Journal of Engineering Technology and Applied Physics

Inline Bandpass Filtering Waveguide Antenna with Two Transmission Zeros Based on All-resonator Structures

Sat, 15 Mar 2025 00:00:00 +0800

Nowadays, a significant amount of effort is being devoted to miniaturizing the design of filtering antennas for future wireless communication systems. However, there are numerous design strategies documented in the literature, most of which are relevant to specific microwave circuit configurations. Moreover, they often require additional matching circuits, which increase the overall size of the filtering antenna. This study introduces a generic coupling matrix approach for developing a second-order filtering antenna with two transmission zeros operating at cross-band frequencies. The last resonator's output is physically connected to free space, and two inline coupled rectangular waveguide cavity resonators operating in the TE₁₀₁ mode are employed. Impressive, simulated results have been achieved, demonstrating a fractional bandwidth (FBW) exceeding 5% at a reflection coefficient S₁₁ of -9.9 dB. Additionally, the gain response remains remarkably flat, spanning from 8.9 to 9.3 GHz, with a negligible variation of ±0.07 dB around 3.77 dB. The tiny and low-profile design of the suggested filtering antenna offers significant advantages for radar applications.

Manuscript Received: 6 May 2024, Accepted: 15 June 2024, Published: 15 March 2025, ORCiD: 0009-0006-5989-7715

An Improved Convolutional Neural Network (CNN) for Disease Detection and Diagnosis for Multi-crop Plants

Florence Choong Chiao Mei, Bryan Ng Jan Hong — Sat, 15 Mar 2025 00:00:00 +0800

Agriculture is one of the largest sectors that contribute to the economic growth of countries, including Malaysia. However, plant diseases affect the quality of the harvest and impede farmers’ maximum yield output. Therefore, early detection of diseases in plants is vital to curb infection, reduce food waste, and reduce their carbon footprint. However, many detection methods are complex, require high computational power and time to perform the required analysis and focus only on a particular species or strain of the disease. These requirements would likely deter most users in remote areas or poorer economic states. This paper proposes a convolutional neural network to determine multi-class plant diseases that is memory efficient, has a small trainable parameter number, and is compact enough to work even on mobile devices. The plant images were pre-processed to ensure that they were validated accurately and to minimise overfitting. Then, the proposed convolutional neural network was trained using a publicly available dataset consisting of 54306 images, followed by validation and testing. Finally, the completed model is saved, and the data obtained is transferred to a cloud network using wireless sensor networks. The proposed method obtained 96.87% accuracy with 100 epoch training iterations, rivalling famous architectures such as VGG16 and MobileNetV2. The experimental results demonstrate the feasibility and robustness of the method for disease detection in multi-crop plants.

Manuscript Received: 17 March 2024, Accepted: 8 July 2024, Published: 15 March 2025, ORCiD: 0000-0002-6958-8725

The Interaction of Australian Winter Monsoon and East Asian Summer Monsoon and Its Impacts on Convergence Around Kalimantan

Sat, 15 Mar 2025 00:00:00 +0800

The Australian Winter Monsoon (AWM) and East Asian Summer Monsoon (EASM) play a crucial factor in altering the global climate. The two monsoons are closely linked to each other through cross-equatorial flow. As the Australian High anomaly increases, the Western Pacific Subtropical High (WPSH) also increases, resulting in an anticyclone anomaly in Australia and the Western Pacific region that intensifies the AWM and EASM. This study examines the effect of variations between the two monsoons by removing ENSO and IOD signals on meteorological parameters in the Kalimantan region. European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 data with a resolution of 0.25° × 0.25° is used to examine the effect at the local scale and rainfall data from local observations for 35 years in the June-July-August (JJA) or boreal summer. Composite and correlation analyses were conducted by calculating the regression coefficients between the composite variables and the target variables. The EASM and AWM were also analyzed using Singular Value Decomposition (SVD) to identify the most relevant spatial patterns. This research reveals that when the AWM and EASM increase at once, two connected anticyclone anomalies over the maritime continent trigger easterly wind anomalies, leading to convergence in Kalimantan, which increases the rainfall intensity in the Kalimantan region.

