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检索条件"主题词=Filtering algorithms"

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Detection of Water Quality in Sediment Filter for Water Purification System

Detection of Water Quality in Sediment Filter for Water Puri...

引用

E-mobility, Power Control and Smart Systems (ICEMPS), International Conference on

作者： T. Kalavathidevi R. Mouleeshuwarapprabhu E.B. Priyanka V.K. Shubhashree K. Srihariramana T.G. Thilochan Electronics and Instrumentation Engineering Kongu Engineering College Erode India (SrG) Electronics and Instrumentation Engineering Kongu Engineering College Erode India Department of Mechatronics Kongu Engineering College Erode India Electronics and Instrumentation Engineering Kongu Engineering College Erode India

ISBN: (数字)9798350394399

ISBN: (纸本)9798350394405

Efficient water purification is vital for ensuring access to clean and safe drinking water. One essential component of water purification systems is the sediment filter, responsible for removing particulate matter and debris from the water. Monitoring and maintaining the performance of sediment filters are critical to guarantee the overall effectiveness of the water purification process. This study focuses on the development of a detection method to assess the water quality within sediment filters. The proposed detection method combines advanced sensing technologies and data analysis techniques to continuously evaluate the sediment filter's efficiency and identify potential issues. The system can promptly detect deviations from optimal performance by integrating real-time monitoring of key water quality parameters, such as turbidity, sediment concentration, and pressure differentials. Additionally, machine learning algorithms are employed to analyze the collected data, enabling the system to predict sediment filter clogging and degradation trends.

关键词： Temperature sensors Temperature measurement Purification Image color analysis Turbidity filtering algorithms Water pollution

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Interactive Counterfactual Exploration of Algorithmic Harms in Recommender Systems

Interactive Counterfactual Exploration of Algorithmic Harms ...

引用

IEEE Visualization in Data Science (VDS)

作者： Yongsu Ahn Quinn K Wolter Jonilyn Dick Janet Dick Yu-Ru Lin University of Pittsburgh Quest Diagnostics

ISBN: (数字)9798331528423

ISBN: (纸本)9798331528430

Recommender systems have become integral to digital experiences, shaping user interactions and preferences across various platforms. Despite their widespread use, these systems often suffer from algorithmic biases that can lead to unfair and unsatisfactory user experiences. This study introduces an interactive tool designed to help users comprehend and explore the impacts of algorithmic harms in recommender systems. By leveraging visualizations, counterfactual explanations, and interactive modules, the tool allows users to investigate how biases such as miscalibration, stereotypes, and filter bubbles affect their recommendations. Informed by in-depth user interviews, this tool benefits both general users and researchers by increasing transparency and offering personalized impact assessments, ultimately fostering a better understanding of algorithmic biases and contributing to more equitable recommendation outcomes. This work provides valuable insights for future research and practical applications in mitigating bias and enhancing fairness in machine learning algorithms.

关键词： Machine learning algorithms Data visualization filtering algorithms Data science Interviews Recommender systems

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A High Accuracy Extraction Method of Point Cloud Vectors for Guiding Robotic Arm Movement

A High Accuracy Extraction Method of Point Cloud Vectors for...

引用

System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Ruoyu He Yihang Li Min Jia Peng Zhang Bin Liu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

A path planning method based on point cloud for robotic arm movement was proposed, which provides the 3D point and its vector direction for each moving position. First, an effective filtering algorithm is utilized to smooth the original point cloud. Then, the least squares method is employed to perform plane fitting on local regions of the filtered point cloud. Finally, the points with the corresponding normal vectors could be obtained for guiding the robotic arm movement. Experiments were designed to evaluate our method. Two filtering algorithms are carefully compared and chosen to simultaneously guarantee the accuracy of the gathered points and normal vectors, an evaluation metric is proposed. The point cloud of a standard sphere was acquired and fitted to calculate the sphere center. Each point and its normal vector determine one spatial line. The distance from the sphere center to each spatial line is defined as the quantitative indicator of the evaluation metric. Experimental results proved that the proposed method and evaluation metric are feasible and effective for precise motion control of robotic arms.

