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Improving Model Performance for Predicting Exfiltration Attacks Through Resampling Strategies
Full text linkAddressing class imbalance is critical in cybersecurity applications, particularly in scenarios like exfiltration detection, where skewed datasets lead to biased predictions and poor generalization for minority classes. This study investigates five Synthetic Minority Oversampling Technique (SMOTE) variants, including BorderlineSMOTE, KMeansSMOTE, SMOTEENC, SMOTEENN, and SMOTETomek, to mitigate severe imbalance in our customized tactic-labeled dataset with dominant majority class influence and weak class separability class imbalance. We use seven imbalance metrics to assess each SMOTE variant’s impact on class distribution stability and separability. Furthermore, we evaluate model performance across five classifiers: Logistic Regression, Naïve Bayes, Support Vector Machine, Random Forest, and XGBoost. Findings reveal that SMOTEENN consistently enhances performance metrics (accuracy, precision, recall, F1-score, and geometric mean) on an average of 99% across most classifiers, establishing itself as the most adaptable variant for handling imbalance. This study provides a comprehensive framework for selecting resampling strategies to enhance classification efficacy in cybersecurity tasks with imbalanced data
Voltage-Induced Void Formation in High-Temperature Oxide Scales of Boiler Tubes
Full text linkCorrosion monitoring remains a significant challenge at high temperatures. Understanding the varying factors in high-temperature cathodic protection is crucial for developing mitigation strategies and predictive maintenance. This study assesses how cathodic protection influences oxidation in T91 alloys at elevated temperatures by evaluating the effects of exposure duration and voltage-induced void development in the oxide layer. It is hypothesized that polarizing the sample affects the diffusivity of cations and anions in the oxide scale, which is the rate-determining step of the oxidation process. This study measured the number of voids directly on T91 alloys exposed at 823K under various induced voltages. T91 alloy was externally induced with voltages of 0V, 50V, and 300V for 43.2 ks, 259.2 ks, and 432 ks at 923 K in air ( = 0.21 atm = 2.1×104 Pa). The presence of oxide layers was analysed using X-Ray Diffraction (XRD), and the void formed was inspected using Scanning Electron Microscopy (SEM). XRD results reveal that Fe2O3, Fe3O4, FeCr2O3, and Cr2O3 peaks were formed on all samples. The parabolic rate constant, Kp, was calculated as 3.83 × 10-14 m2/s, 2.17 × 10-14 m2/s, and 9.25 × 10-14 m2/s, respectively, verifying that the reaction occurred by solid-state diffusion. Changes in Kp at different induced voltages are clear evidence that the diffusivity was altered by external electrical potential. It was observed that the overall void formation decreased by 17%. Inducing voltage onto T91 alloy affects the ionic diffusivity. It changes the void formation, suggesting it may promote the diffusivity of more inert species, such as Cr, to form a protective layer at the early oxidation stage.
