Computer Sciences Commons^™

Intraneti Dhe Pagesat Elektronike Ne Komunen E Istogut, Faton Bytyçi

Theses and Dissertations

Shfrytëzimi i përparësive të teknologjisë informative është bërë pjesë e pandashme e jetës tonë për të punuar, informuar, argëtuar etj. Një sferë e veçantë e përdorimit të teknologjisë informative është edhe e-Qeverisja e cila po gjënë vend çdo ditë në administratë për të ofruar shërbime të shpejta, të lehta e të sakta për ata që punojnë dhe për ata që i marrin shërbimet nga administrata.

Komuna e Istogut në dhjetë vitet e fundit ka avancuar në masë të madhe përdorimin e teknologjisë informative dhe i ka bërë modernizimin e shërbimeve. Një prej shërbimeve elektronike në këtë komunë është edhe Sistemi …

Vlerësimi I Karakteristikave Të Rrjetit Në Testimin E Aplikacioneve Përmes Rrjetit Të Virtualizuar, Redon Berisha

Theses and Dissertations

Aplikacionet rrjetëzuese janë bërë pjesë e rëndësishme e përdorimit personal dhe biznesor duke mundësar shkëmbim dhe menaxhim të informacioneve nga të gjitha vendet ku ndodhemi, ndërsa rëndësia e testimit të aplikacioneve është pikë kyçe në ofrimin e eksperiencës së shfrytëzuesit dhe performancës së saj. Qëllimi i këtij studimi është përdorimi i Rrjetit të Virtualizuar në krijimin e mjedisit testues, për emulimin e trafikut në të cilin aplikacionet pranojnë të dhënat. Punimi ka dy qëllime, që të shërbejë si udhërrefyes për virtualizimin e rrjetit dhe për te testuar performancat e rrjetit në kushte të ndryshme. Në këtë drejtim janë formuluar tre …

Frameworks, Algorithms, And Systems For Efficient Discovery Of Data-Backed Facts, Gensheng Zhang

Computer Science and Engineering Dissertations - Archive

This thesis studies the problem of finding facts from semi-structured and structured data. The amount of data in our world is exploding, and the proliferation of data is making them increasingly inaccessible. It is now more challenging than ever how to efficiently identify useful information where a vast amount of data is available. This thesis first studies the problem of finding facts in semi-structured data, specifically, in knowledge graphs. We built Maverick, a general, extensible framework that discovers exceptional facts about entities in knowledge graphs. We model an exceptional fact about an entity of interest as a context-subspace pair, in …

Robust Human Activity Recognition Using Lesser Number Of Wearable Sensors, Di Wang, Edwin Candinegara, Junhui Hou, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

In recent years, research on the recognition of human physical activities solely using wearable sensors has received more and more attention. Compared to other types of sensory devices such as surveillance cameras, wearable sensors are preferred in most activity recognition applications mainly due to their non-intrusiveness and pervasiveness. However, many existing activity recognition applications or experiments using wearable sensors were conducted in the confined laboratory settings using specifically developed gadgets. These gadgets may be useful for a small group of people in certain specific scenarios, but probably will not gain their popularity because they introduce additional costs and they are …

Leveraging The Trade-Off Between Accuracy And Interpretability In A Hybrid Intelligent System, Di Wang, Chai Quek, Ah-Hwee Tan, Chunyan Miao, Geok See Ng, You Zhou

Research Collection School Of Computing and Information Systems

Neural Fuzzy Inference System (NFIS) is a widely adopted paradigm to develop a data-driven learning system. This hybrid system has been widely adopted due to its accurate reasoning procedure and comprehensible inference rules. Although most NFISs primarily focus on accuracy, we have observed an ever increasing demand on improving the interpretability of NFISs and other types of machine learning systems. In this paper, we illustrate how we leverage the trade-off between accuracy and interpretability in an NFIS called Genetic Algorithm and Rough Set Incorporated Neural Fuzzy Inference System (GARSINFIS). In a nutshell, GARSINFIS self-organizes its network structure with a small …

