• Journal of Intelligence and Information Systems
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• 제20권4호
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Korean Journal of Environment and Ecology
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• 제35권4호
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• pp.316-335
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• 2021

This study reviewed the change of theory of ecological niche(concepts and definitions) over time to provide a theoretical basis for habitat-related studies of animals and plants. Accordingly, it analyzed and summarized the major discussion trends of ecological niche worldwide in each period from the 1900s to the present. Countries advanced in ecological studies, such as the EU and the USA, have conducted theoretical and empirical studies on the ecological niche since the early 1990s. The concept of the ecological niche was introduced in the early 1900s, developed in the mid-1900s, and advanced from the mid-1900s to the late 1900s. Since the 2000s, the advanced concept has diversified with new developments in technologies and research methods. The factors suggested by theoretical and empirical studies in defining the ecological niche of a species include 1) population dynamics of the target species, 2) all biotic conditions to sustain a population (food relationship and material flow in the food chain), 3) all non-biotic conditions to sustain a population (physical environmental conditions), 4) all direct and indirect interactions between these environmental factors, and 5) response and adaptation mechanisms that include the migratory ability of the target species or genetic diversity and adaptability to change. Unlike such international advancement, there have not been sufficient theoretical, philosophical, and empirical studies of ecological niche in Korea. The concepts and definitions by Greennell, Elton, and Hutchinson were selectively and partially borrowed for empirical studies without full description. Considering that the theory of ecological niche becomes the foundation for habitat-based species conservation and restoration, it is necessary to seek diversification and advancement of theoretical and empirical research and research methods and technological development. It will provide an important foundation for the academic advancement of ecology and for establishing and implementing policies to preserve and restore ecology and biodiversity effectively and successfully in Korea.

• Korean Journal of Biological Psychiatry
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• 제11권2호
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• pp.94-103
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• 2004

Objective:There have been a kind of transmethylation theory that high homocysteine serum concentration affects schizophrenia by neurotoxic mechanism and clinical reports that some schizophrenic patients with high homocysteine were improved by high folate ingestion. This study was done to confirm previous research results and find the clinical characteristics of schizophrenia showing high serum homocysteine and low folate. Method:We compared the serum levels of homocysteine, folate and vitamin B12 level between 234 schizophrenic patients(male 99, female 135) group and 234 normal controls(male 99, female 135) group. The subjects of two groups were age and sex matched. The evaluated clinical characteristics items were sex, age, onset of disease, hereditary loading, disease course, hallucination and subtype of schizophrenia. Results:1) Homocysteine level of the schizophrenia group was significantly higher than the normal control group and folate level of the schizophrenia group was significantly lower than the normal control group. Homocysteine level was more negatively correlated with folate level in the schizophrenia group than the normal control group. 2) The percentage of high homocysteine(above 12.46umol/L;90 percentile of normal control) was 33.8% of schizophrenia patients and 51.5% of male schizophrenia. The percentage of low folate(below 3.8nM/L;bottom tertile of normal control) was 66.2% of schizophrenia. 3) In low folate group and not-low folate group, schizophrenia showed significantly higher homocysteine level than normal control. Especially, low folate schizophrenia group showed significantly higher homocysteine level than low folate normal control group. Conclusions:Some schizophrenia patients with high serum homocysteine may be genetic defector and having low folate serum level. In that case, folate ingestion could be a good management for clinical improvement.

• Journal of Educational Research in Mathematics
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• 제11권2호
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• pp.363-384
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• 2001

The purpose of this thesis is, through analysing the characteristics of the definitions in Korean school mathematics textbooks, to explore the levels of them and to make suggestions for definition - teaching as a mathematising activity, Definitions used in academic mathematics are rigorous. But they should be transformed into various types, which are presented in school mathematics textbooks, with didactical purposes. In this thesis we investigated such types of transformation. With the result of this investigation we tried to identify the levels of the definitions in school mathematics textbooks. And in school mathematics textbooks there are definitions which carry out special functions in mathematical contexts or situations. We can say that we understand those definitions, only if we also understand the functions of definitions in those contexts or situations. In this thesis we investigated the cases in school mathematics textbooks, when such functions of definition are accompanied. With the result of this investigation we tried to make suggestions for definition-teaching as an intellectual activity. To begin with we considered definition from two aspects, methods of definition and functions of definition. We tried to construct, with consideration about methods of definition, frame for analysing the types of the definitions in school mathematics and search for a method for definition-teaching through mathematization. Methods of definition are classified as connotative method, denotative method, and synonymous method. Especially we identified that connotative method contains logical definition, genetic definition, relational definition, operational definition, and axiomatic definition. Functions of definition are classified as, description-function, stipulation-function, discrimination-function, analysis-function, demonstration-function, improvement-function. With these analyses we made a frame for investigating the characteristics of the definitions in school mathematics textbooks. With this frame we identified concrete types of transformations of methods of definition. We tried to analyse this result with van Hieles' theory about levels of geometry learning and the mathematical language levels described by Freudenthal, and identify the levels of definitions in school mathematics. We showed the levels of definitions in the geometry area of the Korean school mathematics. And as a result of analysing functions of definition we found that functions of definition appear more often in geometry than in algebra or analysis and that improvement-function, demonstration-function appear regularly after demonstrative geometry while other functions appear before demonstrative geometry. Also, we found that generally speaking, the functions of definition are not explained adequately in school mathematics textbooks. So it is required that the textbook authors should be careful not to miss an opportunity for the functional understanding. And the mathematics teachers should be aware of the functions of definitions. As mentioned above, in this thesis we analysed definitions in school mathematics, identified various types of didactical transformations of definitions, and presented a basis for future researches on definition teaching in school mathematics.

