShareShare onFacebookTwitterLinked InRedditEmail About References [1] Kawaguchi J. I., Fujiwara A. and Uesugi T., “Hayabusa–Its Technology and Science Accomplishment Summary and Hayabusa-2,” Acta Astronautica, Vol. 62, Nos. 10–11, 2008, pp. 639–647. doi:https://doi.org/10.1016/j.actaastro.2008.01.028 AASTCF 0094-5765 CrossrefGoogle Scholar[2] Chesley S. R. and et al., “Orbit and Bulk Density of the OSIRIS-REx Target Asteroid (101955) Bennu,” Icarus, Vol. 235, June 2014, pp. 5–22. doi:https://doi.org/10.1016/j.icarus.2014.02.020 ICRSA5 0019-1035 CrossrefGoogle Scholar[3] Tricarico P. and Sykes M. 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All rights reserved. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-3884 to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp. TopicsAsteroidsAstronomyCelestial Coordinate SystemCelestial MechanicsControl TheoryFeedback ControlGuidance, Navigation, and Control SystemsPlanetary Science and ExplorationPlanetsSolar PhysicsSpace Science and TechnologySpacecraft GuidanceSpacecraft Guidance and Control KeywordsIterative Learning ControlAsteroidsSpacecraft TrajectoriesFeedback ControlNumerical SimulationSolar RadiationConvergence AnalysisRight AscensionSolar SystemOrbital InclinationAcknowledgmentsJ. Long would like to thank the support of the Graduate Technological Innovation Project of Beijing Institute of Technology 2017CX10028 and the China Scholarship Council for sponsoring this research. The authors greatly appreciate the Associate Editor and anonymous reviewers for their patient and rigorous review with high standards, which are of significant benefit for the quality improvement of this paper.PDF Received12 June 2018Accepted18 November 2018Published online2 January 2019 DA - 2019/5// PY - 2019/5// DO - 10.2514/1.G003884 VL - 42 IS - 5 SP - 1195-1203 SN - 1533-3884 ER - TY - JOUR TI - 2018 Best Paper Award AU - Uzsoy, Reha T2 - IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING AB - Each year the Transactions on Semiconductor Manufacturing recognizes the best paper published during the previous calendar year. This year 12 papers were nominated by our reviewers and members of our Editorial Board and Steering Committee. The paper entitled “Maximizing Output During Ramp by Integrating Capacity and Velocity” by Adar A. Kalir and Kosta Rozen of Intel Corporation (vol. 31, no. 3, August 2018) was recognized as the Best Paper of 2018. The authors examine the very important problem of managing starts into a wafer fab during the ramp-up of new capacity, and find that maintaining starts slightly below constraint capacity to reduce cycle times can actually increase total output over the ramp-up duration. DA - 2019/5// PY - 2019/5// DO - 10.1109/TSM.2019.2910984 VL - 32 IS - 2 SP - 139-139 SN - 1558-2345 UR - https://doi.org/10.1109/TSM.2019.2910984 ER - TY - CONF TI - Bounded Verification of Sparse Matrix Computations AU - Dyer, Tristan AU - Altuntas, Alper AU - Baugh, John AB - We show how to model and reason about the structure and behavior of sparse matrices, which are central to many applications in scientific computation. Our approach is state-based, relying on a formalism called Alloy to show that one model is a refinement of another. We present examples of sparse matrix-vector multiplication, transpose, and translation between formats using ELLPACK and compressed sparse row formats to demonstrate the approach. To model matrix computations in a declarative language like Alloy, a new idiom is presented for bounded iteration with incremental updates. Mechanical verification is performed using SAT solvers built into the tool. C2 - 2019/11// C3 - 2019 IEEE/ACM 3rd International Workshop on Software Correctness for HPC Applications (Correctness) DA - 2019/11// DO - 10.1109/correctness49594.2019.00010 SP - 36-43 PB - IEEE/ACM UR - http://dx.doi.org/10.1109/correctness49594.2019.00010 KW - sparse matrix formats KW - state-based formal methods KW - mechanical verification ER - TY - JOUR TI - Performance Analysis of Microservice Design Patterns AU - Akbulut, Akhan AU - Perros, Harry G. T2 - IEEE INTERNET COMPUTING AB - Microservice-based solutions are currently gaining momentum because they do not have the disadvantages of traditional monolithic architectures. Business interest in microservices is increasing since the microservice architecture brings a lightweight, independent, reuse-oriented, and fast service deployment approach that minimizes infrastructural risks. This approach is at an early stage of its development, and in view of this, it is important to understand the performance of its design patterns. In this article, we obtained performance results related to query response time, efficient hardware usage, hosting costs, and packet-loss rate, for three microservice design patterns practiced in the software industry. DA - 2019/// PY - 2019/// DO - 10.1109/MIC.2019.2951094 VL - 23 IS - 6 SP - 19-27 SN - 1941-0131 KW - Time factors KW - Logic gates KW - Computer architecture KW - Random access memory KW - Measurement KW - Internet KW - Message systems KW - Microservices KW - Design Patterns KW - Microservices Architecture KW - Performance Analysis KW - Software Architecture ER - TY - JOUR TI - Influence of demographics and motivational factors on US consumer clothing and shoes disposal behavior AU - Rezaei Arangdad, S. AU - Thoney-Barletta, K. AU - Joines, J. AU - Rothenberg, L. T2 - Research Journal of Textile and Apparel AB - Purpose The purpose of this paper is to study clothing and shoes disposal behavior of US consumers in an attempt to understand how to divert more clothing and shoes from the landfill. Design/methodology/approach A survey was administered to 209 consumers from the general US population. The survey includes questions on demographics, methods of disposal and factors that motivate or prevent consumers from choosing methods other than throwing unwanted clothing in the trash. Findings Analysis of demographic data from the survey indicates that gender, income, marital status, living arrangement and type of dwelling have an effect on whether consumers recycle textiles. Other survey results indicate that helping factors are more influential in motivating consumers to recycle clothing and shoes than economic factors. The condition of clothes and shoes and lack of awareness are the most prominent reasons preventing consumers from recycling more textiles. The results also show that there are statistically significant differences between households with and without children when it comes to disposing adults’ clothing and shoes. Originality/value These results may help policymakers who want to motivate consumers to recycle or develop recycling programs. DA - 2019/9/9/ PY - 2019/9/9/ DO - 10.1108/rjta-08-2018-0051 VL - 23 IS - 3 SP - 170–188 UR - http://dx.doi.org/10.1108/rjta-08-2018-0051 KW - Clothing disposal KW - Clothing recycling KW - Discard practices KW - Recycling behaviour KW - Textile waste ER - TY - JOUR TI - The microfoundations of an operational capability in digital manufacturing AU - Roscoe, Samuel AU - Cousins, Paul D. AU - Handfield, Robert T2 - JOURNAL OF OPERATIONS MANAGEMENT AB - Abstract This article seeks insights into how individuals, processes, and structures interact to form the microfoundations of an operational capability in digital manufacturing. Using a knowledge‐based theory lens, we develop an empirical framework that explains how structures and processes encourage individuals to interact and share knowledge, and through these interactions, operating routines and operational capabilities emerge. The model is further refined using data collected from 40 interviews, steering committee meetings and participant observations at a high technology aerospace company. We find that discrete technologies, used in one component or subassembly, can be developed within authority‐based hierarchies using rigid new product development processes. We also find that whole system technologies that affect multiple aspects of the final product require flexible processes and consensus‐based hierarchical structures. Consensus‐based structures include centers of competence, which provide individuals the freedom to “learn through failure” and develop flexible ad hoc problem solving processes. Such flexible processes encourage individuals to learn from their mistakes and share new knowledge on a repetitive basis, leading to the emergence of operating routines. The paper contributes to the knowledge‐based view by empirically demonstrating how different types of new technology development programs, be they for discrete or whole system technologies, may benefit from different configurations of flexible/rigid processes and authority‐based/consensus‐based structures. DA - 2019/12// PY - 2019/12// DO - 10.1002/joom.1044 VL - 65 IS - 8 SP - 774-793 SN - 1873-1317 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85067411163&partnerID=MN8TOARS KW - 3D printing KW - additive manufacturing KW - capabilities KW - digital manufacturing KW - microfoundations KW - routines ER - TY - JOUR TI - Model Input and Output Dimension Reduction Using Karhunen-Loeve Expansions With Application to Biotransport AU - Alexanderian, Alen AU - Reese, William AU - Smith, Ralph C. AU - Yu, Meilin T2 - ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING AB - Abstract We consider biotransport in tumors with uncertain heterogeneous material properties. Specifically, we focus on the elliptic partial differential equation (PDE) modeling the pressure field inside the tumor. The permeability field is modeled as a log-Gaussian random field with a prespecified covariance function. We numerically explore dimension reduction of the input parameter and model output. Specifically, truncated Karhunen–Loève (KL) expansions are used to decompose the log-permeability field, as well as the resulting random pressure field. We find that although very high-dimensional representations are needed to accurately represent the permeability field, especially in presence of small correlation lengths, the pressure field is not sensitive to high-order KL terms of the input parameter. Moreover, we find that the pressure field itself can be represented accurately using a KL expansion with a small number of terms. These observations are used to guide a reduced-order modeling approach to accelerate computational studies of biotransport in tumors. DA - 2019/12/1/ PY - 2019/12/1/ DO - 10.1115/1.4044317 VL - 5 IS - 4 SP - SN - 2332-9025 ER - TY - JOUR TI - Application and Evaluation of Surrogate Models for Radiation Source Search AU - Cook, Jared A. AU - Smith, Ralph C. AU - Hite, Jason M. AU - Stefanescu, Razvan AU - Mattingly, John T2 - ALGORITHMS AB - Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate models whose discontinuous derivatives preclude the use of gradient-based optimization or data assimilation algorithms. We consider the problem of inferring the 2D location and intensity of a radiation source in an urban environment using a ray-tracing model based on Boltzmann transport theory. Whereas the code implementing this model is relatively efficient, extension to 3D Monte Carlo transport simulations precludes subsequent Bayesian inference to infer source locations, which typically requires thousands to millions of simulations. Additionally, the resulting likelihood exhibits discontinuous derivatives due to the presence of buildings. To address these issues, we discuss the construction of surrogate models for optimization, Bayesian inference, and uncertainty propagation. Specifically, we consider surrogate models based on Legendre polynomials, multivariate adaptive regression splines, radial basis functions, Gaussian processes, and neural networks. We detail strategies for computing training points and discuss the merits and deficits of each method. DA - 2019/12// PY - 2019/12// DO - 10.3390/a12120269 VL - 12 IS - 12 SP - SN - 1999-4893 KW - surrogate modeling KW - bayesian inference KW - radiation source localization ER - TY - JOUR TI - A Bayesian conjugate gradient method AU - Cockayne, Jon AU - Oates, Chris J. AU - Ipsen, Ilse C.F. AU - Girolami, Mark T2 - Bayesian Anal. AB - A fundamental task in numerical computation is the solution of large linear systems. The conjugate gradient method is an iterative method which offers rapid convergence to the solution, particularly when an effective preconditioner is employed. However, for more challenging systems a substantial error can be present even after many iterations have been performed. The estimates obtained in this case are of little value unless further information can be provided about, for example, the magnitude of the error. In this paper we propose a novel statistical model for this error, set in a Bayesian framework. Our approach is a strict generalisation of the conjugate gradient method, which is recovered as the posterior mean for a particular choice of prior. The estimates obtained are analysed with Krylov subspace methods and a contraction result for the posterior is presented. The method is then analysed in a simulation study as well as being applied to a challenging problem in medical imaging. DA - 2019/// PY - 2019/// DO - doi:10.1214/19-BA1145 VL - 14 IS - 3 SP - 937-1012 UR - https://doi.org/10.1214/19-BA1145 ER - TY - CHAP TI - Modeling and Analysis of Deception Games Based on Hypergame Theory AU - Al-Shaer, Ehab AU - Wei, Jinpeng AU - Hamlen, Kevin W. AU - Wang, Cliff T2 - Autonomous Cyber Deception PY - 2019/// DO - 10.1007/978-3-030-02110-8_4 SP - 49-74 OP - PB - Springer International Publishing SN - 9783030021092 9783030021108 UR - http://dx.doi.org/10.1007/978-3-030-02110-8_4 DB - Crossref ER - TY - CONF TI - Requirements Engineering as Science in the Small AU - Singh, Munindar P. AU - Chopra, Amit K. T2 - 2019 IEEE/ACM 41st International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) AB - This paper identifies similarities between requirements engineering (RE) and the scientific method. It argues that RE is concerned with the development of models of small universes and thus relates to natural science despite RE having a prescriptive rather than a descriptive nature. An explicitly philosophical stance sheds light on RE processes and brings up criteria for judging RE processes. C2 - 2019/5// C3 - 2019 IEEE/ACM 41st International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) DA - 2019/5// DO - 10.1109/icse-nier.2019.00020 PB - IEEE SN - 9781728117584 UR - http://dx.doi.org/10.1109/icse-nier.2019.00020 DB - Crossref KW - Philosophy of science KW - Foundations of requirements engineering KW - Requirements engineering process ER - TY - JOUR TI - Çorba: crowdsourcing to obtain requirements from regulations and breaches AU - Guo, Hui AU - Kafalı, Özgür AU - Jeukeng, Anne-Liz AU - Williams, Laurie AU - Singh, Munindar P. T2 - Empirical Software Engineering AB - Modern software systems are deployed in sociotechnical settings, combining social entities (humans and organizations) with technical entities (software and devices). In such settings, on top of technical controls that implement security features of software, regulations specify how users should behave in security-critical situations. No matter how carefully the software is designed and how well regulations are enforced, such systems are subject to breaches due to social (user misuse) and technical (vulnerabilities in software) factors. Breach reports, often legally mandated, describe what went wrong during a breach and how the breach was remedied. However, breach reports are not formally investigated in current practice, leading to valuable lessons being lost regarding past failures. Our research aim is to aid security analysts and software developers in obtaining a set of legal, security, and privacy requirements, by developing a crowdsourcing methodology to extract knowledge from regulations and breach reports. We present Çorba, a methodology that leverages human intelligence via crowdsourcing, and extracts requirements from textual artifacts in the form of regulatory norms. We evaluate Çorba on the US healthcare regulations from the Health Insurance Portability and Accountability Act (HIPAA) and breach reports published by the US Department of Health and Human Services (HHS). Following this methodology, we have conducted a pilot and a final study on the Amazon Mechanical Turk crowdsourcing platform. Çorba yields high quality responses from crowd workers, which we analyze to identify requirements for the purpose of complementing HIPAA regulations. We publish a curated dataset of the worker responses and identified requirements. The results show that the instructions and question formats presented to the crowd workers significantly affect the response quality regarding the identification of requirements. We have observed significant improvement from the pilot to the final study by revising the instructions and question formats. Other factors, such as worker types, breach types, or length of reports, do not have notable effect on the workers’ performance. Moreover, we discuss other potential improvements such as breach report restructuring and text highlighting with automated methods. DA - 2019/8/15/ PY - 2019/8/15/ DO - 10.1007/s10664-019-09753-2 VL - 8 J2 - Empir Software Eng