• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.142-160
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• 2023

The position of the people who participated in the Bapyo Ritual held in the reign of King Sejong and the corresponding costumes were examined. The king, who was the executive body of the ritual, wore Myeon-Bok, a court dress, and Myeon-Bok was Gujang-Bok made of Jang-wha on Guryu-Pyeongcheongwan. Crown princes, royal families, and government officials wore Oryang-Gwan and Jekraeui, which were Jobok. The crown princes' Joboks were changed from Oryang-Gwan to Wukryang-Gwan in the dynasty year 10 of King Sejong, and in the year of King Munjong's accession, Myeon-Bok was received, and after King Danjong, the crown princes wore Palryu-Pyeongcheongwan and Chiljang-Bok. Diplomats and Jongsagwan who were the envoys wore Sangbok. A Sangbok worn by the diplomat was Samo with Danryeong, Seo-Dae, and Hyeopgeum-Hwa, and a Sangbok worn by Jongsagwan was Samo, Danryeong, Heukgak-Dae, and Heukpi-Hwa. Byulgam, who served as an attendant to the king in the king's close quarters, wore Gongbok and Sangbok. Gongbok consisted of Ja-Geon, Danryeong and Heukpi-Hwa, and Sangbok consisted of orange color Cho-Rip, Jikryeong, Joa, and Heukpi-Hwa. The person holding San, Gae , Sujeongjang, and Geumwolbu wore Ja-Geon and Cheong-Ui, and Seon wore Pimoja and Hong-Ui. Siwigun wore armor and helmets equipped with weapons. Among court musicians, Aksa's costumes consisted of Bokdu, Bigongbok, Geumdonghyeokdae, Bibaekdaedae, and Opiri, and Aksaeng's one composed of Gaechaek, Bisuransam, Hyupgo, Mal, Maldae, and Opiri. As a result of the above, the process of ceremonial clothes becoming uniform clothes in the reign of King Sejong was confirmed. The king and lower-ranking officials such as crown princes, government officials, diplomats, Byulgam, armies for ceremonial weaponry, and court musicians participating in the Bapyo Ritual wore the highest grade of ceremonial clothes for each class. King Sejong had repeated discussions to build a nation based on Confucianism, and arranged each rite and corresponding costume, and the Bapyo Ritual costume was also systematically prepared for each position. The ceremonial clothing organized during the reign of King Sejong was regulated in Yejon and became the basis for continuing to the late Joseon Dynasty.

• Journal of Venture Innovation
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• v.4 no.1
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• pp.51-65
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• 2021

The HR policy in the public sector was closed and operated mainly on written tests, but in 2006, a new evaluation, promotion and education system based on competence was introduced in the promotion and selection system of civil servants. In particular, the seniority-oriented promotion system was evaluated based on competence by operating an Assessment Center related to promotion. Competency evaluation is known to be the most reliable and valid evaluation method among the evaluation methods used to date and is also known to have high predictive feasibility for performance. In 2001, 19 government standard competency models were designed. In 2006, the competency assessment was implemented with the implementation of the high-ranking civil service team system. In the public sector, the purpose of the competency evaluation is mainly to select third-grade civil servants, assign fourth-grade civil servants, and promotion fifth-grade civil servants. However, competency assessments in the public sector differ in terms of competency assessment objectives, assessment processes and competency assessment programmes compared to those in the private sector. For the purposes of competency assessment, the public sector is for the promotion of candidates, and the private sector focuses on career development and fostering. Therefore, it is not continuously developing capabilities than the private sector and is not used to enhance performance in performing its duties. In relation to evaluation items, the public sector generally operates a system that passes capacity assessment at 2.5 out of 5 for 6 competencies, lacks feedback on what competencies are lacking, and the private sector uses each individual's competency score. Regarding the selection and operation of evaluators, the public sector focuses on fairness in evaluation, and the private sector focuses on usability, which is inconsistent with the aspect of developing capabilities and utilizing human resources in the right place. Therefore, the public sector should also improve measures to identify outstanding people and motivate them through capacity evaluation and change the operation of the capacity evaluation system so that they can grow into better managers through accurate reports and individual feedback

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.25-37
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• 2022

