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Articles 9421 - 9450 of 10474
Full-Text Articles in Entire DC Network
Higher Order Bias Correcting Moment Equation For M-Estimation And Its Higher Order Efficiency, Kyoo-Il Kim
Higher Order Bias Correcting Moment Equation For M-Estimation And Its Higher Order Efficiency, Kyoo-Il Kim
Research Collection School Of Economics
This paper studies an alternative bias correction for the M-estimator, which is obtained by correcting the moment equation in the spirit of Firth (1993). In particular, this paper compares the stochastic expansions of the analytically bias-corrected estimator and the alternative estimator and finds that the third-order stochastic expansions of these two estimators are identical. This implies that at least in terms of the third order stochastic expansion, we cannot improve on the simple one-step bias correction by using the bias correction of moment equations. Though the result in this paper is for a fixed number of parameters, our intuition may …
Semiparametric Estimation Of Signaling Games, Kyoo-Il Kim
Semiparametric Estimation Of Signaling Games, Kyoo-Il Kim
Research Collection School Of Economics
This paper studies an econometric modeling of a signaling game with two players where one player has one of two types. In particular, we develop an estimation strategy that identifies the payoffs structure and the distribution of types from data of observed actions. We can achieve uniqueness of equilibrium using a refinement, which enables us to identify the parameters of interest. In the game, we consider non-strategic public signals about the types. Because the mixing distribution of these signals is nonparametrically specified, we propose to estimate the model using a sieve conditional MLE. We achieve the consistency and the asymptotic …
Human-Computer Interaction Research In The Management Information Systems Discipline, Fiona Fui-Hoon Nah, Ping Zhang, Scott Mccoy, Munyong Yi
Human-Computer Interaction Research In The Management Information Systems Discipline, Fiona Fui-Hoon Nah, Ping Zhang, Scott Mccoy, Munyong Yi
Research Collection School Of Computing and Information Systems
No abstract provided.
Mining Rdf Metadata For Generalized Association Rules, Tao Jiang, Ah-Hwee Tan
Mining Rdf Metadata For Generalized Association Rules, Tao Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of generalization closure for systematic over-generalization reduction. Empirical experiments conducted on real world RDF data sets show that our method can substantially reduce pattern redundancy and perform much better than the original generalized association rule mining algorithm Cumulate in term of time efficiency.
Wireless Indoor Positioning System With Enhanced Nearest Neighbors In Signal Space Algorithm, Quang Tran, Juki Wirawan Tantra, Ah-Hwee Tan, Ah-Hwee Tan, Kin-Choong Yow, Dongyu Qiu
Wireless Indoor Positioning System With Enhanced Nearest Neighbors In Signal Space Algorithm, Quang Tran, Juki Wirawan Tantra, Ah-Hwee Tan, Ah-Hwee Tan, Kin-Choong Yow, Dongyu Qiu
Research Collection School Of Computing and Information Systems
With the rapid development and wide deployment of wireless Local Area Networks (WLANs), WLAN-based positioning system employing signal-strength-based technique has become an attractive solution for location estimation in indoor environment. In recent years, a number of such systems has been presented, and most of the systems use the common Nearest Neighbor in Signal Space (NNSS) algorithm. In this paper, we propose an enhancement to the NNSS algorithm. We analyze the enhancement to show its effectiveness. The performance of the enhanced NNSS algorithm is evaluated with different values of the parameters. Based on the performance evaluation and analysis, we recommend some …
Continuous Nearest Neighbor Monitoring In Road Networks, Kyriakos Mouratidis, Man Lung Yiu, Dimitris Papadias, Nikos Mamoulis
Continuous Nearest Neighbor Monitoring In Road Networks, Kyriakos Mouratidis, Man Lung Yiu, Dimitris Papadias, Nikos Mamoulis
Research Collection School Of Computing and Information Systems
Recent research has focused on continuous monitoring of nearest neighbors (NN) in highly dynamic scenarios, where the queries and the data objects move frequently and arbitrarily. All existing methods, however, assume the Euclidean distance metric. In this paper we study k-NN monitoring in road networks, where the distance between a query and a data object is determined by the length of the shortest path connecting them. We propose two methods that can handle arbitrary object and query moving patterns, as well as °uctuations of edge weights. The ¯rst one maintains the query results by processing only updates that may invalidate …
Three Architectures For Trusted Data Dissemination In Edge Computing, Shen-Tat Goh, Hwee Hwa Pang, Robert H. Deng, Feng Bao