LA - en OP - SN - 1382-3256 1573-7616 UR - http://dx.doi.org/10.1007/s10664-019-09753-2 DB - Crossref KW - Regulatory norms KW - Sociotechnical systems KW - HIPAA ER - TY - CONF TI - The Interplay of Emotions and Norms in Multiagent Systems AU - Kalia, Anup K. AU - Ajmeri, Nirav AU - Chan, Kevin S. AU - Cho, Jin-Hee AU - Adalı, Sibel AU - Singh, Munindar P. T2 - Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19} AB - We study how emotions influence norm outcomes in decision-making contexts. Following the literature, we provide baseline Dynamic Bayesian models to capture an agent's two perspectives on a directed norm. Unlike the literature, these models are holistic in that they incorporate not only norm outcomes and emotions but also trust and goals. We obtain data from an empirical study involving game play with respect to the above variables. We provide a step-wise process to discover two new Dynamic Bayesian models based on maximizing log-likelihood scores with respect to the data. We compare the new models with the baseline models to discover new insights into the relevant relationships. Our empirically supported models are thus holistic and characterize how emotions influence norm outcomes better than previous approaches. C2 - 2019/8// C3 - Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence DA - 2019/8// DO - 10.24963/ijcai.2019/53 PB - International Joint Conferences on Artificial Intelligence Organization SN - 9780999241141 UR - http://dx.doi.org/10.24963/ijcai.2019/53 DB - Crossref ER - TY - CONF TI - Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery AU - Zhang, Zhe AU - Singh, Munindar T2 - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) AB - Opinionated text often involves attributes such as authorship and location that influence the sentiments expressed for different aspects. We posit that structural and semantic correspondence is both prevalent in opinionated text, especially when associated with attributes, and crucial in accurately revealing its latent aspect and sentiment structure. However, it is not recognized by existing approaches. We propose Trait, an unsupervised probabilistic model that discovers aspects and sentiments from text and associates them with different attributes. To this end, Trait infers and leverages structural and semantic correspondence using a Markov Random Field. We show empirically that by incorporating attributes explicitly Trait significantly outperforms state-of-the-art baselines both by generating attribute profiles that accord with our intuitions, as shown via visualization, and yielding topics of greater semantic cohesion. C2 - 2019/// C3 - Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) DA - 2019/// DO - 10.18653/v1/d19-1555 PB - Association for Computational Linguistics UR - http://dx.doi.org/10.18653/v1/d19-1555 DB - Crossref ER - TY - JOUR TI - Shifts in buyer-seller relationships: A retrospective on Handfield and Bechtel (2002) AU - Handfield, Robert T2 - INDUSTRIAL MARKETING MANAGEMENT AB - One of the most highly cited papers in the Industrial Marketing Management journal was published 17 years ago, and proposed a strong linkage in the elements of buyer-seller trust, asset specificity, contracts, and supply chain performance. In this paper, explore the question of “what has changed”? We note that the emergence of 1) real-time analytic technologies, 2) new governance models that span multiple parties across organizations in a supply chain network, and 3) new digital innovation requiring partnering with new entities are required to produce end to end analytical capabilities. We offer three new propositions that provide some insights towards future research areas, and we also note that although interpersonal buyer-seller relationships will remain important, digital transformation is changing the nature of how these will unfold. Our propositions provide insights on how the role of technology and other shifts in the supply chain ecosystem is shifting the role of buyers and sellers in the industrial landscape. I offer these insights in the hope that they may provide a basis for future researchers to engage in research in the field of emerging industrial buyer-seller relationships, and devote this paper to the memory of Christian. DA - 2019/11// PY - 2019/11// DO - 10.1016/j.indmarman.2019.08.012 VL - 83 SP - 194-206 SN - 1873-2062 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85071449386&partnerID=MN8TOARS ER - TY - JOUR TI - Appreciation to the TSM Community AU - Uzsoy, Reha T2 - IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING AB - 2019 has been a good year at TSM. Our 2017 Impact Factor was 1.35, representing another year of continuous increase since 2011. Over the course of this year, we have revised the Scope and Aims of the journal for the first time since its launch in 1988, in order to broaden the reach of the journal to manufacturing aspects of related areas such as photovoltaic devices and micro-electro-mechanical systems. I would encourage all of you review the new scope on IEEE Xplore. DA - 2019/11// PY - 2019/11// DO - 10.1109/TSM.2019.2946034 VL - 32 IS - 4 SP - 362-362 SN - 1558-2345 UR - https://doi.org/10.1109/TSM.2019.2946034 ER - TY - JOUR TI - Emerging procurement technology: data analytics and cognitive analytics AU - Handfield, Robert AU - Jeong, Seongkyoon AU - Choi, Thomas T2 - INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT AB - Purpose The purpose of this paper is to elucidate the emerging landscape of procurement analytics. This paper focuses on the following questions: what are the current and future state of procurement analytics?; what changes in the procurement process will be required to enable integration of analytical solutions?; and what future areas of research arise when considering the future state of procurement analytics? Design/methodology/approach This paper employs a qualitative approach that relies on three sources of information: executive interviews, a review of current and emerging technology platforms and a small survey of subject matter experts in the field. Findings The procurement analytics landscape developed in this research suggests that the authors will continue to see major shifts in the sourcing and supply chain technology environment in the next five years. However, there currently exists a low usage of advanced procurement analytics, and data integrity and quality issues are preventing significant advances in analytics. This study identifies the need for organizations to establish a coherent approach to collection and storage of trusted organizational data that build on internal sources of spend analysis and contract databases. In addition, current ad hoc approaches to capturing unstructured data must be replaced by a systematic data governance strategy. An important element for organizations in this evolution is managing change and the need to nourish an analytic culture. Originality/value While the majority of forward-looking research and reports merely project broad technological impact of cognitive analytics and big data, much of it does not provide specific insights into functional impacts such as the impact on procurement. The analysis of this study provides us with a clear view of the potential for business analytics and cognitive analytics to be employed in procurement processes, and contributes to development of related research topics for future study. In addition, this study suggests detailed implementation strategies of emerging procurement technologies, contributing to the existing body of the literature and industry reports. DA - 2019/// PY - 2019/// DO - 10.1108/IJPDLM-11-2017-0348 VL - 49 IS - 10 SP - 972-1002 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85066024508&partnerID=MN8TOARS ER - TY - JOUR TI - A Mutual Information-Based Experimental Design Framework to Use High-Fidelity Nuclear Reactor Codes to Calibrate Low-Fidelity Codes AU - Gordon, Natalie AU - Gilkey, Lindsay AU - Smith, Ralph C. AU - Michaud, Isaac AU - Williams, Brian AU - Mousseau, Vincent AU - Hooper, Russell AU - Jones, Chris T2 - NUCLEAR TECHNOLOGY AB - Simulation-based nuclear reactor design requires highly efficient codes that quantify the requisite physics while having the efficiency required for optimization-based design and uncertainty quantification. To achieve the required accuracy and predictive capabilities, phenomenological parameters, often employed in closure relations or to quantify unmodeled or unresolved physics, must be calibrated for considered reactor conditions and designs. When available, experimental data with quantified observation errors are ideally employed for calibration. However, for many thermal-hydraulic, fuel, and Chalk River Unidentified Deposits modeling regimes, experimental data are prohibitively expensive or impossible to collect. For such cases, we demonstrate the use of a mutual information–based experimental design framework to employ validated high-fidelity codes to calibrate parameters in low-fidelity design codes. We demonstrate the use of the high-fidelity computational fluid dynamics package STAR-CCM+ to calibrate the turbulent mixing coefficient β in COBRA-TF (CTF). This includes the construction and verification of a surrogate for CTF, which permits the computationally intensive experimental design and Bayesian calibration steps. We also demonstrate Bayesian inference of parameter distributions for the Dittus-Boelter relation and propagation of these uncertainties through CTF to improve uncertainty bounds for computed maximum fuel temperatures. DA - 2019/12/2/ PY - 2019/12/2/ DO - 10.1080/00295450.2019.1590073 VL - 205 IS - 12 SP - 1685-1696 SN - 1943-7471 KW - Mutual information KW - experimental design KW - Bayesian inference ER - TY - JOUR TI - Real-time implementation and analysis of a modified energy based controller for the swing-up of an inverted pendulum on a cart AU - Kennedy, Emese AU - King, Ethan AU - Tran, Hien T2 - EUROPEAN JOURNAL OF CONTROL AB - In this paper we derive a modified energy based swing-up controller using Lyapunov functions. During the derivation, all effort has been made to use a more complex dynamical model for the single inverted pendulum (SIP) system than the simplified model that is most commonly used. We consider the electrodynamics of the DC motor that drives the cart, and incorporate viscous damping friction as seen at the motor pinion. Furthermore, we use a new method to account for the limitation of having a cart-pendulum system with a finite track length. Two modifications to the controller are also discussed to make the method more appropriate for real-time implementation. One of the modifications improves robustness using a modified Lyapunov function for the derivation, while the other one incorporates viscous damping as seen at the pendulum axis. We present both simulation and real-time experimental results implemented in MATLAB Simulink. DA - 2019/11// PY - 2019/11// DO - 10.1016/j.ejcon.2019.05.002 VL - 50 SP - 176-187 SN - 1435-5671 KW - Inverted pendulum KW - Energy based control KW - Lyapunov functions KW - Real-time implementation ER - TY - JOUR TI - Simulation model of the relationship between cesarean section rates and labor duration AU - Hicklin, Karen T. AU - Ivy, Julie S. AU - Wilson, James R. AU - Cobb Payton, Fay AU - Viswanathan, Meera AU - Myers, Evan R. T2 - Health Care Management Science DA - 2019/12// PY - 2019/12// DO - 10.1007/s10729-018-9449-3 VL - 22 IS - 4 SP - 635–657 SN - 1386-9620 1572-9389 UR - http://dx.doi.org/10.1007/S10729-018-9449-3 KW - Medical decision making KW - Mode of delivery KW - Birth KW - Simulation KW - Dystocia KW - Percentile matching ER - TY - JOUR TI - A PARALLEL DOMAIN DECOMPOSITION METHOD FOR THE HELMHOLTZ EQUATION IN LAYERED MEDIA AU - Heikkola, Erkki AU - Ito, Kazufumi AU - Toivanen, Jari T2 - SIAM JOURNAL ON SCIENTIFIC COMPUTING AB - An efficient domain decomposition method and its parallel implementation for the solution of the Helmholtz equation in three-dimensional layered media are considered. A modified trilinear finite element discretization scheme is applied to the equation system leading to fourth-order phase accuracy and thereby reducing the pollution error considerably. The resulting linear system is solved with the GMRES method using a multiplicative nonoverlapping domain decomposition preconditioner with layers defining the subdomains. This right preconditioner is constructed by embedding each layer into a rectangular domain and by employing a fast direct solver. Due to the construction of the preconditioner the iterations can be reduced to a subspace corresponding to the interfaces between the layers. Numerical experiments with several test cases demonstrate the effectiveness and scalability of the proposed method and ability to solve large-scale problems with up to billions of unknowns. DA - 2019/// PY - 2019/// DO - 10.1137/18M1230906 VL - 41 IS - 5 SP - C505-C521 SN - 1095-7197 KW - Helmholtz equation KW - domain decomposition method KW - preconditioned iterative method KW - ultrasonic tomography KW - geological survey ER - TY - JOUR TI - Editorial: special edition on probabilistic numerics AU - Girolami, M. AU - Ipsen, I. C. F. AU - Oates, C. J. AU - Owen, A. B. AU - Sullivan, T. J. T2 - STATISTICS AND COMPUTING DA - 2019/11// PY - 2019/11// DO - 10.1007/s11222-019-09892-y VL - 29 IS - 6 SP - 1181-1183 SN - 1573-1375 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85072031679&partnerID=MN8TOARS ER - TY - JOUR TI - Probabilistic linear solvers: a unifying view AU - Bartels, Simon AU - Cockayne, Jon AU - Ipsen, Ilse C. F. AU - Hennig, Philipp T2 - STATISTICS AND COMPUTING AB - Abstract Several recent works have developed a new, probabilistic interpretation for numerical algorithms solving linear systems in which the solution is inferred in a Bayesian framework, either directly or by inferring the unknown action of the matrix inverse. These approaches have typically focused on replicating the behaviour of the conjugate gradient method as a prototypical iterative method. In this work, surprisingly general conditions for equivalence of these disparate methods are presented. We also describe connections between probabilistic linear solvers and projection methods for linear systems, providing a probabilistic interpretation of a far more general class of iterative methods. In particular, this provides such an interpretation of the generalised minimum residual method. A probabilistic view of preconditioning is also introduced. These developments unify the literature on probabilistic linear solvers and provide foundational connections to the literature on iterative solvers for linear systems. DA - 2019/11// PY - 2019/11// DO - 10.1007/s11222-019-09897-7 VL - 29 IS - 6 SP - 1249-1263 SN - 1573-1375 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85073975117&partnerID=MN8TOARS KW - Probabilistic linear solvers KW - Projection methods KW - Iterative methods KW - Preconditioning ER - TY - JOUR TI - Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System AU - Yao, Yi AU - Zhang, Yifang AU - Tian, Lixin AU - Zhou, Nianxing AU - Li, Zhilin AU - Wang, Minggang T2 - SUSTAINABILITY AB - To better understand the characteristics of a bike-sharing system, we applied complex network methods to analyze the relationship between stations within the bike-sharing system. Firstly, using Gephi software, we constructed the public bicycle networks of different urban areas based on the real-time data of the Nanjing public bicycle system. Secondly, we analyzed and compared degree, strength, radiation distance, and community structure of the networks to understand the internal relations of the public bicycle system. The results showed that there were many stations with low usage of public bicycles. Furthermore, there was a geographical division between high-demand and low-demand areas for public bicycles. The usage of public bicycles at a station was not only related to land use but also related to the usage of bicycles at stations nearby. Moreover, the average service coverage of the public bicycle system was consistent with the original intention of “the first and last mile”, and public bicycles could meet different travel needs. DA - 2019/10/1/ PY - 2019/10/1/ DO - 10.3390/su11195425 VL - 11 IS - 19 SP - SN - 2071-1050 KW - sustainable mode of transportation KW - bike-sharing system KW - public bicycle KW - complex network KW - network structure ER - TY - JOUR TI - New Controllability Conditions for Networked, Identical LTI Systems AU - Hao, Yuqing AU - Duan, Zhisheng AU - Chen, Guanrong AU - Wu, Fen T2 - IEEE TRANSACTIONS ON AUTOMATIC CONTROL AB - A new necessary and sufficient condition for the controllability of networked linear time-invariant systems is derived, where the network topology is general and the nodes have identical higher dimensional dynamics. The condition is easier to verify, explicitly illustrating how the network topology, node-system dynamics, external control inputs, and inner interactions altogether affect the controllability of the whole networked system. Furthermore, the controllability of the specified Cartesian product networks is revisited, revealing that the necessity of the controllability criterion established in