The purpose of this study is to survey startup founders within 7 years of founding the importance and satisfaction of the components of the scale-up entrepreneurial ecosystem at the national level in Korea and analyze the direction of scale-up policy by component using IPA (importance-performance analysis). Since the perception of founders, who are the subjects of the entrepreneurial ecosystem, affects the quantity and quality of start-ups, research is needed to analyze and diagnose the perception of scale-up components. For the development of the national economy and entrepreneurial ecosystem, companies that emerge from startups to scale-up and unicorns must be produced, and for this, elements for the scale-up entrepreneurial ecosystem are needed. The results of this study are as follows. First, the importance ranking of the components of the scale-up entrepreneurial ecosystem recognized by founders was in the order of "Financial support by growth stage," "Support for customized scale-up for enterprises," "Improvement of regulations," "Funds dedicated to scale-up," "large-scale investment," and "nurturing technical talents." Second, the factors that should be intensively improved in the importance-satisfaction matrix in the future were 'Pan-Government Integration Promotion Plan', 'Scale-Up Specialized Organization Operation', 'Company Customized Scale-Up Support', 'Regulatory Improvement', and 'Building a Korean Scale-Up Model'. As a result, various and large financial capital for the scale-up entrepreneurial ecosystem, diversification of scale-up programs by business sector, linkage of start-ups and scale-up support, deregulation of new technologies and new industries, strengthening corporate-tailored scale-up growth capabilities, and providing overseas networking opportunities can be derived. In addition, it is expected to contribute to policy practice and academic work with research that derives the components of the domestic scale-up entrepreneurial ecosystem and diagnoses its perception.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.55-73
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• 2024

Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.69 no.2
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• pp.123-132
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• 2024

In this study, two types of biodegradable film prototypes were produced using plastic resin containing rice powder. The application of these biodegradable films in sweetpotato (Ipomoea batatas L. Lam) fields and their impacts of plant growth, yield, and the soil environment were assessed, in comparison with Polyethylene (PE) film. The light transmittance of the biodegradable film containing 30% of 350 mesh rice powder (BF30-350RP) was 0.8%, which was lower than the 2.0% light transmittance of the biodegradable film containing 40% of 500 mesh rice powder (BF40-500RP) and 2.7% light transmittance of PE film. Surface temperature measurements on clear day indicated that the PE film exhibited the lowest temperature, with the minimal difference observed between BF40-500RP and BF30-350RP. Assessment of the damage ratio resulting from agricultural work revealed a ranking of 0.4% for the PE film, 3.3% for BF500-400RP, and 5.3% for BF350-30RP. Visible decomposition of BF40-500RP and BF30-350RP commenced after 40 and 30 days of outdoor exposure, reaching 62.3% and 70.4% decomposition at 90 days post-exposure, respectively. The decomposition of biodegradable films applied to sweetpotato fields progressed more slowly in BF40-500RP than in BF30-350RP. The BF40-500RP film on the surface of the ridges was decomposed by 5%, 30%, 55%, and 90% after 30, 60, 90, and 120 days after planting sweetpotato cuttings, respectively. Both types of biodegradable films at the ridge and furrow borders were completely decomposed after 75 days of sweetpotato planting. In a field where the surface was sealed by mulching without growing sweetpotatoes, the soil moisture and its deviation were lower in the order of PE film, BF40-500RP, and BF30-350RP, but the differences were not significant. The soil temperature was higher for PE film mulching than for the biodegradable films containing rice powder, but the differences were small. Two months after sweetpotato planting, the daily average soil moisture decreased by 2.5%point for BF30-350RP mulching, 1.5%point for BF40-500RP mulching, and 1.1%point for PE film mulching over seven days. Soil temperature was similar for both biodegradable film mulches, but increased steadily for the PE film mulch, reaching a daily average of 0.1℃ higher than for the biodegradable films. Sweetpotato vine growth and tuber yield were similar for all the mulching films tested.

• Journal of Global Scholars of Marketing Science
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• v.19 no.3
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• pp.49-61
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• 2009

