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Articles 7321 - 7350 of 9003
Full-Text Articles in Computer Sciences
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 …
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, …
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 …
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 …
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.
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 …
Workshop Report From Web2se 2011: 2nd International Workshop On Web 2.0 For Software Engineering, Christoph Treude, Margaret-Anne Storey, Arie Van Deursen, Andrew Begel, Sue Black
Workshop Report From Web2se 2011: 2nd International Workshop On Web 2.0 For Software Engineering, Christoph Treude, Margaret-Anne Storey, Arie Van Deursen, Andrew Begel, Sue Black
Research Collection School Of Computing and Information Systems
Web 2.0 technologies, such as wikis, blogs, tags and feeds, have been adopted and adapted by software engineers. With the annual Web2SE workshop, we provide a venue for research on Web 2.0 for software engineering by highlighting state-of-the-art work, identifying current research areas, discussing implications of Web 2.0 on software engineering, and outlining the risks and challenges for researchers. This report highlights the paper and tool presentations, and the discussions among participants at Web2SE 2011 in Honolulu, as well as future directions of the Web2SE workshop community.
Development Of An Instrument To Measure The Adoption Of Mobile Services, Shang Gao, John Krogstie, Keng Siau
Development Of An Instrument To Measure The Adoption Of Mobile Services, Shang Gao, John Krogstie, Keng Siau
Research Collection School Of Computing and Information Systems
Currently, there is no standard instrument for measuring user adoption of mobile services. Based on the mobile service acceptance model, this paper reports on the development of a survey instrument designed to measure user perception on mobile services acceptance. A survey instrument was developed by using some existing scales from prior instruments and by creating additional items which might appear to fit the construct definitions. In addition, a pilot study was conducted by distributing the survey to 25 users of a mobile service called Mobile Student Information Systems. As a result, a survey instrument containing 22 items were retained. Furthermore, …
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 …
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.
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 …
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 …
Exploiting Intensity Inhomogeneity To Extract Textured Objects From Natural Scenes, Jundi Ding, Jialie Shen, Hwee Hwa Pang, Songcan Chen, Jingyu Yang
Exploiting Intensity Inhomogeneity To Extract Textured Objects From Natural Scenes, Jundi Ding, Jialie Shen, Hwee Hwa Pang, Songcan Chen, Jingyu Yang
Research Collection School Of Computing and Information Systems
Extracting textured objects from natural scenes is a challenging task in computer vision. The main difficulties arise from the intrinsic randomness of natural textures and the high-semblance between the objects and the background. In this paper, we approach the extraction problem with a seeded region-growing framework that purely exploits the statistical properties of intensity inhomogeneity. The pixels in the interior of potential textured regions are first found as texture seeds in an unsupervised manner. The labels of the texture seeds are then propagated through their respective inhomogeneous neighborhoods, to eventually cover the different texture regions in the image. Extensive experiments …
Dynamic Group Key Exchange Revisited, Guomin Yang, Chik How Tan
Dynamic Group Key Exchange Revisited, Guomin Yang, Chik How Tan
Research Collection School Of Computing and Information Systems
In a dynamic group key exchange protocol, besides the basic group setup protocol, there are also a join protocol and a leave protocol, which allow the membership of an existing group to be changed more efficiently than rerunning the group setup protocol. The join and leave protocols should ensure that the session key is updated upon every membership change so that the subsequent sessions are protected from leaving members (backward security) and the previous sessions are protected from joining members (forward security). In this paper, we present a new security model for dynamic group key exchange. Comparing to existing models, …
Ensemble-Based Method For Task 2: Predicting Traffic Jam, Jingrui He, Qing He, Grzegorz Swirszcz, Yiannis Kamarianakis, Rick Lawrence, Wei Shen, Laura Wynter
Ensemble-Based Method For Task 2: Predicting Traffic Jam, Jingrui He, Qing He, Grzegorz Swirszcz, Yiannis Kamarianakis, Rick Lawrence, Wei Shen, Laura Wynter
Research Collection School Of Computing and Information Systems
In this paper, we describe our solution for ICDM 2010 Contest Task 2 (Jams), where the task is to predict future where the next traffic jams will occur in morning rush hour, given data gathered during the initial phase of this peak period. Our solution, which is based on an ensemble approach, finished Second in the final evaluation.
