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Articles 55561 - 55590 of 63750
Full-Text Articles in Entire DC Network
Packet-Loss Resilient Coding Scheme With Only Xor Operations, Gui Liang Feng, Robert H. Deng, Feng Bao
Packet-Loss Resilient Coding Scheme With Only Xor Operations, Gui Liang Feng, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Application of forward error correction to recover lost packets in higher layers of communication networks is receiving increasing attention. Most of the previous proposals for packet loss recovery use symbol-oriented Reed-Solomon codes operating in symbol erasure-correction mode. A Reed-Solomon code is optimal in the sense that it is maximal distance separable; however, the decoding speed of a Reed-Solomon code is slow since it involves operations over GF(2m) using lookup tables. A packet-oriented (n, k)/(m, l) packet-loss resilient code based on an (n, k) Reed-Solomon code over GF(2m) is given. The code accepts k-packet information sequences and encodes them into n-packet …
Group-Based Relevance Feedback With Support Vector Machine Ensembles, Steven C. H. Hoi, Michael R. Lyu
Group-Based Relevance Feedback With Support Vector Machine Ensembles, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Support vector machines (SVMs) have become one of the most promising techniques for relevance feedback in content-based image retrieval (CBIR). Typical SVM-based relevance feedback techniquessimply apply the strict binary classifications: positive (relevant) class and negative (irrelevant) class. However, in a real-world relevance feedback task, it is more reasonable and practical to assume the data come from multiple positive classes and one negative class. In order to formulate an effective relevance feedback algorithm, we propose a novel group-based relevance feedback scheme constructed with the SVM ensembles technique. Experiments are conducted to evaluate the performance of our proposed scheme and the traditional …
High Accuracy Classification Of Eeg Signal, Wenjie Xu, Cuitai Guan, Chng Eng Siong, S. Ranganatha, Manoj Thulasidas, Jiankang Wu
High Accuracy Classification Of Eeg Signal, Wenjie Xu, Cuitai Guan, Chng Eng Siong, S. Ranganatha, Manoj Thulasidas, Jiankang Wu
Research Collection School Of Computing and Information Systems
Improving classification accuracy is a key issue to advancing brain computer interface (BCI) research from laboratory to real world applications. This article presents a high accuracy EEC signal classification method using single trial EEC signal to detect left and right finger movement. We apply an optimal temporal filter to remove irrelevant signal and subsequently extract key features from spatial patterns of EEG signal to perform classification. Specifically, the proposed method transforms the original EEG signal into a spatial pattern and applies the RBF feature selection method to generate robust feature. Classification is performed by the SVM and our experimental result …
Enhancements To Crisp Possibilistic Reconstructability Analysis, Anas Al-Rabadi, Martin Zwick
Enhancements To Crisp Possibilistic Reconstructability Analysis, Anas Al-Rabadi, Martin Zwick
Complex Systems Faculty Publications and Presentations
Modified Reconstructibility Analysis (MRA), a novel decomposition within the framework of set-theoretic (crisp possibilistic) Reconstructibility Analysis, is presented. It is shown that in some cases while 3-variable NPN-classified Boolean functions are not decomposable using Conventional Reconstructibility Analysis (CRA), they are decomposable using Modified Reconstructibility Analysis (MRA). Also, it is shown that whenever a decomposition of 3-variable NPN-classified Boolean functions exists in both MRA and CRA, MRA yields simpler or equal complexity decompositions. A comparison of the corresponding complexities for Ashenhurst-Curtis decompositions, and Modified Reconstructibility Analysis (MRA) is also presented. While both AC and MRA decompose some but …
Design And Implementation Of A Large-Scale Context Fusion Network, Guanling Chen, Ming Li, David Kotz
Design And Implementation Of A Large-Scale Context Fusion Network, Guanling Chen, Ming Li, David Kotz
Dartmouth Scholarship
In this paper we motivate a Context Fusion Network (CFN), an infrastructure model that allows context-aware applications to select distributed data sources and compose them with customized data-fusion operators into a directed acyclic information fusion graph. Such a graph represents how an application computes high-level understandings of its execution context from low-level sensory data. Multiple graphs by different applications inter-connect with each other to form a global graph. A key advantage of a CFN is re-usability, both at code-level and instance-level, facilitated by operator composition. We designed and implemented a distributed CFN system, Solar, which maps the logical operator graph …
Kerf: Machine Learning To Aid Intrusion Analysts, Javed Aslam, Sergey Bratus, David Kotz, Ron Peterson, Daniela Rus
Kerf: Machine Learning To Aid Intrusion Analysts, Javed Aslam, Sergey Bratus, David Kotz, Ron Peterson, Daniela Rus
Dartmouth Scholarship
Kerf is a toolkit for post-hoc intrusion analysis of available system logs and some types of network logs. It takes the view that this process is inherently interactive and iterative: the human analyst browses the log data for apparent anomalies, and tests and revises his hypothesis of what happened. The hypothesis is alternately refined, as information that partially confirms the hypothesis is discovered, and expanded, as the analyst tries new avenues that broaden the investigation.
