• Journal of dental hygiene science
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• v.17 no.6
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• pp.501-507
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• 2017

The shortage of dental hygienists has been a long-standing problem in Korea. Small-scaled dental clinics suffer from a lack of dental hygienists, who seem to prefer working at large-scaled dental clinics. The purpose of this study was to confirm the differences in the working conditions according to the scales of dental clinics. We collected the working information registered via job advertisements through the web-sites of Korean Dental Hygienists Association, Dental Jobs, and Nurse Jobs from July to August 2016. The results were as follows: 96.7% of the advertisements wanted regular workers, while the proportion of part-time workers was the highest (34.8%) in the group with less than 3 employees. The average workdays per week was $5.32{\pm}0.55$ days, and the group with less than 3 employees had significantly longer workdays than the other groups. The daily working time was $8.99{\pm}0.44$ hours, and there was no difference among the groups. Night overtime hours were needed by 54.4%, 45.0%, and 31.3% of the groups with of the groups with 4~7 employees, more than 8 employees, and less than 3 employees, respectively. Information regarding annual leave (60.5%), monthly leave (63.9%), half a day off (32.4%) and vacations (43.1%) were presented in the job advertisements, and these proportions were significantly higher by the group with more than 8 employees. Information on overtime pay (14.4%), night-work pay (13.4%), incentives (34.1%), lunches (60.2%), vacation bonuses (33.8%), and self-development (20.4%) were presented in job advertisements. The group with 4~7 employees had significantly higher proportions in severance pay, vacation bonuses, self-development, and major national insurance. It is necessary to consider the improvement of working conditions, diversity of working styles, and welfare of dental hygienists, and it is suggested that small dental clinics provide more precise working conditions.

• Journal of the Korea Concrete Institute
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• v.27 no.2
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• pp.185-193
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• 2015

Ultra high performance concrete (UHPC) has been developed to overcome the low tensile strengths and brittleness of conventional concrete. Considering that UHPC, owing to its composition and the use of steel fibers, develops a compressive strength of 180 MPa as well as high stiffness, the top flange of the steel girder may be superfluous in the composite beam combining a slab made of UHPC and the steel girder. In such composite beam, the steel girder takes the form of an inverted-T shaped structure without top flange in which the studs needed for the composition of the steel girder with the UHPC slab are disposed in the web of the steel girder. This study investigates experimentally and analytically the flexural behavior of this new type of composite beam to propose details like stud spacing and slab thickness for further design recommendations. To that goal, eight composite beams with varying stud spacing and slab thickness were fabricated and tested. The test results indicated that stud spacing running from 100 mm to 2 to 3 times the slab thickness can be recommended. In view of the relative characteristic slip limit of Eurocode-4, the results showed that the composite beam developed ductile behavior. Moreover, except for the members with thin slab and large stud spacing, most of the specimens exhibited results different to those predicted by AASHTO LRFD and Eurocode-4 because of the high performance developed by UHPC.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.159-172
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• 2010

The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Journal of the Korea Concrete Institute
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• v.26 no.6
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• pp.761-769
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• 2014

Ultra high performance concrete (UHPC) has been developed to overcome the low strengths and brittleness of conventional concrete. Considering that UHPC, owing to its composition and the use of steel fibers, develops a compressive strength of 180 MPa as well as high stiffness, the top flange of the steel girder may be superfluous in the composite beam combining a slab made of UHPC and the steel girder. In such composite beam, the steel girder takes the form of an inverted-T shaped structure without top flange in which the studs needed for the composition of the steel girder with the UHPC slab are disposed in the web of the steel girder. This study investigates experimentally and analytically the flexural behavior of this new type of composite beam to propose details like stud spacing and slab thickness for further design recommendations. To that goal, eight composite beams with varying stud spacing and slab thickness were fabricated and tested. The test results indicated that stud spacing running from 100 mm to 2 to 3 times the slab thickness can be recommended. In view of the relative characteristic slip limit of Eurocode-4, the results showed that the composite beam developed ductile behavior. Moreover, except for the members with thin slab and large stud spacing, most of the specimens exhibited results different to those predicted by AASHTO LRFD and Eurocode-4 because of the high performance developed by UHPC.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.61-83
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• 2012

A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4291-4297
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• 2015

