IIUM Engineering Journal
type: channel
description: The IIUM Engineering Journal, published tri-annually (January, May and September), is a double-blind peer-reviewed open-access journal of the Kulliyyah of Engineering, International Islamic University Malaysia (IIUM). Our next issue will be on September 2026 We are currently indexed in: Scopus (Since 2016) MyCite WoS(Emerging Sources Citation)
publisher: IIUM Press, IIUM, Malaysia
language: en-US
publication name: IIUM Engineering Journal
issn: 1511-788X
items: Editorial Message Vol. 27 No. 2 2026: Engineering for Resilient, Intelligent, and Sustainable Futures
items: Eco-Friendly Asphalt Mixture: Utilization of Waste Polypropylene as a Partial Replacement of Aggregate
items: Enhancement of Stabilization/Solidification Method with Bioaugmentation for Sludge Remediation
items: A Robust Sensor-Failure-Tolerant Fuzzy Control Framework with Predictive Data Imputation for Sustainable Precision Irrigation
items: Steering Control Precision in Rack Steering Vehicles Using Finite-Time Prescribed Performance Anti-Windup PI Controller with Nonlinear Error Transformation
items: Quantifying Activity of the Erector Spinae Longissimus Subgroup Using EMG During Prolonged Driving
items: Integration of Neutrosophic Methods into Adaptive Control of Nonlinear Systems Using Neuro-Fuzzy Networks With B-Spline Functions
items: A Comprehensive Framework of Ant Colony Optimisation for Optimal Control of Upper Extremity Rehabilitation Robot
items: Optimal and Robust Speed Control of Electric Vehicles using a Hybrid Ant Colony Optimization Tuned Sliding Mode Control
items: Solid-state Fermentation for Production of Bio-coagulant on Rice Bran using Candida utilis, Trichoderma sp., Phanerochaete chrysosporium for Turbidity Removal
items: Optimization and Scale-Up of Solid-State Bioconversion for Microbial Coagulant Production toward Sustainable Water Treatment
items: Optimum Alert For In-Vehicle Safety Technologies
items: Field and Laboratory Evaluation of Reliability in a Novel Cone Deployment System for Safer Highway Operations
items: Analytical and Flight Test-Based Dynamic Characteristic Identification of a Small Fixed-Wing UAV
items: Impact of Aggressive and Moderate Driving Intensity on Vehicle Air–Fuel Ratio Stability
items: Design Optimization and Structural Evaluation of a Hybrid Frame for Next-Generation Electric Scooters
items: Scalable Multi-Objective Optimization for Facility Location Using A Metaheuristic Technique
items: Magnetic Resonance Imaging and Ultrasound-based Breast Tumor Classification using Soft Voting Ensemble Deep Learning Method
items: New Control Strategy of Battery Energy Storage System in Microgrids Integrated with Wind and Solar Power Plants
items: Comparative Performance Analysis of Forward Error Correction Schemes in AX.25-Based APRS Communication Systems with AFSK Modulation using GNU Radio Simulation
items: Quantitative Assessment of Coffee Quality Using Microwave Non-Destructive Testing
items: Experimental Validation of a Labview-Based SFCW Software-Defined Radar System
items: Raindrop Size Distribution and Wind-Driven Rain Specific Attenuation: CCDF-Based Analysis at 18 and 38 GHz in Tropical Country
items: MultiModal Explainable AI and Blockchain Integration for Automated Halal Verification of Cosmetic Products
items: Generative AI Models: A Comparison of Application Analysis on Web AI-Based Decision Support Systems for Satellite Anomaly Identification
items: PromptLessSAM: From Foundational Model to Domain Expert via Lightweight Decoder Adaptation for Crack Segmentation
items: Stability-Aware Evaluation of a CNN–LSTM–DQN Intrusion Detection System for Zero-Day and Drifted Network Traffic
items: A Robust Low-Complexity Star Centroiding Algorithm for Autonomous Navigation under Lunar Noise Conditions
items: Efficiency-Aware Multi-Class Spinal Disorder Classification Using CBAM-Enhanced Lightweight CNNs with Dual-Branch Fusion
items: TSGL-Rust: Teaching Concurrency Through Compile-Time Enforcement via Rust-Based Visualization of Classical Synchronization Problems
items: Constant-Time Bitsliced Rijndael-256 on ARM Cortex-M4: On the Limitations of Fixslicing Beyond AES-128

Editorial Message Vol. 27 No. 2 2026: Engineering for Resilient, Intelligent, and Sustainable Futures
type: item
description: It is with great pleasure that we present the May 2026 edition of the IIUM Engineering Journal, an issue that reflects the expanding role of engineering in shaping a more sustainable, intelligent, safe, and resilient future. The contributions in this volume demonstrate that engineering research today is no longer confined to solving isolated technical problems. It is increasingly directed toward systems, communities, environments, and technologies that must perform reliably in complex real-world conditions. A strong sustainability thread runs throughout this issue. Several contributions explore how waste materials, biological resources, renewable energy systems, and intelligent control can be transformed into practical engineering solutions. Studies on microbial bio-coagulant production, sludge remediation, eco-friendly asphalt mixtures, precision irrigation, and energy storage control for renewable microgrids show that sustainable engineering requires more than good intentions. It requires process optimization, material innovation, system-level thinking, careful validation, and the courage to rethink conventional practices. This issue also highlights the growing maturity of intelligent and data-driven engineering. Artificial intelligence, machine learning, deep learning, foundation models, blockchain, and optimization techniques are applied across diverse problems, including medical image classification, spinal disorder diagnosis, halal verification, satellite anomaly identification, crack segmentation, intrusion detection, facility location, and autonomous navigation. These works show a clear movement beyond algorithmic novelty toward explainability, robustness, efficiency, and practical deployment. In this sense, intelligence is not treated merely as computational performance, but as a means to support better decisions, safer systems, and more trustworthy engineering outcomes. Equally important is the emphasis on safety, resilience, and trust. The papers on commu…
creator: Teddy Surya Gunawan
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
doi: 10.31436/iiumej.v27i2.4413

Eco-Friendly Asphalt Mixture: Utilization of Waste Polypropylene as a Partial Replacement of Aggregate
type: item
description: Recently, many techniques have been developed to improve the properties of asphalt pavement and to reduce environmental pressure. Adding waste polypropylene (WPP) to asphalt mixtures is one of the most often used and effective techniques. Nevertheless, waste plastic aggregate in flake form exhibited the worst performance in the asphalt mixture, as demonstrated in previous investigations. Therefore, a new recycling process is used in this research to produce crushed and angular WPP aggregate (WPPA) with controlled dimensions, usually ranging from 0.075?mm to 12.5?mm, similar to those of natural aggregate. WPPA is used as a partial replacement for coarse aggregates, fine aggregates, and mineral filler, replacing all aggregate sizes from 12.5 mm to less than 0.075 mm. Modified asphalt mixture was designed with replacement proportions of 4%, 6%, and 8% for coarse WPPA; 2%, 4%, and 6% for fine WPPA; and 0.5%, 0.75%, and 1.0% for filler WPPA by the weight of the asphalt mixtures. An abrasion test was performed to assess the resistance and durability of WPPA to tearing and wear. Marshall and indirect tensile strength tests were employed to assess the performance of control and WPP-modified mixtures. Compared to the control mixture, WPPA incorporation provided greater stability and higher stiffness. For instance, notable increases in stability (up to 34.8%) and stiffness (up to 42.8%) were observed upon replacing fine aggregates with 2% WPPA in the asphalt mixture. In addition, a significant enhancement in the resistance of WPPA-modified mixture against moisture damage was achieved as the tensile strength ratio (TSR) was increased substantially, especially at replacement ratios of 4% coarse WPPA, 2% fine WPPA, and 0.75% filler WPPA, where TSR was increased by 14.4%, 10.9%, and 8.8%, respectively. In conclusion, WPPA-modified mixtures are less susceptible to moisture damage with higher stability and stiffness. ABSTRAK: Dalam beberapa tahun terakhir, banyak teknologi telah di…
creator: Israa Daryul
creator: Roaa Latief
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 31
ending page: 50
doi: 10.31436/iiumej.v27i2.3843