This article provides training exercises for executives into interpreting subroutine maps of executives' thinking in processing business and industrial marketing problems and opportunities. This study builds on premises that Schank proposes about learning and teaching including (1) learning occurs by experiencing and the best instruction offers learners opportunities to distill their knowledge and skills from interactive stories in the form of goal.based scenarios, team projects, and understanding stories from experts. Also, (2) telling does not lead to learning because learning requires action-training environments should emphasize active engagement with stories, cases, and projects. Each training case study includes executive exposure to decision system analysis (DSA). The training case requires the executive to write a "Briefing Report" of a DSA map. Instructions to the executive trainee in writing the briefing report include coverage in the briefing report of (1) details of the essence of the DSA map and (2) a statement of warnings and opportunities that the executive map reader interprets within the DSA map. The length maximum for a briefing report is 500 words-an arbitrary rule that works well in executive training programs. Following this introduction, section two of the article briefly summarizes relevant literature on how humans think within contexts in response to problems and opportunities. Section three illustrates the creation and interpreting of DSA maps using a training exercise in pricing a chemical product to different OEM (original equipment manufacturer) customers. Section four presents a training exercise in pricing decisions by a petroleum manufacturing firm. Section five presents a training exercise in marketing strategies by an office furniture distributer along with buying strategies by business customers. Each of the three training exercises is based on research into information processing and decision making of executives operating in marketing contexts. Section six concludes the article with suggestions for use of this training case and for developing additional training cases for honing executives' decision-making skills. Todd and Gigerenzer propose that humans use simple heuristics because they enable adaptive behavior by exploiting the structure of information in natural decision environments. "Simplicity is a virtue, rather than a curse". Bounded rationality theorists emphasize the centrality of Simon's proposition, "Human rational behavior is shaped by a scissors whose blades are the structure of the task environments and the computational capabilities of the actor". Gigerenzer's view is relevant to Simon's environmental blade and to the environmental structures in the three cases in this article, "The term environment, here, does not refer to a description of the total physical and biological environment, but only to that part important to an organism, given its needs and goals." The present article directs attention to research that combines reports on the structure of task environments with the use of adaptive toolbox heuristics of actors. The DSA mapping approach here concerns the match between strategy and an environment-the development and understanding of ecological rationality theory. Aspiration adaptation theory is central to this approach. Aspiration adaptation theory models decision making as a multi-goal problem without aggregation of the goals into a complete preference order over all decision alternatives. The three case studies in this article permit the learner to apply propositions in aspiration level rules in reaching a decision. Aspiration adaptation takes the form of a sequence of adjustment steps. An adjustment step shifts the current aspiration level to a neighboring point on an aspiration grid by a change in only one goal variable. An upward adjustment step is an increase and a downward adjustment step is a decrease of a goal variable. Creating and using aspiration adaptation levels is integral to bounded rationality theory. The present article increases understanding and expertise of both aspiration adaptation and bounded rationality theories by providing learner experiences and practice in using propositions in both theories. Practice in ranking CTSs and writing TOP gists from DSA maps serves to clarify and deepen Selten's view, "Clearly, aspiration adaptation must enter the picture as an integrated part of the search for a solution." The body of "direct research" by Mintzberg, Gladwin's ethnographic decision tree modeling, and Huff's work on mapping strategic thought are suggestions on where to look for research that considers both the structure of the environment and the computational capabilities of the actors making decisions in these environments. Such research on bounded rationality permits both further development of theory in how and why decisions are made in real life and the development of learning exercises in the use of heuristics occurring in natural environments. The exercises in the present article encourage learning skills and principles of using fast and frugal heuristics in contexts of their intended use. The exercises respond to Schank's wisdom, "In a deep sense, education isn't about knowledge or getting students to know what has happened. It is about getting them to feel what has happened. This is not easy to do. Education, as it is in schools today, is emotionless. This is a huge problem." The three cases and accompanying set of exercise questions adhere to Schank's view, "Processes are best taught by actually engaging in them, which can often mean, for mental processing, active discussion."

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.

• Journal of environmental and Sanitary engineering
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• v.24 no.4
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• pp.1-26
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• 2009

