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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Seong-Yoon Shin
Kunsan National University
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

 1 
A forecasting of stock trading price using time series information based on big data Soo-Tai Nam; Chan-Yong Jin; Seong-Yoon Shin
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2548-2554

Abstract

Big data is a large set of structured or unstructured data that can collect, store, manage, and analyze data with existing database management tools. And it means the technique of extracting value from these data and interpreting the results. Big data has three characteristics: The size of existing data and other data (volume), the speed of data generation (velocity), and the variety of information forms (variety). The time series data are obtained by collecting and recording the data generated in accordance with the flow of time. If the analysis of these time series data, found the characteristics of the data implies that feature helps to understand and analyze time series data. The concept of distance is the simplest and the most obvious in dealing with the similarities between objects. The commonly used and widely known method for measuring distance is the Euclidean distance. This study is the result of analyzing the similarity of stock price flow using 793,800 closing prices of 1,323 companies in Korea. Visual studio and Excel presented calculate the Euclidean distance using an analysis tool. We selected “000100” as a target domestic company and prepared for big data analysis. As a result of the analysis, the shortest Euclidean distance is the code “143860” company, and the calculated value is “11.147”. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.
Face Song Player According to Facial Expressions Samule Lee; Seong-Yoon Shin
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.533 KB) | DOI: 10.11591/ijece.v6i6.pp2805-2809

Abstract

Contemporary people have highly insufficient time and means of relieving their stress. Provision of a program that can solve such stress in daily life would make one’s life substantially more enjoyable. In this thesis, Face Song Player, which is a system that recognizes the facial expression of an individual and plays music that is appropriate for such person, is presented. It studies information on the facial contour lines and extracts an average, and acquires the facial shape information. MUCT DB was used as the DB for learning. For the recognition of facial expression, an algorithm was designed by using the differences in the characteristics of each of the expressions on the basis of expressionless images. Facial expression is extracted by acquiring information on the eyes, eyebrows, eyelids, mouth, lips and nasal cheeks for expressions of happiness, surprise and sorrow as well as absence of expression. There is an advantage of being able to obtain a substantial effect with very low cost through this system.
Co-Authors Chan-Yong Jin Guangxing Wang Gwanghyun Jo Jong-Chan Kim Samule Lee Soo-Tai Nam