Manuscript Received: 16 March 2024, Accepted: 13 June 2024, Published: 15 March 2025, ORCiD: 0009-0007-8133-7711

Comprehensive Review of CAN Bus Security: Vulnerabilities, Cryptographic and IDS Approaches, and Countermeasures

Omer Fayyaz Khan, Muhammad Mubashir , Jawaid Iqbal — Sat, 15 Mar 2025 00:00:00 +0800

Vehicle connectivity environments and advancements in vehicular technologies offer users both functional convenience and safety features, including remote diagnosis and assistance. To enable these capabilities, modern vehicles utilize various automotive serial protocols such as FlexRay, Local Interconnect Network (LIN), and the popular Controller Area Network (CAN). The CAN bus serves as a key protocol for in-vehicle networks (IVNs), facilitating the exchange of vehicle parameters among Electronic Control Units (ECUs). Despite its merits, the CAN bus has been found to have internal and external vulnerabilities. While numerous countermeasures are currently in place, the continuous advancements in vehicular interfaces have introduced new attack vectors, necessitating the development of additional safeguards. Existing research has primarily focused on CAN attacks initiated through direct interfaces, telematics and infotainment systems, and sensors. In this study, we aim to present an adversarial model for the CAN bus while also evaluating cryptographic and Intrusion Detection System (IDS) approaches considering real-time constraints and other relevant variables. Furthermore, we will classify available countermeasures into relevant categories and discuss their effectiveness. By conducting a comprehensive analysis of published works, our goal is to provide a comprehensive overview of CAN-related studies. This includes exploring potential mitigation techniques and identifying new research opportunities for IVNs. The synthesis of this information will offer valuable insights into the current state of CAN security, the challenges it faces, and the directions for future exploration. In summary, our study aims to address the vulnerabilities of the CAN bus, considering both existing and emerging attack vectors. By examining cryptographic and IDS approaches, we will assess their viability in real-time scenarios. Additionally, we will categorize and discuss the effectiveness of available countermeasures. Through this analysis, we strive to provide a holistic understanding of CAN-related research, paving the way for prospective mitigation techniques and identifying new horizons for IVNs.

Manuscript Received: 10 January 2024, Accepted: 28 May 2024, Published: 15 March 2025, ORCiD: 0009-0005-3915-6816

Analysis and Simulation of Switched Reluctance Motor Driven Electric Vehicle by Field-Oriented Control

Moe Moe, Soe Win — Sat, 15 Mar 2025 00:00:00 +0800

This paper analyses the performance of Electric Car for speed control of the switched reluctance motor. Closed loop speed control driven by field-oriented control (FOC) is applied for speed control. In these days, electric vehicles are widely used in most of the country because they can reduce the fuel consumption. As a consequence, they can lessen the environmental impact of carbon dioxide emission. The electric motors are the main devices to dive the electric car. The switched reluctance motors are well applied in the recent study instead of other AC motors for the electric vehicle due to their high performance. Using MATLAB/Simulink, the case study model is created and analysis of its results are carried out.

Manuscript Received: 31 March 2024, Accepted: 25 July 2024, Published: 15March 2025, ORCiD: 0009-0005-2086-3203

Maximum Power Enhancement of Partially Shaded Photovoltaic Array by Advanced Total Cross-Tied Based Configuration

Kaung Khant Win, Yin Yin Mya — Sat, 15 Mar 2025 00:00:00 +0800

Partial shading in solar photovoltaic arrays reduce the maximum power produced. Partial shading conditions in PV arrays can be caused by water, dust, tree shadows, bird-drops, nearby building, etc. Special configuration is needed to reduce the effect of partial shadings. In this study, 8 × 8 symmetric photovoltaic arrays configured in different configurations such series-parallel (SP), total cross-tied (TCT), modified complementary sudoku puzzle (MCSDKP) and symmetric matric total cross-tied (SMTCT) are studied under row shading of 25% shaded area and 50% shaded area with two different shading irradiance conditions of uniform shading irradiance and non-uniform shading irradiance. All of the performance results are carried out by MATLAB/Simulink. This study shows that advanced total cross-tied based configurations perform higher than other configurations in all conditions. The objective of this study is to understand the importance of array configurations and to get maximum power under partial shaded conditions.

Manuscript Received: 1 August 2024, Accepted: 27 August 2024, Published: 15 March 2025, ORCiD: 0009-0007-8806-5501

Independently Identifying Noise Clusters in 2D LiDAR Scanning with Clustering Algorithms

Chiew Wei Wen, Chuan Hsian Pu — Sat, 15 Mar 2025 00:00:00 +0800

Light Detection and Ranging (LiDAR) refers to a range imaging method for distance objects based on the principle of laser ranging. LiDAR environmental mapping technology is often highly praised for its precise mapping information with intricate features for various detection or tracking based applications. The research proposes a novel method for independently identifying and filtering noise clusters in 2-Dimensional (2D) LiDAR scans based on 2 distinct clustering algorithms of K-Means and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). Results show DBSCAN to be the better choice as it is more robust and resistance to noise and outliers in the dataset and is capable of identifying clusters of any shape making it more versatile. Furthermore, to address the issue of dead zones present in LiDAR scanning, an innovative solution based on interpolating the discontinuous spatial results of the LiDAR scanning result to further reconstruct a 3-Dimensional (3D) viewing model by stacking multiple copies of 2D LiDAR scanning results with varying elevation is demonstrated by the results of the study to be a viable economical alternative for 3D LiDAR mapping.

