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Student's Attitudes and Motivation Towards the Effectiveness of Open Distance Learning (ODL) in Malaysian Universities
No full text— Online distance learning (ODL) has transformed the educational environment and ensured educational continuity during
global crises. As ODL becomes a permanent mode of education, continuous research into its effectiveness is imperative. This study
investigates the ARCS model as a mediator between student attitudes, learning platforms, and ODL effectiveness, focusing on student
experiences and outcomes. Utilizing a quantitative approach, an online survey comprising 31 items across five domains, including the
ARCS model, was administered to 123 participants currently or previously engaged in ODL. The findings reveal that ODL effectiveness
is significantly enhanced by positive motivational factors supported by psychological and emotional attitudes. Contrary to initial
assumptions, platform availability, and accessibility do not independently influence ODL effectiveness; instead, motivation positively
mediates effectiveness. This study provides institutions with the flexibility to improve learning platforms and offers insights to boost
student motivation. Additionally, the study underscores the importance of fostering supportive attitudes to maximize ODL benefits.
Recommendations for future research include exploring other mediating factors that may impact ODL effectiveness and examining
diverse student populations to generalize the findings further. By addressing these areas, educational institutions can better understand
the dynamics of ODL and implement strategies to enhance student experiences and outcomes. This study contributes to the growing
knowledge of ODL, highlighting critical areas for institutional improvement and student support. It emphasizes the need for a holistic
approach to educational technology, where motivational and attitudinal factors are integral to achieving effective and impactful online
learning
Comparative performance analysis of two novel design MIMO antennas for 5G and Wi-Fi 6 applications
No full textThis research provides a comprehensive evaluation of the performance of two Multiple-Input Multiple-Output (MIMO) antenna designs specifically designed for 5G and Wi-Fi 6 technologies. The initial design is a Compact CPW 4 × 4 MIMO Antenna intended for Wi-Fi 6 (IEEE802.11.ax) and 5G (nr77/nr78/nr79) Communications. The second design is a 4 × 4 MIMO Slot Antenna with a Spanner Shape, specifically designed to minimize mutual coupling for Wi-Fi 6 and 5G Communications. The evaluation of these two designs is based on multiple factors including gain, efficiency, bandwidth, and correlation coefficient. The simulation findings indicate that both designs exhibit favourable performance with respect to these criteria. The Compact CPW 4 × 4 MIMO Antenna possesses a gain of 6 dBi, an efficiency of 80%, and a bandwidth of 2.8 GHz. The 4 × 4 MIMO Slot Antenna exhibits a gain of 3.5 dBi, an efficiency of 80%, and a bandwidth of 4.5 GHz. The correlation coefficient between the antennas is low, suggesting a high level of isolation between them. The results indicate that both designs are compatible with 5G and Wi-Fi 6 applications and can offer dependable and effective communication
Adaptive control techniques for improving anti-lock braking system performance in diverse friction scenarios
No full textAnti-lock braking systems (ABS) enhance vehicle safety by preventing wheel lock-up, but their effectiveness depends on tire-road friction. Traditional braking systems struggle to maintain effective performance due to the risk of wheel lock-up on varying road surfaces, affecting vehicle stability and control. This study presents a novel method to improve ABS efficiency across varying friction conditions. The proposed approach employs a feedback control mechanism to dynamically adjust the braking force of each wheel based on the prevailing friction coefficient. Specifically, we incorporate a P-controller in the input signal and two additional P-controllers as output and input parameters for friction. By manipulating the proportional control values, key parameters such as wheel speed, stopping distance, and slip rate can be effectively managed. Notably, our investigation reveals intriguing interactions between the proportional controls, highlighting the complexity of ABS optimization. The method was evaluated through simulations across various friction conditions, comparing it to conventional ABS in terms of brake performance, stability, and stopping distances. The results indicate that the proposed method significantly enhances ABS performance across varying friction coefficients; however, additional research is warranted to address stopping distance and time issues, particularly in snowy and icy conditions
Machine learning-based technique for gain prediction of mm-wave miniaturized 5G MIMO slotted antenna array with high isolation characteristics
No full textThis study presents the design and analysis of a compact 28GHz MIMO antenna for 5G wireless
networks, incorporating simulations, measurements, and machine learning (ML) techniques to
optimize its performance. With dimensions of 3.19 λ₀×3.19 λ₀, the antenna offers a bandwidth of
5.1GHz, a peak gain of 9.43 dBi, high isolation of 31.37 dB, and an efficiency of 99.6%. Simulations
conducted in CST Studio were validated through prototype measurements, showing strong agreement
between the measured and simulated results. To further validate the design, an equivalent RLC circuit
model was developed and analyzed using ADS, with the reflection coefficient results closely matching
those from CST. Additionally, supervised ML techniques were employed to predict the antenna’s gain,
evaluating nine models using metrics such as R-squared, variance score, mean absolute error, and root
mean squared error. Among the models, Random Forest Regression achieved the highest accuracy,
delivering approximately 99% reliability in gain prediction. This integration of machine learning with
antenna design underscores its potential to optimize performance and enhance design efficiency.
