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Classification and Detection of Cyanosis Images on Lightly and Darkly Pigmented Individual Human Skins using a Fine-Tuned MobileNet Architecture 6

Classification and Detection of Cyanosis Images on Lightly a...

引用

6th international conference on Artificial Intelligence, Big Data, computing and Data Communication Systems, icABCD 2023

作者： Mpova, Lukoki Shongwe, thokozani Hasan, Ali University of Johannesburg Faculty of Engineering and the Built Environment Electrical and Electronic Engineering Science Johannesburg South Africa

ISBN: (纸本)9798350314809

the classification and detection of cyanosis using in-vivo and in-silico image processing approaches are intriguing and very special. In this study, a peripheral and central cyanosis image classification approach, using lightweight-deep learning Convolutional Neural Networks (CNNs), referred to as pre-trained MobileNet architecture, was introduced. this modified MobileNet model was assessed using the sanctioned dataset of 1300-image collected from multiple cyanosis published datasets. the augmentation technique was applied on the training dataset to enrich the productivity. Emphatic results, validation-accuracy and accuracies on the training and test datasets of 95% and 97%, respectively;were obtained as compared to the validation-accuracy of 79% and 82% of the Simple Convolutional Neural Networks (SCNNs) and Fine-tuned VGG16 models attained from prior stud. © 2023 IEEE.

关键词： Convolutional neural networks

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Magnetic Flux Servoing for Precise Localization Based on Gradient Tensor Contractions 19

Magnetic Flux Servoing for Precise Localization Based on Gra...

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19th IEEE international conference on automation science and engineering, CASE 2023

作者： Martinovic, Dean Orsag, Matko University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb10000 Croatia

ISBN: (纸本)9798350320695

this paper focuses on bridge inspections performed by intelligent unmanned aerial vehicles (UAV). For this, small data loggers are placed by the UAVs at the bridge, which have to be removed later. In our previous work we presented the magnetic localization method SRIOD, which not only detects the center of the data logger but also its orientation. In this work we proof SRIOD in a real application and let a robotic arm locate a magnetic target. the hardware involved is presented including the control strategy for the robot. the motions of the robot and the magnetic target are captured with 12 Optitrack cameras in order to validate the localization quality. © 2023 IEEE.

关键词： Antennas

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Coordinated Voltage control Based on Projected Gradient Descent Algorithm for PV-Rich Distribution Network 6

Coordinated Voltage Control Based on Projected Gradient Desc...

引用

6th IEEE international electrical and Energy conference, CIEEC 2023

作者： Zhang, Xiren Li, Yong Wang, Can Peng, Yanjian Liu, Jiayan Chang, Fanrui College of Electrical and Information Engineering Hunan University Changsha China State Grid Hunan Electric Power Company Limited Research Institute Dept. of Electrical Engineering Changsha China

ISBN: (纸本)9798350346671

Large-scale distributed photovoltaic (PV) access to the distribution network has adverse effects on system operation and voltage control. this paper proposes a distributed voltage control strategy based on the projected gradient descent algorithm. the optimal voltage control problem is formulated as an optimization program, with the goal of maintaining the voltage profile of node with PV across the network. the voltage control problem is reduced to a quadratic programming constrained optimization problem. By minimizing the voltage deviation, the reactive power injection problem of PV inverters is solved by the projected gradient descent algorithm. the proposed method only collects neighbor information of PV to communicate with each other without global communication. Finally, the simulation results show that the proposed method can effectively maintain the voltage to the security operating range. © 2023 IEEE.

关键词： Electric power distribution

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PRBJE: A Novel Pre-Relation Bidirectional Joint Extraction Model 6

PRBJE: A Novel Pre-Relation Bidirectional Joint Extraction M...

引用

6th international conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2024

作者： Yu, Qiang Zhou, Wenhui Dong, Shuai Li, Dongyuan School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China

ISBN: (纸本)9798331541699

Joint extraction of entities and their semantic relationships to form factual triples from unstructured text is a fundamental task in information extraction. However, existing methods either ignore the interactions between relationships and entities or extract the subjects and objects in a fixed sequential order, which makes these approaches too sensitive to the extraction results of subjects. To address the two issues, we propose a pre-relation bidirectional joint extraction model (PRBJE). Specifically, we first detect potential relationships from the sentence to assist in the subsequent extraction of head and tail entities. then, we extract all possible entity pairs maintained in the text using two complementary directions: extracting the tail entity based on the head entity and vice versa. Finally, we assign relationships to all entity pairs by a biaffine model, thereby forming complete relational triples. Extensive experimental results demonstrate that our model outperforms state-of-the-art methods, with improved F1 scores across four public datasets, particularly achieving gains of 0.9 and 0.7 on NYT and WebNLG, respectively. © 2024 IEEE.

