• 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.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.47-75
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• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• The Korean Journal of Archival Studies
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• no.30
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• pp.3-55
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• 2011

Recently, a topic of Archival Science can be said 'paradigm shift'. Therefore, this study aims to establish a relationship between oral record and Archival Science through concept of the archiving 'social memory' related to paradigm shift of Archival Science. In addition, an active role theory by an archivist as main agent of archival oral record management reflecting the characteristics of oral record based on this will be supported. Especially, even if it has already been handled through previous studies, it will be focused on drawing new meaning by applying creative perspective. Main content of this study is as follows. Firstly, discussion will be progressed by establishing the concept of the archiving 'social memory'. This is related to the topic of 'paradigm shift' in the Archival Science. Despite that active research has been conducted among mainly archival researchers overseas, it has not been handled yet in Korea. Therefore, this study aims to determine to organize this part as detail purpose. Secondly, the point will be progressed with a special focus on collecting and planning stages among the stages of records management. A viewpoint of the Archival Science should start from the stage of collecting and planning the previous record of production point of time, and then should be reflected for acknowledging the subsequent stages. Therefore, collecting and planning are the most important, and this is closely connected with a characteristic of oral record which production means collecting. Thirdly, the concept of 'oral record' is established with the viewpoint of the Archival Science. The various documents have been producted through oral interview has been known to many oral history researchers as 'oral source'. It aims to conceptualize them as 'oral record' with the viewpoint of the Archival Science. Fourthly, it is an establishment of meaning why oral history should be handled in the Archival Science. It is necessary to rationalize the purpose and its appropriateness handling oral history in the Archival Science. It should clarify the reason why oral history is important in the Archival Science and what it means. This will help examine the meaning of the recording of 'oral record.' A characteristic of the oral record can be effectively revealed through the recording, and ultimately, it aims to be able to shed new light on the value of oral history and oral record. Finally, it defines the role of archivist in oral history. A point that archivist in oral history is not just an assistant who organizes and preserves oral records collected by researchers will be emphasized and persuaded. In this study, oral history study in the Archival Science which has obtained appropriateness by the theoretical discussion as above should be conducted in a connection with other studies without occupying oral history by the Archival Science and in a direction of the leap of Korean oral history study. If this is possible, it will contribute to development of the Archival Science and of study area expansion, enhancement of the role and potential of archivist, at the same time, eventually it will positively influence on oral history study.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.1
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• pp.65-80
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• 1994

In the 20th century, The artistic world was constantly producing new ideas and movements and the world of fashion responded to and reflected them all in greater of lesser degree. Dress designers have always been aware of what is happening In the arts and have always been able to use the discoveries and ideas of the artist to help them solve design problems and create fashion which are new, inventive and reflective of thier time. Up to the present, other researchers have investigated the connections between the fine arts and the Modern Fashion. In this respect, the objective of this research was to clarify the characteristics of painting of the Impressionism on the Modern Fashion. In order to investigate the relationship between the trend of painting and Modern Fashion. Especially, Impressionism's light and color affected both 20th's painting and other sorts of art. That is, the trend of the modern painting, Fauvism, Cubism, Surrealism, Abstract art, Abstract Expressionism, was influenced by Impressionism painting. Similarly, in the sihouette, line, color, fabric pattern of the Modem Fashion was represented characteristics of the Impressionism Painting. The fashion's Fauve, Paul Poiret was excited by the power of color in the same intense way as the 'wild beasts' of art. The color of his clothes during that period was bold and brilliant. Gabrielle Chanel simplified the shape of women's clothes to a square cardigan and rectangular skirt. This was a cubist concept. Art and fashion probably held hands closest in the 1930s, when Elsa Schiaparelli was creating clothes directly influenced by the Surrealist thinking of Salvador Dali. And she burst upon the fashion world with a sweater that had a trompe I'oeil bow. Soma Delaunay was one of great pioneers of Abstract in. She proceeded to mix strong and bright colors into her art and created the geometric and abstract patterns of the clothes and fabrics with her strong color. The influence of Abstract Expressionism was expressed the fabrics of the Modern Fashion. Some fabrics used in Modern Fashion are printed in a dripping pouring and splashing style. For the future, some futher research to investigate the art-fashion connection might involve establishing systematic classifications for silhouette, line, texture, color of the fashion. Moreover, in order to study the influence of fine art on the fashion, a broader approach might wish to analyze the relationship between painting and other plastic arts.

• The Journal of Korean Academic Society of Nursing Education
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• v.4 no.2
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• pp.220-235
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• 1998

