Monica L Nogueira
Also known as: Monica L. Nogueira
Works (17)
Updated: July 5th, 2023 15:13
2022 journal article
Stability modeling for chatter avoidance in self-aware machining: an application of physics-guided machine learning
Journal of Intelligent Manufacturing.
author keywords: Physics-guided machine learning; Informed machine learning; Stability modeling; Milling; Machine learning
TL;DR:
This research explores whether data generated by an uncertain physics-based milling stability model that is used to train a physics-guided machine learning stability model, and then updated with measured data, domain knowledge, and theory-based knowledge provides a useful approximation to the unknown true stability model for a specific set of factory operating conditions.
(via Semantic Scholar)
open access via link.springer.com (publisher PDF)
Source: ORCID
Added: November 10, 2022
2021 article
Digital Twin Framework for Machine Learning-Enabled Integrated Production and Logistics Processes
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AND RESILIENT PRODUCTION SYSTEMS, APMS 2021, PT I, Vol. 630, pp. 218–227.
author keywords: Production scheduling; Supplier risk; Digital twin; Machine learning
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(Web of Science)
12. Responsible Consumption and Production
(Web of Science)
Sources: ORCID, Web Of Science, NC State University Libraries
Added: September 1, 2021
2020 journal article
Application of Machine Learning to the Prediction of Surface Roughness in Diamond Machining
Procedia Manufacturing, 48, 1029–1040.
author keywords: Ultra-precision manufacturing; machine learning; surface roughness; germanium; copper
TL;DR:
Preliminary results show that both classic machine learning methods and artificial neural network (ANN) models offer improved predictive capability when compared with analytical prediction of surface roughness for both materials.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
12. Responsible Consumption and Production
(Web of Science)
Source: ORCID
Added: June 16, 2021
2020 conference paper
Physics-Guided Machine Learning for Self-Aware Machining
2020 AAAI Spring Symposium Series on Artificial Intelligence in Manufacturing. https://aiinmanufacturing.wixsite.com/symposium/physics-guided-machine-learning-for
Source: ORCID
Added: June 16, 2021
2019 article
MANUFACTURING-UBER: Intelligent Operator Assignment in a Connected Factory
IFAC PAPERSONLINE, Vol. 52, pp. 2734–2739.
author keywords: Connected Factory; Intelligent Manufacturing Systems; Cognitive Systems; Operator Assignment; Industry 4.0
TL;DR:
Results show that Manufacturing-Uber outperforms fixed assignment with respect to reduction in required operators, increased machine up-time and more parts completed.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
12. Responsible Consumption and Production
(Web of Science)
Sources: ORCID, Web Of Science, NC State University Libraries
Added: September 4, 2019
2019 conference paper
Machine Learning Model for Surface Finish in Ultra-Precision Diamond Turning
In T. D. Hedberg & M. G. Carlisle (Eds.), Proceedings of the 10th model-based enterprise summit (MBE 2019) (pp. 131–139).
Ed(s): T. Hedberg & M. Carlisle
Event: at Gaithersburg, Maryland
Source: ORCID
Added: September 4, 2019
2016 chapter
A Data-Driven Approach to Food Safety Surveillance and Response
In S. Kennedy (Ed.), Food Protection and Security (pp. 75–99).
Ed(s): S. Kennedy
TL;DR:
This chapter describes a prototype informatics tool called NCFEDA (North Carolina Foodborne Events Data Integration and Analysis) that builds situational awareness of emerging contamination events by fusing traditional and nontraditional data sources, predictive analytics, visualization tools, and real-time collaboration across stakeholders to reduce the latency in detecting and responding to emerging contamination Events.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2013 conference paper
An Answer Set Programming Solution for Supply Chain Traceability
In A. Fred, J. L. G. Dietz, K. Liu, & J. Filipe (Eds.), Knowledge Discovery, Knowledge Engineering and Knowledge Management (pp. 211–227).
Ed(s): A. Fred, J. Dietz, K. Liu & J. Filipe
Event: at Berlin, Heidelberg
TL;DR:
This paper implements the logic-based approach called answer set programming that uses inference rules to trace the flows of contaminated products—both upstream to the source of the contamination and downstream to consumer locations.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2013 conference paper
Supply Chain Tracing of Multiple Products under Uncertainty and Incomplete Information - An Application of Answer Set Programming
Proceedings of the International Conference on Knowledge Engineering and Ontology Development, 399–406.
