• Journal of agricultural medicine and community health
• /
• v.25 no.2
• /
• pp.231-244
• /
• 2000

Classification and research trends were studied to analyze a total of 240 original articles that have been published in 34 volumes of The Korean Journal of Rural Medicine from 1976 to 1999. The results were as follows: 1. A total of 337 articles were published. Among them, 240(71.2%) articles were classified as original articles. This number has been increasing significantly over the years as the number of the articles was 13 in the 1970s, 73 in the 1980s, and 154 in the 1990s. 2. There were 10 authors in the original articles and 55(22.9%) of them were written by 3 of them. There were five research institutions involved in the articles, and 106(44.2%) of the articles were done by one research group. 3. In the original articles. 24(10.0%) were noted to be done using research funds, and only 6(2.5%) were written in English. 4. In the view of the research styles of the original articles, 115(47.9%) used analytical study, 92(38.3%) used technical study, 21(9.2%) used experimental study, and 6(2.5%) used case reports. In the 1970s, 13(100.0%) articles used technical study, and in the 1980s, 47(64.4%) used technical studies and 19(26.0%) used analytical studies. However, in the 1990s, 96(62.8%) articles used analytical studies and 32(20.9%) used technical studies. The statistical methods most commonly used in the articles were technical statistics, the ${\chi}^2$-test, and the t-test respectively. 5. On the classification into three different research fields, 105(43.8%) articles were classified as health management, 96(40.0%) as disease epidemiology, and 39(16.3%) as rural environment and rural occupational disorders. In the 1970s, 12 (92.3 %) of the articles were on disease epidemiology and 1(7.7%) on health management were published. In the 1980s, 33(45.2%) articles on disease epidemiology, 29(39.7%) on health control, and 11(15.1%) on rural environment and rural occupational disorders were recorded. In the 1990s, however, 75(48.7%) articles were on health control, 51(33.1%) on disease control, and 28(18.2%) on the rural environment and rural occupational disorders. 6. According to the research subjects in each research field, the 39 articles in rural environment and rural occupational disorders were composed of 8(20.5%) articles on pesticide intoxication, 7(17,9%) on farmer's diseases, 7(17.9%) on vinyl-house diseases, and 6(15.4%) on accidents. From a total of 96 articles in disease epidemiology 56(58.3%) articles were on parasites, 16(16.7%) on non-infectious diseases, 12(12.5) on infectious diseases. From 105 articles in health control 25(23.8%) articles were on medical care utilization patterns, 18(17.1%) on the health care delivery system, and 13(12.4%) on maternal and child health. In the analysis of the 10 most prevalent subjects dealt in the above articles, 6(46.2%) articles were on parasites and 4(30.8%) on non-infectious diseases were recorded in the 1970s. In the 1980s, 28(38.4%) were on parasites. 9(12.3%) on the health care system, 7(9.6%) on medical care utilization patterns, 5(6.8%) on maternal and child health, and 4(5.5%) were on pesticide intoxication. In the 1990s, 22(14.3%) articles were on parasites. 18(11.7%) on medical care utilization patterns, 16(10.4%) on senile health, 14(9.1%) on the health care system, 10(6.5%) on infectious diseases, arid 10(6.5%) were on non-infectious diseases. In conclusion, the research activity on rural health has been strengthened in this country because the original articles in The Korean Journal of Rural Medicine have significantly increased in the past 24 years. In the 1970s and 1980s, research on disease epidemiology was most prevalent, but in the 1990s papers on health care were most popular. In addition, the articles on parasites were most frequently published in the 1970s, 1980s, and 1990s, showing that parasitic problem was the main theme in those eras. However, in the 1990s, it was evident that the articles on parasites were decreasing and articles on the subject of medical care utilization patterns and senile health increased. Hereafter it was expected that research on health care would be more common in rural health in Korea.

