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2017

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Articles 1621 - 1650 of 2767

Full-Text Articles in Computer Sciences

Theory And Applications Of Network Structure Of Complex Dynamical Systems, Vasu Nephi Chetty Mar 2017

Theory And Applications Of Network Structure Of Complex Dynamical Systems, Vasu Nephi Chetty

Theses and Dissertations

One of the most powerful properties of mathematical systems theory is the fact that interconnecting systems yields composites that are themselves systems. This property allows for the engineering of complex systems by aggregating simpler systems into intricate patterns. We call these interconnection patterns the "structure" of the system. Similarly, this property also enables the understanding of complex systems by decomposing them into simpler parts. We likewise call the relationship between these parts the "structure" of the system. At first glance, these may appear to represent identical views of structure of a system. However, further investigation invites the question: are these …

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Activityaware: An App For Real-Time Daily Activity Level Monitoring On The Amulet Wrist-Worn Device, George Boateng, Ryan Halter, John A. Batsis, David Kotz Mar 2017

Activityaware: An App For Real-Time Daily Activity Level Monitoring On The Amulet Wrist-Worn Device, George Boateng, Ryan Halter, John A. Batsis, David Kotz

Dartmouth Scholarship

Physical activity helps reduce the risk of cardiovascular disease, hypertension and obesity. The ability to monitor a person's daily activity level can inform self-management of physical activity and related interventions. For older adults with obesity, the importance of regular, physical activity is critical to reduce the risk of long-term disability. In this work, we present ActivityAware, an application on the Amulet wrist-worn device that measures daily activity levels (sedentary, moderate and vigorous) of individuals, continuously and in real-time. The app implements an activity-level detection model, continuously collects acceleration data on the Amulet, classifies the current activity level, updates the day's …

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Improving Automated Bug Triaging With Specialized Topic Model, Xin Xia, David Lo, Ying Ding, Jafar M. Al-Kofahi, Tien N. Nguyen, Xinyu Wang Mar 2017

Improving Automated Bug Triaging With Specialized Topic Model, Xin Xia, David Lo, Ying Ding, Jafar M. Al-Kofahi, Tien N. Nguyen, Xinyu Wang

Research Collection School Of Computing and Information Systems

Bug triaging refers to the process of assigning a bug to the most appropriate developer to fix. It becomes more and more difficult and complicated as the size of software and the number of developers increase. In this paper, we propose a new framework for bug triaging, which maps the words in the bug reports (i.e., the term space) to their corresponding topics (i.e., the topic space). We propose a specialized topic modeling algorithm named multi-feature topic model (MTM) which extends Latent Dirichlet Allocation (LDA) for bug triaging. MTM considers product and component information of bug reports to map the …

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Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu Mar 2017

Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu

Research Collection School Of Computing and Information Systems

Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …

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Using Intel Realsense Depth Data For Hand Tracking In Unreal Engine 4, Granger Lang Mar 2017

Using Intel Realsense Depth Data For Hand Tracking In Unreal Engine 4, Granger Lang

Liberal Arts and Engineering Studies

This project describes how to build a hand tracking method for VR/AR using the raw data from a depth sensing camera.

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Metric Similarity Joins Using Mapreduce, Yunjun Gao, Keyu Yang, Lu Chen, Baihua Zheng, Gang Chen, Chun Chen Mar 2017

Metric Similarity Joins Using Mapreduce, Yunjun Gao, Keyu Yang, Lu Chen, Baihua Zheng, Gang Chen, Chun Chen

Research Collection School Of Computing and Information Systems

Given two object sets Q and O , a metric similarity join finds similar object pairs according to a certain criterion. This operation has a wide variety of applications in data cleaning, data mining, to name but a few. However, the rapidly growing volume of data nowadays challenges traditional metric similarity join methods, and thus, a distributed method is required. In this paper, we adopt a popular distributed framework, namely, MapReduce, to support scalable metric similarity joins. To ensure the load balancing, we present two sampling based partition methods. One utilizes the pivot and the space-filling curve mappings to cluster …

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Interdependent Defense Games With Applications To Internet Security At The Level Of Autonomous Systems, Hau Chan, M. Ceyko, L. Ortiz Mar 2017

Interdependent Defense Games With Applications To Internet Security At The Level Of Autonomous Systems, Hau Chan, M. Ceyko, L. Ortiz

