• Analytical Science and Technology
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• v.24 no.6
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• pp.544-555
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• 2011

The acute toxicity in the rainbow trout (Oncorhynchus mykiss) was analyzed and predicted using quantitative structure-activity relationships (QSAR). The aquatic toxicity, 96h $LC_{50}$ (median lethal concentration) of 275 organic pesticides, was obtained from EU-funded project DEMETRA. Prediction models were derived from 558 2D molecular descriptors, calculated in PreADMET. The linear (multiple linear regression) and nonlinear (support vector machine and artificial neural network) learning methods were optimized by taking into account the statistical parameters between the experimental and predicted p$LC_{50}$. After preprocessing, population based forward selection were used to select the best subsets of descriptors in the learning methods including 5-fold cross-validation procedure. The support vector machine model was used as the best model ($R^2_{CV}$=0.677, RMSECV=0.887, MSECV=0.674) and also correctly classified 87% for the training set according to EU regulation criteria. The MLR model could describe the structural characteristics of toxic chemicals and interaction with lipid membrane of fish. All the developed models were validated by 5 fold cross-validation and Y-scrambling test.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.265-274
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• 2020

Free-viewpoint video service is a technology that allows users to watch at any angle, location and distance through interaction. In this paper, the free-viewpoint video services are defined in four viewing modes: Inward view, outward view, 3D object view and first person view. And we developed and implemented a new integrated program that plays all the suggested views. In the contents of girl band performances and basketball games, multi-view cameras suitable for each viewing mode are installed to acquire media, and data stored on the server is streamed over the network, making it available for viewing. Users can freely choose four viewing modes, space location, angle and so on, and the media data such as images and sounds are provided to them by rendering appropriately for the selected the viewpoint. Our system is expected to be a scalable free-viewpoint video service player as well as provide users with immersion and presence by combining various viewing modes.

• 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.