检索结果-内蒙古大学图书馆

33rd Southern African Universities Power engineering Conference, SAUPEC 2025

作者： Raafi, Rafiullah Shirani, Habiburahman Ullah, Wasiq Khan, Wasiullah Akuru, Udochukwu Bola Khan, Faisal Kabul Polytechnic University Faculty of Electromechanics Dept. of Electrical Engineering Kabul Afghanistan Kabul University Faculty of Engineering Dept. of Electrical and Electronics Engineering Kabul Afghanistan Kabul Polytechnic University Vice Chancellor of Research and Journals Kabul Afghanistan Comsats University Islamabad Abbottabad Campus Dept. of Electrical and Computer Engineering Abbottabad Pakistan Tshwane University of Technology Pretoria West Campus Dept. of Electrical Engineering Pretoria South Africa

ISBN: (纸本)9798331535162

In this paper, the performance of various rotor pole configurations in a novel π-shaped stator wound-field flux switching machine (WFFSM) is investigated to address concerns with cost and environmental concerns associated with permanent magnet machines. By employing the finite element analysis (FEA) method, the study focuses on the no-load, on-load and overload performance characteristics of the proposed machines based on four different rotor poles-13P, 14P, 16P and 17P. The 14P rotor configuration emerges as superior machine, showcasing highest torque, lowest torque ripple and best overload capability. The future study will cover full optimization of all four machines with experimental validation. © 2025 IEEE.

关键词： Stators

来源：评论

学校读者我要写书评

暂无评论

Coil Optimization of a Planar Omnidirectional WPT System

Coil Optimization of a Planar Omnidirectional WPT System

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yu, Xipei Feng, Junjie Zhu, Liyan Li, Qiang Virginia Polytechnic Institute and State University Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering Blacksburg United States

ISBN: (纸本)9798350376067

Recently, omnidirectional wireless power transfer (WPT) has gained widespread popularity since 2010s especially in consumer electronics application benefiting from ease of integration with furniture. In such applications, angular misalignment occurs frequently. Obviously, it will affect the stable operation of system significantly. However, the coil optimization is not investigated accurately. In other words, the modelling and effects under angular misalignment are not investigated completely. Targeting at this, this article proposes a planar omnidirectional wireless power transfer system with three sets of planar coils. Afterwards, the modelling process is conducted for the planar omnidirectional WPT system under angular misalignment and Ns effect is investigated. Afterwards, the coil optimization is conducted to increase its usability in real applications. Finally in the experiment, three sets of coils are fabricated and the transfer efficiency are measured under orientation and angular misalignment at 6.78MHz. When charging the mobile phone and electronic watch receivers, the overall efficiency is 69%-78% and 55%-65%, considering the orientation and angular misalignment. © 2024 IEEE.

关键词： Inductive power transmission

来源：评论

学校读者我要写书评

暂无评论

Design Optimization of a 3.3 V Bus Converter for Vertical Power Delivery in Next-Generation Processors

Design Optimization of a 3.3 V Bus Converter for Vertical Po...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Liang, Yan Prakash, Pranav Raj Nabih, Ahmed Li, Qiang Virginia Polytechnic and State University Bradley Department of Electrical and Computer Engineering Blacksburg United States Nvidia Corporation Durham United States

