Digital Commons Network^™

Applications And Control Of Cable-Driven Parallel Robot: A Review, Yasser Hatim Alwan, Muayad Sadik, Ahmed Alaa Oglah

Iraqi Journal of Computers, Communications, Control and Systems Engineering

A cable driven parallel robot (CDPR) is a specific kind of parallel robot that utilizes cables as opposed to traditional rigid links to perform their functions. This gives it the advantages of being lightweight, having a wide operational workspace, and being easier and less expensive to implement than alternatives since it only requires cables operated by motors and fixed to a structure suitable for a certain application, allowing them to move and rotate an end-effector. The concept of this robot is not new though using a fully automated version of it was only started in the mid1980s and witnessed extensive …

Improved Carrier Frequency Offset Measurement With Reduced Latency And Computational Requirements, Niyaz Othman Ali, Jalal Jamal

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Over the past four decades, the communication sector has experienced significant economic growth and widespread adoption. Some emerging applications require high data rates, low latency, and must operate efficiently in environments where wireless devices are moving at high speeds. Noise and high device mobility have a considerable impact on received signal frequency, ultimately affecting system performance. So, accurate frequency estimation for received signals is therefore crucial, prompting extensive research. In this paper, we propose a three-step frequency estimation technique. The first stage, termed the coarse stage, employs a few sampling sizes to perform a fast Fourier transform. The second stage …

Artificial Intelligence For Eeg Analysis: A Comprehensive Review Of Deep Learning Techniques, Hudai Ahmedi Albeiruti

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This review systematically outlines the progression and implementation of artificial intelligence (AI) techniques, with a focus on deep learning (DL), for the analysis of electroencephalogram (EEG) signals. We cover the whole EEG processing pipeline from signal acquisition and preprocessing to feature extraction and classification. The survey begins with traditional machine learning techniques such as Common Spatial Patterns (CSP) and Support Vector Machines (SVMs), then transitions to more recent DL architectures—including ConVolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and their hybrid configurations—that have significantly expanded the analytical capabilities of neurophysiological systems. These methods have been widely applied in fields ranging …

Wybrane Aspekty Transformacji Klimatycznej I Energetycznej, Grzegorz Tchorek, Michał Kołtuniak

Monografie/Monographs

Monografia podejmuje aktualne zagadnienia transformacji energetycznej i zrównoważonego transportu w dobie kryzysu klimatycznego. Autorzy przedstawiają wyzwania, przed jakimi stają krajowe i lokalne władze, a także przedsiębiorcy i inne organizacje oraz wskazują szanse związane z transformacją. Wyzwania te dotyczą m.in. potrzeby dostosowań systemów elektroenergetyczny w związku z dynamicznym rozwojem odnawialnych źródeł energii, takich jak fotowoltaika, energetyka wiatrowa, wodna, biogazowa i wodorowa. Szczególną uwagę poświęcono technologiom magazynowania energii oraz lokalnym formom zarządzania produkcją i konsumpcją energii poprzez klastry i spółdzielnie energetyczne. Poruszono także zagadnienia rozwoju mobilności miejskiej oraz nowoczesne środki transportu nisko- i zeroemisyjnego, a także zagadnienia związane z ciepłownictwem oraz opracowywaniem …

Trichome Density And Herbivore Behaviour On Tomato Is Influenced By Herbivory, Plant Age, And Leaf Surface, Sunil Aryal, Manish Gautam, Justin George, Gadi V.P. Reddy, Rupesh Kariyat

Entomology and Plant Pathology Faculty Publications and Presentations

Leaf trichomes in plants act as the first line of physical defence against herbivory, in addition to many other reported functions. Although trichomes have been found to vary intraspecifically and can be induced by herbivory, their interactive effects under additional factors, such as plant age and abaxial vs. adaxial leaf surfaces, are less understood. Here, using five common tomato varieties, we explored the effects of these factors and their interactions on trichome type and density. We quantified the densities of Type VI glandular trichomes, non-glandular trichomes, and total trichomes on abaxial and adaxial leaf surfaces, and total leaf trichomes with …