ABSTRAK: Pemantauan hakisan kekal sebagai cabaran utama pada suhu tinggi. Memahami pelbagai faktor perlindungan katodik pada suhu tinggi adalah penting untuk membangunkan strategi pengurangan dan ramalan penyelenggaraan. Kajian ini menilai perlindungan katodik mempengaruhi pengoksidaan dalam aloi T91 pada suhu tinggi dengan melihat kesan tempoh pendedahan dan pembangunan rongga yang disebabkan oleh potensi elektrik luaran pada lapisan oksida. Pemolaran sampel mempengaruhi keberaliran kation dan anion dalam oksida, yang menentukan kadar dalam proses pengoksidaan. Melalui kajian ini, jumlah ruang kosong diukur secara langsung pada aloi T91 yang didedahkan pada suhu 823K di bawah pelbagai voltan teraruh. Aloi T91 dikenakan voltan luaran sebanyak 0V, 50V, dan 300V bagi tempoh 43.2 ks, 259.2 ks, dan 432 ks pada suhu 923K dalam udara ( = 0.21 atm = 2.1 × 104 Pa). Kehadiran lapisan oksida dianalisa menggunakan Pembelauan Sinar-X (XRD), dan ruang kosong yang terbentuk diperiksa menggunakan Mikroskop Elektron Imbasan (SEM). Dapatan XRD menunjukkan bahawa puncak Fe2O3, Fe3O4, FeCr2O3, dan Cr?O? terbentuk pada semua sampel. Pemalar kadar parabola, Kp, dikira masing-masing sebanyak 3.83 × 10-14 m²/s, 2.17 × 10-14 m²/s, dan 9.25 × 10-14 m²/s, mengesahkan bahawa tindak balas yang berlaku adalah penyebaran keadaan pepejal. Perubahan dalam Kp pada voltan teraruh berbeza membuktikan bahawa keberaliran telah diubah oleh potensi elektrik luaran. Hasil kajian mendapati bahawa pembentukan ruang kosong secara keseluruhan berkurangan sebanyak 17%. Proses penguraian voltan pada aloi T91 mempengaruhi keberaliran ionik dan mengubah pembentukan ruang kosong, mencadangkan bahawa ia mungkin digunakan bagi mempromosi keberaliran spesies yang lebih lengai seperti Cr bagi membentuk lapisan pelindung pada peringkat awal pengoksidaan
Miniaturized L-Shaped and U-Shaped Resonator-Based 8-Bit and 12-Bit Chipless RFID Tag
Full text linkChipless Radio Frequency Identification (RFID) technology is a wireless technology that uses radio frequency signals (RF) to identify objects automatically. Chipless RFID tags promise a low-cost and printable solution for item tracking, authentication, and sensing in various applications, including supply chain management and the Internet of Things (IoT). In this work, two compact-sized prototypes of 8-bit chipless radio frequency identification (RFID) tags are modeled as L-shaped and U-shaped resonators. The proposed tags are printed on (14.5mm 14.5mm) Rogers RT5880 substrate with a dielectric constant, and a thickness, . The simulated RCS responses for both the L-shaped and the U-shaped 8-bit chipless RFID tags are presented. A prototype of 12 back-to-back L-shaped resonators with different lengths corresponding to resonant frequencies between 5 and 8.5 GHz is proposed to increase the chipless RFID tag capacity. The proposed 12 back-to-back L-shaped resonators chipless RFID tag is printed on (15mm 25mm) Rogers RT5880 substrate. The simulated RCS response for the compact 12-bit L-shaped resonator-based chipless RFID tag is calculated.
ABSTRAK: Teknologi Pengenalan Frekuensi Radio Tanpa Cip (Chipless RFID) merupakan teknologi tanpa wayar yang menggunakan isyarat frekuensi radio (RF) bagi mengenal pasti objek secara automatik. Tag RFID tanpa wayar menawarkan penyelesaian kos rendah yang berpotensi bagi menjejak item, pengesahan, dan pengesanan dalam pelbagai aplikasi termasuk pengurusan rantaian bekalan dan Internet Benda (IoT). Kajian ini membentangkan dua prototaip bersaiz kompak; iaitu tag RFID 8-bit tanpa wayar yang dimodelkan sebagai resonator berbentuk-L dan berbentuk-U. Tag yang dicadangkan ini dicetak pada substrat Rogers RT5880 (14.5 mm × 14.5 mm) dengan pemalar dielektrik, , dan ketebalan, h = 1.575 mm. Respons simulasi RCS bagi kedua-dua tag 8-bit berbentuk-L dan berbentuk-U dibentangkan dalam kajian ini. Bagi meningkatkan kapasiti tag RFID tanpa wayar, satu prototaip yang terdiri daripada 12 resonator berturutan berbentuk-L dengan panjang berbeza dan berfrekuensi resonan antara 5 hingga 8.5 GHz telah dicadangkan. Tag RFID tanpa wayar ini dicetak pada substrat Rogers RT5880 (15 mm × 25 mm). Respons simulasi RCS bagi tag kompak RFID 12-bit tanpa wayar turut dikira
