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检索条件"主题词=Filtering algorithms"

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A PSO-based Surrogate-Assisted Federated Feature Selection Algorithm

A PSO-based Surrogate-Assisted Federated Feature Selection A...

引用

New Trends in Computational Intelligence (NTCI), International Conference on

作者： Xin-yue Wang Ying Hu Yong-long Luo Xin Jin Zi-shun Kan School of Computer and Information Anhui Normal University Wuhu China Electrical Engineering College Tongling China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

High-dimensional feature selection (FS) problems face challenges such as the “curse of dimensionality” and high computational costs. In addition, a large amount of high-dimensional data describing the same learning task may be horizontally distributed among different institutions (called participants) and cannot be shared because of privacy protection limitations, further increasing the difficulty of high-dimensional FS problems. Therefore, a surrogate-assisted federated evolutionary FS algorithm based on particle swarm optimization (PSO) is proposed to solve the FS problem of high-dimensional data with multi-party participation under privacy protection. First, a joint filtered FS method based on the XGBoost model is proposed, which significantly reduces the initial space of features while ensuring privacy. Subsequently, a surrogate-assisted federated evolutionary FS algorithm framework under privacy protection is designed, and based on this framework, a joint construction and management strategy for the surrogate model, a joint evaluation strategy based on the surrogate model, and a joint update strategy for particles are developed. Finally, the proposed algorithm is applied to 10 test datasets, and compared with two typical evolutionary FS algorithms. The experimental results show that the proposed algorithm can not only ensure the classification performance but also significantly improve the efficiency of the algorithm while protecting the privacy of the participant data.

关键词： Privacy Data privacy Federated learning filtering algorithms Feature extraction Market research Classification algorithms Computational efficiency Protection Particle swarm optimization

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A Method for Accelerating Encrypted Data Search in Laravel Applications Using a Coded Search Parameter

A Method for Accelerating Encrypted Data Search in Laravel A...

引用

Telecommunications Forum (TELFOR)

作者： A. Muratovic A. Tanovic Faculty of Engineering and Natural Science University of Zenica Zenica Bosnia and Herzegovina Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9798350391060

ISBN: (纸本)9798350391077

Efficiently searching encrypted data within web applications presents a significant challenge for software engineers, primarily because traditional search methods necessitate decrypting each record individually to check for matches, leading to considerable computational overhead. The authors in this paper introduce an optimized search methodology for encrypted data in Laravel web applications by implementing a Coded Search Parameter (CSP). By incorporating an additional attribute into the MySQL database entity, which stores a coded representation of the initial character of the encrypted data - we substantially reduce server resource consumption and search time. During the search process, the algorithm initially executes a query filtered by the CSP attribute value, effectively narrowing down potential matches before decrypting the now reduced set of records. This approach also ensures that personal data remains protected without compromising data security. In this paper we provide a detailed exposition of the CSP method's implementation, evaluate its impact on search efficiency and present performance improvement analyses compared to traditional encrypted data search methods. Based on the research findings, it is concluded that the CSP method in Laravel applications significantly reduces search time for encrypted data, achieving an average acceleration of 73.58%.

关键词： Matched filters Search methods System performance NoSQL databases Distributed databases filtering algorithms Software Telecommunications Cryptography Servers

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Study on Hybrid Energy Storage Power Allocation Strategies for Smoothing Wind Power Fluctuations

Study on Hybrid Energy Storage Power Allocation Strategies f...

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Energy, Power and Grid (ICEPG), International Conference on

作者： Jianguo Zhang Sihua Wang School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

To solve the wind power fluctuation problem caused by hybrid energy storage system (HESS) connected to wind farms, a HESS power allocation strategy scheme was proposed to control variations in wind power. First, the limiting average filtering algorithm was used to filter the raw wind power and the grid-connected power and HESS reference power complying with the grid connection standard were calculated. Then, the Osprey-Cauchy-Sparrow Search Algorithm (OCSSA), which integrates the osprey and Cauchy variants, was used to optimize the Variational Mode Decomposition (VMD) parameters K (the quantity of modes) and $\alpha$ (the penalty component). After the optimal parameter combination [$K, \alpha$] was obtained, the HESS reference power was decomposed into high and low-frequency power constituents by VMD, which were allocated to the supercapacitor and the battery. The numerical example results showed that the proposed HESS power allocation strategy can effectively improve the economic efficiency of HESS.

