Computer Sciences Commons^™

Integrating Self-Organizing Neural Network And Motivated Learning For Coordinated Multi-Agent Reinforcement Learning In Multi-Stage Stochastic Game, Teck-Hou Teng, Ah-Hwee Tan, Janusz A. Starzyk, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Most non-trivial problems require the coordinated performance of multiple goal-oriented and time-critical tasks. Coordinating the performance of the tasks is required due to the dependencies among the tasks and the sharing of resources. In this work, an agent learns to perform a task using reinforcement learning with a self-organizing neural network as the function approximator. We propose a novel coordination strategy integrating Motivated Learning (ML) and a self-organizing neural network for multi-agent reinforcement learning (MARL). Specifically, we adapt the ML idea of using pain signal to overcome the resource competition issue. Dependency among the agents is resolved using domain knowledge …

Click-Through-Based Cross-View Learning For Image Search, Yingwei Pan, Ting Yao, Tao Mei, Houqiang Li, Chong-Wah Ngo, Yong Rui

Research Collection School Of Computing and Information Systems

One of the fundamental problems in image search is to rank image documents according to a given textual query. Existing search engines highly depend on surrounding texts for ranking images, or leverage the query-image pairs annotated by human labelers to train a series of ranking functions. However, there are two major limitations: 1) the surrounding texts are often noisy or too few to accurately describe the image content, and 2) the human annotations are resourcefully expensive and thus cannot be scaled up. We demonstrate in this paper that the above two fundamental challenges can be mitigated by jointly exploring the …

Cenknn: A Scalable And Effective Text Classifier, Guansong Pang, Huidong Jin, Shengyi Jiang

Research Collection School Of Computing and Information Systems

A big challenge in text classification is to perform classification on a large-scale and high-dimensional text corpus in the presence of imbalanced class distributions and a large number of irrelevant or noisy term features. A number of techniques have been proposed to handle this challenge with varying degrees of success. In this paper, by combining the strengths of two widely used text classification techniques, K-Nearest-Neighbor (KNN) and centroid based (Centroid) classifiers, we propose a scalable and effective flat classifier, called CenKNN, to cope with this challenge. CenKNN projects high-dimensional (often hundreds of thousands) documents into a low-dimensional (normally a few …

Facilitating Crowd Sourced Software Engineering Via Stack Overflow, Ohad Barzilay, Christoph Treude, Alexey Zagalsky

Research Collection School Of Computing and Information Systems

The open source community, as well as numerous technical blogs and community web sites, put online vast quantities of free source code, ranging from snippets to full-blown products. This code embodies the software development community’s domain knowledge, and mirrors the structure of the Internet: it is distributed rather than hierarchical; it is chaotic, incomplete, and inconsistent. StackOverflow.com is a Question and Answer (Q&A) website which uses social media to facilitate knowledge exchange between programmers by mitigating the pitfalls involved in using code from the Internet. Its design nurtures a community of developers, and enables crowd sourced software engineering activities ranging …

A Retail Bank's Bpm Experience, Shankararaman, Venky, Gottipati Swapna, Randall E. Duran

Research Collection School Of Computing and Information Systems

This real-life case study, which was undertaken by a leading financial services group in the Asia-Pacific region, is used to demonstrate the innovative use of BPM (Business Process Management) technology in a competitive business area. It describes how a BPM project, within the Application Verification and Capture (AVC), was conceived, designed and implemented in order to deliver strategic value to the organization. Hereafter, the financial services group will be referred to as “the bank”. The AVC project was targeted at one of the bank's processes called the Application Verification and Capture (AVC) process for unit trust products. This process involved …

High Dimensional Data Set Analysis Using A Large-Scale Manifold Learning Approach, Loc Tran

Electrical & Computer Engineering Theses & Dissertations

Because of technological advances, a trend occurs for data sets increasing in size and dimensionality. Processing these large scale data sets is challenging for conventional computers due to computational limitations. A framework for nonlinear dimensionality reduction on large databases is presented that alleviates the issue of large data sets through sampling, graph construction, manifold learning, and embedding. Neighborhood selection is a key step in this framework and a potential area of improvement. The standard approach to neighborhood selection is setting a fixed neighborhood. This could be a fixed number of neighbors or a fixed neighborhood size. Each of these has …

Improving Structural Features Prediction In Protein Structure Modeling, Ashraf Yaseen

Computer Science Theses & Dissertations

Proteins play a vital role in the biological activities of all living species. In nature, a protein folds into a specific and energetically favorable three-dimensional structure which is critical to its biological function. Hence, there has been a great effort by researchers in both experimentally determining and computationally predicting the structures of proteins.

