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Mapping The Intellectual Landscape of Borneo, Brunei and Sulu: A Three Decade Bibliometric Synthesis of Historical Research
No full textThis study offers the first comprehensive bibliometric mapping of historical scholarship on Borneo, Brunei, and the Sulu region over the past three decades. Using a rigorously curated dataset of 298 publications indexed in Scopus and Web of Science, the analysis applies ScientoPy to examine publication trends, document types, prolific source titles, dominant research themes, conceptual models, institutional contributions, and highly cited works. The findings reveal a clear maturation of the field, with modest and sporadic output in the 1990s giving way to sustained growth from the mid-2000s and a marked acceleration after 2012, reflecting increasing international engagement and interdisciplinary integration. Peer-reviewed journal articles dominate the corpus, indicating a strong orientation toward high-impact scholarly dissemination. Key publication venues include the Journal of Southeast Asian Studies, Quaternary Science Reviews, and JEBAT, which collectively anchor historical, archaeological, and interdisciplinary research on the region. Thematic analysis demonstrates a shift from descriptive, locality-focused narratives toward broader approaches encompassing prehistoric human mobility, colonial and imperial encounters, environmental governance, maritime networks, and transboundary regional histories. Despite this diversification, the limited application of explicit theoretical frameworks illustrated by the marginal presence of the Bayanihan model highlights an underdeveloped dimension of conceptual engagement. Overall, this study provides a systematic overview of the intellectual structure and evolution of Borneo-Brunei-Sulu historiography and identifies critical gaps and future directions for advancing high-impact, interdisciplinary historical research in Island Southeast Asia
MRSI: Mobile Road Safety Information Application using Crowdsourcing
Full text linkRoad deterioration poses a significant challenge for all. Enhancing road security and minimizing accidents necessitates an effective, dependable tool to assist road users, particularly in UNIMAS and Kota Samarahan. Presently, a gap exists as there is no intuitive application available to offer and report on road traffic information. The development of an app to communicate road conditions and safety is therefore essential. With the growing preference for smartphones over traditional desktops or notebooks, leveraging these devices for rapid dissemination and notification about road status and safety proves to be a more time-efficient and convenient method. Test results indicate that over 70% of users found the application to be user-friendly with stable functionality. Additionally, the app provides real-time traffic condition updates
Model Predictive Current Control Fed by Single- Phase Indirect Matrix Converter (SP-IMC) with Reactive Power Minimization
No full textThis study presents a predictive current control and reactive power minimization strategy for a two-level single-phase indirect matrix converter (SP-IMC). The proposed control strategy takes advantage of the discrete nature of the system to predict the future load current and reactive power behaviour to perform switching optimization based on a minimum cost function criterion. Forward Euler’s approximation is used based on unitary power factor condition, minimum reactive power, and minimum load current harmonic content (THD%). An optimized rectifier switching strategy was also conducted to ensure positive fictitious dc-link voltage at any instant. Several robustness tests have been conducted at a laboratory scale and the experimental results of the proposed control are provided in this paper. From the experimental results, the Forward Euler’s approximation exhibits good load current reference tracking and reactive power minimization ability
Leveraging AI for Nurturing Learners With Empathy, Ethics, and Social Responsibility
No full textThis chapter presents how leveraging artificial intelligence (AI) can create a transformative potential in fostering empathy, ethics, and social responsibility in higher education. It discusses the opportunities brought by AI technologies in enhancing both the emotional intelligence and social-emotional intelligence of learners by providing personalized support and developing empathy. While AI-driven tools offer personalised learning experiences that help in a deeper understanding of diverse perspectives, their adoption must be balanced so that technology enhances, not replace human-centric education. Accountability demands that institutions take responsibility for the consequences of the application of AI. Finally, the future of AI in values-based education depends on whether it can complement human educators by upgrading learning without compromising any core human element of teaching. Thoughtful and ethical adoption of AI will allow higher education to prepare learners as responsible global citizens in a fast-growing world
Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Full text linkThis research paper explores the performance of binary nature-inspired optimization algorithms as feature selection to enhance the identification of human activities using
wearable technology. Utilization of nature-inspired algorithms for feature selection, as documented in scholarly literature, presents a promising opportunity to enhance
machine learning and data analysis tasks, given their effectiveness in identifying relevant features, resulting in models with reduced computational complexity,
improved predictive accuracy and easier interpretation. In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired
binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution
algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). The outcomes of this comprehensive experimentation,
conducted on two distinct human activity recognition (HAR) datasets, provide valuable insights. BPSO algorithm emerges as an adaptable and well-rounded performer, achieving a competitive balance between feature selection quality and computational efficiency in SBHAR dataset. Conversely, for the PAMAP2 dataset, BDE algorithm displays superior feature selection quality and BPSO algorithm maintains competitive
performance and adaptability. In both datasets, the nature-inspired optimization algorithms have achieved remarkable feature reduction, demonstrating reductions of
48% and 50% respectively. The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology,
such as feature selection, parameter adjustment, and model optimization
STOP! THAT’S MY SPACE: A PICTURE BOOK-BASED SAFETY EDUCATION TOOL FOR EDUCATORS AND CAREGIVERS TO EMPOWER CHILDREN
No full textThis teaching and learning innovation introduces Stop! That’s My Space, a storytelling-based educational tool developed to help educators and caregivers teach children about personal boundaries, body respect, and consent in a developmentally appropriate and culturally sensitive
manner. The tool centers around a large-format picture book that combines relatable storytelling through thoughtfully designed characters representing Malaysia’s diverse ethnic backgrounds, body types, abilities, and age groups. Each character is crafted to reflect inclusivity and foster a
sense of belonging through familiar cultural and visual cues. The primary objectives of this teaching innovation are to: (1) provide educators and caregivers with a practical and engaging tool to introduce personal space and child safety concepts; (2) promote inclusivity, empathy, and
respect for diversity through culturally relevant storytelling; and (3) encourage meaningful adultchild conversations around personal safety across diverse early childhood education settings.The methodology involves the use of this picture book alongside an instructor guidebook, which includes structured lesson plans, printable resources, and page-by-page facilitation notes. These materials are designed for use in both formal and informal learning environments, including those with limited digital access. Educators deliver the sessions using the materials provided and are invited to offer feedback through a structured questionnaire to assess clarity, usability, and
effectiveness. Findings from the pilot stage indicate positive responses from educators and caregivers. Many observed that children demonstrated increased confidence in asserting their personal boundaries. Children were also able to identify trusted adults and exhibited a clearer
understanding of when and how to seek help. Educators appreciated how the structured, developmentally appropriate materials supported them in facilitating sensitive discussions in a safe and accessible way. Improvements were also noted in children’s use of safety-related vocabulary, their emotional expression, and overall awareness of respectful personal interactions. In conclusion, this book offers a flexible, narrative-based approach to early childhood education that prioritizes child safety through storytelling. Its inclusive design, practical format, and
relevance to multicultural Malaysian classrooms position it as a valuable teaching innovation for fostering safer, more empathetic, and informed learning communities
Nanocellulose/Graphene oxide-modified PVDF membranes for efficient dye removal from wastewater: synthesis, characterization, and performance evaluation
No full textWater pollution has remained a pressing global concern, particularly as access to clean water becomes increasingly limited. Wastewater treatment plays a crucial role
in ensuring sufficient water can be supplied for daily needs. Membrane technology has become a promising method in ensuring the efficiency of eliminating contaminants from the wastewater, whereby poly(vinylidene fluoride) (PVDF) is commonly used in membrane fabrication. However, PVDF often faces limitations related to fouling, hydrophobicity, and mechanical stability, which can affect its long-term
performance. To overcome these limitations, this research aims to develop, characterize, and analyze the performance of PVDF/GO/NC membranes for dye removal.
