Computer Sciences Commons^™

An Investigation Of Low Frequency Noise In Server Rooms, Ahmed Al Naami

Theses

Noise in a server room can have a major impact on the performance and well-being of the occupants. Sound level and low frequency noise are considered factors that influence the hearing ability of workers. This thesis is an investigation of low-frequency noise in server rooms. We conducted the field study in a server room for a large financial institution. Some employees in this study indicated that they experienced headaches from the noise and requested an analysis of the sound to determine if there were any potential adverse health effects. Attributes of the noise were investigated by evaluating the sound pressure …

Detecting Speakers In Video Footage, Michael Williams

Master's Theses

Facial recognition is a powerful tool for identifying people visually. Yet, when the end goal is more specific than merely identifying the person in a picture problems can arise. Speaker identification is one such task which expects more predictive power out of a facial recognition system than can be provided on its own. Speaker identification is the task of identifying who is speaking in video not simply who is present in the video. This extra requirement introduces numerous false positives into the facial recognition system largely due to one main scenario. The person speaking is not on camera. This paper …

A Literature Review Of Research On The Cosmic Microwave Background, Hayden Webb, Jeremy Evert

Student Research

The objective of this research is to establish a better understanding of the current work available in the field of the Cosmic Microwave Background (CMB).

Our thesis is that, while the current state of research has created a base for the understanding of the CMB, more work is necessary through the use of computer science methods to expand upon the field. Our method of study is a literature review.

Our preliminary work suggests that NASA holds a wealth of information on this topic and has made it freely available to the public. Through our partnership with the OneOklahomaCyberinfrastructure Initiative (OneOCII), …

Collecting And Organizing Far-Left Extremist Data From Unstructured Internet Sources, Eric Perez

UNO Student Research and Creative Activity Fair

Far-left extremism refers to a network of groups who adhere to and take direct action in accordance with one or more of the following ideas: Support for bio-centric diversity, the belief that the earth and animals are in immediate danger, and the view that the government and other parts of society are responsible for this danger and incapable/unwilling to fix the crisis and preserve the American wilderness (Chermak, Freilich, Duran, & Parkin). Far-left extremism groups self-report activities using publicly accessible, online communiqués. These activities include arson, property damage, harassment, sabotage, and theft (Loadenthal). The communiqués are structured like blog posts …

A Capability-Centric Approach To Cyber Risk Assessment And Mitigation, Thomas H. Llansó

Masters Theses & Doctoral Dissertations

Cyber-enabled systems are increasingly ubiquitous and interconnected, showing up in traditional enterprise settings as well as increasingly diverse contexts, including critical infrastructure, avionics, cars, smartphones, home automation, and medical devices. Meanwhile, the impact of cyber attacks against these systems on our missions, business objectives, and personal lives has never been greater. Despite these stakes, the analysis of cyber risk and mitigations to that risk tends to be a subjective, labor-intensive, and costly endeavor, with results that can be as suspect as they are perishable. We identified the following gaps in those risk results: concerns for (1) their repeatability/reproducibility, (2) the …

Rpp Panel Chicago: History Of Cafecs, Lucia Dettori, Dale Reed, Steven Mcgee, Don Yanek, Andrew Rasmussen, Ronald Greenberg

Computer Science: Faculty Publications and Other Works

No abstract provided.

Back Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Contents, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

A Call To Promote Soft Skills In Software Engineering, Luiz Fernando Capretz, Fahem Ahmed

Electrical and Computer Engineering Publications

We have been thinking about other aspects of software engineering for many years; the missing link in engineering software is the soft skills set, essential in the software development process. Although soft skills are among the most important aspects in the creation of software, they are often overlooked by educators and practitioners. One of the main reasons for the oversight is that soft skills are usually related to social and personality factors, i.e., teamwork, motivation, commitment, leadership, multi-culturalism, emotions, interpersonal skills, etc. This editorial is a manifesto declaring the importance of soft skills in software engineering with the intention to …

Automating Data Analysis For Two-Dimensional Gas Chromatography/Time-Of-Flight Mass Spectrometry Non-Targeted Analysis Of Comparative Samples, Ivan A. Titaley, O. Maduka Ogba, Leah Chibwe, Eunha Hoh, Paul H.-Y. Cheong, Staci L. Massey Simonich

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Non-targeted analysis of environmental samples, using comprehensive two‐dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC/ToF-MS), poses significant data analysis challenges due to the large number of possible analytes. Non-targeted data analysis of complex mixtures is prone to human bias and is laborious, particularly for comparative environmental samples such as contaminated soil pre- and post-bioremediation. To address this research bottleneck, we developed OCTpy, a Python™ script that acts as a data reduction filter to automate GC × GC/ToF-MS data analysis from LECO^® ChromaTOF^® software and facilitates selection of analytes of interest based on peak area …

Internet Of Underground Things: Sensing And Communications On The Field For Precision Agriculture, Mehmet C. Vuran, Abdul Salam, Rigoberto Wong, Suat Irmak

