• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.97-116
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• 2012

Conceptual modeling is an important step for successful system development. It helps system designers and business practitioners share the same view on domain knowledge. If the work is successful, a result of conceptual modeling can be beneficial in increasing productivity and reducing failures. However, the value of conceptual modeling is unlikely to be evaluated uniformly because we are lack of agreement on how to elicit concepts and how to represent those with conceptual modeling constructs. Especially, designing relationships between components, also known as part-whole relationships, have been regarded as complicated work. The recent study, "Representing Part-Whole Relations in Conceptual Modeling : An Empirical Evaluation" (Shanks et al., 2008), published in MIS Quarterly, can be regarded as one of positive efforts. Not only the study is one of few attempts of trying to clarify how to select modeling alternatives in part-whole design, but also it shows results based on an empirical experiment. Shanks et al. argue that there are two modeling alternatives to represent part-whole relationships : an implicit representation and an explicit one. By conducting an experiment, they insist that the explicit representation increases the value of a conceptual model. Moreover, Shanks et al. justify their findings by citing the BWW ontology. Recently, the study from Shanks et al. faces criticism. Allen and March (2012) argue that Shanks et al.'s experiment is lack of validity and reliability since the experimental setting suffers from error-prone and self-defensive design. They point out that the experiment is intentionally fabricated to support the idea, as such that using concrete UML concepts results in positive results in understanding models. Additionally, Allen and March add that the experiment failed to consider boundary conditions; thus reducing credibility. Shanks and Weber (2012) contradict flatly the argument suggested by Allen and March (2012). To defend, they posit the BWW ontology is righteously applied in supporting the research. Moreover, the experiment, they insist, can be fairly acceptable. Therefore, Shanks and Weber argue that Allen and March distort the true value of Shanks et al. by pointing out minor limitations. In this study, we try to investigate the dispute around Shanks et al. in order to answer to the following question : "What is the proper value of the study conducted by Shanks et al.?" More profoundly, we question whether or not using the BWW ontology can be the only viable option of exploring better conceptual modeling methods and procedures. To understand key issues around the dispute, first we reviewed previous studies relating to the BWW ontology. We critically reviewed both of Shanks and Weber and Allen and March. With those findings, we further discuss theories on part-whole (or part-of) relationships that are rarely treated in the dispute. As a result, we found three additional evidences that are not sufficiently covered by the dispute. The main focus of the dispute is on the errors of experimental methods: Shanks et al. did not use Bunge's Ontology properly; the refutation of a paradigm shift is lack of concrete, logical rationale; the conceptualization on part-whole relations should be reformed. Conclusively, Allen and March indicate properly issues that weaken the value of Shanks et al. In general, their criticism is reasonable; however, they do not provide sufficient answers how to anchor future studies on part-whole relationships. We argue that the use of the BWW ontology should be rigorously evaluated by its original philosophical rationales surrounding part-whole existence. Moreover, conceptual modeling on the part-whole phenomena should be investigated with more plentiful lens of alternative theories. The criticism on Shanks et al. should not be regarded as a contradiction on evaluating modeling methods of alternative part-whole representations. To the contrary, it should be viewed as a call for research on usable and useful approaches to increase value of conceptual modeling.

• Journal of Home Health Care Nursing
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• v.8 no.1
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• pp.5-24
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• 2001

