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共 1594 条记录，以下是21-30 订阅

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Research on Vector Geophone Based on Michelson Fiber-Optic Interference Principle 1

Research on Vector Geophone Based on Michelson Fiber-Optic I...

引用

1st international conference on intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Xu, Hua Yi, Wensuo Ding, Ruiyang Yang, Yuxin Huang, Kaiyang College of Intelligence Science and Technology National University of Defense Technology Hunan Changsha410073 China College of Optoelectronic Engineering Changchun University of Science and Technology Changchun130022 China

ISBN: (纸本)9781643685779

Aiming at the problem of frequent earthquakes and other natural disasters, based on the research on distributed optical fiber sensing technology and the sensing principle and basic theory of Michelson optical fiber interferometer, a vector seismic sensor is designed. The sensitive part of the optical fiber vibration sensor is mainly composed of elastic sheets, The sensor is composed of mass block, ring and sensing fiber element, and the strain effect analysis of the sensor shows that the composite material is an ideal material for the vibrating sheet, which greatly improves the sensitivity of the system and reduces the system error. The overall scheme of the system is designed, and the signal generator is used to simulate the vibration generation. The signal amplitude is 1 and the frequency is 300Hz and 500Hz respectively. Through multiple experiments and analysis of the experimental results, it is shown that the detection sensitivity a is 0.08g and 0.3g respectively. the waveform of the vibration signal is basically consistent with the signal amplitude detected by the sensor, and has a good frequency response, which can be used for seismic wave detection. © 2025 The Authors.

关键词： Michelson interferometers

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Multi-Metric Based Client Selection for Backdoor Defense in Federated Learning 1

Multi-Metric Based Client Selection for Backdoor Defense in ...

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1st international conference on intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Yuan, Changjiang Li, Yidong Chen, Naiyue Zhang, Zikai Key Laboratory of Big Data & Artificial Intelligence in Transportation Beijing Jiaotong University Ministry of Education China School of Computer Science and Technology Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9781643685779

The distributed nature of federated learning makes it highly susceptible to backdoor attacks, which aim to induce the model to produce incorrect results when specific data is input. Existing defense methods based on distance calculations mostly use one single distance, which can be easily circumvented by backdoor attacks. Therefore, we conducted research on the combination of multiple distances. Based on this, we propose a backdoor defense algorithm based on multi metrics, which evaluates models through distance calculation and normalization to select benign models for aggregation. To verify the effectiveness of our method, we conducted experiments on three datasets, and the results prove that our method can provide good defense without reducing the model's main task accuracy. © 2025 The Authors.

关键词： Federated learning

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Research on Cable Vibration Measurement System Based on Michelson Interference Principle 1

Research on Cable Vibration Measurement System Based on Mich...

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1st international conference on intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Kou, Hanpeng Bu, Tianlong Zhang, Dapei Nie, Dayu Feng, Zhenghua Huang, Kaiyang Mengdong Power Grid Company Hohhot120022 China Changchun University of Science and Technology Changchun130022 China

ISBN: (纸本)9781643685779

Extra-high voltage transmission lines and cables are subject to irregular vibration due to icing or unusual weather conditions, which is potentially hazardous to the safety of the towers and the structural strength of the wires. Most of the current monitoring methods use electronic acceleration sensors, which have low sensitivity, poor signal-to-noise ratio, troublesome installation process, need for additional power supply and other issues. distributed fibre optic vibration demodulation method is currently more advanced sensing technology, can achieve long distance, large scale, multi-dimensional online monitoring and structural safety warning. The laser fibre sensing distributed Michaelson coherent technology is used to develop a cable vibrate sensor, which can achieve the vibrate monitoring of cables and towers. The sensor consists of an elastic thin-walled cylinder, a mass ring, a fixed ring, and a sensing fibre, which uses a highly sensitive fine optical fibre and a coupler to build a laser-fibre Michelson coherent optical path, which is very sensitive to vibration signals, and encapsulates the interferometer into a specific metal casing to achieve the encapsulation and integration of the vibrate monitoring sensor. The optical system of this laser fibre sensor has the advantages of high sensitivity and high signal-to-noise ratio. Using the differential cross-multiplication demodulation algorithm for many experiments and results analysis, the demodulation output of the linear correlation coefficient of up to 0.95 in the frequency of 10Hz ~ 200Hz under the conditions of the vibrate, suitable for high-voltage towers and cables for online monitoring of the vibrate. © 2025 The Authors.