Enhancement of Stabilization/Solidification Method with Bioaugmentation for Sludge Remediation
type: item
description: The Stabilization/Solidification (S/S) method encapsulates heavy metals in sludge, while bioaugmentation can degrade organic contaminants. However, each method is limited in its ability to address both contaminants simultaneously. This study aims to enhance the S/S method by integrating bioaugmentation, using either immediate or pre-inoculation of bio-agents. Ordinary Portland Cement (OPC) served as the binder in the S/S process, with the bacteria Sphingobacterium spiritivorum and the fungi Aspergillus brasiliensis acting as bio-agents. Before testing, chemical oxygen demand (COD) and heavy metals in sludge and cement were measured. COD and heavy metal concentrations' leaching behavior were tested using TCLP after 14 and 28 days. The result shows 23.39% of organic contaminants were in the fibreboard sludge. The TOC results for Portland cement were negligible. All heavy metal elements (Cr, Cu, Zn, As, and Pb) in the Portland cement and fibreboard sludge exceeded the standard USEPA limit. COD reduction was evaluated for immediate versus pre-inoculation of fungi and bacteria over 14 and 28 days. Pre-inoculation consistently yielded lower COD levels than immediate inoculation, with fungi pre-inoculation achieving the greatest reduction (579 mg/L at 14 days; 544.7 mg/L at 28 days) and bacteria pre-inoculation showing moderate improvement (579.3 mg/L at 14 days; 570.3 mg/L at 28 days). Concentrations of heavy metal reductions followed a similar trend: after 28 days, pre-inoculated samples contained 0.01 mg/L (Cr), 0.22 mg/L (Cu), 0.06 mg/L (Zn), and 0 mg/L for both As and Pb, whereas immediate-inoculated samples showed 0.04 mg/L (Cr), 0.22 mg/L (Cu), 0.01 mg/L (Zn), and 0 mg/L for As and Pb. Statistical comparison shows significant differences between immediate-inoculation and pre-inoculation, but not between the bio-agents used in this study. To improve the findings, a co-culture method that combines both bio-agents is recommended, offering a viable strategy for industri…
creator: Muhammad Hasanuddin Mohd Kamal
creator: Nasuha Mohd Rais
creator: Nor Amani Filzah Mohd Kamil
creator: Nur Fateha Md Nor
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 51
ending page: 73
doi: 10.31436/iiumej.v27i2.3858

A Robust Sensor-Failure-Tolerant Fuzzy Control Framework with Predictive Data Imputation for Sustainable Precision Irrigation
type: item
description: Effective irrigation management under uncertain conditions remains a major challenge in precision agriculture, particularly when sensor performance degrades or extreme environmental variations lead to unreliable data. This study presents a hybrid framework that combines a linear regression model with a Mamdani fuzzy inference system (FIS) to improve the robustness of soil moisture prediction and irrigation control. The proposed approach trains the regression model using synthetically generated data with controlled noise levels to estimate soil moisture conditions. These predictions are then integrated with real-time temperature and humidity data within the fuzzy inference system to generate appropriate irrigation decisions. To represent extreme sensor conditions, additional adaptive noise is introduced when soil moisture values exceed or fall below predefined thresholds, effectively simulating sensor malfunction scenarios. Time-series simulation results indicate that the proposed system can maintain stable, efficient irrigation performance despite significant sensor disturbances. Overall, this work improves irrigation efficiency and provides insights into how hybrid statistical and fuzzy-logic approaches can mitigate the adverse effects of sensor inaccuracies under highly variable environmental conditions. ABSTRAK: Pengurusan pengairan cekap berkeadaan tidak menentu, kekal sebagai cabaran kritikal dalam pertanian, terutama apabila berlaku kerosakan pada sensor dan persekitaran turun naik yang melampau menyebabkan data yang diperolehi tidak boleh dipercayai. Kajian ini, mencadangkan pendekatan hibrid yang mengintegrasi model regresi linear dengan sistem inferens Mamdani kabur (FIS) bagi meramal kelembapan tanah dan mengawal pengairan. Kaedah ini melibatkan latihan model regresi menggunakan data sintetik yang terhasil melalui tahap bunyi yang dikawal dengan teliti bagi meramal kelembapan tanah, sementara sistem inferens kabur secara dinamik menterjemah ramalan tersebu…
creator: Indra Laksmana
creator: Swivano Agmal
creator: Rosda Syelly
creator: Melda Amalia
creator: Perdana Putera
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 467
ending page: 478
doi: 10.31436/iiumej.v27i2.3647

Steering Control Precision in Rack Steering Vehicles Using Finite-Time Prescribed Performance Anti-Windup PI Controller with Nonlinear Error Transformation
type: item
description: This paper addresses the challenge of maintaining steering precision and yaw stability in rack steering vehicles (RSVs) operating under varying inertial loads and aerodynamic disturbances. Conventional control methods often struggle to ensure bounded tracking performance in the presence of actuator saturation and nonlinear dynamics. To overcome these limitations, a Finite-Time Prescribed Performance Anti-Windup PI Controller with Nonlinear Error Transformation (FPPC-API-NET) is proposed. The outer loop employs a finite-time prescribed performance framework with a nonlinear transformation to constrain the error trajectory within predefined decay envelopes, while the inner loop incorporates antiwindup compensation to mitigate actuator saturation effects. Simulation studies benchmarked against the FTPPC-API and API controllers demonstrate that FPPC-API-NET achieves up to a 95% reduction in steady-state error, a 70% reduction in settling time, and a 87% reduction in transient duration. The proposed method also enhances yaw stability, reduces lateral displacement by 35%, minimizes sideslip magnitude, and maintains tire-friction utilization below saturation, resulting in smoother lateral acceleration with up to 48% lower peaks. These results confirm that FPPC-API-NET offers superior robustness and precision during cornering maneuvers across varying inertia levels. ABSTRAK: Kajian ini membincangkan cabaran dalam mengekalkan ketepatan kawalan stereng dan kestabilan sudut gerakan sisi bagi kenderaan jenis rak stering (RSV) yang beroperasi di bawah beban inersia berubah serta gangguan aerodinamik. Kaedah kawalan konvensional sering menghadapi kesukaran mengekalkan prestasi penjejakan apabila berlaku ketepuan aktuator dan kesan dinamik tak linear. Bagi mengatasi kekurangan ini, satu pengawal tirus berasaskan Finite-Time Prescribed Performance dengan Transformasi Ralat Tak Linear dan Antiwindup PI (FPPC-API-NET) telah dicadangkan. Gelung luar menggunakan rangka kerja prestasi t…
creator: Addie Irawan
creator: Norsharimie Mat Adam
creator: R.M.T Raja Ismail
creator: Aliza Che Amran
creator: Mohd Iskandar Putra Azahar
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 479
ending page: 495
doi: 10.31436/iiumej.v27i2.3982

Quantifying Activity of the Erector Spinae Longissimus Subgroup Using EMG During Prolonged Driving
type: item
description: Prolonged driving has been associated with localized muscle fatigue, particularly in the lumbar region, posing safety and ergonomic concerns. This study investigates the dynamics of multivariate surface electromyography (sEMG) features to detect fatigue during extended driving sessions. EMG signals were recorded from the erector spinae muscles of seven subjects across two backrest inclination angles (100°, 110°) during real-world, multi-hour driving tasks. Spectrogram-based features, including mean frequency (MNF), median frequency (MDF), and root-mean-square (RMS), were extracted using a sliding-window method for analysis. Co-temporal trends in these features were analyzed to identify fatigue regions, marked by simultaneous decreases in MNF and MDF and/or increases in RMS. Paired t-tests were used to compare the two backrest inclination angles across subjects for each fatigue duration and fatigue event count. Results demonstrate that seat inclination angle significantly affects fatigue duration and number of events, with the 100° angle leading to notably more fatigue than 110° (p<0.01). This work could contribute a framework for time-resolved, EMG fatigue modeling in realistic driving scenarios. ABSTRAK: Pemanduan terlalu lama dikaitkan dengan keletihan otot setempat, khususnya di bahagian lumbar, menimbulkan kebimbangan dari segi keselamatan dan ergonomik. Kajian ini mengkaji dinamika ciri permukaan multivarian elektromiografi (sEMG) bagi mengesan keletihan semasa sesi pemanduan jauh. Isyarat EMG direkodkan daripada otot erektor spina dari 7 subjek pada dua sudut kecondongan penyandar (100°, 110°) semasa aktiviti pemanduan sebenar berlangsung selama beberapa jam. Ciri berasaskan spektrogram, termasuk frekuensi purata (MNF), frekuensi median (MDF) dan purata punca kuasa dua (RMS) telah diekstrak menggunakan tetingkap-gelongsor. Corak serentak dalam ciri-ciri ini dianalisa bagi mengenal pasti kawasan keletihan, dibuktikan dengan penurunan MNF dan MDF serta/atau peni…
creator: Muhammad Alfatih Eltayeb
creator: Nur Liyana Azmi
creator: Ahmad Jazlan
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 496
ending page: 505
doi: 10.31436/iiumej.v27i2.3991

