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54th International Universities Power engineering Conference, UPEC 2019

作者： Hussain, Muhammad Majid Rashid Mustafa, Al Chaudary, Muhammad Akmal Razaq, Abdul University of South Wales Faculty of Computing Engineering and Science Cardiff United Kingdom University of South Wales Centre for Automotive Power Systems Engineering Cardiff United Kingdom Ajman University Department of Electrical and Computer Engineering Ajman United Arab Emirates Abertay University School of Design and Informatics Dundee United Kingdom

ISBN: (纸本)9781728133492

The electric motors and its control technology are key components of hybrid electric vehicles (HEVs). Control of the electric motor is a fundamental issue for traction application in electric vehicles and HEVs. This paper presents the design, development and implementation of a hybrid vehicle using both an electric motor and petrol engine to increase efficiency and decrease carbon footprint. Initially, a prototype of a HEV is designed and the performance values are calculated, before a control system is developed and implemented to control the DC motor speed using a microcontroller as the vehicle's electronic control unit along with simple proportional integral derivative (PID) control using speed as a feedback mechanism. The prototype made incorporated voltage, current, speed and torque sensors for feedback resulting in a closed loop control system which successfully matched the speed input of a user-controlled pedal sensor. A user interface was developed to show the driver of the vehicle key variables such as the revolutions per minute (RPM) of the motor, the speed of the vehicle along with the current being drawn, and the voltage applied to the motor with overall power. To output a variable voltage from the Arduino, a digital output was used with pulse width modulation (PWM) capabilities in order to provide a variable DC voltage to the speed controller. © 2019 IEEE.

关键词： User interfaces

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Contrast enhancement on pap smear cell images: A comparison

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AIP Conference Proceedings 2023年第1期2608卷

作者： Mohamed Saifuddin Shahul Hameed Wan Azani Mustafa Syed Zulkarnain Syed Idrus Mohd Aminudin Jamlos Hiam Alquran Faculty of Electrical Engineering Technology University of Malaysia Perlis UniCITI Alam Campus Sungai Chuchuh 02100 Padang Besar Perlis Malaysia Advanced Computing (AdvComp) Centre of Excellence (CoE) Universiti Malaysia Perlis 02600 Arau Perlis Malaysia Faculty of Applied and Human Sciences Universiti Malaysia Perlis 01000 Kangar Perlis Malaysia Faculty of Electronic Engineering Technology University of Malaysia Perlis UniCITI Alam Campus Sungai Chuchuh 02100 Padang Besar Perlis Malaysia Biomedical Systems and Medical Informatics Engineering Yarmouk University 21163 Irbid Jordan

Cervical cancer is a common disease that can be carried by women. It is the 3rd leading cause of female cancer in Malaysia and the 4th most common type of cancer for women globally. Referring to the HPV Information centre in 2018, it is estimated that 1682 women are diagnosed and 944 die from having cervical cells. In 2018, 569, 847 of the 18,078,957 cases were categorised as cervical cancer, which is 3.2%. With the advancement in science and technology, cervical cancer can be detected at an early stage by conducting a Pap smear test. This test will filter abnormal cervical cells and detect precancerous changes in cervical cells based on the colour and shape properties of their nuclei and cytoplasm. The problem is that performing the procedure manually can be time-consuming and cause inconsistencies and errors even further because the cervical cell itself does not show an obvious difference in texture and colour from normal cells. This paper will focus on colour contrast enhancement of the cervical cell using a few methods such as Contrast Stretching (CS), CLAHE, Histogram Equalization (HE), Image Adjustment, and Multi Scale Retinex (MSR). From this research, the cervical cell colour contrast can be enhanced to a better level and the detection of cervical cells can happen faster and more accurately. Hence, the errors in detecting can be reduced again so they can be treated soon.

