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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Dinesh, G. Pawar, Yogesh Shivaji Dinshi, P. Soundararajan, S. Husain, S. Syed Reddy, Ch. Venkata Krishna Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Tamil Nadu Chennai India Bhabha University Department of Electrical Engineering Madhya Pradesh Bhopal India Koneru Lakshmaiah Educational Foundation Department of Computer Science Engineering Andhra Pradesh Guntur India Velammal Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India K. Ramakrishnan College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Tiruchirappalli India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India

ISBN: (纸本)9781665474511

The term MANET stands for Mobile Ad hoc Network. MANET is a structure of wireless communication network that is combined with various nodes that are movable in various directions in the network. They are accompanied with the absence of infrastructure which helps the nodes to interconnect with the neighboring one in a random fashion. They are highly dynamic in nature. The internet of things device have the ability to communicate with the various heterogeneous networks. These IoT nodes helps to communicate with each other without the need of infrastructure. The cloud helps to store the data and tends to transmit through the nodes in the network. The secure data transmission includes the intrusion detection system, neglecting malicious attacks and selfish nodes in the network. The secure data transmission system without any constraints helps in the improvement of overall efficiency of the system. This is done through the machine learning accompanied with genetic algorithm. These biologically inspired algorithms helps to obtain exact optimum solutions helps to provide secure data transmission. © 2023 IEEE.

关键词： Internet of things

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Design of Approximate Multiplier Using Highly Compressed 5_2 Counter

Design of Approximate Multiplier Using Highly Compressed 5_2...

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Mobile computing and Sustainable Informatics (ICMCSI), International Conference on

作者： Bathlin Nelmin N R S Shaji Hariprasad S Sudeshna Shettygari Vasan J K Vijayan V Department of Electronics and Communication Engineering University College of Engineering Nagercoil India Department of Computer Science and Engineering St. Xavier's Catholic College of Engineering Nagercoil India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

Approximate computing effectively impacts low-power VLSI circuits by reducing circuit overhead. It introduces minimal error in the output, which does not significantly affect the application. This paper proposes an approximate multiplier constructed using 5_3 and 5_2 counters. The proposed 5_2 counter delivers two outputs instead of three, thereby achieving 60% compression. The overhead of the 5_2 counter circuit is reduced, achieving a power delay product (PDP) improvement of 18%. This reduction comes with an addition of an 6% error rate. The newly designed multiplier has less delay, where the Mean error distance (MED) is kept as low as possible. The complexity of the 5_2 counter is also reduced since the counter uses only a full adder and three gates. This is achieved by applying various error optimization mechanisms. The error parameters, (i) Error Distance (ED), and (ii) Mean Error Distance (MED) are analyzed and compared with existing works. The proposed multipliers are involved in image contrast application with better Peak Signal to Noise Ratio (PSNR) value.

关键词： Measurement PSNR Image coding Error compensation Very large scale integration Logic gates Delays Standards Optimization Mobile computing

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Automated Assignment Management System: Integrating Email Inbox Parsing, Database Updates, and Notification

Automated Assignment Management System: Integrating Email In...

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Advances in computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： P Varun R.S. Rashika S Kayalvizhi D Preetha P Naveen T A Mohanaprakash Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Department of CSE Panimalar Engineering College Chennai Department of Computer Science and Engineering Velammal Engineering College Department of Information Technology Alpha College of Engineering Department of Computational Intelligence SRM Institute of Science and Technology Kattankulathur Chennai Department of CSE School of Engineering & Technology CMR University Bengalunu Karnataka

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

This paper presents the design and implementation of an automated assignment management system utilizing a bot interface. The system’ s primary objective is to streamline the process of collecting and tracking student assignments, ensuring timely updates to a central database, and facilitating communication between students and teachers. The bot employs email inbox parsing techniques to identify incoming assignment submissions, extracting relevant data such as student names, assignment details, and submission timestamps. Upon receiving a submission, the bot updates an Excel database with the pertinent information, maintaining an organized record of completed ***, the system incorporates a notification feature to promptly alert students who have not yet submitted their assignments by the deadline. Leveraging email integration, the bot sends personalized notifications reminding students of impending deadlines and urging them to submit their work promptly. Additionally, the bot generates a list of incomplete assignments and forwards it to the respective teacher, providing a consolidated overview of students who require *** automating the assignment management process, this system reduces manual intervention, minimizes administrative burden, and enhances efficiency in monitoring student progress. The integration of email parsing, database updates, and notification functionalities ensures seamless communication and facilitates timely submission of assignments, contributing to improved academic outcomes and instructor-student engagement

关键词： Automation Databases Manuals Chatbots Feature extraction Data mining Informatics

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Integrating Instruction-based Learning with Bidirectional LSTM for Autonomous Vehicle Pedestrian Detection

Integrating Instruction-based Learning with Bidirectional LS...

