@article{lang_thuente_ma_2023, title={Better health - A comprehensive and profound research about physical strength consumption estimation methods using machine learning}, volume={45}, ISSN={["1875-8967"]}, DOI={10.3233/JIFS-231691}, abstractNote={In order to better evaluate and promote human health, this paper analyzes the influence of different inertial-measurement-unit signals, different sensor locations, different activity intensities and different signal fusion schemes on the accuracy of physical strength consumption estimation during walking and running activities. Different pattern recognition methods, such as the Counts-based linear regression model, the typical non-linear model based on decision tree and artificial neural network, and the end-to-end convolutional neural network model, are analyzed and compared. Our findings are as follows: 1) For the locations of sensors during walking and running activities, the physical strength consumption prediction accuracy at the ankle location is higher than that at the hip location. Therefore, wearing an inertial-measurement-unit at the ankle can improve the accuracy of the model. 2) Regarding the types of activity signals during walking and running activities, the impact of accelerometer signals on hip and ankle prediction accuracy is not significantly different, while the gyroscope model is more sensitive to the location, with higher prediction accuracy at the ankle than at the hip. In addition, the physical strength consumption prediction accuracy of accelerometer signals is higher than that of gyroscope signals, and fusion of accelerometer and gyroscope signals can improve the accuracy of physical strength consumption prediction. 3) For different data analysis models during walking and running activities, the artificial neural network model that integrates different sensor locations and inertial-measurement-unit signals with different activity intensities has the lowest mean squared error for the measurement of physical strength consumption. The non-linear models based on decision tree and artificial neural network have better physical strength consumption prediction capabilities than the Counts-based linear regression model, especially for high-intensity activity energy consumption prediction. In addition, feature engineering models are generally better than convolutional neural network model in terms of overall performance and prediction results under the three different activity intensities. Furthermore, as the activity intensity increases, the performance of all physical strength consumption calculation models decreases. We recommend using the artificial neural network model based on multi-signal fusion to estimate physical strength consumption during walking and running activities because this model exhibits strong generalization ability in cross-validation and test results, and its stability under different activity intensities is better than that of the other three models. To the best of our knowledge, this paper is the first to delve deeply and in detail into methods for estimating physical strength consumption. Undoubtedly, our paper will have an impact on research related to topics such as intelligent wearable devices and subsequent methods for estimating physical strength consumption, which are directly related to physical health.}, number={6}, journal={JOURNAL OF INTELLIGENT & FUZZY SYSTEMS}, author={Lang, Liping and Thuente, David and Ma, Xiao}, year={2023}, pages={9387–9402} }
 @inproceedings{li_thuente_2017, title={Extensions and improvements of jump-stay rendezvous algorithms for cognitive radios}, DOI={10.1109/mownet.2017.8045952}, abstractNote={Modular-based channel hopping (CH) rendezvous algorithms can provide guaranteed rendezvous for Cognitive Radio Networks (CRNs) without time synchronization or Common Control Channels (i.e., blind rendezvous). The Enhanced Jump-Stay (EJS) scheme [1] has now been recognized as arguably the best in terms of Maximum-Time-To-Rendezvous (MTTR) and bounds for the Expected-Time-To-Rendezvous (ETTR) for users with a different number of channels (asymmetric). In [2], we developed a probabilistic channel detecting jamming attacks that dramatically decreased the rendezvous success rates of EJS and developed the Random Enhanced Jump Stay (REJS) CH rendezvous algorithm that largely mitigated those jamming attack. Here we provide extensions of EJS and REJS and provide guidelines when they should be used. The focus in [2] was jamming mitigation but here we carefully analyze the performance of several new algorithms while still guaranteeing bounded MTTR and improved the ETTR over EJS. In fact, it appears EJS should seldom be used. We show our jump-stay extensions are better than EJS with significant decreases in the average TTR.}, booktitle={International conference on selected topics in mobile and wireless}, author={Li, Z. F. and Thuente, D. J.}, year={2017}, pages={77–84} }
 @article{lee_sichitiu_thuente_2017, title={NEAT: Network link emulation with adaptive time dilation}, volume={104}, ISSN={["1096-0848"]}, DOI={10.1016/j.jpdc.2017.01.013}, abstractNote={In evaluating the performance of highly complex networked systems, emulation is often used as it maintains much of the realism of testbeds, while offering increased flexibility and scalability. In large emulation systems, multiple and heterogeneous virtual machines can be deployed in relatively few general purpose physical hosts. Time dilation is a technique that allows virtual time to pass at a different (and potentially variable) rate with respect to real time, allowing for increased scalability of the emulated system. In this paper we present networking links in a large emulated system employing adaptive time dilation. The link emulation focuses on accurate delay and throughput emulation while allowing varying time dilation factors. To evaluate our system, we measure the delay and throughput of the virtual links under variable system loads.}, journal={JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING}, author={Lee, Hee Won and Sichitiu, Mihail L. and Thuente, David}, year={2017}, month={Jun}, pages={88–98} }
 @inproceedings{riley_kraus_2016, title={Rain gardens: understanding their benefits and their beauty (c)}, volume={1140}, DOI={10.17660/actahortic.2016.1140.92}, booktitle={Proceedings of the 2015 annual meeting of the international plant propagators' society}, author={Riley, E. D. and Kraus, H. T.}, year={2016}, pages={409–412} }
