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4th International Conference on Separation technology, ICoST 2023

作者： Mazlan, N.S.C. Halim Yap, F.A. Yahya, M.S. Ali, N.A. Sazelee, N.A. Ismail, M. Faculty of Innovative Design & Technology Universiti Sultan Zainal Abidin Kampus Gong Badak Gong Badak Terengganu Kuala Nerus21300 Malaysia Energy Storage Research Group Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia

This research uses the ball milling technique to study the preparation of the MgH2-LiAlH4-NaAlH4with a molar ratio of 4:1:1 ternary-hydride system. The hydrogen storage behavior and reaction mechanisms have been carefully explored. The result demonstrates a reduction in the onset decomposition temperature of the 4MgH2-LiAlH4-NaAlH4ternary composite compared to the as-milled MgH2, LiAlH4, and NaAlH4components. Four substantial dehydrogenation processes, corresponding to the decomposition of LiAlH4, NaAlH4, and MgH2were detected in a system with a total hydrogen capacity of 8.4 wt%. The onset decomposition temperature of LiAlH4in this system is around 110 °C, while NaAlH4-relevant decomposition began releasing hydrogen at 153 °C, approximately 52 °C lower than the as-milled NaAlH4. Meanwhile, the destabilized system modifies the reaction route of MgH2, where MgH2-relevant decomposition begins around 270 °C, 82 °C lower than the as-milled MgH2. The apparent activation energy, Ea, for the decomposition of MgH2in the composite was lowered to 124 kJ/mol based on the Kissinger analysis. It is believed that the enhancement of the dehydrogenation properties was attributed to the formation of intermediate compounds, including Li-Mg, Mg-Al and Li-Al alloys, upon dehydrogenation, which improved the thermodynamics properties by altering the de/rehydrogenation pathway. © 2024 Elsevier Ltd. All rights reserved.

关键词： Hydrogen storage

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Software Ageing Assessment and Indexing Model Based on Software Quality Dimension: The Conceptual Model

Software Ageing Assessment and Indexing Model Based on Softw...

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2022 IEEE International Conference on Computing, ICOCO 2022

作者： Abdullah, Zuriani Hayati Yahaya, Jamaiah Mansor, Zulkefli Deraman, Aziz Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi Malaysia Universiti Malaysia Terengganu Faculty of Ocean Engineering Technology and Informatics Kuala Terengganu Malaysia

ISBN: (纸本)9781665489966

Software ageing is an unavoidable phenomenon that can occur with every software product. Software that is unable to evolve and meet current needs will have a limited ability to provide ongoing functionality and relevance. Software performance and quality will degrade when these happen, known as the software ageing phenomena. Even though we cannot escape ageing in software products, it can be delayed and slowed down by understanding which factors contribute to ageing. Software ageing factors can be classified into two categories which are external and internal factors. This study focuses on external factors of software ageing related to or derived from the existing software quality model. Our experience conducting research in software quality and certification motivates us to develop a software ageing assessment and indexing model from the dimension of software quality. This paper presents the background and related issues on software ageing and quality and focuses further on the conceptual model of software ageing. © 2022 IEEE.

关键词： Computer software selection and evaluation

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Layered niobium carbide enabling excellent kinetics and cycling stability of Li-Mg-B-H hydrogen storage material Layered niobium carbide enabling excellent kinetics

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Rare Metals 2024年第3期43卷 1153-1166页

作者： Li-Wen Lu Hui Luo Guang-Xu Li Yun Li Xin-Hua Wang Cun-Ke Huang Zhi-QiangLan Wen-Zheng Zhou Jin Guo Mohammad Ismail Hai-Zhen Liu Guangxi Novel Battery Materials Research Center of Engineering Technology Guangxi Colleges and Universities Key Laboratory of Blue Energy and Systems IntegrationSchool of Physical Science and TechnologyGuangxi UniversityNanning530004China State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures Nanning530004China School of Mechanical and Electrical Engineering Quzhou College of TechnologyQuzhou324000China Department of Materials Science and Engineering Zhejiang UniversityHangzhou310027China Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu21030Kuala NerusTerengganuMalaysia Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) Nankai UniversityTianjin300071China

