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

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

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IEEE International Symposium on Personal, Indoor and Mobile Radio communications (PIMRC)

作者： Selma Yahia Sylia Mekhmoukh Taleb Valeria Loscri Amylia Ait Saadi Tu Dac Ho Van Nhan Vo Hossien Eldeeb Sami Muhaidat Inria Lille-Nord Europe Lille France LIST Laboratory University of M’Hamed Bougara Boumerdes Algeria ESME Engineering School Ivry-sur-Seine France Department of Information Security and Communication Technology Norwegian University of Science and Technology Department of Electrical Engineering the Arctic University of Norway Faculty of Information Technology Duy Tan University Vietnam The Institute of Research and Development Duy Tan University Vietnam 6G Research Center Computer and Communication Engineering Khalifa University Abu Dhabi UAE

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

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 $\mathbf{1 5 \%}$ and $\mathbf{9 0} \mathbf{~ M b i t / s ~ i m p r o v e m e n t s ~}$ in coverage and sum rate, respectively.

关键词： Base stations Three-dimensional displays Closed-form solutions Chaotic communication Heuristic algorithms Wireless networks Autonomous aerial vehicles Reliability Vehicle dynamics Optimization

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Integrating Electronics for Enhanced Energy Management and Efficiency in Electric Vehicles

Integrating Electronics for Enhanced Energy Management and E...

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Automation and Computation (AUTOCOM), International Conference on

作者： Pratibha Sharma Alok Kumar Jena Shivam Khurana Srikantha H Tirumala Vasu Galithoti Awakash Mishra Centre for Interdisciplinary Research for Business and Technology Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Civil Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

The Integrating Electronics for More Suitable Energy Control and Performance in Electric Motors challenge aims to address the demanding situations of enhancing energy management and efficiency in electric cars. This assignment will make use of advanced electronics and manage engineering techniques to combine and optimize various components of electrical automobiles, which include the battery, motor, and powertrain. The important objective is to develop a complete and clever energy management system that can efficiently control and optimize the utilization and distribution of strength in electric-powered vehicles. The proposed gadget can be geared up with sensors and clever algorithms to monitor and analyze the power intake styles of the automobile in real time. These statistics will then be applied to dynamically alter the energy output of the motor and the electricity float from the battery, making sure green usage of strength and extending the riding variety of the automobile. In addition, the IEEME mission will focus on developing innovative solutions to enhance the overall performance of electrical automobiles. This consists of the combination of the regenerative braking era, which captures and converts the car's kinetic power into electrical strength, and the incorporation of lightweight materials to reduce strength intake. On average, the IEEME project targets to seriously decorate the strength management and performance of electric vehicles, making them more practical and value-effective for the mass market. This could contribute to decreasing dependency on fossil fuels and mitigating the terrible impacts of climate change.

关键词： Electric vehicles Real-time systems Sensor systems Batteries Sensors Kinetic theory Automobiles Consumer electronics Optimization Stress

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Quantum Resistance Group Key Management for IoTs

Quantum Resistance Group Key Management for IoTs

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Emerging Trends in Electrical, Control, and Telecommunication engineering (ETECTE), International Conference on

作者： Fouzia Samiullah Ming-Lee Gan Sedat Akleylek Yichiet Aun Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Kampar Perak Malaysia Centre and Department of Computer Engineering Cyber Security and Information Technologies Research and Development Ondokuz Mayis University Samsun Türkiye Chair of Security and Theoretical Computer Science University of Tartu Estonia

Group communication plays a vital role in our interconnected society, facilitating efficient and secure data exchange among multiple endpoints. The issue pertains to the intricate nature that emerges within the limited settings of the Internet of Things and sensor networks. GKM plays a crucial role in maintaining security in group communication schemes. Existing GKM schemes commonly rely on public-key cryptography, which may be susceptible to potential threats posed by quantum computers. This study investigated the usage of post-quantum GKM schemes in the realm of IoTs. To enhance communication security and efficiency in the era of quantum computing, we made significant progress in implementing a post-quantum GKM scheme. Specifically, we have chosen the SABER Key Encapsulation Mechanism, which is one of the four finalists in the National Institute for Standards and Technology (NIST) process. We also present preliminary simulation results for our scheme.

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Investigating The Potential of Self-Supervised Learning in Adversarial Machine Learning

Investigating The Potential of Self-Supervised Learning in A...

