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检索条件"任意字段=3rd International Conference on Informatics in Control, Automation and Robotics"

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Total Harmonic Distortion Reduction in a Power Grid: A UPQC Based Approach

Total Harmonic Distortion Reduction in a Power Grid: A UPQC ...

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international conference on robotics,Electrical and Signal Processing Techniques (ICREST)

作者： Bishwajit Banik Pathik Sanjid Islam Nur Mohammad Akram Md. Salman Zaman Md. Abdullah Al-Nahian Dept. of Electrical and Electronic Engineering American International University-Bangladesh Dhaka Bangladesh

This study shows a novel design for a unified power quality conditioner (UPQC) to improve the power quality. The designed UPQC has two active power filters (APF) in shunt and series combinations. PWM (pulse width modulation) and hysteresis controls are the two control mechanisms used in this study. To reduce harmonics, a direct-quadrature zero (dq0) conversion is performed. In case 1, for a single-bus system, the total harmonic distortion (THD) of the source current in the system without UPQC was 22.22%. After applying the designed method, THD has been reduced significantly to 2.68%. In case 2, for multi-bus systems, the THD was 20.62% and 5.05% with and without the UPQC, respectively. Here the THD in the grid input voltage was 20.62%, whereas the output voltage was 0.80%. The IEEE 519–2014 standard for voltage and current harmonics distortion criterion for electrical system design is followed in the research.

关键词： Total harmonic distortion Power quality Standards organizations Pulse width modulation Harmonic analysis Active filters Power grids

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An effect of process parameters during wire cut electrical discharge machining of Inconel 738 3

An effect of process parameters during wire cut electrical d...

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3rd international conference on Sustainable Energy Solutions for a Better Tomorrow, SESBT 2022

作者： Devanathan, C. Natarajan, M.S. Shankar, E. Giri, R. Vigneshwaran, K. Department of Mechanical Engineering Rajalakshmi Engineering College Chennai602 105 India Department of Robotics and Automation Rajalakshmi Engineering College Chennai602 105 India

In the recent days, super alloys especially nickel based materials are used more than 50% of aerospace gas turbine components such as turbine disc, blades etc., It becomes very hard to shape these materials with the use of traditional machining processes due to its improved strength at higher temperature. To overcome the issues faced during conventional machining, the various advanced machining techniques are tried for machining these super alloys. In the present study, Inconel 738 was cut by wire electrical discharge machining using 0.25 mm diameter copper wire. Demineralized water was used as dielectric fluid between tool and workpiece electrode. During the process, voltage, wire feed rate, time of pulse on and pulse off were adjusted at four different values and totally sixteen slots were cut to analyze the machining characteristics. The machined surfaces were tested for its surface finish, rate of material removal and kerf width. The ANOVA was performed using Minitab software to find out the optimized variables and percentage contribution of each parameter in providing the influencing results. Wire feed rate was the most influencing parameter to have the lowest kerf width. As far as Material removal rate, the four parameters were had the significant impact in increasing the MRR. Voltage is the important process parameter to reduce the surface roughness. © 2023 Elsevier Ltd. All rights reserved.

关键词： Surface roughness

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SP-MAE: Lidar Beam-Induced Domain Adaptation for 3D Object Detection via Semantic Point Masked Autoencoders

SP-MAE: Lidar Beam-Induced Domain Adaptation for 3D Object D...

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Computer, control and robotics (ICCCR), international conference on

作者： Yaolin Liang Zhiming Tu Tao Wu College of Intelligence Science and Technology National University of Defense Technology Changsha China

In autonomous driving scenarios, lidar-based object detectors are widely used in 3D object detection. For the sake of safety redundancy, some self-driving vehicles will be equipped with multiple lidars with different beams, but training multiple lidar-based object detectors requires high costs. In our experiments, the performance of a lidar-based detector model trained on a high-beam lidar domain drops dramatically when transferred to a low-beam lidar domain. At present, there is no public 3D object detection dataset across-lidar-beams domains. In this paper, a 3D object detection dataset adapted across-lidar-beams domain is produced by the LGSVL simulator. The reason for the performance degradation of the lidar-based detectors across lidar-beams domains are mainly due to the large gap in the foreground object point count. To solve this problem, this paper proposed a semantic point generation method based on masked autoencoders, which can bridge the data gap between lidar beam-induced domains by generating more foreground semantic points so as to realize the migration of the detector model. In addition to solving the problem of lidar beam-induced domains migration, SP-MAE can also improve the performance of 3D lidar-based detectors. Experiments showed that the PVRCNN detector can improve 5.11 3D AP of pedestrian on the KITTI dataset after using SP-MAE.

