Computer Sciences Commons^™

Considering Operational Issues For Multiagent Conceptual Inferencing In A Distributed Information Retrieval Application, Leen-Kiat Soh

School of Computing: Faculty Publications

Our system, based on a multiagent framework called collaborative understanding of distributed knowledge (CUDK), is designed with the overall goal of balancing agents’ conceptual learning and task accomplishment. The tradeoff between the two is that while conceptual learning allows an agent to improve its own concept base, it could be counter-productive: conceptual learning is time consuming and requires processing resources necessary for the agent to accomplish its tasks. In our current phase of research, we investigate the roles of resource and knowledge constraints, environmental factors (such as the frequency of queries), and learning mechanisms in a CUDK-based distributed information retrieval …

I-Minds: A Multiagent System For Intelligent Computer- Supported Collaborative Learning And Classroom Management, Leen-Kiat Soh, Nobel Khandaker, Hong Jiang

School of Computing: Faculty Publications

I-MINDS provides a computer-supported collaborative learning (CSCL) infrastructure and environment for learners in synchronous learning and classroom management applications for instructors, for large classroom or distance education situations. For supporting the instructor, I-MINDS includes a teacher agent. The teacher agent allows the instructor to interact with students, manage Q&A sessions, administer quizzes, post evaluations, form groups and monitor individual and group performances. For computer-supported collaborative learning, I-MINDS, which stands for Intelligent Multiagent Infrastructure for Distributed Systems in Education, provides a student agent for each student. Each student agent monitors and models its user and carries out group formation with other …

Partial Forwarding Scheme For Dynamic Window Resizing In Live P2p Streaming Systems, Zhipeng Ouyang, Lisong Xu, Byrav Ramamurthy

School of Computing: Conference and Workshop Papers

Peer-to-peer (P2P) streaming systems, in which individual nodes or peers operated by ordinary Internet users collaborate to serve video streams, have recently aroused considerable interest in both academia and industry. An important problem in P2P streaming systems is how to reduce their consumed bandwidth, which is a major concern of Internet service providers. Our work is motivated by the fact that a user may dynamically change the size of a window displaying a video stream according to his/her personal choice, a scenario we refer to as dynamic window resizing. In this paper, we propose a scheme called the Partial Forwarding …

Computation Of A Face Attractiveness Index Based On Neoclassical Canons, Symmetry, And Golden Ratios, Kendra Schmid, David Marx, Ashok Samal

School of Computing: Faculty Publications

Analysis of attractiveness of faces has long been a topic of research. Literature has identified many different factors that can be related to attractiveness. In this research we analyze the role of symmetry, neoclassical canons, and golden ratio in the determination of attractiveness of a face. We focus on the geometry of a face and use actual faces for our analysis. We find there are some differences in the criteria used by males and females to determine attractiveness. The model we have developed to predict the attractiveness of a face using its geometry is accurate with low residual errors.

Data Assimilation And Visualization For Ensemble Wildland Fire Models, Soham Chakraborty

University of Kentucky Master's Theses

This thesis describes an observation function for a dynamic data driven application system designed to produce short range forecasts of the behavior of a wildland fire. The thesis presents an overview of the atmosphere-fire model, which models the complex interactions between the fire and the surrounding weather and the data assimilation module which is responsible for assimilating sensor information into the model. Observation plays an important role in data assimilation as it is used to estimate the model variables at the sensor locations. Also described is the implementation of a portable and user friendly visualization tool which displays the locations …

Routing Protocol Performance Evaluation For Mobile Ad-Hoc Networks, Pedro A. Lopez-Fernandez

UNF Graduate Theses and Dissertations

Currently, MANETs are a very active area of research, due to their great potential to provide networking capabilities when it is not feasible to have a fixed infrastructure in place, or to provide a complement to the existing infrastructure. Routing in this kind of network is much more challenging than in conventional networks, due to its mobile nature and limited power and hardware resources.

The most practical way to conduct routing studies of MANETs is by means of simulators such as GloMoSim. GloMoSim was utilized in this research to investigate various performance statistics and draw comparisons among different MANET routing …

Business-Oriented Software Process Improvement Based On Cmm And Cmmi Using Qfd, Yan Sun

Doctoral Dissertations

"Software Process Improvement (SPI) has become the key to the survival of many software development organizations. Many international SPI models/standards are developed for SPI. The Capability Maturity Model (CMM) and Capability Maturity Model Integrated (CMMI)) from the Software Engineering Institute are two SPI models. In this study, several existing SPI models and approaches are reviewed, their advantages are identified, and their drawbacks are discussed. A set of new SPI frameworks integrating Quality Function Deployment (QFD) with both CMM and CMMI are developed by combining the best features of previous approaches and addressing their limitations"--Abstract, page iii.

