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2nd International Conference on Sustainable Smart Cities and Territories, SSCT 2023

作者： Chauhan, Uttam Sheth, Vinay Trivedi, Vishvesh Bhatt, Chintan Corchado, Juan Manuel Vishwakarma Government Engineering College Ahmedabad India Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar India BISITE Research Group University of Salamanca Salamanca37007 Spain Air Institute IoT Digital Innovation Hub Salamanca37188 Spain Faculty of Engineering Department of Electronics Information and Communication Osaka Institute of Technology Osaka535-8585 Japan

ISBN: (纸本)9783031369568

Misinformation detection (MID) has recently gained attention as a research question. We discover that many efforts have been made in response to the innovative research issues and MID research approaches as an empowering and developing rapidly research field. Misinformation typically spreads faster, profound, and wider in social networks. It is crucial to identify disinformation on social media since people are less able to distinguish between true information and false information due to an abundance of information and limited attention. Exploration of misinformation detection received little attention from the computational NLP research community. In this paper, we propose a novel architecture for detecting misinformation in Gujarati text. In the architecture, the significance of domain experts, crowd intelligence, and fact-checking website interaction has been depicted. Additionally, we define certain special Gujarati language traits for the early detection of counterfeit news. We have built a classifier incorporating domain experts to identify fake news and present outcomes for the automatic fake news detection and its class. We showed the findings of the experiments performed on the news article corpus that we built by fetching the articles from newspaper websites and applications. We found that stochastic Gradient Descent and NuSVC achieved the accuracy 88% using TFIDF and CV respectively, which is the highest among all models we experimented. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Stochastic systems

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An Enhanced Residual Networks Based Framework for Early Alzheimer’s Disease Classification and Diagnosis 6th

An Enhanced Residual Networks Based Framework for Early Alzh...

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6th International Conference on Communication, Devices and Networking, ICCDN 2022

作者： Awotunde, Joseph Bamidele Sur, Nath Samarendra Imoize, Agbotiname Lucky Misra, Sanjay Gaber, Tarek Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Kwara State Ilorin240003 Nigeria Department of Electronics and Communication Engineering Sikkim Manipal Institute of Technology Sikkim Manipal University East Sikkim Rangpo Majitar737136 India Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos100213 Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum44801 Germany Department of Applied Data Science Institute of Energy Technology Halden Norway Faculty of Computers and Informatics Suez Canal University Ismailia41522 Egypt School of Science Engineering and Environment University of Salford ManchesterM5 4WT United Kingdom

ISBN: (纸本)9789819919826

Alzheimer's disease (AD) is a long-lasting, degenerative brain illness for which there is now no successful treatment. However, there are medications that can delay its growth and stop its tracks. Therefore, stopping and regulating the progression of AD depends greatly on its early diagnosis. computer-aided diagnosis (CAD) in health care has become more and more dependent on deep learning technologies. This has help in early diagnosis and detection of various disease in health care. New techniques for the early diagnosis of neurocognitive abnormalities are now possible thanks to advancements in medical imaging and computational capacity in an effort to stop or slow down cognitive aging. Therefore, this study proposes a residual network (ResNet) type 50 for early diagnosis of AD. Convolutional neural networks (CNNs) are first used in the study for features extraction and then make the ultimate diagnosis using the ResNet-50. To create a better architecture, the problem of AD diagnosis will be addressed by utilizing and incorporating ResNet-50, which improves the current categorization problem's accuracy to its maximum. With a 98.8% accuracy rate, the proposed model using ResNet-50 produces encouraging findings for AD prediction. The study reveals that the model can effectively circumvent CNNs for the diagnostic issue with AD. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： computer aided diagnosis

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Machine Learning Techniques for Detecting DDOS Attacks

Machine Learning Techniques for Detecting DDOS Attacks

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Mamoon M. Saeed Husam Nedhal Rashad Mohammed Othman Abdulkafi Hazaea Gazem Rashid A. Saeed Hossam Mohammed Ahmed Morei Aimen Ebdulkreem Thabet Eidah AbdulGuddoos S.A. Gaid Ameen Sami Ameen Saif Al-Uosfi Mohamed Galal Qasem Al-Madhagi Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen Department of Computer Engineering College of Computers and Information Technology Taif University Taif Saudi Arabia Dept. of Communication & Computer Engineering Faculty of Engineering & Information Technology Taiz University Taiz Yemen