Machining Performance with Respect to Cutting Forces, Vibrations, and Surface Quality in Drilling of Hybrid Abaca and Glass Fibers Reinforced Polymer Composite
Full text linkInitially, polymer composites utilized synthetic fibers as reinforcements due to their high strength and excellent water resistance. However, synthetic fibers are non-biodegradable, and their manufacturing process involves chemicals, rendering them environmentally unfriendly. Consequently, natural fibers began to be employed owing to their low production costs and inherent biodegradability. Nevertheless, natural fibers possess lower strength and non-uniform sizes, making them challenging to shape. Hybrid composites have been developed to address these limitations, combining synthetic and natural fibers to leverage their respective advantages and mitigate each other's shortcomings. As a result, hybrid composites are increasingly being adopted in various industries, including automotive, construction, sports, and electronics. During production, hybrid composite panels still require machining processes, such as milling to smooth the surface and drilling to create connecting holes, to become final products. Careful selection of machining parameters are needed to ensure product quality and minimize defects, including tool wear, fiber debonding, and delamination. Cutting forces and vibrations, critical factors influencing machining performance, can be regulated through optimized cutting conditions. This study examines the effects of cutting conditions on cutting forces and vibrations while drilling hybrid composites composed of abaca and glass fibers. Composite panels were fabricated using the compression molding method, consisting of 10% abaca fiber, 10% glass fiber, and 80% polyester resin with 1% hardener by weight. Drilling experiments were conducted using a two-flute high-speed steel (HSS) cutting tool under varying spindle speeds and feed rates. The results revealed that cutting parameters significantly influenced machining behaviour. Specifically, higher spindle speeds increased cutting forces by up to approximately 15%, whereas higher feed rates amplified vibration acceleration by up to 67.8%. These findings contribute to a deeper understanding of machining performance and provide valuable insights for optimizing drilling parameters to enhance machining efficiency and surface quality in hybrid natural–synthetic fiber composites.
ABSTRAK: Pada mulanya, komposit polimer menggunakan serat sintetik sebagai penguat kerana kekuatannya yang tinggi dan rintangan air terbaik. Walau bagaimanapun, serat sintetik tidak terbiodegradasi, dan proses pembuatannya melibatkan bahan kimia, menjadikannya tidak mesra alam. Akibatnya, serat semula jadi mula digunakan kerana kos pengeluarannya yang rendah dan kebolehbiodegradan. Namun begitu, serat semulajadi mempunyai kekuatan lebih rendah dan saiz tidak seragam, menjadikannya sukar dibentuk. Bagi menangani masalah ini, komposit hibrid dibangunkan, menggabungkan serat sintetik dan semulajadi bagi memanfaatkan kelebihan masing-masing dan mengurangkan kelemahan masing-masing. Hasilnya, komposit hibrid semakin diterima pakai dalam pelbagai industri, termasuk automotif, pembinaan, sukan dan elektronik. Semasa peringkat pengeluaran, panel komposit hibrid masih memerlukan proses pemesinan, seperti milling bagi melicinkan permukaan dan penggerudian bagi mencipta lubang penyambung, sebelum menjadi produk akhir. Pemilihan parameter pemesinan yang teliti diperlukan bagi memastikan kualiti produk dan meminimumkan kecacatan, termasuk haus alat, nyah ikatan gentian dan penyimpangan. Daya pemotongan dan getaran, yang merupakan faktor kritikal mempengaruhi prestasi pemesinan, dapat dikawal melalui keadaan pemotongan yang optimum. Kajian ini mengkaji kesan keadaan pemotongan ke atas daya pemotongan dan getaran semasa penggerudian komposit hibrid yang terdiri daripada serat abaka dan gentian kaca. Panel komposit telah difabrikasi menggunakan kaedah pengacuan mampatan, yang terdiri daripada 10% gentian