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3rd international conference on Microelectronic Devices, Circuits and systems. ICMDCS 2022

3rd International Conference on Microelectronic Devices, Cir...

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3rd international conference on Microelectronic Devices, Circuits and systems. ICMDCS 2022

ISBN: (纸本)9783031239724

The proceedings contain 14 papers. The special focus in this conference is on Microelectronic Devices, Circuits and systems. The topics include: Performance Analysis of Image Caption Generation Using Deep Learning Techniques;The Heroes and Villains of the Mix Zone: The Preservation and Leaking of USer’s Privacy in Future Vehicles;analysis and Design of High Speed and Low Power Finite Impulse Response Filter Using Different Types of Multipliers;MPPT Using P&O Algorithm for Solar-Battery Powered Electric Vehicle;Design of Hardware Accelerator for Facial Recognition System Using Convolutional Neural Networks Based on FPGA;Advanced TSV-BIST Repair Technique to Target the Yield and Test Challenges in 3-D Stacked IC’S;Redundancy Allocation Problem Evaluation Using Interval-Based GA and PSO for Multi-core System Consisting of One Instruction Cores;design of Low Powered and High Speed Compressor Based Multiplier;a Route Planning for Idyllic Coverage in Sensor Networks with Efficient Area Coverage;low Power Mod 2 Synchronous Counter Design Using Modified Gate Diffusion Input Technique;a Novel Blind Zone Free, Low Power Phase Frequency Detector for Fast Locking of Charge Pump Phase Locked Loops;performance Improvement of H-Shaped Antenna for Wireless Local Area Networks.

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Intrusion detection systems.for distributed environment 3

Intrusion detection systems for distributed environment

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3rd international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

作者： Malani, Dhrumil Modi, Jimit Lilani, Siddharth Desai, Yukta Dhanare, Ritesh SVKM's NMIMS MPSTME B.Tech in Information Technology Shirpur India SVKM's NMIMS MPSTME Department of Information Technology Shirpur India

ISBN: (纸本)9780738111834

Security is of utmost importance for any organization's network. Attackers have been attacking distributed networks for quite some time now. In spite of this, a successful distributed Intrusion Detection System (DIDS) is not in place for many organizations. The reason behind this is the lack of a foolproof system that runs on a very efficient algorithm. Improving an existing model of distributed Intrusion Detection System would help in reducing organizational concerns, risk of attacks and vulnerability of a system to get attacked. Most of the existing intrusion detection systems.suffer with the problem of reporting false positive and true negative results which adds to their error rates. It has become essential for such systems.to be worked upon and improved with the objective of increasing their efficiency by reducing probability of giving erroneous results. This paper includes a comprehensive review of the researches relating to distributed Intrusion Detection systems. It acknowledges the need for establishing an efficient distributed Intrusion Detection System. We aim to design a system that uses existing designs of these systems. algorithms used in the past and fuzzy logic theory by simulation, testing and modelling. © 2021 IEEE.

关键词： Intrusion detection

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distributed Generator Rescheduling Optimalization In Sangihe Island Using Unit Commitment Based on Firefly Algorithm

Distributed Generator Rescheduling Optimalization In Sangihe...

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international conference on Smart Cities, Automation & Intelligent computing systems.(ICON-SONICS)

作者： Darabean Aitana Ardyono Priyadi Vita Lystianingrum Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

Optimization problem in remote areas had been a problem that could not be fully fixed and adjusted the field. This research focuses on optimizing distributed generator rescheduling in Sangihe Island, a remote region with power generation and distribution challenges. The primary aim is to enhance efficiency, reliability, and cost-effectiveness. This research proposes integrating the Unit Commitment (UC) problem with the Firefly Algorithm (FA). Sangihe Island’s power system comprises diverse generators, including renewables (photovoltaic) and diesel. To tackle dynamic conditions, we meticulously formulate the UC problem, addressing on/off states and power outputs while considering economic and technical constraints. We use the Firefly Algorithm, renowned for its ability to handle complex problems efficiently. Real-world data validation demonstrates substantial improvements in operational efficiency, cost reduction, and reliability. Comparative analysis confirms the Firefly Algorithm-based Unit Commitment’s superiority in addressing the island’s unique challenges. From the result, the approach offers an innovative method for Sangihe Island’s distributed generator rescheduling, had increased the cost efficiency by IDR15175663 per day or 5.44% more cost efficient for an entire island.

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Research on Digital Twin Testing Theory and Technology for Intelligent Connected Vehicle 3

Research on Digital Twin Testing Theory and Technology for I...