With its compact size, high isolation, and exceptional efficiency, the proposed antenna is a promising
candidate for 28GHz 5G applications, offering innovative solutions for next-generation wireless
communication
Influence of conversational agent on students’ attitude toward mathematics
No full textPurpose – There exists a phenomenon called students’ negative attitude toward mathematics, leading to a
decline in students’ performance in mathematics and influencing their decisions to refrain from pursuing
Science, Technology, Engineering and Mathematics (STEM) majors and careers. Studies show that using
technology in education can reduce anxiety toward mathematics by increasing students’ motivation to explore
and appreciate mathematics. Conversational agents (CAs), automated software that interacts with users via
natural language, can be used in education to support teaching and learning. Unfortunately, despite its nearly 60-
year history, the application ofthistechnology in the education domain isstillscarce. Thisstudy aimsto examine
the effectiveness of integrating CA on students’ attitude toward mathematics.
Design/methodology/approach – To compare the impact of different teaching methods, students were
randomly divided into two groups: a control group receiving only traditional classroom instruction and an
experimental group receiving traditional instruction combined with interaction with a CA. After that, they
participated in a five-point Likert scale questionnaire on attitude toward mathematics.
Findings – The findings revealed that integrating CA in mathematics teaching and learning significantly
reduced experimental students’ anxiety toward mathematics while there was no improvement shown in the
importance of mathematics.
Originality/value – The integration of featuressuch as experiential learning,social dialogue, affective learning
and scaffolding makes this CA a comprehensive tool for promoting personalized and engaging learning
experiences among students thus reducing students’ anxiety and increasing their overall confidence toward
mathematics
Green analytical comparison and central composite design optimization for simultaneous estimation of pain management drugs using RP-liquid chromatography
No full textThe Central Composite Design method was utilized to validate a precise RP-HPLC method for concurrently
determining the quantities of Paracetamol (PC), Diclofenac Sodium (DS), and Eperisone Hydrochloride (EH) in
tablet compositions. By employing Design of Experiment (DOE), the experimental parameters were fine-tuned,
resulting in an optimized eluent consisting of methanol: water (90:10) with 0.1 % orthophosphoic acid at a
eluent velocity of 1 mL/min. The method exhibited exceptional purities: PC (100.83 % ± 0.85), DS (102.01 % ±
0.90), and EH (100.49 % ± 1.29). Regression equations were formulated for PC, DS, and EH as follows: y =
479762x + 151907, y = 2182788x + 2409442, and y = 777144x − 1146334, respectively. The analytical
method underwent comprehensive validation, including tests for: Accuracy, Precision, Linearity and Robustness.
To assess the method’s environmental impact, several Green Analytical Chemistry (GAC) tools were employed.
