Digital Commons Network^™

Ajip Rosidi’S "Kegelisahan" (Restlessness) In Between Sundanese And Indonesian Literature, Teddi Muhtadin, Mikihiro Moriyama

Wacana, Journal of the Humanities of Indonesia

This article explores the literary journey of Ajip Rosidi, one of Indonesia’s most prolific writers, highlighting his unique position between Sundanese and Indonesian literature. Ajip authored over 300 works spanning diverse genres, making significant contributions to literature and the preservation of cultural heritage. The article examines his ambivalence or restlessness (kegelisahan) regarding the tension between regional and national identities in literature, as exemplified in his reflections and creative output. Ajip’s early life in a linguistically mixed region of West Java laid the foundation for his literary pursuits in both Sundanese and Indonesian. His works often oscillated between traditional …

Kathryn Emerson, "Innovation, Style And Spectacle In Wayang; Purbo Asmoro And The Evolution Of An Indonesian Performing Art", F.X. Rahyono

Wacana, Journal of the Humanities of Indonesia

No abstract provided.

Degradation Of Vascular Networks In A Huvec Model Of Dm1, Bonnie E. Butler

Departmental Honors & Graduate Capstone Projects

Myotonic dystrophy type 1 (DM1) is a genetic disease that causes muscle wasting and affects multiple organ systems. DM1 is caused by expanded CTG repeats in the 3’ untranslated region of the dystrophia myotonica protein kinase (DMPK) gene (Harper, 2001). Skeletal muscle relies on capillaries for nutrient delivery and waste clearance (Olfert, 2016). Skeletal muscle and capillaries communicate via a variety of chemicals, including PDGF-BB which both skeletal muscle and endothelial cells secrete and have receptors for (Hamaguchi, 2023). Platelet derived growth factor receptor β (PDGFRβ), when bound to platelet derived growth factor BB (PDGF-BB), induces angiogenesis (Wang, 2012). In …

A Path For A Post-Oil Iraq: A Green Transition Strategy To Prepare Iraq For Climate Change, Jason Edward Harsha

Departmental Honors & Graduate Capstone Projects

Due to resource scarcities from climate change, Iraq needs to reconfigure it's economic policy to resolve them. It needs to have an export model that is diversified from oil due it's weakness as a valuable export. Oil is vulnerable to price shocks and decreased demand from global energy transitions. Instead, Iraq should build knowledge intensive industries that create multiple valuable products to earn the revenue to import scarce resources. This can be attained with a just transition strategy that implements a energy transition while protecting the working class. A energy transition needs policies that lower the relative cost of renewable …

Water As A Natural Souvenir, Grace Winningham

Journal of Contemporary Water Research and Education

This research note explores the significance of natural souvenirs in tourism, emphasizing their contribution to cultural and environmental sustainability. Through a mixed-methods approach including a literature review and oral histories, the study examines how natural souvenirs, particularly water-based ones, foster souvenir-person-place bonding, enhance destination branding, and promote sustainable tourism practices. The findings highlight the unique and authentic nature of water souvenirs, which serve as powerful reminders of travel experiences and strengthen emotional connection to destinations. Additionally, the study discusses the role of natural souvenirs in differentiating destinations, leveraging unique attributes for branding, and stimulating interest through word-of-mouth marketing. Also addressed …

The Virginia Water Resources Research Center’S Experience With An Audio Show, Alan Raflo

Journal of Contemporary Water Research and Education

This article describes one state water center’s 14-year experience in producing a short, audiobased information product and poses key questions for water centers and institutes considering audio technologies to tell their states’ water stories. From 2010 to 2024, Virginia Water Radio (VWR), produced by the Virginia Water Resources Research Center, sought to use a short audio show to inform Virginia residents about the abundance, complexity, and use of the state’s water resources. Originally designed to be carried by radio stations, VWR evolved into a primarily podcasted show that was accompanied by a blog providing supporting material. The show produced 674 …

Long-Term Water Quality Trends In The Monongahela River Basin, Sitraka Rabemanjakasoa, Sarah Nelson, Leslie Hopkinson, Rachel Spirnak, Melissa O'Neal

