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2022 International Conference Automatics and Informatics, ICAI 2022

作者： Omar, Azhar-Husain Malekian, Reza Bogatinoska, Dijana Capeska University of Pretoria Department of Electrical Electronic and Computer Engineering Pretoria082 South Africa Malmö University Department of Computer Science and Media Technology Malmö205 06 Sweden Mach. Intell. and Robotics University of Information Science and Technology St. Paul the Apostle Faculty of Applied IT Ohrid Macedonia

ISBN: (数字)9781665476256

ISBN: (纸本)9781665476256

In this paper, we developed a power line communication (PLC) system design, power measurement sensor design, light sensor design, temperature sensor design, and the integration of these components into an advanced sensor network to allow for energy metering and environment monitoring. A power measurement sensor was implemented through a current and voltage sensing circuitry was interfaced multi-plug power adapter to allow for non-invasive measurement of power usage of appliances. The sensors produce signals corresponding to the drawn voltage and current, which are then sampled and processed to estimate power usage. The PLC communications operated at an average accuracy of 95%. The power measurement sensor had an accuracy of 92%, which made it appropriate for home user estimations. The light sensor had an accuracy of between 91-97%, which was suitable for home lighting measurement. © 2022 IEEE.

关键词： Wireless sensor networks

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Data Fusion Architecture Empowered with Deep Learning for Breast Cancer Classification

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computers, Materials & Continua 2023年第12期77卷 2813-2831页

作者： Sahar Arooj Muhammad Farhan Khan Tariq Shahzad Muhammad Adnan Khan Muhammad Umar Nasir Muhammad Zubair Atta-ur-Rahman Khmaies Ouahada Faculty of Computing Riphah International UniversityIslamabad45000Pakistan Department of Forensic Sciences University of Health SciencesLahore54000Pakistan Department of Electrical and Electronic Engineering Science University of JohannesburgP.O.Box 524Johannesburg2006South Africa School of Computing Skyline University CollegeUniversity City SharjahSharjah1797United Arab Emirates Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Faculty of Artificial Intelligence&SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science Bahria UniversityLahore CampusLahore54000Pakistan Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia

Breast cancer(BC)is the most widespread tumor in females worldwide and is a severe public health *** is the leading reason of death affecting females between the ages of 20 to 59 around the *** detection and therapy can help women receive effective treatment and,as a result,decrease the rate of breast cancer *** cancer tumor develops when cells grow improperly and attack the healthy tissue in the human *** are classified as benign or malignant,and the absence of cancer in the breast is considered *** learning,machine learning,and transfer learning models are applied to detect and identify cancerous tissue like *** research assists in the identification and classification of *** implemented the pre-trained model AlexNet and proposed model Breast cancer identification and classification(BCIC),which are machine learning-based models,by evaluating them in the form of comparative *** used 3 datasets,A,B,and *** fuzzed these datasets and got 2 datasets,A2C and *** A2C is the fusion of A,B,and C with 2 classes categorized as benign and *** B3C is the fusion of datasets A,B,and C with 3 classes classified as benign,malignant,and *** used customized AlexNet according to our datasets and BCIC in our proposed *** achieved an accuracy of 86.5%on Dataset B3C and 76.8%on Dataset A2C by using AlexNet,and we achieved the optimum accuracy of 94.5%on Dataset B3C and 94.9%on Dataset A2C by using proposed model BCIC at 40 epochs with 0.00008 learning *** proposed fuzzed dataset model using transfer *** fuzzed three datasets to get more accurate results and the proposed model achieved the highest prediction accuracy using fuzzed dataset transfer learning technique.

关键词： Breast cancer classification deep learning machine learning transfer learning learning rate

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Chimp Optimization Algorithm Based Feature Selection with Machine Learning for Medical Data Classification

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computer Systems Science & engineering 2023年第12期47卷 2791-2814页

作者： Firas Abedi Hayder M.A.Ghanimi Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Ali Hashim Abbas Zahraa H.Kareem Hussein Muhi Hariz Ahmed Alkhayyat Department of Mathematics College of EducationAl-Zahraa University for WomenKarbalaIraq Biomedical Engineering Department College of EngineeringUniversity ofWarith Al-AnbiyaaKarbalaIraq Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science Department Security Engineering LabPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt College of Information Technology Imam Jaafar Al-Sadiq UniversityAl-Muthanna66002Iraq Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University CollegeHillah51001Iraq Computer Engineering Department Mazaya University CollegeDhi QarIraq College of Technical Engineering the Islamic UniversityNajafIraq