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Neural Networks Application for the Classification Problem Solving with Domain Constraints

Neural Networks Application for the Classification Problem S...

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Technology Enhanced Learning in Higher Education (TELE), international conference on

作者： Ilya Sergeevich Mikhaylov Ye Thu Aung Myo Hlaing Win Zayar Aung Applies Mathematics and Informatics National Research University Moscow Power Engineering Institute (MPEI) Moscow Russian

The paper investigates an approach based on neural networks to solve the classification problem with domain constraints. The practical application of the developed methods in the subject area of oil production for solving the problem of optimizing the control of pumping equipment of oil wells is considered. The solution of the problem is carried out in real time based on the classification of the flow modes of the oil-water-gas flow according to the indications of a multiphase flow meter installed on an oil well.

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Improved noise-adapted semantic SLAM 3

Improved noise-adapted semantic SLAM

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3rd international conference on Industrial Artificial Intelligence, IAI 2021

作者： Zhang, Zheng Li, Decai He, Yuqing Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics shenyang110016 China Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences shenyang110016 China

ISBN: (纸本)9781665435178

Based on the rapid development of deep learning, semantic information has gradually become a research hotspot in the field of SLAM (Simultaneous Location and Mapping). The noise problem caused by the environment and sensor results in the lack of consistency of semantic maps, and affects the accuracy of the algorithms. Loss function can adjust the weights assigned to the outliers, so it can reduce the impact of the outliers. However, the model of loss function used by most semantic SLAM is fixed and cannot adapt well to the changing environment. To solve this problem, this paper proposes a improved noise-adapted semantic SLAM, which uses Gaussian mixture correntropy weight function as loss function. Its model structure is variable by adjusting the parameters in changing environment, so it can adapte the noise distribution to the greatest extent, which is more conducive to reducing the weight of the algorithm for outliers and improving robustness to the outliers. Experiments on the public KITTI dataset show that the average relative translation and rotation error of the proposed method are reduced by 4.08% and 5.55%, the constructed semantic maps are more consistent. © 2021 IEEE.

关键词： Semantics

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Symbolic Analysis of Closed control Systems with Dynamic Links and Park Transform

Symbolic Analysis of Closed Control Systems with Dynamic Lin...

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informatics, Electronics, and Radio Engineering (PIERE), international conference Problems of

作者： Sergey Evdokimov Anatoliy Shchagin Alexey Leontiev Timur Zhoraev Institute of Microdevices and Control Systems National Research University of Electronic Technology Moscow Russia Director JSC NTC RIAS Moscow Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

Various methods are used to analyze closed systems with park transformations and dynamic links in rotating and stationary coordinate systems. Numerical methods in various mathematical modeling programs are mainly used. In this paper, an attempt is made to use a symbolic-analytical method to analyze such systems. To simplify the calculations and demonstrate the analysis method, an orthogonal system is used, which allows avoiding the second harmonic when considering the system. This method allows constructing a root hodograph and analyzing the stability region when varying parameters, and directly determining the values in the steady state. Additionally, it is possible to use this approach to study non-symmetric systems with negative or zero sequences using symbolic methods, in which case it is necessary to solve a cascade of systems of equations for each harmonic with a given accuracy. It is also possible to obtain a solution for systems with cross feedbacks.

关键词： Laplace equations Transforms Harmonic analysis Mathematical models Stability analysis Steady-state Numerical models Transient analysis informatics Numerical stability

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App-Based Operation of a control Room Setup: The LeitstandsApp of the CELSIUZ

App-Based Operation of a Control Room Setup: The LeitstandsA...

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Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), international conference on

作者： Andreas Schulz Michal Dostál Jörg Lässig Department of Computer Science University of Applied Sciences Zittau/Görlitz Görlitz Germany Department of Informatics Technical University of Liberec Liberec Czech Republic

Classical control room hardware, such as that used by energy infrastructure operators, often offers limited and not very user-friendly and flexible interaction options. To improve the situation for users in a given simulation, presentation, and teaching setup, the authors have developed two mobile applications that make use much more intuitive and effective. The aim of this paper is to present ideas for improved user interaction and compare these with out-of-the-box KVM (keyboard video mouse) control options. Furthermore, the additional integrated possibilities beyond the use of a classic KVM switch are described and the architecture of the solution is outlined.

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Security in Robot Operating Systems (ROS): Analytical Review Study 3

Security in Robot Operating Systems (ROS): Analytical Review...

