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8th International Conference on Cloud Computing and Big data Analytics (ICCCBDA)

作者： Yin, Xueyan Guo, Guihang Guangdong Univ Foreign Studies South China Business Coll Sch English Language & Culture Guangzhou Peoples R China Guangdong Univ Foreign Studies Sch English Int Business Guangzhou Peoples R China

ISBN: (纸本)9781665455336

Widely acknowledged as knowledge and cognition about cognitive phenomena, metacognition has become a successful tool for researchers to investigate problem solving and other thinking processes in the instructional domain. However, much of the work on metacognition has studied these constructs piecemeal and mostly qualitatively with little evidence found about cognition in business English problem solving. In light of this, by statistically based re-categorization of metacognition in business English context, we investigated the interplay of metacognitive aspects in BE problem solving. 105 third-year college students participated in the study. Metacognitive aspects (metacognitive experiences, metacognitive knowledge and metacognitive regulation) were quantitatively measured with statistical tools of SPSS, AMOS and Wordclouds, in which questionnaires and semi-structured interviews were employed to further explore 2 questions: (1) What are the prominent factors constituting BE metacognition? (2) To what extent is metacognition positively related to BE problem solving and perceived performance? Three categories of BE metacognition are identified and the data visualization analysis indicate a complex interplay of metacognition in BE problem solving, in which metacognitive knowledge and metacognitive regulation play a statistically significant role.

关键词： data visualization analysis metacognition re-categorization BE problem solving metacognitive regulation metacognitive knowledge metacognitive experience

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User experience of english online classroom E-learning based on routing algorithm and data visualization analysis

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ENTERTAINMENT COMPUTING 2024年 51卷

作者： Yu, Lihua Longdong Univ Sch Literature & Hist Qingyang 745000 Gansu Peoples R China

With the development of the Internet, E-learning has become an important way of education. However, in online English classes, user experience problems still exist, such as network delay and slow video loading speed, which affect the learning effect and user engagement. Therefore, this paper hopes to improve E-learning user experience by studying routing algorithm and data visualization analysis technology. The routing algorithm is used to optimize the network connection. By analyzing the network topology and data transmission path, the optimal route is selected to reduce the network delay and bandwidth consumption. data visualization technology is used to analyze and display the behavior and learning data of learners in the classroom in real time, so as to help learners better understand their learning situation. The experimental results show that the application of routing algorithm and data visualization analysis technology can significantly improve the user experience of online English classes. The stability of learners' network connection in the classroom is improved, the video loading speed is accelerated, and the learning effect is also significantly improved. By optimizing network connectivity and providing real-time data analytics, it is possible to meet the individual needs of learners and improve their learning effectiveness and engagement.

关键词： Routing algorithm data visualization analysis English online classes User experience E-learning

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An Interactive visualization System for Network Security data

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JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2023年第2-3期95卷 393-405页

作者： Zheng, Li Yu, Gang Zheng, Yuntian State Grid WenZhou Power Supply Co Wenzhou 325000 Peoples R China State Grid ShaoXing Power Supply Co Shaoxing 312000 Peoples R China Chongqing Univ Sch Phys Dept Phys Chongqing 400044 Peoples R China

data visualization is an important approach for data analysis, which can reveal the patterns and characteristics of complex datasets through visual processing, and provide aid for data analysts. In recent years, with the expansion of Internet users and the rich diversity of various Internet applications, the importance of network security is increasing. In the field of network security data analysis, it is a developing direction to use data visualization methods and visual analysis tools to assist manual analysis. In this paper, a visualization system for network security data is designed and implemented, which is mainly based on network flow records and security policies. The node centrality measurement and high-dimensional data visualization methods are comprehensively applied, and an interactive visualization approach is proposed. The IP topology is presented in three different view modes: static analysis, temporal analysis and exploration analysis. In addition, the high-dimensional projection map takes flow, security policy and IP address as analysis objects and selects several dimensional features as indicators. After visual presentation, the distribution of the stream set and IP set contained in the record after projection in the selected dimension space can be obtained, so that the analyst can find the points with significant abnormal eigenvalue distribution, and deduce the possible situation based on this. After testing, the system can accept the new original data record file, and quickly generate the corresponding visualization content, which can be used for the visualization analysis of network security optimization tool software, and has been used in the actual system.

关键词： data visualization analysis Network flow Security policy Interactive IP topology High dimensional projection

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Astute Farm Monitoring Using WSN and AI-A Solution for Optimally Monitoring Environmental Conditions 1st

Astute Farm Monitoring Using WSN and AI-A Solution for Optim...

