Engineering Commons^™

Web-Scale Near-Duplicate Search: Techniques And Applications, Chong-Wah Ngo, Changsheng Xu, Wessel Kraaij, Abdulmotaleb El Saddik

Research Collection School Of Computing and Information Systems

This paper presents some of the most recent advances in the research on Web-scale near-duplicate search and explores the potential for bringing this research a substantial step further. It contains high-quality contributions addressing various aspects of the Web-scale near-duplicate search problem in a number of relevant domains. The topics range from feature representation, matching, and indexing from different novel aspects to the adaptation of current technologies for mobile media search and photo archaeology mining.

Inferring Ongoing Human Activities Based On Recurrent Self-Organizing Map Trajectory, Qianru Sun, Hong Liu

Research Collection School Of Computing and Information Systems

Automatically inferring ongoing activities is to enable the early recognition of unfinished activities, which is quite meaningful for applications, such as online human-machine interaction and security monitoring. State-of-the-art methods use the spatiotemporal interest point (STIP) based features as the low-level video description to handle complex scenes. While the existing problem is that typical bag-of-visual words (BoVW) focuses on the statistical distribution of features but ignores the inherent contexts in activity sequences, resulting in low discrimination when directly dealing with limited observations. To solve this problem, the Recurrent Self-Organizing Map (RSOM), which was designed to process sequential data, is novelly adopted …

High Memory Passive Rfid Tags With Multimodal Sensor Design And Application To Asset Monitoring In-Transit, Haifeng Niu, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, new passive Radio Frequency Identification (RFID) tags with multimodal sensors and a high on-tag memory is proposed. First, the features preferred on the new passive RFID tags are motivated followed by a detailed description on the design and fabrication of the tags. Next, the performance of the tags in terms of read range is evaluated. The experiments results show that proposed tags have a range of 5.8 meters when all sensors are disabled while the range reduces when sensors are enabled. However, it is demonstrated that the range can be enhanced to 8 meters by using energy …

A Forward-Secure Certificate-Based Signature Scheme, Jiguo Li, Huiyun Teng, Xinyu Huang, Yichen Zhang, Jianying Zhou

Faculty Publications

Cryptographic computations are often carried out on insecure devices for which the threat of key exposure raises a serious concern. In an effort to address the key exposure problem, the notion of forward security was first presented by Günther in 1990. In a forward-secure scheme, secret keys are updated at regular periods of time; exposure of the secret key corresponding to a given time period does not enable an adversary to ‘break’ the scheme for any prior time period. In this paper, we first introduce forward security into certificate-based cryptography and define the security model of forward-secure certificate-based signatures (CBSs). …

Forensic Analysis Of Whatsapp On Android Smartphones, Neha S. Thakur

LSU New Orleans Theses and Dissertations

Android forensics has evolved over time offering significant opportunities and exciting challenges. On one hand, being an open source platform Android is giving developers the freedom to contribute to the rapid growth of the Android market whereas on the other hand Android users may not be aware of the security and privacy implications of installing these applications on their phones. Users may assume that a password-locked device protects their personal information, but applications may retain private information on devices, in ways that users might not anticipate. In this thesis we will be concentrating on one such application called 'WhatsApp', a …

Scale Reasoning With Fuzzy-El+ Ontologies Based On Mapreduce, Zhangquan Zhou, Guilin Qi, Chang Lui, Pascal Hitzler, Raghava Mutharaju

Computer Science and Engineering Faculty Publications

Fuzzy extension of Description Logics (DLs) allows the formal representation and handling of fuzzy or vague knowledge. In this paper, we consider the problem of reasoning with fuzzy-EL+, which is a fuzzy extension of EL+. We first identify the challenges and present revised completion classification rules for fuzzy-EL+ that can be handled by MapReduce programs. We then propose an algorithm for scale reasoning with fuzzy-EL+ ontologies using MapReduce. Some preliminary experimental results are provided to show the scalability of our algorithm.