abaka, 10% gentian kaca, dan 80% resin poliester dengan 1% pengeras mengikut berat. Eksperimen penggerudian telah dijalankan menggunakan alat pemotong keluli berkelajuan tinggi (HSS) dua mata di bawah kelajuan dan kadar suapan berbeza. Dapatan menunjukkan bahawa parameter pemotongan mempengaruhi tingkah laku pemesinan dengan ketara. Khususnya, kelajuan lebih tinggi menyebabkan daya pemotongan meningkat sehingga kira-kira 15%, manakala kadar suapan lebih tinggi menguatkan pecutan getaran sehingga 67.8%. Penemuan ini menyumbang kepada pemahaman yang lebih mendalam tentang prestasi pemesinan dan menyumbang pandangan berharga dalam mengoptimum parameter penggerudian bagi meningkatkan kecekapan pemesinan dan kualiti permukaan komposit serat semulajadi-sintetik hibrid
Editorial
Full text linkThe IIUM Engineering Journal Vol. 26 No. 2 continues its mission of advancing scholarly excellence by featuring 22 high-quality papers that span a wide spectrum of engineering disciplines. This issue brings together cutting-edge research showcasing the dynamic and multidisciplinary nature of engineering in addressing real-world problems.Researchers explore sustainable and biologically driven innovations in the realm of Chemical and Biotechnology Engineering. Notably, identifying Rhizopus sp. fungi as an alternative lactic acid source and the ozonation of vegetable oils underscore efforts toward environmentally friendly biochemical processes. Civil and Environmental Engineering contributions highlight using natural materials for infrastructure, focusing on the feasibility of treated natural bitumen as a replacement for petroleum-based asphalt—an approach aligned with sustainable construction practices.The most significant representation comes from Electrical, Computer, and Communications Engineering, where numerous works delve into AI, signal processing, secure communications, and sensor networks. From deep learning-based anomaly detection and vision transformer analysis for driver fatigue, to latency evaluations of LEO and GEO networks under tropical conditions, these studies reflect the growing importance of digital intelligence and communication resilience. Contributions on flexible antenna designs, mobile applications for dyslexic learners, and modified grey relational analysis further showcase how electronics and AI are increasingly embedded in daily societal functions.In Materials and Manufacturing Engineering, the research on MSW-derived biochar for iron production and voltage-induced void formation in boiler tubes exemplifies innovation in resource utilization and reliability of industrial systems. Additionally, enhancing photocatalytic materials for water treatment presents promising strides in environmental engineering. Mechatronics and Automation Engineering advances are evident in developing regenerative braking systems for electric motorcycles and smart IoT-based solutions for e-bike sharing systems, both addressing urban mobility and energy efficiency. Finally, contributions in Engineering Mathematics and Applied Science provide theoretical underpinnings crucial for innovation, such as the study on the elliptic drum of vertical spindle cotton pickers, demonstrating the importance of mathematical modeling in optimizing mechanical design.This issue affirms the journal’s commitment to featuring impactful, interdisciplinary research that bridges theory and application. The editorial team extends sincere appreciation to all contributing authors, dedicated reviewers, and section editors whose efforts ensure the continued quality and relevance of the IIUM Engineering Journal.We hope this collection will inspire further research, inform policy and industrial practices, and foster collaborations across academia and industry to pursue sustainable and inclusive technological development..We extend our gratitude to the authors, reviewers, and editorial board for their unwavering commitment to excellence. Your contributions ensure this journal thrives as a beacon of scholarly inquiry and practical impact. Let us embrace these breakthroughs as stepping stones to a brighter, more sustainable future.
