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Hybrid restarting-Lanczos-SVR for solving high dimensions of PDE engineering problems

AIP Conference Proceedings 2022年第1期2472卷

作者： Rehana Thalib Maharani A. Bakar 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia 2Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia

Machine learning (ML) has shown a significant development in the application of several fields such as sciences, engineering, and technology. Its typical supervised and unsupervised learning makes ML desirable for us to use, since it is based on the availability of our data and the research problems. Regarding the prediction data, there are some methods under the ML that can be categorized as supervised learning, such as decision trees, regression analysis, and support vector regression (SVR). The latter one is a well-known regression or prediction tool which aims to find a function that approximates output to an actual target with minimum tolerance error. In this paper, we used SVR to predict a new approximate solution after we generated some iterates using an iterative method called Lanczos algorithm for solving high dimensional non-symmetric systems of linear equations (SLEs). Here, the SLEs are built from partial differential equations (PDEs) problems using the finite difference method (FDM). We solved the variety of PDEs which are typically used as the govern model in engineering problems. Numerical results showed that our proposed methods performed well in solving the high dimensional linear system with small residual norms.

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Identification of connecting rod diesel engine generator set 3516 B series using the finite element method

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AIP Conference Proceedings 2024年第1期3115卷

作者： Wilarso Che Wan Mohd Noor Ahmad Faisal Mohamad Ayob Wan Nurdiyana Wan Mansor Muhamad Ali Pahmi Mastang Sekolah Tinggi Teknologi Muhammadiyah Cileungsi Bogor Indonesia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Terengganu Malaysia

The process of overheating in the engine system, particularly in the #10-cylinder shank section, is the only factor considered in the investigation of this damage or failure. As a piece of scientific literature, the goal of this study is to ascertain the primary reason for the connecting rod’s failure. Analyzing the results of the thermal simulation produced by the finite element approach is the way for identifying the primary source of the damage. The finite element approach was used to do a thermal simulation of radiation heat transfer in steady-state circumstances based on the findings of the analysis (FEM). According to the average temperature coming out of the exhaust valve, the temperature in the cylinder liner is 442°C, and the heat in the piston rod is 90°C, which is in line with the typical operating temperature of the 3516 B Series diesel engine. According to a finite element simulation, the discoloration in the piston rod is mostly caused by radiation, namely the transmission of heat from the liner wall to the piston rod as a result of the combustion gases being trapped in cylinder #10. The connecting rod parts that changed color are still usable according to the finite element approach and the feasibility test.

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Some fixed point results on fuzzy extended rectangular b-metric spaces

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AIP Conference Proceedings 2023年第1期2746卷

作者： Koon Sang Wong Zabidin Salleh Che Mohd Imran Che Taib Ilyani Abdullah Department of Mathematics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia

In this paper, we introduce the notion of fuzzy extended rectangular b-metric space as a new extension in fuzzy metric. This notion generalize fuzzy rectangular b-metric space. We also prove some fixed point results for Banach-type contraction mappings and fuzzy ψ-contraction mappings under the setting of complete fuzzy extended rectangular b-metric space.

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A hybrid classification model for predicting breast cancer survivability using public dataset

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AIP Conference Proceedings 2023年第1期2484卷

作者： N. H. Abd Rahim D. H. Awang Kadir M. S. H. Basri 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia

Breast cancer has been one of the deadliest diseases and becomes the leading cause of cancer deaths in women worldwide. It becomes an issue to any countries as the number of victims developing breast cancer is increasing, and the survivability rate of cancerous women is still ambiguous. In this study, a hybrid classification model is developed for predicting breast cancer survivability. The hybrid classification model is a combination of three single classification models, namely Naive Bayes, J48 Decision Tree and RBF Network. Stacking method has been used to combine those models. This hybrid model has been tested using Breast Cancer Wisconsin dataset which gives result 96.14% of accuracy, 96.30% of precision, 96.10% of recall and 96.20% of f-measure. These results are outperformed each of the single classifiers.