• Journal of Intelligence and Information Systems
• /
• v.26 no.4
• /
• pp.173-198
• /
• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• The Journal of the Korea Contents Association
• /
• v.18 no.5
• /
• pp.191-214
• /
• 2018

This research empirically analyzed the selection factors and the locational selection factors of the medical service facilities according to the gradual increase of the importance of the selection factors and the locational selection factors regarding the establishments of the small- and medium-sized hospitals according to the rapid changes of the socio-economic conditions. By analyzing the priority order according to the levels of the importance of each evaluation item factor through a research related to the selection factors and the locational selection factors of the small- and medium-sized hospitals and by drawing what the important factors that have the influences on the competitiveness of the pre-existent small- and medium-sized hospitals are through the classification of the real estate locational factors and the non-locational factors, the purpose lies in utilizing them as the basic data and materials for the opening strategies of the small- and medium-sized hospitals considering the special, locational characteristics according to the important factors of the selection factors of the small- and medium-sized hospitals, regarding the medical suppliers that have been preparing, for opening the new, small- and medium-sized hospitals. Based on the results of the preceding researches and the researches on the case examples, 28 evaluation factors were arrived at in terms of the level of the medical treatment, the medical services, the accessibilities of the hospitals, the conveniences of the hospitals, and the physical environment. And, regarding the 28 detailed evaluation factors that had been collected, through the interviews with the related experts, the 5 factors of the medical level, the medical service, the expertise of the hospital, the convenience of the hospital, and the physical environment were selected as the upper class evaluation factors. And, according to each upper class, a total of 28 low-part evaluation factors were selected. Regarding the optimal evaluation factors that were selected, the optimal locational factors were selected by carrying out an AHP questionnaire survey investigation with 200 medical experts as the subjects. Regarding the AHP analysis results, similarly with the case examples of the precedent researches, the levels of the importance appeared in the order of the medical level, the medical services, the accessibility of the hospital, the physical environment, and the convenience. And the factors that were related to the facilities of a hospital appeared low. The results of this research can be applied in providing the basis for the decision-makings regarding the selections of the locations of the small- and medium-sized hospitals in the future.

• Progress in Medical Physics
• /
• v.14 no.4
• /
• pp.211-217
• /
• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• Journal of Food Hygiene and Safety
• /
• v.19 no.2
• /
• pp.60-65
• /
• 2004

120 samples of ready-to-eat salad product were purchased at department stores, marts and family restaurants in metro area. Coliform bacteria and food borne pathogenic bacteria were isolated from these samples. In 73 samples among the 120 salad product samples, coliform bacteria and food borne pathogenic bacteria were detected by 60.8％ of isolated rate. Salad were classified into organic and non-organic salad. According to a salad type, salad were classified into vegetable salad and mixed vegetable salad with fried chicken and extra food. According to a packing type, packed salad product and salad-bar product were classified. After the classification, the results of each cases were compared. There is no statistical relation between cultivation or packing methods and contaminated bacteria. But the incidence number of microbial strains was significantly different between vegetable salad and mixed vegetable salad(p＜0.005). In vegetable salad, more various strains were detected. E. coli was isolated in 10 cases among the 90 cases in non-organic vegetable and in 7 cases among the 30 cases in organic salad. Food borne pathogenic bacteria were isolated in non-organic vegetable salad product. Staphylococcus aureus was isolated in 4 cases of vegetable salad product and Salmonella spp. isolated in 1 case. After 5 times examination of each 4 market products, the total number of aerobic bacteria was average 4.8$\pm$0.19 log cfu/g. One sample from this product, saline and a detergent for vegetable were used for 3 minutes to notice the effect. As a result, when saline was used 5 times and detergent for vegetable was used 1 time, bacterial contamination was decreased up to 95.5％.

