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Solvability Of Self Reference Functional Integro-Differential Equation With Nonlocal Initial Condition, A.A. Darwish, M.A. Seddeek, Reda Gamal Ahmed, Ahmed A. El-Deeb, Moataz Ashraf Mohamed, Hossam A. Ghany

Trends in advanced sciences and technology

We present in this paper a new type of self-reference functional integro-differential equation with a nonlocal initial condition. Also, we present a nonlocal problem of the functional integro-differential equation with the infinite point boundary condition for more generalization. An integral representation equivalent to the functional integro-differential equation is obtained to use the theorems needed for proving the existence, and uniqueness. Then we prove the continuous dependence of the solution on the nonlocal parameter and the initial data of the equation. To prove the existence of the solution of the equation we present the Schauder fixed point theorem for both finite …

Analysis Of Second-Order Dynamic Coefficients For Herringbone Grooved Hydrodynamic Thrust Bearings Considering Misalignment, Elsayed K. Elsayed, Tamer.A. El-Sayed, Hussein Sayed

Trends in advanced sciences and technology

A herringbone grooved hydrodynamic thrust bearing is a specialized type of bearing designed to support axial loads in rotating machinery. It is commonly used in turbines, compressors, and pumps. It utilizes a hydrodynamic lubrication mechanism to reduce friction and wear between the rotating and stationary parts. In this paper, a second order dynamic analysis for the herringbone grooved thrust bearing based on the finite perturbation abroach is performed. The Reynolds equation, expressed in polar coordinates, was differentiated to analyze small perturbations from the equilibrium state. This process yielded the first order and then the second-order equations describing these perturbations. Reynold's …

Modeling Earthquake Catalog (1985-2022) In Northern Egypt Using Space-Time Epidemic-Type Aftershock Sequences (Etas), Mariam Ramadan, Amir Ismail, Amin E. Khalil, Hesham Abdelhafiez, Nouran S. Salama

Trends in advanced sciences and technology

Earthquakes have the largest damaging effects among natural disasters on a global scale. Efforts for reducing their effects have taken place for a long time. The prediction of earthquakes was the main target, however the studies conducted were not successful. As a replacement, seismic hazard assessments were adopted to predict the levels of ground motion for the possible future large earthquakes. This approach is probabilistic in nature that rely on the quality of earthquake catalog. The probabilistic model adopted is built on the assumption that the events in the earthquake catalog are random Poisson distribution, assuming that events are independent …

Experimental Process Analysis For Improved Micro-Drilling Quality Of Austenitic Stainless Steel Aisi304, Osama Ali, Ahmed Elkaseer, Azza Barakat, Ahmed Sobhi

Trends in advanced sciences and technology

Austenitic stainless steel AISI304, known for its outstanding mechanical, physical properties, and biocompatibility, is a preferred material for diverse applications. Its hard-to-machine nature presents challenges such as rapid tool wear and poor thermal conductivity, affecting machining quality. This study takes a deep look at the micro drilling of such challenging gap of AISI 304 with 0.8 mm tungsten carbide micro drills, focusing on how key process parameters; linear cutting speed, feed per tooth, and cutting length affect maximum exit burr height and roundness through interaction effects among these factors to identify better drilling conditions with better responses. Utilizing a factorial …

Choral Students’ Perception Of Kinesthetic Pedagogy In The High School Choral Classroom, Molly Bolewski

University of the Pacific Theses and Dissertations

This study examines the incorporation of kinesthetic pedagogy in secondary choral rehearsals and its impact on student engagement and learning. Three experienced high school choral teachers and their students from Northern California participated in the study. Each teacher conducted four consecutive rehearsal sessions, recording themselves instructing on two pieces of music using teacher-modeled and student-imitated kinesthetic gestures. Students completed daily surveys assessing their enjoyment and engagement levels, and teachers provided a final reflection on their usual kinesthetic practices. Video footage of twelve rehearsals and teachers’ final reflections were analyzed to identify patterns in kinesthetic usage, revealing that these teachers’ kinesthetic …

Rocketship Education: An Exploratory Public Policy Case Study, Vladimir Gresham Ivanovic

