• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.212-222
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• 2020

The purpose of this study is to understand the current status and trends of the research studies published by the Society for Industrial and Applied Mathematics which is a leader in the field of industrial mathematics around the world. To perform this purpose, titles and abstracts were collected from 6,255 research articles between 2016 and 2019, and the R program was used to analyze the topic modeling model with LDA techniques and a regression model. As the results of analyses, first, a variety of studies have been studied in the fields of industrial mathematics, such as algebra, discrete mathematics, geometry, topological mathematics, probability and statistics. Second, it was found that the ascending research subjects were fluid mechanics, graph theory, and stochastic differential equations, and the descending research subjects were computational theory and classical geometry. The results of the study, based on the understanding of the overall flows and changes of the intellectual structure in the fields of industrial mathematics, are expected to provide researchers in the field with implications of the future direction of research and how to build an industrial mathematics curriculum that reflects the zeitgeist in the field of education.

• KIEAE Journal
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• v.13 no.6
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• pp.129-136
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• 2013

The rental housing has played a key role to supply a decent living space for the low-income households. The owner of the rental housing should maintain and manage the building physical condition. On the other hand, rents should use the housing without any damage and pay a certain fare for the rent. A rent is classified into two types : private and public. The public rent is mainly to supply a living space for non-available home owner with a low-rent fare. Many of public rent are built and supplied by the public institution or local government. The supplier would take a responsibility to maintain the building and components, reflected by the maintenance plan and repair scope. In this paper, it aimed at providing the repair time in building components of the public rental housing such as lighting, electrical cable, paintings and etc.. The repair time is analyzed with three calculation methods which are solved by the probability and empirical approach. Results are as follows : First, the repair time of the electrical facilities are maintained with 11yr, 10yr and 7 in permanent, public and redevelopment rent respectively. The roof proof has a repair time with 14yr, 11yr and 8 in permanent, public and redevelopment rent housing respectively. Second, Most of the components has a prior length of the repair time in permanent, public and redevelopment rent sequently. There is a difference in repair time according to the rental types. Therefore, it would continue to research the difference in aspect of the living style, building physics, living consciousness and etc.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1249-1263
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• 2009

The power function in sample size determination has to be characterized by an appropriate statistical test for the hypothesis of interest. Nonparametric tests are suitable in the analysis of ordinal data or frequency data with ordered categories which appear frequently in the biomedical research literature. In this paper, we study sample size calculation methods for the Wilcoxon-Mann-Whitney test for one- and two-dimensional ordinal outcomes. While the sample size formula for the univariate outcome which is based on the variances of the test statistic under both null and alternative hypothesis perform well, this formula requires additional information on probability estimates that appear in the variance of the test statistic under alternative hypothesis, and the values of these probabilities are generally unknown. We study the advantages and disadvantages of different sample size formulas with simulations. Sample sizes are calculated for the two-dimensional ordinal outcomes of efficacy and safety, for which bivariate Wilcoxon-Mann-Whitney test is appropriate than the multivariate parametric test.

• Journal of Trauma and Injury
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• v.28 no.4
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• pp.248-255
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• 2015

Purpose: study of the mutual influence of the individual anatomical regions damage in patients associated with falls from heights. Methods: 561 medical reports of patients associated with falls from heights admitted to Republican Research Center of Emergency Medicine (RRCEM), in period of 2010-2013 yy, were analyzed retrospectively. Patient's age range was from 15 to 89. Treatment of these patients held in three stages: period of acute disorders of vital functions; relative stabilization period; stabilization of vital functions. The scope and content of medical diagnostic procedures performed on pre-hospital and intensive care stages. The severity of each injury was scored according to the AIS scale, the total severity of lesions was scored by points due to ISS. Digital material is treated by methods of mathematical statistics. Results: Falls from heights leads to associated injuries for 4 times more than isolated trauma, and increases according to height of fall and falling surface. Patients with TBI+chest trauma, are most serious contingent that has highest mortality and complications (36.8%). TBI+musculoskeletal system trauma are characterized by high blood loss, traumatic shock and fat embolism, forming a vicious circle. Conclusion: in patients associated with falls from heights clinical manifestations of injuries mutual aggravation syndrome will be seen. TBI leads to complication of chest trauma, delayed diagnostics of abdominal and chest trauma, aggravation of coma condition. Developing of high blood loss and fat embolism in musculoskeletal system trauma leads to shock and pulmonary embolism, which increases probability of death in the presence of abdominal or chest trauma, but abdominal trauma or chest trauma has no significant effect on the severity of the musculoskeletal system trauma.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.4 s.334
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• pp.15-20
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• 2005

