scholarly journals Construction and Practice of Blended Teaching Model in the Context of Big Data: A Case Study of ESP Medical English

2021 ◽  
Author(s):  
Yajun Chen
Keyword(s):  
Big Data ◽  
Teaching Model ◽  
Medical English ◽  
Blended Teaching

scholarly journals Research on the Innovative Strategy of Blended Teaching in Network Marketing in the Era of Big Data

2021 ◽  
Vol 5 (11) ◽  
pp. 83-88
Author(s):  
Lei Liang ◽  
Zhiyong Fan
Keyword(s):  
Big Data ◽  
Independent Learning ◽  
Teaching Model ◽  
Network Marketing ◽  
Innovative Strategy ◽  
Model Combining ◽  
Hybrid Teaching ◽  
Core Literacy ◽  
Big Data Technology ◽  
Blended Teaching

Network Marketing is a practical professional compulsory course. With the advent of big data technology, a hybrid teaching model combining online and offline has emerged. Based on the analysis of the advantages of using a hybrid teaching model in Internet Marketing, this article comprehensively considers a variety of factors and put forward the innovative strategy of blended teaching in Network Marketing in the era of big data. This may provide new paths and methods for enhancing teaching effects, cultivating students’ independent learning, and improving core literacy.

scholarly journals An Empirical Study on Innovation of College Blended Teaching under Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qianqian Xie ◽  
Sang-Bing Tsai
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Learning Experience ◽  
Information Age ◽  
Big Data Analysis ◽  
Teaching Model ◽  
Application Technology ◽  
Teaching Mode ◽  
Teaching Content ◽  
Blended Teaching

With the advent of the information age, the way people obtain information has changed profoundly. The wave of informationization in higher education has also come with it, and the teaching mode, teaching content, and teaching form are constantly innovated. How to organically integrate information technology into education teaching in order to care for learners’ learning experience and promote the cultivation of new talents is an issue that current educational technology researchers need to pay great attention to. This paper first builds a complete blended teaching model of public English for higher education, but its application effect needs to be further examined. This paper is an investigation in the background of the current era to build a blended teaching model. Based on the continuous development of the era, the ideology and application technology of this field will keep upgrading, so the teaching model also needs to be changed and updated according to the characteristics of the development of the era. The investigation of mixed teaching modes is not permanent. The investigation of the mixed teaching mode is not permanent. At present, only a few courses apply the blended teaching mode. On the basis of the continuous updating of teaching concepts and the latest technologies, it is foreseen that the focus of subsequent investigations will be on the individualized development of the blended teaching mode.

scholarly journals Fair weather forecasting? The shortcomings of big data for sustainable development, a case study from Hubballi‐Dharwad , India

2021 ◽  
Author(s):  
Andrew Sudmant ◽  
Vincent Viguié ◽  
Quentin Lepetit ◽  
Lucy Oates ◽  
Abhijit Datey ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Big Data ◽  
Weather Forecasting ◽  
Fair Weather

scholarly journals Geospatial Serverless Computing: Architectures, Tools and Future Directions

2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey
Keyword(s):  
Big Data ◽  
Forest Cover ◽  
Mineral Resources ◽  
Hyperspectral Data ◽  
Real Time Analysis ◽  
First Case ◽  
Amazon Web Services ◽  
Aws Lambda ◽  
Physical Features

Several real-world applications involve the aggregation of physical features corresponding to different geographic and topographic phenomena. This information plays a crucial role in analyzing and predicting several events. The application areas, which often require a real-time analysis, include traffic flow, forest cover, disease monitoring and so on. Thus, most of the existing systems portray some limitations at various levels of processing and implementation. Some of the most commonly observed factors involve lack of reliability, scalability and exceeding computational costs. In this paper, we address different well-known scalable serverless frameworks i.e., Amazon Web Services (AWS) Lambda, Google Cloud Functions and Microsoft Azure Functions for the management of geospatial big data. We discuss some of the existing approaches that are popularly used in analyzing geospatial big data and indicate their limitations. We report the applicability of our proposed framework in context of Cloud Geographic Information System (GIS) platform. An account of some state-of-the-art technologies and tools relevant to our problem domain are discussed. We also visualize performance of the proposed framework in terms of reliability, scalability, speed and security parameters. Furthermore, we present the map overlay analysis, point-cluster analysis, the generated heatmap and clustering analysis. Some relevant statistical plots are also visualized. In this paper, we consider two application case-studies. The first case study was explored using the Mineral Resources Data System (MRDS) dataset, which refers to worldwide density of mineral resources in a country-wise fashion. The second case study was performed using the Fairfax Forecast Households dataset, which signifies the parcel-level household prediction for 30 consecutive years. The proposed model integrates a serverless framework to reduce timing constraints and it also improves the performance associated to geospatial data processing for high-dimensional hyperspectral data.

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