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Articles 17221 - 17250 of 20646
Full-Text Articles in Entire DC Network
Designing The Value Curve For Your Next Innovation, Arcot Desai Narasimhalu
Designing The Value Curve For Your Next Innovation, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
This paper introduces an additional feature to the strategy canvas and value curve that will make innovation designers more effective. The new feature is to let the innovators carry out the designs of their new innovations taking into account both the cost of improving the quality of a parameter that the users value highly and the savings accrued from the drop in provisioning for parameters that users place less emphasis in an innovation.
Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng
Predicting Coronary Artery Disease With Medical Profile And Gene Polymorphisms Data, Qiongyu Chen, Guoliang Li, Tze-Yun Leong, Chew-Kiat Heng
Research Collection School Of Computing and Information Systems
Coronary artery disease (CAD) is a main cause of death in the world. Finding cost-effective methods to predict CAD is a major challenge in public health. In this paper, we investigate the combined effects of genetic polymorphisms and non-genetic factors on predicting the risk of CAD by applying well known classification methods, such as Bayesian networks, naïve Bayes, support vector machine, k-nearest neighbor, neural networks and decision trees. Our experiments show that all these classifiers are comparable in terms of accuracy, while Bayesian networks have the additional advantage of being able to provide insights into the relationships among the variables. …
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
An Artificial Immune System Based Approach For English Grammar Correction, Akshat Kumar, Shivashankar B. Nair
Research Collection School Of Computing and Information Systems
Grammar checking and correction comprise of the primary problems in the area of Natural Language Processing (NLP). Traditional approaches fall into two major categories: Rule based and Corpus based. While the former relies heavily on grammar rules the latter approach is statistical in nature. We provide a novel corpus based approach for grammar checking that uses the principles of an Artificial Immune System (AIS).We treat grammatical error as pathogens (in immunological terms) and build antibody detectors capable of detecting grammatical errors while allowing correct constructs to filter through. Our results show that it is possible to detect a range of …
Mapping Better Business Strategies With Gis, Tin Seong Kam
Mapping Better Business Strategies With Gis, Tin Seong Kam
Research Collection School Of Computing and Information Systems
The value of location as a business measure is fast becoming an important consideration for organisations. GIS (Geographical Information Systems), with its capability to manage, display, analyse business information spatially, is emerging as a powerful location intelligence tool. In the US, Starbucks, Blockbuster, Hyundai, and thousands of other businesses use census data and GIS software to help them understand what types of people buy their products and services, and how to better market to these consumers. For example, McDonald’s in Japan uses a GIS system to overlay demographic information on maps to help identify promising new store sites. Singapore Management …
Pre-Conference Proceedings Of The Focus Symposium On Representation Of Context In Software Data → Information → Knowledge, Collaborative Agent Design Research Center
Pre-Conference Proceedings Of The Focus Symposium On Representation Of Context In Software Data → Information → Knowledge, Collaborative Agent Design Research Center
Collaborative Agent Design (CAD) Research Center
For the past 20 years commercial corporations and government agencies have suffered under the limitations of stove-piped computer software applications that function as discrete entities within a fragmented data-processing environment. In the United States of America (US) military services, lack of interoperability has been identified by numerous think tanks, advisory boards, and studies, as the primary information systems problem (e.g., Army Science Board 2000, Air Force SAB 2000 Command and Control Study, and NSB Network-Centric Naval Forces 2000). Yet, despite this level of attention, all attempts to achieve interoperability within the current data-centric information systems environment have proven to be …
Sampling Methods In Ray-Based Global Illumination, David Cline
Sampling Methods In Ray-Based Global Illumination, David Cline
Theses and Dissertations
In computer graphics, algorithms that attempt to create photographic images by simulating light transport are collectively known as Global Illumination methods. The most versatile of these are based on ray tracing (following ray paths through a scene), and numerical integration using random or quasi-random sampling. While ray tracing and sampling methods in global illumination have progressed much in the last two decades, the goal of fast and accurate simulation of light transport remains elusive. This dissertation presents a number of new sampling methods that attempt to address some of the shortcomings of existing global illumination algorithms. The first part of …
Infrastructure Hardening: A Competitive Co-Evolutionary Methodology Inspired By Neo-Darwinian Arms Races, Travis Service, Daniel R. Tauritz, William M. Siever
Infrastructure Hardening: A Competitive Co-Evolutionary Methodology Inspired By Neo-Darwinian Arms Races, Travis Service, Daniel R. Tauritz, William M. Siever
Computer Science Faculty Research & Creative Works