the work presented by Chapman et al., does not hold. In view of this, a modified, necessary, and sufficient condition is established. The effectiveness of the conditions is demonstrated using several examples. DA - 2019/10// PY - 2019/10// DO - 10.1109/TAC.2019.2893899 VL - 64 IS - 10 SP - 4223-4228 SN - 1558-2523 KW - Cartesian product network KW - controllability KW - multiple-input-multiple-output (MIMO) linear time-invariant (LTI) system KW - networked systems KW - observability ER - TY - JOUR TI - BAYESIAN MODELING OF THE STRUCTURAL CONNECTOME FOR STUDYING ALZHEIMER'S DISEASE AU - Roy, Arkaprava AU - Ghosal, Subhashis AU - Prescott, Jeffrey AU - Choudhury, Kingshuk Roy T2 - ANNALS OF APPLIED STATISTICS AB - We study possible relations between Alzheimer’s disease progression and the structure of the connectome which is white matter connecting different regions of the brain. Regression models in covariates including age, gender and disease status for the extent of white matter connecting each pair of regions of the brain are proposed. Subject inhomogeneity is also incorporated in the model through random effects with an unknown distribution. As there is a large number of pairs of regions, we also adopt a dimension reduction technique through graphon (J. Combin. Theory Ser. B 96 (2006) 933–957) functions which reduces the functions of pairs of regions to functions of regions. The connecting graphon functions are considered unknown but the assumed smoothness allows putting priors of low complexity on these functions. We pursue a nonparametric Bayesian approach by assigning a Dirichlet process scale mixture of zero to mean normal prior on the distributions of the random effects and finite random series of tensor products of B-splines priors on the underlying graphon functions. We develop efficient Markov chain Monte Carlo techniques for drawing samples for the posterior distributions using Hamiltonian Monte Carlo (HMC). The proposed Bayesian method overwhelmingly outperforms a competing method based on ANCOVA models in the simulation setup. The proposed Bayesian approach is applied on a dataset of 100 subjects and 83 brain regions and key regions implicated in the changing connectome are identified. DA - 2019/9// PY - 2019/9// DO - 10.1214/19-AOAS1257 VL - 13 IS - 3 SP - 1791-1816 SN - 1932-6157 KW - ADNI KW - B-spline prior KW - brain image KW - connectome KW - graphical model KW - Graphon KW - HMC ER - TY - JOUR TI - The public and legislative impact of hyperconcentrated topic news AU - Sheshadri, Karthik AU - Singh, Munindar P. T2 - SCIENCE ADVANCES AB - News has been shown to influence public perception, affect technology development, and increase public expression. We demonstrate that framing, a subjective aspect of news, appears to influence both significant public perception changes and federal legislation. We show that specific features of news, such as publishing volume, appear to influence sustained public attention, as measured by annual Google Trends data, and federal legislation. We observe that federal legislative activity is often foreshadowed by periods of high news volume and similarity between articles, which we call hyperconcentrated news periods. Last, we contribute the measures of framing density and framing polarity, which provide a quantitative assessment of news framing in a domain. We demonstrate that these measures appear to correlate substantially with the results of earlier human surveys. We note, however, that our analysis does not disprove reverse causality and does not model other confounding factors. DA - 2019/8// PY - 2019/8// DO - 10.1126/sciadv.aat8296 VL - 5 IS - 8 SP - SN - 2375-2548 UR - https://doi.org/10.1126/sciadv.aat8296 ER - TY - JOUR TI - Approximating Periodic Potential Energy Surfaces with Sparse Trigonometric Interpolation AU - Morrow, Zachary AU - Liu, Chang AU - Kelley, C. T. AU - Jakubikova, Elena T2 - The Journal of Physical Chemistry B AB - The potential energy surface (PES) describes the energy of a chemical system as a function of its geometry and is a fundamental concept in computational chemistry. A PES provides much useful information about the system, including the structures and energies of various stationary points, such as local minima, maxima, and transition states. Construction of full-dimensional PESs for molecules with more than 10 atoms is computationally expensive and often not feasible. Previous work in our group used sparse interpolation with polynomial basis functions to construct a surrogate reduced-dimensional PESs along chemically significant reaction coordinates, such as bond lengths, bond angles, and torsion angles. However, polynomial interpolation does not preserve the periodicity of the PES gradient with respect to angular components of geometry, such as torsion angles, which can lead to nonphysical phenomena. In this work, we construct a surrogate PES using trigonometric basis functions, for a system where the selected reaction coordinates all correspond to the torsion angles, resulting in a periodically repeating PES. We find that a trigonometric interpolation basis not only guarantees periodicity of the gradient but also results in slightly lower approximation error than polynomial interpolation. DA - 2019/11/14/ PY - 2019/11/14/ DO - 10.1021/acs.jpcb.9b08210 VL - 123 IS - 45 SP - 9677-9684 UR - https://doi.org/10.1021/acs.jpcb.9b08210 ER - TY - JOUR TI - Computing base-stock levels for a two-stage supply chain with uncertain supply AU - Warsing, Donald P., Jr. AU - Wangwatcharakul, Worawut AU - King, Russell E. T2 - Omega AB - We consider independent decision makers in a two-stage supply chain subject to uncertainty in upstream supply, and we use a recently published computational algorithm to generate independent, single-stage (ISS) base-stock inventory solutions for each stage in the system. These solutions are computed by employing straightforward, linear functions to estimate the parameters that must be set to seed the single-stage computational algorithm. Those linear functions are derived from the system-optimal solutions, which are found by solving a Markov chain model of the two-stage system. We demonstrate that the ISS solutions are often quite close to the system-optimal solution, and moreover, we develop a fast, descent-based search to quickly find the system-optimal solutions starting from the ISS solutions. We use our solution algorithm to generate optimal solutions to 1100 randomly-generated problem instances, allowing us to explore the behavior of the two-stage inventory system under various cost, demand uncertainty, and supply uncertainty conditions. We find that the downstream stocking levels are strongly influenced by the properties of the downstream demand, while the upstream stocking level is very strongly influenced by the holding costs and supply uncertainty, and only marginally by the retailer penalty cost. Moreover, the system responds to changes in the cost and uncertainty environment mostly by shifting the burden of holding cost either upstream or downstream, leaving the downstream penalty cost relative stable across the large set of problem instances we study. DA - 2019/12// PY - 2019/12// DO - 10.1016/j.omega.2018.10.001 VL - 89 SP - 92-109 J2 - Omega LA - en OP - SN - 0305-0483 UR - http://dx.doi.org/10.1016/J.OMEGA.2018.10.001 DB - Crossref KW - Inventory KW - Base-stock system KW - Uncertain supply ER - TY - JOUR TI - Spatiotemporal characteristics of green travel: A classification study on a public bicycle system AU - Yao, Yi AU - Jiang, Xin AU - Li, Zhilin T2 - JOURNAL OF CLEANER PRODUCTION AB - Understanding the characteristics of users and stations provides the foundation for a more efficient public bicycle system. Based on the real-time data of the Nanjing public bicycle system, we presented the spatiotemporal characteristics of users and stations combining data mining and geographic visualization. First, we analyzed users' gender, age, weekly flow, and time-segment flow, and classified the users into different types. In addition, we studied the cycling chains of certain users in details to understand the differences. Second, we analyzed the station distribution, station flow, station time-segment flow, and the surrounding environment, and studied the specific stations of different types to reveal the diverse characteristics. Moreover, we also explored the relationship between the user types and the station types. The results showed that public bicycles were mainly used for commuting or transferring, and social and economic activities around stations greatly influenced the use of public bicycles. However, the usage of the public bicycle system was still at a low level. Furthermore, different types of users had different cycling purposes, and different types of stations showed different characteristics of renting flow and returning flow. At last, we proposed different incentives and management measures for different types of users and stations. DA - 2019/11/20/ PY - 2019/11/20/ DO - 10.1016/j.jclepro.2019.117892 VL - 238 SP - SN - 1879-1786 KW - Green travel KW - Public bicycle KW - Spatiotemporal characteristics KW - Clustering analysis KW - Visualization analysis ER - TY - JOUR TI - Optimal strategies for a three-level contract-farming supply chain with subsidy AU - Peng, Hongjun AU - Pang, Tao T2 - INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS AB - We consider a three-level contract-farming supply chain with a risk-averse farmer, a risk-neutral supplier and a risk-neutral distributor, in which the farmer faces a yield uncertainty and the government offers agricultural subsidy to the farmer. The CVaR criterion is used to describe the risk-averse behavior of the farmer. We derive the optimal strategies of the supply chain and perform some sensitivity analysis to investigate the effects of the government subsidy and other factors. The results indicate that, as the subsidy increases, the farmer's total target production increases. Further analysis shows that the total production increase is mainly from the increased farm size, and the farmer's endeavor actually decreases. In addition, the results indicate that the profits of the supplier and the distributor both increase with respect to the subsidy. However, the impact of the subsidy on the farmer's profit depends on the farmer's degree of risk-averse. In particular, the impact of the subsidy to the farmer's profit tends to be positive for farmers with high degree of risk-averse, and the impact tends to be negative for those with low degree of risk-averse. The sensitivity analysis is also performed for the level of yield uncertainty in term of the standard deviation. DA - 2019/10// PY - 2019/10// DO - 10.1016/j.ijpe.2019.06.011 VL - 216 SP - 274-286 SN - 1873-7579 KW - Contract-farming supply chain KW - Agricultural subsidy policy KW - Risk-averse KW - Yield uncertainty ER - TY - JOUR TI - Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability AU - Scolforo, Henrique Ferraco AU - McTague, John Paul AU - Burkhart, Harold AU - Roise, Joseph AU - McCarter, James AU - Alvares, Clayton Alcarde AU - Stape, Jose Luiz T2 - FOREST ECOLOGY AND MANAGEMENT AB - Growth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation. DA - 2019/9/15/ PY - 2019/9/15/ DO - 10.1016/j.foreco.2019.06.006 VL - 448 SP - 22-33 SN - 1872-7042 KW - Environment KW - Accuracy KW - Climatic water deficit KW - Volume KW - Basal area KW - Forest production ER - TY - JOUR TI - A mutual-aid mechanism for supply chains with capital constraints AU - Peng, Hongjun AU - Pang, Tao T2 - INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT AB - We consider a supply chain in which both the supplier and the distributor experience capital constraints. Due to the capital constraints, the supplier faces a capital deficit during the production period and the distributor faces a capital deficit during the sales period. Under the bank loan financing, we derive the optimal strategies for both the supplier and the distributor. Then we propose a mutual-aid mechanism under which the distributor provides an advance payment to the supplier during the production period, and the supplier offers a deferred payment trade credit to the distributor during the sales period. As the demand is uncertain, there is a bankruptcy risk with the distributor, which is taken into consideration in our model. We develop a Stackelberg game model and derive the optimal strategies under the mutual-aid mechanism. Our results indicate that the mutual-aid mechanism can improve the profits for both the supplier and the distributor, comparing to the bank loan financing case. DA - 2019/// PY - 2019/// DO - 10.1080/17509653.2019.1578275 VL - 14 IS - 4 SP - 304-312 SN - 1750-9661 KW - Supply chain KW - mutual-aid mechanism KW - advance payment KW - deferred payment ER - TY - JOUR TI - A data-driven iterative refinement approach for estimating clearing functions from simulation models of production systems AU - Gopalswamy, Karthick AU - Uzsoy, Reha T2 - INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH AB - Clearing functions that describe the expected output of a production resource as a function of its expected workload have yielded promising production planning models. However, there is as yet no fully satisfactory approach to estimating clearing functions from data. We identify several issues that arise in estimating clearing functions such as sampling issues, systematic underestimation and model misspecification. We address the model misspecification problem by introducing a generalised functional form, and the sampling issues via iterative refinement of initial parameter estimates. The iterative refinement approach yields improved performance for planning models at higher levels of utilisation, and the generalised functional form results in significantly better production plans both alone and when combined with the iterative refinement approach. The IR approach also obtains solutions of similar quality to the much more computationally demanding simulation optimisation approaches used in previous work. DA - 2019/10/2/ PY - 2019/10/2/ DO - 10.1080/00207543.2018.1557351 VL - 57 IS - 19 SP - 6013-6030 SN - 1366-588X KW - regression KW - simulation KW - variable sampling KW - clearing functions KW - production planning ER - TY - JOUR TI - Optimal Server Assignment in Multi-Server Queueing Systems with Random Connectivities AU - Halabian, Hassan AU - Lambadaris, Ioannis AU - Viniotis, Yannis T2 - JOURNAL OF COMMUNICATIONS AND NETWORKS AB - In this paper, we provide complementary results on delay-optimal server allocation in multi-queue multi-server (MQMS) systems with random connectivities. More specifically, we consider an MQMS system where each queue is limited to get service by at most one server during each time slot. It is known that maximum weighted matching (MWM) is a throughput-optimal server assignment policy for such a system. In this paper, using dynamic coupling argument we prove that for a system with i.i.d. Bernoulli arrivals and connectivities, MWM minimizes, in stochastic ordering sense, a range of cost functions of the queue lengths such as total queue occupancy (which implies minimization of average queueing delay). Finally, we propose a low complexity heuristic server assignment policy for MQMS systems namely least connected server first/longest connected queue (LCSF/LCQ) and through simulations we show that it performs very closely compared with the optimal policy in terms of average queueing delay. DA - 2019/8// PY - 2019/8// DO - 10.1109/JCN.2019.000023 VL - 21 IS - 4 SP - 405-415 SN - 1976-5541 KW - Delay-optimal server allocation KW - dynamic coupling KW - maximum weighted matching KW - multi-server queueing systems ER - TY - JOUR TI - Route planning methods for a modular warehouse system AU - Dayıoğlu, Elif G. AU - Karagül, Kenan AU - Şahin, Yusuf AU - Kay, Michael G. T2 - An International Journal of Optimization and Control: Theories & Applications (IJOCTA) AB - In this study, procedures are presented that can be used to determine the routes of the packages transported within a modular storage system. The problem is a variant of robot motion planning problem. The structures of the procedures are developed in three steps for the simultaneous movement of multiple unit-sized packages in a modular warehouse. The proposed heuristic methods consist of route planning, tagging, and main control components. In order to demonstrate the solution performance of the methods, various experiments were conducted with different data sets and the solution times and qualities of the proposed methods were compared with previous studies. It was found that the proposed methods provide better solutions when taking the number of steps and solution time into consideration. DA - 2019/9/19/ PY - 2019/9/19/ DO - 10.11121/ijocta.01.2020.00752 VL - 10 IS - 1 SP - 17 UR - https://doi.org/10.11121/ijocta.01.2020.00752 KW - Warehouse management KW - Motion planning KW - Heuristics algorithms ER - TY - JOUR TI - A Coupled Operational Semantics for Goals and Commitments AU - Telang, Pankaj R. AU - Singh, Munindar P. AU - Yorke-Smith, Neil T2 - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH AB - Commitments capture how an agent relates