Integration of Neutrosophic Methods into Adaptive Control of Nonlinear Systems Using Neuro-Fuzzy Networks With B-Spline Functions
type: item
description: This paper addresses the problem of adaptive control of nonlinear dynamic systems operating under parametric uncertainty, external disturbances, and partial or contradictory information about the system state – conditions under which classical linear Model Reference Adaptive Control (MRAC) and conventional neuro-fuzzy controllers exhibit degraded performance, slow adaptation, and oscillatory behavior. To overcome these limitations, a novel Neuro-Neutrosophic Model Reference Adaptive Controller (NN-MRAC) is proposed, implemented using a neutrosophic neuro-fuzzy network with B-spline basis functions. The key innovation of the proposed approach lies in integrating neutrosophic logic into the adaptive control architecture by explicitly using a three-component uncertainty representation – truth, indeterminacy, and falsity – which enables robust control synthesis in the presence of incomplete, noisy, and conflicting data. In contrast to traditional neuro-fuzzy controllers, the proposed NN-MRAC combines localized B-spline approximation with neutrosophic weighting of local models and an adaptive decomposition into lower-dimensional submodels, effectively mitigating the curse of dimensionality and reducing computational complexity. Comparative simulation studies with a classical linear MRAC demonstrate that the proposed controller reduces the mean-square tracking error by approximately 59%, decreases overshoot by more than 3 times, shortens the transient response time by nearly 1.8 times, and lowers control energy consumption by about 18%. The results confirm that the proposed neuro-neutrosophic MRAC ensures stable, smooth, and energy-efficient control in the presence of noise and deep uncertainty, making it a promising solution for intelligent control of complex nonlinear systems. ABSTRAK: Kajian ini mencadangkan masalah kawalan adaptif bagi sistem dinamik bukan linear yang beroperasi pada ketidakpastian parameter, gangguan luaran, serta maklumat separa atau bercanggah meng…
creator: Oksana Porubay
creator: Dilnoza Umurzakova
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 506
ending page: 528
doi: 10.31436/iiumej.v27i2.4021

A Comprehensive Framework of Ant Colony Optimisation for Optimal Control of Upper Extremity Rehabilitation Robot
type: item
description: Passive rehabilitation of the upper limb requires precise joint positioning to facilitate motor recovery and ensure patient safety. For a two-degree-of-freedom (DOF) elbow robot, the primary challenge is unwanted disturbances arising from human coupling and voluntary and involuntary forces applied by the subject. This study addresses this issue by proposing a comprehensive control framework based on a nature-inspired meta-heuristic approach. The robot dynamics were obtained using the Lagrangian formulation, which was then combined with a realistic actuator model, yielding a closed-loop transfer function that describes system behavior. A two-degree-of-freedom (2-DOF) PID controller was used as the position controller. To determine the optimal PID parameters, an ant colony optimization (ACO) algorithm is used with an appropriate performance index to select the PID parameter values. The resulting ACO-based PID controller showed significant improvement over the conventional Ziegler–Nichols (Z-N) approach, as it could reject significant patient-induced forces, maintain the joint trajectory with the reference, and remain stable even under perturbations. Simulations were performed, confirming that the optimized controller delivers smooth, precise movements, reduces tracking error, and enhances the safety of passive rehabilitation procedures. ABSTRAK: Pemulihan secara pasif di bahagian anggota atas pesakit memerlukan kedudukan sendi yang tepat bagi memudahkan pemulihan motor pesakit daripada bahaya atau cedera. Manakala pada robot siku dua darjah kebebasan (DOF), cabaran utama ialah mengelakkan gangguan yang tidak diingini oleh manusia dan daya sukarela atau tidak sukarela yang dikenakan oleh subjek. Kajian ini mencadangkan rangka kerja kawalan komprehensif berdasarkan pendekatan meta-heuristik yang diilham oleh alam semula jadi. Dinamik robot diwujudkan dengan menggunakan rumusan Lagrangian, diikuti dengan gabungan model penggerak realistik, agar dapat menghasilkan fungsi …
creator: Muhammad Kamran Joyo
creator: Izanoordina Ahmad
creator: Kushsairy Abdul Kadir
creator: Talha Ahmed Khan
creator: Noaman M Noaman
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 529
ending page: 544
doi: 10.31436/iiumej.v27i2.4134

Optimal and Robust Speed Control of Electric Vehicles using a Hybrid Ant Colony Optimization Tuned Sliding Mode Control
type: item
description: Electric vehicle (EV) speed control is significantly affected by nonlinear motor dynamics, external disturbances, and parameter uncertainties, which degrade tracking performance and energy efficiency. Conventional controllers often fail to maintain robustness under varying operating conditions. Although Sliding Mode Control (SMC) provides strong robustness, it suffers from chattering and requires proper tuning of control parameters. To address this, a hybrid Ant Colony Optimization-based Sliding Mode Controller (ACO-SMC) is proposed to optimally tune the SMC control parameters. The performance of the ACO-SMC controller is evaluated using the US06 and FTP-75 driving cycles in MATLAB Simulink. The proposed controller outperforms the ACO-tuned proportional-integral-derivative (ACO-PID), conventional SMC, and PID controllers. The ACO-SMC controller significantly improves stabilization and robustness, even in the presence of measurement noise, external disturbance, and varying vehicle parameters. The results reveal that the hybrid ACO-SMC controller effectively minimizes chattering and maintains accurate speed control, even during sudden load disturbance and reference speed variations across all examined driving cycles. The integral absolute error (IAE) and integral squared error (ISE) are used as performance indices, achieving their minimum values over the complete US06 and FTP-75 driving cycles, thereby confirming the high accuracy of the proposed approach. ABSTRAK: Kawalan kelajuan kenderaan elektrik (EV) dipengaruhi secara signifikan oleh dinamik motor tidak linear, gangguan luaran, serta ketidakpastian parameter, seterusnya menjejaskan prestasi penjejakan dan kecekapan tenaga. Pengawal konvensional lazimnya gagal mengekalkan keteguhan di bawah operasi yang berubah-ubah. Walaupun Kawalan Mod Luncur (SMC) menawarkan keteguhan yang tinggi, kaedah ini mengalami masalah chattering dan memerlukan penalaan parameter kawalan yang teliti. Bagi mengatasi isu ini, satu pengawa…
creator: Parthiban S
creator: Krishna S
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 545
ending page: 559
doi: 10.31436/iiumej.v27i2.4136

Solid-state Fermentation for Production of Bio-coagulant on Rice Bran using Candida utilis, Trichoderma sp., Phanerochaete chrysosporium for Turbidity Removal
type: item
description: Solid-state fermentation is a microbial culture technique used to produce compounds and products of industrial interest. In this study, rice bran, a by-product of the rice processing industry, was used as a coagulant substrate for Candida utilis, Trichoderma sp., and Phanerochaete chrysosporium in solid-state fermentation (SSF). To the best of our knowledge, no study has reported the production of coagulants by Trichoderma sp. and Candida utilis. Moreover, no attempts have been made to utilize rice bran as a substrate for the production of coagulants in solid-state by these three microorganisms. Two different substrate proportions were used to produce natural coagulants. Bio-coagulants produced in this research were used to remove turbidity from the kaolin solution. The experiments were conducted with artificially turbid water and a conventional jar test apparatus. The findings demonstrate that Substrate 2, distinguished by its lower water content, exhibited the highest turbidity removal efficiency compared to Substrate 1, which possessed higher water content. Moreover, Trichoderma sp. showed a maximum turbidity removal of 71%. While the maximum turbidity removal by the coagulants produced from C. utilis and P. chrysosporium was 59 %. The microscopic observation of the microorganism’s growth on rice bran substrate has also been performed. It was revealed that the three microorganisms fully colonized the substrate surface. Further optimization of the SSF process parameters is expected to achieve efficient turbidity reduction in wastewater. ABSTRAK: Penapaian keadaan pepejal ialah teknik kultur mikrob yang digunakan untuk menghasilkan sebatian dan produk yang mempunyai kepentingan industri. Dalam kajian ini, dedak padi, iaitu hasil sampingan daripada industri pemprosesan beras, digunakan sebagai substrat koagulan bagi Candida utilis, Trichoderma sp., dan Phanerochaete chrysosporium dalam penapaian keadaan pepejal (solid-state fermentation, SSF). Sepanjang pengetahuan …
creator: Radhia Nedjai
creator: Abdullah Al Mamun
creator: Md Zahangir Alam
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 1
ending page: 14
doi: 10.31436/iiumej.v27i2.4154

Optimization and Scale-Up of Solid-State Bioconversion for Microbial Coagulant Production toward Sustainable Water Treatment
type: item
description: Microbial coagulants are emerging as an eco-friendly alternative to chemical coagulants owing to their non-toxicity, biodegradability, and sustainability. However, their use is limited by high production costs linked to expensive nutrient media and scalability issues. To address these challenges, this study developed a cost-effective microbial coagulant based on a fungus using cocopeat as a substrate. Growth conditions (malt extract, glucose, and pH) were optimized using the Face-Centered Central Composite Design (FCCCD) under Response Surface Methodology (RSM) to maximize coagulant yield. The performance in water treatment was evaluated using jar tests, and large-scale production techniques were investigated using a tray bioreactor and an agitated drum bioreactor (ADB). The fungal strain used in this study was identified as Phanerochaete concrescens, which demonstrated high turbidity-reducing efficiency, achieving a maximum flocculating activity of 93.06% in a standard jar test. These results were obtained under statistically optimized growth conditions, specifically 5 days of incubation at 25°C, 70% moisture content, 3% malt extract, 2.5% glucose, and pH 7, confirming model predictions. Phanerochaete concrescens was successfully scaled using a tray fermenter, achieving a flocculation rate of 92% after 5 days of incubation at 70% moisture, pH 7, and a 3 cm substrate thickness. However, in a 30 L agitated bioreactor drum, flocculating activity was recorded at 29% due to insufficient fungal growth at the tested agitation rate. This study confirms the feasibility of a cost-effective microbial coagulant that can be scaled appropriately, offering a sustainable and biodegradable alternative to chemical coagulants. ABSTRAK: Koagulan mikrob muncul sebagai alternatif mesra alam pada koagulan kimia kerana sifatnya yang tidak toksik, terbiodegradasi, dan mampan. Walau bagaimanapun, penggunaannya terhad kerana kos pengeluaran tinggi disebabkan oleh media nutrien yang mahal dan…
creator: Maroua Fellah
creator: Md Zahangir Alam
creator: Abdullah Al Mamun
creator: Abdelmohsen Benoudjit
creator: Nassereldeen Ahmed Kabbashi
creator: Nurul Sakinah Engliman
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 15
ending page: 30
doi: 10.31436/iiumej.v27i2.4237

