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Articles 17101 - 17130 of 20647
Full-Text Articles in Entire DC Network
Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Research Collection School Of Computing and Information Systems
Searching answers to complex questions is a challenging IR task. In this paper, we examine the use of query templates with semantic slots to formulate slot-based queries. These queries have query terms assigned to entity and relationship slots. We develop several query expansion methods for slot-based queries so as to improve their retrieval effectiveness on a document collection. Each method consists of a combination of term scoring scheme, term scoring formula, and term assignment scheme. Our preliminary experiments evaluate these different slot-based query expansion methods on a collection of news documents,and conclude that:(1) slot-based queries yield better retrieval accuracy compared …
On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong
On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong
Research Collection School Of Computing and Information Systems
Wikipedia is presently the largest free-and-open online encyclopedia collaboratively edited and maintained by volunteers. While Wikipedia offers full-text search to its users, the accuracy of its relevance-based search can be compromised by poor quality articles edited by non-experts and inexperienced contributors. In this paper, we propose a framework that re-ranks Wikipedia search results considering article quality. We develop two quality measurement models, namely Basic and PeerReview, to derive article quality based on co-authoring data gathered from articles' edit history. Compared with Wikipedia's full-text search engine, Google and Wikiseek, our experimental results showed that (i) quality-only ranking produced by PeerReview gives …
Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun
Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun
Research Collection School Of Computing and Information Systems
Much existing research on blogs focused on posts only, ignoring their comments. Our user study conducted on summarizing blog posts, however, showed that reading comments does change one's understanding about blog posts. In this research, we aim to extract representative sentences from a blog post that best represent the topics discussed among its comments. The proposed solution first derives representative words from comments and then selects sentences containing representative words. The representativeness of words is measured using ReQuT (i.e., Reader, Quotation, and Topic). Evaluated on human labeled sentences, ReQuT together with summation-based sentence selection showed promising results.
An Information-Sharing Based Anti-Phishing System, Yueqing Cheng, Zhen Yuan, Lei Ma, Robert H. Deng
An Information-Sharing Based Anti-Phishing System, Yueqing Cheng, Zhen Yuan, Lei Ma, Robert H. Deng
Research Collection School Of Computing and Information Systems
This paper presents the design of an informationsharing based or server-assisted anti-phishing system. The system follows a client-server architecture and makes decision based on not only client side heuristics but also collective information from multiple clients. When visiting a web site, a client side proxy, installed as a plug-in to a browser, decides on the legitimacy of the web site based on a combination of white list, black list and heuristics. In case the client side proxy does not have sufficient information to make a clear judgment, it reports the suspicious site to a central server which has access to …
Multi-Period Combinatorial Auction Mechanism For Distributed Resource Allocation And Scheduling, Hoong Chuin Lau, Shih-Fen Cheng, Thin Yin Leong, Jong Han Park, Zhengyi Zhao
Multi-Period Combinatorial Auction Mechanism For Distributed Resource Allocation And Scheduling, Hoong Chuin Lau, Shih-Fen Cheng, Thin Yin Leong, Jong Han Park, Zhengyi Zhao
Research Collection School Of Computing and Information Systems
We consider the problem of resource allocation and scheduling where information and decisions are decentralized, and our goal is to propose a market mechanism that allows resources from a central resource pool to be allocated to distributed decision makers (agents) that seek to optimize their respective scheduling goals. We propose a generic combinatorial auction mechanism that allows agents to competitively bid for the resources needed in a multi-period setting, regardless of the respective scheduling problem faced by the agent, and show how agents can design optimal bidding strategies to respond to price adjustment strategies from the auctioneer. We apply our …
