• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.6
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• pp.568-583
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• 2015

In this paper, the conceptual design procedure and results of Earth observation satellite through Multidisciplinary Design Optimization (MDO) are described. The conceptual design equations for major parameters are developed based on the established database of Earth observation satellite so far. The MDO conceptual design tool for Earth observation satellite was developed by applying the Collaborative Optimization (CO) architecture amongst several MDO architecture techniques available today. The objective for this research was set to minimize the total mass of satellite as well as satisfy all design constraints by utilizing the Sequential Quadratic Programming (SQP) algorithm. Eventually the effectiveness of MDO conceptual design tool was verified through proposing a comparison between the conceptual design results with MDO applied and the design specification of ASNARO-1 & IKONOS-2 Earth observation satellite.

• Journal of Biomedical Engineering Research
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• v.37 no.2
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• pp.61-67
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• 2016

This paper presented a method for random forest based the arrhythmia classification using both heart rate (HR) and heart rate variability (HRV) features. We analyzed the MIT-BIH arrhythmia database which contains half-hour ECG recorded from 48 subjects. This study included not only the linear features but also non-linear features for the improvement of classification performance. We classified abnormal ECG using mean_NN (mean of heart rate), SD1/SD2 (geometrical feature of poincare HRV plot), SE (spectral entropy), pNN100 (percentage of a heart rate longer than 100 ms) affecting accurate classification among combined of linear and nonlinear features. We compared our proposed method with Neural Networks to evaluate the accuracy of the algorithm. When we used the features extracted from the HRV as an input variable for classifier, random forest used only the most contributed variable for classification unlike the neural networks. The characteristics of random forest enable the dimensionality reduction of the input variables, increase a efficiency of classifier and can be obtained faster, 11.1% higher accuracy than the neural networks.

• Journal of Society of Preventive Korean Medicine
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• v.17 no.1
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• pp.1-11
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• 2013

Objectives : The aim of this research is to produce information by gathering up the data on the interaction between medicinal herbs which lie scattered in oriental medical books, and to provide people with easy access to the information by visualizing it. Methods : For this purpose, this study established the fundamental data by organizing the patterns of interaction into some kinds after selecting a part of Bonchogangmok(本草綱目) and extracting its text. In addition, in an effort to visualize the data, the study converted the data into 'net' file and visualized the interaction between medicinal herbs on Pajek. The visualization was done targeting a total of three patterns, such as 1 medicinal herb, 2 medicinal herbs, and 1 prescription. With the data on 'Chinese Lacquer(乾漆)' for 1 medicinal herb, data on 'Licorice(甘草)' and 'Chinese Lacquer(乾漆)' for 2 medicinal herbs, and data on 'Iijin-tang(二陳湯)' for prescription, the research conducted the analysis of the network using 'Kamada-Kawaii Algorithm' on Pajek. Results : As a result of the analysis, it was possible to see the meanings at a single glance as the scattered and fractional meanings were integrated with focus on medicinal herbs, but the increasing number of analyzed medicinal herbs tended to more and more complicate their relationships, thus, requiring additional work like filtering. Conclusions : Such results are fairly applicable in on-line database, and it is judged that if further research expands its scope to include systematic classification of medicinal herbs or cover other medical books than Bonchogangmok, it will create more objective, abundant information.

• Journal of the Korean Society of Food Culture
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• v.29 no.6
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• pp.659-667
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• 2014

Fruits are good sources of vitamins, minerals, fiber, and phytochemicals, which are known to reduce serum lipids, oxidative damage, and blood pressure as well as improve blood glucose control. The purpose of this study was to estimate nutrient quality indices of fruits by carrying out a critical analysis of pre-existing methods according to their nutritional compositions. Four methods were used to assess the nutrient indices of 26 fruits, which are frequently consumed by Koreans based on the fourth Korean National Health and Nutrition Examination Survey (2009). Naturally nutrient rich score (NNR), nutrient rich food (NRF), nutrient adequacy score (NAS), and nutrient density score (NDS) were used to calculate nutrient quality indices. The Korean Nutrition Society Food Composition database of fruits based on 100 g edible portions was used. The algorithm of each method included the mean percentage of daily values (Dietary Reference Intakes for Koreans, 2010) for particular nutrients based on consumption of 1,900 kcal/day. The relative score indicated that strawberries, kumquat, and lemon had high nutrient quality indices. In addition, mango, lemon, persimmon, strawberry, apricot, and tangerine fruits are rich in antioxidant nutrients such as ${\beta}$-carotene, vitamin C, vitamin E, and selenium. However, scores of nutrient quality indices did not imply that higher scores of particular fruits are superior. We suggest moderate seasonable consumption a variety of fruits. Our results can be used as a reference for consumers when they choose fruits.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.2
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• pp.209-218
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• 1994