关键词： Economics Fluctuations Limiting Power smoothing Wind power generation filtering algorithms Wind farms Hybrid power systems Resource management Energy storage

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A Novel Approach to Digital Filter Design for Environmental Monitoring applications

A Novel Approach to Digital Filter Design for Environmental ...

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Communication & Computing (WCONF), World Conference on

作者： Mandeep Kaur Department of Electronics and Communication Engineering Punjabi University Patiala Punjab India

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

This research work proposes the design of a latest generation digital filter, which is particularly suitable for the optimization of environment measurements. Filters are important components of signal processing that used for correct acquiring and analysis of environmental information. But in current designs various problems of accuracy, response time and power consumption are usually encountered. In this directed method, we have incorporated novel algorithms as well as optimization procedures that enhance the filter's efficiency. Experiments substantiate the superiority of the proposed approach compared to prior art in such categories as accuracy and time. Other real life environmental monitoring applications also support our observations and the efficiency of our proposed approach. Such profuse outcomes have scientific significance to progress in the Emergency and environmental monitoring systems contributing to higher reliability and accuracy.

关键词： Accuracy Power demand Signal processing algorithms filtering algorithms Information filters Environmental monitoring Time factors Reliability Digital filters Optimization

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Digital Filter Design Using Soft Computing Technique

Digital Filter Design Using Soft Computing Technique

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Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), IEEE International Conference on

作者： Navjot Singh Talwandi Swati Dept of Computer Science Engineering Chandigarh University Punjab India

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382709

Digital filter design plays a crucial role in signal processing applications, aiming to enhance, extract, or suppress specific components of a signal. Soft computing techniques have emerged as effective methods for designing digital filters due to their ability to handle complex, non-linear problems. This paper explores the utilization of soft computing approaches, such as neural networks, fuzzy logic, and evolutionary algorithms, in the design and optimization of digital filters. By leveraging the adaptive and learning capabilities of these techniques, this study aims to achieve efficient and optimized filter designs, catering to various signal processing requirements. The comparative analysis of soft computing-based digital filter designs demonstrates their potential in achieving superior performance metrics compared to conventional methods. Moreover, this paper discusses the advantages, challenges, and future directions in employing soft computing techniques for digital filter design, highlighting their potential for addressing complex signal processing tasks in diverse applications.

关键词： Finite impulse response filters Signal processing algorithms filtering algorithms Signal processing Linear programming Information filters Robustness

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Design of an FPGA-based Image Defogging Algorithm Using Dark Channel Prior

Design of an FPGA-based Image Defogging Algorithm Using Dark...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Tingting Zhang Chengdu University of Information Technology School of Communication Engineering Chengdu Sichuan China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

In recent years, with the rapid advancement of digital image processing technology, image dehazing has become a focal point in both scientific research and practical applications. This paper presents a study on a dehazing algorithm based on the dark channel prior and its optimization for FPGA implementation. To improve image refinement and reduce algorithm complexity, the filter window size for calculating the dark channel is simplified to 3×3. When estimating the global atmospheric light intensity (A), the brightest pixel in the dark channel image is selected as the A value. Based on this, the transmission map is computed, and a guided filter is introduced to smooth the image. Finally, FPGA is utilized to accelerate the algorithm, and a low-pass filter is employed instead of the guided filter to further reduce complexity and enhance processing efficiency, meeting the real-time dehazing requirements for high-resolution images.

关键词： Computer science Digital images Low-pass filters Channel estimation filtering algorithms Information filters Real-time systems Complexity theory Field programmable gate arrays Optimization

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A Step-by-Step Multi-Stage Filter Design Method of an Active Three-Phase Three-Level Rectifier for Aircraft Application

A Step-by-Step Multi-Stage Filter Design Method of an Active...

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International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM

作者： Robin Weiß Sebastian Rode Steffen Bernet Chair of Power Electronics Dresden University of Technology Dresden Germany

ISBN: (数字)9798350387599

ISBN: (纸本)9798350387605

The design of passive filters for rectifier topologies in modern aircraft is complicated by the variable frequency power supply and stringent regulatory requirements. This paper introduces a straightforward design approach that bypasses complex optimization algorithms, aiming to enhance power density. The referred method is applied to develop a passive, multi-stage filter for a bidirectional three-phase, three-level rectifier system.

