Journal of Advanced Research Design

Design and Development of Smart Pedestrian Lighting System in UNITEN

Yaw Long Chua , Amirul Syahmi Aiman Mohd Suhaimi, Koh Yit Yan — Thu, 09 Oct 2025 00:00:00 +0800

This project addresses energy wastage from continuous lighting in university walkways, particularly during low foot traffic after 10 pm, by implementing a Smart Pedestrian Lighting System. This system integrates an Arduino microcontroller, various sensors, and an IoT cloud. The lights operate under normal conditions from 7 am to 7 pm, activating only when ambient light is low. From 7 pm to 10 pm, the lights stay on continuously. After 10 pm, the system uses PIR motion sensors and LDR to illuminate the pathway as needed. All data collected is transmitted to the IoT cloud via the UNITEN Wi-fi for real-time monitoring and assessment. Two prototypes, Pro1 and Pro2, were developed and evaluated. Pro1 includes six LEDs, seven 1k omega resistors, one LDR, six PIR sensors, one ESP-01s, one RTC module, and an Arduino R3 board. Pro2 has similar components but uses an Arduino R4 WIFI board. The results showed that Pro2 is more reliable, effectively addressing high energy consumption and carbon emissions. Stark contrast in energy usage and CO2 emission was obtained as compared to the existing setup. The Smart Lighting System can contribute to the university effort to become a Smart Campus, providing a potential positive step towards energy saving strategies and achieving UNSDG.

Performance of Hyperthermia Applicator under ISM Frequency for Breast Cancer Treatment

Tue, 07 Oct 2025 00:00:00 +0800

Hyperthermia is a treatment procedure that applies heat on the target tissue with a temperature range of 40º to 45º C for a specific duration without affecting the healthy surrounding tissue. The efficacy of hyperthermia treatment relies on the suitable frequency within the Industrial, Scientific, and Medical (ISM) band. The frequency influences both penetration depth and Specific Absorption Rate. This study aims to investigate and compare the performance of the applicator with operating frequencies 434MHz, 915MHz, and 2450MHz with a tumor situated in the middle of the breast phantom. The hyperthermia model is simulated with SEMCAD X. Tissue properties include relative permittivity and conductivity represented with the Generic Dispersive Model. The penetration SAR distribution varies with different frequencies applied to the applicator. The applicator with 434MHz has greater penetration than 915MHz and 2450MHz. The SAR distribution on 2450MHz is more focused on the areola of the breast phantom, while on 915MHz, heat focuses on the middle of the breast phantom. For applicator 434MHz, the heat covers the middle part of the breast phantom to the chest wall. The appropriate applicator is recommended for effective hyperthermia treatment.

Experimental Investigation of Flame Stability and Temperature Profiles in an LPG-Fuelled Combustion System for Industrial Hot Air Generation

Tue, 07 Oct 2025 00:00:00 +0800

A combustion system is used to produce hot air for a variety of industrial and commercial purposes. This system works by burning a fuel source like natural gas, propane, or diesel in a controlled mixture of fuel and air inside a sealed chamber. However, achieving steady combustion has proven to be difficult since specific air pressure and flow rates are critical. The goal of this experiment was to investigate the combustor's combustion characteristics, particularly flame stability and temperature profile. Low air flow rates required 3 bar of air pressure to ensure flame stability, whereas greater flow rates were able to do so at 2 bar. Air flow rates of 30 l/min and above demonstrated stable flames at a 3 bar pressure. It was found that higher air flow rates were important for flame stability, as a fully opened valve sustained the flame for up to 15 minutes compared to only 4 minutes with a half-opened valve. The temperature profile showed decreased stability at lower air flow rates. Additionally, the maximum temperature of the combustor reached 235 ^oC, below the auto-ignition range of LPG between 410 ^oC to 580 ^oC. Therefore, this study highlights the critical role of air flow rate and pressure in maintaining flame stability and thermal consistency in combustion systems. These findings support efforts to optimize operating parameters of this combustor for improved efficiency, safety, and reliability in industrial applications.