The development witnessed by the world of science and technology and the emergence of the Internet, where cybersecurity has become one of the most important areas that are growing rapidly every day, and one of its goals is to maintain access to users at any time. Where it is noted that the biggest enemy for the availability is Distributed Denial of Service (DDoS) attack, which works to prevent access to the service and slow down the service. Through this paper, machine learning will be used to discover the DDoS attack and know its type to be aware of it and take the necessary measures for that. Where the CICDDoS2019 dataset will be used. After it is studied, analyzed, cleaned and the best algorithm was selected. Five classification algorithms (Random Forest, Decision Tree, SVM, Naive Bayes, and xgboost) were used to train and test the data from the datasets, and it can be said that of the five, Random Forest algorithms had the highest level of accuracy (99.95426%).

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A Computational Intelligence Inspired Framework for Intrusion Detection in WSN

A Computational Intelligence Inspired Framework for Intrusio...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Pandey, Vivek Kumar Prakash, Shiv Gupta, Tarun Kumar Yang, Tiansheng Singh, Abhishek Rathore, Rajkumar Singh University of Allahabad Department of Electronics and Communication Prayagraj India University of Delhi Department of Computer Science Miranda House Delhi India University of South Wales Faculty of Business and Creative Industries Pontypridd United Kingdom Institute of Engineering & Technology Department of Computer Science & Engineering Dr. A.P. J. Abdul Kalam Technical University Lucknow India Cardiff School of Technologies Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (纸本)9798350369106

In this growing world of technology, the wide range of uses of wireless sensor networks (WSNs), such as tracking the environment and keeping an eye on the military, makes them indispensable in many applications. However, due to their open nature and limited resources, WSNs have become an easy target for different security threats, like intrusion attempts. Intrusion detection systems (IDSs) protect WSNs from these threats. This research examines the intrusion detection methods for WSNs and focuses on those that use computational intelligence. This review explores the usefulness of different computational intelligence methods in detecting intrusions in WSNs. It also suggests areas where more research is needed and offers possible directions for further exploration. © 2024 IEEE.

关键词： Network intrusion

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An Attention Mechanism Approach for Natural Color Retrieval for Plant Monitoring

An Attention Mechanism Approach for Natural Color Retrieval ...

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International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON

作者： Yanatorn Chadavadh Teerasit Kasetkasem Teera Patrapornnant Sirichai Parittotakapron Tsuyoshi Isshiki Department of Electrical Engineering Faculty of Engineering Kasetsart University Bangkok Thailand National Electronics and Computer-Technology Center Pathunthani Thailand Tokyo Institute of Technology Tokyo Japan

Even though agriculture practices have been continuously developed with the support of modern technologies, many more improvements can be made to enhance agricultural technologies and businesses. One such technology is the use of specific light color combinations to optimize the growth rate of plants. One obvious drawback is that plants’ color will change according to the light color combinations. The light color can fool human eyes and may cause errors when monitoring for plant anomalies. Color correction methods should be applied to help restore the natural plant color with the white light source from the unnaturally colored plant images. Our color correction method uses an application of self-dot-product attention, multi-head attention, and channel attention combined with a U-Net-based model. This proposed method performs the color correction with the input image in the RGB color space in two steps. First, a global transformation network provides the global function that maps the input RGB color vectors from every pixel and produces the corrected RGB color vectors. The global mapping function is the same for all pixels in the image. Next, a local transformation network attempts to correct the local color distortions such as light the flickering of LED light due to the AC power supplier.

