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6th World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2022

作者： Upreti, Kamal Mishra, Prateet Maheshwari, Manish Vats, Prashant Dhankar, Aisha Batra, Reenu Yadav, Saneh Lata Chawla, Tanvi Bhardwaj, Jayant Department of Computer Science and Engineering Dr. Akhilesh Das Gupta Institute of Technology and Management Delhi New Delhi India Department of Computer Science and Information Technology Symbiosis University of Applied Sciences MP Indore India Department of Computer Science and Applications Makhanlal Chaturvedi National University of Journalism and Communication MCNUJC Madhya Pradesh Bhopal India Department of Computer Science and Engineering Faculty of Engineering and Technology SGT University Haryana Gurugram India Department of Electronics and Communication Bhagwan Parshuram Institute of Technology GGSIPU New Delhi India

ISBN: (纸本)9789811976599

Pneumonia is an infectious ailment which affects the respiratory system and is caused by microbes that infect the human by affecting their lung air sacs and fill them with fluid. Using chest X-ray is the most popular approach for detecting pneumonia, and the results must be calculated and examined by medical experts. The inconvenient way of detecting pneumonia results in a loss of human life owing to incorrect approach and treatment. With the advancement of computer and information technology, developing an autonomous system that can help in the diagnosis and prevention of pneumonia is now viable, especially if the patient is in a place where the medical facilities and expert doctors are limited. In order to solve this challenge, this project uses deep learning technologies. The neural network was customized to accomplish the difficult task of detecting diseases such as pneumonia in order to aid medical experts in their diagnosis and treatment options. CNN applies a filter to a photo in order to extract data from a chest X-ray. The above-mentioned goal was achieved using Python programming language, as well as deep learning and neural network methodologies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Chest X-rays Deep CNN Recognition of pneumonia Rectified linear function Thoracic X-ray component

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Visualizing Wellness: The Impact of Deep Learning on Healthcare Image Analysis

Visualizing Wellness: The Impact of Deep Learning on Healthc...

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2023 International Conference on Advances in Computation, communication and Information Technology, ICAICCIT 2023

作者： Sinha, Deepak Kumar Naval, Preeti Fiza, Samreen Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350344387

Deep convolution networks have quickly established itself as the main method for deciphering medical pictures due to their widespread use. This extensive study examined almost 300 recent papers, mostly from the preceding year, that summarized the basic artificial intelligence ideas related to medical picture analysis. Applications of deep learning were explored in detail in a number of disciplines, including object recognition, picture grouping, classification, and registering. This book presents a succinct summary of studies conducted in the fields of neurological disorders, retinal cells, asthma, malignant scans, breasts, cardiovascular and cardiac pelvic, and nerve imaging. Study conducted concludes our assessment with a review of the state-of-the-art at this time, a thorough investigation of outstanding problems, and suggestions for further research. All areas, including computerized pathology, musculoskeletal, pulmonary, the heart, breasts, muscles and tendons, retinal, and neurology imaging, are summarized in a summary of current studies. This thorough review ends with an assessment of the field's current state, a critical analysis of ongoing issues, and specific suggestions for further research and development. © 2023 IEEE.

关键词： Classification Convolutional Neural Networks (CNNs) Deep Learning Detection Healthcare Image Analysis Image Processing and Medical Image Analysis Localization Machine Learning Medical Imaging

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Powering Next-Generation Wireless communication With Cooperative Strategies

Powering Next-Generation Wireless Communication With Coopera...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Nair, Amrutha V Panduranga Rao, M.V. Agrawal, Trapty Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka 562112 India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350357769

Recent research has been focused on RF energy transmission and recovery as a potential strategy to greatly increase the lifespan of resource wireless networks. This method has the ability to remotely supply items with vitality that is comparatively steady and prolonged;as a result, it introduced a new methodological approach known as WPC, that had created numerous new research avenues with broad uses. In these, the creation and evaluation of effective joint plans has recently garnered a lot of study attention. The collaboration continuum communicating initiatives for behavioral connectivity networks, the collaborating crosstalk techniques forward into mobile broadband network security, and the explaining policies and procedures for wap data transmission are all highlighted in this article's general introduction of working in multiple approaches. Again once we wrap up this piece, we also highlight a number of intriguing study paths in this field. © 2023 IEEE.