Enhancing Brand Equity Through Flow: Comparison Of 2d Versus 3d Virtual World, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, David Dewester
Enhancing Brand Equity Through Flow: Comparison Of 2d Versus 3d Virtual World, Fiona Fui-Hoon Nah, Brenda Eschenbrenner, David Dewester
Research Collection School Of Computing and Information Systems
This research uses the theory of flow to examine the effect of 2D versus 3D virtual world environments on brand equity and use intention. The results suggest that a 3D virtual world environment has both positive (indirect) and negative (direct) effects on brand equity. The positive, indirect effect of the 3D virtual world environment occurs through feelings of telepresence and enjoyment, both of which contribute positively to brand equity and, in turn, induces a higher behavioral intention. The negative, direct effect can be explained using distraction-conflict theory, where attentional conflict is faced by users of a highly interactive and rich …
Revisiting Address Space Randomization, Zhi Wang, Renquan Cheng, Debin Gao
Revisiting Address Space Randomization, Zhi Wang, Renquan Cheng, Debin Gao
Research Collection School Of Computing and Information Systems
Address space randomization is believed to be a strong defense against memory error exploits. Many code and data objects in a potentially vulnerable program and the system could be randomized, including those on the stack and heap, base address of code, order of functions, PLT, GOT, etc. Randomizing these code and data objects is believed to be effective in obfuscating the addresses in memory to obscure locations of code and data objects. However, attacking techniques have advanced since the introduction of address space randomization. In particular, return-oriented programming has made attacks without injected code much more powerful than what they …
Evaluation Of Protein Backbone Alphabets : Using Predicted Local Structure For Fold Recognition, Kyong Jin Shim
Evaluation Of Protein Backbone Alphabets : Using Predicted Local Structure For Fold Recognition, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
Optimally combining available information is one of the key challenges in knowledge-driven prediction techniques. In this study, we evaluate six Phi and Psi-based backbone alphabets. We show that the addition of predicted backbone conformations to SVM classifiers can improve fold recognition. Our experimental results show that the inclusion of predicted backbone conformations in our feature representation leads to higher overall accuracy compared to when using amino acid residues alone.
Toward Effective Concept Representation In Decision Support To Improve Patient Safety, Tze-Yun Leong
Toward Effective Concept Representation In Decision Support To Improve Patient Safety, Tze-Yun Leong
Research Collection School Of Computing and Information Systems
Patient safety is an emerging, major health care discipline with significance accentuated in the influential Institute of Medicine (IOM) reports in the United States “To Err is Human” and “Crossing the Quality Chasm”. These reports highlighted the danger and prevalence of medical errors and preventable adverse events, explained the three main sources of system-related, human factors-related and cognitive-related errors, and recommended the use of information and decision support technologies to help alleviate the problem. A number of studies and reports from all over the world with similar findings have since followed, culminating in the 55th World Health Assembly Resolution on …
Map Estimation For Graphical Models By Likelihood Maximization, Akshat Kumar, Shlomo Zilberstein
Map Estimation For Graphical Models By Likelihood Maximization, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Computing a maximum a posteriori (MAP) assignment in graphical models is a crucial inference problem for many practical applications. Several provably convergent approaches have been successfully developed using linear programming (LP) relaxation of the MAP problem. We present an alternative approach, which transforms the MAP problem into that of inference in a finite mixture of simple Bayes nets. We then derive the Expectation Maximization (EM) algorithm for this mixture that also monotonically increases a lower bound on the MAP assignment until convergence. The update equations for the EM algorithm are remarkably simple, both conceptually and computationally, and can be implemented …
Traffic Velocity Prediction Using Gps Data: Ieee Icdm Contest Task 3 Report, Wei Shen, Yiannis Kamarianakis, Laura Wynter, Jingrui He, Qing He, Rick Lawrence, Grzegorz Swirszcz
Traffic Velocity Prediction Using Gps Data: Ieee Icdm Contest Task 3 Report, Wei Shen, Yiannis Kamarianakis, Laura Wynter, Jingrui He, Qing He, Rick Lawrence, Grzegorz Swirszcz
Research Collection School Of Computing and Information Systems
This report summarizes the methodologies and techniques we developed and applied for tackling task 3 of the IEEE ICDM Contest on predicting traffic velocity based on GPS data. The major components of our solution include 1) A pre-processing procedure to map GPS data to the network, 2) A K-nearest neighbor approach for identifying the most similar training hours for every test hour, and 3) A heuristic evaluation framework for optimizing parameters and avoiding over-fitting. Our solution finished Second in the final evaluation.
