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共 31242 条记录，以下是481-490 订阅

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Boost Inverter for Switched Reluctance Motor Drive without Additional Inductor

Boost Inverter for Switched Reluctance Motor Drive without A...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Ohtaki, Satoshi Kato, Hirotaka Watanabe, Hiroki Itoh, Jun-Ichi Nagaoka University of Technology Dept. of Electrical Electronics and Information Engineering Nagaoka Japan

ISBN: (纸本)9798350376067

This paper proposes a novel topology of a boost inverter for a switched reluctance motor (SRM) without an additional inductor. In addition, this paper realizes a design method for a boost-up capacitor. The SRM drive is required to suppress a radial force ripple caused by acoustic noise and vibration. The seamless current control entails a rapid current control response. However, the current control response is limited by the DC link voltage. Moreover, the di/dt is increased due to a back electromagnetic voltage of the SRM at high speed. Applying the additional inductor achieves an increase of the maximum voltage but also provides an increase of the volume. The proposed inverter only adds a boost-up capacitor to the DC part without an additional inductor to boost a DC link voltage. The boost-up capacitor is designed to minimize the volume. The proposed circuit achieves a boost operation at all operating points. The phase current follows the current command, thanks to the boost function under various operating conditions. The capacitor voltage ripple matches the design value with an error rate of -13.5%. The validity of the proposed design method of the boost-up capacitor is confirmed. © 2024 IEEE.

关键词： Reluctance motors

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Aircraft Target Detection Algorithm for SAR Images Based on Improved YOLOv8 30

Aircraft Target Detection Algorithm for SAR Images Based on ...

引用

30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Wang, Chengkun Ding, Haotian Zhao, Maoni Heilongjiang University of Science and Technology Dept. Electronic and Information Engineering Harbin China

ISBN: (纸本)9798350391916

Aiming at the problem of high model complexity of aircraft target detection algorithms on Synthetic Aperture Radar (SAR) images, this paper proposes an optimized YOLOv8 algorithm to detect aircraft targets in SAR images. First, given that most aircraft targets in SAR images are small and medium-sized, the network structure for detecting large targets in the original model was removed, and the feature extraction and fusion network was reconstructed to make the model more lightweight. In addition, Acmix (Self-Attention and Convolution) is introduced in the Head section which can enhance the model's ability to extract global features. Finally, to address the issue of a small number of values with denominators close to zero in the gradient calculation of the optimized model, the calculation of the CIoU was optimized to enhance the model's stability during the calculation process. The results on the SAR-AIRcraft-1.0 dataset show that the optimized model reduces the model size by 19.1%, the number of calculated parameters by 57.8%, and GFLOPs by 9.6%, while maintaining high detection accuracy. Compared with other lightweight models, this model has obvious advantages in complexity. The prediction results confirm that the optimized model is optimal for detection with a confidence setting of 0.6. In summary, the optimized model strikes a balance between detection accuracy and model complexity. © 2024 IEEE.

关键词： ACmix ciou network reconfiguration sar yolov8

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'Do Not Disturb': An Implication Design To Be Alerted But Less Stress

'Do Not Disturb': An Implication Design To Be Alerted But Le...

引用

2023 International Seminar on Application for technology of information and Communication, iSemantic 2023

作者： Jarupreechachan, Weerachaya Kitchat, Kotcharat Surasak, Thattapon Kasetsart University Faculty of Engineering at Kamphaeng Saen Dept. of Computer Engineering Nakhon Pathom Thailand National Central University Dept. of Computer Science and Information Engineering Taoyuan Taiwan King Mongkut's University of Technology North Bangkok Faculty of Applied Science Dept. of Computer and Information Science Bangkok Thailand

ISBN: (纸本)9798350339215

The pervasive utilization of smartphones, while augmenting personal and professional communications, also elicits mental stress and disrupts the work-life balance. Users necessitate staying connected to critical updates without undue disruption, necessitating an optimized, user-friendly smartphone interface. However, current "Do Not Disturb (DND)"features fall short of providing the desired customization options, thereby contributing to heightened anxiety and diminished productivity. Consequently, this study proposes a design modification to the DND mode by incorporating an "Exceptional Apps Notification", feature thereby aiding in alleviating stress and enhancing focus by permitting essential alerts from selected apps or contacts. In other words, the users only need to turn off notifications for specific applications, not every application. This approach addresses the problem of users fearing they will miss some important notifications. Therefore, the design process employed principles of selective attention and color theory, and user experience was assessed through questionnaires and psycho-physiological feedback. Early findings suggest the potential for stress reduction, albeit with opportunities for further optimization, such as including a memory feature for user preferences and allowing selective access for specific contacts. © 2023 IEEE.

