• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.3
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• pp.14-26
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• 2018

The Biotope Area Ratio (BAR) is a quantitative pre-planning index for sustainable development and an integrated indicator for the balanced development of buildings and outdoor spaces. However, it has been pointed out that there are problems in operations management: errors in area calculation, insufficiency in the underground soil condition and depth, reduction in biotope area after construction, and functional failure as a pre-planning index. To address these problems, this study proposes implementing LIM. Since the weights of the BAR are mainly decided by the underground soil condition and depth with land cover types, the study focused on the terrain and pavements. The model should conform to BIM guidelines and standards provided by government agencies and professional organizations. Thus, the scope and Level Of Detail (LOD) of the model were defined, and the method to build a model with BIM software was developed. An apartment complex on sloping ground was selected as a case study, a 3D terrain modeled, paving libraries created with property information on the BAR, and a LIM model completed for the site. Then the BAR was calculated and construction documents were created with the BAR table and pavement details. As results of the study, it was found that the application of the criteria on the BAR and calculation became accurate, and the efficiency of design tasks was improved by LIM. It also enabled the performance of evidence-based design on the terrain and underground structures. To adopt LIM, it is necessary to create and distribute LIM library manuals or templates, and build library content that comply with KBIMS standards. The government policy must also have practitioners submit BIM models in the certification system. Since it is expected that the criteria on planting types in the BAR will be expanded, further research is needed to build and utilize the information model for planting materials.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.21-37
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• 2013

Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

• The Korean Journal of Health Service Management
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• v.2 no.1
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• pp.137-154
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• 2008

The increase of the supply of medical service and the increase of hospitals have intensified the competition of hospitals, and the advancement towards internationalization in the opening of medical industry has triggered the infinite competition of medical profession. In addition, the high expectation of customers and quality improvement in the medical care in accordance with the improvement of overall income, and the change of active role of medical consumers according to the popularization and the improvement of rights awareness reflect the customer needs and choice in the medical service. Customers wanted to receive the kind and pleasant service under the up-to-date medical service. Therefore, as a solution, hospital coordinators were emerged for the purpose of smooth treatment and customer satisfaction by generalizing all service of hospital. Accordingly, this thesis attempted to investigate the effect of hospital coordinator education curriculum on the education satisfaction and the quality of medical service. In order to solve the purpose of this study, I, author reviewed the existing literatures, established hypothesis, and verified hypothesis by using the variety of statistics techniques such as reliability, validity, frequency analysis, and regression analysis. The verification of hypothesis is as followings: First, among education training factors of hospital coordinators, the quality of instructor significantly affects the satisfaction of hospital coordinator education training. Second, among training factors of hospital coordinator, the attitude of trainee significantly affects the training satisfaction of hospital coordinator. Third, among education training factors of hospital coordinator, education course significantly affects the training satisfaction of hospital coordinator education. As the qualities of instructor are better equipped, the satisfaction of education becomes higher. It indicates that the education method of instructors is important as an index to represent the qualities of instructor such as the appropriateness of education method, preparation, passion, visual materials, the adequacy of education procession, and specialized knowledge, and it has important effect on the satisfaction of education. In order to enhance the satisfaction of hospital coordinator education, the creation of education environment, making trainee concentrate on the education, is required by appropriately allocating programs, arousing interest in education, based on the attitude of trainee, discussion, and preliminary programs, preparation, ahead of enforcement of education. Fourth, the satisfaction of hospital coordinator education training significantly affects the reliability among the qualities of medical service. Fifth, satisfaction of hospital coordinator education training significantly affects hospitality I kindness among the qualities of medical service. If the education satisfaction of trainee is high, it is effective in the practical application such as dealing with complaints, the duty performance for the patients, and so on in offering the medical service, related to reliability and furthermore, we can find the positive change in the attitude change of medical professions related to the reliability of hospital coordinator. In addition, in the process of offering medical services such as the kind explanation on the duty, rapid response to the customers inquiry, and tidy uniform, practical effect was verified. Sixth, the education training factor of hospital coordinator significantly affects the reliability among the quality of medical service. Seventh, the education training factors of hospital coordinator significantly affect hospitality/kindness. In the education of hospital coordinator, the methods to attract the interest of trainee by emphasizing reliability should be sought and for gaining the practical effect of hospital coordinator education, the sufficient preparation and investigation on the education curriculum should be prerequisite and under this condition, intensified discussion on the instructor and education course is needed. In the design of education course, more education hours and subjects should be allocated in the part of hospitality in order to improve the practical application of hospitality. Therefore, it is meaningful in a sense that this study newly approached the components of hospital coordinator education and the need to modify the quality components of medical service in accordance with the study subjects was raised. This study also finds its meaning in that it provides basic materials for the study of future hospital coordinator education by suggesting the system development model of hospital coordinator education through preliminary study of education training. In addition, this study is meaningful in the aspect that it suggested the direction of education training by showing how the hospital coordinator education training would applied to the hospital coordinator course of the Continuing Education Center at Pusan and Kyungnam National University to some extent. Since all investigation of this study was approached from the side of hospital coordinator, the thoughts of patients who are beneficiaries of medical service, and care givers cannot be identified. Therefore, the satisfaction of patients and care givers through the experience of medical service, which is the essential prerequisite of medical service, should be importantly considered and investigated. Accordingly, The study of comparing and analyzing the views of both patients and care givers should be carried out in the future.

