scholarly journals Analysis and Prediction of “AI + Education” Attention Based on Baidu Index—Taking Guizhou Province as an Example

2021 ◽  
Vol 13 (5) ◽  
pp. 120
Author(s):  
Yulin Zhao ◽  
Junke Li ◽  
Jiang-E Wang
Keyword(s):  
Artificial Intelligence ◽  
Southwest China ◽  
Arima Model ◽  
Modern Technology ◽  
Guizhou Province ◽  
Western Region ◽  
Elastic Coefficient ◽  
The Sustainable Development ◽  
Intelligence Education ◽  
Coefficient Method

Studying the attention of “artificial intelligence + education” in ethnic areas is of great significance for China for promoting the integrated development of new educational modes and modern technology in the western region. Guizhou province is an area inhabited by ethnic minorities, located in the heart of Southwest China. The development of its intelligent education has strong enlightenment for the whole country and the region. Therefore, this paper selects the Baidu Index of “artificial intelligence (AI) + education” in Guizhou province from 2013 to 2020, analyzes the spatial–temporal characteristics of its network attention by using the elastic coefficient method, and builds the ARIMA model on this basis to predict future development. The results show that the public’s attention to “AI + education” differs significantly in time and space. Then, according to the prediction results, this paper puts forward relevant suggestions for the country to promote the sustainable development of education in western ethnic areas.

scholarly journals Society 5.0: A Japanese Concept for a Superintelligent Society

2021 ◽  
Vol 13 (12) ◽  
pp. 6567
Author(s):  
Carolina Narvaez Rojas ◽  
Gustavo Adolfo Alomia Peñafiel ◽  
Diego Fernando Loaiza Buitrago ◽  
Carlos Andrés Tavera Romero
Keyword(s):  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Modern Technology ◽  
Birth Rates ◽  
The Sustainable Development ◽  
Technological Advances ◽  
Development Goals

This document discusses the Japanese context of Society 5.0. Based on a society-centered approach, Society 5.0 seeks to take advantage of technological advances to finally solve the problems that currently threaten Japan, such as aging, birth rates and lack of competitiveness, among others. Additionally, another objective is to contribute to the progress of the country and develop the foundations for a better world, in which no individual can be excluded from the technological advances of our current society, to achieve this goal, the Sustainable Development Goals (SDG) have been developed. SDGs seek to assess the methods of use of modern technology and thus find the best strategies and tools to use it in a way that guarantees sustainability within the framework of a new society that demands constant renovations.

Research Paper DNA barcode identification of fish products from Guiyang markets in southwest China

2022 ◽  
Author(s):  
Qian Tang ◽  
Qi Luo ◽  
Qian Duan ◽  
Lei Deng ◽  
Renyi Zhang
Keyword(s):  
Dna Barcoding ◽  
Molecular Identification ◽  
Fish Consumption ◽  
Southwest China ◽  
Dna Barcode ◽  
Guizhou Province ◽  
Accurate Identification ◽  
Continuous Growth ◽  
Fish Products ◽  
Fresh Frozen

Nowadays, the global fish consumption continues to rise along with the continuous growth of the population, which has led to the dilemma of overfishing of fishery resources. Especially high-value fish that are overfished are often replaced by other fish. Therefore, the accurate identification of fish products in the market is a problem worthy of attention. In this study, full-DNA barcoding (FDB) and mini-DNA barcoding (MDB) used to detect the fraud of fish products in Guiyang, Guizhou province in China. The molecular identification results showed that 39 of the 191 samples were not consistent with the labels. The mislabelling of fish products for fresh, frozen, cooked and canned were 11.70%, 20.00%, 34.09% and 50.00%, respectively. The average kimura 2 parameter distances of MDB within species and genera were 0.27% and 5.41%, respectively; while average distances of FDB were 0.17% within species and 6.17% within genera. In this study, commercial fraud is noticeable, most of the high-priced fish were replaced of low-priced fish with a similar feature. Our study indicated that DNA barcoding is a valid tool for the identification of fish products and that it allows an idea of conservation and monitoring efforts, while confirming the MDB as a reliable tool for fish products.

