• Cartoon and Animation Studies
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• s.28
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• pp.209-233
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• 2012

The animation cluster in Korea has begun as a part of the local cultural cluster in the late 1990s with components of companies, local governments, educational institutions, and human resources, which were necessary to run the cluster. And, the animation cluster was initiated for the purpose of encouraging regional economies, but the basic unit was the local on a small scale. Because of this inherent weakness in the local cluster, it was needed to add some additional strategies that could expand the local animation industry into the formal leading industry. That is why the development policy was set up, and the local promotion agency based on this policy was established. It has been several years to manage the local promotion agency, and it is reported that there have been some visible effects. But, it is found out that analyzing the outcome of small unit cluster on the basis of existing criteria on a large scale is not reliable, which means it is not possible to evaluate the outcome of local cluster in a material way. Some examples of problems are as follows. First, the local cluster was made not autonomously but deliberately. Second, the animation cluster of each province has the same market as its target. Therefore, this research - on the basis of the diamond model - focuses on analyzing the existence and role of local promotion agencies rather than evaluating the outcome itself. Through the cases of two provincial cities, Chuncheon and Bucheon, this research examines if it is possible to evaluate the outcome of local clusters managed by promotion agencies.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• Journal of Korean Academy of Nursing
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• v.20 no.1
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• pp.88-117
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• 1990

The purposes of this study are to delineate a profile of the state of a stroke patient's adaptation at 3 months after hospitalization and to explore the relationship between the level of adaptation and the variables which influence the adaptation of hemiplegic patients. To these ends, theoretical framework was derived basically from the stress adaptation model. The basic assumption underlying the level of adaptation is influenced by the presenting focal, contextual and residual stimuli. This group of stimuli is further operationalized and represented by a perception of stress. which is the perceived effect of the disability and by the mediating variables such as sociodemographic factors as an external conditioning variables and perceived social support and hardiness personality characteristics as an internal intervening variables. The dependent varibales in this study is the level of physical, psychological and social adaptation and is hypothesized to be a function of the interaction between 3 sets of variables namely, the perceived disability effect, external conditioning variables and internal intevening varibles. A total of fourty three subjects from 3 general hospitals in Seoul were observed and interviewed with the aid of 7 structured instruments. The data were collected twice on each subject : first at the pre-discharge period arid at 3 months post-discharge from hospital for the second time. The study was carried out for the period from February to August, 1988. The instruments used for the study include 4 existing scales and 3 scales developed by the researcher for this study. They are : 1) The ADL dependency scale and the scale of the clinical physical functions for the assessment of physical adaptation. 2) the SDS(self report of depression) to measure the level of psychological adaptation. 3) The scale for the amount of social activities for the measurement of the level of social adaptation. 4) The scale for the perceived effect of disability for the measurement of the focal stimuli. 5) The health related hardiness scale and the perceived interpersonal support self evaluation list(ISEL) for the measurement of the hardiness personality character and the perceived social support. The data obtained were analyzed using percentage, oneway ANOVA, Pearson coefficients correlation and stepwise multiple regression. The findings provide valuable information about the present level of physical adaptation at 3 months after discharge. The patient revealed a decreased ADL dependency and lowered limitation of physical function as compared with pre - discharge state. Psycholcgically, the average degree of depression at follow up was within normal range of depression. Socially, the amount of social activities was very low. The one way ANOVA and the correlational analysis revealed the relationship between the 3 sets of variables and the adaptation level as follows : 1) The perceived disability effect was related to the degree of the depression and the amount of social activities but was not related to the physical adaptation. 2) Among the sociodemographic variables, sex and education were related to the difference of ADL dependency and the change of physical function. These factors indicate that women more than men and educated more than the less educated were found more independent. The education was also related to the degree of depression suggesting that the higher the educational level, the more well adapted the patients were both physically and psychologically. Age, marital status and job state were not found to be related to the patient's adaptation level. 3) Among the internal intervening variables, the health related hardiness characteristic was related to the differences of ADL dependency, physical functions and the social activities, indicating that the higher the hardiness character the higher the level of physical and social adaptation. 4) The perceived social support, another internal intervening variable, was related to the degree of depression and the social activities. This data suggest that the higher the perception of social support, the better adapted the patients were psychogically and socially. In summarizing the results of the correlational analysis, the level of physical adaptation was influenced by sex, the years of education and the hardiness character. The level of psychological adaptation was influenced by the years of education, the perceived disability effect and the perceived social support. And the level of social adaptation was influenced by the perceived disability effect, the hardiness character and the perceived social support. The stepwise multiple regression analysis shows findings as follows : 1) The most important factor to explain the difference of ADL dependency was sex, indicating females were more independent than males. 2) The most important factor to explain the difference of physical function and the degree of depression was the patient's education level. 3) The strongest explaining factor for the amount of social activities was perceived self esteem(one of the subconcepts of perceived social support). Thus the most important factors influencing the level of adaptation were found to be sex, education, the hardiness character and self esteem. From the above findings, the significance of this study can be delineated as follows : 1) Corroboration of the assumed relationship between the various variables and the adaptation level as suggested in the conceptual model. 2) Support for the feasibility of the cognitive approach for nursing intervention such as hardness character training, counselling and teaching for self-care in the chronic patients.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.1
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• pp.1-11
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• 2010

