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检索条件"主题词=Filtering algorithms"

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Gaussian Filter Optimization for Segmentation Retinal Fundus Images in Proliferative Diabetic Retinopathy Screening

Gaussian Filter Optimization for Segmentation Retinal Fundus...

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Informatics International Conference (BTS-I2C), Beyond Technology Summit on

作者： Gayatri Dwi Santika Lailatul Nur Afia Nelly Oktavia Adiwijaya Department of Informatics Faculty of Computer Science University of Jember Jember Indonesia

ISBN: (数字)9798331508579

ISBN: (纸本)9798331508586

Diabetic Retinopathy alludes to a boundary that takes put in diabetes mellitus harming the blood vessel arranged display within the retina. This may imperil the subject's vision if they have diabetes. It can take a little time to perform a DR determination utilizing color fundus pictures since experienced clinicians are required to identify the tumors within the symbolism utilized to distinguish the sickness. This research using 3669 data were collage using open data. CNN are also highly successful at classifying pictures when connected within the display circumstance, especially compared to the high quality and usefulness strategies utilized. To guarantee high results, it needs a cutting-edge CNN show that might decide the characteristics of the fundus pictures. The implementation of the Gaussian filter result image on the identification performance gets the highest accuracy from the 3×3 structural element is 77%. Its shown that algorithm is feasible. The investigation's discoveries that the approach performed way better than elective approaches and can identify the specifics of an image as a health industry option for early detection of disease.

关键词： Diabetic retinopathy Accuracy filtering algorithms Retina Size measurement Real-time systems Convolutional neural networks Optimization Open data Tumors

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FedTMatch: Self-Supervised Federated Semi-Supervised Learning with Dynamic Threshold

FedTMatch: Self-Supervised Federated Semi-Supervised Learnin...

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Industrial Automation, Robotics and Control Engineering (IARCE), International Conference on

作者： Qing Zhao Jielei Chu Zhaoyu Li Hua Yu Tianrui Li School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu China CREC R&D Center for Carbon Peaking and Carbon Neutrality China Railway Eryuan Engineering Group Co. Ltd. Chengdu China China E-port Data Center Chengdu Branch Chengdu China

ISBN: (数字)9798350380323

ISBN: (纸本)9798350380330

Federated semi-supervised learning (FSSL) has emerged as a promising paradigm to address the challenges of data privacy and the scarcity of labeled data. Most existing algorithms adapt the pseudo-labeling and consistency regularization methods in traditional semi-supervised learning (SSL) to exploit raw data from unlabeled clients. However, these methods always use the same high fixed threshold to filter out noisy pseudo-labels for each class, without considering the varying learning conditions and difficulty levels associated with different classes, resulting in a decline in the performance of global model, especially under non-Independent and Identically Distributed (Non-IID) settings. To this end, we propose FedTMatch, a learning framework which adjusts the threshold for each class based on the learning status of each client. Furthermore, we introduce a self-supervised rotation loss in unlabeled clients to increase the utilization of raw data and correct the feature space formed by pseudo-label data to weaken the impact of Non-IID data distribution on global model's performance. Extensive experiments on three benchmark datasets demonstrate the effectiveness of our approach.

关键词： Data privacy Control engineering Service robots Computational modeling Semisupervised learning Predictive models filtering algorithms Data models Noise measurement Convergence

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On the Forgetting Factors of the RLS Algorithm Based on Third-Order Tensor Decomposition

On the Forgetting Factors of the RLS Algorithm Based on Thir...

