• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.15-30
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• 2005

The increasing amount of structures presenting distress due to reinforcement corrosion is urging the establishment of more accurate calculation methods for the service life of concrete structures. In the present paper, a summary of the different approaches is presented that are able to calculate the expected life of new structures, in certain aggressive environments or the residual life of already corroding structures. The methods for the initiation period are based on the proper calculation of the carbonation front or chloride penetration and on the steel corrosion rate. The methods for the residual load-bearing capacity calculations are based in the use of ' indicators ' or in the evaluation of the reduced section and a structural recalculation.

• Journal of Technology Innovation
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• v.22 no.2
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• pp.185-220
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• 2014

The purpose of this study is to get a whole picture of financial conditions of the new and renewable energy sector which have been growing rapidly and predict bankruptcy risk quantitatively. There have been many researches on the methodologies for company failure prediction, such as financial ratios as predictors of failure, analysis of corporate governance, risk factors and survival analysis, and others. The research method for this study is Altman Z-score which has been widely used in the world. Data Set was composed of 121 companies with financial statements from KIS-Value. Covering period for the analysis of the data set is from the year 2006 to 2011. As a result of this study, we found that 38 percent of the data set belongs to "Distress" Zone (on alert) while 38% (on watch), summed into 76%, whose level could be interpreted to doubt about the sustainability. The average of the SMEs in wind energy sector was worse than that of SMEs in solar energy sector. And the average of the SMEs in the "Distress" Zone (on alert) was worse than that of the companies of large group in the "Distress" Zone (on alert). In conclusion, Altman Z-score was well proved to be effective for New & Renewable Energy Industry in Korea as a result of this study. The importance of this study lies on the result to demonstrate empirically that the majority of solar and wind enterprises are facing the risk of bankruptcy. And it is also meaningful to have studied the relationship between SMEs and large companies in addition to advancing research on new start-up companies.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.109-123
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• 2004

Corporate financial distress and bankruptcy prediction is one of the major application areas of artificial neural networks (ANNs) in finance and management. ANNs have showed high prediction performance in this area, but sometimes are confronted with inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large because training the large data set needs much processing time and additional costs of collecting data. Instance selection is one of popular methods for dimensionality reduction and is directly related to data reduction. Although some researchers have addressed the need for instance selection in instance-based learning algorithms, there is little research on instance selection for ANN. This study proposes a genetic algorithm (GA) approach to instance selection in ANN for bankruptcy prediction. In this study, we use ANN supported by the GA to optimize the connection weights between layers and select relevant instances. It is expected that the globally evolved weights mitigate the well-known limitations of gradient descent algorithm of backpropagation algorithm. In addition, genetically selected instances will shorten the learning time and enhance prediction performance. This study will compare the proposed model with other major data mining techniques. Experimental results show that the GA approach is a promising method for instance selection in ANN.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.3
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• pp.670-676
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• 2009

Bankruptcy of firms in Korea can cause distress of financial institutions because these institutions have disterssed bond. Accordingly, social and economical spill-over effects by these results are very big. Even after the difficult times of IMF crisis had ended, bankruptcy of information-based small-medium companies and venture firms listed on the KOSDAQ has been continued. In this context, this study developed and adopted failure prediction models for which discriminant analysis was used. Samples of this study was 81 firms respectively for both failed and non-failed firms listed on the KOSDAQ between the year of 2000 and 2007. The results of this study are as follows. First, the accuracy of classification of the model by years was $74.5%{\sim}76.5%$, and the accuracy of classification of the mean model was $69.6%{\sim}80.4%$. Among the models, the mean model of -one year, -two years, and -three years was highest in accuracy of classification (80.4%). Second, accuracy of prediction of final model adopted on validation samples showed 85% before one year of bankruptcy. The results of this study may be significant in that the results may be used as early warning system for bankruptcy prediction of KOSDAQ firms.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.1
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• pp.42-48
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• 1999

Three experiments were conducted to develop and test equations for predicting carcass composition. In the first study using 52 d-old Cobb ${\times}$ Cobb male broilers, twenty four carcasses were selected from 325 processed birds based upon visual appraisal for abdominal fat (low, medium, high) and assayed for specific gravity (SG), dry matter (DM), fat, protein, and ash. In experiment 2, 120 birds were fed rations containing 2 caloric densities (2,880 and $3,200kcal\;ME_n/kg$ diet) and assayed as described above on weeks 2,3,4,5, and 6. Carcass fat was elevated (p < 0.05) with increased caloric density. In both studies predictive variables were significantly correlated with chemically determined carcass fat, protein, and ash contents. Pooled across the 2 studies, data were used to form SG, DM, and or age based equations for predicting carcass composition. Results were tested in experiment 3, where 576 birds reared to 49-d consumed either 2,880, 3,200, or $3,574kcal\;ME_n/kg$ diet while exposed to constant $24^{\circ}C$ or cycling 24 to $35^{\circ}C$ ambient temperatures. Both dietary and environmental effects impacted (p < 0.05) carcass composition. The fat content analyzed chemically was enhanced from 12.4 to 15.7%, and predicted fat was also elevated from 13.4 to 14.8% with increasing caloric density. Heat distress reduced (p < 0.05) analyzed carcass protein (18.9 vs 18.3%) and predicted protein (18.2 vs 17.5%). Predicted equation values for carcass fat, protein, ash, and energy were correlated with the chemically analyzed values at r=0.96, 0.77, 0.86, and 0.79, respectively. Results suggest that prediction equations based on DM and SG may be used to estimate carcass fat, protein, ash, and energy contents of broilers consuming diets that differ in caloric density (2,800 to $3,574kcal\;ME_n/kg$) and for broilers exposed to either constant ($24^{\circ}C$) or cycling high (24 to $35^{\circ}C$) ambient temperatures during 49-d rearing period tested in the present study.

