Digital Commons Network^™

Machine Learning-Based Mental Health Risk Prediction And Behavioural Clustering Among Malaysian Undergraduates, Norsyela Muhammad Noor Mathivanan, Debbie Yong Xi Foo, Gerard Soon Lee Chong, Siti Fazilah Shamsudin, Marizkays P. Jamison

Malaysian Journal of Computing (MJoC)

Mental health issues among undergraduate students have become increasingly prevalent, affecting emotional well-being, academic performance, and overall quality of life. The growing number of students experiencing stress, anxiety, and depression highlights the need for effective predictive models to support early risk identification and personalized intervention strategies. This study investigates the performance of several machine learning approaches, including Logistic Regression (LR), Random Forest (RF), Gradient Boosting, LightGBM, Extra Trees, XGBoost, Support Vector Classifier (SVC), and a stacked ensemble model for predicting mental health risk among Malaysian undergraduate students. The study utilizes a dataset comprising demographic, academic, lifestyle, and psychological assessment attributes …

Malaysia Tech Stock Forecasting Using Arima: A Comparative Analysis With Kalman Filter Noise Optimization, Sarah Nadirah Mohd Johari, Ahmad Irfan Mohd Sukeri, Restu Ananda Putra, Ahmad Nur Azam Ahmad Ridzuan

Malaysian Journal of Computing (MJoC)

Forecasting stock prices in Malaysia's technology sector is difficult due to market noise. To mimic market behavior, many models have been developed and gradually improved with new algorithms and machine learning techniques. Relying on a single model often has drawbacks, so hybrid models were introduced to improve prediction stability. This study used a time series method, Autoregressive Integrated Moving Average (ARIMA) that has been proven to be reliable in forecasting various types of data. However, the ARIMA model often struggles with handling nonlinear and noisy data; thus, hybrid integration of the Kalman Filter was introduced to help reduce noise. The …

Turning Ontologies Into Vectors: Embedding Malay Ontological Knowledge For Smarter Machine Learning, Zayanah Zafirah Zulkipli, Ruhaila Maskat, Noor Hasimah Ibrahim Teo, Jie Zhang

Malaysian Journal of Computing (MJoC)

This conceptual study proposes a three-layer methodological framework for representing Malay ontological knowledge in continuous vector spaces and integrating ontology-derived representations with machine-learning models. The framework comprises an Ontology Layer, an Embedding Layer, and an Integration Layer. Its contribution is not a new ontology-embedding algorithm rather, it provides a Malay-oriented methodological organization that links ontology construction, embedding-method selection, symbolic-subsymbolic fusion, ontology-guided consistency checking, and downstream evaluation. In the present study, the ontology layer is represented through a prototype Malay linguistic ontology and its class hierarchy and knowledge graph, whereas the embedding, integration, consistency-checking, and downstream evaluation stages are proposed components …

Assessment Of Age-Wise Diabetes Risk Using Biochemical Indicators And Machine Learning Classification Models, Farwa Afzal, Mohibullah Aziz, Shariffah Suhaila Syed Jamaludin

Malaysian Journal of Computing (MJoC)

Diabetes mellitus is a major metabolic disease across the world, leading to serious complications and healthcare challenges. Prediction of diabetes at an early stage with the help of biochemical as well as demographic factors can lead to better diagnosis and preventive measures for the same. This research paper aims to predict diabetes using biochemical parameters in combination with various machine learning classification techniques, stratified by age group. This study uses a dataset of diabetes data that includes demographic and clinical attributes like age, gender, body mass index (BMI), urea, creatinine, HbA1c, cholesterol, TG, HDL, LDL, and VLDL. Machine Learning classifiers, …

A Fuzzy Logic Decision Support System For University Student Dropout Assessment, Adam Aiman A Hamid, Harliza Mohd Hanif, Siti Rahimah Batcha, Nur Zafirah Mohd Sidek, Noratika Nordin, Norain Alwi

Malaysian Journal of Computing (MJoC)

Student dropout continues to be an issue in universities, which has a negative impact on the academic performance of students and the reputation of educational institutions. Since the dropout decision is affected by multiple factors like academic performance, financial situation, stress, and self-motivation, the status of these factors can be highly uncertain, subjective, and conventional assessment methods cannot consider this impreciseness. This study designed a fuzzy logic–based decision support system approach to account for the risk of student dropout in a flexible and human-like way. The purpose of this study was to assess the potential risk of a student dropout …

