• Title/Summary/Keyword: 탐색연구

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Analysis of socio-demographic and dietary factors associated with fruit and vegetable consumption among Korean adolescents: use of data from the 7th and 8th Korea National Health and Nutrition Examination Survey (2016-2019) (한국 청소년의 과일 및 채소 섭취와 관련된 인구사회학적 특성 및 식생활 분석: 국민건강영양조사 제7-8기 (2016-2019) 자료 이용)

  • Bokyeong Yun;Seunghee Kye
    • Journal of Nutrition and Health
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    • v.57 no.3
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    • pp.292-306
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    • 2024
  • Purpose: This study investigated fruit and vegetable intake and associated socio-demographic and dietary factors, and compared the nutritional intake according to the fruit and vegetable intake level among Korean adolescents. Methods: This study was conducted on 1,676 adolescents who participated in the 2016-2019 Korea National Health and Nutrition Examination Survey. The subjects were classified into four groups based on the fruit and vegetable intake recommendations in 2020 Dietary Reference Intakes for Koreans: Application (KDRIs Application): sufficient fruit intake (SF) group, sufficient vegetables intake (SV) group, sufficient fruit and vegetables intake (SFV) group, and not sufficient fruit and vegetable intake (NS) group The nutrient intake per day in each group was compared.. Logistic regression analysis was performed to examine the factors influencing fruit and vegetables intake. Results: In the sample of adolescents surveyed, only 1.40% met the recommended daily intake of fruits and vegetables, while 79.54% fell below the established threshold for adequate consumption. Female adolescents, those with fathers holding university degrees or above, and those who ate breakfast at least three times a week were likelier to have adequate fruit intake. Male adolescents and those from higher-income households were likelier to consume vegetables. Females, those who ate out daily, those from lower-income households, and those who understood food labels were likelier to have adequate fruit and vegetable intake. The daily nutrient intake and intake-to-requirement ratio significantly differed according to the fruit and vegetable intake groups. The NS and SF group had lower ratios for calcium and iron, while the NS group had the lowest vitamin A and C intake. By contrast, the SFV group met almost all daily nutrient requirements, except for calcium and vitamin A. Conclusion: This study highlights the need for nutrition education programs to encourage adolescents to consume adequate amounts of fruits and vegetables.

In vitro micropropagation of radish (Raphanus sativus L.) using callus induction and plant regeneration (캘러스 유기와 식물체 재분화를 이용한 무의 기내 대량증식)

  • You Kyoung Kim;Sug Youn Mo;Su Bin Choi;Han Yong Park
    • Journal of Plant Biotechnology
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    • v.50
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    • pp.155-162
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    • 2023
  • Radish (Raphanus sativus L.), a root vegetable grown worldwide, is consumed in several ways. In the cross between parental lines to produce F1 seeds of radish, the problem of low purity may arise because of pollen contamination. Therefore, we aimed to establish conditions for callus induction and regeneration so that in vitro cultured plants could be used for the propagation of stock seeds. The most effective hormone combination containing various concentrations of 2,4-D, TDZ, and kinetin was selected for callus induction using radish hypocotyl, and the induced calli were transferred to two types of hormone media to investigate the optimal conditions for shoot regeneration of the callus. The combination of 1 mg/L 2,4-D + 0.05 mg/L kin was the most effective for callus induction of RA2 and RA10, 1 mg/L 2,4-D + 0.1 mg/L kin + 0.025 mg/L TDZ of RA4, and 1 mg/L 2,4-D + 0.2 mg/L kin of RA30. Shoot regeneration of the RA4 callus occurred in both shoot regeneration media, but the frequency was much higher in the 5H+1B medium (1 mg/L NAA + 0.1 mg/L 2,4-D + 1 mg/L IPA + 0.02 mg/L GA3 + 2 mg/L zeatin + 1 mg/L BA). For the in vitro micropropagation of radish, the conditions selected in this study can assist in the propagation and maintenance of stock seeds to produce F1 seeds.