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A comparative study of lexical similarity approaches for Malay short text

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AIP Conference Proceedings 2023年第1期2484卷

作者： Madihah Mohammad Arifah Che Alhadi 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia

The short text retrieval is gaining tremendous attention due to rapid exposure and widespread usage of social networks. This type of text is widely used in various applications such as spam filtering, tweet classification, question-answer systems, web search and so forth. Thus, the effective analysis of these texts is of vital need. But, short text retrieval often becomes complex because they are usually contains repeated words, less features and overloaded with noise. Different lexical similarity approaches have been developed to tackle the problem of lexical analysis. However, most of them are in English, and the solutions for problems involving Malay are of limited availability. This paper examined the reliability of lexical similarity approaches focusing on term-based approaches for Malay short text analysis. The Cosine, Overlap coefficient and Jaccard similarity methods were used to quantify the similarities of some news title written in Malay news. Results show that the selected approaches term-based has potential to be used to analyze Malay short texts.

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Thiophene Desulfurization: Effects of Dendritic Silica and Peg as Surface Modifier on Zno Photocatalyst

SSRN

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SSRN 2024年

作者： Makhtar, Siti Nurfatin Nadhirah Mohd Hairom, Nur Hanis Hayati Puasa, Nor Aliffah Jalil, Aishah Abdul Madon, Rais Hanizam Hamzah, Sofiah Ng, Law Yong Yusof, Norhaniza Microelectronics and Nanotechnology Shamsuddin Research Center Institute for Integrated Engineering Universiti Tun Hussein Onn Malaysia Parit Raja Johor Batu Pahat86400 Malaysia Faculty of Engineering Technology Universiti Tun Hussein Onn Malaysia Hab Pendidikan Tinggi Pagoh KM1 Jalan Panchor Johor Muar84600 Malaysia Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia Centre of Hydrogen Energy Institute of Future Energy University Teknologi Malaysia Johor Johor Bahru81310 Malaysia Faculty of Mechanical and Manufacturing Engineering Universiti Tun Hussein Onn Malaysia Parit Raja Johor Batu Pahat86400 Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Jalan Sungai Long Bandar Sungai Long Selangor Kajang43000 Malaysia School of Chemical Engineering Universiti Teknologi Malaysia Johor Johor Bharu81310 Malaysia

This work focused on the desulfurization of thiophene using a photocatalyst comprising zinc oxide (ZnO) and fibrous silica nanospheres (KCC-1) to exploit the photocatalytic process. Six photocatalyst samples (commercial ZnO, KCC-1, ZnO/1.5KCC-1, ZnO/2.0KCC-1, ZnO/2.5KCC-1 and ZnO/PEG) were characterized using field-emission scanning electron microscopy (FESEM), Fourier transform infrared (FTIR) spectroscopy and X-ray diffractometry (XRD). It was found that the properties of ZnO were altered with the incorporation of KCC-1 to enhance the efficiency of thiophene desulfurization. Desulfurization performances were investigated using three parameters, which were initial pH, initial thiophene concentration and photocatalyst loading. Each of the parameters was validated using thiophene desulfurization percentage and turbidity removal percentage. This work discovered that ZnO/2.0KCC-1 was the optimum photocatalyst with 83% thiophene desulfurization. No clear trend was observed for turbidity removal percentage, yet the ZnO/KCC-1 photocatalyst was able to reduce turbidity significantly. The pH of the permeate rose from neutral to the alkaline range due to the hydroxyl radicals (•OH) produced during the desulfurization process. © 2024, The Authors. All rights reserved.

关键词： Zinc oxide

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IR-Eclat: A new algorithm of incremental R-Eclat for infrequent itemset mining

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AIP Conference Proceedings 2023年第1期2484卷

作者： Mustafa Man Nurul Aqilah Ruslan Julaily Aida Jusoh Wan Aezwani Wan Abu Bakar 1Faculty of Ocean Engineering Technology & Informatics Universiti Malaysia Terengganu Terengganu Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Malaysia

The key challenge of association rule mining is to discover and extract a valuable information from databases. However, mining association rule may require repetitious scanning of large databases that leads to the high memory usage and affects the running time. Rare Equivalence Class Transformation (R-Eclat) algorithm is specifically design for infrequent itemset mining. In response to the promising results of mining in speedy processing time and taking consideration of dynamic transaction of data in a database, a new incremental approach is introduced called Incremental R-Eclat (IR-Eclat). This model adopted via relational database engine management system; My Structured Query Language (MySQL) serves as a database engine for testing benchmark datasets. The experimental results on several benchmark datasets indicate that Incremental R-Eclat outperforms the R-Eclat by reducing its running time to process especially in dynamic database as the data is increasing in volume from time to time.

