• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.451-464
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• 2022

The high-level nuclear waste repository is a deep geological disposal system exposed to complex environmental conditions such as high temperature, radiation, and ground-water due to handling spent nuclear fuel. Continuous exposure can lead to cracking and deterioration of the structure over time. On the other hand, the high-level nuclear waste repository requires an ultra-long life expectancy. Thus long-term structural health monitoring is essential. Various sensors such as an accelerometer, earth pressure gauge, and displacement meter can be used to monitor the health of a structure, and a piezoelectric sensor is generally used. Therefore, it is necessary to develop a highly durable sensor based on the durability assessment of the piezoelectric sensor. This study designed an accelerated life test for durability assessment and life prediction of the piezoelectric sensor. Based on the literature review, the number of accelerated stress levels for a single stress factor, and the number of samples for each level were selected. The failure mode and mechanism of the piezoelectric sensor that can occur in the environmental conditions of the high-level waste repository were analyzed. In addition, two methods were proposed to investigate the maximum harsh condition for the temperature stress factor. The reliable operating limit of the piezoelectric sensor was derived, and a reasonable accelerated stress level was set for the accelerated life test. The suggested methods contain economical and practical ideas and can be widely used in designing accelerated life tests of piezoelectric sensors.

• Composites Research
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• v.35 no.4
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• pp.248-254
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• 2022

In this study, TiB₂-steel composite with high-fractional TiB₂ reinforcement was fabricated by gas pressure infiltration process and the microstructure analysis and compressive strength and hardness were evaluated. To elucidate the correlation between microstructure and mechanical properties for fabricated composite, after the compression test of TiB₂-steel composite, the fracture surface was analyzed and the fracture behavior on compression test was predicted. As a result of the compression fracture surface analysis, interfacial failure trace between the steel matrix and the reinforcement was observed, and the interface between the steel matrix and the reinforcement was analyzed using TEM. From the result of microstructure analysis on the fabricated composite, it was confirmed that, in addition to TiB₂ reinforcement and steel matrix, TiC phase and coarse (Fe,M)₂B (M=Cr,Mn) phase were formed. Throughout the thermodynamic calculation, it was confirmed that TiC and (Fe,M)₂B can be formed as a stable phase under the process condition. The fabricated TiB₂-steel composite had a significantly increased hardness, and the compressive strength and Young's modulus were improved by 3.07 times and 1.95 times, respectively, compared to steel matrix. It seems that the coarse (Fe,M)₂B (M=Cr,Mn) phase formed throughout the composite causes the deterioration of mechanical properties, and by controlling the formation of the (Fe,M)₂B (M=Cr,Mn) phase, it is judged that the mechanical properties of the TiB₂-steel composite can be further improved.

• Tuberculosis and Respiratory Diseases
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• v.47 no.3
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• pp.321-330
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• 1999

Background : Early diagnosis and proper antibiotic treatment are very important in the management of ventilator-associated pneumonia (VAP) because of its high mortality. Bronchoscopy with a protected specimen brush (PSB) has been considered the standard method to isolate the causative organisms of VAP. However, this method burdens consumer economically to purchase a PSB. Another useful method for the diagnosis of VAP is quantitative cultures of aspirated specimens through bronchoscopic bronchoalveolar lavage (BAL), for which the infusion of more than 120 m1 of saline has been recommended for adequate sampling of a pulmonary segment. However, occasionally it leads to deterioration of the patient's condition. We studied the diagnostic efficacy of minibronchoalveolar lavage (miniBAL), which retrieves only 25 ml of BAL fluid, in the isolation of causative organisms of VAP. Methods: We included 38 consecutive patients (41 cases) suspected of having VAP on the basis of clinical evidence, who had received antibiotics before the bronchoscopy. The two diagnostic techniques of PSB and miniBAL, which were performed one after another at the same pulmonary segment, 'were compared prospectively. The cut-off values for quantitative cultures to define causative bacteria of VAP were more than $10^3$ colony-forming units (cfu)/ml for PSB and more than $10^4$ cfu/ml for BAL. Results: The amount of instilled normal saline required to retrieve 25 ml of BAL fluid was $93{\pm}32 ml$ (mean${\pm}$SD). The detection rate of causative agents was 46.3% (19/41) with PSB and 43.9% (18/41) with miniBAL. The concordance rate of PSB and miniBAL in the bacterial culture was 85.4% (35/41). Although arterial blood oxygen saturation dropped significantly (p<0.05) during ($92{\pm}10%$) and 10 min after ($95{\pm}3%$) miniBAL compared with the baseline ($97{\pm}3%$), all except 3 cases were within normal ranges. The significantly elevated heart rate during ($l25{\pm}24$/min, p<0.05) miniBAL compared with the baseline ($1l1{\pm}22$/min) recovered again in 10 min after ($111{\pm}26$/min) miniBAL. Transient hypotension was developed during the procedure in two cases. The procedure was stopped in one case due to atrial flutter. Conclusion: MiniBAL is a safe and effective technique to detect the causative organisms of VAP.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47
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• pp.15-32
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• 2002

