Other Computer Engineering Commons^™

Born-Digital Preservation: The Art Of Archiving Photos With Script And Batch Processing, Rachel S. Evans, Leslie Grove, Sharon Bradley

Articles, Chapters and Online Publications

With our IT department preparing to upgrade the University of Georgia’s Alexander Campbell King Law Library (UGA Law Library) website from Drupal 7 to 8 this fall, a web developer, an archivist, and a librarian teamed up a year ago to make plans for preserving thousands of born-digital images. We wanted to harvest photographs housed only in web-based photo galleries on the law school website and import them into our repository’s collection. The problem? There were five types of online photo galleries, and our current repository did not include appropriate categories for all of the photographs. The solution? Expand our …

Machine Learning Applications In Power Systems, Xinan Wang

Electrical Engineering Theses and Dissertations

Machine learning (ML) applications have seen tremendous adoption in power system research and applications. For instance, supervised/unsupervised learning-based load forecasting and fault detection are classic ML topics that have been well studied. Recently, reinforcement learning-based voltage control, distribution analysis, etc., are also gaining popularity. Compared to conventional mathematical methods, ML methods have the following advantages: (i). better robustness against different system configurations due to its data-driven nature; (ii). better adaption to system uncertainties; (iii). less dependent on the modeling accuracy and validity of assumptions. However, due to the unique physics of the power grid, many problems cannot be directly solved …

A Survey On Exploring Key Performance Indicators, Amira Idrees

Future Computing and Informatics Journal

Key Performance Indicators (KPIs) allows gathering knowledge and exploring the best way to achieve organization goals. Many researchers have provided different ideas for determining KPI's either manually, and semi-automatic, or automatic which is applied in different fields. This work concentrates on providing a survey of different approaches for exploring and predicting key performance indicators (KPIs).

Creation Of Mobile Applications For The Shrines Of Al-Hakim Al-Termizi, Mavlyuda Xodjayeva, Turdali Jumayev, Alimjon Dadamuhamedov, Barno Saydakhmedova

The Light of Islam

We recognize that the sustainable development of tourism has great potential for the development of cultural and humanitarian ties around the world. We emphasize the importance of information technology in tourism, especially in the areas of advertising, marketing, differentiation and specialization of tourism products. In addition, we reaffirm our commitment to pilgrimage tourism for the individual growth of people and the strengthening of basic social norms and national values. The program uses modern programming languages such as Php, Java, C ++. Al-Hakim at-Termizi is one of the most famous places of worship in Uzbekistan, which is also known for its …

Artificial Neural Network To Detect Alzheimer's In Mri Scans, James Alden Poirier, Michael Gary Tuttle

Electrical Engineering

Alzheimer’s Disease ranks (AD) as one of the most common diseases in America. Currently, detecting Alzheimer’s Disease relies upon reported symptoms, however changes in the brain can manifest years or decades before symptoms appear. In recent years, researchers have successfully utilized Artificial Neural Networks (ANN) for a variety of image classification tasks. Here, we train an ANN to detect Alzheimer’s Disease using magnetic resonance imaging (MRI) brain scans. Giving an MRI to both a neural network and a doctor will allow the doctor to be more confident in their answer, as well as double-check their answer with an objective report …

Bootstrapping Massively Multiplayer Online Role Playing Games, Mitchell Miller

Master's Theses

Massively Multiplayer Online Role Playing Games (MMORPGs) are a prominent genre in today's video game industry with the most popular MMORPGs generating billions of dollars in revenue and attracting millions of players. As they have grown, they have become a major target for both technological research and sociological research. In such research, it is nearly impossible to reach the same player scale from any self-made technology or sociological experiments. This greatly limits the amount of control and topics that can be explored. In an effort to make up a lacking or non-existent player-base for custom-made MMORPG research scenarios A.I. agents, …

Conference Roundup: Smart Cataloging - Beginning The Move From Batch Processing To Automated Classification, Rachel S. Evans

Articles, Chapters and Online Publications

This article reviewed the Amigos Online Conference titled “Work Smarter, Not Harder: Innovating Technical Services Workflows” keynote session delivered by Dr. Terry Reese on February 13, 2020. Excerpt:

"As the developer of MarcEdit, a popular metadata suite used widely across the library community, Reese’s current work is focused on the ways in which libraries might leverage semantic web techniques in order to transform legacy library metadata into something new. So many sessions related to using new technologies in libraries or academia, although exciting, are not practical enough to put into everyday use by most librarians. Reese’s keynote, titled Smart Cataloging: …

Reading Robot, Gillian Watts, Andrew Myers, Sabrinna Tan, Taylor Klein, Omeed Djassemi

General Engineering

Presently, there is an insufficient availability of human experts to assist students in reading competency and comprehension. Our team’s goal was to create an improved socially assistive robot for use by therapists, teachers, and parents to help children and adults develop reading skills while they do not have access to specialists. HAPI is a socially assistive robot that we created with the goal of helping students practice their reading comprehension skills. HAPI enables a student to improve their reading skills without an educator present, while enabling educators to review the student's performance remotely. Design constraints included: physical size, weight, duration …

Biometric Identification With Ecg Signals, Connor Lindstrom, Jonathan Wood, Jacob Torchia, Jonathan Lee

Electrical Engineering

This project introduces a new form of biometric identification with an ECG signal with the use of machine learning concepts. The ECG signal makes a good candidate for identification because of its unique characteristics that make it easy to distinguish individuals from one another. A patient who has previously had ECG scans stored in a database before, can be verified using this program. This project has the capability of identifying a person or verifying a person solely using their ECG signal. Utilizing this biometric identification, hospitals would be able to add to the reliability of their identification process. Additionally, companies …

Analysis Of Human Affect And Bug Patterns To Improve Software Quality And Security, Md Rakibul Islam

LSU New Orleans Theses and Dissertations

The impact of software is ever increasing as more and more systems are being software operated. Despite the usefulness of software, many instances software failures have been causing tremendous losses in lives and dollars. Software failures take place because of bugs (i.e., faults) in the software systems. These bugs cause the program to malfunction or crash and expose security vulnerabilities exploitable by malicious hackers.