• Journal of Navigation and Port Research
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• 제32권6호
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• pp.459-464
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• 2008

In this paper, we present the model-based fuzzy controller for container cranes which effectively performs set-point tracking control of trolley and anti-swaying control under system parameter and disturbance changes. The first part of this paper focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear model of a container crane. In the second part, we present a design methodology of the model-based fuzzy controller. Sub-controllers are designed using LQ control theory for each subsystem in fuzzy model and then the proposed controller is performed with the combination of these sub-controllers by fuzzy IF-THEN rules. In the results of simulation, the fuzzy model showed almost similar dynamic characteristics compared to the outputs of the nonlinear container crane model. Also, the model-based fuzzy controller showed not only the fast settling time for the change in parameter and disturbance, but also stable and robust control performances without any steady-state error.

• Journal of Korean Philosophical Society
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• 제119권
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• pp.141-172
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• 2011

This thesis, centered on J. Locke and W. v. Humboldt's concept of language, is written for the purpose of illuminating their view of language and investigating the relationship between a matter of language and that of thought. First, Locke considers language was to be the great instrument and common tie of society. And language consists of words, and words are signs of ideas. Locke's discussion in language is shaped by his belief that these conditions of the transference of knowledge were in his time commonly unsatisfied, especially in two domains. First, there was no agreed classification of 'substance' based on careful observation and experiment. Second, the ideas associated with the names of mixed modes often varied both in the usage of different people and in that of the same person at different times. But Humboldt deals with 'the diversity of the structure of human language' and deals with it in respect of 'its influence on the spiritual development of mankind.' According to his theory, a language is not work(ergon) but an activity(energeia). Its true definition may therefore only be genetic. It is after all the continual intellectual effort to make the articulated sound capable of expressing thought. In short, he conceives of language as a particular 'intellectual effort'.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제29권3C호
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Journal of The Korean Association For Science Education
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• 제26권7호
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• pp.856-869
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• 2006

J. J. Schwab is usually considered as the founder of the concept of scientific enquiry, perhaps the most important key word of science education of the 20th century. Mainly through the method of literature review, this study reappraises Schwab's life as a science educator as well as a curriculum scholar, and his ideas concerning several important issues about science and science education. Like other eminent science educators, before the 1950s, who were originally talented scientists but later became engaged in educational activities, Schwab were trained and known as a genetic scientist, but later he concentrated on university reform, curriculum studies and science education. His academic interest was very diverse across different disciplines, from biology and science in general to history, philosophy and education. The essence of his theory of scientific enquiry was 'to teach science as science', and the best way to do it was 'to teach science as enquiry'. With enquiry, however, he tried to deliver some important but differentiated meanings, for example by distinguishing 'science as enquiry' and 'teaching as enquiry', and 'static enquiry' and 'fluid enquiry'. Scientific enquiry was the core concept upon which many of his ideas concerning science education and education in general were based, such as the diversity of science, textbooks, curriculum and roles of teachers. In summary, Schwab can be characterized as a rational reformist of science education, who tried to identify the very nature and goals of the discipline and to bring its substantial changes with concrete and practical guidelines. Nevertheless, some of his ideas, like the diversity of science and conceptual invention, have been handed down by his followers frequently with considerable distortion.

• Asia pacific journal of information systems
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• 제24권2호
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of KIISE:Computer Systems and Theory
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• 제33권3호
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• pp.157-165
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• 2006

The change of external/internal factors of the cell rquires specific biological functions to maintain life. Such functions encourage particular genes to jnteract/regulate each other in multiple ways. Accordingly, we applied a linear decomposition model IFSA, which derives hidden variables, called the 'expression mode' that corresponds to the functions. To interpret gene interaction/regulation, we used a cross-correlation method given an expression mode. Linear decomposition models such as principal component analysis (PCA) and independent component analysis (ICA) were shown to be useful in analyzing high dimensional DNA microarray data, compared to clustering methods. These methods assume that gene expression is controlled by a linear combination of uncorrelated/indepdendent latent variables. However these methods have some difficulty in grouping similar patterns which are slightly time-delayed or asymmetric since only exactly matched Patterns are considered. In order to overcome this, we employ the (IFSA) method of [1] to locate phase- and shut-invariant features. Membership scoring functions play an important role to classify genes since linear decomposition models basically aim at data reduction not but at grouping data. We address a new function essential to the IFSA method. In this paper we stress that IFSA is useful in grouping functionally-related genes in the presence of time-shift and expression phase variance. Ultimately, we propose a new approach to investigate the multiple interaction information of genes.