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Articles 481 - 510 of 1335
Full-Text Articles in Computer Sciences
Graph Summaries For Subgraph Frequency Estimation, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman
Graph Summaries For Subgraph Frequency Estimation, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman
Kno.e.sis Publications
A fundamental problem related to graph structured databases is searching for substructures. One issue with respect to optimizing such searches is the ability to estimate the frequency of substructures within a query graph. In this work, we present and evaluate two techniques for estimating the frequency of subgraphs from a summary of the data graph. In the first technique, we assume that edge occurrences on edge sequences are position independent and summarize only the most informative dependencies. In the second technique, we prune small subgraphs using a valuation scheme that blends information about their importance and estimation power. In both …
Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan
Self-Organizing Neural Models Integrating Rules And Reinforcement Learning, Teck-Hou Teng, Zhong-Ming Tan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Traditional approaches to integrating knowledge into neural network are concerned mainly about supervised learning. This paper presents how a family of self-organizing neural models known as fusion architecture for learning, cognition and navigation (FALCON) can incorporate a priori knowledge and perform knowledge refinement and expansion through reinforcement learning. Symbolic rules are formulated based on pre-existing know-how and inserted into FALCON as a priori knowledge. The availability of knowledge enables FALCON to start performing earlier in the initial learning trials. Through a temporal-difference (TD) learning method, the inserted rules can be refined and expanded according to the evaluative feedback signals received …
Development Of A Night Vision Goggle Heads Up Display For Paratrooper Guidance, Fernando Ontiveros
Development Of A Night Vision Goggle Heads Up Display For Paratrooper Guidance, Fernando Ontiveros
Theses and Dissertations
This thesis provides the proof of concept for the development and implementation of a Global Positioning System (GPS) display via Night Vision Goggles (NVG) Heads-Up Display (HUD) for paratroopers. The system has been designed for soldiers who will be able to utilize the technology in the form of a processing system worn in an ammo pouch and displayed via NVG HUD as a tunnel in the sky. The tunnel in the sky display design is essentially a series of boxes displayed within the goggle's HUD leading the paratrooper to the desired Landing Zone (LZ). The algorithm developed receives GPS and …
Defeasible Inference With Circumscriptive Owl Ontologies, Stephan Grimm, Pascal Hitzler
Defeasible Inference With Circumscriptive Owl Ontologies, Stephan Grimm, Pascal Hitzler
Computer Science and Engineering Faculty Publications
The Web Ontology Language (OWL) adheres to the openworld assumption and can thus not be used for forms of nonmonotonic reasoning or defeasible inference, an acknowledged desirable feature in open Semantic Web environments. We investigate the use of the formalism of circumscriptive description logics (DLs) to realise defeasible inference within the OWL framework. By example, we demonstrate how reasoning with (restricted) circumscribed OWL ontologies facilitates various forms of defeasible inference, also in comparison to alternative approaches. Moreover, we sketch an extension to DL tableaux for handling the circumscriptive case and report on a preliminary implementation.