关键词： Optical fibers

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On the Mathematical Principles of Image Transmission 1

On the Mathematical Principles of Image Transmission

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1st international conference on intelligent Manufacturing and Cloud computing, ICIMCC 2024

作者： Liu, Hong Cheng, Manman School of Law and Journalism Wuhan East Lake University Hubei Province Wuhan City China Guangxi Zhongtu Education Technology Co. Ltd Guangxi Province Nanning City China

ISBN: (纸本)9781643685779

e recognition and transmission of images have made breakthrough progress with the support of neural networks, but there are still many unknowns about the mechanism of image transmission. This paper proposes the theory of aberration and pressure, which initially reveals the mathematical principles of image recognition and transmission. It not only puts forward the corresponding concepts but also analyzes the mathematical formulas of aberration and pressure, image entropy, and image representation. In particular, it compensates for some structural defects in current image recognition and transmission, such as the difficulties in image recognition caused by occlusion and deformation, and promotes the research on image transmission. © 2025 The Authors.

关键词： Erration-image pressure image entropy image recognition image representation image transmission

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A Prospective study on Reliability Analysis of Electrical Network with Electric Vehicle Integration 3rd

A Prospective Study on Reliability Analysis of Electrical Ne...

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3rd international conference on intelligent computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Nandini, K.K. Jayalakshmi, N.S. Jadoun, Vinay Kumar Manipal Institute of Technology Manipal Academy of Higher Education KA Manipal576104 India KA Nitte574110 India

ISBN: (纸本)9789819784639

Electric vehicles (EVs) are replacing conventional gasoline vehicles in the global transportation sector. The rise in penetration of EV load affects the reliability of the distribution systems (DSs). Reliability assessment is vital for designing DSs that operate economically and lessen customer load disruptions. It is important to achieve acceptable reliability regardless of the source, whether it is a distributed system, an electric utility system, or any other type. The integration of EVs and renewable resources (RRs) such as solar energy are significant feature of modern power system networks. The integration of solar energy acts as a backup option by supporting the power supply to the existing DS and improving the system’s reliability. Various reliability indices (RIs) can measure the duration and frequency of customer disruptions over an exact time. The main aim is to achieve consumer satisfaction, which needs proper planning. This paper confers a comprehensive study of different RIs and their importance in the power system. The reliability analysis is accomplished on an IEEE-33 bus radial DS after integrating EV load and solar energy source by applying teaching–learning-based optimization. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Power distribution reliability

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distributed computing and Artificial Intelligence, Special Sessions III - intelligent Systems Applications, 21st international conference 1

Distributed Computing and Artificial Intelligence, Special S...

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Francisco Zayas-Gato Antonio Díaz-Longueira José-Luis Casteleiro-Roca Esteban Jove

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Estimate Initial and Final Data Bounding for Big Data Progressive Sampling in Parallel computing Environment 1st

Estimate Initial and Final Data Bounding for Big Data Progre...

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1st international conference on intelligent Systems in computing and Communications, ISCComm 2023

作者： Aradhya, B. C. Yathish Dinesh, H.A. Lokesh, M.R. Visvesvaraya Technological University-Research Resource Center Jnana Sangama VTU Main Rd Visvesvaraya Technological University Belagavi Karnataka Machhe590018 India Tumakuru Karnataka is affiliated to Visvesvaraya Technological University Karnataka Belagavi572106 India Department of Information Science and Engineering A J Institute of Engineering and Technology Mangalore India

ISBN: (纸本)9783031756078

Big Data Progressive Sampling requires initial and final data bounding values to generate optimal number of samples in order to train any learning algorithm. Any learning algorithm can be trained for minimal hypothesis space. Approximating data bounding to Rademacher Averages of a given hypothesis space and learning algorithm ensure final data bounds with Ε-Approximation. This final Data bounding value serves as stopping criterion for Progressive Sampling. statistically optimal sample size estimation technique ensure minimal initial sample size. In this work, we propose a methodology to approximate initial and final Data bounding to Progressive Sampling using local Rademacher in big data Hadoop environment with experimental values along with computational parameters. Also the performance of learning algorithm to various highly complex big datasets for their corresponding initial minimal value and final Data bound to Rademacher Averages are experimentally shown in Hadoop distributed environment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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NOBGP: A Novel Optimized Balanced Graph Partitioning Algorithm 19th

NOBGP: A Novel Optimized Balanced Graph Partitioning Algorit...