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Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： B Shoba T Raghunathan S.Sam Peter Karthick K Akshya. J M. Sundarrajan Mani Deepak Choudhry Department of Electronics and Communication Engineering PSN College of Engineering and Technology Tirunelveli Department of Artificial Intelligence and Data Science Dr.NG.p.Institute of Technology Coimbatore Department of Computer Science and Engineering Sri Krishna College of Technology Coimbatore Department of Information Technology Sona College of Technology Salem Department of Computational Intelligence SRM Institute of Science and Technology Chennai Department of Networking and Communications SRM Institute of Science and Technology Chennai Department of Computing Technologies SRM Institute of Science and Technology Chennai

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

Pedestrian detection is a crucial aspect of autonomous vehicle (A V) safety, as it enables accurate identification and tracking of individuals in an A V environment. Effective pedestrian detection supports essential A V functions like braking, steering, and speed control to prevent accidents in urban settings. Traditional computer vision methods, such as Support Vector Machines and Random Forests, rely on pre-designed features like the Histogram of Oriented Gradients. While the existing techniques offer some performance, it face significant challenges in dynamic environments, especially under varying lighting conditions, occlusions, and diverse pedestrian poses. Traditional models also require extensive manual feature engineering and tuning, which limits scalability and adaptability. Recent advances in deep learning, particularly with Convolutional Neural Networks (CNNs), have allowed for automatic feature learning, yielding practical improvements over classical methods. However, CNNs can struggle in low light and when facing adversarial attacks, as they mainly capture spatial features. To address these limitations, this research proposes a new methodology combining CNNs for spatial feature extraction with Bidirectional Long Short-Term Memory (BiLSTM) networks to capture temporal dependencies. This hybrid approach enhances detection capabilities by learning both static and dynamic patterns. Our proposed CNN-BiLSTM model achieves a 92 % detection accuracy and an F1 score of 88.5% across diverse conditions, outperforming existing models by up to 15%. By integrating temporal features, the model reduces missed detections and false positives by up to 20%, providing a more reliable and adaptable solution for pedestrian detection in autonomous vehicles.

关键词： Adaptation models Pedestrians Heuristic algorithms Feature extraction Real-time systems Vehicle dynamics Collision avoidance Autonomous vehicles Optimization Logistics

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Detecting and Exploiting Unit Commitment Structures in MIPs 6

Detecting and Exploiting Unit Commitment Structures in MIPs

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6th International Conference on Power and Energy technology, ICPET 2024

作者： Su, Zhao-Gang Chen, Sheng-Jie Li, Yu-Fei Chen, Liang Kou, Caixia Cai, Zhi Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Institute of Applied Mathematics Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China College of Sciences Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (纸本)9798350375855

The unit commitment (UC) problem has been extensively researched in the literature, which is typically formulated as a mixed integer programming (MIP) problem. However, current studies lack effective methods to identify potential UC problem structures within a general MIP problem, making it challenging to leverage well-established valid inequalities for UC problems to accelerate the solution process. In this paper, we present a novel detection method that automatically identifies UC structures within an MIP problem by analyzing the relationships between variables and constraints. Moreover, we enhance the MIP formulation by incorporating three well-studied classes of valid inequalities as cutting planes, based on the identified UC structures. Our experiments demonstrate that our proposed UC detection method greatly improves computational efficacy of a standard MIP solver compared to the default setting. © 2024 IEEE.

关键词： Mixed-integer linear programming

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Multi-Agent Coordination of Autonomous Vehicles for Smart Logistics in Industrial Environments

Multi-Agent Coordination of Autonomous Vehicles for Smart Lo...

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International Conference on System Modeling & Advancement in Research Trends (SMART)

作者： Kirubhakaran D. Karthikeswaran M. Arun R. Arun Chakravarthy J. Akshya M. Sundarrajan Mani Deepak Choudhry Department of Computer Science and Engineering Surya Engineering College Erode Department of Artificial Intelligence and Data Science Nehru Institute of Engineering and Technology Coimbatore Department of Electronics and Communication Engineering KGiSL Institute of Technology Coimbatore Department of Computational Intelligence SRM Institute of Science and Technology Chennai Department of Networking and Communications SRM Institute of Science and Technology Chennai Department of Computing Technologies SRM Institute of Science and Technology Chennai

