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- Peer-to-peer computing (6)
- Data Mining, Software Engineering (5)
- Computer science (4)
- Delay (4)
- Graph theory (4)
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- P2P networks (4)
- Probability (4)
- Resilience (4)
- Analytical models (3)
- Large-scale systems (3)
- Out-of-turn interaction (3)
- Peer to peer computing (3)
- Peer-to-peer (3)
- Random processes (3)
- User churn (3)
- Classification (2)
- Communications Society (2)
- Create-based method (2)
- Failure analysis (2)
- Gnutella networks (2)
- Hierarchical hypermedia (2)
- Hypermedia (2)
- Information Retrieval (2)
- Information personalization (2)
- Internet (2)
- Lifetime estimation (2)
- Navigation (2)
- Node-isolation model (2)
- Routing (2)
- Sampling methods (2)
Articles 1 - 30 of 49
Full-Text Articles in Other Computer Sciences
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 …
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 …
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 …
Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz
Structure Preserving Large Imagery Reconstruction, Ju Shen, Jianjun Yang, Sami Taha Abu Sneineh, Bryson Payne, Markus Hitz
Computer Science Faculty Publications
With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene reconstruction, and other big data applications. However, such tasks are not easy due to the fact the retrieved photos can have large variations in their view perspectives, resolutions, lighting, noises, and distortions. Furthermore, with the occlusion of unexpected objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image …
Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen
Automatic Objects Removal For Scene Completion, Jianjun Yang, Yin Wang, Honggang Wang, Kun Hua, Wei Wang, Ju Shen
Computer Science Faculty Publications
With the explosive growth of Web-based cameras and mobile devices, billions of photographs are uploaded to the Internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually …
Unstructured P2p Link Lifetimes Redux, Zhongmei Yao, Daren B. H. Cline
Unstructured P2p Link Lifetimes Redux, Zhongmei Yao, Daren B. H. Cline
Computer Science Faculty Publications
We revisit link lifetimes in random P2P graphs under dynamic node failure and create a unifying stochastic model that generalizes the majority of previous efforts in this direction. We not only allow nonexponential user lifetimes and age-dependent neighbor selection, but also cover both active and passive neighbor-management strategies, model the lifetimes of incoming and outgoing links, derive churn-related message volume of the system, and obtain the distribution of transient in/out degree at each user. We then discuss the impact of design parameters on overhead and resilience of the network.
A Robust Rgbd Slam System For 3d Environment With Planar Surfaces, Po-Chang Su, Ju Shen, Sen-Ching S. Cheung
A Robust Rgbd Slam System For 3d Environment With Planar Surfaces, Po-Chang Su, Ju Shen, Sen-Ching S. Cheung
Computer Science Faculty Publications
With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in scanning large planar regions such as wall surfaces in a room. The lack of depth …
Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
Stochastic Analysis Of Horizontal Ip Scanning, Derek Leonard, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
Computer Science Faculty Publications
Intrusion Detection Systems (IDS) have become ubiquitous in the defense against virus outbreaks, malicious exploits of OS vulnerabilities, and botnet proliferation. As attackers frequently rely on host scanning for reconnaissance leading to penetration, IDS is often tasked with detecting scans and preventing them. However, it is currently unknown how likely an IDS is to detect a given Internet-wide scan pattern and whether there exist sufficiently fast scan techniques that can remain virtually undetectable at large-scale. To address these questions, we propose a simple analytical model for the window-expiration rules of popular IDS tools (i.e., Snort and Bro) and utilize a …
On Superposition Of Heterogeneous Edge Processes In Dynamic Random Graphs, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov
On Superposition Of Heterogeneous Edge Processes In Dynamic Random Graphs, Zhongmei Yao, Daren B. H. Cline, Dmitri Loguinov
Computer Science Faculty Publications
This paper builds a generic modeling framework for analyzing the edge-creation process in dynamic random graphs in which nodes continuously alternate between active and inactive states, which represent churn behavior of modern distributed systems. We prove that despite heterogeneity of node lifetimes, different initial out-degree, non-Poisson arrival/failure dynamics, and complex spatial and temporal dependency among creation of both initial and replacement edges, a superposition of edge-arrival processes to a live node under uniform selection converges to a Poisson process when system size becomes sufficiently large. Due to the convoluted dependency and non-renewal nature of various point processes, this result significantly …
Automatic Content Generation For Video Self Modeling, Ju Shen, Anusha Raghunathan, Sen-Ching S. Cheung, Ravi R. Patel
Automatic Content Generation For Video Self Modeling, Ju Shen, Anusha Raghunathan, Sen-Ching S. Cheung, Ravi R. 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. Its effectiveness in rehabilitation and education has been repeatedly demonstrated but technical challenges remain in creating video contents that depict previously unseen behaviors. In this paper, we propose a novel system that re-renders new talking-head sequences suitable to be used for VSM treatment of patients with voice disorder. After the raw footage is captured, a new speech track is either synthesized using text-to-speech or selected based on voice similarity from a database of clean speeches. …
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
Computer Science Faculty Publications
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 …
Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan
Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan
Computer Science Faculty Publications
Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of hierarchical …
A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
Computer Science Faculty Publications
Abstract Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality classification models. This paper presents our newly proposed threshold-based feature selection techniques, comparing the performance of these techniques by building classification models using five commonly used classifiers. In order to evaluate the effectiveness of different feature selection techniques, the models are evaluated using eight different performance metrics separately since a given performance metric usually captures only one aspect of the classification performance. All experiments are conducted on three Eclipse data sets with different levels of class imbalance. The …
A Comparative Study Of Filter-Based Feature Ranking Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
A Comparative Study Of Filter-Based Feature Ranking Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
Computer Science Faculty Publications
One factor that affects the success of machine learning is the presence of irrelevant or redundant information in the training data set. Filter-based feature ranking techniques (rankers) rank the features according to their relevance to the target attribute and we choose the most relevant features to build classification models subsequently. In order to evaluate the effectiveness of different feature ranking techniques, a commonly used method is to assess the classification performance of models built with the respective selected feature subsets in terms of a given performance metric (e.g., classification accuracy or misclassification rate). Since a given performance metric usually can …
Personalization By Website Transformation: Theory And Practice, Saverio Perugini
Personalization By Website Transformation: Theory And Practice, Saverio Perugini
Computer Science Faculty Publications
We present an analysis of a progressive series of out-of-turn transformations on a hierarchical website to personalize a user’s interaction with the site. We formalize the transformation in graph-theoretic terms and describe a toolkit we built that enumerates all of the traversals enabled by every possible complete series of these transformations in any site and computes a variety of metrics while simulating each traversal therein to qualify the relationship between a site’s structure and the cumulative effect of support for the transformation in a site. We employed this toolkit in two websites. The results indicate that the transformation enables users …
Supporting Multiple Paths To Objects In Information Hierarchies: Faceted Classification, Faceted Search, And Symbolic Links, Saverio Perugini
Supporting Multiple Paths To Objects In Information Hierarchies: Faceted Classification, Faceted Search, And Symbolic Links, Saverio Perugini
Computer Science Faculty Publications
We present three fundamental, interrelated approaches to support multiple access paths to each terminal object in information hierarchies: faceted classification, faceted search, and web directories with embedded symbolic links. This survey aims to demonstrate how each approach supports users who seek information from multiple perspectives. We achieve this by exploring each approach, the relationships between these approaches, including tradeoffs, and how they can be used in concert, while focusing on a core set of hypermedia elements common to all. This approach provides a foundation from which to study, understand, and synthesize applications which employ these techniques. This survey does not …
Mining Data From Multiple Software Development Projects, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya
Mining Data From Multiple Software Development Projects, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya
Computer Science Faculty Publications
A large system often goes through multiple software project development cycles, in part due to changes in operation and development environments. For example, rapid turnover of the development team between releases can influence software quality, making it important to mine software project data over multiple system releases when building defect predictors. Data collection of software attributes are often conducted independent of the quality improvement goals, leading to the availability of a large number of attributes for analysis. Given the problems associated with variations in development process, data collection, and quality goals from one release to another emphasizes the importance of …
High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
Computer Science Faculty Publications
Software metrics collected during project development play a critical role in software quality assurance. A software practitioner is very keen on learning which software metrics to focus on for software quality prediction. While a concise set of software metrics is often desired, a typical project collects a very large number of metrics. Minimal attention has been devoted to finding the minimum set of software metrics that have the same predictive capability as a larger set of metrics – we strive to answer that question in this paper. We present a comprehensive comparison between seven commonly-used filter-based feature ranking techniques (FRT) …
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
Computer Science Faculty Publications
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 …
An Empirical Investigation Of Filter Attribute Selection Techniques For Software Quality Classification, Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang
An Empirical Investigation Of Filter Attribute Selection Techniques For Software Quality Classification, Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang
Computer Science Faculty Publications
