Physical Sciences and Mathematics Commons^™

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

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. …

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 …

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.

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 …

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 …

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 …

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, …

Moving-Object Detection, Association, And Selection In Home Videos, Zailiang Pan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Due to the prevalence of digital video camcorders, home videos have become an important part of life-logs of personal experiences. To enable efficient video parsing, a critical step is to automatically extract objects, events and scene characteristics present in videos. This paper addresses the problem of extracting objects from home videos. Automatic detection of objects is a classical yet difficult vision problem, particularly for videos with complex scenes and unrestricted domains. Compared with edited and surveillant videos, home videos captured in uncontrolled environment are usually coupled with several notable features such as shaking artifacts, irregular motions, and arbitrary settings. These …

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 …

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

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 …

Lecture Video Enhancement And Editing By Integrating Posture, Gesture, And Text, Feng Wang, Chong-Wah Ngo, Ting-Chuen Pong

Research Collection School Of Computing and Information Systems

This paper describes a novel framework for automatic lecture video editing by gesture, posture, and video text recognition. In content analysis, the trajectory of hand movement is tracked and the intentional gestures are automatically extracted for recognition. In addition, head pose is estimated through overcoming the difficulties due to the complex lighting conditions in classrooms. The aim of recognition is to characterize the flow of lecturing with a series of regional focuses depicted by human postures and gestures. The regions of interest (ROIs) in videos are semantically structured with text recognition and the aid of external documents. By tracing the …

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 …

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 …

Value-At-Risk In It Services Contracts, Robert J. Kauffman, Ryan Sougstad

Research Collection School Of Computing and Information Systems

As information systems (IS) and technology solutions become increasingly service-driven, managers are faced with the task of choosing parameters such as service-levels, pricing, and contract duration. Information technology (IT) services vendors manage portfolios of contracts in which parameters, decided at inception, are often subject to future risks. The contract profit maximization decision may adversely affect the risk position of the firm's portfolio of services contracts. We propose a model to inform vendors on setting optimal parameters for IS contracts subject to acceptable levels of risk. The analytic model presented draws from IS economics research and the principles of value-at-risk (VaR) …

Direct Code Access In Self-Organizing Neural Networks For Reinforcement Learning, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD-FALCON still relies on an iterative process to evaluate each available action in a decision cycle. To remove this deficiency, this paper presents a direct code access procedure whereby TD-FALCON conducts instantaneous searches for cognitive nodes that match with the current states and at the same time provide maximal reward values. Our comparative experiments show that TD-FALCON with direct code access produces comparable performance with the original TD-FALCON while improving significantly in computation efficiency and network complexity.

The Philosophy Of Special Relativity: A Comparison Between Indian And Western Interpretations, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

The Western philosophical phenomenalism could be treated as a kind of philosophical basis of the special theory of relativity. The perceptual limitations of our senses hold the key to the understanding of relativistic postulates. The specialness of the speed of light in our phenomenal space and time is more a matter of our perceptual apparatus, than an input postulate to the special theory of relativity. The author believes that the parallels among the phenomenological, Western spiritual and the Eastern Advaita interpretations of special relativity point to an exciting possibility of unifying the Eastern and Western schools of thought to some …

A Growth Theory Perspective On The International Diffusion Of Electronic Commerce., S.C Ho, Robert John Kauffman, T.P. Liang

Research Collection School Of Computing and Information Systems

Information and communication technologies (ICTs) continue to have a profound effect on the economies and societies where they are used. In this article, we propose three related theories to describe the underlying mechanism for growth in e-commerce revenues at the national level. Endogenous growth theory posits that the primary drivers of e-commerce growth are internal to a country. Exogenous growth theory suggests that the primary drivers of e-commerce growth are external to an economic system, and reflect the forces of the regional economy. A blend of these, a mixed endogenous–exogenous growth theory, incorporates drivers from both the economy and …

Editors' Introduction: Ecra Vol. 6, No. 4, Patrick Y. K. Chau, Robert J. Kauffman, Norman M. Sadeh, J. Christopher Westland

Research Collection School Of Computing and Information Systems

This issue features a total of 13 articles. The first four articles are part of a special section on “Intelligent agents in e-services”, edited by Professors William K. Cheung and Jane Y. Hsu under the supervision of Professor Robert J. Kauffman. Summaries of articles appearing in the special section are provided in the guest editors’ introduction. The following is a summary of the nine regular submission articles also published in this issue. The review of these articles was kindly coordinated by Professor Jae Kyu Lee, former Editor in Chief of ECRA.

The general submission articles in this issue focus on …

Solving The Teacher Assignment-Course Scheduling 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 for solving atimetabling problem, which is commonly encountered in manyuniversities. The problem combines both teacher assignment andcourse scheduling problems simultaneously, and is presented as amathematical programming model. However, this problem becomesintractable and it is unlikely that a proven optimal solution can beobtained by an integer programming approach, especially for largeproblem instances. A hybrid algorithm that combines an integerprogramming approach, a greedy heuristic and a modified simulatedannealing algorithm collaboratively is proposed to solve the problem.Several randomly generated data sets of sizes comparable to that ofan institution in Indonesia are solved using the proposed algorithm.Computational results …

Mining Multiple Visual Appearances Of Semantics For Image Annotation, Hung-Khoon Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single concept point of a category are limited in their effectiveness for image annotation. We propose to use data mining techniques to mine multiple concepts, where each concept may consist of one or more visual parts, to capture the diverse visual appearances of a single keyword category. For training, we use the Apriori principle to efficiently mine a set of frequent blobsets to capture the semantics of a rich and diverse visual category. Each concept is …