Multi-Input, Multi-Output system suffers for the spatial channel correlation due to lack of spatial diversity. To overcome this defect, the antenna selection and switching system is proposed which selects the adequate antenna subset with highest channel diversity gain and switches the trasmission techniques according to channel environments. However. its performance analysis is insufficient due to the difficulty of modeling the spatial channel correlation. In this paper, the theoretical upper bound of symbol error probability is derived by using the statistical properties of Frobenius norm and minimum eigen-value of channel matrix. By computer simulation, it is shown that the derived theoretical upper bound is similar to the simulation results.

• The Journal of Korean Association of Computer Education
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• v.16 no.5
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• pp.9-16
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• 2013

Computational thinking is an ability to resolve problems that may be applied to the various real world problems and is regarded as the core of computer science. Computational thinking may be improved through experiences of analyzing problems and of selecting, applying, and modeling strategies appropriate for problem-solving. In order to enhance computational thinking of learners, it is important to provide experiences of solving various problems. This study designed puzzle based learning in order to educate learners principles of problem solving, let them have experiences of interest and insight, and provide them with problem solving experiences. The puzzle questions used for learning were classified into six types - constraints, optimization, probability, statistics, pattern recognition, and strategies. These questions were applied to Informatics gifted elementary students and, after their education, their computational thinking and problem solving inventory significantly improved.

• Journal of IKEEE
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• v.18 no.1
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• pp.45-56
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• 2014

Recently, damages from disasters such as downpours, earthquakes and typhoons are increasing throughout the world. The downpour days of Korean Peninsula are also increasing every year due to rapid climate change. According to statistics over the last 30 years of the earthquakes in Korean Peninsula, the probability of a future earthquake is very high. In addition, super typhoons will hit Korean Peninsula due to the temperature rise in the nearby sea caused by the deepening of global warming. Thus, damage costs of the waterfront structures by natural disasters are also growing. But damage information system for integrated management of waterfront structures are insufficient. In this paper, we designed and implemented a damage information system for integrated management of waterfront structures. First, we classified damage information caused by natural disaster. Then we designed the databases of damage information and implemented damage information system. Lastly, we checked operations and the feasibility by testing queries on the proposed system.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.891-899
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• 2010

Association rule is the technique to represent the relationship between two or more items by numerical representing for the relevance of each item in vast amounts of databases, and is most being used in data mining. The basic thresholds for association rule are support, confidence, and lift. these are used to generate the association rules. We need standardization of lift because the range of lift value is different from that of support and confidence. And also we need standardization of support and confidence to compare objectively association level of antecedent variables for one descendant variable. In this paper we propose a method for standardization of association thresholds considering marginal probability for each item to grasp objectively and exactly association level, check the conditions for association criteria and then compare association thresholds with standardized association thresholds using some concrete examples.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.853-861
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• 2010

Experimental conditions are set with environmental factors which can affect ship navigation. In FTS simulation, infinite simulation can be theoretically tested with no time constraint but the simulated result with the same experimental condition is repeated due to mathematical model. RTS simulation can give more resonable results but costs at lest 30 minutes for only experimental time. The mixture of two simulation methods using probability density function has been proposed: some of experimental conditions in which ship-handling is most difficult are selected with FTS and are tested in RTS. It has drawback that it does not consider the navigation route but aggregated track index. In this paper, anomaly detection approach is suggested to select some experimental conditions of FTS simulation which are most difficult in ship-handling during the navigation route. An empirical result has been shown.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.61.1-61.1
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• 2017

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT $195{\AA}$, and $304{\AA}$ from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We consider other input images which consist of last two images and their difference image. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the over-fitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). All statistical parameters do not strongly depend on the number of input data sets. Our model can immediately be applied to automatic forecasting service when image data are available.