• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.6
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• pp.1109-1123
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• 2017

This study analyzed a somatotype of teenager's that was suitable to improve the reality of a virtual model size. We analyzed 843 teenagers 12-18 years old from the 6th Size Korea data. First, factor analysis was done for abstracting new criteria and dividing the somatotype; subsequently, we selected the waist height proportion to stature (body proportion) and drop (torso shape). Next, the cluster analysis was done with these criteria; subsequently, 5 body proportion types and 7 torso shapes were distinguished. A virtual model size for 4 somatotype with more than 50 persons was also designed by a regression analysis that constituted sizes for each factor. The designed model size was compared with body size as well as with Clo's virtual model size. The research model showed a high similarity in sizes with body as well as improved reality over the Clo model that presented size problems such as low waist height, bigger bust, and smaller thigh circumference than the real body.

• Bulletin of the Korean Chemical Society
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• v.19 no.5
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• pp.549-553
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• 1998

The structure and layer distribution of cadmium arachidate Langmuir-Blodgett film were analyzed by the small angle X-ray reflectivity measurements using synchrotron radiation. Y-to X type transition was ocurred during the 39th passage of deposition of cadmium arachidate. Based on the measurement of the consumed area of the monolayer, it was determined that about 27.5 layer was deposited. Using the synchrotron X-ray, the reflectivity profile of cadmium arachidate LB film over the wide range of grazing angle was obtained. The X-ray reflectivity profile was analyzed using the recursion formula. By fitting the location and dispersion of the subsidiary maxima between the Bragg peaks of the measured reflectivity profile with that of the calculated reflectivity profile, the average thickness and the distribution of layer thickness were evaluated. The genetic algorithm was adopted to the fitting of reflectivity profile to evaluate the optimum value of the number distribution of layer. Based on the morphology measurement with an atomic force microscopy (AFM), the domain structure and mean roughness of LB films were obtained. The mean roughness value calculated based on the number of layer distribution obtained from the measurement by AFM is consistent with that obtained from X-ray reflectivity analysis.

• Fisheries and Aquatic Sciences
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• v.1 no.1
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• pp.48-62
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• 1998

Seasonal volume transport on the Texas-Louisiana continental shelf is investigated in terms of objectively fitted transport streamfunction fields based on the current meter data of the Texas­Louisiana Shelf Circulation and Transport Processes Study. Adopted here for the objective mapping is a method employing a two-dimensional truncated Fourier representation of the streamfunction over a domain, with the amplitudes determined by least square fit of the observation. The fitting was done with depth-averaged flow rather than depth-integrated flow to reduce the root-mean-square error. The fitting process filters out $11\%$ of the kinetic energy in the monthly mean transport fields. The shelf-wide pattern of streamfunction fields is similar to that of near-surface velocity fields over the region. The nearshore transport, about 0.1 to 0.3 Sv $(1 Sv= 10^6\;m^3/sec)$, is well correlated with the seasonal signal of along-shelf wind stress. The spring transport is weak compared to other seasons in the inner shelf region. The transport along the shelf break is large and variable. In the southwestern shelf break, transport amounts up to 4.7 Sv, which is associated with the activities of the encroaching of energetic anticyclonic eddies originated in Loop Current of the eastern Gulf of Mexico. The first empirical orthogonal function (EOF) of streamfunction variability contains $67.3\%$ of the variance and shows a simple, shelf-wide, along-shelf pattern of transport. The amplitude evolution of the first EOF is highly correlated (correlation coefficient: 0.88) with the evolution of the along-shelf wind stress. This provides strong evidence that the large portion of seasonal variation of the shelf transport is wind-forced. The second EOF contains $23.7\%$ of the variance and shows eddy activities at the southwestern shelf break. The correlation coefficient between the amplitudes of the second EOF and wind stress is 0.42. We assume that this mode is coupled a periodic inner shelf process with a non-periodic eddy process on the shelf break. The third EOF (accounting for $7.2\% of the variance) shows several cell structures near the shelf break associated with the variability of the Loop Current Eddies. The amplitude time series of the third EOF show little correlation with the along-shelf wind.

• Fashion & Textile Research Journal
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• v.16 no.5
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• pp.811-821
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• 2014

The purposes of this study were to investigate difference on recognition, preference, satisfaction and possession of functional textile clothing in psychological comfort groups according to gender and age of the elderly and suggest optimal physical, mental and healthy functional textiles for the elderly. The data was collected from 262 respondents in their age of over 55, who lived in Busan. SPSS 21.0 was used and t-test, cross tabulation analysis, frequency analysis, and descriptive analysis were performed for analysis. The results are as follows. First, high groups of psychological comfort for both gender and age of the elderly showed higher recognition and preference of functional textiles, especially in the high groups of the new silver generation and women. Second, the high groups of psychological comfort for both gender and age of the elderly showed higher satisfaction of functional textiles. However, it was lower than preference of functional textiles. Last, the possession of major clothing function over all the elderly was comfort, fitting motion adaptability, and health safety function in order. Low groups of psychological comfort possessed fitting motion adaptability textile clothing more than the high groups, and the high groups of psychological comfort possessed comfort and health safety textile clothing more than low groups. In conclusion, this research showed the importance of functional textiles for the elderly in terms of psychological comfort as well as the need for healthy comfort textiles for the advanced activities of daily life.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.41-47
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• 2008

Cluster based fuzzy model tree has certain drawbacks to decrease performance of testinB data when over-fitting of training data exists. To reduce the sensitivity of performance due to over-fitting problem, we proposed a modified cluster based fuzzy model tree with node information. To construct model tree, cluster centers are calculated by fuzzy clustering method using all input and output attributes in advance. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. In the prediction step, membership values are calculated by using fuzzy distance between input attributes and all centers that passing the nodes from root to leaf nodes. Finally, data prediction is performed by the weighted average method with the linear models and fuzzy membership values. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional cluster based fuzzy model tree.