Computer Science Faculty Research

We propose interdependent defense (IDD) games, a computational game-theoretic framework to study aspects of the interdependence of risk and security in multi-agent systems under deliberate external attacks. Our model builds upon interdependent security (IDS) games, a model by Heal and Kunreuther that considers the source of the risk to be the result of a fixed randomized-strategy. We adapt IDS games to model the attacker’s deliberate behavior. We define the attacker’s pure-strategy space and utility function and derive appropriate cost functions for the defenders. We provide a complete characterization of mixed-strategy Nash equilibria (MSNE), and design a simple …

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Effective K-Vertex Connected Component Detection In Large-Scale Networks, Yuan Li, Yuha Zhao, Guoren Wang, Feida Zhu, Yubao Wu, Shenglei Shi Mar 2017

Effective K-Vertex Connected Component Detection In Large-Scale Networks, Yuan Li, Yuha Zhao, Guoren Wang, Feida Zhu, Yubao Wu, Shenglei Shi

Research Collection School Of Computing and Information Systems

Finding components with high connectivity is an important problem in component detection with a wide range of applications, e.g., social network analysis, web-page research and bioinformatics. In particular, k-edge connected component (k-ECC) has recently been extensively studied to discover disjoint components. Yet many real applications present needs and challenges for overlapping components. In this paper, we propose a k-vertex connected component (k-VCC) model, which is much more cohesive and therefore allows overlapping between components. To find k-VCCs, a top-down framework is first developed to find the exact k-VCCs. To further reduce the high computational cost for input networks of large …

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Version-Sensitive Mobile App Recommendation, Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Jialie Shen, Shunxiang Wu, Tat-Seng Chua Mar 2017

Version-Sensitive Mobile App Recommendation, Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Jialie Shen, Shunxiang Wu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Being part and parcel of the daily life for billions of people all over the globe, the domain of mobile Applications (Apps) is the fastest growing sector of mobile market today. Users, however, are frequently overwhelmed by the vast number of released Apps and frequently updated versions. Towards this end, we propose a novel version-sensitive mobile App recommendation framework. It is able to recommend appropriate Apps to right users by jointly exploring the version progression and dual-heterogeneous data. It is helpful for alleviating the data sparsity problem caused by version division. As a byproduct, it can be utilized to solve …

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Social Tag Relevance Learning Via Ranking-Oriented Neighbor Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian Mar 2017

Social Tag Relevance Learning Via Ranking-Oriented Neighbor Voting, Chaoran Cui, Jialie Shen, Jun Ma, Tao Lian

Research Collection School Of Computing and Information Systems

High quality tags play a critical role in applications involving online multimedia search, such as social image annotation, sharing and browsing. However, user-generated tags in real world are often imprecise and incomplete to describe the image contents, which severely degrades the performance of current search systems. To improve the descriptive powers of social tags, a fundamental issue is tag relevance learning, which concerns how to interpret the relevance of a tag with respect to the contents of an image effectively. In this paper, we investigate the problem from a new perspective of learning to rank, and develop a novel approach …

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Efficient Motif Discovery In Spatial Trajectories Using Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Kai Wang Mar 2017

Efficient Motif Discovery In Spatial Trajectories Using Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Kai Wang

Research Collection School Of Computing and Information Systems

The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between discrete trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering the pair of most similar subtrajectories, be them parts of the same or of different input trajectories.The identified pair of subtrajectories is called a motif.The adoption of DFD as the similarity measure in motif discovery,although semantically ideal, is hindered by the high computational complexity of DFD calculation. In this paper, we propose a suite …

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Location Matters: Geospatial Policy Analytics Over Time For Household Hazardous Waste Collection In California, Kustini Lim-Wavde, Robert John Kauffman, Tin Seong Kam, Gregory S. Dawson Mar 2017

Location Matters: Geospatial Policy Analytics Over Time For Household Hazardous Waste Collection In California, Kustini Lim-Wavde, Robert John Kauffman, Tin Seong Kam, Gregory S. Dawson

Research Collection School Of Computing and Information Systems

By integrating mapping and geospatial data into a county-level datasetfor exploratory analysis, we will demonstrate how to provide useful insightsfor waste managers and local governments regarding spatial patterns ofhousehold hazardous waste (HHW) collection and how it changes over time. We usemap-based visualization to display patterns of spatial intensity and countylocations for HHW collection in California from 2004 to 2015. We use exploratory spatial data analyticsmethods to characterize the spatial distribution of HHW collected per person.When we considered the spatial relationships, we were able to develop andestimate a geographically-weighted regression to explain how different regionalfactors influence the amount of HHW collected. …