Advances And Challenges With Data Broadcasting In Wireless Mesh Networks, Chun Tung Chou, Junaid Qadir, Joo Ghee Lim, Archan Misra
Advances And Challenges With Data Broadcasting In Wireless Mesh Networks, Chun Tung Chou, Junaid Qadir, Joo Ghee Lim, Archan Misra
Research Collection School Of Computing and Information Systems
Wireless mesh networks have become a promising means to provide low-cost broadband access. Many WMN applications require broadcasting data (IPTV etc.) over the WMN. This article studies how efficient data broadcast, measured in terms of broadcast latency, can be realized by exploiting two features of WMNs: the use of multiple transmission rates at the link layer and the use of multiple radio interfaces on each node. We demonstrate that by exploiting these features, broadcast latency can be reduced severalfold compared to the current default practice in wireless LANs of using the lowest transmission rate for broadcast traffic. We also discuss …
Machine-Assisted Proof Support For Validation Beyond Simulink, Chunqing Chen, Jin Song Dong, Jun Sun
Machine-Assisted Proof Support For Validation Beyond Simulink, Chunqing Chen, Jin Song Dong, Jun Sun
Research Collection School Of Computing and Information Systems
Simulink is popular in industry for modeling and simulating embedded systems. It is deficient to handle requirements of high-level assurance and timing analysis. Previously, we showed the idea of applying Timed Interval Calculus (TIC) to complement Simulink. In this paper, we develop machine-assisted proof support for Simulink models represented in TIC. The work is based on a generic theorem prover, Prototype Verification System (PVS). The TIC specifications of both Simulink models and requirements are transformed to PVS specifications automatically. Verification can be carried out at interval level with a high level of automation. Analysis of continuous and discrete behaviors is …
Analyzing Gene Relationships For Down Syndrome With Labeled Transition Graphs, Hyrum Carroll, Mark J. Clement, Eric G. Mercer, Neha Rungta, Quinn O. Snell, Randall J. Roper
Analyzing Gene Relationships For Down Syndrome With Labeled Transition Graphs, Hyrum Carroll, Mark J. Clement, Eric G. Mercer, Neha Rungta, Quinn O. Snell, Randall J. Roper
Faculty Publications
The relationship between changes in gene expression and physical characteristics associated with Down syndrome is not well understood. Chromosome 21 genes interact with nonchromosome 21 genes to produce Down syndrome characteristics. This indirect influence, however, is difficult to empirically define due to the number, size, and complexity of the involved gene regulatory networks. This work links chromosome 21 genes to non-chromosome 21 genes known to interact in a Down syndrome phenotype through a reachability analysis of labeled transition graphs extracted from published gene regulatory network databases. The analysis provides new relations in a recently discovered link between a specific gene …
Intersection Algorithms Based On Geometric Intervals, Nicholas Stewart North
Intersection Algorithms Based On Geometric Intervals, Nicholas Stewart North
Theses and Dissertations
This thesis introduces new algorithms for solving curve/curve and ray/surface intersections. These algorithms introduce the concept of a geometric interval to extend the technique of Bézier clipping. A geometric interval is used to tightly bound a curve or surface or to contain a point on a curve or surface. Our algorithms retain the desirable characteristics of the Bézier clipping technique such as ease of implementation and the guarantee that all intersections over a given interval will be found. However, these new algorithms generally exhibit cubic convergence, improving on the observed quadratic convergence rate of Bézier clipping. This is achieved without …
Data Center Migration, Shane Wiswell
Data Center Migration, Shane Wiswell
Regis University Student Publications (comprehensive collection)
A successful datacenter migration plan will contribute to a company's productivity by minimizing the downtime of the business critical systems. After the design and construction of the new computer data center, a detailed project plan will be used to demonstrate the effectiveness of the data center migration in relation to the impact on the company's client base.