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Milestones of Wireless Communication Networks and technology Prospect of Next Generation(6G)

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computers, Materials & Continua 2022年第6期71卷 4803-4818页

作者： Mohammed H.Alsharif Md.Sanwar Hossain Abu Jahid Muhammad Asghar Khan Bong Jun Choi Samih M.Mostafa Department of Electrical Engineering College of Electronics and Information EngineeringSejong University209 Neungdong-roGwangjin-guSeoul05006Korea Department of Electrical and Electronic Engineering Bangladesh University of Business and TechnologyDhaka1216Bangladesh Department of Electrical&Computer Engineering University of OttawaOttawaON K1N 6N5Canada Department of Electrical Engineering Hamdard University KarachiIslamabad CampusIslamabad44000Pakistan School of Computer Science and Engineering&School of Electronic Engineering Soongsil UniversitySeoulKorea Faculty of Computers and Information South Valley UniversityQena83523Egypt Academy of Scientific Research and Technology Cairo11516Egypt

Since around 1980,a new generation of wireless technology has arisen approximately every 10 ***-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-generation(3G)and became highly popular in the fourthgeneration(4G).To increase the data rate along with low latency and mass connectivity the fifth-generation(5G)networks are being installed from ***,the 5G technology will not be able to fulfill the data demand at the end of this ***,it is expected that 6G communication networks will rise,providing better services through the implementation of new enabling technologies and allowing users to connect everywhere.6G technology would not be confined to cellular communications networks,but would also comply with non-terrestrial communication system requirements,such as satellite *** ultimate objectives of this work are to address the major challenges of the evolution of cellular communication networks and to discourse the recent growth of the industry based on the key scopes of application and *** main areas of research topics are summarized into(i)major 6G wireless networkmilestones;(ii)key performance indicators;(iii)future new applications;and(iv)potential fields of research,challenges,and open issues.

关键词： Wireless networks beyond 5G 6G communications terahertz frequency terahertz communications holographic calls

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Leveraging AI to Unlock the Potential of Data Science

Leveraging AI to Unlock the Potential of Data Science

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International Conference on Computing and Networking technology (ICCNT)

作者： Rakesh Kumar Yadav Gadug Sudhamsu Manish Kumar Goyal S. Yuvaraj Leena A. Deshpande Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Computer Engineering Vishwakarma Institute of Technology Pune INDIA

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The application of synthetic Intelligence (AI) to records science has spread out a massive array of new possibilities. Via the combination of advanced evaluation strategies, effective understanding-pushed system gaining knowledge of algorithms, and modern computing architectures, AI is allowing researchers to quick and as it should be discover insights from huge and complicated datasets. Furthermore, AI tools are offering corporations with the ability to make higher and more knowledgeable choices from the evaluation of hundreds of thousands of statistics points. The skills of information technology powered by means of AI are revolutionizing industries which includes healthcare, finance, and manufacturing-producing savings, uncovering efficiencies, and identifying new opportunities. As AI-driven records technology maintains to strengthen, organizations that capitalize on its ability stand to gain precious insights and unlock new degrees of overall performance.

关键词： Industries Finance Organizations Medical services computer architecture Data science Artificial intelligence Information technology

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A Multiband Tri-branch Monopole Antenna Base on Step Impedance Technique for WLAN, WiMAX, 5G technology, and IoT Application

A Multiband Tri-branch Monopole Antenna Base on Step Impedan...

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International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON

作者： Maleeya Tangjitjetsada Thanakarn Suangun Wanchalerm Chanwattanapong Chatree Mahatthanajatuphat Kanyanat Phimthai Prayoot Akkaraekthalin Department of Electronics and Telecommunication Engineering Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi (RMUTSB) Nonthaburi Thailand Department of Electrical Engineering Faculty of Engineering University of Phayao Phayao Thailand Department of Electronics and telecommunications Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathum Thani Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok (KMUTNB) Bangkok Thailand

A multiband tri-branch monopole antenna is presented. The antenna structure is constructed of radiating patches with three branches. It is fed by a microstrip transmission line. Essentially, the antenna is a simple structure created by a step impedance technique. In addition, the antenna can be separately regulated for each operational frequency band of 2.44 GHz, 3.36 GHz, and 5.52 GHz by the height of a central patch, a right patch with a thin strip line, and a small patch on the left, respectively. The antenna is manufactured on a size of 50x35 mm 2 FR4 substrate with a thickness of 0.8 mm and a permittivity of 4.3. The suggested antenna is appropriate for network board internet of things (NB-IoT) technology working at 2.4 GHz/5.2 GHz/5.8 GHz (WLAN), 3.5 GHz (WiMAX), and 2.3 GHz/2.6 GHz/3.5 GHz (5G technology). The antenna’s radiation pattern is omnidirectional, and its average gain is approximately 2dBi.