Human Action Recognition Via Fused Kinematic Structure And Surface Representation, Salah R. Althloothi

Electronic Theses and Dissertations

Human action recognition from visual data has remained a challenging problem in the field of computer vision and pattern recognition. This dissertation introduces a new methodology for human action recognition using motion features extracted from kinematic structure, and shape features extracted from surface representation of human body. Motion features are used to provide sufficient information about human movement, whereas shape features are used to describe the structure of silhouette. These features are fused at the kernel level using Multikernel Learning (MKL) technique to enhance the overall performance of human action recognition. In fact, there are advantages in using multiple types …

Scitech Book News Reviews, Susan Fingerman

Sci-Tech News

No abstract provided.

Solving The Search For Source Code, Kathryn T. Stolee

School of Computing: Dissertations, Theses, and Student Research

Programmers frequently search for source code to reuse using keyword searches. When effective and efficient, a code search can boost programmer productivity, however, the search effectiveness depends on the programmer's ability to specify a query that captures how the desired code may have been implemented. Further, the results often include many irrelevant matches that must be filtered manually. More semantic search approaches could address these limitations, yet existing approaches either do not scale, are not flexible enough to find approximate matches, or require complex specifications.

We propose a novel approach to semantic search that addresses some of these limitations and …

Scalable Randomized Patrolling For Securing Rapid Transit Networks, Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan

Research Collection School Of Computing and Information Systems

Mass Rapid Transit using rail is a popular mode of transport employed by millions of people in many urban cities across the world. Typically, these networks are massive, used by many and thus, can be a soft target for criminals. In this paper, we consider the problem of scheduling randomised patrols for improving security of such rail networks. Similar to existing work in randomised patrols for protecting critical infrastructure, we also employ Stackelberg Games to represent the problem. In solving the Stackelberg games for massive rail networks, we make two key contributions. Firstly, we provide an approach called RaPtoR for …

A Multi-Objective Memetic Algorithm For Vehicle Resource Allocation In Sustainable Transportation Planning, Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan

Research Collection School Of Computing and Information Systems

Sustainable supply chain management has been an increasingly important topic of research in recent years. At the strategic level, there are computational models which study supply and distribution networks with environmental considerations. At the operational level, there are, for example, routing and scheduling models which are constrained by carbon emissions. Our paper explores work in tactical planning with regards to vehicle resource allocation from distribution centers to customer locations in a multi-echelon logistics network. We formulate the bi-objective optimization problem exactly and design a memetic algorithm to efficiently derive an approximate Pareto front. We illustrate the applicability of our approach …

Segmentation And Model Generation For Large-Scale Cyber Attacks, Steven E. Strapp

Theses

Raw Cyber attack traffic can present more questions than answers to security analysts. Especially with large-scale observables it is difficult to identify which packets are relevant and what attack behaviors are present. Many existing works in Host or Flow Clustering attempt to group similar behaviors to expedite analysis; these works often phrase the problem directly as offline unsupervised machine learning. This work proposes online processing to simultaneously model coordinating actors and segment traffic that is relevant to a target of interest, all while it is being received. The goal is not just to aggregate similar attack behaviors, but to provide …

Riskvis: Supply Chain Visualization With Risk Management And Real-Time Monitoring, Rick S. M. Goh, Zhaoxia Wang, Xiaofeng Yin, Xiuju Fu, Loganathan Ponnanbalam, Sifei Lu, Xiaorong Li

Research Collection School Of Computing and Information Systems

With increased complexity, supply chain networks (SCNs) of modern era face higher risks and lower efficiency due to limited visibility. Hence, there is an immediate need to provide end-to-end supply chain visibility for efficient management of complex supply chains. This paper proposes a visualization scheme based on multi-hierarchical modular design and develops a supply chain visualization platform with risk management and real-time monitoring, named RiskVis, for realizing better Supply Chain Risk Management (SCRM). A Supply Chain Visualizer (SCV) with a graphical visualization platform is mounted as a part of a SCRM management decision-making dashboard and it provides senior management a …

