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IEEE Annual Conference on Decision and Control

作者： Dinuka Sahabandu Shana Moothedath Joey Allen Andrew Clark Linda Bushnell Wenke Lee Radha Poovendran Department of Electrical and Computer Engineering University of Washington Seattle WA USA College of Computing Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

Dynamic Information Flow Tracking (DIFT) has been proposed to detect and prevent various cyber attacks in computer systems. DIFT tracks suspicious information flows in the system and generates security analysis when anomalous behavior is detected. A system threatened by attackers of different capabilities demands simultaneous analysis of multiple flows. As the number of information flows in a system is typically large and the amount of resource required for analyzing different flows varies, an optimal allocation of the limited resources available to DIFT is essential. We address the problem of detecting multiple attackers using resource constrained DIFT and develop a model that captures the interaction of adversaries and a DIFT-based defender as a multi-player dynamic game. Our model consists of a multi-stage game, in which each stage represents the subset of processes in the system that correspond to the locations of the information flows, and captures the notion of benign flows. Given the attackers' strategies, we prove that finding an optimal defense strategy is equivalent to maximizing an increasing DR-submodular function that enables us to propose an approximation algorithm. Further, given a defense strategy and strategies of other attackers, we show that finding an optimal attacker strategy is equivalent to solving a shortest path problem, where the edge weights are derived from the strategies of the other players. Based on this mapping we propose a polynomial-time algorithm for computing an optimal attacker strategy. Finally, we evaluate the performance of our algorithm on a real-world dataset of a nation state attack obtained using the Refinable Attack INvestigation (RAIN) framework.

关键词： Games Resource management computer security Approximation algorithms Computational modeling Memory management

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Chinese E-romance: Analyzing and visualizing 7.92 million Alibaba Valentine's day purchases

arXiv

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arXiv 2020年

作者： Wang, Yongzhen Liu, Xiaozhong Ju, Yingnan Börner, Katy Lin, Jun Sun, Changlong Si, Luo Wise Lab Institute of Science of Science and S and T Management Faculty of Humanities and Social Sciences Dalian University of Technology Dalian116024 China Computer Science Department Worcester Polytechnic Institute WorcesterMA01609 United States School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Alibaba Damo Academy Hangzhou310030 China

The days that precede Valentine's Day are characterized by extensive gift shopping activities all across the globe. In China, where much shopping takes place online, there has been an explosive growth in e-commerce sales during Valentine's Day over the recent years. This exploratory study investigates the extent to which each product category and each shopper group can exhibit romantic love within China's emarket throughout the 2 weeks leading up to 2019 Valentine's Day. Massive data from Alibaba, the biggest e-commerce retailer worldwide, are utilized to formulate an innovative romance index (RI) to quantitatively measure e-romantic values for products and shoppers. On this basis, millions of shoppers, along with their millions of products purchased around Valentine's Day, are analyzed as a case study to demonstrate their love consumption and romantic gift-giving. The results of the analysis are then illustrated to help understand Chinese e-romance based on the perspectives of different product categories and shopper groups. This empirical information visualization also contributes to improving the segmentation, targeting, and positioning of China's e-market for Valentine's Day. Copyright © 2020, The Authors. All rights reserved.

关键词： Electronic commerce

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Secure control under partial observability with temporal logic constraints

arXiv

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arXiv 2019年

作者： Ramasubramanian, Bhaskar Clark, Andrew Bushnell, Linda Poovendran, Radha Network Security Lab Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

This paper studies the synthesis of control policies for an agent that has to satisfy a temporal logic specification in a partially observable environment, in the presence of an adversary. The interaction of the agent (defender) with the adversary is modeled as a partially observable stochastic game. The search for policies is limited to over the space of finite state controllers, which leads to a tractable approach to determine policies. The goal is to generate a defender policy to maximize satisfaction of a given temporal logic specification under any adversary policy. We relate the satisfaction of the specification in terms of reaching (a subset of) recurrent states of a Markov chain. We then present a procedure to determine a set of defender and adversary finite state controllers of given sizes that will satisfy the temporal logic specification. We illustrate our approach with an example. Copyright © 2019, The Authors. All rights reserved.