关键词： Point cloud compression Measurement Accuracy Three-dimensional displays filtering algorithms Manipulators Vectors Path planning Systems simulation Standards

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Substation Inspection Robot Location Method Based on Improved Particle Filter

Substation Inspection Robot Location Method Based on Improve...

引用

IEEE International Conference of Intelligent Robotic and Control Engineering (IRCE)

作者： Xiaoyan Wei William P. Rey Xinghua Liu School of Information Technology Mapua University Manila Philippine Xi’an Siyuan University Xi’an China School of Electrical Engineering Xi’an University of Technology Xi’an China

ISBN: (数字)9798350352399

ISBN: (纸本)9798350352405

The appearance of substation inspection robot marks the great leap of intelligent automation in the field of substation maintenance. Compared with the traditional manual inspection method, it has the advantages of high efficiency, low cost and improved personnel safety. In order to further improve the positioning accuracy of the robot, this paper first adjusts the relevant parameters in real time on the basis of the elementary particle swarm optimization algorithm to obtain more accurate estimation results. Secondly, aiming at the problem of low location of the basic particle filter algorithm and combining the advantages of particle swarm optimization algorithm, a new improved particle filter algorithm is proposed. Finally, the improved algorithm is applied to the location of substation inspection robot, and compared with extended Kalman filter, unscented Kalman filter and elementary particle filter, the effectiveness of the improved algorithm is verified.

关键词： Substations Accuracy Elementary particles Inspection filtering algorithms Particle filters Kalman filters Particle swarm optimization Robots Optimization

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Design of L-Band Small-Sized Cavity Filters

Design of L-Band Small-Sized Cavity Filters

引用

International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Yuan-Hao Tang China Electronics Technology Group Corporation 38th Research Institute Hefei China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

This paper introduces a third-order cavity filter operating at a frequency range of 1.2-1.4 GHz. The filter adopts a direct coupling topology, which is simple and easy to optimize design and process. Compared to a cross-coupling filter, the direct coupling structure is more widely used in practical industrial applications Additionally, a gradient optimization algorithm is utilized to optimize the coupling matrix, which in turn optimizes the transmission zero points. This results in the filter exhibiting better performance in terms of in-band insertion loss and out-of-band suppression.

关键词： Couplings Hands Antenna theory Simulation Insertion loss filtering algorithms filtering theory Topology Optimization L-band

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Design of Fifth-Order Chebyshev Bandpass Filter Using Group Delay of the Reflection Coefficient Based on Space Mapping

Design of Fifth-Order Chebyshev Bandpass Filter Using Group ...

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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： Yihang Li Feng Feng Jingpei Zhang Wei Liu Kaixue Ma Qi-Jun Zhang School of Microelectronics Tianjin University Tianjin China Department of Electronics Carleton University Ottawa ON Canada

ISBN: (数字)9798350383317

ISBN: (纸本)9798350383324

The group delay characteristics of the reflection coefficient for circuit design are introduced. The waveguide filter is simulated with the group delay of the reflection coefficient of the circuit as the target. Due to the symmetry of the filter, the simulation parameters are halved. After obtaining the initial optimization curve, the space mapping algorithm is applied to filter design optimization. Finally, a 5-pole Chebyshev bandpass filter has been successfully designed according to the proposed design method.

关键词： Band-pass filters Design methodology Space mapping Electromagnetic waveguides filtering algorithms Chebyshev approximation filtering theory

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Optimal Reduced-order Filter for Systems with Deterministic Observations and Stochastic Observations

Optimal Reduced-order Filter for Systems with Deterministic ...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Yuan Gao Shuli Sun School of Electronic Engineering Heilongjiang University Harbin China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

For linear discrete time-invariant systems with deterministic observations and random observations, the optimal reduced-order filtering problem is studied. Some of the state components can be obtained directly by deterministic observation, while others can be obtained by designing a reduced-order state filter. Compared with the method of augmenting the observation, it not only reduces the calculation burden, but also avoids the problem of numerical instability caused by the singular observation noise variance matrix. The method presented in this paper can solve the estimation problem of systems with state equality constraint and singular observation noise variance matrix. A simulation example verifies the effectiveness of algorithm.