The purpose of this paper is to evaluate supply factors of urban parks to answer the research question: What are the causal effects of supply factors of urban parks on visitor satisfaction? After reviewing the literature and the Korean park planning process, we constructed a conceptual framework and have formulated the hypothesis of this research. We had obtained data through a questionnaire, which surveyed 452 visitors at 8 urban parks in Daegu Metropolitan City in 2008, based on a stratified sampling method. After the elimination of 96 unsuitable samples, we have analyzed the data using descriptive statistical methods, Pearson's correlation analysis and a path analysis method. We have found that: 1) While the direct and indirect effect of accessibility(ACC) on visitor satisfaction(VS) turned out to be 0.184 and 0.220, respectively, the indirect effect of information(IFM) and promotion(PRM) on VS turned out to be 0.101 and 0.177, respectively. 2) While the direct and indirect effect of service(SVR) on VS turned out to be 0.130 and 0.236, respectively, the direct effect of ACC turned out to be 0.698. 3) While the direct effect of ACC, SVR and attraction(ATT) on VS turned out to be 0.184, 0.130 and 0.698, respectively, composing 67.96% of causal effect, the indirect effect of ACC, IFM, PRM and SVR on VS turned out to be 0.220, 0.101, 0.177 and 0.236, respectively, composing 42.04% of causal effect. 4) The magnitude of causal effect of supply factors on VS turned out to be ATT(39.98%), ACC(23.14%), SVR(20.96%), PRM(10.14%) and IFM(5.78%) in order, and 5) the causal effect of external supply factors of ACC, IFM and PRM compose 39.06% of the causal effect while that of the internal supply factors of SVR and ATT is 69.94%. The research results suggest that: 1) Planning for park marketing strategy and remedial directions for existing urban parks, in order to increase visitor satisfaction, be focused on IFM and PRM, especially. 2) The research approach and path analysis method adopted by this research be valid and highly useful for planning and evaluation of other recreation areas. It is recommended that: 1) Structural Equation Model on supply factors of urban parks be established in the future. 2) Evaluation of supply factors by type of urban park be performed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.583-590
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• 2015

Submarine cable installation is essentials for grid connection between existing power grid and newly produced electricity which will be from offshore wind farm in Southwest sea area of Korea. Especially, submarine cable route and protection method is designed in order to ensure the economical efficiency, workability and stability of submarine cable installation. On this paper, we will give the basic information about the submarine cable route and protection method of offshore wind farm which will be built in Southwest sea area of Korea. For this, we have a numerical simulation at high and low tide based on the third-generation wave model SWAN(Simulating WAves Nearshore) using the long term wave data from Korea Institute of Ocean Science and Technology(KIOST). The results of the study, year mean Hs is 1.03m, Tz is 4.47s and dominant wave direction is NW and SSW When the incident wave direction is NW(Hs: 7.0 m, Tp: 11.76s), the distribution of shallow water design wave height Hs was calculated about 4.0~5.0m at high tide and 2.0~3.0m at low tide. When the incident wave direction is SSW(Hs: 5.84 m, Tp: 11.15s), the distribution of shallow water design wave height Hs was calculated about 3.5~4.5m at high tide and 1.5~2.5m at low tide. The wave direction on a dominant influence in the section of longitude UTM 249749~251349(about 1.6 km) and UTM 251549~267749(about 16.2 km) in the submarine cable route are each NW and SSW. Prominently, wave focusing phenomenon appears between Wi-do and Hawangdeung-do, in this sea area is showing a relatively high wave hight than the surrounding sea areas.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Journal of Korea Port Economic Association
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• v.36 no.4
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• pp.17-30
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• 2020

In the shipping industry, it is essential to engage in the preemptive prediction of freight rate volatility through market monitoring. Considering that freight rates have already started to fall, the loss of shipping companies will soon be uncontrollable. Therefore, in this study, factors affecting the freight rates of bulk carriers, which have relatively large freight rate volatility as compared to container freight rates, were quantified and analyzed. In doing so, we intended to contribute to future shipping market monitoring. We performed an analysis using a vector error correction model and estimated the influence of six independent variables on the charter rates of bulk carriers by Handy Size, Supramax, Panamax, and Cape Size. The six independent variables included the bulk carrier fleet volume, iron ore traffic volume, ribo interest rate, bunker oil price, and Euro-Dollar exchange rate. The dependent variables were handy size (32,000 DWT) spot charter rates, Supramax 6 T/C average charter rates, Pana Max (75,000 DWT) spot charter, and Cape Size (170,000 DWT) spot charter. The study examined charter rates by size of bulk carriers, which was different from studies on existing specific types of ships or fares in oil tankers and chemical carriers other than bulk carriers. Findings revealed that influencing factors differed for each ship size. The Libo interest rate had a significant effect on all four ship types, and the iron ore traffic volume had a significant effect on three ship types. The Ribo rate showed a negative (-) relationship with Handy Size, Supramax, Panamax, and Cape Size. Iron ore traffic influenced three types of linearity, except for Panamax. The size of shipping companies differed depending on their characteristics. These findings are expected to contribute to the establishment of a management strategy for shipping companies by analyzing the factors influencing changes in the freight rates of charterers, which have a profound effect on the management performance of shipping companies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.51-78
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• 2021

