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7th International Conference on Computing in engineering and Technology, ICCET 2022

作者： Sharma, Anshu Malhotra, Rahul Sharma, Anurag Department of Computer Science & Engineering CT University Ludhiana India Department of Electronics & Communication Engineering CT Group of Institutions Jalandhar India Faculty of Engineering Design and Automation GNA University Phagwara India

ISBN: (纸本)9781839537042

Tuberculosis is the substantial irresistible disease present in human that principally influences lungs, this tuberculosis is one the main ten noticeable reasons for death for human. It has very typical symptoms so without testing it isn't sure that patient has infected with TB. In this paper, an automated framework dependent on image handling is proposed to help specialists and radiologists in deciphering Chest X-beams (CXR) for early identification of lung Tuberculosis (TB). CXR can show the abnormalities in lungs as well as TB which helps to precisely and rapidly distinguish TB on the grounds that early treatment will provide to patients and disease will stop spreading in body. The proposed system comprised of preprocessing, segmentation, features extraction, and classification. In this paper proposed a strategy of image segmentation and AI to conclusion and characterize the tuberculosis (TB). These tool and procedures are utilized to earlier uncover of tuberculosis (TB) illness. Additionally arrange the sort of TB. The framework recognizes the tuberculosis with more prominent precision. © 2022 The Institution of engineering and Technology.

关键词： Diseases

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Mechanistic modeling of cutting forces in milling of unidirectional Glass Fiber Reinforced Polymer (UD-GFRP) 20

Mechanistic modeling of cutting forces in milling of unidire...

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20th CIRP Conference on Modeling of Machining Operations in Mons, CIRP CMMO 2025

作者： Nutte, Matthias Rivière-Lorphèvre, Edouard Dambly, Valentin Arrazola, Pedro-José Lazoglu, Ismail Granjon, Aurélie Ducobu, François Machine Design and Production Engineering Lab Research Institute for Science and Material Engineering UMONS Mons7000 Belgium Mechanical and Manufacturing Department Faculty of Engineering Mondragon Unibertsitatea Loramendi 4 Arrasate-Mondragón20500 Spain Manufacturing and Automation Research Center Koc University Istanbul34450 Turkey Sobelcomp SPRL Rue de l'économie 13 Loncin 4431 Belgium

Mechanistic models, established on experimental data, are recognized for their precision and simplicity in implementation. In this context of milling, the modeling of cutting forces, specifically radial and tangential components, has been extensively explored for unidirectional carbon fiber-reinforced polymer (UD-CFRP) parts. These models account for the anisotropic nature of fiber-reinforced polymers (FRPs), with cutting coefficients that vary based on the instantaneous cutting angle. However, due to the inherent flexibility of these materials, primarily attributed to their low thickness, axial cutting forces must also be incorporated to accurately represent the phenomena occurring during the machining process. This study develops a model for calculating cutting forces in three spatial directions for UD-GFRPs (unidirectional Glass Fiber-reinforced polymers). Building on an existing model from the literature for UD-CFRP, this new version introduces several modifications. First, the model validated for CFRPs must be extended to GFRPs. Secondly, the model must be extended from two dimensions to three dimensions. Finally, to ensure that the model includes only the actual contributions of the trimming operation, machining tests will be performed using only the rolling teeth. The cutting coefficients are modelled as a periodic function with a fundamental period of π. A first-order Fourier series was chosen for this purpose. Fourier series parameters are identified from the milling forces measured during a set of slotting operations at three feed rates and four fiber orientations. While the average levels of cutting forces are accurately modelled for both slotting and shoulder milling (with 50% immersion in up milling), the modeling of force amplitudes still requires improvement. © 2025 The Author(s).