Vision Transformer-Based Classification Of Cervical Cancer Images, Muhammad Daniel Alif Jumairi, Itaza Afiani Mohtar, Suraya Masrom, Masurah Mohamad, Lathifah Alfat

Malaysian Journal of Computing (MJoC)

Cervical cancer is a significant health concern as it is one of the most fatal causes of cancer deaths in women. Detection at an early stage is vital, but conventional diagnostic procedures via Pap smears relies heavily on manual cytopathology inspection, a process prone to human fatigue, diagnostic subjectivity, and severe practitioner shortages in low-resource medical environments. To address these challenges, this study presents an automated cervical cancer image classification framework utilizing advanced Vision Transformer (ViT) architectures. Three ViT variants: Data-efficient Image Transformer (DeiT), Swin Transformer, and Cross-Attention Multi-Scale Vision Transformer (CrossViT) were fine-tuned and evaluated on the benchmark SIPaKMeD …

Comparative Machine Learning Prediction Of Carbon Monoxide Levels And Contributing Factors In Shah Alam, Farzana Zubaidi, Norshahida Shaadan, Septia Devi Prihastuti Yasmirullah

Malaysian Journal of Computing (MJoC)

Carbon monoxide (CO) pollution is a major environmental and public health concern because it is colourless and odourless and is produced mainly by incomplete combustion from vehicles, industries, and household sources. Accurate prediction of CO levels and identification of key contributing factors can support early warning and targeted mitigation strategies. This study compared eight machine-learning regression models—Support Vector Regression (SVR), Random Forest Regression (RFR), Decision Tree Regression (DTR), K-Nearest Neighbours (KNN), CatBoost, XGBoost, LightGBM, and Neural Network Regression (NNR)—using daily air-quality data from the Department of Environment Malaysia for 2018–2023. The dataset comprised 42 input features representing air pollutants, meteorological …

A Data Envelopment Analysis Approach To Benchmarking The Efficiency In Selected Malaysian Food Manufacturing Companies, Zuraida Alwadood, Natasya Syafiah Marlis Elias, Norlenda Mohd Noor, Bekzodjon Fayziev

Malaysian Journal of Computing (MJoC)

Food industry, which includes every stage of the production process, from farming and manufacturing to distribution, retail and services, is one of the biggest and most significant sectors in the global economy. The relative efficiency of Malaysian food manufacturing companies is still unclear since many of them lack benchmarking tools and struggle to allocate labor, energy and raw materials optimally. This study applies the Data Envelopment Analysis (DEA) method to examine the relative efficiency of Malaysian food manufacturing companies. Relative efficiency refers to the ratio of the weighted sum of the outputs to the weighted sum of the inputs. The …

Iot-Enabled Smart Durian Harvesting: An Integrated Platform For Real-Time Orchard Monitoring And Sustainable Harvest Management, Norisan Abd Karim, Nur Carmilla Abdullah Muhammad Shafiq, Nur’Aina Daud, Syibrah Naim, Syaheerah Lebai Lutfi

Malaysian Journal of Computing (MJoC)

Durian harvesting requires timely monitoring to ensure that fallen fruits are collected promptly, thereby reducing quality deterioration and potential economic losses. Traditional orchard monitoring relies heavily on manual inspection, making the process time-consuming, labour-intensive, and inefficient, particularly in large orchards. The Internet of Things (IoT) technology has been widely used in smart agriculture to manage orchards, but there are very few existing systems that combine real-time durian fall detection with a mobile application that sends immediate notifications, automatic image capture of fall events, and orchard management functions. This study develops an Integrated IoT-Based Smart Orchard Platform for real-time durian harvest …

Field Assessment Of Power Link Budget Accuracy In A Residential Ftth Gpon Deployment, Arnita, Zulfadli, Tiara Resti Indah Rahmawati, Aswan Muhammad Azizi, Sangkot Wahyu Pulungan

Malaysian Journal of Computing (MJoC)

