IIUM Engineering Journal
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Editorial
Get PDFCHIEF EDITOR
Ahmad Faris Ismail, IIUM, Malaysia
TECHNICAL EDITOR
Sany Izan Ihsan, IIUM, Malaysia
EXECUTIVE EDITOR
AHM Zahirul Alam, IIUM, Malaysia
ASSOCIATE EDITOR
Nor Farahidah Za’bah, IIUM, Malaysia
LANGUAGE EDITOR
Lynn Mason, Malaysia
COPY EDITOR
Hamzah Mohd. Salleh, IIUM, Malaysia
MALAY TRANSLATOR
Nurul Arfah Che Mustapha, IIUM, Malaysia
EDITORIAL BOARD MEMBERS
Abdullah Al-Mamun, IIUM, Malaysia
Abdumalik Rakhimov, IIUM, Malaysia
Aishah Najiah Bt. Dahnel, IIUM, Malaysia
Alya Naili Binti Rozhan, IIUM, Malaysia
Norsinnira Bt. Zainul Azlan, IIUM, Malaysia
Hanafy Omar, Saudi Arabia
Hazleen Anuar, IIUM, Malaysia
Konstantin Khanin, University of Toronto, Canada
Ma'an Al-Khatib, IIUM, Malaysia
Meftah Hrairi, IIUM, Malaysia
Mohamed B. Trabia, United States
Mohammad S. Alam, Texas A&M University-Kingsville, United States
Mustafizur Rahman, National University Singapore, Singapore
Ossama Abdulkhalik, Michigan Technological University, United States
Mohamed Hadi Habaebi, IIUM, Malaysia
Mohd. Sultan Ibrahim Bin Shaik Dawood, IIUM, Malaysia
Muhammad Ibn Ibrahimy, IIUM, Malaysia
Nor Fadhillah Mohamed Azmin, IIUM, Malaysia
Waqar Asrar, IIUM, Malaysia
INTERNATIONAL ADVISORY COMMITTEE
A. Anwar, United States
Abdul Latif Bin Ahmad, Malaysia
Farzad Ismail, USM, Pulau Pinang, Malaysia
Hanafy Omar, Saudi Arabia
Hany Ammar, United States
Idris Mohammed Bugaje, Nigeria
K.B. Ramachandran, India
Kunzu Abdella, Canada
Luis Le Moyne, ISAT, University of Burgundy, France
M Mujtaba, United Kingdom
Mohamed AI-Rubei, Ireland
Mohamed B Trabia, United States
Syed Kamrul Islam, United States
Tibor Czigany, Budapest University of Technology and Economics, Hungary
Yiu-Wing Mai, The University of Sydney, Australia.
AIMS & SCOPE OF IIUM ENGINEERING JOURNAL
The IIUM Engineering Journal, published biannually (January and July), is a carefully refereed international publication of International Islamic University Malaysia (IIUM). Contributions of high technical merit within the span of engineering disciplines; covering the main areas of engineering: Electrical and Computer Engineering; Mechanical and Manufacturing Engineering; Automation and Mechatronics Engineering; Material and Chemical Engineering; Environmental and Civil Engineering; Biotechnology and Bioengineering; Engineering Mathematics and Physics; and Computer Science and Information Technology are considered for publication in this journal. Contributions from other areas of Engineering and Applied Science are also welcomed. The IIUM Engineering Journal publishes contributions under Regular papers and Invited review papers. It also welcomes contributions that address solutions to the specific challenges of the developing world, and address science and technology issues from an Islamic and multidisciplinary perspective.
REFEREES’ NETWORK
All papers submitted to IIUM Engineering Journal will be subjected to a rigorous reviewing process through a worldwide network of specialized and competent referees. Each accepted paper should have at least two positive referees’ assessments.
SUBMISSION OF A MANUSCRIPT
A manuscript should be submitted online to the IIUM Engineering Journal website at
http://journals.iium.edu.my/ejournal. Further correspondence on the status of the paper could be done through the journal website.
Whilst every effort is made by the publisher and editorial board to see that no inaccurate or misleading data, opinion, or statement appears in this Journal, they wish to make it clear that the data and opinions appearing in the articles and advertisements herein are the responsibility of the contributor or advertiser concerned. Accordingly, the publisher and the editorial committee accept no liability whatsoever for the consequence of any such inaccurate or misleading data, opinion, or statement.
