• Journal of dental hygiene science
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• v.2 no.2
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• pp.95-103
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• 2002

This study was carried out to investigate recognition level and practical application status of oral hygiene devices through making a survey of Seoul inhabitants. And survey was implemented in order to propose oral hygiene device for household health care activities. The following results were obtained by analyzing personal interviews of 347 commuting patients at two university hospitals and seven dental clinics. 1) The average length of toothbrush head was estimated as 22.3 mm and average changing cycle was 2.3 months. The user ratio of flat-headed brush was estimated as 51.9% and 46.7% were using fluoridated toothpaste. 2) Generally the ratio of toothpick users was higher than other device users. But the user ratio of dental floss was higher than toothpick in case of patients under orthodontic treatment. 3) The patients under orthodontic treatment were not familiar with handling orthodontic toothbrush. Though 45.8% among orthodontic patients recognized this type of toothbrush, only 25.4% of them knew how exactly to use it. 4) It was shown very low user ratio of oral hygiene devices that the patients who had periodontal problem, hypersensitive trouble, halitosis, implant or denture 5) The patients who had halitosis showed the highest user ratio of toothpick. The patients who had separation of teeth showed the highest user ratio of dental floss. The patients who're under orthodontic treatment showed the highest user ratio of interproximal brush and motorized brush. 6) In response to the most interesting dental disease, it's surveyed as follows; 60.3% of dental caries, 24.0% of periodontal disease, 14.8% of false occlusion and 0.9% of oral cancer. 7) Regarding the motivation of using those oral hygiene devices, 45% responded that it was because of recommendation by dental clinics. Among the negative answers, 38.6% responded that it was because of no selection guidance. 31.3% answered that they didn't use hygiene device because it's inconvenient. 12.0% answered that it's difficult to buy and expensive. 7.8% responded that they didn't feel significant improvement. 4.8% answered that dental hospitals and clinics didn't even introduce those hygiene devices. Therefore efficient campaign for those hygiene devices over all Korea nation should be developed and education program must be prepared for each case of patients in every dental hospitals and clinics.

• Journal of Korea Port Economic Association
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• v.25 no.1
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• pp.15-28
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• 2009

The purpose of this paper is to show the empirical extraction way of benchmarking ports for overcoming the shortcoming which the traditional DEA method has by using 20 Korean ports in 2003 for 2 inputs (birthing capacity, cargo handling capacity) and 2 outputs(Export and Import Quantity, Number of Ship Calls). Because DEA method has produced the limited set of efficient units which are reference to inefficient units respective of their differences in efficiency scores, it is necessary to adopt the more feasible benchmarking information according to the path analysis(tier or stratification). The core empirical results of this paper are as follows. Benchmarking ports against inefficient ports according to the tier analysis are that Masan Port(Janghang$\rightarrow$Jeju$\rightarrow$Seogoipo$\rightarrow$Yeosu), Jinhae Port(Janghang$\rightarrow$Mogpo$\rightarrow$Seogoipo$\rightarrow$Wando), Pohang&DonghaePort(Janghang$\rightarrow$Samcheonpo$\rightarrow$Pyungtag$\rightarrow$Samcheog), and Sogcho Port(Janghang$\rightarrow$Mogpo$\rightarrow$Seogoipo$\rightarrow$Wando). The policy implication to the Korean seaports and planners is that Korean seaports should introduce the new methods like Tier analysis of this paper for evaluating the port performance and enhancing the efficiency in short term, mid term, and long term according to the tier 3 stage, the tier 2 stage, and the tier 1 stage with original DEA stage.

