• Journal of Korea Technology Innovation Society
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• v.10 no.2
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• pp.183-205
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• 2007

An investigation was undertaken of the optimal discriminant model for predicting the likelihood of insolvency in advance for medium-sized firms based on the technology evaluation. The explanatory variables included in the discriminant model were selected by both factor analysis and discriminant analysis using stepwise selection method. Five explanatory variables were selected in factor analysis in terms of explanatory ratio and communality. Six explanatory variables were selected in stepwise discriminant analysis. The effectiveness of linear discriminant model and logistic discriminant model were assessed by the criteria of the critical probability and correct classification rate. Result showed that both model had similar correct classification rate and the linear discriminant model was preferred to the logistic discriminant model in terms of criteria of the critical probability In case of the linear discriminant model with critical probability of 0.5, the total-group correct classification rate was 70.4% and correct classification rates of insolvent and solvent groups were 73.4% and 69.5% respectively. Correct classification rate is an estimate of the probability that the estimated discriminant function will correctly classify the present sample. However, the actual correct classification rate is an estimate of the probability that the estimated discriminant function will correctly classify a future observation. Unfortunately, the correct classification rate underestimates the actual correct classification rate because the data set used to estimate the discriminant function is also used to evaluate them. The cross-validation method were used to estimate the bias of the correct classification rate. According to the results the estimated bias were 2.9% and the predicted actual correct classification rate was 67.5%. And a threshold value is set to establish an in-doubt category. Results of linear discriminant model can be applied for the technology financing banks to evaluate the possibility of insolvency and give the ranking of the firms applied.

• Korean Journal of Community Nutrition
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• v.5 no.4
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• pp.586-597
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• 2000

The nutrition knowledge and food attitude of obese children were assessed and compared with their normal children counterparts to provide information for nutrition education programs. One hundred forty six obese children and 92 normal children from the fourth to sixth grade in Bucheon and Anyang elementary schools of Kyeong-gi Province were selected for the study. A multiple choice questionnaire, including 12 items of general nutrition knowledge and 13 items of weight control, were used to test the nutrition knowledge of children. The results of this study are as follows : 1) 57.5% of male and 40.9% of female obese children had experience with weight control, but the rate of correct answers on the nutrition knowledge test ranged from 53% to 58%, which does not show any significant difference between the two groups. The rate of correct answers on items conrerning 'general nutrition knowledge' and 'nutrition knowledge for weight control' did not show any significant difference among the two groups. 2) Obese male students showed a higher rate of correct answers(59.2%) on items of 'the proper food selection for obese children', compared with their counterparts and also obese female students showed a higher rate of correct answers(88.6%) on 'physical exercise', compared with their counterparts. 3) The rate of correct answers on nutrition knowledge of 'basic food groups', 'the functions of iron and vitamins', 'the concept of energy', and 'the principle of weight change' were lower than 40%. 4) The obese children frequently did not have breakfast, overate during lunch in many cases, and had low recognition on knowledge that was necessary to weight control. 5) Only 30.9% and 22.7% of male and female obese children replied that they would participate in weight control programs. However, 53.6% of males and 68.2% of females did not show any concern in participating the programs. From these results, it was suggested that it is necessary to motivate the obese to participate in weight-control program. When developing nutrition education programs for the obese, the contents of the questions that showed a low correct answering rates should be emphasized.

• The Journal of Korean Medicine
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• v.28 no.2 s.70
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• pp.22-33
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• 2007

Uterine myoma is a benign tumor of smooth muscle in the uterine wall. Recently, in Oriental medicine, concerns about uterine myoma patients have increased. We analyzed the medical records for 944 patients, including 257 uterine myoma patients, who visited Dongeui University Oriental Medical Center from May 2001 to June 2006. We investigated the DSOM (Diagnosis System of Oriental Medicine) symptom scores which effect uterine myoma patients using stepwise logistic regression model. Logistic regression analysis indicated as follows: In the control group composed of 558 outpatients, 18 items of DSOM were associated with myoma, 9 positively and 9 negatively, and the results showed that the correct rate was equal to 81.1%, sensitivity 72.8%, and specificity 84.9%. In 129 clinical trials data, 33 items of DSOM were associated with myoma, 18 positively and 15 negatively, and the results showed that the correct rate was equal to 85.8%, sensitivity 84.8%, and specificity 87.6%. In 687 outpatient and clinical trials data, 18 items of DSOM were associated with myoma, 10 positively and 8 negatively, and the results showed that the correct rate was equal to 82.8%, sensitivity 70.8%, and specificity 87.3%.