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A Novel Dual-Band Printed SIW Antenna Design Based on Fishnet & CCRR DGS Using Machine Learning for Ku-Band Applications

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Progress In Electromagnetics Research C 2021年 116卷 207-219页

作者： Nakmouche, Mohammed F. Magray, Muhammad I. Allam, Abdemegeed M. Fawzy, Diaa E. Lin, Ding Bing Tarng, Jenn-Hwen Faculty of Engineering Izmir University of Economics Izmir Turkey Hsinchu City Taiwan Department of Communication Engineering German University in Cairo Cairo Egypt Department of Electronics and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan

—This paper analyzes and solves the complexity to determine the optimum positions of the Fishnet & Complementary Circular Ring Resonator (CCRR) based Defected Ground Structures (DGS) for Substrate Integrated Waveguide (SIW) based antennas. A new state-of-art technique based on Artificial Neural Network (ANN)-Machine Learning (ML) is proposed for overcoming the lack of solid and standard formulations for the computation of this parameter related to a targeted frequency. As a proof of concept and to test the performance of our approach, the algorithm is applied for the determination of the CCRR and Fishnet-DGS’s optimal positions for a SIW based antenna. The SIW technique provides the advantages of low cost, small size, and convenient integration with planar circuits. The ANN-ML based technique is optimized to attain dual-band resonances with optimal gain and radiation efficiency. The simulation results of the first Fishnet-DGS based antenna show good minimum return losses at two center frequencies, namely, 16.6 GHz (with gain of 6 dB and radiation efficiency of 95%) and 17.7 GHz (with gain and radiation efficiency of 9 dB and 96%, respectively). The second CCRR-DGS based antenna shows about 8 dB gain and a radiation efficiency of 87% at 17.3 GHz, and gain and efficiency of about 8.5 dB and 85% are observed at 17.8 GHz. The proposed CCRR and Fishnet-DGS based antenna are low profiles, low costs, with good gains and radiation efficiencies, making both designs very suitable for Ku-band applications. There is a fair agreement between the measured and simulated results. The achieved dual-band resonances act as a proof of concept that the proposed ANN-ML techniques can be employed for the determination of the optimal positions for CCRR and Fishnet thereby attaining any target dual-bands in the Ku-band with good accuracy of about 98% and a save of 99% in the overall the computational time. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Radiation efficiency

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A Novel Peak-to-Average Power Ratio Reduction for 5G Advanced Waveforms

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computers, Materials & Continua 2022年第10期73卷 1637-1648页

作者： Rajneesh Pareek Karthikeyan Rajagopal Himanshu Sharma Nidhi Gour Arun Kumar Sami Althahabi Haya Mesfer Alshahrani Mohamed Mousa Manar Ahmed Hamza Department of Computer Science&Engineering JECRC UniversityJaipur303905India Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia Department of Electronics and Communication JECRC UniversityJaipur303905India Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Electrical Engineering Department Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Multi and single carrier waveforms are utilized in cellular systems for high-speed data *** The Fifth Generation(5G)system,several waveform techniques based on multi carrier waveforms are ***,the Peak to Average Power Ratio(PAPR)is seen as one of the significant concerns in advanced waveforms as it degrades the efficiency of the *** proposed article documents the study,progress,and implementation of PAPR reduction algorithms for the 5G radio *** compare the PAPR algorithm performance for advanced and conventional *** simulation results reveal that the advanced Partial Transmission Sequence(PTS)and Selective Mapping(SLM)methods enhanced the throughput and gain of the 5G ***,we have also analyzed the performance of Orthogonal Time Frequency Space Modulation(OTFSM)based on a single carrier system and found that PAPR is significantly low and is best suited to fading *** is seen that the conventional algorithms lower the PAPR but increase the *** proposed PTS and SLM have shown good performance with low computational complexity.

关键词： PAPR 5G OFDM NOMA OTFSM PTS SLM

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