The purpose of this study was to develop a parenting intervention program and determine the efficacy of the program with low-birth weight infants and their mothers. Nine dyads for the experimental group and twelve dyads for the control group discharged from the Neonatal Intensive Care Unit of a University Hospital in Seoul were recruited for the study. For the intervention group, programmed education and support which focused on the maternal sensitivity of the infant's behavior. rearing environment. motherinfant interaction and infant care were given to each subject. Individual counseling and home visits were provided at discharge, one week after discharge. and one and three months of corrected age in every infant. Structured questionaires were administered and feeding interactions were videotaped and coded by a blinded certified observer. A Quasi-experimental design was conducted for this study. Postpartum depression, maternal self esteem. infant care burden, HOME. mother-infant interaction, and infant development were measured. Results were in favor of the intervention versus the control group. On the Beck depression inventory, intervention mothers showed decreasing trends in depressive symptom vs control mothers although, there were statistically no significant differences between the two groups at each time. The mean score of experimental group was 11.55(mild depression state) at discharge and became 8,6(normal state) at 1 month of corrected age. On the other hand, the mean score of the control group was 13.92(mild depression state) at discharge and became 14.0. Maternal self esteem in both groups improved over time. Infant care burden in both groups was also shown to increase over time. There was a significant difference between the two groups in HOME(p=.0340) at 3 months of corrected age. HOME scores of the experimental group and the control's were 31.10 and 25.58, respectively. Mothers' emotional and language responses were significantly high in the intervention group compared with the control group(p=.0155). Intervention group (53.33) showed a significantly high quality of motherinfant interaction compared with the in control group (42.80)(p =.0340). Intervention group mothers appeared have a better quality of mother-infant interaction behaviors. On the other hand, there was no statistical difference in the infant part between groups. Intervention group infants had higher trends in a general developmental quotient: although, there was no statistical difference between groups. The general developmental quotient of intervention infants was 102.56 and control's was 91.28. However, the developmental quotient of the domain of 'individuality-sociality' was higher in the intervention group infants compared with the control's(p=.0155). The concerns identified by parents revealed two domains of an infants' health management -knowledge and skills in caregiving of lowbirthweight-infants, characteristics of lowbirthweight infants, identifying a developmental milestone, coping with emergency situations and relaxation strategies of mothers from the infant care burden. Interview data with the mothers of low-birth weight infants can be used to develop intervention program contents. Limited intervention time and frequency due to time and cost limitations of this study should be modified. The intervention should be continuously implemented when low-birth weight infants become three years old. An NNNS demonstration appeared to be a very effective intervention for the mothers to improve the quality of mother-infant interactions. Therefore intervening in the mothers of low-birth weight infants as early after delivery as possible is desirable. This study has shown that home visit interventions are worthwhile for mothers only beyond the approach as an essential factor in ability of facilitating a growth fostering environment. In conclusion. the intervention program of this study was very effective in enhancing the parenting for the mothers of low-birth weight infants, resulting in health promotion of low-birth weight infants. The home-visit outreach intervention program of this study will contribute to the health delivery system in this country where there is a lack of continuous follow-up programs for low-birth weight infants after discharge from NICU, if it is activated as part of the home visit programs in community health systems.

• Journal of Korean Home Economics Education Association
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• v.20 no.2
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• pp.75-94
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• 2008

The purposes of this paper are to describe the newly established reference values of nutrient intakes: to apply the changed dietary reference intakes to the new text book based on the revised curriculum: and to contrive substantial contents in the domain of dietary life(foods & nutrition) of new text book. Dietary Reference Intakes for Koreans(KDRIs) is newly established reference values of nutrient intakes that are considered necessary to maintain the health of Koreans at the optimal state and to prevent chronic diseases and overnutrition. Unlike previously used Recommended Dietary Allowances for Koreas(KRDA), which presented a single reference value for intake of each nutrient, multiple values are set at levels for nutrients to reduce risk of chronic diseases and toxicity as well as prevention of nutrient deficiency. The new KDRIs include the Estimated Average Requirement(EAR), Recommended Intake(RI), Adequate Intake(AI), and Tolerable Upper Intake Level(UL). The EAR is the daily nutrient intake estimated to meet the requirement of the half of the apparently healthy individuals in a target group and thus is set at the median of the distribution of requirements. The RI is set at two standard deviations above the EAR. The AI is established for nutrients for which existing body of knowledge are inadequate to establish the EAR and RI. The UL is the highest level of daily nutrient intake which is not likely to cause adverse effects for the human health. Age and gender subgroups are established in consideration of physiological characteristics and developmental stages: infancy, toddler, childhood, adolescence, adulthood and old age. Pregnancy and lactation periods were considered separately and gender is divided after early childhood. Reference heights and weights are from the Korean Agency for Technology and Standards, Ministry of Commerce, Industry and Energy. The practical application of DRIs to the new books based on the revision in the 7th curriculum is to assess the dietary and nutrient intake as well as to plan a meal. It can be utilized to set an appropriate nutrient goal for the diet as usually eaten and to develop a plan that the individual will consume using a nutrient based food guidance system in the new books based on the revision in the 7th curriculum.

• 대한공업교육학회지
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• v.39 no.1
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• pp.143-163
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• 2014

This study developed a National Competency Standard(NCS) regarding the casino operations management based on the manual for developing National Competency Standard of 13 years and a revised classification system chart of the National Competency Standard. For the research method, this study developed a national competency standard of relevant jobs after going through review, consultation, modification, supplementation, and reporting procedures 10 times with development experts of the National Competency Standard, the industrial setting professionals, education and training experts, qualification(job analysis) experts, facilitators, and a working group of job verification committee based on the phased range and DACUM procedure of study. The major development results of this study are as follows. First, this study selected and defined duties based on the revised classification system chart of the National Competency Standard, then drew and developed total 8 ability units based on the applicable duties. Secondly, based on the developed ability units, total 27 ability unit factors were deduced and developed. Thirdly, a standard system by ability unit factor was developed based on the level of the national competency standard and revised classification system chart, then this study deduced and developed a supra-domain of the standard system by competency units using the standard tranquility value by these competency unit factors. Based on such development contents and guidelines for the national competency standard ability unit classification number, this study deduced and developed category numbers by relevant competency unit. Fourthly, total 27 relevant performance standard by competency units and knowledge, skill, and attitude were deduced and developed. Fifthly, this study deduced and developed a scope of application, work situation, evaluation guide, core competency, and development history in reference to the total 8 relevant competency units based on the duties.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.281-286
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• 2003