Are Your Secrets Safe?: Imposing A Fiduciary Duty On Healthcare Ai Developers Dealing With Sensitive Health Information, Lauren Quinn

Fordham Law Review

In 1996, Congress passed the Health Insurance Portability and Accountability Act (HIPAA) to establish standards for transmitting health information. For decades, the HIPAA Privacy Rule has operated as the primary regulation protecting health information in the United States. However, in the decades since HIPAA was enacted, new technologies have demonstrated the shortcomings of the Privacy Rule. In particular, the development of healthcare artificial intelligence (AI) has created new privacy concerns and exacerbated existing ones. This Note examines the current healthcare privacy framework in the United States and considers how healthcare AI complicates it. This Note also explores how AI developers …

Legal Insurance And Its Limits, Nora Freeman Engstrom

Michigan Law Review

Courts are buckling under the weight of a staggering access-to-justice crisis. In three-quarters of cases, at least one side lacks a lawyer, default judgments are on the rise, and most Americans with valid claims never take legal action. The situation is dire, and it understandably has policymakers casting about for a fix. On the menu are a range of uncontroversial reform ideas, such as expanding legal aid, supporting system simplification, and promoting pro bono. But it is increasingly clear that those measures—even if accomplished—would not make a dent in the problem. Attention is thus turning to other reform ideas, such …

Recent Advances In The Identification And Quantification Of Xylazine And Medetomidine In Biological Specimens, Bridgit O Crews

2020-Current year OA Pubs

Xylazine is a veterinary sedative that is frequently detected in the illicit drug supply, often found mixed with illicitly manufactured fentanyl (IMF). It has been detected in the blood of overdose victims and patients who use illicit drugs. Xylazine is not approved for use in humans. It is an alpha-2-adrenergic receptor agonist that causes deep sedation that is non-responsive to naloxone, the antidote for opioid overdose. Chronic exposure to xylazine has been linked to severe wounds that can progress to amputation. Medetomidine is another related veterinary sedative that has more recently emerged as an adulterant in IMF. Medetomidine is also …

Chimeric Antigen Receptor Natural Killer (Car-Nk) Cells: From Preclinical Promise To Clinical Reality In Cancer Immunotherapy, Hunter Cassidy Cochran, Kevin Ashkan Ghobadi, Armin Ghobadi

2020-Current year OA Pubs

Chimeric antigen receptor (CAR) natural killer (NK) cell therapy represents an emerging frontier in cancer immunotherapy. CAR-NK cells offer the potential for "off-the-shelf" treatments with a favorable safety profile, due in part to their innate capacity for HLA-unrestricted tumor targeting and an absence of graft-versus-host disease. Landmark clinical studies using cord blood - derived CAR-NK cells and another employing iPSC-derived CAR-NK cells have reported impressive response rates, durable remissions, and minimal toxicity. Furthermore, a growing landscape of ongoing clinical trials is exploring innovative strategies to enhance persistence, overcome solid tumor challenges, and prevent antigen escape. These advances collectively underscore the …

Integration Of Sco2 Brayton Cycles With Carbon Capture Systems, Nathan C. Stearns, Rajarshi Roy, Brian Schooff, Andrew Chiodo, Andrew R. Fry, Brian D. Iverson

Faculty Publications

Increasing global energy consumption and greater market penetration of intermittent energy sources require a baseline power source to enable renewable energies. Here, a case is made for pairing supercritical CO₂ Brayton cycles with carbon capture to create low-emission, high-efficiency, combustion-based power generation systems. Pairing carbon capture and storage (CCS) systems with supercritical carbon dioxide (sCO₂) Brayton cycles enables the reduction of greenhouse gas emissions in combustion systems, but with an associated energy cost. Three different representative models of CCS systems (oxyfuel combustion, amine scrubbing, and cryogenic carbon capture) are considered for pairing with an sCO2 Brayton cycle, …

