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检索条件"机构=Key Laboratory of Intelligent Control Technology for Wuling-Mountain"

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Personalized Learning Path Recommendation Driven by Multi-Modal Knowledge Graphs and Large Models Collaboration

Personalized Learning Path Recommendation Driven by Multi-Mo...

引用

Information technology, Communication Ecosystem and Management (ITCEM), International Conference on

作者： Changhua Zhao Yimei Yang Yujun Yang Bo Tang Chunqiao Mi College of Computer and Artificial Intelligence(Software College) Huaihua University Huaihua China Hunan Provincial Key Laboratory of Ecological Agriculture Intelligent Control Technology Huaihua China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua Hunan China

ISBN: (数字)9798331542696

ISBN: (纸本)9798331542702

This study examines ways to create personalized learning pathways that are influenced by large collaborative models and multi-modal knowledge graphs. By integrating multi-modal data to construct a comprehensive knowledge network, this study utilizes the generative and comprehension capabilities of large models to achieve personalized customization of learning resources. The focus of the research is on accurately depicting learner characteristics through multi-modal profiling techniques, ensuring the transparency and credibility of the content generated by large models. The personalized learning route suggestion model proposed in this paper includes two parts: recommendations for learning paths within courses and recommendations for learning paths within learning tasks, aiming to enhance learning efficiency and outcomes through the collaborative effects of multi-modal knowledge graphs and large models. Experimental results indicate that the learning path recommendation model driven by multi-modal knowledge graphs and large collaborative models performs excellently in improving learning outcomes and recommendation performance.

关键词： Knowledge engineering Analytical models Accuracy Biological system modeling Education Ecosystems Collaboration Knowledge graphs Data models Information technology

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Research on Automatic Identification Algorithm of Corn Diseases and Pests Based on Residual Network 23

Research on Automatic Identification Algorithm of Corn Disea...

引用

Proceedings of the 3rd International Conference on Electronic Information technology and Smart Agriculture

作者： Lingfang Zhou Weiwei Xiang Shasha Wen Caiyun Shi Leiping Chen Shunru Zhang School of physics Electronics and Intelligent Manufacturing Huaihua University China and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China School of physics Electronics and Intelligent Manufacturing Huaihua University China School of physics Electronics and Intelligent Manufacturing Huaihua University China and Huaihua Key Laboratory of Agricultural Ecology Prevention and control Huaihua University China

ISBN: (纸本)9798400716775

This study focuses on the development needs of smart ecological agriculture and proposes an improved network model based on ResNet50. The research aims to improve the accuracy and efficiency of automatic identification of corn pests and diseases. Firstly, the collected leaf data of corn pests and diseases were enhanced. The purpose of doing so is to expand the amount of data and achieve a balance between various types of data. Secondly, the size of the network convolution kernel was adjusted. And introduce SE attention mechanism to the backend of the network to optimize the effect of network detail feature extraction. Finally, through experimental verification, the results show that the network model has high accuracy and robustness in identifying corn pests and diseases, and can effectively improve the efficiency of corn pest control.

关键词： Deep learning Pest identification ResNet50 Residual network

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An Approach for Constructing Concept Tree of Web Content Based on FCA and Thesaurus 1

An Approach for Constructing Concept Tree of Web Content Bas...

引用

1st International Conference on Electronic Information technology and Smart Agriculture, ICEITSA 2021

作者： He, Wei Li, Shuang Huaihua University Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture Hunan Huaihua China College of Music and Dancing Huaihua University Hunan Huaihua China

ISBN: (纸本)9781665413008

In this paper, we propose an approach for constructing concept tree of web content based on FCA and thesaurus, which aims to solve the problem of evaluating web content. Firstly, each paragraph of web content is extracted, and the characteristic phrases of the paragraph are obtained, which is used to generate formal context;Secondly, we exploit FCA to build the concept lattice according to the formal context;finally, thesaurus is used on the process of pruning and renaming the concept of concept lattice to gain the concept tree of web content. Experiment results show that the concept tree constructed by our proposed method in this paper has strong competitiveness in reconstructing web content and rationality judgment of classification of web page. © 2021 IEEE.

关键词： Thesauri

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Design of a Crop Disease and Pest Identification System Based on Deep Learning 23

Design of a Crop Disease and Pest Identification System Base...

