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13th IEEE International Conference on CYBER Technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Sun, Yiwei Wei, Yangjie Chen, Sike Zhao, Ji College of Computer Science and Engineering Northeastern University LN Shenyang China College of Mechanical Engineering and Automation Northeastern University LN Shenyang China

ISBN: (纸本)9798350315196

Existing design methods for off-axis reflective optical systems have certain limitations, such as complicated design processes, lengthy calculations and experience dependence. This study establishes an integrated generation method for the initial system of off-axis reflective optical systems and proposes it as a solution to the aforementioned limitations and for improvement of the design quality and efficiency of off-axis reflective systems. First, the tilt matrix and displacement matrix are introduced to consider changes in the shapes and space poses of the mirrors, and a simplified mathematical modeling method for arbitrary pose mirrors in an off-axis reflective system is proposed. Then, a mirror mathematical model of an arbitrary mirror relative to an arbitrary reference mirror is established by introducing the relative pose relationship between the two mirrors. Then, a model for the mirror-to-mirror and mirror-to-image transfer optical path in the off-axis mirror system is constructed, and the initial system for an off-axis reflective optical system can be automatically and quantitatively calculated. Experimental results show that the method proposed in this paper exhibits the advantages of high practicability, low requirements for designers' experience, easy to obtain design and manufacturing automation and intellectualization. © 2023 IEEE.

关键词： Mirrors

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Multi-Frequency State-Feedback Current Control for Active Power Filters

Multi-Frequency State-Feedback Current Control for Active Po...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Sánchez, Lidia Reigosa, David Nurminen, Tuure Mourouvin, Rayane Hinkkanen, Marko Briz, Fernando University of Oviedo Dept. of Elect. Computer & System Engineering Gijón33204 Spain Aalto University Dept. of Electrical Engineering and Automation Espoo02150 Finland

ISBN: (纸本)9798350376067

Feedback-based methods combining proportional-integral and/or resonant controllers are the most common option for Active Power Filter (APF) control. Alternatively to classical feedback-based control, state-feedback current control could be used, potentially enabling better dynamic performance. State-feedback current control has been previously proposed for grid-connected converters;however, reference tracking response of multiple harmonic components of the controlled current has not been reported. This is highly relevant to comply with grid codes. This paper analyses the design and implementation of state-feedback current control for harmonic current compensation in APFs. © 2024 IEEE.

关键词： Active filters

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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DDT-Net:Deep Detail Tracking Network for Image Tampering Detection

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computers, Materials & Continua 2025年第5期83卷 3451-3469页

作者： Jim Wong Zhaoxiang Zang Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang443002China College of Computer and Information Technology ChinaThree Gorges UniversityYichang443002China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650504China

In the field of image forensics,image tampering detection is a critical and challenging *** methods based on manually designed feature extraction typically focus on a specific type of tampering operation,which limits their effectiveness in complex scenarios involving multiple forms of *** deep learningbasedmethods offer the advantage of automatic feature learning,current approaches still require further improvements in terms of detection accuracy and computational *** address these challenges,this study applies the UNet 3+model to image tampering detection and proposes a hybrid framework,referred to as DDT-Net(Deep Detail Tracking Network),which integrates deep learning with traditional detection *** contrast to traditional additive methods,this approach innovatively applies amultiplicative fusion technique during downsampling,effectively combining the deep learning feature maps at each layer with those generated by the Bayar noise *** design enables noise residual features to guide the learning of semantic features more precisely and efficiently,thus facilitating comprehensive feature-level ***,by leveraging the complementary strengths of deep networks in capturing large-scale semantic manipulations and traditional algorithms’proficiency in detecting fine-grained local traces,the method significantly enhances the accuracy and robustness of tampered region *** with other approaches,the proposed method achieves an F1 score improvement exceeding 30% on the DEFACTO and DIS25k *** addition,it has been extensively validated on other datasets,including CASIA and *** results demonstrate that this method achieves outstanding performance across various types of image tampering detection tasks.

关键词： Image forensics image tampering detection image manipulation detection noise flow Bayar

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Can adaptive strategies sustain bidirectional LoRaWAN traffic? 6

Can adaptive strategies sustain bidirectional LoRaWAN traffi...