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Fi-Eclat: An enhancement of incremental Eclat algorithm

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AIP Conference Proceedings 2023年第1期2484卷

作者： Mahadi Man Masita Abdul Jalil Wan Aezwani Wan Abu Bakar 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Malaysia

Nowadays, there is a large amount of data growth at all organizational scales. To find useful information, the right data mining technique needs to be used. One of the popular techniques is called the equivalence class transformation (Eclat) algorithm which is gaining the benefits of the vertical data format used in the association rule mining technique. However, like horizontal data representation, vertical data still suffering from huge memory consumption. The technique then has been extended by using the Incremental Eclat (i-Eclat) algorithm which is embedded with the incremental approach. Inspired by the dynamic data transactions in a database, a new algorithm has been adopted to optimize the performance of the current algorithm called the Fast Incremental (Fi-Eclat) algorithm. The research proposes an optimization of the performance of the i-Eclat algorithm. It relies on the incremental approach implemented on the database that consists of five (5) benchmark datasets from Frequent Itemset Mining (FIMI). The outcome of the experiment indicates an improvement of 32% in time execution for the proposed algorithm.

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Simulation of heat flow in welding using hybrid restarting FDM-SVR-Lanczos

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AIP Conference Proceedings 2023年第1期2484卷

作者： Rehana Thalib Maharani A. Bakar 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus Terengganu 21300 Malaysia 2Special Interest Group Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus Terengganu 21300 Malaysia

This paper discusses the numerical simulations of heat transfer problem, particularly during the welding materials processing. This process highly depends on the temperature to determine the metallurgical properties, the strength, and the sureness of the joint during welding; hence it is desirable to study its heat flow. Finite difference method (FDM) is used to discretize partial differential equations (PDEs) to obtain the systems of linear equations (SLEs), which can be solved by an iterative method. Here, we used a variant of Lanczos based methods, called Restarting-FDM-SVR-Lanczos to solve two-dimensional heat flow in welding. The proposed method is a combination of Lanczos method and machine learning under the support vector regression (SVR) method, where the SVR plays important role in predicting the non-existing solutions of the Lanczos iterates, due to the breakdown issue in Lanczos method. Numerical results were presented and showed that Hybrid Restarting FDM-SVR-Lanczos performed better in solving the heat flow in welding problem compared with the single FDM and Lanczos methods, with small residual norms.

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Modelling and simulation investigation of multi-string photovoltaic array system with MPPT controlled DC/DC converter

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AIP Conference Proceedings 2023年第1期2484卷

作者： N. Anang W. M. W. Muda. 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia. 2Renewable Energy and Power Research Interest Group (REPRIG) Eastern Corridor Renewable Energy SIG Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia.

This paper presents the simulation of power generation in a photovoltaic (PV) system that applies maximum PV power point tracking (MPPT) in a DC/DC boost converter. The MPPT is responsible to obtain the possible maximum PV power to be extracted to the input of the DC/DC boost converter. Although there are equations available to calculate the value of components in DC/DC circuit in literature, the validation of input parameters of the converter which are crucial in the design process was not properly presented, especially for different solar irradiance and temperature. Thus, this paper shows a step-by-step simulation of multi-string PV with converter, from designing the converter based on the PV specification and constructing the model by using MATLAB/Simulink software system. Next, the algorithm of the incremental conductance method was developed in MPPT to control the duty cycle of the converter. The result shows that the developed system has successfully output the maximum power under different solar irradiance and temperature with high efficiency of 99.0%. Simulation results were validated using the P-V curves of the selected PV modules. Then, the proposed model can then be connected to an inverter for a complete grid-connected PV system in the future.

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