School of Computing: Conference and Workshop Papers

The projected increases in World population and need for food have recently motivated adoption of information technology solutions in crop fields within precision agriculture approaches. Internet of underground things (IOUT), which consists of sensors and communication devices, partly or completely buried underground for real-time soil sensing and monitoring, emerge from this need. This new paradigm facilitates seamless integration of underground sensors, machinery, and irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. In this paper, state-of-the-art communication architectures are reviewed, and underlying sensing technology and communication mechanisms for IOUT are presented. Recent advances in the …

Relating Justification Logic Modality And Type Theory In Curry–Howard Fashion, Konstantinos Pouliasis

Dissertations, Theses, and Capstone Projects

This dissertation is a work in the intersection of Justification Logic and Curry--Howard Isomorphism. Justification logic is an umbrella of modal logics of knowledge with explicit evidence. Justification logics have been used to tackle traditional problems in proof theory (in relation to Godel's provability) and philosophy (Gettier examples, Russel's barn paradox). The Curry--Howard Isomorphism or proofs-as-programs is an understanding of logic that places logical studies in conjunction with type theory and -- in current developments -- category theory. The point being that understanding a system as a logic, a typed calculus and, a language of a class of categories constitutes …

Lecture Capture / Flipping / Clickers, Darrell Lutey

UNLV Best Teaching Practices Expo

Student Success – UNLV needs to improve retention

Natural Language, Mixed-Initiative Personal Assistant Agents, Joshua W. Buck, Saverio Perugini, Tam W. Nguyen

Computer Science Faculty Publications

The increasing popularity and use of personal voice assistant technologies, such as Siri and Google Now, is driving and expanding progress toward the long-term and lofty goal of using artificial intelligence to build human-computer dialog systems capable of understanding natural language. While dialog-based systems such as Siri support utterances communicated through natural language, they are limited in the flexibility they afford to the user in interacting with the system and, thus, support primarily action-requesting and information-seeking tasks. Mixed-initiative interaction, on the other hand, is a flexible interaction technique where the user and the system act as equal participants in an …

Chrono: A System For Normalizing Temporal Expressions, Amy L. Olex, Luke G. Maffey, Nicholas Morton, Bridget T. Mcinnes

Computer Science Publications

The Chrono System: Chrono is a hybrid rule-based and machine learning system written in Python and built from the ground up to identify temporal expressions in text and normalizes them into the SCATE schema. Input text is preprocessed using Python’s NLTK package, and is run through each of the four primary modules highlighted here. Note that Chrono does not remove stopwords because they add temporal information and context, and Chrono does not tokenize sentences. Output is an Anafora XML file with annotated SCATE entities. After minor parsing logic adjustments, Chrono has emerged as the top performing system for SemEval 2018 …

Support Vector Machines For Image Spam Analysis, Aneri Chavda, Katerina Potika, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

Email is one of the most common forms of digital communication. Spam is unsolicited bulk email, while image spam consists of spam text embedded inside an image. Image spam is used as a means to evade text-based spam filters, and hence image spam poses a threat to email-based communication. In this research, we analyze image spam detection using support vector machines (SVMs), which we train on a wide variety of image features. We use a linear SVM to quantify the relative importance of the features under consideration. We also develop and analyze a realistic “challenge” dataset that illustrates the limitations …

Expression Of The Microrna-143/145 Cluster Is Decreased In Hepatitis B Virus-Associated Hepatocellular Carcinoma And May Serve As A Biomarker For Tumorigenesis In Patients With Chronic Hepatitis B, Qi Zhao, Xiangfei Sun, Chao Liu, Tao Li, Juan Cui, Chengyong Qin

School of Computing: Faculty Publications

The aims of the present study were to identify the expression profile of microRNA (miR)‑143/145 in hepatitis B virus (HBV)‑associated hepatocellular carcinoma (HCC), explore its association with prognosis and investigate whether the serum miR‑143/145 expression levels may serve as a diagnostic indicator of HBV‑associated HCC. The microRNA (miRNA) chromatin immunoprecipitation dataset was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus databases, and analyzed using the Wilcoxon signed‑rank test. It was observed that the expression of miR‑143 and miR‑145 was decreased 1.5‑fold in HBV‑associated HCC samples compared with non‑tumor tissue in the TCGA and the GSE22058 datasets …

Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang

Journal of the Arkansas Academy of Science

The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.

Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant

Journal of the Arkansas Academy of Science

This paper discusses data pertaining to space missions to astronomical bodies beyond earth. The analyses provide summarizing facts and graphs obtained by mining data about (1) missions launched by all countries that go to the moon and planets, and (2) Earth satellites obtained from a Union of Concerned Scientists (UCS) dataset and lists of publically available satellite data.