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Disentangling high-order mechanisms and high-order behaviours in complex systems

arXiv

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arXiv 2022年

作者： Rosas, Fernando E. Mediano, Pedro A.M. Luppi, Andrea I. Varley, Thomas F. Lizier, Joseph T. Stramaglia, Sebastiano Jensen, Henrik J. Marinazzo, Daniele Data Science Institute Imperial College London United Kingdom Centre for Psychedelic Research Imperial College London United Kingdom Centre for Complexity Science Imperial College London United Kingdom Department of Psychology University of Cambridge United Kingdom Department of Psychology Queen Mary University of London United Kingdom University Division of Anaesthesia University of Cambridge United Kingdom Department of Clinical Neurosciences University of Cambridge United Kingdom Leverhulme Centre for the Future of Intelligence University of Cambridge United Kingdom Department of Psychological & Brain Sciences Indiana University BloomingtonIN United States School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Centre for Complex Systems Faculty of Engineering The University of Sydney Australia Dipartimento Interateneo di Fisica Università Degli Studi di Bari Aldo Moro Italy INFN Sezione di Bari Italy Department of Mathematics Imperial College London United Kingdom Institute of Innovative Research Tokyo Institute of Technology Japan Department of Data Analysis Ghent University Belgium

Battiston et al. (arXiv:2110.06023) provide a comprehensive overview of how investigations of complex systems should take into account interactions between more than two elements, which can be modelled by hypergraphs and studied via topological data analysis. Following a separate line of enquiry, a broad literature has developed information-theoretic tools to characterize high-order interdependencies from observed data. While these could seem to be competing approaches aiming to address the same question, in this correspondence we clarify that this is not the case, and that a complete account of higher-order phenomena needs to embrace both. Copyright © 2022, The Authors. All rights reserved.

关键词： Large scale systems

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Nucleus region detection of cervical cytology using image channel conversion techniques

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AIP Conference Proceedings 2024年第1期3135卷

作者： Hiam Alquran Alaa Badarneh Mohammed Alsalatie Wan Azani Mustafa Batul Alquraan Department of Biomedical Systems and Medical Informatics Engineering Yarmouk University Irbid Jordan Department of Biomedical Engineering Jordan University of Science and Technology Irbid Jordan The Institute of Biomedical Technology King Hussein Medical Center Royal Jordanian Medical Service Amman 11855 Jordan Faculty of Electrical Engineering & Technology University of Malaysia Perlis UniCITI Alam Campus Sungai Chuchuh Perlis Malaysia Advanced Computing (AdvComp) Centre of Excellence (CoE) Universiti Malaysia Perlis (UniMAP) Campus Pauh Putra 02600 Arau Perlis Malaysia

Cervical cancer is a form of cancer that develops in the cells of the cervix, which links the uterus to the vagina. Cervical cancer can often be prevented by attending the cervical screening, which aims to find and treat changes to cells before they turn into cancer. Pap smear images are a more popular technique for screening cervical cancer. The nucleus and cytoplasm are present in the smear cell images. The spread of cancer is determined by the shape and structure of the nucleus. Thus, nucleus segmentation is an important step in cancer detection. However, overlapping, poor contrast, uneven staining, and other factors make cervical nucleus segmentation difficult. This paper proposes a new segmentation method for the cervical nucleus using digital image processing. In our proposed method, image processing techniques are employed to segment the nucleus. This method mainly compared the performance of using Red Green Blue (RGB) channels and Hue, Saturation, and Value (HSV). The best two channels from each two-colored image representation are compared, where the V channel is the best among H and S channels. On the other hand, G chancel is the best among the G and B channels. Therefore, the best two channels are compared, and the segmentation using the G channel is the best among all, with a sensitivity of 94.3%, specificity of 94.6% and precision of 88.3%. The main impact of this paper will be to assist doctors in diagnosing cervical cancer-based segmentation of the nucleus in Pap smear images.

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Modern computing: Vision and Challenges

arXiv

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arXiv 2024年

作者： Gill, Sukhpal Singh Wu, Huaming Patros, Panos Ottaviani, Carlo Arora, Priyansh Pujol, Victor Casamayor Haunschild, David Parlikad, Ajith Kumar Cetinkaya, Oktay Lutfiyya, Hanan Stankovski, Vlado Li, Ruidong Ding, Yuemin Qadir, Junaid Abraham, Ajith Ghosh, Soumya K. Song, Houbing Herbert Sakellariou, Rizos Rana, Omer Rodrigues, Joel J.P.C. Kanhere, Salil S. Dustdar, Schahram Uhlig, Steve Ramamohanarao, Kotagiri Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Center for Applied Mathematics Tianjin University Tianjin China Raygun Performance Monitoring Wellington New Zealand Department of Computer Science York Centre for Quantum Technologies University of York York United Kingdom Microsoft Schiphol Netherlands Distributed Systems Group Vienna University of Technology Vienna Austria Detecon International GmbH Munich Germany Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science University of Western Ontario London Canada Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Institute of Science and Engineering Kanazawa University Japan Tecnun School of Engineering University of Navarra Spain Department of Computer Science and Engineering College of Engineering Qatar University Doha Qatar Bennett University Greater Noida India Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Baltimore United States Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia COPELABS Lusófona University Lisbon Portugal Sydney Australia The University of Melbourne Victoria Australia Laboratory School of Computing and Information Systems The University of Melbourne Australia

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress. © 2024, CC BY.

