• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.4
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• pp.262-272
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• 2020

A large number of studies on wave breaking have been carried out, and many experimental data have been documented. Moreover, on the basis of various experimental data set, many empirical or semi-empirical formulas based primarily on regression analysis have been proposed to quantitatively estimate wave breaking for engineering applications. However, wave breaking has an inherent variability, which imply that a linear statistical approach such as linear regression analysis might be inadequate. This study presents an alternative nonlinear method using an neural network, one of the machine learning methods, to estimate breaking wave height and breaking depth. The neural network is modeled using Tensorflow, a machine learning open source platform distributed by Google. The neural network is trained by randomly selecting the collected experimental data, and the trained neural network is evaluated using data not used for learning process. The results for wave breaking height and depth predicted by fully trained neural network are more accurate than those obtained by existing empirical formulas. These results show that neural network is an useful tool for the prediction of wave breaking.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.23-34
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• 2017

This study investigated relative explanation of social support, ego-resiliency and stress coping strategies to help adaptive coping style of school-dropout adolescents under stress situation. To this end, 101 school-dropout adolescents were surveyed by visiting and requesting the outofschool youth supporting project, youth detention center, and adolescent protective and treatment facilities in Daejeon, Cheongnam, and Chungbuk. As analysis methods, descriptive statistical analysis, pearson's correlation, and hierarchical analysis were conducted and the research results are as follows. First, stress coping strategies showed positive relationship with social support and ego-resiliency. Second, a variable that showed greater explanation power for stress coping strategies was the environmental variable, the social support. Third, it was identified that there was greater explanation power when the environmental variable, the social support, and the personal variable, the ego-resiliency, were put in at the same time for stress coping strategies. According to the result, this study implies that schools, community, national policy effort and systemetic approach are required as well as improvement of personal coping capabilities in order to overcome difficulties school-dropout adolescents face.

• Journal of Chest Surgery
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• v.36 no.11
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• pp.852-857
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• 2003

Background: Conventional treatment for mesothelioma is largely ineffective. We evaluated the novel approach of adenoviral gene transfection of PTEN gene in mesothelioma cancer cell lines, inflammatory and epithelial subtype, which are sensitive to adenoviral p53. Material and Method: Binary adenoviral PTEN and LacZ (Ad/GT-LacZ and Ad/GV16) vectors were used for transduction of the mesothelioma cell lines, REN (p53 sensitive). Protein levels were determined by Western blotting assay. Apoptosis was assessed by fluorescence-activated cell sorter analysis of subdiploid populations. Cell viability was determined with the XTT assay. Statistical analysis was performed with analysis of variance and the Student t test. Result: 72 hours after the treatment of adenoviral PTEN gene, cell killing were 32.9% for REN compared to control cell (2.5%) at MOI of 20. Also we observed the over-expression of proapoptotic protein, bax and decreased expression of bcl-2 protein in REN cells. But the expression of BCL-xl, Bak, Bad proteins were not altered. Conclusion: Adenovirus Pten-mediated overexpression of the Bax gene induces apoptosis and decreased cellular viability in p53-sensitive mesothelioma cells. These data suggest that the transfection of PTEN gene may represent a alternative gene therapy strategy to treat mesothelioma.

• Korea journal of population studies
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• v.26 no.2
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• pp.111-145
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• 2003

This paper attempts to explore recent socio-demographic changes of the ethnic Korean population in Yanbian autonomous prefecture. Due to rapid decrease in the level of fertility and population ageing, Korean minority society in China has been in a process of profound transition after the introduction of the market economy and establishment of diplomatic relations between South Korea and China. The changes in demographic behaviors and in the structure of population appear to be much faster among Koreans than Hans. Results from the 2000 population census reveal that the Korean population in Yanbian, where ethnic Koreans are most densely populated in China, has been in a decreasing trends in absolute numbers and in its proportion to the total population. The growing tendency of regional mobility for work and for marriage, rapid expansion of residential areas, serious crisis of ethnic schools of Korean community, and weakening social integration and ethnic identification of Koreans in Yanbian are discussed in this study. It is expected that socio-demographic transition of Korean society in Yanbian will be even more drastic over the coming decades. The rapid changes in demographic behaviors and in the structure of population has major consequences and implications for every sphere of human life, and will present enormous challenges for the status of Korean minority society in China. Along with various statistical data on Yanbian, micro-level data as well as published reports from the 1990 Chinese population census for Yanbian and the 2000 Chinese population census are analyzed in this study. In addition to sex ratios and age ratios, various indices are calculated to analyze the characteristics and accuracy of the data from the 1990 and 2000 population censuses of China.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Fire Science and Engineering
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• v.33 no.5
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• pp.94-102
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• 2019