Empowering Translational Research Using Semantic Web Technologies, Amit P. Sheth
Empowering Translational Research Using Semantic Web Technologies, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Language Learning From Positive Data And Negative Counterexamples, Sanjay Jain, Efim Kinber
Language Learning From Positive Data And Negative Counterexamples, Sanjay Jain, Efim Kinber
School of Computer Science & Engineering Faculty Publications
In this paper we introduce a paradigm for learning in the limit of potentially infinite languages from all positive data and negative counterexamples provided in response to the conjectures made by the learner. Several variants of this paradigm are considered that reflect different conditions/constraints on the type and size of negative counterexamples and on the time for obtaining them. In particular, we consider the models where 1) a learner gets the least negative counterexample; 2) the size of a negative counterexample must be bounded by the size of the positive data seen so far; 3) a counterexample may be delayed. …
An Integrated Evaluation Method For Module-Based Undergraduate Information Retrieval Education, Yong Shi, Lei Zhu, Jane Wong, Bradley Sturz, Chun Tang
An Integrated Evaluation Method For Module-Based Undergraduate Information Retrieval Education, Yong Shi, Lei Zhu, Jane Wong, Bradley Sturz, Chun Tang
Faculty Articles
In the Information Age, career and life-long learning increasingly depend on information-retrieval (IR) skills to utilize digital and on-line information effectively. Consequently, IR has become a valuable integral element of many disciplines. To address primary problems in the current college-level IR education, we have proposed a module-based curricular model that facilitates the development of an array of IR course modules that enable flexible adoption and integration. In addition, these modules can be designed to meet the specific needs of various disciplines and programs. This paper presents a preliminary integrated evaluation method which combines subjective and objective evaluation in order to …
On A-Ary Subdivision For Curve Design: I. 4-Point And 6-Point Interpolatory Schemes, Jian-Ao Lian
On A-Ary Subdivision For Curve Design: I. 4-Point And 6-Point Interpolatory Schemes, Jian-Ao Lian
Applications and Applied Mathematics: An International Journal (AAM)
The classical binary 4-point and 6-point interpolatery subdivision schemes are generalized to a-ary setting for any integer a greater than or equal to 3. These new a-ary subdivision schemes for curve design are derived easily from their corresponding two-scale scaling functions, a notion from the context of wavelets.
Architecture And Implementation Of A Trust Model For Pervasive Applications, Sheikh Iqbal Ahamed, Mohammad Zulkernine, Sailaja Bulusu, Mehrab Monjur
Architecture And Implementation Of A Trust Model For Pervasive Applications, Sheikh Iqbal Ahamed, Mohammad Zulkernine, Sailaja Bulusu, Mehrab Monjur
Mathematics, Statistics and Computer Science Faculty Research and Publications
Collaborative effort to share resources is a significant feature of pervasive computing environments. To achieve secure service discovery and sharing, and to distinguish between malevolent and benevolent entities, trust models must be defined. It is critical to estimate a device's initial trust value because of the transient nature of pervasive smart space; however, most of the prior research work on trust models for pervasive applications used the notion of constant initial trust assignment. In this paper, we design and implement a trust model called DIRT. We categorize services in different security levels and depending on the service requester's context information, …
Improving The Computer Science In Bioinformatics Through Open Source Pedagogy, John David N. Dionisio, Kam D. Dahlquist
Improving The Computer Science In Bioinformatics Through Open Source Pedagogy, John David N. Dionisio, Kam D. Dahlquist
Biology Faculty Works
Bioinformatics relies more than ever on information technologies. This pressures scientists to keep up with software development best practices. However, traditional computer science curricula do not necessarily expose students to collaborative and long-lived software development. Using open source principles, practices, and tools forms an effective pedagogy for software development best practices. This paper reports on a bioinformatics teaching framework implemented through courses introducing computer science students to the field. The courses led to an initial product release consisting of software and an Escherichia coli K12 GenMAPP Gene Database, within a total "incubation time" of six months.
Performance Evaluation Of The Factored Model For Arabic To English Phrase Based Statistical Machine Translation, Mireille Anwar
Performance Evaluation Of The Factored Model For Arabic To English Phrase Based Statistical Machine Translation, Mireille Anwar
Archived Theses and Dissertations
No abstract provided.
Hba: Distributed Metadata Management For Large Cluster-Based Storage Systems, Yifeng Zhu, Hong Jiang, Jun Wang, Feng Xian
Hba: Distributed Metadata Management For Large Cluster-Based Storage Systems, Yifeng Zhu, Hong Jiang, Jun Wang, Feng Xian
School of Computing: Faculty Publications
An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers. This paper presents a novel technique called Hierarchical Bloom Filter Arrays (HBA) to map filenames to the metadata servers holding their metadata. Two levels of probabilistic arrays, namely, the Bloom filter arrays with different levels of accuracies, are used on each metadata server. One array, with lower accuracy and representing the distribution of the entire metadata, trades accuracy for significantly reduced memory overhead, whereas the other array, with higher accuracy, caches partial distribution information and exploits the …
Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Context Modeling With Evolutionary Fuzzy Cognitive Map In Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen
Research Collection School Of Computing and Information Systems
To generate a believable and dynamic virtual world is a great challenge in interactive storytelling. In this paper, we propose a model, namely evolutionary fuzzy cognitive map (E-FCM), to model the dynamic causal relationships among different context variables. As an extension to conventional FCM, E-FCM models not only the fuzzy causal relationships among the variables, but also the probabilistic property of causal relationships, and asynchronous activity update of the concepts. With this model, the context variables evolve in a dynamic and uncertain manner with the according evolving time. As a result, the virtual world is presented more realistically and dynamically.
