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Distortion Evaluation of EMP Sensors Using Associated-Hermite Functions

Computers, Materials & Continua 2023年第1期74卷 1093-1105页

作者： Rupo Ma Siping Gao College of Command and Control Engineering Army Engineering UniversityNanjing210007China Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjing210031China Department of Electrical and Computer Engineering National University of Singapore119260Singapore

Electromagnetic pulse(EMP)is a kind of transient electromagnetic phenomenon with short rise time of the leading edge and wide spectrum,which usually disrupts communications and damages electronic equipment and *** is challenging for an EMP sensor to measure a wideband electromagnetic pulse without distortion for the whole ***,analyzing the distortion of EMP measurement is crucial to evaluating the sensor distortion characteristics and correcting the measurement *** fidelity is usually employed to evaluate the distortion of an ***,this metric depends on specific signal waveforms,thus is unsuitable for evaluating and analyzing the distortion of EMP *** this paper,an associated-hermite-function based distortion analysis method including system transfer matrices and distortion rates is proposed,which is general and independent from individual *** system transfer matrix and distortion rate can be straightforwardly calculated by the signal orthogonal transformation coefficients using associated-hermite *** of a sensor *** is then visualized via the system transfer matrix,which is convenient in quantitative analysis of the *** of a current probe,a coaxial pulse voltage probe and a B-field sensor were performed,based on which the feasibility and effectiveness of the proposed distortion analysis method is successfully verified.

关键词： Electromagnetic pulse associated-hermite functions system transfer matrix distortion rate

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Artificial Intelligence Based Employee Attrition Analysis and Prediction 6

Artificial Intelligence Based Employee Attrition Analysis an...

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6th International Conference on Computing and Informatics, ICCI 2024

作者： Ozakca, Nazli Sila Bulus, Ali Cetin, Aydin Havelsan Inc.Command Control and Defence technologies Ankara Turkey Computer Engineering Department Gazi University Faculty of Technology Ankara Turkey

ISBN: (纸本)9798350373875

The use of classification models to predict the probability of an employee leaving the job can greatly improve the ability of human resources to intervene in a timely manner and rectify the situation to prevent attrition. After the so-called "The Great Resignation", which took place after the pandemic period, studies on attrition have increased in order to regain the lost workforce and increase the loyalty of existing employees. In Turkey, however, studies in this field remain insufficient. The aim of this study is to predict the possible loss of employees, to take relevant measures and to reduce the financial losses of companies. The study was made available as SaaS (Software as a Service) based in order to facilitate accessibility to the target audience. For the analysis phase, the columns in the data set were analyzed with Pandas and Scikit-Learn library. Exploratory Data Analysis was performed by visualizing the analyzed data with Plotly and Seaborn libraries. Various insights were obtained with these inferences. The data was subjected to pre-processing stages such as cleaning, missing data completion, scaling, feature selection, data set balancing, dimension reduction, etc. to make it useful. Logistic Regression, KNN, SVM, Desicion Tree, Random Forest, ADABoost and Naive Bayes were used to train the model. In order to enrich the data set and increase the efficiency of the model, artificial intelligence-based synthetic data generation (Data Augmentation) was performed. In case of missing columns in the trained model, KNN-Data Imputation, one of the missing data completion methods, was used. In the optimization process of the model, hyperparameter optimizations were performed to achieve maximum efficiency with improvements. 5-fold cross-validation prevented the model from over-learning. Performance was analyzed on the basis of Accuracy, Recall, Precision and F1-score metrics and the success criterion was determined as F1-Score. The model was presented as a web se

关键词： Efficiency

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Monaural speech enhancement using U-net fused with multi-head self-attention

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Chinese Journal of Acoustics 2023年第1期42卷 98-118页

作者： FAN Junyi YANG Jibin ZHANG Xiongwei ZHENG Changyan Graduate School Army Engineering UniversityNanjing 210007 College of Command and Control Engineering Army Engineering UniversityNanjing 210007 Department of Test Control High-tech InstituteQingzhou 262500

Under low signal-to-noise ratio(SNR)and burst noise conditions,the speech enhancement effect of existing deep learning network models is not *** contrast,humans can exploit the long-term correlation of speech to form an integrated perception of different speech ***,describing the long-term dependencies of speech can help improve the enhancement performance under low SNR and burst noise *** by this feature,a time domain end-to-end monaural speech enhancement model TU-net that fuses the multi-head self-attention mechanism and U-net deep network is *** TU-net model adopts the codec layer structure of U-net to achieve multi-scale feature *** introduces the dual-path Transformer module using the multi-head self-attention mechanism to calculate the speech mask and better model long-term *** TU-net model is trained with a weighted sum loss function in the time,time-frequency,and perceptual *** experiments are carried out and the results show that with maintaining relatively fewer network model parameters,TU-net outperforms other similar monaural enhancement network models in several evaluation metrics such as perceptual evaluation of speech quality(PESQ),short-time objective intelligibility(STOI)and SNR gain under low SNR and burst noise conditions.

