Digital Commons Network^™

A Phenomenological Study Exploring The Lived Experiences Of First-Generation African American Students To Improve Retention Rates, Jaleesa Porter

College of Graduate Studies: Theses & Dissertations

Colleges and universities play an important role in maintaining high retention rates and getting students from matriculation to graduation. There are several studies related to the reasons and barriers that result in low retention rates. This qualitative study examined how one university in southeast Georgia can improve retention rates among first-generation African American students by enhancing its practices. The findings from this study the revealed lived experiences of college students that resulted in a range of emotions, resources and barriers, and communication. Discussion and implications of the findings provide recommendations for practice and future research.

Principal Perceptions Of Leadership Preparedness To Promote Family Engagement In Urban Title I Elementary Schools, Marcus Kimber

College of Graduate Studies: Theses & Dissertations

This qualitative research examines urban Title I elementary school principals’ perceptions of their family engagement readiness based on university leadership preparation and/or district-level professional development. Based on Epstein's Theory of Overlapping Spheres of Influence, this research examines how educational leaders overcome socioeconomic inequities, trust problems, and communication failures to develop equitable relationships with families. Themes that revealed preparation deficiencies and prospective high-impact family engagement methods emerged from semi-structured interviews and ongoing comparison analysis. Principals value family engagement and recognize its impact on student achievement and school climate, but most feel unprepared to implement systematic, sustainable student engagement strategies. Leadership training …

Experimental Study Of Deformation Behavior For A Novel Elastohydrodynamic Seal For Supercritical Carbon Dioxide Power Cycles, William A. Adams

College of Graduate Studies: Theses & Dissertations

Supercritical carbon dioxide (sCO₂) Brayton cycles are a strong contender for future power generation systems due to their high thermal efficiency and compact nature. Sealing is one of the key challenges presented by such systems that has a direct impact on the system's overall efficiency. This research is the first experimental study to investigate the deformation behavior of an elastohydrodynamic (EHD) seal made from bearing-grade polyether ether ketone (PEEK). A testing apparatus was developed to integrate four strain gauges positioned along the seal to quantify the deformation occurring up to pressures of 13 MPa. Mass flow rate measurements …

Computational Investigation Of Underbody Slant Angle Variation Effect On A Hatchback Vehicle, Nufile Uddin Ahmed

College of Graduate Studies: Theses & Dissertations

Electric Vehicles, despite many advantages over their gasoline-powered counterparts, have the following main challenges towards mass adoption – the charging infrastructure and the range of the vehicle. Among the myriads of factors affecting the range, the coefficient of drag and the required power to overcome it are noteworthy. This study aims to investigate the effect of rear underbody slant angle on a common, simplified hatchback-shaped Electric Vehicle. The rear underbody slant angles (upward) assessed were 0°, 5°, 10°, and 15° and they were subjected to three freestream velocities representative of urban (16 m/s), highway (25 m/s) and interstate (40 m/s) …

Machine Learning For Automated Classification Of Tree Species Based On Color-Texture Fusion, Brandon C. Jones

College of Graduate Studies: Theses & Dissertations

This study aimed to develop robust machine learning tools for the classification of southeastern United States tree species based on bark images, addressing challenges posed by significant intraspecies variation in bark texture and color. The primary objectives included constructing specialized machine learning libraries and classification models, identifying optimal algorithms and parameters to maximize accuracy, and integrating the best-performing texture and color classifiers into a unified system to enhance the overall classification performance. The methodology involved collecting a dataset of 360 field images, extracting hue and saturation histograms for color features, and employing Histogram of Gradients (HOG) and Histogram of Binary …

An Investigative Study Of Thermal Fluid Properties When Introducing Metallic Nanoparticles Through A Heat Exchanging System, Levi P. Mckinney