A large number of features are collected for problem solving in real life, but to utilize ail the features collected would be difficult. It is not so easy to collect of correct data about all features. In case it takes advantage of all collected data to learn, complicated learning model is created and good performance result can't get. Also exist interrelationships or hierarchical relations among the features. We can reduce feature's number analyzing relation among the features using heuristic knowledge or statistical method. Heuristic technique refers to learning through repetitive trial and errors and experience. Experts can approach to relevant problem domain through opinion collection process by experience. These properties can be utilized to reduce the number of feature used in learning. Experts generate a new feature (highly abstract) using raw data. This paper describes machine learning model that reduce the number of features used in learning using heuristic function and use abstracted feature by neural network's input value. We have applied this model to the win/lose prediction in pro-baseball games. The result shows the model mixing two techniques not only reduces the complexity of the neural network model but also significantly improves the classification accuracy than when neural network and heuristic model are used separately.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.99-118
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• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.804-811
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• 2010

The lower portion of sloping paddy fields normally contains excessive moisture and the higher water table caused by the inflow of ground water from the upper part of the field resulting in non-uniform water content distribution. Four drainage methods namely Open Ditch, Vinyl Barrier, Pipe Drainage and Tube Bundle for multiple land use were installed within 1-m position from the lower edge of the upper embankment of sloping alluvial paddy fields. Knowledge of the spatial variability of soil water properties is of primary importance for management of agricultural lands. This study was conducted to evaluate the effect of drainage in the soil on spatial variability of soil water content using the geostatistical analysis. The soil water content was collected by a TDR (Time Domain Reflectometry) sensor after the installation of subsurface drainage on regular square grid of 80 m at 20 m paddy field located at Oesan-ri, Buk-myeon, Changwon-si in alluvial slopping paddy fields ($35^{\circ}22^{\prime}$ N, $128^{\circ}35^{\prime}$). In order to obtain the most accurate field information, the sampling grid was divided 3 m by 3 m unit mesh by four drainage types. The results showed that spatial variance of soil water content by subsurface drainage was reduced, though yield of soybean showed the same trends. Value of "sill" of soil water content with semivariogram was 9.7 in Pipe Drainage, 86.2 in Open Ditch, and 66.8 in Vinyl Barrier and 15.7 in Tube Bundle.

• (The)Study of the Eastern Classic
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• no.34
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• pp.63-88
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• 2009

This paper was a quest of pattern of holding "Dae Hak - the Great Learning" during Joseon Period having investigated the characteristics of the Essentials of the Studies of the Sages(聖學輯要, Seong Hak Jibyo) that was compiled by Lee I was a reinterpretation of the Great Learning, and also academic enrichment. During the period of Joseon Dynasty, the Great Learning had held the most important position as core scripture in the intellectual society that pursued Seong Hak(聖學, sage learning). Throughout the Joseon Period, the Great Learning was the essential text for the Emperorship Learning(帝王學, Jewang Hak) as well as Seong Hak, and it can also be said that Seong Hak Jibyo compiled by Yulgok - the courtesy name of Lee I, was the comprehensive collections thereof. While compiling Seong Hak Jibyo, Yulgok presented a model of Seong Hak of Joseon, which was based on "the Great Learning". Yul Gok organized the system of "Seong Hak Jibyo" largely in five parts, and properly arranged the Three Cardinal Principles(三綱領, samgangryeong) and Eight Articles or Steps(八條目, paljomok) therein. Particularly, in the Chapter Two, "Cultivating Oneself(修己, sugi)", Yulgok deal with 'being able to manifest one's bright virtue'(明明德, myeong myeong deok) among the Three Cardinal Principles as the core curriculum, meanwhile, Yulgok also covered "Investigation of things, gyeongmul(格物)," "Extension of knowledge, chiji(致知)," "Sincerity of the will, Seongui(誠意)," "Rectification of the mind, Jeongshim(正心)," "Cultivation of the personal life, susin(修身)," among Paljomok(eight steps) as the ultimate purpose of 'Stopping in perfect goodness'(止於至善, jieojiseon) These well preserve the principal system of Confucianism where "Cultivating oneself and regulating others (修己治人, sugichiin)" are core value, and his instructions as such also back up academic validity logically by presenting specific guidelines for practice according to each domain. Reinterpretation of "The Great Learning" by Yulgok in Seong Hak Jibyo is an arena to investigate the characteristics of Confucianism in Joseon Period, which was different from that of China, furthermore, such guidelines might take a role as criteria to understand the characteristics of humans and learning possessed by Korean people.