Development of an evaluation tool for dietary guideline adherence in the elderly (노인의 식생활지침 실천 평가도구 개발)

  • Young-Suk Lim;Ji Soo Oh;Hye-Young Kim
    • Journal of Nutrition and Health
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    • v.57 no.1
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    • pp.1-15
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    • 2024
  • Purpose: This study aimed to develop a comprehensive tool for assessing dietary guideline adherence among older Korean adults, focusing on the domains of food and nutrient intake, eating habits, and dietary culture. Methods: Candidate items were selected through a literature search and expert advice. The degree of adherence to dietary guidelines was then evaluated through a face-to-face survey conducted on 800 elderly individuals across five nationwide regions. The items for dietary guideline adherence evaluation tool were selected through exploratory factor analysis of the candidate items in each of the three areas of the dietary guidelines, and construct validity was verified by performing confirmatory factor analysis. Using the path coefficient of the structural equation model, weights were assigned to each area and item to calculate the dietary guideline adherence score. A rating system for the evaluation tool was established based on national survey results. Results: A total of twenty-eight items were selected for evaluating dietary guideline adherence among the elderly. Thirteen items related to food intake, seven to eating habits, and eight to dietary culture. The average score for dietary guideline adherence was 56.9 points, with 49.8 points in the food intake area, 63.2 points in the eating habits area, and 58.6 points in the dietary culture area. Statistically significant correlations were found between dietary guideline adherence scores and food literacy (r = 0.679) and nutrition quotient scores (r = 0.750). Conclusion: The developed evaluation tool for dietary guideline adherence among Korean older adults can be used as a simple and effective instrument for comprehensively assessing their food and nutrient intake, dietary habits, and dietary culture.

A Study of Myth of King Heokgeose, the Founder of Shilla Dynasty from a Perspective of Analytical Psychology (신라 시조 혁거세왕 신화에 대한 분석심리학적 연구)

  • Sang Ick Han
    • Sim-seong Yeon-gu
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    • v.28 no.1
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    • pp.50-87
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    • 2013
  • C. G. Jung believed that universal and basic condition of human's Unconscious comes out from Märchen or mythology. We can easily experience these universality of human nature in dreams. Therefore, It is very important to interpret mythogens that appear in myths and märchen in analytical psychology to understand these 'big dreams' which could be seen in clinical practice. As I was interested in interpreting myths in analytic psychology, I tried to find universality of archetypes in Korea's traditional folk tales and took note of the birth myth of Hyeokgeose, the founder of Shilla dynasty, while examining the chater of the Unsual in history in the Heritage of the Three Kingdoms. Shilla was founded earlier than two other countries, but it was located in the very south of the Korean Peninsula, and it was behind times in politically, militarily, and culturally compare to Goguryeo and Baekje. However, Shilla achieved unifying the Three Kingdoms and it lasted 1000 years, the longest unified history in Korean history. I tried to examine archetypes in the birth myth if there are any backgrounds that are related to finding a Shilla Kingdom. It is noted that myth of the founder of Korean Peninsula's small Kingdom Shilla has complete story from before the birth to birth, birth of spouse, growth, marriage, accession, governing, death, after death, and succession. Symbols such as numbers 1, 3, 5, 6, 7, 13 and 61, various azimuthes including north, west, south, east, and central, animals like tiger, white horse, hen, dragon, phoenix, and snakes, natures like main symbol egg, rock, gourd, lightening, spring water, stream, tree, forest, mountain, iron and goddess-image like seon-do Holy Mother gradually appears in the myth. These symbols could show a meaning of human experience such as birth of Conscious, growth and development of paternal and maternal love, and story of regeneration and extinction. Moreover, It could be seen as these progress eternally continues in next generation. I have found out that a word, a sentence or stories that looks meaningless in myth revealed its true symbolical meaning. In addition, interaction between Unconscious and Conscious repeats in different forms, and expressed in layered.