Three Architectures For Trusted Data Dissemination In Edge Computing, Shen-Tat Goh, Hwee Hwa Pang, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Edge computing pushes application logic and the underlying data to the edge of the network, with the aim of improving availability and scalability. As the edge servers are not necessarily secure, there must be provisions for users to validate the results—that values in the result tuples are not tampered with, that no qualifying data are left out, that no spurious tuples are introduced, and that a query result is not actually the output from a different query. This paper aims to address the challenges of ensuring data integrity in edge computing. We study three schemes that enable users to check …
Collaborative Image Retrieval Via Regularized Metric Learning, Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
Collaborative Image Retrieval Via Regularized Metric Learning, Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
In content-based image retrieval (CBIR), relevant images are identified based on their similarities to query images. Most CBIR algorithms are hindered by the semantic gap between the low-level image features used for computing image similarity and the high-level semantic concepts conveyed in images. One way to reduce the semantic gap is to utilize the log data of users' feedback that has been collected by CBIR systems in history, which is also called “collaborative image retrieval.” In this paper, we present a novel metric learning approach, named “regularized metric learning,” for collaborative image retrieval, which learns a distance metric by exploring …
Social Network Dynamics For Open Source Software Projects, Y. Long, Keng Siau
Social Network Dynamics For Open Source Software Projects, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
Drawing on social network theories and previous studies, this research is an initial effort to explore the dynamics of the social network structure in Open Source Software (OSS) teams. Three projects were selected from SourceForge.net in term of their similarities as well as their differences. Monthly data were extracted from the bug tracking system in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of network structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a …
Using Mobile Technology In Education: Perspectives Of Students And Instructors, H. Sheng, F. Nah, Keng Siau
Using Mobile Technology In Education: Perspectives Of Students And Instructors, H. Sheng, F. Nah, Keng Siau
Research Collection School Of Computing and Information Systems
Mobile technology has the tremendous potential in supporting and improving education and its delivery. As a new phenomenon that is gaining popularity, the values of mobile technology in education need to be better researched and understood. In this research, we used the Value-Focused Thinking approach to interview students and instructors to identify the values of education that are enabled by mobile technology. These values are represented in the form of a means-ends objective network that not only captures the values of education facilitated by mobile technology but also depicts the relationships between these values. The values of education enabled by …
An Experimental Study On U-Commerce Adoption: The Impact Of Personalization And Privacy Concerns, H. Sheng, Fiona Fui-Hoon Nah, Keng Siau
An Experimental Study On U-Commerce Adoption: The Impact Of Personalization And Privacy Concerns, H. Sheng, Fiona Fui-Hoon Nah, Keng Siau
Research Collection School Of Computing and Information Systems
U-commerce represents “anytime, anywhere” commerce, which is believed to be the ultimate form of commerce. Ucommerce can provide a high level of personalization, which can bring additional benefits and values to customers. However, despite these promises and potential benefits, customers’ privacy is a major concern and obstacle to the adoption of ucommerce. As customers’ intention to adopt u-commerce is based on the aggregate effect of perceived benefits and risk exposure (e.g., privacy concerns), this research examines how personalization and context can impact on customers’ perceived benefits and privacy concerns, and how this aggregated effect in turn affects u-commerce adoption intention. …
Knowledges Of The Creative Economy: Towards A Relational Geography Of Diffusion And Adaptation In Asia, Lily Kong, Chris Gibson, Louisa-May Khoo, Anne-Louise Semple
Knowledges Of The Creative Economy: Towards A Relational Geography Of Diffusion And Adaptation In Asia, Lily Kong, Chris Gibson, Louisa-May Khoo, Anne-Louise Semple
Research Collection School of Social Sciences
Recent dialogues in geography and the social sciences have reminded researchers of the extent to which academic and policy knowledges are socially and spatially embedded-that is, they circulate through formal and informal systems of publishing, exchange, commodification and cultural influence. Academic and policy knowledges are, in short, very much a part of the creative economy. In light of this, our paper surveys knowledges of the creative economy itself, as reflected in a geography of industry reports and government policy statements in selected Asian countries. Using a post-positivist framework adapted from diffusion theory, we critically interpret the circulation, mutation and adaptation …