Automatic Composition Of Themed Mood Pieces, Heather Chan, Dan A. Ventura

Faculty Publications

Musical harmonization of a given melody is a nontrivial problem; slight variations in instrumentation, voicing, texture, and bass rhythm can lead to significant differences in the mood of the resulting piece. This study explores the possibility of automatic musical composition by using machine learning and statistical natural language processing to tailor a piece to a particular mood using an existing melody.

Digital Cs1 Study Pack Based On Moodle And Python, Atanas Radenski

Mathematics, Physics, and Computer Science Faculty Books and Book Chapters

We believe that CS1 courses can be made more attractive to students:

• by teaching a highly interactive scripting language – Python
• by using an open source course management system - such as Moodle - to make all course resources available in a comprehensive digital study pack, and
• by offering detailed self-guided online labs

We have used Moodle [1] and Python [2] to develop a "Python First" digital study pack [3] which comprises a wealth of new, original learning modules: extensive e-texts, detailed self-guided labs, numerous sample programs, quizzes, and slides. Our digital study pack pedagogy is described in recent ITiCSE …

A Workflow Visual Modeler And Its Interface To Existing Workflow Management Systems, Jyoti Chaturvedi

UNF Graduate Theses and Dissertations

The rapid growth and complexity of today's businesses have created a need for business process management approaches that will promote the efficient functioning of these organizations. Users of business process management tools greatly benefit from using visual process modeling capabilities. Cross-business interaction sets forth the need for standardization of notations in designing these models.

The goal of this thesis is to study state of the art business process management notations and state of the art diagramming frameworks associated with building a Visual Modeler that can be easily integrated with existing workflow management systems. This thesis presents a Visual Modeler that …

Edge-Unfolding Nested Polyhedral Bands, Greg Aloupis, Erik D. Demaine, Stefan Langerman, Pat Morin, Joseph O'Rourke, Ileana Streinu, Godfried Toussaint

Computer Science: Faculty Publications

A band is the intersection of the surface of a convex polyhedron with the space between two parallel planes, as long as this space does not contain any vertices of the polyhedron. The intersection of the planes and the polyhedron produces two convex polygons. If one of these polygons contains the other in the projection orthogonal to the parallel planes, then the band is nested. We prove that all nested bands can be unfolded, by cutting along exactly one edge and folding continuously to place all faces of the band into a plane, without intersection. © 2007 Elsevier B.V.

Book Review: Challenges To Digital Forensic Evidence, Gary C. Kessler

Publications

This document is Dr. Kessler's review of Challenges to Digital Forensic Evidence, by Fred Cohen. Fred Cohen & Associates, 2008. ISBN 1-878109-41-3

Concept Detection: Convergence To Local Features And Opportunities Beyond, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky

Research Collection School Of Computing and Information Systems

No abstract provided.

Fine-Grained Reputation-Based Routing In Wireless Ad Hoc Networks, Alma Cemerlic

Masters Theses and Doctoral Dissertations

Ad hoc networks are very helpful in situations when no fixed network infrastructure is available. They are especially important in emergency situations such as natural disasters and military conflicts. Most developed wireless ad hoc routing protocols are designed to discover and maintain an active path from source to destination with an assumption that every node is friendly and cooperative. However, it is possible that the participating nodes are selfish or malicious. A mechanism to evaluate reputation for each node is essential for the reliability and security of routing protocol in ad hoc networks. We propose a fine-grained reputation system for …

Set Linear Algebra And Set Fuzzy Linear Algebra, Florentin Smarandache, W.B. Vasantha Kandasamy, K. Ilanthenral

Branch Mathematics and Statistics Faculty and Staff Publications

In this book, the authors define the new notion of set vector spaces which is the most generalized form of vector spaces. Set vector spaces make use of the least number of algebraic operations, therefore, even a non-mathematician is comfortable working with it. It is with the passage of time, that we can think of set linear algebras as a paradigm shift from linear algebras. Here, the authors have also given the fuzzy parallels of these new classes of set linear algebras. This book abounds with examples to enable the reader to understand these new concepts easily. Laborious theorems and …

