• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.275-283
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• 2022

This study aims to investigate the influence of internal factors on the bankruptcy risk of an enterprise through a sample of 439 companies listed on the Vietnamese stock exchange. The research collected secondary data from annual audited financial statements from 2008 to 2019 of listing companies. Using two different regression models with two dependent variables, six independent and control variables, we discovered that three of the model's six factors, namely return on total assets, current payment rate, and financial leverage, influence the risk of bankruptcy and account for 86.78% of the variations in firm bankruptcy risk. Financial leverage has the opposite effect on the Z-score index, increasing the risk of bankruptcy of listed firms. Return on total assets and current ratio have a positive impact on the Z-score index, reducing the risk of bankruptcy of listed companies. The findings also revealed that there is no evidence that the size of a corporation, its fixed asset investment ratio, or the size of an auditing firm have an impact on the Z-score index. These findings provide crucial evidence for business owners and managers, as well as shareholders making future capital investment decisions. Our findings can be applied to other businesses in Vietnam and similar jurisdictions.

• The Journal of Industrial Distribution & Business
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• v.9 no.11
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• pp.39-54
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• 2018

Purpose - To success, in spite of deficient resources, a start-up company has to check various circumstances. Many researchers proposed different appraisal methods for technology commercialization. But everybody agrees Merrifield is the first one, who is a pioneer of an appraisal model of technology commercialization. After he proposed it, many researchers and field workers developed a more complicated model, which called a BMO model. In this research, considering the circumstances of start-ups that lack available resources, it proposes a new appraisal method for technology commercialization, which is named a weighted-BMO model. Research design, data, and methology - For the new BMO-model, it studied the preceding studies. And it found that the success factors for start-ups were correlated with technology commercialization. After comparing the success factors for technology commercialization of start-ups with BMO appraisal factor, it withdraws the net BMO appraisal model: which we are calling the weighted-BMO model. Results - This study found a few things. First, actually, the BMO appraisal factors related with the success factors of technology commercialization. Second, the weighted-BMO model, which included the entrepreneur ability factor, was more accurately estimated the success of technology-based start-ups than the BMO model. Third, it overcame the weakness of the BMO-model, which did not include quantitative factors. In addition to evaluating the feasibility of the BMO model, we also presented a strategy for the future direction. But, still, it included a few shortcomings, which we are calling the arbitrage of weighted value. Sometimes, the intentional weighted value can deliberate the different valuation. Conclusitons - Due to this study, the weighted-BMO model included appraisal factors related with the success factors of technology commercialization and the entrepreneur ability factor, and quantitative factors. When evaluating the combined score of the existing Merrified BMO components, 35 points of the first pass criterion accounted for 29.17% of the total score, and 80 points of the merit score of the second rank criterion were 66.67% Considering that the weighted sum is taken into account, the baseline score of the weighted summing method for each component of the modified BMO model is 2.92 points, which is 29.17% of the weighted sum total of 10 points. The evaluation score was 6.67 points, 66.67% of the weighted total score of 10 points.

• Journal of Korea Multimedia Society
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• v.23 no.4
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• pp.595-602
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• 2020

We propose a generative probabilistic model with Dirichlet prior distribution for topic modeling and text similarity analysis. It assigns a topic and calculates text correlation between documents within a corpus. It also provides posterior probabilities that are assigned to each topic of a document based on the prior distribution in the corpus. We then present a Gibbs sampling algorithm for inference about the posterior distribution and compute text correlation among 50 abstracts from the papers published by IEEE. We also conduct a supervised learning to set a benchmark that justifies the performance of the LDA (Latent Dirichlet Allocation). The experiments show that the accuracy for topic assignment to a certain document is 76% for LDA. The results for supervised learning show the accuracy of 61%, the precision of 93% and the f1-score of 96%. A discussion for experimental results indicates a thorough justification based on probabilities, distributions, evaluation metrics and correlation coefficients with respect to topic assignment.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.1-8
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• 2021

Detecting Out-of-Distribution (OOD) data is fundamentally required when Deep Neural Network (DNN) is applied to real-world AI such as autonomous driving. However, modern DNNs are quite vulnerable to the over-confidence problem even if the test data are far away from the trained data distribution. To solve the problem, this paper proposes a novel Adversarial-Mixup training method to let the DNN model be more robust by detecting OOD data effectively. Experimental results show that the proposed Adversarial-Mixup method improves the overall performance of OOD detection by 78% comparing with the State-of-the-Art methods. Furthermore, we show that the proposed method can alleviate the over-confidence problem by reducing the confidence score of OOD data than the previous methods, resulting in more reliable and robust DNNs.