Use Of A Classroom Response System To Enhance Classroom Interactivity, Keng Siau, H. Sheng, Fiona Fui-Hoon Nah
Use Of A Classroom Response System To Enhance Classroom Interactivity, Keng Siau, H. Sheng, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Classroom interactivity is a critical component of teaching and learning. This paper reports on the use of a classroom response system to enhance classroom interactivity in a systems analysis and design course. The success of the project was assessed using both quantitative and qualitative data. A pretest/posttest design was used to examine the effects of a classroom respons system on interactivity. The results show that a classroom response system can significantly improve classroom interactivity. Qualitative data was also collected to identify the strengths and weaknesses of using a classroom response system to enhance classroom interaction. Based on the quantitative and …
An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun
An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun
Research Collection School Of Computing and Information Systems
Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by …
Understanding Intrinsic Factors Influencing Benefit Maximization Of Is Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Intrinsic Factors Influencing Benefit Maximization Of Is Usage, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
This research uses the Repertory Grid technique to understand intrinsic factors influencing benefit maximization of IS usage. The results show that domain-relevant skills, task motivation, cognitive/work style attributes, individual characteristics (identified as creativity traits) and personal characteristics (identified as innovativeness traits) influence benefit maximization of IS usage. The findings not only provide insights on ways to increase quality of IS usage in organizations but are also helpful for identifying approaches that foster attributes leading to increased benefit realization from IS usage.
A Hybrid Architecture Combining Reactive Plan Execution And Reactive Learning, Samin Karim, Liz Sonenberg, Ah-Hwee Tan
A Hybrid Architecture Combining Reactive Plan Execution And Reactive Learning, Samin Karim, Liz Sonenberg, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Developing software agents has been complicated by the problem of how knowledge should be represented and used. Many researchers have identified that agents need not require the use of complex representations, but in many cases suffice to use “the world” as their representation. However, the problem of introspection, both by the agents themselves and by (human) domain experts, requires a knowledge representation with a higher level of abstraction that is more ‘understandable’. Learning and adaptation in agents has traditionally required knowledge to be represented at an arbitrary, low-level of abstraction. We seek to create an agent that has the capability …
Bias And Controversy: Beyond The Statistical Deviation, Hady W. Lauw, Ee Peng Lim, Ke Wang
Bias And Controversy: Beyond The Statistical Deviation, Hady W. Lauw, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a 'data-centric approach' where the evaluation data is assumed to represent the ground truth'. The standard statistical approaches take evaluation and deviation at face value. We argue that attention should be paid to the subjectivity of evaluation, judging the evaluation score not just on 'what is being said' (deviation), but also on 'who says it' (reviewer) as well as on 'whom it is said about' (object). Furthermore, we observe that bias …
Learning The Unified Kernel Machines For Classification, Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
Learning The Unified Kernel Machines For Classification, Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
Research Collection School Of Computing and Information Systems
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel Machines (UKM) from both labeled and unlabeled data. Our proposed framework integrates supervised learning, semi-supervised kernel learning, and active learning in a unified solution. In the suggested framework, we particularly focus our attention on designing a new semi-supervised kernel learning method, i.e., Spectral Kernel Learning (SKL), which is built on the principles of kernel target alignment and unsupervised kernel design. Our algorithm is related to an equivalent quadratic programming problem that can be efficiently …
Architectural Control And Value Migration In Platform Industries, C. Jason Woodard
Architectural Control And Value Migration In Platform Industries, C. Jason Woodard