关键词： User interfaces

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Cooperative Spectrum Sensing Using Energy-Based Detection for Low SNR Regime over Rayleigh Fading Channel

Cooperative Spectrum Sensing Using Energy-Based Detection fo...

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2024 International Conference on Integrated Circuits, Communication, and Computing Systems, ICIC3S 2024

作者： Sharma, Aakanksha Pandit, Shweta Kumar, Rajiv Jaypee University of Information Technology Dept. of Electronics and Communication Engineering Solan India

ISBN: (纸本)9798350364088

The increase in number of wireless user has resulted in spectrum shortage. Cognitive radio network solves this issue of spectrum scarcity in current communication networks by intelligently detecting the licensed spectrum use or vacancy by the primary user so that secondary users can use the vacant licensed spectrum of primary user. Spectrum detection or sensing is an essential stage in the cognitive radio cycle since it is the one that determines how well the cognitive radio network performs. There are various techniques for spectrum detection or sensing, however, energy-based detection is the easiest and most commonly used method. The non-cooperative spectrum sensing faces certain issues such as hidden node/terminal and shadowing which can be resolved by cooperative or collaborative spectrum sensing. We have investigated the performance analysis for cooperative or collaborative spectrum sensing using energy-based detection over Rayleigh fading channel in very low signal-to-noise ratio (SNR) levels (0 dB to -25 dB). © 2024 IEEE.

关键词： Rayleigh fading

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Efficient Kidney Tumor Classification and Segmentation with U-Net 46

Efficient Kidney Tumor Classification and Segmentation with ...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Varalakshmi, P. Tilak Soorya, R. Anugeeta, S. Akshaya, S. Anna University College of Engineering Dept. of Information Science and Technology Chennai India

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371499

A novel approach to kidney tumor identification is introduced, which integrates kidney tumor classification and segmentation algorithms. The multi-faceted approach commences with the classification of kidney images, adaptly discerning between normal and tumor instances. For individuals identified as tumor-positive, a sophisticated UNet-based architecture is intricately employed to achieve precise segmentation, capturing nuanced details of both kidney and tumor regions. Many models, including VGG16, MobileNetV3, DenseNet50, and others, were tested in order to achieve this. Among these, MobilenetV3 performs better than the others in terms of accuracy, with a 99.1% accuracy rate and a 99% precision rate for classification. In this research, we applied a novel U-Net model to accurately segregate kidney and kidney tumor from CT scan data. With this, an average dice coefficient score of 0.9445 is obtained. In advancing the landscape of kidney tumor analysis, this proposed strategy not only bridges classification and segmentation but also showcases a significant leap toward refined clinical applications. © 2024 IEEE.

关键词： Image segmentation

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IT Governance & Management for Smart City: Aligning COBIT 2019 with SPBE Policies for Traditional Market Digitalization Initiatives

IT Governance & Management for Smart City: Aligning COBIT 20...

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2024 International Conference on information technology Systems and Innovation, ICITSI 2024

作者： Restavie Bujung, Rizky Dwiputra Hartanto, Rudy Winarno, Wing Wahyu Gadjah Mada University Dept. of Electrical Engineering and Information Technology Yogyakarta Indonesia

ISBN: (纸本)9798331511470

The digitalization of traditional markets is a significant government initiative aimed at preserving market competitiveness in the digital era. However, the program's success is closely tied to effective IT governance due to the complexity of needs and challenges faced by the government This study proposes an IT Governance and Management (ITGM) framework for traditional market digitalization, leveraging the COBIT 2019 framework in alignment with Indonesia's Electronic-Based Government System (SPBE) policies. Using Yogyakarta City and Sleman Regency as case studies, this research identifies key challenges, including stakeholder engagement, digital literacy gaps, resource limitations, and policy shortcomings. By prioritizing 11 ITGM objectives that address these challenges and align with SPBE policies, the study offers a targeted framework for local governments to advance digitalization efforts within traditional markets, linking them to broader Smart City and SPBE initiatives. This approach offers practical guidance for local governments to effectively structure and sustain traditional market digitalization efforts. Future research could explore its adaptability to other Smart City programs, particularly those lacking robust regulatory and governance frameworks. © 2024 IEEE.

关键词： COBIT 2019 Digitalization IT Governance IT Management SPBE Policy Traditional Market

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LSTM Architecture Valuation in Recognizing Speech-Based Emotion

LSTM Architecture Valuation in Recognizing Speech-Based Emot...