关键词： Temporal logic

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Ultra-heavy dark matter search with electron microscopy of geological quartz

arXiv

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arXiv 2021年

作者： Ebadi, Reza Mathur, Anubhav Tanin, Erwin H. Tailby, Nicholas D. Marshall, Mason C. Ravi, Aakash Trubko, Raisa Fu, Roger R. Phillips, David F. Rajendran, Surjeet Walsworth, Ronald L. Department of Physics University of Maryland College ParkMD20742 United States Quantum Technology Center University of Maryland College ParkMD20742 United States Department of Physics and Astronomy Johns Hopkins University 3400 N. Charles St. BaltimoreMD21218 United States Department of Earth and Planetary Sciences American Museum of Natural History New YorkNY10024 United States Department of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Harvard-Smithsonian Center for Astrophysics CambridgeMA02138 United States Department of Physics Worcester Polytechnic Institute WorcesterMA01609 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Earth and Planetary Sciences Harvard University CambridgeMA02138 United States

Self-interactions within the dark sector could clump dark matter into heavy composite states with low number density, leading to a highly suppressed event rate in existing direct detection experiments. However, the large interaction cross section between such ultra-heavy dark matter (UHDM) and standard model matter results in a distinctive and compelling signature: long, straight damage tracks as they pass through and scatter with matter. In this work, we propose using geologically old quartz samples as large-exposure detectors for UHDM. We describe a high-resolution readout method based on electron microscopy, characterize the most favorable geological samples for this approach, and study its reach in a simple model of the dark sector. The advantage of this search strategy is two-fold: the age of geological quartz compensates for the low number density of UHDMs, and the distinct geometry of the damage track serves as a high-fidelity background rejection tool. © 2021, CC BY.

关键词： Electron microscopy

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BATS: A spectral biclustering approach to single document topic modeling and segmentation

arXiv

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arXiv 2020年

作者： Wu, Qiong Hare, Adam Wang, Sirui Tu, Yuwei Liu, Zhenming Brinton, Christopher G. Li, Yanhua Department of Computer Science College of William and Mary 200 Stadium Dr WilliamsburgVA23185 United States Zoomi Inc. 325 Sentry Parkway Suite 200 Blue BellPA19422 United States School of Electrical and Computer Engineering Purdue University 610 Purdue Mall West LafayetteIN47907 United States Department of Computer Science Worchester Polytechnic Institute 100 Institute Rd WorcesterMA01609 United States

Existing topic modeling and text segmentation methodologies generally require large datasets for training, limiting their capabilities when only small collections of text are available. In this work, we reexamine the inter-related problems of "topic identification" and "text segmentation" for sparse document learning, when there is a single new text of interest. In developing a methodology to handle single documents, we face two major challenges. First is sparse information: with access to only one document, we cannot train traditional topic models or deep learning algorithms. Second is significant noise: a considerable portion of words in any single document will produce only noise and not help discern topics or segments. To tackle these issues, we design an unsupervised, computationally efficient methodology called BATS: Biclustering Approach to Topic modeling and Segmentation. BATS leverages three key ideas to simultaneously identify topics and segment text: (i) a new mechanism that uses word order information to reduce sample complexity, (ii) a statistically sound graph-based biclustering technique that identifies latent structures of words and sentences, and (iii) a collection of effective heuristics that remove noise words and award important words to further improve performance. Experiments on six datasets show that our approach outperforms several state-of-the-art baselines when considering topic coherence, topic diversity, segmentation, and runtime comparison metrics. Copyright © 2020, The Authors. All rights reserved.

关键词： Large dataset

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Methods and outcomes of the NSF project on synthesizing environments for digitally-mediated team learning 126

Methods and outcomes of the NSF project on synthesizing envi...