IIUM Engineering Journal
ISSN: 1511-788X E-ISSN: 2289-7860
Published by: IIUM Press, International Islamic University Malaysia Jalan Gombak, 53100 Kuala Lumpur, Malaysia Phone (+603) 6421-5014, Fax: (+603) 6421-629
CORONARY HEART DISEASE CLASSIFICATION USING IMPROVED PENGUIN EMPEROR OPTIMIZATION-BASED LONG SHORT TERM MEMORY NETWORK
Get PDFVentricular fibrillation (VF) is the most life-threatening and dangerous type of Cardiac Arrhythmia (CA), with a mortality rate of 10-15% in a year. Therefore, early detection of cardiac arrhythmia is important to reduce the mortality rate. Many machine learning algorithms have been proposed and have proven their usefulness in the classification and detection of heart problems. In this research manuscript, a novel Long Short Term Memory (LSTM) classifier with Improved Penguin Optimization (IPEO) is implemented for VF classification. The IPEO is used in finding optimal hyperparameters that overcome the overfitting problem. The presented model is tested, trained, and validated using two standard datasets that are available publicly: Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) and the China Physiological Signal Challenge (CPSC) 2018 dataset. Both of them consist of ECG recordings for five seconds of coronary heart disease (CHD) patients. Furthermore, Fuzzy C-Means and Enhanced Fuzzy Rough Set method (FCM-ETIFRST) are used for feature selection to extract informative features and to cluster membership degree, non-membership degree, and hesitancy degree. On the MIT-BIH dataset, the proposed model achieved accuracy, sensitivity, specificity, precision, and Matthews’s correlation coefficient (MCC) of 99.75%, 98.29%, 98.39%, 98.35%, and 97.79% respectively. On the CPSC 2018 dataset, the proposed model achieved accuracy of 99.79%, sensitivity of 99.11%, specificity of 98.20%, precision of 99.43%, and MCC of 98.57%. Hence, the results proved that the proposed method provides better results in the classification of VF.
ABSTRAK: Pemfibrilan Ventrikel (VF) adalah ancaman nyawa nombor satu dan jenis Aritmia Jantung (CA) berbahaya dengan kadar kematian 10-15% setahun. Oleh itu, pengesanan awal Aritmia Jantung sangat penting bagi mengurangkan kadar kematian. Terdapat banyak algoritma pembelajaran mesin yang telah dicadangkan dan terbukti berkesan dalam pengelasan dan pengesanan sakit jantung. Kajian ini mencadangkan kaedah baru pengelasan Memori Ingatan Jangka Panjang Pendek (LSTM) dengan Pengoptimuman Penambahbaikan Penguin (IPEO) yang dilaksanakan bagi klasifikasi VF. IPEO digunakan bagi mencari hiperparameter yang dapat mengatasi masalah padanan berlebihan. Model yang dicadangkan diuji, dilatih dan disahkan menggunakan dua dataset piawai yang dapat diperoleh secara terbuka: Institut Teknologi Hospital Massachusetts-Beth Israel (MIT-BIH) dan Cabaran Signal Psikologi Cina 2018 (CPSC). Kedua-dua data ini mempunyai rakaman ECG selama lima saat daripada pesakit Penyakit Jantung Koronari (CHD). Malah, kajian itu turut menggunakan Purata-C Kabur dan Kaedah Set Kasar Kabur Dipertingkat (FCM-ETIFRST) untuk pemilihan bagi mengekstrak ciri-ciri dan mengelaskan kelompok tahap keahlian, bukan ahli dan tahap keraguan. Bagi dataset MIT-BIH, model yang dicadangkan mencapai ketepatan, tahap sensitif, tahap spesifik, kejituan dan pekali kaitan Matthews (MCC) sebanyak 99.75%, 98.29%, 98.39%, 98.35%, dan 97.79% masing-masing. Bagi dataset CPSC 2018 pula, model yang dicadangkan mencapai ketepatan sebanyak 99.79%, 99.11% tahap sensitif , 98.20% tahap spesifik, 99.43% kejituan dan 98.57% MCC. Oleh itu, dapatan kajian membuktikan kaedah yang dicadangkan menunjukkan keputusan lebih baik dalam pengelasan VF
TREBLE SEARCH OPTIMIZER: A STOCHASTIC OPTIMIZATION TO OVERCOME BOTH UNIMODAL AND MULTIMODAL PROBLEMS
Get PDFToday, many metaheuristics have used metaphors as their inspiration and baseline for novelty. It makes the novel strategy of these metaheuristics difficult to investigate. Moreover, many metaheuristics use high iteration or swarm size in their first introduction. Based on this consideration, this work proposes a new metaheuristic free from metaphor. This metaheuristic is called treble search optimizer (TSO), representing its main concept in performing three searches performed by each member in each iteration. These three searches consist of two directed searches and one random search. Several seeds are generated from each search. Then, these searches are compared with each other to find the best seed that might substitute the current corresponding member. TSO is also designed to overcome the optimization problem in the low iteration or swarm size circumstance. In this paper, TSO is challenged to overcome the 23 classic optimization functions. In this experiment, TSO is compared with five shortcoming metaheuristics: slime mould algorithm (SMA), hybrid pelican komodo algorithm (HPKA), mixed leader-based optimizer (MLBO), golden search optimizer (GSO), and total interaction algorithm (TIA). The result shows that TSO performs effectively and outperforms these five metaheuristics by making better fitness scores than SMA, HPKA, MLBO, GSO, and TIA in overcoming 21, 21, 23, 23, and 17 functions, consecutively. The result also indicates that TSO performs effectively in overcoming unimodal and multimodal problems in the low iteration and swarm size.