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Innovations in High Speed communication and Signal Processing (IHCSP), International Conference on

作者： Vivek Deshpande A. Sivanantham Ish Kapila Neelesh Singh Jeyalaxmi M Premkumar R Department of Computer Engineering Vishwakarma Institute of Technology Pune India Department of Mechanical Engineering Karpagam Academy of Higher Education Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India Department of S&H Prince Shri Venkateshwara Padmavathy Engineering College Chennai India School of Engineering and Technology Electronics and Communication Engineering JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

Machine learning has enabled innovative usage in numerous fields. These systems are vulnerable to hostile assaults. Small intentional alterations to misclassify data constitute a major security risk. We examine three solutions: "Self-Supervised Adversarial Defense," "Adversarial Mixup," and "Secure and Self-Supervised Learning." These strategies safeguard and protect machine learning models from other computers. We start our study with the theory underlying these approaches and how they are employed in machine learning. A detailed experimental evaluation utilizing a real-world dataset with difficult adversarial situations is shown. These approaches are tested using accuracy, precision, memory, F1 score, and ROC AUC. Results are certain. All indicators suggest that new methods outperform old ones. "Self-Supervised Adversarial Defense" is the most exact and precise, but "Adversarial Mixup" and "Secure and Self-Supervised Learning" are also useful, especially for memory. The ROC AUC values also demonstrate that the recommended approaches can distinguish positive and negative classes, which is crucial in binary classification problems. Finally, our work indicates that these strategies can make machine learning models safer and more resilient in harmful conditions. This study reveals how adversarial perturbations and self-supervised learning might solve the crucial challenge of adversarial assaults. These strategies can make machine learning systems safer, which might impact hacking, healthcare, and self-driving systems.

关键词： Technological innovation Accuracy Supervised learning Machine learning Self-supervised learning Medical services Signal processing computer crime Unsupervised learning Standards

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Classifying Eye Gaze Patterns of ASD And Typically Developing Children Using Convolutional Neural Network

Classifying Eye Gaze Patterns of ASD And Typically Developin...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Hemalatha S Shivam Khurana Premkumar R Pranali S. Kshirsagar S. Prabagaran Nitish Vashisht Department of EEE Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Engineering and Technology Electronics and Communication Engineering JAIN (Deemed to be University) Bangalore Karnataka India Computer Vishwakarma Institute of Technology Pune India Department of Mechanical Engineering Karpagam Academy of Higher Education Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

This research shows that utilising several datasets, autism spectrum disorder (ASD) may be detected at an early stage. The first of the many goals of this thesis is to describe how to use an eye tracking dataset in conjunction with convolutional neural network data to classify children as having autism. The Saliency4ASD Visual centre demonstration for ASD provided the eye tracking data that was acquired at IEEE ICME'19. For 300 pictures, the collection includes focus maps for kids with ASD and TD. It is possible to determine if an observer has ASD by looking at their fixation maps, which reveal the areas of the visual cortex that respond to certain stimuli. To achieve this goal, we will utilise Convolution Neural Networks (CNN) to detect whether an individual has autism spectrum disorder or normal development (TD) just by looking at their photograph. Autism is a neurological syndrome that is marked by difficulties in socialising, communicating through both verbal and nonverbal means, repetitive activity, not playing with others, varying degrees of sensitivity to more or less sensual motives, and a strict adherence to routine. Using the Eye Gaze Image dataset, the model demonstrates its great performance in distinguishing between instances of ASD and TD. This is shown by the model's high accuracy when it correctly identifies two true positives without producing any false positives. When applied to this specific scenario, it would seem that the model constantly generates categories that are the most suitable. With the best accuracy (92.8%), precision (93%), recall (95.6%), and F1 score (93%), the proposed model outperforms both CNN and RF, demonstrating its superior performance when comparing children who are normally developing (TD) to those who have autism spectrum disorder (ASD).

关键词： Radio frequency Autism Visualization Accuracy Sensitivity Convolution Gaze tracking Observers Feature extraction Convolutional neural networks

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Low-Cost Wearable Sensors for Continuous Measurement of Vital Signs in Resource-Limited Settings

Low-Cost Wearable Sensors for Continuous Measurement of Vita...