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Scalable Image Retrieval By Sparse Product Quantization, Qingqun Ning, Jianke Zhu, Zhiyuan Zhong, Steven C. H. Hoi, Chun Chen Mar 2017

Scalable Image Retrieval By Sparse Product Quantization, Qingqun Ning, Jianke Zhu, Zhiyuan Zhong, Steven C. H. Hoi, Chun Chen

Research Collection School Of Computing and Information Systems

Fast approximate nearest neighbor (ANN) search technique for high-dimensional feature indexing and retrieval is the crux of large-scale image retrieval. A recent promising technique is product quantization, which attempts to index high-dimensional image features by decomposing the feature space into a Cartesian product of low-dimensional subspaces and quantizing each of them separately. Despite the promising results reported, their quantization approach follows the typical hard assignment of traditional quantization methods, which may result in large quantization errors, and thus, inferior search performance. Unlike the existing approaches, in this paper, we propose a novel approach called sparse product quantization (SPQ) to encoding …

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The Wonders Of The Spreadsheet Tool For Data Management And Insights, Michelle L. F. Cheong Mar 2017

The Wonders Of The Spreadsheet Tool For Data Management And Insights, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Ask any student at the Singapore Management University (SMU) toname one of the most practical and useful courses offered by theuniversity. The answer would inevitably include CAT. CAT stands forthe "Computer as an Analysis Tool" course. Originally based on acourse of the same title offered by the Wharton Business School, thefocus of CAT was shifted to provide business students the essentialpractical skills and necessary “real-world” exposure to better usepersonal computers for resolving business problems. The course isbasically centred on using the Excel spreadsheet to work onambiguous ill-defined problems (Leong & Cheong, 2009). Over theyears, three editions of a textbook have …

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Are The Trade-Offs For Reducing Cross-Border Cybercrime Manageable?, Steven Mark Miller, Qiu-Hong Wang, Robert John Kauffman Mar 2017

Are The Trade-Offs For Reducing Cross-Border Cybercrime Manageable?, Steven Mark Miller, Qiu-Hong Wang, Robert John Kauffman

Research Collection School Of Computing and Information Systems

Without increased government intervention and government-industry collaboration, the advantages inherent in the next wave of Internet-enabled digital transformation will increasingly tilt toward cybercriminals, and their influence will disproportionately increase. The dilemma that immediately presents itself in such a scenario, however, is that an increased level of government involvement can also lead to undesirable consequences. Increasing security always comes with trade-offs that must be managed. The obvious concerns relate to the erosion of privacy, illegal or extralegal persecution, the abuse of Internet censorship and the impediment to or stifling of innovation.

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Mining Sandboxes For Linux Containers, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai, Shanping Li Mar 2017

Mining Sandboxes For Linux Containers, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai, Shanping Li

Research Collection School Of Computing and Information Systems

A container is a group of processes isolated from other groups via distinct kernel namespaces and resource allocation quota. Attacks against containers often leverage kernel exploits through system call interface. In this paper, we present an approach that mines sandboxes for containers. We first explore the behaviors of a container by leveraging automatic testing, and extract the set of system calls accessed during testing. The set of system calls then results as a sandbox of the container. The mined sandbox restricts the container's access to system calls which are not seen during testing and thus reduces the attack surface. In …

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Probabilistic Public Key Encryption For Controlled Equijoin In Relational Databases, Yujue Wang, Hwee Hwa Pang Mar 2017

Probabilistic Public Key Encryption For Controlled Equijoin In Relational Databases, Yujue Wang, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

We present a public key encryption scheme for relational databases (PKDE) that allows the owner to control the execution of cross-relation joins on an outsourced server. The scheme allows anyone to deposit encrypted records in a database on the server. Thereafter, the database owner may authorize the server to join any two relations to identify matching records across them, while preventing self-joins that would reveal information on records that are unmatched in the join. The security of our construction is formally proved in the random oracle model based on the computational bilinear Diffie-Hellman assumption. Specifically, before a relation is joined, …

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Privacy In Context-Aware Mobile Crowdsourcing Systems, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Hoong Chuin Lau Mar 2017

