• Korean Journal of Heritage: History & Science
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• v.47 no.3
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• pp.42-59
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• 2014

Han Pilgyo (1807~1878) was a scholar-official in the later period of the Joseon Dynasty. The research results on spatial structure and landscape techniques of the central government office reviewed through the Sukcheonjeado(宿踐諸衙圖) album collection edited by Han Pilgyo are as follows. First, Sukcheonjeado(宿踐諸衙圖) using Sabangjeondomyobeob(四方顚倒描法, a Korean traditional drawing type) is uniquely proven historical data which helps to understand the spatial structure of the center and local government offices and the characteristics of cultural landscape. Secondly, the central government office located in Yookcho(六曹) Street which is the outside Gwanghwamun(光化門) of the Main Palace(Gyeongbokgung, 景福宮) of the Joseon Dynasty has a center facility(Dangsangdaecheong, 堂上大廳) and attached buildings which are distributed from high to low or from left to right, according to its order of presidency in square-shaped portion of land. The main building was located facing south and by considering the administrative convenience, the environmental effect and the practice of Confucian norms this structure reflects a hierarchical landuse system. Thirdly, the main buildings such as Dangsangdaecheong and Hyangcheong(鄕廳), which are the working place for government officials had large square front yards for constructing a practical patio garden. The back garden was tended to reflect the meaning landscape, with such as pond and pavilion. A particular point was the repeated crossing of active space and passive space(movement and stillness, building and yard, yard and garden), which implements the Yin-Yang principle. Fourth, the characteristics that can be extracted from the central government office landscapes are (1) expandability of outdoor space, connects of front gardens, emphasizes the characteristic of serviceable gardens and back gardens, which in turn emphasizes scenic sides, (2) introduction of water features(square-shaped ponds) that can be used as fire-water and considers environmental-amenity and landscape characteristics, (3) introduction of pavilions for relaxation, mental and physical discipline, and the development of back gardens, (4) significance of Jeongsimsoo(庭心樹) in such things as selection of concise landscape plants like lotus, willow, pine, zelkova and so on, and limited plant introduction, (5) environmental design techniques which set importance on not only aesthetics and ideality but also practical value. Thus, these aspects of the government office landscape can be said to be the universality and particularity of Korean traditional landscape technique and can be extracted similarly in the palaces, temples, lecture halls, and houses of the upper class of the Joseon Dynasty.

• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.166-180
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• 2022

Objective: This study evaluated the effects of a non-face-to-face obesity management program, implemented during the pandemic. Methods: The non-face-to-face obesity management program used the Intervention mapping protocol (IMP). The program was put into effect over the course of eight weeks, from September 14 to November 13, 2020 in 48 overweight and obese adults, who applied to participate through the Daegu Citizen Health Support Center. Results: IMP was first a needs assessment was conducted; second, goal setting for behavior change was established; third, evidence-based selection of arbitration method and performance strategy was performed; fourth, program design and validation; fifth, the program was run; and sixth, the results were evaluated. The average weight after participation in the program was reduced by 1.2kg, average WC decreased by 3cm, and average BMI decreased by 0.8kg/m² (p<0.05). The results of the health behavior survey showed a positive improvement in lifestyle factors, including average daily intake calories, fruit intake, and time spent in walking exercise before and after participation in the program. A statistically significant difference was seen (p<0.05). The satisfaction level for program process evaluation was high, at 4.57±0.63 point. Conclusion: The non-face-to-face obesity management program was useful for obesity management for adults in communities, as it enables individual counseling by experts and active participation through self-body measurement and recording without restriction by time and place. However, the program had some restrictions on participation that may relate to the age of the subject, such as skill and comfort in using a mobile app.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.79-88
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• 2023

Trifludimoxazin is a triazinone herbicide that inhibits the synthesis of protoporphyrinogen oxidase (PPO). The lack of PPO damages the cell membranes, leading to plant cell death. An official analytical method for the safety management of trifludimoxazin is necessary because it is a newly registered herbicide in Korea. Therefore, this study aimed to develop a residual analysis method to detect trifludimoxazin in five representative agricultural products. The EN method was established as the final extraction method by comparing the recovery test and matrix effect with those of the QuEChERS method. Various sorbent agents were used to establish the clean-up method, and no differences were observed among them. MgSO₄ and PSA were selected as the final clean-up conditions. We used LC-MS/MS considering the selectivity and sensitivity of the target pesticide and analyzed the samples in the MRM mode. The recovery test results using the established analysis method and inter-laboratory validation showed a valid range of 73.5-100.7%, with a relative standard deviation and coefficient of variation less than 12.6% and 14.5%, respectively. Therefore, the presence of trifludimoxazin can be analyzed using a modified QuEChERS method, which is widely available in Korea to ensure the safety of residual insecticides.

