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4th International Conference on Information Science and Education, ICISE-IE 2023

作者： Zhu, Xiaoke Dong, Zhiwei Chen, Xiaopan Shi, Yufeng Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng China School of Computer and Information Engineering Henan University Kaifeng China Henan University Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China

ISBN: (纸本)9798350394610

After the outbreak of the COVID-19 pandemic, online teaching has gradually emerged as an indispensable component of education. Despite its convenience, online education lacks the immediate interactive experience inherent in traditional classrooms. This paper presents a meticulously designed DS-YOLOv8 network model, specifically tailored for real-time recognition of students raising their hands under cameras. On our proprietary dataset, this network model exhibits exceptional accuracy in hand-raising detection, showcasing a 1.3% improvement in the AP50 index compared to the baseline YOLOv8 model. Our focus lies on the application of hand-raising detection within online classrooms with an objective to provide enhanced support for teachers by promptly identifying students raising their hands and thereby improving teaching efficiency while enriching the interactive experience of students in virtual learning environments. © 2023 IEEE.

关键词： Students

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Artificial intelligence-based pathological analysis of liver cancer:Current advancements and interpretative strategies

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iLIVER 2024年第1期3卷 82-89页

作者： Guang-Yu Ding Jie-Yi Shi Xiao-Dong Wang Bo Yan Xi-Yang Liu Qiang Gao Department of Liver Surgery and Transplantation Liver Cancer InstituteZhongshan HospitalShanghai 200032China Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education Fudan UniversityShanghai 200032China School of Computer Science and Technology Xidian UniversityXi'an 710126China School of Computer Science Shanghai Key Laboratory of Intelligent Information ProcessingFudan UniversityShanghai 200433China Institute of Biomedical Sciences Fudan UniversityShanghai 200030China State Key Laboratory of Genetic Engineering Fudan UniversityShanghai 200433China

In recent years,significant advances have been achieved in liver cancer management with the development of artificial intelligence(AI).AI-based pathological analysis can extract crucial information from whole slide images to assist clinicians in all aspects from diagnosis to prognosis and molecular ***,AI techniques have a“black box”nature,which means that interpretability is of utmost importance because it is key to ensuring the reliability of the methods and building trust among clinicians for actual clinical *** this paper,we provide an overview of current technical advancements in the AI-based pathological analysis of liver cancer,and delve into the strategies used in recent studies to unravel the“black box”of AI's decision-making process.

关键词： Liver cancer Artificial intelligence Pathology Interpretative model

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Antifungal activity of curcumin-mediated photodynamic inactivation against Fusarium graminearum on maize

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Grain & Oil Science and technology 2025年第1期8卷 21-31页

作者： Shuliang Dong Lu Chen Shaojie Li Konglong Feng Guang Liu Hao Dong Guizhi Xu Huajian Ou Yang Liu Yong Zhao Jingjing Wang Guangdong Provincial Key Laboratory of Intelligent Food Manufacturing Foshan UniversityFoshan 528225China College of Food Science and Technology Shanghai Ocean UniversityShanghai 201306China Shanghai Sixth People’s Hospital Affiliated to Shanghai JiaoTong University Shanghai 201306China Sericultural&Agri-Food Research Institute Guangdong Academy of Agricultural Sciences/Key Laboratory of Functional Foods Ministry of Agriculture and Rural Affairs/Guangdong Key Laboratory of Agricultural Products ProcessingGuangzhou 510610China College of Light Industry and Food Sciences Zhongkai University of Agriculture and EngineeringGuangzhou 510225China National Technical Center(Foshan)for Quality Control of Famous and Special Agricultural Products Foshan 528225China

The natural curcumin-mediated photodynamic inactivation(PDI)was developed,and its inactivation potency against Fusarium graminearum in vitro and in vivo was systematically investigated by fluorescence probe assay,trypan blue staining,scanning electron microscope(SEM),confocal laser scanning microscopy(CLSM),*** showed that under the irradiation of blue LED,the photosensitizer of curcumin was excited to generate massive reactive oxygen species(ROS)in the cells of ***,and the PDI completely inactivated their mycelia and spores under the treatment of 150μM curcumin and 10.8 J/cm^(2)*** analysis found that the PDI ruptured the cellular microstructures,damaged the cell membrane by increasing its permeability and oxidizing the lipids,degraded the intracellular DNA and proteins inside the spores of ***,the PDI also potently killed>99.99%spores of *** on maize under the treatment of 200μM curcumin and 10.8 J/cm^(2)***,the PDI suppressed the production of zearalenone(ZEN),and residual ZEN could not be detected after the storage of maize for 10 ***,this study systematically explored the inactivation efficiency of curcumin-mediated PDI against both the mycelia and spores of ***,which provides a valid and promising method to control the fungal hazards in grains.

关键词： Fusarium graminearum Photodynamic inactivation(PDI) Spores Mycelia Zearalenone(ZEN)

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A Novel Optimization Method for Raw Coal Blending in Coal Preparation Plants Based on Interval Programming

A Novel Optimization Method for Raw Coal Blending in Coal Pr...