Heuristic Weighted Voting, Kristine Perry Monteith
Heuristic Weighted Voting, Kristine Perry Monteith
Theses and Dissertations
Selecting an effective method for combining the votes of classifiers in an ensemble can have a significant impact on the overall classification accuracy an ensemble is able to achieve. With some methods, the ensemble cannot even achieve as high a classification accuracy as the most accurate individual classifying component. To address this issue, we present the strategy of Heuristic Weighted Voting, a technique that uses heuristics to determine the confidence that a classifier has in its predictions on an instance by instance basis. Using these heuristics to weight the votes in an ensemble results in an overall average increase in …
Alternative Splicing: Associating Frequency With Isoforms, Anuradha Roy, Jennifer Leopold, Anne M. Maglia
Alternative Splicing: Associating Frequency With Isoforms, Anuradha Roy, Jennifer Leopold, Anne M. Maglia
Computer Science Faculty Research & Creative Works
In the simplest model of protein production, a gene gives rise to a single protein; DNA is transcribed to form pre-mRNA, which is converted to mRNA by splicing or removing introns. The result is a chain of exons that is translated to form a protein. Alternative splicing of exons may result in the formation of multiple proteins from the same gene sequence. However, not all of these proteins may be functional. Thus, we ask whether we can predict and rank (in order of frequency of occurrence and functional importance) the set of possible proteins for a gene. Herein we describe …
Analysis, Selection, And Implementation Of A Case Management System For Local City Government Attorney's Office, Patricia D. Hughes
Analysis, Selection, And Implementation Of A Case Management System For Local City Government Attorney's Office, Patricia D. Hughes
Regis University Student Publications (comprehensive collection)
This paper focuses on the business analysis, selection, and implementation of a case management system for a local government City Attorney's Office which is a document management system in addition to calendaring, notes, tasks, and billing. Their current system relies on paper document organization and as well as some electronic documentation in a simple file folder structure on a windows network file server. A business analysis review demonstrated the need for a cost effective automated business system to support and manage daily business processes, automate document creation and filing, track deadlines and tasks, and comply with new document retention and …
A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou
Research Collection School Of Computing and Information Systems
Distributed virtual environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or even more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently …
Spilling: Expanding Hand Held Interaction To Touch Table Displays, Jeffrey Clement, Dan R. Olsen Jr., Aaron Pace
Spilling: Expanding Hand Held Interaction To Touch Table Displays, Jeffrey Clement, Dan R. Olsen Jr., Aaron Pace
Faculty Publications
We envision a nomadic model of interaction where the personal computer fits in your pocket. Such a computer is extremely limited in screen space. A technique is described for “spilling” the display of a hand held computer onto a much larger table top display surface. Because our model of nomadic computing frequently involves the use of untrusted display services we restrict interactive input to the hand held. Navigation techniques such as scrolling or turning the display can be expressed through the table top. The orientation and position of the hand held on the table top is detected using three conductive …
Robust Multi-Modal Biometric Fusion Via Multiple Svms, Jonathan Dinerstein, Sabra Dinerstein, Dan A. Ventura
Robust Multi-Modal Biometric Fusion Via Multiple Svms, Jonathan Dinerstein, Sabra Dinerstein, Dan A. Ventura
Faculty Publications
Existing learning-based multi-modal biometric fusion techniques typically employ a single static Support Vector Machine (SVM). This type of fusion improves the accuracy of biometric classification, but it also has serious limitations because it is based on the assumptions that the set of biometric classifiers to be fused is local, static, and complete. We present a novel multi-SVM approach to multi-modal biometric fusion that addresses the limitations of existing fusion techniques and show empirically that our approach retains good classification accuracy even when some of the biometric modalities are unavailable.
Adtrees For Sequential Data And N-Gram Counting, Robert Van Dam, Dan A. Ventura
Adtrees For Sequential Data And N-Gram Counting, Robert Van Dam, Dan A. Ventura
Faculty Publications
We consider the problem of efficiently storing n-gram counts for large n over very large corpora. In such cases, the efficient storage of sufficient statistics can have a dramatic impact on system performance. One popular model for storing such data derived from tabular data sets with many attributes is the ADtree. Here, we adapt the ADtree to benefit from the sequential structure of corpora-type data. We demonstrate the usefulness of our approach on a portion of the well-known Wall Street Journal corpus from the Penn Treebank and show that our approach is exponentially more efficient than the naïve approach to …
A Data-Dependent Distance Measure For Transductive Instance-Based Learning, Jared Lundell, Dan A. Ventura
A Data-Dependent Distance Measure For Transductive Instance-Based Learning, Jared Lundell, Dan A. Ventura
Faculty Publications
We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labeled training data as well as available unlabeled data (that is to be classified by the model). This new data-driven measure of distance is empirically studied in the context of various instance-based models and is shown to reduce error (compared to traditional models) under certain learning conditions. Generalizations and improvements are suggested.