The current experimental methods of protein structure determination are complicated, time-consuming, and expensive. On the other hand, the sequencing of proteins is fast, simple, and relatively less expensive. Thus, the gap between the number of known sequences and the determined structures is growing, and is expected to …

Narratives As A Fundamental Component Of Consciousness, Sandra L. Vaughan, Robert F. Mills, Michael R. Grimaila, Gilbert L. Peterson, Steven K. Rogers

Faculty Publications

In this paper, we propose a conceptual architecture that models human (spatially-temporally-modally) cohesive narrative development using a computer representation of quale properties. Qualia are proposed to be the fundamental "cognitive" components humans use to generate cohesive narratives. The engineering approach is based on cognitively inspired technologies and incorporates the novel concept of quale representation for computation of primitive cognitive components of narrative. The ultimate objective of this research is to develop an architecture that emulates the human ability to generate cohesive narratives with incomplete or perturbated information.

Back Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.

Masthead

Journal of Digital Forensics, Security and Law

No abstract provided.

Autocompletion Without Static Typing, Nicholas Mckay Shelley

Theses and Dissertations

Code completion systems act both as a way to decrease typing and as a way to easily access documentation, both implicit and explicit. The former is typically done by completing known variable or function names, while the latter is done by providing a list of possible completions or by providing convenient views of or access to documentation. Because static type information makes these goals possible and feasible for qualifying languages, many improvements to completion systems are focused on improving the order of results or trimming less-valuable results. It follows that almost all validation techniques for this work have focused on …

Preliminary Test Of A Real-Time, Interactive Silent Speech Interface Based On Electromagnetic Articulograph, Jun Wang, Ashok Samal, Jordan R. Green

School of Computing: Conference and Workshop Papers

A silent speech interface (SSI) maps articulatory movement data to speech output. Although still in experimental stages, silent speech interfaces hold significant potential for facilitating oral communication in persons after laryngectomy or with other severe voice impairments. Despite the recent efforts on silent speech recognition algorithm development using offline data analysis, online test of SSIs have rarely been conducted. In this paper, we present a preliminary, online test of a real-time, interactive SSI based on electromagnetic motion tracking. The SSI played back synthesized speech sounds in response to the user’s tongue and lip movements. Three English talkers participated in this …

From The Editor-In-Chief, Ibrahim A. Baggili

Journal of Digital Forensics, Security and Law

We are proud to share with you this special edition issue of the JDFSL. This year, JDFSL partnered with both the 6th International Conference on Digital Forensics and Cyber Crime (ICDF2C) and Systematic Approaches to Digital Forensic Engineering (SADFE)–two prominent conferences in our field that were co-hosted. Fifty-three papers were submitted, and the Technical Program Committee accepted only 17 after a rigorous review process.

Improved Computer-Generated Simulation Using Motion Capture Data, Seth A. Brunner

Theses and Dissertations

Ever since the first use of crowds in films and videogames there has been an interest in larger, more efficient and more realistic simulations of crowds. Most crowd simulation algorithms are able to satisfy the viewer from a distance but when inspected from close up the flaws in the individual agent's movements become noticeable. One of the bigger challenges faced in crowd simulation is finding a solution that models the actual movement of an individual in a crowd. This paper simulates a more realistic crowd by using individual motion capture data as well as traditional crowd control techniques to reach …

Bits Of Research, Michele C. Weigle

Computer Science Presentations

PDF of a powerpoint presentation that provides an overview of digital preservation, web archiving, and information visualization research; dated June 26, 2014. Also available on Slideshare.