Privacy In Context-Aware Mobile Crowdsourcing Systems, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Mobile crowd-sourcing can become as a strategy to perform time-sensitive urban tasks (such as municipal monitoring and last mile logistics) by effectively coordinating smartphone users. The success of the mobile crowd-sourcing platform depends mainly on its effectiveness in engaging crowd-workers, and recent studies have shown that compared to the pull-based approach, which relies on crowd-workers to browse and commit to tasks they would want to perform, the push-based approach can take into consideration of worker’s daily routine, and generate highly effective recommendations. As a result, workers waste less time on detours, plan more in advance, and require much less planning …

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Whole-System Analysis For Understanding Publicly Accessible Functions In Android, Huu Hoang Nguyen, Lingxiao Jiang, Thanh Tho Quan Mar 2017

Whole-System Analysis For Understanding Publicly Accessible Functions In Android, Huu Hoang Nguyen, Lingxiao Jiang, Thanh Tho Quan

Research Collection School Of Computing and Information Systems

Android has become the most popular mobile operating system. Millions of applications, including many malwares, haven been developed for it. Android itself evolves constantly with changing features and higher complexities. It is challenging for application developers to keep up with the changes and maintain the compatibility of their apps across Android versions. Therefore, there are many challenges for application analysis tools to accurately model and analyze app behaviors across Android versions. Even though the overall system architecture of Android and many APIs are documented, many other APIs and implementation details are not, not to mention potential bugs and vulnerabilities. Techniques …

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Are The Trade-Offs For Reducing Cross-Border Cybercrime Manageable?, Steven Mark Miller, Qiu-Hong Wang, Robert John Kauffman Mar 2017

Are The Trade-Offs For Reducing Cross-Border Cybercrime Manageable?, Steven Mark Miller, Qiu-Hong Wang, Robert John Kauffman

Research Collection School Of Computing and Information Systems

Without increased government intervention andgovernment-industry collaboration, the advantages inherent in the next wave ofInternet-enabled digital transformation will increasingly tilt towardcyber criminals, and their influence will disproportionately increase. The dilemma that immediately presents itself in such ascenario, however, is that an increased level of government involvement canalso lead to undesirable consequences. Increasing security always comes withtrade-offs that must be managed. The obvious concerns relate to the erosion ofprivacy, illegal or extralegal persecution, the abuse of Internet censorshipand the impediment to or stifling of innovation.

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Dark Hazard: Large-Scale Discovery Of Unknown Hidden Sensitive Operations In Android Apps, Xiaorui Pan, Xueqiang Wang, Yue Duan, Xiaofeng Wang, Heng Yin Mar 2017

Dark Hazard: Large-Scale Discovery Of Unknown Hidden Sensitive Operations In Android Apps, Xiaorui Pan, Xueqiang Wang, Yue Duan, Xiaofeng Wang, Heng Yin

Research Collection School Of Computing and Information Systems

Hidden sensitive operations (HSO) such as stealing privacy user data upon receiving an SMS message are increasingly utilized by mobile malware and other potentially-harmful apps (PHAs) to evade detection. Identification of such behaviors is hard, due to the challenge in triggering them during an app’s runtime. Current static approaches rely on the trigger conditions or hidden behaviors known beforehand and therefore cannot capture previously unknown HSO activities. Also these techniques tend to be computationally intensive and therefore less suitable for analyzing a large number of apps. As a result, our understanding of real-world HSO today is still limited, not to …

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Feature Learning Via Partial Differential Equation With Applications To Face Recognition, Cong Fang, Zhenyu Zhao, Pan Zhou, Zhouchen Lin Mar 2017

Feature Learning Via Partial Differential Equation With Applications To Face Recognition, Cong Fang, Zhenyu Zhao, Pan Zhou, Zhouchen Lin

Research Collection School Of Computing and Information Systems

Feature learning is a critical step in pattern recognition, such as image classification. However, most of the existing methods cannot extract features that are discriminative and at the same time invariant under some transforms. This limits the classification performance, especially in the case of small training sets. To address this issue, in this paper we propose a novel Partial Differential Equation (PDE) based method for feature learning. The feature learned by our PDE is discriminative, also translationally and rotationally invariant, and robust to illumination variation. To our best knowledge, this is the first work that applies PDE to feature learning …

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Ui X-Ray: Interactive Mobile Ui Testing Based On Computer Vision, Chun-Fu Richard Chen, Marco Pistoia, Conglei Shi, Paolo Girolami, Joseph W. Ligman, Yong Wang Mar 2017