Graphmp: An Efficient Semi-External-Memory Big Graph Processing System On A Single Machine, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Recent studies showed that single-machine graph processing systems can be as highly competitive as clusterbased approaches on large-scale problems. While several outof-core graph processing systems and computation models have been proposed, the high disk I/O overhead could significantly reduce performance in many practical cases. In this paper, we propose GraphMP to tackle big graph analytics on a single machine. GraphMP achieves low disk I/O overhead with three techniques. First, we design a vertex-centric sliding window (VSW) computation model to avoid reading and writing vertices on disk. Second, we propose a selective scheduling method to skip loading and processing unnecessary edge …

Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr

Journal of International Technology and Information Management

The discovery of useful or worthwhile process models must be performed with due regards to the transformation that needs to be achieved. The blend of the data representations (i.e data mining) and process modelling methods, often allied to the field of Process Mining (PM), has proven to be effective in the process analysis of the event logs readily available in many organisations information systems. Moreover, the Process Discovery has been lately seen as the most important and most visible intellectual challenge related to the process mining. The method involves automatic construction of process models from event logs about any domain …

A Hybrid Parallel Approach To High-Performance Compression Of Big Genomic Files And In Compresso Data Processing, Sandino N. Vargas Pérez

Dissertations

Due to the rapid development of high-throughput low cost Next-Generation Sequencing, genomic file transmission and storage is now one of the many Big Data challenges in computer science. Highly specialized compression techniques have been devised to tackle this issue, but sequential data compression has become increasingly inefficient and existing parallel algorithms suffer from poor scalability. Even the best available solutions can take hours to compress gigabytes of data, making the use of these techniques for large-scale genomics prohibitively expensive in terms of time and space complexity.

This dissertation responds to the aforementioned problem by presenting a novel hybrid parallel approach …

High Performance Computing Techniques For Analyzing Risky Decision Making, Vinay B. Gavirangaswamy

Dissertations

The process or activity of making choices when subject to gain or loss can be understood as risky decision making (RDM). Risky Decisions consists of outcomes of decisions that may probabilistically result in unfavorable results. Every organism that lives faces this challenge and recent research suggests that there is a computational process involved in making these decisions. This has led to new approaches in the study of RDM. My dissertation is towards contributing to expand on the existing knowledge of RDM processes.

The core contribution of my work is an analysis and development of high performance computing techniques that improves …

A Deep Learníng-Based Data Minimization Algorithm For Big Genomics Data In Support Of Lot And Secure Smart Health Services, Mohammed Aledhari

Dissertations

In the age of Big Genomics Data, institutes such as the National Human Genome Research Institute (NHGRI),1000-Genomes project, and the international cancer sequencing consortium are faced with the challenge of sharing large volumes of data between internationallydispersed sample collectors, data analyzers, and researchers, a process that up until now has been plagued by unreliable transfers and slow connection speeds. These occur due to the inherent throughput bottlenecks of traditional transfer technologies. One suggested solution is using the cloud as an infrastructure to solve the store and analysis challenges. However, the transfer and share of the genomics datasets between biological laboratories …

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

A Mixed-Reality Approach For Cyber-Situation Awareness, Tapas Dipakkumar Joshi

Theses and Dissertations

As the proliferation and adoption of smart devices increase, there is an unprecedented amount of data being released into the network every second. Computer networks are the carriers for the movement of this ever generating amounts of data, but are dumb in a way that they do not distinguish between suspicious data traffic and valid data traffic. Also, for however secure a computer network be, suspicious network traffic activities are bound to happen. These suspicious traffic activities have to be detected, analyzed and stopped before it compromises the entire network and leaves the information and data security of an organization …

A Context-Free Method Of Visualizing Streaming Object Data For The Purpose Of Identifying Known Events: An Implementation And Analysis, Quinn Gregory Carver

Theses and Dissertations

This year, every second, five gigabytes of new data will be streamed to storage and yet less than half a percent of all this data will ever be analyzed. Much of this muted data is high-variety object data, unnoticed in a void of sorely needed tools to make it readily understandable. A software tool for visualizing streaming object data in a context-free manner can be built, and this tool would aid in finding predictor data for known events which are functions of the data. The design of the tool to support the hypothesis is presented and field results from over …