引用

19th CCF conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2024

作者： Chen, Jiebin Hu, Ziqiang Ye, Renjie Zhang, Qishan Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China Xianda College of Economics and Humanities Shanghai International Studies University Shanghai China

ISBN: (纸本)9789819623723

Large-scale graphs have become prevalent with the advent of the big data era. distributed graph computing systems are commonly used for processing and analyzing large-scale graphs, with graph partitioning being a key prerequisite for their efficient computation. Graph partitioning aims to balance the load across partitions while minimizing the number of cut-edges. Moreover, it should achieve high efficiency and scalability. However, the existing popular graph partitioning algorithms do not fully take into account the internal topology of real-world graphs, which affects the final partition quality and convergence. Meanwhile, they easily fall into the local optimum due to partition load constraints. This paper introduces a Novel Optimized Balanced Graph Partitioning algorithm (NOBGP). First, we propose an initialization strategy based on label propagation of core vertices to achieve initial partitions with good locality and accelerate convergence. Second, we optimize the label propagation process to ensure balanced partitions and propose a probability-based disruption strategy to avoid the local optimum. We implement NOBGP on the distributed graph computing framework GraphX. Extensive experimental results on real-world graphs show that the proposed algorithm is scalable and performs better than the existing algorithms. We also run PageRank and Louvain applications using the graph partitioning results to demonstrate the efficiency of our algorithm. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph algorithms

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Fire Detection System Using Deep CNN 1st

Fire Detection System Using Deep CNN

引用

1st international conference on intelligent Systems in computing and Communications, ISCComm 2023

作者： Vikkurty, Sireesha Nagaratna Hegde, P. Chinthakrinda, Vennela Preethi Hegde, G.P. Shetty, Sudheer Department of CSE Vasavi College of Engineering Telangana Hyderabad India SDM Institute of Technolog Ujire India Department of ISE Alvas Institute of Engineering and Technology Moodbidri Affiliated to Visvesvaraya Technological University Karnataka Belagavi India

ISBN: (纸本)9783031756047

The occurrence of fire should be reported by a fire alarm at the earliest. With the advent of convolutional neural networks, this has become more reliable and advanced. The detection of fire conditions as early as possible is a prerequisite of a Fire Detection System, and to give sufficient time for effective counter actions by Automated Fire personnel. Fire detection and forecast by conventional fire detection systems was achieved by using the by-products of fire such as smoke, temperature and flame which take a considerable amount of time to produce a level of fire which will trigger the smoke sensors and heat sensors. In this project, the proposed system is building a deep learning solution using convolutional neural networks. The proposed system is fine-tuned to stabilize the efficiency and accuracy by keeping in mind the nature of the target problem and fire data. The effectiveness of the proposed system is revealed and validated by the experimental results on benchmark fire datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Introducing Competitive Mechanism to Differential Evolution for Numerical Optimization 30th

Introducing Competitive Mechanism to Differential Evolution...

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30th international conference on Parallel and distributed Processing Techniques, PDPTA 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2024

作者： Zhong, Rui Cao, Yang Zhang, Enzhi Munetomo, Masaharu Graduate School of Information Science and Technology Hokkaido University Sapporo Japan Information Initiative Center Hokkaido University Sapporo Japan

ISBN: (纸本)9783031856372

This paper introduces a novel competitive mechanism into differential evolution (DE), presenting an effective DE variant named competitive DE (CDE). CDE features a simple yet efficient mutation strategy: DE/winner-to-best/1. Essentially, the proposed DE/winner-to-best/1 strategy can be recognized as an intelligent integration of the existing mutation strategies of DE/rand-to-best/1 and DE/cur-to-best/1. The incorporation of DE/winner-to-best/1 and the competitive mechanism provide new avenues for advancing DE techniques. Moreover, in CDE, the scaling factor F and mutation rate Cr are determined by a random number generator following a normal distribution, as suggested by previous research. To investigate the performance of the proposed CDE, comprehensive numerical experiments are conducted on CEC2017 and engineering simulation optimization tasks, with CMA-ES, JADE, and other state-of-the-art optimizers and DE variants employed as competitor algorithms. The experimental results and statistical analyses highlight the promising potential of CDE as an alternative optimizer for addressing diverse optimization challenges. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Competitive Mechanism Differential Evolution (DE) Evolutionary Computation (EC) Novel Mutation strategy Numerical Optimization

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