This study aims to generate triangulated irregular network in a form of digital terrain model which is being increasingly used. In general, grid digital elevation model and triangulated irregular network are reasonable units for solving terrain problems. But, triangulated irregular network is an efficient alternative to grid digital elevation model because of their efficiency in storing data and their convenient data structure for accommodating irregularly spaced elevation data. Various methods represented for extracting triangulated irregular networks from grid digital elevation model, and then algorithm that get accurate results for triangulation with their data set was introduced. The new approach for triangulation in this study uses the Elevation and Changeable Distance criterion, and adding interpolation points and restricted constraint lines can generate triangulated irregular network which is more close to real surface. This made database efficient construction and could be used for many applications of geo-spatial information system.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.115-131
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• 2008

Small mobile devices have become commonplace in our everyday life, from cellular phones to PDAs. Discovering dense regions for the mobile devices is one of the problems of grate practical importance. It can be used in monitoring movement of vehicles, concentration of troops, etc. In this paper, we propose a novel algorithm on continuously clustering a large set of mobile objects. We assume that a mobile object reports its position only if it is too far away from the expected position and thus the location data received may be imprecise. To compute the location of each individual object could be costly especially when the number of objects is large. To reduce the complexity of the computation, we want to first cluster objects that are in proximity into a group and treat the members in a group indistinguishable. Each individual object will be examined only when the inaccuracy causes ambiguity in the final results. We conduct extensive experiments on various data sets and analyze the sensitivity and scalability of our algorithms.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1147-1155
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• 2005

This paper deals with Iris recognition as one of biometric techniques which is applied to identify a person using his/her behavior or congenital characteristics. The Iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D Iris pattern having a property of size invariant and using the fuzzy LDA which is further through four types of 2D Gabor wavelet. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use four different matching values obtained from four different directional Gabor wavelet and select the maximum value, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 300 Iris Patterns extracted from 50 subjects and finally got more higher than $90\%$ recognition rate.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.389-395
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• 2007

Collaborative filtering is a popular technique for information filtering to reduce information overload and widely used in application such as recommender system in the E-commerce domain. Collaborative filtering systems collect human ratings and provide Predictions based on the ratings of other people who share the same tastes. The quality of predictions depends on the number of items which are commonly rated by people. Therefore, it is difficult to apply pure collaborative filtering algorithm directly to dynamic collections where items are constantly added or removed. In this paper we suggest a method for managing dynamic collections. It creates taste space for items using a technique called Singular Vector Decomposition (SVD) and maintains clusters of core items on the space to estimate relevance of past and future items. To evaluate the proposed method, we divide database of user ratings into those of old and new items and analyze predicted ratings of the latter. And we experimentally show our method is efficiently applied to dynamic collections.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.13-21
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• 2011

In mobile environment supporting mobility technologies, user requirements have been increased with respect to utilization of location information. In particular, moving object DBMS has consistently posed in order to efficiently maintain traffic information related to location of vehicle which tents to tremendously change over time. Despite the fact that these sorts of researches must be taken into consideration, empirical studies on moving object in terms of map database for lbs service, spatial attribute of which is continuously changed over time, have rarely performed. Therefore, aim of this paper is to suggest efficient spatial index scheme, which is capable of supporting query processing algorithm and location of moving object over time, by developing new empirical model. As a result, we can come to the conclusion that moving object model based on multi-fixed grid index makes it possible to cut down on the number of entity for retrieving. What's more, this model enables hierarchical data to be accessed through efficient spatial filtering on large-scale lbs data and constraints in accordance with level in order to display map.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.367-376
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• 2015

Today, big data has become a hot keyword in that big data may be defined as collection of data sets so huge and complex that it becomes difficult to process by traditional methods. Clustering method is to identify the information in a big database by assigning a set of objects into the clusters so that the objects in the same cluster are more similar to each other clusters. The similarity measures being used in the cluster analysis may be classified into various types depending on the nature of the data. In this paper, we computed upper and lower limits for probability interestingness measure based similarity measures without marginal probability such as Yule I and II, Michael, Digby, Baulieu, and Dispersion measure. And we compared these measures by real data and simulated experiment. By Warrens (2008), Coefficients with the same quantities in the numerator and denominator, that are bounded, and are close to each other in the ordering, are likely to be more similar. Thus, results on bounds provide means of classifying various measures. Also, knowing which coefficients are similar provides insight into the stability of a given algorithm.