Computer Sciences Commons^™

Big Data In Single Player Games, Mohammad Khaldoun Farhan Aldaboubi

Computer Science and Engineering Theses - Archive

Improving video games can be exponentially more efficient by utilizing big data. Big data plays a big part in modern gaming, especially for multiplayer games like poker, first person shooter games. Utilizing the data gathered from video games can be used in ways that will improve the player experience massively and can be eye-opening to find issues, player pattern, and improve the game in ways that will be hard to pin point without gathering data of how the players are playing the game. However, while big data is being utilized in multiplayer games, it’s not utilized as much in single …

Comparative Analysis Of Metabolic Pathways Of Bacteria Used In Fermented Food, Keanu Hoang, Kiran Bastola

Theses/Capstones/Creative Projects

This study presents a novel methodology for analyzing metabolic pathways. Utilizing KEGG REST API through a Biopython package and file parser, data about whether or not a bacteria has an enzyme or not was extracted. The results found that differences in metabolic pathway enrichment values follow along the lines of genera and pathway type. In particular, bacteria found in food spoilage and commercial nitrogen fixing products had high values of enrichment.

Feature Selection And Data Reconstruction Via Robust And Flexible Learning Models, Di Ming

Computer Science and Engineering Dissertations - Archive

Feature selection and data reconstruction are very important topics in machine learning area. In today's big data environment, many data could have high dimensions and come with noise, corruption, etc. Thus, we develop robust and flexible learning models so as to select the relevant features from the high-dimensional data spaces and reconstruct the original clean data from the corrupted input data more efficiently and more effectively. To resolve the inflexibility of the widely used class-shared feature selection methods such as L21-norm, we derive LASSO from probabilistic selection on ridge regression which provides an independent point of view from the usual …

Deep Representation Learning On Giga-Pixel Whole Slide Images, Xinliang Zhu

Computer Science and Engineering Dissertations - Archive

I present my work towards solving the fundamental, challenging and valuable problem for automatically processing the giga-pixel level whole slide pathology images (WSIs): the representation of them. Specifically, I target on solving the combinations of three critical aspects of the problem: (1) it's not engineering feasible to directly fit them into existing convolutional neural networks because they are too large; (2) pre-trained parameters from other domains may not be effectively transferred to pathology images, and (3) both the image samples and annotations for those images are rarely available. To evaluate the effectiveness of the developed methods, I mainly focus on …

Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean

Computational and Data Sciences (PhD) Dissertations

"Social communication is the use of language in social contexts. It encompasses social interaction, social cognition, pragmatics, and language processing” [3]. One presumed prerequisite of social communication is visual attention–the focus of this work. “Visual attention is a process that directs a tiny fraction of the information arriving at primary visual cortex to high-level centers involved in visual working memory and pattern recognition” [7]. This process involves the integration of two streams: the global and local streams; the global stream rapidly processes the scene, and the local stream processes details. This integration is important to social communication in that attending …

Integrated Machine Learning And Bioinformatics Approaches For Prediction Of Cancer-Driving Gene Mutations, Oluyemi Odeyemi

Computational and Data Sciences (PhD) Dissertations

Cancer arises from the accumulation of somatic mutations and genetic alterations in cell division checkpoints and apoptosis, this often leads to abnormal tumor proliferation. Proper classification of cancer-linked driver mutations will considerably help our understanding of the molecular dynamics of cancer. In this study, we compared several cancer-specific predictive models for prediction of driver mutations in cancer-linked genes that were validated on canonical data sets of functionally validated mutations and applied to a raw cancer genomics data. By analyzing pathogenicity prediction and conservation scores, we have shown that evolutionary conservation scores play a pivotal role in the classification of cancer …

Interactions In Visualizations To Support Knowledge Activation, Kari Sandouka

Masters Theses & Doctoral Dissertations

Humans have several exceptional abilities, one of which is the perceptual tasks of their visual sense. Humans have the unique ability to perceive data and identify patterns, trends, and outliers. This research investigates the design of interactive visualizations to identify the benefits of interacting with information. The research question leading the investigation is how does interacting with visualizations support analytical reasoning of emergent information to activate knowledge? The study uses the theory of distributed cognition and human-information interaction to apply the design science research framework. The motivation behind the research is to identify guidelines for interactive visualizations to enhance a …