 @article{lee_sichitiu_thuente_2015, title={High-performance emulation of heterogeneous systems using adaptive time dilation}, volume={29}, ISSN={["1741-2846"]}, DOI={10.1177/1094342014554789}, abstractNote={ Building a testbed for evaluating the performance of large-scale heterogeneous systems can be costly and inefficient. Emulation is often used to evaluate the performance of a system in a controlled environment. Time dilation allows virtual machines (VMs) to emulate higher performance than that of their physical machine. We present an approach using adaptive time dilation to emulate large-scale distributed systems composed of heterogeneous machines and Operating Systems (OSs). In our implementation, VMs are globally synchronized. To evaluate our system, distributed VMs running Linux, Windows, FreeBSD, and Junos are emulated on general-purpose physical machines. }, number={2}, journal={INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS}, author={Lee, Hee Won and Sichitiu, Mihail L. and Thuente, David}, year={2015}, pages={166–183} }
 @inproceedings{formyduval_thuente_2013, title={Priority inversion and queue management for 802.11 priority WLANs}, DOI={10.1109/ccnc.2013.6488500}, abstractNote={All priority-based IEEE 802.11 networks use the 802.11e standard or one of its variants to improve the quality of service (QoS). An enhanced data link layer, which services packets in a manner that is consistent with their priority, is proposed by the standard. Buffer management and packet scheduling are two key components of a QoS mechanism operating at this layer. The 802.11e standard includes a well-defined packet scheduler, but it does not specify a buffer management policy. Buffer management policies determine which packets are discarded during network congestion. The drop tail algorithm is the traditional approach to buffer management and is both computationally simple and widely implemented. However, we show that drop tail can significantly reduce the throughput of a typical wireless network and lead to a priority inversion. We present the reasons for this performance degradation, propose several remedies, and recommend a new buffer management policy for 802.11e networks.}, booktitle={2013 IEEE Consumer Communications and Networking Conference (CCNC)}, author={Formyduval, W. L. and Thuente, D. J.}, year={2013}, pages={565–573} }
 @inproceedings{oh_thuente_2012, title={Enhanced security of random seed DSSS algorithms against seed jamming attacks}, DOI={10.1109/glocom.2012.6503211}, abstractNote={Researchers have recently studied random spread spectrum techniques to protect the wireless broadcast communications from reactive jamming attacks in traditional Direct Sequence Spread Spectrum (DSSS) networks. They proposed mechanisms to eliminate the pre-shared key vulnerability by generating different code sequences for each message using random seeds and disclosing the seeds at the end of the message. In this paper, we present a new type of jamming attack called a seed jamming attack for the fixed message size and these seed disclosure schemes are vulnerable to it. The seed jamming attack focuses on jamming any part of the random seeds of the messages. Their sizes are relatively small and their position in messages is known to the public a priori. Thus, the receivers cannot despread any part of the messages due to the failure of regenerating proper code sequences with the corrupted seed. Jamming the seed precludes the use of any possible FEC since the receiver cannot decode any bits in the message. To overcome the seed attack, we propose an advanced random seed DSSS (ARS-DSSS) scheme which strengthens the previous algorithm called DSD-DSSS [4] by using an additional location seed. The new seed avoids the seed jamming attack by using variable message sizes instead of using known fixed message sizes while incurring almost no additional performance overhead. Our security analysis and implementation results demonstrate how to defeat the seed jamming attacks and how to reduce the computation overhead of DSD-DSSS from the cardinality of seed code set Ce to 1.}, booktitle={2012 ieee global communications conference (globecom)}, author={Oh, Y. H. and Thuente, D. J.}, year={2012}, pages={801–806} }
 @article{sheng_thuente_2011, title={Contextual Decision Making in General Game Playing}, ISSN={["1082-3409"]}, DOI={10.1109/ictai.2011.108}, abstractNote={General Game Playing refers to designing Artificial Intelligence agents that are capable of playing different games without human intervention. The games are defined by sets of rules represented in logic descriptions and the agent players interact in a multi-agent system with a game server coordinating the legality of the operations and keeping the players informed of the state changes. This paper describes a general game agent that isolates the heuristic search coverage for contextual decision making by efficiently creating dynamic decision trees. The influence of certain game features is evaluated within the current decision context rather than on the whole game scale. The benefit of this approach is shown by performance comparison with agents that do search, learning, and learning with decision trees. We show this for a variety of games and have compared favorably against well known general game players and replicated actions of known human expert strategies.}, journal={2011 23RD IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2011)}, author={Sheng, Xinxin and Thuente, David}, year={2011}, pages={679–684} }
 @inproceedings{prasad_thuente_2011, title={Jamming attacks in 802.11g-a cognitive radio based approach}, DOI={10.1109/milcom.2011.6127467}, abstractNote={Wireless networks are susceptible to jamming attacks, which can severely reduce the network throughput. In this paper, we study the behavior and the performance of 802.11g networks under a hybrid jamming attack of configuring a cognitive radio as a jammer. With characteristics such as fast channel switching, quick response time and software reconfigurability, cognitive radios can be used not only to improve the spectrum sharing management, but also to act as an effective jammer. We use a single cognitive radio to simultaneously jam three networks in an energy efficient manner and also to deny any channel change protocol by the targeted network to avoid jamming. We attack the ‘g’ band OFDM channels directly using the fast channel switching capability of the cognitive radio. The jammer sequentially senses traffic on each of the networks without being part of any network. We present the results of the jamming attacks at the MAC and physical layers. We show how the cognitive radio can dynamically adjust its attack to the traffic on each network. We evaluated the performance of three networks individually and together under intelligent and reactive jamming.}, booktitle={2011 - Milcom 2011 Military Communications Conference}, author={Prasad, S. and Thuente, D. J.}, year={2011}, pages={1219–1224} }