Prof. Ir. Ts. Dr. Teddy Surya GunawanExecutive EditorIIUM Engineering Journal
ISSN: 1511-788X E-ISSN: 2289-7860
Published by:IIUM Press,International Islamic University MalaysiaJalan Gombak, 53100 Kuala Lumpur, MalaysiaPhone (+603) 6421-5014, Fax: (+603) 6421-629
Identifying Technical and Vocational Education and Training (TVET) Sentiment from Social Media Using a Machine Learning Approach
Full text linkTechnical and Vocational Education and Training (TVET) has become a key priority for the Malaysian government to enhance the system, better aligning it with industrial demands and workforce needs. The primary priority is to ensure that students and graduates acquire in-demand skills, thereby increasing their employability and creating more attractive job opportunities. Due to rapid technological advancements, social media has emerged as a powerful platform for public discourse where discussions on TVET programs, policies, and perceptions occur extensively. Among these platforms, Facebook is a widely used space for public interactions through posts and comments. This study employs sentiment analysis to analyse TVET-related discussions on Facebook, categorising sentiment into positive, neutral, and negative polarities. The Term Frequency-Inverse Document Frequency (TF-IDF) method is utilised to extract meaningful insights, and six classifiers, comprised of Support Vector Machine (SVM), Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbour (KNN), and Logistic Regression (LR), are applied. Using an 80%-20% training and testing split, results indicate that SVM achieves the highest accuracy performance, with a score of 0.62, outperforming other classifiers. Hence, this study provides valuable insights for policymakers and relevant stakeholders in the TVET ecosystem. By leveraging sentiment analysis and machine learning, decision-makers can better understand public perceptions and develop well-informed strategies to realign and enhance the TVET system.
ABSTRAK: Pendidikan dan Latihan Teknikal dan Vokasional (TVET) menjadi keutamaan kerajaan Malaysia bagi meningkatkan sistem agar lebih selaras dengan permintaan industri dan keperluan tenaga kerja. Keutamaan ini adalah bagi memastikan pelajar dan graduan memperoleh kemahiran yang diperlukan, meningkatkan kebolehpekerjaan serta mewujudkan lebih banyak peluang pekerjaan. Kepesatan kemajuan teknologi menyebabkan media sosial muncul sebagai platfom berpengaruh bagi wacana awam di mana perbincangan mengenai program, dasar, dan persepsi TVET berlangsung secara meluas. Antara platfom tersebut, Facebook menjadi medium terbanyak digunakan bagi interaksi awam melalui hantaran dan komen. Kajian ini menggunakan analisis sentimen bagi menganalisis perbincangan berkaitan TVET di Facebook dengan mengkategorikan sentimen kepada positif, neutral, dan negatif. Kaedah Frekuensi Dokumen Terma Frequency-Inverse (TF-IDF) digunakan bagi mengekstrak pandangan bermakna dan seterusnya menerapkan enam pengklasifikasi yang terdiri daripada Mesin Sokongan Vaktor (SVM), Naïve Bayes (NB), Pokok Keputusan (DT), Rawak Forest (RF), K-Nearest Neighbour (KNN), dan Regriasi Logistik (LR). Menggunakan peratusan data pembahagian latihan dan ujian sebanyak 80%-20%, dapatan kajian menunjukkan bahawa SVM mencapai prestasi ketepatan tertinggi dengan skor 0.62, mengatasi pengklasifikasi lain. Oleh itu, kajian ini memberi pandangan berharga kepada penggubal dasar dan pihak berkepentingan dalam ekosistem TVET. Dengan memanfaatkan analisis sentimen dan pembelajaran mesin, penggubal dasar dapat memperoleh pemahaman mendalam tentang persepsi awam dan membangunkan strategi berinformasi bagi menyelaras dan meningkatkan sistem TVET
Initial Investigation on Improving the Physicomechanical Properties of Clayey Sand Using Clay Brick Dust
Full text linkClayey sand is commonly considered unsuitable for construction due to its high compressibility, low shear strength, and susceptibility to erosion and settlement. The research focuses on enhancing the physical and mechanical properties of the soil by incorporating clay brick dust (CBD) at varying proportions of 15, 20, and 25% by weight. A comprehensive laboratory testing was conducted, including particle size distribution, Atterberg limits, moisture content, Standard Proctor compaction, and California Bearing Ratio (CBR). These tests were used to assess the physical and mechanical behaviour of both untreated and treated soils. The results indicate that the inclusion of CBD significantly improves the soil's strength, as reflected by increased CBR values. However, higher percentages of CBD lead to reductions in moisture content and maximum dry density. The study concluded that the optimum percentage of CBD mixture was found to be 20% by weight, offering the best balance between improved strength and acceptable compaction properties. This study concludes that CBD is a viable and sustainable material for stabilizing clayey sand, making it more suitable for geotechnical and construction applications.