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3rd international conference on Artificial Intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Jiang, Huajun Dong, Hongliang Zhang, Yuan Fang, Zhiyi Taizhou Vocational and Technical College 788 Xueyuan Rd Jiaojiang District Zhejiang Taizhou China Jilin University No.2699 Qianjin Street Changchun City China

ISBN: (纸本)9781510671485

Due to the difficulty and high cost of conducting sufficient real-world road tests, it is widely accepted in the industry to use a digital twin testing system that combines virtual simulation testing with real-world road testing to test and evaluate autonomous driving systems. Digital twin testing can simulate a road test environment using technologies such as sensor simulation and vehicle dynamics simulation, advanced graphics processing, traffic flow simulation, digital simulation, and road modelling. We integrated simulation testing tools, V2X communication devices, and real testing vehicles to achieve digital twin autonomous driving testing based on virtual simulation and real environments. It generates scene data based on virtual scene simulation software, constructs simulated scenarios mapping to reality, and uses V2X communication devices to transmit simulated scene environment data in real time to the real testing vehicles. It also receives real-time status data from the vehicles and feeds them back to the scene controllers, enabling autonomous vehicles to test different scenarios on real roads. In active safety-related testing, virtual scenes can avoid accidents and save unnecessary equipment losses. The system has high repeatability, and after a large number of repetitive in-vehicle tests, it can significantly reduce functional defects in the tested system, reducing the workload of actual vehicle field testing and road testing and improving testing efficiency and cost savings. © 2023 SPIE.

关键词： Autonomous vehicles

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A Review of Available Standard Dataset for Automated Medicine Pill Recognition Technology 3

A Review of Available Standard Dataset for Automated Medicin...

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3rd international conference on Intelligent computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Islam, Sayeed Hossan, Md. Zakir Manarat International University Department of Electrical & Electronics Engineering Ashulia Dhaka Savar Bangladesh Computer Vision and Cybernetics Group Department of Computer Science & Engineering Independent University Bashundhara R/A Dhaka Bangladesh

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

In this paper, we'll review available standard datasets for automated medicine pill recognition technology. A process whereupon a dataset people discover or provide highly creative technique and tools for sorting and ranking consumer photos of prescription pills. To the need for healthcare providers and the general public to quickly identify unknown prescription medications all of these databases or datasets were created in response. Most of the prescription pills come in blister, alu-alu containers, or Ziploc packs. After unpacking the medical drugs, it is a very difficult tasks for a patient as well as professional medical staff to differentiate between them due to the lack of variability in size, shape, and color though it is a daily task for all of them. Often it is the case that label of the pack is somehow damaged, and for those how to have to take more than one medication at a time it is difficult to differentiate and find the right one between one and another from where the label is me deface or several pills are mistakenly come down from required containers. This error prone nature of the task as many of the pills have almost similar features, increases the medication error which sometimes appears as fatal for patients. The complications are even worse for elderly people with low vision and visually challenged people are at risk because they are not able to identify the color of the text printed on the pill. © 2022 IEEE.

关键词： Computer vision

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An Adaptive Load Balancing Strategy for distributed Machine Learning

An Adaptive Load Balancing Strategy for Distributed Machine ...

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Frontiers of Electronics, Information and Computation Technologies (ICFEICT), international conference on

作者： Haozhe Min Meiting Xue Weibo Zhu Yan Zeng Nailiang Zhao Jilin Zhang College of Cyberspace Hangzhou Dianzi University HangZhou China School of Computer Seience and Techrology Hangzhou Dianzi University HangZhou China

Within a distributed deep learning training system, variances in performance among computing nodes, as well as the influence of external environmental factors, can result in training interruptions or reduced convergence speed. As such, this paper presents an approach to address this issue by proposing a dynamic task allocation strategy among nodes, aimed at mitigating the impact of performance discrepancies on the training efficiency of distributed deep learning systems. This proposed approach is referred to as the “Auto weight-based load balancing strategy” (Auto-WLBS) and involves dynamically adjusting the task allocation among computing nodes based on their performance characteristics. In order to maximize computing power while minimizing the lag effect on the training of the entire system, Auto-WLBS partitions and alters the errands by introductory division and halfway alteration. Combined with LSP model, AW-LSP model is proposed. Finally, a comparative experiment was conducted on the cifar10 and cifar100 datasets, and Auto-WLBS was experimentally verified from the perspective of model training loss function changes, model accuracy, and training time. The experimental findings demonstrate that compared to the BSP model, SSP model, and LSP model, the AW-LSP model has a smaller communication overhead, and the communication overhead can be reduced by up to 23.70%. Compared with the SSP model and the LSP model, the model accuracy can be improved by up to 14.5% and 8.6%, respectively.

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distributed Ledger Methods in Securing Software-Defined Networks 3

Distributed Ledger Methods in Securing Software-Defined Netw...

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3rd international conference on Control systems. Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Dautov, Damir Khayretdinov, Rinat Vulfin, Alexey Mironov, Konstantin Ufa State Aviation Technical University Dept. of Computed Engineering and Information Security Ufa Russia Inmt Ural Federal University Ufa State Aviation Technical University Comp. Engineering and Inf. Sec. Dept. Ufa Russia

ISBN: (纸本)9781665439817

Software-defined networks are becoming more popular as the number of devices in large enterprise networks continues to grow. However, this technology has vulnerabilities that can be very dangerous for company. An algorithm of implementation of the distributed ledgers in software-defined networks for security purposes is proposed in this paper. © 2021 IEEE.