Faculty Perceptions Of Open Educational Resources In Cyber Curriculum: A Pilot Study, Alan Stines

Masters Theses & Doctoral Dissertations

The cyber landscape is growing and evolving at a fast pace. Public and private industries need qualified applicants to protect and defend information systems that drive the digital economy. Currently, there are not enough candidates in the pipeline to fill this need in the workforce. The digital economy is still growing, thus presenting an even greater need for skilled workers in the future. The lack of a strong workforce in cybersecurity presents many challenges to safeguarding U.S. national security and citizens across the world. The William and Flora Hewlett Foundation defines Open Educational Resources (OER) as teaching, learning, and research …

Learning Transferable Meta-Policies For Hierarchical Task Decomposition And Planning Composition, Predrag Djurdjevic

Computer Science and Engineering Dissertations - Archive

In real world scenarios where situated agents are faced with dynamic, high-dimensional, partially observable environments with action and reward uncertainty, the traditional states space Reinforcement Learning (RL) becomes easily prohibitively large for policy learning. In such scenarios, addressing the curse of dimensionality and eventual transfer to closely related tasks is one of the principal challenges and motivations for Hierarchical Reinforcement Learning (HRL). The prime appeal of hierarchal and particularly recursive approaches is in effective factored state, transition and reward representations which abstract out aspects that are not relevant to subtasks and allow potential transfer of skills which represent solutions to …

Modelet E Vlerësimit Të Rrezikshmërisë Së Të Dhënave, Arbër Demhasaj

Theses and Dissertations

Tema paraqet disa modele për të përmirësuar njohuritë tona për sigurinë e informacionit dhe menaxhimin e rrezikut në bizneset bashkëkohorë dhe në organizata të tjera. Në botën e sulmeve kibernetike të vazhdueshme në sistemet e informacionit, njohurit rreth menaxhimit të rrezikut janë duke u bërë një detyrë vendimtare për minimizimin e rreziqeve të mundshme që mund të bëjnë përpjekjet e tyre. Prandaj, kërkohet njohuri të mira në fushën e sigurisë së informacionit. Parandalimi i humbjeve të rënda që mund të ndodhin për shkak të sulmeve kibernetike dhe dështimeve të tjera në një organizatë zakonisht lidhet me njohuritë rreth investimeve të …

Using Neural Networks To Predict Neurological Disorders, Gresa Gela

Theses and Dissertations

The growth and development of Artificial Intelligence (AI) is fast becoming a powerful influence in our present day reality. In medicine there is a vast number of patients who suffers or even dies for the cause of the late detection of their disorders. Some of the biggest research institutes have been able to contribute in some areas of medicine by creating different complex systems. Even though this field is having a wide range of applications, there is still a lack in the field of neuroscience. In this thesis we will prove how efficiently ANNs can be used in early detection …

Siguria Dhe Privatësia Në Shfyrtëzimin E Internetit, Rina Nebihu

Theses and Dissertations

Teknologjia e informacionit përfshinë të gjitha llojet e teknologjisë së përdorur për shkëmbimin, ruajtjen, përdorimin ose krijimin e informacionit. Teknologjia e informacionit përfiton nga bota e biznesit duke lejuar organizatat të punojnë në mënyrë më efikase dhe maksimizojnë produktivitetin. Komunikimi më i shpejtë, ruajtja elektronike dhe mbrojtja e të dhënave janë përparësi që teknologjia informative mund të ketë në ndërmarrjen tuaj. Siguria dhe privatësia e atyre të dhënave ka rëndësi jashtzakonisht të madhe, sidomos në ditët e sotme, ku siguria dhe privatësia mund të cenohen mjaft lehtë.

