• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.194-205
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• 2006

The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Cartoon and Animation Studies
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• s.47
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• pp.31-52
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• 2017

NCS education was created to realize a society in which skills and abilities are respected, such as transcending specifications, establishing recruitment systems, and developing and disseminating national incompetence standards. At the university level, special lectures and job training are being strengthened to raise industrial experts. Especially, in the field of animation, new technologies are rapidly emerging and demanding convergent talents with various fields. In order to meet these social demands, there is a limit to the existing one-class teaching method. In order to solve this problem, it is necessary to participate in a variety of specialized teachers. In other words, rather than solving problems of students' job training and job creation, It is aimed to solve jointly, Team teaching was suggested as a method for this. The expected effects that can be obtained through this are as follows. First, the field of animation is becoming more diverse and complex. The ability to use NCS job-related skills pools can be matched with professors from other departments to enable a wider range of professional instruction. Second, it is possible to use partial professorships in other departments by actively utilizing professors in the university. This leads to the strengthening of the capacity of teachers in universities. Third, it is possible to build a broader and more integrated educational system through cooperative teaching of professors in other departments. Finally, the advantages of special lectures and mentor support of college professors' pools are broader than those of field specialists. A variety of guidance for students can be made with responsible professors. In other words, time and space constraints can be avoided because the mentor is easily met and guided by the university.

• 대한공업교육학회지
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• v.38 no.2
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• pp.48-67
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• 2013

This study tried to suggest implications about operation direction of specialized high schools (SHS) by researching awareness of middle school students (MSS), school parents (SP), human resources directors in industrial institutions (HRDII) who will be the main users of SHS education, about entering SHS and career after graduating from SHS. Seniors of middle school, SP and HRDII in Asan, Chungnam were the subject of this survey research. The summary of the result of this study is as follow: First, MSS and SP usually hoped to enter general high schools rather than vocational education schools such as SHS, meister high schools, and MSS considered school records and SP considered aptitude and talent for the factors to choose high school. Second, MSS, SP, and HRDII recognized purposes of SHS as improvement of talent and aptitude, and getting a job. As for positive images of SHS, they recognized it as applying talent and aptitude to life early, getting good jobs easily, fast independence after graduation, and learning excellent technologies, and as for negative images of SHS, they recognized it as social prejudices and discrimination, students with bad school records enter them, disadvantages about promotion and wages, and being unfavorable for entering universities. They also recognized education of SHS as being effective for improvement of basic and executive ability and key competency, development of creative human resources, and improvement of right personality and courteous manners. Third, many MSS and SP showed intention to enter SHS if it is established in Asan. They wished to enter SHS because they would like to apply their aptitude and talent to life early, learn excellent skill, and hope for early employment, on the other hand, they did not wish to enter SHS because it was not suited for their aptitude and talent, awareness about SHS is low, it is unfavorable to enter universities, and there were social prejudices and discrimination. They also similarly hoped for getting jobs and entering universities after graduating from SHS. And the reason they wanted to get a job was usually because they want to be successful by advancing into society early, or because it is still hard to get a job even after graduate from the university, on the other hand, the reason they want to enter university is because is usually in-depth education about major and social discrimination about level of education. The ability to perform duties forms the greatest part of the employment standard that MSS, SP, and HRDII aware. MSS and SP usually hoped for industrial, home economics and housework and commercial majors in SHS, and considered aptitude and talent, the promising future, and being favorable for employment for choosing major. The reason HRDII hire SHS student was to develop student into talent of industrial institution, ability of student, and need for manpower with high school graduation level, and there were also partial answer that they can hire SHS student if they have ability to perform duties. The proposals about operation direction of SHS according to the results above are as follow: SHS should diversify major and curriculum to meet various requirements of student and parents, establish SHS admission system based on career guidance, and improve student's ability to perform duties by establishing work-based learning. The Government should organize work-to-school policy to enable practical career development of students from SHS, and promote relevant policy to reinforcing SHS education rather than quantitative evaluation such as employment rate, and cooperative support from each government departments is required to make manpower with skill related to SHS to get proper evaluation and treatment.