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IAENG International Journal of computer science 2024年第12期51卷 2074-2082页

作者： Wang, Yayun Tao, Ye Cui, Wenhua Shen, Lijia Anshan Normal University Anshan China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan China

This article designs the PELAN structure based on the lightweight YOLOv7-tiny model for surface defect detection of hot-rolled steel strips. At the same time, the CA (Channel Attention) is embedded in the feature pyramid structure and the Slim-Neck structure is introduced at the neck. Through experimental result analysis, it is proved that the lightweight algorithm not only reduces model complexity, but also has better detection accuracy and processing speed. This article focuses on exploring the potential of lightweight YOLOv7-tiny models in steel surface defect detection. With the advancement of Industry 4.0, quickly and accurately detecting surface defects on steel strips has become crucial. However, traditional defect detection methods often face issues such as large computational requirements and poor real-time performance. Therefore, we have designed a novel PELAN structure that combines CA(Channel Attention)and Slim-Neck structure. The aim is to reduce model complexity while maintaining or even improving detection accuracy and processing speed. © (2024), (International Association of Engineers). All rights reserved.

关键词： Hot rolling

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Demonstration of high-performance STO-based WORM devices controlled by oxygen-vacancies and metal filament growth

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Journal of Materials Chemistry C 2024年第23期12卷 8418-8425页

作者： Hsu, Chih-Chieh Wen, Xiu-Ming Xiao, Kai-Zer Jhang, Wun-Ciang Joodaki, Mojtaba Department of Electronic Engineering National Yunlin University of Science and Technology Douliu64002 Taiwan Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Douliu64002 Taiwan School of Computer Science and Engineering Constructor University Bremen28759 Germany

Herein, we propose high-performance Ti/STO/n+-Si and Ag/STO/n+-Si write-once-read-many-times devices, where the resistance transition mechanisms are controlled by oxygen vacancies in the STO layer and metal atoms from the electrochemically active Ag electrode, respectively. The as-deposited STO films have a low oxygen-vacancy content of 12.2%. When the Ti electrode is deposited, the formation of a thin TiOx interfacial layer at the Ti/STO interface is achieved, which leads to an increase of oxygen vacancy content in the STO layer to 28.6%. The relatively higher oxygen vacancy density means that the Ti/STO/n+-Si device can provide a voltage-polarity-independent memory function. In contrast, the resistance transition of the Ag/STO/n+-Si device can be limited in the positive voltage region because Ag cations can only be driven into the STO layer using a positive bias. Both devices show high ILRS/IHRS ratios, superior data retention capability, and fast transition speeds. © 2024 The Royal Society of Chemistry.

关键词： Oxygen vacancies

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GRU combined model based on multi-objective optimization for short-term residential load forecasting

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10423-10440页

作者： Yi, Lingzhi Peng, Xinlong Fan, Chaodong Wang, Yahui Li, Yunfan Liu, Jiangyong College of Automation and Electronic Engineering Xiangtan University Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan China School of Computer Science and Technology Hainan University Hainan China College of Electrical and Information Engineering Hunan University Changsha China

Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditional methods have been used to address the problem of residential load forecasting. A single load forecast model in the traditional method does not allow for comprehensive learning of data characteristics for residential loads, and utilizing RNNs faces the problem of long-term memory with vanishing or exploding gradients in backpropagation. Therefore, a gated GRU combined model based on multi-objective optimization is proposed to improve the short-term residential load forecasting accuracy in this paper. In order to demonstrate the effectiveness, GRUCC-MOP is first experimentally tested with the unimproved model to verify the model performance and forecasting effectiveness. Secondly the method is evaluated experimentally with other excellent forecasting methods: models such as DBN, LSTM, GRU, EMD-DBN and EMD-MODBN. By comparing simulation experiments, the proposed GRU combined model can get better results in terms of MAPE on January, April, July, and November load data, so this proposed method has better performance than other research methods in short-term residential load forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

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Tile-size aware bitrate allocation for adaptive 360∘ video streaming

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Multimedia Tools and Applications 2025年第13期84卷 12615-12632页

作者： Huang, Jiawei Liu, Mingyue Liu, Jingling Gao, Feng Li, Weihe Wang, Jianxin School of Computer Science and Engineering Central South University Hunan Changsha410083 China School of Informatics The University of Edinburgh Edinburgh United Kingdom

