Digital Commons Network^™

Parkinson's Disease Detection Using Deep Learning Approach Based On Wearable Sensor-Based Daily Monitoring, Bahaulddin N. Adday, Khalid Shaker, Ihsan Salman, Hothefa Shaker

Mesopotamian Journal of Artificial Intelligence in Healthcare

Parkinson's disease (PD) is a movement disorder characterized by motor dysfunction commonly bradyphemia, tremor, rigidity, akinesia, or slowness of movement. Noting that motor states can fluctuate in PD the primary aim of this current paper was to differentiate multiple states using wearable sensors in the patients and detection of this PD based on deep learning (CNN). Methodology: In this paper, the researchers recorded the signals of the accelerometer and gyroscope fixed on the wrist of PD in their regular daily functioning after using this dataset collection. The deep learning architecture developed was to optimize a CNN for analyzing the sensor …

The Next Frontier In Computer Science, Trends And Research Opportunities, Mostafa Abdulghafoor Mohammed, Z. T. Al-Qaysi, Tahsien Al-Quraishi

Mesopotamian Journal of Computer Science

No abstract provided.

A Deep Learning Approach For Identifying Malicious Activities In The Industrial Internet Of Things, Mohammed Amin Almaiah, Fuad Ali El-Qirem, Rami Shehab, Khaled Sulieman Momani

Mesopotamian Journal of Computer Science

Data-driven decision-making, real-time connectivity, and automation have transformed industrial operations with the Industrial Internet of Things. However, the integration also introduces substantial cybersecurity vulnerabilities, making IIoT networks a prime target for malicious activities. Cyber threats are evolving and becoming more sophisticated, which makes traditional security mechanisms inadequate. An approach using deep learning to detect malicious activities in IIoT environments is examined. It is investigated whether Deep Feed Forward neural networks, autoencoders, and convolutional neural networks are effective at detecting anomalies and mitigating cyber threats. NSL-KDD and UNSW-NB15 benchmark datasets are used to evaluate the proposed model's accuracy, precision, and detection …

Woa-Covid-19: Whale Optimization Algorithm For Selection Of Multi-Examination Features Based On Covid-19 Infections, Karrar Hameed Abdulkareem, Mazin Abed Mohammed, Zaid Abdi Alkareem Alyasseri, Dawood Zahi Khutar, Osama Ahmad Alomari

Mesopotamian Journal of Computer Science

Since its emergence in late 2019, COVID-19 (Coronavirus Disease 2019) has become one of the most critical global health threats, claiming millions of lives and placing many more at serious risk. The complexity of diagnosing COVID-19 lies in the wide range of clinical and examination features involved, prompting researchers to explore various advanced diagnostic methods. However, one of the main challenges is identifying the most relevant features that can streamline and improve diagnostic accuracy. In this study, we propose a feature selection approach based on the Whale Optimization Algorithm (WOA) to identify key examination indicators associated with COVID-19. We used …

Self-Attention Enhanced Dual Bigru For Arabic Fake News Detection, Baqer M. Merzah, Jafar Razmara, Jaber Karimpour

Mesopotamian Journal of Computer Science

The rapid proliferation of social media platforms has greatly amplified the dissemination of fake news, representing significant obstacles to public trust and evidence-based decision-making, particularly for the Arabic-speaking population. Meeting the challenge of Arabic fake news detection is a problem compounded by the complex morphological nature of the language, as well as limited resources. This study presents a hybrid deep learning framework that integrates two Bidirectional Gated Recurrent Units (BiGRUs) along with an attention mechanism for efficiently detecting misinformation in Arabic news. The method leverages FastText word embeddings for disambiguating the intricate semantics of the Arabic language. The model is …

Diabetes At A Glance: Assessing Ai Strategies For Early Diabetes Detection And Intervention Via A Mobile App, Ayad Hameed Mousa, Ibrahim Oday Alrubaye, Mayameen S. Kadhim, Ahmed Dheyaa Radhi, Mudatheer M. Al-Slivani, Rusul Mansoor Al-Amri, Liaw Geok Pheng

Mesopotamian Journal of Computer Science

Diabetes is a widespread disease worldwide that does not differentiate between children and adults. It also affects the elderly and pregnant women. However, early detection of the disease facilitates its control to avoid the effects resulting from delayed diagnosis. With the emergence of artificial intelligence represented by machine learning techniques and its use in most sectors, accordingly, the adoption of machine learning techniques to help in disease prediction has become a necessity. This study proposes a machine learning algorithm-based approach for diabetes prediction. This study uses three datasets, two of which are private and the other includes the Pima Indians …

