Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Sciences (226)
- Databases and Information Systems (94)
- Software Engineering (49)
- Information Security (38)
- Engineering (32)
-
- Business (31)
- Social and Behavioral Sciences (30)
- Numerical Analysis and Scientific Computing (29)
- Artificial Intelligence and Robotics (24)
- Communication (20)
- Operations Research, Systems Engineering and Industrial Engineering (18)
- Theory and Algorithms (15)
- Computer Engineering (13)
- Graphics and Human Computer Interfaces (13)
- Social Media (13)
- Management Information Systems (8)
- Programming Languages and Compilers (8)
- Data Storage Systems (7)
- Technology and Innovation (7)
- Communication Technology and New Media (5)
- E-Commerce (5)
- Environmental Sciences (4)
- Computer and Systems Architecture (3)
- Public Affairs, Public Policy and Public Administration (3)
- Applied Mathematics (2)
- Asian Studies (2)
- Bioinformatics (2)
- Digital Communications and Networking (2)
- Econometrics (2)
- Keyword
-
- RFID (4)
- Social images (4)
- Social media (4)
- Uncertainty (4)
- Design (3)
-
- Distance metric learning (3)
- Linear Temporal Logic (3)
- Machine learning (3)
- Model Check (3)
- Operational Semantic (3)
- Sand animation (3)
- Tabletop computing (3)
- Algorithm (2)
- Algorithms (2)
- Animation (2)
- Authenticated Key Exchange (2)
- Auto face annotation (2)
- Certificateless cryptography (2)
- Chameleon All-But-One Trapdoor Functions (2)
- Classification (2)
- Conformal parameterization (2)
- Content-based image retrieval (2)
- Creativity (2)
- Debugging (2)
- End-user programming (2)
- Experimentation (2)
- Fault detection (2)
- Identity-based cryptography (2)
- Information retrieval (2)
- Innovation (2)
- Publication
- Publication Type
Articles 211 - 232 of 232
Full-Text Articles in Physical Sciences and Mathematics
Towards Rio 2012 And Collaborative Governance For Sustainable Development, Jem Bendell
Towards Rio 2012 And Collaborative Governance For Sustainable Development, Jem Bendell
Social Space
Since the global Earth Summit in 1992, non-governmental organisations and businesses have made some strides towards sustainable development, but as Jem Bendell explains, governments need to join them.
Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Concept-Driven Multi-Modality Fusion For Video Search, Xiao-Yong Wei, Yu-Gang Jiang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
As it is true for human perception that we gather information from different sources in natural and multi-modality forms, learning from multi-modalities has become an effective scheme for various information retrieval problems. In this paper, we propose a novel multi-modality fusion approach for video search, where the search modalities are derived from a diverse set of knowledge sources, such as text transcript from speech recognition, low-level visual features from video frames, and high-level semantic visual concepts from supervised learning. Since the effectiveness of each search modality greatly depends on specific user queries, prompt determination of the importance of a modality …
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Research Collection School Of Economics
We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …
Innovation And Price Competition In A Two-Sided Market, Mei Lin, Shaojin Li, Andrew B. Whinston
Innovation And Price Competition In A Two-Sided Market, Mei Lin, Shaojin Li, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
We examine a platform's optimal two-sided pricing strategy while considering seller-side innovation decisions and price competition. We model the innovation race among sellers in both finite and infinite horizons. In the finite case, we analytically show that the platform's optimal seller-side access fee fully extracts the sellers' surplus, and that the optimal buyer-side access fee mitigates price competition among sellers. The platform's optimal strategy may be to charge or subsidize buyers depending on the degree of variation in the buyers' willingness to pay for quality; this optimal strategy induces full participation on both sides. Furthermore, a wider quality gap among …
Near-Duplicate Keyframe Retrieval By Semi-Supervised Learning And Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Near-Duplicate Keyframe Retrieval By Semi-Supervised Learning And Nonrigid Image Matching, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Near-duplicate keyframe (NDK) retrieval techniques are critical to many real-world multimedia applications. Over the last few years, we have witnessed a surge of attention on studying near-duplicate image/keyframe retrieval in multimedia community. To facilitate an effective approach to NDK retrieval on large-scale data, we suggest an effective Multi-Level Ranking (MLR) scheme that effectively retrieves NDKs in a coarse-to-fine manner. One key stage of the MLR ranking scheme is how to learn an effective ranking function with extremely small training examples in a near-duplicate detection task. To attack this challenge, we employ a semi-supervised learning method, semi-supervised support vector machines, which …
Lightweight Delegated Subset Test With Privacy Protection, Xuhua Zhou, Xuhua Ding, Kefei Chen
Lightweight Delegated Subset Test With Privacy Protection, Xuhua Zhou, Xuhua Ding, Kefei Chen
Research Collection School Of Computing and Information Systems
Delegated subset tests are mandatory in many applications, such as content-based networks and outsourced text retrieval, where an untrusted server evaluates the degree of matching between two data sets. We design a novel scheme to protect the privacy of the data sets in comparison against the untrusted server, with half of the computation cost and half of the ciphertext size of existing solutions based on predicate only encryption supporting inner product.