Research Collection School Of Computing and Information Systems
carry some pre-computation information of each region. We also propose multiple client-side algorithms to facilitate the processing of
Keyframe Retrieval By Keypoints: Can Point-To-Point Matching Help?, Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
Keyframe Retrieval By Keypoints: Can Point-To-Point Matching Help?, Wanlei Zhao, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Bag-of-words representation with visual keypoints has recently emerged as an attractive approach for video search. In this paper, we study the degree of improvement when point-to-point (P2P) constraint is imposed on the bag-of-words. We conduct investigation on two tasks: near-duplicate keyframe (NDK) retrieval, and high-level concept classification, covering parts of TRECVID 2003 and 2005 datasets. In P2P matching, we propose a one-to-one symmetric keypoint matching strategy to diminish the noise effect during keyframe comparison. In addition, a new multi-dimensional index structure is proposed to speed up the matching process with keypoint filtering. Through experiments, we demonstrate that P2P constraint can …
Ontosearch: A Full-Text Search Engine For The Semantic Web, Xing Jiang, Ah-Hwee Tan
Ontosearch: A Full-Text Search Engine For The Semantic Web, Xing Jiang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
OntoSearch, a full-text search engine that exploits ontological knowledge for document retrieval, is presented in this paper. Different from other ontology based search engines, OntoSearch does not require a user to specify the associated concepts of his/her queries. Domain ontology in OntoSearch is in the form of a semantic network. Given a keyword based query, OntoSearch infers the related concepts through a spreading activation process in the domain ontology. To provide personalized information access, we further develop algorithms to learn and exploit user ontology model based on a customized view of the domain ontology. The proposed system has been applied …
Hierarchical Hidden Markov Model For Rushes Structuring And Indexing, Chong-Wah Ngo, Zailiang Pan, Xiaoyong Wei
Hierarchical Hidden Markov Model For Rushes Structuring And Indexing, Chong-Wah Ngo, Zailiang Pan, Xiaoyong Wei
Research Collection School Of Computing and Information Systems
Rushes footage are considered as cheap gold mine with the potential for reuse in broadcasting and filmmaking industries. However, it is difficult to mine the "gold" from the rushes since usually only minimum metadata is available. This paper focuses on the structuring and indexing of the rushes to facilitate mining and retrieval of "gold". We present a new approach for rushes structuring and indexing based on motion feature. We model the problem by a two-level Hierarchical Hidden Markov Model (HHMM). The HHMM, on one hand, represents the semantic concepts in its higher level to provide simultaneous structuring and indexing, on …
Prediction-Based Gesture Detection In Lecture Videos By Combining Visual, Speech And Electronic Slides, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Prediction-Based Gesture Detection In Lecture Videos By Combining Visual, Speech And Electronic Slides, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong
Research Collection School Of Computing and Information Systems
This paper presents an efficient algorithm for gesture detection in lecture videos by combining visual, speech and electronic slides. Besides accuracy, response time is also considered to cope with the efficiency requirements of real-time applications. Candidate gestures are first detected by visual cue. Then we modifity HMM models for complete gestures to predict and recognize incomplete gestures before the whole gestures paths are observed. Gesture recognition is used to verify the results of gesture detection. The relations between visual, speech and slides are analyzed. The correspondence between speech and gesture is employed to improve the accuracy and the responsiveness of …
Generalized On-Demand Service Architecture For Interactive Applications [Us 2006/0168107 A1], Rajesh K. Balan, Paul C. Castro, Maria R. Ebling, Archan Misra
Generalized On-Demand Service Architecture For Interactive Applications [Us 2006/0168107 A1], Rajesh K. Balan, Paul C. Castro, Maria R. Ebling, Archan Misra
Research Collection School Of Computing and Information Systems
A method, system, and computer program for executing a network-based distributed application. An infrastructure is described that includes application containers configured to execute an application instance of the distributed application and measure quality of service metrics for the application instance. Workload management elements form a decentralized workload management layer. The workload management layer is configured to assign a workload to application containers based on the quality of service metrics received by the application containers.