关键词： network speech noise

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Operational Modelling of Rotor-Magnetic Bearing Systems in Rotation 39

Operational Modelling of Rotor-Magnetic Bearing Systems in R...

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39th Annual Meeting of the American Society for Precision engineering, ASPE 2024

作者： Wallace, Brett Lee, Jihyun Farhat, Armand Department of Mechanical and Manufacturing Engineering University of Calgary CalgaryAB Canada Department of Control Command Research SKF S2M Magnetic Mechatronics Saint-Marcel Normandy France

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Design and Tuning of Fuzzy controller using Human Inspired Algorithm for Speed control of PMSM 2

Design and Tuning of Fuzzy Controller using Human Inspired A...

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2nd International Conference on Electronics, Energy and Measurement, IC2EM 2023

作者： Nouaoui, Tahar Dendouga, Abdelhakim Bendaikha, Abdelmalik University of Biskra Laboratory of Identification Command Control and Comunication Biskra Algeria University of Biskra Electrical Engineering Department Biskra Algeria University of m'Sila Electrical Engineering Department Msila Algeria

ISBN: (纸本)9798350314243

designing a decent controller for a speed control of an alternative current (AC) machine, such as the PMSM can be very challenging, the conventional PID and PI controllers are the most used in the industry, but they lack the robustness and the rapid response of A fuzzy controller(FC), the fuzzy controller however needs a very precise scaling of its inputs, outputs, and its membership functions (MFS), this could be done with some serious user experience, or via trial and error technique, which is very time consuming and inconsistent, in this paper a human inspired optimization algorithm called Sewing Training-Based Optimization (STBO) was used to tune the parameters of a specially designed FC, within an hour of tuning the obtained FC managed to achieve significantly better speed tracking, and produce way less current harmonics than the conventional PID and PI controllers. © 2023 IEEE.

关键词： Speed control

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Fractional Order PID Tuned using Symbiotic Organism Search Algorithm for Field Oriented control of The Permanent Magnet Synchronous Motor

Fractional Order PID Tuned using Symbiotic Organism Search A...

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2023 International Conference on Advances in Electronics, control and Communication Systems, ICAECCS 2023

作者： Nouaoui, Tahar Dendouga, Abdelhakim Bendaikha, Abdelmalik University of Biskra Laboratory of Identificationcommandcontrol and Comunication Biskra Algeria University of Biskra Electrical Engineering Department Biskra Algeria University of m'Sila Electrical Engineering Department M'sila Algeria

ISBN: (纸本)9781665463102

This paper presents the model of the permanent magnet synchronous motor (PMSM) controlled by the field oriented control (FOC) technique using the fractional order proportional, integral, and derivative (FOPID) regulators. To bring out the maximum potential of the FOPID controller the algorithm of symbiotic organism search (SOS) has been used to obtain the gains of the latter. SOS, FOC, and fractional calculus were explained. The tuning efficiency of SOS has been compared to that of the algorithm of particle swarm optimization (PSO) when tuning the FOPID controllers for the PMSM under identical conditions and constraints. SOS algorithm managed to achieve better fitness than PSO. The obtained controllers were tested under various speeds and load charges. The inspection of the simulated results of speed, torque and induced currents proved the supremacy of SOS over PSO when tuning the parameters of the FOPID. © 2023 IEEE.

关键词： Vector control (Electric machinery)

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Multi-agent Reinforcement Learning Algorithm Based on Role Parameter Sharing 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhang, Hui Xu, Chi Zhang, Ting-Ting Zhang, Ya School of Automation Southeast University Nanjing210096 China High-Tech Department Jiangsu Automation Research Institute Lianyungang222061 China School of Command and Control Engineering Army Engineering University Jiangsu Nanjing210017 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