引用

Proceedings of the 3rd International Conference on Electronic Information technology and Smart Agriculture

作者： Chengling Zhou Lingfang Zhou Siyi Liu Wen Deng Jing Xiao Shiyang Hang Shunru Zhang School of physics Electronics and Intelligent Manufacturing Huaihua University China School of physics Electronics and Intelligent Manufacturing Huaihua University China and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China School of physics Electronics and Intelligent Manufacturing Huaihua University China and Huaihua Key Laboratory of Agricultural Ecology Prevention and control Huaihua University China

ISBN: (纸本)9798400716775

Traditional conventional methods for identifying pests and diseases often rely depended on manual experience, making it difficult to ensure accuracy and low efficiency. Deep learning technology Learning technology deeply can automatically extract useful features from a large amount of image data, classify and recognize them, and improve enhance accuracy and efficiency This approach can help assist farmers detect pests and diseases in a timely manner, thus taking timely prevention and control measures to reduce the spread and loss of pests and diseases taking immediate steps to minimize its diffusion and loss as much as possible. This article in this paper, designs a deep learning based crop pest identification system designing a crop pest and disease recognition system which is based on deep learning, aiming to improve the accuracy and efficiency of crop pest identification. The system uses utilizes three classic convolutional neural networks (CNNs) as training models to achieve recognition of various common crop pest pests and disease types. After system testing and analysis, the results show demonstrate that the system has significant advantages in accuracy, real-time performance, and can meet fulfil practical application requirements. Future research directions Future studies can further optimize models, expand datasets, reduce false fake positives, and provide more accurate and efficient pest identification support for agricultural production.

关键词： Convolutional neural network Deep learning Identification of pests and diseases

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An Effective and Real-time Time-Slot Power Detection Method 23

An Effective and Real-time Time-Slot Power Detection Method

引用

Proceedings of the 3rd International Conference on Electronic Information technology and Smart Agriculture

作者： Xian Zhang Xinhui Luo Taiguo Qu Dong Yin School of Computer and Artificial Intelligence (School of Software) Huaihua University China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China and Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China Department of Art Design Huaihua Tourism School China School of Computer and Artificial Intelligence (School of Software) Huaihua University China

ISBN: (纸本)9798400716775

To efficiently detect the time-slot power of the Time Division Multiple Access (TDMA) communication systems such as repeaters and base stations in real-time. This article designs a signal-sampling hardware circuit based on the Advanced RISC Machine (ARM) platform and proposes a comprehensive method to calculate the time-slot power values. The signal sampling circuit uses the ADC108S052 chip with an 8-channel linked to the ARM via the Serial Peripheral Interface (SPI), and the time-slot power detection approach consists of a signal timing sampling module, sampling data reading module, and sampling data processing module to compute the detected time-slot power comprehensively. We design experiments to evaluate the efficacy of the approach to detect the time-slot power with the system power-on and normality running condition, the detection of the system CPU resource consumption for the time-slot power, the detection of the error value for the time-slot power, etc. The experimental results demonstrate that the approach can be efficient, and real-time detection of the time-slot power of the TDMA system, the system of repeaters and base stations and other systems of signal coverage, optimization and so on is of great significance.

关键词： ARM Analog-to-Digital Converter (ADC) Signal sampling Time division multiple access Time slot power

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A Self-Adaptive Trust Region Method to Solve the Tensor Eigenvalue Complementarity Problems 23

A Self-Adaptive Trust Region Method to Solve the Tensor Eige...

引用

Proceedings of the 3rd International Conference on Electronic Information technology and Smart Agriculture

作者： Ping Wang Jianguo Liu Yong Zhang Yueming Xiang School of Mathematics and Computational Science Huaihua University China School of Mathematics and Computational Science Huaihua University China and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua Huaihua University China

ISBN: (纸本)9798400716775

In this paper, according to utilizing a self-adaptive technique, we present a self-adaptive trust region method for effectively solving tensor eigenvalue complementarity problems of various structures. Our proposed method demonstrates global convergence under suitable conditions. The numerical examples conducted in this study highlight the superior efficiency of our approach in comparison to the inexact Levenberg-Marquardt method and modified spectral PRP conjugate gradient method for computing tensor eigenvalue complementarity problems.

关键词： Generalized tensor eigenvalue complementarity problem Global convergence Self-adaptive technique Trust region

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intelligent Mobile Power Sharing and Rental System Based on BeiDou Navigation 2

Intelligent Mobile Power Sharing and Rental System Based on ...

引用

2nd International Conference on Electronic Information technology and Smart Agriculture, ICEITSA 2022

作者： Hu, Hui Li, Xinhu Wu, Jiaxin Zeng, Qingli Zhang, Renmin College of Communication and Electronic Engineering Jishou University Hunan Jishou416000 China Hunan Provincial Key Lab. of Intelligent Control Technology for Ecological Agriculture in Wuling Mountain Area Huaihua University Hunan Huaihua418000 China

ISBN: (纸本)9781665464017

Aiming at the problems that the mobile power supply in the market cannot output AC voltage and manually adjustable DC voltage at the same time, expensive and cannot be accurately located, an intelligent mobile power sharing and rental system based on BeiDou navigation is designed. The device mainly consists of three major parts: power circuit module, controller module and mobile APP, which solves a series of problems such as location finding, rental use, visual power management and positioning return of shared power by users. The power circuit module converts the battery voltage into 220V AC output and adjustable DC precision output. The controller module realizes the functions of power supply DC output voltage collection, Battery power Detection, Beidou positioning and data uploading to the server. The mobile APP realizes the functions such as displaying the location, voltage, power and other data of multiple power supply units and sharing the rental under the shared rental mode by the APP. The system realized in this paper can greatly promote the development of China's shared energy storage industry and effectively change the current dilemma that people have difficulties in using electricity outdoors. © 2022 IEEE.