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2023 China Automation Congress, CAC 2023

作者： Lei, Jiahui Liu, Hanwen Zhao, Jun Wang, Wei Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China Chn Energy Wuda Coal Processing Co. Ltd. Wuhai China

ISBN: (纸本)9798350303759

In the process of coal blending and washing in coal preparation plants, there are various raw coals with different quality that changes greatly, which results in poor quality and low profit. To solve these problems, a novel optimization method for raw coal blending based on interval programming is proposed. Interval numbers are introduced to represent the fluctuation range of ash and sulfur content at each density level of raw coals. A predictive model of quantity and quality of dense medium cyclone products is constructed, which uses Hermite interpolation to obtain washability curves of each raw coal and adopts fitting methods to obtain the distribution curve. In order to obtain optimal coal blending schemes, considering operation and maintenance costs of raw coal feeding line, a mixed integer nonlinear programming (MINLP) model is built, whose objective is to maximize profit with the main constraints of clean coal quality and inventory of raw coal. Interval possibility is introduced to transform constraints with interval number and a customized branch and bound algorithm is used to solve it. In order to verify the effectiveness of the method in this paper, experiments are conducted using manufacturing data from a domestic coal preparation plant. The experimental results indicate that the proposed method is practical and has better economic performance. © 2023 IEEE.

关键词： Profitability

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User Information Enhanced Knowledge Graph Convolutional Networks for Recommender Systems 14

User Information Enhanced Knowledge Graph Convolutional Netw...

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14th International Conference on Measuring technology and Mechatronics Automation, ICMTMA 2022

作者： Hao, Junyu Li, Xiaoge School of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Xi'an71012 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Shaanxi Xi'an710121 China Xi'an Key laboratory of Big Data and Intelligent Computing Shaanxi Xi'an710121 China

ISBN: (纸本)9781665499781

To deeply excavate the information contained in user data and better alleviate cold start problem, we propose KGCN++, a user information enhanced knowledge graph convolutional networks model for recommender system, which simulates nerves' influence diffusion of information of user and items in a unified framework. The model combines user information and user-item interaction information into a user knowledge graph, which advances KGCN by injecting high-order user potential information reflected in user graph and high-order influence of items reflected in item knowledge graph. In addition, we have designed the influence factors of different items on users, which are used to characterize the weight of items on the user's information dissemination, so as to distinguish users with different information. Through extensive experiments on real-world datasets, we demonstrate that KGCN++ achieves substantial gains in a variety of ecenarios, including movie and book recommendation, better performance compared to the other methods. © 2022 IEEE

关键词： Recommender systems

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Path Planning based on Reinforcement Learning with Improved APF model for Synergistic Multi-UAVs 26

Path Planning based on Reinforcement Learning with Improved ...

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Ding, Qun Xu, Xiaolong Gui, Wenming Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing210023 China Nanjing University of Posts and Telecommunications School of Computer Science Nanjing210023 China Jinling Institute of Technology School of Computer Science Nanjing211169 China

ISBN: (纸本)9798350331684

As the emerging technology of Unmanned Aerial Vehicles (UAVs) becomes mature, UAVs are widely used in environmental monitoring, communication and other fields. In view of this, this paper analyzed the task of synergistic multi-UAVs exploration of unknown environments, and proposed a path planning method for them based on reinforcement learning. Firstly, the path planning task of the UAVs was divided into two parts: the path travel strategy module and the information exploration strategy module. Models of the two modules were based on the Deep Deterministic Policy Gradient algorithm (DDPG), and an improved Artificial Potential Field (APF) force traction mechanism was introduced in the path travel strategy module. Its aim was to assist in guiding the generation of UAV flight path trajectories. Also it could enhance the learning capability of the model. The path travel strategy module would generate the complete flight path of the whole cluster in a distributed manner. A series of temporary target points provided by the information exploration strategy module helped. In maps with 21.5%, 25.3% and 29.6% of obstacles, multi-UAVs could achieve 84.2%, 76.7% and 69.9% of environmental exploration by the designed method. Compared with the APF method, the A star method and the Breath First Search (BFS) method, the proposed method is not only able to plan feasible paths in a more complex map model, but also the curvature of the planned paths is smoother, thus achieving the goal of reducing the energy cost of UAVs. © 2023 IEEE.

关键词： Reinforcement learning

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Power equipment fault entity recognition based on BERT-CRF model 5

Power equipment fault entity recognition based on BERT-CRF m...

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5th International Conference on Artificial Intelligence and Computer Science, AICS 2023

作者： Zhang, Yanfang Zhong, Yanru Luo, Xiaonan Guangxi Key Laboratory of Intelligent Processing of Computer Images and Graphic Guilin University of Electronic Technology Guangxi Guilin541004 China National Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin University of Electronic Technology Guangxi Guilin541004 China

ISBN: (纸本)9781510668621

With the ongoing development of the national power grid, fault data from power equipment exhibits various characteristics, including a wide range of entity types, weak interrelationships, and high complexity. Consequently, traditional methods fail to extract adequate entity information and struggle with situations involving the multiple meanings of terminology in different contexts. To tackle these challenges, this paper proposes a method for recognizing power equipment fault entities based on the BERT-CRF model. The method initially employs web crawlers to retrieve literature related to power equipment faults. It then inductively designs five distinct types of power equipment fault entities and annotates a dataset accordingly. Subsequently, the BERT model is combined with the CRF model to recognize power equipment fault entities. The experimental results are then compared with those of the BiLSTM-CRF model and other domain datasets to evaluate the impact of power equipment fault entity types and label quantities. The experimental results confirm the feasibility and effectiveness of the BERT-CRF model, enabling the extraction of a wider range of power equipment fault entities from a smaller corpus of data. © 2023 SPIE.

