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Articles 9301 - 9330 of 10474
Full-Text Articles in Entire DC Network
Deckard: Scalable And Accurate Tree-Based Detection Of Code Clones, Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Stephane Glondu
Deckard: Scalable And Accurate Tree-Based Detection Of Code Clones, Lingxiao Jiang, Ghassan Misherghi, Zhendong Su, Stephane Glondu
Research Collection School Of Computing and Information Systems
Detecting code clones has many software engineering applications. Existing approaches either do not scale to large code bases or are not robust against minor code modifications. In this paper, we present an efficient algorithm for identifying similar subtrees and apply it to tree representations of source code. Our algorithm is based on a novel characterization of subtrees with numerical vectors in the Euclidean Rn and an efficient algorithm to cluster these vectors w.r.t. the Euclidean distance metric. Subtrees with vectors in one cluster are considered similar. We have implemented our tree similarity algorithm as a clone detection tool called DECKARD …
Achieving End-To-End Authentication In Intermediary-Enabled Multimedia Delivery Systems, Robert H. Deng, Yanjiang Yang
Achieving End-To-End Authentication In Intermediary-Enabled Multimedia Delivery Systems, Robert H. Deng, Yanjiang Yang
Research Collection School Of Computing and Information Systems
Considerable research and experiment results in recent years have shown that the server-proxy-user architecture represents an efficient and scalable new paradigm for multimedia content delivery. However, not much effort has been spent on the security issues in such systems. In this paper, we study data authentication in multimedia content delivery, and in particular, we focus on achieving end-to-end authentication from the multimedia server to end users in the server-proxy-user architecture where intermediary proxies transcode multimedia content dynamically. We present a formal model for the end-to-end authentication problem, and propose a basic construction for generic data modality and prove its security. …
Machine Scheduling Performance With Maintenance And Failure, Yunsong Guo, Andrew Lim, Brian Rodrigues, Shuang Yu
Machine Scheduling Performance With Maintenance And Failure, Yunsong Guo, Andrew Lim, Brian Rodrigues, Shuang Yu
Research Collection Lee Kong Chian School Of Business
In manufacturing control, machine scheduling research has mostly dealt with problems either without maintenance or with deterministic maintenance when no failure can occur. This can be unrealistic in practical settings. In this work, an experimental model is developed to evaluate the effect of corrective and preventive maintenance schemes on scheduling performance in the presence of machine failure where the scheduling objective is to minimize schedule duration. We show that neither scheme is clearly superior, but that the applicability of each depends on several system parameters as well as the scheduling environment itself. Further, we show that parameter values can be …
As Citigroup Increases Its High-Skilled Headcount In India, Will Others Follow?, Knowledge@Smu
As Citigroup Increases Its High-Skilled Headcount In India, Will Others Follow?, Knowledge@Smu
Knowledge@SMU
On April 11, Citigroup CEO Charles Prince announced a massive restructuring program that involves cutting 17,000 jobs and moving more than 9,500 to locations in low-cost countries. Citigroup watchers expect some 8,000 jobs to head for India, including the outsourcing of select high-end back-office functions. If that phenomenon gathers momentum beyond the financial services industry, the U.S. could lose far more jobs than previously predicted across the skills and wage spectrum. India Knowledge@Wharton spoke with Wharton professors to understand this emerging trend in global job movements. --------------------------------------------------------------------------------
Compact Vertically-Coupled Microring Laser Array Dual-Wavelength Source For Terahertz Mode Beating, Chyng Wen Tee, K. A. Williams, R. V. Penty, I. H. White
Compact Vertically-Coupled Microring Laser Array Dual-Wavelength Source For Terahertz Mode Beating, Chyng Wen Tee, K. A. Williams, R. V. Penty, I. H. White
Research Collection Lee Kong Chian School Of Business
Continuous-wave operation of a fully tunable compact microring twin-laser array is demonstrated for the first time. The two active microrings, with radii of 70μm and 74μm, are vertically- coupled to a single passive waveguide. Tuning of the current facilitates a wavelength separation from 4.9nm to 6.3nm.
Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng
Mining Colossal Frequent Patterns By Core Pattern Fusion, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hong Cheng
Research Collection School Of Computing and Information Systems
Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the existing frequent-pattern mining algorithms encounter challenges at mining rather large patterns, called colossal frequent patterns, in the presence of an explosive number of frequent patterns. Colossal patterns are critical to many applications, especially in domains like bioinformatics. In this study, we investigate a novel mining approach called Pattern-Fusion to efficiently find a good approximation to the colossal patterns. With Pattern-Fusion, a colossal pattern is discovered by fusing its small core patterns in one step, …
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …
Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau
Social Network Structures In Open Source Software Development Teams, Y. Long, Keng Siau
Research Collection School Of Computing and Information Systems
Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a corel periphery model as the projects …
Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang
Summarizing Review Scores Of "Unequal" Reviewers, Hady W. Lauw, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
A frequently encountered problem in decision making is the following review problem: review a large number of objects and select a small number of the best ones. An example is selecting conference papers from a large number of submissions. This problem involves two sub-problems: assigning reviewers to each object, and summarizing reviewers ’ scores into an overall score that supposedly reflects the quality of an object. In this paper, we address the score summarization sub-problem for the scenario where a small number of reviewers evaluate each object. Simply averaging the scores may not work as even a single reviewer could …
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
A Multimodal And Multilevel Ranking Framework For Content-Based Video Retrieval, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
One critical task in content-based video retrieval is to rank search results with combinations of multimodal resources effectively. This paper proposes a novel multimodal and multilevel ranking framework for content-based video retrieval. The main idea of our approach is to represent videos by graphs and learn harmonic ranking functions through fusing multimodal resources over these graphs smoothly. We further tackle the efficiency issue by a multilevel learning scheme, which makes the semi-supervised ranking method practical for large-scale applications. Our empirical evaluations on TRECVID 2005 dataset show that the proposed multimodal and multilevel ranking framework is effective and promising for content-based …
Vulnerability Analysis Of Emap: An Efficient Rfid Mutual Authentication Protocol, Tieyan Li, Robert H. Deng
Vulnerability Analysis Of Emap: An Efficient Rfid Mutual Authentication Protocol, Tieyan Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In this paper, we analyze the security vulnerabilities of EMAP, an efficient RFID mutual authentication protocol recently proposed by Peris-Lopez et al. (2006). We present two effective attacks, a de-synchronization attack and a full-disclosure attack, against the protocol. The former permanently disables the authentication capability of a RFID tag by destroying synchronization between the tag and the RFID reader. The latter completely compromises a tag by extracting all the secret information stored in the tag. The de-synchronization attack can be carried out in just round of interaction in EMAP while the full-disclosure attack is accomplished across several runs of EMAP. …
Optimal Liquidation Strategies And Their Implications, Christopher Ting, Mitch Warachka, Yonggan Zhao
Optimal Liquidation Strategies And Their Implications, Christopher Ting, Mitch Warachka, Yonggan Zhao
Research Collection Lee Kong Chian School Of Business
This paper studies optimal liquidation when the selling price depends on the rate of liquidation, transaction time, volume, and the asset's intrinsic value. A generic closed-form solution for maximizing the discounted liquidation proceeds is derived. To obtain financial insights, three parametric specifications that proxy for increasingly realistic market conditions are examined. In our framework, maximizing liquidation proceeds and minimizing liquidity costs are equivalent. The optimal strategies imply more rapid liquidations in less liquid markets. We also show that volatility is stochastic when market liquidity is unpredictable.
Experiences With Tracking The Effects Of Changing Requirements On Morphbank: A Web-Based Bioinformatics Application, Subhajit Datta, Robert Van Engelen, David Gaitros, Neelima Jammigumpula
Experiences With Tracking The Effects Of Changing Requirements On Morphbank: A Web-Based Bioinformatics Application, Subhajit Datta, Robert Van Engelen, David Gaitros, Neelima Jammigumpula
Research Collection School Of Computing and Information Systems
In this paper, we present a case study of applying the metrics Mutation Index, Component Set, Dependency Index on Morphbank- a web based bioinformatics application - to track the effects of changing requirements on a software system and suggest design modifications to mitigate such impact. Morphbank is "an open web repository of biological images documenting specimen-based research in comparative anatomy, morphological phylogenetics, taxonomy and related fields focused on increasing our knowledge about biodiversity". This paper discusses the context of the case study, analyzes the results, highlights observations and learning, and mentions directions of future work.
