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检索条件"主题词=filtering algorithms"

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Novel Civil Engineering Construction Site Safety Monitoring and Warning System based on Machine Vision

Novel Civil Engineering Construction Site Safety Monitoring ...

引用

Electronics and Renewable Systems (ICEARS), International Conference on

作者： Qiankun Zhang Qibin Cheng Zhejiang Construction Investment Innovation Technology Co. Ltd. Hangzhou China Zhejiang Construction Engineering Group Co. Ltd. Hangzhou China

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Machine vision is widely used in the engineering field, especially in the intelligent monitoring, safety warning and information recognition scenarios. In this study, the novel civil engineering construction site safety monitoring and warning system based on machine vision is proposed. As a pioneering research, this system realizes all-weather real-time security monitoring by combining the daytime and nighttime image processing technology. In daytime image processing scenarios, this study proposes a new image de-hazing algorithm. This algorithm models the imaging process by improving the atmospheric scattering model. At the same time, the guided filtering algorithm is used for optimization, which significantly improves the image clarity in low-visibility environments. In the night image processing scenario, this study uses infrared imaging technology and filtering algorithms for image enhancement. This operation can effectively solve the challenges of image noise and detail loss in low-light environments. As the core of the model, this study proposes a safety warning framework based on image anomaly detection to meet the special needs of construction sites. This innovative architecture includes human posture rotation detection and image color deviation anomaly recognition. Through such operations, automatic recognition and warning of dangerous behaviors are achieved. Experimental results prove the effectiveness of the recognition algorithm.

关键词： Renewable energy sources Machine vision Atmospheric modeling Scattering Alarm systems filtering algorithms Real-time systems Monitoring Civil engineering Optimization

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Intelligent Intrusion Detection in IoT: Integrating Machine Learning and Feature Automation

Intelligent Intrusion Detection in IoT: Integrating Machine ...

引用

International Conference on Computer and Automation Engineering, ICCAE

作者： Nazratun Naim Neha A. A. M. Muzahid Md Shamsuzzoha Imrul Jahid Hua Han Yujin Zhang Md Musabbir Hossain Ferdous Sohel School of Electronic and Electric Engineering Shanghai University of Engineering Science Shanghai China Hawaii Natural Energy Institute University of Hawaii at Manoa Honolulu HI USA School of Information Technology Murdoch University Murdoch WA Australia

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

The rapid growth of the internet of things (IoT) raises serious security concerns, demanding effective protection from cyber-attacks. Intrusion detection depends on identifying key features, but despite advances in automation, manual feature selection remains necessary, limiting scalability. To address this limitation, we introduced a hybrid feature selection method that combines filter and wrapper techniques to automatically select important features and enhance the efficiency of machine learning (ML) models for intrusion detection tasks. We utilized the mutual information (MI) algorithm as the filter method and recursive feature elimination (RFE) as the wrapper method. We evaluated the performance of the proposed model on publicly available datasets, HIKARI2021 and UNSW-NB15. We compared the results with several existing methods, and our approach outperformed the state-of-the-art (SOTA) methods in terms of accuracy and training time. We presented comprehensive results, including both quantitative and qualitative analysis, to demonstrate the effectiveness and efficiency of our proposed methods.

关键词： Training Automation Machine learning algorithms Limiting Intrusion detection filtering algorithms Feature extraction Information filters Internet of Things Security

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Optimal Design of LLCL Parameters Based on APSO

Optimal Design of LLCL Parameters Based on APSO

引用

Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Zeyuan Huang Youhang Deng Northeast Electric Power University China Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

For the novel LLCL structure, current research primarily focuses on damping strategies. For instance, [4] developed a biquad filter-based active damping method combined with a proportional-integral multiresonant repetitive controller. However, the control strategy must be adjusted accordingly, increasing the complexity of the control algorithm and reducing system reliability and robustness. In contrast, research on LLCL filter parameter design is limited. [5] determined the parameters of each filter component through iterative calculations under various constraints, but this method is complex and often relies on empirical tuning, leading to imprecision.

关键词： Damping Passive filters Design methodology filtering algorithms Robustness Inverters Smart grids Iterative methods Optimization Tuning

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Trajectory PHD Filter for Extended Traffic Target Tracking with Interaction and Constraint

Trajectory PHD Filter for Extended Traffic Target Tracking w...