Optimum Alert For In-Vehicle Safety Technologies
type: item
description: Vehicle safety technologies have played a critical role in protecting vehicle drivers for several decades. Auditory signals, for example, convey relevant data to the driver without interfering with the driving task. Vehicle auditory alerts help ensure the safest driving experience possible by providing warnings, thereby reducing road accidents caused by reckless or careless driving. Nonetheless, auditory alerts have long been a source of contention in vehicle safety features due to driver annoyance and false-alarm issues. This study aims to investigate drivers’ awareness and perceptions of in-vehicle safety technology and auditory alerts, and how these factors affect drivers’ reactions to the driving environment. A structured questionnaire was designed and distributed to 150 licensed drivers to collect data on their exposure to safety features, perceived usefulness and urgency of alerts, and preferred auditory characteristics. Descriptive and comparative analyses were conducted to evaluate drivers’ perceptions alongside benchmark data from Original Equipment Manufacturers (OEMs). Results show that 87% of respondents are aware of major in-vehicle safety technologies, yet 48.7% perceive them as potentially distracting while driving. Findings also identify 1000 Hz at 65 dB as the preferred auditory frequencies for safety alerts based on user responses. This study provides insights for policymakers, manufacturers, and safety stakeholders to enhance the design, acceptance, and effectiveness of in-vehicle auditory warning systems. ABSTRAK: Teknologi keselamatan kenderaan memainkan peranan penting dalam melindungi pemandu melalui ciri amaran seperti isyarat auditori yang menyampaikan maklumat keselamatan tanpa mengganggu tugas pemanduan. Walaupun amaran auditori dapat membantu mengurangkan risiko kemalangan jalan raya, isu seperti gangguan kepada pemandu dan amaran palsu masih menjadi cabaran utama. Kajian ini meneliti tahap kesedaran dan persepsi pemandu terhadap teknolog…
creator: Noor Irza Mohd Zaki
creator: Mohd Khairi Abu Husain
creator: Nurulakmar Abu Husain
creator: Siti Mahirah Che Husin
creator: Yahaya Ahmad
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 377
ending page: 396
doi: 10.31436/iiumej.v27i2.3968

Field and Laboratory Evaluation of Reliability in a Novel Cone Deployment System for Safer Highway Operations
type: item
description: This study evaluates the reliability and maintainability of the Cone Collecting and Laying (C2L) machine, developed to enhance safety and efficiency in highway maintenance operations by automating the deployment of traffic cones. The objective is to investigate the use of reliability metrics, which are Mean Time to Failure (MTTF), Mean Time to Repair (MTTR), and Mean Time Between Failures (MTBF), as a systematic approach to assess the operational efficiency and failure behavior of the C2L machine in real highway maintenance scenarios. The methodology encompasses controlled laboratory and field testing conducted over 68 hours in Test Motion A and 3,192 hours in Test Motion B. During these tests, real-time failure data were recorded for six critical components of the C2L machine, namely the bearing, cone lifter, chain, sensor, PLC, and hook spring. Findings from Test Motion A revealed component vulnerabilities, including a low MTTF in bearings and a high MTTR in welded joints. In contrast, Test Motion B identified frequent failures in the PLC system, attributed to vibration stress, as well as a rare but critical hook spring failure caused by material fatigue. All reliability metrics were calculated from empirical failure and repair times, enabling accurate quantification of component durability and overall system availability. Failure data were further categorized into repairable and non-repairable types to inform targeted design improvements. In conclusion, integrating MTTF, MTTR, and MTBF into the evaluation of the C2L machine proved essential for identifying weaknesses and enhancing operational performance. The study recommends proactive maintenance scheduling, structural reinforcement, and redesign of vulnerable components to ensure system resilience. These findings contribute to improved worker safety, reduced operational downtime, and the enhanced long-term deployment potential of the C2L machine in highway maintenance applications. ABSTRAK: Kajian ini menilai k…
creator: Azilah Ismail
creator: Mohd Azli Salim
creator: Nor Azmmi Masripan
creator: Mohd Zaid Akop
creator: Siti Wardatulaina Mohd Yusof
creator: Chonlatee Photong
creator: Alan Watson
creator: Mohammed Hussin A. Al-Mola
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 397
ending page: 414
doi: 10.31436/iiumej.v27i2.3971

Analytical and Flight Test-Based Dynamic Characteristic Identification of a Small Fixed-Wing UAV
type: item
description: Reliable and efficient UAV flight control design requires accurate knowledge of the vehicle’s dynamic characteristics, which are rarely provided by manufacturers and must therefore be determined independently. These characteristics can be obtained through analytical calculations, wind tunnel testing, and flight testing. However, in small UAV development, the process is often simplified by skipping directly to flight tests for control tuning, without first examining the underlying dynamic behavior. To address this gap, this research compares the dynamic characteristics derived from analytical calculations and flight testing. The case study focuses on BRIN’s bMFE-UAV, in which longitudinal and lateral/directional dynamics are identified using control-surface deflections as inputs and measured responses of speed, altitude, attitude, acceleration, and rotational rate as outputs. Results reveal consistent oscillatory behaviors: two oscillatory modes in longitudinal dynamics and, in lateral/directional dynamics, one oscillatory mode accompanied by two non-oscillatory modes. Only the damping ratio of the short-period mode showed close agreement (<10% difference), while other parameters exhibited substantial discrepancies. The discrepancies demonstrate the limitations of analytical methods in accurately reflecting real flight dynamics, reinforcing the necessity of flight testing to ensure reliable data for small UAV flight-control design. ABSTRAK: Reka bentuk kawalan penerbangan UAV yang boleh dipercayai dan cekap memerlukan pengetahuan tepat pada ciri dinamik kenderaan. Ianya jarang didapati daripada pengeluar dan oleh itu mesti ditentukan secara bebas. Ciri-ciri ini boleh diperolehi melalui pengiraan analitika, ujian terowong angin, dan ujian penerbangan. Walau bagaimanapun, dalam pembangunan UAV kecil, prosesnya sering dipermudahkan dengan melangkau terus ke ujian penerbangan bagi kawalan penalaan, tanpa terlebih dahulu memeriksa tingkah laku dinamik. Kajian ini bertujua…
creator: Eries Bagita Jayanti
creator: Yazdi Ibrahim Jenie
creator: Ardian Rizaldi
creator: Novita Atmasari
creator: Fuad Surastyo Pranoto
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 415
ending page: 433
doi: 10.31436/iiumej.v27i2.4013

Impact of Aggressive and Moderate Driving Intensity on Vehicle Air–Fuel Ratio Stability
type: item
description: Aggressive driving behavior occurs when drivers neglect traffic rules, leading to violations, accidents, and increased road hazards. Such behavior endangers the driver and places other road users at risk. In contrast, moderate driving reflects disciplined patterns that reduce risks and improve vehicle efficiency. This study examines the influence of aggressive and moderate driving behaviors on engine performance, with a focus on air–fuel ratio (AFR) stability. The investigation used On-Board Diagnostics (OBD-II) data collected during 11.7 km driving sessions under two conditions: aggressive and moderate. The test vehicle, equipped with a 1.8-liter engine, was driven at controlled speeds. Aggressive driving was defined as driving in the 60–90 km/h range, while moderate driving occurred below 60 km/h, representing typical urban operation. Results show distinct differences in AFR behavior. Aggressive driving produced greater instability, with richer AFR outliers near 12.5, higher global wavelet spectrum (GWS) peaks of about 40 units compared to 20, and longer time in fuel-rich regions (12–17% versus 5–14%). These fluctuations indicate unstable combustion, increased fuel use, and higher emissions. In contrast, moderate driving maintained a more stable AFR distribution, with a greater proportion of leaner readings (~36% versus 30%) and closer alignment with stoichiometric values. This stability supports improved combustion efficiency, reduced emissions, and better fuel economy. Overall, the findings show that driving intensity significantly influences AFR stability, with moderate driving promoting cleaner and more efficient engine operation. ABSTRAK: Tingkah laku pemanduan agresif berlaku apabila pemandu mengabai peraturan lalu lintas, menyebabkan pelanggaran, kemalangan dan peningkatan bahaya di jalan raya. Tingkah laku sedemikian membahayakan pemandu dan membahayakan pengguna jalan raya lain. Sebaliknya, pemanduan sederhana mengurangkan risiko dan meningkatkan kecekapa…
creator: Mohamad Norsyafiq Ab Hamid
creator: Muhammad Yusri Bin Ismail
creator: Najmi Haziq Badrulhisam
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 434
ending page: 449
doi: 10.31436/iiumej.v27i2.4062

