• Journal of Preventive Medicine and Public Health
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• v.16 no.1
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• pp.135-152
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• 1983

Emergency medical service is an important part of the health care delivery system, and the optimal allocation of resources and their efficient utilization are essentially demanded. Since these conditions are the prerequisite to prompt treatment which, in turn, will be crucial for life saving and in reducing the undesirable sequelae of the event. This study, taking the hyperbaric chamber for carbon monoxide poisoning as an example, is to develop a stochastic approach for solving the problems of optimal allocation of such emergency medical facility in Korea. The hyperbaric chamber, in Korea, is used almost exclusively for the treatment of acute carbon monoxide poisoning, most of which occur at home, since the coal briquette is used as domestic fuel by 69.6 per cent of the Korean population. The annual incidence rate of the comatous and fatal carbon monoxide poisoning is estimated at 45.5 per 10,000 of coal briquette-using population. It offers a serious public health problem and occupies a large portion of the emergency outpatients, especially in the winter season. The requirement of hyperbaric chambers can be calculated by setting the level of the annual queueing rate, which is here defined as the proportion of the annual number of the queued patients among the annual number of the total patients. The rate is determined by the size of the coal briquette-using population which generate a certain number of carbon monoxide poisoning patients in terms of the annual incidence rate, and the number of hyperbaric chambers per hospital to which the patients are sent, assuming that there is no referral of the patients among hospitals. The queueing occurs due to the conflicting events of the 'arrival' of the patients and the 'service' of the hyperbaric chambers. Here, we can assume that the length of the service time of hyperbaric chambers is fixed at sixty minutes, and the service discipline is based on 'first come, first served'. The arrival pattern of the carbon monoxide poisoning is relatively unique, because it usually occurs while the people are in bed. Diurnal variation of the carbon monoxide poisoning can hardly be formulated mathematically, so empirical cumulative distribution of the probability of the hourly arrival of the patients was used for Monte Carlo simulation to calculate the probability of queueing by the number of the patients per day, for the cases of one, two or three hyperbaric chambers assumed to be available per hospital. Incidence of the carbon monoxide poisoning also has strong seasonal variation, because of the four distinctive seasons in Korea. So the number of the patients per day could not be assumed to be distributed according to the Poisson distribution. Testing the fitness of various distributions of rare event, it turned out to be that the daily distribution of the carbon monoxide poisoning fits well to the Polya-Eggenberger distribution. With this model, we could forecast the number of the poisonings per day by the size of the coal-briquette using population. By combining the probability of queueing by the number of patients per day, and the probability of the number of patients per day in a year, we can estimate the number of the queued patients and the number of the patients in a year by the number of hyperbaric chamber per hospital and by the size of coal briquette-using population. Setting 5 per cent as the annual queueing rate, the required number of hyperbaric chambers was calculated for each province and for the whole country, in the cases of 25, 50, 75 and 100 per cent of the treatment rate which stand for the rate of the patients treated by hyperbaric chamber among the patients who are to be treated. Findings of the study were as follows. 1. Probability of the number of patients per day follows Polya-Eggenberger distribution. $$P(X=\gamma)=\frac{\Pi\limits_{k=1}^\gamma[m+(K-1)\times10.86]}{\gamma!}\times11.86^{-{(\frac{m}{10.86}+\gamma)}}$$ when$${\gamma}=1,2,...,n$$$$P(X=0)=11.86^{-(m/10.86)}$$ when $${\gamma}=0$$ Hourly arrival pattern of the patients turned out to be bimodal, the large peak was observed in $7 : 00{\sim}8 : 00$ a.m., and the small peak in $11 : 00{\sim}12 : 00$ p.m. 2. In the cases of only one or two hyperbaric chambers installed per hospital, the annual queueing rate will be at the level of more than 5 per cent. Only in case of three chambers, however, the rate will reach 5 per cent when the average number of the patients per day is 0.481. 3. According to the results above, a hospital equipped with three hyperbaric chambers will be able to serve 166,485, 83,242, 55,495 and 41,620 of population, when the treatmet rate are 25, 50, 75 and 100 per cent. 4. The required number of hyperbaric chambers are estimated at 483, 963, 1,441 and 1,923 when the treatment rate are taken as 25, 50, 75 and 100 per cent. Therefore, the shortage are respectively turned out to be 312, 791. 1,270 and 1,752. The author believes that the methodology developed in this study will also be applicable to the problems of resource allocation for the other kinds of the emergency medical facilities.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.311-324
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• 2021