Improving Throughput By Link Distance Control In A Multi-Rate Ad Hoc Network, Xiaoxin Wu, Gang Ding, Bharat Bhargava, Shan Lei
Improving Throughput By Link Distance Control In A Multi-Rate Ad Hoc Network, Xiaoxin Wu, Gang Ding, Bharat Bhargava, Shan Lei
Department of Computer Science Technical Reports
No abstract provided.
Theoretical And Practical Complexity Of Uml, J. Erickson, Keng Siau
Theoretical And Practical Complexity Of Uml, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Systems have become increasingly complex, and as a result development methods have become more complex as well. The unified modeling language (UML) has been criticized for the often cited and sometimes over-whelming complexity it presents to its users, and those seeking to learn to use it. Using Rossi and Brinkkemper’s (1996) complexity metrics, Siau and Cao (2001) completed a complexity analysis of UML and 36 other modeling techniques, finding that UML is indeed more complex than other techniques. Siau, Erickson and Lee (2002) proposed that Rossi and Brinkkemper’s metrics present the theoretical maximum complexity, known as theoretical complexity. This is …
Sa&D And Database: Should We Be Researching What We Are Teaching?, Jeffrey B. Parson, Akhilesh. Bajaj, Dinesh Batra, Alan Hevner, Keng Siau
Sa&D And Database: Should We Be Researching What We Are Teaching?, Jeffrey B. Parson, Akhilesh. Bajaj, Dinesh Batra, Alan Hevner, Keng Siau
Research Collection School Of Computing and Information Systems
The panel will examine the reasons for the mismatch between SA&D and database teaching and research. The implication of this mismatch on the MIS academic and practitioner communities will also be discussed and debated.
Gesture Tracking And Recognition For Lecture Video Editing, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Gesture Tracking And Recognition For Lecture Video Editing, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
This paper presents a gesture based driven approach for video editing. Given a lecture video, we adopt novel approaches to automatically detect and synchronize its content with electronic slides. The gestures in each synchronized topic (or shot) are then tracked and recognized continuously. By registering shots and slides and recovering their transformation, the regions where the gestures take place can be known. Based on the recognized gestures and their registered positions, the information in slides can be seamlessly extracted, not only to assist video editing, but also to enhance the quality of original lecture video.
Investigating Deception In Cyberspace, Holtjona Galanxhi, Fiona Fui-Hoon Nah
Investigating Deception In Cyberspace, Holtjona Galanxhi, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
The use of anthropomorphic avatars provides Internet users the opportunity and freedom to present their desired identity. As cyberspace becomes a heaven for deceptive behavior, human-computer interaction research will need to be carried out to study and understand these deceptive behaviors. The objective of this research is to investigate the behavior of deceivers and truthtellers in the cyberspace environment and to examine how their intention to deceive may influence the choice of their avatars. The effect of using avatars to support communication will also be studied. This research provides insights on communication and trust issues in avatar environments.
Ica-Fx Features For Classification Of Singing Voice And Instrumental Sound, Tat-Wan Leung, Chong-Wah Ngo, Rynson W. H Lau
Ica-Fx Features For Classification Of Singing Voice And Instrumental Sound, Tat-Wan Leung, Chong-Wah Ngo, Rynson W. H Lau
Research Collection School Of Computing and Information Systems
This paper describes a new approach in locating the segments of singing voice in pop musical songs. Initially, GLR distance measure is employed to temporally detect the boundaries of singing voices and instrumental sounds. ICAFX is then adopted to extract the independent components of acoustic features for SVM classification. Experimental results indicate that ICA-FX can improve the classification performance by significantly reducing the independent components that are not related to class label information.
