• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Current Research on Agriculture and Life Sciences
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• v.1
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• pp.11-18
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• 1983

This study was performed to obtain the basic informations for red dry pepper fruit with more pericarp weight(or in percentage) with a complete diallel cross(excluding reciprocals) using eight cultivars. Heterosis, combining ability and inheritance of the dry red fruit weight and its components(stem, placenta, seed, and pericarp) were evaluated. The results obtained were summarized as follows : Dry weight/fruit and its four antomical components were heavier in the earlier harvest fruit than in that of the later fruit. They showed 1% significance among parents and $F_1s$, and those of $F_1$ were significantly heavier than in parent. All characters in earlier fruit of parent, however, were higher than in later fruit of $F_1$. Dry weight percentage of pericarp to dry weight/fruit was highest followed by seed. Percentage of pericarp in the later fruit was increased while the seed decreased and percentages of stem and placenta were not differed between the earlier and later fruit. $F_1$ hybrids above the higher parent were observed in all characters. Mean heterosis (%) was positive in all characters while mean heterobeltiosis (%) was negative excepting seed and dry weight/fruit. GCA and SCA variances were highly significant, and GCA vaiances were greater than SCA in all characters. The directions of dominance were positive. Partial dominance was shown in stem, complete dominance in placenta, pericarp and dry weight/fruit, and over dominance in seed. The effective genes were estimated as one for stem and placenta, and two for seed, pericarp and dry weight/fruit. Heritabilities in narrow and broad sense were higher.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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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.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.3773-3777
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• 2015

Background: This study aimed to establish a nomogram by combining clinicopathologic factors with overall survival of stage IA-IIB cervical cancer patients after complete resection with pelvic lymphadenectomy. Materials and Methods: This nomogram was based on a retrospective study on 1,563 stage IA-IIB cervical cancer patients who underwent complete resection and lymphadenectomy from 2002 to 2008. The nomogram was constructed based on multivariate analysis using Cox proportional hazard regression. The accuracy and discriminative ability of the nomogram were measured by concordance index (C-index) and calibration curve. Results: Multivariate analysis identified lymph node metastasis (LNM), lymph-vascular space invasion (LVSI), stromal invasion, parametrial invasion, tumor diameter and histology as independent prognostic factors associated with cervical cancer survival. These factors were selected for construction of the nomogram. The C-index of the nomogram was 0.71 (95% CI, 0.65 to 0.77), and calibration of the nomogram showed good agreement between the 5-year predicted survival and the actual observation. Conclusions: We developed a nomogram predicting 5-year overall survival of surgically treated stage IA-IIB cervical cancer patients. More comprehensive information that is provided by this nomogram could provide further insight into personalized therapy selection.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.3
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• pp.15-22
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• 2010

Today's rapid shifts toward a new paradigm are combining city spaces with reality and technology, which is known as a ubiquitous environment. An ubiquitous environment means that 'whenever' and 'wherever' become connected. It is a great possibility that this will change our future lifestyle. Korea has the biggest advantage in the implementation of this new environment, such as having an excellent network infrastructure. Using these attributes of a ubiquitous environment, changes are being made toward ubiquitous cities within developing fields of construction, landscaping, streets, art, and the environment. This research is based on background of research that activated media pole in public city space has been done research about reality of digital skill, fusion, and sense of ubitizen, and Kang-Nam U-street applied by ubiquitous technique. While reflecting an environment that can be utilized in a modern digital society, the application of ubiquitous technology to media pole can be a space for the two-way communication of the current paradigm. It would also be meaningful to create a new cultural space through media pole. Through evaluation, citizens of the ubiquitous age are going to interact to raise the satisfaction that media pole in city space can prevent giving direction to develop and trial and error about service ability, identity, and publicity. Finally, the media pole can be used as a fundamental element to suggest directions for change when viewed as future development.

• Korean Journal of Heritage: History & Science
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• v.44 no.1
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• pp.30-51
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• 2011

During the process of modernization, many rural villages in Korea have experienced degeneration and breakdown, losing sustainability. However, Oeam village in Asan City, South Chungcheong Province (State-designated cultural heritage, Important Folk Material No. 236) has established itself as a unique folk village, which evolves with sustainability, pursuing the revival of Neo-traditionalism. Oeam village is a tribal village of the Yis from the Yean region and has maintained environmental, economic, and social sustainability and soundness for over five centuries. Thus, the village has sustained itself well enough to be a cultural asset with 'Outstanding Universal Value', in terms of its value as world cultural heritage. The village maintains its own identity, filled with a variety of traditional and scenic cultural assets that symbolize a gentry village. Those assets include Confucian sceneries (head family houses, ancestral shrines, tombs, gravestones, commemorative monuments, and pavilions), various assets of folk religion (totem poles, protective trees at the entrance of a village, shrines for mountain spirits, village forests), tangible and intangible cultural assets related to daily lives (vigorous family activities, rigorous ancestral rituals, family rituals, collective agriculture and protection of ecosystem), which have all been well preserved and inherited. In particular, this village is an example of a well-being community with a well-preserved folksy atmosphere, which is based on environmentally sound settlements (nature + economy + environment + community) in a village established according to geomancy, East Asia's unique principle of environmental design. In addition, the village has kept the sustainability and authenticity for more than 500 years, combining restraint towards the environment and the view of the environment which respects the natural order and cultural values (capacity + healthy + sustainability). Therefore, the Oeam folk village can be a representative example of a folksy and scenic Korean community which falls into the category of IV (to exemplify an outstanding type of building, architectural or technological ensemble, or landscape which illustrates significant stages in human history) and V (to exemplify an outstanding traditional human settlement, land-use, or sea-use which is representative of cultures, or human interaction with the environment especially when it has become vulnerable under the impact of irreversible change) of Unesco's World Cultural Heritage.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.1
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• pp.67-74
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• 2023