The world is increasingly dependent on critical infrastructures such as the electric power grid, water, gas, and oil transport systems, which are susceptible to cascading failures that can result from a few faults. Due to the combinatorial complexity in the search spaces involved, most traditional search techniques are inappropriate for identifying these faults and potential protections against them. This paper provides a computational methodology employing competitive coevolution to simultaneously identify low-effort, high-impact faults and corresponding means of hardening infrastructures against them. A power system case study provides empirical evidence that our proposed methodology is capable of identifying cost effective modifications …
Specification Of Non-Functional Requirements For Contract Specification In The Ngoss Framework For Quality Management And Product Evaluation, Manooch Amoozdeh, Nektarios Georgalas, Xiaoqing Frank Liu
Specification Of Non-Functional Requirements For Contract Specification In The Ngoss Framework For Quality Management And Product Evaluation, Manooch Amoozdeh, Nektarios Georgalas, Xiaoqing Frank Liu
Computer Science Faculty Research & Creative Works
The community of operation support systems (OSS) for telecom applications defined a set of fundamental principles, processes, and architectures for developing the next generation OSS through the TeleManagement Forum TMF. At the heart of NGOSS lies the notion of a "contract" which embodies the specification of services offered by an OSS component for quality management and product evaluation. However, TMF does not provide any method (or process) for specification of the non-functional part in the NGOSS contract specification. In this paper, we develop a systematic approach for specifying non-functional requirements of telecom OSS applications for contracts in the NGOSS framework …
Or Best Offer: A Privacy Policy Negotiation Protocol, Daniel David Walker
Or Best Offer: A Privacy Policy Negotiation Protocol, Daniel David Walker
Theses and Dissertations
Users today are concerned about how their information is collected, stored and used by Internet sites. Privacy policy languages, such as the Platform for Privacy Preferences (P3P), allow websites to publish their privacy practices and policies in machine readable form. Currently, software agents designed to protect users' privacy follow a "take it or leave it" approach when evaluating these privacy policies. This approach is inflexible and gives the server ultimate control over the privacy of web transactions. Privacy policy negotiation is one approach to leveling the playing field by allowing a client to negotiate with a server to determine how …
Extensible Pre-Authentication In Kerberos, Phillip L. Hellewell
Extensible Pre-Authentication In Kerberos, Phillip L. Hellewell
Theses and Dissertations
Organizations need to provide services to a wide range of people, including strangers outside their local security domain. As the number of users grows larger, it becomes increasingly tedious to maintain and provision user accounts. It remains an open problem to create a system for provisioning outsiders that is secure, flexible, efficient, scalable, and easy to manage. Kerberos is a secure, industry-standard protocol. Currently, Kerberos operates as a closed system; all users must be specified upfront and managed on an individual basis. This paper presents EPAK (Extensible Pre-Authentication in Kerberos), a framework that enables Kerberos to operate as an open …
Obstacle Avoidance And Path Traversal Using Interactive Machine Learning, Jonathan M. Turner
Obstacle Avoidance And Path Traversal Using Interactive Machine Learning, Jonathan M. Turner
Theses and Dissertations
Recently there has been a growing interest in using robots in activities that are dangerous or cost prohibitive for humans to do. Such activities include military uses and space exploration. While robotic hardware is often capable of being used in these types of situations, the ability of human operators to control robots in an effective manner is often limited. This deficiency is often related to the control interface of the robot and the level of autonomy that control system affords the human operator. This thesis describes a robot control system, called the safe/unsafe system, which gives a human operator the …
Game Theoretical Data Replication Techniques For Large-Scale Autonomous Distributed Computing Systems, Samee Ullah Khan
Game Theoretical Data Replication Techniques For Large-Scale Autonomous Distributed Computing Systems, Samee Ullah Khan
Computer Science and Engineering Dissertations - Archive
Data replication in geographically dispersed servers is an essential technique for reducing the user perceived access time in large-scale distributed computing systems. A majority of the conventional replica placement techniques lack scalability and solution quality. To counteract such issues, this thesis proposes a game theoretical replica placement framework, in which autonomous agents compete for the allocation or reallocation of replicas onto their representative servers in a self-managed fashion. Naturally, each agent's goal is to maximize its own benefit. However, the framework is designed to suppress individualism and to ensure system-wide optimization. Using this framework as an environment, several cooperative and …
A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng
A Dynamic Attribute-Based Load Shedding Scheme For Data Stream Management Systems, Amit Ahuja, Yiu-Kai D. Ng
Faculty Publications
A data stream being transmitted over a network channel with capacity less than the data transmission rate of the data stream causes sequential network problems. In this paper, we present a new approach for shedding less-informative attribute data from a data stream to maintain a data transmission rate less than the network channel capacity. A scheme for shedding attributes and their data, instead of tuples, becomes imperative in data stream load shedding, since shedding a complete tuple would lead to shedding informative attribute data along with less-informative attribute data in the tuple. Our load shedding approach handles intra-stream, as well …
Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe
Is Interpersonal Trust A Necessary Condition For Organisational Learning?, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
The organisational behaviour and management literature has devoted a lot attention on various factors affecting organisational learning. While there has been much work done to examine trust in promoting organisational learning, there is a lack of consensus on the specific type of trust involved. The purpose of this paper is to highlight the importance of interpersonal trust in promoting organisational learning and propose a research agenda to test the extent of interpersonal trust on organisational learning. This paper contributes to the existing organisational learning literature by specifying a specific form of trust, interpersonal trust, which promotes organisational learning and proposing …
Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Discovering And Exploiting Causal Dependencies For Robust Mobile Context-Aware Recommenders, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Acquisition of context poses unique challenges to mobile context-aware recommender systems. The limited resources in these systems make minimizing their context acquisition a practical need, and the uncertainty in the mobile environment makes missing and erroneous context inputs a major concern. In this paper, we propose an approach based on Bayesian networks (BNs) for building recommender systems that minimize context acquisition. Our learning approach iteratively trims the BN-based context model until it contains only the minimal set of context parameters that are important to a user. In addition, we show that a two-tiered context model can effectively capture the causal …
Association-Based Image Retrieval, Arun D. Kulkarni, H. Gunturu, S. Dalta
Association-Based Image Retrieval, Arun D. Kulkarni, H. Gunturu, S. Dalta
Computer Science Faculty Publications and Presentations
With advances in the computer technology and the World Wide Web there has been an explosion in the amount and complexity of multimedia data that are generated, stored, transmitted, analyzed, and accessed. In order to extract useful information from this huge amount of data, many content-based image retrieval (CBIR) systems have been developed in the last decade. A typical CBIR system captures image features that represent image properties such as color, texture, or shape of objects in the query image and try to retrieve images from the database with similar features. Recent advances in CBIR systems include relevance feedback based …
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.
Online Reinforcement Learning-Based Neural Network Controller Design For Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani
Online Reinforcement Learning-Based Neural Network Controller Design For Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel reinforcement learning neural network (NN)-based controller, referred to adaptive critic controller, is proposed for general multi-input and multi- output affine unknown nonlinear discrete-time systems in the presence of bounded disturbances. Adaptive critic designs consist of two entities, an action network that produces optimal solution and a critic that evaluates the performance of the action network. The critic is termed adaptive as it adapts itself to output the optimal cost-to-go function and the action network is adapted simultaneously based on the information from the critic. In our online learning method, one NN is designated as the …
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Reinforcement Learning Based Output-Feedback Control Of Nonlinear Nonstrict Feedback Discrete-Time Systems With Application To Engines, Peter Shih, Jonathan B. Vance, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Appraisal - Who Needs It?, M. Thulasidas
Appraisal - Who Needs It?, M. Thulasidas
Research Collection School Of Computing and Information Systems
WE GO through this ordeal every year when our boss- es appraise our performance. Our career progression, bonus and salary depend on it. So, we spend sleepless nights agonising over it.
Efficient Near-Duplicate Keyframe Retrieval With Visual Language Models, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Efficient Near-Duplicate Keyframe Retrieval With Visual Language Models, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframe retrieval is a critical task for video similarity measure, video threading and tracking. In this paper, instead of using expensive point-to-point matching on keypoints, we investigate the visual language models built on visual keywords to speed up the near-duplicate keyframe retrieval. The main idea is to estimate a visual language model on visual keywords for each keyframe and compare keyframes by the likelihood of their visual language models. Experiments on a subset of TRECVID-2004 video corpus show that visual language models built on visual keywords demonstrate promising performance for near-duplicate keyframe retrieval, which greatly speed up the retrieval …
An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee
An Examination Of Online Product Comparison Service: Fit Between Product Type And Disposition Style, Fiona Fui-Hoon Nah, W. Hong, L. Chen, H. Lee
Research Collection School Of Computing and Information Systems
Horizontal and vertical disposition styles are two main formats used in product comparison service on e-commerce websites. In this research, we hypothesize that there is a fit between product type (‘think’ vs. ‘feel’ product) and disposition style (horizontal vs. vertical style), where horizontal disposition style is more appropriate for ‘feel’ products and vertical disposition style is a better fit for ‘think’ products. An experiment will be carried out to test the hypotheses.