关键词： filtering Noise Estimation filtering algorithms filtering theory

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Android Malware Detection using Fast Correlation Based Filter and Random Forest Algorithm

Android Malware Detection using Fast Correlation Based Filte...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Sabrina Aska Amalina Fauzi Adi Rafrastara Muhammad Ibadullah Faculty of Computer Science Universitas Dian Nuswantoro Semarang Indonesia

ISBN: (数字)9798350366648

ISBN: (纸本)9798350366655

Malware analysts have faced several difficulties in the past few years due to the rapid growth of Android malware. This surge in Android malware not only threatens the security and privacy of users but also undermines the integrity of the Android ecosystem. As cybercriminals get more advanced, the methods for detecting and dealing with malware need to grow more sophisticated. To find the best combination for identifying Android malware, this study compares different machine learning algorithms and feature selection techniques. The dataset used in this research is the CICMaldroid2020 dataset. The results indicate that the combination of the Fast Correlation-Based Filter feature selection method and the Random Forest algorithm achieved the highest performance, with both accuracy and F1-Score at 92.5%.

关键词： Seminars Privacy Machine learning algorithms filtering algorithms Information filters Feature extraction Malware Security Surges Random forests

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Algorithm for the Multi-target Joint Detection and Ambiguity Resolving Based on Dynamic Programming

Algorithm for the Multi-target Joint Detection and Ambiguity...

引用

Progress in Electromagnetic Research Symposium (PIERS)

作者： Yitong Mao Chong Song Bingnan Wang Chenhao Zhao National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences China State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The mode of wide range surveillance and over-sight detection of satellite platform brings serious range ambiguity. The traditional method is to transmit multiple Pulse Repetition Frequencies (PRFs) and correlate them to solve the ambiguity. To ensure the detection of targets by using low threshold, which will lead to a large number of false alarms. In order to solve this problem, a new algorithm for the multi-target joint detection and range ambiguity resolving based on dynamic programming algorithm (DP) is presented. The algorithm divides the false alarm suppression and deblurring into several sub-problems. By splitting into sub-sequences for association operations, and then the sub-results are associated to obtain the unambiguous target state prediction that suppresses false alarms. It effectively alleviates the problem of sudden increase in computational complexity caused by the multi-target, and has better real-time performance.

关键词： Satellites Heuristic algorithms Surveillance Estimation filtering algorithms Prediction algorithms Real-time systems

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Smart Recommendation System For Flourishing Gardens Using Deep Learning Techniques

Smart Recommendation System For Flourishing Gardens Using De...

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Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： M. Meenalochini S. Kishore V. Sabarika S. Nandhakumar Department of CSD Kongu Engineering College Tamil Nadu India

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Our project introduces a specialized model focusing on companion planting, specifically for the onion-carrot pair. It integrates advanced deep learning algorithms, including graph neural networks (GNNs), collaborative filtering, and content-based filtering. The model offers personalized companion plant recommendations based on user input and incorporates pest control and disease prediction functionalities tailored to selected plants. Through thorough data analysis and consideration of user preferences, the model provides customized suggestions to optimize plant growth and health, taking into account environmental factors such as climate conditions. Utilizing GNNs, the model enhances pest control by analyzing images to identify pests, while collaborative filtering refines pest management strategies based on similar contexts. For disease prediction, content-based filtering evaluates historical data and plant traits to forecast disease risks, facilitating proactive measures for plant health protection. By harnessing advanced deep learning techniques and tailored recommendations, this project aims to empower agricultural practitioners with actionable insights for sustainable gardening practices, enhancing crop productivity, and promoting environmental stewardship in agriculture.

关键词： Deep learning Productivity Analytical models filtering Collaborative filtering Pest control filtering algorithms Prediction algorithms Graph neural networks Diseases

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