ISBN: (纸本)9798350376067

The advancements in artificial intelligence and machine learning are driving the development of a new generation of ultra-powerful graphical processing units (GPUs). The latest datacenter-grade GPU cards use the two-stage lateral power delivery with a traditional 12V intermediate bus voltage (IBV). The next-generation GPUs are expected to double in power and package size, resulting in less space for higher power delivery. A previous study proposed a two-stage vertical power delivery solution by relocating the 2nd stage converters with a lower IBV. In this architecture, an unregulated LLC resonant converter (DCX) based 1st stage intermediate bus converter (IBC) steps down 48V to a low IBV, and the 2nd stage is a packaged voltage regulator stacked under the GPU minimizing the power delivery network (PDN) length;however, the I2R losses at a very low IBV will limit the overall high-power delivery. To ensure the high-power delivery to future GPUs, this paper focuses on the design of a high-efficiency, high-density 1st stage IBC with an IBV of 3.3V. A high-density LLC DCX based unit-cell design is implemented enabling the high-power delivery symmetrically. By optimizing the winding arrangement, the leakage flux and winding ac resistance of the transformer are minimized. Additionally, the non-ideal current sharing associated with the top-cooled module is mitigated. The elimination of these issues is critical as they lead to the degradation of parallel winding effectiveness and a reduction in efficiency. The proposed improvements are verified by developing an 840W 3.3V bus converter prototype with a peak efficiency of 97.3% and a power density of 2300 W/in. © 2024 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Triple-Branch Deep Network for Polyp Image Segmentation

Triple-Branch Deep Network for Polyp Image Segmentation

引用

2025 International Workshop on Advanced Imaging Technology, IWAIT 2025

作者： Jian, Muwei Zhong, Yanjie Lam, Kin-Man School of Computer Science and Technology Shandong University of Finance and Economics Jinan China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong

ISBN: (数字)9781510688131

ISBN: (纸本)9781510688124

Medical image segmentation is essential for accurately extracting tissue structures or pathological regions from medical ***, medical image segmentation methods are often influenced by factors such as image noise and irregular shapes, making precise segmentation *** tackle these challenges, this paper proposes a triple-branch medical image segmentation network (TB-Net) that incorporates implicit boundary *** boundary map, acquired through a boundary detection algorithm, is used to restrict the results of the boundary *** experiments indicate that TB-Net achieves state-of-the-art performance on publicly available polyp datasets. © 2024 SPIE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Mutual Inductance Extraction and Power Allocation of a Planar Omnidirectional WPT System

Mutual Inductance Extraction and Power Allocation of a Plana...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

ISBN: (纸本)9798350376067

In recent times, planar omnidirectional wireless power transfer has emerged as a prominent technology, especially in consumer electronics application. However, in such scenario, the presence of multiple receivers with angular misalignment often results in unstable operation due to variations in mutual inductance. To address this challenge, this article undertakes the modelling of several receiver coils and proposes a method to extract mutual inductance between them utilizing additional DC/DC converters. This extraction process serves to mitigate these effects, thereby enabling effective power allocation among multiple receivers Finally, the experimental validation is conducted. at 6.78MHz. When charging the mobile phone and electronic watch receivers, the overall efficiency is 68%-77% and 56%-66%, considering the orientation and angular misalignment. © 2024 IEEE.

关键词： Inductive power transmission

来源：评论

学校读者我要写书评

暂无评论

Enhancing Multimodal Rumor Detection with Statistical Image Features and Modal Alignment via Contrastive Learning 21st

Enhancing Multimodal Rumor Detection with Statistical Image...

引用

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Zhou, Chenyu Li, Xiuhong Li, Zhe Chen, Fan Sheng, Jiabao Chen, Bin Wang, Haoyu School of Computer Science and Technology Xinjiang University Xinjiang China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong Department of Electrical Engineering Stanford University CA United States Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9789819601219

The swift proliferation of multimodal rumors on social media, particularly those with manipulated images and complex intermodal interactions, significantly challenges current detection methods. In response, we utilize statistical image features, including mean and variance, to capture spatial attributes effectively and improve the detection of image-tampered tweets. To tackle complex intermodal correlations, we introduce a contrastive learning approach that aligns features across modalities efficiently. Additionally, we introduce a cross-attention fusion module (CAFM) that enhances the integration of image and text modalities, thereby improving multimodal rumor detection performance. In conclusion, we propose the cross-attention fusion network (ConCAFN), leveraging contrastive learning for robust multimodal rumor detection. Extensive experiments on two real-world datasets confirm the model’s enhanced capability to detect multimodal rumors accurately, demonstrating our methods’ effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