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6th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2023

作者： Sisinni, Emiliano Depari, Alessandro Bellagente, Paolo Flammini, Alessandra Silva, Ivanovitvh Flores, Thommas Ferrari, Paolo University of Brescia Dept. of Information Engineering Brescia Italy Ufrn Dept. of Computer Engineering and Automation Natal Brazil Postgraduate Program in Electrical and Computer Enigeneering Ufrn Natal Brazil

ISBN: (纸本)9798350396577

Low Power Wide Area Networks (LPWANs) are a viable solution for addressing the requirements of Internet of Things (IoT) applications that can tolerate sporadic updates, possibly only in the uplink (from the field towards the cloud and the user) direction. LoRaWAN is currently the most diffused example of LPWAN, exploiting LoRa radios. LoRa, an enhanced version of chirp spread spectrum modulation, trades off the radio sensitivity for the data rate, permitting extensive area coverage. However, the price is a relatively long frame duration, leading to high collision probability in dense, asynchronous scenarios;fortunately, polarity inversion minimizes collisions between uplink and downlink traffic. Therefore, adaptive strategies (based on some feedback from the backend) have also been suggested to adapt the data rate depending on the environment condition dynamically. This work compares the ADR (Adaptive Data Rate) and the ADP (Adaptive Data Payload) strategies when bidirectional traffic exists, using a purposely designed simulator. Results considering a different number of gateways show that ADP tries to maximize the amount of data effectively received in both direction but suffer from the adoption of longer frame duration, leading to higher collision probability. In contrast, ADR tries to force the adoption of the fastest data rate, limiting the overall amount of transferred data. © 2023 IEEE.

关键词： Wide area networks

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BACFuse: Toward Noise-Resistant BAC Detection Based on Multimodal Fusion on Smartphone

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IEEE Internet of Things Journal 2025年第11期12卷 16410-16423页

作者： Wu, Yuan Zhao, Gaorong Yang, Zheng Feng, Yong Wang, Yongmei Ding, Lei Chen, Jia Zhang, Jian Chen, Yanjiao Wuhan Textile University School of Computer Science and Artificial Intelligence Engineering Research Center of Hubei Province for Clothing Information Wuhan430200 China Wuhan University School of Computer Science Wuhan230036 China Kunming University of Science and Technology School of Information Engineering and Automation Kunming650500 China Anhui Agricultural University School of Information and Artificial Intelligence Hefei230036 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

Drunk-driving is an important factor causing road traffic accidents and deaths, which deserves a lot of research. However, most current methods for detecting drunk-driving depend on customized hardware or require users’ active participation, making it impractical to monitor blood alcohol content (BAC) during driving. This article introduces BACFuse, a device-free, contactless, and noninvasive system utilizing smartphone in driving environments, which achieves relatively high accuracy in drunk-driving monitoring by integrating various voice sensing modalities. BACFuse first captures vocal cord vibration from ultrasonic signals, then records voice commands from audio signals. BACFuse combines the ultrasonic signals with audio signals and effectively detects drunk-driving and BAC. A key enabler lies in our modeling of latent interaction between acoustic and ultrasonic signals to mitigate ambient noise, realizing noise-resistant drunk-driving detection. Additionally, we propose an effective modules within the co-attention method to fuse the multimodal signals, further enhancing the accuracy of drunk-driving detection. We conduct extensive experiments to evaluate BACFuse’s performance on 20 participants in safe laboratory experiments. The results demonstrate that our system achieves BAC measurement with an MAE of 2.13 mg/dl, showing promise for future in-car driving management paradigms. © 2014 IEEE.

关键词： Ultrasonic devices

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Algorithms of Natural Language Dialogue with Intelligent Robot NAO EVOLUTION 6

Algorithms of Natural Language Dialogue with Intelligent Rob...

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6th International Conference on Information Technologies in engineering Education, Inforino 2022

作者： Shvetcov, Anatoliy Gorbunov, Vyacheslav Dianov, Sergey Sukonschikov, Alexey Rapakov, George Kinyakin, Kyril Vologda State University Department of Automation and Computer Engineering Vologda Russia

ISBN: (纸本)9781665405775

This article is devoted to the usage of anthropomorphic robot NAO Evolution in teaching process of bachelors and masters at automation and computer engineering department of Vologda State University. The paper discusses the content and implementation of software system of the dialogue man-robot on natural Russian language using the software package Choreography and dialogue creation tool QIChat. Fragments of software modules that implement the developed features are given. © 2022 IEEE.