Followed by 'start-up', the theme of 'scale-up' has been considered as an important agenda in both corporate and policy spheres. In particular, although it is a term commonly used in industry and policy fields, even a conceptual definition has not been achieved from the academic perspective. "Corporate Growth" in the academic aspect and "Business Growth" in the practical management field have different understandings (Achtenhagen et al., 2010). Previous research on corporate growth has not departed from Penrose(1959)'s "Firm as a bundle of resources" and "the role of managers". Based on the theory and background of economics, existing research has mainly examined factors that contribute to firms' growth and their growth patterns. Comparatively, we lack knowledge on the firms' growth with a focus on 'annual revenue growth rate'. In the early stage of the firms, they tend to exhibit a high growth rate as it started with a lower level of annual revenue. However, when the firms reach annual revenue of more than 100 billion KRW, a threshold to be classified as a 'middle-standing enterprise' by Korean standards, they are unlikely to reach a high level of revenue growth rate. In our study, we used our sample of 333 companies (6.7% out of 5,000 'fastest-growing' companies) which reached 15% of the compound annual growth rate in the last three years with more than USD 100 million. It shows that sustaining 'high-growth' above a certain firm size is difficult. The study focuses on firms with annual revenue of more than $100 billion (approximately 120 billion KRW) from the 'Inc. 2020 fast-growing companies 5,000' list. The companies have been categorized into 1) Fast-growing companies (revenue CAGR 15%~40% between 2016 and 2019), 2) Hyper-growing companies (40%~99.9%), and 3) Super-growing (100% or more) with in-depth analysis of each group's characteristics. Also, the relationship between the revenue growth rate, individual company's strategy choice (market orientation, generic strategy, growth strategy, pioneer strategy), industry/market environment, and firm age is investigated with a quantitative approach. Through conducting the study, it aims to provide a reference to the 'Hyper-Growing Model' that combines the paths and factors of growth strategies. For policymakers, our study intends to provide a reference to which factors or environmental variables should be considered for 'optimal effective combinations' to promote firms' growth.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.13-29
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• 2021

The purpose of this study was to analyze the spatial distribution and location factors of startups by generation (young and middle-aged) in Seoul. To this end, a research model was established that included factors of industry, population, and startup institutions by generation in 424 administrative districts using the Seoul Business Enterprise Survey(2018), which includes data on the age group of entrepreneurs. As an analysis method, descriptive statistics were conducted to confirm the frequency, average and standard deviation of startups by generation and major variables in the administrative districts of Seoul, and spatial distribution and characteristics of startups by generation were analyzed through global and local spatial autocorrelation analysis. In particular, the spatial distribution of startups in Seoul was confirmed in-depth by categorizing and analyzing startups by major industries. Afterwards, an appropriate spatial regression analysis model was selected through the Lagrange test, and based on this, the location factors affecting startups by generation were analyzed. The main results derived from the research results are as follows. First, there was a significant difference in the spatial distribution of young and middle-aged startups. The young people started to startups in the belt-shaped area that connects Seocho·Gangnam-Yongsan-Mapo-Gangseo, while middle-aged people were relatively active in the southeastern region represented by Seocho, Gangnam, Songpa, and Gangdong. Second, startups by generation in Seoul showed various spatial distributions according to the type of business. In the knowledge high-tech industries(ICT, professional services) in common, Seocho, Gangnam, Mapo, Guro, and Geumcheon were the centers, and the manufacturing industry was focused on existing clusters. On the other hand, in the case of the life service industry, young people were active in startups near universities and cultural centers, while middle-aged people were concentrated on new towns. Third, there was a difference in factors that influenced the startup location of each generation in Seoul. For young people, high-tech industries, universities, cultural capital, and densely populated areas were significant factors for startup, and for middle-aged people, professional service areas, low average age, and the level of concentration of start-up support institutions had a significant influence on startup. Also, these location factors had different influences for each industry. The implications suggested through the study are as follows. First, it is necessary to support systematic startups considering the characteristics of each region, industry, and generation in Seoul. As there are significant differences in startup regions and industries by generation, it is necessary to strengthen a customized startup support system that takes into account these regional and industrial characteristics. Second, in terms of research methods, a follow-up study is needed that comprehensively considers culture and finance at the large districts(Gu) level through data accumulation.