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Propelling Pedagogical Paradigms: A Study of Advanced Human-Computer Interaction Learning in data Structure and Algorithms Based on Virtual Reality Technology 18th

Propelling Pedagogical Paradigms: A Study of Advanced Human-...

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18th International Conference on Computer Science and Education, ICCSE 2023

作者： Yahui, Yang Yanxia, Gao Ling, Peng Yingxi, Xiang Huan, He Yiwen, Liu School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China School of Fine Arts and Design Huaihua University Hunan Huaihua418000 China

ISBN: (纸本)9789819707362

data Structure and Algorithms (DSA) is a course with strong practice and abstract theoretical knowledge. In view of the complexity of the knowledge points of the course and the difficulty of understanding, we design and implement a virtual simulation experiment teaching system of the course--Virtual simulation experiment platform. In this platform, DSA through simulation practice into animation effects, and combined with the unity engine and C# code to achieve user interaction, to provide users with a way to intuitively understand the principles of DSA, while increasing the user’s subjective initiative to learn, and to achieve the high level, Innovative and challenging teaching classroom, so that students in colleges and universities can feel relaxed and happy in the process of learning this course. What is more, they can better accept and understand DSA. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： data structures

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Automatic Fault Diagnosis of Smart Water Meter Based on BP Neural Network

Automatic Fault Diagnosis of Smart Water Meter Based on BP N...

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2020国际计算机前沿大会

作者： Jing Lin Chunqiao Mi School of Computer Science and Engineering Huaihua University 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

The smart water meter in water supply network can directly affect water production and usage when faults occur. The traditional method of fault detection is inefficient with time lagging, which is not helpful for modernization of water supply system. The capability of automatic fault diagnosis of smart water meter is an important means to improve the service quality of water supply. In this paper, an automatic fault diagnosis method for the smart device is proposed based on BP neural network. And it was applied on Google Tensorflow platform. Fault symptom vectors were constructed using water meter status data and were used to train the neural network model. In order to improve the learning convergence speed and fault classification effect of the network, a method of weighted symptom was also employed. Experimental results show that it has good performance with a general fault diagnosis accuracy of 98.82%.

关键词： Automaticfaultdiagnosis Smartwatermeter BPneuralnetwork Tensorflow

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Fault Localization of Statement Coverage Based on DNN

Fault Localization of Statement Coverage Based on DNN

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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Ling Peng Chunqiao Mi School of Computer Science and Engineering Huaihua University Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application Hunan Province Universities Huaihua China

ISBN: (纸本)9781665413015

In view of the inconvenience of parameter setting in the existing fault location method based on deep neural network, this paper combines the global random search ability of Genetic Algorithm, L2 regularization to prevent model overfitting and deep neural network to learn complex nonlinear ability, a fault location algorithm based on G-DNN is proposed. The optimal number of hidden layer neurons, learning rate, training period and L2 regularization coefficient of deep neural network are obtained by Genetic Algorithm; Input the statement coverage information and state values into the deep neural network to calculate the suspiciousness value of each executable statement; Locate defects from high to low according to the suspiciousness values. The Siemens Suite is used as the experimental sample, and the G-DNN is compared with the five defect location algorithms. The results show that the defect of the G-DNN can locate defects more accurately, and the positioning efficiency is improved.

关键词： Deep learning Training Location awareness Neurons Fault location Information technology Biological neural networks

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A Study on application of Artificial Intelligence in College English Teaching Management and Evaluation 3

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

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3rd International Conference on Electronic InformationTechnology and Smart Agriculture, ICEITSA 2023

作者： Feng, Tao Deng, Jianjie Liu, Yiwen Gao, Yanxia Peng, Ling Fu, Jinrong School of Foreign Languages Huaihua University Hunan Huaihua418000 China School of Computer and Artificial Intelligence Huaihua University Hunan Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China School of Computing Science University of Glasgow GlasgowG12 8QQ United Kingdom

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. © 2023 ACM.

关键词： Artificial intelligence

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Human-AI Collaboration: A Study on Anti-ChatGPT Strategies Employed in Innovative Practical Homework Towards "One-Click-Answer" Issue in AIGC 18th

Human-AI Collaboration: A Study on Anti-ChatGPT Strategies E...

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18th International Conference on Computer Science and Education, ICCSE 2023

作者： Yiwen, Liu Yahui, Yang Jinrong, Fu Tao, Feng Ting, Yin Yingxi, Xiang Yanxia, Gao Taiguo, Qu Xian, Zhang School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China School of Foreign Languages Huaihua University Huaihua418000 China Furong School of Xinhong Dong Autonomous County Huaihua418000 China School of Fine Arts and Design Huaihua University Huaihua418000 China

ISBN: (纸本)9789819707362

ChatGPT as a representative of Artificial Intelligence in Generative Computing (AIGC) has had an impact on higher education. It promotes "human-computer collaboration" in coursework, showing both positive and negative effects. ChatGPT has the potential to provide students with personalized learning support. However, students may become too reliant on these tools and lack independent thinking. Aiming at the above problems, this paper introduces the idea of practical homework resource construction, and provides a series of anti-ChatGPT strategies, which can prevent students ChatGPT’s "one-click answer" from the source. By comparing activities such as teaching effectiveness, questionnaires, and talkback interviews conducted in the pilot course, the data illustrate the effectiveness of the methodology. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

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Research on Waxiang Dialect Recognition Based on Wav2vec2.0 Pre-Training and Transfer Learning

Research on Waxiang Dialect Recognition Based on Wav2vec2.0 ...

