Computer Sciences Commons^™

Neutrosophic Mcdm Methodology For Evaluation Onshore Wind For Electricity Generation And Sustainability Ecological, Karam M. Sallam, Ali Wagdy Mohamed

Neutrosophic Systems with Applications

The conviction in the necessity of renewable energy has been prompted by both the constantly increasing need for power production and the ecological issues of recent years. When it comes to generating power in a sustainable manner, wind is among the most essential renewable energy sources. This research attempts to present a structural technique for assessing the performance of operational onshore wind facilities with respect to the three dimensions of sustainability. The energy production, environmental effect, and practicability of onshore wind facilities are all dependent on accurate assessments. Wind resources, site accessibility, environmental impact, permitting and regulatory requirements, turbine technology, …

Inaugural Artificial Intelligence For Public Health Practice (Ai4php) Retreat: Ontario, Canada, Jacqueline K. Kueper, Laura C. Rosella, Richard G. Booth, Brent D. Davis, Sarah Nayani, Maxwell J. Smith, Dan Lizotte

Computer Science Publications

The Artificial Intelligence (AI) for Public Health Practice Retreat was a hybrid event held in October 2022 in London, Ontario to achieve three main goals: 1) Identify both the goals of public health practitioners and the tasks that they undertake as part of their practice to achieve those goals that could be supported by AI, 2) Learn from existing examples and the experience of others about facilitators and barriers to AI for public health, and 3) Support new and strengthen existing connections between public health practitioners and AI researchers. The retreat included a keynote presentation, group brainstorming exercises, breakout group …

Neutrosophic Mcdm Methodology For Evaluation Onshore Wind For Electricity Generation And Sustainability Ecological, Karam M. Sallam, Ali Wagdy Mohamed

Neutrosophic Systems with Applications

The conviction in the necessity of renewable energy has been prompted by both the constantly increasing need for power production and the ecological issues of recent years. When it comes to generating power in a sustainable manner, wind is among the most essential renewable energy sources. This research attempts to present a structural technique for assessing the performance of operational onshore wind facilities with respect to the three dimensions of sustainability. The energy production, environmental effect, and practicability of onshore wind facilities are all dependent on accurate assessments. Wind resources, site accessibility, environmental impact, permitting and regulatory requirements, turbine technology, …

Quantification Of Various Types Of Biases In Large Language Models, Sudhashree Sayenju

Doctor of Data Science and Analytics Dissertations

Natural Language Processing (NLP) systems are included everywhere on the internet from search engines, language translations to more advanced systems like voice assistant and customer service. Since humans are always on the receiving end of NLP technologies, it is very important to analyze whether or not the Large Language Models (LLMs) in use have bias and are therefore unfair. The majority of the research in NLP bias has focused on societal stereotype biases embedded in LLMs. However, our research focuses on all types of biases, namely model class level bias, stereotype bias and domain bias present in LLMs. Model class …

Automated Classification Of Pectinodon Bakkeri Teeth Images Using Machine Learning, Jacob A. Bahn

MS in Computer Science Project Reports

Microfossil dinosaur teeth are studied by paleontologists in order to better under- stand dinosaurs. Currently, tooth classification is a long, manual, error-ridden process. Deep learning offers a solution that allows for an automated way of classifying images of these microfossil teeth. In this thesis, we aimed to use deep learning in order to develop an automated approach for classifying images of Pectinodon bakkeri teeth. The proposed model was trained using a custom topology and it classified the images based on clusters created via K-Means. The model had an accuracy of 71%, a precision of 71%, a recall of 70.5%, and …

Head And Neck Tumor Histopathological Image Representation With Pre- Trained Convolutional Neural Network And Vision Transformer, Ranny Rahaningrum Herdiantoputri, Daisuke Komura, Tohru Ikeda, Shumpei Ishikawa

Journal of Dentistry Indonesia

Image representation via machine learning is an approach to quantitatively represent histopathological images of head and neck tumors for future applications of artificial intelligence-assisted pathological diagnosis systems. Objective: This study compares image representations produced by a pre-trained convolutional neural network (VGG16) to those produced by a vision transformer (ViT-L/14) in terms of the classification performance of head and neck tumors. Methods: W hole-slide images of five oral t umor categories (n = 319 cases) were analyzed. Image patches were created from manually annotated regions at 4096, 2048, and 1024 pixels and rescaled to 256 pixels. Image representations were …

Comparing Igneous Geochemical Data From Hawaii And Southern California Via Machine Learning, Miro Manestar

MS in Computer Science Project Reports

Bi-plots are commonly used in geochemical analyses. However, their use can become cumbersome in the case of multi-variate analyses. Therefore, this thesis explores the application of unsupervised machine learning techniques, specifically PCA and K-Means, to analyze large geochemical data sets from two distinct regions, Hawaii and the \acrfull{prb} in Southern California. The IBM Foundational Methodology for Data Science was utilized to ensure proper data preparation and analysis. PCA provided dimensionality reduction, revealing which features correlated most strongly with variances within the data. K-Means clustering allowed for deeper interpretation of the data. The analysis yielded valuable insights into the composition and …

Instaanalytica, Sapna Maduraimuthu

Masters Projects

This project aims to analyze social media trends using Instagram as the primary source of data extraction and provides insights such as understanding engagement rates, top hashtags, optimal posting times, and post rankings based on engagement rates and sentiment scores thus the users can understand their audience and improve their posting strategies. Firstly, the profile trend chart and area chart based on the average engagement rate is generated to obtain day, week, or month engagement rates. Secondly, text preprocessing is done before generating a word cloud displaying the most frequently occurring words in the captions. The size of each word …

Analyzing And Computing Complete Solution For Dots And Boxes Game, Carl Mcaninch

Undergraduate Theses and Capstone Projects

This thesis improves a process that analyzes all the states of a game of Dots and Boxes. We use retrograde analysis and simulations to create a solution that provides significant performance improvements over our previous best solution. Expanding upon a previous 4x4 solution using rotations, reflections, better optimization, and cloud computing to limit the processing time and gather more data efficiently. We compute a file and the number of states associated with each file and process every state starting with a completely filled board. We optimized the data for cloud computing by running simulations to find the most efficient number …

Co-Designing Assistive Technology With And For Persons Living With Dementia, Dympna O'Sullivan, Jonathan Turner, Siobhan O'Neill, Micheal Wilson, Julie Doyle

Conference papers

Dementia is a chronic and progressive neurodegenerative illness, which can lead to significant difficulties in a person’s capacity to perform activities of daily living (ADLs) and engage in meaningful activities. There is an acute need, which digital health technologies can potentially fulfil, to provide proactive support for persons living with dementia (PLwD) and their caregivers. However, there is limited involvement of PLwD in the design of technology that could be used to support their personal plans for independent living at home. In this paper, we describe how we are employing a co-design methodology to support engagement in an assistive technology …

Blind Fighter – A Video Game For The Visually Impaired, Avery Wayne Harrah

ATU Scholars Symposium

Blind Fighter is a video game made to be playable by anyone, regardless of any visual impairments the player may have. The game relies on auditory queues to allow players to understand what is happening in the game without ever having to see the screen. The project’s goal is to serve as a proof of concept that video games can be made inclusive with a few additions during development, without sacrificing overall quality. To do this, the game features full graphics in addition to testing many strategies for visually impaired players, including direction-based audio, unique sound effects for each game …

Crime Prediction Using Machine Learning: The Case Of The City Of Little Rock, Zurab Sabakhtarishvili, Sijan Panday, Clayton Jensen

ATU Scholars Symposium

Crime is a severe problem in the city of Little Rock, Arkansas. In this study, we aim to develop a machine-learning model to predict criminal activities in the city and provide insights into crime patterns. We will analyze publicly available crime datasets from Little Rock Police Department from January 2017 to March 2023 to identify trends and patterns in crime occurrence. We used data cleaning and exploratory data analysis techniques, such as figured-based visualizations, to prepare the data for machine learning. We will employ the Neural Prophet, a time-series machine learning model, to predict daily crime counts. The model will …

Reworking Of The Arkansas Tech Human Resources Employee Records Software, Dalton J. George, Brayan Bonilla-Chavez, John Modica, Angelina Das

ATU Scholars Symposium

Evisions Argos is a real-time reporting tool used by Arkansas Tech in many record-keeping departments. Reworking HR's software using this tool, security and database access concerns were negated, as Argos is already connected to the University's backend. Using Argos, we have made ATU HR's employee records software more user friendly and built a system that can be pushed to production for use by the university. As a secondary portion to this final project, we developed a proof-of-concept web application using the MEAN (Mongo, Express, Angular, Node) stack. This gave us the opportunity to produce a full-stack application from scratch as …

The Ozark Getaway, Houston Barber, Marcus Gasca, Evan Reece Matlock, Avery Wayne Harrah

ATU Scholars Symposium

Website designed for usage of renting AirBnb houses outside of the original website under the specific owner.

Premium Wireless, Dakota Burkhart, Andrew Clark, Garrett Kenney, Brandon Monroe

ATU Scholars Symposium

Our work implements an inventory system and appointment system for the Premium Wireless phone company. It includes separate views for employees to manage inventory and view appointments for the day and the near future and allows customers to view all current inventory and set an appointment.

Arkavalley Liquor: Simplifying Restaurant Alcohol Orders, Isaiah A. Kitts, Dayton Drilling, Bradlee Treece, Cameron Lumpkin

ATU Scholars Symposium

The ArkaValley Liquor system is a web-based ordering platform designed to simplify the process of ordering alcohol for local restaurants. Currently, restaurants place orders by emailing the store, which makes it difficult to maintain a paper trail and track order details. With the ArkaValley Liquor system, the ordering process is automated, and all order details are saved in one central location. Each restaurant will have a login, ensuring only authorized individuals can place orders. The system will also provide a record of each restaurant's most recent order, making it easy to reorder if necessary. By using the ArkaValley Liquor system, …

Analysis Of Honeypots In Detecting Tactics, Techniques, And Procedure (Ttp) Changes In Threat Actors Based On Source Ip Address, Carson Reynolds, Andy Green

Symposium of Student Scholars

The financial and national security impacts of cybercrime globally are well documented. According to the 2020 FBI Internet Crime Report, financially motivated threat actors committed 86% of reported breaches, resulting in a total loss of approximately $4.1 billion in the United States alone. In order to combat this, our research seeks to determine if threat actors change their tactics, techniques, and procedures (TTPs) based on the geolocation of their target’s IP address. We will construct a honeypot network distributed across multiple continents to collect attack data from geographically separate locations concurrently to answer this research question. We will configure the …

Analysis Impact Of Intrinsic And Extrinsic Motivation On Job Satisfaction In Logistics Service Sector: An Intelligent Neutrosophic Model, Zenat Mohamed, Mahmoud M. Ismail, Amal F. Abd El-Gawad

Neutrosophic Systems with Applications

The success of every company relies heavily on the happiness of its workforce, and the logistics service sector is no exception. The capacity of logistics suppliers to satisfy the demands of their clients depends on the efficiency and efficacy of operations, which in turn is affected by the level of employee satisfaction. This paper aims to analyze the factors of employee satisfaction in the logistic service industry to achieve productivity and a satisfied workforce. This paper used the multi-criteria decision-making (MCDM) methodology to handle various factors. The SWARA method is an MCDM method used to compute the importance of factors. …

Analysis Impact Of Intrinsic And Extrinsic Motivation On Job Satisfaction In Logistics Service Sector: An Intelligent Neutrosophic Model, Zenat Mohamed, Mahmoud M. Ismail, Amal F. Abd El-Gawad

Neutrosophic Systems with Applications

The success of every company relies heavily on the happiness of its workforce, and the logistics service sector is no exception. The capacity of logistics suppliers to satisfy the demands of their clients depends on the efficiency and efficacy of operations, which in turn is affected by the level of employee satisfaction. This paper aims to analyze the factors of employee satisfaction in the logistic service industry to achieve productivity and a satisfied workforce. This paper used the multi-criteria decision-making (MCDM) methodology to handle various factors. The SWARA method is an MCDM method used to compute the importance of factors. …

The Impact Of Virtual Reality On The Healthcare Industry, Peter Sullivan

Honors Projects in Information Systems and Analytics

Virtual reality (VR) took off in 2013 and has touched many public sectors, from gaming, to business, to healthcare. This study looks at virtual reality's impact has affected the healthcare system, with a focus on its use for medical training, patient recovery, patient pain management, and mental health care. A literature review was conducted on the current state of the industry addressing virtual reality's performance in the field, the perception of experts, and an estimation of financial undertakings. Looking at cost analyses brought a fuller approach to the research. Surveying researchers and workers within the realm of healthcare and VR …

From Deep Mutational Mapping Of Allosteric Protein Landscapes To Deep Learning Of Allostery And Hidden Allosteric Sites: Zooming In On “Allosteric Intersection” Of Biochemical And Big Data Approaches, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta, Sian Xiao, Peng Tao

Mathematics, Physics, and Computer Science Faculty Articles and Research

The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric …

Gr-342 Integration Of Blockchain In Computer Networking: Overview, Applications, And Future Perspectives For Software-Defined Networking (Sdn), Network Security And Protocols, Md Jobair Hossain Faruk

C-Day Computing Showcase

The rapid advancement and increasing complexity of computer networks have created a need for robust, secure, and scalable solutions to manage and protect network resources. Blockchain, an emerging distributed ledger technology, offers enhanced security, transparency, and privacy preservation, making it a promising solution for addressing networking challenges. This paper presents a comprehensive survey of blockchain integration in computer networking, focusing on its potential applications, benefits, and future perspectives in Software-defined Networking (SDN), network security, and networking protocols. We identify that blockchain's tamper-proof nature could significantly improve network security by mitigating risks associated with centralized control and single points of failure. …

Ec-371 Planit Crm - Refactoring For The Future, Justin Hall, Oluwaseyi Falaiye, Thomas Anderson, Sai Krupa Bariki Vidura, Samet Yekta Guclu, Ahmet Bugra Dogan

C-Day Computing Showcase

Planit CRM is a Customer Relationship Management (CRM) software that helps in managing and tracking projects, tasks, invoices, quotes, leads, customers, transactions and much more. This software allows anyone to manage leads, create invoices, and start collecting payments seamlessly. The system was developed by Driven Software Solutions under the guidance of Shahzib Sarfraz in 2018. The software has since been used by business owners to allow for easier management of the income and expenses of their operation. It is supported by a team of around fifty developers who maintain the PlanIT CRM software off the site https://planitcrm.com, which can be …

Gr-334 Comparative Evaluation Of Embed Dataset For Mammogram Classification Using Deep Learning Techniques, Nalla Vineela

C-Day Computing Showcase

Breast cancer is a global health concern for women. The detection of breast cancer in its early stages is crucial, and screening mammography serves as a vital leading-edge tool for achieving this goal. In this study, we evaluated the performance of centralized versions of Resnet 50v2 and Resnet 152v2 models for classification of mammograms using different datasets, which were divided by location number extracted from the EMBED dataset. The datasets were preprocessed and used various techniques to improve the performance of the models. The models are trained and evaluated using metrics such as accuracy, area under the curve (AUC), F1 …

The State Of Accessibility In Blackboard: Survey And User Reviews Case Study, Mohamed Wiem Mkaouer, Wajdi Aljedaani, Stephanie Ludi, Mohammed Alkahtani, Marcelo M. Eler, Marouane Kessentini, Ali Ouni

Articles

Context: Nowadays, mobile applications (or apps) have become vital in our daily life, particularly within education. Many institutions increasingly rely on mobile apps to provide access to all their students. However, many education mobile apps remain inaccessible to users with disabilities who need to utilize accessibility features like talkback or screen reader features. Accessibility features have to be considered in mobile apps to foster equity and inclusion in the educational environment allowing to use of such apps without limitations. Gaps in the accessibility to educational systems persist.

Objective: In this paper, we focus on the accessibility of the Blackboard mobile …

The Impact Of Artificial Intelligence On The Cybersecurity Industry, Lindsey Shearstone

Honors Projects in Information Systems and Analytics

As our world becomes more digitalized, cyber criminals have an increasing landscape to launch their attacks. Developments in Artificial Intelligence are being used both to attack and defend networks, therefore, what is the next step for cybersecurity companies when it comes to beating these criminals? A study was conducted that utilizes previous literature sources written on the topic of Artificial Intelligence (AI) in the cybersecurity industry. In addition, the insights of professionals in the industry today are included through a survey and interviews to dive into the details of this battle and what lays in its future. The purpose of …

Code Generation Based On Inference And Controlled Natural Language Input, Howard R. Dittmer

College of Computing and Digital Media Dissertations

Over time the level of abstraction embodied in programming languages has continued to grow. Paradoxically, most programming languages still require programmers to conform to the language's rigid constructs. These constructs have been implemented in the name of efficiency for the computer. However, the continual increase in computing power allows us to consider techniques not so limited. To this end, we have created CABERNET, a Controlled Natural Language (CNL) based approach to program creation. CABERNET allows programmers to use a simple outline-based syntax. This syntax enables increased programmer efficiency.

CNLs have previously been used to document requirements. We have taken this …

Visual Art In The Age Of Ai, Roshnica Gurung

Cybersecurity Undergraduate Research Showcase

Artists and researchers have been deeply interested in using AI programs that generate art for quite some time now. As a result, there have been many advancements in making AI more accessible and easier to use for the public. This is because AI is not just for business anymore. Nowadays an individual without a college degree with even the slightest interest in art can go on a website like Stable Diffusion and create an artistic image using a text prompt in a quick couple minutes. The only limit is your imagination- and your internet’s stability. This accessibility was a huge …

A Study Of The Collection And Sharing Of Student Data With Virginia Universities, Titus Voell

Cybersecurity Undergraduate Research Showcase

Data collection is a vital component in any organization in regards to keeping track of user activity, gaining statistics and improving the user experience, and user identification. While the underlying basis of data collection is understandable, the use of this data has to be closely regulated and documented. In many cases, the VCDPA (Virginia Consumer Data Protection Act) outlines the guidelines for data use, data controller responsibilities, and limitations however nonprofit organizations are exempt from compliance. Colleges and universities, although still held to some degree of limitation, range in permissiveness with what data they choose to collect and retain but …

In-Vitro Validated Methods For Encoding Digital Data In Deoxyribonucleic Acid (Dna), Golam Md Mortuza, Jorge Guerrero, Shoshanna Llewellyn, Michael D. Tobiason, George D. Dickinson, William L. Hughes, Reza Zadegan, Tim Andersen

Computer Science Faculty Publications and Presentations

Deoxyribonucleic acid (DNA) is emerging as an alternative archival memory technology. Recent advancements in DNA synthesis and sequencing have both increased the capacity and decreased the cost of storing information in de novo synthesized DNA pools. In this survey, we review methods for translating digital data to and/or from DNA molecules. An emphasis is placed on methods which have been validated by storing and retrieving real-world data via in-vitro experiments.