Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Computer science (2)
- Delay (2)
- Large-scale systems (2)
- Peer-to-peer computing (2)
- Routing (2)
-
- Sampling methods (2)
- Algorithm design and analysis (1)
- Algorithms (1)
- Analytical models (1)
- Automatic Query Optimization (1)
- Bandwidth (1)
- Battle Tetris (1)
- Classification (1)
- Clustering (1)
- Collaborative filtering (1)
- Communications Society (1)
- Complex Event Processing (1)
- Computer network reliability (1)
- Computer software (1)
- Crawlers (1)
- Create-based method (1)
- Evolutionary algorithms (1)
- Failure analysis (1)
- Functional requirements (1)
- Genetic Algorithms (1)
- Gnutella networks (1)
- Governance (1)
- Grid Computing (1)
- Grid Scheduling (1)
- Head-mounted display (HMD) (1)
- Publication
- Publication Type
- File Type
Articles 1 - 20 of 20
Full-Text Articles in Theory and Algorithms
Battle Bot Ai – Patriot Bot, James Johnston
Battle Bot Ai – Patriot Bot, James Johnston
Computer Engineering
An entry in the the 'Battle Block AI' competition hosted by 'The AI Games'.
An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang
An Immersive Telepresence System Using Rgb-D Sensors And Head-Mounted Display, Xinzhong Lu, Ju Shen, Saverio Perugini, Jianjun Yang
Computer Science Faculty Publications
We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to effectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The …
Computational Approaches For Remote Monitoring Of Symptoms And Activities, Ferdaus Kawsar
Computational Approaches For Remote Monitoring Of Symptoms And Activities, Ferdaus Kawsar
Dissertations (1934 -)
We now have a unique phenomenon where significant computational power, storage, connectivity, and built-in sensors are carried by many people willingly as part of their life style; two billion people now use smart phones. Unique and innovative solutions using smart phones are motivated by rising health care cost in both the developed and developing worlds. In this work, development of a methodology for building a remote symptom monitoring system for rural people in developing countries has been explored. Design, development, deployment, and evaluation of e-ESAS is described. The system’s performance was studied by analyzing feedback from users. A smart phone …
Functional Requirements Identification Using Item-To-Item Collaborative Filtering, Proceso L. Fernandez Jr, Reynald Jay F. Hidalgo
Functional Requirements Identification Using Item-To-Item Collaborative Filtering, Proceso L. Fernandez Jr, Reynald Jay F. Hidalgo
Department of Information Systems & Computer Science Faculty Publications
One of the most difficult tasks in the development of software is the identification of the functional requirements. A well-defined functional requirement will eventually map the success of a software project. A support tool that can recommend candidate functional requirements for a software project being developed will help software engineers to deliver the right software to the clients.
The purpose of this study is to determine whether a collection of previously developed software applications can serve as basis for the development of a model to identify functional requirements of a project to be developed. Completed software project documentations of Master …
Optimizing Selection Of Competing Features Via Feedback-Directed Evolutionary Algorithms, Tian Huat Tan, Yinxing Xue, Manman Chen, Jun Sun, Yang Liu, Jin Song Dong Dong
Optimizing Selection Of Competing Features Via Feedback-Directed Evolutionary Algorithms, Tian Huat Tan, Yinxing Xue, Manman Chen, Jun Sun, Yang Liu, Jin Song Dong Dong
Research Collection School Of Computing and Information Systems
Software that support various groups of customers usually require complicated configurations to attain different functionalities. To model the configuration options, feature model is proposed to capture the commonalities and competing variabilities of the product variants in software family or Software Product Line (SPL). A key challenge for deriving a new product is to find a set of features that do not have inconsistencies or conflicts, yet optimize multiple objectives (e.g., minimizing cost and maximizing number of features), which are often competing with each other. Existing works have attempted to make use of evolutionary algorithms (EAs) to address this problem. In …
Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel
Automatic Video Self Modeling For Voice Disorder, Ju Shen, Changpeng Ti, Anusha Raghunathan, Sen-Ching S. Cheung, Rita Patel
Computer Science Faculty Publications
Video self modeling (VSM) is a behavioral intervention technique in which a learner models a target behavior by watching a video of him- or herself. In the field of speech language pathology, the approach of VSM has been successfully used for treatment of language in children with Autism and in individuals with fluency disorder of stuttering. Technical challenges remain in creating VSM contents that depict previously unseen behaviors. In this paper, we propose a novel system that synthesizes new video sequences for VSM treatment of patients with voice disorders. Starting with a video recording of a voice-disorder patient, the proposed …