关键词： Obsolescence

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Correction: Machine learning classification meets migraine: recommendations for study evaluation

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The journal of headache and pain 2024年第1期25卷 223页

作者： Igor Petrušić Andrej Savić Katarina Mitrović Nebojša Bačanin Gabriele Sebastianelli Daniele Secci Gianluca Coppola Laboratory for Advanced Analysis of Neuroimages Faculty of Physical Chemistry University of Belgrade Belgrade Serbia. ip7med@***. Science and Research Centre School of Electrical Engineering University of Belgrade University of Belgrade Belgrade Serbia. Department of Information Technologies Faculty of Technical Sciences Čačak University of Kragujevac Čačak Serbia. Department of Informatics and Computing Singidunum University Belgrade Serbia. Department of Medico-Surgical Sciences and Biotechnologies Sapienza University of Rome Polo Pontino ICOT Latina Italy. Department of Engineering and Architecture University of Parma Parma Italy.

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A Chaotic Jerk System with Three Cubic Nonlinearities, Dynamical Analysis, Adaptive Chaos Synchronization and Circuit Simulation 1

A Chaotic Jerk System with Three Cubic Nonlinearities, Dynam...

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1st International Conference on Computer, Science, engineering and Technology, ICComSET 2018

作者： Vaidyanathan, S. Sambas, A. Zhang, S. Mujiarto Mamat, M. Subiyanto Research and Development Centre Vel Tech University Avadi Chennai India Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Indonesia School of Physics and Opotoelectric Engineering Xiangtan University Hunan China Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia Department of Marine Science Faculty of Fishery and Marine Science Universitas Padjadjaran Indonesia

A 3-D new chaotic jerk system with three cubic nonlinearities is proposed in this paper. The dynamical properties of the new jerk system are described in terms of phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, symmetry, dissipativity, etc. Also, a detailed dynamical analysis of the jerk system has been carried out with bifurcation diagram and Lyapunov exponents. As an engineering application, adaptive synchronization of the new chaotic jerk system with itself is designed via backstepping control method. Furthermore, an electronic circuit realization of the new chaotic jerk system is presented in detail to confirm the feasibility of the theoretical chaotic jerk model. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Circuit simulation

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Pap smear images classification based on surrounding tissues: A comparative study

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AIP Conference Proceedings 2024年第1期2934卷

作者： Mohammed Alsalatie Wan Azani Mustafa Lugain Nammneh Feras Fares Almashakbah Hiam Alquran Yasmin Mohd Yacob The Institute of Biomedical Technology King Hussein Medical Center Royal Jordanian Medical Service Amman 11855 Jordan Faculty of Electrical Engineering Technology Campus Pauh Putra Universiti Malaysia Perlis 02000 Arau Perlis Malaysia Advanced Computing Centre of Excellence (CoE) Universiti Malaysia Perlis (UniMAP) 02000 Arau Perlis Malaysia Faculty of Medicine Jordan University of Science and Technology Ramtha Irbid 22110 Jordan Information Technology Faculty Internet Technology Department Zarqa University Zarqa 13110 Jordan Department of Biomedical Engineering Jordan University of Science and Technology Irbid 22110 Jordan Department of Biomedical Systems and Informatics Engineering Yarmouk University 556 Irbid 21163 Jordan Faculty of Electronic Engineering Technology Campus Pauh Putra Universiti Malaysia Perlis 02000 Arau Perlis Malaysia

Cervical cancer is one of the most known health problems faced by women around the world. Early detection of cervical cancer may reduce the mortality rate. Pap smear images are new techniques used for screening cervical cancer. This paper excludes the nucleus of pap smear images, and the resultant images are classified into seven classes based on the surrounding region nucleus. Automated features are extracted using three pre-trained convolutional neural networks (CNN). The resultant features are twenty-one. The principal component analysis reduces the dimensionality and selects the most significant features into ten features. These features are fed to two types of machine learning algorithms: support vector machine (SVM) classifier and random forest classifier. The support vector machine classifier achieved the highest accuracy for seven classes, reaching 93.1%. This method will help the physicians in the diagnosis of cervical cancer depending on the tissues, not the nucleus. Furthermore, the result can be enhanced using a huge amount of data.