PAC-MC: An Efficient Password-Based Access Control Framework for Time Sequence Aware Media Cloud

引用

IEEE Transactions on Mobile Computing 2025年第7期24卷 5632-5648页

作者： Wang, Haiyan Liu, Penghui Zhong, Xiaoxiong Luo, Fucai Xiao, Bin Yang, Yuanyuan Peng Cheng Laboratory Department of New Networks Shenzhen518000 China Zhejiang Gongshang University School of Computer Science and Technology Hangzhou China Hong Kong Polytechnic University Department of Computing Hong Kong Stony Brook University Department of Electrical and Computer Engineering Stony BrookNY11794 United States

Cloud storage makes it easier for users to access and share data remotely, but it often requires integration with cryptographic technologies to address consumer-oriented applications, such as fine-grained data access, secure data sharing and retrieval. This paper focuses on the fine-grained access problem of media applications based on time sequence, that is, certain critical media applications based on time sequences should ideally be accessible only to authorized clients. The traditional keyword-based searchable encryption (SE) allows effective search and access over encrypted data while preserving data privacy, but most existing solutions do not support temporal access control (i.e., a mechanism that grants access permissions to users within a specified time range). In this paper, we propose PAC-MC, an efficient password-based access control framework for media cloud relying on content control with the time sequence attribute. PAC-MC not only supports multi-keyword search using any monotonic boolean formulas but also allows media owners to control content-encryption keys for different time periods with an updatable password. Furthermore, it supports the self-retrieval of content-encryption keys. In addition, PAC-MC is provably secure under the standard model. Finally, the detailed performance evaluation results and experimental comparisons indicate that PAC-MC is very efficient and outperforms the previous solutions in terms of computation, communication, and storage costs. © 2025 IEEE.

关键词： Media Encryption Access Control Cloud Computing Servers Passwords Keyword Search Copyright Protection Streaming Media Performance Evaluation Access Control Content Protection Media Cloud Password Searchable Encryption Time Sequence Access Policy Access Control Framework Computational Cost Cloud Computing Communication Cost Storage Cost Encrypted Data Security Proof User Data Hash Function Computational Overhead Secret Key Public Key Access Structure Symmetric Encryption Data Owner Communication Overhead Key Material Encryption Scheme Number Of Keywords Cloud Users Encryption Key Bilinear Pairing Security Model Encrypted File Media Services Single Search L 2 Cache Internet Of Things

来源：评论

学校读者我要写书评

暂无评论

PneuTeleCNN: Deep Learning-assisted Framework for Pneumonia Identification in Web-enabled Telemedicine Systems 10

PneuTeleCNN: Deep Learning-assisted Framework for Pneumonia ...

引用

10th International Conference on Web Research, ICWR 2024

作者： Mahida, Nikunjkumar Parikh, Keertan Amit Darji, Krisha Gupta, Rajesh Tanwar, Sudeep Shahinzadeh, Hossein Mohammad-Hosseini, Melika Nirma University Institute of Technology Department of Computer Science and Engineering Ahmedabad India Amirkabir University of Technology Tehran Polytechnic Department of Electrical Engineering Tehran Iran Najafabad Branch Islamic Azad University Department of Electrical Engineering Najafabad Iran

ISBN: (纸本)9798350394986

An important development can be observed in the current environment of rapid technological progress in the healthcare industry, which can be demonstrated by the emergence of telemedicine as a key paradigm. Extensive use of telemedical techniques has happened with a particular focus on Tele-Pneumonia examinations, which provide doctors with crucial resources in remote diagnostic situations. In response to the necessity of accurate pneumonia prediction, we present a novel architecture PneuTeleCNN that makes utilization of pretrained models such as DenseNet-121, Visual Geometry Group (VGG-16), MobileNet, and InceptionV3. This thorough approach of PneuTeleCNN meticulously evaluates how effectively the system detects pneumonia in web-based telemedicine environments, establishing the stage for improved remote healthcare solutions. These model's performance is rigorously evaluated using key performance indicators, including accuracy, F1-score, recall, and precision. In addition, the evaluation includes sophisticated measures like the confusion matrix and receiver operating characteristic (ROC) curve, which offer an intricate perspective on the model's performance. To help in the identification of the model that performs better in this scenario, a comparative study is made more more straightforward by presenting of each model's validation accuracy and validation loss graphs. This PneuTeleCNN framework underscores the commitment to ensuring the robustness and reliability of the proposed telemedical approach for pneumonia detection in remote healthcare scenarios. © 2024 IEEE.