Design Optimization and Structural Evaluation of a Hybrid Frame for Next-Generation Electric Scooters
type: item
description: The increasing adoption of electric scooters has introduced unique challenges in chassis design, where packaging constraints imposed by predefined outer shells often conflict with structural efficiency. This study presents the conceptual design, structural analysis, and validation of a hybrid chassis tailored for an electric scooter within such constraints. The frame integrates a step-through central region with a trellis-inspired rear subframe and a reinforced headstock. Three design iterations were modeled in SolidWorks and evaluated using finite element analysis (ANSYS) for static loads (1–3G), fatigue under cyclic loading, equivalent static impact loads, and modal behavior. Analytical stress checks and literature comparisons supported the simulations. Under 3G static loading, the final steel frame exhibited a maximum deformation of 3.16 mm with a minimum factor of safety of 1.48. Fatigue analysis predicted a life of 1.75 × 10? cycles, while modal analysis confirmed the first natural frequency at 28.56 Hz, above the expected excitation frequencies, and thus free from resonance. Although crash simulations showed localized yielding in severe impacts, the frame maintained integrity under operational conditions. These findings demonstrate that high structural performance can be achieved within strictly styling-defined packaging envelopes, validating the hybrid trellis–step-through configuration for electric scooters. ABSTRAK: Peningkatan penggunaan skuter elektrik telah menyebabkan cabaran unik pada reka bentuk casis, di mana kekurangan pada pembungkusan, yang ditentukan oleh struktur luaran, sering bercanggah dengan kecekapan struktur. Kajian ini membentangkan reka bentuk konseptual, analisis struktur, dan pengesahan bagi casis hibrid yang direka khusus untuk skuter elektrik. Rangka casis ini mengintegrasi bahagian tengah jenis telus langkah dengan subrangka belakang berinspirasi jalaran serta stok kepala yang diperkukuh. Tiga iterasi reka bentuk dimodel menggunakan…
creator: Sridhar R
creator: Mahantesh M Math
creator: Sujan Chakraborty
creator: Sourabha H
creator: Vivekanand S Gog
creator: Jeevathith R
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 450
ending page: 466
doi: 10.31436/iiumej.v27i2.4068

Scalable Multi-Objective Optimization for Facility Location Using A Metaheuristic Technique
type: item
description: Rapid growth in e-commerce and service expectations forces large-scale logistics networks to balance facility operating cost, service coverage, and delivery equity simultaneously. This study aims to develop a scalable discrete multi-objective particle swarm optimization (MOPSO-FLP) framework for constraint-rich facility location problems, where traditional exact approaches become impractical. The proposed method integrates discrete encoding, feasibility repair, adaptive parameter control, and an archive-based leader selection strategy, and it is evaluated using benchmark instances and a national postal logistics network case. Across 30 independent runs, MOPSO-FLP achieves superior convergence and diversity compared with representative multi-objective metaheuristics (e.g., NSGA-II and related baselines), and the deployment validation yields a Pareto set of 47 non-dominated solutions that clearly exposes cost–coverage–equity trade-offs. Overall, the results demonstrate that the proposed framework provides decision makers with interpreted alternatives and actionable policies for large-scale logistics planning. ABSTRAK: Pertumbuhan pesat dalam e-dagang serta peningkatan jangkaan perkhidmatan memaksa rangkaian logistik berskala besar untuk mengimbangi kos operasi fasiliti, liputan perkhidmatan, dan keadilan penghantaran secara serentak. Kajian ini bertujuan membangunkan satu kerangka pengoptimuman zarah berbilang objektif diskret yang berskala, iaitu Multi-Objective Particle Swarm Optimization bagi masalah penentuan lokasi fasiliti (MOPSO-FLP), khusus untuk persekitaran berkekangan tinggi di mana pendekatan tepat tradisional menjadi tidak praktikal. Kaedah yang dicadangkan mengintegrasikan pengekodan diskret, mekanisme pembaikan kebolehlaksanaan, kawalan parameter adaptif, serta strategi pemilihan pemimpin berasaskan arkib, dan dinilai menggunakan set data penanda aras serta kajian kes rangkaian logistik pos kebangsaan. Merentasi 30 ulangan bebas, MOPSO-FLP menunjukkan p…
creator: Thanathorn Karot
creator: Choosak Pornsing
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 363
ending page: 376
doi: 10.31436/iiumej.v27i2.4072

Magnetic Resonance Imaging and Ultrasound-based Breast Tumor Classification using Soft Voting Ensemble Deep Learning Method
type: item
description: In recent years, breast cancer (BC) has been considered the most common cause of death in women worldwide. Commonly, BC occurs in breast cells or fatty tissues within the breast, and these tissues tend to grow faster and lead to death. The survival of patients with BC can be enhanced with early and accurate diagnosis. Therefore, this research proposes an ensemble learning approach that uses Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and a soft-voting mechanism to make early predictions and diagnoses of BC. The input sample images are initially passed through the convolutional layer to extract features from each modality separately. The Multi-Modality Adaptive Feature Fusion (MMAFF) technique combines generic features across modalities. Compared with existing techniques such as Deep Convolutional Neural Networks (DCNN) and Resolution Adaptive Network (RANet), the proposed ensemble learning technique achieves 89.6% accuracy for clinical indicator prediction and 99.25% accuracy for final tumor classification on the MRI-US dataset. ABSTRAK: Dalam beberapa tahun kebelakangan ini, kanser payudara (Breast Cancer, BC) telah dikenal pasti sebagai antara punca utama kematian dalam kalangan wanita di seluruh dunia. Secara umum, BC berlaku pada sel-sel payudara atau tisu lemak dalam payudara, di mana sel-sel ini cenderung membiak dengan cepat dan berpotensi membawa kepada kematian. Kadar kelangsungan hidup pesakit BC dapat ditingkatkan melalui diagnosis awal yang tepat dan boleh dipercayai. Sehubungan itu, kajian ini mencadangkan satu pendekatan pembelajaran ansambel yang menggabungkan Rangkaian Neural Berulang (Recurrent Neural Networks, RNN), Rangkaian Neural Konvolusi (Convolutional Neural Networks, CNN), Memori Jangka Pendek Panjang (Long Short-Term Memory, LSTM), serta mekanisme pengundian lembut (soft voting) bagi tujuan ramalan awal dan diagnosis BC. Imej sampel input pada peringkat awal diproses melalui lapisan k…
creator: Suresh Ramayanam
creator: Vijaya Bathini
creator: Sankar Babu Jangili
creator: Santosh Kumar Reddy Thikkam
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 74
ending page: 86
doi: 10.31436/iiumej.v27i2.3387

New Control Strategy of Battery Energy Storage System in Microgrids Integrated with Wind and Solar Power Plants
type: item
description: The global shift toward renewable energy, particularly wind and solar, has led to the rapid growth and diversification of distributed energy resources (DERs). However, integrating these sources sustainably and efficiently presents major challenges for researchers, investors, and power system operators. Their impact on distribution grids, along with operational uncertainties and disturbances, requires a comprehensive, system-wide perspective. This study proposes targeted strategies to enhance renewable energy utilization, offering both economic and environmental benefits while maintaining technical reliability and energy security. The study develops a microgrid model that includes a solar plant, a wind farm, an energy storage system, a distribution grid, and loads. As the core component, the battery energy storage system (BESS) plays a vital role in grid stabilization, power quality enhancement, and voltage/frequency regulation through advanced control strategies. Simulation results are analyzed to assess grid performance, evaluate the influence of renewable sources, and verify the effectiveness of the BESS in maintaining stable microgrid operation under realistic operating conditions. ABSTRAK: Peralihan global ke arah tenaga boleh diperbaharui, khususnya angin dan solar, telah membawa kepada pertumbuhan pesat serta kepelbagaian sumber tenaga teragih (DERs). Walau bagaimanapun, pengintegrasian sumber-sumber ini secara mampan dan cekap menimbulkan cabaran besar kepada para penyelidik, pelabur, dan pengendali sistem kuasa. Kesan sumber tersebut terhadap grid pengagihan, bersama-sama dengan ketidakpastian operasi dan gangguan, memerlukan perspektif menyeluruh pada skala sistem. Kajian ini mencadangkan strategi berfokus bagi meningkatkan penggunaan tenaga boleh diperbaharui, yang menawarkan manfaat ekonomi dan alam sekitar sambil mengekalkan kebolehpercayaan teknikal serta keselamatan tenaga. Kajian ini membangunkan model mikrogrid yang merangkumi loji solar, ladang angi…
creator: Duy Quang Nguyen
creator: Minh Khoa Ngo
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 87
ending page: 116
doi: 10.31436/iiumej.v27i2.3683