Recently, ten geosites have been considered in Hwaseong for endorsement as national geoparks, including the Jebudo, Gojeongri Dinosaur Egg Fossils, and Ueumdo geosites. The Jebudo geosite in the southern part of the Seoul metropolitan area has great potential for development as a new geoscience educational site because it has geological, geographical (landscape), and ecological significance. In this study, we described the geological characteristics through field surveys in the Jebudo geosite. We evaluated its potential as a geo-education site based on comparative analysis with other geosites in Hwaseong Geopark. In addition, we reviewed the practical effect of field education at geosites on the essential concepts and critical competence-oriented education emphasized in the current 2015 revised science curriculum. The Jebudo Geosite is geologically diverse, with various metamorphic rocks belonging to the Precambrian Seosan Group, such as quartzite, schist, and phyllite. Various geological structures, such as clastic dikes, faults, joints, foliation, and schistosity have also been recorded. Moreover, coastal geological features have been observed, including depositional landforms (gravel and sand beaches, dunes, and mudflats), sedimentary structures (ripples), erosional landforms (sea cliffs, sea caves, and sea stacks), and sea parting. The Jebudo geosite has considerable value as a new geo-education site with geological and geomorphological distinction from the Gojeongri Dinosaur Egg Fossils and Ueumdo geosites. The Jebudo geosite also has opportunities for geo-education and geo-tourism, such as mudflat experiences and infrastructures, such as coastal trails and viewing points. This geosite can help develop diverse geo-education programs that improve key competencies in the science curriculum, such as critical thinking, inquiry, and problem-solving. Furthermore, by conducting optimized geo-education focused on the characteristics of each geosite, the following can be established: (1) the expansion of learning space from school to geopark, (2) the improvement of understanding of specific content elements and linkage between essential concepts, and (3) the extension of the education scope throughout the earth system. There will be positive impacts on communication, participation, and lifelong learning skills through geopark education.

• 한국노년학
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• v.38 no.4
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• pp.1057-1081
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• 2018

This study analyzed the case of elderly care cluster in Gwangjin-gu to explore the possibilities of social economy as a provider of community-based social services. Community-based means the approach by which community organizations build a voluntary and collaborative network to enhance collective problem-solving abilities. Therefore, it is very likely that the social economy that emphasizes people, labor, community, and democratic principles can contribute to community-based social services. This study analyzed social economic network by using four characteristics of social economy suggested by OECD community economy and employment program as an analysis framework. The results of this study are as follows: First, it is found that social economy would hardly supply community-based social services through network cooperation because of a large variation in community identity, investment to new product, and labor protection. Second, community users are not the consumers of the social economy and the products of the social economy stay in market products only for the organizations in social economy. In order to create good services that meet the needs of residents, community development approaches are required at the same time. The importance of community space where local residents and social economy meet is derived. Third, public support such as purchasing support has weakened the ecosystem of social economy by making the distinction between public economy and social economy more obscure. On the other hand, public investment in community infrastructure is an indirect aid to social economy to communicate with residents and to promote good supply and consumption. In the end, community-based social services need a platform where the social economy and the people meet. This type of public investment can create the ecosystem of the social economy.

• Journal of vocational education research
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• v.35 no.4
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• pp.131-153
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• 2016

The purpose of this study was to derive evaluator's role and capability for institution accreditation evaluation of NCS-based vocational competency development training. This study attempted to explore in various ways evaluator's minute roles using Delphi method, and to derive knowledge, skill, attitude and integrity needed to verify the validity. To the end, this study conducted the Delphi research for over three rounds by selecting education training professionals and review evaluation professions as professional panels. From the results, roles of evaluators were defined as the total eight items including operator, moderator-mediator, cooperator, analyzer, verifier, institution evaluator, institution consultant, and learner, and the derived capabilities with respect to each role were 25 items in total. The area of knowledge included four items of capabilities such as HRD knowledge, NCS knowledge, knowledge of vocational competency development training, and knowledge of training institution accreditation evaluation, and the area of skill comprised fourteen items of capabilities such as conflict management ability, interpersonal relation ability, word processing ability, problem-solving ability, analysis ability, pre-preparation ability, time management ability, decision making ability, information comprehension and utilization ability, comprehensive thinking ability, understanding ability of vocational competency development training institutions, communication ability, feedback ability, and core understanding ability. The area of attitude was summarized with the seven items in total including subjectivity and fairness, service mind, sense of calling, ethics, self-development, responsibility, and teamwork. The knowledge, skill and attitude derived from the results of this study may be utilized to design and provide education programs conducive to qualitative and systematic accreditation and assessment to evaluators equipped with essential prerequisites. It is finally expected that this study will be helpful for designing module education programs by ability and for managing evaluator's quality in order to perform pre-service education and in-service education according to evaluator's experience and role.