Popularity Prediction, Andrew Furgiuele

Computer Science

With the rise in popularity of the Internet, data describing unique types of items has been collected into easy to access sources. Using this newly acquired data, is it possible to predict if an item will become a bestseller while another fade away with time? Popularity prediction is a problem that has attracted a great deal of research recently, and for good reason. The ability to predict an items future rise to popularity or fall to obscurity is a possibly priceless skill and sought out in many different industries such as sales, investments, and marketing. This report enumerates and analyzes …

Predicting The Author Of Twitter Posts With Markov Chain Analysis, Daniel Freeman

Honors Theses

Given a set of text with known authors, is it possible to take new text, not knowing who wrote it, and correctly identify the author? One way to do this is to analyze the text using Markov chains. This research project will first attempt to answer this question using books available in the public domain. Using what is learned from trying to identify authors of books, the primary goal of this project is to identify the best way to guess the author of a post on the social media network Twitter using Markov chains.

A Cluster Analysis Of Challenging Behaviors In Autism Spectrum Disorder, Elizabeth Stevens, Abigail Atchison, Laura Stevens, Esther Hong, Doreen Granpeesheh, Dennis Dixon, Erik J. Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

We apply cluster analysis to a sample of 2,116 children with Autism Spectrum Disorder in order to identify patterns of challenging behaviors observed in home and centerbased clinical settings. The largest study of this type to date, and the first to employ machine learning, our results indicate that while the presence of multiple challenging behaviors is common, in most cases a dominant behavior emerges. Furthermore, the trend is also observed when we train our cluster models on the male and female samples separately. This work provides a basis for future studies to understand the relationship of challenging behavior profiles to …

Optimal Layout For A Component Grid, Michael W. Ebert

Computer Science and Software Engineering

Several puzzle games include a specific type of optimization problem: given components that produce and consume different resources and a grid of squares, find the optimal way to place the components to maximize output. I developed a method to evaluate potential solutions quickly and automated the solving of the problem using a genetic algorithm.

Using Virtual Reality To Improve Sitting Balance, Alice Kay Barnes

Graduate Theses/Dissertations

This thesis focuses on using virtual reality (VR) to enhance sitting balance and core strength. It is a study in how to create a VR exercise program which is interesting enough to keep players/patients motivated, but comfortable to play and not overwhelming to the senses. The software used for this study was written with the hope that a later version of it might be used with occupational/physical therapy patients one day. For this master’s thesis, the initial testing has been done with healthy volunteers. The software incorporates what developers know thus far about designing for VR, and it is hoped …

Altering The Expression Of Artemisinin Through Osmotic Manipulation, Tyler Friesen

Theses/Capstones/Creative Projects

Artemisinin is an anti-malarial drug used in combination therapy to treat all malarial parasites in the blood stage. The expression of artemisinin within the plant Artemisia annua is only 1% of the dry weight. Methods for increasing the level of artemisinin within the plant were proposed. This paper looks into finding homologous enzymes across multiple species in order to find species where genetic manipulations will be useful. The second part of this paper looks at the use of osmotic stress to increase the reactive oxygen species in order to increase the amount of artemisinin within the plant. The database portion …

Cultivating Community Interactions In Citizen Science: Connecting People To Each Other And The Environment, Bret Allen Finley

Boise State University Theses and Dissertations

Citizen science leverages a distributed user-base which participates in crowd-sourced scientific inquiry. Geotagger is a citizen science project that allows people to collaboratively investigate the natural world around them and share their findings. Citizens are rarely compensated for their work and individual contributors can feel isolated which leads to motivation problems. This thesis focuses on engaging citizen scientists and motivating their contributions via social interaction and engagement. As a part of this work, a number of social enhancements have been developed as extensions to the existing Geotagger project. These enhancements and their effect on social engagement were evaluated using in-field …

Amake: Cached Builds Of Top-Level Targets, Jim Buffenbarger

Computer Science Faculty Publications and Presentations

This paper describes a software-build tool named Amake, an extension of GNU Make. Its additional features solve important problems that have, until now, only been addressed by “high-end” build tools (e.g., ClearCase and Vesta).

