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Computing, Robotics and System Sciences (ICRSS), International Conference on

作者： Mixuan Deng Pengju Tang Yanxia Gao Huixuan Li Guodong Zhen Kaifeng Fu Xiaotian Wu College of Computer and Artificial Intelligence(Software College) Huaihua University Huaihua China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua China

ISBN: (数字)9798331511296

ISBN: (纸本)9798331511302

As a unique local dialect, Waxiang dialect carries rich regional culture and historical information. However, with the acceleration of modernization and the increase of population mobility, the inheritance and protection of Waxiang dialect are facing severe challenges. By constructing the ‘Xuewatong’ APP- Waxiang dialect digital protection platform, based on cloud storage technology, digital resource display, multimedia integration and other technologies, and providing learning resources through big data analysis of user needs, it can effectively promote the digital recording and preservation of Waxiang dialect language resources, and significantly improve the dissemination and educational effect of Waxiang dialect culture, showing the great potential of digital technology in dialect protection.

关键词： Technological innovation Cloud computing Transfer learning Media Information age Digital recording Global communication Cultural differences Protection Robots

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A Method of Realizing External Network Access to Intranet for Embedded Web Server 2

A Method of Realizing External Network Access to Intranet fo...

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

作者： Zhang, Xian Qu, Taiguo Tang, Pengju Liu, Yiwen Key Lab. of Intelligent Contr. Technol. for Wuling Mountain Ecological Agriculture in Hunan Province Huaihua China Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Key Laboratory of Wuling Huaihua China College of Computer Science and Electronic Engineering Hunan University ChangSha China School of Computer Science and Engineering Huaihua University Huaihua China

ISBN: (纸本)9781665464017

Based on the application requirements of the embedded Web server for external network access to the internal network, this paper designs and builds an embedded Web server scheme for external network access to the internal network based on the embedded Boa server and phddns program. This solution mainly transplants the Boa server and phddns program in embedded devices. Boa provides a Web server application function, and phddns software realizes the mapping and binding mapping between the IP address and the domain name of embedded devices in the intranet. An experiment is designed to test this scheme's connection success rate, response time, stable running time, domain name mapping success rate, CPU utilization and other performance indicators. The test results show that this scheme can better meet the system requirements of external network access to the internal network. Therefore, this scheme can support the information and intelligent monitoring and control of embedded devices and has good practical value and application prospects. © 2022 IEEE.

关键词： Intranets

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Prediction of chilling damage risk in maize growth period based on probabilistic neural network approach

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International Journal of Agricultural and Biological Engineering 2021年第2期14卷 120-125页

作者： Chunqiao Mi Changhua Zhao Qingyou Deng Xiaowu Deng School of Computer Science and Engineering Huaihua UniversityHuaihua 418000HunanChina Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture Huaihua 418000HunanChina Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua 418000HunanChina Human Resource Department Huaihua UniversityHuaihua 418000HunanChina

Low temperature chilling damage is one of the most serious disasters in maize production,which is a typical non-linear complex issue with numerous influencing factors and strong *** to predict it is not only a hot theoretical research topic,but also an urgent practical problem to be ***,most of the current researches are focusing on post-disaster static descriptive assessment rather than pre-disaster dynamic predictive analysis,resulting in the problems such as no indicative result and low *** this study,the satisfaction rate of environmental accumulated temperature for maize production was used to measure the chilling damage risk,and a model for maize chilling damage risk prediction based on probabilistic neural network was *** model was composed of input layer,pattern layer,summation layer and output *** obtained results showed that the prediction accuracy for the most serious risk level was as high as 0.91,and the rates of the Type I Error and Type II Error made by the model were 0.1 and 0.09,*** indicated that the model employed was promising with good *** results of this research are of both theoretical significance for providing a new reference method of pre-disaster prediction to study maize chilling disaster risk and practical significance for reducing maize production risk and ensuring yield safety.

关键词： maize chilling damage risk prediction probabilistic neural network

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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...

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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 Crop Disease and Pest Surveillance based on big data and Image processing Technologies

Research on Crop Disease and Pest Surveillance based on Big ...

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

作者： Yimei Yang Yujun Yang Huixia Shu Changhua Zhao Shaowei Deng 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

Recently, with the increasing complexity of agricultural systems and climate change, agricultural pest and disease surveillance and early detection have become critical tasks for guaranteeing food stability and promoting sustainable farming growth. Agricultural pest and disease surveillance is a key component of agricultural production, directly affecting crop yield and quality. As big data advances and image processing technologies rapidly, their application in crop pest and disease surveillance has become increasingly widespread. By integrating multi-source data, such as remote sensing data, meteorological data, ecological data, and pest and disease survey data, researchers can build more accurate and efficient pest and disease surveillance models. This paper reviews the research progress of big data and image processing technologies in crop pest and disease surveillance, analyzes the advantages and challenges of current technologies, and proposes future research directions to enhance the automation and intelligence of systems. Additionally, it discusses the integration of deep learning and other techniques to achieve efficient information mining and accurate retrieval of disaster-related data, aiming to provide scientific guidance and technical support for agricultural production.

