Radiation therapy for lung cancer is an effective treatment during monotherapy or combination therapy. Studies have reported that the optimum utilization rate of radiation therapy is estimated at 61% to 74%. Radiation therapy in Korea has been investigated to be low; further studies are needed. This study was intended to assess the appropriateness of the use of radiation and to reveal the use of radiation therapy-related factors by examining radiation therapy in lung cancer patients of Busan and South Gyeongnam Province. This study was aimed at the population diagnosed with lung cancer in Busan and South Gyeongnam Province. To conduct the study, 1036 patients enrolled in two hospitals were collected and 897 appropriate as subjects were selected. We compared the optimum utilization rate and actual rate of radiation therapy, and revealed the adequacy and related factors for use of radiotherapy. Of 897 patients, 503 (56%) were treated with medical therapy and 394 (44%) were given radiotherapy. The radiotherapy utilization rate of all lung cancer patients was 42%. The proportion of non-small cell lung cancer by histologic type was 33% and that of small cell lung cancer was 90%. Factors related to radiation therapy used in cancer were age, histological type, clinical stage, doctor refereed to, and clinical examination. Compared to radiation utilization by region (site), curative chest therapy was 42%; palliative treatment was 26%. In the comparison of histologic types, utilization of small-cell lung cancer is lower; the lowest especially in the stage III. Utilization of radiation therapy in Busan and South Gyeongnam Province was lower than the reasonable one. Utilization difference could be explained by patient factors, tumor factors, and health service factors. To improve utilization,development ofoutreach service programs and activation of the multidisciplinary team are required.
This study was aimed at looking into the distribution status and age structure of Abies holophylla population in Sudo-Am temple forest. It was found that a total of 302 individuals of Abies holophylla existed which were more than 2m in height within the study area. Furthermore the population size is one of the largest in the southern region of Korea. The CBH of Abies holophylla ranged from 1.5 cm to 500.8 cm. Age structure of Abies holophylla looks like a gourd-shaped bottle. This means that they have an unstable structure status and do not survive very long. This status results from a variety of factors including, vegetation succession, anthropogenic activities, and global warming. The environmental characteristics of Abies holophylla population was $931{\pm}64.5m$ in mean altitude, $19.2{\pm}8.7^{\circ}$ in mean slope in the northeastern and southeastern area of the slope direction, and $1,324,323{\pm}174,459wh\;m^{-2}$ in average of direct normal irradiation. Among the site environmental factors, the significant ones which influence the potential habitat for Abies holophylla distribution were chosen using the MaxEnt model. According to the results of this study, altitude and slope were found as the important factors. The average value of environmental conditions by ROC analysis were altitude 903.2 m, slope $20.04^{\circ}$, irradiation $1,352.248wh\;m^{-2}$, and the southeastern aspect.
This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.
Journal of the Korean Institute of Landscape Architecture
/
v.38
no.5
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pp.1-11
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2010
The outdoor space of an elementary school is the most familiar and most educational area for children. A paradigm shift in education has demanded a new role and direction for these outdoor spaces. The construction of children-friendly spaces, however, lags behind. The child-participatory design process is very meaningful at a time when many outdoor spaces have difficulties in reflecting the varied and specific demands of children. This study realized the necessity for a design that includes a child-participatory design process in construction the outdoor spaces of elementary schools. Through reference study and a theoretical approach of related laws, this study established a child-participatory design process model and applied it to Seoul Don-Am Elementary School. The design process included playing games and providing interesting tools to increase the participation of children in suggesting and presenting their opinions more freely. The design process of this study is described in five steps(eliciting interest in and recognition of the target space, Understanding children's expectations and the expressing thereof, Establishing factors for planning, Visualizing and arranging spaces, and Decision-making and building a final design plan). This process was applied to the planning and design of an outdoor space for Seoul Don-Am Elementary School. In this study, it is clear that the design of the participators and experts have a different purpose. Thus, the process of the design has more meaning than the final product. In addition, it is expected that an improvement in both tangible and intangible designs will be seen. Using a participatory design process, this study successfully improved the facilities and arrangement planning of an outdoor space. At the same time, it also enhanced the interest and participation of children in the process of creating the kind of school they desire. The significance of this study is that it has suggested an effective model to reflect the demands of children, the true users of the outdoor space, and the results were actually applied to elementary school outdoor planning and designing. This study enhanced the awareness of school members in the process of building the school's outdoor space.
Natural environmental ecology ofthe environmental impact assessment(EIA)is very much lacking in quantitative evaluation. Thus, this study attempted to evaluate quantitative assessment for ecosystem service in the site of Eco-delta project in Busan. As a part of climate change adaptation, this study evaluated and compared with the value for carbon fixation and habitat quality using the InVEST model before and after development with three alternatives of land-use change. Carbon fixation showed 216,674.48 Mg of C (year 2000), and 203,474.25 Mg of C (year 2015)reducing about 6.1%, and in the future of year 2030 the value was dropped to 120,490.84 Mg of C which is 40% lower than year 2015. Alternative 3 of land use planning was the best in terms of carbon fixation showing 6,811.31 Mg of C. Habitat quality also changed from 0.57 (year 2000), 0.35 (year 2015), and 0.21 (year 2030) with continued degradation as development goes further. Alternative 3 also was the highest with 0.21(Alternative 1 : 0.20, Alternative 2 : 0.18). In conclusion,this study illustrated that quantitative method forland use change in the process of EIA can helpdecision making for stakeholders anddevelopers with serving the best scenario forlow impact of carbon. Also it can help better for land use plan, greenhouse gas and natural environmental assets in EIA. This study could be able to use in the environmental policy with numerical data of ecosystem and prediction. Supplemented with detailed analysis and accessibility of basic data, this method will make it possible for wide application in the ecosystem evaluation.