Journal of Contemporary Water Research and Education

The West Virginia Water Research Institute (WVWRI) has been monitoring water quality in the Monongahela River basin since 2009 through its Three Rivers QUEST (3RQ) initiative. This study examined 3RQ data for trends in the water quality of the Monongahela River basin. Water quality was monitored at 18 sampling locations in the Monongahela River basin with six locations on the main stem and 12 locations on main tributaries. Temperature, pH, electrical conductivity (EC), dissolved alkalinity, dissolved sulfate (SO4), and dissolved analyte concentrations (aluminum (Al), calcium (Ca), chlorine (Cl), iron (Fe), magnesium (Mg), manganese (Mn), and sodium (Na)) were measured during …

National Institutes For Water Resources: Fulfilling The Water Resource Research Act Mission, 2016–2020, Jonathan Yoder

Journal of Contemporary Water Research and Education

The Water Resources Research Act of 1964 (WRRA) established the network of Water Resource Research Institutes (WRRIs). 60 years on, 54 Institutes carry out water research, education, and science communication for the benefit of the state or territory in which each resides. This article summarizes organizational and fiscal characteristics of the WRRIs and their activities based on Institute reports submitted to the U.S. Geological Survey for the period 2016-2020. The data show that these Institutes are highly diverse fiscally, organizationally, and in the focus of their activities, suggesting that the WRRA provides critical support to sustain the network of Institutes …

A Retrospective Review Of Emergency Department Leave Against Medical Advice Cases: Tracking Pregnant Women Presenting With Opioid Use Disorder, Rastassia Armstrong

MUSC Theses and Dissertations

Pregnant and post-partum women are not excluded from the growing number of individuals impacted by the opioid epidemic. The opioid epidemic is well understood as a widespread public health crisis. The impact has far-reaching effects beyond the individual user, data shows that there are serious implications for families, the healthcare system, taxpayers, and communities.

Pregnancy is a particularly vulnerable period in a woman’s healthcare journey, and for women struggling with opioid use disorder (OUD), it is an extremely high-risk time. Opioid misuse during pregnancy carries serious risks for both the mother and the infant. It is extremely important to identify …

The Impact Of Biomaterial Characteristics On Macrophage Phenotypes In Tissue Engineering: A Review, Julian Jackson, Hani Samarah, William Palmer, Zachary Kaplan, Marianna Nicodem, Parvesh Kumar, Spenser Short, Kelly Bridgham, Larry Harshyne, Joseph Curry

Department of Otolaryngology - Head and Neck Surgery Faculty Papers

Macrophages are highly plastic cells central to pathogen removal, tissue regeneration, and inflammation, making them key targets in biomaterial design for improved clinical outcomes. Foreign body responses (FBRs) to implanted biomaterials often involve excessive macrophage-mediated inflammation, leading to fibrotic encapsulation, infection, and implant failure. Advances in tissue engineering demonstrate that macrophage polarization - the transition from pro-inflammatory M1 to anti-inflammatory M2 phenotypes - can be influenced by biomaterial properties to mitigate these responses and enhance regeneration. This review synthesizes the relationship between biomaterial properties, such as surface chemistry, structure, and stiffness, and their ability to modulate macrophage behavior. Key innovations, …

Integrated Coastal Science And Dune Management: A South Carolina Perspective, Michelle Harris

Theses and Dissertations

Historically, coastal dunes have been poorly understood from a societal perspective despite their protective role in attenuating incoming waves to reduce onshore flood risk. As developed coastlines promote strategies to design and maintain managed dune systems, it is necessary to ensure these strategies are optimized for dune health and resilience, particularly given the increasing threat of natural and anthropogenic stressors. This dissertation work aims to identify strategies that influence coastal dune management in South Carolina (SC), USA from an integrated approach, including a current use assessment, a mesoscale field-based study on strategy efficacy, and by incorporating a societal assessment and …

Thematic Geo-Inquiry In Seventh Grade Geography, Rebekah Driscoll Austing

Theses and Dissertations

With the growth of globalization, geography is an important subject for students of the 21^st Century to understand. Being adept in geography will aid our future generations to be able to use geographic skills to answer complex world issues. Unfortunately, geography has been a long-neglected subject of social studies; often considered boring and not worthwhile with teachers using teacher-centered curriculum methods and memorization. A teacher’s job is to provide appropriate experiences, materials, and context for students to construct and connect knowledge that is useful and beneficial to them. Through a constructivist lens, inquiry-based thematic units can be used by …

Out Of The Ashes: One Teacher's Journey Implementing A Blended Learning Intervention Integrating The Flipped Classroom Model And Student-Selected Independent Reading, Michael John Hockwater

Theses and Dissertations

Sixth-grade Academic Intervention Services (AIS) students at Wyndemere Middle School (WMS) in Western New York demonstrated a lack of engagement in AIS English Language Arts (ELA) class. In hopes of increasing their engagement, the teacher-researcher implemented a blended learning intervention that incorporated aspects of the flipped classroom model and student-selected texts. The results of this action research qualitative case study were promising, with many student participants expressing an increased sense of engagement and enjoyment of AIS ELA class.