关键词： Slotting

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Non-aqueous Al-ion batteries:cathode materials and corresponding underlying ion storage mechanisms

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Rare Metals 2022年第3期41卷 762-774页

作者： Wen-Ding Pan Cheng Liu Ming-Yue Wang Zheng-Jie Zhang Xiao-Yu Yan Shi-Chun Yang Xin-Hua Liu Yi-Fei Wang Dennis Y.C.Leung School of Electronic and Information Engineering Beihang UniversityBeijing 100091China Department of Mechanical Engineering the University of Hong KongPok Fu Lam 999077Hong KongChina State Grid Haiyang Power Supply Company Yantai 265100China Faculty of Engineering Dyson School of Design EngineeringImperial College LondonLondon SW72AZUK School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China

Aluminum-ion batteries(AIBs)are recognized as one of the promising candidates for future energy stor-age devices due to their merits of cost-effectiveness,high voltage,and high-power *** efforts have been devoted to the development of cathode materials,and the progress has been well summarized in this review ***,in addition to materials,the intercalation mechanism also plays a key role in determining cell ***,the research progress of cathode materials and corresponding ion intercalation mechanism in AIBs are summarized,including intercalation of AlCl_(4)-,intercala-tion of Al^(3+),and coordination of AlCl_(2)^(+)/AlCl^(2+).This minireview provides comprehensive guidance on the design of cathode materials for the development of high-performance AIBs.

关键词： Multivalent-ion battery Al-ion battery Nonaqueous electrolyte Cathode material Ion intercalation mechanism

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Trajectory Tracking Using Linear State Feedback Controller for a Mecanum Wheel Omnidirectional 6th

Trajectory Tracking Using Linear State Feedback Controller f...

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6th IFToMM Asian Mechanisms and Machine Science Conference, Asian MMS 2021

作者： Thai, Nguyen Hong Ly, Trinh Thi Khanh Long, Nguyen Thanh Dzung, Le Quoc Department of Mechanical Design and Robotics School of Mechanical Engineering HanoiUniversity of Science and Technology Hanoi Viet Nam Faculty of Automation Technology Electric Power University Hanoi Viet Nam

ISBN: (纸本)9783030918910

This paper presents a method to design a linear state feedback controller for the mecanum wheel omnidirectional to track a NURBS curve trajectory. Firstly, the robot's kinematic model and kinematic error were established to design a linear state feedback controller. Then, determine the parameters of the controller according to the varying angular velocity for the desired trajectory. An omnidirectional robot platform has been experimental designed and manufactured for experimental verification of the proposed controller. The simulation and experimental results show that the kinematic controller devel-oped by this study has high-performance trajectory tracking with minor tracking errors. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Controllers

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NURBS Curve Trajectory Tracking Control for Differential-Drive Mobile Robot by a Linear State Feedback Dynamic Controller

NURBS Curve Trajectory Tracking Control for Differential-Dri...

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AUN/SEED-Net Joint Regional Conference in Transportation, Energy, and Mechanical Manufacturing engineering, RCTEMME 2021

作者： Thai, Nguyen Hong Thien, Hoang Ly, Trinh Thi Khanh Department of Mechanical Design and Robotics School of Mechanical Engineering Hanoi University of Science and Technology Hanoi Viet Nam Faculty of Automation Technology Electric Power University Hanoi Viet Nam

ISBN: (纸本)9789811919671

In this paper, the authors present a method of designing a linear state feedback dynamic controller to control a differential-driven mobile robot to trajectory tracking with small error. The nonlinear dynamics model of the robot linearized around the working point. On that basis, design the controller according to the pole assignment method based on the position and velocity error model. Another difference with previous studies is that the coefficients of the controller vary with time. It depends on the travel velocity and the curvature radius of the desired motion trajectory. NURBS curve is applied to design the robot’s motion trajectory to avoid acceleration and deceleration to stabilize the robot’s motion. The research results have important implications in the design of dynamic controllers of the differential-drive AGV in the industry. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Differential-drive mobile robot Linear state feedback dynamic controller NURBS curve Trajectory tracking

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Deep Learning Wind Power Forecasting Method Integrating Architecture Comparison-based Evolutionary Neural Architecture Search 43

Deep Learning Wind Power Forecasting Method Integrating Arch...

