• Journal of Practical Engineering Education
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• v.7 no.1
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• pp.31-37
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• 2015

Terrestrial digital multimedia broadcasting (TDMB) is a method of bringing multimedia images, radio, internet, and television to portable devices through terrestrial digital radio transmissions. TDMB related educations being carried out in colleges are focusing on developing firmware which enables users to choose a wanted service. TDMB transmission frame is made up of synchronization channel (SC), fast information channel (FIC), and main service channel (MSC). Services such as video, audio and date are transmitted in the form of subchannel in the MSC. FIC carries information related to each services and subchannels. This paper presents a TDMB frame analysis simulator for analyzing and displaying FIC data on PC. TDMB frame analysis simulator contains functions such as controlling TDMB receiver through USB, establishing the frequency, bringing FIC to PC, displaying ensemble ID and levels, and displaying informations related to services and subchannels. In addition to that, this simulator has a function of being able to store FIC date and subchannel data. This simulator being developed with C++ is expected to be used to view those data visually so that it helps students to understand the TDMB system better and bring about the educational motivation.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.22-25
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• 2012

In this paper, we proposed a method of the resonant frequency shift of a microstrip patch antenna using $LiNbO_3$, PVDF and FR-4 substrates. We designed and analyzed from these parametars optimized using Ensemble V 7.0 of the simulation tool. We observed the resonant frequency by DC appled electric field in a microstrip patch antenna. When $LiNbO_3$ substrate were applied from -300 to 300 V/mm, we obtained the resonant frequency shift of maximum 29 MHz. The microstrip patch antenna with PVDF (poly vinylidene fluoride) substrate, we obtained the resonant frequency shift of maximum 17 MHz at frequency 6 GHz. but when Epoxy FR-4 substrates used, the resonant frequency does not changed. This results showed the resonant frequency shift without physical strains in a microstrip patch antenna.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.639-647
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• 2008

This study used the characteristics of the knowledge discovery and data mining algorithms to develop tailored hypertension follow up management model - hypertension care predictive model and hypertension care compliance segmentation model - for hypertension management using the Korea National Health Insurance Corporation database(the insureds’ screening and health care benefit data). This study validated the predictive power of data mining algorithms by comparing the performance of logistic regression, decision tree, and ensemble technique. On the basis of internal and external validation, it was found that the model performance of logistic regression method was the best among the above three techniques on hypertension care predictive model and hypertension care compliance segmentation model was developed by Decision tree analysis. This study produced several factors affecting the outbreak of hypertension using screening. It is considered to be a contributing factor towards the nation’s building of a Hypertension follow up Management System in the near future by bringing forth representative results on the rise and care of hypertension.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.10
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• pp.1417-1426
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• 2001

Turbulent flow characteristics in the near wake of a square cylinder have been studied experimentally by using a Digital PIV method. Experiments are performed at the Reynolds numbers of 1600 and 3900 based on the free-stream velocity and the square height. The ensemble averaged turbulence statistics are acquired from 2030 realizations of instantaneous fluctuating velocity field after the conventional Reynolds decomposition. The differences in turbulent intensity and Reynolds shear stress profiles fur both oases indicate that the effect of Reynolds number seems to be descernible mainly due to the occurrence of transition in the separated shear layer. Because of the periodic nature of vortex shedding process, transverse velocity fluctuations contribute dominantly , to turbulent kinetic energy distribution. A comparison with previous LDV data obtained at much higher Reynolds number shows a fairly good agreement each other. It turns out that the effect of Reynolds number diminishes as increasing Reynolds number, which is a well-known feature of a sharp-edged bluff body wake. The streamwise variation of turbulence intensities are compared with those from a circular cylinder along the centerline at the same Reynolds number. The overall magnitudes and the decay rates of turbulence intensities are quite similar, but some differences are noticeble especially in the transverse intensity variation.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.1-12
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• 2015

The study aimed to project inflows and demmands for the agricultural reservoir watersheds in South Korea considering a variety of regional characteristics and the uncertainty of future climate information. The study bias-corrected and spatially downscaled retrospective daily Global Climate Model (GCM) outputs under Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios using non-parametric quantile mapping method to force Soil and Water Assessment Tool (SWAT) model. Using the historical simulation, the skills of un-calibrated SWAT model (without calibration process) was evaluated for 5 reservoir watersheds (selected as well-monitored representatives). The study then, evaluated the performance of 9 GCMs in reproducing historical upstream inflow and irrigation demand at the five representative reservoirs. Finally future inflows and demands for 58 watersheds were projected using 9 GCMs projections under the two RCP scenarios. We demonstrated that (1) un-calibrated SWAT model is likely applicable to agricultural watershed, (2) the uncertainty of future climate information from different GCMs is significant, (3) multi-model ensemble (MME) shows comparatively resonable skills in reproducing water balances over the study area. The results of projection under the RCP 4.5 and RCP 8.5 scenario generally showed the increase of inflow by 9.4% and 10.8% and demand by 1.4% and 1.7%, respectively. More importantly, the results for different seasons and reservoirs varied considerably in the impacts of climate change.