EEG has been used to measure the emotion of amenity and discomfort in the interior space. EEG is limited to the experiment, because it is a equipment of contact type. However, Vibraimage can measure the emotion with a web camera. Because Vibraimage is a equipment of non-contact type, it is more suitable for the interior space than EEG. Therefor, it tries to find a correlation variable between EEG and Vibraimage to measure the human emotions. In this study, it were analyzed correlation of EEG and vibraimage due to variation of loudness 60[dB], 90[dB] and rosemary, jasmine scents. Check the health status of subjects who were selected 3 male students, and the period of this experiment was about months. The condition of the environmental test room was in temperature 25[$^{\circ}C$], relative humidity 50[RH%], air current speed 0.02[m/s] and illuminance 1000[lux]. It were analyzed correlation of twenty-three index of EEG(absolute ${\theta}$, relative ${\theta}$, absolute $S{\alpha}$, relative $S{\alpha}$, absolute ${\alpha}$, relative ${\alpha}$, absolute ${\beta}$, relative ${\beta}$, absolute $\gamma$, relative $\gamma$, absolute $F{\alpha}$, relative $F{\alpha}$, absolute SMR, relative SMR, $SMR/{\theta}$, $SMR+M{\beta}/{\theta}$, absolute $H{\beta}$, relative $H{\beta}$, $H{\beta}/{\alpha}$, absolute $M{\beta}$, relative $M{\beta}$, SEF50, ASEF50) and ten index of Vibraimage(Aggression, Stress, Tension/Anxiety, Suspect, Balance, Charm, Energy, Self regulation, Inhibition, Neuroticism). As a result, I was found that relative ${\gamma}$ index of EEG and neuroticism index of Vibraimage have a high correlation as (${\pm}$).414 and (${\pm}$).424.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.1
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• pp.16-21
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• 2022

Objectives : The purpose of this study is to investigate depression and suicide ideation according to socioeconomic changes after COVID-19 among Korean adolescent. Methods : Data on the study population were obtained from the 16th Korea Youth Risk Behavior Web-based Survey (KYRBS). The KYRBS is a nationally representative sample of Korean adolescents (aged 12-18 years) that originally included over 103 questions in 15 domains of health-risk behaviors. In the 16th KYRBS, a total 54,948 students from 793 schools responded to the survey. Chi-square test and logistic regression analysis were conducted regarding depression and suicide ideation. Results : This study suggests that changes in the family household before and after COVID-19 pandemic are also affecting the mental health of the adolescents. The study shows that worse change of family household is significant associations with suicidal ideation and depression. Adolescents reporting worse (AOR 1.38; 95% CI 1.38-1.57) and much worse (AOR 2.07; 95% CI 1.87-2.29) were significantly more likely to report depression. Adolescents reporting worse (AOR 1.34; 95% CI 1.34-1.60) and much worse (AOR 2.01; 95% CI 1.76-2.29) were significantly more likely to report suicide ideation. Conclusions : In this study, it was confirmed that young people from socially disadvantaged backgrounds are at high risk of suicide ideation and more depression. The results of this study suggest that we should consider improving the screening and prevention of mental health problems for adolescents with poor socioeconomic changes of COVID-19.

• Journal of Korean Home Economics Education Association
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• v.26 no.4
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• pp.85-114
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• 2014

The main purpose of this study was to develop teaching and learning plans and a smart textbook for food and nutrition education in Home Economics focusing on 'healthy diet and meal plans' unit in "Technology home Economics" textbooks for 7th graders to evaluate the effectiveness of the instruction conducted with the smart textbook. The content of the study to achieve the purpose is as follows: First, design a smart education-based teaching and learning curriculum for food and nutrition education in Home Economics, focusing on 'healthy diet and meal plans' unit. Second, develop a smart textbook for food and nutrition education based on the teaching and learning curriculum, using a smart content authoring tool. Third, evaluate the effectiveness of the instruction after applying the curriculum in real classroom situations. The results of this study were as follows: First, teaching and learning plans and materials were developed for two units, 'issues regarding teenagers' diet' and 'implementation of a healthy and balanced diet', under 'teenagers' life'. The first unit, 'issues regarding teenagers' diet', dealt with topics such as teenagers' dietary behaviors, nutrition, and health. Learning objectives for this unit were to help students identify and evaluate their own dietary behaviors. The second unit, 'implementation of a healthy and balanced diet', encouraged students to diagnose problems with their diet and plan nutrient rich meals. The objectives for this unit were to help students implement a healthy and balanced diet by providing them with nutrition and dietary guidelines for Koreans, sample meal plans, and guidelines for developing healthy eating habits for teenagers. In order to develop a teaching and learning plans to achieve these objectives, teaching and learning materials including inquiry tasks, materials for group activities, multimedia, applications and various pop-up learning materials were developed. Second, a smart textbook using DocZoom, which was a smart content authoring tool was developed. The textbook dealt with issues regarding teenagers' diet and implementation of a healthy and balanced diet. Multimedia material used in the textbook come from the Ministry of Food and Drug Safety's food and nutrition education web sites and other sources. To develop student-oriented material, relevant video clips were added to the smart textbook to motivate students and enhance their interest in the course. Third, the outcome of this study indicated that the instruction using teaching and learning plans and learning materials with the smart textbook was effective for enhancing students' interest in Home Economics classes (t-value=-3.99, p<.001), creating enthusiasm for learning(t-value = -2.61, p<.05), encouraging self-directed and independent learning(t-value = -4.77, p<.001), and improving students' interest in food and nutrition courses(t-value = -3.83, p<.001). The students' evaluation of the instruction were as follows: the instruction using teaching and learning plans and learning materials with smart textbooks, instead of paper textbooks, helped them save time looking for learning materials; students evaluated that it was easier for them to see and understand video clips and charts. In addition, most students answered that instruction with smart textbooks were more fun and convenient, and they agreed that the courses enhanced their learning experience.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.