Adding Simple Simulations To Video Games To Improve Realism, Leonard Kinnaird-Heether

Master's Theses and Doctoral Dissertations

In this paper a method of enhancing the realism of certain computer game types, particularly First Person Shooter games, is explored by attempting to include intelligent neutral background characters to the game environment. This method also requires that the inclusion of these background characters will not adversely affect the performance of a game by drastically increasing the computational complexity of the game. A simulation was created to show how this can be done using a group of intelligent agents based in a simulated world, and a simplified system of norms designed to influence the agents’ behavior. The agents are designed …

Model-Driven Search-Based Loop Fusion Optimization For Handwritten Code, Pamela Bhattacharya

LSU Master's Theses

The Tensor Contraction Engine (TCE) is a compiler that translates high-level, mathematical tensor contraction expressions into efficient, parallel Fortran code. A pair of optimizations in the TCE, the fusion and tiling optimizations, have proven successful for minimizing disk-to-memory traffic for dense tensor computations. While other optimizations are specific to tensor contraction expressions, these two model-driven search-based optimization algorithms could also be useful for optimizing handwritten dense array computations to minimize disk to memory traffic. In this thesis, we show how to apply the loop fusion algorithm to handwritten code in a procedural language. While in the TCE the loop fusion …

Dynamic Workflow Management For Large Scale Scientific Applications, Emir Mahmut Bahsi

LSU Master's Theses

The increasing computational and data requirements of scientific applications have made the usage of large clustered systems as well as distributed resources inevitable. Although executing large applications in these environments brings increased performance, the automation of the process becomes more and more challenging. The use of complex workflow management systems has been a viable solution for this automation process. In this thesis, we study a broad range of workflow management tools and compare their capabilities especially in terms of dynamic and conditional structures they support, which are crucial for the automation of complex applications. We then apply some of these …

Design Of A Fully Autonomous Mobile Pipeline Exploration Robot (Famper), Jong-Hoon Kim

LSU Master's Theses

Pipelines have been an integral part of our constructions for many centuries. However, need to be maintained, and the cost of maintenance continues to increase. Robots have been considered as an attractive alternative, and many different types of pipeline robots have been proposed in the past. Unfortunately many of them work under only very restricted environments such as customized pipelines, often have no vertical mobility, or can traverse through only a simple pipeline structure due to wired control. This thesis presents the design and implementation of a robot based on novel idea we call “caterpillar navigational mechanism”. A Fully Autonomous …

Failure-Awareness And Dynamic Adaptation In Data Scheduling, Mehmet Balman

LSU Master's Theses

Over the years, scientific applications have become more complex and more data intensive. Especially large scale simulations and scientific experiments in areas such as physics, biology, astronomy and earth sciences demand highly distributed resources to satisfy excessive computational requirements. Increasing data requirements and the distributed nature of the resources made I/O the major bottleneck for end-to-end application performance. Existing systems fail to address issues such as reliability, scalability, and efficiency in dealing with wide area data access, retrieval and processing. In this study, we explore data-intensive distributed computing and study challenges in data placement in distributed environments. After analyzing different …

Data Exploration By Using The Monotonicity Property, Hongyi Chen

LSU Master's Theses

Dealing with different misclassification costs has been a big problem for classification. Some algorithms can predict quite accurately when assuming the misclassification costs for each class are the same, like most rule induction methods. However, when the misclassification costs change, which is a common phenomenon in reality, these algorithms are not capable of adjusting their results. Some other algorithms, like the Bayesian methods, have the ability to yield probabilities of a certain unclassified example belonging to given classes, which is helpful to make modification on the results according to different misclassification costs. The shortcoming of such algorithms is, when the …

Enhancing Recursive Supervised Learning Using Clustering And Combinatorial Optimization (Rsl-Cc), Kiruthika Ramanathan, Sheng Uei Guan

Research Collection School Of Computing and Information Systems

The use of a team of weak learners to learn a dataset has been shown better than the use of one 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 one of the best off-the-shelf classifiers. However, some problems still remain, including determining the optimal number of weak learners and the overfitting of data. In an earlier work, we developed the RPHP algorithm which solves both these problems by using a combination of genetic algorithm, weak learner and pattern distributor. In this paper, …

Probabilistic Sales Forecasting For Small And Medium-Size Business Operations, Randall E. Duran