The Li-Mg-B-H composite(2LiBH_(4)+MgH_(2))has a high capacity of 11.4 wt%as a hydrogen storage ***,the slow kinetics and poor cycling stability severely restrict its practical *** this work,a layered Nb_(2)C MXene was first synthesized and then introduced to tailor the kinetics and cycling stability of the Li-Mg-B-H *** milled 2LiH+MgB_(2)composites were initially hydrogenated to obtain the 2LiBH_(4)+MgH_(2)*** 2LiBH_(4)+MgH_(2)+5wt%Nb_(2)C can release 9.0 wt%H_(2)in 30 min at 400℃,while it is only 2.7 wt%for the undoped 2LiBH_(4)+MgH_(2).The dehydrogenation activation energies of MgH_(2)and LiBH_(4)are 123 and 154 kJ·mol^(-1)respectively for the 5 wt%Nb_(2)C-doped composite,lower than the undoped composite(164 and 165 kJ·mol^(-1)).The 2LiBH_(4)+MgH_(2)+5 wt%Nb_(2)C possesses excellent cycling stability,with the reversible capacity only slightly reduced from 9.4 wt%for the 1st cycle to 9.3 wt%for the 20th ***_(2)C keeps stable in the composite and acts as an efficient catalyst for the Li-Mg-B-H *** is believed that both the layered structure and the active Nb element contribu te to the enhanced hydrogen storage performances of the Li-Mg-B-H *** work confirms that the Nb_(2)C MXene with layered stru cture has a significant enhancing impact on the Li-Mg-B-H hydrogen storage materials,which is different from the bulk NbC.

关键词： Hydrogen storage Lithium borohydride Magnesium hydride Nb_(2)C MXene

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On Type-1 Granulation and Approximation of Tolerance Based Rough Neutrosophic Sets 1

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8th International Conference on Computational Science and technology, ICCST 2021

作者： Ab Ghani, Ahmad Termimi Abdullah, Lazim Peng, NingNing Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu21030 Malaysia Department of Mathematics Wuhan University of Technology Wuhan China

ISBN: (数字)9789811685156

ISBN: (纸本)9789811685149

In this study, we introduced two new types of granulation of rough neutrosophic set models. We first defined the type-1 of two granulation based on tolerance relation (T1-TGRNS). The latter one we called type-1 multi-granulation of rough neutrosophic sets also induced by tolerance class (T1-MGRNS). Various interesting features of these kinds of granulation are presented. From the results, we can observe the granulation of the rough neutrosophic set model is a distinctive augmentation of those in granulation in rough set theory, especially on inclusion properties. One can see that this study is significant primarily in the theory of incomplete information systems and data analysis. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Granulation

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UMTCSF: A Graduate Forum Platform Utilizing an Ensemble Similarity Model

UMTCSF: A Graduate Forum Platform Utilizing an Ensemble Simi...

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informatics engineering, Science & technology (INCITEST), International Conference on

作者： Arifah Che Alhadi Wan Nural Jawahir Wan Yussof Akashah Amin Mohamed Aziz Deraman Masita Masila Abdul Jalil Rosmayati Mohemad Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia

Online forum platforms have emerged as highly popular digital communities for seeking and sharing valuable information. Within these platforms, searches are typically constrained to keyword-based queries. However, the presence of noise in keywords, such as spelling errors or abbreviations, often impedes accurate information retrieval. The impact of this noise on search results poses challenges to both the effectiveness and efficiency of the retrieval process. This study introduces an ensemble similarity model that combines the Vector Space Model (VSM) with edit distance models to enhance thread analysis within a graduate discussion forum. The UMT Computer Science Forum System (UMTCSF) serves as an online platform for Computer Science students to engage in discussions encompassing questions, answers, and topic exploration. Operating in real-time through a web-based application, UMTCSF employs similarity analysis while effectively addressing keyword search noise. An ensemble similarity model demonstrates its potential and practicality in improving search result rankings. By adeptly combining different models and addressing keyword-related challenges, UMTCSF presents a valuable solution for facilitating efficient and accurate information retrieval within the realm of graduate forum discussions.