关键词： Semantics

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Single-phase Grid-forming Inverters: A Review 6

Single-phase Grid-forming Inverters: A Review

引用

6th international conference on computing, Electronics and Communications engineering, iCCECE 2023

作者： Rezazadeh, Hamed Monfared, Mohammad Fazeli, Meghdad Golestan, Saeed Swansea University Department of Electronic and Electrical Engineering Swansea United Kingdom Aalborg University AAU Energy Aalborg Denmark

ISBN: (纸本)9798350340921

Ever-increasing share of inverter-based resources (IBRs) has resulted in a significant reduction in system damping and inertia, posing significant stability and new performance challenges for electric power grids. To resolve these issues and provide reliable support to the existing power grid, advanced control schemes are already being researched and some are successfully implemented. Grid-forming (GFM) control methods are emerging to enhance grid-connected inverter stability and response to abnormal conditions. While research is more focused on three-phase converters, the ever-increasing contribution of single-phase IBRs calls for similar solutions to be developed for single-phase converters. In this paper, the state-of-the-Art single-phase GFM techniques for IBRs are presented and the main challenge for successful implementation of them is highlighted. © 2023 IEEE.

关键词： Electric power system control

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the Design and Energy Management Strategy of an Integrated Energy Router Oriented towards Rural Areas 6

The Design and Energy Management Strategy of an Integrated E...

引用

6th international conference on electrical engineering and control Technologies, CEECT 2024

作者： Zhang, Linyi Zhou, Lidan Yao, Gang Gan, Lin Wang, Xiaoxia Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Department of Electrical Engineering Shanghai200240 China State Power Investment Group Southwest Research Institute Co. Ltd State Power Investment Corporation Chengdu610218 China East China University of Science and Technologyline School of Mechanical and Power Engineering Shanghai200237 China

ISBN: (纸本)9798331528096

With the proposal of the 'dual carbon goals', China is vigorously developing a new type of power system with new energy as the main body, and the energy router, as the core of the new power system, has also attracted much attention. this paper takes the smart livable countryside as the application scenario and studies the 'wind-solar-hydrogen-oxygen' integrated energy router, proposing an energy router that can comprehensively utilize photovoltaic arrays, wind turbine sets, and energy stored in batteries, and supply them to AC and DC loads, and utilize electrolyzers, expanding the application scenarios of small power level energy routers. the paper first emphasizes the importance of developing energy routers, analyzes the current state of research at home and abroad in this field, and then describes the hardware topology of energy routers, control strategies for each unit, and energy management strategies based on this, using simulation models to verify the feasibility of the suggested scheme. In the design of energy routers, the article provides a detailed account of the overall design of the energy router, including the characteristics of various energy modules and their corresponding topologies of power electronic converters. the paper further formulates an energy management strategy founded on the actual situation of daily life in the countryside, divides into six working conditions, and simulates the operation of the energy router under each working condition. the simulation results demonstrate that the and simulates the operation of the energy router under each working condition. the simulation results demonstrate that the suggested energy management strategy can cope with different working conditions and achieve optimized operation of the suggested energy management strategy can cope with different working conditions and achieve optimized operation of the energy router. © 2024 IEEE.

关键词： Energy management

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Optimization of SVM Based on IPSO Algorithm for Tool Life Prediction 6

Optimization of SVM Based on IPSO Algorithm for Tool Life Pr...

引用

6th international conference on Computer Network, Electronic and automation, ICCNEA 2023

作者： Gao, Xianghong Cao, Yan Xi'an Technological University School of Mechanical and Electrical Engineering Xi'an China Xi'an Technological University School of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798350305388

As the basic parts of workshop processing, the life of the tool will affect the processing efficiency and processing quality, and the life of the tool will be affected by a variety of uncertain factors in the processing process, which makes it difficult to accurately predict. In order to improve the prediction accuracy, an improved IPSO algorithm was proposed to optimize the penalty factor c and kernel parameter g of SVM based on particle swarm optimization (PSO). Firstly, the influencing parameters of tool life are analyzed and the experimental data are extracted, and then the data is brought into the IPSO-SVM model to obtain the predicted data. IPSO algorithm can realize the adaptive change of inertia weight and introduce asynchronous learning formula to dynamically adjust the learning factor, which can effectively improve the prediction accuracy of tool life. Compared with the traditional PSO-SVM prediction model, the average relative error and average absolute error of IPSO-SVM are reduced by 5.275% and 5.006% respectively, which indicates that the SVM model optimized by IPSO algorithm has higher prediction accuracy. © 2023 IEEE.