Opportunistic Routing In Wireless Sensor Networks Powered By Ambient Energy Harvesting, Zhi Ang Eu, Hwee-Pink Tan, Winston K. G. Seah
Opportunistic Routing In Wireless Sensor Networks Powered By Ambient Energy Harvesting, Zhi Ang Eu, Hwee-Pink Tan, Winston K. G. Seah
Research Collection School Of Computing and Information Systems
Energy consumption is an important issue in the design of wireless sensor networks (WSNs) which typically rely on portable energy sources like batteries for power. Recent advances in ambient energy harvesting technologies have made it possible for sensor nodes to be powered by ambient energy entirely without the use of batteries. However, since the energy harvesting process is stochastic, exact sleep-and-wakeup schedules cannot be determined in WSNs Powered solely using Ambient Energy Harvesters (WSN–HEAP). Therefore, many existing WSN routing protocols cannot be used in WSN–HEAP. In this paper, we design an opportunistic routing protocol (EHOR) for multi-hop WSN–HEAP. Unlike traditional …
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects, Rui Zhang, H.V. Jagadish, Bing Tian Dai, Kotagiri Ramamohanarao
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects, Rui Zhang, H.V. Jagadish, Bing Tian Dai, Kotagiri Ramamohanarao
Research Collection School Of Computing and Information Systems
There have been many studies on management of moving objects recently. Most of them try to optimize the performance of predictive window queries. However, not much attention is paid to two other important query types: the predictive range query and the predictive k nearest neighbor query. In this article, we focus on these two types of queries. The novelty of our work mainly lies in the introduction of the Transformed Minkowski Sum, which can be used to determine whether a moving bounding rectangle intersects a moving circular query region. This enables us to use the traditional tree traversal algorithms to …
3-D Virtual World Education: An Empirical Comparison With Face-To-Face Classroom, Xiaofeng Chen, Keng Siau, Fiona Fui-Hoon Nah
3-D Virtual World Education: An Empirical Comparison With Face-To-Face Classroom, Xiaofeng Chen, Keng Siau, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
3-D virtual worlds are increasing in popularity as a means of pedagogical delivery in higher education. In this research, we assess the relative effectiveness of a 3-D virtual world learning environment, Second Life, and traditional face-to-face learning environment. We also assess the efficacy of instructional strategies in these two learning environments and their effects on interactivity, perceived learning, and satisfaction. Our findings suggest that there is an interaction effect of learning environment and instructional strategy. Pair-wise comparisons indicate that when interactive instructional strategy is used, there is no significant difference for perceived learning and satisfaction between 3-D virtual world and …
Sequence Alignment Based Analysis Of Player Behavior In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Jaideep Srivastava
Sequence Alignment Based Analysis Of Player Behavior In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
This study proposes a sequence alignment-based behavior analysis framework (SABAF) developed for predicting inactive game players that either leave the game permanently or stop playing the game for a long period of time. Sequence similarity scores and derived statistics form profile databases of inactive players and active players from the past. SABAF uses global and local sequence alignment algorithms and a unique scoring scheme to measure similarity between activity sequences. SABAF is tested on the game player activity data of Ever Quest II, a popular massively multiplayer online role-playing game developed by Sony Online Entertainment. SABAF consists of the following …
A Structure First Image Inpainting Approach Based On Self-Organizing Map (Som), Bo Chen, Zhaoxia Wang, Ming Bai, Quan Wang, Zhen Sun
A Structure First Image Inpainting Approach Based On Self-Organizing Map (Som), Bo Chen, Zhaoxia Wang, Ming Bai, Quan Wang, Zhen Sun
Research Collection School Of Computing and Information Systems
This paper presents a structure first image inpainting method based on self-organizing map (SOM). SOM is employed to find the useful structure information of the damaged image. The useful structure information which includes relevant edges of the image is used to simulate the structure information of the lost or damaged area in the image. The structure information is described by distinct or indistinct curves in an image in this paper. The obtained target curves separate the damaged area of the image into several parts. As soon as each part of the damaged image is restored respectively, the damaged image is …
Automobile Exhaust Gas Detection Based On Fuzzy Temperature Compensation System, Zhiyong Wang, Hao Ding, Fufei Hao, Zhaoxia Wang, Zhen Sun, Shujin Li
Automobile Exhaust Gas Detection Based On Fuzzy Temperature Compensation System, Zhiyong Wang, Hao Ding, Fufei Hao, Zhaoxia Wang, Zhen Sun, Shujin Li
Research Collection School Of Computing and Information Systems
A temperature compensation scheme of detecting automobile exhaust gas based on fuzzy logic inference is presented in this paper. The principles of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer are discussed. A fuzzy inference system is designed to improve the measurement accuracy of the measurement equipment by reducing the measurement errors caused by environmental temperature. The case studies demonstrate the effectiveness of the proposed method. The fuzzy compensation scheme is promising as demonstrated by the simulation results in this paper.
Time Cost Evaluation For Executing Rfid Authentication Protocols, Kevin Chiew, Yingjiu Li, Tieyan Li, Robert H. Deng, Manfred Aigner
Time Cost Evaluation For Executing Rfid Authentication Protocols, Kevin Chiew, Yingjiu Li, Tieyan Li, Robert H. Deng, Manfred Aigner
Research Collection School Of Computing and Information Systems
There are various reader/tag authentication protocols proposed for the security of RFID systems. Such a protocol normally contains several rounds of conversations between a tag and a reader and involves cryptographic operations at both reader and tag sides. Currently there is a lack of benchmarks that provide a fair comparison platform for (a) the time cost of cryptographic operations at the tag side and (b) the time cost of data exchange between a reader and a tag, making it impossible to evaluate the total time cost for executing a protocol. Based on our experiments implemented on IAIK UHF tag emulators …
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Search engines are used to return a long list of hundreds or even thousands of videos in response to a query topic. Efficient navigation of videos becomes difficult and users often need to painstakingly explore the search list for a gist of the search result. This paper addresses the challenge of topical summarization by providing a timeline-based visualization of videos through matching of heterogeneous sources. To overcome the so called sparse-text problem of web videos, auxiliary information from Google context is exploited. Google Trends is used to predict the milestone events of a topic. Meanwhile, the typical scenes of web …