The Construction Of Mathematical Reasoning As A Pedagogical Object, Nick Pratt, Julie Alderton

School of Law, Humanities and Social Sciences

This paper explores how policy aims in mathematics curricula appear in classrooms and, crucially, how the resulting pedagogical practice affects the nature of mathematics itself. Whereas there have been many studies of policy and its relationship with teachers’ practices, few have examined epistemological effects; what mathematics becomes as it is translated from an educational, and political, intention into classroom activity. To focus the study, we examine reasoning as a central idea in mathematics, in the English primary (5-11 years) context. Rather than concentrating on best practice, as an objective account of how to teach reasoning, we adopt a post-structural theoretical …

Examining The Role Of Social Environment On Covid-19 Infections And Vaccine Uptake Among Migrants In Japan: Findings From Nationwide Surveys In 2021 And 2023, Yuanyuan Teng, Clive E Sabel, Tomoya Hanibuchi, Tomoki Nakaya

School of Geography, Earth and Environmental Sciences

Studies have shown that migrants and ethnic minority groups were disproportionately affected by the COVID-19 pandemic, yet the role of the social environment in shaping their vulnerabilities remains underexplored in Japan. This study explored the experiences of migrants in Japan during the COVID-19 pandemic and examined the association between social environmental factors (i.e., population density, neighborhood deprivation, ethnic density, and social networks) and both COVID-19 infections and vaccination uptake. Two nationwide online surveys were conducted in 2021 and 2023 to capture migrants' experiences and analyze these associations during the middle and waning stages of the pandemic. Modified Poisson regressions with …

Performances In Last-Mile Deliveries Involving Cyclic Services Of Shuttles And Cargo Bikes, Byung Kwon Lee, Young Joo Kim, Joyce M. W. Low

Research Collection Lee Kong Chian School Of Business

This study introduces a novel approximation model that integrates the ideologies of order statistics and max-plus algebra in representing the collection and distribution service schemes of a last-mile delivery system. Under the respective schemes, electric cargo bikes (e-bikes) perform the last-mile delivery near a microhub with shuttles collecting packages from multiple local logistics hubs (or local hubs, for short) and/or distributing packages to multiple microhubs. The framework is designed to estimate the cyclic capacity under varying cargo carrying capacities of the e-bikes and service network configurations. Real-world data, such as the geographic conditions of the streets around the microhubs in …

Personality And Personnel Selection: Going Beyond Self-Reports And Linear Relationships, Filip Lievens, Jinyan Fan, Jingyi Li

Research Collection Lee Kong Chian School Of Business

The study of personality in selection and assessment represents one of the most longstanding and voluminous literature in industrial and organizational psychology. In this paper, we review two important recent research streams. First, we review studies on alternatives to self-report personality inventories, namely the use of Situational Judgment Tests (SJTs), assessment center (AC) exercises, and a multi-rater framework. Second, we review studies that go beyond linear relationships between personality and job performance. Generally, our review reveals that these alternative approaches show promises in better understanding personality and how personality relates to performance.

Coarse Salary-Setting And Behavioral Teams, Chengyuan Hua

Economics Faculty Working Papers Series

Among National Hockey League (NHL) player contracts signed in 2011-24, over 38% are divisible by $100,000. This paper shows that the bunching of NHL contracts at round numbers is partly driven by team coarse wage-setting. I first show that teams with more coarse contracts have worse team performance. Then, my empirical results validate two model predictions derived from a wage-setting model in which optimization costs lead to the adoption of rounded wages. With a novel measure of management quality, I document a negative relationship between management quality and coarse salary-setting. Next, I find that coarse salary-setting is associated with higher …