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Influence of Milling Parameters on the Characteristics of Alumina-Titania Nanocomposite Prepared by High-Energy Ball Milling 1

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5th International Conference on Advances in Manufacturing and Materials engineering, ICAMME 2022

作者： Asari, Siti Atikah Mohammad Yusoff, Mahani Masri, Mohamad Najmi Jaafar, Hidayani Razali, Mohd Hasmizam Nik, Wan Mohd Norsani Wan Faculty of Bioengineering and Technology Universiti Malaysia Kelantan Jeli Kelantan17600 Malaysia Faculty of Science and Marine Environment Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 21030 Kuala Nerus Terengganu Malaysia

ISBN: (数字)9789811995095

ISBN: (纸本)9789811995088

High energy ball milling (HEBM) is a simple mechanical technique used for particle size reduction and mixing different materials from bulk to nanostructured materials. It is able to produce nano-size grains of ceramic-based composite and sometimes with sufficient energy new phase can be formed through the diffusion process. The present study focuses on the effect of HEBM on the structure, microstructure, and properties of alumina—titania (Al2O3-TiO2) nanocomposite. Elemental powders of Al2O3 and TiO2 were milled in a planetary ball mill at different milling times and milling speeds, then heated to 600 °C. The composites were characterized for phase identification, structural properties, morphology, and compaction behavior. The peak broadening was significant with increasing milling time. The unstable Al2TiO5 was formed at a lower milling time for 300 rpm but diminished after heat treatment. The lowest crystallite size was obtained after 10 h milling time and with the speed of 300 rpm which originated from grain refinement due to a large amount of defects generation during milling. Increasing milling time and milling speed influenced the green density as a result of fine composite particle size and TiO2 particles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Titanium dioxide

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Ti_(3)AICN MAX for tailoring MgH_(2) hydrogen storage material:from performance to mechanism

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Rare Metals 2023年第6期42卷 1923-1934页

作者： Xing-Qing Duan Guang-Xu Li Wen-Hui Zhang Hui Luo Hai-Mei Tang Li Xu Peng Sheng Xin-Hua Wang Xian-Tun Huang Cun-Ke Huang Zhi-Qiang Lan Wen-Zheng Zhou Jin Guo Mohammd Bin Ismail Hai-Zhen Liu Guangxi Novel Battery Materials Research Center of Engineering Technology Guangxi Colleges and Universities Key Laboratory of Novel Energy Materials and Related TechnologySchool of Physical Science and TechnologyGuangxi UniversityNanning530004China State Key Laboratory of Advanced Power Transmission Technology State Grid Smart Grid Research Institute Co.Ltd.Beijing102209China Department of Materials Science and Engineering Zhejiang UniversityHangzhou310027China Department of Materials Science and Engineering Baise CollegeBaise533000China Energy Storage Research Group Faculty of Ocean Engineering Technology and InformaticsUniversiti Malaysia TerengganuKuala Nerus21030Malaysia

Many MXenes are efficient catalysts for MgH_(2)hydrogen storage ***,the synthesis of MXenes should consume a large amount of corrosive HF to etch out the Al layers from the transition metal aluminum carbides or nitrides(MAX) phases,which is environmentally *** this work,Ti_(3)AlCN MAX without HFetching was employed directly to observably enhance the kinetics and the cycling stability of MgH_(2).With addition of10 wt% Ti_(3)AlCN,the onset dehydrogenation temperature of MgH2 was dropped from 320 to 205℃,and the rehydrogenation of MgH2 under 6 MPa H2 began at as low as50℃.Furthermore,at 300℃,it could provide 6.2 wt% of hydrogen in 10 *** cycling,the composite underwent an activation process during the initial 40 cycles,with the reversible capacity increased from 4.7 wt% to 6.5 wt%.After that,the capacity showed almost no attenuation for up to 100 *** enhancing effect of Ti_(3)AICN on MgH_(2) was comparable to many *** was demonstrated that Ti_(3)AICN did not destabilize MgH_(2) but acted as an efficient catalyst for MgH_(2).Ti_(3)AICN was observed to be the active sites for the nucleation and growth of MgH_(2)and might also help in dissociation and recombination of hydrogen *** two factors are believed to contribute to the improvement of MgH_(2).This study not only provides a promising strategy for improving the hydrogen storage performances of MgH_(2) by using noncorrosive MAX materials,but also adds evidence of nucleation and growth of MgH_(2) on a catalyst.

关键词： Hydrogen storage Magnesium hydride MAX MXene Titanium aluminum carbonitride

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Lung Cancer Detection on CT Scan Images with Deep Learning Methods: Sugeno Fuzzy Integral-Based CNN Ensemble Method

Lung Cancer Detection on CT Scan Images with Deep Learning M...