• Communications of Mathematical Education
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• v.32 no.3
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• pp.435-453
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• 2018

The results analysis of National Assessment of Educational Achievement(NAEA) can provide various implications for teaching and learning in the school field. In this study we analyzed the deviation of NAEA achievement level-based correct-answer rate and the distribution of the responses percentages for three years from 2015 to 2017 focused on multiple-choice items. First we calculated the deviation of correct-answer rate between advanced level and proficient level and between proficient level and basic level, and then we selected the items whose deviation of correct-answer rate is more than the third quartile. We explored what the content areas, behavior areas and achievement standards of each item are and what the achievement standards and characteristics of these questions are. Based on the results of the analysis, we intended to derive implications for appropriate teaching-learning methods at each achievement-level.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.171-176
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• 2023

This study is about a speech recognition error correction system designed to detect and correct speech recognition errors before natural language processing to increase the success rate of intent analysis in natural language processing with optimal efficiency in various service domains. An encoder is constructed to embedded the correct speech token and one or more error speech tokens corresponding to the correct speech token so that they are all located in a dense vector space for each correct token with similar vector values. One or more utterance tokens within a preset Manhattan distance based on the correct utterance token in the dense vector space for each embedded correct utterance token are detected through an error detector, and the correct answer closest to the detected error utterance token is based on the Manhattan distance. Errors are corrected by extracting the utterance token as the correct answer.

• Journal of the Korean Society of Safety
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• v.25 no.4
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• pp.90-95
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• 2010

This study deals with the accident model of arterial link section in Cheongju. The objective is to develop the accident model of arterial link section using the logistic regression. In pursuing the above, the study uses the 258 accident data occurred at the 322 arterial link section. The main results are as follows. First, Nagellerke $R^2$ of developed accident model is analyzed to be 0.309 and t-values of variable that explains goodness of fit are evaluated to be significant. Second, the variables adopted in the model are AADT, the number of exit and entry. These variables are all analyzed to be statistically significant. Finally, the analysis of correct classification rate shows that the total accident of correct classification rate is analyzed to be 72.7% at the arterial link section.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.1
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• pp.95-108
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• 2022

Purpose - This study attempts a multifaceted analysis utilizing the Chinese test takers' results of the Economy & Business Aptitude Test. Since Chinese students study socialist theories of economics along with market-based ones, comparing Chinese university students' basic knowledge of economics and business and its application to those of Korean test takers is also very meaningful from the perspective of economics education research. Research design, data, and methodology - This study investigates the results on the test of economy and business understanding between Korea and China. For comparison of the result, we conducted MK-TEST for two universities in China. Result - This study finds that the average correct answer rate of Korea is higher than one of China according to the overall results. The average difference rate is about 15% between Korea and China. More concretely, the correct answer rate of business area is higher than one of economy area, identifying them by subject area. Conclusion - According to the results, this study can infer that there are no or little differences in the ability of examinee to solve applied questions between Korea and China and the differences of the scope and emphasis point in an academic curriculum between both countries might bring these kinds of results. Finally, Chinese students shows higher correct answer rate to the questions about the economy issues and policies related to China than one of Korea examinee.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.173-182
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• 1996

In this paper, we propose the parallel, self-organizing, hierarchical neural netowrks as a handwritten digit recognition system. This system can absorb the various shape variations of handwritten digits by using the different methods of extracting the features in each stage neural network (SNN) of the PSHNN, and can reduce training time by using the single layer neural network as the SNN, and can obtain high rate of correct recognition by using the certainty area in all the output nodes individually. experiments have been performed with NIST database. In which we use 21, 315 digits (10, 625 digits for training and 10,663 digits for testing). The results show that the correct rate is 97.48% the error rate is 1.72% and the reject rate is 0.78%.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.148-158
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• 2012

In the world, the flow of globalization are causing that many cities in the world are trying to enhance city awareness and city image through the establishment of their identity. Seoul has also preceded various studies in order to establish its identity of the urban landscape in this flow. But, most of studies have only considered some of the problems of the urban landscape and its improvement. Therefore, a study to understand the current built urban landscape and its own identity has not been studied yet. In this study, we propose an analyzing and visualizing framework of the urban landscape through an internet survey using the compare contents based on the differences in Cognition and recognition. The core of the framework which analyses the differences in Cognitions and recognition about the urban landscape was performed by the correct and clear rate. In addition, it was extracted from the answers of the survey and the visualization, was performed by diagrams of accuracy rate that was derived from the correlation between the correct rate and the clear rate.