• IE interfaces
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• v.20 no.4
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• pp.448-457
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• 2007

The small & micro business has the characteristics of both consumer credit risk and business credit risk. In predicting the bankruptcy for small-micro businesses, the problem is that in most cases, the financial data for evaluating business credit risks of small & micro businesses are not available. To alleviate such problem, we propose a bankruptcy prediction mechanism using the credit card sales information available, because most small businesses are member store of some credit card issuers, which is the main purpose of this study. In order to perform this study, we derive some variables and analyze the relationship between good and bad signs. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data for evaluating business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0 multivariate discriminant analysis (MDA), and logistic regression.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.182-183
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• 2018

Big data analysis is the process of discovering a meaningful correlation, pattern, and trends in large data set stored in existing data warehouse management tools and creating new values. In addition, by extracts new value from structured and unstructured data set in big volume means a technology to analyze the results. Most of the methods of Big data analysis technology are data mining, machine learning, natural language processing, pattern recognition, etc. used in existing statistical computer science. Global research institutes have identified Big data as the most notable new technology since 2011.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.369-376
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• 2006

This paper presents a new method of significantly improving conventional Bayesian statistical text classifier by incorporating accelerated EM(Expectation Maximization) algorithm. EM algorithm experiences a slow convergence and performance degrade in its iterative process, especially when real online-textual documents do not follow EM's assumptions. In this study, we propose a new accelerated EM algorithm with uncertainty-based selective sampling, which is simple yet has a fast convergence speed and allow to estimate a more accurate classification model on Naive Bayesian text classifier. Experiments using the popular Reuters-21578 document collection showed that the proposed algorithm effectively improves classification accuracy.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.1
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• pp.65-87
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• 2016

The purpose of this study is to examine Korean journals related to science education in order to analyze research trends into Nature of science in Korea. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, "Nature of science" in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to Word Cloud Analysis the frequency of key words, Centrality Analysis, co-occurrence and Cluster Dendrogram Analysis throughout a variety of research articles. The results show that 91 research papers were published in 25 journals from 1991 to 2015. Specifically, the 2 major journals published more than 50% of the total papers. In relation to research fields., In addition, key phrases, such as 'Analysis', 'recognition', 'lessons', 'science textbook', 'History of Science' and 'influence' are the most frequently used among the research studies. Finally, there are small language networks that appear concurrently as below: [Nature of science - high school student - recognize], [Explicit - lesson - effect], [elementary school - science textbook - analysis]. Research topic have been gradually diversified. However, many studies still put their focus on analysis and research aspects, and there have been little research on the Teaching and learning methods.

• Journal of Korean Neurosurgical Society
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• v.47 no.3
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• pp.191-198
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• 2010

Objective : This study is planned to determine the neurocognitive difficulties of hydrocephalic adults. Methods : The research group contained healthy adults (control group, n : 15), and hydrocephalic adults (n : 15). Hydrocephalic group consisted of patients with idiopathic aquaduct stenosis and post-meningitis hydrocephalus. All patients were followed with shunted hydrocephalus and not gone to shunt revision during last two years. They were chosen from either asymptomatic or had only minor symptoms without motor and sensorineural deficit. A neuropsychological test battery (Raven Standart Progressive Matrices, Bender-Gestalt Test, Cancellation Test, Clock Drawing Test, Facial Recognition Test, Line Orientation Test, Serial Digit Learning Test, Stroop Color Word Interference Test-TBAG Form, Verbal Fluency Test, Verbal Fluency Test, Visual-Aural Digit Span Test-B) was applied to all groups. Results : Neuropsychological assessment of hydrocephalic patients demonstrated that they had poor performance on visual, semantic and working memory, visuoconstructive and frontal functions, reading, attention, motor coordination and executive function of parietal lobe which related with complex and perseverative behaviour. Eventually, these patients had significant impairment on the neurocognitive functions of their frontal, parietal and temporal lobes. On the other hand, the statistical analyses performed on demographic data showed that the aetiology of the hydrocephalus, age, sex and localization of the shunt (frontal or posterior parietal) did not affect the test results. Conclusion : This prospective study showed that adult patients with hydrocephalus have serious neuropsychological problems which might be directly caused by the hydrocephalus; and these problems may cause serious adaptive difficulties in their social, cultural, behavioral and academic life.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.341-346
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• 2011