On Finite Groups With Essential Dimension 2 Over ℚ, Michael Huggins

Theses and Dissertations

We determine all finite subgroups of Aut(X) which have essential dimension 2 over ℚ, where X is a minimal Del Pezzo surface of degree at least 5. Additionally, finite groups with essential dimension 2 whose order is divisible only by the prime numbers 2 and 3 are classified with the exception of the groups dic ₁₂ , C₁₂, and Dih₂₄, whose essential dimensions remain unknown, but may possibly be equal to 2.

Exploring The Correlation Between Self-Esteem And Academic Success Among Special Needs Students In Kwara State, Nigeria, Florence Famolu

Jurnal Kajian Bimbingan dan Konseling

Special education has shifted from a position of delivering professional services to students with disabilities to a system that seeks to encompass the broad concept of promoting quality education for students. This study examined the correlation between self-esteem and academic success among special needs students in Kwara State, Nigeria. the study adopted a descriptive survey research type. special needs students in the three local government areas in Ilorin, Ilorin South, East, and West Local Governments Area constituted the total population for this research. The researcher designed questionnaire was entitled: self-esteem as correlate of academic success among special needs students’ questionnaire” …

Improving Image Quality In Electrical Capacitance Tomography Using Otsu Thresholding, Josiah Nombo

Tanzania Journal of Engineering and Technology (TJET)

Electrical Capacitance Tomography (ECT) is an imaging technique used in industrial process monitoring, particularly for monitoring and measuring the composition of multiphase flows. Despite its widespread application, the commonly used Linear Back Projection (LBP) algorithm often produces low-quality images due to its limited ability to handle high permittivity contrasts and nonlinearities. This study investigates the use of Otsu thresholding as a post-processing technique to enhance ECT image quality. By maximizing inter-class variance in the image histogram, Otsu thresholding improves contrast, clarity, and structural definition, enabling more effective segmentation of oil and gas components in multiphase flows. The proposed Otsu-based reconstruction …

Artificial Intelligence Applications For Grid-Connected Solar Inverters, Utkirjon Ubaydullaev, Sarvinoz Mirzaeva, Hasan Mustafoev

Chemical Technology, Control and Management

The increasing global demand for renewable energy has highlighted the importance of grid-connected solar inverters in ensuring efficient and stable power conversion. However, challenges such as fluctuations in solar energy generation, grid disturbances, and power quality issues necessitate advanced control strategies. The integration of artificial intelligence (AI) into solar inverters presents a transformative solution, enhancing performance, adaptability, and reliability in real-world applications.

This review explores the role of AI techniques, including machine learning (ML), deep learning (DL), fuzzy logic, and reinforcement learning (RL), in optimizing key inverter functionalities such as maximum power point tracking (MPPT), fault detection, power quality enhancement, …

Detection Of Http Flood Attacks Based On Machine Learning Algorithms, Norbek Karimov, Furkat Rakhmatov, Oybek Xolmuminov

Chemical Technology, Control and Management

This paper analyzes the effectiveness of Random Forest and SVM models for detecting HTTP Flood attacks. Experimental results demonstrate that both models achieve high accuracy. Evaluation was conducted using Precision, Recall, and F1 Score metrics. Additionally, key features of network traffic were extracted through correlation analysis to enable real-time application of the models in attack detection. The findings provide important insights into detecting DDoS attacks using machine learning and improving model performance.