关键词： Forecasting

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Heavy Overload Transformer Oil Temperature Prediction Method Based on Multivariate Spatio-Temporal Convolutional Network 6

Heavy Overload Transformer Oil Temperature Prediction Method...

引用

6th international conference on Communications, Information System and Computer engineering, CISCE 2024

作者： Qin, Jinfei Li, Binbin Luo, Sha Huang, Weimin Lu, Yixiang Lyu, Junwen State Grid Anhui Electric Power Co. Ltd. Power Science Research Institute China Anhui Electric Power Company Limited The Equipment Department of State Grid China College of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9798350353174

the top layer oil temperature of a transformer under heavy overload conditions can change rapidly, which affects the insulation performance of the transformer and shortens its operational life. therefore, the prediction of top layer oil temperature can provide an important basis for early warning of transformer failure. However, single oil temperature data cannot accurately reflect the oil temperature change rule, and the multivariate oil temperature spatio-temporal features are difficult to capture. In order to solve the existing problems, this paper proposes a new heavy overload transformer oil temperature prediction method based on multivariate spatio-temporal convolutional network (MSTCN). the top oil temperature, environmental temperature and load data are first normalized. then the dataset is inputted into MSTCN to explore the temporal information through gated recurrent unit, utilized the dimensionality-enhanced channel attention mechanism to focus on more important variables and detailed features, and took the convolutional and self-attention mechanism to mine the spatial information. Finally, the prediction results are output through fully connected layers and denormalization. the method is compared with the advanced techniques, and the effectiveness and advancement of the method is proved through experiments. © 2024 IEEE.

关键词： Oil filled transformers

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High Spectral Image Classification Model Based on Residual-Corrected Adaptive Jigsaw Capsule Network 6

High Spectral Image Classification Model Based on Residual-C...

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6th IEEE international conference on automation, Electronics and electrical engineering, AUTEEE 2023

作者： Wei, Lin Ran, Haoxiang Yin, Yuping Liaoning Technical University School of Software Liaoning Huludao China Liaoning Technical University School of Electrical and Control Engineering Liaoning Huludao China

ISBN: (纸本)9798350305623

To improve the precision of hyperspectral image classification, this paper introduces an Adaptive Capsule Residual Jigsaw Network (abbreviated as ACRJ-Net), which builds upon the capsule network structure with an integrated residual correction. Firstly, considering the intricate non-linear inter-band characteristics and global interactions of hyperspectral images, we design a Band Attention Module (BAM) to highlight key features and reinforce inter-feature correlations. Secondly, to thoroughly harness spatial features and optimize local representations, we improve upon the foundational capsule network by integrating a jigsaw-puzzling concept. To ensure its seamless fusion with the capsule network, an adaptive pooling layer is proposed to balance feature dimensions. Lastly, to counteract gradient vanishing in the jigsaw capsule network and enhance feature representation capacity, a residual algorithm module is introduced. this ensures effective fusion and optimization of deep features, ultimately boosting the model's classification performance. Experimental results reveal that ACRJ-Net surpasses other similar models in terms of overall classification accuracy on the KSC, Pavia University, and Salinas datasets, showing average improvements of 3.48%, 5.80%, and 3.49%, respectively. Ablation experiments in comparison with the base matrix capsule network demonstrate increases in overall accuracy by 1.44%, 1.30%, and 0.33% respectively, validating the model's efficacy. © 2023 IEEE.

关键词： Adaptive Pooling Layer Capsule Network Hyperspectral Imaging Jigsaw Network Residual Correction

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Design of the Tri-redundant Permanent-Magnet Synchronous Machine for More-electric Aircraft 6

Design of the Tri-redundant Permanent-Magnet Synchronous Mac...

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6th IEEE international electrical and Energy conference, CIEEC 2023

作者： Wan, Yuan Zhang, Xu Li, Wenlong Liyang Research Institute Southeast University Liyang China School of Electrical Engineering Southeast University Nanjing China School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350346671

there is a strict demand on the reliability of the driving motor for the electrical actuator of the more electric aircraft. However, the power density is inevitably decreased if inceasing the reliability only by arranging multiple sets of windings to the stator. Given that, this paper provides a dual-stator tri-redundant permanent magnet fault-tolerant motor, which can output the rated power with single-redundancy winding faulty and 50% rated power with two-redundancy winding faulty, improving the reliability while maintaining the high power density. the selection of the winding topology was discussed comprehensively to choose that having lower coupling degree between different sets of three-phase windings. the structure of the rotor was optimized to reduce the rotor-eddy loss, and the strength of the rotor was evaluated as well. then the thermal-analysis model was built and the thermal characteristics of the motor were calculated under different running conditions. Finally, a 6 kW, 12 000 rpm prototype was manufactured to verify the theoretical analysis. © 2023 IEEE.

关键词： Winding

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