to another agent, whereas goals describe states of the world that an agent is motivated to bring about. Commitments are elements of the social state of a set of agents whereas goals are elements of the private states of individual agents. It makes intuitive sense that goals and commitments are understood as being complementary to each other. More importantly, an agent's goals and commitments ought to be coherent, in the sense that an agent's goals would lead it to adopt or modify relevant commitments and an agent's commitments would lead it to adopt or modify relevant goals. However, despite the intuitive naturalness of the above connections, they have not been adequately studied in a formal framework. This article provides a combined operational semantics for goals and commitments by relating their respective life cycles as a basis for how these concepts (1) cohere for an individual agent and (2) engender cooperation among agents. Our semantics yields important desirable properties of convergence of the configurations of cooperating agents, thereby delineating some theoretically well-founded yet practical modes of cooperation in a multiagent system. DA - 2019/// PY - 2019/// DO - 10.1613/jair.1.11494 VL - 65 SP - 31-85 SN - 1943-5037 UR - https://doi.org/10.1613/jair.1.11494 ER - TY - JOUR TI - Optimization of processor allocation for domain decomposed Monte Carlo calculations AU - Ellis, J. Austin AU - Evans, Thomas M. AU - Hamilton, Steven P. AU - Kelley, C.T. AU - Pandya, Tara M. T2 - Parallel Computing AB - Load imbalance plagues domain decomposed Monte Carlo calculations when sources are not uniform. Parallel efficiency for domain decomposed Monte Carlo transport calculations improves through a nonuniform allocation of processors over subdomains. We optimize the allocation with runtime diagnostics collected during a calibration step, then complete the full calculation. The diagnostic-based approach is compared to implicit filtering, an optimization algorithm for bound constrained noisy optimization problems. We consider both forward and hybrid radiation transport calculations to measure performance. DA - 2019/9// PY - 2019/9// DO - 10.1016/j.parco.2019.06.001 VL - 87 SP - 77-86 J2 - Parallel Computing LA - en OP - SN - 0167-8191 UR - http://dx.doi.org/10.1016/j.parco.2019.06.001 DB - Crossref KW - Monte Carlo transport KW - Load imbalance KW - Domain decomposition KW - Noisy optimization ER - TY - JOUR TI - Robust Regression Models for Load Forecasting AU - Luo, Jian AU - Hong, Tao AU - Fang, Shu-Cherng T2 - IEEE Transactions on Smart Grid AB - Electric load forecasting has been extensively studied during the past century. While many models and their variants have been proposed and tested in load forecasting literature, most of the existing case studies have been conducted using the data collected under normal operating conditions. A recent case study shows that four representative load forecasting models easily fail under data integrity attacks. To address this challenge, we propose three robust load forecasting models including two variants of the iteratively re-weighted least squares regression models and an L 1 regression model. Numerical experiments indicate the dominating performance of the three proposed robust regression models, especially L 1 regression, compared to other representative load forecasting models. DA - 2019/9// PY - 2019/9// DO - 10.1109/TSG.2018.2881562 VL - 10 IS - 5 SP - 5397-5404 J2 - IEEE Trans. Smart Grid OP - SN - 1949-3053 1949-3061 UR - http://dx.doi.org/10.1109/TSG.2018.2881562 DB - Crossref KW - Cybersecurity KW - data integrity attack KW - electric load forecasting KW - iteratively re-weighted least squares KW - L-1 regression KW - robust regression ER - TY - MGZN TI - How Data Analytics Will Improve Logistics Planning AU - Schwartz, B. AU - McConnell, B.M. AU - Parlier, G.H.Jul–Sep T2 - Army Sustainment DA - 2019/// PY - 2019/// VL - 51 SP - 54–57 M1 - 3 UR - https://www.army.mil/article/223842/how_data_analytics_will_improve_logistics_planning ER - TY - JOUR TI - Global Sensitivity Analysis of Fractional-Order Viscoelasticity Models AU - Miles, Paul R. AU - Pash, Graham T. AU - Smith, Ralph C. AU - Oates, William S. T2 - BEHAVIOR AND MECHANICS OF MULTIFUNCTIONAL MATERIALS XIII AB - In this paper, we investigate hyperelastic and viscoelastic model parameters using Global Sensitivity Analysis (GSA). These models are used to characterize the physical response of many soft-elastomers, which are used in a wide variety of smart material applications. Recent research has shown the effectiveness of using fractionalorder calculus operators in modeling the viscoelastic response. The GSA is performed using parameter subset selection (PSS), which quantifies the relative parameter contributions to the linear and nonlinear, fractionalorder viscoelastic models. Calibration has been performed to quantify the model parameter uncertainty; however, this analysis has led to questions regarding parameter sensitivity and whether or not the parameters can be uniquely identified given the available data. By performing GSA we can determine which parameters are most influential in the model, and fix non-influential parameters at a nominal value. The model calibration can then be performed to quantify the uncertainty of the influential parameters. DA - 2019/// PY - 2019/// DO - 10.1117/12.2514160 VL - 10968 SP - SN - 1996-756X KW - Viscoelasticity KW - Global Sensitivity Analysis KW - Fractional-Order Calculus ER - TY - JOUR TI - Parameter-dependent Surrogate Model Development for PZT Bimorph Actuators Employed for Micro-air Vehicles AU - Bravo, Nikolas AU - Smith, Ralph C. T2 - BEHAVIOR AND MECHANICS OF MULTIFUNCTIONAL MATERIALS XIII AB - In the paper, we discuss the use of the homogenized energy model (HEM) to develop a dynamic mode decomposition surrogate model for a PZT bimorph actuator used for micro-air vehicles including Robobee. The HEM quantifies the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT in highly dynamic operating regimes. Due to the computation complexity of the HEM, we must develop a surrogate model. The surrogate model must be parameter- and control-dependent to be able to perform inverse problems or uncertainty quantification in different driving regimes. In the literature, DMD can be adapted to address different control inputs. We will discuss using interpolation over the parameters to adapt the DMD to include parameter dependence. Finally, we will discuss the results and limitations of the new surrogate model. DA - 2019/// PY - 2019/// DO - 10.1117/12.2514246 VL - 10968 SP - SN - 1996-756X KW - Uncertainty Quantification KW - PZT Bimorph KW - Modeling KW - Surrogate KW - Homogenized Energy Model ER - TY - JOUR TI - Molecular Dynamics Simulations on Relaxed Reduced-Dimensional Potential Energy Surfaces AU - Liu, Chang AU - Kelley, C. T. AU - Jakubikova, Elena T2 - The Journal of Physical Chemistry A AB - Molecular dynamics (MD) simulations with full-dimensional potential energy surfaces (PESs) obtained from high-level ab initio calculations are frequently used to model reaction dynamics of small molecules (i.e., molecules with up to 10 atoms). Construction of full-dimensional PESs for larger molecules is, however, not feasible since the number of ab initio calculations required grows rapidly with the increase of dimension. Only a small number of coordinates are often essential for describing the reactivity of even very large systems, and reduced-dimensional PESs with these coordinates can be built for reaction dynamics studies. While analytical methods based on transition-state theory framework are well established for analyzing the reduced-dimensional PESs, MD simulation algorithms capable of generating trajectories on such surfaces are more rare. In this work, we present a new MD implementation that utilizes the relaxed reduced-dimensional PES for standard microcanonical (NVE) and canonical (NVT) MD simulations. The method is applied to the pyramidal inversion of a NH3 molecule. The results from the MD simulations on a reduced, three-dimensional PES are validated against the ab initio MD simulations, as well as MD simulations on full-dimensional PES and experimental data. DA - 2019/4/30/ PY - 2019/4/30/ DO - 10.1021/acs.jpca.9b02298 VL - 123 IS - 21 SP - 4543-4554 J2 - J. Phys. Chem. A LA - en OP - SN - 1089-5639 1520-5215 UR - http://dx.doi.org/10.1021/acs.jpca.9b02298 DB - Crossref ER - TY - JOUR TI - Genomic Selection with Allele Dosage in Panicum maximum Jacq. AU - Lara, Leticia A. de C. AU - Santos, Mateus F. AU - Jank, Liana AU - Chiari, Lucimara AU - Vilela, Mariane de M. AU - Amadeu, Rodrigo R. AU - Santos, Jhonathan P. R. AU - Pereira, Guilherme da S. AU - Zeng, Zhao-Bang AU - Garcia, Antonio Augusto F. T2 - G3-GENES GENOMES GENETICS AB - Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum, an autotetraploid forage grass. We also investigated the effect of the allele dosage in the prediction, i.e., considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotyping-by-sequencing markers were obtained using 96-plex and Pst1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum. DA - 2019/8// PY - 2019/8// DO - 10.1534/g3.118.200986 VL - 9 IS - 8 SP - 2463-2475 SN - 2160-1836 KW - Plant Breeding KW - Guinea Grass KW - Quantitative Genotyping KW - Polyploidy KW - Genotyping-by-sequencing (GBS) KW - Recurrent Genomic Selection KW - Genomic Prediction KW - GenPred KW - Shared Data Resources ER - TY - JOUR TI - Resilience of IoT Systems Against Edge-Induced Cascade-of-Failures: A Networking Perspective AU - Wang, Jie AU - Pambudi, Sigit AU - Wang, Wenye AU - Song, Min T2 - IEEE INTERNET OF THINGS JOURNAL AB - Internet of Things (IoT) is a networking paradigm that interconnects physical systems to the cyber world, to provide automation and intelligence via interdependent links between the two domains. Such interdependence renders IoT systems vulnerable to random failures, e.g., broken communication links or crashed cyber instances, because a single incident in one domain can develop into a cascade-of-failures across domains, which dissolves the network structure, and has devastating consequences. To answer how robust an IoT system is, this paper studies its resilience by examining the impact of edge- and jointly-induced cascades, that is, a sequence of failures caused by randomly broken physical links (and simultaneous failing cyber nodes). Resilience of an IoT system is quantified by two new metrics, the critical edge disconnecting probability φ cr , i.e., the maximum intensity of random failures the system can withstand, and the cascade length τ cf , i.e., the lifetime of a cascade. For IoT systems with Poisson degree distributions, we derive exact solutions for the critical disconnecting probability φ cr , above which an edge-induced cascade will completely fragment the network. We also find that the critical condition φ cr marks a dichotomy of the expected cascade length E(τ cf ): for the super-critical (φ > φ cr ) scenario, we obtain E(τ cf ) ~ exp(1 - φ) through analysis, while for the subcritical scenario, we observe E(τ cf ) ~ exp(1/1 - φ) through simulations. With these results, the final outcome of a cascade can be anticipated upon the initial failures, while the reaction window of time-sensitive countermeasures can be obtained before a cascade fully unfolds. DA - 2019/8// PY - 2019/8// DO - 10.1109/JIOT.2019.2913140 VL - 6 IS - 4 SP - 6952-6963 SN - 2327-4662 KW - Interdependent networks KW - Internet of Things (IoT) architecture KW - network resilience ER - TY - JOUR TI - A gradient recovery-based adaptive finite element method for convection-diffusion-reaction equations on surfaces AU - Xiao, Xufeng AU - Feng, Xinlong AU - Li, Zhilin T2 - INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING AB - Summary In this paper, we present an adaptive mesh refinement method for solving convection‐diffusion‐reaction equations on surfaces, which is a fundamental subproblem in many models for simulating the transport of substances on biological films and solid surfaces. The method considered is a combination of well‐known techniques: the surface finite element method, streamline diffusion stabilization, and the gradient recovery–based Zienkiewicz‐Zhu error estimator. The streamline diffusion method overcomes the instability issue of the finite element method for the dominance of the convection. The gradient recovery–based adaptive mesh refinement strategy enables the method to provide high‐resolution numerical solutions by relatively fewer degrees of freedom. Moreover, the implementation detail of a surface mesh refinement technique is presented. Various numerical examples, including the convection‐dominated diffusion problems with large variations of solutions, nearly singular solutions, discontinuous sources, and internal layers on surfaces, are presented to demonstrate the efficacy and accuracy of the proposed method. DA - 2019/11/16/ PY - 2019/11/16/ DO - 10.1002/nme.6163 VL - 120 IS - 7 SP - 901-917 SN - 1097-0207 KW - adaptive strategy KW - recovery-based error estimator KW - streamline diffusion method KW - surface convection-diffusion-reaction equations KW - surface finite element method ER - TY - JOUR TI - Cardiovascular dynamics during head-up tilt assessed via pulsatile and non-pulsatile models AU - Williams, Nakeya D. AU - Brady, Renee AU - Gilmore, Steven AU - Gremaud, Pierre AU - Tran, Hien T. AU - Ottesen, Johnny T. AU - Mehlsen, Jesper AU - Olufsen, Mette S. T2 - Journal of Mathematical Biology AB - This study develops non-pulsatile and pulsatile models for the prediction of blood flow and pressure during head-up tilt. This test is used to diagnose potential pathologies within the autonomic control system, which acts to keep the cardiovascular system at homeostasis. We show that mathematical modeling can be used to predict changes in cardiac contractility, vascular resistance, and arterial compliance, quantities that cannot be measured but are useful to assess the system's state. These quantities are predicted as time-varying parameters modeled using piecewise linear splines. Having models with various levels of complexity formulated with a common set of parameters, allows us to combine long-term non-pulsatile simulations with pulsatile simulations on a shorter time-scale. We illustrate results for a representative subject tilted head-up from a supine position to a [Formula: see text] angle. The tilt is maintained for 5 min before the subject is tilted back down. Results show that if volume data is available for all vascular compartments three parameters can be identified, cardiovascular resistance, vascular compliance, and ventricular contractility, whereas if model predictions are made against arterial pressure and cardiac output data alone, only two parameters can be estimated either resistance and contractility or resistance and compliance. DA - 2019/5/31/ PY - 2019/5/31/ DO - 10.1007/s00285-019-01386-9 VL - 79 IS - 3 SP - 987-1014 J2 - J. Math. Biol. LA - en OP - SN - 0303-6812 1432-1416 UR - http://dx.doi.org/10.1007/s00285-019-01386-9 DB - Crossref KW - Cardiovascular dynamics modeling KW - Head-up tilt KW - Pulsatile versus non-pulsatile modeling KW - Parameter estimation KW - Orthostatic intolerance ER - TY - JOUR TI - Active subspace analysis and uncertainty quantification for a polydomain ferroelectric phase-field model AU - Leon, Lider S. AU - Miles, Paul R. AU - Smith, Ralph C. AU - Oates, William S. T2 - JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES AB - We perform parameter subset selection and uncertainty analysis for phase-field models that are applied to the ferroelectric material lead titanate. A motivating objective is to determine which parameters are influential in the sense that their uncertainties directly affect the uncertainty in the model response, and fix noninfluential parameters at nominal values for subsequent uncertainty propagation. We employ Bayesian inference to quantify the uncertainties of gradient exchange parameters governing 180° and 90° tetragonal phase domain wall energies. The uncertainties of influential parameters determined by parameter subset selection are then propagated through the models to obtain credible intervals when estimating energy densities quantifying polarization and strain across domain walls. The results illustrate various properties of Landau and electromechanical coupling parameters and their influence on domain wall interactions. We employ energy statistics, which quantify distances between statistical observations, to compare credible intervals constructed using a complete set of parameters against an influential subset of parameters. These intervals are obtained from the uncertainty propagation of the model input parameters on the domain wall energy densities. The investigation provides critical insight into the development of parameter subset selection, uncertainty quantification, and propagation methodologies for material modeling domain wall structure evolution, informed by density functional theory simulations. DA - 2019/8// PY - 2019/8// DO - 10.1177/1045389X19853636 VL - 30 IS - 14 SP - 2027-2051 SN - 1530-8138 KW - Ferroelectric KW - active subspace analysis KW - uncertainty