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International Conference on Information Fusion

作者： Xi Cao Yunlian Tian Jiaye Yang Wujun Li Wei Yi School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

With the increasing demand for traffic situation awareness, extended traffic target (ETT) tracking is a significant yet challenging task especially in tough scenarios with dense and various ETTs. Due to the spatial proximity of ETTs and a noisy sensor, it is challenging for multi-target tracking algorithms to effectively distinguish and track ETTs. To improve the accuracy and robustness of ETT tracking in tough traffic scenarios, we analyze the interaction among ETTs and the lane constraint. Firstly, we develop an interactive motion model for collision avoidance to address trajectory confusion when ETTs are in close proximity. Additionally, we propose a lane constraint method that models lanes as pseudo measurements and constrains the motion of ETTs via pseudo update. Considering the complexity and extendibility, the extended target trajectory probability hypothesis density (ETTPHD) filter is adopted to achieve a more accurate estimation of ETT trajectories. Specifically, we realize the proposed interactive motion model and lane constraint method based on the ETTPHD (IC-ET-TPHD) filter. Performance comparisons between our proposed filter and other algorithms are conducted through both simulations and experiments.

关键词： Target tracking Accuracy Estimation filtering algorithms Information filters Robustness Trajectory Noise measurement Collision avoidance Standards

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Distributed Estimation of Anomalies using a Low Complexity PSO Algorithm

Distributed Estimation of Anomalies using a Low Complexity P...

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Emerging Trends in Smart Technologies (ICETST), 2020 International Conference on

作者： Muhammad Omer Bin Saeed Salman A. Khan Naveed R. Butt Nazeeruddin Mohammad Azzedine Zerguine Faculty of Engineering Sciences GIK Institute of Engineering Sciences & Technology Topi Pakistan College of Computing & Information Sciences Karachi Institute of Economics & Technology Karachi Pakistan College of Computer Engineering and Science Prince Mohammad Bin Fahd University AlKhobar Saudi Arabia Department of Electrical Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331515850

ISBN: (纸本)9798331515867

Any wireless sensor network can experience anomalies that can hinder performance. This work presents a distributed estimation algorithm that estimates any such anomalies using a PSO algorithm. PSO algorithms are computationally expensive. This work presents a low complexity version of the algorithm that removes redundant computations and achieves excellent performance as well. Low complexity algorithms are essential for a longer battery life of wireless sensor so this algorithm provides an excellent alternative to the basic linear adaptive filtering algorithms that have low complexity but require a lot more time to achieve similar results.

关键词： Wireless communication Wireless sensor networks Estimation filtering algorithms Market research Computational efficiency Particle swarm optimization Computational complexity Standards Convergence

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Optimal Design of Tunable Bandpass Audio Filter using Variable Learning Rate Backpropagation Algorithm

Optimal Design of Tunable Bandpass Audio Filter using Variab...

引用

IEEE International Conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Adedayo Olukayode Ojo Oladapo Tolulope Ibitoye Moses Oluwafemi Onibonoje Saheed Lekan Gbadamosi Oluwasemilore E. Aina Ezeobidi Clementina Oyinyechukwu Department of Electrical/Electronics and Computer Engineering College of Engineering Afe Babalola University Ado-Ekiti Ado-Ekiti Ekiti State Nigeria Department of Electrical Electronics Engineering Bowen University Iwo Osun State Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Artificial intelligence techniques are increasingly being employed for solving optimization problems due to their simplicity and speed. And artificial neural networks and their many variants are unsurprisingly at the forefront of this growing trend. In this paper, a variable learning rate backpropagation algorithm (VLRBA) was deployed to train a designed tunable bandpass audio filter for optimal performance. Different configurations of the neural network were evaluated and the best performing network was selected for the task. The performance of the neural network was analyzed using standard metrics such as regression and mean square error. The high training regression value of 0.99328 and testing regression value of 0.98381, achieved after 129 iterations, demonstrate the effectiveness of the variable learning rate backpropagation model in optimizing the tunable bandpass filter circuit. This, therefore, represents an important addition in the quest for faster and efficient circuit designs, especially in the sound engineering domain.

关键词： Band-pass filters Training Measurement Backpropagation Backpropagation algorithms Artificial neural networks Learning (artificial intelligence) filtering algorithms Integrated circuit modeling Optimization

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Deployment of an Advanced Wi-Fi Data Firewall System to Enhance Security in the IoT Ecosystem

Deployment of an Advanced Wi-Fi Data Firewall System to Enha...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Blessy Thankachan Hilda Jerlin C M Rakshit Kothari KK Dewan Gotte Ranjith Kumar Shashikant JECRC University Jaipur India Panimalar Engineering College Chennai India College of Technology and Engineering MPUAT Udaipur India NITRA Technical Campus Ghaziabad India SR University Warangal India Babu Banarasi Das University Lucknow India