We conclude the following with air pollution data measured from city measurement net administered and managed in Gwangju for the last 7 years from January in 2001 to December in 2007. In addition, some major statistics governed by Gwangju city and data administered by Gwangju as national official statistics obtained by estimating the amount of national air pollutant emission from National Institute of Environmental Research were used. The results are as follows ; 1. The distribution by main managements of air emission factory is the following ; Gwangju City Hall(67.8%) > Gwangsan District Office(13.6%) > Buk District Office(9.8%) > Seo District Office(5.5%) > Nam District Office(3.0%) > Dong District Office(0.3%) and the distribution by districts of air emission factory ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%). That by types(Year 2004~2007 average) is also following ; Type 5(45.2%) > Type 4(40.7%) > Type 3(8.6%) > Type 2(3.2%) > Type 1(2.2%) and the most of them are small size of factory, Type 4 and 5. 2. The distribution by districts of the number of car registrations is the following ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%) and the distribution by use of car fuel in 2001 ; Gasoline(56.3%) > Diesel(30.3%) > LPG(13.4%) > etc.(0.2%). In 2007, there was no ranking change ; Gasoline(47.8%) > Diesel(35.6%) > LPG(16.2%) >etc.(0.4%). The number of gasoline cars increased slightly, but that of diesel and LPG cars increased remarkably. 3. The distribution by items of the amount of air pollutant emission in Gwangju is the following; CO(36.7%) > NOx(32.7%) > VOC(26.7%) > SOx(2.3%) > PM-10(1.5%). The amount of CO and NOx, which are generally generated from cars, is very large percentage among them. 4. The distribution by mean of air pollutant emission(SOx, NOx, CO, VOC, PM-10) of each county for 5 years(2001~2005) is the following ; Buk District(31.0%) > Gwangsan District(28.2%) > Seo District(20.4%) > Nam District(12.5%) > Dong District(7.9%). The amount of air pollutant emission in Buk District, which has the most population, car registrations, and air pollutant emission businesses, was the highest. On the other hand, that of air pollutant emission in Dong District, which has the least population, car registrations, and air pollutant emission businesses, was the least. 5. The average rates of SOx for 5 years(2001~2005) in Gwangju is the following ; Non industrial combustion(59.5%) > Combustion in manufacturing industry(20.4%) > Road transportation(11.4%) > Non-road transportation(3.8%) > Waste disposal(3.7%) > Production process(1.1%). And the distribution of average amount of SOx emission of each county is shown as Gwangsan District(33.3%) > Buk District(28.0%) > Seo District(19.3%) > Nam District(10.2%) > Dong District(9.1%). 6. The distribution of the amount of NOx emission in Gwangju is shown as Road transportation(59.1%) > Non-road transportation(18.9%) > Non industrial combustion(13.3%) > Combustion in manufacturing industry(6.9%) > Waste disposal(1.6%) > Production process(0.1%). And the distribution of the amount of NOx emission from each county is the following ; Buk District(30.7%) > Gwangsan District(28.8%) > Seo District(20.5%) > Nam District(12.2%) > Dong District(7.8%). 7. The distribution of the amount of carbon monoxide emission in Gwangju is shown as Road transportation(82.0%) > Non industrial combustion(10.6%) > Non-road transportation(5.4%) > Combustion in manufacturing industry(1.7%) > Waste disposal(0.3%). And the distribution of the amount of carbon monoxide emission from each county is the following ; Buk District(33.0%) > Seo District(22.3%) > Gwangsan District(21.3%) > Nam District(14.3%) > Dong District(9.1%). 8. The distribution of the amount of Volatile Organic Compound emission in Gwangju is shown as Solvent utilization(69.5%) > Road transportation(19.8%) > Energy storage & transport(4.4%) > Non-road transportation(2.8%) > Waste disposal(2.4%) > Non industrial combustion(0.5%) > Production process(0.4%) > Combustion in manufacturing industry(0.3%). And the distribution of the amount of Volatile Organic Compound emission from each county is the following ; Gwangsan District(36.8%) > Buk District(28.7%) > Seo District(17.8%) > Nam District(10.4%) > Dong District(6.3%). 9. The distribution of the amount of minute dust emission in Gwangju is shown as Road transportation(76.7%) > Non-road transportation(16.3%) > Non industrial combustion(6.1%) > Combustion in manufacturing industry(0.7%) > Waste disposal(0.2%) > Production process(0.1%). And the distribution of the amount of minute dust emission from each county is the following ; Buk District(32.8%) > Gwangsan District(26.0%) > Seo District(19.5%) > Nam District(13.2%) > Dong District(8.5%). 10. According to the major source of emission of each items, that of oxides of sulfur is Non industrial combustion, heating of residence, business and agriculture and stockbreeding. And that of NOx, carbon monoxide, minute dust is Road transportation, emission of cars and two-wheeled vehicles. Also, that of VOC is Solvent utilization emission facilities due to Solvent utilization. 11. The concentration of sulfurous acid gas has been 0.004ppm since 2001 and there has not been no concentration change year by year. It is considered that the use of sulfurous acid gas is now reaching to the stabilization stage. This is found by the facts that the use of fuel is steadily changing from solid or liquid fuel to low sulfur liquid fuel containing very little amount of sulfur element or gas, so that nearly no change in concentration has been shown regularly. 12. Concerning changes of the concentration of throughout time, the concentration of NO has been shown relatively higher than that of $NO_2$ between 6AM~1PM and the concentration of $NO_2$ higher during the other time. The concentration of NOx(NO, $NO_2$) has been relatively high during weekday evenings. This result shows that there is correlation between the concentration of NOx and car traffics as we can see the Road transportation which accounts for 59.1% among the amount of NOx emission. 13. 49.1~61.2% of PM-10 shows PM-2.5 concerning the relationship between PM-10 and PM-2.5 and PM-2.5 among dust accounts for 45.4%~44.5% of PM-10 during March and April which is the lowest rates. This proves that particles of yellow sand that are bigger than the size $2.5\;{\mu}m$ are sent more than those that are smaller from China. This result shows that particles smaller than $2.5\;{\mu}m$ among dust exist much during July~August and December~January and 76.7% of minute dust is proved to be road transportation in Gwangju.