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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Singla, Abhishek Divya, K. Manohar, K. Kantak, Ganesh Kumar Singh, Akhilendra Pratap Rajesh, A. Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India

ISBN: (纸本)9798350319125

Gadget studying can be used to enhance the accuracy of actual-time records evaluation. System-gaining knowledge can discover patterns and tendencies in information extra quickly and accurately while not having to manually analyze the data, allowing for decisions to be made with extra self-belief and accuracy. By means of incorporating capabilities that tune user interaction, machines gaining knowledge can use supervised and unsupervised studying to regulate the models to beautify accuracy. This paper explores the use of machine learning tools to improve the accuracy of real-time data analysis. With the constant influx of data in various industries, accurate and timely analysis is crucial for making informed decisions. However, traditional data analysis methods may fall short in handling the complexity and volume of real-time data. Machine learning algorithms offer the potential to overcome these challenges by autonomously identifying patterns and trends in real-time data. This paper discusses the benefits of incorporating machine learning in real-time data analysis and provides a comprehensive review of existing tools and techniques. Through case studies and experiments, we demonstrate the effectiveness of machine learning in improving the accuracy of real-time data analysis. The results of our study highlight the potential of machine learning tools in enhancing decision-making processes and driving better outcomes in various industries. Furthermore, we discuss the challenges and limitations of using machine learning in real-time data analysis and provide recommendations for future research in this area. This method of the usage of system gaining knowledge of tools will increase the efficiency and accuracy of real-time records evaluation and allows to make knowledgeable choices which can result in better effects. © 2023 IEEE.

关键词： Anomaly detection

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Enabling Autonomous Deep Learning Strategies for Real-Time Data Analysis in Machine Learning 3

Enabling Autonomous Deep Learning Strategies for Real-Time D...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Sahoo, Girija Shankar Sekaran, Ramesh Renuka, G. Dhabliya, Dharmesh Faujdar, Pramod Kumar Minhas, Deepak Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350319125

This studies focuses on leveraging self-sustaining deep getting to know techniques for real-time records analysis in device getting to know. We propose a machine this is enabled by means of artificial intelligence to streamline the technique of extracting significant insights from sensor-based records. Our approach considers two middle components: interpreting data with recurrent neural networks and deploying a mastering agent to routinely whole the statistics analysis process. The getting to know agent's training is based on supervised mastering, enabling it to discover and traverse styles inside the information. The recurrent neural community (RNN) offers the functionality to seize temporal styles within the information, with its capacity to make predictions based on previous input. As a result, our system can produce fairly correct insights with minimal human intervention. This makes it suitable for time-sensitive information analysis situations in the industrial area in which decisions have to be taken in actual-time. © 2023 IEEE.

关键词： Recurrent neural networks

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Multipath Routing Strategies for End-to-End Traffic Management in Underwater High Speed Networks 3

Multipath Routing Strategies for End-to-End Traffic Manageme...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Singh, Akhilendra Pratap Srisathirapathy, S. Dhabliya, Dharmesh Kaur, Ashmeet Mamatha, G.N. Seth, Jyoti Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Faculty of Engineering and Technology Department of Electronics and Communication Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India

ISBN: (纸本)9798350319125

Underwater high-speed networks (HSN s) use several environmental, operational, and technical demanding situations, making their layout and efficient operation challenging. The underwater medium introduces variabilities on the acoustic channels that, in turn, increase the complexity of the routing and site visitors' control. Multipath routing has been proposed to manage agile, nice-grain, and actual-time cease-to-end visitors in these networks. This painting provides and evaluates several multipath routing techniques for excessive velocity Underwater Networks (HSUN s), The proposed algorithms originate from direction Vector protocols and think about link metrics, hop to be counted, put-off jitter, packet loss fee, and other applicable parameters. We examine the performance of the proposed multipath routing strategies, based totally on the standard packet put-off, packet loss fee, and jitter average in a large-scale natural experiment carried out using acoustic modems underneath controlled channel conditions in an underwater tunnel. The experiment results show vast enhancements in the performance of the network when compared to single-route routing. Furthermore, the effects display the strong effect of the multipath routing techniques on the community's overall performance. In step with the acquired outcomes, the offered multipath routing techniques may be increased and used to enhance the throughput and first-rate service of excessive-velocity underwater networks. © 2023 IEEE.

