• KDI Journal of Economic Policy
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• 제13권4호
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• pp.141-153
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• 1991

The optimal choice of the tax rate and the inflation rate framework is extended to yield relevant interpretations for the optimal fiscal and monetary policy regime in Korea. To study the relationship between the government budget and monetary growth in different environments of policy coordination, two models assuming different degrees of fiscal dominance are developed. By modelling differing institutional arrangements of the fiscal and the monetary authority from an optimal government finance viewpoint, we find the optimal relationship among some important fiscal and monetary variables. By testing the existence of the relationship empirically, we find the characteristics of the optimal policy-mix regime in Korea. The first model-the strong from of fiscal dominance-studies the optimal collection of seigniorage in a period-by-period optimization with standard assumptions on the income velocity of money, deriving a general testable result: the optimal inflation/tax rate ratio co-vary with the marginal revenue ratio. The second model-the weak form of fiscal dominance-studies an implication of the inflationary bias of discretionary monetary policy in the presence of fiscal side distortions. This model shows that the tax rate and the inflation rate can have a positive correlation. Empirical tests of the theoretical results are done for the Korean economy for 1972-1989 period. The test results show that the macroeconomic policy regime in Korea can be characterized by the strong form of fiscal dominance, implying the importance of the government budget in explaining money growth and inflation.

• Journal of the Korean earth science society
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• 제26권3호
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• pp.268-275
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• 2005

One of the nonlinear statistical modelling, neural network method was applied to predict the Sea Surface Temperature Anomalies (SSTA) in the Nino regions, which represent El Nino indices. The data used as inputs in the training step of neural network model were the first seven empirical orthogonal functions in the tropical Pacific $(120^{\circ}\;E,\;20^{\circ}\;S-20^{\circ}\;N)$ obtained from the NCEP/NCAR reanalysis data. The period of 1951 to 1993 was adopted for the training of neural network model, and the period 1994 to 2003 for the forecasting validation. Forecasting results suggested that neural network models were resonable for SSTA forecasting until 9-month lead time. They also predicted greatly the development and decay of strong E1 Nino occurred in 1997-1998 years. Especially, Nino3 region appeared to be the best forecast region, while the forecast skills rapidly decreased since 9-month lead time. However, in the Nino1+2 region where they are relatively low by the influence of local effects, they did not decrease even after 9-month lead time.

• Journal of the Korean association of regional geographers
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• 제23권2호
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• pp.376-387
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• 2017

This paper attempts to analyze the geographical characters of Twitter data and presents analysis potentials for social network analysis in geography. First, this paper suggests a methodology for a topic modeling-based approach in order to identify the geographical characteristics of tweets, including an analysis flow of Twitter data sets, tweet data collection and conversion, textural pre-processing and structural analysis, topic discovery, and interpretation of tweets' topics. GPS coordinates referencing tweets(geotweets) were extracted among sampled Twitter data sets because it contains the tweet place where it was created. This paper identifies a correlated relationship between some specific topics and local places in Jeju. This correlation is closely associated with some place names and local sites in Jeju Island. We assume it is the intention of tweeters to record their tweet places and to share and retweet with other tweeters in some cases. A surface density map shows the hotspots of tweets, detecting around some specific places and sites such as Jeju airport, sightseeing sites, and local places in Jeju Island. The hotspots show similar patterns of the floating population of Jeju, especially the thirty-year age group. In addition, a topic modeling algorithm is applied for the geographical topic discovery and comparison of the spatial patterns of tweets. Finally, this empirical analysis presents that Twitter data, as social network data, provide geographical significance, with topic modeling approach being useful in analyzing the textural features reflecting the geographical characteristics in large data sets of tweets.

• Journal of Korea Water Resources Association
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• 제46권5호
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• pp.477-490
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• 2013

A rip-current warning index function, which is estimated from the likelihood of rip current quantified based on numerical simulations under various sea environments and is varied according to real-time buoy-observations, was studied to help protect against rip current accidents at Haeundae beach. For the quantification, the definition of likelihood of rip current, which proposed by Choi et al. (2011, 2012b), was employed and estimated based on Boussinesq modelling. The distribution of likelihood of rip current was evaluated by using various simulations according to scenarios established based on physical quantities(i.e., wave parameters) of buoy-observations. To index the likelihood of rip current, empirical functions were derived based on the distribution and adjusted to observational environments. In this study, the observations from June to September in 2011 at Haeundae beach were applied to the rip-current index functions, and its applications into the real events found based on CCTV images were presented and investigated. In addition, limitations and improvements of the rip-current index function were discussed.

• Korean Journal of Construction Engineering and Management
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• 제20권1호
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• pp.73-85
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• 2019

Since the beginning of a new century, many Korean construction and engineering companies are facing a very dynamic and fast changing business environment which includes severe competition, higher risk, economic depression, declining revenues and profits, etc. In order to cope with these challenges, they need to secure special capabilities to actively adapt to the paradigm changes. One of those capabilities could be project management capability which allows us to manage organizational resources dynamically and integratively based on project portfolio management concept. The objective of this study is to investigate how the dynamic capability of a project-based organization to control the resource affects the firm performance and the competitive advantages. Data was collected from the construction and engineering companies in South Korea by using survey questionnaire, and analyzed for empirical tests by using statistical methods such as structural equation modelling and path analysis. The results showed that the organizational resources, if they had the VRIN characteristics, would have positive impacts on creating the dynamic capabilities for project organization. In turn, the dynamic capabilities of a project organization would have impacts on improving business performance and creating competitive advantages. Also, it was found that the organizational resources may have direct impact on business performance and competitive advantages. The academic contribution of this study is that it attempts to integrate resource based view and the dynamic capability theory about creating competitive advantages for project based organization. This study also provided practical implications to the companies in construction industry by showing how to use organizational resources strategically to create competitive advantages.