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126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019

作者： DeMara, Ronald F. Campbell, Laurie O. Hartshorne, Richard Dagley, Melissa A. Spiegel, Sam Tian, Tian Tian Chen, Zhongzhou Donnelly, Julie Tatulian, Adrian Hernandez, Florencio Eloy Sheikhfaal, Shadi Pourmeidani, Hossein Esteves, Hans Beck, Joseph E. Gibson, Tara University of Central Florida United States Colorado School of Mines United States Department of Chemistry Karen L. Smith Faculty Center for Teaching and Learning University of Central Florida United States Department of Electrical and Computer Engineering Department of Learning Sciences and Educational Research Department of Physics Center for Initiatives in Science Technology Engineering and Mathematics Department of Chemistry Department of Mechanical and Aerospace Engineering Division of Digital Learning University of Central Florida OrlandoFL32816 United States Trefny Innovative Instruction Center University of Colorado Mines GoldenCO80401 United States Department of Computer Science Worcester Polytechnic Institute WorcesterMA01609 United States

This poster paper describes the authors' single-year National Science Foundation (NSF) project DRL-1825007 titled, "DCL: Synthesis and Design Workshop on Digitally-Mediated Team Learning" which has been conducted as one of nine awards within NSF-18-017: Principles for the Design of Digital STEM Learning Environments. Beginning in September 2018, the project conducted the activities herein to deliver a three-day workshop on Digitally-Mediated Team Learning (DMTL) to convene, invigorate, and task interdisciplinary science and engineering researchers, developers, and educators to coalesce the leading strategies for digital team learning. The deliverable of the workshop is a White Paper composed to identify one-year, three-year, and five-year research and practice roadmaps for highly-adaptable environments for computer-supported collaborative learning within STEM curricula. As subject to the chronology of events, highlights of the White Paper's outcomes will be showcased within the poster itself. Collaborations during this workshop identified near-term and future research directions to facilitate adaptable digital environments for highly-effective, rewarding, and scalable team-based learning. An emphasis of the workshop included the personalization of collaborations among diverse learners by automating the identification and utilization of learners' efficacies and knowledge gaps to create complementary collaborative teams that maximize avenues for peer teaching and learning. The workshop targeted the utilization and efficacy of next-generation learning architectures through a focus on instructional technologies that facilitate digitally-mediated team-based learning. These included technical objectives of: (1) identifying new research in learning analytics required to automate more optimal composition, formation, and adaptation of learner design teams;(2) detecting advances in physical and virtual learning environments that can achieve more effective and scalable observa

关键词： Curricula

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Area Determination of Diabetic Foot Ulcer Images Using a Cascaded Two-Stage SVM-Based Classification

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IEEE Transactions on Biomedical engineering 2017年第9期64卷 2098-2109页

作者： Wang, Lei Pedersen, Peder C. Agu, Emmanuel Strong, DIane M. Tulu, Bengisu Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute United States Department of Computer Science Worcester Polytechnic Institute United States Foisie School of Business Worcester Polytechnic Institute United States

The standard chronic wound assessment method based on visual examination is potentially inaccurate and also represents a significant clinical workload. Hence, computer-based systems providing quantitative wound assessment may be valuable for accurately monitoring wound healing status, with the wound area the best suited for automated analysis. Here, we present a novel approach, using support vector machines (SVM) to determine the wound boundaries on foot ulcer images captured with an image capture box, which provides controlled lighting and range. After superpixel segmentation, a cascaded two-stage classifier operates as follows: In the first stage, a set of k binary SVM classifiers are trained and applied to different subsets of the entire training images dataset, and incorrectly classified instances are collected. In the second stage, another binary SVM classifier is trained on the incorrectly classified set. We extracted various color and texture descriptors from superpixels that are used as input for each stage in the classifier training. Specifically, color and bag-of-word representations of local dense scale invariant feature transformation features are descriptors for ruling out irrelevant regions, and color and wavelet-based features are descriptors for distinguishing healthy tissue from wound regions. Finally, the detected wound boundary is refined by applying the conditional random field method. We have implemented the wound classification on a Nexus 5 smartphone platform, except for training which was done offline. Results are compared with other classifiers and show that our approach provides high global performance rates (average sensitivity = 73.3%, specificity = 94.6%) and is sufficiently efficient for a smartphone-based image analysis. © 2017 IEEE.