ABSTRAK: Dewasa ini, terdapat ramai metaheuristik menggunakan metafora sebagai inspirasi dan garis dasar pembaharuan. Ini menyebabkan strategi baharu metaheuristik ini susah untuk dikaji. Tambahan, ramai metaheuristik menggunakan ulangan berulang atau saiz kerumunan dalam pengenalan mereka. Berdasarkan penilaian ini, kajian ini mencadangkan metaheuristk baharu bebas metafora. Metaheuristik ini dipanggil pengoptimum pencarian ganda tiga (TSO), mewakilkan konsep utama dalam pemilihan tiga pencarian yang dilakukan oleh setiap ahli dalam setiap ulangan. Ketiga-tiga carian ini terdiri daripada dua pencarian terarah dan satu pencarian rawak. Beberapa benih dihasilkan dalam setiap carian. Kemudian, carian ini dibandingkan antara satu sama lain bagi mencari benih terbaik yang mungkin berpotensi menggantikan ahli yang sedang digunakan. TSO juga direka bagi mengatasi masalah pengoptimuman dalam ulangan rendah atau lingkungan saiz kerumunan. Kajian ini TSO dicabar bagi mengatasi 23 fungsi pengoptimuman klasik. Eksperimen ini TSO dibandingkan dengan lima kekurangan metaheuristik: algoritma acuan lendir (SMA), algorithma hibrid komodo burung undan (HPKA), Pengoptimum Campuran berdasarkan-Ketua (MLBO), Pengoptimuman Carian Emas (GSO), dan algoritma jumlah interaksi (TIA). Dapatan kajian menunjukkan TSO berkesan menghasilkan dan lebih baik daripada kelima-lima metaheuristik dengan menghasilkan pemarkahan padanan terbaik berbanding SMA, HPKA, MLBO, GSO, dan TIA dalam mengatasi fungsi 21, 21, 23, 23, dan 17, secara berurutan. Dapatan kajian juga menunjukkan TSO turut berperanan efektif dalam mengatasi masalah modal tunggal dan modal ganda dalam iterasi rendah dan saiz kerumunan
A Quick and Facile Solution-Processed Method for PEDOT:PSS Transparent Conductive Thin Film
Get PDFPEDOT:PSS is a conducting organic polymer widely studied for a transparent conductive electrode. The conventional method to fabricate PEDOT:PSS thin film involves a post-treatment process entailing dipping into strong and toxic saturated acid to enhance the film’s conductivity. Eliminating the post-treatment process reduces excess strong saturated acid or solvent waste, shortening the fabricating time by half. Therefore, this study presents a quick and facile solution-processed method for fabricating the PEDOT:PSS transparent conductive thin film (without a post-treatment process) while still achieving the requirements for a transparent conductive electrode (TCE). A parametric study was conducted by adding 5 wt% to 80 wt% of benzene sulfonic acid (BA) to PEDOT:PSS during the formulation stage before being dried at elevated temperatures from 80 °C to 200 °C. The optimum sheet resistance and transmittance value could be achieved for a thin film fabricated from PEDOT:PSS added with 40 wt% of BA, and dried at 120 °C. The sheet resistance and transmittance values are 80 ?/sq and 93.6%, respectively. The generated figure of merit (FOM) value is 70.1, indicating an improvement of almost five times compared to the FOM value of 14.6 generated using the conventional method, requiring a post-treatment process.
ABSTRAK: PEDOT:PSS adalah bahan polimer organik yang mengkonduksi arus dan dikaji secara meluas bagi digunakan sebagai elektrod konduktif telus. Kaedah konvensional untuk menghasilkan filem nipis PEDOT:PSS melibatkan proses pasca rawatan iaitu dengan mencelupkan filem nipis PEDOT:PSS ke dalam asid pekat bertoksik bagi meningkatkan konduksi filem tersebut. Tanpa proses pasca rawatan ini dapat mengurangkan penghasilan sisa lebihan seperti asid pekat bertoksik atau pelarut buangan, memendekkan masa fabrikasi sebanyak separuh. Oleh itu, kajian ini menghasilkan kaedah proses-penyelesaian yang cepat dan mudah bagi fabrikasi filem nipis PEDOT:PSS (tanpa proses pasca rawatan) disamping masih mencapai keperluan sebagai elektrod konduktif telus (TCE). Kajian parametrik telah dijalankan dengan menambah 5 wt% hingga 80 wt% asid sulfonik benzena (BA) ke dalam PEDOT:PSS pada peringkat percampuran kimia sebelum dikeringkan pada kenaikan suhu secara berperingkat dari 80 °C sehingga 200 °C. Nilai optimum bagi rintangan lapisan dan nilai ketelusan bagi filem nipis PEDOT:PSS yang difabrikasi dapat dicapai melalui penambahan sebanyak 40 wt% BA dan dikeringkan pada suhu 120 °C. Rintangan lapisan dan nilai ketelusan telah dicapai sebanyak 80 ?/sq dan 93.6%, masing-masing. Nilai gambaran merit (FOM) yang terhasil adalah 70.1, menunjukkan peningkatan hampir lima kali ganda berbanding nilai FOM 14.6 yang terhasil menggunakan kaedah konvensional yang memerlukan proses pasca-rawatan
EXPERIMENTAL AND COMPUTATIONAL ANALYSIS FOR OPTIMIZATION OF SEAWATER BIODEGRADABILITY USING PHOTO CATALYSIS