关键词： distributed ledger

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Cloud-Enhanced Transfer Learning Framework for Medical Image Analysis: Advancing Diagnostic Speed and Accuracy in Healthcare 3

Cloud-Enhanced Transfer Learning Framework for Medical Image...

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3rd international conference on Integrated Circuits and Communication systems. ICICACS 2025

作者： Prabu, S. Chandra, N. Subhash Bhavani, M. Varma, V. K. Chaitanya Soni, Mukesh Mahendra Institute of Technology Department of Electronics and Communication Engineering Namakkal India Cvr College of Engineering Department of Computer Science and Engineering Mangalpalle India Rajalakshmi Institute of Technology Department of Artificial Intelligence and Data Science Chennai India Sagi Rama Krishnam Raju Engineering College Department of Mechanical Engineering Bhimavaram India Dr. D. Y. Patil Vidyapeeth Dr. D. Y. Patil School of Science & Technology Pune India

ISBN: (纸本)9798331508456

When it comes to medical image analysis, problems arise due to the scarce amount of data and computational resources in medical environments. This is because, as earlier stated, cloud settings demand efficient models capable of delivering more reliable diagnostic results without straining the cloud's computing resources. In this work, we presented a transfer learning based on DenseNet-201 as well ResNet-152 architectures with a new large dataset containing 15,000 medical images of different modality. By utilizing the distributed cloud computing and hypermeters precision strategy, the proposed model was found to have 95.8 % of accuracy, 94.2% sensitivity, and 96.3%specificity. It also reduced the processing time by sixty-eight percent over standard methods across the facilities. Five different datasets validated the proposed approach, achieving an external accuracy of 92.4%, indicating improved generalization performance. The enhancement of accuracy to approximately 90% and the reduction in required computation demonstrate its feasibility for extensive clinical applications on the cloud, spanning across hospitals. © 2025 IEEE.

关键词： distributed cloud

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DEM Generation from Mono-Multispectral Images via Uncalibrated Epipolar Rectification and 3D Registration 3

DEM Generation from Mono-Multispectral Images via Uncalibrat...

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3rd IEEE international conference on Recent Advances in systems.Science and Engineering, RASSE 2023

作者： Gupta, Ashutosh Lalwani, Hemant K. Paul, Subhajit Dhar, Debajyoti Ahmedabad380015 India

ISBN: (纸本)9798350341676

Generation of Digital Elevation Models (DEM) typically requires fine image matching between set of images acquired with a wide-baseline and appropriate B/H ratio. Wide baseline stereo imaging is an expensive process since it requires two or more acquisitions at the cost of nominal mono-imaging operations. Due to the wide-baseline, angular separation in views is required, which results in increased occlusion problems leading to holes in the generated DEM. Multiview images taken with wide baselines also have lower overlap area compared to images taken from narrow-baseline systems. Moreover, while making orthorectified maps, large tilts need to be corrected using processing techniques to obtain a top-down view. To alleviate these issues, we propose a novel DEM generation pipeline that utilizes the narrow-baseline information between bands of a single multispectral image. Our method can generate sub-pixel accurate disparity maps while tackling spectral information change. Final DEM is generated from the disparity by using reference Ground Control Points (GCPs) and an iterative control point registration procedure. We demonstrate the effectiveness of our DEM generation pipeline on Resourcesat-2 LISS-IV multispectral image with a BIH ratio as low as 0.018. Our results show that sub pixel disparity of the order of 1/50th of a pixel can be computed. A visual and quantitative comparison of the generated DEM with the wide-baseline DEM from Cartosat-l shows that the elevation information is estimated with good overall agreement even for a hilly region. Our technique makes it possible to extract elevation information from mono-multispectral images with unusually low B/H ratios, potentially enabling the generation of DEMs from multispectral images that would not normall be considered viable for this purpose. © 2023 IEEE.

关键词： Pipelines

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An Optimal distributed Scheduling Model for Data Centers and Renewable Energy Integrated systems 3

An Optimal Distributed Scheduling Model for Data Centers and...

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3rd IEEE international Power Electronics and Application conference and Exposition, PEAC 2022

作者： Cheng, Xinyun Zou, Haodong Chen, Xin Yu, Jinghang Tang, Ming Xiao, Maoran State Grid Jiangsu Electric Power Co. Ltd. Information & Telecommunication Branch Jiangsu Nanjing China

ISBN: (数字)9781665491419

ISBN: (纸本)9781665491419

Data centers (DCs) are large power consumers with demand response (DR) capabilities in both time and special dimensions. This paper proposes a scheduling model for renewable energy integrated systems.with DCs to improve renewable energy utilization. To protect the data privacy of data center operators (DCOs), a two-level distributed algorithm is proposed in this work. Finally, the proposed model is verified on an improved IEEE 118-bus power system with renewable energy farms and DCs. Simulation results prove that DCs' participation in DR has a positive effect on reducing renewable energy curtailment and the proposed algorithm has high solution accuracy on the premise of privacy data protection of DCOs. © 2022 IEEE.

关键词： Energy utilization

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