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Automation and Computation (AUTOCOM), International Conference on

作者： Jatin Khurana Dasarathy A K Gowri K Ankita Agarwal Sulabh Mahajan Abhijit Pal Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India Department of Civil Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Wearable or noninvasive sensors capable of measuring vital signs continuously can help narrow the resource gap in rarefied environments. The challenge for adoption, though, is the cost of traditional sensors and, in particular, the need for such infrastructure in these settings. To this end, the rapid development of inexpensive wearables allows continuous monitoring of vital signs such as heart rate, respiratory rate, blood oxygen saturation, and body temperature. The sensors are also lightweight, portable and non-invasive, making them useful for resource-limited settings that have limited access to medical technologies. Utilizing high-tech components like wireless communication and digital signal processing, the sensors provide fast, continuous, real-time monitoring of vital signs. They are easily operated and require little training. These sensors can wirelessly send the gathered data to smartphones or tablets, enabling healthcare workers to monitor patients remotely in real-time. This helps early identification of any unusual readings, allowing timely intervention. These low-cost, noninvasive sensors can compel a paradigm shift in healthcare delivery for resource-constrained settings. Their ability to monitor vital signs 24/7 without the time and expense of patient visits could save both lives and money at a fraction of the cost offered by traditional sensors. These can help us make an early diagnosis and intervention, thus improving the outcomes of patients. Such sensors may provide a solution for the healthcare disparity gap and achieve low-cost, accessible vital sign monitoring to target individuals who need it most.

关键词： Temperature sensors Training Temperature measurement Wireless communication Costs Surveillance Real-time systems Biomedical monitoring Wearable devices Wearable sensors

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The Role of Cyber-Physical Systems in Revolutionizing Transportation: From Connected Cars to Autonomous Vehicles

The Role of Cyber-Physical Systems in Revolutionizing Transp...

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Automation and Computation (AUTOCOM), International Conference on

作者： Anilloy Augustine Frank Trapty Agarwal Divya Sharma Arup Kumar Dutta Shikhar Gupta Aravindan M K Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Mechaical Engineering JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Cyber-physical systems have technologically advanced the transportation industry with their ability to connect physical systems with virtual functions. A cyber-physical system uses real-time data generation and communication technologies to make transportation systems safer, more efficient, more sustainable and more reliable. Connected cars are one of the primary use cases of CPS in transportation. They utilize sensors, cameras, and internet connectivity to capture information regarding road conditions, traffic patterns, and other drivers on the road. This information is then communicated to the backend system for analysis and decision-making to enhance safety or alleviate traffic congestion. It has also contributed towards developing independent vehicles. They employ ACH and CPS technologies to drive on roads driving without the need for human intervention. This could lead to a huge reduction in human error-related accidents and improve the efficiency of transportation. CPS also helps build smart transportation systems or link multiple modes of transport to escape congestion and reduce travel time. For example, it involves the integration of different modes of transportation, such as public transit, ride-sharing services and self-driving cars, to minimize travel time while maximizing usage. CPS has revolutionized the transport sector into a more connected, effective and secures system.

关键词： Technological innovation Connected vehicles Roads Transportation industry Transportation Cyber-physical systems Traffic control Smart transportation Traffic congestion Accidents

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Advanced Urban Air Quality Control and Management Using XM and RFE Models for Enhanced Predictive Analysis

Advanced Urban Air Quality Control and Management Using XM a...

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Mobile Networks and Wireless communications (ICMNWC), IEEE International Conference on

作者： Bolisetty Sreelatha V. Bhoopathy Saravanan B Tulasirao Vattikolla Deepak Asrani S. Kaliappan Department of Electronics and Communication Engineering Geethanjali College of Engineering and Technology Medchal India Department of CSE Sree Rama Engineering College Tirupati India Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore India Department of Englis Malla Reddy Engineering College (A) Hyderabad India School of Information Technology Institute of Management Studies Noida India Division of Research and Development Lovely Professional University Phagwara India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

Urban air pollution, particularly in large cities, has historically been exacerbated by construction activity, resulting in significant surges. Pollutants such as Sulphur dioxide and soot have, however, been significantly reduced in the industrialized Western world as a result of developments in abatement technologies. As a result, the attention has shifted to pollutants related with mobility, such as nitrogen oxides, organic compounds, and fine particulate matter. This work uses a machine learning approach to analyze urban air quality, with a focus on feature selection and data preparation. Data preprocessing, feature selection using Principal Component Analysis (PCA), and model training are all important steps. Normalization of Life Cycle Assessment (LCA) results was also added as a preprocessing step. The model had a maximum accuracy of 91.93% in categorizing and predicting urban air quality. This outcome was greatly influenced by the selection of important features using PCA and model refining by feature deletion. The findings highlight the efficacy of sophisticated machine learning approaches, specifically PCA and normalization, in improving air quality prediction models. The findings show that, while traditional pollutants have been significantly reduced, new concerns in urban air pollution necessitate specific solutions centered on transportation-related particles and other minute pollutants. This paper establishes a paradigm for better urban air quality management and emphasizes the value of adaptive approaches in environmental monitoring.