These tools provided a multifaceted evaluation of the method’s sustainability and eco-friendlines
Handling class imbalance in education using data-level and deep learning methods
No full textIn the current field of education, universities must be highly competitive to
thrive and grow. Education data mining has helped universities in bringing
in new students and retaining old ones. However, there is a major issue in
this task, which is the class imbalance between the successful students and
at-risk students that causes inaccurate predictions. To address this issue, 12
methods from data-level sampling techniques and 2 methods from deep
learning synthesizers were compared against each other and an ideal class
balancing method for the dataset was identified. The evaluation was done
using the light gradient boosting machine ensemble model, and the metrics
included receiver operating characteristic curve, precision, recall and
F1 score. The two best methods were Tomek links and neighbourhood
cleaning rule from undersampling technique with a F1 score of 0.72 and 0.71
respectively. The results of this paper identified the best class balancing
method between the two approaches and identified the limitations of the
deep learning approach
Optimizing Sustainable Resource Efficiency: A Fuzzy‐Set Qualitative Comparative Analysis of Sustainable Practices in SMEs
No full textThis study examines the influence of sustainability practices on resource efficiency in Ghana's small and medium-sized enterprises (SMEs), utilizing a comprehensive framework that integrates environmental and social dimensions, enabling conditions,
innovative practices, and technological advancements. Through a survey of 462 manufacturing SMEs, the research uncovers
the complex interrelationships between sustainability practices and their impact on resource efficiency. The findings reveal
four distinct sustainability pathways: the first underscores the critical importance of environmental dimensions and enabling
conditions without robust social dimensions and innovative practices. The second highlights the significance of environmental and enabling conditions, even when technological innovativeness is limited. The third and fourth pathways emphasize the
pivotal role of social dimensions and technological innovation, with innovative practices as supportive elements. Additionally,
two typologies emerge, illustrating the integration of environmental and social dimensions with enabling conditions and the
synergy between technological innovation, social dimensions, and innovative practices. This research advances the discourse
on sustainability within SMEs, emphasizing the necessity for reduced resource consumption, conservation, efficient production,
circular economy principles, and waste minimization. The findings suggest that achieving SDG 8.4 by 2030, which targets global
resource efficiency, hinges on adopting these sustainable pathways with emphasis on Ghanaian SMEs. This study provides a
deeper understanding of sustainability practices among developing economy SMEs, shedding light on the intricate dynamics that
enhance resource management. It offers critical insights for policymakers and practitioners seeking to promote sustainability
in local SMEs, particularly in Ghana, advocating for a holistic approach that considers the multifaceted nature of sustainabilit
Time-resolved optical fiber measurements: a review of scintillator materials and applications
No full textBackground Optical fber radioluminescence measurement (OFRLM) is a cutting-edge technique poised to play a major
role in radiation detection and dosimetry. Time-resolved measurement involves capturing the temporal dynamics of light
emission from scintillators, providing detailed information about radiation pulses.
Objective This review aims to evaluate various scintillator materials used in time-resolved OFRLM systems and their critical
importance in capturing ionizing radiation pulses.
Content The article discusses the properties of scintillator materials, including organic, inorganic, and composite compositions, and highlights their unique properties and suitability for time-resolved measurements with OFRLM systems. Performance characteristics, advantages, and limitations of diferent scintillator materials are thoroughly reviewed.
Conclusion This review provides insights into the optimal selection of scintillator materials for time-resolved OFRLM systems, ofering criteria for improving their performance and facilitating advancements in radiation detection and dosimetry
Law and Economics Scholarship in Malaysia
No full textThis article reports law and economics activities from Malaysia or by Malaysians. It surveys the resulting literature and identifies selected personalities who have contributed to advancing law and economics research in Malaysia. Other past activities, such as organising an online conference for the Asian Law and Economics Association in 2020, are recounted. It notes the extent to which Malaysian universities offer law and economics courses. The Malaysian government's requirement for regulatory impact statements is the right direction to instill further interest in law and economics in government officers. Finally, some existing challenges and opportunities for future development are examined for future actions