关键词： Knowledge engineering Software packages Software algorithms Natural languages Software systems Teamwork Information technology

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SC-YOLO: An Improved Yolo Network for PCB Defect Detection 5

SC-YOLO: An Improved Yolo Network for PCB Defect Detection

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5th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2024

作者： Wang, Shuo Li, Changxian Song, Xudong Wang, Yucheng Dalian Jiaotong University School of Software Engineering Dalian China Dalian Jiaotong University School of Automation and Electrical Engineering Dalian China Dalian Jiaotong University Computer and Communication Engineering Institute Dalian China

ISBN: (纸本)9798350385557

Defect detection is a crucial aspect of quality control in the manufacturing of printed circuit boards (PCBs). In order to enhance detection accuracy and address issues related to background redundancy and small target challenges, an improved YOLOv7 network for surface defect detection on PCBs is proposed in this study. Firstly, the Shape-IOU is adopted as the loss function, focusing on the self-shape and self-scale of the bounding box for precise bounding box regression. Subsequently, the CBAM attention mechanism is introduced into the feature extraction section to augment the network's feature extraction capabilities and improve the detection ability for small target defects. Experimental results demonstrate that the proposed SCYOLO achieves a mAP of 97.6% on a public PCB dataset, surpassing the original YOLOv7 by 2.3%, signifying a significant improvement in detection accuracy. This detection network holds substantial significance for quality control in the industrial production of printed circuit boards. © 2024 IEEE.

关键词： Printed circuit boards

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Classification of brain ischemia and hemorrhagic stroke using a hybrid method 4

Classification of brain ischemia and hemorrhagic stroke usin...

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4th International Conference on Data Analytics for Business and Industry, ICDABI 2023

作者： Cinar, Necip Kaya, Buket Kaya, Mehmet Dicle University Dept. of Computer Engineering Diyabakir Turkey Firat University Dept. of Electronics and Automation Elaziǧ Turkey Firat University Dept. of Computer Engineering Elaziǧ Turkey

ISBN: (纸本)9798350369786

The availability of artificial intelligence applications has expanded with the development of extremely powerful computers. This speeds up the diagnosis of many ailments and allows for the application of effective treatments. This facilitates the work of numerous experts in the field of health, and more trustworthy outcomes are attained. Many researchers have started working in this topic as a result of how swiftly artificial intelligence has entered human life and the promising outcomes that have been obtained. The detection of brain strokes from CT images, which are the most prevalent in the world and a major threat to human life, is a field that is currently seeing a flurry of deep learning and machine learning-based approaches. This study attempted to distinguish between ischemic and hemorrhagic brain stroke types using CT images. Utilizing a hybrid methodology, multi-classification was carried out utilizing EfficientNetB0 and SVM model from ischemic, hemorrhagic, and normal brain CT images in our dataset. The purpose of this study is to demonstrate a higher classification performance by combining the feature extraction skills of deep learning networks with the classification capability of machine learning models. The ischemic, hemorrhagic, and normal CT images in our dataset were used to train the EfficientNet-B0 + SVM, EfficientNet-B0 + KNN, ResNet50 + SVM, ResNet50 + KNN, ResNet50, VGG19 + SVM, VGG19 + KNN, and VGG19 models. There was a triple classification. According to the study, the hybrid EfficientNet-B0 + SVM architecture had the highest load success rate. The model had 95.13%, 94.93, 95.06, and 94.94% accuracy, recall, precision, and F1 values, respectively. These findings demonstrated that the EfficientNet-B0 + SVM architecture is a highly effective method for classifying different types of brain strokes from CT images. © 2023 IEEE.

关键词： computerized tomography

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A comparison study between Modbus and IEC 61850 MMS Protocols 33

A comparison study between Modbus and IEC 61850 MMS Protocol...

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33rd Southern African Universities Power engineering Conference, SAUPEC 2025

作者： Johnson, Rayner Krishnamurthy, Senthil Mataifa, Haltor Esmail, Mohammed Cape Peninsula University of Technology Center for Substation Automation and Energy Management Systems Department of Electrical Electronic and Computer Engineering Cape Town7530 South Africa

ISBN: (纸本)9798331535162

The growing adoption of renewable energy primary plants has been seen globally. South Africa has seen a significant development in utility-scale photovoltaic (PV) farms in recent years due to the alleviated regulations stipulated in the latest Electricity Regulation Amendment Act. Connecting the PV plants to the power grid has also undergone a technical evolution by incorporating modern embedded computers known as Intelligent Electronic Devices (IEDs). The International Electrotechnical Committee (IEC) 61850 standard defines a suite of protocols used in modern power systems. This study compares the IEC 61850 Manufacturing Messaging Specification (MMS) with the well-known MODBUS protocol. The comparison is achieved by simulating a solar farm's Power Plant Controller (PPC). © 2025 IEEE.

关键词： Solar power plants

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