Mitigating Reversing Vulnerabilities In .Net Applications Using Virtualized Software Protection, Matthew A. Zimmerman
Mitigating Reversing Vulnerabilities In .Net Applications Using Virtualized Software Protection, Matthew A. Zimmerman
Theses and Dissertations
Protecting intellectual property contained in application source code and preventing tampering with application binaries are both major concerns for software developers. Simply by possessing an application binary, any user is able to attempt to reverse engineer valuable information or produce unanticipated execution results through tampering. As reverse engineering tools become more prevalent, and as the knowledge required to effectively use those tools decreases, applications come under increased attack from malicious users. Emerging development tools such as Microsoft's .NET Application Framework allow diverse source code composed of multiple programming languages to be integrated into a single application binary, but the potential …
Poster Abstract: Reliable People-Centric Sensing With Unreliable Voluntary Carriers, Cory Cornelius, Apu Kapadia, David Kotz, Dan Peebles, Minho Shin, Patrick Tsang
Poster Abstract: Reliable People-Centric Sensing With Unreliable Voluntary Carriers, Cory Cornelius, Apu Kapadia, David Kotz, Dan Peebles, Minho Shin, Patrick Tsang
Dartmouth Scholarship
As sensor technology becomes increasingly easy to integrate into personal devices such as mobile phones, clothing, and athletic equipment, there will be new applications involving opportunistic, people-centric sensing. These applications, which gather information about human activities and personal social context, raise many security and privacy challenges. In particular, data integrity is important for many applications, whether using traffic data for city planning or medical data for diagnosis. Although our AnonySense system (presented at MobiSys) addresses privacy in people-centric sensing, protecting data integrity in people-centric sensing still remains a challenge. Some mechanisms to protect privacy provide anonymity, and thus provide limited …
Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta
Wikinetviz: Visualizing Friends And Adversaries In Implicit Social Networks, Minh-Tam Le, Hoang-Vu Dang, Ee Peng Lim, Anwitaman Datta
Research Collection School Of Computing and Information Systems
When multiple users with diverse backgrounds and beliefs edit Wikipedia together, disputes often arise due to disagreements among the users. In this paper, we introduce a novel visualization tool known as WikiNetViz to visualize and analyze disputes among users in a dispute-induced social network. WikiNetViz is designed to quantify the degree of dispute between a pair of users using the article history. Each user (and article) is also assigned a controversy score by our proposed controversy rank model so as to measure the degree of controversy of a user (and an article) by the amount of disputes between the user …
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval, Steven Hoi, Wei Liu, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, relevance feedback has been adopted as a promising approach to improve the search performance. In this paper, we propose a novel idea of learning with historical relevance feedback log data, and adopt a new paradigm called “Collaborative Image Retrieval” (CIR). To effectively explore the log data, we propose a novel semi-supervised distance metric learning technique, called “Laplacian Regularized Metric Learning” (LRML), for learning robust distance metrics for CIR. Different from previous methods, the proposed LRML method integrates both …
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Scheme For Large-Scale Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
A critical issue of large-scale multimedia retrieval is how to develop an effective framework for ranking the search results. This problem is particularly challenging for content-based video retrieval due to some issues such as short text queries, insufficient sample learning, fusion of multimodal contents, and large-scale learning with huge media data. In this paper, we propose a novel multimodal and multilevel (MMML) ranking framework to attack the challenging ranking problem of content-based video retrieval. We represent the video retrieval task by graphs and suggest a graph based semi-supervised ranking (SSR) scheme, which can learn with small samples effectively and integrate …
Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Predicting Trusts Among Users Of Online Communities: An Epinions Case Study, Haifeng Liu, Ee Peng Lim, Hady W. Lauw, Minh-Tam Le, Aixin Sun, Jaideep Srivastava, Young Ae Kim
Research Collection School Of Computing and Information Systems
