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2nd IEEE Virtual Conference on communications, VCC 2024

作者： Koutsonas, Evangelos Boulogeorgos, Alexandros-Apostolos A. Trevlakis, Stylianos E. Ali, Tanweer Tsiftis, Theodoros A. University of Western Macedonia Department of Electrical and Computer Engineering Kozani50100 Greece InnoCube P.C. Research and Development Department Thessaloniki55535 Greece Manipal Institute of Technology Manipal Academy of Higher Education Department of Electronics and Communication Engineering Manipal576104 India University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China

ISBN: (纸本)9798331530099

While the wireless word moves towards higher frequency bands, new challenges arises, due to the inherent characteristics of the transmission links, such as high path and penetration losses. Penetration losses causes blockages that in turn can significantly reduce the signal strength at the receiver. Most published contributions consider a binary blockage stage, i.e. either fully blocked or blockage-free links. However, in realistic scenarios, a link can be partially blocked. Motivated by this, in this paper, we present two low-complexity models that are based on tight approximations and accommodates the impact of partial blockage in high-frequency links. To demonstrate the applicability of the derived framework, we present closed-form expressions for the outage probability for the case in which the distance between the center of the receiver plane and the blocker's shadow center follow uniform distribution. Numerical results verify the derived framework and reveal how the transmission parameters affect blockage. © 2024 IEEE.

关键词： Blockage high-frequency communications modeling outage probability

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Framework for Ship Trajectory Forecasting Based on Linear Stationary Models Using Automatic Identification System

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Procedia computer Science 2023年 218卷 1463-1474页

作者： Smita Srivastava Lovneet Kumar R. Jeyanthi K. Deepa Vinay Aggrawal Department of Computer Science and Engineering Centre for Artificial Intelligence and Robotics Defense Research and Development Organization Bangalore Karnataka Department of Electronics and Communication Engineering Department of Electrical and Electronics Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India

Maritime surveillance is of utmost priority for a nation's security, and hence it's economy. For maritime awareness, coastal surveillance, and maritime activities in the Region of Interest (ROI) should be monitored. One of the ways to keep this in check is to restrain unwanted infiltration. Monitoring unwanted infiltration is feasible through vessel trajectory forecasting and anomaly detection in real time. Most solutions for trajectory predictions are available but require a huge amount of historical data, and high-power computing resources. Here, the requirement is developing a decision support framework consisting of both lite weight approaches for short-term predictions and deep learning-based techniques for long-term forecasting. This paper aims to find the suitability of Linear Stationary Models (LSM) like the Auto-Regressive Integrated Moving Average Model (ARIMA) for predicting and forecasting the Vessel Trajectory as means of lite weight short-term predictions. For this purpose, the Automatic Identification System (AIS) dataset of the U.S. West Coast is used. The significant effort was for data pre-processing to create a robust dataset for model training. An appropriate model after the model-selection process is used for trajectory forecasting. The model's accuracy is validated using Root Mean Square Error (RMSE) performance indices for residual and forecast errors. A window generator model is integrated with the best-fitted ARIMA model for recursive real-time predictions, with varied sizes and visualization. The proposed time-series model provided a very high accuracy as the RMSE value for prediction and 48 hours forecast are 0.023 and 0.017, respectively.

关键词： Maritime Surveillance Trajectory Forecast Time Series Analysis Auto-Regressive Integrated Moving Average Model Automatic Identification System Window Generator

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An Innovative Way of Empirical Analysis of Various Structures used in DL Algorithms for the Better Practices 4

An Innovative Way of Empirical Analysis of Various Structure...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Kumar, Himanshu Jasim, Laith Gehlot, Anita Devi, Guntoju Kalpana Yadav, Kanchan Kumar, Neelam Sanjeev Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India The Islamic University Najaf Iraq Uttaranchal Institute of Technology Uttaranchal University Department of Electronics & Communication Engineering Dehradun248007 India Cmr Technical Campus Department of Cse Telangana Hyderabad India Gla University Department of Electrical Engineering Mathura India Srm Institute of Science & Technology Department of Computer Science & Engineering Chennai Vadapalani26 India