College of Graduate Studies: Theses & Dissertations

Heat-exchanging systems are essential in applications ranging from automobiles to air-conditioning units, and ongoing improvements aim to enhance efficiency while reducing system size. Conventional coolant upgrades often rely on ethylene glycol, which increases thermal stability and lowers freezing point but reduces water’s inherent heat-transfer capability. Advances in nanotechnology provide an alternative approach: suspending nanoparticles in base fluids can significantly modify thermal properties, with some formulations exhibiting conductivity increases of up to 60%. This thesis examines the thermal and tribological performance of three working fluids—distilled water, a 50:50 water–ethylene glycol mixture, and the same mixture enhanced with Al₂O₃ nanoparticles. Distilled water …

Accelerated Test Method (Atm) For The Evaluation Of External Sulfate And Chloride Attack On Concrete Using Artificial Climate Environment (Ace): An Assessment Of Methodology, Eli Walker

College of Graduate Studies: Theses & Dissertations

This study seeks to investigate a testing methodology that utilizes accelerated testing methods (ATM) in conjunction with nondestructive testing methods (NDT) to assess destructive ion attacks on concrete. Through the testing of concrete samples, the impacts of chloride and sulfate ions on concrete will be tested by subjecting concrete to cyclic testing in an artificial climate environment. Electrical resistivity (ER) and ultrasonic pulse velocity (UPV) testing will evaluate the impact of the accelerated testing on the migration of destructive ions within the pore structure of the tested concrete. Based on this investigation, comparisons between accelerated, non-accelerated, and control samples will …

Evaluating The Effectiveness Of Lidar And Photogrammetry For Inspecting Mse Walls In Bridges, Shakil Ahmed

College of Graduate Studies: Theses & Dissertations

Mechanically Stabilized Earth (MSE) retaining walls are vital components of transportation infrastructure, providing structural support for embankments and bridge approaches. As many walls approach or exceed their design life, concerns regarding long-term stability, settlement, and displacement have increased. Traditional visual inspection remains the most common assessment method; however, it is subjective and often unable to detect subtle geometric changes that may precede structural distress or failure. This study evaluates Terrestrial LiDAR (Light Detection and Ranging) Scanning (TLS) and Close-Range Photogrammetry (CRP) as nondestructive, noncontact alternatives for detecting displacement in MSE retaining walls. Three representative sites were investigated: a Control Wall …

Hybrid Rans-Les Analysis Of Turbulent Flame Under Near Blow-Off Condition In A Multi-Stage Swirl Combustor, Brandon O'Brien

College of Graduate Studies: Theses & Dissertations

Advances in computational resources are making computational fluid dynamics (CFD) increasingly accessible for a variety of engineering applications. However, certain complex problems, such as simulating detailed flame kinetics, remain computationally prohibitive for many users. Developing cost-effective methods to simulate these challenges would greatly benefit applications involving flame dynamics, such as turbine engines or industrial burners. This study investigates the effect of main stage swirler intensity on near lean blow-off characteristics in a multi-staged swirl combustor using Ansys Fluent. The hybrid RANS-LES turbulence model, Stress Blended Eddy Simulation (SBES) coupled with Flamelet Generated Manifold (FGM) combustion model was selected to model …

Carceral Bonds, Tyler E. Dougherty

Lewis & Clark Law Review

Over the past 50 years, the U.S. financed a massive physical and fiscal expansion of prisons via the municipal bond market—with devastating results. This project is the first to shine a light on the role of municipal debt in state-level carceral decision making, spotlighting the ways that the municipal bond market affects states’ capacities to incarcerate.

This Article argues that the two primary controls of states’ use of the carceral bond market—(1) market discipline and (2) states’ fiscal constitutions—are particularly ineffective at limiting states’ spending on prisons. This failure to restrain states’ spending through the carceral bond market enables private …

The Legal Ramifications Of Israel’S Destruction Of Gaza’S Healthcare System, Serene Mistkawi

Lewis & Clark Law Review

This Comment argues that Israel’s attacks on the medical infrastructure of Gaza are a violation of international law because hospitals are protected zones and medical personnel are civilians. To Israel’s response that Hamas is attack-ing from hospitals, thereby rendering them legitimate targets, this Comment presents a number of responses: (1) there is little to no evidence that Hamas is doing this; (2) even if Hamas is doing this, the military gains from attacking hospitals are outweighed by the civilian deaths; (3) even if Hamas is doing this and there is significant military gain from attacking hospitals, the interna-tional rules have …