Fiber to the Home (FTTH) based on Gigabit Passive Optical Network (GPON) is widely used for residential broadband access because of its high bandwidth capacity, scalability, and efficient use of passive optical infrastructure. During FTTH network planning, Power Link Budget (PLB) analysis is commonly applied to estimate cumulative optical losses and received optical power. However, differences may occur between theoretical PLB calculations and actual field measurements due to practical deployment conditions. This study assesses the consistency of PLB predictions using field measurements from a residential FTTH GPON deployment. Measurements were conducted at two Fiber Access Terminal (FAT) points using an …

Modelling Malaysian Mortality With Cause-Of-Death: A Compositional Data Approach To Lee-Carter Extension, Saiful Azril Ishak, Norazliani Md Lazam, Shamshimah Shamsuddin, Nurin Haniah Asmuni, Nordiana Rosdi

Malaysian Journal of Computing (MJoC)

Forecasting cause-specific mortality is at the core of actuarial valuation, annuity pricing, and long-term public health planning. In traditional extrapolation frameworks such as the Lee-Carter and Li-Lee models, probability leakage is a structural flaw which causes the independently projected cause death rates to not sum to total mortality and results in implausible trajectory crossovers. To overcome these shortcomings, this study explores the application of Compositional Data Analysis (CoDA) extensions namely CoDA Lee-Carter (CDLC) and CoDA Li-Lee (CDLL) to historical Malaysian cause of death data. We transform cause proportions to the unit simplex using centred log-ratio coordinates. This transformation imposes exact …

Teacher And Principal Turnover In Alaska: Statewide Trends From 2013-2024, Dayna Jean Defeo, Noah Burke, Trang C. Tran

CAEPR Reports

Research consistently affirms that good teachers are critical for a child’s academic success, as well as their long-term social and economic outcomes. However, high teacher turnover disrupts instructional continuity and hurts student achievement. In Alaska, maintaining a stable educator workforce has been a challenge for nearly three decades. This report updates the state’s longitudinal retention data to report on trends in teacher turnover from 2013 to 2024. The report finds that, while the majority of Alaska’s educators stay at their main schools from year to year, overall turnover has trended upward since 2013 (with the exception of reduced turnover during …

Law School Record, Vol. 73, No. 1 (Fall 2026), Law School Record Editors

Law School Record

• Message from the Dean
• Legal Education in the Age of AI
• Speaking Out Beyond The Bench
• Theory In Practice
• Asked and Answered
• Meet the Five Alumni Now Clerking at the US Supreme Court
• Meet Lucy Msall, MLS '23 Newest Member of the Law School Faculty
• Faculty awards and recognition
• Trial By Fire: Inside the Law School's Intensive Trial Practice Workshop
• Development News
• Law School Unveils Portrait Honoring Geoffrey Stone, '71
• In Memoriam
• A Tribute to Professor Randal C. Picker, '85
• Giving Back: Peter Kolker, '66

Treatment Of Municipal Solid Waste Incineration Bottom Ash Using Cement For Integrated Recovery Of Hydrogen And Production Of Supplementary Cementitious Material, Muhammad Haris Javed, Wenyu Liao, Fathma Zuhra, David Vollero, David Schmidenberg, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Municipal solid waste incineration (MSWI) bottom ash (MBA) represents both a disposal challenge and a potential resource for sustainable construction materials, including use as a supplementary cementitious material (SCM). However, the conventional use of MBA in cement-based materials is hindered by its high metallic aluminum content, which reacts in alkaline environments to release hydrogen gas and causes volumetric instability (e.g., expansion and cracking). This study investigates a cement-based alkali pretreatment method using diluted cement suspension to stabilize metallic aluminum and improve the compatibility of MBA as an SCM. Compared to conventional alkali solutions, the proposed approach avoids the direct use …

Replenishing Resources With Enterprise Social Media (Esm): Overload-Moderated Effects On Work-Life Balance, Exhaustion, And Turnover, Murad Moqbel, Mohamed Hédi Charki, Amr Soror

Information Systems Faculty Publications

Purpose: This study investigates the double-edged impact of Enterprise social media (ESM) use on employee well-being through Conservation of Resources (COR) theory. We examine how work- and nonwork-related ESM use affects work exhaustion and turnover intention via work–life balance (WLB), and how these effects are contingent on perceived work overload.