ISBN: (纸本)9798350360165

The importance of deep learning is growing with artificial intelligence. It operates quickly. Entangled nerve fibres (CNNs), a well-known deep learning method, have shown impressive results in painting, classification, and semantic division. The actuator function-a crucial part of CNNs -was looked at in the context of low velocities in this book study, engineering Vehicle Rear System Programme. The text begins with a comprehensive analysis of all four conventional activation functions, including the well recognised sigmoid function, and a summary of their respective benefits. It then discusses the potential benefits. Swish, FTS, and Relu- are the three new operating systems that are offered with SoftPlus. The research then includes a combination of new activators and extra activation functions. It operates at the TensorFlow framework level. On the CIFAR-10 dataset, more image recognition comparisons are carried out. According to the results, using a combination of novel activation functions produces better recognition accuracy than using just one new activation function. Moreover, the hybrid technique shows higher convergence speeds and shorter average processing times, indicating its effectiveness in real-world applications. © 2024 IEEE.

关键词： Deep learning

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Application-Specific Image and Video Processing Techniques for Security and Surveillance 15

Application-Specific Image and Video Processing Techniques f...

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

作者： Kalanandhini, G. Sidhu, Amritpal Malathi, H. Dedgaonkar, Suruchi G. Singh, K. Ranjith Rampal, Sourav Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh 174103 India Karnataka Bangalore India Department of Information Technology Vishwakarma Institute of Technology Pune India Department of Computer Science Karpagam Academy of Higher Education Coimbatore641021 India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India

ISBN: (纸本)9798350370249

Utility-particular photo and video processing strategies for protection and surveillance are a set of algorithms and techniques used to procedure and examine pictures and motion pictures captured by protection and surveillance systems. These techniques are used to discover and understand items and identify suspicious activities and music-shifting objects in actual time. Common strategies include motion detection, item recognition, facial recognition, item monitoring, and anomaly detection. Those strategies are used to enhance the accuracy and efficiency of security and surveillance structures and to provide extra dependable and relaxed monitoring. ©2024 IEEE.

关键词： Video signal processing

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AI-Enhanced Multi-Cloud Security Management: Ensuring Robust Cybersecurity in Hybrid Cloud Environments

AI-Enhanced Multi-Cloud Security Management: Ensuring Robust...

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2023 International Conference on Innovative Computing, Intelligent communication and Smart Electrical Systems, ICSES 2023

作者： Srimathi, J. Kanagasabapathi, K. Mahajan, Kirti Ahamad, Shahanawaj Soumya, E. Barthwal, Shivangi KPR College of Arts Science and Research Department of Information Technology Covai Arasur641407 India Karpagam College of Engineering Computer Science and Technology Coimbatore India Bharati Vidyapeeth Deemed University Institute of Management & Entrepreneurship Development Department of Information Technology Pune411030 India University of Hail College of Computer Science and Engineering Department of Software Engineering Hail City Saudi Arabia St. Martins Engineering College Department of Computer Science and Engineering Telangana Secunderabad India Graphic Era Deemed to Be University Department of Electronics & Communication Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350319200

The complex landscape of multi-cloud settings is the result of the fast growth of cloud computing and the ever-changing needs of contemporary organizations. Strong cyber defenses are of fundamental importance in this setting. In this study, we investigate the use of AI in hybrid cloud settings for the purpose of multi-cloud security management. To help businesses improve their productivity and resilience, we provide a mathematical model for optimal resource allocation. Our methodology streamlines dynamic threat assessments, making it easier for security teams to efficiently priorities vulnerabilities. The advent of a new age of real-time threat response is heralded by the incorporation of AI-driven security tactics. The technique we use has real-world implications that may help businesses stay ahead of constantly changing threats. In the future, scientists will focus on autonomous security systems, interoperability, ethics, interoperability, and cutting-edge AI models that have been validated in the real world. This study provides a detailed road map for businesses to follow as they navigate the complex cybersecurity landscape of multi-cloud settings, therefore promoting resilience and agility in this era of digital transformation. © 2023 IEEE.