Enhanced Audio Encryption Scheme: Integrating Blowfish, Hmac-Sha256, And Md5 For Secure Communication, Jenan Ayad, Noor Qaddoori, Hasanain Maytham

Mesopotamian Journal of CyberSecurity

In today's communications, it is vital to protect audio data privacy before and after transfer. This work therefore introduces the enhanced audio encryption scheme (EAES), which employs the most effective techniques of cryptography and processes them to make it impossible for unauthorized persons or programs to access or change the contents of audio files. This method uses RSA to encrypt the Blowfish key, which is used for data encryption, the HMAC-SHA256 algorithm for integrity checks, and the Message-Digest algorithm (MD5) for the checking phase. The performance of the EAES is measured statistically via the MSE, PSNR, and correlation coefficient. For …

Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie

Mesopotamian Journal of CyberSecurity

Securing big data in power plants is an important and fundamental step in the infrastructure of smart cities. In addition, it becomes a barrier if it is not controlled from the beginning. Security must be a combination of fast and robust properties. This research presents a traffic security system (TSS) in a smart city (SC). It is a novel paradigm meant to improve data security and integrity by means of a multilayered method. Advanced fault analysis, dual-stage pseudonymizing, quantum key distribution via the BB84 protocol, and Falcon signatures (FS) are combined in the proposed system. TSS enhances data security by …

Learning Techniques-Based Malware Detection: A Comprehensive Review, Sarah Fouad Ali, Musaab Riyadh Abdulrazzaq, Methaq Talib Gaata

Mesopotamian Journal of CyberSecurity

The rapid proliferation of Internet of Things (IoT) devices has significantly increased the threat landscape, with malwares arising as a critical concern. Advanced learning methods such as machine learning (ML), deep learning (DL), and federated learning (FL) are essential for handling complex IoT data. ML provides tools for pattern identification and detecting anomalies. DL boosts malware detection by automatically extracting features and identifying patterns. FL enables collaborative model training across decentralized devices, ensuring data privacy, which is crucial for diverse IoT systems. This comprehensive review specifically synthesizes ML, DL and FL for malware detection in the IoT environment, highlighting key …

Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi

Mesopotamian Journal of CyberSecurity

In the current digital landscape, information security has become a critical necessity given the escalating frequency and sophistication of cyberattacks across global computing networks. Cryptography is the science and practice of securing information by transforming it into a format that is unreadable or inaccessible to unauthorized parties. The strength of the cryptography algorithm lies in the strength of used encryption key. Recently, the nonlinear behavior of chaotic maps has been utilized as a random source to generate robust key stream bits for cryptographic purposes. The aim of this paper is to introduce an efficient and robust system for generating strong …

Therapeutic Potential Of Brassica Carinata Microgreens Extract In Alleviating Symptoms Of Type 2 Diabetes In Wistar Rats, Lilian Nakakaawa, Ifeoluwa D. Gbala, Joel L. Bargul, Xavier Cheseto, John M. Wesonga

All Peer-Reviewed Publications

Microgreens of Brassica plants have attracted increasing research interest in the management of the prevailing epidemic of Type 2 diabetes mellitus (T2DM) because of their high nutritional value. This study evaluated the antidiabetic effects of Brassica carinata Microgreens Ethanolic Extract (BMEE) in type-2 diabetic rats. For the normoglycemic assay, rats were divided into five groups and received a single oral dose of 100, 250, and 500 mg/kg of BMEE while the control groups received distilled water and Glibenclamide. Fasting blood glucose (FBG) levels were determined on a weekly basis for 28 days in diabetic rats after treatment with BMEE at …