Click-Boosting Random Walk For Image Search Reranking, Xiaopeng Yang, Yongdong Zhang, Ting Yao, Zheng-Jun Zha, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Image reranking is an effective way for improving the retrieval performance of keyword-based image search engines. A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns or relevant training examples from the initial search results. Ideally, these patterns and examples can be leveraged to upgrade the ranks of visually similar images, which are also likely to be relevant. The challenge, nevertheless, originates from the fact that keyword-based queries are used to be ambiguous, resulting in difficulty in predicting the search intention. Mining useful patterns and examples without understanding query is …

An Agent-Based Network Analytic Perspective On The Evolution Of Complex Adaptive Supply Chain Networks, L. Ponnambalam, A. Tan, X. Fu, X. F. Yin, Zhaoxia Wang, R. S. Goh

Research Collection School Of Computing and Information Systems

Supply chain networks of modern era are complex adaptive systems that are dynamic and highly interdependent in nature. Business continuity of these complex systems depend vastly on understanding as to how the supply chain network evolves over time (based on the policies it adapts), and identifying the susceptibility of the evolved networks to external disruptions. The objective of this article is to illustrate as to how an agent-based network analytic perspective can aid this understanding on the network-evolution dynamics, and identification of disruption effects on the evolved networks. To this end, we developed a 4-tier agent based supply chain model …

Multi-Agent Orienteering Problem With Time-Dependent Capacity Constraints, Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The Orienteering Problem (OP), as originally defined by Tsiligirides, is the problem of cross-countr sport in which participants get rewards from visiting a predefined set of checkpoints. As Orienteering Problem can be used to describe a wide variety of real-world problems like route planning for facility inspection, patrolling of strategic location, and reward-weighted traveling salesman problem, it has attracted continuous interests from researchers and a large number of variants and corresponding algorithms for solving them have been introduced.

Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Resource Allocation Policies, Kar Way Tan, Wei Hao Tan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this work, we consider the problem of allocating doctors in the ambulatory area of a hospital's emergency department (ED) based on a set of policies. Traditional staffing methods are static, hence do not react well to surges in patient demands. We study strategies that intelligently adjust the number of doctors based on current and historical information about the patient arrival. Our main contribution is our proposed data-driven online approach that performs adaptive allocation by utilizing historical as well as current arrivals by running symbiotic simulation in real-time. We build a simulation prototype that models ED process that is close …

Near-Duplicate Video Retrieval: Current Research And Future Trends, Jiajun Liu, Zi Huang, Hongyun Cai, Heng Tao Shen, Chong-Wah Ngo, Wei Wang

Research Collection School Of Computing and Information Systems

The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon during the last decade. User's time spent on video capturing, editing, uploading, searching, and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to the existence of an already large amount of near-duplicate content. This imposes urgent demands on near-duplicate video retrieval as a key role in novel tasks such as video search, video copyright protection, video recommendation, and many more. Driven by its significance, near-duplicate video retrieval has recently attracted …

Flotra: Flower-Shape Trajectory Mining For Instance-Specific Parameter Tuning, Lindawati Lindawati, Feida Zhu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The performance of a heuristic algorithm is highly dependent on its parameter configuration, yet finding a good parameter configuration is often a time-consuming task. In this paper we propose FloTra, a Flower graph mining for graph search Trajectory pattern extraction for generic instance-specific automated parameter tuning. This algorithm provides efficient extraction of compact and discriminative features of the search trajectory, upon which problem instances are clustered and the corresponding optimal parameter configurations are computed. Experimental evaluations of our approach on the Quadratic Assignment Problem (QAP) show that our approach offers promising improvement over existing parameter tuning algorithms. In this work, …

Interacting Knapsack Problem In Designing Resource Bundles, Truong Huy D. Nguyen, Pradeep Reddy Varakantham, Hoong Chuin Lau, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In many real-life businesses, the service provider/seller keeps a log of the visitors’ behavior as a way to assess the efficiency of the current business/operation model and find room for improvement. For example, by tracking when visitors entering attractions in a theme park, theme park owners can detect when and where congestion may occur, thus having contingency plans to reroute the visitors accordingly. Similarly, a Cable TV service provider can track channel switching events at each household to identify uninteresting channels. Subsequently, the repertoire of channels up for subscription can evolve over time to better serve the entertainment demand of …