关键词： Adaptive Security Systems Artificial Intelligence Autonomous Security Cybersecurity Hybrid Cloud Multi-Cloud Security Quantum Computing Real-Time Threat Response Threat Assessment

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A Novel Optimized Deep Learning Model for Canola Crop Yield Prediction on Edge Devices

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2024年第2期2卷 436-444页

作者： Valarezo-Plaza, Stephany Torres-Tello, Julio Singh, Keshav Shirtliffe, Steve Deivalakshmi, S. Ko, Seok-Bum University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonSKS7N 5A9 Canada Agriculture and Agri Food Canada in Lethbridge Lethbridge Research and Development Centre LethbridgeABT1J 4B1 Canada University of Saskatchewan Department of Plant Sciences SaskatoonSKS7N 5A9 Canada National Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Tiruchirappalli620015 India

The escalating global demand for food, coupled with challenges in sustaining crop production, deteriorating ocean health, and depleting natural resources, underscores the critical role of agricultural technology. This article addresses the imperative of developing an optimal deep-learning model for predicting canola crop yield using hyperspectral images captured by drone flights. Our primary objective is to identify the most efficient model in terms of performance and size, considering the storage limitations on edge devices like Raspberry Pi 4 (RPi4). We start with the baseline 1D_CNN model, which achieves an R2 score of 0.82, and compress it into the proposed fs_model (fp32). To achieve the compression, we apply pruning through sparsity and feature selection using SHAP values. Further reduction in model size is accomplished by quantizing the weights of the proposed model to a lower precision, such as int16. This combined approach substantially decreases the proposed model's size by approximately 92.6% and inference time by approximately ×9013 in comparison to the baseline 1D_CNN model. In addition, we propose the novel fsp_model posit(8,3) that uses posit quantization to further reduce the computation requirements compared to the proposed fs_model (int16). Our findings indicate that the utilization of posit numbers enables us to shrink the model size to 94% of the original base model, while only reducing the R2 score by 5.7%. © 2024 IEEE.

关键词： Hyperspectral imaging

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Optimizing Shielding Techniques for High-Frequency EMC Applications in Aerospace Systems 15

Optimizing Shielding Techniques for High-Frequency EMC Appli...

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

作者： Mahalle, Parikshit N. Kalanandhini, G. Hemelatha, S. Samrat, Bhavuk Mishra, Mukul Ramachandran, T. Department of Artificial Intelligence & Data Science Vishwakarma Institute of Technology Pune India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore641021 India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh 174103 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140417 India Karnataka Bangalore India

ISBN: (纸本)9798350370249

The defense of high-frequency electromagnetic compatibility (EMC) for aerospace systems is important to ensure the functionality and reliability of aerospace cars. Moreover, the performance of the system has to follow each plane's requirements and electromagnetic regulations, such as Federal Aviation Administration (FAA) regulations, to hold protection and trustworthiness. While protecting excessive-frequency EMC application is only sometimes taken into consideration, the electrical gadgets, wiring, and numerous components may be electrically laid low with electrical fields, resulting in malfunction of the machine, mistakes in calculations, and faulty indicators. This paper evaluates the optimization of protective techniques for high-frequency EMC packages in aerospace systems through the usage of a mixture of simulation and size strategies. The objectives of the look are to expand an efficient shielding structure and optimize the design to reduce the reflection of electromagnetic wave radiation in the system. A two-layered shielding method with an internal shield of aluminum foil is used to reduce the reflection of electromagnetic wave radiation. Furthermore, the field studies and the simulations executed permit the optimization of the measurements to be greater than it should be predicted. The obtained results imply that the optimized defensive approach makes a good sized enhancement in the defensive overall performance of the device, thereby disposing of errors due to outside EMC resources. ©2024 IEEE.

关键词： Electromagnetic wave reflection

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Dynamic 3D UAV Placement Optimization: Improved Bonobo Optimizer for Enhanced Coverage and communication 35

Dynamic 3D UAV Placement Optimization: Improved Bonobo Optim...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio communications, PIMRC 2024

作者： Yahia, Selma Taleb, Sylia Mekhmoukh Loscri, Valeria Saadi, Amylia Ait Ho, Tu Dac Vo, Van Nhan Eldeeb, Hossien Muhaidat, Sami Inria Lille-Nord Europe Lille 59000 France University of m'Hamed Bougara List Laboratory Boumerdes35000 Algeria Esme Engineering School Ivry-sur-Seine94200 France Norwegian University of Science and Technology Department of Information Security and Communication Technology Norway The Arctic University of Norway Department of Electrical Engineering Norway Duy Tan University Faculty of Information Technology Viet Nam Duy Tan University The Institute of Research and Development Viet Nam Khalifa University 6G Research Center Computer and Communication Engineering Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350362244