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informatics engineering, Science & technology (INCITEST), International Conference on

作者： Soong Xian Lim Masita Masila Abdul Jalil Wiwied Virgiyanti Farizah Yunus Faculty of Ocean Engineering Soong Xian Lim Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus Malaysia

Lung cancer causes the highest mortality rate among all cancers. Existing methods for detecting Lung cancer are not optimal, as they rely mostly on a single model or multiple models employing probability averaging. This study is proposed to differentiate malignant, benign and normal cells of lung by employing the Sugeno Ensemble method in conjunction with four Convolutional Neural Networks (CNN): VGG11, SqueezeNet, GoogLeNet, and Wide ResNet-50-2 to improve accuracy of Lung cancer detection. Each model will be individually trained with the dataset before Sugeno ensemble is performed to produce the final accuracy. This study evaluates the accuracy of applying Sugeno fuzzy logic techniques to CT scan images of Lung cancer to determine if it outperforms existing methods and investigates the limitations of earlier research. This study examines the image of cancer morphologies from various patients. The confusion matrix is then utilized to evaluate the performance of the framework. The ultimate achieved accuracy rate is 98.47%. This study found that integrating the Sugeno ensemble technique with the four CNN models increases Lung cancer detection performance. These discoveries could aid in the development of systems to identify Lung cancer patients and provide implications for artificial intelligence and the medical industry.

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Deep learning algorithm vs XGBoost using Wisconsin breast cancer diagnosis 3

Deep learning algorithm vs XGBoost using Wisconsin breast ca...

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3rd International Conference on Computer Science and Communication technology, ICCSCT 2022

作者： Bakar, Wan Aezwani Wan Abu Zuhairi, Muhamad Amierusyahmi Man, Mustafa Jusoh, Julaily Aida Josdi, Nur Laila Najwa Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Besut22200 Malaysia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus21030 Malaysia

ISBN: (纸本)9781510661240

Breast cancer is causing a significant increase in the number of deaths every year. It is the most common kind of cancer and the leading cause of death in women all over the world. Any improvement in cancer illness prediction and detection is critical for a healthy life. As a result, high accuracy in cancer prediction is critical for keeping patients' treatment and survival standards up to date. Machine learning and deep learning approaches, which have been shown to have a significant impact on the process of breast cancer prediction and early diagnosis, have become a research hotspot and have been proven to be a powerful technique. We went through one machine learning method, XGBoost and deep neural network in this research on the Wisconsin Breast Cancer Diagnostic (WBCD) dataset. After getting the outcomes, these distinct classifiers' performance is evaluated and compared. The major goal of this research is to use machine-learning and deep learning algorithms to predict and diagnose breast cancer, and to determine which algorithms are the most efficient in terms of confusion matrix, precision, and accuracy. © 2022 SPIE.

关键词： Forecasting

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Color-based image processing techniques for laser range finder: a comparative study on air and water distance detection 16

Color-based image processing techniques for laser range find...

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16th International Conference on Correlation Optics, COR 2023

作者： Multajam, Rizki Ayob, Ahmad Faisal Mohamad Sanjaya, W. S. Mada Sambas, Aceng Rusyn, Volodymyr Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus21030 Malaysia Dept. of Physics Faculty of Science and Technology Universitas Islam Negeri Sunan Gunung Djati Bandung40614 Indonesia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu22200 Malaysia Dept. of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tasikmalaya46196 Indonesia Dept. of Radio Engineering and Information Security Yuriy Fedkovych Chernivtsi National University 2 Kotsjubynskyi Str. Chernivtsi58000 Ukraine

ISBN: (纸本)9781510671829

In this paper, we studied comparative distance detection using a Laser Rangefinder equipped with color detection and image processing techniques in air and water environments. The main objective of this study is to evaluate the performance and accuracy of the distance detection methods in these two mediums. Furthermore, color detection is employed in the air environment to identify objects within the captured images, followed by image processing techniques such as edge detection and contour analysis to calculate the distances between the objects and the Laser Range Finder. In the water environment, challenges arise due to the refractive properties of water, which can distort object appearances. To overcome this, we employ an underwater Laser Range Finder system, along with color detection and image processing methods adjusted for the refractive index of water. The findings show that the distance measurement in the air has a small error value of 0.63 %. Meanwhile, measuring distances in water has a high error value of 35.18 %. These results indicate that measurements in the air perform better than measurements in water. Water's scattering and refractive properties caused significant deviations and higher error values. The light intensity fluctuations had minimal impact on measurements in water but were significant in water. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Refractive index

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