The endeavors enhancing the grain quality of high-yielding japonica rice were steadily continued during 1980s-1990s along with the self-sufficiency of rice production and the increasing demands of high-quality rices. During this time, considerably great progress and success was obtained in development of high-quality japonica cultivars and quality evaluation techniques including the elucidation of interrelationship between the physicochemical properties of rice grain and the physical or palatability components of cooked rice. In 1990s, some high-quality japonica rice cultivars and special rices adaptable for food processing such as large kernel, chalky endosperm, aromatic and colored rices were developed and its objective preference and utility was also examined by a palatability meter, rapid-visco analyzer and texture analyzer, Recently, new special rices such as extremely low-amylose dull or opaque non-glutinous endosperm mutants were developed. Also, a high-lysine rice variety was developed for higher nutritional utility. The water uptake rate and the maximum water absorption ratio showed significantly negative correlations with the K/Mg ratio and alkali digestion value(ADV) of milled rice. The rice materials showing the higher amount of hot water absorption exhibited the larger volume expansion of cooked rice. The harder rices with lower moisture content revealed the higher rate of water uptake at twenty minutes after soaking and the higher ratio of maximum water uptake under the room temperature condition. These water uptake characteristics were not associated with the protein and amylose contents of milled rice and the palatability of cooked rice. The water/rice ratio (in w/w basis) for optimum cooking was averaged to 1.52 in dry milled rices (12% wet basis) with varietal range from 1.45 to 1.61 and the expansion ratio of milled rice after proper boiling was average to 2.63(in v/v basis). The major physicochemical components of rice grain associated with the palatability of cooked rice were examined using japonica rice materials showing narrow varietal variation in grain size and shape, alkali digestibility, gel consistency, amylose and protein contents, but considerable difference in appearance and texture of cooked rice. The glossiness or gross palatability score of cooked rice were closely associated with the peak, hot paste and consistency viscosities of viscosities with year difference. The high-quality rice variety "IIpumbyeo" showed less portion of amylose on the outer layer of milled rice grain and less and slower change in iodine blue value of extracted paste during twenty minutes of boiling. This highly palatable rice also exhibited very fine net structure in outer layer and fine-spongy and well-swollen shape of gelatinized starch granules in inner layer and core of cooked rice kernel compared with the poor palatable rice through image of scanning electronic microscope. Gross sensory score of cooked rice could be estimated by multiple linear regression formula, deduced from relationship between rice quality components mentioned above and eating quality of cooked rice, with high probability of determination. The $\alpha$-amylose-iodine method was adopted for checking the varietal difference in retrogradation of cooked rice. The rice cultivars revealing the relatively slow retrogradation in aged cooked rice were IIpumbyeo, Chucheongyeo, Sasanishiki, Jinbubyeo and Koshihikari. A Tonsil-type rice, Taebaegbyeo, and a japonica cultivar, Seomjinbyeo, showed the relatively fast deterioration of cooked rice. Generally, the better rice cultivars in eating quality of cooked rice showed less retrogradation and much sponginess in cooled cooked rice. Also, the rice varieties exhibiting less retrogradation in cooled cooked rice revealed higher hot viscosity and lower cool viscosity of rice flour in amylogram. The sponginess of cooled cooked rice was closely associated with magnesium content and volume expansion of cooked rice. The hardness-changed ratio of cooked rice by cooling was negatively correlated with solids amount extracted during boiling and volume expansion of cooked rice. The major physicochemical properties of rice grain closely related to the palatability of cooked rice may be directly or indirectly associated with the retrogradation characteristics of cooked rice. The softer gel consistency and lower amylose content in milled rice revealed the higher ratio of popped rice and larger bulk density of popping. The stronger hardness of rice grain showed relatively higher ratio of popping and the more chalky or less translucent rice exhibited the lower ratio of intact popped brown rice. The potassium and magnesium contents of milled rice were negatively associated with gross score of noodle making mixed with wheat flour in half and the better rice for noodle making revealed relatively less amount of solid extraction during boiling. The more volume expansion of batters for making brown rice bread resulted the better loaf formation and more springiness in rice breed. The higher protein rices produced relatively the more moist white rice bread. The springiness of rice bread was also significantly correlated with high amylose content and hard gel consistency. The completely chalky and large grain rices showed better suitability far fermentation and brewing. The glutinous rice were classified into nine different varietal groups based on various physicochemical and structural characteristics of endosperm. There was some close associations among these grain properties and large varietal difference in suitability to various traditional food processing. Our breeding efforts on improvement of rice quality for high palatability and processing utility or value-adding products in the future should focus on not only continuous enhancement of marketing and eating qualities but also the diversification in morphological, physicochemical and nutritional characteristics of rice grain suitable for processing various value-added rice foods.ice foods.