Entropy, Information, Landauer’S Limit And Moore’S Law, Paul Tobin, Jonathan Blackledge

Conference papers

In this paper we explore the link between information and entropy by considering the infamous Maxwell demon thought experiment. A non-rigorous mathematical solution by Le´o Szil´ard established this link for the first time, as did Claude Shannon nineteen years later. In 1961, Rolf Landauer’s mathematical solution resulted in the Landauer limit, which is still being hotly debated, but here we discuss the implication of this limit on Moore’s law and future growth in computing power. A workaround the limit is proposed using an Analogue Artificial Neural Network (AANN). Here, we mimic the action of a human brain synapse formed from …

Towards An Automated System For Evaluation Of Visualizations, Douglas Taggart

Theses and Dissertations

The Information Visualization field focuses on the visualization of abstract data, and with the growing interest in big data analysis, the need for analyzing complex datasets is nowadays highly relevant. With the growing amount and diversity of these datasets new and exciting ways to visualize them are being developed. However, being able to thoroughly test and evaluate the effectiveness of these new visualization techniques is an arduous manual process. Moreover, different researchers hold different opinions on how to thoroughly evaluate a new visualization method. A step towards automating the process of evaluation of visualizations, called the Framework for the Evaluation …

Necessary And Sufficient Conditions For State-Space Network Realization, Philip E. Paré Jr.

Theses and Dissertations

This thesis presents the formulation and solution of a new problem in systems and control theory, called the Network Realization Problem. Its relationship to other problems, such as State Realization and Structural Identifiability, is shown. The motivation for this work is the desire to completely quantify the conditions for transitioning between different mathematical representations of linear time-invariant systems. The solution to this problem is useful for theorists because it lays a foundation for quantifying the information cost of identifying a system's complete network structure from the transfer function.

Stroke Patient Rehabilitation: A Pilot Study Of An Android-Based Game, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

Background

Cerebral vascular accidents (strokes) are the primary cause of disability worldwide and the second leading cause of death both in the Philippines and internationally. In recent years, a number of computer-based applications have been developed to assist in the stroke recovery process.

Aim

This article discusses an Android-based tablet game, FINDEX, that aids in the rehabilitation process of stroke survivors with impaired fine motor skills.

Method

FINDEX was designed and developed in the Philippines. The game contains assessment and monitoring support for tracking the patient’s progress in terms of fine finger dexterity, for example, finger control, isolation and coordination, …

Assisting Coordination During Crisis: A Domain Ontology Based Approach To Infer Resource Needs From Tweets, Shreyansh Bhatt, Hemant Purohit, Andrew J. Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach

Kno.e.sis Publications

Ubiquitous social media during crises provides citizen reports on the situation, needs and supplies. Previous research extracts resource needs directly from the text (e.g. "Power cut to Coney Island and Brighton beach" indicates a power need). This approach assumes that citizens derive and write about specific needs from their observations, properly specified for the emergency response system, an assumption that is not consistent with general conversational behavior. In our study, Twitter messages (tweets) from Hurricane Sandy in 2012 clearly indicate power blackouts, but not their probable implications (e.g. loss of power to hospital life support systems). We use a domain …

From Media Reporting To International Relations: A Case Study Of Asia-Pacific Economic Cooperation (Apec), Chun-Hua Tsai, Yu-Ru Lin

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper reviews logical approaches and challenges raised for explaining AI. We discuss the issues of presenting explanations as accurate computational models that users cannot understand or use. Then, we introduce pragmatic approaches that consider explanation a sort of speech act that commits to felicity conditions, including intelligibility, trustworthiness, and usefulness to the users. We argue Explainable AI (XAI) is more than a matter of accurate and complete computational explanation, that it requires pragmatics to address the issues it seeks to address. At the end of this paper, we draw a historical analogy to usability. This term was understood logically …

The Use And Effectiveness Of Online Social Media In Volunteer Organizations, Amy J. Connolly

USF Tampa Graduate Theses and Dissertations

Volunteer organizations face two challenges not found in non-volunteer organizations: recruiting and retaining volunteers. While social media use is increasing amongst individuals, its use and effectiveness for volunteer recruitment and retention by volunteer organizations is unknown. The dissertation reports the results of three studies to investigate this important question. Using a mixed-methods approach, it addressed the dual nature of social media and its effectiveness by including volunteer organizations and social media users.