• Journal of the Korean Society of Hazard Mitigation
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• v.2 no.4 s.7
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• pp.123-129
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• 2002

In this study the results of Chungju reservoir inflow forecasting using 3 layered neural network model were analyzed in order to investigate the characteristics of neural network model for reservoir inflow forecasting. The proper neuron numbers of input and hidden layer were proposed after examining the variations of forecasted values according to neuron number and training epoch changes, and the probability of underestimation was judged by deliberating the variation characteristics of forecasting according to the differences between training and forecasting peak inflow magnitudes. In addition, necessary minimum training data size for precise forecasting was proposed. As a result, We confirmed the probability that excessive neuron number and training epoch cause over-fitting and judged that applying $8{\sim}10$ neurons, $1500{\sim}3000$ training epochs might be suitable in the case of Chungju reservoir inflow forecasting. When the peak inflow of training data set was larger than the forecasted one, it was confirmed that the forecasted values could be underestimated. And when the comparative short period training data was applied to neural networks, relatively inaccurate forecasting outputs were resulted and applying more than 600 training data was recommended for more precise forecasting in Chungju reservoir.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.795-805
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• 2019

Recently, there is a growing interest in network anomaly detection technology to tackle unknown attacks. For this purpose, diverse studies using data mining, machine learning, and deep learning have been applied to detect network anomalies. In this paper, we evaluate the decision tree to see its feasibility for network anomaly detection on NSL-KDD data set, which is one of the most popular data mining techniques for classification. In order to handle the over-fitting problem of decision tree, we select 13 features from the original 41 features of the data set using chi-square test, and then model the decision tree using TensorFlow and Scik-Learn, yielding 84% and 70% of binary classification accuracies on the KDDTest+ and KDDTest-21 of NSL-KDD test data set. This result shows 3% and 6% improvements compared to the previous 81% and 64% of binary classification accuracies by decision tree technologies, respectively.

• The Journal of Information Systems
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• v.28 no.3
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• pp.249-276
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• 2019

Purpose The purpose of this study is to develop a prediction model and decision rules for the elderly's suicidal ideation based on the Korean Welfare Panel survey data. By utilizing this data, we obtained many decision rules to predict the elderly's suicide ideation. Design/methodology/approach This study used classification analysis to derive decision rules to predict on the basis of decision tree technique. Weka 3.8 is used as the data mining tool in this study. The decision tree algorithm uses J48, also known as C4.5. In addition, 66.6% of the total data was divided into learning data and verification data. We considered all possible variables based on previous studies in predicting suicidal ideation of the elderly. Finally, 99 variables including the target variable were used. Classification analysis was performed by introducing sampling technique through backward elimination and data balancing. Findings As a result, there were significant differences between the data sets. The selected data sets have different, various decision tree and several rules. Based on the decision tree method, we derived the rules for suicide prevention. The decision tree derives not only the rules for the suicidal ideation of the depressed group, but also the rules for the suicidal ideation of the non-depressed group. In addition, in developing the predictive model, the problem of over-fitting due to the data imbalance phenomenon was directly identified through the application of data balancing. We could conclude that it is necessary to balance the data on the target variables in order to perform the correct classification analysis without over-fitting. In addition, although data balancing is applied, it is shown that performance is not inferior in prediction rate when compared with a biased prediction model.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.249-257
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• 2014

This paper presents methods to the construction of regular and irregular low-density parity-check (LDPC) codes based on Euclidean geometries over the Galois field. Codes constructed by these methods have quasi-cyclic (QC) structure and large girth. By decomposing hyperplanes in Euclidean geometry, the proposed irregular LDPC codes have flexible column/row weights. Therefore, the degree distributions of proposed irregular LDPC codes can be optimized by technologies like the curve fitting in the extrinsic information transfer (EXIT) charts. Simulation results show that the proposed codes perform very well with an iterative decoding over the AWGN channel.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.449-455
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• 2014

This paper presents a method for developing a TM (Traversability Map) from a DTM (Digital Terrain Model) collected by remote sensors of autonomous mobile robots. Such a map can be used to plan traversable paths and estimate navigation speed quantitatively in real time for robots capable of performing autonomous tasks over rough terrain environments. The proposed method consists of three parts: a DTM partition module which divides the DTM into equally spaced patches, a terrain information module which extracts the slope and roughness of the partitioned patches using the curve fitting and the fractal-based triangular prism method, and a traversability analysis module which assesses traversability incorporating with extracted terrain information and fuzzy inference to construct a TM. The potential of the proposed method is validated via simulation works over a set of fractal DTMs.