Comparative Performance Analysis of Forward Error Correction Schemes in AX.25-Based APRS Communication Systems with AFSK Modulation using GNU Radio Simulation
type: item
description: This paper presents a comparative analysis of Forward Error Correction (FEC) schemes in AX.25-based Automatic Packet Reporting System (APRS) communications using AFSK modulation through GNU Radio simulations. The study evaluates uncoded transmission, Reed–Solomon (255,223), several convolutional code configurations, and concatenated Reed–Solomon + convolutional coding under both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels. Results show that convolutional coding with rate 1/3 and constraint length K=7 achieves the best trade-off, reaching error-free performance at Eb/No = -2.5 dB under AWGN and maintaining robustness under fading. Reed–Solomon codes proved effective for correcting burst errors, while concatenated coding showed strong potential but required interleaving for stable operation. These findings highlight that convolutional coding offers the most practical balance between performance and complexity for real-world APRS and satellite systems, providing insights for future enhancements in robust low-SNR communication links. ABSTRAK: Kajian ini membentangkan analisis perbandingan bagi skim Forward Error Correction (FEC) dalam komunikasi Automatic Packet Reporting System (APRS) berasaskan protokol AX.25 dengan modulasi AFSK melalui simulasi GNU Radio. Penyelidikan ini menilai penghantaran tanpa FEC, kod Reed–Solomon (255,223), beberapa konfigurasi kod konvolusional, serta kod gabungan Reed–Solomon + konvolusional pada saluran Additive White Gaussian Noise (AWGN) dan Rayleigh fading. Dapatan menunjukkan bahawa kod konvolusional dengan kadar 1/3 dan panjang kekangan K=7 memberikan prestasi terbaik, mencapai komunikasi bebas ralat pada Eb/No = –2.5 dB dalam saluran AWGN dan kekal teguh di bawah keadaan fading. Kod Reed–Solomon berkesan untuk pembetulan ralat berurutan, manakala kod gabungan menunjukkan potensi yang kukuh namun memerlukan interleaver untuk operasi yang stabil. Hasil ini menegaskan bahawa kod konvolusional menawarkan keseimbanga…
creator: Rifki Ardinal
creator: Agfianto Eko Putra
creator: Wahyudi Hasbi
creator: Eriko Nasemudin Nasser
creator: Widya Roza
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 117
ending page: 128
doi: 10.31436/iiumej.v27i2.3951

Quantitative Assessment of Coffee Quality Using Microwave Non-Destructive Testing
type: item
description: The geographical origin, processing, roast level, and post-roasting resting time affect coffee quality in multiple ways. The traditional quality assessments in the coffee industry (sensory and chemical analyses) are subject to analysts' biases and are destructive, requiring the coffee to be destroyed to run tests. This analysis uses Microwave Non-Destructive Testing (MNDT) to study the dielectric characteristics of specialty coffee (Coffea arabica L.) associated with roasting and resting period. Coffee beans were roasted to produce light, medium, and dark roasts, and the beans were tested for dielectric properties over 30 days in 5-day intervals. The dielectric permittivity was negatively correlated with the level of roasting (r = -0.590, p = 0.005) and the resting period (r = -0.483, p = 0.027). The multiple linear regression showed strong predictive ability (R = 0.762, Adjusted R² = 0.534), explaining the effects of roasting and resting period, and their combined effect on the coffee's dielectric properties. This study shows, for the first time, how MNDT can be applied to the coffee industry to evaluate and assess coffee quality. ABSTRAK: Kualiti kopi dipengaruhi oleh pelbagai faktor seperti asal geografi, teknik pemprosesan, tahap panggang dan tempoh rehat selepas dipanggang. Kaedah tradisional bagi penilaian kualiti, termasuk penilaian deria dan analisis kimia, terdedah kepada subjektiviti dan keperluan ujian yang merosakkan sampel. Kajian ini menggunakan kaedah Microwave Non-Destructive Testing (MNDT) bagi menilai sifat dielektrik kopi istimewa (Coffea arabica L.) yang dipengaruhi oleh tahap pemanggangan dan tempoh rehat selepas dipanggang. Sampel kopi ini dipanggang pada tahap terang, sederhana dan gelap, dengan sifat dielektrik yang diukur selama 30 hari pada selang 5 hari. Keputusan menunjukkan korelasi negatif ketara antara kebolehtelapan dielektrik dan kedua-dua tahap panggang (r = -0.590, p = 0.005) dan tempoh rehat (r = -0.483, p = 0.027). Model regresi …
creator: Mohd Khairil Adzhar Mahmood
creator: Zuhani Ismail Khan
creator: Megat Syahirul Amin Megat Ali
creator: Ahmad Ihsan Mohd Yassin
creator: Norziaton Ismail Khan
creator: Michael Kwan Yeow Tan
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 129
ending page: 145
doi: 10.31436/iiumej.v27i2.3969

Experimental Validation of a Labview-Based SFCW Software-Defined Radar System
type: item
description: Software-defined radar (SDR) provides a flexible and cost-effective platform for implementing and testing diverse radar techniques without hardware redesign. Among these techniques, Stepped-Frequency Continuous Wave (SFCW) radar has shown promise in addressing some of the limitations of Frequency Modulated Continuous Wave (FMCW). This paper presents the experimental validation of an SDR system based on the SFCW technique. The radar system was developed using a USRP N210 with a WBX daughterboard, fully controlled through LabVIEW for waveform generation, data acquisition, and signal processing. Experimental validation was conducted in a controlled indoor environment using a 30 × 30 cm metal target placed at distances from 0.7 m to 1.25 m. According to the data, this research has shown accurate detection at longer ranges, with error rates below 0.5%. However, the increasing inaccuracy at lower ranges highlighted issues in near-field measurements. The findings have confirmed the feasibility of SFCW-based SDR for compact, reconfigurable radar platforms and suggest opportunities for enhancing near-field accuracy through advanced signal processing and calibration. ABSTRAK: Perisian takrifan radar (SDR) menyediakan platform fleksibel dan kos efektif bagi melaksana dan menguji pelbagai teknik radar tanpa reka bentuk semula perkakas. Antara teknik ini, radar gelombang berterusan frekuensi lanjutan (SFCW) telah menunjukkan kebolehan dalam menangani beberapa batasan gelombang berterusan modul berfrekuensi (FMCW). Kajian ini membentangkan pengesahan eksperimen sistem SDR berdasarkan teknik SFCW. Sistem radar dibangunkan menggunakan USRP N210 bersama papan WBX. Ia dikawal sepenuhnya melalui LabVIEW bagi penjanaan bentuk gelombang, perolehan data dan prosesan isyarat. Pengesahan eksperimen dijalankan dalam persekitaran dalaman terkawal menggunakan sasaran logam 30 × 30 cm yang diletakkan pada jarak 0.7 m hingga 1.25 m. Dapatan penyelidikan ini menunjukkan pengesanan tepat pada jul…
creator: Nor Hazima Ardzemi
creator: Farah Nadia Mohd Isa
creator: Norun Farihah Abdul Malek
creator: Huda Adibah Mohd Ramli
creator: Ahmad Fadzil Ismail
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 146
ending page: 161
doi: 10.31436/iiumej.v27i2.3988

Raindrop Size Distribution and Wind-Driven Rain Specific Attenuation: CCDF-Based Analysis at 18 and 38 GHz in Tropical Country
type: item
description: Seasonal monsoons, frequency dependence, and wind effects were investigated for rain-specific attenuation at millimeter-wave (mm-wave) frequencies in a tropical environment. Using one-minute RD-69 DSD data and matched wind observations, CCDFs of specific attenuation were evaluated at 18 and 38 GHz for three monsoon phases (SW, NE, IM) and four wind-direction sectors under unconstrained and constrained winds (9–11 m/s). The CCDF results show clear seasonal variability, with the SW monsoon producing the strongest attenuation and the largest mismatch from ITU-R P.838-3, particularly at 38 GHz. Error statistics show that the maximum deviation occurs in the SW 270°–360° sector, with an RMSE of 1.550 dB/km and a positive bias, confirming ITU-R underestimation. Meanwhile, the NE monsoon exhibits smaller overall deviations (worst-case RMSE below about 0.6 dB/km at 38 GHz). The IM period exhibits mixed behavior, where wind direction can shift the deviation between under- and overestimation under constrained winds. Exceedance levels of 0.01% and 0.001% were emphasized as design-relevant extremes, corresponding to approximately 52.6 min/year and 5.26 min/year, respectively, under one-minute sampling. Overall, the results indicate that ITU-R P.838-3 accuracy in tropical conditions depends on monsoon phase and wind direction, supporting monsoon-aware, direction-sensitive fade-margin planning and link-orientation considerations for robust 5G/6G terrestrial mm-wave systems. ABSTRAK: Monsun bermusim, kebergantungan frekuensi, dan kesan angin telah dikaji terhadap pelemahan spesifik hujan pada frekuensi gelombang milimeter (mm-wave) dalam persekitaran tropika. Menggunakan data DSD RD-69 beresolusi satu minit dan melalui pemerhatian padanan angin, pelemahan CCDF spesifik dinilai pada 18 dan 38 GHz untuk tiga fasa monsun (SW, NE, IM) dan empat sektor arah angin di bawah angin tidak terkekang serta angin terkekang (9–11 m/s). Penyimpangan terbesar daripada ITU-R P.838-3 berlaku pada 38…
creator: Nurul Najwa Md Yusof
creator: Omar Abdul Aziz
creator: Lam Hong Yin
creator: Jafri Din
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 162
ending page: 174
doi: 10.31436/iiumej.v27i2.4008

