• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.3
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• pp.1-12
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• 2016

This study aimed to interpret the fundamental cause of road-kill occurrences and analyzed spatial characteristics of the road-kill locations from Route 44 in Seorak National Park, Korea. Logistic regression analysis was utilized for backward elimination on variables. Seorak National Park Service has constructed GIS-data of 81 road-kill occurrences from 2008 to 2013 and these data were assigned as dependent variables in this study. Considered as independent variables from previous studies and field surveys, vegetation age-class, distance to streams, coverage of fences and retaining walls, and distance to building sites were assigned as road-kill impact factors. The coverage of fences and retaining walls(-1.0135) was shown as the most influential factor whereas vegetation age-class(0.0001) was the least influential among all of the significant factor estimates. Accordingly, the rate of road-kill occurrence can increase as the distance to building sites and stream becomes closer and vegetation age-class becomes higher. The predictive accuracy of road-kill occurrence was shown to be 72.2% as a result of analysis, assuming as partial causes of road-kill occurrences reflecting spatial characteristics. This study can be regarded as beneficial to provide objective basis for spatial decision making including road-kill occurrence mitigation policies and plans in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.348-356
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• 2018

Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.

• Journal of the Korean Orthopaedic Association
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• v.56 no.6
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• pp.498-503
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• 2021

Purpose: The aim of this study were to find ideal entry point of straight antegrade humeral intramedullary nail (SAHN) for the treatment of proximal humerus fracture in Korean and to analyze anatomical conformity using computed tomography. Materials and Methods: From May 2014 to October 2016, the study was conducted retrospectively on 74 Korean patients who had taken computed tomography on both normal and affected shoulder joint as result of shoulder injury. The mean age of the patients was 64.5 years (range, 22-95 years). Radiologic evaluation was done using multiplanar reconstruction technique of the computer tomography on normal proximal humerus. We located ideal entry point of SAHN as the point where humerus intramedullary center axis and humeral head meet. Distance between the entry point and local anatomical landmark was measured. We defined the critical distance as the distance between entry point and the most medial point of the supraspinatus attachment site. For adequate fixation and avoidance of injury to rotator cuff, critical distance should be over 8 mm according to Euler, and we defined the critical type when it is less than 8 mm. Critical distance, sex, age, height, body weight, body mass index was evaluated for the statistical significance. Results: The ideal entry point was as follows: the mean anteroposterior distance, the sagittal distance to the lateral margin of bicipital groove, was 11.5 mm and the mean mediolateral distance, the coronal distance to the lateral margin of grater tuberosity, was 20.5 mm. The mean critical distance, distance from the entry point to the just medial to insertion of the supraspinatus tendon, was 8.0 mm. Critical type with critical distance less than 8 mm was found in 41 in 74 patients (55.4%). Conclusion: The ideal entry point of SAHN in Korean was located on 11.5 mm posteriorly from the lateral margin of bicipital groove and 20.5 mm medially from lateral margin of greater tuberosity. More than half of the cases were critical type. Since critical type can possibly cause rotate cuff injury during nail insertion on entry point, surgeon should consider anatomical variance before choosing surgical option.

• Analytical Science and Technology
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• v.34 no.6
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• pp.259-266
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• 2021

Cannabis (Marijuana) is one of the most widely used drugs in the world, and its distribution has been controlled in South Korea since 1976. Identification of 11-nor-Δ⁹-carboxy-tetrahydrocannabinol (THCCOOH) in urine can provide important proof of cannabis use, and it is considered scientific evidence in the forensic field. In this study, we describe a simultaneous quantitative method for identifying THCCOOH and THCCOOH-glucuronide in urine, using simple liquid-liquid extraction (LLE), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). THCCOOH-D₃ and THCCOOH-glucuronide-D₃ were used as internal standards. Validation results of the matrix effect, as well as recovery, linearity, precision, accuracy, process efficiency, and stability were all satisfactory. No carryover, endogenous or exogenous interferences were observed. The limit of detection (LOD) of THCCOOH and THCCOOH-glucuronide were 0.3 and 0.2 ng/mL, respectively. The developed method was applied to 28 authentic human urine samples that tested positive in immunoassay screening and gas chromatography/mass spectrometry (GC/MS) tests. The ranges of concentrations of THCCOOH and THCCOOH-glucuronide in the samples were less than LOQ~266.90 ng/mL and 6.43~2133.03 ng/mL, respectively. The concentrations of THCCOOH-glucuronide were higher than those of THCCOOH in all samples. This method can be effectively and successfully applied for the confirmation of cannabinoid use in human urine samples in the forensic field.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• The Journal of Korean Philosophical History
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• no.28
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• pp.183-212
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• 2010

