• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.43-58
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• 2014

As the use of trading systems has increased rapidly, many researchers have become interested in developing effective stock market prediction models using artificial intelligence techniques. Stock market prediction involves multifaceted interactions between market-controlling factors and unknown random processes. A successful stock prediction model achieves the most accurate result from minimum input data with the least complex model. In this research, we develop a combination model of ${\pi}$-fuzzy logic and support vector machine (SVM) models, using a genetic algorithm to optimize the parameters of the SVM and ${\pi}$-fuzzy functions, as well as feature subset selection to improve the performance of stock market prediction. To evaluate the performance of our proposed model, we compare the performance of our model to other comparative models, including the logistic regression, multiple discriminant analysis, classification and regression tree, artificial neural network, SVM, and fuzzy SVM models, with the same data. The results show that our model outperforms all other comparative models in prediction accuracy as well as return on investment.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.99-110
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• 1999

This study deals with the adaptability questions of O-D table estimation models. Its objectives are two-fold; (1) to estimate the characteristics of various O-D table estimation models(i.e. linear regression models. entropy models and statistic models) and (2) to find the model which estimates the O-D table with the best accuracy under the various data conditions. In Pursuing the above, this study gives the particular attentions to the test of the models, using the Sioux Falls network and equilibrium assignment method of MINUTP. The major findings are the followings. Firstly. it finds that the statistic models have the most goodness of fat among all models, if the required data are all Prepared. But it Presents that statistic models are the most sensitive against the underspecification and inconsistency problems of link data. Secondly, It shows that the linear regression models have the worst goodness of fat among all models. But the linear regression models are the most insensitive to the underspecification and inconsistency problems. Thirdly, THE/1 model of entropy model is sensitive against the underspecification and incon-sistency problems, but THE/2 model is insensitive. Finally, other informations like total volume, zonal Production and attraction volumes in 0-D table, help models to gain the better goodness of fit. Especially, in the statistic models. both the zonal production and attraction volume data are helpful to estimate the link volumes. It can be expected that the results dive some implications not only to the selection of optimal model under the various given data, but also to the development or modification of model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.545-551
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• 2018

For domestic application of the temperature gradient model proposed by foreign design standards, a specimen of steel box girder bridge was fabricated with the following dimensions: 2.0 m width, 2.0 m height and 3.0 m length. Temperature was measured using 24 temperature gauges during the summer of 2016. The reliability of the measured data was verified by comparing the measured air temperature with the ambient air temperature of the Korea Meteorological Administration. Of the measured gauges, four temperature gauges that can be compared with the temperature difference of the Euro code were selected and used to analyze the distribution of the measured temperatures at each point. The reference atmospheric temperature for the selection of the maximum temperature difference was determined by considering the standard error. Maximum and minimum temperatures were calculated from the four selected points and the resulting temperature difference was calculated. The model for the temperature difference in the steel box girder bridge was shown by graphing the temperature difference. Compared to the temperature distribution of the Euro code, the presented temperature difference model showed a temperature difference of $0.9^{\circ}C$ at the top and of $0.3^{\circ}$ to $0.4^{\circ}C$ at the intermediate part. These results suggested that the presented model could be considered relatively similar to the Euro code The calculated standard error coefficient was 2.71 to 2.84 times the standard error and represents a range of values. The proposed temperature difference model may be used to generate basic data for calculating the temperature difference in temperature load design.

• Journal of the Korean association of regional geographers
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• v.15 no.2
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• pp.307-315
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• 2009

The purpose of map generalization is a method of map making to transmit the concise cartographic representation and geographic meaning. New generalization algorithm has been developed to be applied in the digital environments by the development of computer cartography. This study aims to look into possibilities of the multiscale mapping by generalization in application with the coordinate transformation and LoD(level of detail) in the web cartography. A method of the coordinate transformation is to improve a transmission of spatial data. Lod is a method which is making web map with selection spatial data by zoom level of users. Layers for test constructed contour line, stream network, the name of a place, a summit of mountain, and administrative office. The generalization was applied to zoom levels by scale for the linear and polygonal features using XML-Based scalable vector graphics(SVG). Resultantly, storage capacity of data was minimized 41% from 9.76mb to 4.08mb in SVG. Generalization of LoD was applied to map elements by stages of the zoom level. In the first stages of zoom level, the main name of places and administrative office, higher order of stream channels, main summit of mountain was represented, and become increase numbers of map elements in the higher levels. Results of this study can help to improve esthetic map and data minimization in web cartography, and also need to make an efforts to research an algorithm on the map generalization over the web.

• The Journal of Korean Medicine
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• v.41 no.2
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• pp.58-79
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• 2020

Objectives: The purpose of this study is to predict the weight loss by applying machine learning using real-world clinical data from overweight and obese adults on weight loss program in 4 Korean Medicine obesity clinics. Methods: From January, 2017 to May, 2019, we collected data from overweight and obese adults (BMI≥23 kg/m2) who registered for a 3-month Gamitaeeumjowi-tang prescription program. Predictive analysis was conducted at the time of three prescriptions, and the expected reduced rate and reduced weight at the next order of prescription were predicted as binary classification (classification benchmark: highest quartile, median, lowest quartile). For the median, further analysis was conducted after using the variable selection method. The data set for each analysis was 25,988 in the first, 6,304 in the second, and 833 in the third. 5-fold cross validation was used to prevent overfitting. Results: Prediction accuracy was increased from 1^st to 2^nd and 3^rd analysis. After selecting the variables based on the median, artificial neural network showed the highest accuracy in 1^st (54.69%), 2^nd (73.52%), and 3^rd (81.88%) prediction analysis based on reduced rate. The prediction performance was additionally confirmed through AUC, Random Forest showed the highest in 1^st (0.640), 2^nd (0.816), and 3^rd (0.939) prediction analysis based on reduced weight. Conclusions: The prediction of weight loss by applying machine learning showed that the accuracy was improved by using the initial weight loss information. There is a possibility that it can be used to screen patients who need intensive intervention when expected weight loss is low.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.286-296
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• 2010