• Journal of Distribution Science
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• v.16 no.11
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• pp.21-27
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• 2018

Purpose - This study investigates the financial ratio of savings banks and the effect of the ratio having influence upon bankruptcy by quantitative empirical analysis of forecast model to give material of better management and objective evidence of management strategy and way of advancement and risk control. Research design, data, and methodology - The author added two growth indexes, three fluidity indexes, five profitability indexes, and four activity indexes CAMEL rating to not only the balance sheets but also the income statement of thirty savings banks that suspended business from 2011 to 2015 and collected fourteen financial ratio indexes. IBMSPSS VER. 21.0 was used. Results - Variables having influence upon bankruptcy forecast models included total asset increase ratio and operating income increase ratio of growth index and sales to account receivable ratio, and tangible equity ratio and liquidity ratio of liquidity ratio. The study selected total asset operating ratio, and earning and expenditure ratio from profitability index, and receivable turnover ratio of activity index. Conclusions - Financial supervising system should be improved and financial consumers should be protected to develop saving bank and to control risk, and information on financial companies should be strengthened.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.17-22
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• 2018

According to the World Health Organization, the top 10 causes of death worldwide include heart disease. Heart diseases include coronary disease, which induces acute myocardial infarction. Ticagrelor drugs are being used to treat acute alliances, but it has become difficult to breathe due to the drugs. In a related study, Tobias predicted that uric acid causes acute respiratory distress independently of other factors, including BNP. And in the Ahmad study, serum uric acid numbers were related to the left ventricle depending on the level of uric acid. Experimental data are data used after 155 patients who received coronary intervention took ticagrelor. The research methods were leveraged by gradient decent algorithm and linear regression. In order to avoid overfitting in the experiment, training data and test data were separated into 70 and 30 percent respectively. The experimental results lacked the predictability of other attributes except DT in the correlation coefficient and crystal coefficient. However, all attributes related to dyspnea other than DT are determined to be related to causing relaxation of the heart in the left ventricle. Therefore, the attribute causing dyspnea is determined to be an attribute causing relaxation of the heart of the DT and left ventricle.

• Tuberculosis and Respiratory Diseases
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• v.62 no.5
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• pp.389-397
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• 2007

Background B-type natriuretic peptide (BNP) has been shown to be strong mortality predictors in a wide variety of cardiovascular syndromes. Little is known about BNP in patients with acute respiratory distress syndrome (ARDS). We studied whether BNP can predict mortality in patients with ARDS. Method Echocardiographic study was done to all patients with ARDS, and we excluded patient with low ejection fraction (less than 50%) or showing any features of diastolic dysfunction. 47 patients were enrolled between December, 2003 and February, 2006. Parameters including BNP were obtained within 24h hours at the time of enrollment. Result Mean BNP concentrations and APACHE II scores differed between the survivors and nonsurvivors (BNP, $219.5{\pm}57.7pg/mL$ vs $492.3{\pm}88.8pg/mL$; p=0.013, APACHE II score, $17.4{\pm}1.6$ vs $23.1{\pm}1.3$, p=0.009, respectively). With the use of the threshold value for BNP of 585 pg/mL, the specificity for the prediction of mortality was 94%. The threshold value for APACHE II of 15.5 showed sensitivity of 87%. 'APACHE II + $11{\times}logBNP$' showed sensitivity 63%, and specificity 82%, using threshold value for 46.14. Conclusion BNP concentrations and APCHE II scores were more elevated in nonsurvivors than survivors in patients with ARDS who have normal ejection fraction. BNP can predict mortality. Further study should be done.

• International Journal of Highway Engineering
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• v.8 no.1 s.27
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• pp.131-138
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• 2006

Methods of back calculation for either design procedures or elastic moduli obtained from FWD(Falling Weight Deflectometer) tests have widely been used to predict remaining life of airfield concrete pavements. Since the variation of the elastic modulus obtained from the FWD test depends on the back calculation methods, prediction of remaining life of airfield pavement using the back calculation method has not been reliable. In addition, the FWD method only concentrates on the structural integrity of the pavement without considering functional distress. In this study, a newly developed remaining life estimation procedure is proposed. This methodology includes both structural and functional consideration and suggests models and decision criteria for each stage. In order to improve the estimation procedure on remaining life of pavement, conducted the several tests on an old airfield concrete pavement. As a result, it is concluded that the load transfer efficiency on joint is better for predicting remaining life of pavement than the elastic modulus, which is commonly used. In order to verify applicability of the newly developed estimation procedure and detailed models, investigation and analysis were conducted according to the new methodology on C-airfield pavement. Finally, it is confirmed that the efficiency of the proposed method for practical application was good enough.