关键词： Life cycle assessment Training Analytical models Atmospheric measurements Atmospheric modeling Machine learning Predictive models Air pollution Pollution measurement Principal component analysis

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Analyzing the Efficiency of Cross-Layer Design for Location-Aware Ad Hoc Networks

Analyzing the Efficiency of Cross-Layer Design for Location-...

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International Conference on Computing and Networking Technology (ICCNT)

作者： S Srividhya Romil Jain K Preetham Vishal A. Meshram K. Yuvaraj Manpreet Singh Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Mangement-UG Management JAIN (Deemed to be University) Bangalore Karnataka Department of Computer Engineering Vishwakarma Institute of Technology Pune INDIA Department of Computer Science Karpagam Academy of Higher Education Coimbatore India Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This paper affords an evaluation of the performance of pass-layer design for region-aware advert hoc networks in phrases of mobility, node density, distributed monitoring, and network performance. First, a theoretical analysis of the longitudinal mobility of a cell ad hoc community is performed, and the effects of this analysis are confirmed through simulations. Then, the influence of node density on connectivity metrics is discussed, and it’s far observed that a boom in density can enhance global node connectivity. Similarly, distributed tracking of the network is evaluated with the aid of introducing the area your neighbor (LYN) metric, and the outcomes are in comparison with the prevailing distributed tracking procedures. Sooner or later, overall performance signs for advert hoc networks are examined in phrases of put off, throughput, and packet transport ratio, and the outcomes of the go-layer design are located to be higher than the conventional layered layout. The overall outcomes highlight the potential of pass-layer design for enhancing the performance of place-aware advert hoc networks.

关键词： Measurement Cross layer design Analytical models Scalability Microprocessors Layout computer architecture Throughput Ad hoc networks Monitoring

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The Potential of IoT and Sensor-Enabled Drones for Precision Agriculture and Crop Monitoring

The Potential of IoT and Sensor-Enabled Drones for Precision...

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Automation and Computation (AUTOCOM), International Conference on

作者： Gopalakrishna V Gaonkar Renuka Manish Bhagwat Trapty Agarwal Mridula Gupta Sankarsan Sahoo Bhavuk Samrat Department of Civil Engineering JAIN (Deemed to be University) School of Engineering and Technology Bangalore Karnataka India Department of Electronics and Communication Engineering Presidency University Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

They involve monitoring and analyzing daanalyzeeal-time, real-time farmers to derive key insights on their crops or soil at any given time. You install IoT sensors in several locations across the farm that measure temperature, humidity, soil moisture, etc. The telemetry is then transmitted to a central database or cloud platform for processing, storage, and analysis. A farmer can, in near real-time, for instance, decide to change the timing of irrigation based on measured soil moisture and how much water is required. Drones can also provide a high-level image of the farm using specialized cameras, sensors, and on-ground sensors. They are capable of taking high-defbig-bitmaps-big and sensing subtle changes. They can send the information to a cloud server where farmers can red-flag areas they feel might need attention so booms or sprayers addressing liquid dirt drenchers travel. Brparriti. Drones can also be used for crop spraying to minimize manual labor and increase efficiency. IoT and Sensor-Enabled Drones in Agriculture Crop Monitoring: There is a huge potential in using IoT & sensor-caped drones for precision agriculture and crop monitoring. They also have the potential to revolutionize farming techniques, making them more sustainable, efficient, and cheap. Large-scale data collection and analysis capabilities allow farmers to optimize yields through data-driven decision-making. Precision agriculture and crop monitoring Since farmers can make the best decisions based on real-time data, it is one of the most exciting IoT applications in the internet landscape. These technologies allow data about crops and soil levels to be instantaneously and analyzed quickly. IoT sensors can measure the temperature, humidity, soil moisture, and other parameters across farms. The data could then be sent to a central database or cloud for analysis and further decision-making based on the studies. Therefore, agriculture farmers can determine the optimal irrigation schedule based on

关键词： Temperature sensors Temperature measurement Precision agriculture Soil measurements Soil moisture Real-time systems Sensors Internet of Things Monitoring Drones

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