• Informatization Policy
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• v.23 no.2
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• pp.73-97
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• 2016

Social changes due to ICT like Big Data, IoT, Cloud and Mobile is progressing rapidly. Now, we get out of the old-fashioned frame was measured at the level of the information society through the introduction of PC, Internet speed and Internet subscribers etc and there is a need for a new type of diagnostic information society framework. This study is the study for the framework established to diagnose and measure post-information society. The framework and indicators were chosen in accordance with the technological society coevolution theory and information society-related indicators presented from authoritative international organizations. Empirical results utilizing the indicators and framework developed in this study were as follows: First, the three sectors, six clusters (items), 25 nodes (indicators) that make up the information society showed that all strongly connected. Second, it was diagnosed as information society development (50.34%), technology-based expansion (25.03%) and ICT effect (24.63%) through a network analysis (ANP) for the measurement of importance of the information society. Third, the result of calculating the relative importance of the cluster and nodes showed us (1)social development potential (26.04%), (2)competitiveness (15.9%), (3)ICT literacy (15.5%) (4) (social)capital (24.3 %), (5)ICT acceptance(9.54%), (6)quality of life(8.7%). Consequently, We should take into account the effect of the economy and quality of life beyond ICT infrastructure-centric when we measure the post-information society. By applying the weighting we should performs a comparison between countries and we should diagnose the level of Korea and provide policy implications for the preparation of post-information society.

• Smart Media Journal
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• v.9 no.2
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• pp.51-62
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• 2020

Starting with the "Smart Grid National Road Map" in 2010, the Smart Grid 2030 was introduced through the basic plan and implementation plan of the intelligent power grid with the goal of building the world's first national smart grid. In this paper, we intend to build a power domain ontology based on the power business platform based on the upper and lower conceptual models of the "Smart Grid Interoperability Standard Framework and Roadmap", the standard of implementation plan. Ontology is suitable for expressing and utilizing the smart grid conceptual model because it considers hierarchical structure as knowledge defines the properties of entities and relationships between entities, but there is no research related to them. Therefore, in this paper, the upper ontology was defined as a major category for smart grid-related fields, and the lower ontology was defined as detailed systems and functions for the upper ontology to construct the ontology. In addition, scenarios in various situations that could occur in the power system were constructed and significant inference results were derived through inference engines and queries.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.402-411
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• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.

• Journal of the Korean association of regional geographers
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• v.10 no.2
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• pp.407-427
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• 2004

The rapid innovation of information and communication technology and its sharp falling prices have brought about the expansion of the Internet, integrating the world as one space under converged space and time. This rapid expansion of the Internet and its application in the economy have spurred the emergence of the digital economy. The Internet has influenced strongly on the changes of not only economic activities but also political, social and cultural activities. In this context, a rapidly increasing Internet expansion renders the rhetoric about the death of distance and about the meaningless of geographical place. However, the development and expansion of Internet induces a growing digital divide among nations and also a spatial inequality in a nation as the supply of the Internet has concentrated towards demand-affluent large cities. A large gap of digital access has been occurred between high income and low income countries according to a measurement of the international digital access index. In a national level, the Internet backbone has been built around large cities which favor a large amount of the Internet demand, and the affordable accessibility of these cities for the Internet services has influenced strongly on the agglomeration of Internet related industries, further inducing the construction and investment of the Internet backbone into large cities as cumulative causation effects. As a result, the expansion of the Internet affects immensely on the changes of spatial structure in a nation resulting in the new spatial phenomena such as centralization, concentration and splintering in the digitalized space-economy.

• Journal of Family Resource Management and Policy Review
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• v.25 no.2
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• pp.41-52
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• 2021

The purpose of this study is to examine how female labor force participation, family policies, and gender equality are related to fertility rate across countries. Multiple measures has been collected from various data sources(such as OECD, UNDP, and WVS) and the panel data set which includes (mostly) OECD countries range from 1990 to 2019 are analyzed. The major findings are as follows. First, based on OECD countries samples, female labor force participation is positively associated with the fertility rate, which implies that women's labor force participation does not lead to a reduction in fertility rate. Second, the length of paternity leave is positively associated with fertility rate whereas the direction is the opposite for the relationship between the length of maternity leave and fertility rate. This is attributed to the possibility that a longer period of maternity leave incurs the a higher opportunity cost of earning income, which leads to a reduced fertility rate. Third, countries with higher gender inequality index tend to have a higher fertility rate. Similarly, countries with higher gender equality value have a lower fertility rate. When the gender equality value is devideed into three sub-categories, education, politics, and employment, the gender equality value in education is the only sub-category which is negatively associated with the fertility rate. This study confirms that female labor force participation may not be a contributing factor in the lowering of fertility rate but instead can be positively associated with the fertility rate. Also, the results show that family policies or gender equality values can be significantly affect fertility rate.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.337-342
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• 2019