Datamining plays a crucial role in extractingmeaningful knowledge fromlarge-scale data repositories,such as data warehouses and *** rule mining,a fundamental process in data mining,involves discovering correlations,patterns,and causal structures within *** the healthcare domain,association rules offer valuable opportunities for building knowledge bases,enabling intelligent diagnoses,and extracting invaluable information *** paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System(MLARMC-HDMS).The MLARMC-HDMS technique integrates classification and association rule mining(ARM)***,the chimp optimization algorithm-based feature selection(COAFS)technique is employed within MLARMC-HDMS to select relevant *** by the foraging behavior of chimpanzees,the COA algorithm mimics their search strategy for ***,the classification process utilizes stochastic gradient descent with a multilayer perceptron(SGD-MLP)model,while the Apriori algorithm determines attribute *** propose a COA-based feature selection approach for medical data classification using machine learning *** approach involves selecting pertinent features from medical datasets through COA and training machine learning models using the reduced feature *** evaluate the performance of our approach on various medical datasets employing diverse machine learning *** results demonstrate that our proposed approach surpasses alternative feature selection methods,achieving higher accuracy and precision rates in medical data classification *** study showcases the effectiveness and efficiency of the COA-based feature selection approach in identifying relevant features,thereby enhancing the diagnosis and treatment of various *** provide further validation,we conduct detailed experiments on a benchmark

关键词： Association rule mining data classification healthcare data machine learning parameter tuning data mining feature selection MLARMC-HDMS COA stochastic gradient descent Apriori algorithm

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Solving Transmission-Line (TL) Problems Using Simple Coupled Integral Equations and the Method of Moments (MM) for Undergraduate Education

Solving Transmission-Line (TL) Problems Using Simple Coupled...

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2021 Research, Invention, and Innovation Congress: Innovation Electricals and electronics, RI2C 2021

作者： Jongsuebchoke, Itthinat Torrungrueng, Danai Kittiwittayapong, Sangwon Akkaraekthalin, Prayoot Asian University Faculty of Engineering and Technology Department of Electrical and Electronic Engineering Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education Bangkok10800 Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok10800 Thailand

ISBN: (纸本)9781665403009

Integral equations (IEs) have been commonly used in solving electromagnetic problems. Thus, it is important to expose undergraduate students to IEs by illustrating with familiar, simple and intuitive examples. Using uncoupled IEs to solve transmission line (TL) problems as an example for undergraduate students was proposed in the literature, but a mathematical complexity still remains, which should be avoided for the introductory course on IEs. In this paper, solving TL problems using coupled IEs and the method of moments (MM) is proposed instead to further reduce the mathematical complexity and gain better understanding of the coupled nature of associated voltage and current distributed along TLs. Several numerical examples for different load terminations are given to illustrate that the coupled IEs with the MM can provide accurate results indeed. © 2021 IEEE.

关键词： Electric lines

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Slots Effect on CPW Pentagonal Patch Antenna for 3.5 GHz 5G and 5.9 GHz DSRC Applications

Slots Effect on CPW Pentagonal Patch Antenna for 3.5 GHz 5G ...

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International Symposium on Antennas and Propagation (ISAP)

作者： Amier Hafizun Ab Rashid Badrul Hisham Ahmad Nornikman Hassan Saidatul Norlyna Azemi Centre of Telecommunication Research and Innovation Faculty of Electronics and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka (UTeM) Durian Tunggal Melaka Malaysia Kolej Komuniti Segamat Johor Segamat Johor Malaysia Advanced Communication Engineering Center of Excellence Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Arau Perlis Malaysia

ISBN: (数字)9798350364774

ISBN: (纸本)9798350364781

This research investigates the effects of two different slots on the CPW pentagonal patch antenna for 5G and Dedicated short-range communications (DSRC). Initially, first antenna design, Antenna A is pentagonal patch antenna with pentagonal slots while the second antenna design B is constructed by a pentagonal patch antenna with mini multiple slots structure. This Antenna A performs best at 3.32 GHz and 5.77 GHz with - 20.83 dB and - 49.56 dB, respectively. Besised that, the Antenna B perfoms at 3.50 GHz and 5.92 GHz with - 46.13 dB and - 20.09 dB, respectively.