Get PDFSeawater pollution is a significant global environmental problem. Various technologies and methods have been used to remove the contaminants found in saltwater. This experimental study investigates the degradation of contaminants present in seawater using solar photocatalysis, where a combination of TiO2 and ZnO was used. The effects of catalyst dosage, pH, and reaction duration were assessed using percentage removal efficiencies of total organic carbon (TOC), chemical oxygen demand (COD), biological oxygen demand (BOD), and biodegradability (BOD/COD). Biodegradability is essential for removing pollutants from saltwater and plays a vital role. The higher the biodegradability, the more efficient the treatment procedure will be. The most effective percentage reduction rates from the experimental data obtained were TOC=59.80%, COD=75.20%, BOD=23.94%, and biodegradability=0.055. For modeling, optimizing, and assessing the effects of parameters, the Design Expert based on Box Behnken design (RSM-BBD) and a predictive model based on the MATLAB adaptive neuro-fuzzy inference system (ANFIS) tools were used. The coefficient of determination R2 was found to be 0.977 for the RSM-BBD model and 0.99 for the ANFIS model. According to the RSM-BBD design, the maximum percentage pollutant elimination efficiencies were found to be TOC=55.4, COD=73.4, BOD=23.70%, and BOD/COD=0.054, but for the ANFIS model, they were TOC=59.4, COD=75.4, BOD=24.1%, and BOD/COD=0.055. It was discovered that the ANFIS model outperformed RSM-BBD in process optimization.
ABSTRAK: : Pencemaran air laut adalah masalah alam sekitar global yang ketara. Pelbagai teknologi dan kaedah telah digunakan bagi menyingkirkan pencemaran yang dijumpai dalam air laut. Kajian eksperimen ini menilai degradasi pencemaran yang hadir dalam air laut menggunakan fotopemangkin, di mana kombinasi TiO2 dan ZnO digunakan. Kesan dos pemangkin, pH, dan tempoh reaksi dipantau menggunakan peratus kecekapan penyingkiran jumlah karbon organik (TOC), keperluan kimia oksigen (COD), keperluan biologi oksigen (BOD), dan kebolehdegradasian (BOD/COD). Kebolehdegradasian adalah sangat penting bagi menyingkirkan bahan cemar dari air laut dan berperanan penting. Semakin tinggi kebolehdegradasian, semakin cekap prosedur rawatan. Peratus kadar pengurangan yang paling berkesan daripada data eksperimen adalah didapati pada TOC=59.80%, COD=75.20%, BOD=23.94%, dan biodegradasi=0.055. Bagi mengkaji kesan parameter terhadap model, kadar optimum, dan memantau keberkesanan parameter, kaedah Pakar Reka Bentuk pada rekaan Kotak Behnken (RSM-BBD) dan model ramalan berdasarkan sistem pengaruh menggunakan sistem MATLAB iaitu Inferens Neural-Fuzi Boleh Suai (ANFIS) digunakan. Pekali penentu R2 terhasil pada 0.977 bagi model RSM-BBD dan 0.99 pada model ANFIS. Berdasarkan reka bentuk RSM-BBD, peratus maksimum keberkesanan penyingkiran bahan cemar dijumpai pada TOC=55.4, COD=73.4, BOD=23.70%, dan BOD/COD=0.054, tetapi bagi model ANFIS, TOC=59.4, COD=75.4, BOD=24.1%, dan BOD/COD=0.055. Model ANFIS adalah lebih berkesan daripada model RSM-BBD dalam proses pengoptimuman
Performance Analysis of Predictive Functional Control for Automobile Adaptive Cruise Control System
Get PDFThis paper presents the performance analysis of Predictive Functional Control (PFC) for Adaptive Cruise Control (ACC) application. To cope with multiple driving objectives of modern ACC systems such as passenger comfort, safe distancing, and fast time response, an advanced optimal controller such as Model Predictive Control (MPC) is often used. Nevertheless, MPC requires a high computation load due to its complex formulation and may overload the processing power of a microcontroller. Thus, the prime objective of this work is to propose a PFC algorithm as an alternative controller, while providing a formal comparison between MPC and the traditional Proportional Integral (PI) controller. A standard kinematic model for vehicle longitudinal dynamics was modelled and used to derive the control law of PFC. Since the open-loop dynamic of the derived transfer function is not stable, the second objective is to propose a pre-stabilized loop or cascade PFC structure for the system. A complete tuning procedure and analysis were presented. The simulation result shows that although MPC performance is the best for the ACC application with Root Mean Square Error (RMSE) of 1.4873, PFC has shown a promising response with RMSE of 1.5501, which is better compared to the PI controller with RMSE of 1.6219. All the imposed driving constraints such as maximum acceleration, maximum deceleration and safe distance were satisfied in the car following application. Thus, the findings from this work can become a good initial motivation to further explore the capability of the PFC algorithm for future ACC development.