360∘ videos have become increasingly popular recently, but consume much more bandwidth than non-360∘ videos. Usually, 360∘ video streaming partitions the video surface into multiple tiles and encodes the tiles independently to effectively and flexibly use limited link bandwidth. However, current bitrate adaptive algorithms generally aim to maximize the bitrate, rather than perceptual quality, resulting in degradation of user experience. More importantly, we reveal that the distribution of tile size is very skewed, that is, a small number of large tiles consumes more bandwidth than a large number of small tiles, further hurting the overall viewing quality. Therefore, in this paper, we propose a tile-size aware bitrate allocation scheme TSA for adaptive 360∘ video streaming to improve the viewing experience of users. Specifically, TSA cautiously decreases the quality of a few large tiles to allocate more bandwidth to large number of small tiles, thus improving the perceptual quality of overall video, without sacrificing large tiles excessively. Experiments over real-world datasets show that TSA effectively improves V-VMAF by up to 39% compared with several state-of-the-art adaptive bitrate algorithms. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Video streaming

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COVID-19 Pandemic: A Worldwide Critical Review with the Machine Learning Model-Based Prediction

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Journal of The Institution of Engineers (India): Series B 2025年第1期106卷 339-349页

作者： Misra, Neeraj Kumar Das, Sanchali Satpathy, Sambit Addula, Santosh Reddy Trivedi, Munesh Chandra School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravathi522237 India School of Computer Science Engineering and Technology Bennett University Greater Noida India Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida India Information Technology University of the Cumberlands Williamsburg United States Computer Science and Engineering PSSCIVE Bhopal Bhopal India

Machine learning (ML) with data analysis has many successful applications and is widely employed daily. Additionally, they have played a significant role in combating the global coronavirus (COVID-19) outbreak. International occurrences of the COVID-19 pandemic have resulted from the rapid global spread of the SARS-CoV-2 virus. In this study, we examine the ML and data analysis techniques for diagnosis, treatment, and impact of COVID-19, which are based on artificial intelligence (AI). Moreover, we provide an overview of the current state of the art in AI-based machine learning and deep learning techniques as well as the datasets, tools, and performance of the tools that can be used to combat COVID-19. In this survey, we have attempted to provide a comprehensive overview of the most recent state-of-the-art approaches available to researchers in Mathematical and Statistical analysis and the larger medical community as a whole. It also includes information on how data and ML can be used to improve COVID-19 status and encourage further research to prevent COVID-19 outbreaks. Future directions and problems are also described in detail. © The Institution of Engineers (India) 2024.

关键词： COVID-19

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Controllable chaos in the coupled waveguide-optomechanical system with phase shifter

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science China(Physics,Mechanics & Astronomy) 2025年第4期68卷 26-34页

作者： Deng-Wei Zhang Pei-Qi Qin Li-Li Zheng Zhi-Ming Zhan Xin-You Lü Department of Mathematics and Physics Luoyang Institute of Science and TechnologyLuoyang 471023China School of Computer and Information Engineering School of SoftwareLuoyang Institute of Science and TechnologyLuoyang 471023China School of Artificial Intelligence Jianghan UniversityWuhan 430056China School of Physics Huazhong University of Science and TechnologyWuhan 430074China

We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the coupling strength via a unidirectional waveguide(IWG)can induce chaotic *** underlying reason for this phenomenon is that adjusting the phase and coupling strength via the phase shifter and IWG bring the system close to an exceptional point(EP),where field localization dynamically enhances the optomechanical nonlinearity,leading to the generation of chaotic *** addition,due to the sensitivity of chaos to phase in the vicinity of the EP,we propose a theoretical scheme to measure the optical phase perturbations using *** work may offer an alternative approach to chaos generation with current experimental technology and provide theoretical guidance for optical signal processing and chaotic secure communication.

关键词： cavity optomechanics chaos exceptional point

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Manganese-based oxides cathodes for potassium-ion batteries: a review

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Journal of Energy Chemistry 2025年 108卷 1-18页

作者： Yue, Qinggang Xia, Maoting Zhou, Jiang Cheng, Juanjuan Lu, Bingan School of Physics and Electronics Hunan University Hunan Changsha410082 China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Hunan Changsha410082 China School of Materials Science and Engineering and Key Laboratory of Nonferrous Metal Materials Science and Engineering Ministry of Education Central South University Hunan Changsha410083 China School of Materials Science and Engineering Hunan Provincial Key Lab of Advanced Materials for New Energy Storage and Conversion Hunan University of Science and Technology Hunan Xiangtan411201 China