MultiModal Explainable AI and Blockchain Integration for Automated Halal Verification of Cosmetic Products
type: item
description: This research develops a framework that integrates blockchain technology and MXAI (Multimodal Explainable Artificial Intelligence) to automate the authentication and verification of halal cosmetic products. Two data sources were used: text extracted by OCR (Optical Character Recognition) and text manually input from cosmetic labels. After the pre-processing stage, the text data are analyzed using zero-shot classification to determine the inspection results, namely halal, haram, or syubhat. The inspection is conducted using MXAI, with decisions based on confidence scores and SHAP values. The inspection results are converted into digital reports as SHA-256 hashes and stored as Merkle roots on the blockchain, allowing users to download certificates as QR codes. The halal status experiment on the cosmetics dataset achieved an accuracy of 94.5% for classification, with a 3.3% improvement over baseline models, evaluated using stratified 5-fold cross-validation. This system enhances transparency, accountability, and public trust in automated halal certification. The contribution of this research is the integration of MXAI and blockchain technology into a single intelligent halal verification system, which can be extended to other supply chain sectors. ABSTRAK: Kajian ini menggabungkan teknologi rantaian blok dan MXAI (Kecerdasan Buatan Penjelasan Multimodal) bagi automasi dan jaminan pengesahan produk kosmetik halal. Dua sumber data digunakan: teks yang diekstrak oleh OCR (Pengesahan Optik Karakter) dan teks yang dimasukkan secara manual daripada label kosmetik. Selepas peringkat pra-pemprosesan, data teks dianalisis menggunakan klasifikasi sifar-tembakan bagi menentukan keputusan pemeriksaan, iaitu halal, haram, atau syubhat. Pemeriksaan dijalankan menggunakan MXAI, dengan keputusan berdasarkan skor keyakinan dan nilai SHAP. Keputusan pemeriksaan ditukar menjadi laporan digital dalam bentuk hash SHA-256 dan disimpan sebagai punca Merkle pada rantaian blok, membolehkan pen…
creator: Endang Supriyati
creator: Mohammad Iqbal
creator: Tri Listyorini
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 175
ending page: 188
doi: 10.31436/iiumej.v27i2.4059

Generative AI Models: A Comparison of Application Analysis on Web AI-Based Decision Support Systems for Satellite Anomaly Identification
type: item
description: The rapid innovation of Generative Artificial Intelligence (GenAI) has transformed Decision Support Systems (DSS) across various domains, including satellite operations. This paper presents a comparative analysis of four free Generative AI models, including Gemma 3 by Google, Llama 4 Maverick by Meta AI, Nemotron Nano 2 by NVIDIA, and Devstral Small by Mistral, in the context of integrating them into a Web AI-based Decision Support System (DSS) for satellite anomaly identification. Using a dataset of over 4,455 satellite anomaly records covering 1957 to 2024 provided by Seradata, with scalability and adaptability to diverse mission profiles. We evaluate these models by generating anomaly analyses for clarity, accuracy, completeness, and relevance across the Incident Overview, Reliability Trend, Insight, and Stakeholder Recommendation categories, using a 5-point Likert scale and Fleiss' Kappa for internal consistency. The comprehensive evaluation of GenAI models for Web AI-based DSS delineates a clear performance stratification, with scores of 4.44 and 4.39 for Nemotron Nano 2 and Llama 4 Maverick, respectively, confirming their positions as the leading systems based on overall Likert scores. However, the analysis further revealed a critical trade-off between absolute quality and internal consistency (Fleiss' Kappa). The superior models, Nemotron Nano 2 and Llama 4 Maverick, achieved high Likert scores by displaying pronounced performance peaks but suffered the lowest internal predictability, with ? = 0.18 on Llama 4 Maverick, indicating a highly volatile output structure in which strong clarity often masked critical incompleteness. Conversely, Devstrall Small, despite its suboptimal mean score of 3.44, demonstrated the highest internal consistency, with ? = 0.66. This robust predictability, even at a lower level, underscores a significant implication for DSS development. The model selection must prioritize the required balance between absolute performance ceiling an…
creator: Abdul Mutholib
creator: Nadirah Abdul Rahim
creator: Teddy Surya Gunawan
creator: Ahmad Shah Hizam Md Yasir
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 189
ending page: 209
doi: 10.31436/iiumej.v27i2.4061

PromptLessSAM: From Foundational Model to Domain Expert via Lightweight Decoder Adaptation for Crack Segmentation
type: item
description: Maintaining infrastructure such as roads and bridges is very important for safety. This is called Structural Health Monitoring (SHM). A key part of SHM is automatically finding cracks in pavements. Recent foundation models, such as the Segment Anything Model (SAM), can segment a wide range of object types. However, they are not well-suited for specific tasks such as detecting thin cracks in complex environments. They also require user input to function, making them unsuitable for fully automatic inspection systems. Therefore, this paper proposes PromptLessSAM to transform the general SAM model into a domain expert for crack segmentation. We use a lightweight method in which we freeze the powerful image encoder of SAM, except for the encoder’s neck, which remains trainable, and we add a new, small decoder. Our model is very efficient and has only about 1.1 million trainable parameters. We trained and tested our model on the public Crack500 dataset. The experimental results show that our model achieved high performance (a Dice score of 72.7% and an IoU of 57.11% on Crack500), outperforming many state-of-the-art models, including TransUNet and PaveSAM. Also, our model showed good generalization capabilities on the DeepCrack dataset (Dice score of 74.7% and IoU of 62.43%), which it did not see during training. PromptLessSAM provides a new, efficient, and effective method. It shows how to adapt large foundation models for a specific task. Our work provides a strong, high-performance solution trained on a very small number of parameters. ABSTRAK: Penyelenggaraan infrastruktur seperti jalan raya dan jambatan sangat penting bagi tujuan keselamatan. Ini dikenali sebagai Pemantauan Kesihatan Struktur (Structural Health Monitoring, SHM). Salah satu komponen utama pada SHM ialah mengesan rekahan pada turapan secara automatik. Model asas terkini, seperti Model Sesuatu Bahagian (SAM), boleh melakukan segmentasi pelbagai objek. Namun, model ini kurang berkesan bagi tugas khusus se…
creator: Mohammed Al-Mustafa Hendo
creator: Israa H. Ali
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 210
ending page: 226
doi: 10.31436/iiumej.v27i2.4124

Stability-Aware Evaluation of a CNN–LSTM–DQN Intrusion Detection System for Zero-Day and Drifted Network Traffic
type: item
description: Intrusion Detection Systems (IDS) deployed in real-world environments must operate under severe class imbalance, evolving attack strategies, and non-stationary traffic distributions. Conventional supervised and deep learning–based IDS rely on fixed decision functions, limiting their adaptability to zero-day attacks and concept drift. This paper proposes a hybrid CNN–LSTM–DQN framework combined with a stability-aware evaluation methodology. The CNN–LSTM backbone extracts spatio-temporal representations, while a Deep Q-Network (DQN) learns adaptive detection policies using an ARMF-aware reward formulation. The framework is evaluated on eleven experimental stages (E1-11), including supervised baselines, reinforcement learning optimization, zero-day generalization (LOAO), and drift scenarios. Experimental results show that supervised models have high recall (up to 98.39%) but generate too many alerts (ARMF up to 44,845). The reinforcement learning model with prioritized experience replay (E7) achieves a more balanced performance with a recall of 91.40% and an ARMF of 1,031. The proposed PER-based approach significantly improves detection performance while maintaining low alert rates, achieving a recall of 42.47% compared to naive reinforcement learning (E5). Further evaluation in real drifting conditions showed robust recall (89-92%) with a tolerable number of alerts (ARMF ? 1,189). These results indicate that adaptive policy learning enables a more effective trade-off between detection performance and operational cost, while ARMF-based evaluation provides a practical complement to accuracy metrics for real-world IDS deployment. ABSTRAK: Sistem Pengesanan Pencerobohan (IDS) dalam dunia nyata perlu beroperasi di bawah ketidakseimbangan kelas yang teruk, strategi serangan berevolusi, dan taburan trafik tidak pegun. IDS berasaskan pembelajaran penyeliaan dan pembelajaran mendalam konvensional bergantung pada fungsi keputusan tetap, mengehadkan kebolehsuaian terhadap serang…
creator: Rushendra
creator: Kalamullah Ramli
creator: Prima Dewi Purnamasari
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 227
ending page: 256
doi: 10.31436/iiumej.v27i2.4240