• The korean journal of orthodontics
• /
• v.30 no.4 s.81
• /
• pp.491-507
• /
• 2000

The purpose of this study was to investigate if there were a significant differences in mandibular position between cephalometric measurements from a centric occlusion tracing compared to those of a acquired centric relation by stabilization splint on malocclusion patient with TMD. 60 malocclusion patients, who had TMD and CO-CR discrepancy beyond normal range, were selected and subdivided into Class I, II, III by Angle's classification and also subdivided into clockwise, straight downward, and counterclockwise group by Jarabak's posterior facial height/anterior facial height ratio. Lateral cephaolmetric radiographs with the mandible in centric occlusion were taken and measured, and for each Patient the stabilization splint with mutually protected occlusal scheme was applied for minimum 3months. After each patient's CO-CR discrepancy was in normal range, lateral cephalometric radiographs were retaken and measured. The comparison of the difference between CO-CR cephalometric measurements in all sample, Class I, II, III groups, and Clockwise, Straight downward, Counterclockwise groups were studied. The finding of this study can be summarized as follows: 1 In all sample, the value of cephalometric measurements was significantly different between CO-CR. The mandible rotated to down and posterior position and the vertical change was greater than the horizontal change (overjet-1.3mm increase, overbite-1.9mm decrease). 2. In Class II malocclusion group, most of the mean difference value between CO-CR is higher than that of the other groups and more measurements was statically significant. 3. In clockwise and counterclockwise group, some of the mean difference value is higher than that of straight downward group and more measurements was statically significant. 4. There ware no measurements that explain centric relation measurements from the type of malocclusion, facial pattern and centric occlusion measurements. Henceforth, it is strongly recommended that stabilization splint therapy for orthodontic treatment on TMD patient should be excuted upon overall facial types prior to orthodontic diagnosis and treatment planning.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_3
• /
• pp.1475-1490
• /
• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Journal of Global Scholars of Marketing Science
• /
• v.20 no.1
• /
• pp.59-69
• /
• 2010