Estimating Party Policy Positions: Comparing Expert Surveys And Hand-Coded Content Analysis, Kenneth Benoit, Michael Laver
Estimating Party Policy Positions: Comparing Expert Surveys And Hand-Coded Content Analysis, Kenneth Benoit, Michael Laver
Research Collection School of Social Sciences
In this paper we compare estimates of the left-right positions of political parties derived from an expert survey recently completed by the authors with those derived by the Comparative Manifestos Project (CMP) from the content analysis of party manifestos. Having briefly described the expert survey, we first explore the substantive policy content of left and right in the expert survey estimates. We then compare the expert survey to the CMP method on methodological grounds. Third, we directly compare the expert survey results to the CMP results for the most recent time period available, revealing some agreement but also numerous inconsistencies …
Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March
Valuing Information Technology Infrastructures: A Growth Options Approach, Qizhi Dai, Robert J. Kauffman, Salvatore T. March
Research Collection School Of Computing and Information Systems
Decisions to invest in information technology (IT) infrastructure are often made based on an assessment of its immediate value to the organization. However, an important source of value comes from the fact that such technologies have the potential to be leveraged in the development of future applications. From a real options perspective, IT infrastructure investments create growth options that can be exercised if and when an organization decides to develop systems to provide new or enhanced IT capabilities. We present an analytical model based on real options that shows the process by which this potential is converted into business value, …
Tube (Text-Cube) For Discovering Documentary Evidence Of Associations Among Entities, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang
Tube (Text-Cube) For Discovering Documentary Evidence Of Associations Among Entities, Hady Lauw, Ee Peng Lim, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
User-driven discovery of associations among entities, and documents that provide evidence for these associations, is an important search task conducted by researchers and do-main information specialists. Entities here refer to real or abstract objects such as people, organizations, ideologies, etc. Associations are the inter-relationships among entities. Most current works in query-driven document retrieval and finding representative subgraphs are ill-suited for the task as they lack an awareness of entity types as well as an intuitive representation of associations. We propose the TUBE model, a text cube approach for discovering associations and documentary evidence of these associations. The model consists of …
A Cautionary Note On The Effects Of Range Restriction On Predictor Intercorrelations, Paul R. Sackett, Filip Lievens, Christopher M. Berry, Richard N. Landers
A Cautionary Note On The Effects Of Range Restriction On Predictor Intercorrelations, Paul R. Sackett, Filip Lievens, Christopher M. Berry, Richard N. Landers
Research Collection Lee Kong Chian School Of Business
The purpose of this research report is to highlight a unique set of issues that arise when considering the effects of range restriction in the context of estimating predictor intercorrelations. Three approaches are used to illustrate the issue: simulation, a concrete applied example, and a reanalysis of a meta-analysis of ability-interview correlations. The general conclusion is that a predictor intercorrelation can differ dramatically from the population value when both predictors are used in a composite that is used operationally for selection. The compensatory nature of a composite means that low scorers on one predictor can only obtain high scores on …
Privacy-Preserving Credentials Upon Trusted Computing Augmented Servers, Yanjiang Yang, Robert H. Deng, Feng Bao
Privacy-Preserving Credentials Upon Trusted Computing Augmented Servers, Yanjiang Yang, Robert H. Deng, Feng Bao
Research Collection School Of Computing and Information Systems
Credentials are an indispensable means for service access control in electronic commerce. However, regular credentials such as X.509 certificates and SPKI/SDSI certificates do not address user privacy at all, while anonymous credentials that protect user privacy are complex and have compatibility problems with existing PKIs. In this paper we propose privacy-preserving credentials, a concept between regular credentials and anonymous credentials. The privacy-preserving credentials enjoy the advantageous features of both regular credentials and anonymous credentials, and strike a balance between user anonymity and system complexity. We achieve this by employing computer servers equipped with TPMs (Trusted Platform Modules). We present a …
Malicious Kgc Attacks In Certificateless Cryptography, Man Ho Au, Jing Chen, Joseph K. Liu, Yi Mu, Duncan S. Wong, Guomin Yang, Guomin Yang