A Robust Low-Complexity Star Centroiding Algorithm for Autonomous Navigation under Lunar Noise Conditions
type: item
description: Star-based navigation on the lunar surface is severely degraded by strong regolith reflections, abrupt illumination transitions, and sensor-induced noise, all of which lower the signal-to-noise ratio (SNR) and impair centroiding accuracy. Existing methods address this trade-off poorly: classical center-of-mass (COM) and Gaussian fitting are computationally light but noise-sensitive, whereas iterative weighting and learning-based approaches improve accuracy at the cost of high computational load and large training data. This study addresses this gap by proposing a low-complexity yet robust star centroiding algorithm tailored for lunar-surface imagery. The pipeline integrates median filtering for impulse-noise suppression, an adaptive global threshold (set at 30% of peak intensity) for star-region segmentation, and an intensity-weighted COM estimator for sub-pixel localization. The method was implemented in MATLAB R2023b and evaluated on 30 Stellarium-derived star fields, each corrupted by Gaussian, Poisson, salt-and-pepper, speckle, and solar-glare noise spanning SNRs from ?4.71 dB to 0.72 dB. Benchmarked against standard COM, Gaussian fitting, and the Sieve Search Algorithm (SSA), the proposed method achieves the lowest average root-mean-square error (RMSE = 1.218 pixels), the lowest Euclidean distance error (1.143 pixels), and the lowest false detection rate (FDR = 6.716%), corresponding to relative reductions of 21.5%, 16.7%, and 32.7% over the best baseline, respectively. The algorithm’s favorable accuracy–complexity trade-off makes it well-suited for resource-constrained onboard processors in future lunar exploration and autonomous spacecraft navigation missions. ABSTRAK: Navigasi berasaskan bintang di permukaan bulan terjejas dengan ketara akibat pantulan regolit yang kuat, perubahan pencahayaan yang mendadak, dan hingar daripada penderia, yang kesemuanya menurunkan nisbah isyarat kepada hingar (SNR) dan menjejaskan ketepatan penganggaran sentroid. Kaedah sedia…
creator: Anisa Hannani Razaman
creator: Yasser Asrul Ahmad
creator: Teddy Surya Gunawan
creator: Othman Omran Khalifa
creator: Mila Popović
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 257
ending page: 277
doi: 10.31436/iiumej.v27i2.4246

Efficiency-Aware Multi-Class Spinal Disorder Classification Using CBAM-Enhanced Lightweight CNNs with Dual-Branch Fusion
type: item
description: Spinal X-rays are still often read through manual measurements, yet the patients who most need timely assessment cannot afford delay, inconsistency, or heavy computational pipelines. Motivated by this clinical tension, this study proposes an efficiency-aware deep learning framework for three-class spinal disorder classification that asks a practical question rarely centered in prior work: not only which model is most accurate, but which model is accurate enough, light enough, and fast enough to matter in real screening settings. Using a public dataset of 338 subjects, five lightweight backbones, CBAM-enhanced variants, and a dual-branch fusion model were evaluated through stratified 5-fold cross-validation under multiple balancing strategies, with performance measured by accuracy, precision, recall, F1-score, parameter count, FLOPs, model size, latency, and throughput. The results reveal an unexpected pattern: bigger models do not win. MobileNetV3Small delivers the strongest efficiency-performance balance, reaching an F1-score of 0.962 with only 1.0 million parameters, while the best overall result is achieved by the Fusion_MNv3_MNAS model under augmentation-only training, with an F1-score of 0.976. Ablation findings further show that attention and fusion are not universally beneficial, but become most effective when paired with sufficient data-driven regularization, and that fine-tuning about 30% of backbone parameters yields the most favorable adaptation. Taken together, these findings show that performance in spinal X-ray classification depends less on model size alone than on the fit between architecture and training strategy. The study therefore offers a concrete and clinically relevant message: lightweight, well-regularized models can match or surpass heavier alternatives while remaining more practical for scalable deployment. ABSTRAK: Radiograf tulang belakang masih kerap dinilai melalui pengukuran manual, sedangkan pesakit yang memerlukan rawatan awal tidak …
creator: Teddy Surya Gunawan
creator: Nurul Jannah
creator: Mira Kartiwi
creator: Noreha Abdul Malik
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 278
ending page: 319
doi: 10.31436/iiumej.v27i2.4341

TSGL-Rust: Teaching Concurrency Through Compile-Time Enforcement via Rust-Based Visualization of Classical Synchronization Problems
type: item
description: Concurrent programming remains a persistent challenge in undergraduate computer science and engineering education, largely because its failure modes are difficult to observe and reason about. Race conditions and deadlocks often emerge only under specific thread interleavings, leaving students to reconcile correct-looking code with unpredictable runtime behavior. Prior instructional approaches, such as the Thread-Safe Graphics Library (TSGL), address this issue by enabling real-time visualization, but they rely on languages that do not enforce safe access to shared state. This separation between observation and enforcement leaves a gap between how concurrency errors are detected and how they are prevented. This paper presents TSGL-Rust, a Rust-based reimplementation of classical TSGL visualizations that integrates compile-time safety guarantees with runtime visualization. Implemented using the egui/eframe framework, the system reproduces three canonical synchronization problems, namely Producer–Consumer, Reader–Writer, and Dining Philosophers, while shifting certain classes of errors from runtime to compilation through Rust's ownership model and borrow checker. The architecture deliberately separates concurrency logic from rendering through a crossbeam channel, decoupling worker threads from the egui main-thread render loop. This paper is presented as a system and tool description: it focuses on architectural design, the mapping from C++ TSGL primitives to Rust constructs, the channel-based communication pattern, and the instructional affordances that follow from these design choices. The contribution lies in the system itself and in the boundary it makes visible between data-race prevention and logical errors, such as deadlock, rather than in any claim about measured learning gains. ABSTRAK: Pengaturcaraan serentak kekal sebagai cabaran utama dalam pendidikan sarjana muda sains komputer dan kejuruteraan, kerana mod kegagalannya sukar dicari dan difahami secara siste…
creator: Teddy Surya Gunawan
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 320
ending page: 339
doi: 10.31436/iiumej.v27i2.4361

Constant-Time Bitsliced Rijndael-256 on ARM Cortex-M4: On the Limitations of Fixslicing Beyond AES-128
type: item
description: Wider-block ciphers are increasingly needed in high-volume applications, because 128-bit blocks in modes such as Galois/Counter Mode (GCM) limit each invocation to roughly 64 GiB of plaintext per key-nonce pair, forcing complex re-keying strategies. Rijndael-256, the 256-bit-block variant of Rijndael with a 256-bit key, has therefore attracted renewed interest as a natural wider-block companion to Advanced Encryption Standard (AES). At the same time, 32-bit ARM Cortex-M microcontrollers dominate the IoT and embedded landscape, yet, to the best of our knowledge, no constant-time software implementation of Rijndael-256 targeting this platform has been published. This paper addresses that gap. We present a constant-time bitsliced implementation of Rijndael-256 on the ARM Cortex-M4 and provide a systematic structural analysis explaining why fixslicing, the technique that achieves the best-known AES-128 performance on this platform, becomes suboptimal when applied to Rijndael-256. Specifically, the irregular ShiftRows offsets (0, 1, 3, 4) of Rijndael-256 break the uniform register rotation exploited by fixslicing, requiring eight distinct MixColumns compensation variants instead of four. We demonstrate that these compensation variants cost 3.00× as much as executing an explicit, in-place ShiftRows routing using ARM's bitfield instructions. Our macro-inlined assembly variant achieves 6,199 cycles (193.7 cycles/byte) at -O2, including packing and unpacking. We provide benchmarks across five compiler optimization levels, constant-time verification over samples via DUDECT (maximum t-statistic well below the vulnerability threshold), and per-component cycle breakdowns, showing that the optimal bitslicing strategy is inherently cipher-specific and architecture-dependent. ABSTRAK: Sifer blok yang lebih lebar semakin diperlukan dalam aplikasi berisipadu tinggi kerana blok 128-bit dalam mod seperti Galois/Counter Mode (GCM) mengehadkan setiap invokasi kepada kira-kira 64 GiB teks…
creator: Andriani Adi Lestari
creator: Suryadi MT
creator: Kalamullah Ramli
creator: Teddy Surya Gunawan
creator: Esti Rahmawati Agustina
creator: Susila Windarta
rights: Copyright (c) 2026 IIUM Press https://creativecommons.org/licenses/by-nc/4.0
license: https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-10
publication date: 2026-05-10
volume: 27
number: 2
starting page: 340
ending page: 362
doi: 10.31436/iiumej.v27i2.4405