Randomly Projected Kd-Trees With Distance Metric Learning For Image Retrieval, Pengcheng Wu, Steven Hoi, Duc Dung Nguyen, Ying He
Randomly Projected Kd-Trees With Distance Metric Learning For Image Retrieval, Pengcheng Wu, Steven Hoi, Duc Dung Nguyen, Ying He
Research Collection School Of Computing and Information Systems
Efficient nearest neighbor (NN) search techniques for highdimensional data are crucial to content-based image retrieval (CBIR). Traditional data structures (e.g., kd-tree) usually are only efficient for low dimensional data, but often perform no better than a simple exhaustive linear search when the number of dimensions is large enough. Recently, approximate NN search techniques have been proposed for high-dimensional search, such as Locality-Sensitive Hashing (LSH), which adopts some random projection approach. Motivated by similar idea, in this paper, we propose a new high dimensional NN search method, called Randomly Projected kd-Trees (RP-kd-Trees), which is to project data points into a lower-dimensional …
Identity-Based Strong Designated Verifier Signature Revisited, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Identity-Based Strong Designated Verifier Signature Revisited, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Designated verifier signature (DVS) allows the signer to persuade a verifier the validity of a statement but prevent the verifier from transferring the conviction. Strong designated verifier signature (SDVS) is a variant of DVS, which only allows the verifier to privately check the validity of the signer’s signature. In this work we observe that the unforgeability model considered in the existing identity-based SDVS schemes is not strong enough to capture practical attacks, and propose to consider another model which is shown to be strictly stronger than the old one. We then propose a new efficient construction of identity-based SDVS scheme, …
Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo
Research Collection School Of Computing and Information Systems
This paper is concerned with automated tuning of parameters in local-search based meta-heuristics. Several generic approaches have been introduced in the literature that returns a ”one-size-fits-all” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instance-based automated tuning, but they are usually problem-specific. In this paper, we propose CluPaTra, a generic (problem-independent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as …
A Usability Study Of A Mobile Content Sharing System, Alton Yeow-Kuan Chua, Dion Hoe-Lian Goh, Khasfariyati Razikin, Ee Peng Lim
A Usability Study Of A Mobile Content Sharing System, Alton Yeow-Kuan Chua, Dion Hoe-Lian Goh, Khasfariyati Razikin, Ee Peng Lim
Research Collection School Of Computing and Information Systems
We investigate the usability of MobiTOP (Mobile Tagging of Objects and People), a mobile location-based content sharing system. MobiTOP allows users to annotate real world locations with both multimedia and textual content and concurrently, share the annotations among its users. In addition, MobiTOP provides additional functionality such as clustering of annotations and advanced search and filtering options. A usability evaluation of the system was conducted in the context of a travel companion for tourists. The results suggested the potential of the system in terms of functionality for mobile content sharing. Participants agreed that the features in MobiTOP were generally usable …
Enhancing Bag-Of-Words Models By Efficient Semantics-Preserving Metric Learning, Lei Wu, Steven C. H. Hoi
Enhancing Bag-Of-Words Models By Efficient Semantics-Preserving Metric Learning, Lei Wu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The authors present an online semantics preserving, metric learning technique for improving the bag-of-words model and addressing the semantic-gap issue. This article investigates the challenge of reducing the semantic gap for building BoW models for image representation; propose a novel OSPML algorithm for enhancing BoW by minimizing the semantic loss, which is efficient and scalable for enhancing BoW models for large-scale applications; apply the proposed technique for large-scale image annotation and object recognition; and compare it to the state of the art.
Efficient Strong Designated Verifier Signature Schemes Without Random Oracle Or With Non-Delegatability, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Efficient Strong Designated Verifier Signature Schemes Without Random Oracle Or With Non-Delegatability, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Research Collection School Of Computing and Information Systems
Designated verifier signature (DVS) allows a signer to convince a designated verifier that a signature is generated by the signer without letting the verifier transfer the conviction to others, while the public can still tell that the signature must be generated by one of them. Strong DVS (SDVS) strengthens the latter part by restricting the public from telling whether the signature is generated by one of them or by someone else. In this paper, we propose two new SDVS schemes. Compared with existing SDVS schemes, the first new scheme has almost the same signature size and meanwhile, is proven secure …
An Effective Approach To Pose Invariant 3d Face Recognition, Dayong Wang, Steven C. H. Hoi, Ying He
An Effective Approach To Pose Invariant 3d Face Recognition, Dayong Wang, Steven C. H. Hoi, Ying He
Research Collection School Of Computing and Information Systems
One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry based alignment approach, which transforms a 3D face mesh model to a well-aligned 2D image. Secondly, we propose to represent the facial images by a Locality Preserving Sparse Coding (LPSC) algorithm, which is more effective than the regular sparse coding algorithm for face representation. We conducted a set of extensive experiments on both 2D and 3D …
Editorial: Special Issue On Ubiquitous Electronic Commerce Systems, Robert H. Deng, Jari Veijalainen, Shiguo Lian, Dimitris Kanellopoulos
Editorial: Special Issue On Ubiquitous Electronic Commerce Systems, Robert H. Deng, Jari Veijalainen, Shiguo Lian, Dimitris Kanellopoulos
Research Collection School Of Computing and Information Systems
Ubiquitous computing is a post-desktop model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. Emerging ubiquitous electronic commerce systems (UECS) are expected to be available anytime, anywhere, and using different official or personal computing devices. Systems and services such as digital libraries, on-line business transactions, mobile office and mobile TV are widely deployed. Users will be able to access these services anytime, anywhere, while using any computing device in a pervasive way.
Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu
Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu
Research Collection School Of Computing and Information Systems
This paper is concerned with the problem of Just-In-Time (JIT) job scheduling in a dynamic environment under uncertainty to attain timely service. We provide an approach, based on robust scheduling concepts, to analytically evaluate the expected cost of earliness and tardiness for each job and also the project. In addition, we search for a schedule execution policy with the minimum robust cost such that for a given risk level (epsilon), the actual realized schedule has (1 - epsilon) probability of completing with less than or equal to this robust cost. Our method is quite generic, and can be applied to …
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati
Research Collection School Of Computing and Information Systems
Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …
Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh
Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh
Research Collection School Of Computing and Information Systems
On May 6, 2010, the U.S. equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (see Figure 1) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. The authors contend that the events of May 6, 2010 exhibit patterns consistent with the type of "flash crash" observed in their earlier study (2010). This paper describes the results of nine different simulations created by using a large-scale computer model to reconstruct the critical elements …
Trends And Controversies: Ai, Virtual Worlds, And Massively Multiplayer Online Games, Hsinchun Chen, Yulei Zhang, W. S. Bainbridge, Kyong Jin Shim, N. Pathak, M. A. Ahmad, C. Delong, Z. Borbora, A. Mahapatra, J. Srivastava
Trends And Controversies: Ai, Virtual Worlds, And Massively Multiplayer Online Games, Hsinchun Chen, Yulei Zhang, W. S. Bainbridge, Kyong Jin Shim, N. Pathak, M. A. Ahmad, C. Delong, Z. Borbora, A. Mahapatra, J. Srivastava
Research Collection School Of Computing and Information Systems
The rich social media data generated in virtual worlds has important implications for business, education, social science, and society at large. Similarly, massively multiplayer online games (MMOGs) have become increasingly popular and have online communities comprising tens of millions of players. They serve as unprecedented tools for theorizing about and empirically modeling the social and behavioral dynamics of individuals, groups, and networks within large communities. Some technologists consider virtual worlds and MMOGs to be likely candidates to become the Web 3.0. AI can play a significant role, from multiagent avatar research and immersive virtual interface design to virtual world and …
Solving The Teacher Assignment Problem By Two Metaheuristics, Aldy Gunawan, Kien Ming Ng
Solving The Teacher Assignment Problem By Two Metaheuristics, Aldy Gunawan, Kien Ming Ng
Research Collection School Of Computing and Information Systems
The timetabling problem arising from a university in Indonesia is addressed in this paper.It involves the assignment of teachers to the courses and course sections. We formulate theproblem as a mathematical programming model. Two different algorithms, mainly basedon simulated annealing (SA) and tabu search (TS) algorithms, are proposed for solving theproblem. The proposed algorithms consist of two phases. The first phase involves allocatingthe teachers to the courses and determining the number of courses to be assigned to eachteacher. The second phase involves assigning the teachers to the course sections in order tobalance the teachers’ load. The performance of the proposed …
Solving The Quadratic Assignment Problem By A Hybrid Algorithm, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
Solving The Quadratic Assignment Problem By A Hybrid Algorithm, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
Research Collection School Of Computing and Information Systems
This paper presents a hybrid algorithm to solve the Quadratic Assignment Problem (QAP). The proposed algorithminvolves using the Greedy Randomized Adaptive Search Procedure (GRASP) to obtain an initial solution, and then using a combinedSimulated Annealing (SA) and Tabu Search (TS) algorithm to improve the solution. Experimental results indicate that the hybridalgorithm is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time.
Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo
Mining Event Structures From Web Videos, Xiao Wu, Yi-Jie Lu, Qiang Peng, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The article is discussing the issues of mining event structures from Web video search results using text analysis, burst detection, and clustering as with the proliferation of social media, the volume of Web videos have grown exponentially.
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.