• The Journal of Korean Society for School & Community Health Education
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• v.6
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• pp.17-34
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• 2005

The purpose of this study was to examine the sex-consciousness and sexual values of school children by geographic region. It's specifically attempted to make a comparative analysis of sex-consciousness and sexual values between urban and rural elementary schoolers to help provide efficient sex education for them to build the right sexual values. The subjects in this study were 400 elementary schoolers in their sixth year of elementary schools located in Danyang-gun and Chungju city, north Chungcheong province. After a survey was conducted, answer sheets from 387 students that were analyzable were analyzed. For data handling, SPSS program was employed, and t-test was utilized to see if there's any differences between the urban and rural elementary school youngsters in sex consciousness and sexual values. And $x^2$ test was used to make a comparative analysis of their view of sex education. The findings of the study were as follows : First, regarding sex-consciousness, they had general knowledge on sex. Especially, they were highly aware of sexual violence and the generation of baby, but many of them didn't know about where and how egg cells were produced. This indicated that systematic education should be offered in various ways. Concerning geographic gap, there was a significant difference in sexual knowledge between the urban and rural students. As to sexual attitude, they took a relatively positive attitude toward display of affection or sex-related talk on TV or in movies, as they viewed it as natural. This finding implied that the elementary schoolers were recipient toward sex and took an active attitude toward sexual expressions. Concerning geographic gap, there was no difference between the rural and urban students. As for sexual practices, the largest group of the students had a liking for the opposite sex, which showed that their needs for sex were unveiled in the course of having some trouble due to the other sex rather than through firsthand experiences or activities. As to geographic gap, there was a significant difference between the urban and rural students in that regard. Besides, the urban students put their sex-consciousness in practice more often than the rural students did. After they are educated to build the right sexual values, systematic sex-education programs should also be offered for them to be exposed to sustained sex education and to team how to apply their sex-consciousness to real life. Second, as for sexual values, the school children had relatively positive and equalitarian sexual values. Regarding geographic gap, there were significant gaps between the two groups' view of the opposite sex, sexual roles and chastity. Concerning view of the opposite sex, they attached more importance to the inner aspects of the opposite sex than his or her look, and they wanted to date in a natural manner. Regarding sexual roles, they were relatively well cognizant of gender equity and the importance of male and female roles. As to view of chastity, they looked upon sex as natural, not as what's ugly or ashamed of. Third, concerning their outlook on sex education, approximately more than half the students felt the needs for sex education, and there was a significant difference between the urban and rural students. They wanted to receive education about the prevention of sexual violence and physical changes during puberty the most, and there was a significant gap between the urban and rural students in this aspect. As to the time for sex education, they thought that students should start to be exposed to sex education in their fifth or sixth year. This finding signified that fifth or sixth graders who were in the beginning of puberty started to have a lot of interest in their own physical changes. Therefore, sex education would produce better effects when it's provided to fifth or sixth graders. Nearly half them preferred single-gender class when they received sex education, and there's no gap between the urban and rural students in that regard.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.268-276
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• 2018

BACKGROUND: In the month of January 2018, fine dust alerts and warnings were issued 36 times for $PM_{10}$ and 81 times for PM2.5. Air quality is becoming a serious issue nation-wide. Although interest in air-purifying plants is growing due to the controversy over the risk of chemical substances of regular air-purifying solutions, industrial spread of the plants has been limited due to their efficiency in air-conditioning perspective. METHODS AND RESULTS: This study aims to propose a vegetation-based bio-filter system that can assure total indoor air volume for the efficient application of air-purifying plants. In order to evaluate the quantitative performance of the system, time-series analysis was conducted on air-conditioning performance, indoor air quality, and comfort index improvement effects in a lecture room-style laboratory with 16 persons present in the room. The system provided 4.24 ACH ventilation rate and reduced indoor temperature by $1.6^{\circ}C$ and black bulb temperature by $1.0^{\circ}C$. Relative humidity increased by 24.4% and deteriorated comfort index. However, this seemed to be offset by turbulent flow created from the operation of air blowers. While $PM_{10}$ was reduced by 39.5% to $22.11{\mu}g/m^3$, $CO_2$ increased up to 1,329ppm. It is interpreted that released $CO_2$ could not be processed because light compensation point was not reached. As for the indoor comfort index, PMV was reduced by 83.6 % and PPD was reduced by 47.0% on average, indicating that indoor space in a comfort range could be created by operating vegetation-based bio-filters. CONCLUSION: The study confirmed that the vegetation-based bio-filter system is effective in lowering indoor temperature and $PM_{10}$ and has positive effects on creating comfortable indoor space in terms of PMV and PPD.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.