Impact Of Feature Standardization On Heart Disease Prediction A Comparative Analysis Of Logistic Regression And Support Vector Machine Models, Norsyela Muhammad Noor Mathivanan, Eric Foo Zhi Xian, Debbie Foo Yong, Hiang Kiat Chua

Malaysian Journal of Computing (MJoC)

Cardiovascular diseases are among the leading causes of global mortality. Heart disease, in particular, remains a major contributor to this burden, highlighting the need for effective predictive models to enable early detection. This study investigates the impact of feature standardization using StandardScaler on the performance of two prominent machine learning models involving Logistic Regression (LR) and Support Vector Machine (SVM) for predicting heart disease. The research utilizes a dataset comprising demographic and clinical attributes of patients, focusing on the role of feature standardization in enhancing model performance. The study compares models trained on raw data and standardized data, applying performance …

Haar Cascade Algorithm For Microsleep Detection, Norkhushaini Awang, Ahmad Mirza Azhar

Malaysian Journal of Computing (MJoC)

Drowsy driving, particularly due to microsleep episodes, is a significant cause of traffic accidents, with existing solutions being often too costly or limited for widespread adoption. This project addresses this critical gap by developing a cost-effective, real-time Internet of Things (IoT)-based anti-microsleep alarm system. The system's development followed a fourstage process: Planning, Design, Development, and Evaluation. During the development phase, the system was built in Python using OpenCV and dlib for real-time facial analysis and the Haar Cascade algorithm for efficient facial feature detection. Key metrics like the Eye Aspect Ratio (EAR) and lip distance were monitored to identify signs …

Prevalence Of Risk Factors And Severity Level Of Diabetic Retinopathy In Uitm Medical Specialist Centre:An Ordinal Analysis, Aniza Ayuna Che Jani, Zuraida Khairudin, Nornadiah Mohd Razali, Nor Azimah Abd Aziz, Hezlin Aryani Abd Rahman, Nur Syamimi Haji Abu Bakar

Malaysian Journal of Computing (MJoC)

Diabetic Retinopathy (DR) has become a major concern as the number of diabetic patients who are diagnosed with DR has been on the rise each year. Hence, the adoption of a strategic approach is needed to determine the factors that contribute to the level of severity in DR patients. This research aims to determine the significant risk factors influencing the severity level of DR as well as to evaluate the classification rate between the severity level of 157 patients at UiTM Private Specialist Centre by employing the Ordinal Logistic Regression (OLR) analysis. The study revealed that there were 60 (38%) …

Review And Gap Analysis On Mathematical Programming Models For Urban E Grocery Delivery, Nur Hazimah Basir, Adibah Shuib

Malaysian Journal of Computing (MJoC)

Online grocery shopping or e-grocery has becoming more relevant nowadays when consumers' shopping habit changed due to pandemic COVID-19 while e-Commerce rapidly transformed consumers’ lifestyle and buying behaviour in recent years, Consumers’ expectation for faster, better and cheaper delivery put e-grocers under rising pressure to improve delivery speed, achieving environmentally friendly delivery methods and addressing issues of making profit. There have been studies worldwide on development of more efficient e-grocery delivery system. However, studies concerning e-grocery delivery in Malaysia are still lacking especially on those utilizing mathematical programming models for delivery optimization. Our study focuses on the formulation of mixed …

E-Commerce Requirement Analysis And Design With Fogg Behavior Model Fbm, Fauziah Ahmad, Syafiyana Elysha Asmadi, Norjansalika Janom

Malaysian Journal of Computing (MJoC)

E-commerce platforms often struggle to convert user visits into meaningful actions, and this paper explores how the Fogg Behavior Model (FBM) can be used to design a more effective e-commerce (EC) platform. FBM focuses on three key factors that influence user behavior: motivation, ability, and triggers. It offers a structured framework for designing systems that not only meet functional needs but also enhance user engagement and actions. The Web Development Life Cycle (WDLC) method was employed to develop an EC platform for Carro Empire, a small business enterprise that wanted to improve its EC platform to attract and expand its …