Design/Methodology/Approach: A survey was administered to professionals at a major IT corporation in the Midwestern United States. Data from 276 employees were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings Only nonwork-related ESM use directly promotes WLB. Both work-related and nonwork-related ESM use enhance WLB for employees experiencing …

Graphene Oxide–Driven In Situ Bismuth Reduction Enables Highly Efficient Electroreduction Of Co2 To Formic Acid, Hao Feng, Bohong Zhang, Jie Huang, Xinhua Liang

Electrical and Computer Engineering Faculty Research & Creative Works

To enable large scale efficient electrochemical CO₂ reduction reaction (CO₂RR) to formic acid (HCOOH), it is important to develop catalysts that can be operated in a wide potential window with good stability. Herein, we successfully synthesized Bi₂O₃ catalyst supported on graphene oxide (GO) and graphene (G) and found that Bi₂O₃/GO catalyst had a better overall performance than Bi₂O₃/G. The Bi₂O₃/GO catalyst demonstrated an outstanding CO₂RR performance with a greater than 90% faradaic efficiency (FE) across a wide applied potential window …

Thermo-Mechanical Behaviour Of Metal-Coated Optical Fibers For Distributed High-Temperature Sensing: From Laboratory Characterization To Industrial Case Validation, Koustav Dey, Rony Kumer Saha, Bohong Zhang, Laura Bartlett, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Reliable distributed temperature sensing in high-temperature environments remains a significant challenge due to the thermal and mechanical limitations of conventional optical fibers. In particular, polymer-coated fibers degrade above ∼300 °C due to coating failure, mechanical fragility and hydrogen ingress. Metal-coated optical fibers offer a robust alternative for harsh environments such as Electric Arc Furnaces (EAFs), aerospace engines, nuclear systems, and oil and gas wells, owing to their superior mechanical strength and hermetic sealing. In this work, a first comprehensive experimental investigation of the thermo-mechanical behavior of metal-coated optical fibers for distributed high temperature sensing is presented over a wide temperature …

Shsp Dean's Newsletter, Fall 2026, Brian J. Nickerson

SHSP Dean’s Newsletter

No abstract provided.

Graduate School Blog - October 2026, Cynthia Haynes

UofM Grad School Blog

This issue highlights Dr. Deborah Tollefsen’s latest reflection on clarity and removing barriers to graduate student success, along with opportunities to get involved through the GSA Fall 2026 Election. We also feature upcoming graduate student events, academic webinars, Homecoming celebrations, and graduate recruitment activities. These stories and opportunities showcase resources designed to help graduate students navigate their academic journeys, build meaningful connections, and achieve their professional goals.

Teaching Prevention Before Disease Management: A Sustained Curriculum Innovation In Pre-Licensure Nursing Education, Selam Stephanos, Jan M. Nick Phd

Loma Linda University Research Reports

Chronic noncommunicable diseases are the leading causes of death worldwide, yet many are preventable or reversible through lifestyle change (Dean et al., 2014). Although nurses are well-positioned to support health behavior change, pre-licensure nursing education remains largely didactic, disease-focused, and introduced late in the curriculum (Kemppainen et al., 2013; Shea et al., 2021). To align with national priorities, we redesigned a pre-licensure health promotion course around lifestyle medicine and experiential teaching strategies. This presentation describes the process and sustained implementation results.

Rheology Modifiers For Water-Based Slurry Pipeline Transportation: Overview, Efficiency, And Intensification, Ahmed Alalou, Mohammed El Asri, Ahmed Boulahna, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Owing to their cost-efficiency and eco-friendliness, water-based slurry pipelines are the state-of-the-art technology for the transportation of several types of solids such as coal, fly ash, petcoke, iron ore, phosphate rock and other minerals. This review comprehensively examines the effect of numerous commercial dispersants and novel chemical additives that are used as rheology modifiers to enhance the slurryability and fluidity of solid-water slurries at high solids loading. Several key performance parameters such as the rheological characteristics (shear stress, apparent viscosity, yields stress, and flow behavior), the potential stability, surface tension and contact angle that highlight the efficiency of the rheology …

In Brief, Case Western Reserve University School Of Law

In Brief

Table of Contents

• Message from the Dean
• The Country's Pioneering Health Law Center
• Celebrating the 25th Anniversary of our War Crimes Research Office
• Foundations of Practice: Beginning the Journey from Law Student to Lawyer
• CWRU Law School's Teams Win Two National Championships in 2026
• Scholarly Impact
• 2025-2026 Conferences and Lectures Roundup
• Alumni Spotlight
• Class Notes
• In Memoriam
• Campus Comeback
• Diploma Day

Submission Guidelines For Graduation Requirements, Heather Hankins

Training Materials, User Guides, and Documentation

Last Updated October 2026

These submission guidelines support:

• Bachelor of Architecture submissions
• Honors capstone and thesis submissions
• Master's Thesis submissions
• Master's Project submissions (any non-thesis master's level culminating project)
• Dissertation submissions

All graduating KSU students should use this submission guide to identify the correct collection and submit their required deliverable, whether is it a thesis, dissertation, or other project.