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International Symposium for Design and Technology of Electronics Packages (SIITME)

作者： Radu Otopeleanu Constantin Paleologu Camelia Elisei-Iliescu Cristian-Lucian Stanciu Cristian Anghel Jacob Benesty National University of Science and Technology POLITEHNICA Bucharest Romania INRS-EMT University of Quebec Montreal Canada

ISBN: (数字)9798331539511

ISBN: (纸本)9798331539528

The recently developed recursive least-squares algorithm based on third-order tensor decomposition, namely RLSTOT, proves to be efficient for the identification of long length impulse responses. Such systems can be encountered in many real-world applications, like network/acoustic echo cancellation. The RLS-TOT combines the estimates of three shorter adaptive filters, which have different convergence parameters. In this paper, we investigate some strategies for setting the forgetting factors of the RLS-TOT. These are the main parameters that control the memory of the algorithm and, consequently, its main performance criteria. Simulations performed in the framework of echo cancellation support the theoretical findings.

关键词： Adaptation models Tensors Echo cancellers Adaptive filters filtering algorithms Electronics packaging Convergence

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Electronic Load Modeling Using Enhanced Opposition Based Differential Evolution Optimization

Electronic Load Modeling Using Enhanced Opposition Based Dif...

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National Power Systems Conference (NPSC)

作者： Abhinav Kumar Sanjeev Kumar Mallik Department of Electrical Engineering National Institute of Technology Patna Patna India

ISBN: (数字)9798331519568

ISBN: (纸本)9798331519575

Every day, the proportion of electronic loads in a load sector increases. As such, familiarity with and monitoring the electronic load model is crucial. This work addresses the novel challenge of parameter estimation of the electronic load model using enhanced opposition-based differential evolution (EOBDE) optimization. Based on the load terminal voltage value, an electronic load model is created. Electronic load operates in five different modes. Different mathematical models are used for each mode to determine the electronic load's active and reactive power consumption. On the 30th bus, this load is connected to the New England (NE) 39 bus system. Additive white Gaussian noise is applied to the voltage, active power, and reactive power data that are collected. Noises are filtered using the wavelet denoising technique. In light of this, using a measurement-based approach, this filtered data is compared with estimated power output and the error between filtered data and estimated output is fed to the parameter tuning algorithm (EOBDE), and iteratively, by minimizing the error between estimated and filtered output, the parameter of the electronic load is estimated. EOBDE is an improved version of differential evolution optimization that excels in parameter estimation because, when the enhanced opposition section is called, it is based on the opposite of the solution. In the lowest period and with the fewest number of iterations, it minimizes the possibility of local minima and locates the global optimum.

关键词： Reactive power Parameter estimation filtering algorithms Active filters Mathematical models Threshold voltage Scattering parameters Optimization Tuning Load modeling

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Rapid Detection of Arsenic in Water Based on Hyperspectral Imaging

Rapid Detection of Arsenic in Water Based on Hyperspectral I...

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International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Wang Guo Manjiao Chen Xinqiang Yi Xinjun Hu Jianping Tian School of Mechanical Engineering Sichuan University of Science and Engineering Zigong China

ISBN: (数字)9798350385106

ISBN: (纸本)9798350385113

With the intensification of industrialization and urbanization, arsenic pollution in water bodies has become a serious global issue. A rapid and pollution-free method for detecting arsenic content in water bodies is of great significance for water protection. In this study, quantitative analysis of arsenic content in water was conducted using hyperspectral imaging technology combined with a carrier. The arsenic solution was divided into three concentration gradients: 0.96879.0369 mg/l, 9.961190.0331 mg/l, and 99.9591∼900.0494 mg/l, totaling 540 samples, to investigate the concentration-dependent effects. The influence of filter paper on arsenic content detection was studied by adding different amounts of arsenic solution onto filter paper. A particle swarm optimization-least squares support vector machine (PSO-LSSVM) model was established using different preprocessing methods to determine the optimal preprocessing method. The competitive adaptive reweighted sampling (CARS) algorithm was used to extract characteristic wavelengths. Three models (PSO-LSSVM, BPNN, and SSA-KELM) were established based on full wavelengths and characteristic wavelengths, respectively. The results indicate that the PSO-LSSVM model established through characteristic wavelengths has a good predictive effect on arsenic content among all models. Specifically, at low concentrations, $\textbf{Rp}^{2}=0.9951,\textbf{RMSE=0.1992},\textbf{RPD =12.5988}$ ; at medium concentrations, $\mathbf{R p}^2=0.9957,\textbf{RMSE =1.6853},\textbf{RPD=12.9468}$ ; at high concentrations, $\textbf{R}_{{p}^{2}}=0.9962,\textbf{RMSE =14.3584},\textbf{RPD=14.6843}$ . Hyperspectral imaging technology combined with a carrier was found to enable rapid and accurate prediction of arsenic content in water, potentially serving as an attractive alternative for online analysis in the field of water quality testing.

