• Journal of the Korean Regional Science Association
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• v.34 no.4
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• pp.61-74
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• 2018

This study aims to analyze the convergence change of smart city industries in Korea. Industries of Smart city can be defined ICTs and Knowledge embedded construction industry. The input output model and structural path analysis have been done using the input output tables published by Bank of Korea in 1980 and 2014. GDP deflator was applied to the input output tables. 403 industries were reclassified into 27 industries and 8 industries categories: Agriculture and Mining(AM), Non-IT Manufacture(NITM), IT Manufacture(ITM), Energy Supply(EnS), Construction as smart city(C), IT Service(ITS), Knowledge Service(KS), Etc. Service(EtS). The results are as follows; First, the input output coefficient analysis showed that The information and communication service industry(ITS) and the energy supply industry(EnS) have increased input to the construction industry(C). On the other hands, knowledge service industry(KS) and etc. service industries(EtS) decreased. Second, the multiplier analysis revealed that construction industry(C) led by smart city had a great influence on ITS, EnS, ITM and NITM directly and indirectly. Furthermore, The IT industry had the biggest change from 1980 to 2014. Third, the smart city industry has created a new convergence of 117, and it has been leading to segmentation of the structure. Change of convergence has been proceeding mainly in the ITS and EnS, NITM, ITM industries.

• Economic Analysis
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• v.27 no.3
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• pp.61-96
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• 2021

This study is to structurally examine the regional income disparity in Korea. It measures the regional income inducement by household consumption expenditure per unit income, and the regional interdependency of income using 2005 and 2015 Regional Input-Output Tables of 16 provincial regions of Korea. The results are as follows. Firstly, the income inducement by consumption expenditure per unit income decreased overall, mainly due to the decrease in the income inducement of other regions than due to that of their region. Secondly, in many regions, the inter-relational income dependency per unit income decreased also, this too, mainly due to the decrease in the income transfer to other region. And, the income inducement effects of consumption expenditure per unit income of Seoul and Gyeonggi, which occupy a large portion of the Korean economy, were lower than that of other regions, but took the largest portion of income inducements generated by other regions as well as by themselves and absorbed the income transfers from other regions the most. The higher income inducement and income absorption in Seoul and Gyeonggi by consumption expenditure of other regions were mainly because of the high share in service of their consumption structure, the progress in tertiarization of their industrial structure, and the high wage portion. These results also mean that viewed from the regional interdependency of income, the income of Seoul and that of Gyeonggi are highly dependent on the income of other regions. Especially, Gyeonggi which leads the overseas exports of high-tech based manufactured products, has other external factors that contribute to their high income inducement, whereas, Seoul which shows high income absorption using its inter-relations with other domestic regions based on the services, has an income-generating structure that is sensitive to other regions' economic situation. Amid overall declines in regional income inducements and in income transfers, and continuing concentrations into Seoul and Gyeonggi regions, to alleviate the regional disparity, the regional industry policies should, rather than benchmarking the policies of the two concentrated regions, enhance their own inter-regional relationships by strengthening the comparative advantage of their regionally specialized industry.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.1
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• pp.5-25
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• 2022

In most countries, public libraries are knowledge information centers, complex cultural spaces, lifelong learning facilities, and third places for local residents. The social homage spoken on the premise of this identity and socio-cultural role is the knowledge and information agora, cultural infrastructure, living room in the city, and the university of the people. However, if there is a significant gap between public libraries regardless of country or region, it will inevitably lead to information gaps, regional gaps, and cultural inequality and cultural welfare gaps among local residents. This study is regarded as the essence of regional cultural facilities and premised that the regional gap in public libraries is a factor of regional cultural gaps. Based on this premise, the gap between the location quotient, input indicators, and output indicators of public libraries of regional governments in Korea and basic local governments in the Gyeongbuk region was analyzed. And this study derived core elements through correlation and regression analysis of input and output indicators of all public libraries nationwide, developed a management model for each indicator, and suggested a plan to resolve the relative gap for public libraries by city and county in Gyeongbuk.