Please contact [email protected] if you have any questions.

Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe, Homayoon Soleimani Dinani, Bohong Zhang, Maryam Karimi, Rex E. Gerald, Shelley D. Minteer, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We report a dual-modal fiber-optic probe that integrates electrochemical quantification of hydrogen peroxide (H₂O₂) with co-localized fluorescent pH sensing for pH-indexed interpretation of the H₂O₂ response. H₂O₂ is a reactive oxygen species involved in oxidative stress, inflammation, and cellular signaling, and local pH modulates both its production and electrochemical response. Many electrochemical H₂O₂ sensors exhibit pH-dependent sensitivity, creating ambiguity unless pH is measured and used for compensation, which is difficult in small, heterogeneous, or rapidly changing microenvironments. A three-electrode configuration—working (WE), counter (CE), and Ag/AgCl pseudo-reference (pRE) electrodes—is fabricated directly on the cylindrical surface of a 710-µm-diameter optical fiber using …

Front Matter, Art Inquiries, Kris K. Belden-Adams

Art Inquiries

No abstract provided.

Here Come The Brides: Sylvia Sleigh, Lawrence Alloway, And Hetty Remington, Andrew D. Hottle

Art Inquiries

Sylvia Sleigh (1916–2010), a Welsh-born artist who lived and worked in England before settling in the United States, is known primarily for her uninhibited portraits of nude men, many of which were painted in New York City during the feminist art movement of the 1970s. Over the last half-century, Sleigh’s male nudes have been both admired and derided for disrupting the conventional paradigm of the male artist and unclothed female model. Among them are Philip Golub Reclining (1971; private collection) and The Turkish Bath (1973; David and Alfred Smart Museum of Art, University of Chicago), which were inspired by canonical …

On Canvas: The Origins And Implications Of A Common Phrase, Kerr Houston

Art Inquiries

Why do modern art historians and conservators describe paintings executed on cloth in Europe in the fourteenth and fifteenth centuries as works on canvas, when late medieval and early Renaissance sources never do the same? This article answers that question by tracing and analyzing the evolution of canvas as a term in the history of painting. Until the late 1400s, it will be argued, the term canvas and its regional variants connoted coarse woven fabrics made of hemp that were associated with rugged, utilitarian needs and rural poverty—but not with painting. By contrast, artists and related texts relied on …

A Bibliography Of Faculty Scholarship, Kathryn J. Dufour Law Library

Scholarly Articles

The purpose of this bibliography is to record in one place the substantial body of scholarship produced by the current faculty at the Catholic University, Columbus School of Law. From its humble beginnings under the tutelage of founding Dean William Callyhan Robinson, through its adolescent period when, like so many other American law schools, it was trying to define its pedagogical niche, to its eventual merger with the Columbus University Law School in 1954, the law school at Catholic University has always retained a scholarly and remarkably productive faculty. The sheer quantity of writing, the breadth of research and the …

Can Cirilo Change The World? Cirilo F. Bautista's Lyric Poems In Times Of Crisis, Kristal Joyce Ibarra

Akda: The Asian Journal of Literature, Culture, Performance

Contemporary crises continue to confront Filipinos. These include the lingering effects of the COVID-19 pandemic, systemic corruption within the Philippine government, the red-tagging of activists, the deterioration of institutional integrity and public confidence in the Philippine government, and the US war against Iran, together with its global repercussions such as rising oil prices and displacement. This paper proposes that individuals turn to literature, beyond the fields of science or policymaking, during times of crisis and distress. Specifically, the lyric poems of National Artist for Literature Cirilo F. Bautista, distinguished by their evident relevance, form, and capacity to influence readers both …

Editorial Foreword Ijsls Volume 6 Number 1, Sulistyowati Irianto

The Indonesian Journal of Socio-Legal Studies

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