Automated Refactoring Of Legacy Java Software To Enumerated Types, Raffi Khatchadourian, Jason Sawin, Atanas Rountev
Automated Refactoring Of Legacy Java Software To Enumerated Types, Raffi Khatchadourian, Jason Sawin, Atanas Rountev
Publications and Research
Modern Java languages introduce several new features that offer significant improvements over older Java technology. In this article we consider the new enum construct, which provides language support for enumerated types. Prior to recent Java languages, programmers needed to employ various patterns (e.g., the weak enum pattern) to compensate for the absence of enumerated types in Java. Unfortunately, these compensation patterns lack several highly-desirable properties of the enum construct, most notably, type safety. We present a novel fully-automated approach for transforming legacy Java code to use the new enumeration construct. This semantics-preserving approach increases type safety, produces code that is …
Ecological Interfaces For Improving Mobile Robot Teleoperation, Michael A. Goodrich, Curtis W. Nielsen, Robert W. Ricks
Ecological Interfaces For Improving Mobile Robot Teleoperation, Michael A. Goodrich, Curtis W. Nielsen, Robert W. Ricks
Faculty Publications
Navigation is an essential element of many remote robot operations including search and rescue, reconnaissance, and space exploration. Previous reports on using remote mobile robots suggest that navigation is difficult due to poor situation awareness. It has been recommended by experts in human–robot interaction that interfaces between humans and robots provide more spatial information and better situational context in order to improve an operator’s situation awareness. This paper presents an ecological interface paradigm that combines video, map, and robotpose information into a 3-D mixed-reality display. The ecological paradigm is validated in planar worlds by comparing it against the standard interface …
Psoda: Better Tasting And Less Filling Than Paup, Hyrum Carroll, Mark J. Clement, Mark Ebbert, Quinn O. Snell
Psoda: Better Tasting And Less Filling Than Paup, Hyrum Carroll, Mark J. Clement, Mark Ebbert, Quinn O. Snell
Faculty Publications
PSODA is an open-source phylogenetic search application that implements traditional parsimony and likelihood search techniques as well as advanced search algorithms. PSODA is compatible with PAUP and the search algorithms are competitive with those in PAUP. PSODA also adds a basic scripting language to the PAUP block, making it possible to easily create advanced meta-searches. Additionally, PSODA provides a user-friendly GUI with real-time graphing visualizations and phylogeny viewer, and a multiple sequence alignment algorithm PSODA is freely available from the PSODA web site: http://csl.cs.byu.edu/psoda.
Psodascript: Applying Advanced Language Constructs To Open-Source Phylogenetic Search, Hyrum Carroll, Mark J. Clement, Jonathan Krein, Quinn O. Snell, Adam R. Teichert
Psodascript: Applying Advanced Language Constructs To Open-Source Phylogenetic Search, Hyrum Carroll, Mark J. Clement, Jonathan Krein, Quinn O. Snell, Adam R. Teichert
Faculty Publications
Due to the immensity of phylogenetic tree space for large data sets, researches must rely on heuristic searches to infer reasonable phylogenies. By designing meta-searches which appropriately combine a variety of heuristics and parameter settings, researchers can significantly improve the performance of heuristic searches. Advanced language constructs in the open-source PSODA project—including variables, mathematical and logical expressions, conditional statements, and user-defined commands—give researchers a better framework for the exploration and exploitation of phylogenetic meta-search algorithms. PSODA’s approach to scripting meta-search algorithms is unique among open-source packages and addresses several limitations of other phylogenetic applications.
Using Parsimony To Guide Maximum Likelihood Searches, Hyrum Carroll, Mark J. Clement, Timothy O'Connor, Quinn O. Snell, Kenneth Sundberg
Using Parsimony To Guide Maximum Likelihood Searches, Hyrum Carroll, Mark J. Clement, Timothy O'Connor, Quinn O. Snell, Kenneth Sundberg
Faculty Publications
The performance of maximum likelihood searches can be boosted by using the most parsimonious tree as a starting point for the search. The time spent in performing the parsimony search to find this starting tree is insignificant compared to the time spent in the maximum likelihood search, leading to an overall gain in search time. These parsimony boosted maximum likelihood searches lead to topologies with scores statisitically similar to the unboosted searches, but in less time.
