Computer Sciences Commons^™

Efficient String Algorithms With Applications In Bioinformatics, Sahar Hooshmand

Electronic Theses and Dissertations, 2020-2023

The work presented in this dissertation deals with establishing efficient methods for solving some algorithmic problems, which have applications to Bioinformatics. After a short introduction in Chapter 1, an algorithm for genome mappability problem is presented in Chapter 2. Genome mappability is a measure for the approximate repeat structure of the genome with respect to substrings of specific length and a tolerance to define the number of mismatches. The similarity between reads is measured by using the Hamming distance function. Genome mappability is computed for each position in the string and has several applications in designing high-throughput short-read sequencing experiments. …

Learning Context-Sensitive Human Emotions In Categorical And Dimensional Domains, Pooyan Balouchian

Electronic Theses and Dissertations, 2020-2023

Still image emotion recognition (ER) has been receiving increasing attention in recent years due to the tremendous amount of social media content on the Web. Many works offer both categorical and dimensional methods to detect image sentiments, while others focus on extracting the true social signals, such as happiness and anger. Deep learning architectures have delivered great suc- cess, however, their dependency on large-scale datasets labeled with (1) emotion, and (2) valence, arousal and dominance, in categorical and dimensional domains respectively, introduce challenges the community tries to tackle. Emotions offer dissimilar semantics when aroused in different con- texts, however "context-sensitive" …

Improving The Security Of Critical Infrastructure: Metrics, Measurements, And Analysis, Jeman Park

Electronic Theses and Dissertations, 2020-2023

In this work, we propose three important contributions needed in the process of improving the security of the critical infrastructure: metrics, measurement, and analysis. To improve security, metrics are key to ensuring the accuracy of the assessment and evaluation. Measurements are the core of the process of identifying the causality and effectiveness of various behaviors, and accurate measurement with the right assumptions is a cornerstone for accurate analysis. Finally, contextualized analysis essential for understanding measurements. Different results can be derived for the same data according to the analysis method, and it can serve as a basis for understanding and improving …

Decentralized Adaptable Task Allocation For Ongoing Tasks, Vera Kazakova

Electronic Theses and Dissertations, 2020-2023

This thesis extends an existing bio-inspired model for decentralized task allocation and benchmarks it against alternative approaches to assess robustness in dynamic conditions, applicability to domains with ongoing and hierarchical tasks, and scalability to large teams of agents. The work addresses decentralized task allocation of simple non-communicating agents in dynamic environments of multiple tasks. Multi-area patrolling is used as the sample domain: specific number of agents is required to successfully patrol each area on each timestep, indefinitely, until the system's security needs. Agents must individually decide whether to patrol and where (i.e., task availability is not limited by task demand …

Local Alignment Of Frame Of Reference Assignment In English And Swedish Dialogue, Simon Dobnik, John D. Kelleher, Christine Howes

Conference papers

In this paper we examine how people assign, interpret, negotiate and repair the frame of reference (FoR) in online text-based dialogues discussing spatial scenes in English and Swedish. We describe our corpus and data collection which involves a coordination experiment in which dyadic dialogue participants have to identify differences in their picture of a visual scene. As their perspectives of the scene are different, they must coordinate their FoRs in order to complete the task. Results show that participants do not align on a global FoR, but tend to align locally, for sub-portions (or particular conversational games) in the dialogue. …

On The Automorphisms And Isomorphisms Of Mds Matrices And Their Efficient Implementations, Muharrem Tolga Sakalli, Sedat Akleylek, Kemal Akkanat, Vincent Rijmen

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we explicitly define the automorphisms of MDS matrices over the same binary extension field. By extending this idea, we present the isomorphisms between MDS matrices over $\mathbb{F}_{2^{m}}$ and MDS matrices over $\mathbb{F}_{2^{mt}}$, where $t \ge 1$ and $m>1$, which preserves the software implementation properties in view of XOR operations and table lookups of any given MDS matrix over $\mathbb{F}_{2^{m}}$. Then we propose a novel method to obtain distinct functions related to these automorphisms and isomorphisms to be used in generating isomorphic MDS matrices (new MDS matrices in view of implementation properties) using the existing ones. The …

Wideband Patch Array Antenna Using Superstrate Configuration For Future 5gapplications, Sidra Farhat, Farzana Arshad, Yasar Amin, Jonathan Loo

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, four distinct antenna configurations for future-centric 5G applications are proposed. Initially, a single rectangular patch is designed to operate at the frequency of 28 GHz while maintaining a wide operational band. Performance of the antenna is improved by incorporating an array of identical rectangular elements resulting in a higher gain and wider bandwidth. The proposed arrangement consists of three rectangular elements realized using 0.508-mm thick Rogers RT/Duroid 5880 laminate. The bandwidth is further enhanced by increasing the number of radiating elements in the array from three to five. Evolution of the proposed design is concluded by stacking …