关键词： Slot antennas 5G mobile communication Patch antennas Design methodology Coplanar waveguides Dedicated short range communication Gain Antenna radiation patterns

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Dynamic-Matrix-Encryption Based Secure Strong PUF for Device Authentication Protocols

Dynamic-Matrix-Encryption Based Secure Strong PUF for Device...

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International Conference on Solid-State and Integrated Circuit technology

作者： Liangxiao Zhao Gang Li Pengjun Wang Xuejiao Ma Ziyu Zhou The College of Electrical and Electronic Engineering Wenzhou University Wenzhou China School of Data Science and Artificial Intelligence Wenzhou University of Technology Wenzhou China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

Strong physical unsolvable function (PUF) has a wide range of applications in internet of things (IoT) security. However, it is vulnerable to machine learning (ML) modeling attacks. This paper proposes a strong PUF anti-ML attack method based on dynamic-matrix encryption. It obfuscates the challenge by multiplying the dynamic encryption matrix (DEM) with the challenge matrix synchronizing initial values during the registration phase of the device security authentication protocol prevents our obfuscation from being invalidated when the algorithms and structures motivating the obfuscation are made public. Each round of DEM is updated with respect to each previous round of challenge which is similar to the properties of sequential logic circuits in that the current response does not depend only on the current challenge but is related to previous challenge. Experimental results show that even if an attacker collects 1 million challenge response pairs, the prediction accuracies of the several ML attacks we use are below 53%, with negligible effects on randomness, reliability, and uniqueness.

关键词： Support vector machines Protocols Accuracy Heuristic algorithms Authentication Encryption Sequential circuits Internet of Things Synchronization Integrated circuit modeling

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Embedding SDGs in Higher Education Curricula: A Case Study

Embedding SDGs in Higher Education Curricula: A Case Study

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Sri Devi Ravana Myat Noe Win Nasa Zata Dina Maria Fasli Department of Information Systems Faculty of Computer Science & Information Technology Universiti Malaya Kuala Lumpur Malaysia School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom

Data analytics has enabled evidence-based decision-making, monitoring, and implementation across multiple sectors, making datasets easier to collect, analyze, and understand. Data analytics presents an opportunity for the application of advanced techniques to address challenges in the real world including at the global level such as those associated with the Sustainable Development Goals (SDGs). In educating the next generation of professionals, instilling them with the desire to use technologies for public good and support the implementation of SDGs is highly desirable, but how to do this in higher education settings so as to develop talents and future professionals who can create meaningful impacts towards a nation's and global sustainable growth is not clear. It is still challenging to transform students' perspectives from seeing data analytics projects as purely academic exercises to developing real-world solutions that can have an impact on policy and sustainable development. This paper describes a case study on developing students as professionals and their understanding of SDGs utilizing the Data Analytics Group Project curriculum at the University of Malaya. With the findings, this paper intends to inspire academics to consider how SDGs can be included in the curriculum so that students as trained professionals can adopt a holistic viewpoint of their professional contributions to society and the SDGs in particular, taking into account the cultural, economic, and environmental influences on a country's sustainable development initiatives.

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Deep learning based DeepFake video detection

Deep learning based DeepFake video detection

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Guefrachi, Sarra Ben Jabra, Marwa Alsharabi, Naif A. Ben Othman, Mohamed Tahar Alharabi, Yasser O. Alkholidi, Abdulsalam Hammam, Habib Université de Moncton Faculty of Engineering MonctonNBE1A3E9 Canada Spectrum of Knowledge Production & Skills Development Sfax3027 Tunisia Computer Engineering University of Ha'il Computer Science Amran University Yemen Ha'il55476 Saudi Arabia College of Computer Qassim University Department of Computer Science Buraydah51452 Saudi Arabia College of Computer Sc. & Engneering Ha'il University Computer Science and Information Ha'il Saudi Arabia Canadian Institute of Technology College Department of Software Engineering Tirana Albania International Institute of Technology and Management Commune d'Akanda BP Libreville1989 Gabon School of Electrical Engineering University of Johannes-burg Dept of Electrical and Electronic Eng. Science Tirana Albania