• Proceeding of EDISON Challenge
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• 2014.03a
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• pp.63-74
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• 2014

Predicting protein loop structures is an important modeling problem since protein loops are often involved in diverse biological functions by participating in enzyme active sites, ligand binding sites, etc. However, loop structure prediction is difficult even when structures of homologous proteins are known due to large sequence and structure variability among loops of homologous proteins. Therefore, an ab initio approach is necessary to solve loop modeling problems. One of the difficulties in the development of ab initio loop modeling method is to derive an accurate scoring function that closely approximates the true free energy function. In particular, entropy as well as energy contribution have to be considered adequately for loops because loops tend to be flexible compared to other parts of protein. In this study, the contribution of conformational entropy is considered in scoring loop conformations by employing "colony energy" which was previously proposed to estimate the free energy for an ensemble of conformations. Loop conformations were generated by using two EDISON_Chem programs GalaxyFill and GalaxySC, and colony energy was designed for this sampling by tuning relevant parameters. On a test set of 40 loops, the accuracy of predicted loop structure improved on average by scoring with the colony energy compared to scoring by energy alone. In addition, high correlation between colony energy and deviation from the native structure suggested that more extensive sampling can further improve the prediction accuracy. In another test on 6 ligand-binding loops that show conformational changes by ligand binding, both ligand-free and ligand-bound states could be identified by using colony energy when no information on the ligand-bound conformation is used.

• Korean Journal of Health Education and Promotion
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• v.23 no.4
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• pp.13-28
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• 2006

Objectives: This study used the characteristics of the knowledge discovery and data mining algorithms to develop hypertension predictive model for hypertension management using the Korea National Health Insurance Corporation database(the insureds' screening and health care benefit data). Methods: This study validated the predictive power of data mining algorithms by comparing the performance of logistic regression, decision tree, and ensemble technique. On the basis of internal and external validation, it was found that the model performance of logistic regression method was the best among the above three techniques. Results: Major results of logistic regression analysis suggested that the probability of hypertension was: - lower for the female(compared with the male)(OR=0.834) - higher for the persons whose ages were 60 or above(compared with below 40)(OR=4.628) - higher for obese persons(compared with normal persons)(OR= 2.103) - higher for the persons with high level of glucose(compared with normal persons)(OR=1.086) - higher for the persons who had family history of hypertension(compared with the persons who had not)(OR=1.512) - higher for the persons who periodically drank alcohol(compared with the persons who did not)$(OR=1.037{\sim}1.291)$ Conclusions: This study produced several factors affecting the outbreak of hypertension using screening. It is considered to be a contributing factor towards the nation's building of a Hypertension Management System in the near future by bringing forth representative results on the rise and care of hypertension.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.289-293
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• 2005

Pattern classification extracts various types of pattern information expressing objects in the real world and decides their class. The top priority of pattern classification technologies is to improve the performance of classification and, for this, many researches have tried various approaches for the last 40 years. Classification methods used in pattern classification include base classifier based on the probabilistic inference of patterns, decision tree, method based on distance function, neural network and clustering but they are not efficient in analyzing a large amount of multi-dimensional data. Thus, there are active researches on multiple classifier systems, which improve the performance of classification by combining problems using a number of mutually compensatory classifiers. The present study identifies problems in previous researches on multiple SVM classifiers, and proposes BORSE, a model that, based on 1:M policy in order to expand SVM to a multiple class classifier, regards each SVM output as a signal with non-linear pattern, trains the neural network for the pattern and combine the final results of classification performance.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.84-90
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• 2010

In this paper, we propose a quadratic discriminant analysis based approach for improving the discriminating strength of weak classifiers based on simple Haar-like features that were used in the Viola-Jones object detection framework. Viola and Jones built a strong classifier using a boosted ensemble of weak classifiers. However, their single threshold (or decision boundary) based weak classifier is sub-optimal and too weak for efficient discrimination between object class and background. A quadratic discriminant analysis based approach is presented which leads to hyper-quadric boundary between the object class and background class, thus realizing multiple thresholds based weak classifiers. Experiments carried out for car detection using 1000 positive and 3000 negative images for training, and 500 positive and 500 negative images for testing show that our method yields higher classification performance with fewer classifiers than single threshold based weak classifiers.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.121-130
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• 2016

An ansemble of N players arranged in a circle play a spatially dependent Parrondo game B. One player is randomly selected to play game B, which is based on the toss of a biased coin, with the amount of the bias depending on states of the selected player's two nearest neighbors. The player wins one unit with heads and loses one unit with tails. In game A' the randomly chosen player transfers one unit of capital to another player who is randomly chosen among N - 1 players. Game A' is fair with respect to the ensemble's total profit. The games are said to exhibit the Parrondo effect if game B is losing and the random mixture game C is winning and the reverse-Parrondo effect if game B is winning and the random mixture game C is losing. We compute the exact mean profits for games B and C by applying a state space reduction method with lumped Markov chains and we sketch the Parrondo and reverse-Parrondo regions for $3{\leq}N{\leq}6$.