Hamming Distance Of Generalised L-R Intuitionistic Fuzzy Number And Its Application, Muhammad Asyran Shafie, Nor Hanimah Kamis, Daud Mohamad, Seripah Awang Kechil

Malaysian Journal of Computing (MJoC)

This paper proposes a distance measure for generalised L-R intuitionistic fuzzy number (GLRIFN) which is Hamming distance, aiming to enhance the theoretical and practical tools available for decision-making under uncertainty. The properties of the Hamming distance of generalised L-R intuitionistic fuzzy number are also discussed in this study. GLRIFN extends traditional L-R intuitionistic fuzzy number by incorporating confidence level for both membership and non-membership functions, making them more reliable in the evaluation process. To demonstrate the practical utility of the proposed measure, it is applied within the Generalised L-R Intuitionistic Fuzzy Technique for Order of Preference by Similarity to Ideal …

A Multicriteria Decision Model For Sustainable Port Functions In Environmental Perspectives

Malaysian Journal of Computing (MJoC)

Port operations, while critical to global trade and economic growth, contribute significantly to environmental pressures through activities such as vessel traffic, cargo handling, dredging, and on-dock transportation, leading to emissions of greenhouse gases and other pollutants. Hence, it is of priority to have a systematic evaluation and prioritization of sustainability measures across port functions. This study employs a multi-criteria decision-making (MCDM) approach, the Analytic Hierarchy Process (AHP), to evaluate and prioritize key functional roles and subfunctions that contribute to port sustainability performance. By engaging expert judgment from two leading ports in Malaysia, the analysis identifies stakeholder priorities on the emphasis …

Towards A Unified Framework For Knowledge Tracing With Graph Convolutional And Neural Architectures, Yaxi Su, Mohamad Yusof Darus, Norizan Mat Diah, Jinpeng Huang, Azlin Ramli

Malaysian Journal of Computing (MJoC)

This paper sets out to propose a unified theoretical framework for knowledge tracing (KT) that combines graph convolutional networks (GCNs) with neural sequence architectures in intelligent tutoring systems. While existing methods have achieved some success, they face limitations in modelling relational dependencies among concepts and the temporal progression of learner behaviour. Building on socio-constructivist views of knowledge as a network of relations and connectionist accounts of learning as adaptation over time, the framework integrates graph-based relational reasoning with sequence-based temporal modelling. The argument advanced here is that the integration offers interpretable representations of knowledge states while preserving predictive performance. The …

Designing A Community Based Information System Using Activity Theory A Case Study In Taman Lapangan Jaya, Norsyazwani Hafizah Reduan, Kamalia Azma Kamaruddin

Malaysian Journal of Computing (MJoC)

Effective communication and information sharing are vital for active neighbourhood participation, yet many communities still rely on informal group chats that lead to fragmented updates, lost documents, and frequent miscommunication. This study addresses this gap by applying Activity Theory (AT) to systematically identify requirements for a centralized community communication and information-sharing platform in Taman Lapangan Jaya. Using AT, the seven elements of activity were mapped to reveal key issues such as the communication bottleneck, lack of document accessibility, and unclear division of responsibilities. These findings informed the design of a web-based system featuring structured document repositories, role-based information management, and …

Utilizing Mathematical Software For The Teaching And Learning Of Mathematics In Malaysia, Naiim Fatimi Che Mansor, Saufianim Jana Aksah, Nor Aziyatul Izni, Khairul Huda Yusof, M. N. Mohammed

Malaysian Journal of Computing (MJoC)

The paper examines the effects of mathematical software on the academic performance of secondary school students, along with its roles in facilitating technological adaptation among the students in mathematics education. The study is motivated by persistent challenges in students’ mathematics achievement and the limited integration of technology in classroom practices, despite the increasing availability of digital tools in schools. Two main objectives guided the research are to evaluate the effectiveness of mathematical software in improving students’ comprehension of mathematics, and to measure the extent of technology integration among students in mathematics learning. A quantitative research design was employed, involving 100 …