The Symbiotic Evolution of AI and Media: A Technological Leap in Knowledge Sharing and Decision-Making

Tue, 07 Oct 2025 00:00:00 +0800

Artificial Intelligence (AI) is more than just an innovation, it is a force reshaping how information flows through society. But how does this impact on media communication? This study uncovers the answer. AI is no longer a new or unfamiliar concept in today's world. Its widespread use across almost every industry highlights its growing influence. AI adoption has largely had a positive impact, driven by various factors. One of the most significant is its role in information dissemination. However, the dynamics of this relationship remain unclear. This study explores the symbiotic relationship between AI and media communication, examining how AI shapes and enhances the flow of information. Additionally, this symbiotic relationship is examined in the context of a crucial global concern which is public health. The findings reveal that AI and media technology work together harmoniously to provide individuals with essential information, empowering them to make well-informed decisions more quickly. In this essence, this research highlights how AI, when integrated with media technology, serves as a powerful tool for knowledge sharing within society. Additionally, the insights from this study offer valuable implications for various stakeholders, particularly those navigating the rapid evolution of AI-driven technologies. Understanding these dynamics can help industries and policymakers maximize AI’s potential for relevance benefits.

Machinability Assessment of Hole-Making in Rubberwood–Plastic Composites Using Abrasive Waterjet Cutting

Kunlapat Thongkaew, Thanate Ratanawilai, Luksika Peter, Zaleha Mustafa — Wed, 08 Oct 2025 00:00:00 +0800

The application of wood-plastic composites (WPCs) in industrial and structural applications has increased; however, the secondary machining process of hole-making for assembly remains challenging due to tool wear, dimensional inaccuracy, and surface defects in conventional drilling.

Therefore, this study examines the machinability of abrasive waterjet (AWJ) cutting as an alternative approach for creating holes in single-layer and three-layer WPCs. Experiments were conducted using different cutting parameters, including water pressure, traverse speed, abrasive mass flow rate, and hole diameter. The effect on hole characteristics, roundness, and surface quality was analyzed. The results indicated that AWJ achieved through-cuts in both single-layer and three-layer WPCs, providing greater hole roundness and surface polish, while WJ produced complete cuts mainly at 350 MPa. The recommended AWJ parameters are abrasive flow rate of 6.67 g/s, water pressure of 350 MPa, and traverse speed of 30 mm/s, results in a roundness of 0.351 mm. A regression model was created to predict roundness, attaining an acceptability of 84.8%. A comparison with drilling bit suggested that AWJ cutting enabled shorter processing times, more flexibility, and without tool changes, although yielding lower roundness values. The results indicate that AWJ is a feasible and efficient alternative for hole fabrication in WPCs for manufacturing purposes.

Industrial Machine Overheat Detection System

Fri, 10 Oct 2025 00:00:00 +0800

Industrial machines are highly specialized equipment used in manufacturing and production processes. However, malfunctions or deterioration in their electrical, pneumatic, or hydraulic systems can lead to overheating, posing risks to the working environment and causing production downtime and financial losses. The objectives of this study are to develop an industrial machine overheat detection system using a microcontroller, monitor and control machine temperature, and measure the response rate of the system for overheat detection. The project implemented various components, including programmable logic controller (PLC) Siemens S7-1200, Thermocouple K-type, Max 6675 module, Arduino Uno, buzzer, relay, light crystal display (LCD) with I2C module, cooling fan, Arduino Ethernet shield, and project structure, to ensure the successful operation of the industrial machine overheat detection system. The results of the project focused on analysing the response rate of the temperature sensor when an overheat event occurs. By measuring this response rate, insights can be gained into the effectiveness of the system in promptly detecting and responding to overheat conditions. This research study aims to contribute to the understanding of overheating consequences, implement preventive measures, and address the issues associated with industrial machine overheating.