ABSTRAK: Kajian ini adalah berkenaan analisis prestasi Kawalan Fungsi Ramalan (PFC) aplikasi Kawalan Mudah Suai (ACC). Bagi memenuhi pelbagai keperluan objektif sistem pemanduan moden ACC seperti keselesaan penumpang, penjarakan selamat dan tindak balas pantas, kawalan optimum terbaru seperti Model Kawalan Ramalan (MPC) sering digunakan. Walau bagaimanapun, MPC memerlukan beban pengiraan tinggi kerana rumusnya yang kompleks dan mungkin mengakibatkan beban berlebihan kuasa pemprosesan mikrokawalan. Oleh itu, matlamat utama kajian ini adalah bagi mencadangkan algoritma PFC yang mempunyai pengiraan mudah sebagai kawalan alternatif, sementara menyediakan perbandingan formal antara MPC dan kawalan tradisional Berkadar Keseluruhan (PI). Oleh kerana model ini tidak stabil, objektif kedua adalah mencadangkan penggunaan struktur PFC berlapis bagi menstabilkan sistem terlebih dahulu sebelum algorithma kawalan digunakan atau dengan menggunakan struktur PFC secara berturut pada sistem. Prosedur lengkap dan terperinci untuk analisis PFC dibentangkan. Dapatan simulasi kajian menunjukkan walaupun prestasi MPC adalah baik bagi aplikasi ACC dengan Ralat Punca Min Kuasa Dua (RMSE) bernilai 1.4873, namun PFC menunjukkan tindak balas baik dengan RMSE bernilai 1.5501 berbanding kawalan PI yang mempunyai RMSE sebanyak 1.6219. Kesemua kekangan seperti pecutan dan nyahpecutan maksima, dan penjarakan selamat bertepatan dengan aplikasi kenderaan ini. Dengan itu, penemuan ini adalah motivasi awal yang baik bagi meneroka lebih jauh keupayaan algoritma PFC bagi membangun ACC pada masa hadapan
Effect of the lignocellulolytic substrates and fermentation process parameters on myco-coagulant production for water treatment
Get PDFIn the present research, a fungal strain was used to produce a myco-coagulant via solid-state bioconversion to reduce water turbidity. The production of myco-coagulant was achieved using several low-cost lignocellulolytic substrates, namely coco peat, sawdust, palm kernel cake, and rice bran as sources of carbon and nitrogen. This research involves the study of both the effect of lignocellulolytic substrates and the parameters involved in the fermentation process for myco-coagulant production. Coco peat was chosen as a suitable lignocellulolytic substrate to serve as a carbon source for producing myco-coagulant, potentially reducing the turbidity by 84.6% from the kaolin suspension. Sawdust, palm kernel cake, and rice bran showed 33.06%, 30.18, and 21.18 %, respectively. Furthermore, a statistical approach to the Plackett-Burman design was conducted to evaluate the significant parameters that affect the production of myco-coagulant. Eleven fermentation process parameters were selected: concentration of coco peat (2- 4 %), incubation time (5-9 days), temperature (25-35 °C), pH (5-9), glucose (0-2 %), malt extract (1-2 %), yeast extract (0-2%), wheat flour (0-2 %), ammonium sulfate (0-1 %), inoculum size (1-3 %) and potassium dihydrogen phosphate (0-0.5 %). The selected variables were assessed through statistical analysis (main effects) based on their significance. Based on the main effect of each variable on flocculation activity, three variables, namely glucose, malt extract, and pH influenced high levels. On the other hand, the remaining eight variables did not significantly affect the production of myco-coagulant. Furthermore, a deeper study was conducted to further optimize the three effective variables involved in the fermentation process to evaluate these factors' influence on flocculation activity.