• KIEAE Journal
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• v.17 no.2
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• pp.45-51
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• 2017

Purpose: Housing is the most essential element for well-being in a society. The government would continuously supply decent housings to make a better living condition for people. As various housing policies have been implemented into practice, the effectiveness of policies need to be assessed and improved to rearrange the financial resources. The indicators, such as quality of life, housing supply amount and etc, could be used to estimate housing policy to provide a guidance for a new policy direction. Though various indicators are utilized to assess the policy effect, most of the items are depend upon a relativeness in aspect to assessment goal, items, time and its weighting. Therefore, it needs an absolute indicator to compare the policy effectiveness regardless of time elapse or items. In this paper, it developed the housing welfare indicator to assess the level of living condition, utilizing the Gini coefficient which is used for explanation on income distribution. Method: To suggest an inequity indicator, this paper used Gini coefficient to explain the level of living condition which is used on economics to provide the level of income distribution. Data are collected through the Korea Housing Survey by Ministry of Land, Infrastructure and Transport between 2006 and 2014. Indicators of living condition focused on the development of the estimation model using the frequency of room use. Result: Gini coefficient between 2004 and 2014 is about 1.5 score except in year 2013, and the trend of score has been decreased slowly which means the inequality gradually improved. In this result, it implies the living condition and distribution level would be improved than before.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.277-286
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• 2012

For credit assessment models, the ROC curves evaluate the classification performance using two univariate cumulative distribution functions of the false positive rate and true positive rate. In this paper, it is extended to two bivariate normal distribution functions of default and non-default borrowers; in addition, the bivariate ROC curves are proposed to represent the joint cumulative distribution functions by making use of the linear function that passes though the mean vectors of two score random variables. We explore the classification performance based on these ROC curves obtained from various bivariate normal distributions, and analyze with the corresponding AUROC. The optimal threshold could be derived from the bivariate ROC curve using many well known classification criteria and it is possible to establish an optimal cut-off criteria of bivariate mixture distribution functions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.301-301
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• 1993

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.419-437
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• 1995

Given the specific mean shift outlier model, several standard approaches to obtaining test statistic for outliers are discussed. Each of these is developed in detail for the nonlinear regression model, and each leads to an equivalent distribution. The geometric interpretations of the statistics and accuracy of linear approximation are also presented.

• Journal of The Korean Association For Science Education
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• v.14 no.2
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• pp.225-235
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• 1994

Concidering environmental education as an ultimate resolution for environmental problems, we conducted a study focusing on affective matters. An instrument was developed to evaluate attitudes of elementary and middle school students toward environmental problems. To develop a reliable Likert-type evaluation instrument scale with which emotional intensity could be judged, mean, standard deviation, response frequency distribution, discrimination index, reliability were calculated. As a result, 21 statements for recognition level and 14 statements for behavioral level were made(The Cronbach alpha coefficient of the instrument was .786). This instrument was used to evaluate 5th and 6th grade elementary school students and 1st and 2nd grade middle school students(total number of subjects was 980). The result of this survey can be summarized as follows. 1. Students recognized the seriousness of environmental problems but they did not behave in such a manner as to prevent it. 2. As a result of t-test, behavioral level score of elemenatary school students was significantly higher than that of middle school students(p<.001). 3. This study showed that there was a significant correlation between the recognition level score and the behavioral level score(r=.386, p<.001). 4. Two-Way ANOVA was used to analyze that there was any significant difference according to grade and sex. The results were as follows. (1) No significant difference was found in total score. (2) On recognition level, female students' score was signigicantly higher than that of male students(p<.01). (3) On behavioral level, higher-grade students' score was lower than that of lower-grade-students (p<.001).

• Journal of Korean Home Economics Education Association
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• v.12 no.3
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• pp.105-114
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• 2000

The purpose of this study was to investigate the effects of instructional multi-media in Home Economics Education perceived by teachers. The data for this research were attained from 139 middle & high school teachers of Home Economics. The data were analyzed by frequency of distribution, mean, stand deviation. t-test and analysis of variance, scheffe test with SPSSWin 7.5 program. The results of this study are as follows: The effects of instructional multi-media were composed of four dimensions in this study; need, frequency of use, pros and cons. 1. From these four dimensions, the need has the highest and the frequency of use has the lowest score. 2. The effects of instructional multi-media are significantly related to personal & environmental characteristics. 1)Need of the instructional multi-media effects is significantly different according to age, experience of computer education and possession of a computer at home. Low and high age groups are higher in the need of the instructional multi-media effects score than middle group age and the more experience of computer education and possession of a computer at home are higher in that score. 2) Frequency of use is significantly different according to LAN system in school. The higher score of frequency of use is in a LAN system’s school. 3) Pros of the instructional multi-media effects is significantly different according to the level of education, experience of computer education and the type of school. Undergraduate high school teachers and the lower o experience of computer education are higher in the pros of the instructional multi-media effects score. 4) Cons of the instructional multi-media effects is significantly different according to the level of education. Graduate teachers are higher in the cons of the instructional multi-media effects score.