ABSTRAK: Pasir berlempung kebiasaannya tidak sesuai bagi tujuan pembinaan disebabkan oleh kemampatannya yang tinggi, kekuatan ricih yang rendah, serta kerentanan terhadap hakisan dan pemendapan. Kajian ini memfokuskan kepada penambahbaikan sifat fizikal dan mekanikal tanah dengan campuran serbuk bata tanah liat (CBD) pada kadar berbeza iaitu 15%, 20% dan 25% mengikut berat. Ujian makmal menyeluruh telah dijalankan merangkumi taburan saiz zarah, had-had Atterberg, kandungan lembapan, pemadatan Proktor piawai, dan ujian Nisbah Galas California (CBR). Ujian-ujian ini digunakan bagi menilai sifat fizikal dan mekanikal tanah sebelum dan selepas rawatan. Dapatan kajian menunjukkan bahawa penambahan CBD secara signifikan meningkatkan kekuatan tanah, seperti yang dibuktikan melalui peningkatan nilai CBR. Walau bagaimanapun, peratusan CBD yang lebih tinggi mengakibatkan pengurangan kandungan lembapan dan ketumpatan kering maksimum. Kajian ini merumuskan bahawa campuran optimum CBD adalah pada 20% berat, yang memberikan keseimbangan terbaik antara peningkatan kekuatan dan sifat pemadatan terbaik. Kajian ini membuktikan bahawa CBD merupakan bahan berdaya guna dan mampan bagi menstabilkan pasir berlempung, sekaligus menjadikannya lebih sesuai untuk aplikasi geoteknik dan pembinaan
Fuzzy Logic-Based Arrival Time Estimation for Indoor Navigation Using Augmented Reality
Full text linkIn recent years, Augmented Reality (AR) has gained popularity in various industries due to its ability to enhance efficiency, provide real-time information and data, and maintain user awareness of their surroundings. One of the applications of AR is in navigation, but most existing systems primarily focus on outdoor environments, neglecting indoor spaces. Mobile applications designed for indoor navigation often rely on expensive and computationally demanding beacons or natural markers to track the user's location along a predetermined path. Furthermore, traditional navigation estimation methods based on GPS are ineffective for indoor navigation. This study proposes a mobile AR application for indoor navigation that uses an intelligent signage algorithm based on fuzzy logic to estimate arrival time. The algorithm takes phone acceleration in the x and z directions as inputs and employs triangular-shaped membership functions for input and output variables. The experimental results indicate the feasibility of using fuzzy logic to estimate arrival time for indoor navigation, with an average prediction error of 5.82%.