ISBN: (数字)9798350380583

ISBN: (纸本)9798350380590

Dynamic effects in industrial logistics demand more creative solutions towards the pursuit of efficiency and agility in evolving environments. Though static path-planning and taskallocation algorithms have provided the basis for how autonomous vehicles are guided within structured environments, those approaches usually fail to contend with indeterminacy outside of their modelled world, where there is dynamic obstacle appearance and changing task requirements, thus raising inefficiencies and costs of operations. To address these issues, the paper introduces a new multi-agent coordination system that uses a hybrid A* algorithm, integrating path planning with sophisticated detection methods for dynamic obstacles and improving superior task allocation. The system is supposed to provide improvements in real-time coordination in industries of autonomous vehicles to achieve efficient management of tasks and paths in changing environments. We integrate the latest in machine learning techniques for improved and real-time updates within the changes of the vehicle routing process based on both immediate sensory input and environmental interactions. Simulations show that our system performs the task much faster than classic systems: up to 30% improvement in completing tasks compared with classic models, and an average improvement of 25% in allround energy efficiency. It intelligently integrates machine learning techniques with real-time data processing. With the ability to scale up or down, or to adapt itself, this system addresses the chief challenges existing methods face and could revolutionize logistics operations within any industry.

关键词： Industries Adaptation models Heuristic algorithms Real-time systems Path planning Vehicle dynamics Collision avoidance Autonomous vehicles Optimization Logistics

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Implementing Asynchronous Jacobi Iteration on GPUs

Implementing Asynchronous Jacobi Iteration on GPUs

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Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA)

作者： Yu-Hsiang Mike Tsai Pratik Nayak Edmond Chow Hartwig Anzt Steinbuch Centre for Computing Karlsruhe Institute of Technology School of Computational Science and Engineering Georgia Institute of Technology Innovative Computing Laboratory University of Tennessee

ISBN: (纸本)9781665475716

Computation on architectures that feature fine-grained parallelism requires algorithms that overcome load imbalance, inefficient memory access, serialization, and excessive synchronization. In this paper, we explore an algorithm for iteratively solving systems of linear equations that allows for asynchronous updates by different execution units and completely removes the need for synchronization. Methods of this type have been identified as potentially competitive for computations on Exascale machines, but practical implementations for GPU platforms have scarcely been studied. We present an asynchronous Jacobi iteration optimized for high-end GPUs, demonstrate the superiority of the algorithm over a highly tuned synchronous Jacobi iteration, and deploy the algorithm as production-ready implementation in the Ginkgo open source library. The ideas presented here on the algorithm design, implementation and performance can help guide the design of other asynchronous iterative methods on GPUs.

关键词： Jacobian matrices Schedules Runtime Three-dimensional displays Software algorithms Graphics processing units Parallel processing

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Incorporating 5G NR Sidelink with MQTT to Maximize Energy Efficiency in IoT-Enabled Microgrids

Incorporating 5G NR Sidelink with MQTT to Maximize Energy Ef...

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Smart Power Control and Renewable Energy (ICSPCRE), IEEE International Conference on

作者： G Neelamegam Hermina JM Ashforn Mohamed S Raja J. Priyadharshini J Akshya Mani Deepak Choudhry M. Sundarrajan Department of Computer Science and Engineering VSB College of Engineering and Technology Coimbatore Department of Artificial Intelligence and Data Science Bannari Amman Institute of Technology Erode Department of Computer Science and Engineering Kalaignarkarunanidhi Institute of Technology Coimbatore Department of Information Technology K. Ramakrishnan College of Engineering Trichy Department of Computational Intelligence SRM Institute of Science and Technology Chennai Department of Computing Technologies SRM Institute of Science and Technology Chennai Department of Networking and Communications SRM Institute of Science and Technology Chennai

ISBN: (数字)9798350377002

ISBN: (纸本)9798350377019

IoT for smart microgrids is an innovative disruption at the cutting edge of energy management, relying on interconnectedness provided by smart sensors and devices to enhance power generation and distribution precision in metropolitan areas. The problems of the real-time operational capabilities required for efficient energy resource management thus progress, inhibit rapid control and management. The main goal of this research proposal consists of to use of the advanced technology of 5G NR Sidelink combined with MQTT to conduct a revolutionary communication system of Microgrid running through the IoT devices. The 5G NR (New Radio) Sidelink enables direct D2D communication, which leads to a dramatic lowering of the latency in the absence of traditional network infrastructures for communication, while the MQTT protocol improves the communication efficiency among networks of numerous IoT devices. The introduction of this system was followed by a 15% decrease in energy transmission losses and by 20% improvement in response times in comparison to conventional models specified in the quantitative evaluation thus increasing operational efficiency by far. These efficiencies not only reduce operating expenses and power consumption but also increase the solution's scalability, pointing out the possibility of building the solution for bigger urban microgrid implementations. In consideration of that, the suggested mechanism with 5G NR Sidelink along with MQTT overcomes elaborate barriers of IoT-based microgrids and establishes a new potency in advanced energy management in smart cities which could make the distribution network in the urban areas on the edge of the verge of a change.