ISBN: (数字)9798350396157

ISBN: (纸本)9798350396164

The need for effective security measures has expanded enormously in the fast-changing Internet of Things (IoT) environment of today. Protecting the confidentiality and integrity of data flows has become increasingly important as more devices connect to networks, especially in corporate settings where sensitive information is shared. The proposed set out on a quest to envision and put into practice a thorough Wi-Fi Data Firewall using the adaptable ESP32 development board in order to address these important issues, strengthen IoT security, and Employ optimization techniques like algorithmic efficiency and resource management to reduce computation load. This research primarily focuses on developing an intelligent security gateway to safeguard data for the Internet of Things while monitoring, auditing, and identifying intrusions. The system's brain is the ESP32 microcontroller, which is used to connect to Wi-Fi networks and gather all the data in the suggested innovation. To increase the high security for IoT data, a solution has been proposed: a filter algorithm based on the ESP32 board used here to filter all the data that organization used to send or receive through internet or intranet. All the algorithm has been stored in the esp32 so that real-time monitoring and filtering can be done based on the stored algorithm. IP filtering is accomplished by comparing source and destination IP addresses with predefined rules deciding whether to allow or deny packets based on these addresses. The main goal of the proposed hardware to provide a flexible & adaptive Wi-Fi Data Firewall based on hardware filter for use in office and commercial networks so that it can improve those networks' overall security posture. Additionally, this hardware-based firewall helps to monitor and quick detection of security threats and provide alert of any breaches to the organization's authority. The purpose of this study is to provide IoT data security filter and monitoring for the organization

关键词： Technological innovation Firewalls (computing) Organizations filtering algorithms Hardware Real-time systems Security

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Automatic Filter Design Algorithm based on Machine Learning and Synthesis

Automatic Filter Design Algorithm based on Machine Learning ...

引用

IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Lihang Liao Xiangyu Zou Zhiyuan Wang Chen Ma Feixuan Huang Xi He Qinghua Ren Fengyuan Yang Yiming Ma Jianlin Chen Nan Wang School of Microelectronics Shanghai University Shanghai China Proto Univista Shanghai China

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

The traditional Film Bulk Acoustic Resonator (FBAR) filter design process is usually assisted by optimization algorithms. The design process requires multiple iterations of parameters in a large range to reach convergence, resulting in high time cost and low design efficiency.A algorithm combining machine learning and circuit synthesis is proposed in order to improve the design efficiency of FBAR filters. Through this algorithm, the structure of each FBAR can be obtained by only inputting the sampled value of S parameter, instead of iterating the structure of FBAR in the conventional *** filter constructed by this algorithm has better performance. At the same time,the design time is much shorter than the traditional algorithm, thus the design efficiency can be significantly improved.

关键词： Machine learning algorithms Resonator filters Process control Machine learning filtering algorithms Scattering parameters Film bulk acoustic resonators Passband Frequency control Optimization

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Using a Stochastic Differential Equations to Form of Non-Gaussian Random Processes. Part 1

Using a Stochastic Differential Equations to Form of Non-Gau...

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Dynamics of Systems, Mechanisms and Machines (Dynamics)

作者： V. M. Artyushenko V. I. Volovach Information technology and management systems department Technological University Korolev city Russia Informational and electronic service department Volga Region State University of Service Togliatty city Russian Federation Voronezh State University Voronezh city Russia

ISBN: (数字)9798331509019

ISBN: (纸本)9798331509026

The formation of non-Gaussian random processes by using stochastic differential equations is described. algorithms for the formation of scalar continuousvalued, vector and discrete processes, as well as multi-linked sequences are presented. The analysis of the forming filter with parametric noise is carried out. The block diagram of the named filter is given. It is shown that the choice of parameters of input influences of the forming filter allows receiving an output signal with density of distribution of probabilities of Pearson family. It is also shown that in systems with parametric noise the probability density of the output variables is not Gaussian.

关键词： Maximum likelihood detection Noise Differential equations Nonlinear filters filtering algorithms Probability density function Markov processes Vectors Mathematical models Random processes

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Analysis of the Kalman Filter with the MPU6050 Accelerometer and Gyroscope

Analysis of the Kalman Filter with the MPU6050 Accelerometer...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Pranav Swarup Kumar U. Vignesh School of Computer Science and Engineering Vellore Institute of Technology (VIT) Chennai Tamil Nadu India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Abstmet -Reliable sensor measurements are essental for autonomous navigation, control systems and various other applications. We studied a model of a gesture controlled wheelchair. A key finding is that the processing unit must be able to filter out noise so that the efficacy of the wearable device is improved. In this paper, we demonstrate the application of the Kalman filter to combine measurements in the presence of noise or drift, to calculate the orientation from the inertial measurement unit, MPU6050. We report the behoviour of the gyroscope and accelerometer by measuring their output values individually first, and then passing them through the Kalman Filter. Alternatives such as the recursive average and moving average filters are also discussed. The characteristics of the filter for different parameters such as the standard deviation are plotted. Finally, the Kalman gain convergence for a steady state is verified.

关键词： Accelerometers Wheelchairs Noise Process control filtering algorithms Gyroscopes Kalman filters Noise measurement Standards Convergence

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