Optimization of Multiclass Support Vector Machine using Genetic Algorithm: Application to the Prediction of Corporate Credit Rating (유전자 알고리즘을 이용한 다분류 SVM의 최적화: 기업신용등급 예측에의 응용)

  • Ahn, Hyunchul
    • Information Systems Review
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    • v.16 no.3
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    • pp.161-177
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    • 2014
  • Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

A Study on the Improvement of Recommendation Accuracy by Using Category Association Rule Mining (카테고리 연관 규칙 마이닝을 활용한 추천 정확도 향상 기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.27-42
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    • 2020
  • Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

Review of the Korean Indigenous Species Investigation Project (2006-2020) by the National Institute of Biological Resources under the Ministry of Environment, Republic of Korea (한반도 자생생물 조사·발굴 연구사업 고찰(2006~2020))

  • Bae, Yeon Jae;Cho, Kijong;Min, Gi-Sik;Kim, Byung-Jik;Hyun, Jin-Oh;Lee, Jin Hwan;Lee, Hyang Burm;Yoon, Jung-Hoon;Hwang, Jeong Mi;Yum, Jin Hwa
    • Korean Journal of Environmental Biology
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    • v.39 no.1
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    • pp.119-135
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    • 2021
  • Korea has stepped up efforts to investigate and catalog its flora and fauna to conserve the biodiversity of the Korean Peninsula and secure biological resources since the ratification of the Convention on Biological Diversity (CBD) in 1992 and the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits (ABS) in 2010. Thus, after its establishment in 2007, the National Institute of Biological Resources (NIBR) of the Ministry of Environment of Korea initiated a project called the Korean Indigenous Species Investigation Project to investigate indigenous species on the Korean Peninsula. For 15 years since its beginning in 2006, this project has been carried out in five phases, Phase 1 from 2006-2008, Phase 2 from 2009-2011, Phase 3 from 2012-2014, Phase 4 from 2015-2017, and Phase 5 from 2018-2020. Before this project, in 2006, the number of indigenous species surveyed was 29,916. The figure was cumulatively aggregated at the end of each phase as 33,253 species for Phase 1 (2008), 38,011 species for Phase 2 (2011), 42,756 species for Phase 3 (2014), 49,027 species for Phase 4 (2017), and 54,428 species for Phase 5(2020). The number of indigenous species surveyed grew rapidly, showing an approximately 1.8-fold increase as the project progressed. These statistics showed an annual average of 2,320 newly recorded species during the project period. Among the recorded species, a total of 5,242 new species were reported in scientific publications, a great scientific achievement. During this project period, newly recorded species on the Korean Peninsula were identified using the recent taxonomic classifications as follows: 4,440 insect species (including 988 new species), 4,333 invertebrate species except for insects (including 1,492 new species), 98 vertebrate species (fish) (including nine new species), 309 plant species (including 176 vascular plant species, 133 bryophyte species, and 39 new species), 1,916 algae species (including 178 new species), 1,716 fungi and lichen species(including 309 new species), and 4,812 prokaryotic species (including 2,226 new species). The number of collected biological specimens in each phase was aggregated as follows: 247,226 for Phase 1 (2008), 207,827 for Phase 2 (2011), 287,133 for Phase 3 (2014), 244,920 for Phase 4(2017), and 144,333 for Phase 5(2020). A total of 1,131,439 specimens were obtained with an annual average of 75,429. More specifically, 281,054 insect specimens, 194,667 invertebrate specimens (except for insects), 40,100 fish specimens, 378,251 plant specimens, 140,490 algae specimens, 61,695 fungi specimens, and 35,182 prokaryotic specimens were collected. The cumulative number of researchers, which were nearly all professional taxonomists and graduate students majoring in taxonomy across the country, involved in this project was around 5,000, with an annual average of 395. The number of researchers/assistant researchers or mainly graduate students participating in Phase 1 was 597/268; 522/191 in Phase 2; 939/292 in Phase 3; 575/852 in Phase 4; and 601/1,097 in Phase 5. During this project period, 3,488 papers were published in major scientific journals. Of these, 2,320 papers were published in domestic journals and 1,168 papers were published in Science Citation Index(SCI) journals. During the project period, a total of 83.3 billion won (annual average of 5.5 billion won) or approximately US $75 million (annual average of US $5 million) was invested in investigating indigenous species and collecting specimens. This project was a large-scale research study led by the Korean government. It is considered to be a successful example of Korea's compressed development as it attracted almost all of the taxonomists in Korea and made remarkable achievements with a massive budget in a short time. The results from this project led to the National List of Species of Korea, where all species were organized by taxonomic classification. Information regarding the National List of Species of Korea is available to experts, students, and the general public (https://species.nibr.go.kr/index.do). The information, including descriptions, DNA sequences, habitats, distributions, ecological aspects, images, and multimedia, has been digitized, making contributions to scientific advancement in research fields such as phylogenetics and evolution. The species information also serves as a basis for projects aimed at species distribution and biological monitoring such as climate-sensitive biological indicator species. Moreover, the species information helps bio-industries search for useful biological resources. The most meaningful achievement of this project can be in providing support for nurturing young taxonomists like graduate students. This project has continued for the past 15 years and is still ongoing. Efforts to address issues, including species misidentification and invalid synonyms, still have to be made to enhance taxonomic research. Research needs to be conducted to investigate another 50,000 species out of the estimated 100,000 indigenous species on the Korean Peninsula.