With a typical build tool, if a top-level target must be updated, intermediate targets must be built from sources, and then combined to build the top-level target. The enhancements described here allow a top-level target to be fetched from a shared cache, without building, or even fetching its intermediate-target dependencies. Thus, a developer’s workspace may need only contain sources and top-level targets. This reduces build time, …

Decision Support For Shared Responsibility Of Cloud Security Metrics, Moteeb Aieed Al Moteri

Theses and Dissertations

With the rapid growth of cloud computing and the increasing importance of measuring the security of cloud systems, more attention has been focused on the need for security metrics that are specific to cloud computing. The use of metrics in cloud computing enables improved service selection, service agreement, and service verification. This dissertation presents a taxonomy of cloud security metrics and guideline and a framework for allocating cloud security metrics shared responsibility. The taxonomy considers several novel viewpoints. Metrics are organized by cloud capability type (Application, Platform, Infrastructure) along with the type of cloud deployment (public, private, hybrid, community), and …

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Journal of Digital Forensics, Security and Law

No abstract provided.

Varying Instructional Approaches To Physical Extraction Of Mobile Device Memory, Joan Runs Through, Gary D. Cantrell

Journal of Digital Forensics, Security and Law

Digital forensics is a multidisciplinary field encompassing both computer science and criminal justice. This action research compared demonstrated skill levels of university students enrolled in a semester course in small device forensics with 54 hours of instruction in mobile forensics with an emphasis on physical techniques such as JTAG and Chip-Off extraction against the skill levels of industry professionals who have completed an accelerated 40 hour advanced mobile forensics training covering much of the same material to include JTAG and Chip-Off extraction. Participant backgrounds were also examined to determine if those participants with a background in computer science had an …

Digital Forensic Readiness In Organizations: Issues And Challenges, Nickson Menza Karie, Simon Maina Karume Dr.

Journal of Digital Forensics, Security and Law

With the evolution in digital technologies, organizations have been forced to change the way they plan, develop, and enact their information technology strategies. This is because modern digital technologies do not only present new opportunities to business organizations but also a different set of issues and challenges that need to be resolved. With the rising threats of cybercrimes, for example, which have been accelerated by the emergence of new digital technologies, many organizations as well as law enforcement agencies globally are now erecting proactive measures as a way to increase their ability to respond to security incidents as well as …

Broadband Router Security: History, Challenges And Future Implications, Patryk Szewczyk, Rose Macdonald

Journal of Digital Forensics, Security and Law

Consumer grade broadband routers are integral to accessing the Internet and are primarily responsible for the reliable routing of data between networks. Despite the importance of broadband routers, security has never been at the forefront of their evolution. Consumers are often in possession of broadband routers that are rich in consumer-orientated features yet riddled with vulnerabilities that make the routers susceptible to exploitation. This amalgamation of theoretical research examines consumer grade broadband routers from the perspective of how they evolved, what makes them vulnerable, how they are targeted and the challenges concerning the application of security. The research further explores …

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd

Journal of Digital Forensics, Security and Law

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random …

Research Proposal: Present A New Method For Energy Efficient Routing For Wireless Body Area Networks, Farshid Bagheri Saravi

Student Scholarship

This is the research proposal for the Master's Thesis. Problem statement and research approach: How can routing be optimized in wireless body area networks to improve energy consumption? 1. What methods are available to reduce energy consumption in routing wireless body area networks, and which approach is better? 2. How can we provide a suitable solution for optimizing energy-efficient routing in wireless body area networks? 3. How can the proposed solution be compared and evaluated with state-of-the-art methods? Goals: 1. Examining the current methods to reduce energy consumption in optimizing the routing of wireless body networks and selecting the best …

An Unmanned Aerial System For Prescribed Fires, Evan M. Beachly

School of Computing: Dissertations, Theses, and Student Research

Prescribed fires can lessen wildfire severity and control invasive species, but some terrains may be difficult, dangerous, or costly to burn with existing tools. This thesis presents the design of an unmanned aerial system that can ignite prescribed fires from the air, with less cost and risk than with aerial ignition from a manned aircraft. The prototype was evaluated in-lab and successfully used to ignite interior areas of two prescribed fires. Additionally, we introduce an approach that integrates a lightweight fire simulation to autonomously plan safe flight trajectories and suggest effective fire lines. Both components are unique in that they …

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Journal of Digital Forensics, Security and Law

No abstract provided.