Towards Efficient Computation Of Quality Bounded Solutions In Pomdps: Expected Value Approximation And Dynamic Disjunctive Beliefs, Pradeep Reddy Varakantham, Rajiv Maheswaran, Tapana Gupta, Milind Tambe

Research Collection School Of Computing and Information Systems

While POMDPs (partially observable markov decision problems) are a popular computational model with wide-ranging applications, the computational cost for optimal policy generation is prohibitive. Researchers are investigating ever-more efficient algorithms, yet many applications demand such algorithms bound any loss in policy quality when chasing efficiency. To address this challenge, we present two new techniques. The first approximates in the value space to obtain solutions efficiently for a pre-specified error bound. Unlike existing techniques, our technique guarantees the resulting policy will meet this bound. Furthermore, it does not require costly computations to determine the quality loss of the policy. Our second …

Real-Time Supply Chain Control Via Multi-Agent Adjustable Autonomy, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo

Research Collection School Of Computing and Information Systems

Real-time supply chain management in a rapidly changing environment requires reactive and dynamic collaboration among participating entities. In this work, we model supply chain as a multi-agent system where agents are subject to an adjustable autonomy. The autonomy of an agent refers to its capability to make and influence decisions within a multi-agent system. Adjustable autonomy means changing the autonomy of the agents during runtime as a response to changes in the environment. In the context of a supply chain, different entities will have different autonomy levels and objective functions as the environment changes, and the goal is to design …

Iterated Weaker-Than-Weak Dominance, Shih-Fen Cheng, Michael P. Wellman

Research Collection School Of Computing and Information Systems

We introduce a weakening of standard gametheoretic δ-dominance conditions, called dominance, which enables more aggressive pruning of candidate strategies at the cost of solution accuracy. Equilibria of a game obtained by eliminating a δ-dominated strategy are guaranteed to be approximate equilibria of the original game, with degree of approximation bounded by the dominance parameter. We can apply elimination of δ-dominated strategies iteratively, but the for which a strategy may be eliminated depends on prior eliminations. We discuss implications of this order independence, and propose greedy heuristics for determining a sequence of eliminations to reduce the game as far as possible …

Businessfinder: Harnessing Presence To Enable Live Yellow Pages For Small, Medium And Micro Mobile Businesses, D. Chakraborty, K. Dasgupta, S. Mittal, Archan Misra, C. Oberle, A. Gupta, E. Newmark

Research Collection School Of Computing and Information Systems

Applications leveraging network presence in next-generation cellular networks have so far focused on subscription queries, where "presence" information is extracted from specific devices and sent to entities who have subscribed to such presence information. In this article we present BusinessFinder, a service that leverages the underlying cellular presence substrate to provide efficient, on-demand, context-aware matching of customer requests to nomadic micro businesses as well as small and medium businesses having a mobile workforce. Presence, in the context of BusinessFinder, is not simply limited to phone location and device status, but also encompasses dynamic attributes of vendors (both "mobile" and "static"), …

Anticipatory Event Detection Via Classification, He Qi, Kuiyu Chang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The idea of event detection is to identify interesting patterns from a constant stream of incoming news documents. Previous research in event detection has largely focused on identifying the first event or tracking subsequent events belonging to a set of pre-assigned topics such as earthquakes, airline disasters, etc. In this paper, we describe a new problem, called anticipatory event detection (AED), which aims to detect if a user-specified event has transpired. AED can be viewed as a personalized combination of event tracking and new event detection. We propose using sentence-level and document-level classification approaches to solve the AED problem for …

Image Segmentation Using Multi-Coloured Active Illumination, Tze Ki (Xu Shuqi) Koh, Nicholas Miles, Barrie Hayes-Gill

Research Collection School Of Computing and Information Systems

In this paper, the use of active illumination is extended to image segmentation, specifically in the case of overlapping particles. This work is based on Multi-Flash Imaging (MFI), originally developed by Mitsubishi Electric Labs, to detect depth discontinuities. Illuminations of different wavelengths are projected from multiple positions, providing additional information about a scene compared to conventional segmentation techniques. Shadows are used to identify true object edges. The identification of non- occluded particles is made possible by exploiting the fact that shadows are cast on underlying particles. Implementation issues such as selecting the appropriate colour model and number of illuminations are …

Integrating Semantic Templates With Decision Tree For Image Semantic Learning, Ying Liu, Dengsheng Zhang, Guojun Lu, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Decision tree (DT) has great potential in image semantic learning due to its simplicity in implementation and its robustness to incomplete and noisy data. Decision tree learning naturally requires the input attributes to be nominal (discrete). However, proper discretization of continuous-valued image features is a difficult task. In this paper, we present a decision tree based image semantic learning method, which avoids the difficult image feature discretization problem by making use of semantic template (ST) defined for each concept in our database. A ST is the representative feature of a concept, generated from the low-level features of a collection of …

An Improvement Heuristic For The Timetabling Problem, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh

Research Collection School Of Computing and Information Systems

This paper formulates a timetabling problem, which is often encountered in a university, as a mathematical programming model. The proposed model combines both teacher assignment and course scheduling problems simultaneously, which causes the entire model to become more complex. We propose an improvement heuristic algorithm to solve such a model. The proposed algorithm has been tested with several randomly generated datasets of sizes that are comparable to those occurring in a university in Indonesia. The computational results show that the improvement heuristic is not only able to obtain good solutions, but is also able to do so within reasonable computational …