ABSTRAK: Beberapa tahun ini, Realiti Terimbuh (AR) telah menjadi popular dalam pelbagai industri kerana keupayaannya meningkatkan kecekapan, menyediakan maklumat dan data secara masa nyata, dan mengekalkan kesedaran pengguna terhadap persekitaran sekeliling. Salah satu aplikasi AR adalah dalam navigasi, tetapi kebanyakan sistem sedia ada lebih menumpukan kepada persekitaran luar, mengabaikan ruang dalaman. Aplikasi mudah alih yang direka untuk navigasi dalaman sering bergantung pada bekon mahal dan memerlukan komputasi tinggi atau penanda semula jadi bagi menjejaki lokasi pengguna sepanjang laluan yang ditetapkan. Selain itu, kaedah anggaran navigasi tradisional berdasarkan GPS tidak berkesan bagi navigasi dalaman. Kajian ini mencadangkan aplikasi AR mudah alih bagi navigasi dalaman yang menggunakan algoritma papan tanda pintar berdasarkan logik kabur bagi menganggarkan masa ketibaan. Algoritma ini mengambil pecutan telefon dalam arah x dan z sebagai input dan menggunakan fungsi keahlian berbentuk segi tiga bagi pemboleh ubah masuk dan keluar. Dapatan eksperimen menunjukkan kebolehan menggunakan logik kabur bagi menganggarkan masa ketibaan bagi navigasi dalaman, dengan kesilapan anggaran purata sebanyak 5.82%
Application of Kansei Engineering in Various Train Compartment Designs to Determine the User's Affective Response
Full text linkVisual appearance (shapes, colors, materials, and surfaces) applied to product design can provide users with emotional and positive affective responses. The desire of such users will provide essential guidelines for companies to develop products, in this case, trains, in the form of private spaces called compartments. Trains are in great demand for long trips, so there is a need for market segmentation. However, current research only focuses on designs that examine functionality needs. Lack of study of design based on visual appearance, research on user preferences, and more scientific evaluation of design is needed. Therefore, this study aims to translate the user's affective response into the interior design specifications of train compartments with the Kansei Engineering method. This research consists of 5 steps: (1) Determining product semantics (Kansei Words assignment); (2) Define product properties (items and categories), as many as eight design samples; (3) Distributing questionnaires to 150 respondents (75 men and 75 women); (4) Data analysis with multivariate statistics, KMO, Barlett's Test, Principal Component Analysis, and clustering of respondents; (5) Evaluate the results of the most optimal design specifications. The results of this study obtained design recommendations: straight shape, studio green color, pine wood HPL material texture, and doff surface. In addition, several user clusters were formed based on gender, age, and monthly income to segment train compartments when commercialized. This research is expected to be helpful for the wider community and the development of the interior design of train compartments.
ABSTRAK: Penampilan visual (bentuk, warna, bahan dan permukaan) yang digunakan pada reka bentuk produk dapat memberikan tindak balas emosi dan tindak balas afektif positif daripada pengguna. Keinginan pengguna akan memberikan garis panduan penting bagi syarikat untuk membangunkan produk, dalam kes ini kereta api dalam bentuk ruang peribadi yang dipanggil petak ruang kereta api. Kereta api mendapat permintaan yang tinggi bagi perjalanan jauh, jadi terdapat keperluan untuk pembahagian pasaran. Walau bagaimanapun, penyelidikan semasa hanya memberi tumpuan kepada reka bentuk yang mengkaji keperluan fungsi sahaja. Terdapat kekurangan kajian mengenai reka bentuk berdasarkan penampilan visual, penyelidikan mengenai keutamaan pengguna, dan penilaian reka bentuk yang lebih saintifik diperlukan. Oleh itu, kajian ini bertujuan untuk menterjemahkan tindak balas afektif pengguna ke dalam spesifikasi reka bentuk dalaman petak ruang kereta api menggunakan kaedah Kansei Engineering. Penyelidikan ini terdiri daripada 5 langkah: (1) Menentukan semantik produk (penentuan patah kata Kansei); (2) Tentukan sifat produk (item dan kategori), sebanyak lapan sampel reka bentuk; (3) Mengagihkan soal selidik kepada 150 responden (75 lelaki dan 75 perempuan); (4) Analisis data dengan statistik multivarian, KMO, Ujian Bartlett, analisis komponen utama, dan kelompok responden; (5) Penilaian keputusan spesifikasi reka bentuk paling optimum. Hasil kajian mencadangkan reka bentuk: bentuk lurus, warna hijau studio, tekstur bahan HPL kayu pain, dan permukaan doff. Di samping itu, beberapa kluster pengguna dibentuk berdasarkan jantina, umur dan pendapatan bulanan bagi memudahkan pembahagian petak ruang kereta api apabila dikomersialkan. Kajian ini dijangka berguna kepada masyarakat yang lebih luas dan pembangunan reka bentuk dalaman petak ruang kereta api pada masa hadapan