Dissertations

This dissertation is an exploratory case study of the finances of the Rocketship charter school chain, especially those related to real estate. Rocketship is a not-for-profit charter management organization, one of the first in Santa Clara County, California. This study seeks to determine if the financial transactions related to Rocketship charter schools yield profits for investors, despite Rocketship itself being a non-profit entity, and if they do, how and where do they do so. In order to characterize fairly and completely the profits of Rocketship Education itself and Rocketship-related entities, this study uses publicly available documents to track money flowing …

In Their Words: Voices Of High School Graduates Who Were Labeled English Learners, Yolanda K. Jimenez

Dissertations

This research captures the experiences of high school graduates who were labeled English Learners while they were enrolled in a public high school in the greater Sacramento area of California. The study examined what these bilingual high school graduates report as beneficial and detrimental experiences faced while completing the course requirements for high school graduation. This study builds on research that includes secondary classroom teachers and their perceptions of English Learners, classroom teaching and learning, and experiences of emergent bilingual students. The study expands the body of research and informs praxis pertaining to supporting emergent bilingual students as they attempt …

On The Use Of The Local Reflection Coefficient To Assess The Diffuse Field Sound Absorption Coefficient Of A Porous Material, Franck Sgard, Noureddine Atalla, Olivier Robin

Études primaires

The diffuse field sound absorption coefficient (SAC) of a sound absorber can be obtained from an average over the incidence angles of the oblique incidence plane wave SAC. The plane wave SAC can be derived from the plane wave complex-valued reflection coefficient defined as the ratio of the reflected sound pressure at a given point on the material surface to the incident sound pressure at the same point. In practice, the material is excited by a monopole, and the reflection coefficient becomes a local quantity which is a function of the source height and the radial distance from the source. …

New Recruitment Approach Based On Logistic Regression Model, Ishraq Hatif Abd Almajed, Ghalia Nassreddine, Joumana Younis

Mesopotamian Journal of Computer Science

Artificial intelligence (AI) is a pivotal technological advancement developed by humans with the aim of enhancing the quality of human existence.  It signifies the capacity of a computerized machine resembling a robot to execute tasks typically performed by humans and replicate human behavior. Machine learning (ML), a subfield of AI, involves the construction of systems that acquire the ability to make predictions about new output values by leveraging existing data, without the need for human interaction. Currently, ML has been incorporated into various fields, including but not limited to medical diagnosis, image processing, prediction, classification, learning association, commerce, finance, and …

Examining Ghana's National Health Insurance Act, 2003 (Act 650) To Improve Accessibility Of Artificial Intelligence Therapies And Address Compensation Issues In Cases Of Medical Negligence, George Benneh Mensah, Maad M. Mijwil, Mostafa Abotaleb

Mesopotamian Journal of Computer Science

Objective: Examine Ghana’s National Health Insurance Act (Act 650) to identify coverage gaps limiting artificial intelligence (AI) therapy access and address medical negligence liability issues surrounding automated healthcare systems. Methods: Legal and regulatory analysis of Act 650 were conducted, review of academic literature on global uptake of AI interventions and medical negligence principles were elucidated, examination of case studies implementing pilot AI therapy programs under insurance schemes were considered. Results & Conclusions: Act 650 lacks clear provisions for funding innovative AI treatments with proven efficacy and undefined negligence determination guidelines involving AI systems, contributing to accessibility and accountability issues. Proposed …

A Comparative Study Of Chest Radiographs And Detection Of The Covid 19 Virus Using Machine Learning Algorithm, Shaimaa Q. Sabri, Jahwar Y. Arif, Ghada A. Taqa, Ahmet Çınar

Mesopotamian Journal of Computer Science

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak that is causing coronavirus disease 2019 is being deemed a pandemic because of its quick spread around the globe.  Because chest X-ray pictures have shown to be beneficial in monitoring a variety of lung disorders, they have recently been utilized to monitor COVID-19 disease. It takes time to manually analyze a lot of chest X-ray pictures. Several previous studies have suggested machine-learning (ML)-based techniques for COVID-19 detection from chest X-ray pictures as a solution to this issue. Though little effort has been made to use traditional machine learning (ML) methods, the …

Advanced Image Processing Techniques For Automated Detection Of Healthy And Infected Leaves In Agricultural Systems, E.D. Kanmani Ruby, G. Amirthayogam, G. Sasi, T. Chitra, Abhishek Choubey, S. Gopalakrishnan

