Data Component:An Innovative Framework for Information Value Metrics in the Digital Economy

The increasing dependence on data highlights the need for a detailed understanding of its behavior,encompassing the challenges involved in processing and evaluating it.However,current research lacks a comprehensive structure for measuring the worth of data elements,hindering effective navigation of the changing digital environment.This paper aims to fill this research gap by introducing the innovative concept of“data components.”It proposes a graphtheoretic representation model that presents a clear mathematical definition and demonstrates the superiority of data components over traditional processing methods.Additionally,the paper introduces an information measurement model that provides a way to calculate the information entropy of data components and establish their increased informational value.The paper also assesses the value of information,suggesting a pricing mechanism based on its significance.In conclusion,this paper establishes a robust framework for understanding and quantifying the value of implicit information in data,laying the groundwork for future research and practical applications.

Rapid prediction of floating and sinking components of raw coal

A model that rapidly predicts the density components of raw coal is described.It is based on a threegrade fast float/sink test.The recent comprehensive monthly floating and sinking data are used for comparison.The predicted data are used to draw washability curves and to provide a rapid evaluation of the effect from heavy medium induced separation.Thirty-one production shifts worth of fast float/sink data and the corresponding quick ash data are used to verify the model.The results show a small error with an arithmetic average of 0.53 and an absolute average error of 1.50.This indicates that this model has high precision.The theoretical yield from the washability curves is 76.47% for the monthly comprehensive data and 81.31% using the model data.This is for a desired cleaned coal ash of 9%.The relative error between these two is 6.33%,which is small and indicates that the predicted data can be used to rapidly evaluate the separation effect of gravity separation equipment.

The Research on the Interreact act Development of Agricultural Modernization and Internationalization in the Area of Eastern Shandong

With the Chinese reform and opening-up, especially when entering the 90s of the 20th century, the internationalization process of China＇s economy is accelerated constantly, and at the same time the modernization of China＇s agriculture is also accelerated constantly. It makes China＇s agriculture modernization under the background of internationalization. Therefore, the integration of China＇s agricultural modernization and internationalization becomes an inevitable choice in developing China＇s modem agriculture. This paper takes the practice of agricultural modernization and internationalization in the area of eastern Shandong province as a basis and uses Panel Data model to analyze the interact relationship between agricultural modernization and internationalization quantificationally with the data of the seven cities in the area of eastern Shandong. The result indicates that agricultural modernization and internationalization have the relationship of interact development.

Functional singular component analysis based functional additive models

We propose a method which uses functional singular component to establish functional additive models. The proposed methodology reduces the curve regression problem to ordinary(i.e., scalar) additive regression problems of the singular components of the predictor process and response process. Consistency of estimators for the nonparametric function and prediction are proved, respectively. A simulation study is conducted to investigate the finite sample performances of the proposed estimators.