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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 Multi-Step Speed Prediction Method for Traffic Networks Based on MAF-GCN-Seq2Seq Model

A Multi-Step Speed Prediction Method for Traffic Networks Ba...

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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Yi Long Hongbo Xiao Jianhua Xiao Xiaoning Peng School of Computer Science and Engineering Huaihua University 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 Hunan P. R. China

ISBN: (纸本)9781665464024

Accurately predicting the future trend of traffic flow is of great significance to the planning of urban traffic. The great challenge of predicting traffic flow stems from the complexity and uncertainty of traffic flow. To address the complexity of traffic flow, this paper proposes a MAF-GCN $\text{Seq}2$ Seq model. The model uses a moving average filter to filter the time series data, extracts the spatial features between each node through a graph convolutional neural network, and forms a time series matrix for input into the encoder (GRU), and introduces a self-attention mechanism to mine the spatial features. time-domain features for multi-step traffic speed prediction. In order to verify the advanced nature of the model, this paper uses the traffic flow data set in Shenzhen to predict the traffic flow. Through the comparison experiments, it can be seen that the prediction accuracy of the MAF-GCN $\text{Seq}2$ Seq model reaches 90%, which has obvious advantages compared with other models.

关键词： Training Uncertainty Time series analysis Predictive models Feature extraction data models Spatial databases

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Design and Implementation of Log data Analysis Management System Based on Hadoop

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Journal of Information Hiding and Privacy Protection 2020年第2期2卷 59-65页

作者： Dunhong Yao Yu Chen School of Computer Science and Engineering Huaihua UniversityHuaihua418000China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000China School of Computer Science and Engineering Yulin Normal UniversityYulin537000China

With the rapid development of the Internet,many enterprises have launched their network *** users browse,search,and click the products of these platforms,most platforms will keep records of these network behaviors,these records are often heterogeneous,and it is called log *** effectively to analyze and manage these heterogeneous log data,so that enterprises can grasp the behavior characteristics of their platform users in time,to realize targeted recommendation of users,increase the sales volume of enterprises’products,and accelerate the development of ***,we follow the process of big data collection,storage,analysis,and visualization to design the system,then,we adopt HDFS storage technology,Yarn resource management technology,and gink load balancing technology to build a Hadoop cluster to process the log data,and adopt MapReduce processing technology and data warehouse hive technology analyze the log data to obtain the ***,the obtained results are displayed visually,and a log data analysis system is successfully *** has been proved by practice that the system effectively realizes the collection,analysis and visualization of log data,and can accurately realize the recommendation of products by *** system is stable and effective.

关键词： Log data Hadoop data analysis data visualization

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Specific Design and Implementation of the Characteristic Species database in wuling mountain Area

Specific Design and Implementation of the Characteristic Spe...

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

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

ISBN: (数字)9798331542696

ISBN: (纸本)9798331542702

This article aims to design and implement a database system for characteristic species in the wuling mountain area. The system will collect, organize, store, and analyze information on characteristic species in the wuling mountain area, providing data support for ecological research, biodiversity conservation, agricultural production, and other fields. This article will provide a detailed introduction to database requirements analysis, data model design, database structure implementation, data security management, and system testing and optimization.

关键词： System testing data security Ecosystems Production database systems data models Biodiversity Information technology Optimization

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DT-ASGNRU: A Comprehensive Framework for Traffic Flow Forecasting

DT-ASGNRU: A Comprehensive Framework for Traffic Flow Foreca...

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

作者： Jiaju He Jianhua Xiao Hongbo Xiao Yujun Yang Liming Ding Dunhong Yao Pan Yang School of Computer and Artificial Intelligence (School of Software) Huaihua University 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

Traffic prediction plays a crucial role in alleviating congestion, enhancing road utilization, and reducing traffic accidents. In order to tackle the challenge of dynamic spatiotemporal correlations in traffic data, this paper introduces a new traffic flow prediction model, DT-ASGNRU. This model combines Gated Recurrent Units (GRU), a multi-attention mechanism, and a Graph Convolutional Network (GCN), while introducing an expansion convolution layer to enhance the multi-attention mechanism. This modification expands the acceptance domain, which enhances the model’s capacity to grasp local temporal dependencies. The expanded convolution based on multi-head attention mechanism enhances the sensitivity of the model to time series data and captures the temporal correlation in traffic flow effectively. Additionally, the integration of attention mechanisms with graph convolutions allows for dynamic modeling of spatial relationships within traffic networks. We conducted assessment trials utilizing an extensive collection of genuine traffic information, and the outcomes indicate that DT-ASGNRU surpasses all comparative methodologies in terms of performance.

关键词： Adaptation models Technological innovation Attention mechanisms Correlation Convolution Graph convolutional networks Time series analysis Predictive models data models Forecasting

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