quantification ER - TY - JOUR TI - Sequest: A Sequential Procedure for Estimating Quantiles in Steady-State Simulations AU - Alexopoulos, Christos AU - Goldsman, David AU - Mokashi, Anup C. AU - Tien, Kal-Wen AU - Wilson, James R. T2 - OPERATIONS RESEARCH DA - 2019/// PY - 2019/// DO - 10.1287/opre.2018:1829 VL - 67 IS - 4 SP - 1162-1183 ER - TY - JOUR TI - Sequential optimal positioning of mobile sensors using mutual information AU - Schmidt, Kathleen AU - Smith, Ralph C. AU - Hite, Jason AU - Mattingly, John AU - Azmy, Yousry AU - Rajan, Deepak AU - Goldhahn, Ryan T2 - STATISTICAL ANALYSIS AND DATA MINING AB - Abstract Source localization, such as detecting a nuclear source in an urban area or ascertaining the origin of a chemical plume, is generally regarded as a well‐documented inverse problem; however, optimally placing sensors to collect data for such problems is a more challenging task. In particular, optimal sensor placement—that is, measurement locations resulting in the least uncertainty in the estimated source parameters—depends on the location of the source, which is typically unknown a priori . Mobile sensors are advantageous because they have the flexibility to adapt to any given source position. While most mobile sensor strategies designate a trajectory for sensor movement, we instead employ mutual information, based on Shannon entropy, to choose the next measurement location from a discrete set of design conditions. DA - 2019/12// PY - 2019/12// DO - 10.1002/sam.11431 VL - 12 IS - 6 SP - 465-478 SN - 1932-1872 KW - Bayesian inference KW - inverse problem KW - mutual information KW - sensor placement KW - source localization ER - TY - JOUR TI - Bidding Decisions with Nonequilibrium Strategic Thinking in Reverse Auctions AU - Qian, Xiaohu AU - Fang, Shu-Cherng AU - Huang, Min AU - Nie, Tiantian AU - Wang, Xingwei T2 - Group Decision and Negotiation DA - 2019/6/8/ PY - 2019/6/8/ DO - 10.1007/s10726-019-09624-7 VL - 28 IS - 4 SP - 757-786 J2 - Group Decis Negot LA - en OP - SN - 0926-2644 1572-9907 UR - http://dx.doi.org/10.1007/s10726-019-09624-7 DB - Crossref KW - Reverse auction KW - Bounded rationality KW - Nonequilibrium strategic thinking KW - Level-k model ER - TY - JOUR TI - The magnitude of a product recall: offshore outsourcing vs. captive offshoring effects AU - Bruccoleri, Manfredi AU - Perrone, Giovanni AU - Mazzola, Erica AU - Handfield, Robert T2 - INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH AB - The escalation in product recalls in recent years is attributed to the rise of globalisation and associated challenges of offshoring. Extant SCM research suggests that product recalls have a significant negative impact on financial performance, but gaps exist relative to the managerial actions to minimise their impact. Recall response strategies have become more important in the press, given that a single recall may result in the mandatory withdrawal of millions of products from the market, with firms incurring enormous logistics costs and brand damage. In this study, we address this gap in the research, and using a measure of product recall defined as the volume of products withdrawn from the market due to product quality failure. We explore the scale of the recall in the context of pharmaceutical sector global sourcing strategies, exploring whether the variation in global sourcing decisions not only increases the likelihood of a recall, but also influences the capability to minimise the total cost of recall. Our results suggest that offshore outsourcing and captive offshoring have opposite effects in terms of their influence on the magnitude of product recall. We summarise the implications through a compelling set of insights for future global sourcing strategy research themes. DA - 2019/7/3/ PY - 2019/7/3/ DO - 10.1080/00207543.2018.1533652 VL - 57 IS - 13 SP - 4211-4227 SN - 1366-588X UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85055125961&partnerID=MN8TOARS KW - product recalls KW - offshore outsourcing KW - captive offshoring KW - country distance KW - agency theory ER - TY - JOUR TI - Numerical Validations of the Tangent Linear Model for the Lorenz Equations AU - Zhao, Tengjin AU - Zhang, Jing AU - Li, Zhilin AU - Zhang, Zhiyue T2 - CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES AB - The validity of the tangent linear model (TLM) is studied numerically using the example of the Lorenz equations in this paper. The relationship between the limit of the validity time of the TLM and initial perturbations for the Lorenz equations is investigated using the Monte Carlo sampling method. A new error function between the nonlinear and the linear evolution of the perturbations is proposed. Furthermore, numerical sensitivity analysis is carried to establish the relationship between parameters and the validity of the TLM, such as the initial perturbation, the prediction time, the time step size and so on, by the method of mathematical statistics. DA - 2019/// PY - 2019/// DO - 10.32604/cmes.2019.04483 VL - 120 IS - 1 SP - 83-104 SN - 1526-1506 KW - Lorenz model KW - tangent linear model KW - nonlinear model KW - Monte Carlo ER - TY - JOUR TI - Bayesian nonparametric estimation of ROC surface under verification bias AU - Zhu, Rui AU - Ghosal, Subhashis T2 - STATISTICS IN MEDICINE AB - The receiver operating characteristic (ROC) surface, as a generalization of the ROC curve, has been widely used to assess the accuracy of a diagnostic test for three categories. A common problem is verification bias, referring to the situation where not all subjects have their true classes verified. In this paper, we consider the problem of estimating the ROC surface under verification bias. We adopt a Bayesian nonparametric approach by directly modeling the underlying distributions of the three categories by Dirichlet process mixture priors. We propose a robust computing algorithm by only imposing a missing at random assumption for the verification process but no assumption on the distributions. The method can also accommodate covariates information in estimating the ROC surface, which can lead to a more comprehensive understanding of the diagnostic accuracy. It can be adapted and hugely simplified in the case where there is no verification bias, and very fast computation is possible through the Bayesian bootstrap process. The proposed method is compared with other commonly used methods by extensive simulations. We find that the proposed method generally outperforms other approaches. Applying the method to two real datasets, the key findings are as follows: (1) human epididymis protein 4 has a slightly better diagnosis ability compared to CA125 in discriminating healthy, early stage, and late stage patients of epithelial ovarian cancer. (2) Serum albumin has a prognostic ability in distinguishing different stages of hepatocellular carcinoma. DA - 2019/8/15/ PY - 2019/8/15/ DO - 10.1002/sim.8181 VL - 38 IS - 18 SP - 3361-3377 SN - 1097-0258 KW - Bayesian bootstrap KW - Dirichlet process KW - MAR assumption KW - ROC surface KW - verification bias correction ER - TY - JOUR TI - Assessing uncertainty and risk in an expeditionary military logistics network AU - McConnell, Brandon M AU - Hodgson, Thom J AU - Kay, Michael G AU - King, Russell E AU - Liu, Yunan AU - Parlier, Greg H AU - Thoney-Barletta, Kristin AU - Wilson, James R T2 - The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology AB - Uncertainty is rampant in military expeditionary operations spanning high-intensity combat to humanitarian operations. These missions require rapid planning and decision-support tools to address the logistical challenges involved in providing support in often austere environments. The US Army’s adoption of an enterprise resource planning system provides an opportunity to develop automated decision-support tools and other analytical models designed to take advantage of newly available logistical data. This research presents a tool that runs in near-real time to assess risk while conducting capacity planning and performance analysis designed for inclusion in a suite of applications dubbed the Military Logistics Network Planning System, which previously only evaluated the mean sample path. Logistical data from combat operations during Operation Iraqi Freedom drive supply requisition forecasts for a contingency scenario in a similar geographic environment. A nonstationary queueing network model is linked with a heuristic logistics scheduling methodology to provide a stochastic framework to account for uncertainty and assess risk. DA - 2019/7/10/ PY - 2019/7/10/ DO - 10.1177/1548512919860595 VL - 7 IS - 2 SP - 154851291986059 J2 - Journal of Defense Modeling & Simulation LA - en OP - SN - 1548-5129 1557-380X UR - http://dx.doi.org/10.1177/1548512919860595 DB - Crossref KW - Logistics KW - capacity planning KW - queueing KW - networks KW - forecasting KW - risk analysis KW - nonstationary arrival process KW - time-dependent arrival rate KW - dispersion ratio KW - index of dispersion for counts ER - TY - JOUR TI - Convexified H-infinity output-feedback consensus synthesis for linear multi-agent systems AU - Xue, Xiangming AU - Yuan, Chengzhi AU - Wu, Fen T2 - IET CONTROL THEORY AND APPLICATIONS AB - This study addresses the consensus problem for linear multi-agent systems subject to external disturbances under the leaderless framework. A novel distributed dynamic output feedback control protocol is proposed, which utilises not only relative output information of neighbouring agents but also relative state information of neighbouring controllers. Through model transformation, the consensus control problem of multi-agents network is reduced to a set of independent stabilisation subproblems for n -dimensional linear systems. Sufficient analysis conditions are derived using the Lyapunov method. An important contribution of this work lies in that the leaderless output-feedback consensus synthesis conditions are convexified without introducing any conservatism and formulated as linear matrix inequalities, which can be solved efficiently via convex optimisation. This is achieved by using a novel dynamic output-feedback controller structure. A numerical example has been used to demonstrate the advantage of theoretical results. DA - 2019/7/23/ PY - 2019/7/23/ DO - 10.1049/iet-cta.2018.5337 VL - 13 IS - 11 SP - 1619-1628 SN - 1751-8652 ER - TY - JOUR TI - Surrogate-Based Robust Design for a Non-Smooth Radiation Source Detection Problem AU - Stefanescu, Razvan AU - Hite, Jason AU - Cook, Jared AU - Smith, Ralph C. AU - Mattingly, John T2 - ALGORITHMS AB - In this paper, we develop and numerically illustrate a robust sensor network design to optimally detect a radiation source in an urban environment. This problem exhibits several challenges: penalty functionals are non-smooth due to the presence of buildings, radiation transport models are often computationally expensive, sensor locations are not limited to a discrete number of points, and source intensity and location responses, based on a fixed number of sensors, are not unique. We consider a radiation source located in a prototypical 250 m × 180 m urban setting. To address the non-smooth properties of the model and computationally expensive simulation codes, we employ a verified surrogate model based on radial basis functions. Using this surrogate, we formulate and solve a robust design problem that is optimal in an average sense for detecting source location and intensity with minimized uncertainty. DA - 2019/6// PY - 2019/6// DO - 10.3390/a12060113 VL - 12 IS - 6 SP - SN - 1999-4893 KW - robust design in the average sense KW - Particle Swarm KW - radial basis functions KW - radiation source detection ER - TY - JOUR TI - Recovering optimal solutions via SOC-SDP relaxation of trust region subproblem with nonintersecting linear constraints AU - Dai, Jinyu AU - Fang, Shu-Cherng AU - Xing, Wenxun T2 - Journal of Industrial & Management Optimization AB - In this paper, we study an extended trust region subproblem (eTRS) in which the unit ball intersects with $m$ linear inequality constraints. In the literature, Burer et al. proved that an SOC-SDP relaxation (SOCSDPr) of eTRS is exact, under the condition that the nonredundant constraints do not intersect each other in the unit ball. Furthermore, Yuan et al. gave a necessary and sufficient condition for the corresponding SOCSDPr to be a tight relaxation when $m = 2$. However, there lacks a recovering algorithm to generate an optimal solution of eTRS from an optimal solution $X^*$ of SOCSDPr when rank $(X^*)≥ 2$ and $m≥ 3$. This paper provides such a recovering algorithm to complement those known works. DA - 2019/// PY - 2019/// DO - 10.3934/jimo.2018117 VL - 15 IS - 4 SP - 1677-1699 LA - en OP - SN - 1553-166X UR - http://dx.doi.org/10.3934/jimo.2018117 DB - Crossref KW - Trust region subproblem KW - SOC-SDP relaxation KW - slater condition KW - matrix decomposition KW - recovering algorithm ER - TY - JOUR TI - Uncertainty quantification of two-phase flow and boiling heat transfer simulations through a data-driven modular Bayesian approach AU - Liu, Yang AU - Dinh, Nam T. AU - Smith, Ralph C. AU - Sun, Xiaodong T2 - INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER AB - In this paper, we present an approach to inversely quantify the uncertainty of MCFD simulations through a data-driven modular Bayesian inference. Both the model parameter uncertainty and the model form uncertainty are evaluated in the proposed approach. Considering the high-dimensionality of parameter space related to the solver, we performed a sensitivity analysis to reduce the input parameter dimension for the Bayesian inference. Based on the reduced parameter dimension, surrogate models based on Gaussian Process (GP) and Principal Component Analysis (PCA) are constructed to reduce the computational cost in the Bayesian inference. Two case studies based on the proposed approach are performed, focusing on two-phase flow dynamics and on wall boiling heat transfer, respectively. In case study I, we are able to construct a GP-based surrogate model based on 8 principal components to represent the total 208 MCFD solver outputs. Moreover, both cases show that the proposed approach is able to quantify and reduce the parameter uncertainties with the support of experimental measurements. The posterior uncertainties of investigated parameters have 50%-90% narrowed uncertainty ranges compared to their prior uncertainties. Furthermore, a forward uncertainty propagation of the MCFD solver with the obtained uncertainties shows that the agreement between the solver predictions and experimental measurements are significantly improved. DA - 2019/8// PY - 2019/8// DO - 10.1016/j.ijheatmasstransfer.2019.04.075 VL - 138 SP - 1096-1116 SN - 1879-2189 ER - TY - JOUR TI - Portfolio Optimization for Assets with Stochastic Yields and Stochastic Volatility AU - Pang, Tao AU - Varga, Katherine T2 - JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS DA - 2019/8// PY - 2019/8// DO - 10.1007/s10957-019-01513-y VL - 182 IS - 2 SP - 691-729 SN - 1573-2878 KW - Portfolio optimization KW - Stochastic volatility KW - Stochastic yield KW - HJB equation KW - Subsolution KW - Supersolution ER - TY - JOUR TI - Winner determination of loss-averse buyers with incomplete information in multiattribute reverse auctions for clean energy device procurement AU - Qian, Xiaohu AU - Fang, Shu-Cherng AU - Huang, Min AU - Wang, Xingwei T2 - Energy AB - Clean energy is an important source to mitigate the pressure of resources shortage and environmental effects. While multiattribute reverse auction is frequently adopted for the procurement efficiency of clean energy devices, the associated winner determination problem is explicitly studied for a utility company/buyer to select the most appropriate supplier in the clean energy market. Considering the buyer's loss-averse behavior with incomplete information and suppliers' conflicting attributes in different types evaluated by multiple experts, we incorporate an IULOWAf (induced uncertain linguistic ordered weighted averaging) operator and a revised TODIM (an acronym in Portuguese of Interactive and Multi-attribute Decision Making) measure that is consistent with prospect theory into the “benefits, opportunities, costs and risks” (BOCR) framework to develop a novel BOCR-uRTODIM solution method for multi-attribute decision making. Numerical experiments illustrate the effectiveness and robustness of the proposed method by comparing it with some known methods. An interesting result indicates that the risk aversion degree of the buyer increases as the variance of suppliers' attributes expands. The BOCR-uRTODIM could be a useful tool for utility companies to avoid losses and for associated suppliers to improve their attributes for a win in the clean energy industry. DA - 2019/6// PY - 2019/6// DO - 10.1016/j.energy.2019.04.072 VL - 177 SP - 276-292 J2 - Energy LA - en OP - SN - 0360-5442 UR - http://dx.doi.org/10.1016/j.energy.2019.04.072 DB - Crossref KW - Clean energy market KW - Reverse auction KW - Multi-attribute decision making KW - Incomplete information KW - Winner determination KW - Loss aversion ER - TY - JOUR TI - Bayesian mode and maximum estimation and