关键词： controlled demonstrate experiment improvements performance

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Conflict Resolution Strategy in Handover Management for 4G and 5G Networks

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computers, Materials & Continua 2022年第9期72卷 5215-5232页

作者： Abdulraqeb Alhammadi Wan Haslina Hassan Ayman A.El-Saleh Ibraheem Shayea Hafizal Mohamad Yousef Ibrahim Daradkeh Communication Systems and Networks Research Lab Malaysia-Japan International Institute of TechnologyUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia College of Engineering A’sharqiyah University(ASU)Ibra400Oman Department of Electronics and Communication Engineering Faculty of Electrical and Electronics EngineeringIstanbul Technical University(ITU)Istanbul34467Turke Faculty of Engineering and Built Environment Universiti Sains Islam MalaysiaBandar Baru Nilai71800Malaysia Department of Computer Engineering and Networks College of Engineering at Wadi AddawasirPrince Sattam Bin Abdulaziz UniversityAl Kharj11991KSA

Fifth-generation(5G)cellular networks offer high transmission rates in dense urban ***,a massive deployment of small cells will be required to provide wide-area coverage,which leads to an increase in the number of handovers(HOs).Mobility management is an important issue that requires considerable attention in heterogeneous networks,where 5G ultra-dense small cells coexist with current fourth-generation(4G)*** mobility robustness optimization(MRO)and load balancing optimization(LBO)functions have been introduced in the 3GPP standard to address HO problems,non-robust and nonoptimal algorithms for selecting appropriate HO control parameters(HCPs)still exist,and an optimal solution is subjected to compromise between LBO and MRO ***,HO decision algorithms become *** paper proposes a conflict resolution technique to address the contradiction between MRO and LBO *** proposed technique exploits received signal reference power(RSRP),cell load and user speed to adapt HO margin(HM)and time to trigger(TTT).Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during *** proposed technique is validated with other existing algorithms from the *** results demonstrate that the proposed technique outperforms existing algorithms overall performance *** proposed technique reduces the overall average HO ping-pong probability,HO failure rate and interruption time by more than 90%,46%and 58%,respectively,compared with the other schemes overall speed scenarios and simulation time.

关键词： Mobility management handover 5G heterogeneous networks

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Audio-based tissue classification - preliminary investigation for a needle procedure

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Current Directions in Biomedical engineering 2023年第1期9卷 347-350页

作者： Serwatka, Witold Heryan, Katarzyna Sorysz, Joanna Illanes, Alfredo Boese, Axel Krombach, Gabrielle A. Friebe, Michael Faculty of Computer Science Electronics and Telecommunications AGH University of Science and Technology al. A. Mickiewicza 30 Kraków Poland Department of Measurement and Electronics AGH University of Science and Technology Kraków Poland Intelligente Katheter Otto-von-Guericke Universtät Magdeburg Germany Department of Diagnostic and Interventional Radiology University Hospital Justus-Liebig-University Giessen Germany Department of Biocybernetics and Biomedical Engineering AGH University of Science and Technology Kraków Poland

Image-guided and minimally invasive procedures still require confirmation on having reached a target. Intraoperative imaging is not always sufficient or conclusive as it comes with artifacts that can come with a certain amount of ambiguity and inaccurate location information. As an alternative to imaging, we want to explore sounds produced by the biopsy needle tip while advancing and interacting with tissue. In this paper, we show that by analyzing vibroacoustic signals acquired at the proximal end of the needle we are able to differentiate the tissue type. In total, 419 audio samples of 5 tissues were acquired and converted to spectrograms used as input to a convolutional neural network. Using this experimental setup we were able to differentiate the tissue types with an F1 score of 71.64%. Based on these results we were able to demonstrate the feasibility of our approach, as well as the importance of further experiments to ensure that vibroacoustic sounds produced by the needle tip can be a new navigation method. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Needles