Tema e marrë në studim është një çështje shumë e rëndësishme për të …

Fraud Detection Using Data-Driven Approach, Arianit Mehana

Theses and Dissertations

The extensive use of internet is continuously drifting businesses to incorporate their services in the online environment. One of the first spectrums to embrace this evolution was the banking sector. In fact, the first known online banking service came in 1980. It was deployed from a community bank located in Knoxville, called the United American Bank. Since then, internet banking has been offering ease and efficiency to costumers in completing their daily banking tasks.

The ever increasing use of internet banking and the large number of online transactions, increased fraudulent behaviour also. As if fraud increase wasn’t enough, the massive …

Përdorimi I Teknikave Të Mësuarit Të Makinave Për Personalizimin E Rrugëve Mësimore Të Studentëve, Burbuqe Beqiraj

Theses and Dissertations

Krijimi i rrugëve mësimore duke u përshtatur në mënyrë dinamike me nevojat individuale të studentëve ka potencialin të luajnë rol të rëndësishëm në procesin mësimor. Prandaj, qëllimi kryesor i punimit është trajtimi i teknikave dhe algoritmeve të ndryshme si pjesë e mësimit të makinave që kanë ndikim në personalizimin e procesit mësimor në aspektin e mësimnxënies varësisht variablave të ndryshme të profilit të studentëve.

Gjithashtu, punimi është fokusuar në krijimin e modelit për personalizimin e rrugëve mësimore. Bazuar në modelin e propozuar është zhvilluar një prototip i cili mundëson personalizimin e procesit mësimor sipas nevojave të secilit student. Ky prototip …

Semi-Supervised Deep Learning With Applications In Surgical Video Analysis And Bioinformatics, Sheng Wang

Computer Science and Engineering Dissertations - Archive

In the current era of big data, deep learning has been the state-of-the-art model for various applications. Image-based applications such as image classification, object detection, image segmentation, benefit most from deep learning networks. One reason for the successful applications of deep learning is that there are a large number of labeled training samples for the model to learn from. People are interested in reducing the cost of getting labeled training samples, and there are various research going on with unsupervised, semi-supervised, and self-supervised deep learning. The cost of health-related data is even higher. Labeling the surgical videos with tools being …

Sl2mf: Predicting Synthetic Lethality In Human Cancers Via Logistic Matrix Factorization, Yong Liu, Min Wu, Chenghao Liu, Xiao-Li Li, Jie Zheng

Student Publications

Synthetic lethality (SL) is a promising concept for novel discovery of anti-cancer drug targets. However, wet-lab experiments for detecting SLs are faced with various challenges, such as high cost, low consistency across platforms, or cell lines. Therefore, computational prediction methods are needed to address these issues. This paper proposes a novel SL prediction method, named $\mathsf{SL}^2 \mathsf{MF}$, which employs logistic matrix factorization to learn latent representations of genes from the observed SL data. The probability that two genes are likely to form SL is modeled by the linear combination of gene latent vectors. As known SL pairs are more trustworthy …

Efficient Network Design For High Dimensional Data, Xin Miao

Computer Science and Engineering Dissertations - Archive

Due to the powerful feature representation capabilities, deep learning has became a powerful tool in the field of computer vision. Especially in the aspect of high-dimensional images, deep learning can achieve fast inference compared with most traditional methods. This paper focuses on how to design an efficient neural network and apply it to two high-dimensional images application, video facial landmarks detections and compressive imaging system. In this first part of this paper, we focus on landmarks detection for video facial images. Existing methods for facial landmarks detection mainly rely on cascaded regression. It is an indirect method and progressively estimates …

Early Detection Of Mild Cognitive Impairment With In-Home Sensors To Monitor Behavior Patterns In Community-Dwelling Senior Citizens In Singapore: Cross-Sectional Feasibility Study, Iris Rawtaer, Rathi Mahendran, Ee Heok Kua, Hwee-Pink Tan, Hwee Xian Tan, Tih-Shih Lee, Tze Pin Ng