The revolution of nursing curriculum has been focused on clinical competency for nursing graduates to flexibly respond to changes in societal health needs and disciplinary requirements. In this trend, the study was designed to identify basic concepts of nursing education that reflects the changes in societal needs and nursing discipline, and to develop the instrument to measure performance level in each dimension of clinical competency. The study was conducted in two phases. In phase 1, principal concepts consisted of nursing education were determined through literature review as well as series of discussion sessions on nursing philosophies and educational objectives among researchers. Though the process, the conceptual framework of competency based nursing curriculum was constructed with nursing process and professional role as horizontal threads, client, health needs, and nursing interventions as vertical threads. Then, items were developed to represent each dimension of competency : client and health need, nursing process, professional role, and nursing interventions. The total of 273 items were included as to represent clinical competency required for BSN graduates. In phase 2, questionnaires were distributed to nursing faculties of 41 BSN programs to validate the 273-item Instrument developed to measure competency. The total of 34 subjects returned the questionnaire with 81% of response rates. The subjects of the study had an average of 42 months of clinical experience and 13 years of education experience in various nursing areas with an age range of 30 to 52 years. The data were analyzed by utilizing SPSSWIN and the results are as follows. 1) The mean score of the nursing process dimension was supported most with the mean of 3.60(SD=0.32) compared to client and health need dimension(M=3.49, SD=.40), professional role(M=3.41, SD=.44), and nursing interventions(M=3.57, SD=.34). 2) The dimensions of competency were moderately correlated to each other with a range of r=.433 to r=.829, confirming that four dimensions of competency were related but distinct concepts. 3) The items of each dimension were analyzed based on its appropriateness. 'Assessing risk factors of the clients' were most highly supported in client and health need dimension. Most items of nursing process dimension were considered appropriate, while items related to efficient communication were well supported in professional role dimension. In nursing intervention dimension, items on basic nursing skills were highly supported while items on specific nursing interventions such as music therapy or art therapy were considered relatively inappropriate to competency for BSN graduates. The findings clearly showed that the current nursing education more emphasizes nursing interventions based on nursing process than other dimensions of competency. There is a need to reconceptualize nursing curriculum that is able to reflect more of nursing professional role and client/health need dimensions. Further research to validate the instrument by confirming competency dimensions of nursing graduates who are currently working at the hospital has been suggested.

• Science of Emotion and Sensibility
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• v.12 no.3
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• pp.267-278
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• 2009

Today an embodied agent generates a large amount of interest because of its vital role for human-human interactions and human-computer interactions in virtual world. A number of researchers have found that we can recognize and distinguish between various emotions expressed by an embodied agent. In addition many studies found that we respond to simulated emotions in a similar way to human emotion. This study investigates interpretation of mismatched emotions expressed by an embodied agent (e.g. a happy face with a sad voice); whether audio-visual channel integration occurs or one channel dominates when participants judge the emotion. The study employed a 4 (visual: happy, sad, warm, cold) $\times$ 4 (audio: happy, sad, warm, cold) within-subjects repeated measure design. The results suggest that people perceive emotions not depending on just one channel but depending on both channels. Additionally facial expression (happy face vs. sad face) makes a difference in influence of two channels; Audio channel has more influence in interpretation of emotions when facial expression is happy. People were able to feel other emotion which was not expressed by face or voice from mismatched emotional expressions, so there is a possibility that we may express various and delicate emotions with embodied agent by using only several kinds of emotions.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.313-313
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• 2012

In recent years there have been many studies of InGaN/GaN based light emitting diodes (LEDs) in order to progress the performance of luminescence. Many previous literatures showed the performance of LEDs by changing the LED structures and substrates. However, the studies carried out by the researchers so far were very complicated and sometimes difficult to apply in practice. Therefore, we propose one simple method of changing the thickness and the numbers of multiple quantum wells (MQWs) in order to optimize their effects. In our research, we investigated electrical and optical properties by changing the well thickness and the number of quantum well (QW) pair in LED structures by growing the structure -inch Si (111) wafer. We defined the samples from LED_1 to LED_3 according to MQW structure. Samples LED_1, LED_2 and LED_3 consist of 5-pair InGaN/GaN (3.5 nm/ 4.5 nm), 5-pair InGaN/GaN (3 nm/4.5 nm) and 7-pair InGaN/GaN (3.5 nm/4.5 nm), respectively. We characterized electrical and optical properties by using electroluminescence (EL) measurement. Also, Efficiency droop was analyzed by calculating external quantum efficiency (EQE) with varying injection current. The EL spectra of three samples show different emission wavelength peaks, FWHM and the blueshift of wavelength caused by screening the internal electric field because of the effect of different MQW structure. The results of optical properties show that the LED_2 sample reduce the internal electric field in QW than LED_1 from EL spectra. the increase in the number of QW pairs reduces the strain and increase the In composition in MQW. And, the points of efficiency droop's peak show different trend from LED_1 to LED_3. It is related with the carrier density in active region. Thus, from the results of experiments, we are able to achieve high performance LEDs and a reduction of efficiency droop and emission wavelength blueshift by optimizing MQWs structure.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1183-1191
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• 2017

In order to support the service efficiently, a Science and Technology information platform that can share the same contents and technologies is needed. Therefore this study develop a platform that can use various contents and technologies as a common utilization factor, and support a fast and efficient service. In addition, It suggest examples of various APIs in a platform environment system that can utilize scientific data and technologies in various forms according to their use. Throughout the studies, various contents and technologies will be able to connect and interact with each other through the API Gateway on the platform, as well as to integrate Science and Technology contents based on identified researchers, institutions, and terminology data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.43-54
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• 2016

The occurrence of cyber crime is on the rise every year, and the security control center, which should play a crucial role in monitoring and early response against the cyber attacks targeting various information systems, its importance has increased accordingly. Every endeavors to prevent cyber attacks is being attempted by information security personnel of government and financial sector's security control center, threat response Center, cyber terror response center, Cert Team, SOC(Security Operator Center) and else. The ordinary method to monitor cyber attacks consists of utilizing the security system or the network security device. It is anticipated, however, to be insufficient since this is simply one dimensional way of monitoring them based on signatures. There has been considerable improvement of the security control system and researchers also have conducted a number of studies on monitoring methods to prevent threats to security. In accordance with the environment changes from ESM to SIEM, the security control system is able to be provided with more input data as well as generate the correlation analysis which integrates the processed data, by extraction and parsing, into the potential scenarios of attack or threat. This article shows case studies how to detect the threat to security in effective ways, from the initial phase of the security control system to current SIEM circumstances. Furthermore, scenarios based security control systems rather than simple monitoring is introduced, and finally methods of producing the correlation analysis and its verification methods are presented. It is expected that this result contributes to the development of cyber attack monitoring system in other security centers.