• Journal of Korea Technology Innovation Society
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• v.12 no.4
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• pp.788-818
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• 2009

Renewable energy refers to solar energy, biomass energy, hydrogen energy, wind power, fuel cell, coal liquefaction and vaporization, marine energy, waste energy, and liquidity fuel made out of byproduct of geothermal heat, hydrogen and coal; it excludes energy based on coal, oil, nuclear energy and natural gas. Developed countries have recognized the importance of these energies and thus have set the mid to long term plans to develop and commercialize the technology and supported them with drastic political and financial measures. Considering the growing recognition to the field, it is necessary to analysis up-to-now achievement of the government's related projects, in the standards of type of renewable energy, management of sectional goals, and its commercialization. Korean government is chiefly following suit the USA and British policies of developing and distributing renewable energy. However, unlike Japan which is in the lead role in solar rays industry, it still lacks in state-directed support, participation of enterprises and social recognition. The research regarding renewable energy has mainly examinedthe state of supply of each technology and suitability of specific region for applying the technology. The evaluation shows that the research has been focused on supply and demand of renewable as well as general energy and solution for the enhancement of supply capacity in certain area. However, in-depth study for commercialization and the increase of capacity in industry followed by development of the technology is still inadequate. 'Cost-benefit model for each energy source' is used in analysis of technology development of renewable energy and quantitative and macro economical effects of its commercialization in order to foresee following expand in related industries and increase in added value. First, Investment on the renewable energy technology development is in direct proportion both to the product and growth, but product shows slightly higher index under the same amount of R&D investment than growth. It indicates that advance in technology greatly influences the final product, the energy growth. Moreover, while R&D investment on renewable energy product as well as the government funds included in the investment have proportionate influence on the renewable energy growth, private investment in the total amount invested has reciprocal influence. This statistic shows that research and development is mainly driven by government funds rather than private investment. Finally, while R&D investment on renewable energy growth affects proportionately, government funds and private investment shows no direct relations, which indicates that the effects of research and development on renewable energy do not affect government funds or private investment. All of the results signify that although it is important to have government policy in technology development and commercialization, private investment and active participation of enterprises are the key to the success in the industry.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of Korean Society of Forest Science
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• v.106 no.3
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• pp.288-299
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• 2017

This study was conducted to find out the influence of drought stress on physiological responses of Synurus deltoides. Drought stress was induced by withholding water for 25 days. Leaf water potentials were decreased of both predawn (${\Psi}_{pd}$) and mid-day (${\Psi}_{mid}$) with increasing drought stress, but water saturation dificit (WSD) was 7 times increased. ${\Psi}_{pd}-{\Psi}_{mid}$ showed the significant difference of 0.22~0.18 MPa in stressed before 10 days, and nonsignificant as treatment time became longer. A strong reduction of stomatal conductance ($gH_2O$) and stomatal transpiration rate (E) were observed after 15 days of drought stress Significant reductions of net apparent quantum yield (${\Phi}$) and maximum photosynthesis rate ($Pn_{max}$) were observed after 20 days of drought stress; However, water use efficiency (WUE) was shown the opposite trend. This implies that decrease of photosynthesis rate may be due to an inability to regulate water and $CO_2$ exchanged through the stomata. From JIP analysis, flux ratios (${\Psi}_O$ and ${\Phi}_{EO}$) and performance index on absorption basis ($PI_{ABS}$) were dramatically decreased withholding water after 15 days, which reflects the relative reduction of photosystem II activity. The leaf of S. deltoides showed osmotic adjustment of -0.35 MPa at full turgor and -0.40 MPa at zero turgor, and also cell-wall elastic adjustment of 9.4 MPa, indicating that S. deltoides tolerate drought stress through osmotic adjustment and cell-wall elastic adjustment. The degree of change in water relations parameters such as Vo/DW, Vt/DW decreased with increasing drought stress. This result showed that S. deltoides was exhibited a strong reduction of photosynthetic activity to approximately -0.93 MPa of predawn leaf water potential, and both of osmotic adjustment and cell-wall elastic adjustment in drought stress condition appears to be an important adaptation for restoration in this species.

• Journal of Preventive Medicine and Public Health
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• v.31 no.3 s.62
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• pp.490-502
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• 1998

This study purports to find the predictor of hospital bankruptcy in Korea and to examine the predictive power of the discriminant function model of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 31 bankrupt and 31 profitable hospitals of 1, 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the discriminant function model of hospital bankruptcy was developed. The major findings are as follows 1. As for profitability indicators, net worth to total assets, operating profit to total capital, operating profit ratio to gross revenues, normal profit to total assets, normal profit to gross revenues, net profit to total assets were significantly different in mean comparison test in 1, 2, and 3 years before hospital bankruptcy. With regard to liquidity indicators, current ratio and quick ratio were significant in 1 year before bankruptcy. For activity indicators, patients receivable turnover was significant in 2 and 3 years before bankruptcy and added value per adjusted inpatient days was significant in 3 years before bankruptcy. 2. The discriminant function in 1, 2, and 3 years before bankruptcy were; $Z=-0.0166{\times}quick$ ratio-$0.1356{\times}normal$ profit to total assets-$1.545{\times}total$ assets turnrounds in 1 year before bankruptcy, $Z=-0.0119{\times}quick$ ratio-$0.1433{\times}operating$ profit to total assets-$0.0227{\times}value$ added to total assets in 2 years before bankruptcy, and $Z=-0.3533{\times}net$ profit to total assets-$0.1336{\times}patients$ receivables turn-rounds-$0.04301{\times}added$ value per adjusted $patient+0.00119{\times}average$ daily inpatient census in 3 years before bankruptcy. 3. The discriminant function's discriminant power in 1, 2, and 3 years before bankruptcy was 77.42, 79.03, 82.25% respectively.