ISBN: (纸本)9798350347050

Recent advances in DeepFake face-swapping technology have made it simple to create fake videos that appear remarkably real. Since it has been employed in numerous instances for deceit, extortion, and the falsification of facts, its widespread use has generated a huge social, security, and political risk. Its use on websites and social media has become more widespread. Detecting this crime is becoming more and more important due to the potential harm false videos may inflict on a global scale. This research offers a method for building a deep learning model that really can tell the difference between authentic and false videos. The article describes how to create new models based on the VGG16 neural network, a previously created neural network that does image categorization, using transfer learning in the computer vision field. Deep learning is still becoming better at both producing and spotting DeepFakes. DeepFake detection algorithms are developed using dated public datasets, and as a result, they may become obsolete with time. and require continual updating. The research findings are encouraging, and our results reached an accuracy rate of over 90%. © 2023 IEEE.

关键词： Crime

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A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

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Earth and Planetary Physics 2024年第2期8卷 423-435页

作者： Kozo Yamashita Hironobu Fujisaka DaoHong Wang Hiroyuki Iwasaki Kazuo Yamamoto Koichiro Michimoto Masashi Hayakawa Department of Production Systems Engineering and Sciences Komatsu UniversityNu 1-3 Shicho-machiKomatsuIshikawa 923-8511Japan Fujisaka Technology Office 1058-5 Yoshizawa-choOhta-shiGunma 373-0019Japan Department of Electrical Electronic and Computer EngineeringGifu University1-1 YanagidoGifu CityGifu 501-1193Japan Cooperative Faculty of Education Gunma University4-2-Aramaki-machiMaebashiGunma 371-8510Japan Department of Electrical and Electronic Engineering Chubu University1200 Matsumoto-choKasugaiAichi 487-8501Japan Independent Researcher Kosenba Town 2-44-11-406Kawagoe CitySaitama350-0036Japan Advanced Wireless&Communications Research Center The University of Electro-Communications1-5-1 ChofugaokaChofuTokyo 182-8585Japan

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning *** is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple *** multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed ***,there is no such EFM with specified speed and phase control performance of the rotary ***,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS *** EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test *** we describe the design and a simple calibration method for our new EFM *** analysis method based on the assumption of a simple monopole charge structure is also *** validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF *** results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

关键词： lightning electrostatic field electric field mill electric field change

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Novel Universal Windowing Multicarrier Waveform for 5G Systems

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computers, Materials & Continua 2021年第5期67卷 1523-1536页

作者： Ahmed Hammoodi Lukman Audah Montadar Abas Taher Mazin Abed Mohammed Mustafa S.Aljumaily Adeeb Salh Shipun A.Hamzah Wireless and Radio Science Centre Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn MalaysiaParit Raja86400Malaysia Department Communications Engineering University of DiyalaBaqubah32001Iraq College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN37901USA

Fifth Generation(5G)systems aim to improve flexibility,coexistence and diverse service in several aspects to achieve the emerging applications *** and filtering of the traditional multicarrier waveforms are now considered common sense when designing more flexible *** paper proposed a Universal Windowing Multi-Carrier(UWMC)waveform design platform that is flexible,providing more easily coexists with different pulse shapes,and reduces the Out of Band Emissions(OOBE),which is generated by the traditional multicarrier methods that used in the previous generations of the mobile *** novel proposed approach is different from other approaches that have been proposed,and it is based on applying a novel modulation approach for the Quadrature-Amplitude Modulation(64-QAM)which is considered very popular in mobile *** new approach is done by employing flexible pulse shaping windowing,by assigning windows to various *** leads to decreased side-lobes,which are going to reduce OOBE and boost the spectral efficiency by assigning them to edge subscribers *** new subband windowing(UWMC)will also maintain comprehensively the non-orthogonality by a variety of windowing and make sure to keep window time the same for all *** addition,this paper shows that the new approach made the Bit Error Rate(BER)equal to the conventional Windowed-Orthogonal Frequency Division Multiplexing(W-OFDM).This platform achieved great improvement for some other Key Performance Indicators(KPI),such as the Peak to Average Power Ratio(PAPR)compared with the conventional(W-OFDM)and the conventional Universal Filtered Multicarrier(UFMC)*** particular,the proposed windowing scheme outperforms previous designs in terms of the Power Spectral Density(PSD)by 58%and the(BER)by 1.5 dB and reduces the Complementary Cumulative Distribution Function Cubic Metric(CCDF-CM)by 24%.

关键词： 5G waveform window-OFDM universal filtered multi-carrier key performance indicators

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