Graph Based Image Matching, Hui Jiang, Chong-Wah Ngo
Graph Based Image Matching, Hui Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Given two or more images, we can define different but related problems on pattern matching such as image registration, pattern detection and localization, and common pattern discovery. These problems have different levels of purpose and difficulties, as a result, often associate with different solutions. In this paper, we propose a novel approach to solve these problems under a unified framework based on graph matching. We first split the images into small blocks and represent each block as a node in a bipartite graph. A maximum weighted bipartite graph matching algorithm is then employed in an iterative way to find the …
Novel Seed Selection For Multiple Objects Detection And Tracking, Zailiang Pan, Chong-Wah Ngo
Novel Seed Selection For Multiple Objects Detection And Tracking, Zailiang Pan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper proposes a unified approach for initializing, detecting and tracking of multiple moving objects. Object initialization is achieved through novel seed selection which is adaptively activated, depending on the quality of tracking, to select the best possible frames along the temporal direction for object detection. EM algorithm is then employed to robustly segment and detect multiple objects in a selected frame. Each detected object is represented by an appearance-based model and mean shift tracking procedure is adopted to rapidly and effectively track the target objects.
Solar: Building A Context Fusion Network For Pervasive Computing, Guanling Chen
Solar: Building A Context Fusion Network For Pervasive Computing, Guanling Chen
Dartmouth College Ph.D Dissertations
The complexity of developing context-aware pervasive-computing applications calls for distributed software infrastructures that assist applications to collect, aggregate, and disseminate contextual data. In this dissertation, we present a Context Fusion Network (CFN), called Solar, which is built with a scalable and self-organized service overlay. Solar is flexible and allows applications to select distributed data sources and compose them with customized data-fusion operators into a directed acyclic information flow graph. Such a graph represents how an application computes high-level understandings of its execution context from low-level sensory data. To manage application-specified operators on a set of overlay nodes called Planets, Solar …
Values Of Mobile Technology In Education, Fiona Fui-Hoon Nah, Keng Siau, H. Sheng
Values Of Mobile Technology In Education, Fiona Fui-Hoon Nah, Keng Siau, H. Sheng
Research Collection School Of Computing and Information Systems
Mobile technology shows promise in supporting and improving education and its delivery. Coupled with the use of mobile devices and software/hardware solutions that make it possible to access educational content, students can be exposed to new educational experience. Applications of mobile technology in education can provide many benefits including greater flexibility, more available education resources, as well as greater convenience, accessibility and responsiveness. As a new phenomenon that will be widely used and adopted in the years to come, the values of mobile technology in education should be better understood and researched. This research outlines our empirical study to examine …
Rating Information Security Maturity, Arcot Desai Narasimhalu, Nagarajan Dayasindhu
Rating Information Security Maturity, Arcot Desai Narasimhalu, Nagarajan Dayasindhu
Research Collection School Of Computing and Information Systems
Most CEOs have difficulty relating to the information security investments in their companies. This article presents a summary of a the information security maturity model that the CEOs could use to determine the desired level of investments into information security infrastructure, tools and applications.