accelerated rates of contraction AU - Yoo, William Weimin AU - Ghosal, Subhashis T2 - BERNOULLI AB - We study the problem of estimating the mode and maximum of an unknown regression function in the presence of noise. We adopt the Bayesian approach by using tensor-product B-splines and endowing the coefficients with Gaussian priors. In the usual fixed-in-advanced sampling plan, we establish posterior contraction rates for mode and maximum and show that they coincide with the minimax rates for this problem. To quantify estimation uncertainty, we construct credible sets for these two quantities that have high coverage probabilities with optimal sizes. If one is allowed to collect data sequentially, we further propose a Bayesian two-stage estimation procedure, where a second stage posterior is built based on samples collected within a credible set constructed from a first stage posterior. Under appropriate conditions on the radius of this credible set, we can accelerate optimal contraction rates from the fixed-in-advanced setting to the minimax sequential rates. A simulation experiment shows that our Bayesian two-stage procedure outperforms single-stage procedure and also slightly improves upon a non-Bayesian two-stage procedure. DA - 2019/8// PY - 2019/8// DO - 10.3150/18-BEJ1056 VL - 25 IS - 3 SP - 2330-2358 SN - 1573-9759 KW - anisotropic Holder space KW - credible set KW - maximum value KW - mode KW - nonparametric regression KW - posterior contraction KW - sequential KW - tensor-product B-splines KW - two-stage ER - TY - JOUR TI - A problem reduction approach for production planning using clearing functions AU - Kacar, N. Baris AU - Moench, Lars AU - Uzsoy, Reha T2 - AT-AUTOMATISIERUNGSTECHNIK AB - Zusammenfassung Eine Schwäche vieler linearer Optimierungsansätze für die Produktionsplanung besteht darin, dass sie nicht in der Lage sind, den nichtlinearen Zusammenhang zwischen Umlaufbestand und Durchlaufzeit korrekt abzubilden. Der Umlaufbestand wird dabei durch die auf Bearbeitung wartenden bzw. sich in Bearbeitung befindlichen Jobs gebildet. Nichtlineare Auslastungsfunktionen modellieren diesen Zusammenhang und haben sich als vielversprechend für die Entwicklung effektiver Formulierungen erwiesen. Die Verwendung von Auslastungsfunktionen führt aber zu viel größeren Modellen als für konventionelle Produktionsplanungsformulierungen mit festen Durchlaufzeiten. Außerdem ist erheblicher Aufwand erforderlich, um die Auslastungsfunktionen zu ermitteln. Dieser Artikel untersucht die Leistungsfähigkeit von reduzierten Modellen, bei denen lediglich eine Teilmenge der potentiell kritischen Maschinengruppen durch Auslastungsfunktionen repräsentiert wird, in Bezug auf Kosten und Gewinn. Simulationsexperimente für ein Modell einer großen Halbleiterfabrik zeigen, dass sogar dann reduzierte Modelle wesentlich weniger leistungsfähig sind als Modelle, in denen für alle Maschinengruppen Auslastungsfunktionen verwendet werden, wenn 75 % des Umlaufbestands an Maschinengruppen mit Auslastungsfunktionen anfallen. Diese Ergebnisse belegen, dass die Interaktionen zwischen den Maschinengruppen komplex sind und Modelle, die nur eine eingeschränkte Anzahl von Auslastungsfunktionen verwenden, zu einer falschen Einschätzung der Leistungsfähigkeit des Produktionssystems führen können. Das beobachtete Verhalten wird durch Analyse der Dualvariablen, die zu den Maschinengruppen gehören, erklärt. DA - 2019/6// PY - 2019/6// DO - 10.1515/auto-2018-0109 VL - 67 IS - 6 SP - 455-467 SN - 0178-2312 KW - production planning KW - clearing functions KW - model reduction KW - simulation experiments KW - semiconductor manufacturing ER - TY - JOUR TI - Modeling and Simulation of Nonstationary Non-Poisson Arrival Processes AU - Liu, Ran AU - Kuhl, Michael E. AU - Liu, Yunan AU - Wilson, James R. T2 - INFORMS JOURNAL ON COMPUTING AB - We develop CIATA, a combined inversion-and-thinning approach for modeling a nonstationary non-Poisson process (NNPP), where the target arrival process is described by a given rate function and its associated mean-value function together with a given asymptotic variance-to-mean (dispersion) ratio. CIATA is based on the following: (i) a piecewise-constant majorizing rate function that closely approximates the given rate function from above; (ii) the associated piecewise-linear majorizing mean-value function; and (iii) an equilibrium renewal process (ERP) whose noninitial interrenewal times have mean 1 and variance equal to the given dispersion ratio. Transforming the ERP by the inverse of the majorizing mean-value function yields a majorizing NNPP whose arrival epochs are then thinned to deliver an NNPP having the specified properties. CIATA-Ph is a simulation algorithm that implements this approach based on an ERP whose noninitial interrenewal times have a phase-type distribution. Supporting theorems establish that CIATA-Ph can generate an NNPP having the desired mean-value function and asymptotic dispersion ratio. Extensive simulation experiments substantiated the effectiveness of CIATA-Ph with various rate functions and dispersion ratios. In all cases, we found approximate convergence of the dispersion ratio to its asymptotic value beyond a relatively short warm-up period. The online supplement is available at https://doi.org/10.1287/ijoc.2018.0828 . DA - 2019/// PY - 2019/// DO - 10.1287/ijoc.2018.0828 VL - 31 IS - 2 SP - 347-366 SN - 1526-5528 KW - nonstationary arrival process KW - non-poisson process KW - time-dependent arrival rate KW - dispersion radio KW - index of dispersion for counts ER - TY - JOUR TI - A machine learning approach to mitigating fragmentation and crosstalk in space division multiplexing elastic optical networks AU - Xiong, Yu AU - Yang, Yaya AU - Ye, Yulong AU - Rouskas, George N. T2 - OPTICAL FIBER TECHNOLOGY AB - As network traffic is expected to continue to grow at high rates for the foreseeable future, it becomes imperative to introduce space division multiplexing elastic optical networks (SDM-EONs) into the optical transport network. However, spectrum fragmentation and crosstalk present significant challenges that may negatively impact the performance of SDM-EONs. In this paper, we leverage machine learning techniques to enhance the transmission performance of SDM-EONs, and make two contributions. Specifically, we use an Elman neural network to forecast traffic demands, and use a two-dimensional rectangular packing model to allocate spectrum so as to decrease unnecessary spectrum fragmentation (and, in turn, increase resource utilization). We also present a novel spectrum partition scheme to reduce crosstalk. Our evaluation study confirms that the proposed strategy is effective in improving spectrum utilization while reducing blocking probability and crosstalk. DA - 2019/7// PY - 2019/7// DO - 10.1016/j.yofte.2019.03.001 VL - 50 SP - 99-107 SN - 1095-9912 KW - Space division multiplexing elastic optical networks KW - Spectrum fragmentation KW - Machine learning KW - Crosstalk ER - TY - JOUR TI - Generalized stem taper and tree volume equations applied to eucalyptus of varying genetics in Brazil AU - Scolforo, Henrique Ferraco AU - McTague, John Paul AU - Burkhart, Harold AU - Roise, Joseph AU - Carneiro, Rafaela Lorenzato AU - Stape, Jose Luiz T2 - CANADIAN JOURNAL OF FOREST RESEARCH AB - Lack of generalized equations has prevailed in Brazil, because it is assumed that localized or climate-specific equations are needed. This study aimed to develop generalized stem taper and volume equations applicable to 11 eucalyptus clones and evaluate if climate variation impacts the accuracy of the estimates. A total of 693 trees evenly distributed across 11 clones at 21 sites were used for model fittings and predictive validation. The penalized mixed spline (PMS) approach was developed for predicting stem taper and volume along the stem profile. The Schumacher and Hall (1933) equation was used to predict total tree volume, while volume ratio equations were applied to predict merchantable volume. For every fitted equation, an annual climatic variable was included to assess the improvement in model performance. The overall results highlighted that climatic variation does not need to be accounted for in stem taper and volume modeling. All of the equations displayed desirable accuracy, but the generalized PMS equation may be preferred when the forestry enterprise looks to furnish a range of multiple forest products. The generalized total tree volume equation, combined with the ratio equations, is highly recommended when the forestry enterprise produces a single product. DA - 2019/5// PY - 2019/5// DO - 10.1139/cjfr-2018-0276 VL - 49 IS - 5 SP - 447-462 SN - 1208-6037 KW - penalized mixed spline KW - volume ratio KW - climate ER - TY - JOUR TI - An introduction to a new direct testing method for characterizing pressure in compression fabrics AU - Kwon, Cassandra AU - Hegarty, Meghan AU - Oxenham, William AU - Thoney-Barletta, Kristin AU - Grant, Edward AU - Reid, Lawrence T2 - JOURNAL OF THE TEXTILE INSTITUTE AB - A newly developed direct pressure measuring system known as the CRIM Pressure System was compared with a traditional direct measuring device, the PicoPress Compression System, for compression bandage and hosiery samples. PicoPress measurements were taken both on the CRIM system and on research participants. Initial results indicated a good correlation between CRIM Pressure System and PicoPress participants’ measurements. DA - 2019/6/3/ PY - 2019/6/3/ DO - 10.1080/00405000.2018.1527966 VL - 110 IS - 6 SP - 822-831 SN - 1754-2340 KW - Compression medical textiles KW - compression garments KW - interface pressure KW - body measurement KW - sensor measuring ER - TY - JOUR TI - A sub-one quasi-norm-based similarity measure for collaborative filtering in recommender systems AU - Jiang, Shan AU - Fang, Shu-Cherng AU - An, Qi AU - Lavery, John E. T2 - Information Sciences AB - Collaborative filtering (CF) is one of the most successful approaches for an online store to make personalized recommendations through its recommender systems. A neighborhood-based CF method makes recommendations to a target customer based on the similar preference of the target customer and those in the database. Similarity measuring between users directly contributes to an effective recommendation. In this paper, we propose a sub-one quasi-norm-based similarity measure for collaborative filtering in a recommender system. The proposed similarity measure shows its advantages over those commonly used similarity measures in the literature by making better use of rating values and deemphasizing the dissimilarity between users. Computational experiments using various real-life datasets clearly indicate the superiority of the proposed similarity measure, no matter in fully co-rated, sparsely co-rated or cold-start scenarios. DA - 2019/6// PY - 2019/6// DO - 10.1016/j.ins.2019.03.011 VL - 487 SP - 142-155 J2 - Information Sciences LA - en OP - SN - 0020-0255 UR - http://dx.doi.org/10.1016/j.ins.2019.03.011 DB - Crossref KW - Recommender system KW - Collaborative filtering KW - Neighborhood-based CF KW - Similarity measure KW - l(p)quasi-norm ER - TY - JOUR TI - IMMUNOSUPPRESSANT TREATMENT DYNAMICS IN RENAL TRANSPLANT RECIPIENTS: AN ITERATIVE MODELING APPROACH AU - Murad, Neha AU - Tran, H. T. AU - Banks, H. T. AU - Everett, R. A. AU - Rosenberg, Eric S. T2 - DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES B AB - Finding the optimal balance between over-suppression and under-suppression of the immune response is difficult to achieve in renal transplant patients, all of whom require lifelong immunosuppression. Our ultimate goal is to apply control theory to adaptively predict the optimal amount of immunosuppression; however, we first need to formulate a biologically realistic model. The process of quantitively modeling biological processes is iterative and often leads to new insights with every iteration. We illustrate this iterative process of modeling for renal transplant recipients infected by BK virus. We analyze and improve on the current mathematical model by modifying it to be more biologically realistic and amenable for designing an adaptive treatment strategy. DA - 2019/6// PY - 2019/6// DO - 10.3934/dcdsb.2018274 VL - 24 IS - 6 SP - 2781-2797 SN - 1553-524X KW - Inverse problem KW - infection dynamics KW - differential equations KW - renal transplantation KW - immunosuppression therapy KW - iterative modeling process KW - BKV ER - TY - JOUR TI - Message coverage maximization in infrastructure-based urban vehicular networks AU - Jalooli, Ali AU - Song, Min AU - Wang, Wenye T2 - VEHICULAR COMMUNICATIONS AB - The success of vehicular networks is highly dependent on the coverage of messages, which refers to the trajectory of messages over time. Many of the existing works primarily performed in 1-D environments (i.e., straight highways) and/or merely focused on vehicle-to-vehicle (V2V) communications to enhance the coverage in a given road network. Consequently, there still lacks a clear comprehension of using road infrastructures (e.g., roadside units), to improve the message coverage in 2-D environments (i.e., urban areas). In this paper, we study the problem of optimal utilization of roadside units in 2-D environments. Specifically, we develop a message coverage maximization algorithm (MCMA) that carefully deploys the roadside units to achieve the maximum message coverage. Considering that the vehicle density is heterogeneous across the road networks, we study the message coverage for V2V networks by deriving analytical lower bounds of message dissemination distance for areas with different vehicle densities. The MCMA then utilizes the derived lower bounds to estimate the minimum spacing allowed between neighbor roadside units based on the prevailing traffic stream and delay constraint of applications. In addition, we propose a disseminator selection algorithm for infrastructure-based urban vehicular networks to further improve the message coverage. By selecting desired types of applications (i.e., safety and non-safety), we obtain two different roadside unit deployment sets from MCMA for the evaluation purpose. Extensive simulation studies show that MCMA outperforms the alternative algorithms in terms of the message coverage and message dissemination speed. The results also demonstrate that MCMA improves traffic efficiency in a post-crash scenario. DA - 2019/4// PY - 2019/4// DO - 10.1016/j.vehcom.2019.02.001 VL - 16 SP - 1-14 SN - 2214-2096 KW - Vehicular ad-hoc network KW - Vehicle-to-vehicle KW - Roadside unit KW - Safety applications KW - Traffic efficiency KW - Intelligent transportation systems ER - TY - JOUR TI - Gradient-Free Construction of Active Subspaces for Dimension Reduction in Complex Models with Applications to Neutronics AU - Coleman, Kayla D. AU - Lewis, Allison AU - Smith, Ralph C. AU - Williams, Brian AU - Morris, Max AU - Khuwaileh, Bassam T2 - SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION AB - Recent developments in the field of reduced-order modeling---and, in particular, active subspace construction---have made it possible to efficiently approximate complex models by constructing low-order response surfaces based upon a small subspace of the original high-dimensional parameter space. These methods rely upon the fact that the response tends to vary more prominently in a few dominant directions defined by linear combinations of the original inputs, allowing for a rotation of the coordinate axis and a consequent transformation of the parameters. In this paper, we discuss a gradient-free active subspace algorithm that is feasible for high-dimensional parameter spaces where finite-difference techniques are impractical. This analysis extends the gradient-free algorithm introduced in [A. Lewis, R. Smith, and B. Williams, Comput. Math. Appl., 72 (2016), pp. 1603--1615] in two significant ways: (i) we introduce an initialization algorithm to identify lower-dimensional subspaces of influential directions to seed the gradient-free algorithm for high-dimensional problems, and (ii) we analyze dimension selection criteria to verify the algorithms. We illustrate the initialized gradient-free active subspace algorithm for a neutronics example implemented with SCALE6.1 for input dimensions up to 7700. DA - 2019/// PY - 2019/// DO - 10.1137/16M1075119 VL - 7 IS - 1 SP - 117-142 SN - 2166-2525 KW - gradient-free active subspaces KW - neutronics applications ER - TY - JOUR TI - Building conflict uncertainty into electricity planning: A South Sudan case study AU - Patankar, Neha AU - Queiroz, Anderson Rodrigo AU - DeCarolis, Joseph F. AU - Bazilian, Morgan D. AU - Chattopadhyay, Debabrata T2 - ENERGY FOR SUSTAINABLE DEVELOPMENT AB - This paper explores electricity planning strategies in South Sudan under future conflict uncertainty. A stochastic energy system optimization model that explicitly considers the possibility of armed conflict leading to electric power generator damage is presented. Strategies that hedge against future conflict have the greatest economic value in moderate conflict-related damage scenarios by avoiding expensive near-term investments in infrastructure that may be subsequently damaged. Model results show that solar