关键词： Cognitive Radio Networks Collaborative Strategies Cooperative Jamming and Network Topologies Energy Harvesting Relay Selection Secure communications Spectrum Sharing Wireless-Powered communications Energy Transmission

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Mobile Device Security in Wireless Networks: Challenges, issues and Solutions 15

Mobile Device Security in Wireless Networks: Challenges, iss...

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15th International Conference on Computing communication and Networking Technologies, ICCCNT 2024

作者： Gopalakrishna, K. Sahoo, Laxman Arunadevi, R. Wasatkar, Namrata N. Sahoo, Girija Shankar Singh, Dhiraj Faculty of Engineering and Technology Department of Electronics and Communication Engineering Karnataka Ramnagar District562112 India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Technology Department of Computer Engineering Pune India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Chitkara University Institute of Engineering and technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350370249

Mobile device protection has emerged as an increasingly important difficulty as more and more customers depend upon wireless networks for everyday conversation and other duties. Wi-Fi networks offer convenience and versatility for users;however, they also come with safety worries. This paper presents an overview of the safety-demanding situations related to Wi -Fi networks, discusses safety issues related to cellular devices, and offers more than a few answers for creating cozy cell surroundings. It focuses on defensive person identification, privacy, statistics, and defending against possible malicious activities. Primarily, the paper explores security solutions, encryption, authentication, community access control, and tool control. Moreover, it appears on the role of service carriers in cell tool protection and shows an aggregate of quality practices and generation to sell secure usage. Finally, the paper recommends persevering with studies to identify new threats and answers to decorate mobile safety similarly. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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URLLC in 5G & Beyond: Specifications and Technologies

URLLC in 5G & Beyond: Specifications and Technologies

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Sudhamsu, Gadug Mishra, Awakash Kale, Kiran Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350357769

With the ability to communicate between machines and people, the Tactile Internet (TI) represents a substantial advancement over the Internet of Things (IoT). TI wants to make it easier to develop real-time interactive applications in a variety of fields, including as engineering, social engagement, and business. The future 5th Generation (5G) technology is focused on offering Ultra-Reliable Low Latency communication (URLLC) services to satisfy the demanding needs of TI applications. According to 3GPP specifications, URLLC may transmit a single 32-byte packet with a latency of less than one millisecond and achieve 99.99% dependability. In order to accomplish these objectives, the 3GPP presents 5G New Radio (5G NR), a flexible orthogonal frequency division multiplexing (OFDM) approach, as a new radio access technology (RAT). With the introduction of this new RAT, it is clear that we need next-generation solutions, especially ones that include network intelligence. To fulfil the URLLC needs of 5G NR, machine learning (ML) methods are anticipated to be crucial in building intelligent network resource distribution algorithms. This review analyses the possible use of Federated reinforcement learned, an ML approach, to satisfy the needs of 5G NR URLLC and lists the pertinent URLLC accomplishments. Plane channel entry techniques that support URLLC in 5G NR for TI workloads are covered in great detail in this study. It also pinpoints seven crucial upcoming situations where FRL might function as a possible facilitator for URLLC in 5G NR. © 2023 IEEE.

关键词： 3GPP specifications 5G Federated reinforcement learning latency and reliability machine learning network architecture New Radio Tactile Internet URLLC

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Utilizing Machine Learning Algorithms for Effectively Detection IoT DDoS Attacks 1st

Utilizing Machine Learning Algorithms for Effectively Detect...

