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8th International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2023

作者： Liu, Ziqiong Li, Wenju Cui, Liu Gao, Xiaosong Shanghai Institute of Technology School of Computer Science and Information Engineering Shanghai China ShangHai CRRC Ro-Intelligent System. Co. Ltd. Shanghai China

ISBN: (纸本)9798350369564

Traffic sign recognition has long been an essential part of automatic driving. Accurate traffic sign recognition algorithms are conducive to the development of automatic driving. However, traffic signs in natural scenes are often small targets, which contain less feature information and are difficult to detect and recognize. Aiming at the problem of low recognition accuracy of small targets in traffic sign recognition, a traffic sign recognition algorithm based on a Bi-Level Routing Attention is proposed. It utilizes a single-stage detector YOLOv5 as the basic network, with a double-layer routing attention mechanism introduced, realizing more flexible computing allocation and content awareness through double-layer routing, which could capture long-range data without incurring an increasing computational overhead and memory usage. Furthermore, our approach achieves noteworthy recognition accuracy by extracting fine-grained information of small targets. In particular, the experiment shows the appealing results on the TT100K dataset, which detection accuracy map of reaches 92.9%, and the frame processing rate is 119.8FPS. © 2023 IEEE.

关键词： Object detection

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AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis of the Femoral Head Detection 37

AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis o...

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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Chen, Haoyang Liu, Shuai Lu, Feng Li, Wei Sheng, Bin Li, Mi Jin, Hai Zomaya, Albert Y. National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Department of Computer Science and Engineering Shanghai Jiao Tong University China Tongji Hospital Tongji Medical College Huazhong University of Science and Technology China

ISBN: (纸本)9781577358800

Early diagnosis of osteonecrosis of the femoral head (ONFH) can inhibit the progression and improve femoral head preservation. The radiograph difference between early ONFH and healthy ones is not apparent to the naked eye. It is also hard to produce a large dataset to train the classification model. In this paper, we propose Asymmetric-Sensitive Transformer (AsT) to capture the uneven development of the bilateral femoral head to enable robust ONFH detection. Our ONFH detection is realized using the self-attention mechanism to femoral head regions while conferring sensitivity to the uneven development by the attention-shared transformer. The real-world experiment studies show that AsT achieves the best performance of AUC 0.9313 in the early diagnosis of ONFH and can find out misdiagnosis cases firmly. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Large dataset

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Hardware Implementation of a Traveling Wave Protection Device for DC Microgrids 4

Hardware Implementation of a Traveling Wave Protection Devic...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Paruthiyil, Sajay Krishnan Bidram, Ali Aparicio, Miguel Jimenez Hernandez-Alvidrez, Javier Reno, Matthew J. University of New Mexico Department of Electrical and Computer Engineering AlbuquerqueNM United States Electric Power System Research Sandia National Laboratories AlbuquerqueNM United States

ISBN: (纸本)9798350335408

This paper elaborates the results of the hardware implementation of a traveling wave (TW) protection device (PD) for DC microgrids. The proposed TWPD is implemented on a commercial digital signal processor (DSP) board. In the developed TWPD, first, the DSP board's Analog to Digital Converter (ADC) is used to sample the input at a 1 MHz sampling rate. The Analog Input card of DSP board measures the pole current at the TWPD location in DC microgrid. Then, a TW detection algorithm is applied on the output of the ADC to detect the fault occurrence instance. Once this instance is detected, multi-resolution analysis (MRA) is performed on a 128-sample data butter that is created around the fault instance. The MRA utilizes discrete wavelet transform (DWT) to extract the high-frequency signatures of measured pole current. To quantity the extracted TW features, the Parseval theorem is used to calculate the Parseval energy of reconstructed wavelet coefficients created by MRA. These Parseval energy values are later used as inputs to a polynomial linear regression tool to estimate the fault location. The performance of the created TWPD is verified using an experimental testbed. © 2023 IEEE.