Studies confirm that software defects and vulnerabilities appear in source code largely due to the human mistakes and errors of the developers. Human performance is impacted by the underlying development process and human affects, such as …

Security Camera Using Raspberry Pi, Tejendra Khatri

Student Academic Conference

No abstract provided.

Predictive Analysis Of Ethanol Prices With Machine Learning, Benjamin Schilling

Student Academic Conference

Overview of a predictive analysis regression developed using machine learning alongside ETL process techniques.

Estimating The Tempo Of Audio Files, Parker Ostertag

Student Academic Conference

On the market today, there exists a multitude of software that allows for the detection and prediction of beats per minute (BPM) contained in audio files. There are both free and monetized versions of these programs, but there is one thing that they all have in common: they are inaccurate. This is simply because the science behind beat detection is unfinished, and may never be. In this project, I decided to use a method of audio peak detection to help me detect the tempo that may exist in any audio file. I started by researching existing programs and the science …

Less-Java, More Type Safety: Type Inference And Static Analysis In Less-Java, Charles D. Hines

Senior Honors Projects, 2020-current

Less-Java is an object-oriented programming language whose primary goal is to help new programmers learn programming. Some of the features of Less-Java that might make it better for beginners are static typing, implicit typing, low verbosity, and built-in support for unit testing. The primary focus of this project is on improving type inference (especially with regards to object-oriented programming) and adding static analysis in the Less-Java compiler.

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

Campuspartner: An Assistive Technology For Pedestrians With Mobility Impairments, Cynthia R. Zastudil

Senior Honors Projects, 2020-current

Route-planning applications such as Google Maps and Apple Maps are used by millions of people each month. However, these mapping applications are optimized for vehicle navigation, and although they provide pedestrian routing, the route customization options aren’t sufficient for pedestrian users, especially those with mobility impairments. CampusPartner is an assistive mobile application that was designed with the purpose of supporting people with mobility impairments in planning and previewing their walking routes. By viewing routes in advance, users can see an overview and detailed information about them as well as turn-by-turn instructions. CampusPartner integrates existing services, GraphHopper, OpenStreetMap, and Mapbox, to …

A Capacitive Sensing Gym Mat For Exercise Classification & Tracking, Adam Goertz

Computer Science and Computer Engineering Undergraduate Honors Theses

Effective monitoring of adherence to at-home exercise programs as prescribed by physiotherapy protocols is essential to promoting effective rehabilitation and therapeutic interventions. Currently physical therapists and other health professionals have no reliable means of tracking patients' progress in or adherence to a prescribed regimen. This project aims to develop a low-cost, privacy-conserving means of monitoring at-home exercise activity using a gym mat equipped with an array of capacitive sensors. The ability of the mat to classify different types of exercises was evaluated using several machine learning models trained on an existing dataset of physiotherapy exercises.

Lexicon Based Approaches To Sentiment Analysis Of Spanish Tweets: A Comparative Study, Jean Roca

Computer Science and Computer Engineering Undergraduate Honors Theses

Sentiment analysis is a natural language processing technique that aims to classify text based on the emotions expressed in them. It is a research area that has been around for almost 20 years and has seen a lot of development. The works presented in this paper attempts to target a less-developed area in sentiment analysis known as multilingual sentiment analysis. More specifically, multilingual sentiment analysis of micro-texts. Using the existing WordNet lexicon and a domain-specific lexicon for a corpus of Spanish tweets, we analyze the effectiveness of these techniques.

Computational Techniques In Medical Image Analysis Application For White Blood Cells Classification., Omar Dekhil

Electronic Theses and Dissertations

White blood cells play important rule in the human body immunity and any change in their count may cause serious diseases. In this study, a system is introduced for white blood cells localization and classification. The dataset used in this study is formed by two components, the first is the annotation dataset that will be used in the localization (364 images), and the second is labeled classes that will be used in the classification (12,444 images). For the localization, two approaches will be discussed, a classical approach and a deep learning based approach. For the classification, 5 different deep learning …

Qlime-A Quadratic Local Interpretable Model-Agnostic Explanation Approach, Steven Bramhall, Hayley Horn, Michael Tieu, Nibhrat Lohia

SMU Data Science Review

In this paper, we introduce a proof of concept that addresses the assumption and limitation of linear local boundaries by Local Interpretable Model-Agnostic Explanations (LIME), a popular technique used to add interpretability and explainability to black box models. LIME is a versatile explainer capable of handling different types of data and models. At the local level, LIME creates a linear relationship for a given prediction through generated sample points to present feature importance. We redefine the linear relationships presented by LIME as quadratic relationships and expand its flexibility in non-linear cases and improve the accuracy of feature interpretations. We coin …