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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Xu, Mingwang Wang, Wei Wang, Kuanquan Dong, Suyu Sun, Pengzhong Sun, Jinwei Luo, Gongning Harbin Institute of Technology Faculty of Computing Harbin China Harbin Institute of Technology School of Computer Science and Technology Shenzhen China Northeast Forestry University College of Computer and Control Engineering Harbin China Harbin Institute of Technology School of Instrumentation Science and Engineering Harbin China

ISBN: (纸本)9798350337488

Breast cancer continues to be a pressing global health concern, emphasizing the essential need for effective diagnostic techniques. Automated Breast Ultrasound Systems (ABUS) provide a promising advance in breast tumor detection, yet they require significant expertise in interpreting 3D ABUS images, a task fraught with distinctive challenges. Although Vision Transformers (ViT) display remarkable potential for image processing, their low inductive bias and significant data requirements pose obstacles, particularly in the data-constrained medical field. To mitigate these issues, we introduce a Mask-Recover strategy for pretraining Transformer models on 3D ABUS images, enhancing model adaptability and reducing the data demands of the ViT model. Moreover, recognizing the risk that ViTs' average pooling approach may unintentionally mask small but vital features, we propose Dual-CapsViT, an inventive model combining Transformers and Capsule Networks. This integration affords efficient token routing while preserving fine-grained details. To reconcile potential inconsistencies between capsules and tokens, we engineer a novel dual-channel routing algorithm, strengthening the decoder's performance. We benchmarked our models against well-known standards such as ResNet and ViT for classifying breast tumors in ABUS images. Our models exhibited superior performance, as evidenced by improved accuracy, specificity, and Area Under the Receiver Operating Characteristic Curve (AUC) metrics, thereby affirming Dual-CapsViT's potential to enhance breast cancer diagnostics. © 2023 IEEE.

关键词： abus breast cancer capsule network classification vit

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A Surrogate-Assisted Evolutionary Algorithm Based on K-Means Clustering and Lévy Flight

A Surrogate-Assisted Evolutionary Algorithm Based on K-Means...

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2023 China Automation Congress, CAC 2023

作者： Kang, Yaxin Yu, Haibo Kang, Li Qiao, Gangzhu Guo, Dongpeng Zeng, Jianchao College of Electrical and Control Engineering North University of China Taiyuan030051 China College of Computer Science and Technology North University of China Taiyuan030051 China College of Environment and Safety Engineering North University of China Taiyuan030051 China College of Environment and Resources Taiyuan University of Science and Technology Taiyuan030024 China

ISBN: (纸本)9798350303759

Expensive optimization problem refers to a category of problems for which numerical simulations or physical experiments are expensive and intractable. Evolutionary algorithm (EA) cannot be directly applied to such problems due to the large number of fitness evaluations consumed to determine the global best solution. Hence, this paper proposes a surrogate-assisted evolutionary algorithm based on k-means clustering and Lévy flight (SAEA-KL), where the Radial Basis Function network (RBFN) is selected as a promising surrogate for saving the number of expensive evaluations, and the dual-start Lévy flight and k-means clustering method are deployed to initialize the population of the competitive swarm optimizer in consideration of both optimal and fitness landscape information. Experimental results on common benchmark problems indicate that the proposed method is competitive with seven state-of-the-art algorithms under a limited computational budget. © 2023 IEEE.

关键词： Evolutionary algorithms

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High-Frequency Resonance Suppression Based on Active and Passive Joint Damping for MMC-HVDC

High-Frequency Resonance Suppression Based on Active and Pas...

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Power Electronics and Application Symposium (PEAS), IEEE International

作者： Yiqi Liu Jiayi Liu Wei Liu Yucheng Wu Laicheng Yin Mingfei Ban College of Computer and Control Engineering Northeast Forestry University Harbin China

High-frequency resonance (HFR) incidents have occurred in several Modular Multilevel Converter-based high voltage direct current (MMC-HVDC) projects recently. The interaction between the impedance characteristic of MMC and the grid is assumed as the main factor of HFR, caused by a large time delay. Complex operating conditions arouse the issue of resonance frequency shifts, making the conventional suppression method ineffective. Thus, an active and passive joint damping suppression method is proposed based on the cross-coupled filter (CCF) and improved C-type filter damper. This method can remove the risk of HFR and provide a sufficient phase margin, enhancing the stability and robustness of the MMC-HVDC system. The effectiveness of the proposed method is verified through simulations.

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Dynamic Response Analysis of High Voltage Transmission Tower-Line Coupling System Under Ice and Wind Loads

Dynamic Response Analysis of High Voltage Transmission Tower...