Green or an environmental consciousness has been a major issue for businesses and government offices, as well as consumers, worldwide. In response to this movement, the Korean government announced, in the early 2000s, the era of "Green Growth" as a way to encourage green-related business activities. The Korean fashion industry, in various levels of involvement, presents diverse eco-friendly products as a part of the green movement. These apparel products include organic products and recycled clothing. For these companies to be successful, they need information about who are the consumers who consider green issues (e.g., environmental sustainability) as part of their personal values when making a decision for product purchase, use, and disposal. These consumers can be considered as eco-sumers. Previous studies have examined consumers' purchase intention for or with eco-friendly products. In addition, studies have examined influential factors used to identify the eco-sumers or green consumers. However, limited attention was paid to eco-sumers' disposal or recycling behavior of clothes in comparison with their green product purchases. Clothing disposal behaviors are ways that consumer can get rid of unused clothing and in clue temporarily lending the item or permanently eliminating the item by "handing down" (e.g., giving it to a younger sibling), donating, exchanging, selling, or simply throwing it away. Accordingly, examining purchasing behaviors of eco-friendly fashion items in conjunction with clothing disposal behaviors should improve understanding of a consumer's clothing consumption behavior from the environmental perspective. The purpose of this exploratory study is to provide descriptive information about Korean eco-sumers who have ecologically-favorable lifestyles and behaviors when buying and disposing of clothes. The objectives of this study are to (a) categorize Koreans on the basis of clothing disposal behaviors; (b) investigate the differences in demographics, lifestyles, and clothing consumption values among segments; and (c) compare the purchase intention of eco-friendly fashion items and influential factors among segments. A self-administered questionnaire was developed based on previous studies. The questionnaire included 10 items of clothing disposal behavior, 22 items of LOHAS (Lifestyles of Health and Sustainability) characteristics, and 19 items of consumption values, measured by five-point Likert-type scales. In addition, the purchase intention of two eco-friendly fashion items and 11 attributes of each item were measured by seven-point Likert type scales. Two polyester fleece pullovers, made from fabric created from recycled bottles with the PET identification code, were selected from one Korean brand and one US imported brand among outdoor sportswear brands. A brief description of each product with a color picture was provided in the survey. Demographic variables (i.e., gender, age, marital status, education level, income, occupation) were also included. The data were collected through a professional web survey agency during May 2009. A total of 600 final usable questionnaires were analyzed. The age of respondents ranged from 20 to 49 years old with a mean age of 34 years. Fifty percent of the respondents were males and about 58% were married, and 62% reported having earned university degrees. Principal components factor analysis with varimax rotation was used to identify the underlying dimensions of the clothing disposal behavior scale, and three factors were generated (i.e., reselling behavior, donating behavior, non-recycling behavior). To categorize the respondents on the basis of clothing disposal behaviors, k-mean cluster analysis was used, and three segments were obtained. These consumer segments were labeled as 'Resale Group', 'Donation Group', and 'Non-Recycling Group.' The classification results indicated approximately 98 percent of the original cases were correctly classified. With respect to demographic characteristics among the three segments, significant differences were found in gender, marital status, occupation, and age. LOHAS characteristics were reduced into the following five factors: self-satisfaction, family orientation, health concern, environmental concern, and voluntary service. Significant differences were found in the LOHAS factors among the three clusters. Resale Group and Donation Group showed a similar predisposition to LOHAS issues while the Non-Recycling Group presented the lowest mean scores on the LOHAS factors compared to the other segments. The Resale and Donation Groups described themselves as enjoying or being satisfied with their lives and spending spare-time with family. In addition, these two groups cared about health and organic foods, and tried to conserve energy and resources. Principal components factor analysis generated clothing consumption values into the following three factors: personal values, social value, and practical value. The ANOVA test with the factors showed differences primarily between the Resale Group and the other two groups. The Resale Group was more concerned about personal value and social value than the other segments. In contrast, the Non-Recycling Group presented the higher level of social value than did Donation Group. In a comparison of the intention to purchase eco-friendly products, the Resale Group showed the highest mean score on intent to purchase Product A. On the other hand, the Donation Group presented the highest intention to purchase for Product B among segments. In addition, the mean scores indicated that the Korean product (Product B) was more preferable for purchase than the U.S. product (Product A). Stepwise regression analysis was used to identify the influence of product attributes on the purchase intention of eco product. With respect to Product A, design, price and contribution to environmental preservation were significant to predict purchase intention for the Resale Group, while price and compatibility with my image factors were significant for the Donation Group. For the Non-Recycling Group, design, price compatibility with the factors of my image, participation to eco campaign, and contribution to environmental preservation were significant. Price appropriateness was significant for each of the three clusters. With respect to Product B, design, price and compatibility with my image factors were important, but different attributes were associated significantly with purchase intention for each of the three groups. The influence of LOHAS characteristics and clothing consumption values on intention to purchase Products A and B were also examined. The LOHAS factor of health concern and the personal value factor were significant in the relationships with the purchase intention; however, the explanatory powers were low in the three segments. Findings showed that each group as classified by clothing disposal behaviors showed differences in the attributes of a product, personal values, and the LOHAS characteristics that influenced their purchase intention of eco-friendly products. Findings would enable organizations to understand eco-friendly behavior and to design appropriate strategic decisions to appeal eco-sumers.

• Korean Journal of Ecology and Environment
• /
• v.47 no.3
• /
• pp.135-145
• /
• 2014