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1st International Conference on Advances in Computing Research, ACR’23

作者： Mughaid, Ala Alqahtani, Ali AlZu’bi, Shadi Obaidat, Ibrahim Alqura’n, Rabee AlJamal, Mahmoud AL-Marayah, Raid Department of Information Technology Faculty of Prince Al-Hussien Bin Abdullah for IT The Hashemite University Zarqa Jordan Department of Networks and Communication Engineering College of Computer Science and Information Systems Najran University Najran Saudi Arabia Computer Science Department Faculty of Science and Information Technology Al Zaytoonah University of Jordan Amman Jordan

ISBN: (纸本)9783031337420

One of the most critical features of the Internet of Things (IoT) is that it allows a massive number of devices to communicate with each other at the same time, for example (cars, smoke alarms, watches, glasses, web cameras, etc.). Given that they can connect to the Internet, the huge demand to convert systems into smart systems that can be controlled remotely increases the chances of cyber-attacks that threaten security and availability becoming more frequent, severe, and in a different form. Distributed Denial of Service (DDoS) attacks have become the most common threats in IoT. These attacks make IoT systems unreliable because complex DDoS attacks cannot be detected by traditional security countermeasures such as firewalls and intrusion detection systems (IDS). In this research, we proposed a model dedicated to work on prediction and detection of DDoS attacks on networks IoT, where we run this model on a NF-BoT-IoT-v2 dataset, which contains 37,763,497 records divided into five categories (Benign, Reconnaissance, DDoS, DoS, and Theft), and then we process our dataset to be more business friendly so it only has two categories (100,000 records broken down into 23,906 benign attacks and 76,094 DDoS attacks). This study used WEKA and MATLAB tools to perform the classification efficiently and find the most important features through feature selection. We used a decision tree (J48) machine learning classifier, a Naive Bayes (NB) classifier, and a random forest (RF) classifier. However, the results were as expected and improved accuracy and efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Denial-of-service attack

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Using Augmented Reality to Teach Primary Students Time Concepts: Development and Evaluation of AR Clock 6

Using Augmented Reality to Teach Primary Students Time Conce...

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6th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2024

作者： Setyadinsa, Radinal Pendit, Ulka Chandini Kamsin, Afifah Dolhait, Lutfi University of Pembangunan Nasional 'Veteran' Jakarta Faculty of Computer Science Jakarta Indonesia College of Business Technology and Engineering Sheffield Hallam University Sheffield United Kingdom Content Tree Malaysia University of Teknikal Malaysia Melaka Faculty of Information and Communication Technology Melaka Malaysia

ISBN: (纸本)9798331533243

This study presents the development and evaluation of AR Clock, a mobile Augmented Reality (AR) application designed to teach time concepts to primary school students. The application addresses the growing concern about children's limited understanding of time and their difficulty in reading analogue clocks. AR Clock was developed using Agile methodology, Unity, and Vuforia SDK to create an interactive and engaging learning experience. The application features multiple levels of time-telling exercises, from basic hour reading to complex time concepts, complemented by a quiz feature for self-assessment. A user study was conducted with 25 primary school students (ages 5-6) and one mathematics teacher to evaluate the effectiveness of AR Clock showed positive outcomes that indicated AR Clock effectively combines AR technology with educational content to create an engaging learning tool for time concepts. The application's strengths lie in its intuitive interface, interactive features, and the use of AR to enhance the learning experience. This study contributes to the growing body of research on AR applications in education, particularly in teaching fundamental mathematical concepts to young learners. © 2024 IEEE.