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Heart failure prediction using machine learning technique

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AIP Conference Proceedings 2023年第1期2608卷

作者： Mohammad Naser Hasan Radaideh Hiam Alquran Wan Azani Mustafa Mohd Aminudin Jamlos Syed Zulkarnain Syed Idrus Department of Biomedical Engineering Jordan University of Science and Technology Al-Ramtha Jordan Biomedical Systems and Medical Informatics Engineering Yarmouk University 21163 Irbid Jordan Faculty of Electrical Engineering Technology University of Malaysia Perlis UniCITI Alam Campus Sungai Chuchuh 02100 Padang Besar Perlis Malaysia Advanced Computing (AdvComp) Centre of Excellence (CoE) Universiti Malaysia Perlis 02600 Arau Perlis Malaysia Faculty of Electronic Engineering Technology University of Malaysia Perlis UniCITI Alam Campus Sungai Chuchuh 02100 Padang Besar Perlis Malaysia Faculty of Applied and Human Sciences Universiti Malaysia Perlis 01000 Kangar Perlis Malaysia

Heart failure is one of the familiar diseases that needs a special care and its prediction in early stage helps to take caution of its symptoms. By the invention of machine learning, some tasks become easier to handle like expectations, classification and clusstering. The main goal of this article is to predict heart failure using the patient record. This paper focus on building more than one model to predict the prescne or absence of heart failure. These models aim to reduce the risk of death and to make the life is more adaptive with this non-cureable disease. The three models are built with different number of features. The comparisin between these models is evaluated. The first model is build with 12 features and it achived the highest accurcy 84.6% in Bagged Tree classifier, whereas the second model is exploited with 6 features, its accuracy reduced to 75.6% Cosine KNN classifier. The last model is performed around 75.9 % with just two features. This study recommend s to use the whole record fetures to obtain the highest accuracy for predicting heart failar cases.

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Improving data latency in ETL with filtering algorithms for stream processing an experimental setup

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AIP Conference Proceedings 2024年第1期2991卷

作者： Adilah Sabtu Mahadi Bahari Nurulhuda Firdaus Mohd Azmi Nor Azizah Ali Zuraidah Sulaiman Nur Aqidah Mohd Fauzi Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia 54100 Kuala Lumpur Malaysia Azman Hashim International Business School Universiti Teknologi Malaysia 81310 Johor Bharu Johor Malaysia UTM Big Data Centre Ibnu Sina Institute for Scientific and Industrial Research Universiti Teknologi Malaysia 81310 Johor Bharu Johor Malaysia School of Computing Faculty of Engineering Universiti Teknologi Malaysia 81310 Johor Bharu Johor Malaysia School of Professional and Continuing Education Universiti Teknologi Malaysia 81310 Johor Bharu Johor Malaysia

The Extract, Transform and Load (ETL) system is a standard approach of managing and sustaining movement and transaction of data assets. The exponential growth of data necessitates the development of better approaches and ways of surpassing the traditional ETL limits and effectively manage these big data in near real-time, in terms of availability, speed of delivery or latency and scalability in processing, thus enhance the functionality and increase data value. The purpose of this research is to identify approaches and series of combination of implementing ETL for streaming and near real-time data with special focus on data latency. It is important to note that while the approaches might improve latency, it is also possible that other aspects such as availability and scalability could be compromised, as well as other limitations. The research then presents an experimental setup to simulate a near real-time scenario for landslide mapping using Lidar data, introduces 3 sets of algorithms combo: (1) data model transformation, (2) alert threshold (3) query filter techniques in stream processing with the aim of achieving low latency. Furthermore, the research expects to contribute some modified filtering techniques for accelerating queries for prioritized datasets and reduce overall data filtering time. The experiment will be performed on a Hadoop platform.

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