Manuscript Received: 1 August 2024, Accepted: 11 October 2024, Published: 15 March 2025, ORCiD: 0000-0003-4121-733X

A Flash Flood Warning System Using Solar Powered Node MCU

Irfan Yahaya, Ahmad Nazrul Rosli — Sat, 15 Mar 2025 00:00:00 +0800

Flash flood disasters are natural phenomena in Malaysia that can occur anytime and anywhere. For safety precautions, a notification message should be sent to the people early to avoid any losses of property or life. This system is designed as an earlier flood alert system that can detect water levels using an ultrasonic sensor. The objectives of this research are to develop a system that can be aware of the water level of flood to the user and send a notification to people about the flood’s condition through the mobile application. NodeMCU, an ultrasonic sensor, and solar technology developed the system. This project focuses on monitoring water levels, using Wi-Fi as a medium to send warning notifications to people through mobile phones, and the accuracy of ultrasonic sensors using and without pipes. This prototype can send short warning notifications to Blynk apps. The average percentage error of the water level distance from the ultrasonic sensor with pipe was lower than without pipe, which was 2.55% and 3.11%, respectively. This system improved the notification message-sending method and detection of the ultrasonic sensor.

Manuscript Received: 16 December 2024, Accepted: 23 January 2025, Published: 15 March 2025, ORCiD: 0000-0002-8834-8567

Experimental and Numerical Study of Shape Memory Alloys for Vibration Amplitude Reduction in Mechanical Structures

Sat, 15 Mar 2025 00:00:00 +0800

This study explores the effectiveness of Shape Memory Alloys (SMAs) for adaptive vibration control in mechanical structures through both experimental and numerical methods. SMAs were integrated into a cantilever beam, and their performance was assessed across different temperatures and vibration frequencies. The results demonstrate that SMAs can reduce vibration amplitudes by up to 45%, particularly at resonant frequencies when activated at elevated temperatures (75°C). A finite element model was developed to simulate the behavior of the system, showing strong correlation with experimental data, with a root mean square error (RMSE) of less than 4%. The validated model was further used to predict SMA performance under conditions not tested experimentally, confirming its reliability for broader applications. These findings show the potential of SMAs as compact, adaptive, and energy-efficient solutions for vibration control in sectors such as aerospace, automotive, and civil engineering. Future research should focus on optimizing activation response times, improving long-term durability, and exploring more complex structural designs for enhanced performance.

Manuscript Received: 7 December 2024, Accepted: 23 January 2025, Published: 15 March 2025, ORCiD: 0000-0002-2016-4825

Design and Fabrication of An Automated Glass Bottle Cutter for Reuse and Recycling Bottle Glass Products

Sat, 15 Mar 2025 00:00:00 +0800

The glass bottle cutter has a substantial commercialisation potential, as present trends indicate a growing interest in repurposing waste materials. This apparatus enables communities to manufacture new items from discarded glass bottles, including drinking glasses, ashtrays, and vases. Disposal at recycling centres or craft stores is essential for businesses such as restaurants and bars that often produce excess glass waste. Hence, this apparatus is resilient and long-lasting, designed to handle significantly larger amounts more efficiently than manual glass bottle cutters, which require scoring the bottle and alternating between hot and cold water. The main goals of this project are to develop a prototype for a glass bottle-cutting machine and to manufacture the machine according to the designed prototype. The manufacturing process encompasses measuring, cutting, welding, and drilling, with the machine predominantly constructed from metals. It employs a DC motor to facilitate the rotation of the diamond blade, substituting conventional wheel cutters. This design markedly diminishes the necessity for physical labour and enables bottles to be severed in under one minute. The cutter accelerates the procedure, yielding a superior finish with reduced physical exertion. The design and analysis of the prototype have been successful. Potential enhancements may involve the integration of a safety button, applying a coolant to inhibit the dispersion of glass dust, and including a polishing mechanism for smoother edges. These upgrades would boost the machine's efficiency and desirability.

Manuscript Received: 3 December 2024, Accepted: 4 February 2025, Published: 15 March 2025, ORCiD: 0000-0002-9700-0714

Modelling of Water Droplet Wettability on Anti-wetting Sheet of Sand/HDPE

Sat, 15 Mar 2025 00:00:00 +0800

High-density polyethene (HDPE) is widely used in personal protective equipment due to its distinctive mechanical and physical properties. In medical applications, its hydrophobic properties are precious for repelling body fluids and maintaining cleanliness. For instance, HDPE is used in coveralls, which require a durable material that protects against liquids and droplets. To further improve HDPE's performance, fillers can be added to enhance its mechanical and surface properties. One important characteristic to investigate is its wettability, which affects how fluids interact with the surface. In this study, computational simulations were conducted to assess the wettability of HDPE by measuring contact angles. These results were validated against published experimental data. The findings show that the contact angles from the simulations closely matched the experimental values, indicating that the computational method can successfully predict the wettability of HDPE and HDPE reinforced with sand fillers without extensive experimentation.