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43rd Chinese Control Conference, CCC 2024

作者： Zhou, Wang Cao, Yundong Jin, Huaikang Fan, Shouyuan Wang, Bin Jin, Huaiping Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Kunming650500 China Huaneng Renewables CO. Ltd Yunnan Branch Kunming650000 China China Energy Engineering Group Yunnan Electric Power Design Institute Kunming650051 China

ISBN: (纸本)9789887581581

Wind energy has become an important part of the power system due to its versatility, low cost, and environmental friendliness. However, the instability and volatility of wind energy pose a huge challenge to the grid-connected operation of wind power, affecting the effective scheduling of the power grid. In this situation, accurate forecasting of wind power becomes crucial, and deep neural networks have been widely used in this field due to their excellent ability to process high-dimensional nonlinear spatiotemporal data. However, excellent deep neural network architectures are often manually designed by users with extensive expertise, which is time-consuming and results in high uncertainty. In order to automatically design suitable deep neural network architectures for different wind power forecasting tasks, this paper proposes a deep learning wind power forecasting method based on architecture comparison evolutionary neural architecture search. This method first encodes neural network architectures and then uses evolutionary algorithms to search for the optimal architecture. Among them, to address the problem of slow fitness calculation in evolutionary algorithms, architectures comparison-based the method is used instead of fitness calculation for architecture search, greatly accelerating search efficiency. The effectiveness and superiority of the proposed method were verified through case studies on actual wind farm datasets. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Wind forecasting

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Multi-stage Attention Mechanism based Deep Learning for Wind Power Forecasting 43

Multi-stage Attention Mechanism based Deep Learning for Wind...

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43rd Chinese Control Conference, CCC 2024

作者： Yang, Guanzhi Cao, Yundong Jin, Huaikang Fan, Shouyuan Wang, Bin Jin, Huaiping Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Kunming650500 China Huaneng Renewables Co. Ltd Yunnan Branch Kunming650000 China China Energy Engineering Group Yunnan Electric Power Design Institute Kunming650051 China

ISBN: (纸本)9789887581581

The accurate prediction of wind power is of great significance for the stable operation of the power system. However, due to the inherent intermittency and randomness of wind speed, existing time series prediction models struggle to capture the complex nonlinear relationship between wind speed and wind power, resulting in low prediction accuracy. Therefore, this study proposes a multi-stage attention long short-term memory network (MA-LSTM) prediction model. Firstly, convolution and attention mechanisms are fused to form the first stage of attention, extracting multi-dimensional features of dynamic changes in wind power data. Secondly, the feature vectors with spatial importance weights are input into the LSTM network for temporal feature extraction. Subsequently, a second stage attention mechanism assigns different weights to hidden state features at various time points. Finally, to counteract the low quality of the second stage attention extraction hidden state caused by the randomness of wind power data, a random difference structure is employed, forming multi-stage attention and LSTM units in parallel to develop the proposed model. The proposed method is evaluated using a real wind farm dataset, and the experimental results show that the MA-LSTM model can better capture the spatiotemporal characteristics of historical wind power data and provide higher quality time step hidden features, thereby significantly improving the accuracy of wind power prediction. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Wind forecasting

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High-Voltage Impulse Converter

High-Voltage Impulse Converter

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2023 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2023

作者： Sorokin, Dmitriy Volskiy, Sergey Kornev, Aleksandr Transconverter Design Office Moscow Russia Moscow Aviation Institute Technical University Directorates of Institute No. 3 Moscow Russia St. Petersburg State Marine Technical University Faculty of Ship Power Engineering and Automation St. Petersburg Russia

ISBN: (纸本)9781665475952

High-voltage impulse converter is meant for a stability test of power converters to emergency states which occur at input overvoltage impulse. It is developed with the use of two switching units based at IGBT. The proposed converter forms an output overvoltage impulse with the required values both in amplitude and in duration of rise and fall. Analytical expressions which describe transient processes in the proposed electric circuit of the converter are determined. Computer simulation using MATLAB Simulink confirmed the accuracy of the analytical expressions obtained. A prototype sample of the proposed high-voltage impulse DC converter is developed. For example, the results of using the developed converter when testing the power converter of PSN235Y2 type are presented. The article is of interest for electrical engineering specialists who develop technological equipment for manufacture and testing the power converters both for railway transport and for industrial. © 2023 IEEE.