Revised Polyhedral Conic Functions Algorithm For Supervised Classification, Gürhan Ceylan, Gürkan Öztürk

Turkish Journal of Electrical Engineering and Computer Sciences

In supervised classification, obtaining nonlinear separating functions from an algorithm is crucial for prediction accuracy. This paper analyzes the polyhedral conic functions (PCF) algorithm that generates nonlinear separating functions by only solving simple subproblems. Then, a revised version of the algorithm is developed that achieves better generalization and fast training while maintaining the simplicity and high prediction accuracy of the original PCF algorithm. This is accomplished by making the following modifications to the subproblem: extension of the objective function with a regularization term, relaxation of a hard constraint set and introduction of a new error term. Experimental results show that …

Multi-Modal Medical Imaging Analysis With Modern Neural Networks, Gongbo Liang

Theses and Dissertations--Computer Science

Medical imaging is an important non-invasive tool for diagnostic and treatment purposes in medical practice. However, interpreting medical images is a time consuming and challenging task. Computer-aided diagnosis (CAD) tools have been used in clinical practice to assist medical practitioners in medical imaging analysis since the 1990s. Most of the current generation of CADs are built on conventional computer vision techniques, such as manually defined feature descriptors. Deep convolutional neural networks (CNNs) provide robust end-to-end methods that can automatically learn feature representations. CNNs are a promising building block of next-generation CADs. However, applying CNNs to medical imaging analysis tasks is …

Analiza E Trafikut Në Rrjete Të Enkriptuara, Faton Bekteshi

Theses and Dissertations

Kjo tezë, është punuar në bashkëpunim me Profesor Selman Haxhijaha MSc dhe Profesor Betan Karahoda PHd dhe është testuar përmes simulatorit të rrjetës GNS3, si dhe në laboratorin e Universitetit për Biznes dhe Teknologji në Prishtinë (http://www.ubt-uni.net/). Objektivi kryesor i kësaj teze, është shfaqja e përparësive dhe mangësive të procesit të analizës së një trafiku të dendur të komunikimit dhe bartjes së të dhënave në rrjetën e enkriptuar, duke analizuar dhe krahasuar disa parametra si ai: i kohës, gabimeve, vonesave dhe mbi të gjitha rëndësisë së sigurisë. Do të krijojmë një topologji të rrjetit të ngjajshëm me organizatën tonë, me …

A Cool Brisk Walk Through Discrete Mathematics, Stephen Davies

Computer Science Articles

A Cool Brisk Walk Through Discrete Mathematics - and its companion site "allthemath" - are completely-and-forever-free-and-open-source educational materials dedicated to the mathematics that budding computer science practitioners actually need to know. They feature the fun and addictive teaching of award-winning lecturer Dr. Stephen Davies of the University of Mary Washington in Fredericksburg, Virginia!

Initiating A Collaborative Cybersecurity Governance Framework At The State Level, Autum C. Pylant

West Chester University Doctoral Projects

Cybersecurity risk is dynamic and rapidly evolving. Today, cyber incidents can significantly impair government operations, erode public confidence, undermine operations of critical infrastructures, and put citizen data and whole industries at risk. Managing these risks to cyber assets must be part of a state’s overall risk management portfolio. To do this successfully, state leaders must have effective cybersecurity governance. To achieve this, governors and state legislatures must ensure that their states have the essential governance mechanisms necessary for understanding and managing cybersecurity risk and for translating awareness about cyber threats into action. This dissertation gives an overview of three different …

Computation And Research In Data Science (Cards) Report - 2020, Computation And Research In Data Science, East Tennessee State University

Computation and Research in Data Science (CaRDS) Board Meeting Minutes

No abstract provided.

Power-Over-Tether Uas Leveraged For Nearly Indefinite Meteorological Data Acquisition In The Platte River Basin, Daniel Rico, Carrick Detweiler, Francisco Munoz-Arriola

School of Computing: Conference and Workshop Papers

The integration of unmanned aerial systems (UASs) has increased in the field of agriculture. These systems can provide data that was previously difficult to obtain to help increase efficiency and production. Typical commercial off the shelf (COTS) UASs have significant limitations in the form of small payloads, and short flight times which inhibit their ability to provide significant quantities of useful data. We present the development of a novel power-over-tether UAS that leverages the physical presence of the tether to integrate sensors at multiple altitudes along the tether. The UAS can acquire data nearly indefinitely to sense atmospheric conditions and …

Special Topics In Natural Language Processing: Mwe Identification, Opinion Question Answering And Summarization, Aishwarya Ashok