Attribute selection is an important activity in data preprocessing for software quality modeling and other data mining problems. The software quality models have been used to improve the fault detection process. Finding faulty components in a software system during early stages of software development process can lead to a more reliable final product and can reduce development and maintenance costs. It has been shown in some studies that prediction accuracy of the models improves when irrelevant and redundant features are removed from the original data set. In this study, we investigated four filter attribute selection techniques, Automatic Hybrid Search (AHS), …
Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Residual-Based Estimation Of Peer And Link Lifetimes In P2p Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Computer Science Faculty Publications
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called Create-BasedMethod (CBM), which divides a given observation window into two halves and samples users ldquocreatedrdquo 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 first 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 …
Node Isolation Model And Age-Based Neighbor Selection In Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov
Node Isolation Model And Age-Based Neighbor Selection In Unstructured P2p Networks, Zhongmei Yao, Derek Leonard, Dmitri Loguinov
Computer Science Faculty Publications
Previous analytical studies of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared with uniform selection of neighbors. In fact, the second strategy based on random walks on age-proportional graphs demonstrates that, for lifetimes with infinite variance, the system monotonically increases …
User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang
User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang
Computer Science Faculty Publications
As detailed in Chap. 1, system implementations for dynamic taxonomies and faceted search allow a wide range of query possibilities on the data. Only when these are made accessible by appropriate user interfaces, the resulting applications can support a variety of search, browsing and analysis tasks. User interface design in this area is confronted with specific challenges. This chapter presents an overview of both established and novel principles and solutions.
Exploring Out-Of-Turn Interactions With Websites, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones, Mary E. Pinney, Mary Beth Rosson
Exploring Out-Of-Turn Interactions With Websites, Saverio Perugini, Naren Ramakrishnan, Manuel A. Pérez-Quiñones, Mary E. Pinney, Mary Beth Rosson
Computer Science Faculty Publications
Hierarchies are ubiquitous on the web for structuring online catalogs and indexing multidimensional attributed data sets. They are a natural metaphor for information seeking if their levelwise structure mirrors the user's conception of the underlying domain. In other cases, they can be frustrating, especially if multiple drill‐downs are necessary to arrive at information of interest. To support a broad range of users, site designers often expose multiple faceted classifications or provide within‐page pruning mechanisms. We present a new technique, called out-of-turn interaction, that increases the richness of user interaction at hierarchical sites, without enumerating all possible completion paths in the …
On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Zhongmei Yao, Derek Leonard, Xiaoming Wang, Dmitri Loguinov
On Static And Dynamic Partitioning Behavior Of Large-Scale Networks, Zhongmei Yao, Derek Leonard, Xiaoming Wang, Dmitri Loguinov
Computer Science Faculty Publications
In this paper, we analyze the problem of network disconnection in the context of large-scale P2P networks and understand how both static and dynamic patterns of node failure affect the resilience of such graphs. We start by applying classical results from random graph theory to show that a large variety of deterministic and random P2P graphs almost surely (i.e., with probability 1 − o(1)) remain connected under random failure if and only if they have no isolated nodes. This simple, yet powerful, result subsequently allows us to derive in closed-form the probability that a P2P network develops isolated nodes, and …
Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov
Link Lifetimes And Randomized Neighbor Selection In Dhts, Zhongmei Yao, Dmitri Loguinov
Computer Science Faculty Publications
Several models of user churn, resilience, and link lifetime have recently appeared in the literature [12], [13], [34], [35]; however, these results do not directly apply to classical Distributed Hash Tables (DHTs) in which neighbor replacement occurs not only when current users die, but also when new user arrive into the system, and where replacement choices are often restricted to the successor of the failed zone in the DHT space. To understand neighbor churn in such networks, this paper proposes a simple, yet accurate, model for capturing link dynamics in structured P2P systems and obtains the distribution of link lifetimes …
Symbolic Links In The Open Directory Project, Saverio Perugini
Symbolic Links In The Open Directory Project, Saverio Perugini
Computer Science Faculty Publications
We present a study to develop an improved understanding of symbolic links in web directories. A symbolic link is a hyperlink that makes a directed connection from a web page along one path through a directory to a page along another path. While symbolic links are ubiquitous in web directories such as Yahoo!, they are under-studied, and as a result, their uses are poorly understood. A cursory analysis of symbolic links reveals multiple uses: to provide navigational shortcuts deeper into a directory, backlinks to more general categories, and multiclassification. We investigated these uses in the Open Directory Project (ODP), the …
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
Computer Science Faculty Publications
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 …