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3rd International Conference on Technological Advancements in Computational sciences, ICTACS 2023

作者： Kumar, Jeetendra Gupta, Rashmi Kaur, Tejinder Atal Bihari Vaipayyee Vishwavidyalya Department of Computer Science and Application C.G. Bilaspur India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350342338

it then selects the node with the smallest distance and adds it to the set of visited nodes. The heuristic function estimates the distance between each node and the goal node, allowing the algorithm to explore nodes that are likely to lead to the goal node first.. Once the graph is constructed, you can apply Dijkstra algorithm. Traditional algorithms, such as Dijkstra and Floyd-War shall, have been used to solve this problem efficiently, but their performance can be affected by the complexity and size of the network. © 2023 IEEE.

关键词： genetic algorithm network optimization path finding shortest path problem

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Autonomous and Adaptive Communications Systems in Mobile Ad-Hoc Networks 5th

Autonomous and Adaptive Communications Systems in Mobile Ad-...

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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： J, Bhuvana Yadav, Dhyan Chandra Goyal, Manish Kumar Sharma, Himanshu Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Luckow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819780426

Protocols, enabling communication, manipulation, and coordination among cell nodes. Those techniques can efficiently use the community topology, connectivity, to-be-had assets, and consumer requirements to alter communication parameters and path selection for record transmissions robotically. Self-sufficient/adaptive systems also manage user requests and sensor measurements in real-time to dynamically regulate verbal exchange protocols and network configurations for higher verbal exchange performance. Furthermore, those structures also provide capabilities, including self-configuration, self-organization, fault-tolerance, and communique reliability. Various mechanisms may permit autonomous and adaptive verbal exchange in MANETs, including geo-vicinity-based total routing, location-established network coding, allotted garages, energy-conscious communication protocols, and allotted coordination techniques. Additionally, simulated annealing and particle swarm optimization can be used to optimize conversation and routing protocols. Self-sufficient and adaptive communications systems in cellular ad hoc networks have become a need in today’s international, as cell gadgets are used extra often and for more complex tasks. These structures are essential for preserving a clean float of verbal exchange without a centralized infrastructure or constant direction topologies. Self-reliant communications systems offer sturdy, self-configuring, self-healing, and self-organizing communication networks. Such structures are designed to constantly alter parameters primarily based on facts amassed from community resources and a person’s desired preference. Adaptive systems, on the other hand, dynamically create a superior topology by way of considering to-be-had assets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Simulated annealing

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An Evaluation of Interactive Communication Media Algorithms and Their Usage for Networking applications 5th

An Evaluation of Interactive Communication Media Algorithms ...

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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： Kudari, Jayashree M. Yadav, Rakesh Kumar Yadav, Surendra Kapse, Vinod Mansiram Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India Department of Electronics and Communication Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819780426

This paper evaluates using interactive conversation media algorithms inside the context of networking applications. Exceptional forms of algorithms are mentioned, which includes media movement algorithms, interactive conversation protocols, recording algorithms, and video compression protocols. The overall performance of those algorithms is classified and evaluated thru a quantitative analysis that includes measurements of common latency and packet loss. Additionally, the paper investigates using interactive communication media algorithms for one of kind programs together with video conferencing, on line gaming, and voice over IP offerings. Sooner or later, a contrast of various algorithms is made, with hints for the fine answers primarily based on the evaluated performance and application necessities.. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Video conferencing

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Optimizing Drug Dosage and Medication Management for Geriatric Patients with Artificial Neural Networks 3

Optimizing Drug Dosage and Medication Management for Geriatr...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Beemkumar, N. Singh, Daljeet Pal Ahmed, Zahid Faculty of Engineering and Technology Department of Mechanical Engineering Bagalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350343274

In this paper, we utilize ANNs to investigate how medicine dosing and management might be improved for the elderly population. The suggested strategy calls for the use of patient-specific data as inputs for the ANNs, such as age, renal and hepatic function, body mass index, and preexisting prescription profiles. The neural network model dynamically changes drug doses using the combination of the Multilayer Perceptron (MLP) algorithm, Backpropagation, and the Stochastic Gradient Descent (SGD) algorithm to maximize therapeutic benefits and reduce the likelihood of adverse drug events. The research highlights the improved accuracy, sensitivity, specificity, precision, and F1 score of the suggested technique compared to numerous conventional methods. As a result, the suggested system has great potential to revolutionize medication management for the elderly population since it is more personalized, flexible, patient-safe, effective, and efficient in its use of resources. © 2023 IEEE.