The membranes were developed using the NIPS method, and characterization to determine the physical and chemical properties of the developed membranes was conducted using Fourier transform infrared (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), membrane porosity measurement, and Ultraviolet-visible (UV-vis) spectroscopy. The membrane performance was evaluated through water permeation flux and dye removal efficiency using methylene blue (MB) as a model dye. The incorporation of nanocellulose (NC) and graphene oxide (GO) is expected to enhance the hydrophilicity, antifouling properties, and
overall filtration performance of PVDF membranes, offering a more sustainable and effective approach to wastewater treatment
Photosynthetic Performance of Zea mays integrated with Neolamarckia cadamba under climate change condition
No full textAnthropogenic activities have increased CO2 emissions, elevating global temperatures and disrupting rainfall patterns, thus affecting crop productivity. This study
examines the photosynthetic performance of Zea mays under elevated temperatures (25˚C and 30˚C) and CO2 levels (400 and 700 ppm) in two cropping systems: monoculture and an agroforestry system combining Z. mays with Neolamarckia cadamba.
The experiment consisted of three water treatments: P1 (low rainfall), P2 (normal rainfall), and P3 (high rainfall), each with four replicates, giving a total of 12 pots
per cropping system and 36 pots overall across the three experimental conditions.
Key photosynthetic parameters measured were CO2 assimilation rate (A), stomatal conductance (Gs), transpiration rate (E), and water use efficiency. Results revealed that Z. mays in the agroforestry system under normal rainfall, 25˚C, and 700 ppm CO2 recorded the highest net assimilation rate. This is likely due to favorable microclimatic conditions provided by the tree canopy, including better moisture retention
and reduced heat stress. In contrast, the lowest photosynthetic performance occurred under low rainfall (P1), higher temperature (30˚C), and ambient CO2 concentration
(400 ppm). Under these stress conditions, stomatal conductance declined significantly, restricting CO2 uptake and reducing photosynthetic efficiency. These findings
suggest that agroforestry systems could help mitigate the negative impacts of climate change on crop productivity. Integrating trees with crops could enhance photosynthetic performance under future climate scenarios, supporting sustainable agriculture and food security
Structure-property relationships in bio-based polyurethane/carbon nanotube composite coatings revealed by principal component analysis
No full textThis study investigates the structural, thermal, morphological, and electrical properties of bio-based polyurethane (PU) composites reinforced with carbon nanotubes (CNTs). PU was synthesized using methylene
diphenyl diisocyanate (MDI) and palm kernel oil-derived polyol, while CNTs were incorporated in varying
concentrations (1 %, 2 %, 5 %, and 10 %) via a sonication-assisted solution casting method. The chemical
structure and successful incorporation of CNTs were confirmed using Fourier Transform Infrared Spectroscopy
(FTIR), revealing the preservation of the PU backbone and the presence of non-covalent interactions such as
hydrogen bonding. Principal Component Analysis (PCA) of FTIR data demonstrated effective differentiation
between PU and PU/CNT composites based on subtle changes in the fingerprint region. Field Emission Scanning
Electron Microscopy (FESEM) confirmed a uniform and well-integrated dispersion of CNTs in the PU matrix, with
minimal aggregation, supporting effective nanofiller incorporation. Thermal analyses using Thermogravimetric
Analysis (TGA) and Differential Scanning Calorimetry (DSC) revealed that CNTs improved the thermal stability,
delayed decomposition onset, and increased residual char content, particularly at 5–10 wt% CNT. These enhancements were attributed to CNTs' barrier effect and high thermal conductivity. Electrochemical Impedance
Spectroscopy (EIS) further demonstrated a significant reduction in bulk resistance with increasing CNT concentration, confirming enhanced electrical conductivity and the formation of conductive networks. The PU/CNT
composites exhibited characteristic impedance behavior in line with the Randles circuit model, supporting their
potential for electrochemical applications. Overall, the results indicate that CNT-reinforced PU composites
possess enhanced thermal, structural, and electrochemical properties, making them promising candidates for
flexible electronics, electrochemical sensors, and anti-corrosion coatings