关键词： Students

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Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

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International Journal of Intelligent Computing and Cybernetics 2022年第3期15卷 363-382页

作者： G.Merlin Linda N.V.S.Sree Rathna Lakshmi N.Senthil Murugan Rajendra Prasad Mahapatra V.Muthukumaran M.Sivaram Department of Computer Science and Engineering SRM Institute of Science and Technology–Vadapalani CampusChennaiIndia Department of Electronics and Communication Engineering Agni College of TechnologyChennaiIndia School of Computer Science and Engineering VIT-AP UniversityAmaravatiIndia Department of Computer Science and Engineering SRM Institute of Science and TechnologyGhaziabadIndia Department of Mathematics School of Applied SciencesREVA UniversityBangaloreIndia Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam

Purpose-The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and *** proposes a convolutional neural network-based capsule network(CNN-CapsNet)model and outlining the performance of the system in recognition of gait and speech *** proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech ***/methodology/approach-This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNNand used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in *** proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of ***-This research work provides recognition of signal,biometric-based gait recognition and sound/speech *** evaluations are conducted on three aspects of scenarios,namely fixed-view,cross-view and multi-view *** main parameters for recognition of gait are speed,change in clothes,subjects walking with carrying object and intensity of *** limitations/implications-The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware *** implications-This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware ***/value-This proposed research work proves to be performing better for the recognition of gait and speech when

关键词： Intelligent system Gait recognition Convolutional neural network Deep learning Capsule network Viewpoint variations

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Performance Enhancement in Terms of BER and Data Rate of Next Generation Optical Networking System using Raman Amplifier

Performance Enhancement in Terms of BER and Data Rate of Nex...

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Integrated Circuits and communication Systems (ICICACS), IEEE International Conference on

作者： Shailesh Khant Mayur Makwana Atul Patel Dip Patel Faculty of Computer Science and Applications CHARUSAT Changa Anand India Faculty of Electronics and Communication Engineering CHARUSAT Changa Anand India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

This study explores the integration of Raman optical amplifiers in a Wavelength Division Multiplexing Passive Optical Network (WDM-PON) system to enhance high-speed data transmission. Traditional amplifiers like Erbium doped fiber amplifier (EDFA) and Semiconductor amplifier (SOA) face limitations in noise performance and gain efficiency over long distances. To address these challenges, a four-channel WDM-PON system was designed and simulated over a 50 km fiber link. Performance metrics, including Bit Error Rate (BER), Quality Factor (Q-Factor), and eye diagram characteristics, were analyzed. The results demonstrate that Raman amplification significantly reduces BER, improves Q-Factor, and enhances signal integrity, making it a robust solution for long-reach optical networks. This study contributes to the advancement of optical communication by showcasing the effectiveness of Raman amplifiers in supporting high-capacity, high-speed transmission. The main findings are Raman amplification is used for improving signal quality and network efficiency in next-generation optical systems and is better compared to other optical amplifiers.

关键词： Optical fiber amplifiers Q-factor Semiconductor optical amplifiers Integrated optics Stimulated emission Bit error rate Erbium-doped fiber amplifiers Passive optical networks Next generation networking High-speed optical techniques

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Threshold public key-sharing technique in block chain

Threshold public key-sharing technique in block chain

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Pande, Sagar Dhanraj Singh, Gurpreet Zekrifa, Djabeur Mohamed Seifeddine Kodgire, Shilpa Prashant Patel, Sunil A. Le, Viet-Thanh School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India Faculty of Computational Science GNA University Phagwara India Centre for Quantum Computation and Communication Technology Sydney Australia Maharashtra Institute of Technology Maharashtra Aurangabad India Computer Engineering Department L.D. College of Engineering Ahmedabad India Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9781032669663

A threshold key-sharing technology-based publicly verifiable key-sharing technology is presented to explore blockchain users’ private keys’ security. After receiving key fragments, participating nodes validate them. When splitting the key, the central splitting node does evil. In the critical recovery stage, the key fragments of the nodes participating in key splicing are publicly verified to prevent them from doing evil. In the critical distribution stage, add IDs to participating nodes to track malicious nodes and update node status in real-time, and a dynamic threshold mechanism is designed. To maintain private key fragment integrity, the owner of the key fragment and the controller node redistribute it to the new participating nodes once the vital fragment node goes offline. Experimental results reveal that this scheme’s private key recovery rate is 80% and has threshold properties, traceability, unforgeability, and recoverability. © 2024 The Author(s).

关键词： Blockchain

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