“Network-Theoretic” Queuing Delay Estimation In Theme Park Attractions, Ajay Aravamudhan, Archan Misra, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Queuing is a common phenomenon in theme parks which negatively affects visitor experience and revenue yields. There is thus a need for park operators to infer the real queuing delays without expensive investment in human effort or complex tracking infrastructure. In this paper, we depart from the classical queuing theory approach and provide a data-driven and online approach for estimating the time-varying queuing delays experienced at different attractions in a theme park. This work is novel in that it relies purely on empirical observations of the entry time of individual visitors at different attractions, and also accommodates the reality that …

Sroiq Syntax Approximation By Using Nominal Schemas, Cong Wang, David Carral, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Nominal schemas is a recently introduced extension of description logics which makes it possible to express rules which generalize DL-safe ones. A tractable description logic, ELROV_n, has been identified. This leads us to the question: can we improve approximate reasoning results by employing nominal schemas? In this paper, we investigate how to approximately cast SROIQ into ELROV_n. Using a datalog-based tractable algorithm, a preliminary evaluation shows that our approach can indeed do approximate SROIQ-reasoning with a high recall.

Towards An Efficient Algorithm To Reason Over Description Logics Extended With Nominal Schemas, David Carral, Cong Wang, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Extending description logics with so-called nominal schemas has been shown to be a major step towards integrating description logics with rules paradigms. However, establishing efficient algorithms for reasoning with nominal schemas has so far been a challenge. In this paper, we present an algorithm to reason with the description logic fragment ELROV_n, a fragment that extends EL⁺⁺ with nominal schemas. We also report on an implementation and experimental evaluation of the algorithm, which shows that our approach is indeed rather efficient.

Cs 3100: Data Structures And Algorithms, Erik Marlow Buck

Computer Science & Engineering Syllabi

Student learning outcomes include:

• Analyze basic algorithms for space and time complexity
• Design abstract data types appropriate for a given problem
• Implement data structures in an efficient manner
• Design and Implement non-graphical user-interfaces
• Select and implement appropriate data structures for a given problem
• Design algorithms to solve specific problems

Cs 1161: Introduction To Computer Programming Ii, Vanessa Starkey

Computer Science & Engineering Syllabi

Introduction to advanced programming concepts and techniques. Emphasis is on object-oriented programming and graphical user interfaces. Integrated lecture/lab.

Cs 3180/5180: Comparative Languages, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course will introduce fundamental concepts and paradigms underlying the design of modern programming languages. For concreteness, we study the details of an object-oriented language (e.g. Java, C#, C++), a functional language (e.g. Scheme), and get introduced to multiparadigm languages (e.g. Python, Scala). The overall goal is to enable comparison and evaluation of existing languages. The programming assignments will largely be coded in Java and in Racket (formerly, Scheme) and optionally in Python or Scala.

Cs 4000: Social Implications Of Computing, Leo Finkelstein

Computer Science & Engineering Syllabi

CS 4000 is a communication skills course using as its subject matter current salient issues associated with the social implications of computing. IN addition to the course text, you will need to use certain reading materials in the library and elsewhere, and you will be responsible for using concepts and theories provided in class lectures and discussions.

Cs 7840: Soft Computing, John C. Gallagher

Computer Science & Engineering Syllabi

This course explores soft computation from historical, theoretical, and application viewpoints. Soft computing methods to be considered include evolutionary computation, neural computation, fuzzy set theory, and approximate reasoning. Applications to problems in optimization, control, and classification will be presented.

Cs 1181: Computer Science Ii, Dan C. Wlodarski

Computer Science & Engineering Syllabi

This is the second course in a two-semester sequence introducing fundamental concepts and techniques for computer science and engineering. The course focuses on problem analysis, advanced programming concepts using JAVA and fundamental data structures. Students learn to analyze problems and evaluate potential solutions with respect to choice of data structures and computational efficiency. Student are exposed to the underlying implementation of basic data structures available in JAVA libraries and develop the skilled needs to extend existing data structures and design new data structures to solve increasingly complex problems. This is an integrated writing course.

Ceg 4422/6422-01: Secure Computing Practices, Bin Wang

Computer Science & Engineering Syllabi

No abstract provided.