关键词： Telemedicine

来源：评论

学校读者我要写书评

暂无评论

A Rule and Network Dual-Driven Dynamic Scheduling Approach for Complex Flexible Manufacturing Job Shop 7

A Rule and Network Dual-Driven Dynamic Scheduling Approach f...

引用

7th International Conference on Robotics, Control and Automation engineering, RCAE 2024

作者： Xu, Kai Xu, Binzi Huang, Dengchao Wang, Chun Anhui Polytechnic University School of Electrical Engineering Wuhu241000 China Huaibei Normal University School of Computer Science and Technology Huaibei235000 China

ISBN: (纸本)9798350355642

Traditional manually designed dispatching rules (DRs) cannot cope with the variety and rapid changes in production environments due to their inflexibility and lack of adaptability. Meanwhile, the development in manufacturing intelligence and informatization allows for storing a vast amount of scheduling data during production. Consequently, a novel approach emerges in constructing scheduling models and decision-making strategies based on historical data. Following this idea, this paper proposes a dual-driven dynamic scheduling approach for complex flexible manufacturing job shops, utilizing a combination of manually designed DRs and backpropagation neural network (BPNN) technology. Specifically, six different production scenarios are designed to optimize different objectives, simulating the actual complex manufacturing environment. Then, a real-time scheduling mapping network model is developed with the production states as input and selected DRs as output by training the BPNN. The results demonstrate the effectiveness and practicality of the proposed method in resolving dynamic scheduling issues of complex flexible manufacturing job shops, surpassing traditional manual DRs. © 2024 IEEE.

关键词： Flexible manufacturing systems

来源：评论

学校读者我要写书评

暂无评论

A hybrid attention deep learning network for refined segmentation of cracks from shield tunnel lining images

引用

Journal of Rock Mechanics and Geotechnical engineering 2023年第12期15卷 3105-3117页

作者： Shuai Zhao Guokai Zhang Dongming Zhang Daoyuan Tan Hongwei Huang Department of Civil and Environmental Engineering The Hong Kong Polytechnic University999077Hong KongChina School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji UniversityShanghai200092China

This research developed a hybrid position-channel network (named PCNet) through incorporating newly designed channel and position attention modules into U-Net to alleviate the crack discontinuity problem in channel and spatial dimensions. In PCNet, the U-Net is used as a baseline to extract informative spatial and channel-wise features from shield tunnel lining crack images. A channel and a position attention module are designed and embedded after each convolution layer of U-Net to model the feature interdependencies in channel and spatial dimensions. These attention modules can make the U-Net adaptively integrate local crack features with their global dependencies. Experiments were conducted utilizing the dataset based on the images from Shanghai metro shield tunnels. The results validate the effectiveness of the designed channel and position attention modules, since they can individually increase balanced accuracy (BA) by 11.25% and 12.95%, intersection over union (IoU) by 10.79% and 11.83%, and F1 score by 9.96% and 10.63%, respectively. In comparison with the state-of-the-art models (i.e. LinkNet, PSPNet, U-Net, PANet, and Mask R–CNN) on the testing dataset, the proposed PCNet outperforms others with an improvement of BA, IoU, and F1 score owing to the implementation of the channel and position attention modules. These evaluation metrics indicate that the proposed PCNet presents refined crack segmentation with improved performance and is a practicable approach to segment shield tunnel lining cracks in field practice.

关键词： Crack segmentation Crack disjoint problem U-net Channel attention Position attention

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：