关键词： Optimization

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An Architecture of Enhanced EMG Signal Classification based on Multi-Agent System 3

An Architecture of Enhanced EMG Signal Classification based ...

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3rd International Conference on Intelligent engineering and Management, ICIEM 2022

作者： Jain, Reema Garg, Vijay Kumar Lovely Professional University Department of Computer Application Punjab Phagwara India Lovely Professional University Department of Computer Science and Engineering Punjab Phagwara India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

An Electromyography (EMG) signal provides reliable information and represents an important step towards man-machine communication to address neuro-muscular movements. The vital aspects of this research focus on data acquisition, signal pre-processing, feature extraction, and accurate classification to meet the practical challenges in terms of reliability. The recorded signals first undergo pre-processing in which the uploaded EMG signals are first segmented into clusters using K-means followed by a Genetic Algorithm (GA) that precisely extracts the rows that exhibit potential signal data. The multi-agent system is designed using a Support Vector Machine (SVM) with neural network architecture. This information of trained features deduced using SVM kernel function, also known as Support Vectors (SVs), is fed to Neural Network (NN) for the classification of EMG signals into two classes, namely, normal and pain. The performance of the proposed classification work is evaluated against the Electro- Myography-EMG dataset in terms of precision, sensitivity, f- measure, and accuracy. The simulation analysis over 1000 simulation rounds had demonstrated an average precision of 0.931, sensitivity of 0.915, f-measure of 0.923, and classification accuracy of 95.51%. The results illustrate a better classification accuracy when SVM support vectors are used by FFBPNN to learn the features of normal, and pain class in comparison to the existing EMG signal classification approaches. © 2022 IEEE.

关键词： Support vector machines

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Research on Virtual Synchronous Generator Control for Parallel Connection of Multiple Grid-Forming Energy Storage Converters 9

Research on Virtual Synchronous Generator Control for Parall...

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9th Asia Conference on Power and Electrical engineering, ACPEE 2024

作者： Chen, Guowei Yang, Bo Li, Haoyuan Wang, Hui Wang, Baonan Res. Center for Energy Storage Conversion and Application China Electric Power Research Institute Jiangsu Engineering Technology Nanjing China Shanghai University of Electric Power College of Computer Science and Technology Shanghai China

ISBN: (纸本)9798350309638

The parallel connection of converters facilitates the modularization of the operating system, making the internal structure of the system more flexible and variable. However, due to the low damping and low inertia characteristics of power electronic equipment, which may be certain risks when the energy storage system is connected to the power grid through a power conversion system. To address this issue, the control strategy based on virtual synchronous machine control technology for grid-forming energy storage converters is proposed, which can improve system inertia and damping. Secondly, the conduct research on the off grid control of grid type energy storage converters. Finally, the proposed control strategy was validated through simulation experiments. © 2024 IEEE.

关键词： Synchronous generators

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Kernel Based Fuzzy Simulation Model for Early Detection of Cancer to Avoid Metastasis 3

Kernel Based Fuzzy Simulation Model for Early Detection of C...

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3rd IEEE International Conference of Electron Devices Society Kolkata Chapter, EDKCON 2024

作者： Santra, Soumen Majumdar, Dipankar Mandal, Surajit Deyasi, Arpan Techno International New Town Department of Computer Application Kolkata India RCC Institute of information Technology Department of Computer Science and Engineering Kolkata India B. P. Poddar Institute of Management & Technology Department of Electronics and Communication Engineering Kolkata India RCC Institute of Information Technology Department of Electronics and Communication Engineering Kolkata India

ISBN: (纸本)9798350374643

In this paper, novel cancer detection method using Kernel Based Fuzzy Simulation Model (KBFSM) represented with enhanced accuracy of 12%, considering MRI based breast cancer images. Developed framework, as suggested in this paper, Effectiveness and superiority of the suggested approach are proven by thorough testing on a variety of datasets and thorough assessment metrics, highlighting its capacity to produce accurate and nuanced segmentation results. Fuzzification and defuzzification of images using Fuzzy C means algorithm, speaks in favor of the proposed analysis, as tested over several dataset, owing to minute pixel intensity modification when associated with malignant tissues. Result is supported by histogram analysis, which paves the way of future research in the field of lung cancer using the same technique. © 2024 IEEE.