ABSTRAK: Penyelidikan ini adalah berkenaan strain fungus yang digunakan bagi menghasilkan miko-koagulan melalui penukaran-bio berkeadaan pepejal bagi mengurangkan kekeruhan air. Miko-koagulan dihasilkan dengan menggunakan beberapa substrat lignoselulolitik berkos rendah, iaitu habuk kelapa, habuk papan, hampas kelapa sawit, dan dedak padi sebagai sumber karbon dan nitrogen. Penyelidikan ini mengkaji kesan substrat lignoselulolitik dan faktor-faktor yang terlibat dalam proses fermentasi bagi menghasilkan miko-koagulan. Habuk kelapa dipilih sebagai substrat lignoselulolitik yang sesuai berfungsi sebagai sumber karbon dalam menghasilkan miko-koagulan, berpotensi mengurangkan kekeruhan sebanyak 84.6% daripada ampaian kaolin. Sebaliknya, habuk papan, hampas kelapa sawit, dan dedak padi menunjukkan 33.06%, 30.18, dan 21.18 %, masing-masing. Tambahan pula, pendekatan statistik ke atas reka bentuk Plackett-Burman telah dijalankan bagi menilai parameter penting yang mempengaruhi penghasilan miko-koagulan. Sebelas parameter proses penapaian telah dipilih: kepekatan habuk kelapa (2- 4 %), masa pengeraman (5-9 hari), suhu (25-35 C), pH (5-9), glukosa (0-2 %), ekstrak malt (1-2), tepung gandum (0-2 %), ammonium sulfat (0-1%), saiz inokulum (1-3 %) dan Kalium dihidrogen fosfat (0-0.5 %). Pemboleh ubah yang dipilih dinilai melalui analisis statistik berdasarkan kepentingannya. Berdasarkan kesan utama setiap pemboleh ubah terhadap aktiviti penggumpalan, tiga pemboleh ubah ini adalah glukosa, ekstrak malt, dan pH yang memberi kesan tertinggi. Sebaliknya, lapan pemboleh ubah lain tidak mempengaruhi penghasilan miko-koagulan dengan ketara. Tambahan lagi, kajian yang lebih mendalam telah dijalankan bagi membaiki tiga pemboleh ubah utama yang terlibat dalam proses fermentasi bagi menilai kesan yang mempengaruhi aktiviti penggumpalan
Battery Energy Storage System (BESS) Modeling for Microgrid
Get PDFIn the age of technology, microgrids have become well known because of their capability to back up the grid when an unpleasant event is about to occur or during power disruptions, at any time. However, the microgrid will not function well during power disruptions if the controller does not respond fast enough and the BESS will be affected. Many types of controllers can be used for microgrid systems. The controllers may take the form of Maximum Power Point Tracking (MPPT) Controller, Proportional Integral Derivative (PID) Controller, and Model Predictive Controller (MPC). Each of the controllers stated has its functions for the microgrid. However, two controllers that must be considered are PID and MPC. Both controllers will be compared based on their efficiency results which can be obtained through simulations by observing both graphs in charging and discharging states. Most researchers implied that MPC is better than PID because of several factors such as MPC is more robust and stable because of its complexity. Other than that, MPC can handle more inputs and outputs than PID which can cater to one input and output only. Although MPC has many benefits over the PID, still it is not ideal due to its complex algorithm. This work proposed an algorithm of simulations for the MPC to operate to get the best output for microgrid and BESS and compare the performance of MPC with PID. Using Simulink and MATLAB as the main simulation software is a very ideal way to simulate the dynamic performance of MPC. Furthermore, with Simulink, unpredictable variables such as Renewable Energy (RE) sources input and loads demands that are related to MPC can be measured easily. The algorithm of MPC is a cost function. Then the performance of the MPC is calculated using Fast-Fourier Transform (FFT) and Total Harmonic Distortion (THD). Lower THD means a higher power factor, this results in higher efficiency. This paper recorded THD of 9.57% and 12.77% in charging states and 16.51% and 18.15% in discharging states of MPC. Besides, PID recorded THD of 22.10% and 29.73% in charging states and 84.29% and 85.58% in discharging states. All of the recorded THD is below 25% in MPC and it shows a good efficiency while PID’s THD is above 25% shows its inefficiency.
ABSTRAK: Pada zaman teknologi, mikrogrid menjadi terkenal kerana keupayaannya untuk menjana kuasa grid apabila kejadian yang tidak menyenangkan bakal berlaku atau ketika terjadinya gangguan kuasa, pada bila-bila masa. Walau bagaimanapun, mikrogrid tidak dapat berfungsi dengan baik semasa gangguan kuasa jika alat kawalan tidak bertindak balas dengan cukup pantas dan BESS akan terjejas. Banyak alat kawalan (pengawal) boleh digunakan bagi keseluruhan sistem mikrogrid. Setiap pengawal adalah berbeza seperti Pengawal Penjejakan Titik Kuasa Maksimum (MPPT), Pengawal Berkadar Terbitan Kamilan (PID) dan Pengawal Model Ramalan (MPC). Setiap pengawal yang dinyatakan mempunyai fungsinya yang tersendiri bagi mikrogrid. Walau bagaimanapun, dua pengawal yang perlu dipertimbangkan adalah PID dan MPC. Kedua-dua pengawal ini akan dibandingkan berdasarkan keputusan kecekapan yang boleh didapati melalui simulasi dengan memerhati kedua-dua graf pada keadaan pengecasan dan nyahcas. Ramai penyelidik menganggap bahawa MPC adalah lebih baik berbanding PID kerana beberapa faktor seperti MPC lebih teguh dan stabil kerana kerumitannya. Selain itu, MPC dapat mengendalikan lebih banyak input dan output berbanding PID