Query Analyzer And Manager For Complex Event Processing As A Service, Wilson Higashino, Cedric Eichler, Miriam A M Capretz, Thierry Monteil, M. Beatriz F. Toledo, Patricia Stolf
Query Analyzer And Manager For Complex Event Processing As A Service, Wilson Higashino, Cedric Eichler, Miriam A M Capretz, Thierry Monteil, M. Beatriz F. Toledo, Patricia Stolf
Wilson A Higashino
Complex Event Processing (CEP) is a set of tools and techniques that can be used to obtain insights from high-volume, high-velocity continuous streams of events. CEP-based systems have been adopted in many situations that require prompt establishment of system diagnostics and execution of reaction plans, such as in monitoring of complex systems. This article describes the Query Analyzer and Manager (QAM) module, a first effort toward the development of a CEP as a Service (CEPaaS) system. This module is responsible for analyzing user-defined CEP queries and for managing their execution in distributed cloud-based environments. Using a language-agnostic internal query representation, …
Evaluation Of Particle Swarm Optimization Applied To Grid Scheduling, Wilson Higashino, Miriam Capretz, M. Beatriz Toledo
Evaluation Of Particle Swarm Optimization Applied To Grid Scheduling, Wilson Higashino, Miriam Capretz, M. Beatriz Toledo
Wilson A Higashino
The problem of scheduling independent users’ jobs to resources in Grid Computing systems is of paramount importance. This problem is known to be NP-hard, and many techniques have been proposed to solve it, such as heuristics, genetic algorithms (GA), and, more recently, particle swarm optimization (PSO). This article aims to use PSO to solve grid scheduling problems, and compare it with other techniques. It is shown that many often-overlooked implementation details can have a huge impact on the performance of the method. In addition, experiments also show that the PSO has a tendency to stagnate around local minima in high-dimensional …
Network And Energy-Aware Resource Selection Model For Opportunistic Grids, Izaias Faria, Mario Dantas, Miriam A M Capretz, Wilson Higashino
Network And Energy-Aware Resource Selection Model For Opportunistic Grids, Izaias Faria, Mario Dantas, Miriam A M Capretz, Wilson Higashino
Wilson A Higashino
Due to increasing hardware capacity, computing grids have been handling and processing more data. This has led to higher amount of energy being consumed by grids; hence the necessity for strategies to reduce their energy consumption. Scheduling is a process carried out to define in which node tasks will be executed in the grid. This process can significantly impact the global system performance, including energy consumption. This paper focuses on a scheduling model for opportunistic grids that considers network traffic, distance between input files and execution node as well as the execution node status. The model was tested in a …
Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua
Compression Of Video Tracking And Bandwidth Balancing Routing In Wireless Multimedia Sensor Networks, Yin Wang, Jianjun Yang, Ju Shen, Bryson Payne, Juan Guo, Kun Hua
Computer Science Faculty Publications
There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select …
Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen
Leading Undergraduate Students To Big Data Generation, Jianjun Yang, Ju Shen
Computer Science Faculty Publications
People are facing a flood of data today. Data are being collected at unprecedented scale in many areas, such as networking, image processing, virtualization, scientific computation, and algorithms. The huge data nowadays are called Big Data. Big data is an all encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. In this article, the authors present a unique way which uses network simulator and tools of image processing to train students abilities to learn, analyze, manipulate, and apply Big Data. Thus they develop students hands-on …
Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen
Hole Detection And Shape-Free Representation And Double Landmarks Based Geographic Routing In Wireless Sensor Networks, Jianjun Yang, Zongming Fei, Ju Shen
Computer Science Faculty Publications
In wireless sensor networks, an important issue of geographic routing is “local minimum” problem, which is caused by a “hole” that blocks the greedy forwarding process. Existing geographic routing algorithms use perimeter routing strategies to find a long detour path when such a situation occurs. To avoid the long detour path, recent research focuses on detecting the hole in advance, then the nodes located on the boundary of the hole advertise the hole information to the nodes near the hole. Hence the long detour path can be avoided in future routing. We propose a heuristic hole detecting algorithm which identifies …
Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Zhongmei Yao
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent …
Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang
Modeling Heterogeneous User Churn And Local Resilience Of Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov, Xiaoming Wang
Zhongmei Yao
Previous analytical results on the resilience of unstructured P2P systems have not explicitly modeled heterogeneity of user churn (i.e., difference in online behavior) or the impact of in-degree on system resilience. To overcome these limitations, we introduce a generic model of heterogeneous user churn, derive the distribution of the various metrics observed in prior experimental studies (e.g., lifetime distribution of joining users, joint distribution of session time of alive peers, and residual lifetime of a randomly selected user), derive several closed-form results on the transient behavior of in-degree, and eventually obtain the joint in/out degree isolation probability as a simple …
Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov
Robust Lifetime Measurement In Large-Scale P2p Systems With Non-Stationary Arrivals, Xiaoming Wang, Zhongmei Yao, Yueping Zhang, Dmitri Loguinov
Zhongmei Yao
Characterizing user churn has become an important topic in studying P2P networks, both in theoretical analysis and system design. Recent work has shown that direct sampling of user lifetimes may lead to certain bias (arising from missed peers and round-off inconsistencies) and proposed a technique that estimates lifetimes based on sampled residuals. In this paper, however, we show that under non-stationary arrivals, which are often present in real systems, residual-based sampling does not correctly reconstruct user lifetimes and suffers a varying degree of bias, which in some cases makes estimation completely impossible. We overcome this problem using two contributions: a …
In-Degree Dynamics Of Large-Scale P2p Systems, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov
In-Degree Dynamics Of Large-Scale P2p Systems, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov
Zhongmei Yao
This paper builds a complete modeling framework for understanding user churn and in-degree dynamics in unstructured P2P systems in which each user can be viewed as a stationary alternating renewal process. While the classical Poisson result on the superposition of n stationary renewal processes for n→∞ requires that each point process become sparser as n increases, it is often difficult to rigorously show this condition in practice. In this paper, we first prove that despite user heterogeneity and non-Poisson arrival dynamics, a superposition of edge-arrival processes to a live user under uniform selection converges to a Poisson process when …
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Zhongmei Yao
Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …
Knotswithstanding!, Erik S. Nestor
Knotswithstanding!, Erik S. Nestor
Honors Projects
Knotswithstanding! is an internet based application built using HTML5, CSS, and JavaScript. It is a pedagogical utility that facilitates the construction and analysis of mathematical knots, as well as the demonstration of knot theory fundamentals. It uses a "stick based" tile layout system, allowing a user to draw a knot by dragging the mouse pointer across a grid. Once a knot is complete, functionality is available to check for validity, identify the number of crossings, and determine other invariants including tricolorability and Dowker notation. It features 500 iterable storage banks, and functionality for a sequence of knot renderings to be …
Natural Language Processing For Foreign Language Learning, Jacob Kausler
Natural Language Processing For Foreign Language Learning, Jacob Kausler
Honors Theses
This research presents novel algorithms which generate sentences in a natural language, using natural language generation techniques. The purpose of the algorithms is to benefit foreign language learning. As far as we can tell, ours is the first such research being done in the field. In creating the algorithms, we also developed a piece of software to showcase the work and allow testing by users. The main algorithm begins by generating sentence models by using one of two methods, namely modeled sentence generation and semantic sentence generation. Each of these have benefits and drawbacks, which the user must take into …
Research Agenda Into Human-Intelligence/Machine-Intelligence Governance, Teddy Steven Cotter
Research Agenda Into Human-Intelligence/Machine-Intelligence Governance, Teddy Steven Cotter
Engineering Management & Systems Engineering Faculty Publications
Since the birth of modern artificial intelligence (AI) at the 1956 Dartmouth Conference, the AI community has pursued modeling and coding of human intelligence into AI reasoning processes (HI Þ MI). The Dartmouth Conference's fundamental assertion was that every aspect of human learning and intelligence could be so precisely described that it could be simulated in AI. With the exception of knowledge specific areas (such as IBM's Big Blue and a few others), sixty years later the AI community is not close to coding global human intelligence into AI. In parallel, the knowledge management (KM) community has pursued understanding of …