Research Collection School Of Computing and Information Systems

Background: Dementia is a global epidemic and incurs substantial burden on the affected families and the health care system. A window of opportunity for intervention is the predementia stage known as mild cognitive impairment (MCI). Individuals often present to services late in the course of their disease and more needs to be done for early detection; sensor technology is a potential method for detection.Objective: The aim of this cross-sectional study was to establish the feasibility and acceptability of utilizing sensors in the homes of senior citizens to detect changes in behaviors unobtrusively.Methods: We recruited 59 community-dwelling seniors (aged >65 years …

Applications Of Digital Remote Sensing To Quantify Glacier Change In Glacier And Mount Rainier National Parks, Brianna Clark

Electronic Theses and Dissertations

Digital remote sensing and geographic information systems were employed in performing area and volume calculations on glacial landscapes. Characteristics of glaciers from two geographic regions, the Intermountain Region (between the Rocky Mountain and Cascade Ranges) and the Pacific Northwest, were estimated for the years 1985, 2000, and 2015. Glacier National Park was studied for the Intermountain Region whereas Mount Rainier National Park was representative of the glaciers in the Pacific Northwest. Within the thirty year period of the study, the glaciers in Glacier National Park decreased in area by 27.5 percent while those on Mount Rainier only decreased by 5.7 …

Heuristics For Sparsest Cut Approximations In Network Flow Applications, Fernando Vilas

Computer Science and Engineering Theses and Dissertations

The Maximum Concurrent Flow Problem (MCFP) is a polynomially bounded problem that has been used over the years in a variety of applications. Sometimes it is used to attempt to find the Sparsest Cut, an NP-hard problem, and other times to find communities in Social Network Analysis (SNA) in its hierarchical formulation, the HMCFP. Though it is polynomially bounded, the MCFP quickly grows in space utilization, rendering it useful on only small problems. When it was defined, only a few hundred nodes could be solved, where a few decades later, graphs of one to two thousand nodes can still be …

A Bio-Inspired Classification System For Cyber-Physical-Human Identity Resolution, Mary Catherine (Kay) Michel

Theses and Dissertations

The Internet has created a need for understanding complex technology and identities today. Cybercrime can take years to solve, and a systematic design may aid in more rapid resolution. Classification of identities involves the arrangement of shared qualities or characteristics known as features set expression, useful for identifying specific types of cybercriminals based on empirical evidence and logic. In order for classification of a cyber identity to be explainable and acceptable to researchers, a holistic systematic approach is beneficial to organize natural and synthetic features of living and non-living organisms into a standardized model. Proven scientific methods in the biology …

Blockchain For Educational Certificate Distribution, Layla Asiri

Theses and Dissertations

There are many authenticity problems associated with paper certificates and diplomas. Besides the increase in the forgery of paper certificates and diplomas, other quality problems regarding paper certificates and diplomas deserve attention too. This study seeks to evaluate how alternative technologies may mitigate concerns for Florida Institute of Technology students and faculty and determine whether they support the adoption of Blockchain technology. In particular, this research aims to investigate the challenges of using Blockchain technology for issuing and verifying academic records, certificates, and diplomas for Florida Institute of Technology students and faculty. Blockchain technology can be difficult for institutions to …

Dfl-Opt : A Daily Fantasy Lineup Optimizer, Francis Aurori

Theses, Dissertations and Culminating Projects

[Background] Daily fantasy sports (DFS) are a variety of fantasy sports where contests take place in a matter of days or hours rather than over a whole season. A disparity exists between skilled professionals and casual participants in the creation of line-ups (i.e. teams) w.r.t their chances of winning in these contests. The purpose of the current project was to create a user-friendly, open source platform (named DFL-Opt) for participants of all skill levels to utilize in the creation of DFS line-ups. In addition, efficacy of the DFL-Opt platform was determined by playing the lineups generated by the DFL-Opt tool …

Secure And Efficient Models For Retrieving Data From Encrypted Databases In Cloud, Sultan Ahmed A Almakdi