Computer Science and Engineering Dissertations - Archive

Natural Language Processing (NLP) is the use of computers for the analysis of text. The approaches used to solve problems in NLP has transitioned from human tagging to statistical methods and currently many of the approaches make use of techniques from Machine Learning (ML) and Artificial Intelligence (AI). Some of the text-based problems in NLP include question answering, summarization, and text-based recommendation systems. The amount of text data that is available is increasing by the day. With the growing size of text data, the research in NLP needs more sophisticated methods than traditional statistical methods. Current day approaches make use …

Creating A Sample Of Off-Color Galaxies Using Big Data Tools, Christopher Becker

Honors Program Theses

This thesis begins an investigation into the presence of off-colored galaxies in the Sloan Digital Sky Survey. Through establishing the emergence and history of Astroinformatics, the thesis introduces the concepts surrounding both off-color galaxies and the Big Data tools helpful in analyzing the data to find them. A discussion of initial implementation methods and revised implementation due to difficulties with previous plans follows. Results are presented, with well in excess of 500,000 candidates for off-color galaxies present in the sample. Conclusions are then drawn regarding such a large sample and the implications this may have on the conventional understanding of …

Machines Finding Injustice, Hannah S. Lacqueur, Ryan W. Copus

Faculty Works

With rising caseloads, review systems are increasingly taxed, stymieing traditional methods of case screening. We propose an automated solution: predictive models of legal decisions can be used to identify and focus review resources on outlier decisions—those decisions that are most likely the product of biases, ideological extremism, unusual moods, and carelessness and thus most at odds with a court’s considered, collective judgment. By using algorithms to find and focus human attention on likely injustices, adjudication systems can largely sidestep the most serious objections to the use of algorithms in the law: that algorithms can embed racial biases, deprive parties of …

Towards A General Solution For Layout Of Visual Goal Models With Actors: Supplemental Material, Yilin Lucy Wang, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper:

"Towards a General Solution for Layout of Visual Goal Models with Actors"

This paper presents early results and lays a foundation for discussion within our GORE community.

Poisoning Attacks On Learning-Based Keystroke Authentication And A Residue Feature Based Defense, Zibo Wang

Doctoral Dissertations

Behavioral biometrics, such as keystroke dynamics, are characterized by relatively large variation in the input samples as compared to physiological biometrics such as fingerprints and iris. Recent advances in machine learning have resulted in behaviorbased pattern learning methods that obviate the effects of variation by mapping the variable behavior patterns to a unique identity with high accuracy. However, it has also exposed the learning systems to attacks that use updating mechanisms in learning by injecting imposter samples to deliberately drift the data to impostors’ patterns. Using the principles of adversarial drift, we develop a class of poisoning attacks, named Frog-Boiling …

A Framework Of Multi-Dimensional And Multi-Scale Modeling With Applications, Zilong Li

Doctoral Dissertations

In this dissertation, a framework for multi-dimensional and multi-scale modeling is proposed. The essential idea is based on oriented space curves, which can be represented as a 3D slender object or 1D step parameters. SMILES and Masks provide functionalities that extend slender objects into branched and other objects. We treat the conversion between 1D, 2D, 3D, and 4D representations as data unification. A mathematical analysis of different methods applied to helices (a special type of space curves) is also provided. Computational implementation utilizes Model-ViewController design principles to integrate data unification with graphical visualizations to create a dashboard. Applications of multi-dimensional …

Study Of The Feasibility Of A Virtual Environment For Home User Cybersecurity, Sean Powell

OUR Journal: ODU Undergraduate Research Journal

This research focuses on the average home computer user’s ability to download, install and manage a virtual machine software program. The findings of this research is to be used as a foundation to the possibility of using a virtual machine software program as another form of defense for the home user’s computer. Virtual machines already have various uses, some in the cybersecurity field; this possibility could add another useful application for the software program. This research is conducted by monitoring volunteers’ ability to download, install, set up, and perform basic instructions on the virtual environment. It was from the volunteers’ …

Evaluating And Improving Child-Directed Automatic Speech Recognition, Eric Booth, Jake Carns, Casey Kennington, Nader Rafla

Computer Science Faculty Publications and Presentations

Speech recognition has seen dramatic improvements in the last decade, though those improvements have focused primarily on adult speech. In this paper, we assess child-directed speech recognition and leverage a transfer learning approach to improve child-directed speech recognition by training the recent DeepSpeech2 model on adult data, then apply additional tuning to varied amounts of child speech data. We evaluate our model using the CMU Kids dataset as well as our own recordings of child-directed prompts. The results from our experiment show that even a small amount of child audio data improves significantly over a baseline of adult-only or child-only …

Predicting Early Indicators Of Cognitive Decline From Verbal Utterances, Swati Padhee, Anurag Illendula, Megan Sadler, Valerie L. Shalin, Tanvi Banerjee, Krishnaprasad Thirunarayan, William Romine