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UAV Fleet Routing Under Weather and Customer Orders Uncertainty Parameters

UAV Fleet Routing Under Weather and Customer Orders Uncertai...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Grzegorz Radzki Grzegorz Bocewicz Peter Nielsen Małgorzata Jasiulewicz-Kaczmarek Zbigniew Banaszak Faculty of Electronics and Computer Science Koszalin University of Technology Koszalin Poland Faculty of Engineering and Science Aalborg University Denamark Faculty of Engineering Management Poznan University of Technology

The problem considered in this paper concerns the proactive mission planning of a UAV fleet, taking into account simultaneous changes in weather conditions and delivery dates. This problem belongs to the VRP class of fuzzy weather forecast and fuzzy delivery time window constraints where UAV delivery routes must be resistant to simultaneous changes in weather conditions and delivery dates. The applied methodology, based on the declarative modeling paradigm, allows the use of commercially available constraint programming packages and considers new cases extended by demand and travel time constraints. To illustrate the possibilities of practical use of the proposed approach, multiple simulation experiments of potential scenarios of planned missions have been carried out. The obtained results indicate the proposed approach can be used for planning UAV fleet mission sizes occurring in practice while being robust to selected environmental disruptions in online mode.

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Securing Healthcare Data in IoMT Network Using Enhanced Chaos Based Substitution and Diffusion

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computer Systems Science & engineering 2023年第11期47卷 2361-2380页

作者： Musheer Ahmad Reem Ibrahim Alkanhel Naglaa FSoliman Abeer D.Algarni Fathi E.Abd El-Samie Walid El-Shafai Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia

Patient privacy and data protection have been crucial concerns in Ehealthcare systems for many *** modern-day applications,patient data usually holds clinical imagery,records,and other medical ***,the Internet of Medical Things(IoMT),equipped with cloud computing,has come out to be a beneficial paradigm in the healthcare ***,the openness of networks and systems leads to security threats and illegal ***,reliable,fast,and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT *** paper presents an image protection scheme for healthcare applications to protect patients’medical image data exchanged in IoMT *** proposed security scheme depends on an enhanced 2D discrete chaotic map and allows dynamic substitution based on an optimized highly-nonlinear S-box and diffusion to gain an excellent security *** optimized S-box has an excellent nonlinearity score of *** new image protection scheme is efficient enough to exhibit correlation values less than 0.0022,entropy values higher than 7.999,and NPCR values around 99.6%.To reveal the efficacy of the scheme,several comparison studies are *** comparison studies reveal that the novel protection scheme is robust,efficient,and capable of securing healthcare imagery in IoMT systems.

关键词： Secure communication healthcare data encryption Internet of Medical Things(IoMT) discrete chaotic map substitution box(S-box)

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Microwave Sensor for Ethanol Intensity Determination Based on Fractal Resonators

Microwave Sensor for Ethanol Intensity Determination Based o...

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International Technical Conference o Circuits/Systems, computers and Communications (ITC-CSCC)

作者： Pubet Sangmahamad Tanaporn Pechrkool Thanakorn Sutham Boonyarit Kumkhet Nipont Tangthong Virote Pirajnanchai Patchadaporn Sangpet Deparment of Electronics and Telecommunication Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathum Thani Thailand Deparment of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

This paper presents a fractal resonator and square patch microstrip-line structure with a central drill hole as a means of achieving ethanol concentration characterization. The liquid under test (LUT), which is a binary mixed liquid made up of ethanol and water, is used to measure and detect the effectiveness of the suggested sensor. The LUT was injected into a glass capillary tube that was positioned in the middle of the square patch microstrip-line structure for the ethanol concentration test. The sensors were designed and fabricated on an FR-4 substrate with a thickness of 0.8 mm, highlighting in general measurements of 15 × 15 mm², and operating at 2.50 GHz under an unloaded condition. The detected ethanol concentrations ranging from 10% up to 95% within the ethanol-water mixtures. Measurement comes about demonstrating the sensor's capability to identify ethanol concentration by comparing the shifted resonance frequency within the transmission coefficient.