In multi-agent reinforcement learning, scalability is a significant challenge. Applying reinforcement learning algorithms in large-scale multi-agent systems requires consideration of algorithm efficiency. This paper attempts to reduce network parameter quantity and training time from the perspective of parameter sharing. However, parameter sharing may also bring some disadvantages, such as policy similarity, which may limit the formation of cooperative policies and affect the efficiency of the entire system. To address the problems caused by parameter sharing, this paper proposes a multi-agent reinforcement learning algorithm with role parameter sharing (R-PS). By dynamically dividing roles and selecting objects for parameter sharing, R-PS automatically identifies intelligent agents that may generate beneficial parameter sharing and conducts partial parameter sharing within the roles. Meanwhile, intrinsic rewards are introduced to increase the diversity of agent strategies. Experimental results show that R-PS can effectively divide roles, benefit from partial parameter sharing, and form diverse policies through intrinsic rewards. It also reduces training time, produces excellent performance and collaboration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Parameter tuning of active disturbance rejection control based on improved differential evolution algorithm 7

Parameter tuning of active disturbance rejection control bas...

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7th International Conference on Intelligent Computing and Signal Processing, ICSP 2022

作者： Gao, Li Guo, Xiaofeng Mei, Dan Qu, Zhigang Naval Aviation University Department of Aeronautical Electric Control Engineering and Command Qingdao Campus Qingdao266041 China

ISBN: (纸本)9781665478571

Aiming at the problem that it is difficult to obtain the optimal parameters and performance of nonlinear active disturbances rejection controller (ADRC) by the method of conventional empirical turning, a parameter tuning method based on improved differential evolution algorithm (DE) is proposed to enhance the accuracy of the controller. Firstly, to balance the global and local search abilities appropriately, the random neighborhood-based mutation strategy is proposed. In addition, a history-driven parameters self-adaptation method is implemented to enhance the accuracy of the optimization and accelerate the searching progress. Lastly, the generalized opposition-based learning (GOBL) scheme is applied to avert the DE getting trapped in local optimum and improve the diversity of the population. The result of optimized ADRC shows that it has less overshoot and higher control accuracy. After adding external disturbance, the optimized ADRC can still maintain perfect performance of control which indicates that it has good anti-interference ability. © 2022 IEEE.

关键词： controllers

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Research on Indoor Positioning of Multi-source Information Fusion Based on Improved Particle Filter 22

Research on Indoor Positioning of Multi-source Information F...

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6th International Conference on Computer Science and Application engineering, CSAE 2022

作者： Zhou, Chulin Chen, Shiyou Chen, Jingdong Department of Command and Control Systems Wuhan Institute of Digital Engineering Wuhan China Department of Information and Electronics Wuhan Institute of Digital Engineering Wuhan China

ISBN: (纸本)9781450396004

In the information age, people are increasingly demanding location-based services. The traditional indoor positioning based on a single signal source has low accuracy and poor stability. On the one hand, the occlusion and echo interference in the indoor environment are serious, especially in the case of crowded environment and non-line-of-sight propagation, the UWB (Ultra Wide band) positioning accuracy will be greatly reduced. On the other hand, IMU (inertial Measurement Unit) can provide an accurate inertial navigation solution in a short time but its positioning error increases fast with time due to the cumulative error of accelerometer measurement. Therefore, in the process of pedestrian walking, we use the key information obtained by PDR (Pedestrian Dead Reckoning) to establish and update the real-time motion model of the target and calculate the prior information in the process of fusion filtering. Then, the initial position of the target is obtained through the UWB positioning solution, and the PDR positioning trajectory is corrected as the observation information in the fusion filtering process. Finally, the improved differential particle filter algorithm is used to fuse the above UWB positioning results and PDR positioning results, and make up for the advantages and disadvantages of the two positioning to improve the accuracy and stability of fusion positioning. © 2022 Association for Computing Machinery.

关键词： Location based services

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Computer Practice Course Lightweight Online Teaching Design Based on CSCL 3

Computer Practice Course Lightweight Online Teaching Design ...

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3rd IEEE International Conference on Computer Science and Educational Informatization, CSEI 2021

作者： Zhang, Wenyu Zhao, Honghua Wang, Rui Yuan, En Tang, Yanqin Wu, Yongfen Army Engineering University of Pla Department of Command and Control Engineering Nanjing China

ISBN: (纸本)9781728184739

Computer practice teaching need efficient and lightweight online collaborative learning platform between teachers and students. Based on CSCL learning scenario, we propose a method of building online teaching platform of computer practice course by combining various lightweight mobile Internet tools, and conducts an empirical study in the course of 'Innovation engineering Practice'. The results show that lightweight online collaboration platform can promote efficient interaction between learners, improve self-management of learners, and improve learning effect and self-evaluation of learners. © 2021 IEEE.

关键词： Curricula

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