• Journal of agricultural medicine and community health
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• v.48 no.4
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• pp.239-250
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• 2023

Objective: This study was a preliminary study for the prevention programs for farmers' occupational diseases. It selected the priorities recognized by farmers, such as occupational diseases, and also identifies the effectiveness and feasibility of prevention programs among diseases recognized by farmers. Therefore, we plan to use it as basis data for future farmer safety and health programs. Method: The subjects of the study were farmers living in the region, selected through a snowball recruitment method, and a total of 671 people were targeted. The priority selection method was the Basic Priority Rating System (BPRS) method, and among the occupational diseases, programs to prevent musculoskeletal diseases, cardiovascular and respiratory diseases, and pesticide poisoning were surveyed on the effectiveness and feasibility of farmers. Results: Among occupational diseases, the highest priority was musculo-skeletal disease, followed by respiratory disease and pesticide poisoning. Among the programs for musculoskeletal disease, 'use of agricultural work convenience equipment and auxiliary tools' had the highest perceived effectiveness and feasibility. Among the five programs for pesticide poisoning, 'equipment of protective equipment such as pesticide protective clothing/glove' had the highest effectiveness at 67.4%, and 'compliance with pesticide use instructions' had the highest level of feasibility at 64.3%. Among the four programs to prevent respiratory diseases, 'wearing a dust mask or gas mask' was the highest at 65.5% in terms of both effectiveness and feasibility. Conclusion: When carrying out safety and health programs for farmers, the priorities recognized by farmers should be taken into consideration, and the program contents should also be developed taking into account the size of effect and feasibility recognized by farmers.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.685-698
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• 2023

This study aimed to identify binge-eating behavior and food addiction in Korean population and to determine their associations with obesity, eating behaviors, mental health and cognitive characteristics. We collected clinical questionnaire scores related to eating problems (e.g. binge eating, food addiction, food cravings), mental health (e.g. depression), and cognitive functions (e.g. impulsivity, emotion regulation) in 257 Korean adults in the normal and the obese weight ranges. Binge-eating and food addiction were most frequent in obese women (binge-eating: 46.6%, food addiction: 29.3%) when we divided the participants into 4 groups depending on gender and obesity status. The independence test using the data with propensity score matching confirmed that binge-eating and food addiction were more prevalent in obese individuals. Finally, we constructed the logistic regression models using forward selection method to evaluate the influence of various clinical questionnaire scores on binge-eating and food addiction respectively. Binge-eating was significantly associated with the clinical scales of eating disorders, food craving, state anxiety, and emotion regulation (cognitive reappraisal) as well as food addiction. Food addiction demonstrated the significant effect of food craving, binge-eating, the interaction of obesity and age, and years of education. In conclusion, we found that binge-eating and food addiction are much more frequent in females and obese individuals. Both binge-eating and food addiction commonly involved eating problems (e.g. food craving), but there was difference in mental health and cognitive risk factors. Therefore, it is required to distinguish food addiction from binge-eating and investigate intrinsic and environmental risk factors for each pathology.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Cartoon and Animation Studies
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• s.9
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• pp.127-142
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• 2005

Not only in Korea but throughout the entire world millions of people are in contact with images. Images have become a medium through which to transmit anything from simple visualizations of moving images to knowledge and information. The age of the internet has arisen thanks to scientific development, and the internet generation's acquisition of information is continuously becoming faster. The spectators, ufo must choose amongst the excessive amount of available information, are changing along with it just as quickly. The method of visual transmission has changed to match the demands of the fast-changing pace of the new generation. In order to receive an instantaneous selection amongst much information, the primary requisite is attracting one's attention, and then presenting a corresponding feeling of satisfaction. The early stages of film arose from the desire to capture one's actual situation as it realty is. Unsatisfied with the still picture, people developed the motion picture. Research has succeeded in reproducing 3-dimensional images more realistic than the actual image we perceive as a result of the difference in visual perspective of both eyes and their response to rays of light From color film to 3-dimensional pictures, people enjoy the magnificent results of this. All fields within the category of film are continuously studying the human desire to pursue their visual side, namely the pursuit of visual images with a maximum sense of reality. The images that millions of people around the world see now are flat. The screen's depth and optical illusions effectively give a sense of reality while conveying information. However, although the flat screen is able to create a sense of depth using the different visual perspective of each eye for the realization of a cubic effect, there are limitations. Entering the 21s1 century, there is a quickly-arising branch within the field of image media which seeks to overcome these limitations Although 3-dimensional images began in films, entering the latter half of the 20th century, due to development of 3-dimensional images using the mediums of the animation field, cellular phones, advertisement screens, television etc., without restriction is designated as 'image.'. With research having started around 1900 and continuing for over 100 years, we are now able to witness the popularization of 3-dimensional films happening before our very eyes. Within our own country, we can frequently see them at amusement parks and museums. In the future, through the popularization of HDTV etc., there is a good outlook for practical use of 3-dimensional images in televisions with advanced picture qualify as well as in other areas. Together with the international current, research on 3-dimensional films has been activated in Korea and is rising as a main current in the film industry. Within this context, the contents and understanding of 3-dimensional images must keep in step with the pace of technical advancements. In order to accelerate of development of film contents to keep in pace with technical developments, this dissertation presents the techniques and technical aspects of future developments, and shows the need to prepare in advance to make the field grow- and thereby avoid having a lack of experts and being conquered by other nations in the field - rather than only advancing the technical aspects and importing the contents. This dissertation aims to stimulate interest and continual research by progressive-thinking people related to the film industry. Part II looks into the definition and types of 3-dimensional motion pictures, the terminology, the fundamentals of image formation, current market fluctuations, and looks into 3-dimensional techniques which can be borrowed and introduced in 3-dimensional animations. Part III concerns 3-dimensional animated films. It analyzes 3-dimensional production techniques while using the introduction of specific animation techniques in the 2004 production Lee Sun Shin and Nelson - Naval Heroes 3-dimensional animation produced in 2004 by Clay & Puppet Stop-Motion Animation & Computer Graphic. Original Korean title: 해전영웅 이순신과 넬슨. as an example, and it also looks into how current film techniques used in animations can be applied in 3-dimensional films. Additionally, the actual stages of the various fields of 3-dimensional animations are presented. Given the current direction and advancement of 3-dimensional films making use of animations and the possible realization of this field, the author plans to weigh the development of this yet unexploited new market Not looking at the current progress of the field, but rather the direction of the hypothetical types of animation techniques, the author predicts the marketability and possibility of development of each area.