In this study, for a natural cosmetics market, we sought to explore alternatives that can replace polyvinyl alcohol (PVA) of peel-off packs. A peel-off type pack was prepared by combining pullulan, a water-soluble polysaccharide, and other polysaccharides (sodium hyaluronate, cellulose gum, hydroxyethyl cellulose, sodium alginate, corn starch), and the pH, viscosity, and stability against temperature of each peel-off type pack were confirmed. The thickness and tensile strength of the manufactured film were measured for comparison with the PVA peel-off type pack, and applicability, drying speed, and removal degree were measured. Among them, the pullulan-sodium hyaluronate peel-off type pack showed excellent film formation ability to replace the peel-off type pack containing PVA with 5.12% thin film thickness and 4.23% high film tensile strength. When applied to actual skin, the degree of spread of the pack, the usability that can be uniformly applied, and the formation and removal strength of the film when removed after drying were also similar to the peel-off type pack containing PVA. Therefore, it was confirmed that the film formed of pullulan-sodium hyaluronate showed enough physical properties to replace the PVA of the peel-off type pack as a natural peel-off type pack.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Korean Journal of Heritage: History & Science
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• v.49 no.3
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• pp.32-51
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• 2016

This study examines, based on the database of the Institute for the Translation of Korean Classics(ITKC), the garden plants and their symbolism, and the landscape culture recorded in 'Jipkyungjaeyoungsi(the Series of Poems on Gardens Poetry)' in relevance to traditional houses. First, Jipkyungjaeyoungsi had been continuously written since mid-Goryeo dynasty, when it was first brought in, until the late Joseon dynasty. It was mainly enjoyed by the upper class who chose the path of civil servants. 33 pieces of Jaeyoungsi(題詠詩) in 25 books out of a total of 165 books are related to residential gardens. The first person who wrote a poem in relation to this is believed to be Lee GyuBo(1168~1241) in the late Goryeo dynasty. He is believed to be the first person to contribute to the expansion of natural materials and the variation of entertainment in landscape culture with such books as 'Toesikjaepalyoung(退食齋八詠)', 'Gabeunjeungyukyoung(家盆中六詠)'and 'Gapoyukyoung(家圃六詠)'. Second, most of the poems used the names of the guesthouses. Out of the 33 sections, 19(57.5%) used 8 yeong(詠), then it was in the sequence of 4 yeong(詠), 6 yeong, 10 yeong, 14 yeong, 15 yeong, 16 yeong, 36 yeong(詠) and so on. In the poem writing, it appears to break the patterns of Sosangpalkyung(瀟湘八景) type of writings and is differentiated by (1) focusing on the independent title of the scenery, (2) combining the names of the place and landscape, (3) focusing on the name of the landscape. Third, the subtitles were derived from (1) mostly natural landscape focused on nature and garden plants(22 sections, 66.7%), (2) cultural landscape focused on landscape facilities such as guesthouses, ponds and pavilions(3 sections), (3) complex cultural scenery focused on the activities of people in nature(8 sections). Residents enjoy not only their aesthetic preferences and actual view, but the ideation of the scenery. Especially, they display attachment to and preference for vegetables and herbs, which had been neglected. Fourth, the percentage of deciduous tree population(17 species) rated higher(80.9%) compared to the evergreens(4 species). These aspects are similar results with the listed rate in 'Imwonkyungjaeji(林園經濟志)' by Seo YuGu [evergreen 18 species(21.2%) and deciduous trees 67 species(78.8%)] and precedent researches [Byun WooHyuk(1976), Jung DongOh(1977), Lee Sun(2006)]. Fifth, the frequency of the occurrence of garden plants were plum blossoms(14 times), bamboos(14 times), pine trees(11 times), lotus(11 times), chrysanthemum(10 times), willows(5 times), pomegranates(4 times), maple trees(14 times), royal foxglove trees, common crapemyrtle, chestnut trees, peony, plantains, reeds and a cockscombs(2 times). Thus, the frequency were higher with symbolic plants in relations to (1) Confucian norms(pine trees, oriental arbor vitae, plum blossoms, chrysanthemums, bamboos and lotus), (2) living philosophy of sustain-ability(chrysanthemum, willow), (3) the ideology of seclusion and seeking peace of mind(royal foxglove ree, bamboo). Sixth, it was possible to trace plants in the courtyard and outer garden, vegetable and herb garden. Many symbolic plants were introduced in the courtyard, and it became cultural landscape beyond aesthetic taste. In the vegetable and herb garden, vegetables, fruits and medicinal plants are apparently introduced for epigenetic use. The plants that were displayed to be observed and enjoyed were the sweet flag, pomegranate, daphne odora, chrysanthemum, bamboo, lotus and plum blossom. Seventh, it was possible to understand garden culture related to landscaping materials through poetic words such as pavilions, ponds, stream, flower pot, oddly shaped stones, backyard, orchard, herb garden, flower bed, chrysanthemum fence, boating, fishing, passing the glass around, feet bathing, flower blossom, forest of apricot trees, peach blossoms, stroking the pine tree, plum flower blossoming through the snow and frosted chrysanthemum.