Entrepreneurial Opportunities And Market Analysis Of The Information Technology And Software Development Sector Of Pakistan, Toshio Fujita, Hassan Tajuddin
Entrepreneurial Opportunities And Market Analysis Of The Information Technology And Software Development Sector Of Pakistan, Toshio Fujita, Hassan Tajuddin
Business Review
This study investigates the Information Technology and the Software Development sector of Pakistan. It discusses the reasons for the lack of trust in Pakistani IT companies and different problems faced by an entrepreneur starting an IT company in Pakistan. The data was analyzed by qualitative content analysis. The findings are discussed with reference to previous research, and implications for entrepreneurial setups are noted.
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Cross-Lingual Query Suggestion Using Query Logs Of Different Languages, Wei Gao, Cheng Niu, Jian-Yun Nie, Ming Zhou, Jian Hu, Kam-Fai Wong, Hsiao-Wuen Hon
Research Collection School Of Computing and Information Systems
Query suggestion aims to suggest relevant queries for a given query, which help users better specify their information needs. Previously, the suggested terms are mostly in the same language of the input query. In this paper, we extend it to cross-lingual query suggestion (CLQS): for a query in one language, we suggest similar or relevant queries in other languages. This is very important to scenarios of cross-language information retrieval (CLIR) and cross-lingual keyword bidding for search engine advertisement. Instead of relying on existing query translation technologies for CLQS, we present an effective means to map the input query of one …
Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
Continuous Monitoring Of Top-K Queries Over Sliding Windows, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
Research Collection School Of Computing and Information Systems
Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in conventional databases, the existing methods are inapplicable to highly dynamic environments involving numerous long-running queries. This paper studies continuous monitoring of top-k queries over a fixed-size window W of the most recent data. The window size can be expressed either in terms of the number of active tuples or time units. We propose a general methodology for top-k monitoring that restricts processing to the sub-domains of the workspace …
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by exploring both visual and textual cues from the visual vocabulary and semantic context respectively. The vocabulary, which provides entries for visual keywords, is formed by the clustering of local keypoints. The semantic context is inferred from the speech transcript surrounding a keyframe. We experiment the usefulness of visual keywords and semantic context, separately and jointly, using cosine similarity and language models. By linearly fusing both modalities, performance improvement is reported compared with the …
Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang
Towards Optimal Bag-Of-Features For Object Categorization And Semantic Video Retrieval, Yu-Gang Jiang, Chong-Wah Ngo, Jun Yang
Research Collection School Of Computing and Information Systems
Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as reliability and scalability of visual classification, nevertheless, remains uncertain due to various implementation choices. In this paper, we evaluate various factors which govern the performance of BoF. The factors include the choices of detector, kernel, vocabulary size and weighting scheme. We offer some practical insights in how to optimize the performance by choosing good keypoint detector and kernel. For the weighting scheme, we propose a novel soft-weighting method to assess the significance of a visual word …
Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis
Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In the k-medoid problem, given a dataset P, we are asked to choose kpoints in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and existing algorithms aim at approximate answers, i.e., they compute medoids that achieve a small, yet not minimal, average distance. Similarly in this paper, we also aim at approximate solutions. We consider, however, the continuous version of the problem, where the points in P move and our task is to maintain the medoid set on-the-fly …
On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee
On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee
Research Collection School Of Computing and Information Systems
A continuous nearest neighbor (CNN) search, which retrieves the nearest neighbors corresponding to every point in a given query line segment, is important for location-based services such as vehicular navigation and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client-server systems but not in the environment of wireless data broadcast, where uplink communication channels from mobile devices to the …
Analyzing Feature Trajectories For Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim
Analyzing Feature Trajectories For Event Detection, Qi He, Kuiyu Chang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
We consider the problem of analyzing word trajectories in both time and frequency domains, with the specific goal of identifying important and less-reported, periodic and aperiodic words. A set of words with identical trends can be grouped together to reconstruct an event in a completely un-supervised manner. The document frequency of each word across time is treated like a time series, where each element is the document frequency - inverse document frequency (DFIDF) score at one time point. In this paper, we 1) first applied spectral analysis to categorize features for different event characteristics: important and less-reported, periodic and aperiodic; …