Physical and Psychological Health Problems of Senior Citizens in Pandemic: A Case Study of Kirtipur Municipality, Nepal

Acharya, Milan; Acharya, Kamal Prasad; Gyawali, Kalpana; Acharya, Pitambar; Devkota, Balram

doi:10.26855/ijcemr.2021.07.027

Cited by 8 publications

(7 citation statements)

References 16 publications

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“…It is the raw material for knowledge discovery, while data mining is the process of deeper processing of data, which is an advanced process of data processing. The model is shown in Figure 1 including the processes of problem definition, data selection, data preprocessing, data transformation, data mining, knowledge evaluation, and knowledge representation [11]. Data mining technology refers to the technology of data processing in the process of data mining.…”

Section: Data Miningmentioning

confidence: 99%

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Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Dong

2022

Advances in Materials Science and Engineering

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The finite element method divides the existing solid structure into a finite number of elements. It integrates and analyzes the divided elements according to preset criteria, and then solves the equilibrium equation of the overall structure according to the corresponding boundary conditions. The problem is analyzed through a finite element model. A large amount of data from the experiment are derived, and then data mining technique is used to find out the data that are useful for the experiment. The purpose of this paper is to test bridge engineering through data mining technology, and then simulate different fiber-reinforced concrete models through finite element method. In this paper, three kinds of nanofibers, carbon fiber (CFRP), glass fiber (GFRP), and aramid fiber (AFRP) are used to make concrete bridges. Loading experiments are also carried out with different degrees of load on the bridge and 100 experiments on the error interval. The experimental results show that the displacement is proportional to the load to a certain extent. The carbon fiber concrete has a stronger positive correlation than the other two materials. Its finite element simulation experimental data have 78% error difference between 0 and 10, while the other two are around 40%.

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Section: Data Miningmentioning

confidence: 99%

“…Therefore, in the process of selecting the constitutive relationship of reinforced concrete in this simulation, the constitutive relationship provided by the relevant codes is mainly referred to. The stress-strain relationship of concrete under compression is as formulas (11) and (12):…”

Section: Finite Element Analysismentioning

confidence: 99%

Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Dong

2022

Advances in Materials Science and Engineering

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“…e root node is the attribute with the most common data in each model, and the page is the value of the model [13]. A decision tree is a tree structure similar to the structure of the branches, in which each interior of the tree corresponds to the test of the determination of the structure in the form of milk (1). Its branch is the test result.…”

Section: Definition and Representation Of Decision Treementioning

confidence: 99%

“…rough scientific and efficient ideological education and psychological education, colleges and universities can better help cultivate students' good morality [1]. Since the beginning of the new century, the rapid development of industry, the prosperity of human beings, and the continuous improvement of information networks have promoted not only the cohesion and integration of society, but also the integration of society, culture, and school environment, where the students of modern colleges and universities live.…”

Section: Introductionmentioning

confidence: 99%

The Architecture of College Psychological Teaching Management System Based on Data Mining Technology

Huang

Leng

2022

Security and Communication Networks

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In order to meet the requirements of the development of educational informatization, combined with data mining technology, this article studies the architecture of the college psychological teaching management system. To experience the benefits brought by the Internet age, in order to further improve performance and meet the needs of the Internet information age, many colleges and universities have begun to strengthen the development of teaching management. Based on this background, this article proposes a standardized mode of mental health management in colleges and universities based on information technology. With the help of data warehouse and data mining technology, the ID3 algorithm, organizational rules, and other algorithms are used to develop a psychology subject evaluation system. Based on the improvement of grades and the behavioral characteristics of college students, this article formulates cross-platform operation rules, determines the B/S type as the normal state, and solves the best problem through comparison and selection. Then, a more specific system architecture design is carried out. The architecture of the software system selects the classic three-tier structure, which makes the client independent of the use platform and meets the requirements of user diversity and system portability. The design of functional modules such as the system fully meets the requirements of the ideological education management system for college students in the above analysis, with reasonable structure and clear logic. Finally, the advantages of the designed system architecture are summarized, including clarifying the grading idea of ideological education and training. It expands the transplantation ability of the system in a cross-platform way.

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“…In recent years, the concept of big data has gradually emerged. It is used to describe and defne the massive data generated in the era of information explosion, as well as related technology development and innovation opportunities brought by big data [6]. Data mining is extracting information that people do not know in advance.…”

Section: Introductionmentioning

confidence: 99%

English Teaching Achievement Prediction by Big Data Analysis under Deep Intervention

Guo¹

2023

Journal of Electrical and Computer Engineering

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Appropriate data analysis technology can make people use the online degree education, obtain the data and information generated in the learning management system, and provide a useful decision basis for optimizing the teaching and management process of online degree education. Data analysis technology can help English teachers better grasp students’ learning situations and progress and optimize management. First, data analysis methods and decision tree algorithms are analyzed. Second, in data mining technology, the C4.5 decision tree method is used to construct an English score prediction model. Through the analysis of English learning-related information such as questionnaires and collected student test score data, the prediction of English teaching performance is analyzed from the perspective of teachers’ in-depth intervention. The survey results are shown as follows: (1) The model is simulated and tested. The model’s prediction accuracy is 98.20%, 99.10%, 99.40%, 98.70%, and 98.90%, higher than the standard accuracy of 97.5%. Additionally, the average response efficiency of the model is 99.42%, which can be used. (2) The failure rate of boys’ final grades is 11%, and the failure rate of female students’ final grades is 10%. There is only a 1% difference in the final grade failure rate between male and female students. The effect of gender on teaching performance is less pronounced. (3) As the number of practice questions increases, the rate of failing grades decreases. Thus, the data suggest that the number of practice questions affects instructional performance. (4) Teachers’ intervention can improve students’ English achievement. Increasing the intensity of the intervention also improves student achievement. Therefore, the follow-up research should increase the number of practice questions and teacher intervention in English teaching. The English teaching achievement prediction suggestion based on big data analysis is put forward, providing a reference for prediction management.

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Physical and Psychological Health Problems of Senior Citizens in Pandemic: A Case Study of Kirtipur Municipality, Nepal

Cited by 8 publications

References 16 publications

Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

Finite Element of Nanoscale Carbon Fiber-Reinforced Concrete Bridge Engineering Monitoring Based on Data Mining Technology

The Architecture of College Psychological Teaching Management System Based on Data Mining Technology

English Teaching Achievement Prediction by Big Data Analysis under Deep Intervention

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