This letter describes the development of WRI (Wildfire Risk Index) using GDAPS (Global Data Assimilation and Prediction System) and satellite data, and its application to the Goseong-Sokcho and Gangneung-Donghae wildfires in April 4, 2019. We made sure that the proposed WRI represented the change of wildfire risk of around March 19 and April 4 very well. Our approach can be a viable option for wildfire risk monitoring, and future works will be necessary for the utilization of GK-2A products and the coupling with the wildfire prediction model of the Korea Forest Service.

• Journal of Technology Innovation
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• v.30 no.1
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• pp.1-20
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• 2022

Digital transformation refers to the economic and social effects of digitisation and digitalisation. Although digital transformation acts as a useful tool for economic/social development and enhancing the convenience of life, it can have negative effects (misuse of personal information, ethical problems, deepening social gaps, etc.). The government is actively establishing policies to promote digital transformation to secure competitiveness and technological hegemony, however, understanding of digital transformation-related risk issues and implementing policies to prevent them are relatively slow. Thus, this study systematically identifies risk issues of the future society that can be caused by digital transformation based on quantitative analysis of media articles big data through the Embedded Topic Modeling method. Specifically, first, detailed issues of negative effects of digital transformation in major countries were identified. Then detailed issues of negative effects of artificial intelligence in major countries and Korea were identified. Further, by synthesizing the results, future direction of the government's digital transformation policies for responding the negative effects was proposed. The policy implications are as follows. First, since the negative effects of digital transformation does not only affect technological fields but also affect the overall society, such as national security, social issues, and fairness issues. Therefore, the government should not only promote the positive functions of digital transformation, but also prepare policies to counter the negative functions of digital transformation. Second, the detailed issues of future social risks of digital transformation appear differently depending on contexts, so the government should establish a policy to respond to the negative effects of digital transformation in consideration of the national and social context. Third, the government should set a major direction for responding negative effects of digital transformation to minimize confusion among stakeholders, and prepare effective policy measures.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.20-33
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• 2021

This study is to suggest improvements of personal information protection in South Korea, according to requiring the safety of process and protection of personal information. Accordingly, based on data collection and analysis through literature research, this study derived the issues and suitable standards of personal information for major artificial intelligence services. In addition, this cases studies were reviewed, focusing on the legal compliance and porcessing compliance for personal information proection in major countries. And it suggested the improvement plan applied in South Korea. As the results, in legal compliance, it is required reorganization of related laws, responsibility and compliance to develop and provide AI, and operation of risk management for personal information protection laws in AI services. In terms of processing compliance, first, in pre-processing and refining, it is necessary to standardize data set reference models, control data set quality, and voluntarily label AI applications. Second, in development and utilization of algorithm, it is need to establish and apply a clear regulation of the algorithm. As such, South Korea should apply suitable improvement tasks for personal information protection of safe AI service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.1-14
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• 2014

The expansion of the physical road in response to changes in social conditions and policy of the country has reached the limit. In order to alleviate congestion on the existing road to reconsider the effectiveness of this method should be asking. Currently, how to collect traffic information for management of the intersection is limited to point detection systems. Intelligent Transport Systems (ITS) was the traffic information collection system of point detection method such as through video and loop detector in the past. However, intelligent transportation systems of the next generation(C-ITS) has evolved rapidly in real time interval detection system of collecting various systems between the pedestrian, road, and car. Therefore, this study is designed to evaluate the development of an algorithm for queue length based real-time traffic signal control methodology. Four coordinates estimate on time-space diagram using the travel time each individual vehicle collected via the interval detector. Using the coordinate value estimated during the cycle for estimating the velocity of the shock wave the queue is created. Using the queue length is estimated, and determine the signal timing the total queue length is minimized at intersection. Therefore, in this study, it was confirmed that the calculation of the signal timing of the intersection queue is minimized.