The purpose of this study was to examine the characteristics of Seoul Olympic Organizing Committee's official documents. To conduct this work, the fundamental of producing archives were examined by analyzing structure and management of Seoul Olympic Organizing Committee and structure of official document production. After all, simultaneous and synthesis characteristics of Seoul Olympic Organizing Committee's official documents were presented through overall analysis of production fundamental and relationship between their management and remained archives. The result of this study are as follows. Firstly, The Organizing Committee had bicameral organizational structure and matrix organizational format consisting of functional department and project department. Indicating the institutions and development phase of decision making in the committee, most of institutions were in name only. Also, there were many problems occurred in the procedure of decision making since the president of committee exercised all of the authorities. Secondly, It was found that existing official documents of the committee were partial and caused fragment phenomenon and severe situations because of unsystematic archival management department and regulations. Moreover, as the result of investigating production procedure and management of official documents, procedure of production, distribution, preservation and abolition of them were specifically verified. Thirdly, It was verified that the official documents were abolished arbitrarily because of unsystematic archival management department and insufficient regulations. For the actual condition of management, filing or description activity which is essential measure for using and utilizing the official documents has not been conducted yet. Based on these facts, the characteristics of Seoul Olympic Organizing Committee's official documents can be referred as follows. The official archives of the committee have multiplicity of the origin and severe fragment phenomenon damaging the origin and the elementary substance of the archives. Also, the format of existing archives was unbalance. Besides, there was not enough related research since they were in adverse situation to utilize them as the archives which are not assessed or not arranged. Thus, it was hard to grasp the utility value at present and future, and was also limited for usage object.
Journal of Korean Society of Disaster and Security
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v.12
no.1
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pp.11-21
/
2019
This study assessed the risk of disaster by using QRE(Quick Risk Estimation - UNISDR Roll Model City of Basic Evaluation Tool) tools for three natural disasters and sixteen social disasters managed by the Seoul Metropolitan Government. The criteria for selecting 19 disaster types in Seoul are limited to disasters that occur frequently in the past and cause a lot of damage to people and property if they occur. We also considered disasters that are likely to occur in the future. According to the results of the QRE tools for disaster type in Seoul, the most dangerous type of disaster among the Seoul city disasters was "suicide accident" and "deterioration of air quality". Suicide risk is high and it is not easy to take measures against the economic and psychological problems of suicide. This corresponds to the Risk ratings(Likelihood ranking score & Severity rating) "M6". In contrast, disaster types with low risk during the disaster managed by the city of Seoul were analyzed as flooding, water leakage, and water pollution accidents. In the case of floods, there is a high likelihood of disaster such as localized heavy rains and typhoons. However, the city of Seoul has established a comprehensive plan to reduce floods and water every five years. This aspect is considered to be appropriate for disaster prevention preparedness and relatively low disaster risk was analyzed. This corresponds to the disaster Risk ratings(Likelihood ranking score & Severity rating) "VL1". Finally, the QRE tool provides the city's leaders and disaster managers with a quick reference to the risk of a disaster so that decisions can be made faster. In addition, the risk assessment using the QRE tool has helped many aspects such as systematic evaluation of resilience against the city's safety risks, basic data on future investment plans, and disaster response.
Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.
Kyeong-Soo Lee;Jung Jeung Lee;Keon-Yeop Kim;Jong-Yeon Kim;Tae-Yoon Hwang;Nam-Soo Hong;Jun Hyun Hwang;Jaeyoung Ha
Journal of agricultural medicine and community health
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v.49
no.1
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pp.13-36
/
2024
Objectives: The purpose of this field case report is 1) to analyze the community's strategy and performance in responding to infectious diseases through the case of COVID-19 infectious disease crisis response of Daegu Metropolitan City, and 2) to interpret this case using governance theory and infectious disease response governance framework. and 3) to propose a strategic model to prepare for future infectious disease outbreaks of the community. Methods: Cases of Daegu Metropolitan City's infectious disease crisis response were analyzed through researchers' participatory observations. And review of OVID-19 White Paper of Daegu Metropolitan City, Daegu Medical Association's COVID-19 White Paper, and literature review of domestic and international governance, and administrative documents. Results: Through the researcher's participatory observation and literature review, 1) establishment of leadership and response system to respond to the infectious disease crisis in Daegu Metropolitan City, 2) citizen's participation and communication strategy through the pan-citizen response committee, 3) cooperation between Daegu Metropolitan City and governance of public-private medical facilities, 4) decision-making and crisis response through participation and communication between the Daegu Metropolitan City Medical Association, Medi-City Daegu Council, and medical experts of private sector, 5) symptom monitoring and patient triage strategies and treatment response for confirmed infectious disease patients by member of Daegu Medical Association, 6) strategies and implications for establishing and utilizing a local infectious disease crisis response information system were derived. Conclusions: The results of the study empirically demonstrate that collaborative governance of the community through the participation of citizens, private sector experts, and community medical facilities is a key element for effective response to infectious disease crises.
With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.
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