Ui X-Ray: Interactive Mobile Ui Testing Based On Computer Vision, Chun-Fu Richard Chen, Marco Pistoia, Conglei Shi, Paolo Girolami, Joseph W. Ligman, Yong Wang

Research Collection School Of Computing and Information Systems

User Interface/eXperience (UI/UX) significantly affects the lifetime of any software program, particularly mobile apps. A bad UX can undermine the success of a mobile app even if that app enables sophisticated capabilities. A good UX, however, needs to be supported of a highly functional and user friendly UI design. In spite of the importance of building mobile apps based on solid UI designs, UI discrepancies- inconsistencies between UI design and implementation-Are among the most numerous and expensive defects encountered during testing. This paper presents UI X-RAY, an interactive UI testing system that integrates computer-vision methods to facilitate the correction of …

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Collaboration Trumps Homophily In Urban Mobile Crowdsourcing, Thivya Kandappu, Archan Misra, Randy Tandriansyah Mar 2017

Collaboration Trumps Homophily In Urban Mobile Crowdsourcing, Thivya Kandappu, Archan Misra, Randy Tandriansyah

Research Collection School Of Computing and Information Systems

This paper establishes the power of dynamic collaborative task completion among workers for urban mobile crowdsourcing. Collaboration is defined via the notion of peer referrals, whereby a worker who has accepted a location-specific task, but is unlikely to visit that location, offloads the task to a willing friend. Such a collaborative framework might be particularly useful for task bundles, especially for bundles that have higher geographic dispersion. The challenge, however, comes from the high similarity observed in the spatiotemporal pattern of task completion among friends. Using extensive real-world crowd-sourcing studies conducted over 7 weeks and 1000+ workers on a campus-based …

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Parameter Selection And Performance Comparison Of Particle Swarm Optimization In Sensor Networks Localization, Huanqing Cui, Minglei Shu, Min Song, Yinglong Wang Mar 2017

Parameter Selection And Performance Comparison Of Particle Swarm Optimization In Sensor Networks Localization, Huanqing Cui, Minglei Shu, Min Song, Yinglong Wang

Michigan Tech Publications, Part 1

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys …

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Whitelisting System State In Windows Forensic Memory Visualizations, Joshua A. Lapso, Gilbert L. Peterson, James S. Okolica Mar 2017

Whitelisting System State In Windows Forensic Memory Visualizations, Joshua A. Lapso, Gilbert L. Peterson, James S. Okolica

Faculty Publications

Examiners in the field of digital forensics regularly encounter enormous amounts of data and must identify the few artifacts of evidentiary value. One challenge these examiners face is manual reconstruction of complex datasets with both hierarchical and associative relationships. The complexity of this data requires significant knowledge, training, and experience to correctly and efficiently examine. Current methods provide text-based representations or low-level visualizations, but levee the task of maintaining global context of system state on the examiner. This research presents a visualization tool that improves analysis methods through simultaneous representation of the hierarchical and associative relationships and local detailed data …

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Hadoop-Based Replica Exchange Over Heterogeneous Distributed Cyberinfrastructures, Richard Platania, Shayan Shams, Chui Hui Chiu, Nayong Kim, Joohyun Kim, Seung Jong Park Feb 2017

Hadoop-Based Replica Exchange Over Heterogeneous Distributed Cyberinfrastructures, Richard Platania, Shayan Shams, Chui Hui Chiu, Nayong Kim, Joohyun Kim, Seung Jong Park

Computer Science Faculty Research & Creative Works

We present Hadoop-based replica exchange (HaRE), a Hadoop-based implementation of the replica exchange scheme developed primarily for replica exchange statistical temperature molecular dynamics, an example of a large-scale, advanced sampling molecular dynamics simulation. By using Hadoop as a framework and the MapReduce model for driving replica exchange, an efficient task-level parallelism is introduced to replica exchange statistical temperature molecular dynamics simulations. In order to demonstrate this, we investigate the performance of our application over various distributed cyberinfrastructures (DCI), including several high-performance computing systems, our cyberinfrastructure for reconfigurable optical networks testbed, the global environment for network innovations testbed, and the CloudLab …