关键词： Support vector machines

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State Estimation for Mitigating Positioning Errors in V2V Networks Employing Dual Beamforming

State Estimation for Mitigating Positioning Errors in V2V Ne...

引用

IEEE Vehicular Technology Conference

作者： Nivetha Kanthasamy Raghvendra V. Cowlagi Alexander M. Wyglinski Department of Mechanical Engineering Worcester Polytechnic Institute Department of Electrical and Computer Engineering Worcester Polytechnic Institute

ISBN: (纸本)9781538663592;9781538663585

In this paper, we present a novel approach for mitigating positioning errors in vehicle-to-vehicle (V2V) networking environments where digital beamforming is conducted at both transmitters and receivers. Location information of all transmitters and receivers in V2V networks performing beamforming is essential in order to ensure reliable link quality. However, there exists several sources of error where this location information can be corrupted or out-of-date. By leveraging the proposed approach in this paper employing state estimation, these errors can be mitigated, thus providing more accurate location information relative to V2V networking architectures that do not employ techniques to help mitigate potential sources of location error. Simulation results show a 99% improvement of the proposed approach relative to V2V beamformiong architectures that do not account for location errors.

关键词： POSITION INFORMATION V2V location error State estimation Error Sources Beamforming Transmitters Receivers

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Assessment of Positioning Errors on V2V Networks Employing Dual Beamforming

Assessment of Positioning Errors on V2V Networks Employing D...

引用

IEEE Vehicular Technology Conference

作者： Nivetha Kanthasamy Ruixiang Du Kuldeep S. Gill Alexander M. Wyglinski Raghvendra Cowlagi Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA Department of Mechanical Engineering Worcester Polytechnic Institute Worcester MA

ISBN: (纸本)9781538663592;9781538663585

In this paper, we present an analysis of Vehicle-to-Vehicle (V2V) Networks employing beamforming at both the transmitter and the receiver when positioning errors are present. Specifically, we will examine the performance of this system setup when the source of the positioning errors are from the Global Positioning System (GPS) measurements as well as from variations in the delays due to the overhead communication channels. To achieve adequate performance, beamforming requires precise location information of the transmitter and the receiver, and when accurate information is unavailable the system performance can potentially deteriorate. This is especially challenging in highly mobile vehicle networking environments where the operating conditions and location information varies rapidly in time. Simulation results are obtained showing Bit Error Rate (BER) values increasing by 99.9% when the exact GPS locations are known by the vehicles when compared to a 6.6m error in GPS location.

关键词： array signal processing error statistics Global Positioning System mobile radio location error Global Positioning Systems Mobile radios array signal processing POSITION INFORMATION Beamforming V2V transmitter receivers Error analysis System performance

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On The Capacity Bounds For Bumblebee-Inspired Connected Vehicle Networks Via Queuing Theory

On The Capacity Bounds For Bumblebee-Inspired Connected Vehi...

引用

IEEE Vehicular Technology Conference

作者： Kuldeep Gill Kevin N. Heath Robert J. Gegear Elizabeth F. Ryder Alexander M. Wyglinski Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA Department of Biology & Biotechnology Worcester Polytechnic Institute Worcester MA

The bumblebee has recently been proposed as a model to optimize channel allocation in connected vehicle networks where the quality of each channel varies unpredictably over time and space. A fundamental mathematical challenge that must be overcome before implementing the bumblebee model is determining the theoretical upper bound of spectrum optimization that can be achieved under such stochastic channel conditions. In this paper, we leverage the concept of queuing theory in order to conduct the performance bound analysis of bumblebee-inspired distributed optimization operation in vehicle-to-vehicle (V2V) environments. We initially established the maximum switching costs associated with urban and highway environment, and then used GEMV~2 and SUMO to compute the performance bounds for several metrics in a time-variant urban environment, including P_m (the probability of all channels being busy) and mean response time. We discuss the implications of these results for future development of bumblebee-inspired vehicular communication systems.

关键词： Optimization Switches Queueing analysis Servers Computational modeling Mathematical model Road transportation

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