关键词： Digital storage

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Research on A New Connection Mode of 10kV Medium Voltage Cable Intermediate Joint 8

Research on A New Connection Mode of 10kV Medium Voltage Cab...

引用

8th International Conference on Energy Materials and Electrical Engineering, ICEMEE 2022

作者： Liu, Bohan He, DaJiang Chen, Lingxi Shu, You Cai, Yaoxing Duan, Tao School of Physics Electronics and Intelligent Manufacturing Huaihua University Hunan Huaihua418000 China Huaihua University Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China Academy of Fine Arts &art Instute Huaihua University Hunan Huaihua418000 China Preparation Technology of Polyvinyl Alcohol Fiber Materials Hunan Engineering Laboratory Hunan Huaihua418000 China State Grid Huaihua Power Supply Company Hunan Huaihua418000 China

ISBN: (纸本)9781510663220

Due to the on-site production of the middle joint of the cable, there are problems of loose contact, obvious heat generation and easy failure at the joint. In order to ensure the safe and stable operation of power cables and reduce the harm caused by the accidents of power cable intermediate joint to the power grid, this paper studies a preliminary design scheme of plug-in intermediate joint in view of the fact that there are many accessories of traditional power cable intermediate joint, the operation is cumbersome, and there are certain requirements for the technical level of installers. This scheme is easy to operate and requires less on-site process for operators. In this paper, a new connection mode of 10kV medium voltage cable intermediate joint is designed. The intermediate joint device is pre-made. the handle of the device is pulled open, the cable is inserted, and the connection is totally competed by closing the handle, which speeds up the recovery speed, improves the work efficiency, ensures the safe and stable operation of power cables, reduces the power system faults caused by the connection faults of intermediate cables, and provides a reliable guarantee for the safe operation of medium and low voltage distribution networks in China. © 2023 SPIE.

关键词： Electric power distribution

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Research on Fast Adaptive Transmission Models for International Inland Port Based on Edge Intelligence

Research on Fast Adaptive Transmission Models for Internatio...

引用

IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)

作者： Liu Yiwen Zhu Zhirong Tangyan Wen Wenkan Peng Xiaoning Shi Yuanquan School of Computer and Artificial Intelligence Huaihua University Huaihua Hunan P. R. China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing Application in Hunan Province Universities Huaihua Hunan P. R. China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua Hunan P. R. China

In this paper, we propose a logistics International Inland Port resource allocation method based on intelligent edge scheduling, and we do a reasonable pre-allocation of logistics resources by building an edge network in the urban system. By using multiple integrated learning models and regional prevalence classification algorithms, the distribution demand of each sub-distribution point is predicted. The proposed method is able to cope with uncertainties such as high distribution volume, variable distribution situations or long transportation distances. We use the HuaiHua International Inland Port as the simulation object, and the simulation results show that the proposed method has the highest efficiency in logistics distribution and is still highly adaptive in emergency situations.

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Real-Time Student Classroom Action Recognition: Based on Improved YOLOv8n 23

Real-Time Student Classroom Action Recognition: Based on Imp...

引用

Proceedings of the 3rd International Conference on Electronic Information technology and Smart Agriculture

作者： Weiwei Xiang Haoyu Lei Liming Ding Lingfang Zhou School of Computer and Artificial Intelligence(School of Software) Huaihua University China and Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua University China School of Computer and Artificial Intelligence(School of Software) Huaihua University China

ISBN: (纸本)9798400716775

Real-time student classroom action recognition allows the creation of a closed-loop teaching system and efficient teaching methods. To address the issue of a lack of open dataset in the SCAR re- search field, we proposed a challenging dataset SCAR-dataset with a total of 7194 samples, which was collected in college classrooms and after exploratory experiments. The dataset were defined into six categories: focused, head_drop, bored_distraction, looking_around, sleeping, and stand_up. We benchmarked the SCAR dataset for real-time deployment using YOLOv5, YOLOv7, and YOLOv8 algorithms, which served as the foundation for subsequent classroom concentration analysis research. By combining depth-separable convolution, a lightweight asymmetric detector head LADH was proposed. Experiments show that improving the Yolov8n model increases the map value by 2.5 points while don't in- creasing the number of parameters and Gflops.

关键词： LADH Student Classroom Action Recognition Yolov8

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