• Journal of agricultural medicine and community health
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• v.27 no.2
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• pp.87-105
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• 2002

In order to find out the knowledge, attitude, and experience of community health practitioners(CHP) on complementary therapy, 393 community health practitioners who provide primary health care service in Busan, Kyeongnam, and Daegu, Gyeongbuk regions were interviewed or surveyed by mail from February 1st to March 31st, 2002. In terms of interest of CHPs toward 11 different hinds of complementary therapy, the rate of interest for soojichim was the highest with 75.3%. Aroma therapy had the interest of 71.0% of the CHPs, oriental medicine had 67.4%, and massage had 67.4%. The interest for shiatsu was 64.6%, while homeopath had the lowest rate of interest of 18.1%. In terms of reliance on the treatment results, oriental medicine scored the highest with 92.6%, and soojichim, massage, and shiatsu followed with 85.5%, 83.7%, and 81.7% respectively. Homeopath had the lowest reliance of 18.1%. The 65.1% of the CHPs had the experience of recommending oriental medicine to patients. 50.4% indicated that they had recommended soojichim, and 44.8% had recommended massage before. Shiatsu and aromatherapy followed with 34.4% and Homeopath had the lowest rate of 2.80%. When CHPs were asked if they had received any training in complementary therapy, 33.1% indicated that they had studied soojichim and 13.2%stated that they had learned oriental medicine. Aromatherapy, massage, and shiatsu followed with 11.2%, 8.4%, and 5.6% respectively On the other hand, none of the CHPs had received training in homeopath. In terms of using complementary therapy during the past 5 years, 23.9% had been treated with oriental medicine, and 18.896 had received soojichim. 5.9% had received aromatherapy, 5.3% had used massage, and 5.1% had experience with shiatsu. None of the practitioners had used homeopath during the past 5 years. Significantly many number of practitioners indicated that they had excellent treatment results with all hinds of complementary therapy, and there were rare cares of side effects. When they were asked if they wanted complementary therapy to become part of the curriculum during re-training or training for public service personnels, 78100 wanted soojichim, 69.2% wanted oriental medicine, and 67.9% wanted aroma therapy. 63.9% wanted shiatsu to be included, and 63.1% wanted massage. When CHPs were asked if they wanted to use complementary therapy during primary health care, 63.6% wanted to use soojichim, 52.9% wanted massage, and 51.9% wanted to use aroma therapy. Oriental medicine also showed a high rate of 50.1%. On the other hand, only a small percentage wanted to use chiropractic or homeopath with 17.0% and 12,2% respectively. Among the CHPs, there were some who had administered complementary therapy during the past 5 years. 84% had administered soojichim, 4.6% had administered oriental medicine, and 2.5% had administered massage 2.5% of the CHPs answered that they had administered aromatherapy. However, none of them had administered apitherapy or homeopath. Most of patients showed positive responses, and the rate of side effect was very low. As shown in the above results, although CHPs have a high rate of interest, reliance, and experience in recommending complementary therapy, only a low percentage of them had received any training in complementary therapy. In addition, since there were little side effects when they received or administered complementary therapy, they hoped complementary therapy, which can be beneficial to health, to be introduced to the curriculum. Therefore, in order to provide community members with complementary therapy and the correct information regarding the selection of complementary therapy that could be beneficial to health, a policy of continuous interest and support is needed so that CHPs can he provided with a systemic and rational curriculum of complementary therapy.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.