Earth Observations Reveal Impacts Of Climate Variability On Maize Cropping Systems In Sub-Saharan Africa, Adomas Liepa, Michael Thiel, Hannes Taubenböck, Doris Klein, Ingolf Steffan-Dewenter, Marcell K. Peters, Sarah Schönbrodt-Stitt, Insa Otte, Tobias Landmann, Zeyaur R. Khan, Michael Ochieng Obondo, Frank Chidawanyika, Emily A. Martin, Tobias Ullmann

All Peer-Reviewed Publications

In Kenya, climate variability and change threaten smallholder, rainfed farms, with crop failures, yield reductions, and pest infestations. Efficient agroecological strategies, such as Push-Pull intercropping, offer documented benefits including pest control, improved soil fertility, and water conservation compared to traditional maize monocropping. To date, no studies exist comparing traditional maize monocropping and Push-Pull intercropping using earth observation tools over several growing seasons in East Africa. Our research addresses this by harmonizing Landsat 7, 8, 9 with Sentinel-2 remote sensing time series from 2016 to 2023. Phenological metrics of 15 growing seasons are extracted based on a threshold method using the …

Enhancing Intrusion Detection Systems With Adaptive Neuro-Fuzzy Inference Systems, Jitender Sharma, Sonia ., Karan Kumar, Pankaj Jain, Pankaj Jain, Hussein Alkattan

Mesopotamian Journal of CyberSecurity

Network security has become increasingly critical in recent years. Among the various aspects of network security and considering several approaches to network security, intrusion detection systems (IDSs) have gained considerable attention. The prominence of this factor, among other factors of network security, is due to its ability to address the complex and uncertain nature of security breaches. Whenever data flow over the network, precise categorization of normal and malicious data is necessary. Past IDS systems lack precise categorization. Thus, the present study focuses on the use of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier to categorize network instances …

Encrypting Text Messages Via Iris Recognition And Gaze Tracking Technology, Sura Abed Sarab Hussien, Basim Najim Al-Din Abed, Kamaran Adil Ibrahim

Mesopotamian Journal of CyberSecurity

This study explores the integration of eye-tracking technology, specifically the gaze point (GP3) eye tracker, to develop a novel encryption and decryption model that leverages an individual's unique eye patterns as a cryptographic key. This research addresses the critical problem of balancing user-friendly encryption mechanisms with robust security. This study aims to design a gaze-based encryption system that uses the eye's binary matrix as a dynamic encryption key. The methodology involves capturing an eye image, converting it into a binary matrix, and using the extracted matrix to generate a unique iris key (IK) applied to encrypt and decrypt text messages …

A Comprehensive Study Of Energy, Exergy, Exergoeconomic, And Exergoenvironment Analysis Of Combined Cycle Power Plant, Ahmed Sarhan Abdulsitar, Arkan Fawzi Saeed, Hatem Hasan Ismaeel

Babylonian Journal of Mechanical Engineering

One of the most effective ways to generate electricity in the thermal power plant is with a Combined Cycle Power Plant (CCPP), which uses both gas and steam turbines to their full potential. This research employs energy, exergy, exergoeconomic, and exergoenvironmental analyses to assess the CCPP performance. Energy analysis indicates the plant's overall efficiency, while exergy analysis identifies losses due to system irreversibilities and proposes methods for enhancement. Exergoeconomic analysis, which integrates thermodynamic and economic factors, quantifies the financial impact of exergy losses and identifies cost-effective improvement strategies. Reducing emissions of pollutants and greenhouse gases is possible through the use …

Design And Fabrication Of An Integrated Solar Still And Uv/Pasteurization System For Domestic Use, Majid H. Ali, D A. Al-Saadi, V V. Ostrikov

Babylonian Journal of Mechanical Engineering

Water, that miraculous liquid, is the fundamental foundation upon which life on Earth is based. The first human civilizations were founded on water, and wherever water is found, civilization is found. Given the increasing population, rising living standards, and developments that have led to increased water pollution and limited water resources, and given the expected rise in fuel and electricity prices in the future, and to rationalize electricity consumption, the use of solar energy is an effective solution for desalination and sterilization of water.In this research, a solar-powered desalination and sterilization system was designed and manufactured to make water potable. …