关键词： Discrete wavelet transforms

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Emotion Recognition of Humans using modern technology of AI: A Survey 7

Emotion Recognition of Humans using modern technology of AI:...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Alheeti, Ahmed Adil Mohammed Salih, Mustafa Muhanad M. Mohammed, Alaa Hamid Hamood, Mostafa A. Khudhair, Nemer Radhwan Shakir, Ahmed Thair Karabuk University Department of Computer Engineering Turkey AL Mansour University College Department of Computer Science and Information System Baghdad Iraq Al-Maarif University College Department of Medical Instruments Techniques Engineering Iraq University of Baghdad College of Engineering Department of Chemical Engineering Baghdad Iraq University of Anbar College of Applied Sciences Department of Biophysics Ramadi Iraq

ISBN: (纸本)9798350383065

This comprehensive investigation and evaluation of the subject matter of emotion recognition is presented, focusing on the broader implications for society at large. The study utilizes a thorough analysis of scholarly literature and practical observations to establish a theoretical framework that facilitates comprehension of the topic under investigation. The findings have considerable implications for future investigations and pragmatic applications. Emotion recognition holds immense importance in diverse domains such as human-computer interaction and healthcare. The analysis of techniques used for emotional recognition includes facial expression assessment, speech patterns analysis, physiological signal interpretation, music perception, and written expression evaluation. The study presents a comprehensive overview of research methodologies commonly used in emotion recognition, discussing datasets, feature extraction techniques, and classification algorithms. The analysis of challenges and limitations pertaining to emotion recognition systems, including privacy concerns, is also discussed. Performance evaluation is analyzed through various methods, including machine assessment and self-report. The significance of continued investigation within the domains encompassing data integration across diverse modalities, the creation of robust classification algorithms, and the exploration of the intricate connection between the brain and affective states is underscored. © 2023 IEEE.

关键词： Emotion Recognition

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Automatic License Plate Detection Using Information Processing system Vision and Deep Learning 2

Automatic License Plate Detection Using Information Processi...

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Sharma, Avinash Dwivedi, Ishita Dawar, Divya Saxena, Rini Barua, Tarkcshwar Goyel, Parul Chandigarh Engineering Chandigarh Group of Colleges Department of information processing system Science and Engineering Mohali140307 India Mohali140307 India Roorkee Institute of Technology Computer Science & Engineering Department Roorkee India M. M. Engineering College Maharishi Markandeshwar University CSE Department Mullana Haryana Ambala133207 India

ISBN: (纸本)9798350366570

The content of this probe is to overcome the current cognitive content with ALPR playacting, with a special accent on developing a dead and impelling playacting for distinguishing License plates from video film. The study attempts to ameliorate the presentation norms of ALPR technology by utilizing the powerful accumulation of optical character identification (OCR)[20] and deep learning based object detection algorithmic program. The core of this occupation is the use of the cutting-edge YOLOv8. object distinguishing hypothesis, which has been pains taking and disciplined on an unequaled dataset premeditated with License plate detection in mind. Focusing on quality and efficiency, the YOLOv8 model accomplish an amazing 99.8 quality rate when it comes to accurately localization and categorization License plates[18] inside video frames. This occupation aims to formalize the willingness and dependability of the advisable ALPR playacting through extensive scientific research. The project aims to intensify ALPR technology and determinant the forthcoming of transport and police investigation playactings[18] by breaking through current obstruction and establishing new presentation norms. © 2024 IEEE.

关键词： Deep learning

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On the Security of Smart Home systems:A Survey

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Journal of computer Science & Technology 2023年第2期38卷 228-247页

作者：袁斌万俊吴宇晗邹德清金海 School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Distributed System Security Huazhong University of Science and Technology Wuhan 430074China Hubei Engineering Research Center on Big Data Security Huazhong University of Science and Technology Wuhan 430074China National Engineering Research Center for Big Data Technology and System Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System Lab Huazhong University of Science and TechnologyWuhan 430074China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518057China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Lab Huazhong University of Science and TechnologyWuhan 430074China

Among the plethora of IoT(Internet of Things)applications,the smart home is one of the ***,the rapid development of the smart home has also made smart home systems a target for ***,researchers have made many efforts to investigate and enhance the security of smart home *** a more secure smart home ecosystem,we present a detailed literature review on the security of smart home ***,we categorize smart home systems’security issues into the platform,device,and communication *** exploring the research and specific issues in each of these security areas,we summarize the root causes of the security flaws in today's smart home systems,which include the heterogeneity of internal components of the systems,vendors'customization,the lack of clear responsibility boundaries and the absence of standard security ***,to better understand the security of smart home systems and potentially provide better protection for smart home systems,we propose research directions,including automated vulnerability mining,vigorous security checking,and data-driven security analysis.

关键词： IoT(Internet of Things) smart home IoT security smart home security

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Track Slab Crack Detection Algorithm with Few Samples Based on Deep Learning 8

Track Slab Crack Detection Algorithm with Few Samples Based ...