Research Collection School Of Computing and Information Systems

One of the most important aspects of operating a business is the forecasting of sales and allocation of resources to fulfill sales. Sales assessments are usually based on mental models that are not well defined, may be biased, and are difficult to refine and improve over time. Defining sales forecasting models for small- and medium-size business operations is especially difficult when the number of sales events is small but the revenue per sales event is large. This chapter reviews the challenges of sales forecasting in this environment and describes how incomplete and potentially suspect information can be used to produce …

Columbia University/Vireo-Cityu/Irit Trecvid2008 High-Level Feature Extraction And Interactive Video Search, Shih-Fu Chang, Junfeng He, Yu-Gang Jiang, Elie El Khoury, Chong-Wah Ngo, Akira Yanagawa, Eric Zavesky

Research Collection School Of Computing and Information Systems

In this report, we present overview and comparative analysis of our HLF detection system, which achieves the top performance among all type-A submissions in 2008. We also describe preliminary evaluation of our video search system, CuZero, in the interactive search task.

Factors Affecting The Information Quality Of Personal Web Portfolios, P. Katerattanakul, Keng Siau

Research Collection School Of Computing and Information Systems

Personal Web portfolios have become a popular information source and an effective method for individuals to present themselves to others in cyberspace. Thus, the quality of personal Web portfolios is critical and affects the perception that others have of the individuals. But how do we measure quality of personal Web portfolios? What are the important factors affecting quality of personal Web portfolios? This study presents the development of an instrument measuring factors affecting information quality of personal Web portfolios. The proposed instrument, based on the Information Quality framework, was refined and validated to assess its construct validity, convergent validity, and …

Multi-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song

Research Collection School Of Computing and Information Systems

Classical multi-echelon repairable item inventory models are based either on steady-state analysis or infinite repair capacity, which may not work well in situations when the demand is nonstationary, or repair capacity is limited. In this paper, we propose an analytical model for evaluating system performance that works well under limited repair capacity and nonstationary demands. Following the METRIC methodology, we then develop an optimisation algorithm to solve the corrective maintenance problem in military logistics. Experimental results show that our approach yields good solutions efficiently. This work has also resulted in a software that has been field-tested by a military organisation.

Document Selection For Extracting Entity And Relationship Instances Of Terrorist Events, Zhen Sun, Ee Peng Lim, Kuiyu Chang, Maggy Anastasia Suryanto, Rohan Kumar Gunaratna

Research Collection School Of Computing and Information Systems

In this chapter, we study the problem of selecting documents so as to extract terrorist event information from a collection of documents. We represent an event by its entity and relation instances. Very often, these entity and relation instances have to be extracted from multiple documents. We therefore define an information extraction (IE) task as selecting documents and extracting from which entity and relation instances relevant to a user-specified event (aka domain specific event entity and relation extraction). We adopt domain specific IE patterns to extract potentially relevant entity and relation instances from documents, and develop a number of document …

The Oil Drilling Model And Iterative Deepening Genetic Annealing Algorithm For The Traveling Salesman Problem, Hoong Chuin Lau, Fei Xiao

Research Collection School Of Computing and Information Systems

In this work, we liken the solving of combinatorial optimization problems under a prescribed computational budget as hunting for oil in an unexplored ground. Using this generic model, we instantiate an iterative deepening genetic annealing (IDGA) algorithm, which is a variant of memetic algorithms. Computational results on the traveling salesman problem show that IDGA is more effective than standard genetic algorithms or simulated annealing algorithms or a straightforward hybrid of them. Our model is readily applicable to solve other combinatorial optimization problems.

Private Query On Encrypted Data In Multi-User Setting, Feng Bao, Robert H. Deng, Xuhua Ding, Yanjiang Yang

Research Collection School Of Computing and Information Systems

Searchable encryption schemes allow users to perform keyword based searches on an encrypted database. Almost all existing such schemes only consider the scenario where a single user acts as both the data owner and the querier. However, most databases in practice do not just serve one user; instead, they support search and write operations by multiple users. In this paper, we systematically study searchable encryption in a practical multi-user setting. Our results include a set of security notions for multi-user searchable encryption as well as a construction which is provably secure under the newly introduced security notions.

Efficient Corona Training Protocols For Sensor Networks, Alan A. Bertossi, Stephan Olariu, Cristina M. Pinotti

Computer Science Faculty Publications

Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. It is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. Due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be GPS-enabled. Moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. The task of acquiring such a coarse-grain location awareness is referred to as training. …