• Journal of the Korean association of regional geographers
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• v.23 no.1
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• pp.118-135
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• 2017

The decline in urban center, changes in the population structure, economic slump and etc. have caused empty or deserted houses in the city. The government recognizes the houses as the reason for the accelerated formation of local slum, and as the negative element threatening the residential environment, urban landscape, social stability and others. This research aims at investigating the spatial distribution of empty or deserted houses in Gwangju metro city, identifying hotspots and classifying those hotspot according to the socioeconomic indicators as well as physical ones, and examining their characteristics and problems in the urban space. The results of this study are as follows. First of all, there is a positive spatial autocorrelation in the spatial distribution of empty and deserted houses in Gwangju metro city. Second, several hotspots are identified mainly around the old CBD area showing a sign of urban decline. Third, the indicators of urban decline were visualized using triangulation charts, and hotspots of empty(deserted) houses are classified so that the classification could serve for effective urban regeneration policy making tailored for each region.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.14-25
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• 2018

The operation of high-speed rail (HSR) has an effect on the agglomeration economies, and the impact is shown as a relocation of individual firm and worker to where business activity can be maximized. The proximity to the HSR station could be considered as a core district to maximize the industrial benefit through the HSR network. From this perspective, this study considers the agglomeration effect of HSR within the HSR station-area and analyzed the agglomerated spatial pattern through hotspot analysis by service industry in the cases of Korea and Japan using GIS. This study analyzed the service industry within 1km distance from 8 HSR stations of Korea and 4 Kyushu Shinkansen stations of Japan. The results suggest that the hotspot patterns are observed in the service industry within 1km distance from the HSR station of Korea and Japan, except for two HSR stations of Gupo station and Kagoshima-Chuo station. Leisure, amusement, association, and other specific service industries could be affected by HSR passengers and knowledge-spillovers through HSR station. Therefore, the observed hotspot districts near the HSR station-area could explain an agglomeration pattern of the service industry through a closeness to the HSR station. Further, we could expect that the impact of HSR affects the service industry, and the impact could attract business activities of the service-area to maximize their benefit from HSR travelers. With the result, it is required to build up a supportive policy to maximize the HSR's impact on the service industry when considering the HSR station-area development.

• Analyses & Alternatives
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• v.6 no.2
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• pp.155-183
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• 2022

The purpose of this study is to econometrically analyze the negative impact of the May 18 Democratic Uprising on the Gwangju/Jeonnam regionional economy using the Synthetic Control Method (SCM). The SCM SCM is a methodology similar to the difference-in-difference(DID) method of microeconometrics. It is applied to macroeconomic variables such as country, region, etc. to estimate the causal relationship between specific events and the dependent variable. In this study, as of 1980, local tax revenue data of metropolitan local governments were used as a proxy variable for the economy of the region, and the impact of the May 18 Democratic Uprising on the economy of Gwangju/Jeonnam region was analyzed through various socio-economic indicators. In this study, data were used to analyze from 1971 to 2000, and as a result of empirical analysis, local tax revenues in Gwangju/Jeonnam area were less collected than normal routes up to 17%. In addition, the significance of this analysis was confirmed through in-time placebo effect analysis and in-space placebo effect analysis, which are methods of analyzing the robustness of the control group synthesis method.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.157-165
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• 2024

The evolution of the Distributed Denial of Service Attack(DDoS Attack) method has increased the difficulty in the detection process. One of the solutions to overcome the problems caused by the limitations of the existing victim-side detection method was the source-side detection technique. However, there was a problem of performance degradation due to network traffic irregularities. In order to solve this problem, research has been conducted to detect attacks using a collaborative network between several nodes based on artificial intelligence. Existing methods have shown limitations, especially in nonlinear traffic environments with high Burstness and jitter. To overcome this problem, this paper presents a collaborative source-side DDoS attack detection technique introduced with an attention mechanism. The proposed method aggregates detection results from multiple sources and assigns weights to each region, and through this, it is possible to effectively detect overall attacks and attacks in specific few areas. In particular, it shows a high detection rate with a low false positive of about 6% and a high detection rate of up to 4.3% in a nonlinear traffic dataset, and it can also confirm improvement in attack detection problems in a small number of regions compared to methods that showed limitations in the existing nonlinear traffic environment.