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Power System and Green Energy Conference (PSGEC)

作者： Bingzhao Qiu Mingfei Ban Yiqi Liu Long Dai College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350365573

ISBN: (纸本)9798350365580

Investigating the dynamic characteristics of high-voltage (HV) transmission line coupling systems under ice-wind loads is crucial for bolstering the system's resilience to ice and snow disasters, thereby ensuring power supply safety. Currently, developing an effective analysis method is a focal point in this research domain. This study selects a representative HV transmission line as the subject of investigation and constructs an ice-wind loads coupling model. Using the 220kV ice-covered HV transmission line of the Fujian power grid as a case study, the comprehensive effects of ice thickness, wind attack angle and speed are considered based on the coupled finite element model (FEM). The response characteristics of the HV transmission line ice-wind loads are analyzed, and key parameters such as stress response and displacement response are evaluated. The findings indicate that the ice-wind response of the tower-line system can be effectively analyzed. The simulation calculation model of the transmission line under the tower-line coupling factors presented in this paper aligns more closely with actual working conditions, making it a valuable reference for the design, mechanical analysis, and operation and maintenance of HV transmission lines in specific regions.

关键词： Couplings Power transmission lines Wind speed Power system dynamics Ice thickness High-voltage techniques Power grids Finite element analysis Stress Load modeling

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Multi-Objective Optimization of Asymmetric PM-Assisted Synchronous Reluctance Motor Based on NSGA-III

Multi-Objective Optimization of Asymmetric PM-Assisted Synch...

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China International Electrical and Energy Conference (CIEEC)

作者： Weinan Wang Shuo Wang Xiaokun Zhao Liangkuan Zhu Yiqi Liu Jian Wei College of Computer and Control Engineering Northeast Forestry University Harbin China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Reluctance motor has the advantages of simple structure, low amount of permanent magnet and high stability. But reluctance motor's limited torque density hinders its widespread application. However, the problem of high torque ripple caused by the asymmetric topology of the permanent magnet still needs further optimization. Firstly, the structure of APMA-SynRM and the parameters to be optimized are introduced. The APMA-SynRM optimization steps are then designed. Then, the range of optimization variables is determined by parametric scanning of APMA-SynRM parameters, and the response surface of APMA-SynRM is established. The final optimal design was obtained by non-dominating genetic algorithm (NSGA-III), In conclusion, the comparison and analysis of the key performance indicators before and after APMA-SynRM optimization are presented.

关键词： Torque Accuracy Key performance indicator Permanent magnets Stability analysis Response surface methodology Topology

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Crop Planting Layout Generative Adversarial Network Model

Crop Planting Layout Generative Adversarial Network Model

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： WenLong Chen Meiling Liu YaMeng Zhen Lin Guo Ying Zeng College of Computer and Control Engineering Northeast Forestry University Harbin China

The task of crop planting layout generation aims to synthesize realistic crop planting layout images by combining elements with different attributes, including crop category, planting area, position, and crop interrelationships. This task can assist farmers in the design of crop planting layout, and generate a reasonable crop planting layout that satisfies the description based on the description of relevant attribute information such as the type and area of the planted crops, so as to reduce the burden of crop planting design. However, for different application scenarios, including conditional generation and unconditional generation, crop planting layout generation faces the problems of lack of datasets and low quality of generated images. To address these issues, we construct a new dataset CPL-dataset and propose a model CPLGAN (Crop Planting Layout Generative Adversarial Network). CPLGAN model adopts the structure of generative adversarial network, which can realize the parallel synthesis of images with different attributes. CPLGAN model treats missing or rough module layouts as intermediate states of completed layouts, which can be generated from scratch or conditioned on arbitrary available attributes. Due to the different semantics and features of each attribute, we incorporate the global context and employ a dynamic memory gate to facilitate image generation, enhancing the quality and diversity of generated images. We evaluate the CPLGAN model on our self-built CPL-dataset, and the experimental results showed its superior performance in generating crop planting layouts.

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Structure Comparison and Performance Analysis of Multi-Layer Flux-Barrier Hybrid-Pole Permanent-Magnet Synchronous Machine

Structure Comparison and Performance Analysis of Multi-Layer...

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China International Electrical and Energy Conference (CIEEC)

作者： Weinan Wang Lingfang Fu Ningxin Wang Liangkuan Zhu Xiaokun Zhao Jian Wei College of Computer and Control Engineering Northeast Forestry University Harbin China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

As its numerous excellent performances., multi-layer flux-barrier hybrid-pole permanent magnet synchronous machine (MLFB-HP-PMSM) is applied in a lot of fields., for example electric vehicles., aerospace., home appliances and so on. In this paper., the comparison of structure and performances of MLFB-HP-PMSM are investigated. First of all., two structures of different PM arrangements of two layers hybrid poles are established and recommended. Then., on the premise of ensuring consistent use of permanent magnets of two structures., the electromagnetic performances of two motor structures are compared. After that., the better performing motor structures have been used for further research., involving the influence of motor structural parameters (flux-barrier angles) on electromagnetic torque.