Unmanned aerial vehicles (UAVs) offer a promising solution for enhancing network coverage, reliability, and data speed in future wireless network generations. However, deploying UAVs as aerial base stations requires careful consideration of crucial design factors, including three-dimensional (3D) placement and performance optimization tailored to specific applications. In this paper, the 3D placement of multiple UAVs, acting as aerial base stations, is investigated in a dynamic user scenario. First, a closed-form expression for the coverage probability is derived. Then, to maximize the network coverage and sum rate while ensuring reliable and energy efficient system, a joint multi-objective optimization problem is formulated considering the real-time user movements. To solve the problem, an improved Chaos-based Bonobo Optimizer (CBO) scheme is proposed which combines chaotic maps with the Bonobo Optimizer (BO) algorithm. The obtained results demonstrate the superior performance of the proposed approach compared with different benchmark algorithms. The results reveal that the proposed CBO algorithm offers a minimum of 1 5 % and 9 0 ~ M b i t / s ~ i m p r o v e m e n t s ~ in coverage and sum rate, respectively. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Routing Protocols in Wireless Body Area Networks: Architecture, Challenges, and Classification

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Wireless communications and Mobile Computing 2023年第1期2023卷

作者： Goyal, Reema Mittal, Nitin Gupta, Lipika Surana, Amit Department of Computer Science and Engineering Chandigarh University Mohali India University Centre for Research and Development Chandigarh University Mohali India Department of Electronics and Communication Engineering Chitkara University Punjab 140401 India Department of Electronics and Communication Eastern College of Engineering Biratnagar Nepal

The wireless body area network (WBAN) is a branch of the wireless sensor network (WSN) intended for tracking essential patients' physiological signals and transferring this knowledge to the coordinator. During the routing of data, WBANs encounter critical routing problems like WSNs. Moreover, the particular constraints of WBANs make it more challenging that they need to be addressed. This survey article categorizes and briefly analyzes a range of current routing methods utilized in WBANs. The routing protocol is essential to the creation of any efficient and reliable wireless body area network due to a limited size of battery in the body sensor nodes. A comparison study of numerous routing protocols has been made in this paper, which is helpful in selecting the optimal routing protocol for the application being targeted. The article describes the WBAN architecture and addresses numerous challenges in the context of successful WBAN routing. In this paper, several existing WBAN routing methods are presented which are influenced by network structure, energy, quality of service (QoS), node temperature, human position, node transmission range, and other factors. The protocols, including cross-layered, cluster-based, QoS-aware, postural movement-based, temperature-aware, postural movement-based, and routing protocols, are given in an expressive taxonomy. Different routing protocols that have already been developed for WBANs are compared with more advanced protocols. The pros and cons of each protocol are looked at based on factors like delay, packet delivery ratio, and energy use. The researchers can utilize this survey paper as a reference for studying various routing protocols particularly in the medical and healthcare systems. © 2023 Reema Goyal et al.

关键词： Routing protocols

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Dynamic Spectrum Access in Cognitive Radio Networks: A Game-Theoretic Approach 15

Dynamic Spectrum Access in Cognitive Radio Networks: A Game-...

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

作者： Dhabliya, Dharmesh Vigenesh, M. Minhas, Deepak Shalini, M. Das, Sidhant Renukajyothi, S. Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore641021 India Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India School of Sciences Department of Biotechnology and Genetics Karnataka Bangalore India

ISBN: (纸本)9798350370249

Cognitive radio networks (CRNs) are a promising technology which could offer better spectrum efficiency and utilization via permitting dynamic spectrum get right of entry to (DSA). Game idea has been an increasing number of hired as a tool for analyzing and addressing optimization problems in CRNs. This abstract discusses the utility of sport theory to the evaluation and optimization of DSA in CRNs. the main consciousness is to broaden a widespread recreation-theoretic approach for DSA that can model numerous styles of interactions among cognitive customers. Specifically, we speak 8 exceptional styles of games that may be used to model the DSA problem, including static, dynamic, and multi-attribute games. Moreover, we speak 3 critical DSA optimization issues: spectrum allocation, spectrum sharing, and energy manipulate. Sooner or later, we speak a few crucial challenges and possibilities for similarly research in this place. Using game principle for DSA in CRNs can assist to enhance the performance of CRNs in terms of throughput, fairness, energy efficiency, and security. © 2024 IEEE.

关键词： Cognitive radio

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