关键词： Microwave measurement Liquids Three-dimensional displays Ethanol Resonant frequency Fractals Table lookup

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Improved RC6 Block Cipher Based on Data Dependent Rotations

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computers, Materials & Continua 2022年第1期70卷 1921-1934页

作者： Osama S.Faragallah Ibrahim F.Elashry Ahmed AlGhamdi Walid El-Shafai S.El-Rabaie Fathi E.Abd El-Samie Hala S.El-sayed Mohamed A.Elaskily Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electrical Communications Faculty of EngineeringKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Informatics Electronic Research Institute(ERI)CairoEgypt

This paper introduces an Improved RC6(IRC6)cipher for data encryption based on data-dependent *** proposed scheme is designed with the potential of meeting the needs of the Advanced Encryption Standard(AES).Four parameters are used to characterize the proposed *** parameters are the size of the word(w)in bits,the number of rounds(r),the length of the secret key(b)in bytes,and the size of the block(L)in *** main feature of IRC6 is the variable number of working registers instead of just four registers as in RC6,resulting in a variable block size for plaintext and *** IRC6 cipher is designed to improve the robustness against attacks by increasing the diffusion for each round and providing greater security with fewer *** effectiveness of the proposed IRC6 scheme is verified against theoretical *** proposed IRC6 scheme depends on full diffusion and confusion mechanisms regardless of the utilized block *** proposed IRC6 scheme saves 70%of the encryption time and 64%of the decryption time of *** simulation results prove that the IRC6 achieves a better encryption/decryption time compared to the ***,the proposed IRC6 is anticipated to fulfill the market needs and system security requirements.

关键词： Cryptography block cipher RC6,IRC6,AES

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Augmented Reality for Public Engagement in Sustainable City Planning: Cloud and Machine Learning Integration

Augmented Reality for Public Engagement in Sustainable City ...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Sabitha, R. Gowriswari, S. Yuvaraj, S. Gayathri Devi, M. Babuji, R. Murugan, S. Rajalakshmi Engineering College Department Of Computer Science And Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department Of Instrumentation And Communication Engineering Tamil Nadu Chennai India Srm Institute Of Science And Technology Faculty Of Engineering And Technology Department Of Electronics And Communication Engineering Kattankulathur Tamil Nadu Chennai India Department Of Biomedical Engineering Tamil Nadu Rasipuram India R.M.K. Engineering College Department Of Electronics And Communication Engineering Tamil Nadu Chennai India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350371567

This paper explores how the convergence of augmented reality (AR), cloud computing, and machine learning might transform public engagement in sustainable city planning in today's dynamic urban environment. Citizens may experience proposed urban developments in unprecedented detail, including their possible social, environmental, and infrastructural impacts, due to the use of augmented reality. The potential for AR, cloud computing, and Support Vector Machines (SVM) to dramatically increase citizen participation in green urban design is investigated. With AR, individuals may explore potential new developments in virtual cityscapes. Intricate linkages within the dynamic dataset created during public participation are captured by the system's usage of SVM to evaluate and understand user comments. The ability of SVM to deal with non-linear patterns is crucial to gleaning useful insights from stakeholders' complex and varied contributions. In order to ensure that all parties involved in a system have access to the most up-to-date information, cloud computing plays a crucial role by enabling real-time collaboration and changes to the AR models This all-encompassing method not only improves the effectiveness of eco-friendly city planning, but also encourages openness and participation in policymaking. The suggested system represents a paradigm shift, demonstrating that innovative technology may be combined with informed citizenry to produce ecologically responsible and socially dynamic cities. © 2024 IEEE.

关键词： Support vector machines

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