• Pediatric Infection and Vaccine
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• v.31 no.1
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• pp.55-63
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• 2024

Purpose: A 2-dose varicella vaccination strategy has been introduced in many countries worldwide, aiming to increase vaccine effectiveness (VE) against varicella infection. In this network meta-analysis, we aimed to provide a comprehensive evaluation and an overall estimated effect of varicella vaccination strategies, via a Bayesian model. Methods: For each eligible study, we collected trial characteristics, such as: 1-dose vs. 2-dose, demographic characteristics, and outcomes of interest. For studies involving different doses, we aggregated the data for the same number of doses delivered into one arm. The preventive effect of 1-dose vs. 2-dose of varicella vaccine were evaluated in terms of the odds ratio (OR) and corresponding equal-tailed 95% confidence interval (95% CI). Results: A total of 903 studies were retrieved during our literature search, and 25 interventional or observational studies were selected for the Bayesian network meta-analysis. A total of 49,265 observed individuals were included in this network meta-analysis. Compared to the 0-dose control group, the OR of all varicella infections were 0.087 (95% CI, 0.046-0.164) and 0.310 (95% CI, 0.198-0.484) for 2-doses and one-dose, respectively, which corresponded to VE of 69.0% (95% CI, 51.6-81.2) and VE of 91.3% (95% CI, 83.6-95.4) for 1- and 2-doses, respectively. Conclusions: A 2-dose vaccine strategy was able to significantly reduce varicella burden. The effectiveness of 2-dose vaccination on reducing the risk of infection was demonstrated by sound statistical evidence, which highlights the public health need for a 2-dose vaccine recommendation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.55-73
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• 2024

Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.119-129
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• 2004

This paper is designed to report the results of development and validation procedures in relation to the Freeway Incident Management System (FIMS) prototype development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but the integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Korean freeway system. After through review and analysis of vehicle detection data, the pilot site led to the utilization of different technologies in relation to the specific needs and character of the implementation. This meant that the existing system was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The system validation specifications have identified two component data collection and analysis patterns which were outlined in the validation specifications; the on-line and off-line testing procedural frameworks. The off-line testing was achieved using asynchronous analysis, commonly in conjunction with simulation of device input data to take full advantage of the opportunity to test and calibrate the incident detection algorithms focused on APID, DES, DELOS and McMaster. The simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.76-82
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• 2017

Purpose Whole body bone scan is one of the most frequently performed in nuclear medicine. Basically, both the anterior and posterior views are acquired simultaneously. Occasionally, it is difficult to distinguish the lesion by only the anterior view and the posterior view. In this case, accurate location of the lesion through SPECT / CT or additional static scan images are important. Therefore, in this study, various improvement activities have been carried out in order to enhance the work capacity of technologists. In this study, we investigate the effect of technologist training and standardized work process processes on bone scan error reduction. Materials and Methods Several systems have been introduced in sequence for the application of new processes. The first is the implementation of education and testing with physicians, the second is the classification of patients who are expected to undergo further scanning, introducing a pre-filtration system that allows technologists to check in advance, and finally, The communication system called NMQA is applied. From January, 2014 to December, 2016, we examined the whole body bone scan patients who visited the Department of Nuclear Medicine, Asan Medical Center, Seoul, Korea Results We investigated errors based on the Bone Scan NMQA sent from January 2014 to December 2016. The number of tests in which NMQA was transmitted over the entire bone scan during the survey period was calculated as a percentage. The annual output is 141 cases in 2014, 88 cases in 2015, and 86 cases in 2016. The rate of NMQA has decreased to 0.88% in 2014, 0.53% in 2015 and 0.45% in 2016. Conclusion The incidence of NMQA has decreased since 2014 when the new process was applied. However, we believe that it will be necessary to accumulate data continuously in the future because of insufficient data until statistically confirming its usefulness. This study confirmed the necessity of standardized work and education to improve the quality of Bone Scan image, and it is thought that update is needed for continuous research and interest in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.