This dissertation found that although volunteer organizations are not using social media effectively, they could virtualize requirements of the recruitment process by focusing on relatable events instead of …

Overcoming The Obstacles Of Motion Capture, Matthew Asanuma, Brent Adams

Journal of Undergraduate Research

Facial motion capture is used to capture the intimate and subtle motions of the facial features and apply them to a digital character’s face. Animation for the character, Davy Jones, in the Pirates of the Caribbean movies was achieved using this technique. In Overcoming the Obstacles of Motion Capture, I’ve tried to develop a relatively low-cost, yet high-performing technique suitable for a target market of students and independent artists.

Malware Target Recognition, Thomas E. Dube, Richard A. Raines, Steven K. Rogers

AFIT Patents

A method, apparatus and program product are provided to recognize malware in a computing environment having at least one computer. A sample is received. An automatic determination is made by the at least one computer to determine if the sample is malware using static analysis methods. If the static analysis methods determine the sample is malware, dynamic analysis methods are used by the at least one computer to automatically determine if the sample is malware. If the dynamic analysis methods determine the sample is malware, the sample is presented to a malware analyst to adjudicate the automatic determinations of the …

Creating A Phrase Similarity Graph From Wikipedia, Lubomir Stanchev

Computer Science and Software Engineering

The paper addresses the problem of modeling the relationship between phrases in English using a similarity graph. The mathematical model stores data about the strength of the relationship between phrases expressed as a decimal number. Both structured data from Wikipedia, such as that the Wikipedia page with title “Dog” belongs to theWikipedia category “Domesticated animals”, and textual descriptions, such as that the Wikipedia page with title “Dog” contains the word “wolf” thirty one times are used in creating the graph. The quality of the graph data is validated by comparing the similarity of pairs of phrases using our software that …

Simexplorer: A Testing Framework To Detect Elusive Software Faults, Tingting Yu

School of Computing: Dissertations, Theses, and Student Research

Modern computer software systems are prone to various classes of runtime faults due to their reliance on features such as concurrency and peripheral devices such as sensors. Testing remains a common method for uncovering faults in these systems. However, commonly used testing techniques that execute the program with test inputs and inspect program outputs to detect failures are often ineffective on these systems. In addition, existing testing techniques focus primarily on single applications, neglecting elusive faults that occur at the whole-system level due to complex system event interactions.

This research provides a framework, SIMEXPLORER, that allows engineers to effectively test …

Power Management In The Cluster System, Leping Wang

School of Computing: Dissertations, Theses, and Student Research

With growing cost of electricity, the power management of server clusters has become an important problem. However, most previous researchers have only addressed the challenge in traditional homogeneous environments. Considering the increasing popularity of heterogeneous and virtualized systems, this thesis develops a series of efficient algorithms respectively for power management of heterogeneous soft real-time clusters and a virtualized cluster system. It is built on simple but effective mathematical models. When deployed to a new platform, the software incurs low configuration cost because no extensive performance measurements and profiling are required. Built upon optimization, queuing theory and control theory techniques, our …

Gpu-In-Hadoop: Mapreduce On Distributed Heterogeneous Platforms, Jie Zhu

Student Theses and Dissertations

There are four main challenges that have arisen as the scales of high performance distributed systems grow. Those challenges are the resilience to failure, the programmability, the heterogeneity, and the energy efficiency of those systems. Accomplishing all four without sacrificing performance requires a rethinking of legacy distributed programming models processors and homogeneous clusters. In this paper, the Hadoop system is integrated with CUDA to implement the utilization of heterogeneous processors in a distributed system. This process is achieved by exploiting the implicit data parallelism of mapper and reducer in the Hadoop MapReduce. Combining Hadoop with CUDA provides three excellent merits. …

Trustworthy, Useful Languages For Probabilistic Modeling And Inference, Neil B. Toronto

Theses and Dissertations

The ideals of exact modeling, and of putting off approximations as long as possible, make Bayesian practice both successful and difficult. Languages for modeling probabilistic processes, whose implementations answer questions about them under asserted conditions, promise to ease much of the difficulty. Unfortunately, very few of these languages have mathematical specifications. This makes them difficult to trust: there is no way to distinguish between an implementation error and a feature, and there is no standard by which to prove optimizations correct. Further, because the languages are based on the incomplete theories of probability typically used in Bayesian practice, they place …