Exploiting Information Theory For Adaptive Mobility And Resource Management In Future Cellular Networks, Abhishek Roy, Sajal K. Das, Archan Misra
Exploiting Information Theory For Adaptive Mobility And Resource Management In Future Cellular Networks, Abhishek Roy, Sajal K. Das, Archan Misra
Research Collection School Of Computing and Information Systems
We utilize tools from information theory to develop adaptive algorithms for two key problems in cellular networks: location tracking and resource management. The use of information theory is motivated by the fundamental observation that overheads in many aspects of mobile computing can be traced to the randomness or uncertainty in an individual user's movement behavior. We present a model-independent information-theoretic approach for estimating and managing this uncertainty, and relate it to the entropy or information content of the user's movement process. Information-theoretic mobility management algorithms are very simple, yet reduce overhead by ∼80 percent in simulated scenarios by optimally adapting …
Ltam: A Location-Temporal Authorization Model, Hai Yu, Ee Peng Lim
Ltam: A Location-Temporal Authorization Model, Hai Yu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
This paper describes an authorization model for specifying access privileges of users who make requests to access a set of locations in a building or more generally a physical or virtual infrastructure. In the model, primitive locations can be grouped into composite locations and the connectivities among locations are represented in a multilevel location graph. Authorizations are defined with temporal constraints on the time to enter and leave a location and constraints on the number of times users can access a location. Access control enforcement is conducted by monitoring user movement and checking access requests against an authorization database. The …
Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani
Feedback Linearization Based Power System Stabilizer Design With Control Limits, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In power system controls, simplified analytical models are used to represent the dynamics of power system and controller designs are not rigorous with no stability analysis. One reason is because the power systems are complex nonlinear systems which pose difficulty for analysis. This paper presents a feedback linearization based power system stabilizer design for a single machine infinite bus power system. Since practical operating conditions require the magnitude of control signal to be within certain limits, the stability of the control system under control limits is also analyzed. Simulation results under different kinds of operating conditions show that the controller …
Pre-Conference Proceedings Of The Focus Symposium On Intelligent Software Systems For The New Infostructure: Baden-Baden, Germany, Collaborative Agent Design Research Center
Pre-Conference Proceedings Of The Focus Symposium On Intelligent Software Systems For The New Infostructure: Baden-Baden, Germany, Collaborative Agent Design Research Center
Collaborative Agent Design (CAD) Research Center
Over the past several years the papers in this annual series of symposia have increasingly centered on the realization of a human-computer collaboration environment in which computer-based software agents with reasoning capabilities provide meaningful support to human decision makers. It is therefore quite appropriate that the first paper in the 2004 Proceedings should address the historical evolutionary path of ‘intelligent’ software leading to the goal of a semantic Web environment. The realization of this goal is now in sight, driven by public security threats that are increasingly relying on technology for effective countermeasures.
The Evolution Of Intelligent Computer Software And The Semantic Web, Jens G. Pohl
The Evolution Of Intelligent Computer Software And The Semantic Web, Jens G. Pohl
Collaborative Agent Design (CAD) Research Center
The purpose of this paper is to trace the evolution of intelligent software from data-centric applications that essentially encapsulate their data environment to ontology-based applications with automated reasoning capabilities. The author draws a distinction between human intelligence and component capabilities within a more general definition of intelligence, which may be embedded in computer software. The primary vehicle in the quest for intelligent software has been the gradual recognition of the central role played by data and information, rather than the logic and functionality of the application. The three milestones in this evolution have been: the separation of data management from …
An Adaptive Mechanism For Improving File Transfer Performance, Eric Moss, Leen-Kiat Soh
An Adaptive Mechanism For Improving File Transfer Performance, Eric Moss, Leen-Kiat Soh
School of Computing: Technical Reports
A variant of instance-based learning is described which detects periodic patterns in the presence of sparse data. A weighted average gives higher weight to values in the recent past as well as those at expected periods in the past. After each new measurement, the space of weights near the current set is searched for a set that minimizes the error of prediction, thus providing a learning mechanism. The method is described in terms of an application which minimizes file download times by choosing between available servers.
Feature Weighting Using Neural Networks, Tony R. Martinez, Xinchuan Zeng
Feature Weighting Using Neural Networks, Tony R. Martinez, Xinchuan Zeng
Faculty Publications
In this work we propose a feature weighting method for classification tasks by extracting relevant information from a trained neural network. This method weights an attribute based on strengths (weights) of related links in the neural network, in which an important feature is typically connected to strong links and has more impact on the outputs. This method is applied to feature weighting br the nearest neighbor classifier and is tested on 15 real-world classification tasks. The results show that it can improve the nearest neighbor classifier on 14 of the 15 tested tasks, and also outperforms the neural network on …
Softprop: Softmax Neural Network Backpropagation Learning, Tony R. Martinez, Michael E. Rimer
Softprop: Softmax Neural Network Backpropagation Learning, Tony R. Martinez, Michael E. Rimer
Faculty Publications
Multi-layer backpropagation, like many learning algorithms that can create complex decision surfaces, is prone to overfitting. Softprop is a novel learning approach presented here that is reminiscent of the softmax explore-exploit Q-learning search heuristic It fits the problem while delaying settling into error minima to achieve better generalization and more robust learning. This is accomplished by blending standard SSE optimization with lazy training, a new objective function well suited to learning classification tasks, to form a more stable learning model. Over several machine learning data sets, softprop reduces classification error by 17.1 percent and the variance in results by 38.6 …
Using Permutations Instead Of Student’S T Distribution For P-Values In Paired-Difference Algorithm Comparisons, Tony R. Martinez, Joshua Menke
Using Permutations Instead Of Student’S T Distribution For P-Values In Paired-Difference Algorithm Comparisons, Tony R. Martinez, Joshua Menke
Faculty Publications
The paired-difference t-test is commonly used in the machine learning community to determine whether one learning algorithm is better than another on a given learning task. This paper suggests the use of the permutation test instead hecause it calculates the exact p-value instead of an estimate. The permutation test is also distribution free and the time complexity is trivial for the commonly used 10-fold cross-validation paired-difference test. Results of experiments on real-world problems suggest it is not uncommon to see the t-test estimate deviate up to 30-50% from the exact p-value.