photovoltaics can play a critical role in South Sudan's future electric power system. In addition to mitigating greenhouse gas emissions and increasing access to electricity, this analysis suggests that solar can be used to hedge against economic losses incurred by conflict. While this analysis focuses on South Sudan, the analytical framework can be applied to other conflict-prone countries. DA - 2019/4// PY - 2019/4// DO - 10.1016/j.esd.2019.01.003 VL - 49 SP - 53-64 SN - 0973-0826 KW - Stochastic programming KW - Conflict uncertainty KW - South Sudan ER - TY - JOUR TI - LOW-RANK MATRIX APPROXIMATIONS DO NOT NEED A SINGULAR VALUE GAP AU - Drineas, Petros AU - Ipsen, Ilse C. F. T2 - SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS AB - Low-rank approximations to a real matrix $\mathbf{A}$ can be computed from $\mathbf{Z}\mathbf{Z}^T\mathbf{A}$, where $\mathbf{Z}$ is a matrix with orthonormal columns, and the accuracy of the approximation can be estimated from some norm of $\mathbf{A}-\mathbf{Z}\mathbf{Z}^T\mathbf{A}$. We show that computing $\mathbf{A}-\mathbf{Z}\mathbf{Z}^T\mathbf{A}$ in the two-norm, Frobenius norms, and more generally any Schatten $p$-norm is a well-posed mathematical problem; and, in contrast to dominant subspace computations, it does not require a singular value gap. We also show that this problem is well-conditioned (insensitive) to additive perturbations in $\mathbf{A}$ and $\mathbf{Z}$, and to dimension-changing or multiplicative perturbations in $\mathbf{A}$---regardless of the accuracy of the approximation. For the special case when $\mathbf{A}$ does indeed have a singular values gap, connections are established between low-rank approximations and subspace angles. DA - 2019/// PY - 2019/// DO - 10.1137/18M1163658 VL - 40 IS - 1 SP - 299-319 SN - 1095-7162 UR - https://doi.org/10.1137/18M1163658 KW - singular value decomposition KW - principal angles KW - additive perturbations KW - multiplicative perturbations ER - TY - JOUR TI - Analytical foundations for development of real-time supply chain capabilities AU - Oliveira, Marcos Paulo AU - Handfield, Robert T2 - INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH AB - The emergence of real-time supply chain visibility technologies has raised challenges for organisations in developing the required management capabilities required to exploit enhanced visibility. The convergence of cloud computing, mobile technology, distributed computing, and data integration technologies has enabled managers for the first time to have real-time visibility of material flows in end to end supply chains, enhancing their ability to identify bottlenecks and disruptions of material flows anywhere in their network. To effectively harness these technologies, a new set of managerial decision-making capabilities as well as enhanced data governance disciplines will be required. In this research, we employ organisational information processing theory to explore the relationship of analytical capabilities, data quality, reporting quality, and real-time data capabilities on supply chain performance. Our research model suggests that the benefits of real-time information technologies are dependent on quality reporting and managerial analytical strengths to derive supply chain benefits. The implications for managerial applications and research are further described based on these findings. DA - 2019/3/4/ PY - 2019/3/4/ DO - 10.1080/00207543.2018.1493240 VL - 57 IS - 5 SP - 1571-1589 SN - 1366-588X UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85049803750&partnerID=MN8TOARS KW - real-time control KW - supply chain coordination KW - analytics ER - TY - JOUR TI - Performance analysis of the reserve capacity policy for dynamic VM allocation in a SaaS environment AU - Bouterse, Brian AU - Perros, Harry T2 - SIMULATION MODELLING PRACTICE AND THEORY AB - We consider a periodic-review provision scheme with constant inspection intervals for allocating dynamically virtual machines (VMs) in a Software-as-a Service (SaaS) environment. At each interval, we determine how many virtual machines (VMs) to provisioned or de-provision using a simple heuristic referred to as the reserve capacity policy, since it maintains a fixed reserve capacity of VMs. We analyze the performance of the reserve capacity policy within the context of a periodic-review provision scheme using a Markov Chain embedded at the inspection intervals. We assume a single stream of jobs with each job requiring a single VM. Jobs arrive in a Poisson fashion and the execution time of a job in a VM is exponentially distributed. We calculate the probability distribution of the number of customers in the system, the number of in-service VMs, the utilization, and the queue-length distribution of the waiting customers. The embedded Markov Chain is solved numerically. For cases where the underlying transition matrix is very large, we have proposed approximations and showed that they have a root mean square error (RMSE) of less than 2%. DA - 2019/5// PY - 2019/5// DO - 10.1016/j.simpat.2018.07.002 VL - 93 SP - 293-304 SN - 1878-1462 KW - Provision of virtual machines (VMs) KW - Embedded Markov Chain KW - Reserve capacity policy KW - Periodic-review model KW - Capacity planning ER - TY - JOUR TI - An optimal control approach for blood pressure regulation during head-up tilt AU - Williams, Nakeya D. AU - Mehlsen, Jesper AU - Tran, Hien T. AU - Olufsen, Mette S. T2 - BIOLOGICAL CYBERNETICS AB - This paper presents an optimal control approach to modeling effects of cardiovascular regulation during head-up tilt (HUT). Many patients who suffer from dizziness or light-headedness are administered a head-up tilt test to explore potential deficits within the autonomic control system, which maintains the cardiovascular system at homeostasis. This system is complex and difficult to study in vivo, and thus we propose to use mathematical modeling to achieve a better understanding of cardiovascular regulation during HUT. In particular, we show the feasibility of using optimal control theory to compute physiological control variables, vascular resistance and cardiac contractility, quantities that cannot be measured directly, but which are useful to assess the state of the cardiovascular system. A non-pulsatile lumped parameter model together with pseudo- and clinical data are utilized in the optimal control problem formulation. Results show that the optimal control approach can predict time-varying quantities regulated by the cardiovascular control system. Our results compare favorable to our previous study using a piecewise linear spline approach, less a priori knowledge is needed, and results were obtained at a significantly lower computational cost. DA - 2019/4// PY - 2019/4// DO - 10.1007/s00422-018-0783-9 VL - 113 IS - 1-2 SP - 149-159 SN - 1432-0770 KW - Cardiovascular dynamics modeling KW - Head-up tilt KW - Non-pulsatile model KW - Orthostatic intolerance KW - Optimal control ER - TY - JOUR TI - Bayesian Method for Causal Inference in Spatially-Correlated Multivariate Time Series AU - Ning, Bo AU - Ghosal, Subhashis AU - Thomas, Jewell T2 - BAYESIAN ANALYSIS AB - Measuring the causal impact of an advertising campaign on sales is an essential task for advertising companies. Challenges arise when companies run advertising campaigns in multiple stores which are spatially correlated, and when the sales data have a low signal-to-noise ratio which makes the advertising effects hard to detect. This paper proposes a solution to address both of these challenges. A novel Bayesian method is proposed to detect weaker impacts and a multivariate structural time series model is used to capture the spatial correlation between stores through placing a G-Wishart prior on the precision matrix. The new method is to compare two posterior distributions of a latent variable—one obtained by using the observed data from the test stores and the other one obtained by using the data from their counterfactual potential outcomes. The counterfactual potential outcomes are estimated from the data of synthetic controls, each of which is a linear combination of sales figures at many control stores over the causal period. Control stores are selected using a revised Expectation-Maximization variable selection (EMVS) method. A two-stage algorithm is proposed to estimate the parameters of the model. To prevent the prediction intervals from being explosive, a stationarity constraint is imposed on the local linear trend of the model through a recently proposed prior. The benefit of using this prior is discussed in this paper. A detailed simulation study shows the effectiveness of using our proposed method to detect weaker causal impact. The new method is applied to measure the causal effect of an advertising campaign for a consumer product sold at stores of a large national retail chain. DA - 2019/3// PY - 2019/3// DO - 10.1214/18-BA1102 VL - 14 IS - 1 SP - 1-28 SN - 1936-0975 KW - advertising campaign KW - Bayesian variable selection KW - causal inference KW - graphical model KW - stationarity KW - time series ER - TY - JOUR TI - Parameter subset selection techniques for problems in mathematical biology AU - Olsen, Christian Haargaard AU - Ottesen, Johnny T. AU - Smith, Ralph C. AU - Olufsen, Mette S. T2 - BIOLOGICAL CYBERNETICS AB - Patient-specific models for diagnostics and treatment planning require reliable parameter estimation and model predictions. Mathematical models of physiological systems are often formulated as systems of nonlinear ordinary differential equations with many parameters and few options for measuring all state variables. Consequently, it can be difficult to determine which parameters can reliably be estimated from available data. This investigation highlights pitfalls associated with practical parameter identifiability and subset selection. The latter refer to the process associated with selecting a subset of parameters that can be identified uniquely by parameter estimation protocols. The methods will be demonstrated using five examples of increasing complexity, as well as with patient-specific model predicting arterial blood pressure. This study demonstrates that methods based on local sensitivities are preferable in terms of computational cost and model fit when good initial parameter values are available, but that global methods should be considered when initial parameter value is not known or poorly understood. For global sensitivity analysis, Morris screening provides results in terms of parameter sensitivity ranking at a much lower computational cost. DA - 2019/4// PY - 2019/4// DO - 10.1007/s00422-018-0784-8 VL - 113 IS - 1-2 SP - 121-138 SN - 1432-0770 KW - Parameter identifiability KW - Parameter subset selection KW - Parameter estimation KW - Modeling ER - TY - JOUR TI - A direct method for accurate solution and gradient computations for elliptic interface problems AU - Chen, Xiaohong AU - Feng, Xiufang AU - Li, Zhilin T2 - NUMERICAL ALGORITHMS DA - 2019/3// PY - 2019/3// DO - 10.1007/s11075-018-0503-5 VL - 80 IS - 3 SP - 709-740 SN - 1572-9265 KW - Elliptic interface problem KW - Accurate solution and gradient computation KW - Variable coefficient with discontinuities KW - Convergence proof KW - Discrete Green's function KW - Discrete elliptic maximum principle KW - Compact finite difference scheme ER - TY - JOUR TI - Bayesian Semiparametric ROC surface estimation under verification bias AU - Zhu, Rui AU - Ghosal, Subhashis T2 - COMPUTATIONAL STATISTICS & DATA ANALYSIS AB - The Receiver Operating Characteristic (ROC) surface is a generalization of the ROC curve and is widely used for assessment of the accuracy of diagnostic tests on three categories. Verification bias occurs when not all subjects have their labels observed. This is a common problem in disease diagnosis since the gold standard test to get labels, i.e., the true disease status, can be invasive and expensive. The same situation happens in the evaluation of semi-supervised learning, where the unlabeled data are incorporated. A Bayesian approach for estimating the ROC surface is proposed based on continuous data under a semi-parametric trinormality assumption. The proposed method is then extended to situations in the presence of verification bias. The posterior distribution is computed under the trinormality assumption using a rank-based likelihood. The consistency of the posterior under a mild condition is also established. The proposed method is compared with existing methods for estimating an ROC surface. Simulation results show that it performs well in terms of accuracy. The method is applied to evaluate the performance of CA125 and HE4 in the diagnosis of epithelial ovarian cancer (EOC) as a demonstration. DA - 2019/5// PY - 2019/5// DO - 10.1016/j.csda.2018.09.003 VL - 133 SP - 40-52 SN - 1872-7352 KW - ROC surface KW - Verification bias correction KW - Trinormal model KW - MAR assumption ER - TY - JOUR TI - Sustainable supplier selection and order allocation: A novel multi-objective programming model with a hybrid solution approach AU - Moheb-Alizadeh, Hadi AU - Handfield, Robert T2 - COMPUTERS & INDUSTRIAL ENGINEERING AB - Sustainable supplier selection is the process of identifying the appropriate supply partners of an organization with the most beneficial monetary value, while diminishing the various effects of its operations on society and environment. Therefore, it plays a significant role in moving an organization toward sustainable development. Alongside sustainable supplier selection, assigning proper quantity of orders to suppliers satisfying sustainability criteria is another activity that should be simultaneously carried out in order to develop a comprehensive tool in sustainable supplier management. Meanwhile, the issue of sustainable supplier selection and order allocation has attracted limited attention in the literature. The present paper aims at developing an inclusive multi-objective mixed integer linear programming model, which accounts for multiple periods, multiple products and multimodal transportation, to evaluate suppliers and allocate order quantities. Furthermore, the developed model that includes all sustainability aspects also takes both shortage and discount conditions into account. A hybrid three-step solution methodology is then presented, using which the original multi-objective problem is firstly converted to a single objective model by ε-constraint method. In the second step, the current single objective programming model is solved using the Benders decomposition algorithm that in turn is accelerated by a variety of algorithmic enhancements. Finally, among all the Pareto optimal solutions of the original multi-objective programming problem, the preferable solution is intelligently selected based on the DEA super efficiency score of all purchasing firms as a decision support tool. The applicability of the proposed approach is illustrated by a real-world case study in automotive industry. DA - 2019/3// PY - 2019/3// DO - 10.1016/j.cie.2019.01.011 VL - 129 SP - 192-209 SN - 1879-0550 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85060500491&partnerID=MN8TOARS KW - Supplier selection KW - Order allocation KW - Sustainability KW - epsilon-constraint method KW - Benders decomposition algorithm KW - Data envelopment analysis ER - TY - JOUR TI - Optimal control of immunosuppressants in renal transplant recipients susceptible to BKV infection AU - Murad, Neha AU - Tran, H. T. AU - Banks, H. T. T2 - OPTIMAL CONTROL APPLICATIONS & METHODS AB - Summary Kidney transplant recipients are put on a lifelong regime of immunosuppressants to prevent the body from rejecting the allograft. Suppressing the immune system renders the body susceptible to infections. The key to a successful transplant is to ensure the immune system is sufficiently suppressed to prevent organ rejection but adequately strong to fight infections. Finding the optimal balance between over and undersuppression of the immune response is crucial in preventing allograft failure. In this paper, we design a feedback control formulation to predict the optimal amount of immunosuppression required by renal transplant recipients in the context of infections caused by BK virus. We use a receding horizon control methodology to construct the feedback control. Data, as they are currently collected, provide information for only some model states, so we use nonlinear Kalman filtering to estimate the remaining model states for feedback control. We conclude that, using the presented methodology, an individualized adaptive treatment schedule can be built for renal transplant recipients. DA - 2019/3// PY - 2019/3// DO - 10.1002/oca.2478 VL - 40 IS - 2 SP - 292-309 SN - 1099-1514 KW - BK virus KW - immunosuppression KW - Kalman filtering KW - optimal feedback control KW - receding horizon control KW - renal transplant ER - TY - JOUR TI - Convergence of the EDIIS Algorithm for Nonlinear Equations AU - Chen, Xiaojun AU - Kelley, C. T. T2 - SIAM Journal on Scientific Computing AB - The Energy Direct Inversion on the Iterative Subspace (EDIIS) algorithm was designed to globalize Anderson acceleration, a method for improving the performance of fixed point iteration. The motivating application is electronic