Trust between a pair of users is an important piece of information for users in an online community (such as electronic commerce websites and product review websites) where users may rely on trust information to make decisions. In this paper, we address the problem of predicting whether a user trusts another user. Most prior work infers unknown trust ratings from known trust ratings. The effectiveness of this approach depends on the connectivity of the known web of trust and can be quite poor when the connectivity is very sparse which is often the case in an online community. In this …
Use Of Cognitive Mapping Techniques In Information Systems Development, Keng Siau, X. Tan
Use Of Cognitive Mapping Techniques In Information Systems Development, Keng Siau, X. Tan
Research Collection School Of Computing and Information Systems
Cognitive mapping techniques as a communication tool can be used in various information systems (IS) development and implementation activities. The three major cognitive mapping techniques include causal mapping, semantic mapping, and concept mapping. A causal map represents a set of causal relationships among constructs within a belief system. Semantic mapping, also known as idea mapping, is used to explore an idea without the constraints of a superimposed structure. The result of concept mapping is a graphical representation in which nodes represent concepts and links represent the relationships between concepts. Cognitive mapping techniques have been proposed to be applied in requirements …
Multi-View Ear Recognition Based On B-Spline Pose Manifold Construction, Zhiyuan Zhang, Heng Liu
Multi-View Ear Recognition Based On B-Spline Pose Manifold Construction, Zhiyuan Zhang, Heng Liu
Research Collection School Of Computing and Information Systems
In this work, multi-view ear recognition problems are examined in detail. A new multi-view ear recognition approach based on B-Spline pose manifold construction in discriminative projection space which is formed by null kernel discriminant analysis (NKDA) feature extraction is presented. Many experiments and comparisons are provided to show the effectiveness of our multi-view ear recognition approach.
Information-Theory Based Optimal Location Management Schemes For Integrated Multi-System Wireless Networks, Archan Misra, Abhishek Roy, Sajal K. Das
Information-Theory Based Optimal Location Management Schemes For Integrated Multi-System Wireless Networks, Archan Misra, Abhishek Roy, Sajal K. Das
Research Collection School Of Computing and Information Systems
In a multisystem environment where a mobile node can utilize multiple interfaces and simultaneously connect to multiple providers, new opportunities exist for efficient location management strategies spanning heterogeneous cellular wireless networks. In this paper, an integrated framework is developed for location management in such a multi-system, fourth generation (4 G) wireless networks. This information-theoretic framework allows each individual sub-system to operate fairly independently, and does not require the knowledge of individual sub-network topologies. An efficient location management in such a loosely coupled network is designed by having a mobile node view its movement as a vector-valued sequence, and then transmit …
Probabilistically Reliable On-Demand Multicast In Wireless Mesh Networks, Xin Zhao, Chun Tung Chou, Jun Guo, Sanjay Jha, Archan Misra
Probabilistically Reliable On-Demand Multicast In Wireless Mesh Networks, Xin Zhao, Chun Tung Chou, Jun Guo, Sanjay Jha, Archan Misra
Research Collection School Of Computing and Information Systems
This paper studies probabilistically reliable multicast in wireless mesh networks (WMNs), utilizing MAC layer re-transmission and wireless broadcast advantage to improve both the multicast throughput and the delivery rate. We first present a new multicast routing metric which we call the expected multicast transmissions (EMT). EMT captures the effect of link packet delivery ratio, MAC layer retransmission and wireless broadcast advantage at the same time. The EMT of a MAC layer multicast transmission is the expected number of data transmissions (including retransmissions) required for a packet to reach all the recipients. The EMT of a multicast tree is the sum …
Work Dispersion, Process-Based Learning And Offshore Software Development Performance, Narayanasamy Ramasubbu, Sunil Mithas, M. S. Krishnan, Chris Kemerer
Work Dispersion, Process-Based Learning And Offshore Software Development Performance, Narayanasamy Ramasubbu, Sunil Mithas, M. S. Krishnan, Chris Kemerer
Research Collection School Of Computing and Information Systems