Manuscript Received: 5 January 2025, Accepted: 13 February 2025, Published: 15 March 2025, ORCiD: 0000-0002-9700-0714

E-Commerce Customer Segmentation: A Clustering Approach in A Web-Based Platform

P. Rajapandian, A. Karunamurthy, V. Vasanth, M. Meganathan — Sat, 15 Mar 2025 00:00:00 +0800

This study develops a K-means clustering model to segment e-commerce customers into distinct personality groups (e.g., Platinum, Gold, Silver, Bronze). The model utilizes a dataset encompassing customer demographics (income, age, family size), spending behavior (total expenditure, product preferences), customer tenure, and engagement with marketing campaigns (campaign responses). Model accuracy is evaluated through comparison of predicted cluster assignments to established customer segment characteristics. A web application, built with the Flask framework, provides an interactive interface allowing users to input new customer data for personalized predictions and detailed cluster-specific insights regarding product preferences, campaign responsiveness, and suggested marketing strategies. The application outputs cluster assignments, key spending/purchase tendencies, typical campaign response profiles within a respective segment, and prioritized product recommendations. Findings demonstrate the model's ability to effectively group customers with theoretical implications and suggests potential for improving targeted marketing campaigns. This work highlights the application of K-Means clustering with a practical online platform through an implemented web app for data visualization. Acknowledged limitations in the generalizability of the dataset to the entire customer base are addressed.

Manuscript Received: 22 November 2024, Accepted: 13 February 2025, Published: 15 March 2025, ORCiD: 0000-0001-6667-3011

Model Based Implementation of Wireless Power Transfer System for Charging of E-Vehicles

Alok Kumar Mohanty — Sat, 15 Mar 2025 00:00:00 +0800

The popularity of electric vehicles has been increasing day by day due to the effect of the pollution caused by the fossil fuels. In the present scenario the difficulty arising in the use of the electric based transportation is the unavailability of the charging stations. So wireless charging system have emerged as one of the solutions for charging of electricity based vehicles. Wireless based electric vehicles come with an opportunity of charging those vehicles that can have the priority of not having charging plugs. Wireless charging technology comes with an option of spark free operation, reliable and user friendly as compared to the plug charging option. This technology makes use of a common charger that can be used for all types of electric operated vehicles. Wireless power transfer technology requires design of inductive coils which involves proper selection of inductances values. A high frequency full bridge converter has to be tuned for wireless power transfer between the transmitter and receiver coils. This paper presents an effective way of charging electric vehicles that has been implemented in Matlab/Simulink simulations. Rigorous simulations were carried out and analysis were conducted to evaluate the system's performance.

Manuscript Received: 13 February 2025, Accepted: 28 February 2025, Published: 15 March 2025, ORCiD: 0000-0002-9882-6040

Mesh Convergence Analysis on The Aerodynamic Performance of A Sedan Vehicle

Afzatul Najwa Nor Azman, Kausalyah Venkatason, Shasthri Sivaguru — Sat, 15 Mar 2025 00:00:00 +0800

This article performs a comprehensive mesh convergence analysis on the aerodynamic efficiency of sedan vehicles. Leading CAD and CFD tools, such as CATIA and ANSYS Fluent are used to model the geometry and run the aerodynamic simulations. The simulations are centred on evaluating the drag coefficient (Cd) for four different sedan profiles. A full scale and half scale profile model configuration were used to analyse and assess the simulations’ impact precision and computational efficiency. A thorough mesh sensitivity investigation is conducted to determine the effect and influence of the element sizing on Cd precision and processing time. The finding points to an element size of 0.5 m, as the optimal choice offering a balance between computational resource efficacy and precision on aerodynamic predictions. The full-scale model reduces the computational time significantly without compromising accuracy hence making it the selected choice for the aerodynamic simulations. The findings of this study underscore the importance of selecting an appropriate mesh element size for vehicle aerodynamic model. This study recommends a 0.5 m element size for future aerodynamic evaluations, thereby improving the equilibrium between simulation accuracy and computational cost in sedan aerodynamics.

Manuscript Received: 27 January 2025, Accepted: 3 March 2025, Published: 15 March 2025, ORCiD: 0000-0001-9707-0782