Computer Science and Engineering Faculty Publications

Dementia is a group of irreversible, chronic, and progressive neurodegenerative disorders resulting in impaired memory, communication, and thought processes. In recent years, clinical research advances in brain aging have focused on the earliest clinically detectable stage of incipient dementia, commonly known as mild cognitive impairment (MCI). Currently, these disorders are diagnosed using a manual analysis of neuropsychological examinations. We measure the feasibility of using the linguistic characteristics of verbal utterances elicited during neuropsychological exams of elderly subjects to distinguish between elderly control groups, people with MCI, people diagnosed with possible Alzheimer's disease (AD), and probable AD. We investigated the performance …

Modular Ontology Modeling Meets Upper Ontologies: The Upper Ontology Alignment Tool, Abhilekha Dalal, Cogan Shimizu, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We provide an extension to the Protege-based modular on- tology engineering tool CoModIDE, in order to make it possible for ontol- ogy engineers to adhere to traditional ontology modeling processes based on upper or foundational ontologies. As a bridge between the more re- cently proposed modular ontology modeling approach and more classical ones based on foundational ontologies, it enables a best-of-both worlds approach for ontology engineering.

Hierarchical Anomaly Detection For Time Series Data, Ryan E. Sperl

Browse all Theses and Dissertations

With the rise of Big Data and the Internet of Things, there is an increasing availability of large volumes of real-time streaming data. Unusual occurrences in the underlying system will be reflected in these streams, but any human analysis will quickly become out of date. There is a need for automatic analysis of streaming data capable of identifying these anomalous behaviors as they occur, to give ample time to react. In order to handle many high-velocity data streams, detectors must minimize the processing requirements per value. In this thesis, we have developed a novel anomaly detection method which makes use …

Deep Neural Networks For Sentiment Analysis In Tweets With Emoticons, Mutharasu Narayanaperumal

CCAC Theses and Dissertations

Businesses glean meaningful feedback in regard to products and services from social media posts in order to improve the quality of products and services, as well as to meet customer expectations. Sentiment analysis is increasingly being used to help businesses by assigning positive or negative polarity to such posts. Although methods currently exist to determine the polarity of sentiments, such methods are unreliable when posts contain terms that are not typically part of a standard dictionary used for sentiment analysis, such as slang and informal language. This dissertation has aimed to empirically investigate alternative methods to improve the classification accuracy …

Identifying Physicians’ User Experience (Ux) Pain Points In Using Electronic Health Record (Ehr) Systems, Elizabeth Janelle Arceneaux

CCAC Theses and Dissertations

Healthcare institutions have migrated to online electronic documentation through the means of Electronic Health Record (EHR) systems. Physicians rely on these systems to support their various clinical work processes, such as entering clinical orders, reviewing essential clinical data, and making important medical decisions using reporting analytics. Although EHR systems appear to be useful and have known advantages over paper records, studies suggest there are persistent user interface design problems that may hinder physician productivity. The study focused on the research problem that EHR system designs create productivity problems for physician users who frequently report that system workflows are inefficient and …

A Covid-19 Induced Shift: From Introducing High School Females To Computing Careers To An Assessment Of Technological Readiness Among Stem Teachers, Jareau Almeyda

CCAC Theses and Dissertations

Prior to the global COVID-19 pandemic, this study aimed to explore how exposure to information systems (IS) project management impacts perceptions of computing careers among high school female participants. Given the demand for computing professionals continues to grow, enrollment in some computing disciplines across institutions of higher education have experienced declining enrollments. Studies have shown that one of the reasons high school students do not enroll in computing disciplines is because they perceive computing as difficult, boring, and irrelevant.

As a computing discipline, information systems is focused on developing professionals who are able to integrate technologies into systems that run …

Predictive Accuracy Of Recommender Algorithms, William Blake Noffsinger

CCAC Theses and Dissertations

Recommender systems present a customized list of items based upon user or item characteristics with the objective of reducing a large number of possible choices to a smaller ranked set most likely to appeal to the user. A variety of algorithms for recommender systems have been developed and refined including applications of deep learning neural networks. Recent research reports point to a need to perform carefully controlled experiments to gain insights about the relative accuracy of different recommender algorithms, because studies evaluating different methods have not used a common set of benchmark data sets, baseline models, and evaluation metrics. The …

Building Something With The Raspberry Pi, Richard Kordel

Harrisburg University Presidential Research Grants

In 2017 Ryan Korn and I submitted a grant proposal in the annual Harrisburg University President’s Grant process. Our proposal was to partner with a local high school to install a classroom of 20 Raspberry Pi’s, along with the requisite peripherals. In that classroom students would be challenged to design something that combined programming with physical computing. In our presentation to the school we suggested that this project would give students the opportunity to be “amazing.”

As part of the grant, the top three students would be given scholarships to HU and the top five finalists would all be permitted …