• Journal of Korean Medicine for Obesity Research
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• v.20 no.1
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• pp.52-68
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• 2020

Objectives: The purpose of this study is to investigate the weight loss effects of auricular acupuncture in obese patients. Methods: Six databases (Research Information Sharing Service [RISS], Korean studies Information Service System [KISS], Oriental Medicine Advanced Searching Integrated System [OASIS], PubMed, The Cochrane Library, China National Knowledge Infrastructure [CNKI]) were searched up to May 20, 2020. Eight eligible randomized controlled trials were included the present study. The quality of included studies was assessed by the Cochrane risk of bias tool and a meta-analysis was performed by Review Manager software. A meta-analysis was conducted using a random-effects model and a subgroup analysis was performed to detect the sources of heterogeneity, identify the selection of acupuncture methods and explore its contributions to the weight loss effects. Results: Among 8 trials, 5 trials used auricular acupuncture and 2 trials used auricular acupressure, 1 trial used both types of intervention. Most commonly selected acupoints were Shenmen (TF4) and stomach (CO4). Treatment duration was six to twelve weeks, and total treatment session was six to twelve. Compared to the control groups, auricular acupuncture significantly decreased body weight, body mass index (BMI), high density lipoprotein-cholesterol (HDL) and ghrelin. For the selection of acupuncture methods, both methods performed similarly in most outcome except waist circumference (WC), body fat percentage (BFP), and triglycerides (TG). Conclusions: We found that auricular acupuncture can be effective for weight loss and controlling appetite. However, the findings should be interpreted with caution due to heterogeneity. So further vigorous and well-designed studies should be conducted to strengthen the evidence of the use of auricular acupuncture for obesity.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.722-729
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• 2015

Powdery mildew (PM) caused by Podosphaera aphanis is a major disease that can result in significant yield losses in strawberry (Fragaria ${\times}$ ananassa Duchesne). For preventing PM, pesticides are usually applied in strawberry. In this study, molecular markers were developed to increase breeding efficiency of PM-resistance cultivars by marker-assisted selection (MAS). An $F_2$ population derived from a cross between PM-resistance 'Seolhyang' and PM-susceptibility 'Akihime' was evaluated for disease resistance to PM and RAPD (random amplification of polymorphic DNA)-BSA (bulked segregant analysis). Among 200 RAPD primers tested, OPE10 primer amplified a 311bp-band present in with 331bp. Sequence alignment performed for searching polymorphisms and six single nucleotide polymorphism (SNP) were found in amplified regions. To develop polymorphic marker for distinguishing between resistant and susceptible, RAPD was converted to cleaved amplified polymorphic sequence (CAPS) marker. Among restriction enzymes associated with six SNPs, Eae I (Y/GGCCR) was successfully digested to 231bp in susceptible. The results suggest that the selected CAPS marker could be used for increasing efficiency of selecting powdery mildew resistant strawberry in breeding system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.599-601
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• 2009

In currently being adopted as a e-leaning standard, SCORM it is difficult to provide the customized contents to a learner by changing the learner's level at runtime, and to control selective studying. So, we designed and implemented the customized contents organization engine(CCOE) in order to complement SCORM's faults in this paper. The CCOE consists of a level evaluation module, a contents re-organization module and a question item selection module. A level evaluation module evaluates the learner's level based on a question item reaction theory. And a question item selection module selects some random items by each level or by considering the learner's level which is then provided to a studying before evaluation, a section evaluation, and a quiz. And then this module transmits the selected items to the contents reorganization module for providing the quiz. A contents re-organization module selects the customized contents based on the learner's level by searching the tagged difficulty to the content, and creates the sequence with the selected items and the transmitted items from the question item selection module. If proposed in this paper CCOE is applied, the higher effectiveness of learning is expected by providing the customized learning contents based on the re-evaluated learner's level by each section.

• The Korean Journal of Emergency Medical Services
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• v.6 no.1
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• pp.141-152
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• 2002

The purpose of this study is to provide the basic materials for searching the way of improvement to heighten the emergency medical welfare level by one step further. To achieve this purpose, the subjects of this study were selected 452 college students in Gwangju, using a random sampling method. The statistical analysis methods utilized for analyzing the collected data are frequency analysis, $x^2$ test. The conclusions obtained from these analyses are as following ; 1. In question about necessary optimum number of persons for rescue first aid activity, health and non-health major college students responded by 39.2%, 45.3% respectively that rescue team 15 people, first aid team 3 people is most suitable. But there was no significant difference in major department(p<0.05). 2. In question about security of the public health doctor and the emergency medical technician, all health and non-health major college students are recognizing necessity urgently, but there was no significant difference in major department(p<0.05). 3. In question about 119 rescue first aid team member applying for an examination qualification grant to the department of EMT's graduate, all health and non-health major college students were highest by 52.9%, 52.4% respectively in "necessity" item. But there was no significant difference in major department(p<0.05). 4. Because rescue first aid equipment level appears higher than 41.7% in non-health major college student's case by 54.2% in health major college student's case, health major college students are recognizing that equipment level should be supplemented more but there was no significant difference in major department(p<0.05). 5. In question about equipment supplement, all health and non-health major college students appeared highest by 64.8%, 69.3% in accident type different special equipment. But there was no significant difference in major department(p<0.05). 6. In question about rescue ambulance car size, we could know being thinking that health and non-health major college student each 61.2%, 56.5% is small and narrow that large size of the rescue ambulance amount need. But there was no significant difference in major department(p<0.05). 7. In question about patient's state is worsened, because rescue first aid equipment is inferior, health major college student responded sometimes 55.1%, many 29.5%. very many by 11.5%, while non-health major college student responded 65.8%, 23.1%, 4.0% respectively. There was significant difference in major department(p<0.05). 8. In question about emergency patient must utilize for 119 rescue ambulance car, all health and non-health major college students appeared highest by 38.8%, 41.3% in "not so" item. In question about rescue first aid team's first-aid treatment ability improves more, all health and non-health major college students appeared highest by 58.1% and 58.7% respectively in "improve" item. In question about "119 rescue ambulance car must go more rapidly than now", all health and non-health major college students are recognizing that should be quicker by 58.1%, 60.9% respectively. When called to 119 all health and non-health major college students responded highest by 55.5%, 53.3% respectively that we must receive first-aid treatment direction from a doctor. In question about "119 rescue ambulance car must be made the pay system", all health and non-health major college students responded 74%, 80% respectively in "not so" item. There was significant difference in major department(p<0.05). In conclusions, In oder to provide superior rescue first aid service to people, a public health doctor should be placed in the situation room inside the fire station so that the doctor could instruct the proper emergency treatment suitable for each situation to the rescue first aid team. Also, national education about a first-aid treatment that do to all people is necessarily necessary in emergency delivery system and this should be spread extensively through school education and broadcasting medium and education should be gone side by side, and see that will can save emergency patients' life which is more when these education consists continuously fixed period for public institution of policeman, fire officer etc. specially. And for reinforcement of patient transfer system, public organization must procure special ambulance car so that emergency patient receive first aid treatment while transfer.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.