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1st International Conference on Intelligent Systems and Applications

作者： Kulkarni, Sanjivani Budhavale, Shilpa Langote, Vaishali DVK MIT World Peace Univ Comp Sci & Engn Pune Maharashtra India

ISBN: (纸本)9789811965814;9789811965807

Agriculture is very significant economic sectors in every country. Farm Monitoring aims to accomplish exact management of irrigation, fertilizer, disease, and insect prevention in crop farming. In agricultural area, wireless sensor networks (WSNs) are used to gather data and communicate it to servers over a wireless link. Eighteen input characteristics were utilized to create the model, and crop yield was found and organized into three key components. When creating the multiclass model, the relative significance of the components is taken into account. For categorization of three crops: rice, groundnut, and sugarcane, an objective function is defined. A multiclass model based on a hybrid deep learning classifier approach (CNN + LSTM) is used. Furthermore, data visualization analysis is utilized to identify essential approaches in progress of smart agriculture that efficiently increase efficacy of production and assure agricultural product quality. Use of smart agriculture is progressively being incorporated into agricultural production, and advent of Internet of Things (IoT) is giving it a technological boost. Agricultural tasks precisely accomplished using the IoT' detecting, transmission, observing, and input capacities, which saves farmers' time and enhances crop yields and advantages them in long run. We installed smart agriculture IoT equipment in farm for monitoring reasons and used the algorithm in our research to do an actual-scenario analysis;the findings show that this suggested scheme is actually practical. The categorization findings are compared to the results acquired from on-the-ground agricultural specialists.

关键词： data visualization analysis Deep learning classifier Hybrid classification Smart farming

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Supply Chain Demand Forecast Based on SSA-XGBoost Model

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Journal of Computer and Communications 2022年第12期10卷 71-83页

作者： Shifeng Ni Yan Peng Ke Peng Zijian Liu School of Computer Science and Engineering Sichuan University of Science and Engineering Yibin China

Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts. To solve these problems, using artificial intelligence and big data technology to achieve market demand forecasting and intelligent decision-making is becoming a strategic technology trend of supply chain management in the future. Firstly, this paper makes a visual analysis of the historical data of the Stock Keeping Unit (SKU);Then, the characteristic factors affecting the future demand are constructed from the storage level, product level, historical usage of SKU, etc;Finally, a supply chain demand forecasting algorithm based on SSA-XGBoost model has proposed around three aspects of feature engineering, parameter optimization and model integration, and is compared with other machine learning models. The experiment shows that the forecasting result of SSA-XGBoost forecasting model is highly consistent with the actual value, so it is of practical significance to adopt this forecasting model to solve the supply chain demand forecasting problem.

关键词： data visualization analysis SSA-XGBoost Supply Chain Demand Forecast

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Intelligent Agriculture and Its Key Technologies Based on Internet of Things Architecture

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IEEE ACCESS 2019年 7卷 77134-77141页

作者： Chen, Jinyu Yang, Ao Southwest Univ Sci & Technol Sch Econ & Management Mianyang 621000 Sichuan Peoples R China Henan Univ Technol Sch Econ & Trade Zhengzhou 450066 Henan Peoples R China

In order to promote the efficient development of agriculture, the Internet of Things technology is applied to modern agricultural production, and a smart agricultural system is constructed in this paper. Moreover, the data visualization analysis and cluster analysis are used to find the key technologies in the development of the intelligent agriculture, which can effectively improve the production efficiency and ensure the quality of the agricultural products. Intellectualized products are gradually integrated into agricultural production, and the development of the Internet of Things also gives technical impetus to intelligent agriculture. Through the functions of sensing, identification, transmission, monitoring, and feedback of the Internet of Things, related agricultural activities can be accurately completed, which not only saves the time cost of farmers but also improves the crop yields and, ultimately, benefits the farmers. Therefore, the Internet of Things is used for agriculture induction, identification, monitoring, and feedback, and it is also applied to find the key technology in the application process to achieve intelligent, scientific, and efficient agriculture. It also has certain reference significance for the research of the front-end induction recognition and the intelligence of the Internet of Things in the aquaculture industry.

关键词： Intelligent agriculture Internet of Things technology data visualization analysis cluster analysis

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Software Applications in data Acquisition and analysis of Battery Parameters Measurement

Software Applications in Data Acquisition and Analysis of Ba...

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作者： ZHANG Li-guo Gao Jing Northeast Petroleum University Qinhuangdao Branch

This paper builds a battery charge and discharge experiment platform, using the data acquisition board to complete the acquisition, experimental control and data communication. PC software and SCM build bridges through serial communication. The computer puts a large amount of data information through software to complete the storage and analysis. This paper describes the use of VB serial communication method, using Labview 2D/3D data visualization capabilities for data analysis and visualization software Matlab, intuitive analysis of the collected *** a number of software in the process of data collection and analysis of integrated use. This paper also describes the feasibility and practicality of experimental data analysis to verify meter program.

关键词： data collection VB data visualization analysis Labview

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