关键词： Adaptation models Analytical models Arsenic Imaging Predictive models filtering algorithms Water pollution

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Research on IPMSM Sensorless Control Based on Lattice Kalman Filters

Research on IPMSM Sensorless Control Based on Lattice Kalman...

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International Conference on Smart Grid and Clean Energy Technologies (ICSGCE)

作者： Lianshan Xia Jikun Yang Jianmin Zhang College of Electrical and Information Beihua University Jilin China Hohhot Power Supply Branch InnerMongolia Electric Power (Group) Co. Ltd Inner Mongolia China

ISBN: (数字)9798350356571

ISBN: (纸本)9798350356588

Embedded permanent magnet synchronous motor (IPMSM) sensorless control system. In view of the problems of traditional Kalman filter algorithm, such as the decline of filtering accuracy when the system state changes suddenly, long running time, slow convergence speed, and large amount of data required for calculation, an improved algorithm of lattice Kalman filter is proposed to estimate the motor speed, and it is applied to the research of IPMSM sensorless control. This method uses the Quasi Monte Carlo method of lattice rules, uses the Kropov lattice rules to generate sample points, and uses the Cranley-Patterson rotation shift method to perform random shift. In the case of extracting a small number of sample points, it can quickly ensure the accuracy and strong robustness in the estimation process. Under the environment of MATLAB/Simulink, the simulation experiment of sudden load in the process of given speed is carried out. Lattice Kalman filter algorithm has high filtering accuracy, strong speed tracking and small amount of data required for calculation. It can realize high-precision control of IPMSM and has practical engineering value.

关键词： Accuracy filtering Magnetic separation Lattices Estimation Sensorless control filtering algorithms Smart grids Kalman filters Convergence

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Examining the Structure for Handling and Addressing Consumer Issues within the Water Utilities Industry

Examining the Structure for Handling and Addressing Consumer...

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International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)

作者： D.Roopa S.Mathupriya A. Lazha R. Prabha Department of Computer Science and Engineering Sri Sai Ram Institute of Technology Sri Sai Ram Siddha Medical College

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

Authorities' reactive approach to water quality issues and infrastructure can cause delays. Predicting future complaints based on environmental factors can help to improve infrastructure and prevent complaints. It is possible to predict the number of complaints for future years by analyzing water-related complaints data and identifying correlations between various environmental factors using machine learning algorithms such as Random Forest. This data can help manage water quality issues and enhance infrastructure. Identifying common difficulties in specific areas can also aid in determining the main cause of a problem and preventing future complaints. In this study, Python libraries are used to examine data on water quality complaints in New York City from 2010 to 2020. The first dataset filtered out water-related searches from a vast dataset, while the second comprised data on water quality and environmental aspects from 2015 to 2021. According to the findings, there is a link between specific environmental conditions and the frequency of complaints. Based on past data, the Random Forest algorithm was used to forecast complaints.

关键词： Industries Codes Machine learning algorithms Urban areas Water quality filtering algorithms Market research Libraries Environmental factors Random forests

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Identification of Capacitor Degradation in LCL Filter for Energy Storage Systems Converter

Identification of Capacitor Degradation in LCL Filter for En...