Programming: Predicting Student Success Early In Cs1. A Re-Validation And Replication Study, Keith Quille, Susan Bergin

Articles

This paper describes a large, multi-institutional revalidation study conducted in the academic year 2015-16. Six hundred and ninetytwo students participated in this study, from 11 institutions (ten institutions in Ireland and one in Denmark). The primary goal was to validate and further develop an existing computational prediction model called Predict Student Success (PreSS). In doing so, this study addressed a call from the 2015 ITiCSE working group (the second "Grand Challenge"), to "systematically analyse and verify previous studies using data from multiple contexts to tease out tacit factors that contribute to previously observed outcomes". PreSS was developed and validated in …

Glyph Based Segmentation Of Chinese Calligraphy Characters In The "Collected Characters" Stele., David A. Mcinnis

EWU Masters Thesis Collection

Text character segmentation is the process of detecting the bounding box position of individual characters within a written text document image. The character segmentation problem remains extremely difficult for ancient Chinese calligraphy documents. This paper examines a glyph-based segmentation technique for segmenting Chinese Calligraphy characters in the "Collected Characters". The glyph-based character segmentation pipeline utilizes a combination of well-understood image processing techniques in a novel pipeline which is able to detect Chinese calligraphy characters from ink-blots with a good reliability.

A Practical And Efficient Algorithm For The K-Mismatch Shortest Unique Substring Finding Problem, Daniel Robert Allen

EWU Masters Thesis Collection

This thesis revisits the k-mismatch shortest unique substring (SUS) finding problem and demonstrates that a technique recently presented in the context of solving the k-mismatch average common substring problem can be adapted and combined with parts of the existing solution, resulting in a new algorithm which has expected time complexity of O(n log^k n), while maintaining a practical space complexity at O(kn), where n is the string length. When k > 0, which is the hard case, the new proposal significantly improves the any-case O(n²) time complexity of the prior best method for k-mismatch SUS finding. Experimental study …

Old English Character Recognition Using Neural Networks, Sattajit Sutradhar

College of Graduate Studies: Theses & Dissertations

Character recognition has been capturing the interest of researchers since the beginning of the twentieth century. While the Optical Character Recognition for printed material is very robust and widespread nowadays, the recognition of handwritten materials lags behind. In our digital era more and more historical, handwritten documents are digitized and made available to the general public. However, these digital copies of handwritten materials lack the automatic content recognition feature of their printed materials counterparts. We are proposing a practical, accurate, and computationally efficient method for Old English character recognition from manuscript images. Our method relies on a modern machine learning …

Scenario Development For Unmanned Aircraft System Simulation-Based Immersive Experiential Learning, Nickolas D. Macchiarella, Alexander J. Mirot

Journal of Aviation/Aerospace Education & Research

Application of scenario-based training can serve as practical means of educating remote pilots and sensor operators as they seek professional levels of knowledge. Both education and training can build upon time-tested training and simulation methodologies that apply simulators in settings that mirror real-world operations. Embry-Riddle Aeronautical University’s unmanned aircraft system (UAS) program curriculum is rooted in immersive simulation that offers students an experiential learning experience that is aimed to develop higher-order thinking skills. Skills that are critical to professional levels of performance. The degree program builds from basic application skills to critical thinking skills by using immersive scenario-based training in …

Comparing The Usage Of React Native And Ionic, Sam Borick

Williams Honors College, Honors Research Projects

This project will compare two popular programming frameworks for building mobile applications. These frameworks are called ‘cross-platform frameworks’ as they can develop applications on multiple platforms. The scope of this project is to understand the structural reasons for the differences in these frameworks. While this project does speculate on reasons for choosing either framework, this project does not attempt to make a hard recommendation.

In this project, I built two applications, as similar as possible, in React Native and Ionic. I found that there were differences in the goals of these frameworks, lending each of the two better to different …

Grocery List: An Android Application, Daniel Mcfadden

Williams Honors College, Honors Research Projects

Grocery List is an android application that allows the user to save a grocery list to their device for reference at a store as opposed to the traditional pen and paper. Grocery List was created in Android developer, and uses Java and XML to run the application and display different layouts.

Grocery Lists' main purpose is to be an easy to use, flexible listing application that can serve multiple different listing uses such as grocery lists, to do tasks, and even just some simple reminders.

Computational Analysis Of Composite Fiber Diameter, Cailin Simpson

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

A Systematic Approach To Rna-Associated Motif Discovery, Tian Gao, Jiang Shu, Juan Cui

School of Computing: Faculty Publications

Background: Sequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications.

Results: We first perform motif analysis on microRNAs and longer RNA fragments from …

A Comparison Of Information Technology Mediated Customer Services Between The U.S. And China, Suhong Li, Hal Records, Robert Behling

Information Systems and Analytics Department Faculty Journal Articles

Information technology mediated customer service is a reality of the 21st century. More and more companies have moved their customer services from in store and in person to online through computer or mobile devices. Using 442 responses collected from one USA university (234 responses) and two Chinese universities (208 responses), the study investigates customer preferences over two service delivery models (either in store or online) on five types of purchasing (retail, eating-out, banking, travel and entertainment) and their perception difference in customer service quality between those two delivery models in the U.S. and China. The results show that the majority …