yang hanya dapat menyediakan satu input dan output sahaja. Walaupun MPC mempunyai banyak faedah berbanding PID, ianya masih tidak sesuai kerana algoritma yang kompleks. Kajian ini mencadangkan algoritma simulasi bagi MPC beroperasi mendapatkan output terbaik untuk mikrogrid dan BESS dan membandingkan prestasi MPC dengan PID. Perisian simulasi utama yang sangat ideal bagi mensimulasi prestasi dinamik MPC adalah dengan menggunakan Simulink dan MATLAB. Tambahan, dengan Simulink, pembolehubah yang tidak terjangka seperti sumber Tenaga Boleh Diperbaharui (RE) dan permintaan beban yang berkaitan MPC boleh diukur dengan mudah. Algoritma MPC adalah satu fungsi kos. Kemudian prestasi MPC dikira menggunakan Penjelmaan Fourier Pantas (FFT) dan Total Pengherotan Harmonik (THD). THD yang lebih rendah bermakna faktor kuasa meningkat, ini menghasilkan kecekapan yang lebih tinggi. Kajian ini mencatatkan THD sebanyak 9.57% dan 12.77% dalam keadaan mengecas dan 16.51% dan 18.15% dalam keadaan nyahcas oleh MPC. Selain itu, PID mencatatkan THD sebanyak 22.10% dan 29.73% dalam keadaan mengecas dan 84.29% dan 85.58% dalam keadaan nyahcas. Semua THD yang direkodkan adalah di bawah 25% bagi MPC dan ia menunjukkan kecekapan yang baik manakala THD bagi PID adalah melebihi 25% menunjukkan ketidakcekapan
MODIFIED SEIRD MODEL: A NOVEL SYSTEM DYNAMICS APPROACH IN MODELLING THE SPREAD OF COVID-19 IN MALAYSIA DURING THE PRE-VACCINATION PERIOD
Get PDFMathematical modelling is an effective tool for understanding the complex structures and behaviors of natural phenomena, such as coronavirus disease 2019 (COVID-19), which is an infectious disease caused by a life-threatening virus called SARS-CoV-2. It has rapidly spread across the world in the last three years, including Malaysia. Adopting a novel system dynamics approach, this paper aims to explain how mathematics can play a significant role in modelling the COVID-19 spread and suggests practical methods for controlling it. It forecasts the data of infected (I), recovered (R) and death (D) cases for decision-making. This paper proposes a modified Susceptible-Exposed-Infected-Recovered-Death (SEIRD) model with time-varying parameters considering the sporadic cases, the reinfection cases, the implementation of a movement control order, and the percentage of humans abiding by the rules to forecast future growth patterns of COVID-19 in Malaysia and to study the effects of the consideration on the number of forecasted COVID-19 cases, during the pre-vaccination period. This study implemented the preliminary stage of forecasting the COVID-19 data using the proposed SEIRD model and highlighted the importance of parameter optimization. The mathematical model is solved numerically using built-in Python function ‘odeint’ from the Scipy library, which by default uses LSODA algorithm from the Fortran library Odepack that adopts the integration method of non-stiff Adams and stiff Backward Differentiation (BDF) with automatic stiffness detection and switching. This paper suggests that the effects of factors of sporadic cases, reinfection cases, government intervention of movement control order and population behavior are important to be studied through mathematical modelling as it helps in understanding the more complex behavior of COVID-19 transmission dynamics in Malaysia and further helps in decision-making.
ABSTRAK: Pemodelan matematik adalah alat berkesan bagi memahami struktur kompleks dan tingkah laku fenomena semula jadi, seperti penyakit coronavirus 2019 (COVID-19), iaitu penyakit berjangkit yang disebabkan oleh virus pengancam nyawa yang dipanggil SARS-CoV-2. Ia telah merebak dengan pantas ke seluruh dunia sejak tiga tahun lepas, termasuk Malaysia. Mengguna pakai pendekatan baharu sistem dinamik, kajian ini bertujuan bagi menerangkan bagaimana matematik boleh memainkan peranan penting dalam membentuk model penyebaran COVID-19, dan mencadangkan kaedah praktikal bagi mengawalnya. Model ini dapat meramalkan data sebenar kes yang dijangkiti, pulih dan kematian bagi membuat keputusan. Kajian ini mencadangkan model populasi Rentan-Terdedah-Terjangkiti-Pulih-Mati (SEIRD) yang diubah suai bersama parameter masa berbeza seperti kes sporadis, kes jangkitan semula, pelaksanaan perintah kawalan pergerakan, dan peratusan manusia patuh peraturan bagi meramal pertumbuhan corak kes COVID-19 di Malaysia pada masa hadapan dan mengkaji kesan–kesan pertimbangan parameter tersebut ke atas bilangan kes COVID-19 yang diramalkan ketika tempoh sebelum vaksinasi. Kajian ini melaksanakan peringkat awal ramalan data COVID-19 menggunakan model SEIRD yang dicadangkan dan menekankan kepentingan pengoptimuman parameter. Model matematik ini diselesaikan secara berangka menggunakan fungsi terbina Python ‘odeint’ daripada perpustakaan Scipy, yang menggunakan algoritma LSODA daripada perpustakaan Fortran Odepack menerusi kaedah penyepaduan Adams tidak kaku dan Pembezaan Belakang (BDF) kaku dengan pengesanan dan pertukaran kekakuan automatik. Kajian ini mencadangkan kesan faktor kes sporadis, kes jangkitan semula, campur tangan kerajaan terhadap perintah kawalan pergerakan dan tingkah laku penduduk adalah penting untuk dikaji melalui pemodelan matematik kerana ia membantu dalam memahami tingkah laku yang lebih kompleks dalam dinamik penularan COVID-19 di Malaysia dan seterusnya membantu dalam membuat keputusan.