关键词： Renewable energy sources 5G mobile communication Scalability Microgrids Sidelink Propagation losses Smart grids

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MediGuard:A Survey on Security Attacks in Blockchain-IoT Ecosystems for e-Healthcare Applications

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Computers, Materials & Continua 2025年第6期83卷 3975-4029页

作者： Shrabani Sutradhar Rajesh Bose Sudipta Majumder Arfat Ahmad Khan Sandip Roy Fasee Ullah Deepak Prashar Institute of Engineering and Technology Dibrugarh UniversityDibrugarh786004AssamIndia Departments of Computational Sciences Brainware UniversityKolkata700125West BengalIndia Department of Computer Science&Engineering JIS UniversityKolkata700109West BengalIndia Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand Department of Computer and Information Sciences Universiti Teknologi PETRONASSeri Iskandar32610Perak Darul RidzuanMalaysia Department of Computer Science and Engineering(CSE) Lovely Professional UniversityPhagwara144411PunjabIndia Jadara University Research Center Jadara UniversityIrbid21110Jordan

Cloud-based setups are intertwined with the Internet of Things and advanced,and technologies such as blockchain revolutionize conventional healthcare *** digitization has major advantages,mainly enhancing the security barriers of the green tree *** this study,we conducted a systematic review of over 150 articles that focused exclusively on blockchain-based healthcare systems,security vulnerabilities,cyberattacks,and system *** addition,we considered several solutions proposed by thousands of researchers *** results mostly delineate sustained threats and security concerns in blockchain-based medical health infrastructures for data management,transmission,and ***,we describe 17 security threats that violate the privacy and data integrity of a system,over 21 cyber-attacks on security and QoS,and some system implementation problems such as node compromise,scalability,efficiency,regulatory issues,computation speed,and power *** propose a multi-layered architecture for the future healthcare ***,we classify all threats and security concerns based on these layers and assess suggested solutions in terms of these *** thorough theoretical examination of several performance criteria—including confidentiality,access control,interoperability problems,and energy efficiency—as well as mathematical verifications establishes the superiority of security,privacy maintenance,reliability,and efficiency over conventional *** conducted in-depth comparative studies on different interoperability parameters in the blockchain *** research justifies the use of various positive protocols and optimization methods to improve the quality of services in e-healthcare and overcome problems arising fromlaws and *** the theoretical aspects,their scope,and future expectations encourages us to design reliable,secure,and privacy-preserving systems.

关键词： Blockchain internet of medical things cloud infrastructure cyber-attacks privacy issues

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Improved Red Deer Algorithm for Scientific Workflow Scheduling in Cloud Environment 5

Improved Red Deer Algorithm for Scientific Workflow Scheduli...

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5th International Conference on Inventive Research in computing Applications, ICIRCA 2023

作者： Venkata Srinivas, Chandra Mouli Rena, Hajiyeva Arunarani, A.R. Naitik, S.T. Al Ansari, Mohammed Saleh Younas, Ammar Bonam Venkata Chalamayya Engineering College Andhra Pradesh Odalarevu India Azerbaijan Western Caspian University Department of Information Technologies Azerbaijan School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department of Computational Intelligence Tamilnadu Chennai India Dayananda Sagar University Cse Department Karnataka Bangalore India College of Engineering University of Bahrain Department of Chemical Engineering Bahrain Tashkent State University of Law Department of Business Law Uzbekistan

ISBN: (纸本)9798350321425

One of the most difficult problems in the technological sector is the versatility of cloud computing, which can offer a flexible and responsive infrastructure in the realm of information technology. A significant problem in cloud computing that is addressed in recent research is workflow scheduling. With the quick advancement of cloud computing, scheduling the intricate scientific process on the cloud has grown to be an incredibly difficult task. It has been identified that one of the key challenges to optimizing the performance of cloud computing is scheduling workflow tasks so that it is processed by the most effective cloud network resources. Meta-heuristic optimization algorithms are frequently utilized to find a solution to effective task scheduling because of the intricacy of the problem and the extent of the search space. This research suggests a unique Improved Red Deer Algorithm (IRDA) to shorten execution time subject to a set budget. The performance of the proposed algorithm is evaluated against conventional optimization algorithms by applying it to scientific workflows including Montage and Epigenomics. The experimental results reveal that the proposed algorithm works better than other compared methods in reducing workflow task execution time and cost. © 2023 IEEE.

关键词： Cloud computing

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