• Journal of Korean Society of Transportation
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• v.6 no.2
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• pp.7-20
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• 1988

Recent developments in combining transportation planning models and input-output approaches, together with inclusion of intensity of land uses, have made it possible to construct realistic comprehensive urban and regional activity models. These modes form the basis for a rigorous approach to studying the interactions among urban activities. However, efficient computational solution methods for implementing such comprehensive models are still not available. In this paper an efficient solution method for the urban activity model is developed by combining Evans' partial linearization technique with Powell's hybrid method. The solution algorithm is applied to a small but realistic urban area with a detailed transportation network.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.263-271
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• 2024

This paper analysis of spatial differences in the efficiency of regional industrial enterprises in China from 2011 to 2021. The efficiency analysis uses the DEA-CCR model. The input variables for efficiency analysis are total assets and annual average employees, and the output variables are revenue from principal business and total profits. Using trend surface analysis and gravity center model, to analysis the spatial differences of efficiency in different regions. From the results of the gravity center model, the coordinates of the gravity center of China's regional industrial enterprise efficiency in 2011 are 112.303°E & 34.239°N, and 2021 are 111.753°E & 33.791°N, which indicates that the gravity center of the efficiency of China's regional industrial enterprises in the 2011-2021 period generally moves to the southwest. From the results of the trend surface analysis, the efficiency of industrial enterprises in China's regional industrial enterprises appears to show spatial differences in both the eastwest and the northsouth directions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.270-279
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• 2017

Regional assessment of crop productivity using a gridded simulation approach could aid policy making and crop management. Still, little effort has been made to develop the systems that allows gridded simulations of crop growth using ORYZA 2000 model, which has been used for predicting rice yield in Korea. The objectives of this study were to develop a series of data processing modules for creating input data files, running the crop model, and aggregating output files in a region of interest using gridded data files. These modules were implemented using C++ and R to make the best use of the features provided by these programming languages. In a case study, 13000 input files in a plain text format were prepared using daily gridded weather data that had spatial resolution of 1km and 12.5 km for the period of 2001-2010. Using the text files as inputs to ORYZA2000 model, crop yield simulations were performed for each grid cell using a scenario of crop management practices. After output files were created for grid cells that represent a paddy rice field in South Korea, each output file was aggregated into an output file in the netCDF format. It was found that the spatial pattern of crop yield was relatively similar to actual distribution of yields in Korea, although there were biases of crop yield depending on regions. It seemed that those differences resulted from uncertainties incurred in input data, e.g., transplanting date, cultivar in an area, as well as weather data. Our results indicated that a set of tools developed in this study would be useful for gridded simulation of different crop models. In the further study, it would be worthwhile to take into account compatibility to a modeling interface library for integrated simulation of an agricultural ecosystem.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.146-157
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• 2007

Fishing villages have rich potential on account of serving as a base of fishing activities with various maritime ecosystem, culture and maritime resources as well. The object of the study is ports located in Gijang, Busan and it presents the overall development direction in ports within this area. Through systematic and well-planned developing small-sized ports, this research analyzes regional economic implications by improving settlement conditions for fishing villagers scattered around this area taking the ports' natural traits into consideration. The research correlates regional input output analysis by fishing port arrangement project with connection between inter-industries and inter-regions according to the model of input-output analysis and attempts to systematically analyze regional economic structure with the economic implication divided into production, employment and income, influenced upon by the change of political exogenous variable.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.57-65
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• 2018

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS : For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS : The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination ($R^2$) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as $R^2$ had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.95-116
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• 1998

Many different kinds of wargame models have been developed and used in training and analysis purpose. However, there has been few wargame model which analyze corps or division level operational analysis. Recently KIDA develops corps level operational analysis model based on START(simplified tool for analysis of regional treats) model developed by RAND. This model runs in a PC level with 2MB memory and provides one day combat results within 30 seconds. Only one or three person can operate this model and evaluate multiple corps level operational analysis including chemical effects, $C^3I$ capacity, new weapon system effectiveness and other qualitative effects. We tested this model and evaluated input and output data. We showed that this model can be applied in division level operational analysis also. As an example division level application procedure and sensitivity analysis data was provided. We also find some limitation and problems in the model and suggest application areas and improving methods.