Enhancing Routing Efficiency In Vanets By Leveraging 5g To Mitigate Congestion, Yusor Rafid Bahar Al-Mayouf, Omar Adil Mahdi, Heba Hussain Hadi, Suleman Khan, Mazin Abed Mohammed

Mesopotamian Journal of Computer Science

Transportation networks impact millions of people daily. Their efficiency immediately affects travel time, safety, and environmental sustainability. Unfortunately, various issues hinder the expected performance and efficiency of these networks. Traffic congestion is an up-to-date issue in the urban environment. Fuel consumption is high because travel time has increased, which has a passive environmental impact. Extensive research has been conducted to progress the intelligent transportation systems installed on communication networks and information to treat this congestion. However, there is a significant amount of affront residue in combining real-time data, estimation analytics, and 5G abilities effectively. This paper offers a novel routing …

Roi – Enhancing Detection Of Citrus Disease Based On Yolov10, Raya N. Ismail, Armaneesa Naaman Hasoon, Israa Rafaa Abdulqader, Salwa Khalid Abdulateef

Mesopotamian Journal of Computer Science

One of the most important fruit crops in the world is citrus. However, some citrus diseases spread rapidly, which is why early detection at an accurate stage is important for timely intervention. YOLO-based object detection models, such as the latest YOLOv10, where small lesions are difficult to identify among noisy backgrounds, have recently been developed, yet their accuracy tends to degrade. Therefore, we proposed a citrus disease detection model by integrating the region of interest (ROI) for object segmentation with the YOLOv10 model, thus addressing the issues of low detection accuracy and slow inference time. The proposed model was trained …

Colorado River Insights, 2025: Dancing With Deadpool, Colorado River Research Group

Books, Reports, and Studies

No abstract provided.

Booklet, "Fifty Years Of Service To Memphis, 1893-1943," Family Welfare Agency Of Memphis, 1943

Documents

Booklet, "Fifty Years of Service to Memphis, 1893-1943," published by the Family Welfare Agency of Memphis, Inc., illustrated by Mrs. W. H. Reeves, financed by special gifts, 1943.

Pamphlet, "Supplementary List Of Subscribers And Amounts Given To Associated Charities," Memphis, 1917-1918

Documents

Pamphlet, "Supplementary List of Subscribers and Amounts Given to Associated Charities," Memphis, Fiscal Year 1917-1918.

Annual Report, Associated Charities, Memphis, 1916

Documents

Annual Report of the Associated Charities, Memphis, TN. It covers the time period of 1915 September 1 - 1916 October 16.

Annual Report, Associated Charities, Memphis, 1914

Documents

Annual Report of the Associated Charities, Memphis, TN. It covers the time period of 1913 September 1 - 1914 September 1.

Annual Report, Associated Charities, Memphis, 1913

Documents

Annual Report of the Associated Charities, Memphis, TN. It covers the time period of 1912 September 1 - 1913 September 1.

A Structurationally Informed View Of Emergency Medical Services Professionals’ Work-Related Communication And Behaviors While Off Duty, Susan J. Burnett

Electronic Theses & Dissertations (2024 - present)

Work-life interrelationships and boundaries are common areas of study in communication research. While some scholars maintain that the domains of work and personal lives and their boundaries are static and exist in designated times and spaces, others argue that domains are constructed around situated contexts and through the performance of situated activities that not only produce a time and place for the domain but call upon enactment of an identity appropriate for managing the domain and the boundaries around it. The people who work in emergency medical services (EMS), emergency medical services professionals (EMSPs) face special challenges in managing work-life …

Crises, Coloniality, And Energy Transformations In Puerto Rico, Laura Kuhl, Marla Perez-Lugo, Carlos Arriaga Serrano, Cecilio Ortiz Garcia, Ryan Ellis, Jennie C. Stephens

Sociology Faculty Publications

Increased attention to inclusive processes is essential to ensure injustices are not perpetuated during energy transitions. Crises, such as the collapse of the electric grid in Puerto Rico after Hurricane Maria, present the promise of opening windows of opportunity for new ideas and voices to inform the future, but they also create opportunities for powerful interests to reinforce existing power dynamics. While coloniality has been recognized as a barrier to sustainable energy transformations, greater integration of the literature on climate coloniality and sustainability transitions is needed. This chapter analyzes visions of the future of the energy system among diverse constituents …

Gen Y More Black Corporate Directors, Chaz Brooks

Scholarly Articles in Law Reviews & Journals

Corporate diversity has been in the spotlight for decades. Recent efforts have followed years of legal scholarship, arguments on the business rationale for greater diversity, and more recently, the racial unrest during the summer of 2020. Called by some, a “racial reckoning,” the summer of 2020 catalyzed many corporate declarations on the importance of diversity, and more to the point of this article, the necessity of righting the economic disadvantages of Black Americans. This article looks specifically at one intervention by a corporate player following summer 2020, Nasdaq’s volley to increase corporate diversity through required disclosure. This article reviews the …