Mesopotamian Journal of Computer Science

Advances in computer vision and machine learning have transformed leaf disease detection by enabling efficient and accurate identification of subtle disease signs in leaves. Leveraging high-resolution imaging, pattern recognition algorithms, and deep learning models, researchers and farmers can now conduct automated detection across various plant species. The development focuses on sophisticated image processing techniques applied to diverse datasets captured under controlled conditions, ensuring comprehensive coverage of lighting, time, and weather variations. Expert annotation of infection stages and types enhances dataset reliability, while pre-processing stages such as resizing and normalization optimize image consistency for robust model training. Data augmentation techniques enrich …

Introduction To Wi-Fi 7: A Review Of History, Applications, Challenges, Economical Impact And Research Development, Sallar Salam Murad, Rozin Badeel, Banan Badeel Abdal, Tasmeea Rahman, Tahsien Al-Quraishi

Mesopotamian Journal of Computer Science

Wi-Fi 7, commonly referred to as IEEE 802.11be, is the most recent development in wireless communication technology. It provides significant improvements in terms of speed, capacity, and efficiency. The purpose of this study is to investigate Wi-Fi 7, a standard for wireless communication technology, with a particular focus on the technological advancements and security issues associated with it. In addition, it offers historical perspectives and investigates the institution's present capabilities as well as its potential for the future. The purpose of this study is to provide a complete examination of the development of Wi-Fi technology and its influence on a …

Deep Learning Model For Hand Movement Rehabilitation, Reem D. Ismail, Qabas A. Hameed, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Fatimah N. Ameen

Mesopotamian Journal of Computer Science

Electroencephalography (EEG) can control machines for human purposes, especially for disabled people doing rehabilitation exercises or regular tasks. Brain-computer interface (BCI) for Robotic hand uses deep learning to convert (EEG) brain activity into orders for robotic hand allowing users to move their hands right or left by the movement imagining. It could enable paralyzed individuals to perform basic hand movements and help in rehabilitation robots that help stroke patients regain hand function by offering guided exercises based on machine learning interpretations of their movements and intents. Artificial intelligence algorithms, particularly deep learning, classify and recognize patterns and intents implicit brainwaves …

Potato Disease Identification Using Transfer Learning Approaches, Tarza Hasan Abdullah

Mesopotamian Journal of Computer Science

Potato crop is one of the prominent consumed foods by human beings. When potato crops are infected by diseases it affects farmers negatively and to run in a loss. Therefore, early detection of the potato crop disease can play a vital role in minimizing the loss of the farmers. Nowadays, artificial intelligence technologies, more specifically deep learning techniques, provide solutions to many crops disease-related problems. However, training deep learning models requires a high computational power and huge amount of data as they are data hungry models. Also, designing a custom CNN models a difficult task and there are some variations …

Enhancing Motion Detection In Video Surveillance Systems Using The Three-Frame Difference Algorithm, Suhaib Qassem Yahya Al-Hashemi, Majid Salal Naghmash, Ahmad Ghandour

Mesopotamian Journal of Computer Science

This paper outlines a methodology for motion detection in video surveillance systems, leveraging advanced algorithms and TCP/IP networks for real-time data acquisition and analysis. The primary focus is on the implementation of the Three-Frame Difference Algorithm, which detects moving targets by analyzing the differences between three consecutive video frames. This method significantly reduces redundant data transmission and storage, addressing the challenges posed by limited wireless network capabilities. The surveillance model, designed in MATLAB using SIMULINK, integrates computer vision systems with embedded coders to facilitate effective communication and processing of video data. The results demonstrate the system's capability to detect motion …

Credit Card Fraud Detection Based On Deep Learning Models, El-Sayed M. El-Kenawy, Ahmed Mohamed Zaki, Wei Hong Lim, Abdelhameed Ibrahim, Marwa M. Eid, Ahmed Osman Osman, Ahmed M. Elshewey

Mesopotamian Journal of Computer Science

Credit card fraud detection (FD) protects consumers and financial institutions by identifying suspicious or unauthorized transactions. To improve security and reduce false positives, fraud detection systems can analyze transaction data patterns in real time using advanced machine learning (ML) and deep learning (DL). This paper exploits DL models to detects transactional data which includes anomalies through Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) to verify data and mitigate fraud. The models used precision, recall, F1-score, and AUC on a balanced shared 559856-record Kaggle repository dataset. The RNN model detected anomalies with 99.39% accuracy, 0.9939 …