As the importance of first responses for fire accidents has grown in the safety management of nuclear power plants, a systematic approach to measure firefighters' psychological states and competence is needed. The current study investigated the construct of the risk perception of the firefighters working near nuclear power plant sites, and then developed and validated a new scale to measure firefighters' risk perception regarding nuclear power plant accidents. The scale items were developed on the basis of literature review and interviews with the firefighters working near nuclear power plant sites. In order to validate the new scale, we recruited 180 firefighters from five fire stations in the vicinity of the nuclear power plants in Jeonnam Province, Gyeongbuk Province, and Busan. The results of exploratory factor analyses revealed that the scale consisted of five factors: "manual" reflecting a lack of response guidelines and manuals for fire incidents and radioactive material release; "fear" reflecting a fear of fire incidents in the nuclear power plants and their catastrophic consequences; "resource" reflecting a lack of protective equipment and manpower for responding to fire incidents in the nuclear power plants; "trust" reflecting trust and cooperation with the counterpart institutions for firefighting in the nuclear power plants; and "knowledge" reflecting the knowledge of radioactivity and firefighting in the nuclear power plants. Further analyses provided statistical evidence supporting for the 15-item scale's internal consistency and construct validity. Finally, We discussed the implication and limitations of the current research.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1249-1263
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• 2013

In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.395-408
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• 2020

This paper aims to develop and apply three different machine learning approaches (i.e., artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and wavelet-based neural networks (WNN)) combined with an evolutionary optimization algorithm and the k-fold cross validation for multi-step (days) streamflow forecasting at the catchment located in Algeria, North Africa. The ANN and ANFIS models yielded similar performances, based on four different statistical indices (i.e., root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), correlation coefficient (R), and peak flow criteria (PFC)) for training and testing phases. The values of RMSE and PFC for the WNN model (e.g., RMSE = 8.590 ㎥/sec, PFC = 0.252 for (t+1) day, testing phase) were lower than those of ANN (e.g., RMSE = 19.120 ㎥/sec, PFC = 0.446 for (t+1) day, testing phase) and ANFIS (e.g., RMSE = 18.520 ㎥/sec, PFC = 0.444 for (t+1) day, testing phase) models, while the values of NSE and R for WNN model were higher than those of ANNs and ANFIS models. Therefore, the new approach can be a robust tool for multi-step (days) streamflow forecasting in the Seybous River, Algeria.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.49-57
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• 2012

Recently as the user experience's importance has been emphasized, there has been many tries of various research methodology in order to understand the user. Specially, as the political investigation method's user understanding method based on the statistical analysis so far has encountered a limit, there has been a continuous tendency to try to introduce a humanitarian or cultural anthropological methodology. As part of this effort, there has been many tries of various approach methods of the Ethnography which is the cultural anthropological typical research methodology, but among those the Diary Study Method is mentioned as one of the effective methodologies. Therefore this thesis applies the Diary Study Method to the notebook PC bundle SW's attitude research and tries a deep rooted research about the user attitude. Also centered to the project of understanding the notebook PC bundle SW's user receptivity. it shows a specific example of the Diary Study applied to the user understanding. Through this process, we will examine the summary about the Ethnography research method, and will discuss an effective research methodology by through the process of analyzing and deducting the user inclination by applying and designing the Diary Study to the project. That is to say, it was progressed by actually applying the research methodology through a specific case, with the purpose of breaking away from the textbook discussion and progress with an application aspect discussion. Through the current research, we will verify an active user-inclined process about the user's notebook PC SW, and it is expected to be useful in establishing a SW UX strategy and distribution related to the bundle software.