Agribusiness Sheep Updates - 2004 Part 3, Ken Hart, Keith Croker, Rob Davidson, Mario D'Antuono, Evan Burt, Tanya Kilminster, Diana Fedorenko, Darryl Mcclements, Robert Beard, Sandy Turton, Martin Atwell, Robert Beard
Agribusiness Sheep Updates - 2004 Part 3, Ken Hart, Keith Croker, Rob Davidson, Mario D'Antuono, Evan Burt, Tanya Kilminster, Diana Fedorenko, Darryl Mcclements, Robert Beard, Sandy Turton, Martin Atwell, Robert Beard
Sheep Updates
Posters Can Merino Ewes be Teased to Synchronise Oestrus for a Summer/Autumn Mating? Ken Hart, Keith Croker, Department of Agriculture Western Australia, Rob Davidson, School of Animal Biology, University of Western Australia. Mario D'Antuono, Department of Agriculture Western Australia Damara Sheep: Now Looking Domestic Evan Burt and Tanya Kilminster, Department of Agriculture Western Australia Production and Water Use of Lucerne and French Serradella Under Three Sowing Rates Diana Fedorenko1,4, Darryl McClements1,4 , Robert Beard3,4 1Department of Agriculture, 3 Farmer, Meckering, 4CRC for Plant-based Management of Dryland Salinity. E-SHEEP - Individual Animal Management is here Sandy Turton & Martin Atwell, Department …
Transport Logistics Planning With Service-Level Constraints, Hoong Chuin Lau, K. M. Ng, Xintao Wu
Transport Logistics Planning With Service-Level Constraints, Hoong Chuin Lau, K. M. Ng, Xintao Wu
Research Collection School Of Computing and Information Systems
In this paper, we study a logistics problem arising in military transport planning. A military organization operates a large fleet of vehicles in a depot to serve the requests of various operational units. Each request has a fixed start and end time, and is served by a prescribed number of vehicles. We address the following two problems: (1) how many vehicles are at least needed to meet a given service level of requests; and (2) suppose we allow each request to shift its start time by a constant duration, call all the requests be met? A Niche genetic algorithm, together …
An Online Survey Framework Using The Life Events Calendar, Jared Kite, Leen-Kiat Soh
An Online Survey Framework Using The Life Events Calendar, Jared Kite, Leen-Kiat Soh
School of Computing: Technical Reports
We describe an online survey framework programmed as a Java applet with a MySQL back-end. Our framework is built specifically as a Event History Calendar for the study of tobacco users and their behavior over a six month period. We introduce the notion of a Life Events Calendar and the relevance of an intelligent survey system in this context. We describe our methods and our component application approach and expand on the opportunities for artificial intelligence research with the system.
Discovering Transcriptional Regulatory Rules From Gene Expression And Tf-Dna Binding Data By Decision Tree Learning, Jianhua Ruan, Weixiong Zhang
Discovering Transcriptional Regulatory Rules From Gene Expression And Tf-Dna Binding Data By Decision Tree Learning, Jianhua Ruan, Weixiong Zhang
All Computer Science and Engineering Research
Background: One of the most promising but challenging task in the post-genomic era is to reconstruct the transcriptional regulatory networks. The goal is to reveal, for each gene that responds to a certain biological event, which transcription factors affect its transcription, and how several transcription factors coordinate to accomplish specific regulations. Results: Here we propose a supervised machine learning approach to address these questions. We build decision trees to associate the expression level of a gene with the transcription factor binding data of its promoter. From the decision trees, we extract regulatory rules that specify how the binding of a …