关键词： Permanent magnet machines Home appliances Torque Motors Permanent magnets Structural engineering Electromagnetics

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Dehazing Quality Evaluation Algorithm Integrating Dark Channel Theory and Image Depth Estimation

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第2期9卷 1119-1133页

作者： Huang, Jia-Yan Xu, Xin-Xin Luo, Shao-Ye Zhao, Wan-Qi Fan, Hao-Yi Grau, Antoni Guerra, Edmundo Wang, Chuan-Sheng Zhang, Fu-Quan New Engineering Industry College Putian University Putian351100 China The University of Sheffield SheffieldS10 2TN United Kingdom School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

Image dehazing is an important research topic and hotspot in the fields of image processing and computer vision. Therefore, evaluating the performance of image dehazing algorithms has become an import research issue. However, current image quality assessment (IQA) algorithms only judge the final dehazed image and do not give an analysis of the capabilities of the image dehazing algorithm. In order to fill this gap, we propose an image dehazing quality assessment method that integrated the dark channel prior with image depth estimation. The proposed method first uses the dark channel prior to estimate the absolute amount of haze removed from each pixel as an indication of the performance of dehazing. Then, a dual-scale variance ratio method is introduced to estimate the scene depth of the image. Finally, the relative dehazing is calculated from the obtained absolute dehazing and the image depth to represent the capability of the dehazing algorithm. The method proposed in this paper first introduces the concepts of relative and absolute dehazing quantities, along with pioneering a pixel-level evaluation of dehazing outcomes. Extensive experiments show that the algorithm proposed in this paper is more in line with human subjective judgment than other IQA algorithms. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Pixels

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Hunger games search optimization with deep learning model for sustainable supply chain management

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Discover Internet of Things 2023年第1期3卷 10页

作者： Xu, Zheng Jain, Deepak Kumar Neelakandan, S. Abawajy, Jemal School of Computer and Information Engineering Institute for Artificial Intelligence Shanghai Polytechnic University Shanghai201209 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China School of Artificial Intelligence Dalian China Symbiosis Institute of Technology Symbiosis International University Pune India Department of Computer Science and Engineering R.M.K Engineering College Taluk India Deakin University Geelong Australia

The supply chain network is one of the most important areas of focus in the majority of business circumstances. Blockchain technology is a feasible choice for secure information sharing in a supply chain network. Despite the fact that maintaining security at all levels of the blockchain is difficult, cryptographic methods are commonly used in existing works. Effective supply chain management (SCM) offers various benefits to organizations, such as enhanced customer satisfaction, increased operational efficiency, competitive advantage, and cost reduction. Potential SCM for agricultural and food supply chains needs distributors, coordination and collaboration among farmers, retailers, and stakeholders. The use of technology like Block Chain (BC), sensors, and data analytics, can boost traceability and visibility, decrease waste, and ensure safety and quality throughout the supply chain. Therefore, this study develops a Hunger Games Search Optimization with Deep Learning Model for Sustainable agricultural and food Supply Chain Management (HGSODL-ASCM) technique. The fundamental goal of the HGSODL-ASCM technique is to improve decision-making processes for agricultural and food commodity production and storage in order to optimise revenue. In the provided HGSODL-ASCM technique, a bidirectional long short-term memory (Bi-LSTM) model is built to determine the amount of productivity and storage required to maximise profit. In order to boost the performance of the Bi-LSTM classification process, the HGSO algorithm has been utilized in this work. The presented HGSODL-ASCM technique can independently achieve the SCM policies via interaction with complicated and adaptive environments. A brief set of simulations were performed to ensure the improved performance of the HGSODL-ASCM technique. The simulation results demonstrated how superior the HGSODL-ASCM method is to other methods already in use. © The Author(s) 2023.

关键词： Food supply

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Research on Magnetic Circuit and Electromagnetic Performance of Combined-Pole Less-Rare-Earth Permanent-Magnet Synchronous Machine Used for Fully Electric Unmanned Aerial Vehicle

Research on Magnetic Circuit and Electromagnetic Performance...

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IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Weinan Wang Liangkuan Zhu Lingfang Fu Yiqi Liu Shuo Wang Jian Wei College of Computer and Control Engineering Northeast Forestry University Harbin China

The combined-pole less-rare-earth permanent-magnet synchronous machine (CP-LRE-PMSM) has a series of advantages, such as better sinusoidal air-gap field, reduced reliance on rare-earth permanent-magnet materials. and lower cost. This paper firstly founds CP-LRE-PMSM’s equivalent magnetic circuit model, then the calculation formulas of air-gap field are deduced, meanwhile the model accuracy is examined by finite element analysis (FEA). After that, based on machine performance requirements used for fully electric unmanned aerial vehicle (FE-UAV), the electromagnetic performance of CP-LRE-PMSM is analyzed. The total harmonics distortion (THD) and fundamental component of air-gap field versus permanent magnet width, permanent magnet thickness and flux-barrier position angle are studied, respectively. The torque characteristics and the machine efficiency map are investigated, which provides the reference for theoretical analysis and design of the CP-LRE-PMSM

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