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Genome Resources For Climate‐Resilient Cowpea, An Essential Crop For Food Security, Maria Munoz-Amatriain, Hamid Mirebrahim, Pei Xu, Steve Wanamaker, Ming-Cheng Luo, Hind Alhakami, Matthew Alpert, Ibrahim Atokple, Benoit J. Batieno, Ousmane Boukar, Serdar Bozdag, Ndiaga Cisse, Issa Drabo, Jeffrey D. Ehlers, Andrew Farmer, Christian Fatokun, Yong Q. Gu, Yi-Ning Guo, Bao-Lam Huynh, Scott A. Jackson, Francis Kusi, Cynthia T. Lawley, Mitchell R. Lucas, Yaqin Ma, Michael P. Timko, Jiajie Wu, Frank You, Noelle A. Barkley, Philip A. Roberts, Stefano Lonardi, Timothy J. Close Feb 2017

Genome Resources For Climate‐Resilient Cowpea, An Essential Crop For Food Security, Maria Munoz-Amatriain, Hamid Mirebrahim, Pei Xu, Steve Wanamaker, Ming-Cheng Luo, Hind Alhakami, Matthew Alpert, Ibrahim Atokple, Benoit J. Batieno, Ousmane Boukar, Serdar Bozdag, Ndiaga Cisse, Issa Drabo, Jeffrey D. Ehlers, Andrew Farmer, Christian Fatokun, Yong Q. Gu, Yi-Ning Guo, Bao-Lam Huynh, Scott A. Jackson, Francis Kusi, Cynthia T. Lawley, Mitchell R. Lucas, Yaqin Ma, Michael P. Timko, Jiajie Wu, Frank You, Noelle A. Barkley, Philip A. Roberts, Stefano Lonardi, Timothy J. Close

Mathematics, Statistics and Computer Science Faculty Research and Publications

Cowpea (Vigna unguiculata L. Walp.) is a legume crop that is resilient to hot and drought‐prone climates, and a primary source of protein in sub‐Saharan Africa and other parts of the developing world. However, genome resources for cowpea have lagged behind most other major crops. Here we describe foundational genome resources and their application to the analysis of germplasm currently in use in West African breeding programs. Resources developed from the African cultivar IT97K‐499‐35 include a whole‐genome shotgun (WGS) assembly, a bacterial artificial chromosome (BAC) physical map, and assembled sequences from 4355 BACs. These resources and WGS sequences of …

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Modeling, Simulation, And Performance Analysis Of Decoy State Enabled Quantum Key Distribution Systems, Logan O. Mailloux, Michael R. Grimaila, Douglas D. Hodson, Ryan D. Engle, Colin V. Mclaughlin, Gerald B. Baumgartner Feb 2017

Modeling, Simulation, And Performance Analysis Of Decoy State Enabled Quantum Key Distribution Systems, Logan O. Mailloux, Michael R. Grimaila, Douglas D. Hodson, Ryan D. Engle, Colin V. Mclaughlin, Gerald B. Baumgartner

Faculty Publications

Quantum Key Distribution (QKD) systems exploit the laws of quantum mechanics to generate secure keying material for cryptographic purposes. To date, several commercially viable decoy state enabled QKD systems have been successfully demonstrated and show promise for high-security applications such as banking, government, and military environments. In this work, a detailed performance analysis of decoy state enabled QKD systems is conducted through model and simulation of several common decoy state configurations. The results of this study uniquely demonstrate that the decoy state protocol can ensure Photon Number Splitting (PNS) attacks are detected with high confidence, while maximizing the system’s quantum …

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Directed Acyclic Graph Continuous Max-Flow Image Segmentation For Unconstrained Label Orderings, John Sh Baxter, Martin Rajchl, A. Jonathan Mcleod, Jing Yuan, Terry M. Peters Feb 2017

Directed Acyclic Graph Continuous Max-Flow Image Segmentation For Unconstrained Label Orderings, John Sh Baxter, Martin Rajchl, A. Jonathan Mcleod, Jing Yuan, Terry M. Peters

Robarts Imaging Publications

Label ordering, the specification of subset–superset relationships for segmentation labels, has been of increasing interest in image segmentation as they allow for complex regions to be represented as a collection of simple parts. Recent advances in continuous max-flow segmentation have widely expanded the possible label orderings from binary background/foreground problems to extendable frameworks in which the label ordering can be specified. This article presents Directed Acyclic Graph Max-Flow image segmentation which is flexible enough to incorporate any label ordering without constraints. This framework uses augmented Lagrangian multipliers and primal–dual optimization to develop a highly parallelized solver implemented using GPGPU. This …

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