关键词： Power system measurements Passive filters Power supplies Rectifiers Resonant frequency filtering algorithms Power electronics

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Implementation of Machine Learning-Based QoS Traffic Classification In Software-Defined Networking

Implementation of Machine Learning-Based QoS Traffic Classif...

引用

Asia-Pacific Conference on Applied Electromagnetics, APACE

作者： Nur Fatin Nabilah Mohd Fauzi Tan Saw Chin Fatimah Audah Md Zaki Faculty of Computing & Informatics Multimedia University Malaysia

ISBN: (数字)9798350364163

ISBN: (纸本)9798350364170

The concept of Software-Defined Networking (SDN) in network management involves controlling network behaviour through software applications. The implementation of SDN centralizes network management, ensuring efficient performance and reducing computational costs. With the vast amount of network traffic today, traffic classification is crucial in SDN, improving performance by prioritizing applications that require higher Quality of Service (QoS). The occurrence of imbalanced datasets, which focus more on the majority class rather than the minority class, leads to poor performance in SDN. This paper explores the implementation of feature selection using filter and wrapper methods to tackle imbalanced datasets and enhance network management performance. Using a real-time dataset containing 930 features from the University of Cambridge, the Symmetrical Uncertainty and C4.5 algorithm achieve a classification accuracy of 97.69% and reduced the dataset size by 50%. These findings demonstrate that the proposed methods significantly improve computational efficiency and classification performance, making them suitable for real-time SDN applications.

关键词： Accuracy Uncertainty Machine learning algorithms Quality of service Telecommunication traffic filtering algorithms Real-time systems Software Computational efficiency Software defined networking

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Diverse Image Processing Techniques for Machine Learning Methods

Diverse Image Processing Techniques for Machine Learning Met...

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IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)

作者： A. Bhagya S. Perumal Department of Computer Science Vels Institute of science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Machine learning is a trending topic in the area of computer vision, which makes the machine able to learn about it without being expressly programmed using various algorithms. When a model is designed to predict future-based on historical data using machine learning algorithms, data is vital because high quality data is needed to run the model efficiently and to predict highly accurate results. Machine learning algorithms receive data in many forms, like audio (speech recognition), images (feature recognition), numeric data (like height and weight) etc. When it comes to computer vision, the machine learning algorithms must be able to understand the image data, and before the images are processed to the algorithms it should be pre-processed (cleaned and set to the desired format) using various image pre-processing techniques. This research paper presents various image processing techniques, literature reviews on various image processing techniques and image PSNR value after applying median filter, grayscale filter and box filters.

关键词： Machine learning algorithms Image processing Signal processing algorithms Speech recognition Machine learning Gray-scale filtering algorithms

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Hardware Implementation of Two Level Authentication Algorithm Using Cryptography with Steganography for Text-Image Security

Hardware Implementation of Two Level Authentication Algorith...

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IEEE Electron Devices Kolkata Conference (EDKCON)

作者： Poulomi Ghosh Sudip Ghosh Hafizur Rahaman IIEST School of VLSI Technology Shibpur Howrah India

ISBN: (数字)9798350374643

ISBN: (纸本)9798350374650

This paper proposes two level authentication for an image communication through world wide web. The algorithm presented here mainly consist of techniques combined with symmetric key cryptography and LSB based steganography. Here two factor authentication are used that requires two forms of identification to access sensitive data. Symmetric key algorithms are algorithm for cryptography that use the same cryptographic keys for both the encryption of plaintext and the decryption of cipher text to maintain a private and secure communication. LSB steganography is commonly used technique for hiding secret messages within images. This algorithm can detoriate the secret message quality but still secret message is mostly recognized and is smoothed fine and noise reduced using Gaussian filter. Here the algorithm is implemented in software(using MATLAB) and in hardware(using FPGA and PSoC).

关键词： Steganography Image communication Noise Authentication filtering algorithms Hardware Encryption Web sites MATLAB Field programmable gate arrays

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