• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1427-1434
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• 2017

Due to the acceleration of the 4th industrialization, the data around us rapidly increased. Therefore, it is necessary to be able to more easily grasp the nature and meaning of data obtained through data analysis than to collect data, and apply it flexibly to the value judgment of data. Visualization technology is now attracting attention in many fields. Visualization allows the user to more easily grasp the information of the data with graphs, charts, etc. so that the data analysis result can be understood more easily, so that the user can make an immediate judgment and make a quick decision. Among them, there is a high degree of interest in visualization using public data, which is highly useful to users. In this paper, we implemented R - library and R Studio to visualize public data at the installation sites of bicycle storage sites among various software that can express visualization.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.203-211
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• 2024

Utilizing programming languages for data visualization can enhance the efficiency and effectiveness in handling data volume, processing time, and flexibility. However, practice is required to become proficient in programming. Therefore public data-based the problem bank was developed to practice data visualization in a programming automatic assessment system. Public data were collected based on topics suggested in the curriculum and were preprocessed to make it suitable for users to visualize. The problem bank was associated with the mathematics curriculum to learn various data visualization methods. The developed problems were reviewed to expert and pilot testing, which validated the level of the questions and the potential of integrating data visualization in math education. However, feedback indicated a lack of student interest in the topics, leading us to develop additional questions using student-center data. The developed problem bank is expected to be used when students who have learned Python in primary school information gifted or middle school or higher learn data visualization.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.33-41
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• 2020

Nowadays, distributed mobility management (DMM) approaches have been widely adopted to address the limitations of centralized architectural methods to support seamless data transmission schemes in wireless sensor networks. This paper deals with the end-to-end (E2E) integration of Network Mobility (NEMO) basic support protocol in distributed wireless sensor network systems in structural health and environmental monitoring of social overhead capital (SOC) public infrastructures such as bridges, national highways, tunnels, and railroads. The proposed scheme takes advantage of the features of both the NEMO basic support protocol and partially distributed network-based DMM framework in providing seamless data transmission and robust mobility support. The E2E seamless data transmission scheme allows mobile users to roam from fixed-point network access locations and mobile platforms (i.e., vehicles such as cars, buses, and trains) without disconnecting its current sessions (i.e., seamless handover).

• Journal of the Korean Professional Engineers Association
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• v.16 no.1
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• pp.4-12
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• 1983

Data communication has historically evolved from leased lines, to use of the public telephone network, and eventually to dedicated(exclusive) data networks. It requires an enormous amount of money for establishing a separate and independent data network at the beginning stage. No country has ever adopted this method In the Republic of Korea too the age of leased circuits is passing and it is scheduled to open the public telephone network to the data transmission and to install packet mode processor in the last half of 1983. This paper presents a survey on characteristics of the public telephone network in Seoul and a future development of the data communication of Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.81-90
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• 2017

This study aimed to construct an integrated database using the same spatio-temporal unit by employing various public-data types with different real-time information provision cycles and spatial units. Towards this end, three temporal interpolation methods (piecewise constant interpolation, linear interpolation, nonlinear interpolation) and a spatial matching method by district boundaries was proposed. The case study revealed that the linear interpolation is an excellent method, and the spatial matching method also showed good results. It is hoped that various prediction models and data analysis methods will be developed in the future using different types of data in the analysis database.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• The Journal of Economics, Marketing and Management
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• v.11 no.3
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• pp.25-35
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• 2023

Purpose: This paper examines whether foreign aid influences public sector efficiency in policy areas of administration, education, and stability. Research design, data and methodology: The study uses panel data of 77 aid recipient developing countries over the period 2000-2020 and employs various panel data techniques to estimate. Results: We found that a percentage change in foreign aid increases administrative efficiency by 0.02 to 0.04 on average ceteris paribus in the short run. On the other hand, a percentage increase in foreign aid decreases education efficiency by 0.005 to 0.006 on average. While the impact of foreign aid on the policy area of stability is insignificant. Conclusions: The empirical results of this study have important implications for both donors and aid recipient countries. It suggests that to get positive influence from foreign aid, in the area of education and stability, the recipient countries need to increase accessibility of secondary schools with quality education especially; technical and vocational. Also, the donor should provide a minimum threshold amount of foreign aid to developing countries for reforming the institutions' capacity building.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.133-139
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• 2020

The purpose of this study is to contribute to the provision of basic data for psychological quarantine policy and counseling by examining the public perception of the "corona blue" phenomenon through analysis of social media big data. To do this, key words related to the word 'Corona Blue' were derived and analyzed using the big data analysis program 'Textom'. As a result of the analysis, words such as 'Corona 19', 'depression', 'problem' and 'overcome' were derived as key words. For the analysis results,"pride and awarenes as the public perception of Corona 19", "depression and anxiety as a group trauma as the corona blue phenomenon", "spreading a psychological quarantine culture and demanding social healing as the perception of overcoming corona Blue," and "hope for return to daily life and changes in daily life as the perception of post corona" were discussed. In conclusion, we have identified the need for active psychological support from the community By revealing that Corona Blue is a depression as a group trauma. At this time, it is confirmed that it is necessary to prioritize social healing and psychological quarantine for the main risk groups such as youth or the vulnerable, who are the socially weak.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.751-759
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• 2020

This study examines the impact of mergers on the financial performance of the Jordanian public shareholding companies. The study employs data collected for a sample of 10 Jordanian non-financial public firms that were engaged in legal horizontal merger deals between 2000 and 2013. The data was collected from the published annual financial reports of the merging companies and comparative companies for three years before the merger and three years after the merger. Event study methodology was applied to examine the data. Four measures of financial performance (FP) were used, which are return on assets (ROA), return on equity (ROE), earnings per share (EPS), and net profit margin (NPM). Two methods were used in the analysis - the change model and the intercept model using financial performance raw data and industry-adjusted data. The findings in general showed no significant impact of mergers on the financial performance of merging firms using the change model. However, by using the intercept model, significant impact of mergers on the financial performance was found on the sample of the study. The significant impact was found for mergers on the raw ROE of the merging firms, and on the ROA and NPM of the industry-adjusted firms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.57-68
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• 2018

This paper presents a smart firefighting appliances monitoring system based on big data analytics platform using GS1 for Smart City. Typical firefighting appliances are fire hydrant, fire extinguisher, fire alarm, sprinkler, fire engine, etc. for the fire of classes A/B/C/D/E. Among them, the dry chemical fire extinguisher have been widely supplied and 6 millions ones were replaced for the aging ones over 10 years in the past year. However, only 5% of them have been collected for recycling of chemical materials included the heavy metals of environment pollution. Therefore, we considered the trace of firefighting appliances from production to disposal for the public open service. In the paper, we suggest 1) a smart firefighting appliances system using GS1, 2) a big data analytics platform and 3) a public open service and visualization with the analyzed information, for fire extinguishers from production to disposal. It can give the information and the visualized diagrams with the analyzed data through the public open service and the free Apps.