structure computations. In this paper we prove a convergence result for that algorithm and illustrate the theory with a computational example. DA - 2019/1// PY - 2019/1// DO - 10.1137/18M1171084 VL - 41 IS - 1 SP - A365-A379 J2 - SIAM J. Sci. Comput. LA - en OP - SN - 1064-8275 1095-7197 UR - http://dx.doi.org/10.1137/18M1171084 DB - Crossref KW - nonlinear equations KW - Anderson acceleration KW - EDIIS ER - TY - JOUR TI - Mobility As an Alternative Communication Channel: A Survey AU - Baron, Benjamin AU - Spathis, Promethee AU - Amorim, Marcelo Dias AU - Viniotis, Yannis AU - Ammar, Mostafa H. T2 - IEEE COMMUNICATIONS SURVEYS AND TUTORIALS AB - We review the research literature investigating systems in which mobile entities can carry data while they move. These entities can be either mobile by nature (e.g., human beings and animals) or mobile by design (e.g., trains, airplanes, and cars). The movements of such entities equipped with storage capabilities create a communication channel which can help overcome the limitations or the lack of conventional data networks. Common limitations include the mismatch between the capacity offered by these networks and the traffic demand or their limited deployment owing to environmental factors. Application scenarios include offloading traffic off legacy networks for capacity improvement, bridging connectivity gaps, or deploying ad hoc networks in challenging environments for coverage enhancement. DA - 2019/// PY - 2019/// DO - 10.1109/COMST.2018.2841192 VL - 21 IS - 1 SP - 289-314 SN - 1553-877X KW - Mobility KW - data transfers KW - offloading KW - disruption-tolerant networks KW - ad-hoc networks KW - challenged networks ER - TY - JOUR TI - Valid inequalities for concave piecewise linear regression AU - Gopalswamy, Karthick AU - Fathi, Yahya AU - Uzsoy, Reha T2 - OPERATIONS RESEARCH LETTERS AB - Abstract We consider the problem of fitting a concave piecewise linear function to multivariate data using the Least Absolute Deviation objective. We propose new valid inequalities for the problem using the properties of concave functions. Results with univariate data show that the proposed valid inequalities improve the root relaxation lower bound, permitting significant improvements in solution time. DA - 2019/1// PY - 2019/1// DO - 10.1016/j.orl.2018.12.004 VL - 47 IS - 1 SP - 52-58 SN - 1872-7468 KW - Concave regression KW - Piecewise linear fitting KW - Valid inequalities KW - Clearing function ER - TY - JOUR TI - Hybrid manufacturing-Locating AM hubs using a two-stage facility location approach AU - Strong, Danielle AU - Kay, Michael AU - Conner, Brett AU - Wakefield, Thomas AU - Manogharan, Guha T2 - ADDITIVE MANUFACTURING AB - Hybrid Manufacturing is defined as the integration of Additive Manufacturing (AM), specifically metal AM, with traditional manufacturing post-processing such as heat treatment and machining. Hybrid AM enables Small and Medium Enterprises (SME) who can offer post-processing services to integrate into the growing AM supply chain. Most near-net metal AM parts require heat treatment processes (e.g. residual stress relieving/annealing) before machining to achieve final engineering specification. This research investigates a two-stage facility model to optimize the locations and capacities for new metal AM hubs which require two sequential post-processing services: heat treatment and machining. Using North American Industry Classification System (NAICS) data for machine shops and heat treatment facilities in the U.S., a p-median location model is used to determine the optimal locations for AM hub centers based on: (1) geographical data, (2) demand and (3) fixed and operational costs of hybrid-AM processing. Results from this study have identified: (a) candidate US counties to locate metal AM hubs, (b) total cost (fixed, operational and transportation), (c) capacity utilization of the AM hubs and (d) demand assignments across machine shops – heat treatment facilities – AM hubs. It was found that 2-stage p-Median model identified 22 A M hub locations as the initial sites for AM hubs which grows to 35 A M hubs as demand increases. It was also found that relatively fewer number of heat treatment facilities than machine shops resulted in a more concentrated locations of AM hubs. In addition, transportation costs were not adversely affected by the inclusion of as-build plates and showed that including heat treatment facilities as part of the hybrid AM supply chain will be mutually beneficial to all stakeholders of metal hybrid AM supply chain, i.e. AM → Heat treatment → Machining. DA - 2019/1// PY - 2019/1// DO - 10.1016/j.addma.2018.11.027 VL - 25 SP - 469-476 SN - 2214-7810 UR - https://doi.org/10.1016/j.addma.2018.11.027 KW - Additive manufacturing KW - Hybrid manufacturing KW - Heat treatment KW - Machining KW - Supply Chain KW - Facility location KW - Logistics ER - TY - JOUR TI - Modeling whole-stand survival in clonal eucalypt stands in Brazil as a function of water availability AU - Scolforo, Henrique Ferraco AU - McTague, John Paul AU - Burkhart, Harold AU - Roise, Joseph AU - Alvares, Clayton Alcarde AU - Stape, Jose Luiz T2 - FOREST ECOLOGY AND MANAGEMENT AB - Several approaches for modeling whole-stand survival or mortality have been reported in the literature, although this component is often times neglected for clonal eucalypt stands in Brazil. In addition, the traditional form for projecting whole-stand survival appears incomplete for clonal eucalypt stands, since this tree species is highly sensitive to lack of water in the environment. Consequently, this study aimed to define the best approach to estimate whole-stand survival in clonal eucalypt stands and to develop a new approach for modeling whole-stand survival as a function of cumulative soil water deficit. Remeasurement of sixteen research sites composed the database used in this study. At each research site, the same eleven eucalypt clones were planted in single block plots, which results in a total of 176 plots distributed across Brazil. Two traditional approaches (two-step approach and direct estimation) were tested for modeling whole-stand survival. Additionally a new approach that replaces the age term by cumulative soil water deficit (cumulative SWD) was compared to the best selected traditional approach to estimate whole-stand survival in clonal eucalypt stands. The direct projection approach of whole-stand survival displayed better results when compared to the two-step approach. In addition, the replacement of age by cumulative SWD in the direct estimation approach allowed for an increase in the explanatory ability of the developed difference model. The newly developed difference model employing the direct estimation approach constrained by cumulative SWD ensures that the environmental stress effect is reflected on the survival of clonal eucalypt stands over time, and it is more biologically sound for extrapolation purposes. DA - 2019/1/15/ PY - 2019/1/15/ DO - 10.1016/j.foreco.2018.10.044 VL - 432 SP - 1002-1012 SN - 1872-7042 KW - Tree mortality KW - Direct estimation KW - Environmental stress ER - TY - JOUR TI - Special issue on advanced analysis and control design of switching linear parameter-varying systems and its applications AU - Zhu, Yanzheng AU - Wu, Fen AU - Karimi, Hamid Reza AU - Lu, Bei T2 - PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING DA - 2019/1// PY - 2019/1// DO - 10.1177/0959651818819594 VL - 233 IS - 1 SP - 3-4 SN - 2041-3041 ER - TY - JOUR TI - A large-scale nesting ring multi-chip architecture for manycore processor systems AU - Li, Wenzhe AU - Guo, Bingli AU - Li, Xin AU - Zhou, Yu AU - Huang, Shanguo AU - Rouskas, George N. T2 - OPTICAL SWITCHING AND NETWORKING AB - The optical network on chip (ONoC) paradigm has emerged as a promising solution to multi-core/many-core processor systems for offering enormous bandwidth and low power consumption. As chip multiprocessors (CMPs) scale to unprecedented numbers of cores, the performance of next-generation CMPs will be bounded by the process yield and power density of single chip. In earlier work we proposed a multi-chip ONoC architecture that scales to large numbers of CMPs and delivers high performance in terms of delay and throughout. Building on that work, in this paper we propose an optimized architecture for integrating a large number of cores into chips with a novel control strategy, including a contention resolution scheme and a resource reservation scheme. The proposed control strategy is crucial to large scale ONoCs, because the resource reservation scheme ensures efficient wavelength allocation for the traffic while the contention management scheme is effective in reducing the impact of contentions. To sustain good performance and energy efficiency of large-scale ONoC, the topology is optimized to reduce the average transmission distance with minimum increase of power consumption. We evaluate the proposed architecture within a 1000-core processor system and compare it with CMesh and several previously proposed topologies with different control strategies. The simulation results show that, our new large-scale architecture can achieve better performance on throughput and delay. DA - 2019/1// PY - 2019/1// DO - 10.1016/j.osn.2018.10.004 VL - 31 SP - 183-192 SN - 1872-9770 UR - https://doi.org/10.1016/j.osn.2018.10.004 KW - ONoC KW - Large-scale KW - Routing algorithm KW - Resource reservation ER - TY - JOUR TI - Yield pattern of eucalypt clones across tropical Brazil: An approach to clonal grouping AU - Scolforo AU - McTague, J.P. AU - Burkhart, H. AU - Roise, J. AU - Campoe, O. AU - Stape, J. T2 - Forest Ecology and Management AB - The research objective of this paper was to group eleven widely planted eucalypt clones based on their volume yield pattern by assessing how climatic variation impacts their productivity in tropical Brazil. A total of 187 plots evenly distributed across eleven clones and 17 sites (from Paraná to Pará State) were used. Plot measurements were carried out every six months (from 2013 to 2017) to evaluate eucalyptus growth. Since the year of plot establishment differs across the sites, volumes of all the plots and sites were standardized at a common age of 5 years. Clonal grouping analysis was performed based on the common age for volume yields using a new approach, which consisted of three steps: (1) create general groups based on testing of the slope coefficient, which was applied to every clonal-specific regression with volume yield as a function of annual water deficit index (WDI); (2) split each general group using volume yield deviation computations into subgroups of high and low productivity; (3) apply linear mixed effects models for every subgroup in order to confirm the non-existence of statistical difference among the volume yield of the clones. Statistical tests showed satisfactory yield estimates at the common age of 5 years. Clonal grouping revealed the identification of four groups (A: high productivity and non-sensitive to climate variation, B: high productivity and sensitive to climate variation, C: low productivity and sensitive to climate variation, D: low productivity and non-sensitive to climate variation). The volume yield of the Clonal group B was detected to be the most impacted by annual water deficit index variation, followed by clonal groups C, A and D. The findings of the study highlighted the utility of the proposed approach for grouping clones. Group identification and detection of the climatic impact on yield patterns was evaluated as a measure to increase site-specific productivity. DA - 2019/// PY - 2019/// DO - 10.1016/j.foreco.2018.08.051 VL - 432 SP - 30–39 KW - Mixed effect modeling KW - Annual water deficit index KW - Productivity ER - TY - JOUR TI - Eucalyptus growth and yield system: linking individual-tree and stand-level growth models in clonal eucalypt plantations in Brazil AU - Scolforo, H. AU - McTauge, J.P. AU - Burkhart, H. AU - Roise, J. AU - Campoe, O. AU - Stape, J. T2 - Forest Ecology and Management AB - Linking individual-tree and stand-level growth models is required for estimating future forest stand structure, while maintaining the desired accuracy for forest management decision making. There is a scarcity of studies addressing this issue for clonal Eucalypt stands in Brazil. Thus, this paper aims to develop a compatible individual-tree and stand-level growth and yield system for clonal Eucalypt stands in Brazil. The dataset used in this study is derived from remeasurement information of sixteen TECHS sites. At every site, eleven Eucalypt clones were planted in single block plots, while extra plots under a rainfall exclusion regime were also installed in fourteen sites. Prediction and projection diameter percentile equations were developed, as well as an individual-tree mortality equation and a generalized height-diameter equation. In addition, a detailed explanation of the structural architecture of the developed compatible growth and yield system is provided. Differences when forecasting forest afforestation and updating forest inventories were highlighted in order to provide the proper use of the developed growth and yield system. Finally, the individual-tree equations were validated through the use of the rainfall exclusion regime plots as was the growth and yield system when applied for prediction and projection purposes. The individual-tree level equations provided accurate estimates. The newly developed compatible growth and yield system also displayed unbiased and accurate estimates. The system achieved full compatibility between individual-tree and stand-level estimates and produced accurate stand table estimates. The growth and yield system presented is a powerful analytical tool that can serve to update inventory data in tropical Brazil and also to provide estimates for expected forest afforestation. The system has the capability of providing detailed outputs, which allows forest managers to consider merchandizing the clonal Eucalypt stands into multiple products. DA - 2019/// PY - 2019/// DO - 10.1016/j.foreco.2018.08.045 VL - 432 SP - 1–16 J2 - Forest Ecology and Management LA - en OP - SN - 0378-1127 UR - http://dx.doi.org/10.1016/j.foreco.2018.08.045 DB - Crossref KW - Multiple products KW - Compatibility KW - Climate variation KW - Consistency KW - Stand table ER - TY - JOUR TI - Effective methods for solving the Bi-criteria p-Center and p-Dispersion problem AU - Tutunchi, Golbarg Kazemi AU - Fathi, Yahya T2 - COMPUTERS & OPERATIONS RESEARCH AB - Given a collection of n locations and a symmetric measure of distance (difference) between each pair of locations, we seek to identify (select) a subset of p locations so as to achieve two distinct objectives. The first objective is to minimize the maximum dissimilarity (i.e., distance) between the selected locations and other locations. The second objective is to maximize the minimum distance (diversity) among the selected locations themselves. Based on the relationship between the max-min diversity problem and the node packing problem, we propose an integer programming (IP) model and a corresponding incremental algorithm to find the non-dominated frontier for this bi-criteria optimization problem. Subsequently we use the relationship between this IP model and a corresponding set-covering problem to propose effective methods for solving the former. Finally we employ the relationship between the node packing constraints and the set covering constraints to propose a new family of valid inequalities for the corresponding IP models that are potentially effective when solving large instances of these models. Through computational experiments we demonstrate the effectiveness of our proposed methods for solving relatively large instances of this bi-criteria optimization problem. DA - 2019/1// PY - 2019/1// DO - 10.1016/j.cor.2018.08.009 VL - 101 SP - 43-54 SN - 1873-765X KW - Location KW - Max-min diversity KW - p-center partitioning KW - Integer programming KW - Valid inequalities ER - TY - JOUR TI - Multivariate Gaussian network structure learning AU - Du, Xingqi AU - Ghosal, Subhashis T2 - JOURNAL OF STATISTICAL PLANNING AND INFERENCE AB - We consider a graphical model where a multivariate normal vector is associated with each node of the underlying graph and estimate the graphical structure. We minimize a loss function obtained by regressing the vector at each node on those at the remaining ones under a group penalty. We show that the proposed estimator can be computed by a fast convex optimization algorithm. We show that as the sample size increases, the estimated regression coefficients and the correct graphical structure are correctly estimated with probability tending to one. By extensive simulations, we show the superiority of the proposed method over comparable procedures. We apply the technique on two real datasets. The first one is to identify gene and protein networks showing up in cancer cell lines, and the second one is to reveal the connections among different industries in the US. DA - 2019/3// PY - 2019/3// DO - 10.1016/j.jspi.2018.07.009 VL - 199 SP - 327-342 SN - 1873-1171 KW - Graphical model KW - Group penalty KW - Multivariate normal KW - Rate of convergence ER -