Overview Of The Ciciot2023 Dataset For Internet Of Things Intrusion Detection Systems, Wisam Ali Hussein Salman, Chan Huah Yong

Mesopotamian Journal of Big Data

The rapid expansion of the use of the Internet of Things (IoT) has encouraged many attackers to exploit the vulnerabilities in these networks to violate data privacy or disrupt service; they are easy targets due to the diversity of devices within the network, which has led to the loss of unified security standards. intrusion detection system (IDS) play a pivotal role in securing IoT networks by monitoring inbound and outbound traffic to these networks and issuing a security alarm when there is an attack; moreover, they respond directly to these security threats to prevent them from harming the network and …

Coupling A Dual Tree - Complex Wavelet Transform With K-Means To Clustering The Epileptic Seizures In Eeg Signals, Raid Lafta, Rasha Hallem Razzaq

Mesopotamian Journal of Big Data

Electroencephalography (EEG) signals are routinely recorded in clinical settings for the diagnosis of epilepsy, that is, brain electrical disorders, by a neurologist. Nevertheless, both the reliability and safety of GB analysis of EEG parameters are not satisfactory. Therefore, identifying the effectiveness of EEG for diagnosis is a considerable challenge for hospitals. This study was conducted to improve the efficiency of detecting epileptic seizures in EEG signals by combining three methodologies: the double tree complex wavelet transform (DT-CWT), K means clustering, and the ChaCha20 encryption algorithm. EEG segments are initially partitioned into regular segments, each of which is further partitioned into …

A Comparative Study Of Rfid System Performance In Large-Scale Network Planning Facility, Ali Abdulqader Al Qisi, Azli Bin Nawawi, Adel Muhsin Elewe

Mesopotamian Journal of Big Data

Big data in manufacturing fields present several challenges leads to reduce profitability and missed opportunity for innovation. One of the used strategies is the use of radio frequency identification system.  considered a business strategy to increase productivity, speed up decision-making, and enhance production monitoring and control while preserving the structure and integrity of current manufacturing systems. The present research compares five artificial inelegant algorithms based on RFID system in facility layout design to investigate the fitness of each algorithm in manufacturing big data processing. The objective functions have been used are the minimum number of required readers, minimum readers overlap, …

Intelligent Techniques For Autism Spectrum Disorder Diagnosis: A Review, Ekraam Jabier, Ali Fadhil Marhoon, Ammar A. Aldair

Mesopotamian Journal of Big Data

Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose prevalence has increased drastically around the world due to the shortcomings of the traditional method of diagnosis, which has been shown to be unsustainable since it is usually time-consuming, expensive, and subjective to clinical interpretation. These difficulties make finding more scalable, efficient, and objective methods of diagnosis incredibly expedient. This review explores the impacts of intelligent technologies such as artificial intelligence (AI), machine learning (ML), deep learning (DL), and Internet of Things (IoT) sensor-supported systems and the revolution they are bringing into the diagnosis of ASD. This work reviews the recent …

Utilizing Graph Theory Algorithms For The Modeling And Analysis Of Covid-19 Infection Dynamics, Ioannis Adamopoulos, Antonios Valamontes, Niki Syrou, Jovanna Adamopoulou, Antonios Bardavouras

Mesopotamian Journal of Artificial Intelligence in Healthcare

The COVID-19 outbreak has shown how urgently good models are needed to understand and project the dissemination of infectious diseases. Graph theory's excellent basis for presenting and analyzing complex networks helps one to grasp COVID-19 transmission dynamics. This work investigates the simulation and evaluation of the COVID-19 spread using multiple graph theory approaches. We utilize algorithms, including centrality assessments, community detection, and epidemic spreading models, to identify significant transmission channels and viable intervention sites; we also study the usage of network-building strategies to show relationships between individuals and communities. By incorporating real-world data with graph-based models, we demonstrate how these …

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 …