Security In Biometric Access Control Systems Based On Fingerprints, Elmurad Jamuradovich Qilichev, Baxodir Saydullaevich Achilov, Ismoil Ergash OʻGʻLi Isroilov, Mirshod Mirkomil O'G'Li Ahmadov

Chemical Technology, Control and Management

This article analyzes biometric access control systems using fingerprints. The article considers the advantages of using biometric technologies, including solutions aimed at ensuring security, protecting users' personal data, and increasing the efficiency of systems. A detailed explanation of the principles of operation of fingerprint biometric systems, their underlying algorithms, and technological advances is provided. Problems that arise when assessing the level of security, ease of use, and technological and social aspects of biometric access systems and methods for combating them are also covered. At the end of the article, opinions are expressed about the future of fingerprint-based biometric systems and …

Sahhel: An Ai-Driven It Help Desk And Ticketing Mobile Application For Arabic Users, Arwa Wali, Maria Tamim, Nashwa Aljawi, Renad Alharthi

Journal of King Abdulaziz University: Computing and Information Technology Sciences

This paper presents Sahhel, an AI-based IT help desk and mobile ticketing application designed for Arabic-speaking users. The application aims to enhance communication between employees and IT support teams by providing a user-friendly platform to address technical issues. Sahhel leverages AI technologies to efficiently provide solutions to common IT problems. The application was developed and evaluated based on a case study conducted at Ibrahim Al-Qurashi Perfume Company. The survey results indicate a high level of user satisfaction, with the system usability scale (SUS) reaching 87.35%, with 79% of the participants liking the application frequently, and 70% and 85% finding it …

Supporting Airport Lost And Found Units With Surveillance Technologies Based On Deep Learning, Doaa Alahmadi, Elaf Alghamdi, Hind Bitar, Rsha Mirza

Journal of King Abdulaziz University: Computing and Information Technology Sciences

Currently, rapid growth in airports is encountered. Thus, enhancing customer experience, safety, and satisfaction using advanced technologies, such as deep learning (DL), is important. This research study explores the available DL and image processing algorithms to identify the most suitable algorithms that provide high detection accuracy to support the lost and found units in airports. Using the collected data from the surveillance camera technology in the airports, the performance of the algorithms is benchmarked and evaluated on an identical dataset to acquire an understanding of the distinctive features of each algorithm, the ability to distinguish between the algorithms and choose …

Baseer: A Drone-Based System Leveraging Facial And Pattern Recognition For Efficient Real-Time Child Recovery, Afraa Attiah, Abeer Hakeem

Journal of King Abdulaziz University: Computing and Information Technology Sciences

The loss of a child is a profound event that poses substantial emotional, psychological, and logistical challenges for families. Conventional child recovery methods, like search parties and media campaigns, often falter due to delayed responses, limited outreach, and ineffective data management. These methods struggle to handle vast information or employ modern tools efficiently. In response, this study introduces Baseer, a system merging drone technology with AI to enhance the efficacy of locating missing children. Baseer utilizes drones with high-resolution imaging systems for rapid aerial surveillance, expanding search capabilities beyond standard ground-based approaches. AI algorithms analyze real-time images for automated identification …

Iot Resource Management Based On The Sparrow Search Algorithm In Healthcare Applications, Entisar Alkayal, Nesreen M. Alharbi

Journal of King Abdulaziz University: Computing and Information Technology Sciences

Healthcare applications, such as remote patient monitoring systems (RPMSs), utilize various Internet of Things (IoT) devices, including headsets, pulse oximeters, EEG monitors, ECG monitors, and smartwatches, to remotely gather critical patient data, such as heart rate, body temperature, and blood pressure. This technology enables healthcare professionals to collect patient information without needing in-person visits, streamlining data collection. Once the data is collected, these IoT devices transmit the information to smartphones, which serve as edge devices. Given the limited processing capabilities of smartphones, data preprocessing is necessary before transferring the data to the fog layer, where it can be analyzed using …

Determining Patterns Of Instructors’ Usage Of Blackboard Features Using A Clustering Technique, Maryam A. Alamoudi, Arwa A. Allinjawi

Journal of King Abdulaziz University: Computing and Information Technology Sciences

Learning Management Systems (LMSs), such as Blackboard, have been shown to be valuable for online teaching and learning activities. They offer many tools for students and instructors. Moreover, they can track and record users’ activities, which can be analyzed using data mining techniques. The success of LMSs depends heavily on instructors because they typically initiate the activities and encourage the students to use LMSs. However, several studies indicate that instructors’ use of LMS features is often limited. This study aimed to identify the patterns of instructors’ usage of Blackboard features using a clustering technique. The experiment was conducted at King …

A Decision Support System For Predicting Covid-19 Mortality Using Machine Learning, Mohammed Alnaqash