The purpose of this study is to provide a theoretical base for making a character education program and to develop a school violence prevention program and analysis the effects of the program in elementary schools. The prevention program was designed to target students, teachers, parents and community residents and utilized the above groups as participants. This study is developed on the basis of Social Emotional Learning as well as Emotional Intelligence which put on the importance on the role of emotion in the problem solving. In concrete, school violence prevention program based on the social and emotional learning, development of integrative programs articulating three key domains directly and indirectly influencing students' character formation, maximum use of the educational institutes' moral education curriculums and potential curriculums in the surrounding environment. To do so, bibliographical study and analysis of the research materials are carried out, and also the professionals' advice is received. The study object is 113 elementary school students of 2 elementary schools in Seoul. For them, the preparatory program is carried out from September 2009 to November 2009. And then, the analysis for the satisfaction degree of participation in the program and for the descriptive results of the school violence prevention education is carried out.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.35-52
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• 2023

Recently, as the non-face-to-face environment has developed due to COVID-19 and environmental pollution, the importance of online digital healthcare is increasing, and venture start-ups and activities such as health care, telemedicine, and digital treatments are also actively underway. This study conducted the impact on the acceptability of digital healthcare smartwatches with an integrated approach of the expanded integrated technology acceptance model (UTAUT2) and the behavioral inference model (BRT). The most advanced integrated technology acceptance model for innovative technology acceptance research was used to identify major factors such as utility expectations, social effects, convenience, price barriers, lack of alternatives, and behavioral intentions. For the study, about 410 responses from ordinary people in their teens to 60s across the country were collected, and based on this, the hypothesis was verified using structural equations after testing reliability and validity of the data. SPSS 23 and AMOS 23 were used for research analysis. Studies have shown that personal innovation has a significant impact on the reasons for acceptance (use value, social impact, convenience of use), attitude, and non-use (price barriers, lack of alternatives, and barriers to use). These results are the same as the results of previous studies that confirmed the influence of the main value of innovative ICT on user acceptance intention. In addition, the reason for acceptance had a significant effect on attitude, but the effect of the reason for non-acceptance was not significant. It can be analyzed that consumers are interested in new ICT products and new services, but purchase them more carefully and selectively. This study has evolved from the acceptance analysis of general-purpose consumer innovation technology to the acceptance analysis of consumer value in smartwatch digital healthcare, which is a new and important area in the future. Industrially, it can contribute to the product's purchase and marketing. It is hoped that this study will contribute to increasing research in the digital healthcare sector, which will play an important role in our lives in the future, and that it will develop into in-depth factors that are more suitable for consumer value through integrated approach models and integrated analysis of consumer acceptance and non-acceptance.

• Research in Plant Disease
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• v.30 no.3
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• pp.229-235
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• 2024

Conidial production is a critical factor in testing pathogenicity and studying the physiology and ecology of fungal pathogens. Therefore, selecting an appropriate condition and medium for consistent conidia production is essential. In this study, we investigated light conditions and suitable medium conditions using the slide culture method to establish optimal conditions for continuous spore acquisition of Bipolaris oryzae. Primarily, we observed conidial production using two B. oryzae isolates, CM23-042 and 23CM10, under two different light conditions: (1) consistent near-ultraviolet (NUV) with fluorescent light, and (2) a 12-hr shift of the NUV-dark cycle. Secondly, we examined conidial formation under seven different media on potato dextrose agar (PDA), V8-Juice agar, minimal medium (MM), sucrose-proline agar (SPA), rabbit food agar (RFA), rice bran agar (RBA), and rice leaf agar (RLA). Under consistent NUV light with fluorescent conditions, conidia were induced in both isolates, whereas conidia were not produced under other conditions after 7 days post-inoculation (dpi). Moreover, B. oryzae isolate CM23-042 produced the highest number of conidia in MM, while isolate 23CM10 yielded the highest number of conidia in PDA after 7 dpi. In summary, our data demonstrated that the consistent NUV light with fluorescent conditions were most conducive for conidia induction in B. oryzae. The selection of a medium for conidiation may vary depending on the B. oryzae isolates, but using MM and PDA or SPA and RFA medium could be effective for spore induction. These findings will contribute to improving conidiation according to the characteristics of collected isolates of B. oryzae.

• 한국사회복지학회:학술대회논문집
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• 2003.10a
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• pp.185-216
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• 2003

This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.