• Korean Journal of Child Education & Care
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• v.19 no.2
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• pp.177-196
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• 2019

Objective: This study aims to analyze research trends related to software education for young children, focusing on studies published in Korea from 2016 to 2019 March. Methods: A total of 26 research publications on software education for young children, searched from Korea Citation Index and Research Information Sharing Service were identified for the analysis. The trend in these publications was classified and examined respectively by publication dates, types of publications, and the fields of study. To investigate a means of research, the analysis included key topics, types of research methods, and characteristics of the study variables. Results: The results of the analysis show that the number of publications on the topic of software education for young children has increased over the three years, of which most were published as a scholarly journal article. Among the 26 research studies analyzed, 16 (61.5%) are related to the field of early childhood education or child studies. Key topics and target subjects of the most research include the curriculum development of software education for young children or the effectiveness of software education on 4- and 5-year-old children. Most of the analyzed studies are experimental research designs or in the form of literature reviews. The most frequently studied research variable is young children's cognitive characteristics. For the studies that employ educational programs, the use of a physical computing environment is prevalent, and the most frequently used robot as a programming tool is "Albert". The duration of the program implementation varies, ranging from 5 weeks to 48 weeks. In the analyzed research studies, computational thinking is conceptualized as a problem-solving skill that can be improved by software education, and assessed by individual instruments measuring sub-factors of computational thinking. Conclusion/Implications: The present study reveals that, although the number of research publications in software education for young children has increased, the overall sufficiency of the accumulated research data and a variety of research methods are still lacking. An increased interest in software education for young children and more research activities in this area are needed to develop and implement developmentally appropriate software education programs in early childhood settings.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.197-217
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• 2018

Music is one of the most creative act that can express human sentiment with sound. Also, since music invoke people's sentiment to get empathized with it easily, it can either encourage or discourage people's sentiment with music what they are listening. Thus, sentiment is the primary factor when it comes to searching or recommending music to people. Regard to the music recommendation system, there are still lack of recommendation systems that are based on customer sentiment. An algorithm's that were used in previous music recommendation systems are mostly user based, for example, user's play history and playlists etc. Based on play history or playlists between multiple users, distance between music were calculated refer to basic information such as genre, singer, beat etc. It can filter out similar music to the users as a recommendation system. However those methodology have limitations like filter bubble. For example, if user listen to rock music only, it would be hard to get hip-hop or R&B music which have similar sentiment as a recommendation. In this study, we have focused on sentiment of music itself, and finally developed methodology of defining new index for music recommendation system. Concretely, we are proposing "SWEMS" index and using this index, we also extracted "Sentiment Pattern" for each music which was used for this research. Using this "SWEMS" index and "Sentiment Pattern", we expect that it can be used for a variety of purposes not only the music recommendation system but also as an algorithm which used for buildup predicting model etc. In this study, we had to develop the music recommendation system based on emotional adjectives which people generally feel when they listening to music. For that reason, it was necessary to collect a large amount of emotional adjectives as we can. Emotional adjectives were collected via previous study which is related to them. Also more emotional adjectives has collected via social metrics and qualitative interview. Finally, we could collect 134 individual adjectives. Through several steps, the collected adjectives were selected as the final 60 adjectives. Based on the final adjectives, music survey has taken as each item to evaluated the sentiment of a song. Surveys were taken by expert panels who like to listen to music. During the survey, all survey questions were based on emotional adjectives, no other information were collected. The music which evaluated from the previous step is divided into popular and unpopular songs, and the most relevant variables were derived from the popularity of music. The derived variables were reclassified through factor analysis and assigned a weight to the adjectives which belongs to the factor. We define the extracted factors as "SWEMS" index, which describes sentiment score of music in numeric value. In this study, we attempted to apply Case Based Reasoning method to implement an algorithm. Compare to other methodology, we used Case Based Reasoning because it shows similar problem solving method as what human do. Using "SWEMS" index of each music, an algorithm will be implemented based on the Euclidean distance to recommend a song similar to the emotion value which given by the factor for each music. Also, using "SWEMS" index, we can also draw "Sentiment Pattern" for each song. In this study, we found that the song which gives a similar emotion shows similar "Sentiment Pattern" each other. Through "Sentiment Pattern", we could also suggest a new group of music, which is different from the previous format of genre. This research would help people to quantify qualitative data. Also the algorithms can be used to quantify the content itself, which would help users to search the similar content more quickly.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.595-609
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• 2020