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2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2024

作者： Halimah, Noor Siti Hidayat, Risanuri Mustika, I. Wayan Dept. of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9798350353464

Using Recurrent Neural Networks Long Short-Term Memory (RNN-LSTM) as a classification model can yield varied results. This research explores the effectiveness of LSTM as a classification model for Speech Emotion Recognition (SER) system, and how its architecture influences accuracy. The study compared various LSTM models with different numbers of layers and cells configurations using the TESS dataset. These models were evaluated through univariate ANOVA and correlation tests. Our results indicate that the number of LSTM cells significantly impacts accuracy, while the number of layers does not. The single-layer LSTM with 128 cells achieved the best training accuracy at 0.994 and test accuracy at 0.993. ©2024 IEEE.

关键词： Long short-term memory

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A Deep Learning Analysis on Facial Skin Using CNN 3

A Deep Learning Analysis on Facial Skin Using CNN

引用

3rd IEEE International Conference on Intelligent Systems, Smart and Green Technologies, ICISSGT 2024

作者： Chandana, Kavuri Swathi, Nerusu Vijay, Vemuri Kumar, M. Ashok Velagapudi Ramakrishna Siddhartha Engineering College Dept. of Information Technology Kanuru India

ISBN: (纸本)9798350304329

Skin Diseases can have cerebral goods in addition to medical bones, especially for those who have disfigurement or facial trauma. Since smart widgets are so extensively used, utmost people may readily take clinical filmland of their skin issues on their faces. In image processing, convolutional neural networks (CNNs) have demonstrated amazing performance, constantly outperforming mortal bents. Using clinical images, this study investigates different CNN algorithms for the bracket of six current skin conditions on the face rosacea, actinic keratosis, seborrheic keratosis, lupus erythematosus, rudimentary cell melanoma, and scaled cell melanoma. Xiangya- Derm was used to produce a dataset of 2656 facial prints that represented the forenamed skin conditions. In China, this is the largest clinical imaging dataset for skin conditions. Five extensively used network approaches for these complaint groups were compared. An independent dataset with the same conditions from several body locales was used to apply transfer literacy. Transfer literacy models demonstrated better average recall and perfection. In a test dataset conforming of 388 facial filmland, the bestmodel attained recalls of 92.9,89.2, and 84.3 for lupus erythematosus, rudimentary cell melanoma, and seborrheic keratosis, independently. Recall and perfection were on average 77.0 and 70.8, independently. © 2024 IEEE.

关键词： Convolutional neural networks

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Innovative Currency Identifier for the Blind through Audio Output using Deep Learning

Innovative Currency Identifier for the Blind through Audio O...

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2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Maganti, Rajasri Gutla, Jessica Mallimpalli, Yaswanth Yellisetti, Sandeep Velagapudi Ramakrishna Siddhartha Engineering College Dept. of Information Technology Vijayawada India

ISBN: (纸本)9798350382723

With an estimated 4.95 million blind people and 70 million visually impaired individuals in India are facing challenges in their day-to-day monetary transactions, worsened by the complexities in identifying tactile features of notes post-demonetization, this research presents an approach to enhance independence and accessibility. The introduction of the Currency Identification System (CIS), which is specifically designed for Indian cash and is accomplished via an android application with a camera interface for voice output and recording. We examine the shortcomings of current systems while highlighting the particular difficulties experienced by the blind people in our society. As a result, we have developed a novel CIS that combines two deep learning algorithms: Convolutional Neural Networks (CNN) and Residual Networks (ResNet). We trained a model using these two algorithms and compared the algorithms to use the best model for our application. The outcomes demonstrate the ResNet's exceptional performance, with an 90% accuracy rate. By demonstrating the effectiveness of deep learning models in these kinds of applications, our research adds to the growing field of assistive technology. With the help of our research, we shed light on the ways in which technology can promote independence and inclusion in the lives of people, which is a critical step in the direction of increased financial accessibility and control. © 2024 IEEE.

关键词： Convolutional neural networks

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Revolutionizing Healthcare with IoT: Integrated Monitoring of BMI and ECG

Revolutionizing Healthcare with IoT: Integrated Monitoring o...

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2024 International Conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Srinivas, M.G.C. Sangeetha, Y. Vinay, P Sai Kumar, S Tharun V R Siddhartha Engineering College Dept. of Information Technology Vijayawada India

ISBN: (纸本)9798350381887

People lacking awareness of the importance of BMI may not acknowledge the potential health hazards associated with being underweight, overweight, or obese. Insufficient awareness may result in neglecting potential concerns, such as cardiovascular diseases and diabetes, commonly associated with BMI. Without knowledge of ECG and its role in monitoring heart health, individuals may not be aware of early signs of cardiovascular problems. Delayed detection of irregular heart patterns or abnormalities may increase the risk of heart disease or other cardiac-related complications. This project combines hardware components with software development to create a holistic health monitoring system that promotes user awareness and engagement. © 2024 IEEE.

关键词： Heart

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