Fintech And Techno-Solutionism, Hilary J. Allen

Scholarly Articles in Law Reviews & Journals

Silicon Valley-style technological innovation is ill-suited to addressing complex problems like financial inclusion, concentrated market power, and privacy harms, yet promises abound that “fintech” can fix them. This oversimplified reduction of complex structural problems into technological puzzles is known as “techno-solutionism,” and it poses real dangers for public policy. When we start with the tech industry’s favored tools and then ask how to solve complex problems using those tools – rather than starting by defining the problem to be solved – it can distract policymakers from supporting real, structural solutions. Techno-solutionism can also deter policymakers from interrogating the limitations, and …

Experiential Learning Through Simulations In Fully Online Asynchronous Courses: Exploring The Role Of Self-Debriefing, David De Jong, Sara Dexter

Research & Publications

Online preparation of professionals is increasing in higher education, which in educational leadership prepa ration programs raises the need for a means to provide authentic simulations of leadership experiences and help aspirants learn from them. This study presents a content analysis of 826 responses from 59 different school leadership students who, following each of the 14 simulations they experienced, wrote one response in an asynchronous format as a form of self-debriefing. The five themes identified map to the four phases of the experiential learning cycle (Kolb, 1984), suggesting that virtual opportunities to practice leadership in tions may serve as grounding …

Setup And Design Of Growstem At Dsu Year One Summary Report, Richard I. Avery, Tom Halverson, Viki Johnson

Grant Reports

GROWSTEM is a DSU scholarship program funded by the National Science Foundations S-STEM program. The goal of the program is for participating scholars to build a sense of belonging through engagement. The program activities designed to accomplish this goal include faculty mentorship, a summer bridge program, study tables and an undergraduate research seminar.

Evaluating Sms Spam Classification: Human Judgement Vs Machine Learning Models, Gabe Miller

Honors

In the age of artificial intelligence, spam messages have become increasingly widespread and sophisticated. Their rapid evolution is driven by ongoing efforts to filter and block them, prompting spammers to constantly adapt their tactics. Since machine learning algorithms require time and data to retrain and adjust, it becomes essential for humans to step in and help classify messages manually when needed. This layered approach,referred to as defensive-indepth, adds multiple barriers through which spam and smishing messages must pass, reducing the likelihood of them reaching the end user. This case study explores the detection rates of various machine learning algorithms compared …

Opinion Mining On Offshore Wind Energy For Environmental Engineering, Isabele Bittencourt, Aparna S. Varde, Pankaj Lal

School of Computing Faculty Scholarship and Creative Works

Renewable energy sources are vital to help mitigate the effects of climate change, and reducing the carbon dioxide emissions of fossil fuels, e.g. the state of New Jersey has a goal of producing 100% clean energy by 2050. However, the plans for offshore wind energy by the shore of the state still brings much controversy between residents due to the wind farms’ impact on wildlife, coastline, and the people’s view from the beaches. In this context, we perform sentiment analysis on social media data to investigate people’s opinions and concerns regarding offshore wind energy. We adapt 3 machine learning models, …

Inspection Technologies For Construction And Maintenance Of Highway Infrastructure – Review And Analysis, Manideep Tummalapudi, Prem Raj Timilsena

Mineta Transportation Institute

The Federal Highway Administration (FHWA) and state Departments of Transportation (DOTs) seek to provide high quality infrastructure that meets or exceeds the desired quality standards crucial for ensuring safety and efficiency in our nation's transportation systems. Efficient inspection practices—which enable conformance with plans, specifications, and quality standards—are an essential part of this effort. In this digital age, state DOTs are relying on emerging technologies to improve inspection practices. However, there is limited knowledge available regarding various emerging technologies used for highway infrastructure construction and maintenance inspection. This study identifies various emerging technologies that are implemented at the state DOTs and …

Comparative Analysis Of Electrode Encapsulation Reliability: Planar Vs. Thermoformed Interdigitated Neural Electrodes In Biomedical Engineering, Tatum Peyerl

Graduate Theses, Dissertations, and Problem Reports (ETD)

Durable dielectric encapsulation is crucial for the long-term function of implantable neural electrodes; however, the reliability of curved, thermoformed coatings remains underexplored. This study addresses that gap by comparing planar (non-thermoformed) and thermoformed interdigitated neural electrodes (IDEs) encapsulated in Polyimide-2611. Both device types underwent accelerated in vitro aging in phosphate‑buffered saline (PBS) at 67 °C for approximately 91 days, simulating two years of physiological exposure. Post-accelerated aging evaluation included electrochemical impedance spectroscopy (EIS) from 0.1 Hz to 100 kHz to monitor moisture‑induced leakage, and high‑voltage breakdown testing under saline immersion to assess dielectric strength. After aging, all electrodes maintained impedance …