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8th International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2023

作者： Liu, Zhongjie Li, Wenju Gao, Xiaosong Liu, Cui Shanghai Institute of Technology School of Computer Science and Information Engineering Shanghai China Shanghai Crrc Ro-Intelligent System. Co. Ltd. Shanghai China

ISBN: (纸本)9798350369564

In order to solve the problem of track slab crack detection under few samples' conditions, this paper proposes a track slab crack detection algorithm with few samples based on deep learning. Firstly, after extracting multi-scale query and support features through the Swin Transformer backbone, the similarity between query pixels and support pixels is computed according to the scaled dot-product attention of the Transformer architecture, and the query masks are aggregated;in order to filter a large amount of irrelevant background information in the crack image, multi-scale prototypes are computed by using prototypical learning, highlighting the class information of the cracks, and introducing a lightweight attention module to generate class-representative attention feature maps using support features at different scales, which guides the network to focus its attention on the target region;finally, the final prediction of cracks is realized by the feature fusion module. The experimental results show that the track slab crack IoU reaches 66.94% and the FB-IoU reaches 83.02% under the few samples' condition and exhibits strong generalization performance on the crack set of other scenarios as well. © 2023 IEEE.

关键词： Crack detection

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Internet of Things in Textile Sensors 5

Internet of Things in Textile Sensors

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5th National Conference of Saudi computers Colleges, NCCC 2022

作者： Ballaji, Hattan Khaled Umm Al-Qura University College of Computers and Information System Computer Engineering Department Makkah24381 Saudi Arabia

ISBN: (纸本)9798350333688

New integration options with conformable sensors have been made possible by the digitization of textiles (textronics), allowing for the continuous, unobtrusive, and noninvasive decoding of essential physiological signals. This article offers a thorough analysis of the Internet of Things' textile sensors and the fabrication techniques utilized for textronic sensors according to the form factors of fiber, yarn, fabric, and apparel. It also emphasizes the significance of pretreatment and conditioning reporting of the textile formfactors due to their influence on the mechanical and electrical performance of the textronic sensor. The study comes to the conclusion that in addition to being able to communicate information, textile-based sensors can be used as smart sensing devices to access the mobile internet through wearable computing devices that can be attached to or worn on the human body. The next generation of human-computer interfaces may be built on top of these sensors. One of the factors influencing the development of textile sensors is the ongoing discovery of novel conductive materials. © 2022 IEEE.

关键词： Smart textiles

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MPC Implementation for Optimal Active Power Control of Large-Scale Wind-PV-Battery Hybrid system 42

MPC Implementation for Optimal Active Power Control of Large...

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42nd Chinese Control Conference, CCC 2023

作者： Zhang, Zihan Lin, Zhongwei Zhao, Ze Zhou, Jiawei Qu, Chenzhi School of Control and Computer Engineering North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China

ISBN: (纸本)9789887581543

This paper investigates the operational strategy for real-time optimal active power control of large-scale wind-PV-battery hybrid system. The MPC strategy is established with objective, forecast models and constraints for active power control of wind-PV-battery hybrid system, which simultaneously maximizes tracking accuracy and minimizes settling time. To guarantee the industrial reliability, the corresponding optimization solver and control architecture have been specifically developed and designed. Hardware-in-loop (HIL) experiments are conducted using the real-time digital simulator (RTDS) and programmable logic controllers (PLCs). Under different operating scenarios, HIL-RTDS testing results demonstrate that the MPC strategy significantly improves the tracking speed and accuracy compared to the conventional strategy in both normal and abnormal operating scenarios, which also sustain the feasibility of industrial implementation. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Programmable logic controllers

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Sensitivity Analysis for Stopping Criteria with Application to Organ Transplantations

Sensitivity Analysis for Stopping Criteria with Application ...

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2023 Winter Simulation Conference, WSC 2023

作者： Ren, Xingyu Fu, Michael C. Marcus, Steven I. University of Maryland Institute for System Research Department of Electrical and Computer Engineering College ParkMD20742 United States University of Maryland Robert H. Smith School of Business Institute for System Research College ParkMD20742 United States

ISBN: (纸本)9798350369663

We consider a stopping problem and its application to the decision-making process regarding the optimal timing of organ transplantation for individual patients. At each decision period, the patient state is inspected and a decision is made whether to transplant. If the organ is transplanted, the process terminates;otherwise, the process continues until a transplant happens or the patient dies. Under suitable conditions, we show that there exists a control limit optimal policy. We propose a smoothed perturbation analysis (SPA) estimator for the gradient of the total expected discounted reward with respect to the control limit. Moreover, we show that the SPA estimator is asymptotically unbiased. © 2023 IEEE.

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