关键词： Power converters

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Enabling Industry 4.0 impact assessment with manufacturing system simulation: an OEE based methodology 55

Enabling Industry 4.0 impact assessment with manufacturing s...

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55th CIRP Conference on Manufacturing Systems, CIRP CMS 2022

作者： Tumbajoy, Luisa M. Muñoz-Añasco, Mariela Thiede, Sebastian Industrial Automation Group Faculty of Electronics and Telecommunications Engineering University of Cauca Popayán 190002 Colombia Manufacturing Systems Faculty of Engineering Technology Department of Design Production and Management University of Twente De Horst 2 Building 20 Enschede7522 LW Netherlands

Increasing digitalization in manufacturing, often associated with terms like Industry 4.0 (I4.0) or Smart Manufacturing, is a topic of crucial concern for manufacturing companies. Different digital technologies (DTs) can be integrated into manufacturing processes and systems aiming at increasing flexibility, product quality or productivity. The type and scope of potential DTs must be carefully selected when planning and improving a manufacturing system. The definition and configuration could be supported by simulation techniques that assess the DTs' impact on the manufacturing system and its final performance. However, parametrizing the DTs into a simulation tool is not straightforward since appropriate models might be challenging to obtain and actual impacts of DTs are uncertain. Against this background, the paper presents methods to enable a simulation-based assessment while considering the impact of not just individual but also a combination of DTs. The paper introduces a framework to define the base characteristics of selected DTs within a manufacturing system and their parameterization into a commercial simulation tool. Furthermore, the usability and expectable results are demonstrated in a case study. © 2022 The Authors. Published by Elsevier B.V.

关键词： Industry 4.0 Key Performance Indicator Simulation Smart Manufacturing

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Feasibility of Comparing Constructive Spatial Processes in Real and Virtual Spaces among School-Age Children: A Randomized Pilot Study 2

Feasibility of Comparing Constructive Spatial Processes in R...

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2nd IEEE International Conference on Cognitive Aspects of Virtual Reality, CVR 2023

作者： Pulay, Mark Agoston Geszten, Dalma Szakal, Vince Abosa Forstner, Bertalan Szentandrasi, Dora Budapest University of Technology and Economics Faculty of Economic and Social Sciences Department of Ergonomics and Psychology BudapestH-1111 Hungary Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics BudapestH-1111 Hungary Moholy-Nagy University of Art and Design BudapestH-1121 Hungary

ISBN: (纸本)9798350338638

Nowadays new information and communication technologies (IT) directly influence teaching methods, practices and resources. The use of virtual reality (VR) technology in education enables new approaches that can enhance, guide, and stimulate students' interest in learning while allowing them to experience the subject and acquire sensory and intuitive cognition in a more personal and realistic environment. This research aims to answer the question: can constructive spatial activity with real materials in real space be replaced by virtual space and digital tools in terms of assessing stability and knowledge acquisition? This current pilot study aims to examine the feasibility of our research setup and analysis methods while children are asked to perform an intuitive creative process to construct a structure in real and digital space. We involved twelve school-Age (8,47 years average) from an elementary school, and we randomly allocated them to group 1 (real space construction) and to group 2 (tablet application construction). We created a behavioral coding scheme for the widely used and validated Noldus Observer XT (version 15) video behavior analyzer software. The video analyses showed that the creation phases defined in the construction process appeared on both real space and in a virtual setting, confirming the assumption that the acquisition of knowledge and skills related to stability can also be phased. Based on our pilot research on a small sample, the chosen observation and research methodology is feasible. We predict that the real-space constructive task applied in the measurement can be replaced by a digital interface to experience stability. © 2023 IEEE.

关键词： Virtual reality

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