I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon
I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon
Research Collection School Of Computing and Information Systems
User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with …
Cs 415: Social Implications Of Computing, Leo Finkelstein
Cs 415: Social Implications Of Computing, Leo Finkelstein
Computer Science & Engineering Syllabi
CS 415 is a communication skills course using as its subject matter current salient issues associated with the social implications of computing. In addition to the course text, you will need to use certain reading materials in the library and elsewhere, and you will be responsible for using concepts and theories provided in class lectures and discussions.
Control Of Nonholonomic Mobile Robot Formations Using Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks
Control Of Nonholonomic Mobile Robot Formations Using Neural Networks, Jagannathan Sarangapani, Travis Alan Dierks
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper the control of formations of multiple nonholonomic mobile robots is attempted by integrating a kinematic controller with a neural network (NN) computed-torque controller. A combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers. The NN is introduced to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are uniformly ultimately bounded, and numerical results are provided.
Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes
Neural Network Based Decentralized Controls Of Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, Li Liu, David A. Cartes
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a suite of neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control inputs are calculated using local signals, the transient and overall system stability can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system dynamics and the inter-connection terms, thus the requirements for exact system parameters are relaxed. Simulation studies with a three-machine power system demonstrate the effectiveness of the proposed controller designs.
Energy-Efficient Hybrid Key Management Protocol For Wireless Sensor Networks, Timothy J. Landstra, Maciej Jan Zawodniok, Jagannathan Sarangapani
Energy-Efficient Hybrid Key Management Protocol For Wireless Sensor Networks, Timothy J. Landstra, Maciej Jan Zawodniok, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, we propose a subnetwork key management strategy in which the heterogeneous security requirements of a wireless sensor network are considered to provide differing levels of security with minimum communication overhead. Additionally, it allows the dynamic creation of high security subnetworks within the wireless sensor network and provides subnetworks with a mechanism for dynamically creating a secure key using a novel and dynamic group key management protocol. The proposed energy-efficient protocol utilizes a combination of pre-deployed group keys and initial trustworthiness of nodes to create a level of trust between neighbors in the network. This trust is later …
Use Of Max-Flow On Facts Devices, Adam Lininger, Bruce M. Mcmillin, Badrul H. Chowdhury, Mariesa Crow
Use Of Max-Flow On Facts Devices, Adam Lininger, Bruce M. Mcmillin, Badrul H. Chowdhury, Mariesa Crow
Computer Science Faculty Research & Creative Works
FACTS devices can be used to mitigate cascading failures in a power grid by controlling the power flow in individual lines. Placement and control are significant issues. We present a procedure for determining whether a scenario can be mitigated using the concept of maximum flow. If it can be mitigated, we determine what placement and control setting will solve the scenario. This paper treats fourteen cascading failure scenarios and reports on the use of the max-flow algorithm both in determining the mitigation of each scenario and in finding FACTS settings that will mitigate the scenario.
Determining Domain Similarity And Domain-Protein Similarity Using Functional Similarity Measurements Of Gene Ontology Terms, Lisa Michelle Guntly, Jennifer Leopold, Anne M. Maglia
Determining Domain Similarity And Domain-Protein Similarity Using Functional Similarity Measurements Of Gene Ontology Terms, Lisa Michelle Guntly, Jennifer Leopold, Anne M. Maglia
Computer Science Faculty Research & Creative Works
Protein domains typically correspond to major functional sites of a protein. Therefore, determining similarity between domains can aid in the comparison of protein functions, and can provide a basis for grouping domains based on function. One strategy for comparing domain similarity and domain-protein similarity is to use similarity measurements of annotation terms from the Gene Ontology (GO). In this paper five methods are analyzed in terms of their usefulness for comparing domains, and comparing domains to proteins based on GO terms.