Autonomic Management Of Stream Processing Applications Via Adaptive Bandwidth Control, Dimitrios Pendarakis, Jeremy Silber, Laura Wynter
Autonomic Management Of Stream Processing Applications Via Adaptive Bandwidth Control, Dimitrios Pendarakis, Jeremy Silber, Laura Wynter
Research Collection School Of Computing and Information Systems
We present a novel autonomic control system for high performance stream processing systems. The system uses bandwidth controls on incoming or outgoing streams to achieve a desired resource utilization balance among a set of concurrently executing stream processing tasks. We show that CPU prioritization and allocation mechanisms in schedulers and virtual machine managers are not sufficient to control such I/O-centric applications, and present an autonomic bandwidth control system that adaptively adjusts incoming and outgoing traffic rates to achieve system management goals. The system dynamically learns the bandwidth rate necessary to meet the system management goals using stochastic nonlinear optimization, and …
Temporal Dynamics Of The Urban Heat Island Of Singapore, Winston T. L. Chow, Matthias Roth
Temporal Dynamics Of The Urban Heat Island Of Singapore, Winston T. L. Chow, Matthias Roth
Research Collection School of Social Sciences
The temporal variability of the canopy‐level urban heat island (UHI) of Singapore is examined for different temporal scales on the basis of observations during a 1‐year period. Temperature data obtained from different urban areas (commercial, Central Business District (CBD), high‐rise and low‐rise housing) are compared with ‘rural’ reference data and analysed with respect to meteorological variables and differences in land use. The results indicate that the peak UHI magnitude occurs 3–4 h (>6 h) after sunset in the commercial area, (at other urban sites). Higher UHI intensities generally occur during the southwest monsoon period of May–August, with a maximum …
Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai
Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai
Research Collection School Of Computing and Information Systems
In information retrieval, retrieving relevant passages, as opposed to whole documents, not only directly benefits the end user by filtering out the irrelevant information within a long relevant document, but also improves retrieval accuracy in general. A critical problem in passage retrieval is to extract coherent relevant passages accurately from a document, which we refer to as passage extraction. While much work has been done on passage retrieval, the passage extraction problem has not been seriously studied. Most existing work tends to rely on presegmenting documents into fixed-length passages which are unlikely optimal because the length of a relevant passage …
Crossing The Chasm: The Xid Technologies Story, Arcot Desai Narasimhalu, Roberto Mariani
Crossing The Chasm: The Xid Technologies Story, Arcot Desai Narasimhalu, Roberto Mariani
Research Collection School Of Computing and Information Systems
XID Technologies is a face processing start up company built initially around a disruptive face recognition technology. The technology innovation came from Kent Ridge Digital Labs, a publicly funded software research laboratory in Singapore. Face recognition is the least intrusive and harmless among the various biometric solutions available in the market. The basic approach to human face recognition is to identify a robust feature set that was unique enough to differentiate amongst the many millions of human faces that the system was required to verify. The technology innovation used by XID framed the problem differently and thereby overcame the challenges …
Private Information Retrieval Using Trusted Hardware, Shuhong Wang, Xuhua Ding, Robert H. Deng, Feng Bao
Private Information Retrieval Using Trusted Hardware, Shuhong Wang, Xuhua Ding, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Many theoretical PIR (Private Information Retrieval) constructions have been proposed in the past years. Though information theoretically secure, most of them are impractical to deploy due to the prohibitively high communication and computation complexity. The recent trend in outsourcing databases fuels the research on practical PIR schemes. In this paper, we propose a new PIR system by making use of trusted hardware. Our system is proven to be information theoretically secure. Furthermore, we derive the computation complexity lower bound for hardware-based PIR schemes and show that our construction meets the lower bounds for both the communication and computation costs, respectively.
A Modified Family Of Power Transformations, Zhenlin Yang
A Modified Family Of Power Transformations, Zhenlin Yang
Research Collection School Of Economics
A modified family of power transformation, called the dual power transformation, is proposed. The new transformation is shown to possess properties similar to those of the well-known Box-Cox power transformation, but overcomes the long-standing truncation problem of the latter. It generates a rich family of distributions that is seen to be very useful in modeling and analysis of durations and event-times.