Advancing Solar Power Predictions: Exploring Neural Network Architecture through Transfer Function and Hidden Layer Analysis

Tue, 07 Oct 2025 00:00:00 +0800

Artificial Neural Network (ANN) models have demonstrated robustness in capturing variations in the input-output relationship between weather parameters and photovoltaic (PV) output power. However, despite their success in solar power forecasting, the challenge of determining the optimal architecture. This study aims to enhance the precision of photovoltaic (PV) output prediction by focusing on four inputs where irradiance, ambient temperature, PV module temperature, and humidity. The primary objective is to discern the most effective neural network architecture, specifically identifying the optimal number of neurons and hidden layers. The study employs the Multilayer Perceptron (MLP) technique, a type of ANN, to develop the model. Training shows that varying the number of neurons in the hidden layer, explicitly using 18 neurons, leads to optimal performance. Furthermore, it compares the best activation function between different activation functions, including linear, Hyperbolic Tangent Sigmoid (tan-sig), and Logistic Sigmoid (log-sig). The analysis concludes that the best activation function is achieved when the MLP model is designed using log-sig- linear- log-sig in the hidden layer with a structure of (4-18-18-18-4) for 560 data entries, using the MATLAB Deep Learning Toolbox. The results obtained from the neural network are thoroughly analyzed, indicating that using 18 neurons across the 3 hidden layers proves to be the most effective configuration for training, testing, and validation. This configuration yields minimal Root Mean Square Error (RMSE), emphasizing its strong performance in this study. The obtained result from this study, highlights the significance of fine-tuning neural network architecture for accurate and reliable solar power forecasting, contributing to advancements in renewable energy applications.

Challenges in the Enforcement of Syariah Criminal Law on Social Media in Malaysia: A Review from the Perspective of Syariah Evidence Law

Tue, 07 Oct 2025 00:00:00 +0800

The widespread use of social media has transformed the global communication landscape, making the sharing of information more accessible. However, it has also introduced new challenges in the enforcement of laws. The enforcement of Syariah criminal law serves as a key mechanism for safeguarding the welfare of Muslims in Malaysia. Nonetheless, its implementation faces significant obstacles in this era of borderless technology, particularly with the pervasive use of social media. Syariah criminal offences committed via social media encompass a variety of issues, including offences against the faith such as the dissemination of deviant teachings, religious defamation and the spread of doctrines contrary to Islamic teachings. While these offences contravene Syariah principles, enforcement is often hindered by various challenges, particularly those related to evidentiary law. These challenges render the enforcement of Syariah criminal law misaligned with contemporary technological advancements. This study aims to analyse the enforcement of Syariah criminal offences committed on social media and to identify the challenges encountered, particularly from the perspective of evidentiary law. Furthermore, it seeks to propose recommendations to address the issues identified. A qualitative, doctrinal approach was adopted for this research. Data were collected through library-based research, drawing from sources such as books, journal articles, statutory provisions and both reported and unreported cases. The data gathered was analysed using content and descriptive analysis methods. The findings reveal that gaps in the Syariah Evidence Law and outdated legal provisions constitute major obstacles to the effective enforcement of Syariah criminal law on social media platforms. Consequently, this study recommends that the legislative body take immediate steps to amend the existing evidentiary laws. Such amendments are essential to ensure that the enforcement of Syariah criminal law on social media is aligned with technological developments and becomes more effective in addressing contemporary challenges.

A Comprehensive Structured Review of Organizational Commitment and Job Satisfaction

Thu, 09 Oct 2025 00:00:00 +0800

This paper presents a comprehensive, structured review of the existing literature on organizational commitment and job satisfaction, two critical constructs in organizational behavior and human resource management. The study employs a systematic literature review (SLR) methodology to synthesize and analyze the body of knowledge on these topics. Data were extracted from three prominent databases—Scopus, EconBiz, and ERIC—using a rigorous search protocol that included criteria such as language (English), publication type (peer-reviewed journal articles), timeline (2000–2023), and subject area (business, management, psychology, and education). The review identifies key themes, theoretical frameworks, and empirical findings that elucidate the relationship between organizational commitment and job satisfaction, as well as their antecedents and outcomes. The findings reveal that organizational commitment and job satisfaction are interrelated constructs that significantly influence employee performance, retention, and organizational success. The study also highlights gaps in the literature, such as the need for more cross-cultural studies and longitudinal research to understand the dynamic nature of these constructions. By providing a structured overview of the field, this paper contributes to academic discourse and offers practical insights for managers and policymakers aiming to enhance employee engagement and organizational effectiveness.