Potassium-ion batteries (PIBs) were recognized for their natural abundance, high theoretical output voltage, and the availability of commercialized graphite anodes. However, the development of high-performance manganese-based layered oxide cathodes—a leading candidate for PIB systems—has been fundamentally constrained by irreversible phase transitions (PT) during the cycling process, manifesting as severe structural degradation and capacity fading. This review presents a transformative paradigm integrating machine learning (ML) with multiscale characterization to analyse the complex phase transition mechanisms in Mn-based cathodes. Through systematic ML-driven interrogation of structure–property relationships, we establish quantitative descriptors for phase stability and develop predictive models for transition dynamics. Furthermore, we highlight recent breakthroughs in cross-disciplinary approaches, enabling the rational design of PT-mitigated cathode architectures. By consolidating these insights into a unified knowledge framework, this work provides strategic guidelines for developing structurally robust Mn-based cathodes and outlines future research directions for next-generation PIB systems. © 2025 science Press and Dalian Institute of Chemical Physics, Chinese Academy of sciences.

关键词： Setting

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Mean-square exponential stability of stochastic Volterra systems in infinite dimensions

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science China(Information sciences) 2024年第10期67卷 298-314页

作者： Lin FU Shiguo PENG Feiqi DENG Quanxin ZHU School of Automation Guangdong University of Technology School of Automation Science and Engineering South China University of Technology Key Laboratory of Computing and Stochastic Mathematics(Ministry of Education) School of Mathematics and StatisticsHunan Normal University

Over the past decade, the study of stability theory in integro-differential systems has grown significantly owing to their relevance in solving physical and engineering problems, such as viscoelasticity and thermo-viscoelasticity in materials with memory properties. This paper concentrates on a class of infinite-dimensional stochastic integro-differential systems. We establish the well-posedness of the system and identify mild solutions to the system and an abstract stochastic Cauchy problem. This identification is identified by employing a semigroup approach combined with Yosida approximation. We derive sufficient conditions that ensure the mean-square exponential stability of mild solutions to the system boils down to the boundedness of a certain function and a norm estimate for the stochastic part. These conditions are implemented through the semigroup approach and the composition operator method. Illustrative examples are provided and the obtained theoretical results are validated by numerical simulations.

关键词： stochastic integro-differential equations mean-square exponential stability stochastic distributed parameter systems Hardy space composition operators

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Event-Driven Attention Network:A Cross-Modal Framework for Efficient Image-Text Retrieval in Mass Gathering Events

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computers, Materials & Continua 2025年第5期83卷 3277-3301页

作者： Kamil Yasen Heyan Jin Sijie Yang Li Zhan Xuyang Zhang Ke Qin Ye Li School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Information and Software Engineering University of Electronic Science and Technology ofChinaChengdu611731China Kashi Institute of Electronics and Information Industry Kashi844508China

Research on mass gathering events is critical for ensuring public security and maintaining social ***,most of the existing works focus on crowd behavior analysis areas such as anomaly detection and crowd counting,and there is a relative lack of research on mass gathering *** believe real-time detection and monitoring of mass gathering behaviors are essential formigrating potential security risks and ***,it is imperative to develop a method capable of accurately identifying and localizing mass gatherings before disasters occur,enabling prompt and effective *** address this problem,we propose an innovative Event-Driven Attention Network(EDAN),which achieves image-text matching in the scenario of mass gathering events with good results for the first *** image-text retrieval methods based on global alignment are difficult to capture the local details within complex scenes,limiting retrieval *** local alignment-based methods aremore effective at extracting detailed features,they frequently process raw textual features directly,which often contain ambiguities and redundant information that can diminish retrieval efficiency and degrade model *** overcome these challenges,EDAN introduces an Event-Driven AttentionModule that adaptively focuses attention on image regions or textual words relevant to the event *** calculating the semantic distance between event labels and textual content,this module effectively significantly reduces computational complexity and enhances retrieval *** validate the effectiveness of EDAN,we construct a dedicated multimodal dataset tailored for the analysis of mass gathering events,providing a reliable foundation for subsequent *** conduct comparative experiments with other methods on our dataset,the experimental results demonstrate the effectiveness of *** the image-to-text retrieval task,EDAN achieved the best performance on the R@5 metric,w

关键词： Mass gathering events image-text retrieval attention mechanism

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Large circuit models: opportunities and challenges

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science China(Information sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark Lab School of Integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of Integrated Circuits Southeast University Huawei HiSilicon Peng Cheng Laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

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