ABSTRAK: Pemodelan matematik adalah alat berkesan bagi memahami struktur kompleks dan tingkah laku fenomena semula jadi, seperti penyakit coronavirus 2019 (COVID-19), iaitu penyakit berjangkit yang disebabkan oleh virus pengancam nyawa yang dipanggil SARS-CoV-2. Ia telah merebak dengan pantas ke seluruh dunia sejak tiga tahun lepas, termasuk Malaysia. Mengguna pakai pendekatan baharu sistem dinamik, kajian ini bertujuan bagi menerangkan bagaimana matematik boleh memainkan peranan penting dalam membentuk model penyebaran COVID-19, dan mencadangkan kaedah praktikal bagi mengawalnya. Model ini dapat meramalkan data sebenar kes yang dijangkiti, pulih dan kematian bagi membuat keputusan. Kajian ini mencadangkan model populasi Rentan-Terdedah-Terjangkiti-Pulih-Mati (SEIRD) yang diubah suai bersama parameter masa berbeza seperti kes sporadis, kes jangkitan semula, pelaksanaan perintah kawalan pergerakan, dan peratusan manusia patuh peraturan bagi meramal pertumbuhan corak kes COVID-19 di Malaysia pada masa hadapan dan mengkaji kesan–kesan pertimbangan parameter tersebut ke atas bilangan kes COVID-19 yang diramalkan ketika tempoh sebelum vaksinasi. Kajian ini melaksanakan peringkat awal ramalan data COVID-19 menggunakan model SEIRD yang dicadangkan dan menekankan kepentingan pengoptimuman parameter. Model matematik ini diselesaikan secara berangka menggunakan fungsi terbina Python ‘odeint’ daripada perpustakaan Scipy, yang menggunakan algoritma LSODA daripada perpustakaan Fortran Odepack menerusi kaedah penyepaduan Adams tidak kaku dan Pembezaan Belakang (BDF) kaku dengan pengesanan dan pertukaran kekakuan automatik. Kajian ini mencadangkan kesan faktor kes sporadis, kes jangkitan semula, campur tangan kerajaan terhadap perintah kawalan pergerakan dan tingkah laku penduduk adalah penting untuk dikaji melalui pemodelan matematik kerana ia membantu dalam memahami tingkah laku yang lebih kompleks dalam dinamik penularan COVID-19 di Malaysia dan seterusnya membantu dalam membuat keputusan
Comparative Assessment of Numerical Techniques for Weibull Parameters’ Estimation and the Performance of Wind Energy Conversion Systems in Nigeria
Get PDFThe wind speed of a location is a critical parameter for analyzing wind energy conversion systems. Background knowledge has revealed that the two-parameter Weibull distribution is commonly used for fitting wind speed data because of its simplicity, flexibility and suitability. This research study examines wind speed data from five locations in Nigeria (Kano, Maiduguri, Jos, Abuja and Akure). It employs five numerical techniques, namely the maximum likelihood method, method of moment, power density method, empirical method and the logarithmic moment method, to estimate the Weibull parameters based on the locations’ data. The goodness of fit test is used to determine which numerical method best fits the distribution. The paper also considers the techno-economic design of wind electricity of five 25 kW pitch-controlled wind turbines with dissimilar characteristics. The test result presents the method of moment and empirical method as the best methods for calculating the Weibull parameters. Results also show that wind turbine-3 has the least cost of energy and wind turbine-5 has the highest cost of energy.
ABSTRAK: Kelajuan angin sesuatu lokasi adalah parameter kritikal bagi menganalisa sistem penukaran tenaga angin. Latar belakang berkaitan telah mendedahkan 2-parameter taburan Weibull (Wbl) lazimnya digunakan bagi memadan data kelajuan angin berdasarkan kesederhanaan, fleksibiliti dan kesesuaian. Kajian penyelidikan ini adalah berkaitan ujian data kelajuan angin pada lima lokasi di Nigeria (Kano, Maiduguri, Jos, Abuja dan Akure). Ia menggunakan lima teknik berangka iaitu kaedah kemungkinan maksimum, kaedah momen, kaedah ketumpatan kuasa, kaedah empirikal dan kaedah momen logaritma bagi menganggar parameter Weibull berdasarkan lokasi data. Ujian kesesuaian digunakan bagi memastikan kaedah berangka adalah padanan paling sesuai bagi taburan. Kajian ini juga turut menimbang reka bentuk tekno-ekonomi elektrik angin bagi lima turbin angin 25 kW kawalan anggul dengan ciri berbeza. Dapatan kajian menunjukkan momen dan kaedah empirikal adalah kaedah terbaik bagi mengira parameter Weibull. Ini menunjukkan bahawa turbin angin-3 mempunyai kos tenaga paling rendah dan turbin angin-5 mempunyai kos tenaga tertinggi