The Efficiency Impact Of Gershgorin Circle Theorem For Feature Extraction In Computer Vision And Biomedical Signal Analysis, Sahaj Anilbhai Patel

All ETDs from UAB

In graph theory, a fundamental problem arises when signals or images are transformed into graphs where they are subsequently represented in the form of matrices, typically as Adjacency or Laplacian matrices. As the number of the samples increases, the dimensionality of these matrices also increases, leading to the "curse of dimensionality." This increase in dimensionality poses significant computational challenges, particularly in biomedical signal analysis or computer vision applications, where the computational efficiency of large-scale data is crucial. Traditional methods of feature extraction and then clustering become computationally intensive and less effective in handling of high-dimensional data, underscoring the need for …

Fundamentals Of Vehicle Modeling For Mobility And Maneuver, Jordan Whitson

All ETDs from UAB

The direction of research for off-road ground vehicles is an ever-growing interdisciplinary field. The strategies and modeling methods range from simple terramechanics mathematical models to complex terramechanics that involve the use of high-performance computing (HPC) systems with varying vehicle metric and performance analysis and information extraction. Current advanced methods based on terrain properties and dynamic models utilize conventional performance metrics that have been supported through decades of research. As automated driving systems (ADS) and unmanned ground vehicles (UGVs) research and development progress, more complexities are unraveled and present the need for novel directions of research. Whereas on-road vehicles have the …

Associations Between Grit, Life Satisfaction, And Academic Outcomes In Elementary And Middle School Students, Charles Jaylon Williams

All ETDs from UAB

Grit is used to predict various positive benefits within students. Grit is trying to get back up to attempt another try at one’s goal after failure. Recently, grit has been seen as a potential candidate in improving the life satisfaction and academic performance of individuals. Grit is conceptualized as having two components, perseverance of effort and consistency of interest. Perseverance of effort is trying again until you finally accomplish your goal, while consistency of interest is a constant drive to complete one’s goals over a long-time span. This study measured the effects that grit has on elementary and middle school …

Entity Information Extraction And Normalization From Scientific And Clinical Texts, Abdullateef Ibrahim Almudaifer

All ETDs from UAB

In the analysis of scientific and clinical texts, the extraction of named entities and their relevant information, such as modifiers, play a pivotal role. Recent advancements in natural language processing (NLP), particularly through the application of transfer learning from pre-trained Transformer models, have greatly enhanced the performance of entity extraction tasks. However, challenges persist with nested entities. This thesis investigates the impact of transfer learning on extracting nested entities and their modifiers, using Opioid Use Disorder (OUD) as a prototype. By adopting a multi-task training strategy, this work enhances the model's capacity to discern and categorize overlapping entities, a task …

A Note On Three-Fold Branched Covers Of S4, Ryan Blair, Patricia Cahn, Alexandra Kjuchukova, Jeffrey Meier

Mathematics Sciences: Faculty Publications

We show that any 4-manifold admitting a (g;k₁,k₂,0)-trisection is an irregular 3-fold cover of the 4-sphere whose branching set is a surface in S⁴, smoothly embedded except for one singular point which is the cone on a link. A 4-manifold admits such a trisection if and only if it has a handle decomposition with no 1-handles; it is conjectured that all simply-connected 4-manifolds have this property.

Effect Of Fluid Elasticity On The Emergence Of Oscillations In An Active Elastic Filament, Kathryn G. Link, Robert D. Guy, Becca Thomases, Paulo E. Arratia

Mathematics Sciences: Faculty Publications

Many microorganisms propel themselves through complex media by deforming their flagella. The beat is thought to emerge from interactions between forces of the surrounding fluid, the passive elastic response from deformations of the flagellum and active forces from internal molecular motors. The beat varies in response to changes in the fluid rheology, including elasticity, but there are limited data on how systematic changes in elasticity alter the beat. This work analyses a related problem with fixed-strength driving force: the emergence of beating of an elastic planar filament driven by a follower force at the tip of a viscoelastic fluid. This …

Platform-Independent Estimation Of Human Physiological Time From Single Blood Samples, Yitong Huang, Rosemary Braun