The mountain forest vegetation of Gyebangsan (1,577 m) in Odaesan National Park is classified into deciduous broad-leaved forest, mountain valley forest, coniferous forest, subalpine coniferous forest, subalpine deciduous forest, plantation forest, and other vegetation which includes Actinidia argute community and agricultural land. As for the number of communities distributed in the each forest vegetation which were categorized by the physiognomy classification, deciduous broad-leaved forest had 33 communities, mountain valley forest 41 communities, coniferous forest 8 communities, subalpine coniferous forest 4 communities, subalpine deciduous forest 2 communities, plantation forest 6 communities and other vegetation 4 communities. Regarding the distribution rate of communities in the vegetation, in the deciduous broad-leaved forest. Quercus mongolica community accounted for 80.226% with $30,909,942.967m^2$, followed by Quercus variabilis community of 2.771% with $1,067,479.335m^2$. 55.463% of deciduous broad-leaved forest in the Gyebangsan had Quercus mongolica as a dominant or second dominant species. In the mountain valley forest, Fraxinus rhynchophylla - Juglans mandshurica community accounted for 10.955%. And there were ten mixed communities having Fraxinus rhynchophylla and upper layer at a similar level of coverage, taking up 32.776%. In the coniferous forest, Pinus densiflora and the community living with Pinus densiflora accounted for 100%, showing that the coniferous forest has the community with Pinus densiflora as a dominant species at upper layer. For other vegetation, subalpine coniferous forest had a total of four communities including Abies holophylla - Quercus mongolica community, and accounted for 4.980% of vegetation area of Odaesan National Park. Two communities including Betula ermani - Cornus controversa community were found in the subalpine deciduous forest, taking up 0.006% of total vegetation area of Odaesan National Park. Regarding plantation forest, Larix leptolepis was planted the most with 51.652%, followed by Betula platyphylla var. japonica with 38.975%, and Pinus koraiensis with 7.969%. These three species combined accounted for 98.565%. In conclusion, the forest vegetation found in the Gyebangsan of Odaesan National Park has Quercus mongolica as a dominant species at the top layer. A lot of other communities related with this species are expected to be quickly replaced due to vegetation succession and climatic causes. Therefore, Quercus mongolica is expected to become the main species in the deciduous broad-leaved forest, Fraxinus rhynchophylla, Juglans mandshurica and Fraxinus mandshurica in the mountain valley forest. Around the border line between deciduous broad-leaved forest and mountain valley forest, highly humid valley area is expected to be quickly taken up by Cornus controversa and Fraxinus mandshurica, and the slope area by Quercus mongolica. However, in the subalpine coniferous forest, the distribution rate of deciduous broad-leaved trees is expected to increase due to climate warming.

• Journal of agricultural medicine and community health
• /
• v.27 no.1
• /
• pp.115-123
• /
• 2002

Objective: The aim of this study was to evaluate the patterns of helicopter emergency medical services (HEMS) in Ullung Island. Methods : The authors reviewed the records from emergency room diaries and the lists of helicopter transfers in the Ullung Public Health Medical Center over the 5-year period from Jan 1, 1997 to Dec 31, 2001. Results : One hundred thirteen cases were transferred by helicopters in 88 flights. According to year, the number of flights was 13(14.8%) and the number of cases was 15(13.3%) in 1997; 17(19.3%) and 21(18.6%) in 1998; 18(20.5%) and 20(17.7%) in 1999; 17(19.3%) and 20(17.7%) in 2000; and 23(26.1%) and 37(32.7%) in 2001. According to the kind of helicopter, the number of flights was 46(52.3%) and the number of cases was 60(53.1%) by Maritime police; and 19(21.6%) and 28(25.1%) by 119 rescue. According to time zone, there were no night flights. According to sex and age, there were 75 male cases(66.4%) and 28 cases(28.3%) of patients aged sixty years and over. The number of flights was 11(12.5%) and the number of cases was 15(13.3%) in November; 10 flights(11.4%) and 14 cases(12.4%) in March; and 7 cases(8.0%) in each of September, October and April. The most common season of helicopter transfer cases was autumn. According to transfer area, there were 48 cases (42.5%) in Pohang city, Gyeonsangbukdo; 35(31.0%) in Gangnung city, Gangwondo; and 17(15.0%) in Daegu metropolitan city. According to condition, there were 27 cases(23.9%) of cerebro-vascular accident, 13(11.5%) of fracture and 11(9.7%) of head injury. According to admission department, there were 42 cases(37.2%) in Neurosurgery, 21(18.6%) in Internal Medicine and 13(11.5%) in Orthopedic Surgery. According tothe Korea Standard Classification of Disease(3-KSCD), circulatory systemic disease(IX) and injury, intoxication and others (XIX) were the two most frequent categories with 34 cases(30.1%) each, followed by digestive system disease (XI) with 23 cases(20.4%). Conclusions : HEMS in Ullung Island leave much to be desired. Helicopters cannot make a night flight and are not equipped with medical facilities. HEMS in islands such as Ullung Island are essential. We hope that night flights, equipment-monitoring systems for emergency patients in the helicopters, and a law related to HEMS in the island will all be established.