Journal of King Abdulaziz University: Computing and Information Technology Sciences

The coronavirus disease 2019 (COVID-19) has diverse impacts on human lives beyond being just a disease, causing mortality and morbidity. Existing studies have played a key role in curbing the disease’s progression. However, these studies are inconclusive because hospitals’ patients-to-bed ratio is way larger than that of beds-to-patients in some developing countries. In this study, I proposed and developed a novel decision support system that guides medical staff in identifying patients who need to be hospitalized as well as predicting the mortality caused by COVID-19. Five machine-learning models were tested: Decision Tree (DT), Random Forest(RF), Support Vector Machine (SVM), K-Nearest …

Developer Analytics: A Novel Approach To Analyzing Developer Performance Through Football Comparisons, Ahmed Harbaoui, Waseem Ahmed

Journal of King Abdulaziz University: Computing and Information Technology Sciences

This article explores a novel approach to evaluating developer performance and software quality by drawing parallels between programmers and football players. We highlight the inefficiencies in current assessment methods, which often rely on years of experience rather than quantitative metrics that truly reflect a developer's capabilities. By examining the historical evolution of both fields, we identify the significant advancements in performance analysis in football, which are rooted in statistical data. We propose a framework for developer analytics that utilizes performance metrics derived from programming contests, allowing for a more nuanced classification of programmers based on their skills and roles. Our …

Deep Learning Model With Hybrid Resampling Technique For Electricity Theft Detection In Smart Grid, Fawzia Algarni, Laila Nassef, Nahed Alowidi

Journal of King Abdulaziz University: Computing and Information Technology Sciences

Electricity theft is a serious problem that results in significant revenue losses and jeopardizes economic stability. The accurate detection of theft is hindered by the prevalence of imbalanced, real-world electricity consumption datasets. Consequently, data balancing is necessary prior to the classification of normal and abnormal consumers in order to mitigate the classifier’s inherent biases toward the majority class. This study proposes a deep learning–based electricity theft detection model coupled with a hybrid resampling technique (synthetic minority over-sampling technique–edited nearest neighbor (SMOTEENN)). This hybrid technique resolves the bias problem in classifying the imbalanced data, reduces the risk of overfitting, and preserves …

Studying The Technology For Obtaining Zinc Chloride From Spent Supporter Waste In Ammonia Production, A.T. Dadaxo‘Jaev, Sodikjon Kadirov

Chemical Technology, Control and Management

This article presents the results of research on the recycling of spent zinc adsorbents formed during the ammonia production process, aimed at obtaining zinc chloride (ZnCl₂), which can be utilized in various industrial sectors, including electroplating. The research covers the optimization of technological parameters such as hydrochloric acid concentration, temperature, and reaction time to efficiently extract zinc chloride. The experiments revealed that the best results are achieved by using a 20% hydrochloric acid solution, at a temperature of 60°C, with a reaction time of 60 minutes. The resulting 40% zinc chloride solution was tested in electroplating production, where it met …

Development Of Fuzzy Ontology For Explainable Artificial Intelligence For Decision-Making In Fuzzy Environment, Pavel Kosov

Chemical Technology, Control and Management

In modern artificial intelligence systems, there is an acute need to understand the decision-making logic of "black box" algorithms. Our research proposes an innovative method for increasing the transparency of such systems through the formalization of fuzzy explanatory mechanisms. We have developed an extension of existing ontological approaches by introducing the concept of fuzziness into the structure of explanatory properties, which allows overcoming the fundamental limitations of traditional XAI methods. The proposed formalization is based on the theory of collective mental models and principles of fuzzy logic, providing a more accurate reflection of uncertainty and subjectivity in expert knowledge. Our …

Research Of The Dynamic Characteristics Of A Time-Pulse Ultrasonic Sensor, Aliev Ravshan, A.U. Djalilov

Chemical Technology, Control and Management

This article investigates the dynamic characteristics of a time-pulsed ultrasonic sensor used to measure water flow in open channels. The operating principle of the sensor, its response time in various hydrodynamic conditions, speed, and factors affecting measurement accuracy are analyzed. In the process of research, the improved ultrasonic sensor was tested and its effectiveness in measuring water flow in real time was evaluated. The results obtained showed that the sensor adapts to the velocity, temperature and turbulence level of the water flow. Based on the results of the research, the possibilities of working of time-impulse ultrasound sensors in open channels …