• Korean Journal of Remote Sensing
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• 제34권6_2호
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• pp.1261-1272
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• 2018

It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권6A호
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• pp.543-560
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• 2010

Safety-related concrete structures in a nuclear power plant must be protected against the impact of flying objects, referred to in the profession as missiles. In practice, the structural verification is usually carried out by means of empirical formulas, which relate the velocity of the impinging missile to the wall thickness needed to prevent scabbing or perforation. The purpose of this study is to reevaluate the predictability of the local effect prediction formulas for the penetration and scabbing depths and perforation thickness. Therefore, available formulas for predicting the penetration depth, scabbing thickness, and perforation thickness of concrete structures impacted by solid missiles are summarized, reviewed, and compared. A series of impact analyses is performed to predict the local effects of the projectile at impact velocities varing from 95 to 215 m/s. The results obtained from the numerical simulations have been compared with tests that were carried out at Kojima to validate numerical modelling. The simulation results show reasonable agreement with the Kojima test results for the overall impact response of the RC slabs. From these results, it seems that the Degen equation give a very good estimate of perforation thickness against a tornado projectile for test data. Finally, the results obtained from the impact analysis have been compared with Degen formula to determine the perforation thickness of the RC slab.

• The Korean Journal of Applied Statistics
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• 제37권3호
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• pp.339-353
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• 2024

In cases where the response variable in proportional data is confined to a limited interval, a regression model based on the assumption of normality can yield inaccurate results due to issues such as asymmetry and heteroscedasticity. In such cases, the beta regression model can be considered as an alternative. This model reparametrizes the beta distribution in terms of mean and precision parameters, assuming that the response variable follows a beta distribution. This allows for easy consideration of heteroscedasticity in the data. In this paper, we therefore aim to analyze proportional data using the beta regression model in two empirical analyses. Specifically, we investigate the relationship between smoking rates and coffee consumption using data from the 6th National Health Survey, and examine the association between regional characteristics in the U.S. and cumulative mortality rates based on COVID-19 data. In each analysis, we apply the ordinary least squares regression model, the beta regression model, and the extended beta regression model to analyze the data and interpret the results with the selected optimal model. The results demonstrate the appropriateness of applying the beta regression model and its extended version in proportional data.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.157-169
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• 2024

The article presents an analysis of innovative teaching technologies as a way to increase students' competitiveness. The author found that innovative technologies in education are information and communication technologies relying on computer-based learning. The structure, content of educational software, organization of Web-space are important when using innovative teaching technologies in English classes. We conducted the study in several stages: comparative analysis, synthesis, classification and systematization of the results of psychological and pedagogical, educational and methodological research; study of legislative acts, periodicals in order to identify the state of the research issue, and determining the directions of its solution, as well as subject, goal and objectives of the study. We used modelling to create situations of foreign language professional communication of future IT specialists. Empirical methods involved questionnaires used for identifying the motives of professional development and determining the features of the educational activities of future IT specialists in the process of training. The methods of mathematical statistics allowed to scientifically describe and systematize the obtained data, to identify the quantitative relationship between the studied phenomena, to analyse and summarize the results. We conducted a socio-psychological study during 2016 - 2019. It involved 255 first- and fourth-year students of National Technical University of Ukraine "Igor Sikorsky Kyiv Poly-technic Institute." Innovative information and communication technologies that improve the educational and cognitive activity of students, as well as increase the level of their knowledge have become important in teaching a foreign language in higher educational institutions. These technologies include MOODLE - Modular Object-Oriented Dynamic Learning Environment, business game, integrated pedagogical technology, case study technology. Thus, the information-rich learning process in combination with the use of innovative technologies, well-organized e-learning, interactive training courses, multimedia tools improves the program of teaching and learning foreign languages in general, and English in particular, improves the level of knowledge of future IT specialists and motivation to study and learn foreign languages, allows students to use a variety of authentic materials. We state that all these factors influence the process of individualization of learning and contribute to the successful mastery of a foreign language.

• Journal of Technology Innovation
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• 제25권4호
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• pp.107-143
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• 2017

This study aims to understand the impact of internal and external environments and innovation efforts on a company's performance. First, the relationships and patterns between variables were determined through an exploratory factor analysis. Afterwards, a cluster analysis was conducted, in which the influential factors summarized in the factor analysis were classified. Finally, structural equation modeling was used to carry out an empirical analysis of the structural relationship between innovation efforts and the company's performance in the classified clusters. 7 factors were derived from the exploratory factor analysis of 40 input variables from external and internal environments. 4 clusters (n=1,022) were formed based on the 7 factors. Empirical analysis of the 4 clusters using structural equation modelling showed the following: Only independent technology development had a positive impact on the company's performance for Cluster 1, which is characterized by sensitivity to a technological/competitive environment and innovativeness. Only independent technology development and joint research had positive impacts on the company's performance for Cluster 2, which is characterized by sensitivity to a market environment and internal orientation. Joint research and the mediating variable of government support program utilization had positive impacts, while the introduction of technology had a negative impact on the company's performance for Cluster 3, which is characterized by sensitivity to a competitive environment, innovativeness, and willingness to cooperate with the government and related institutions. Independent technology development as well as the mediating variables of network utilization and government support program utilization had positive impacts on the company's performance for Cluster 4, which is characterized by openness and external cooperation.