Modified Hungarian Method For Lecturer To Course Assignment A Multi Objective Mathematical Programming Model, Nur Syahirah Ibrahim, Adibah Shuib, Zati Aqmar Zaharudin

Malaysian Journal of Computing (MJoC)

Efficient lecturer-to-course assignment is crucial for ensuring both faculty satisfaction and optimal teaching outcomes in higher education institutions. This study presents an advanced optimization model based on the Modified Hungarian Method (MHM) to address this challenge by integrating lecturers' preference levels and competency scores. While previous research has primarily focused on the traditional Hungarian Method (HM), limited attention has been given to its modified version. Moreover, the incorporation of preference-competency-based criteria in lecturer assignments is still lacking. To bridge these gaps, this study develops a mathematical programming approach to refine the MHM framework. The proposed model, called the Preference-Competency Multi-Objective …

Human-Computer Interaction Experience And Customer Loyalty In Chinese Hotels The Moderating Effect Of Brand Trust, Xie Lu, Xinying Yuan, Zeyu Chen, Johanudin Lahap

Malaysian Journal of Computing (MJoC)

In the era of digital transformation, human-computer interaction has become a critical factor in shaping customer experiences and loyalty, particularly in the hospitality industry. This study investigates the relationship between human-computer interaction experiences and customer loyalty in Chinese hotels, with a focus on the moderating role of brand trust. Drawing on the Technology Acceptance Model, the research explores how perceived ease of use and perceived usefulness of human-computer interaction systems influence customer loyalty while considering the impact of brand trust as a moderating variable. Using a quantitative research design, data were collected from 350 hotel guests in China who had …

The Complexity Of Long-Distance Dependencies And Their Impact On Language Models, Abhijit Shrikant Mahalunkar

Doctoral

Sequential data modeling is an important challenge in various fields and in particular in natural language processing. Building effective sequential models faces a notable challenge in the form of Long-Distance Dependencies (LDDs) within the sequence data. Hence, successfully overcoming this challenge is imperative for developing robust and accurate sequential models across various domains and applications. To tackle this challenge, the first step is to conduct a detailed analysis of the complexity of LDDs observed in various sequence datasets. This thesis offers a thorough exploration and documentation of this analysis. An important finding from this thesis is the consistent patterns of …

Necrobiosis Lipoidica Arising In A Port Wine Stain Treated With Topical Ruxolitinib, Neena Edupuganti, Jay Nguyen, Fahad S. Siddiqui, Victoria Dukharan, Rajiv Nathoo

GME Publications

We present a unique case of necrobiosis lipoidica (NL) arising within a port-wine stain (PWS), which, to our knowledge, has not been previously reported. NL is a rare granulomatous disorder often associated with diabetes mellitus, characterized by chronic inflammation and microvascular dysfunction. PWS, a congenital vascular malformation, results from defective endothelial differentiation and capillary malformation. The coexistence of these conditions suggests a potential link in their pathophysiological mechanisms, including inflammation, endothelial dysfunction, and shared signaling pathways such as mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase (PI3K), and tumor necrosis factor (TNF)-alpha. Our patient's NL lesions demonstrated improvement with topical ruxolitinib, a …

Charting An Open Future, Michael Fernandez, Rachel E. Scott

Faculty and Staff Publications – Milner Library

[In the absence of an abstract, the opening is presented.]

Here at LRTS, we are excited to mark the conclusion of our third year as a fully open access (OA) journal. The editors feel honored to be able to showcase top-tier research and new developments in best practice within the field of library technical services, brought directly to our readers without paywalls or embargoes and without article fees for our authors. Nonetheless, making content OA is one matter; sustainability for open publishing is another matter altogether. That sustainability for LRTS has been top of mind since we followed the …