The study of the development of DJ robots is to meet the demands of the music services which are changing very rapidly in the digital and network era. Existing studies, as a whole, develop music services on the premise of personalized environment and equipment, but the DJ robot is on the premise of the open space shared by the public. DJ robot gives priority to traditional space and music. Recently as the hospitality and demand for cultural contents of South Korea expand to worldwide, industrial use of the contents based on traditional or our unique characteristics is getting more and more. Meanwhile, the DJ robot is composed of a combination of two modules. One is to detect changes in the external environment and the other is to set the properties of the music by psychology, emotional engineering, etc. DJ robot detect the footprint of the temperature, humidity, illumination, wind, noise and other environmental factors measured, and will ensure the objectivity of the music source by repeated experiments and verification with human sensibility ergonomics based on Hevner Adjective Circle. DJ robot will change the soundscape of the traditional space being more beautiful and make the revival and prosperity of traditional music with the use of traditional music through BGM.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.746-758
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• 2006

Many objects existing on wide area environments have the replication characteristics according to how to categorize using their own names or properties. From the clients' requests, the existing naming and trading services have not supported with the binding service for replicated solver object with the same service type. For this reason, we present an integrated model that can support the selection of replicated object and dynamic binding services on wide-area computing environments. This model suggests provides not only location management of replicated objects but also active binding service which enables to select a least-loaded object on the system to keep the balance of load between systems. In this purpose, constructing both the service plan and model for support solver object's binding with replication property on wide area computing environments has been researched. In this paper, we showed the test environment and analyzed the performance evaluation of client/server binding procedures via integrated binding service in federation model and verified our model under the condition to see whether load balance can be applied to our model. For the performance evaluation of suggested wide area integrated binding service federation model, evaluated the integrated binding service of each domain and analyzed the performance evaluation of process for non-replication object's under federation model environment. Also, we analyzed the performance evaluation of the federation model between domains for wide area environment. From the execution results, we showed the federation model provides lowers search-cost on the physical tree structure of network.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.63-74
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• 2018

Purpose - The current study is to compare the cognition of stakeholders on hosting a mega sports event between Korea and the United States. In particular, to understand their cognition and perceptual conflict towards hosting a mega sports event, the study employed conflict theory. Furthermore, the study reviewed the role of social capital in the process of managing the mega sports events. Research Design, Data, and Methodology - Of homogeneous sampling, purposeful sampling method and criterion-based selection approach were used to collect interview data from key stakeholders who have been involved in hosting a mega sports events in Korea and the United States. In-depth interview transcripts were reviewed multiple tiems after transcription to extract concepts and meanings that were pertinenet to the experience involving hosting a mega sports event. Further member checks was conducted to increase the credibility of the results. Results - Results can be summarized as followed: First, stakeholders of Korea have a strong desire for positive economic effects of a mega sports event, compared to those in the United States who are more concerned in enhancing the public interests and concerns. Second, in Korea, various socio-political issues emerged at the same time and conflicts among multiple stakeholders have aggravated the situations to coordinate the issues. This was because legal system supporting socio-trust has not been established. On the other hand, major stakeholders of the United States consisted of community members who have socio-trust and networks. Thereby these social resources have been found playing a key role in building social capital that assists the stakeholders to coordinate the current issues and to solve them. Conclusions - The current study analyzed the cognition and perceptual conflict of stakehoders in a mega sports event. Social capital has beend found as a key catalyst to increase a network and cooperation among stakeholders. In order to enhance social capital in managing a mega sports event hosted in Korea, legal systems that establish networks and relationships among the related stakeholders need to be developed. Furthermore, the systematic guideline needs to be developed, organizing the sub-committees according to the types of stakeholders and the categorized common needs.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.403-410
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• 2015

Since 1970, MRI has greatly been developing in terms of strength of magnetic field, the number of receipt channels, and short time of examination. With the development of digital systems and wireless network, hospitals have also acquired, saved, and managed digital images taken by various kinds of medical imaging equipment. However, domestic universities fail to provide practice training course independently thanks to expensive practice equipment and high maintenance cost, and rely on clinical training. Therefore, this study developed a MR patient diagnosis program based on Windows PC to help out students before their working in clinical filed. The designed Relational Database of MRI Simulator is made up of seven tables according to functions and data characteristics. Regarding the designed patient information, each stepwise function was classified by the patient registration method in clinical field. In addition, on the assumption of the basic information for diagnosis, each setting and content were classified. The menu by execution step was arrayed on the left side for easy view. For patient registration, a patient's name, gender, unique ID, birth date, weight, and other types of basic information were entered, and the patient's posture and diagnosis direction were set up. In addition, the body regions for diagnosis and Pulse Sequence were listed for selection. Also, Protocol name and other additional factors were allowed to be entered. The final window was designed to check diagnosis images, patient information, and diagnosis conditions. By learning how to enter patient information and change diagnosis conditions in this program, users will be able to understand more theories and terms learned in practice and thereby to shorten their learning time in actual clinical work.