In this paper we develop a learning-mediated model of offshore software project productivity and quality to examine whether widely adopted structured software processes are effective in mitigating the negative effects of work dispersion in offshore software development. We explicate how the key process areas of the capability maturity model (CMM) can be utilized as a platform to launch learning routines in offshore software development and thereby explain why some offshore software development process improvement initiatives are more effective than others. We validate our learning-mediated model of offshore software project performance by utilizing data collected from 42 offshore software projects of …
Semi-Supervised Svm Batch Mode Active Learning For Image Retrieval, Steven Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
Semi-Supervised Svm Batch Mode Active Learning For Image Retrieval, Steven Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learning is popular for its application to relevance feedback in CBIR. However, the regular SVM active learning has two main drawbacks when used for relevance feedback. First, SVM often suffers from learning with a small number of labeled examples, which is the case in relevance feedback. Second, SVM active learning usually does not take into account the redundancy among examples, and therefore could select multiple examples in relevance feedback that are similar (or even identical) to …
Seemon: Scalable And Energy-Efficient Context Monitoring Framework For Sensor-Rich Mobile Environments, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, Junehwa Song
Seemon: Scalable And Energy-Efficient Context Monitoring Framework For Sensor-Rich Mobile Environments, Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, Junehwa Song
Research Collection School Of Computing and Information Systems
Proactively providing services to mobile individuals is essential for emerging ubiquitous applications. The major challenge in providing users with proactive services lies in continuously monitoring their contexts based on numerous sensors. The context monitoring with rich sensors imposes heavy workloads on mobile devices with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the device can proactively understand users' contexts and react appropriately. This paper proposes …
Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang
Visual Analytics For Supporting Entity Relationship Discovery On Text Data, Hanbo Dai, Ee Peng Lim, Hady W. Lauw, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
To conduct content analysis over text data, one may look out for important named objects and entities that refer to real world instances, synthesizing them into knowledge relevant to a given information seeking task. In this paper, we introduce a visual analytics tool called ER-Explorer to support such an analysis task. ER-Explorer consists of a data model known as TUBE and a set of data manipulation operations specially designed for examining entities and relationships in text. As part of TUBE, a set of interestingness measures is defined to help exploring entities and their relationships. We illustrate the use of ER-Explorer …
Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis
Capacity Constrained Assignment In Spatial Databases, Hou U Leong, Man Lung Yiu, Kyriakos Mouratidis, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q 2 Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M Q × P such that (i) each point q 2 Q (p 2 P) appears at most k times (at most nce) in M, (ii) the size of M is maximized (i.e., it comprises min{|P|,P q2Q q.k} pairs), and (iii) the total assignment cost (i.e., the sum of Euclidean distances within all pairs) is minimized. Thus, the CCA problem is …
An Office Survival Guide, M. Thulasidas
An Office Survival Guide, M. Thulasidas
Research Collection School Of Computing and Information Systems
In the unforgiving, dog-eat-dog corporate jungle, when you find yourself in a new corporate setting, you need to be sure of the welcome. More importantly, you need to prove yourself worthy of it.
Traceable And Retrievable Identity-Based Encryption, Man Ho Au, Qiong Huang, Joseph K. Liu, Willy Susilo, Duncan S. Wong, Guomin Yang
Traceable And Retrievable Identity-Based Encryption, Man Ho Au, Qiong Huang, Joseph K. Liu, Willy Susilo, Duncan S. Wong, Guomin Yang
Research Collection School Of Computing and Information Systems
Very recently, the concept of Traceable Identity-based Encryption (IBE) scheme (or Accountable Authority Identity based Encryption scheme) was introduced in Crypto 2007. This concept enables some mechanisms to reduce the trust of a private key generator (PKG) in an IBE system. The aim of this paper is threefold. First, we discuss some subtleties in the first traceable IBE scheme in the Crypto 2007 paper. Second, we present an extension to this work by having the PKG’s master secret key retrieved automatically if more than one user secret key are released. This way, the user can produce a concrete proof of …