关键词： Web crawler

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Leveraging Timbre Semantic Descriptors for Cross-Dataset Instrument Recognition

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language processing 2025年 33卷 1196-1207页

作者： Shenyang Xu Yuan Wang Zijin Li Feng Yu Wei Li Department of Music AI and Information Technology Central Conservatory of Music Beijing China School of Computer Science and Technology Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China

Timbre, a perceptual attribute of musical sound, plays a critical role in both instrument recognition and timbre perception research. However, these fields are rarely integrated, and as a result, their findings rarely benefit one another. This study investigates how integrating timbre semantic descriptors as an auxiliary task can enhance musical instrument recognition under challenging cross-dataset conditions via multi-task learning (MTL). A standard flat MTL framework is introduced, alongside an asymmetric MTL proposed to amplify the influence of timbre semantic descriptors on instrument recognition. Experiments are conducted on Western and Chinese instrument datasets to evaluate cross-cultural performance. The results demonstrate significant improvements on both datasets using the flat MTL, with further analysis revealing the varying contributions of individual timbre descriptors and demonstrating its robustness across different hyperparameter settings. The asymmetric MTL achieves additional performance gains on Western datasets but not on Chinese ones. A dedicated analysis is carried out to investigate this discrepancy, offering insights into potential dataset-specific or cultural challenges.

关键词： Instruments Timbre Semantics Vectors Training Accuracy Testing Multitasking Standards Speech processing

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Information Express of Soft Bionic Finger Based on Visual Recognition

Information Express of Soft Bionic Finger Based on Visual Re...

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IEEE International Conference on Cyborg and Bionic Systems (CBS)

作者： Sai Li Jiarun Wang Xinpeng Li Zixin Huang School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan China Ministry of Education Key Laboratory of Textile Fiber and Products (Wuhan Textile University) Wuhan China State Key Laboratory of New Textile Materials and Advanced Processing Technologies (Wuhan Textile University) Wuhan China

Soft robots have developed rapidly because of their own structure, adaptability and safety, which can be applied in different fields. However, the human robot interaction of soft robots faces enormous challenges. In this paper, we take the soft bionic finger (SBF) as the research object, design a multi chamber SBF, and propose a visual recognition to drive SBF. The bending information of the finger is converted into the information of driving air pressure, and drive the SBF. The SBF can simulate the bending of human finger and replace human finger to express some information. Finally, in the visual bending experiment, it is verified that the error between the bending angle of the human finger and the bending angle of the SBF is within a certain allowable range. It shows the feasibility of driving SBF to express information based on visual recognition, and also reflects strong human robot interaction.

关键词： Deformable models Visualization Computational modeling Fingers Human-robot interaction Bending Soft robotics

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An End-to-End Autoencoder-based Probabilistic Shaping Method for Optical Communication 7

An End-to-End Autoencoder-based Probabilistic Shaping Method...

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7th Optics Young Scientist Summit, OYSS 2024

作者： Teng, Ziqiang Guo, Dong Gao, Ran Kong, Leyi Han, Wentao Chang, Huan Li, Zhipei Xin, Xiangjun School of Information and Electronics Beijing Institute of Technology 5 Zhongguancun South Street Haidian District Beijing100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology 5 Zhongguancun South Street Haidian District Beijing100081 China Institute of Science and Technology Research Beijing Institute of Technology 5 Zhongguancun South Street Haidian District Beijing100081 China

ISBN: (数字)9781510688377

ISBN: (纸本)9781510688360

The advent of services such as big data and cloud computing has driven a continuous increase in the required transmission rate and capacity of optical fiber communication systems, which now support over 90% of global data traffic. Probability shaping (PS), which adjusts the probability distribution of constellation points, enhances both data transmission rates and the resilience of signals to channel nonlinearity. However, traditional PS methods, such as those using constant composition distribution matching (CCDM), cannot dynamically adjust the probability distribution of constellation points based on channel conditions. To address this limitation, we propose an end-to-end Autoencoder (AE)-based PS technique for optical communication. Simulation results show that compared to traditional 16/64/256QAM, this scheme achieves a maximum improvement of 0.356 bit/symbol in mutual information over the AWGN channel. In the optical fiber channel, under varying signal power and fiber length conditions, the mutual information is improved in different degrees and the influence of channel nonlinearity on the signal is reduced. Innovatively, residual connections are added to the decoder to enhance the model's generalization performance, enabling a deeper network structure and improving its ability to handle complex optical fiber channels. © 2025 SPIE.

关键词： Optical fiber communication

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