Malicious Kgc Attacks In Certificateless Cryptography, Man Ho Au, Jing Chen, Joseph K. Liu, Yi Mu, Duncan S. Wong, Guomin Yang, Guomin Yang
Research Collection School Of Computing and Information Systems
Identity-based cryptosystems have an inherent key escrow issue, that is, the Key Generation Center (KGC) always knows user secret key. If the KGC is malicious, it can always impersonate the user. Certificateless cryptography, introduced by Al-Riyami and Paterson in 2003, is intended to solve this problem. However, in all the previously proposed certificateless schemes, it is always assumed that the malicious KGC starts launching attacks (so-called Type II attacks) only after it has generated a master public/secret key pair honestly. In this paper, we propose new security models that remove this assumption for both certificateless signature and encryption schemes. Under …
Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau
Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposed into two subproblems—sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an executable schedule from the semi-schedule via idle-time insertion. Sequencing is strongly NP-hard in general. Although timetabling is polynomial-time solvable, it can become a computational bottleneck if the procedure is executed many times within a larger framework. This paper makes two contributions. We …
Percentage-Based Hybrid Pattern Training With Neural Network Specific Cross Over, Sheng-Uei Guan, Kiruthika Ramanathan
Percentage-Based Hybrid Pattern Training With Neural Network Specific Cross Over, Sheng-Uei Guan, Kiruthika Ramanathan
Research Collection School Of Computing and Information Systems
In this paper, a new weight-setting method is proposed to improve the training time and generalization accuracy of feed-forward neural networks. This method introduces a percentage-based hybrid pattern training (PHP) scheme and aims to provide a solution to the problem dependency of other Genetic Algorithm (GA)-based Neural Network weight-setting methods. A neural network is trained using a neural network specific GA until a certain percentage of the training patterns is learned. The weights thus obtained are used as the initial weights for backpropagation (BP) training, which is then applied to complete the network training. Further improvement to the method was …
Realized Daily Variance Of S&P500 Cash Index: A Revaluation Of Stylized Facts, Shirley J. Huang, Qianqiu Liu, Jun Yu
Realized Daily Variance Of S&P500 Cash Index: A Revaluation Of Stylized Facts, Shirley J. Huang, Qianqiu Liu, Jun Yu
Research Collection Lee Kong Chian School Of Business
In this paper, the realized daily variance is obtained from intraday transaction prices of the S&P 500 cash index over the period from January 1993 to December 2004. When constructing realized daily variance, market microstructure noise is taken into account using a technique proposed by Zhang, Mykland, and Ait-Sahalia (2005). The time series properties of realized daily variance are compared with those of variance estimates obtained from parametric GARCH and stochastic volatility models. Unconditional and dynamic properties concerning the realized daily variance are examined, the relationship between realized variance and returns is investigated, and the stylized facts concerning realized daily …
Segmentation Of Overlapping Particles In Automatic Size Analysis Using Multi-Flash Imaging, Tze K Koh, Nicholas Miles, Steve Morgan, Barrie Hayes-Gill
Segmentation Of Overlapping Particles In Automatic Size Analysis Using Multi-Flash Imaging, Tze K Koh, Nicholas Miles, Steve Morgan, Barrie Hayes-Gill
Research Collection College of Integrative Studies
In this paper, we propose a novel hardware approach to image segmentation, specifically in the case of overlapping particles. Our research is based on multi-flash imaging (MFI), originally developed to detect depth discontinuities. Multiple images captured with different illumination conditions provide additional information about a scene compared to conventional segmentation techniques. Shadows are used to identify true object edges and underlying particles. We applied the new approach in automated particle size analysis and evaluated it against the watershed and canny edge detection techniques. Evaluation results confirm that MFI can be applied in image segmentation and reveals the superiority of the …
Logistics Network Design With Supplier Consolidation Hubs And Multiple Shipment Options, Michelle L. F. Cheong, Rohit Bhatnagar, Stephen C. Graves
Logistics Network Design With Supplier Consolidation Hubs And Multiple Shipment Options, Michelle L. F. Cheong, Rohit Bhatnagar, Stephen C. Graves
Research Collection School Of Computing and Information Systems
An important service provided by third-party logistics (3PL) firms is to manage the inbound logistics of raw materials and components from multiple suppliers to several manufacturing plants. A key challenge for these 3PL firms is to determine how to coordinate and consolidate the transportation flow, so as to get the best overall logistics performance. One tactic is to establish consolidation hubs that collect shipments from several suppliers, consolidate these shipments, and direct the consolidated shipments to the appropriate manufacturing plant. We consider the network design problem to implement this tactic, namely deciding the number, location and operation of consolidation hubs …
Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham
Towards Efficient Planning For Real World Partially Observable Domains, Pradeep R. Varakantham
Research Collection School Of Computing and Information Systems
My research goal is to build large-scale intelligent systems (both single- and multi-agent) that reason with uncertainty in complex, real-world environments. I foresee an integration of such systems in many critical facets of human life ranging from intelligent assistants in hospitals to offices, from rescue agents in large scale disaster response to sensor agents tracking weather phenomena in earth observing sensor webs, and others. In my thesis, I have taken steps towards achieving this goal in the context of systems that operate in partially observable domains that also have transitional (non-deterministic outcomes to actions) uncertainty. Given this uncertainty, Partially Observable …
Clustering And Combinatorial Optimization In Recursive Supervised Learning, Kiruthika Ramanathan, Sheng Uei Guan
Clustering And Combinatorial Optimization In Recursive Supervised Learning, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
The use of combinations of weak learners to learn a dataset has been shown to be better than the use of a single strong learner. In fact, the idea is so successful that boosting, an algorithm combining several weak learners for supervised learning, has been considered to be the best off the shelf classifier. However, some problems still exist, including determining the optimal number of weak learners and the over fitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of global search, weak learning and pattern distribution. In …
Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang
Mining Generalized Associations Of Semantic Relations From Textual Web Content, Tao Jiang, Ah-Hwee Tan, We Wang
Research Collection School Of Computing and Information Systems
Traditional text mining techniques transform free text into flat bags of words representation, which does not preserve sufficient semantics for the purpose of knowledge discovery. In this paper, we present a two-step procedure to mine generalized associations of semantic relations conveyed by the textual content of Web documents. First, RDF (resource description framework) metadata representing semantic relations are extracted from raw text using a myriad of natural language processing techniques. The relation extraction process also creates a term taxonomy in the form of a sense hierarchy inferred from WordNet. Then, a novel generalized association pattern mining algorithm (GP-Close) is applied …
On Stiffness In Affine Asset Pricing Models, Shirley Junying Huang, Jun Yu
On Stiffness In Affine Asset Pricing Models, Shirley Junying Huang, Jun Yu
Research Collection Lee Kong Chian School Of Business
Economic and econometric analysis of continuous-time affine asset pricing models often necessitates solving systems of ordinary differential equations (ODEs) numerically. Explicit RungeûKutta (ERK) methods have been suggested to solve these ODEs both in the theoretical finance literature and in the financial econometrics literature. In this paper we show that under many empirically relevant circumstances the ODEs involve stiffness, a phenomenon which leads to some practical difficulties for numerical methods with a finite region of absolute stability, including the whole class of ERK methods. The difficulties are highlighted in the present paper in the context of pricing zero-coupon bonds as well …
A Novel Intra-Cavity Lens Design For Compact High Efficiency Tapered Laser Diodes, F. K. Lau, Chyng Wen Tee, R. V. Penty, I. H. White, N. Michel, M. Krakowski
A Novel Intra-Cavity Lens Design For Compact High Efficiency Tapered Laser Diodes, F. K. Lau, Chyng Wen Tee, R. V. Penty, I. H. White, N. Michel, M. Krakowski
Research Collection Lee Kong Chian School Of Business
An integrated parabolic lens capable of introducing a diverging effect to the optical mode propagating within the cavity of a tapered laser is proposed and demonstrated. This idea allows broader high-power beams to be generated by shorter cavities. Diverging lenses with etch depths of 0.13 and 0.27 mum are implemented, with 12 (9.5%) and 16.8 mum (13.3%) overall broadening of the near-fields widths measured at 1/e2 intensity. The peak output power as well as the threshold current is found to increase following the lens etching process, confirming the beneficial broadening effect introduced by the diverging lens.
Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen
Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen
Research Collection School Of Computing and Information Systems
A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates …