Computer Sciences Commons^™

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, …

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 …

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 …

Creating And Evaluating Dimensional Analysis Software For University Students, Ac Hýbl

Campus Research Month

Most scientific disciplines depend on mathematics to varying degrees. Real-world problems often include quantifiable measurements with units. For example, chemistry, physics, and pharmacology require flawless unit conversions and dimensional homogeneity to obtain acceptable results. Students often choose to ignore units until the end of the problem-solving process, but this introduces errors and robs students of a deep understanding of units. Current tools for teaching dimensional analysis are limited both in scope and accessibility. Unit Playground addresses this issue by providing an interactive interface to experiment with units and their relationships.

A Study Of A Collaborative Task Management Application Built On React Native Using The Basic Ux Framework, Andrei Modiga

Campus Research Month

Many times it can be difficult to accomplish all this is proposed in a meeting. This project aimed to build a simple planner application using React Native that allows groups of people to collaborate and stay organized. The application was built using the BASIC Framework as a guide, and featured a collaboration feature that enabled users to share tasks, projects, and communicate with one another in order to stay coordinated and productive. The user interface was designed for easy use, allowing for quick and efficient task management within a group. The goal of the application was to provide a useful …

Game-Based Learning Activities And Assignments, Samuel Rivera, Siegwart Mayr

Campus Research Month

The Center for Innovation and Research in Computing (CIRC) is creating a web application that uses game-based learning to help students be engaged and collaborate, as an adventure-based quest.

In this research project, the activity module was created for this web application. This module contains assignment creation, completion, and grading. These assignments can be included in the quests and courses. The seamless connection between the activity module and the course module was possible with the Yii framework.

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

Designing An Equity-Centered Framework And Crosswalk For Integrated Elementary Computer Science Curriculum And Instruction, Carla Strickland, Andrea Ramírez-Salgado, Lauren Weisberg, Latoya Chandler, Jeanne Di Domenico, Elizabeth M. Lehman, Maya Israel

Journal of Computer Science Integration

As computer science (CS) education becomes more prevalent in K-12 instruction, it is critical for educators, researchers, and curriculum developers to identify culturally responsive and pedagogically inclusive approaches that can increase participation, access, and feelings of belonging for students from historically marginalized communities. In response, we developed an equity-centered curricular framework and illustrative crosswalk that synchronizes three distinct pedagogical approaches: culturally responsive pedagogy (CRP), Universal Design for Learning (UDL), and project-based learning (PBL). We describe the framework’s theoretical underpinnings and explain how this framework informed the development of an integrated elementary science+CS curricular unit and provide examples of its implementation. …

Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand

LSU Doctoral Dissertations

Mobile applications (apps) constantly demand access to sensitive user information in exchange for more personalized services. These-mostly unjustified-data collection tactics have raised major privacy concerns among mobile app users. Existing research on mobile app privacy aims to identify these concerns, expose apps with malicious data collection practices, assess the quality of apps' privacy policies, and propose automated solutions for privacy leak detection and prevention. However, existing solutions are generic, frequently missing the contextual characteristics of different application domains. To address these limitations, in this dissertation, we study privacy in the app store at a domain level. Our objective is to …

Automatic Assessment Of Oral Reading Fluency From Children's Read Speech In The Filipino Language, Francis Dimzon

Software Technology Dissertations

With the end view of helping the Philippine education system in its literacy initiatives, this study aims to develop methods for automatic assessment of oral reading fluency from children's read speech in the Filipino language. Thus, this study seeks to design methods of automatically extracting and analyzing prosodic features of children's read speech in Filipino. To achieve this, the four-fold set of research activities was conducted to describe an automated oral reading fluency assessment system. It consisted of 1) building a children's Filipino speech corpus, 2) designing methods of extracting and analyzing prosodic features, 3) developing methods of automatically assessing …

Investigating The Use Of Recurrent Neural Networks In Modeling Guitar Distortion Effects, Caleb Koch, Scott Hawley, Andrew Fyfe

[Archive] Belmont University Research Symposium (BURS)

Guitar players have been modifying their guitar tone with audio effects ever since the mid-20th century. Traditionally, these effects have been achieved by passing a guitar signal through a series of electronic circuits which modify the signal to produce the desired audio effect. With advances in computer technology, audio “plugins” have been created to produce audio effects digitally through programming algorithms. More recently, machine learning researchers have been exploring the use of neural networks to replicate and produce audio effects initially created by analog and digital effects units. Recurrent Neural Networks have proven to be exceptional at modeling audio effects …

Interactive Emirate Sign Language E-Dictionary Based On Deep Learning Recognition Models, Ahmed Abdelhadi Abdelhadi

Theses

According to the ministry of community development database in the United Arab Emirates (UAE) about 3065 people with disabilities are hearing disabled (Emirates News Agency - Ministry of Community Development). Hearing-impaired people find it difficult to communicate with the rest of society. They usually need Sign Language (SL) interpreters but as the number of hearing-impaired individuals grows the number of Sign Language interpreters can almost be non-existent. In addition, specialized schools lack a unified Sign Language (SL) dictionary, which can be linked to the Arabic language being of a diglossia nature, hence many dialects of the language co-exist. Moreover, there …

Data-Driven Modeling Of Student Performance In The Time Of Distance Learning, Iman Saad Megdadi

Theses

One of the important aspects that all academic institutions work towards improving is Student Performance. It is obviously the primary indicator of success or failure of institutions. Student performance predictions are vital to instructors and educational decision makers to help, across all levels, tailor learning according to the students’ needs. Therefore, it is essential for Higher Education Institutions to predict student performance in distance learning which has been, and remains, the primary method of learning in some countries due to Corona Virus pandemic. For this reason, this research is going to predetermine a fitting definition of student performance in time …

Defining Safe Training Datasets For Machine Learning Models Using Ontologies, Lynn C. Vonder Haar

Doctoral Dissertations and Master's Theses

Machine Learning (ML) models have been gaining popularity in recent years in a wide variety of domains, including safety-critical domains. While ML models have shown high accuracy in their predictions, they are still considered black boxes, meaning that developers and users do not know how the models make their decisions. While this is simply a nuisance in some domains, in safetycritical domains, this makes ML models difficult to trust. To fully utilize ML models in safetycritical domains, there needs to be a method to improve trust in their safety and accuracy without human experts checking each decision. This research proposes …

Does Deep Learning Improve The Performance Of Duplicate Bug Report Detection? An Empirical Study, Yuan Jiang, Xiaohong Su, Christoph Treude, Chao Shang, Tiantian Wang

Research Collection School Of Computing and Information Systems

Do Deep Learning (DL) techniques actually help to improve the performance of duplicate bug report detection? Prior studies suggest that they do, if the duplicate bug report detection task is treated as a binary classification problem. However, in realistic scenarios, the task is often viewed as a ranking problem, which predicts potential duplicate bug reports by ranking based on similarities with existing historical bug reports. There is little empirical evidence to support that DL can be effectively applied to detect duplicate bug reports in the ranking scenario. Therefore, in this paper, we investigate whether well-known DL-based methods outperform classic information …

Giving Back: Contributions Congruent To Library Dependency Changes In A Software Ecosystem, Supatsara Wattanakriengkrai, Dong Wang, Raula Gaikovina Kula, Christoph Treude, Patanamon Thongtanunam, Takashi Ishio, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

The widespread adoption of third-party libraries for contemporary software development has led to the creation of large inter-dependency networks, where sustainability issues of a single library can have widespread network effects. Maintainers of these libraries are often overworked, relying on the contributions of volunteers to sustain these libraries. To understand these contributions, in this work, we leverage socio-technical techniques to introduce and formalise dependency-contribution congruence (DC congruence) at both ecosystem and library level, i.e., to understand the degree and origins of contributions congruent to dependency changes, analyze whether they contribute to library dormancy (i.e., a lack of activity), and investigate …

Design, Development, And Evaluation Of An Interactive Personalized Social Robot To Monitor And Coach Post-Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermudez I Badia

Research Collection School Of Computing and Information Systems

Socially assistive robots are increasingly being explored to improve the engagement of older adults and people with disability in health and well-being-related exercises. However, even if people have various physical conditions, most prior work on social robot exercise coaching systems has utilized generic, predefined feedback. The deployment of these systems still remains a challenge. In this paper, we present our work of iteratively engaging therapists and post-stroke survivors to design, develop, and evaluate a social robot exercise coaching system for personalized rehabilitation. Through interviews with therapists, we designed how this system interacts with the user and then developed an interactive …

Dsdnet: Toward Single Image Deraining With Self-Paced Curricular Dual Stimulations, Yong Du, Junjie Deng, Yulong Zheng, Junyu Dong, Shengfeng He

Research Collection School Of Computing and Information Systems

A crucial challenge regarding the single image deraining task is to completely remove rain streaks while still preserving explicit image details. Due to the inherent overlapping between rain streaks and background scenes, the texture details could be inevitably lost when clearing rain away from the degraded image, making the two purposes contradictory. Existing deep learning based approaches endeavor to resolve the two issues successively in a cascaded framework or to treat them as independent tasks in a parallel structure. However, none of the models explores a proper interaction between rain distributions and hidden feature responses, which intuitively would provide more …

Making Music Social: Creating A Spotify-Based Social Media Platform, Dalton J. Craven

Senior Theses

DKMS is a new type of social media platform for music lovers and groups of friends. It integrates tightly with Spotify, one of the largest music streaming services in the world. Users of DKMS can see what their friends are listening to, receive recommendations of new songs to listen to, and analyze their several key numerical metrics (happiness, danceability, loudness, and energy) of their top songs.

DKMS was built as part of the year-long Capstone senior design course at the University of South Carolina. A deployed app is visible at https://dkms.vercel.app, and the open-source code is visible at https://github.com/SCCapstone/DKMS.

Code Will Tell: Visual Identification Of Ponzi Schemes On Ethereum, Xiaolin Wen, Kim Siang Yeo, Yong Wang, Ling Cheng, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

Ethereum has become a popular blockchain with smart contracts for investors nowadays. Due to the decentralization and anonymity of Ethereum, Ponzi schemes have been easily deployed and caused significant losses to investors. However, there are still no explainable and effective methods to help investors easily identify Ponzi schemes and validate whether a smart contract is actually a Ponzi scheme. To fill the research gap, we propose PonziLens, a novel visualization approach to help investors achieve early identification of Ponzi schemes by investigating the operation codes of smart contracts. Specifically, we conduct symbolic execution of opcode and extract the control flow …

Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu

Research Collection School Of Computing and Information Systems

Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs such as (on GitHub or Stack Overflow), identifying and localizing the precise code is critical for the software developers. In addition, Deep learning has recently been widely applied to different code-related scenarios, ., vulnerability detection, source code summarization. However, automated deep code search is still challenging since it requires a high-level semantic mapping between code and natural language queries. Most existing deep learning-based approaches for code search rely on the sequential text ., …

How To Find Actionable Static Analysis Warnings: A Case Study With Findbugs, Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies

Research Collection School Of Computing and Information Systems

Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict which static code warnings should ot be ignored, we suggest that analysts need to look deeper into their algorithms to find choices that better improve the particulars of their specific problem. Specifically, we show here that effective predictors of such warnings can be created by methods that ocally adjust the decision boundary (between actionable warnings and others). These methods yield a new high water-mark for recognizing actionable static code warnings. For eight …

Bubbleu: Exploring Augmented Reality Game Design With Uncertain Ai-Based Interaction, Minji Kim, Kyungjin Lee, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Object detection, while being an attractive interaction method for Augmented Reality (AR), is fundamentally error-prone due to the probabilistic nature of the underlying AI models, resulting in sub-optimal user experiences. In this paper, we explore the effect of three game design concepts, Ambiguity, Transparency, and Controllability, to provide better gameplay experiences in AR games that use error-prone object detection-based interaction modalities. First, we developed a base AR pet breeding game, called Bubbleu that uses object detection as a key interaction method. We then implemented three different variants, each according to the three concepts, to investigate the impact of each design …

Ureca – The Research Ethics And Data Protection Online Review Platform Used By The University Of Malta, Joel Azzopardi

The Journal of Electronic Theses and Dissertations

Nowadays, research ethics and data protection are given very high importance, and research organizations, including universities, need to safeguard their level of professionalism and integrity by providing the necessary guidelines. Moreover, they need to ensure that these guidelines are being adhered to by their affiliated researchers, including students. This is needed for protection of the research subjects, researchers, and the organization (university) itself. However, care must be taken so that the research ethics review process is streamlined as much as possible to minimize bureaucracy, as such guidelines would then be viewed as a research barrier. This study describes URECA, the …

Predicting Code Refactoring Via Analyzing The History Of Quality Metrics And Code Anti-Patterns, Sarah Alanqari

College of Computing and Digital Media Dissertations

Code refactoring is the process of improving the internal structure of existing code without altering its functionality. Refactoring can help to reduce technical debt, enhance the quality of the code and make the code easy to evolve. However, the manual identification of the proper code refactoring operations to apply can be time-consuming and not scalable. In this thesis, we propose an approach based on data mining and machine learning techniques to analyze historical data and predict refactoring operations that may occur in a future release of a project. The approach uses a combination of techniques to identify patterns in the …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Conversations With Chatgpt About C Programming: An Ongoing Study, James C. Davis, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

AI (Artificial Intelligence) Generative Models have attracted great attention in recent years. Generative models can be used to create new articles, visual arts, music composition, even computer programs from English specifications. Among all generative models, ChatGPT is becoming one of the most well-known since its public announcement in November 2022. GPT means {\it Generative Pre-trained Transformer}. ChatGPT is an online program that can interact with human users in text formats and is able to answer questions in many topics, including computer programming. Many computer programmers, including students and professionals, are considering the use of ChatGPT as an aid. The quality …

Exploring Methods Used In Face Swapping, Joshua Eklund

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Face swapping involves replacing the face in one image (the target) with a face in a different image (the source) while maintaining the pose and expression of the target face. Previous methods of face swapping required extensive computer power and man hours. As such, new methods are being developed that are quicker, less resource intensive, and more accessible to the non-expert. This paper provides background information on key methods used for face swapping and outlines three recently developed approaches: one based on generative adversarial networks, one based on linear 3D morphable models, and one based on encoder-decoders.

A Unified Approach To Regression Testing For Mobile Apps, Zeinab Saad Abdalla

Electronic Theses and Dissertations

Mobile Applications have been widely used in recent years daily all over the world and are essential in our personal lives and at work. Because Mobile Applications update frequently, it is important that developers perform regression testing to ensure their quality. In addition, the Mobile Applications market has been growing rapidly, allowing anyone to write and publish an application without appropriate validation. A need for regression testing has arisen with the growth of different Mobile Apps and the added functionalities and complexities. In this dissertation, we adapted the FSMWeb [14] approach for selective regression testing to allow for selective regression …

Twitch Trivia Battle Royale: Interactive Entertainment Engineering Game, Noah Tyler Ravetch

Computer Science and Software Engineering

As the world of digital media evolves, so too does the way producers and consumers of entertainment content interact with each other. Live streaming is one such evolution. In this format, one person broadcasts their camera and/or their computer screen to a large audience of viewers in real time. People tuning in can communicate with other viewers and the streamer using the chat feature built-in to the streaming platform.

A new type of entertainment has recently entered the marketplace: interactive entertainment. Concerts are being held virtually in games like Fortnite (Epic Games 2021). TV Shows on Netflix are beginning to …