关键词： Lung cancer

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On Road Vehicle Detection and Tracking in Various Weather Conditions

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Journal of The Institution of Engineers (India): Series B 2022年 1-10页

作者： Anandhalli, Mallikarjun Baligar, Pavana Baligar, Vishwanath P. Hiremath, Prakash S. Department of Electronics and Communication Engineering KLS Gogte Institute of Technology Belagavi Belagavi India Department of Information Science and Engineering Smt. Kamala and Sri Venkappa M. Agadi College of Engineering and Technology Laxmeshwar India Department of Computer Science and Engineering KLE Technological University Hubballi India Department of Master of Computer Application KLE Technological University Hubballi India

The paper aims in presenting distinctive pattern in identification of vehicles using basic and sequential algorithms. Vehicle detection and classification are crucial in traffic control and management decision-making. Vehicle characteristics are critical elements for identifying vehicles. For vehicle detection, the programmer additionally employs thresholds and corner detection techniques. This technique shall be used in order to extract the interest points from an image, while background subtraction method can remove unwanted points. Within a region of object, many corner points will be compacted, which is regarded an initial prerequisite. Thickly surrounded ends are clustered;which provides clue of points related to each vehicle, which is an important part in vehicle identification. The non-vehicle region is separated when the grouping is completed. The corner points are traced using the LK algorithm to ensure that they remain stable. A 93.95% success rate is achieved. © 2022, The Institution of Engineers (India).

关键词： Decision making

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Investigating Wireless Networks with Network Coding Algorithms 5th

Investigating Wireless Networks with Network Coding Algorith...

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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： Ahmed, Zahid Gupta, Anjali Preethi, D. Singh, Akhilendra Pratap Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Electrical and Electronic Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Community coding algorithms had been demonstrated to have capability to improve the performance of wireless networks. This paper offers a research, assessment, and implementation of community coding algorithms for Wi-Fi networks. The paper affords an overview of community coding algorithms and discusses the related blessings, drawbacks, and tradeoffs that have to be taken into account while evaluating the performance of these algorithms. Furthermore, simulation outcomes are offered to assess the overall performance of one of a kind network coding algorithms while implemented in a wireless community surroundings. Ultimately, the paper outlines the hardware and software elements required to correctly put into effect and test those algorithms in an operational wireless community. The promising consequences of the experiments imply that these community coding algorithms can be used to efficiently improve the overall performance of Wi-Fi networks within the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network coding

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A Statistical Review on Machine Learning Based Medical Diagnostic Systems for Chronic Kidney Disease 3

A Statistical Review on Machine Learning Based Medical Diagn...

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3rd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2022

作者： Sharma, Arvind Singh, Dalwinder Lovely Professional University Phagwara Department of Computer Application Punjab India Lovely Professional University Phagwara Department of Computer Science and Engineering Punjab India

ISBN: (数字)9781665453196

ISBN: (纸本)9781665453196

The decision making is a very challenging and complex process while doing the diagnosis of any specific illness. Huge ambiguities and problems are faced in the process of diagnosing by using the human visual system, which leads to conclusions that are inappropriate and unsuitable for a chronic kidney disease diagnosis. The employment of artificial intelligence approaches can overcome these limitations as these techniques help an expert doctor to offer precise and high-quality care to the patent suffering from CKD. Numerous publications enlighten the usage of machine learning methodologies along with its benefits, and the number of publications is elevated day by day. The primary focus of this study is to statistically review the various proposed and developed medical diagnostic systems for the diagnosis of chronic kidney disease using machine learning algorithms. The conducted review is categorized based on some criteria such as the objective of research work, its publication year, research gap and results obtained by researchers. © 2022 IEEE.

关键词： Expert systems

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