A Structural Relationship among Job Requirements, Job Resources and Job Burnout, and Organizational Effectiveness of Private Security Guards (민간경비원의 직무요구 직무자원과 소진, 조직유효성의 구조적 관계)

  • Kim, Sung-Cheol;Kim, Young-Hyun
    • Korean Security Journal
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    • no.48
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    • pp.9-33
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    • 2016
  • The purpose of the present study was to find out cause-and-effect relationship between job requirements and job resources, with job burnout as a mediator variable, and the effects of these variables on organizational effectiveness. The population in the present study was private security guards employed by 13 private security companies in Seoul and Gyeonggi-do areas, and a survey was conducted on 500 security guards selected using purposive sampling technique. Out of 460 questionnaires distributed, 429 responses, excluding 31 outliers or insincere responses, were used for data analysis. For analysis, data were coded and entered into SPSS 18.0 and AMOS 18.0, which were used to analyze the data. Descriptive analyses were performed to find out sociodemographic characteristics of the respondents. The exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to test the validity of the measurement tool, and the Cronbach's Alpha coefficients were calculated to test the reliability. To find out the significance of relationships among variables, Pearson's correlation analysis was performed. Covariance Structure Analysis (CSA) was performed to test the relationship among latent factors of a model for job requirements, job resources, job burnout, and organizational effectiveness of the private security guards, and the fitness of the model analyzed with CSA was determined by the goodness-of-fit index ($x^2$, df, p, RMR, GFI, CFI, TLI, RMSEA). The level of significance was set at .05, and the following results were obtained. First, even though the effect of job requirements on job burnout was not statistically significant, it had a positive influence overall, and this result can be considered such that the higher the perception of job requirements by the member of the organization, the higher the perception of job burnout. Second, the influence of job resources on job burnout was negative, which can be considered that the higher the perception of job resources, the lower the perception of job burnout. Third, even though the influence of job requirements on organizational effectiveness was statistically nonsignificant, it had a negative influence overall, and this result can be considered that the higher the perception of job requirements, the lower the perception of organizational effectiveness. Fourth, job resources had a positive influence on organizational effectiveness, and it can be considered that the higher the perception of job resources, the higher the perception of organizational effectiveness. Fifth, the results of the analysis between job burnout and organizational effectiveness revealed that, even though the influence of job burnout on organizational effectiveness was statistically nonsignificant, it had partial negative influences on sublevels of organizational effectiveness, and this may suggest that the higher the perception of job burnout by the organization members, the lower the organizational effectiveness. Sixth, the analysis of mediating role in the relationship between job requirements and organizational effectiveness, job burnout was taking partial mediating role between job requirements and organizational effectiveness. These results suggest that reducing job burnout by managing job requirements, organizational effectiveness that leads to job satisfaction, organizational commitment, and turnover intention can be maximized. Seventh, the analysis of mediating role in the relationship among job requirements, job resources, and organizational effectiveness, job burnout was assuming a partial mediating role in the relationships among job requirements, job resources, and organizational effectiveness. These results suggest that organizational effectiveness can be maximized by either lowering job requirements or burnout management through reorganizing job resources.