关键词： Crops Plant diseases Climate change Pest control Agriculture big data Surveillance Image processing

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A Study on Highly Accurate Swearing Detection Model Based on Multimodal data 23

A Study on Highly Accurate Swearing Detection Model Based on...

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

作者： Jianjie Deng Yiwen Liu Ling Peng Pengju Tang Youmin Lu School of Computer and Artificial Intelligence Huaihua University China School of Computer and Artificial Intelligence Huaihua University China and Key Laboratory of Wuling Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China

ISBN: (纸本)9798400716775

The current surge in popularity of social platforms like Twitter, Weibo International, TikTok, and online games has greatly increased users' online information interaction. However, it has also brought about the issue of online profanity speech abuse. Profanity speech, i.e., insulting or offensive remarks about individuals or groups, negatively affects the public environment and user experience, making the development of profanity detection techniques particularly important. In this study, CNN and LSTM are used to extract the sentiment features in the sentence and the dirty word features in the sentence using I-gram, cross-screening, respectively Subsequently, the raw scores of these two features are mapped to the range of probability distribution of [0, 1] by SoftMax function. Then, the probability distributions of these two features are combined together, and a value can be obtained by weighted average or crosstabulation operation, according to which the sentence can be judged whether it contains swear words or not. At the end of the article, the model is compared with other models, which fully demonstrates the advantages of this model.

关键词： CNN Deep learning LSTM Swearing detection Word2vec

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Research on Indifference Management of Differentiated Computer Room

Research on Indifference Management of Differentiated Comput...

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

作者： Pengju Tang Yanxia Gao Yujun Yang Meixiu Tang College of Computer and Artificial Intelligence (Software College) Huaihua University Huaihua China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua China Huaihua University Library Huaihua University Huaihua China

ISBN: (数字)9798331542696

ISBN: (纸本)9798331542702

University computer rooms generally prefer batch purchasing strategy to simplify the management process such as system deployment and software update. However, with the growth of the life of the equipment, the failure of electronic products is inevitable, especially once the motherboard problem occurs, it is often difficult to find a replacement that exactly matches the original motherboard. Even if the replacement is found, its price is far beyond the market average level. After several years of operation, even the motherboard purchased in the same batch may also lead to the coexistence of a variety of models due to various reasons. In this situation, it becomes impractical to carry out unified network cloning. To solve this problem, we propose an innovative solution: deploying a local backup system combined with a server-controlled startup mode. The core of this solution is that through the local backup system, we can effectively deal with the challenge of different motherboard models, and ensure that each machine can have its own system snapshot. At the same time, the server-controlled boot mode further enhances the flexibility and efficiency of management, so that even in the hardware diversity of the environment, it can also achieve batch system recovery. The introduction of local backup system not only solves the problem of differentiated computer room management, but also significantly improves the convenience and stability of computer room operation and maintenance.

关键词： Biological system modeling Ecosystems Cloning System recovery Stability analysis Software Hardware Maintenance Information technology Consumer electronics

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Study on the Modification of Fingerprint Lock Based on Remote Switching 23

Study on the Modification of Fingerprint Lock Based on Remot...

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

作者： Pengju Tang Yanxia Gao Meixiu Tang Dong Wang School of Computer and Artificial Intelligence Huaihua University China School of Computer and Artificial Intelligence Huaihua University China and Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China Huaihua University Library Huaihua University China

ISBN: (纸本)9798400716775

The old fingerprint locks need to be operated on site, and there are great limitations; with the development of technology, various fingerprint locks with remote door opening have appeared, and if all of them are replaced, the cost is high, which will result in a certain amount of waste, so it is worthwhile to study the modification of the existing fingerprint locks to add the function of opening the door remotely. This paper proposes a method to increase the function of remote door opening by simple modification, which can well solve the above problems.

关键词： Control Fingerprint Lock Relay Remote

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A Study on application of Artificial Intelligence in College English Teaching Management and Evaluation 23

A Study on Application of Artificial Intelligence in College...

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

作者： Tao Feng Jianjie Deng Yiwen Liu Yanxia Gao Ling Peng Jinrong Fu School of Foreign Languages Huaihua University China School of Computer and Artificial Intelligence Huaihua University China School of Computer and Artificial Intelligence Huaihua University China and Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua University China

ISBN: (纸本)9798400716775

With the rapid development of artificial intelligence, AI technology has been widely applied in various industries, including education. In English teaching, AI technology provides teachers with objective and instructive feedback, offers students a more personalized learning experience, helping them improve their English language skills, etc., and brings new development opportunities and challenges to English teaching as well. However, there are still some problems that need to be solved in college English teaching in our university. For this reason, based on the application of AI technology in college English teaching, this paper mainly explores the impact and application countermeasures of AI on college English teaching from the following four aspects: individuals with differences, teaching management, classroom teaching and teaching evaluation. In addition, the profound integration of college English education and AI will foster the advancement and transformation of college English instruction, ultimately serving as a catalyst for its reform.

关键词： Artificial Intelligence College English Teaching Teaching Evaluation

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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...

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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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