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International Conference on Power Electronics and Motion Control (IPEMC)

作者： Yuheng Bu Da Kang Xikui Yu Hanxin Zhang Wenli Yao Auotmation School Northwestern Polytechnical University Xi’An China Shenyang Aircraft Designand Research Institute Shenyang China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

Active damping has been applied to LCL- filtered converter in energy storage systems to ensure a stable current control. However, the aging effect and operational conditions may lead to a significant parameter drifting of the filter capacitance. This may result in a new resonant frequency beyond the designed active damping region. To address the issue, this paper analyzes the resonance characteristic of the LCL filter with all-pass filter based active damping. The analysis reveals that a resonant at 0dB- magnitude crossing point will be detected by utilizing all-pass filter move the -180°-phase crossing point to the 0dB- magnitude crossing point, which is filter inductance and capacitance dependent. To decouple the magnitude crossing points with the LCL parameters, six-order harmonic injection method is used to identify the ratio between capacitance and inductance, then the filter capacitance can be calculated based on identified 0dB-magnitude crossing point by LCL system model. Real-time Simulation tests are performed, and the results verify that the proposed method can accurately obtain the filter capacitance.

关键词： Damping Degradation Inductance Capacitors filtering algorithms Capacitance Harmonic analysis

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Optimization of Fifth Order Band-Pass Ladder Filter and Statistical Analysis of Reverse Problem

Optimization of Fifth Order Band-Pass Ladder Filter and Stat...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Sayyed Ali Alizadeh Mahmoud Kamarei School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (数字)9798350376340

ISBN: (纸本)9798350376357

In this article, elements of a fifth order ladder type filter circuit are found through optimization, and circuits having optimum or near optimum responses statistically analyzed. algorithms used for optimization are: GA, PSO, TLBO and combinations of GA with two others. In addition, a modified version of PSO-GA is introduced for multi-modal optimization and results shown. At last, PSO-GA algorithm along with a parameter change technique is used to find distribution of elements around optimum point.

关键词： Band-pass filters Electrical engineering Statistical analysis Fitting Bandwidth filtering algorithms Frequency response

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Efficient and Verifiable Skyline Computation on Blockchain System with Merkle B+ Tree Index

Efficient and Verifiable Skyline Computation on Blockchain S...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Hao Ding Xuefeng Piao Huihui Song Jiasi Li Zhenzhou Ji Meng Liu Jie Liu Wenjie Dong School of Computer Science and Engineering Harbin Institute of Technology Harbin China School of New Energy Harbin Institute of Technology Weihai China Electric Power Research Institute State Grid Shandong Electric Power Company Jinan China Yantai Power Supply Company State Grid Shandong Electric Power Company Yantai China Dongfang Electronics Co. Ltd. Yantai China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

With the advancement of blockchain technology, its application in data management and query processing has garnered increasing attention. However, as a distributed database system, blockchain currently falls short in supporting diverse data query requirements. Skyline computation, which identifies Pareto optimal solutions in multi-dimensional data, has become an increasingly necessary feature in blockchain environments. Traditional skyline computation methods struggle with inefficiency when handling large-scale and multi-dimensional data, and they lack effective verification mechanisms within a blockchain context. This paper proposes a multi-dimensional data index structure for skyline computation based on a hybrid blockchain architecture of full nodes and light nodes, utilizing Merkle tree and B+ tree. Additionally, an early pruning-based divide-and-conquer strategy is designed based on this index structure. This approach optimizes the skyline query process by computing local skylines to derive the global skyline. Simultaneously, by introducing Bloom filter, we reduce unnecessary I/O operations during result verification, enabling light nodes to perform verification operations more efficiently. Extensive experiments have demonstrated the effectiveness of our proposed scheme, which can improve query speed by an average of 90.08% compared to the BNL algorithm and by an average of 86.12% compared to the SFS algorithm.

关键词： Distributed processing Query processing Computer architecture Pareto optimization filtering algorithms Blockchains Computational efficiency Indexes

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