Event: INSTICC
TL;DR:
This paper uses the example of a recent Salmonella contamination involving tomatoes and peppers imported from Mexico into the U.S. to demonstrate the use of Answer Set Programming to localize the source of contamination in a complex supply chain characterized by uncertainty and incomplete information.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2012 conference paper
Recall-driven Product Tracing and Supply Chain Tracking using Answer Set Programming
Proceedings of the International Conference on Knowledge Engineering and Ontology Development, 125–133.
TL;DR:
This paper implements the logic-based approach called answer set programming that uses inference rules to determine the set of all companies that may be linked to a contaminated product and demonstrates this approach using the example of a food recall involving pork products.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2011 conference paper
Application of Answer Set Programming for Public Health Data Integration and Analysis
In A. M. Tjoa, G. Quirchmayr, I. You, & L. Xu (Eds.), Availability, Reliability and Security for Business, Enterprise and Health Information Systems (pp. 118–134).
Ed(s): A. Tjoa, G. Quirchmayr, I. You & L. Xu
Event: at Berlin, Heidelberg
TL;DR:
An answer set programming (ASP) application to assist public health officials in detecting an emerging foodborne disease outbreak by integrating and analyzing in near real-time temporally, spatially and symptomatically diverse data.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2011 conference paper
Rule-Based Complex Event Processing for Food Safety and Public Health
In N. Bassiliades, G. Governatori, & A. Paschke (Eds.), Rule-Based Reasoning, Programming, and Applications (pp. 376–383).
Ed(s): N. Bassiliades, G. Governatori & A. Paschke
Event: at Berlin, Heidelberg
TL;DR:
A foodborne disease outbreak is formalized as a complex event and an event-driven rulebased engine is applied to the problem of detecting emerging events to compute the strength of the evidence set as a basis for response by public health officials.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2010 report
Food Safety—Emerging Public-Private Approaches: A Perspective for Local, State, and Federal Government Leaders
In IBM Center for The Business of Government (pp. 6–43). http://www.businessofgovernment.org/sites/default/files/Food%20Safety.pdf
Source: ORCID
Added: September 4, 2019
2006 journal article
Answer set based design of knowledge systems
Annals of Mathematics and Artificial Intelligence, 47(1), 183–219.
author keywords: knowledge representation; answer set programming; reasoning; planning; diagnosis; logic programming
TL;DR:
The aim of this paper is to demonstrate that A-Prolog is a powerful language for the construction of reasoning systems by describing in detail the design of USA-Advisor, an A- prolog based decision support system for the Space Shuttle flight controllers.
(via Semantic Scholar)
Source: ORCID
Added: September 4, 2019
2001 chapter
An A-Prolog Decision Support System for the Space Shuttle
In Practical Aspects of Declarative Languages (pp. 169–183).
TL;DR:
A programming methodology based on the declarative language A-Prolog and the systems for computing answer sets of such programs, can be successfully applied to the development of medium size knowledge-intensive applications.
(via Semantic Scholar)
Source: ORCID
Added: June 16, 2021
2001 chapter
The USA-Advisor: A Case Study in Answer Set Planning
In Logic Programming and Nonmotonic Reasoning (pp. 439–442).
TL;DR:
Experimental results are presented here, illustrating how control knowledge was used to improve planning in the USA-Advisor decision support system for the Space Shuttle.
(via Semantic Scholar)
Source: ORCID
Added: June 16, 2021
1998 journal article
Why Intervals? Because If We Allow Other Sets, Tractable Problems Become Intractable
Reliable Computing, 4(4), 389–394.
TL;DR:
It is shown that if at least one non-interval set is added to the family of all intervals, then some reasonable interval computation problems that were previously computationally feasible become intractable.
(via Semantic Scholar)
Source: ORCID
Added: June 16, 2021
Employment
Updated: November 17th, 2021 16:52
2021 - present
University of North Carolina at Charlotte Charlotte, NC, US
Research Associate
Department of Mechanical Engineering and Engineering Science
2018 - 2021
North Carolina State University Raleigh, NC, US
Research Associate Professor
Poole College of Management
2006 - 2018
University of North Carolina at Chapel Hill Chapel Hill, NC, US
Senior Researcher/Digital Enterprise Lab Director
Kenan Institute of Private Enterprise
Education
Updated: June 15th, 2021 05:35
1996 - 2003
University of Texas at El Paso El Paso, TX, US
Ph.D in Computer Engineering
Computer Science
1986 - 1989
Universidade Estadual de Campinas Campinas, SP, BR
M.S. Computer Science
Instituto de Computacao
1979 - 1983
Universidade Federal do Amazonas Manaus, AM, BR
B.S. Electrical Engineering
Engineering
1979 - 1982
Instituto de Tecnologia da Amazonia Manaus, AM, BR
B.S. Electronics Engineering
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