Graduate Theses and Dissertations

Recently, database users have begun to use cloud database services to outsource their databases. The reason for this is the high computation speed and the huge storage capacity that cloud owners provide at low prices. However, despite the attractiveness of the cloud computing environment to database users, privacy issues remain a cause for concern for database owners since data access is out of their control. Encryption is the only way of assuaging users’ fears surrounding data privacy, but executing Structured Query Language (SQL) queries over encrypted data is a challenging task, especially if the data are encrypted by a randomized …

Using Continuous Sensor Data To Formalize A Model Of In-Home Activity Patterns, Beiyu Lin, Diane J. Cook, Maureen Schmitter-Edgecombe

Computer Science Faculty Publications

Formal modeling and analysis of human behavior can properly advance disciplines ranging from psychology to economics. The ability to perform such modeling has been limited by a lack of ecologically-valid data collected regarding human daily activity. We propose a formal model of indoor routine behavior based on data from automatically-sensed and recognized activities. A mechanistic description of behavior patterns for identical activity is offered to both investigate behavioral norms with 99 smart homes and compare these norms between subgroups. We identify and model the patterns of human behaviors based on inter-arrival times, the time interval between two successive activities, for …

Tidytouch: An Interactive Visualization Tool For Data Science Education, Jonah E. Devaney

Undergraduate Honors Theses

Accessibility and usability of software define the programs used for both professional and academic activities. While many proprietary tools are easy to grasp, some challenges exist in using more technical resources, such as the statistical programming language R. The creative project tidyTouch is a web application designed to help educate any user in basic R data visualization and transformation using the popular ggplot2 and dplyr packages. Providing point-and-click interactivity to explore potential modifications of graphics for data presentation, the application uses an intuitive interface to make R more accessible to those without programming experience. This project is in a state …

Cyber Security’S Influence On Modern Society, Nicholas Vallarelli

Honors College Theses

The world of cyber security is evolving every day, and cyber-criminals are trying to take advantage of it to gain as much money and power as possible. As the Internet continues to grow, more people around the world join the Internet. The purpose of this is to see how much of an importance cyber security has and how cyber-criminals are able to utilize the cyberworld for their own personal gain. Research has been done on how the cyberworld got where it is today. Additionally, individual research has been done in an effort to learn how to hack. A hack lab …

Shakespeare In The Eighteenth Century: Algorithm For Quotation Identification, Marion Pauline Chiariglione

Graduate Theses and Dissertations

Quoting a borrowed excerpt of text within another literary work was infrequently done prior to the beginning of the eighteenth century. However, quoting other texts, particularly Shakespeare, became quite common after that. Our work develops automatic approaches to identify that trend. Initial work focuses on identifying exact and modified sections of texts taken from works of Shakespeare in novels spanning the eighteenth century. We then introduce a novel approach to identifying modified quotes by adapting the Edit Distance metric, which is character based, to a word based approach. This paper offers an introduction to previous uses of this metric within …

Dynamic Fraud Detection Via Sequential Modeling, Panpan Zheng

Graduate Theses and Dissertations

The impacts of information revolution are omnipresent from life to work. The web services have signicantly changed our living styles in daily life, such as Facebook for communication and Wikipedia for knowledge acquirement. Besides, varieties of information systems, such as data management system and management information system, make us work more eciently. However, it is usually a double-edged sword. With the popularity of web services, relevant security issues are arising, such as fake news on Facebook and vandalism on Wikipedia, which denitely impose severe security threats to OSNs and their legitimate participants. Likewise, oce automation incurs another challenging security issue, …

An Fpga-Based Hardware Accelerator For The Digital Image Correlation Engine, Keaten Stokke

Graduate Theses and Dissertations

The work presented in this thesis was aimed at the development of a hardware accelerator for the Digital Image Correlation engine (DICe) and compare two methods of data access, USB and Ethernet. The original DICe software package was created by Sandia National Laboratories and is written in C++. The software runs on any typical workstation PC and performs image correlation on available frame data produced by a camera. When DICe is introduced to a high volume of frames, the correlation time is on the order of days. The time to process and analyze data with DICe becomes a concern when …