Search Results - "Loper, Margaret"

Simulation Trust and the Internet of Things by Loper, Margaret L.

“…The urban environment is becoming increasingly more connected and complex. In the coming decades, we will be surrounded by billions of sensors, devices, and…”
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The application of applied category theory to quantify mission success by Garrett, Robert K, Fairbanks, James P, Loper, Margaret L, Moreland, James D

“…Mission engineering is the quantification of the effects applied by a system of systems to achieve measurable desired results. The execution of the mission is…”
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Agent-based modeling of a stadium evacuation in a smart city by Zhang, Wenxin, Terrier, Vincent, Fei, Xiaoshu, Markov, Alex, Duncan, Scott, Balchanos, Michael, Sung, Woong Je, Mavris, Dimitri N., Loper, Margaret L., Whitaker, Elizabeth, Riley, Michael

“…The concept of Smart Cities is introduced to deal with the problems and challenges that come along with the growth of urbanization. Among all the challenges…”
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Machine to Machine Trust in Smart Cities by Loper, Margaret L., Swenson, Brian

“…In the coming decades, we will live in a world surrounded by tens of billions of devices that will interoperate and collaborate in an effort to deliver…”
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Modeling &Amp; Simulation in Systems Engineering: A Survey Course by Loper, Margaret L., Bronston, Marshall, Berenbach, Brian

“…Systems engineering is a bit different from other engineering disciplines in that students from many disciplines are enrolled in the program. Therefore, the…”
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Designing and Enabling Simulation of Real-World GPU Network Applications with ns-3 and DCE by Ivey, Jared, Riley, George, Swenson, Brian, Loper, Margaret

“…The ability to execute the original source code for network protocols and applications within a network simulation environment frees the simulation modeler…”
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Computational challenges in modeling & simulation of complex systems by Fujimoto, Richard M., Carothers, Christopher, Ferscha, Alois, Jefferson, David, Loper, Margaret, Marathe, Madhav, Taylor, Simon J. E.

“…Modeling and simulation faces many new computational challenges in the design of complex engineered systems. The systems that need to be modeled are…”
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Trust as a Service: Building and Managing Trust in the Internet of Things by Liu, Ling, Loper, Margaret

“…Trust is an abstract, multi-faceted and subjective concept. It is difficult to define trust and identify the elements that establish trust. At the same time,…”
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Modeling an emergency operations center with agents by Loper, Margaret L., Presnell, Bart

“…The Georgia Emergency Management Agency (GEMA) operates the State Operations Center, which is the centralized hub for all communications regarding state…”
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Adversarial Objectness Gradient Attacks in Real-time Object Detection Systems by Chow, Ka-Ho, Liu, Ling, Loper, Margaret, Bae, Juhyun, Gursoy, Mehmet Emre, Truex, Stacey, Wei, Wenqi, Wu, Yanzhao

“…Real-time object detection is one of the key applications of deep neural networks (DNNs) for real-world mission-critical systems. While DNN-powered object…”
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Data Poisoning and Leakage Analysis in Federated Learning by Wei, Wenqi, Huang, Tiansheng, Yahn, Zachary, Singhal, Anoop, Loper, Margaret, Liu, Ling

“…Data poisoning and leakage risks impede the massive deployment of federated learning in the real world. This chapter reveals the truths and pitfalls of…”
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Deep Neural Network Ensembles Against Deception: Ensemble Diversity, Accuracy and Robustness by Liu, Ling, Wei, Wenqi, Chow, Ka-Ho, Loper, Margaret, Gursoy, Emre, Truex, Stacey, Wu, Yanzhao

“…Ensemble learning is a methodology that integrates multiple DNN learners for improving prediction performance of individual learners. Diversity is greater when…”
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Lessons from a conceptual modeling exercise by Loper, M. L., Birta, L. G., Arbez, G.

“…There is considerable need to educate students in the process of developing conceptual models within the modeling and simulation discipline. The challenge is…”
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Exploiting temporal uncertainty in process-oriented distributed simulations by Loper, Margaret L., Fujimoto, Richard M.

“…Existing research has defined a new type of simulation time called Approximate Time, where the simulation's knowledge about the values that represent time is…”
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Robust Few-Shot Ensemble Learning with Focal Diversity-Based Pruning by Tekin, Selim Furkan, Ilhan, Fatih, Huang, Tiansheng, Hu, Sihao, Chow, Ka-Ho, Loper, Margaret L, Liu, Ling

“…This paper presents FusionShot, a focal diversity optimized few-shot ensemble learning approach for boosting the robustness and generalization performance of…”
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Cross-Layer Strategic Ensemble Defense Against Adversarial Examples by Wei, Wenqi, Liu, Ling, Loper, Margaret, Chow, Ka-Ho, Gursoy, Emre, Truex, Stacey, Wu, Yanzhao

“…Deep neural network (DNN) has demonstrated its success in multiple domains. However, DNN models are inherently vulnerable to adversarial examples, which are…”
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Educating the workforce: M&S professional education by Loper, M. L., Diem, J. W., Henninger, Amy, Petty, Mikel D., Tolk, Andreas

“…As Modeling & Simulation (M&S) becomes increasingly important, there is a significant and growing need to educate and train M&S practitioners and researchers…”
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A Framework for Evaluating Gradient Leakage Attacks in Federated Learning by Wei, Wenqi, Liu, Ling, Loper, Margaret, Chow, Ka-Ho, Gursoy, Mehmet Emre, Truex, Stacey, Wu, Yanzhao

“…Federated learning (FL) is an emerging distributed machine learning framework for collaborative model training with a network of clients (edge devices). FL…”
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PrivacyZone: A Novel Approach to Protecting Location Privacy of Mobile Users by Yigitoglu, Emre, Gursoy, Mehmet Emre, Liu, Ling, Loper, Margaret, Bamba, Bhuvan, Lee, Kisung

“…While location-based services and applications are increasing in popularity, there are growing concerns over users' location privacy. Although there exist…”
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Adversarial Deception in Deep Learning: Analysis and Mitigation by Wei, Wenqi, Liu, Ling, Loper, Margaret, Chow, Ka-Ho, Gursoy, Mehmet Emre, Truex, Stacey, Wu, Yanzhao

“…The burgeoning success of deep learning has raised the security and privacy concerns as more and more tasks are accompanied with sensitive data. Adversarial…”
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