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The Comparative Imaging Study on Mn-phthalocyanine and Mangafodipir trisodium in Experimental VX2 Animal Model (실험적으로 유발시킨 VX2 동물모델에서의 Mn-phthalocyanine과 Mangafodipir trisodium의 비교영상)

  • Park Hyun-Jeong;Ko Sung-Min;Kim Yong-Sun;Chang Yongmin
    • Investigative Magnetic Resonance Imaging
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    • v.8 no.1
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    • pp.32-41
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    • 2004
  • Purpose : To measure the NMR relaxation properties of MnPC, to observe the characteristics of liver enhancement patterns on MR images in experimentally implanted rabbit VX2 tumor model, and to estimate the possibility of tissue specific contrast agent for MnPC in comparison with the hepatobiliary agent. Materials and Methods : Phthalocyanine (PC) was chelated with paramagnetic ions, manganese (Mn). 2.01 g (5.2 mmol) of phthalocyanine was mixed with 0.37 g (1.4 nlmol) of Mn chloride at $310^{\circ}C$ for 36 hours and then purified by chromatography ($CHCl_3:\;CH_3OH=98:2$, volume ratio) to obtain 1.04 g $(46\%)$ of MnPC (molecular weight = 2000 daltons). The T1/T2 relaxivity (R1/R2) for MnPC were determined at a 1.5 T (64 MHz) MR spectrometer. VX2 tumor model was experimentally implanted in the liver parenchyma of rabbits. All MR studies were performed on 1.5 T. The human extremity radio frequency coil of a bird cage type was employed. MR images were acquired at 17 to 24 days after VX2 carcinoma implantation.4 mmol/kg MnPC and 0.01 mmol/kg Mn-DPDP were injected via the ear vein of rabbits. T1-weighted images were obtained with spin-echo (TR/TE=516/14 msec) and fast multiplanar spoiled gradient recalled (TR/TE : 80/4 msec, $60^{\circ}$ flip angle) pulse sequence. Fast spin-echo (TR/TE=1200/85 msec) was used to obtain the T2-weighted images. Results : The value of T1/T2 relaxivity (R1/R2) of MnPC was $7.28\;mM^{-1}S^{-1}$ and $55.56\;mM^{-1}S^{-1}$ respectively at 1.5 T (64 MHz). Because the T2 relaxivity of MnPC that bonded strongly, covalently manganese with phthalocyanine was very high, the signal intensity of liver parenchyma was decreased on postcontrast T2-weighted images and we could easily distinguish the VX2 carcinoma within the liver parenchyma. When MnPC was administrated intravenously, the tumor margin delineation was more remarkable than Mn-DPDP-enhanced images. The enhancement of liver parenchyma with MnPC persisted at relatively high levels over at least one hour after injection of the contrast agents. Conclusion : The hepatic uptake and biliary excretion of MnPC, which are similar to Mn-DPDP, suggest that this agent is a new liver-specific agent. Also, MnPC seems to be used as a dual contrast agent (T1 and T2) with high T2 relaxivity. However, it is warranted that MnPC needs further investigation as a potential contrast agent for MR imaging of the liver. That is, further characterizations of MnPC are needed in vivo and in vitro before clinical trials. The diagnostic potential of MnPC will also have to be examined more in the animal models of additional types.

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