The Effect Of Carrier Type And Material Used On Results Of 1,1,1,2-Tetrafluoroethane Application To Teeth, Jonathon Logan Williams Dds

Graduate Theses, Dissertations, and Problem Reports (ETD)

Introduction: The formulation of a pulpal diagnosis is crucial to prescribe appropriate treatment recommendations for endodontics. The application of a cold stimulus to the tooth’s surface utilizing the refrigerant 1,1,1,2-Tetrafluoroethane (R-134a) is a common way to obtain a pulpal diagnosis. Cotton as a form of applicator is used to absorb the R-134a and create a temperature change in the pulp. There is limited research if there is a better material than cotton to generate this cold response. No studies to date have been found to determine if a sponge as an applicator would generate a more significant cold response than …

Prioritizing Amd Impaired Watersheds For Watershed-Scale Restoration Using Multi-Criteria Decision Analysis, James Nicholas Marino

Graduate Theses, Dissertations, and Problem Reports (ETD)

Acid Mine Drainage (AMD) remains a significant environmental challenge in coal-mining and hard rock regions like West Virginia, degrading water quality and ecosystem health. Traditional site-specific remediation efforts often prove inefficient in addressing AMD at large scale. This study explores watershed-scale restoration as a more effective solution, leveraging centralized treatment facilities and multi-source pollution management. This study will follow Multi-criteria Decision Analysis (MCDA), specifically the Analytical Hierarchy Process (AHP), to develop a structured rubric for grading watersheds. The process involves identifying critical criteria, organizing them into a hierarchy, and generating weights for clusters of criteria through collaboration with decision makers. …

Using Visual Prompts To Analyze Ejection Fraction In Echocardiograms, Kevin Reisch

Graduate Theses, Dissertations, and Problem Reports (ETD)

Left ventricular ejection fraction (LVEF) is a critical biomarker for heart failure, but manual estimation from echocardiograms is time-consuming. Artificial intelligence can be used to accelerate this process, allowing clinicians to focus on other critical tasks. Current methods typically train models from scratch on echocardiogram datasets; however, this approach is limited by the scarcity of large medical imaging datasets, which are expensive and difficult to acquire. We present a transfer learning approach that leverages pretrained models from massive datasets, enabling continuous improvement as foundation models advance. Our method employs visual prompting to generate trainable masks for echocardiogram videos, transforming the …

Academic Agency Within The Curricular Reform Of Gateway Stem Courses: A Faculty Perspective, Katie Beck

Graduate Theses, Dissertations, and Problem Reports (ETD)

The research regarding faculty agency during curricular reform is a burgeoning field within higher education as the faculty perspective within the current research concerning curriculum reform is limited. This study seeks to illuminate the faculty perspective of the curricular reform process of gateway STEM courses and how faculty experienced the reform process through a qualitative case study. The site of the case study is a public four-year institution on the eastern coast of the United States that has undergone and continues to undergo significant academic restructuring. The research utilized a structured survey and semi-structured interviews with seven total participants from …

Reuse Of Calcium Carbonate (Caco3) Recovered From Discarded Carpets As Filler In Fiber-Reinforced Polymer (Frp) Composites, Roshan Devkota

Graduate Theses, Dissertations, and Problem Reports (ETD)

Over four billion pounds of carpet are discarded annually in the United States, making carpet waste a significant environmental concern. Calcium carbonate (CaCo₃) constitutes up to 45% of the mass of most synthetic carpets. Reusing this CaCo₃ as a filler in the rapidly growing fiber-reinforced polymer (FRP) industry, which is projected to reach USD 10.38 billion, presents a low-cost, practical approach to developing a market-based solution to post-consumer carpet waste.

This study investigates the reuse of CaCo₃ recovered from discarded carpet backing as a filler in FRP composites, focusing on its mechanical viability in comparison to virgin CaCo₃. The methodology …

A Review Of Reasoning In Artificial Agents Using Large Language Models, Nagraj Naidu, Omar F. El-Gayar

Research & Publications

The increasing sophistication and the use of large language models (LLMs) in artificial agents highlights the need to investigate their reasoning capabilities and limitations. Understanding these aspects is crucial, given the integral role of reasoning in decision-making processes, which are central to a software or embodied agent. This research paper presents a systematic review of the topic. We review the literature by selecting and analyzing highly cited papers using both PRISMA and snowballing. The gathered literature is categorized using a detailed framework of facets and categories. In the results section, we elaborate on our findings and illustrate the mapping through …