Mathematics Sciences: Faculty Publications

Abundant epidemiological evidence links circadian rhythms to human health, from heart disease to neurodegeneration. Accurate determination of an individual's circadian phase is critical for precision diagnostics and personalized timing of therapeutic interventions. To date, however, we still lack an assay for physiological time that is accurate, minimally burdensome to the patient, and readily generalizable to new data. Here, we present TimeMachine, an algorithm to predict the human circadian phase using gene expression in peripheral blood mononuclear cells from a single blood draw. Once trained on data from a single study, we validated the trained predictor against four independent datasets with …

Topological And Dynamic Properties Of The Sublinearly Morse Boundary And The Quasi-Redirecting Boundary., Jacob D. Garcia, Yulan Qing, Elliott Vest

Mathematics Sciences: Faculty Publications

Sublinearly Morse boundaries of proper geodesic spaces are introduced by Qing, Rafi and Tiozzo. Expanding on this work, Qing and Rafi recently developed the quasi-redirecting boundary, denoted ∂G, to include all directions of metric spaces at infinity. Both boundaries are topological spaces that consist of equivalence classes of quasi-geodesic rays and are quasi-isometrically invariant. In this paper, we study these boundaries when the space is equipped with a geometric group action. In particular, we show that G acts minimally on ∂κG and that contracting elements of G induces a weak north-south dynamic on ∂κG. We also prove, when ∂G exists …

The Exclusion Of Black Girls: A Quantitative Study, Ursula Moorer

Selected Full Text Dissertations, 2011-

Existing research consistently indicates that Black girls are assigned disproportionately exclusionary disciplinary consequences such as, suspension and expulsion rates, surpassing their White counterparts and Black boys. According to the Report to Congressional Requesters, (United States Governmental Accountability Office, 2018), exclusionary discipline is any type of removal from a student’s normal educational setting. This quantitative correlational study examined the relationship between the racial demographics within a school's student and personnel populations and occurrences of suspensions faced by Black female students in grades 9 through 12. Archival data were used from the New York State Education Department (NYSED) website. NYSED data are …

6.Can Social Robot Teaching Assistants Innovate The Irish Primary Education System, John Pender, Debbie Woodward

Irish Journal of Applied Social Studies

No abstract provided.

Savings Associated With Surgical Aortic Valve Replacement With A Resilia Tissue Valve Based On Seven-Year Commence Trial Results, Tom Nguyen

All Publications

Background: Bioprostheses with RESILIA tissue demonstrate a reduction in calcification and improve health outcomes in pre-clinical and clinical studies. Prior economic analyses which relied on 5 years of evidence from the COMMENCE trial demonstrate financial savings for RESILIA tissue valves relative to mechanical valves after surgical aortic valve replacement (SAVR). Given the recent release of 7-year COMMENCE data, this economic evaluation updates the estimate for long-run savings of bioprosthetic valves with RESILIA.

Methods: Simulation models estimated disease progression across two hypothetical SAVR cohorts (tissue vs. mechanical) of 10,000 patients each in the US. The primary comparison calculated the SAVR-related expenditures …

Critical Data For Critical Care: A Primer On Leveraging Electronic Health Record Data For Research From Society Of Critical Care Medicine's Panel On Data Sharing And Harmonization, Donna Lee Armaignac

All Publications

A growing body of critical care research draws on real-world data from electronic health records (EHRs). The bedside clinician has myriad data sources to aid in clinical decision-making, but the lack of data sharing and harmonization standards leaves much of this data out of reach for multi-institution critical care research. The Society of Critical Care Medicine (SCCM) Discovery Data Science Campaign convened a panel of critical care and data science experts to explore and document unique advantages and opportunities for leveraging EHR data in critical care research. This article reviews and illustrates six organizing topics (data domains and common data …

A Model For International Summer Research Experiences For Stem Students, Mika Munakata, Su San Lim, Carlos A. Molina

Department of Mathematics Faculty Scholarship and Creative Works

In this article, we report on a National Science Foundation-funded immersive international summer research program for biology students. Six students, representing Cohort 1 of a three-year program, spent 9 weeks at one of three institutes in Japan, working on related molecular, cellular, and developmental research projects under the mentorship of a Japanese researcher. We describe the recruitment process, pre-departure activities, orientation week, research projects, and mentorship structure. Data were collected to determine the impact of the program on students’ views about science and to seek feedback about the structure of the program. The pre-, mid- and post-program interviews with the …