A comparative study of short-term load forecasting methods in distribution network

2021 ◽  
Vol 15 (1) ◽  
pp. 23-35
Author(s):  
Tuan Ho Le ◽  
◽  
Quang Hung Le ◽  
Thanh Hoang Phan
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
Arima Model ◽  
Distribution Network ◽  
Load Forecasting ◽  
Short Term ◽  
Load Demand ◽  
Forecasting Methods ◽  
Short Term Load Forecasting

Short-term load forecasting plays an important role in building operation strategies and ensuring reliability of any electric power system. Generally, short-term load forecasting methods can be classified into three main categories: statistical approaches, artificial intelligence based-approaches and hybrid approaches. Each method has its own advantages and shortcomings. Therefore, the primary objective of this paper is to investigate the effectiveness of ARIMA model (e.g., statistical method) and artificial neural network (e.g., artificial intelligence based-method) in short-term load forecasting of distribution network. Firstly, the short-term load demand of Quy Nhon distribution network and short-term load demand of Phu Cat distribution network are analyzed. Secondly, the ARIMA model is applied to predict the load demand of two distribution networks. Thirdly, the artificial neural network is utilized to estimate the load demand of these networks. Finally, the estimated results from two applied methods are conducted for comparative purposes.

scholarly journals Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-Determination Theory Perspective

2020 ◽  
Vol 12 (14) ◽  
pp. 5568 ◽  
Author(s):  
Thomas K.F. Chiu ◽  
Ching-sing Chai
Keyword(s):  
Artificial Intelligence ◽  
Curriculum Design ◽  
Teaching Experience ◽  
Self Determination Theory ◽  
Curriculum Planning ◽  
Self Determination ◽  
Structured Interviews ◽  
Theoretical Frameworks ◽  
Intelligence Education ◽  
K 12

The teaching of artificial intelligence (AI) topics in school curricula is an important global strategic initiative in educating the next generation. As AI technologies are new to K-12 schools, there is a lack of studies that inform schools’ teachers about AI curriculum design. How to prepare and engage teachers, and which approaches are suitable for planning the curriculum for sustainable development, are unclear. Therefore, this case study aimed to explore the views of teachers with and without AI teaching experience on key considerations for the preparation, implementation and continuous refinement of a formal AI curriculum for K-12 schools. It drew on the self-determination theory (SDT) and four basic curriculum planning approaches—content, product, process and praxis—as theoretical frameworks to explain the research problems and findings. We conducted semi-structured interviews with 24 teachers—twelve with and twelve without experience in teaching AI—and used thematic analysis to analyze the interview data. Our findings revealed that genuine curriculum creation should encompass all four forms of curriculum design approach that are coordinated by teachers’ self-determination to be orchestrators of student learning experiences. This study also proposed a curriculum development cycle for teachers and curriculum officers.

scholarly journals Overview of Smart Aquaculture System: Focusing on Applications of Machine Learning and Computer Vision

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2882
Author(s):  
Thi Thu Em Vo ◽  
Hyeyoung Ko ◽  
Jun-Ho Huh ◽  
Yonghoon Kim
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Sustainable Development ◽  
Species Classification ◽  
The Sustainable Development ◽  
Aquaculture System ◽  
Aquaculture Industry ◽  
Intelligent Technology ◽  
Applications Of Machine Learning ◽  
Aquaculture Production

Smart aquaculture is nowadays one of the sustainable development trends for the aquaculture industry in intelligence and automation. Modern intelligent technologies have brought huge benefits to many fields including aquaculture to reduce labor, enhance aquaculture production, and be friendly to the environment. Machine learning is a subdivision of artificial intelligence (AI) by using trained algorithm models to recognize and learn traits from the data it watches. To date, there are several studies about applications of machine learning for smart aquaculture including measuring size, weight, grading, disease detection, and species classification. This review provides and overview of the development of smart aquaculture and intelligent technology. We summarized and collected 100 articles about machine learning in smart aquaculture from nearly 10 years about the methodology, results as well as the recent technology that should be used for development of smart aquaculture. We hope that this review will give readers interested in this field useful information.

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