The purpose of this study is to analyze the experiences of teachers who participated in the development of online science class videos in the context of covid-19, their perception of online science class, and the characteristics of the online science class content developed by teachers. A survey and interviews were conducted with ten elementary school teachers who made online science class videos themselves. Also the characteristics of the online science class were investigated by analyzing the online science class video produced by the participants. As a result, participants in the study recognized the lack of production time, difficulty in filming and editing, concerns over misconceptions, the problem of solving copyrights for existing materials, and the burden of external disclosure. Although it was a teacher who had experience producing online science class video contents, no research participants actively answered the merits of online science class. On the other hand, the study participants cited that the shortcomings of online science classes were that students had fewer opportunities for inquiry and lack of communication or interaction. In particular, these shortcomings were thought to have a great influence on the quality of online science classes, especially in making inquiry classes difficult. Some teachers took a negative view that online science classes could not completely replace face-to-face classes. However, if multiple teachers are presented with supplementary teaching activities that complement the content-based online teaching method, the method of combining online science classes and face-to-face classes is not. Through the analysis of the contents of the online science class, the introduction and arrangement steps of the online science class were similar to the process of the face-to-face science class, but the inquiry step and the conceptual explanation step showed a big difference from the face-to-face science class.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.4
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• pp.5-13
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• 2022

The current environmental problem is that environmental pollution is accelerating due to the generation of large amounts of waste and indiscriminate consumption of energy. Fossil fuels, a representative energy production fuel, are burned in the process of producing energy, generating a large amount of greenhouse gases and eventually causing climate change. In addition, the amount of waste generated worldwide is continuously increasing, and environmental pollution is occurring in the process of waste treatment. One of the methods for simultaneously solving these problems is the energy recovery from and reduction of organic wastes. Sewage sludge generated in sewage treatment plants has been treated in various ways since ocean disposal was completely prohibited, but the amount generated has been continuously increasing. Since the sewage sludge contains a large amount of organic materials, it is desirable to recover energy from the sewage sludge and reduce the final discharged waste through anaerobic digestion. However, most of the excess sludge is a mass of microorganisms used in sewage treatment, and in order for the excess sludge to be anaerobically digested, the cell walls of the microorganisms must be destroyed first, but it takes a lot of time to destroy the cell walls, so high rates of biogas production and waste reduction cannot be achieved only by anaerobic digestion. Therefore, the pre-treatment process of solubilizing excess sludge is required, and the thermal solubilization process is verified to be the most efficient among various solubilization methods, and high rates of biogas production and waste reduction can be achieved by anaerobic digestion after destroying cell walls the thermal solubilization process. In this study, when pretreating TS 10% thickened excess sludge through a thermal solubilization system, a study was conducted on solubilization characteristics according to retention time and operating temperature variables. The experimental variables for the retention time of the thermal solubilization system were 30 minutes, 60 minutes, 90 minutes, and 120 minutes, respectively, while the operating temperature was fixed at 160℃. The soulbilization rates calculated through TCOD and SCOD derived from the experimental results increased in the order of 12.11%, 20.52%, 28.62%, and 31.40%, respectively. And the variables according to operating temperature were 120℃, 140℃, 160℃, 180℃, and 200℃, respectively, while the operating retention time was fixed at 60 minutes. And the solubilization rates increased in the order of 7.14%, 14.52%, 20.52%, 40.72%, and 57.85%, respectively. In addition, TS, VS, T-N, T-P, NH₄⁺-N, and VFAs were analyzed to evaluate thermal solubilization characteristics of thickened excess sludge. As a result, in order to obtain 30% or more solubilization rate through thermal solubilization of TS 10% thickened excess sludge, 120 minutes of retention time is required when the operating temperature is fixed to 160℃, and 170℃ or more of operating temperature is needed when the operating time is fixed to 60 minutes.

• Journal of the Korean Geosynthetics Society
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• v.20 no.2
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• pp.23-33
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• 2021

In Korea, many reservoirs have been built for the purpose of solving the food shortage problem and supplying agricultural water. However, the current 75.6% of the reservoirs are in serious aged as more than 50 years have passed since the year of construction. In the case of such an aging reservoir, the stability due to scour and erosion inside the reservoir is very reduced, and if concentrated rainfall due to recent abnormal weather occurs, the aging reservoir may collapse, leading to a lot of damage to property and human life. Accordingly, each agency that manages aging reservoirs uses Ordinary Portland Cement (OPC) as an injection material and applies the grouting method. However, in the case of OPC, it may deteriorate over time and water leakage may occur again. And there are environmental problems such as consumption of natural resources and generation of greenhouse gases. So, there is a need to develop new materials and methods that can replace the OPC. In this study, an laboratory test and analysis were performed on the grout material developed to induce a curing reaction similar to that of OPC by recycling power plant byproduct. In addition, test in the field such as electric resistivity survey, Standard Penetration Test (SPT), and field permeability test were performed to analyzed to reinforcement effect and determine the possibility of using instead of OPC. As a results of the test, in the case of recycled power plant byproduct, the compressive strength was 2.9 to 3.2 times and the deformation modulus was 2.3 to 3.3 times higher, indicating that it is excellent in strength and can be used instead of OPC. And it was analyzed that the N value of the reservoir was increased by 1~2, and the coefficient of permeability (k) decreased to the level of 8.9~42.5%. showing sufficient reinforcing effect in terms of order.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.