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3rd international conference on Distributed Sensing and Intelligent Systems, ICDSIS 2022

作者： Mokhamed, Takua Dakalbab, Fatima Mohamad Abbas, Sohail Talib, Manar Abu Department of Computer Science College of Computing and Informatics University of Sharjah United Arab Emirates

ISBN: (纸本)9781839538186

The Robotic Operating System (ROS) is a popular framework for robotics research and development. It's a system that provides hardware abstraction with low-level device management to handle communications and services. ROS is a distributed system, which allows various nodes in a network to communicate using a method such as message passing. When integrating systems using ROS, it is vital to consider the security and privacy of the data and information shared across ROS nodes, which is considered to be one of the most challenging aspects of ROS systems. The goal of this study is to examine the ROS architecture, primary components, and versions, as well as the types of vulnerabilities that might compromise the system. In order to achieve the CIA's three fundamental security criteria on a ROS-based platform, we categorized these vulnerabilities and looked into various security solutions proposed by researchers. We provide a comparative analysis of the ROS-related security solutions, the security threats and issues they addressed, the targeted architecture of the protection or defense system, the solution's evaluation methodology and the evaluation metric, and the limitations that might be viewed as unresolved issues for the future course of action. Finally, we look into future possibilities and open challenges to assist researchers to develop more secure and efficient ROS systems. © IET conference Proceedings 2022.

关键词： Robot Operating System

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Study on the prediction model of wound infection after spinal fusion and internal fixation based on logistic regression

Study on the prediction model of wound infection after spina...

引用

3rd international conference on Biomedicine and Bioinformatics Engineering, ICBBE 2023

作者： Wang, Chunling Miao, Cuicui Institute of Robotics Engineering Anhui Sanlian University AHefei China

ISBN: (纸本)9781643684321

With the development of the times, spinal problems are not only one of the diseases that older people pay close attention to, but also gradually spread among teenagers. Therefore, it is very important to predict the possibility of wound infection in patients after spinal fusion and internal fixation. The method is to statistically analyze the clinical data of patients with clinical spinal disease, and to propose individualized treatment and recovery plan for each patient's pathological characteristics and postoperative recovery, so as to realize humanized service and minimize the possibility of wound infection. In this paper, Logistic logistic regression, SMOTE algorithm and confusion matrix are used to model the probability of infection after spinal fusion and internal fixation. In the positive confirmation analysis part, the information data of 449 clinical cases were selected for analysis, and 14 variables such as gender, age, number of internal fusion fixation segments, past medical history, intraoperative blood transfusion and bleeding volume were selected as research indicators to explore the related factors of postoperative infection. The classification method adopts two classifications. The two types of data are postoperative infection' and postoperative non-infection'. In the statistical description of the data, it is found that age, selection of internal fusion fixation segments, preoperative hospitalization days, cerebrospinal fluid leakage, and preoperative ASA score are all important factors affecting the incidence of postoperative infection. © 2023 IOS Press. All rights reserved.

关键词： Cerebrospinal fluid

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Spectral and Morphological Classification of Celestial Objects using Physics Informed Machine Learning

Spectral and Morphological Classification of Celestial Objec...

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robotics, automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE international conference on

作者： Md Fairuz Siddiquee Md Mehedi Hasan Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

The classification of celestial objects has traditionally relied on spectral analysis, which involves identifying unique patterns in the light emitted or absorbed by the objects. In this study, we present a novel approach to categorizing celestial objects based on their spectral properties and morphological structures, leveraging physics-informed machine learning (PIML) techniques to enhance the classification accuracy and efficiency. In the spectral analysis, using Sloan Digital Sky Survey (SDSS) dataset, we classified stars, galaxies, and quasars, focusing on redshift and near-infrared values with i and z filters. Our analysis employed three machine learning models (K-Neighbors, SVM, Random Forest), and the performances were verified to be resilient applying hyperparameter tuning and cross-validation. The best-performing model, Random Forest Classifier, achieved 98% accuracy. In the morphological analysis, the YOLO v5 model was utilized on a customized dataset of astronomical images to further classify the Galaxy Class into five distinct categories and the YOLOv5 model detected those with an average precision of 92.6% and recall of 68.9%. In addition, the interpretability of the model is enhanced by the incorporation of physical knowledge, allowing astronomers to gain deeper insights into the underlying processes. Integrating physical knowledge into these ML models enhances interpretability, facilitating automated real-time analysis of big astronomical data and advancing our understanding of the cosmos.

关键词： YOLO Surveys Support vector machines Analytical models Accuracy Stars Spectral analysis Random forests Tuning Robots

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