Optimizing N-1 Contingency Rankings Using a Nature-Inspired Modified Sine Cosine Algorithm
Full text linkEnsuring the reliability and sustainability of power systems is essential for maintaining efficient and uninterrupted operations, especially under varying load conditions and potential faults. This study tackles the critical task of contingency ranking by evaluating the severity of disturbances caused by transmission line disconnections. Such evaluations enable power system operators to make informed and strategic decisions during real-time scenarios. A novel approach utilizing the Modified Sine Cosine Algorithm (MSCA), a nature-inspired metaheuristic optimization technique, is proposed to resolve (N-1) contingency rankings efficiently. The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. Results demonstrate that MSCA achieves a high capture ratio of 96.67%, explores only 8.33 × 10??% of the search space, and requires a processing time of 3.69 seconds. Compared with established methods such as Ant Colony Optimization (ACO) and Genetic Algorithm (GA), MSCA exhibits superior computational efficiency while maintaining competitive accuracy. These findings underline the potential of MSCA in real-time applications where speed and precision are critical. By closely matching manual contingency rankings, the proposed method integrates reliability assessment and optimization techniques, offering practical value for improving system resilience and reducing risks associated with disruptions. This research advances state-of-the-art power system reliability assessment and optimization approaches, providing operators and planners with a robust tool for addressing complex contingency challenges.
ABSTRAK: Memastikan keandalan dan kelestarian sistem tenaga elektrik adalah penting untuk mengekalkan operasi yang cekap dan tidak terganggu, terutamanya dalam menghadapi keadaan beban yang berubah-ubah dan kemungkinan kerosakan. Kajian ini menangani tugas kritikal dalam perangkingan kontingensi dengan menilai tahap keparahan gangguan yang disebabkan oleh pemutusan talian penghantaran. Penilaian sebegini membolehkan pengendali sistem tenaga membuat keputusan yang berinformasi dan strategik dalam senario masa nyata. Pendekatan baharu yang menggunakan Modified Sine Cosine Algorithm (MSCA), satu teknik pengoptimuman metaheuristik yang diilhamkan oleh alam, dicadangkan untuk menyelesaikan perangkingan kontingensi (N-1) dengan cekap. Kaedah MSCA ini disahkan menggunakan kes ujian IEEE 30-bus dengan memberi tumpuan kepada penalaan parameter optimum untuk saiz populasi, iterasi, dan pemboleh ubah utama. Keputusan menunjukkan bahawa MSCA mencapai nisbah tangkapan yang tinggi sebanyak 96.67%, hanya meneroka 8.33 × 10??% daripada ruang pencarian, dan memerlukan masa pemprosesan sebanyak 3.69 saat. Berbanding dengan kaedah sedia ada seperti Ant Colony Optimization (ACO) dan Genetic Algorithm (GA), MSCA menunjukkan kecekapan pengiraan yang unggul sambil mengekalkan ketepatan yang kompetitif. Penemuan ini menekankan potensi MSCA dalam aplikasi masa nyata di mana kelajuan dan ketepatan adalah kritikal. Dengan hasil yang hampir menyamai perangkingan kontingensi manual, kaedah yang dicadangkan ini mengintegrasikan penilaian keandalan dan teknik pengoptimuman, memberikan nilai praktikal untuk meningkatkan daya tahan sistem dan mengurangkan risiko yang berkaitan dengan gangguan. Penyelidikan ini memajukan pendekatan terkini dalam penilaian keandalan sistem tenaga dan pengoptimuman, menyediakan pengendali dan perancang dengan alat yang kukuh untuk menangani cabaran kontingensi yang kompleks