A vacant technology forecasting is an important issue in management of technology. The forecast of vacant technology leads to the growth of nation and company. So, we need the results of technology developments until now to predict the vacant technology. Patent is an objective thing of the results in research and development of technology. We study a predictive method for forecasting the vacant technology quantitatively using patent data in this paper. We propose an ensemble model that is to vote some clustering criteria because we can't guarantee a model is optimal. Therefore, an objective and accurate forecasting model of vacant technology is researched in our paper. This model combines statistical analysis methods with machine learning algorithms. To verify our performance evaluation objectively, we make experiments using patent documents of diverse technology fields.

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.174-183
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• 2002

In this paper a control chart pattern recognition methodology based on the back propagation algorithm and Multi layer perceptron, a neural computing theory, is presented. This pattern recognition algorithm, suitable for real time statistical process control. evaluates observations routinely collected for control charting to determine whether a Pattern, such as a cycle. trend or shift, which is exists in the data. This approach is promising because of its flexible training and high speed computation with low-end workstation. The artificial neural network methodology is developed utilizing the delta learning rule, sigmoid activation function with two hidden layers. In a computer integrated manufacturing environment, the operator need not routinely monitor the control chart but, rather, can be alerted to patterns by a computer signal generated by the proposed system.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.329-338
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• 2021

This study predicts the amount of wind power generation for rational operation plan of wind power generation and capacity calculation of ESS. For forecasting, we present a method of predicting wind power generation by combining a physical approach and a statistical approach. The factors of wind power generation are analyzed and variables are selected. By collecting historical data of the selected variables, the amount of wind power generation is predicted using deep learning. The model used is a hybrid model that combines a bidirectional long short term memory (LSTM) and a convolution neural network (CNN) algorithm. To compare the prediction performance, this model is compared with the model and the error which consist of the MLP(:Multi Layer Perceptron) algorithm, The results is presented to evaluate the prediction performance.

• International Journal of Knowledge Content Development & Technology
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• v.9 no.2
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• pp.45-64
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• 2019

This study examined the perception and use of web 2.0 applications for academic purposes by medical students of Ambrose Alli University, Ekpoma. The objective was to investigate the medical students' perceptions of web 2.0 applications, web 2.0 tools use, extent of use, perception and purpose for using web 2.0 applications. Descriptive survey method was used for this study. The total population of this study was 3670 and the sample size was 367 representing 10% of the study. The purposive sampling technique was adopted, and the instrument used for this study was questionnaire, a total of 367 copies were administered and 321 were found useful for the study. Percentage means and standard deviation on table and chart were used to analyze the data collected using Statistical Package for the Social Sciences (SPSS) software. Findings showed that the perception of web 2.0 applications of medical students AAU was positive and few of web 2.0 applications were used for academic purposes. It was recommended in the study that medical students should be provided with the facilities in a format more familiar to them and used by most of them and institutions need to equip the learning process with the needed facilities which will be of utmost benefit even for future purposes.

• Journal of Engineering Education Research
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• v.22 no.3
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• pp.32-40
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• 2019

This paper deals with the effects of teamwork competence on problem solving ability through the mediating effect of creative personality for the engineering students. For this purpose, a regression-based statistical mediation analysis has been performed for a simple mediation model in which teamwork competence and problem solving ability were treated as independent and dependent variables respectively, and creative personality was included as a mediation variable. The analysis results showed that the teamwork competence has direct effect on the problem solving ability as well as indirect effect through the creative personality. This result implies that the problem solving ability can be improved directly by improving the teamwork competence, and moreover, it can be further improved indirectly or through the mediation effect by improving the creative personality. Thus, in order to develop excellent problem solving ability, it is necessary to form team members in a balanced way between teamwork competence and creative personality in the team-based learning.