• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.45-53
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• 2019

We face problems from excessive information served with websites in this rapidly changing information era. We find little information useful and much useless and spend a lot of time to select information needed. Many websites including search engines use web crawling in order to make data updated. Web crawling is usually used to generate copies of all the pages of visited sites. Search engines index the pages for faster searching. With regard to data collection for wholesale and order information changing in realtime, the keyword-oriented web data collection is not adequate. The alternative for selective collection of web information in realtime has not been suggested. In this paper, we propose a method of collecting information of restricted web sites by using Web crawling distributed monitoring system (R-WCMS) and estimating collection time through detailed analysis of data and storing them in parallel system. Experimental results show that web site information retrieval is applied to the proposed model, reducing the time of 15-17%.

• Korean Journal of Family Social Work
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• no.55
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• pp.91-128
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• 2017

The purpose of this study is to develop an effective intervention strategy for marriage migrant woman in family therapy. For this purpose, we collected counseling cases of professional counselors who successfully completed counseling and attempted the qualitative analysis of treatment intervention strategies and effects. The results of the study were obtained by dividing the meaning units in the immigrant woman's statements made during the counseling process composed of a total of 6 sessions. The counselors were analyzed to have tried the following intervention strategies. They attempted the following six strategies: Helping emotional differentiation by searching for unresolved emotional problems, dealing with undifferentiation due to family projection process and love triangle, dealing with multi-generational transfer process of the original family relationship patterns and coping mechanism, shedding lihgt on ineffectiveness of inconsistent communication due to emotional oppression applying a communication model of MRI, switching client's awareness through reorganization, suggesting a way of communication that leads to real self. Such counselors' attempts resulted in positive changes and treatment effects were found to include first, cognitive insights and motivation for change, second, improved communication skills and third, anxiety reduction and self-differentiation. Due to their husbands' refusal to participate in counseling, marriage migrant women often get involved in counseling alone, so they tend to worry that the effectiveness of family therapy may be low but it was found that the proper intervention of the counselor could improve the ability of the wife to resolve conflicts, which would be a great help in solving problems such as family violence and this study is meaningful in that it provided the appropriate therapeutic intervention strategies needed.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.131-139
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• 2019

From 2019, software education has become a required subject for all elementary school students. However, many teachers are still unfamiliar with how the classes should be instructed. So this paper presented the meaning, detailed competencies and achievement standard in order to help in the collection, analysis and representation of data among the computational thinking that are key to software education. And it also suggested the applicability of the classes. The full course of the paper is summarized as follows. First, existing studies have summarized the meaning, detail and achievement standard of data related competencies. Based on this, a preliminary investigation was instructed. Pilot study carried out both FGI and closed questions at the same time. This was done in response to the survey's questionnaire reflecting the opinions of experts. Second, the results of the questionnaire generated as a result of the above were verified for validity, stability, and reliability among the PhD, PhD courses, software education teachers, and software education workers. Third, I developed and applied the five lessons as a class objective as 'Choosing collection method-Select the collection method according to the problem situation.', 'Searching for meaning of data-Understand what the analyzed data mean..', 'Using various expression methods-Use a variety of expression tools.' using the backward design model to integrate education, class, and assessment. As a result, the detailed competencies of data collection, analysis, and representation and achievement standard were presented. This may help in setting specific and specific criteria for what direction classes are recommended when planning data-related classes in elementary schools.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.3
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• pp.61-78
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• 2021

Records on Japanese "Comfort Women" have been individually managed by private sectors or institutions, and some are provided as digital archives on the Internet. However, records of digital archives differ in the composition and representation of metadata by individual institutions. Meanwhile, there is a lack of a consistent structure to describe the relationships between and among these records, leading to their fragmentation and disconnectedness. This paper proposes a knowledge model for interlinking the digital archival resources and builds a knowledge graph by integrating the records from distributed digital archives. It derives common elements by analyzing metadata from the diverse digital archives and expresses them in standard vocabularies to semantically describe multiple entities and relationships of the digital archival resources. In particular, the study includes the refinement of collected data to search and thread dispersed records and the enrichment of external data to provide significant contextual information of records. An evaluation of the knowledge graph is performed via a query measuring the (dis)connectivity between the distributed records. As a result, the knowledge graph is capable of interlinking and retrieving fragmented records, providing substantial contextual information on the records with external data enrichment, and searching accurately to match the user's intentions through semantic-based queries.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.505-514
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• 2020

This research introduces the method of developing Korea BIM standard (KBIMS) architectural and structural element library and the methodology of converting KBIMS IFC property names with special characters. Diverse BIM tools are utilizing in project, however BIM library researches lack diversity on BIM tool selection. This research described the method to generate twelve categories and seven hundred and ninety-three elements library containing geometrical and numerical data in CATIA V6. KBIMS has its special property data naming systems which was the challenge inputting to ENOVIA IFC database. Three mapping methods for special naming characters had been developed and the ASCII code method was applied. In addition, the convertor prototype had been developed for searching and replacing the ASCII codes into the original KBIMS IFC property names. The methodology was verified by exporting 2,443 entities without data loss in the sample model conversion test. This research would provide a wider choice of BIM tool selection for applying KBIMS. Furthermore, the research would help on the reduction of data interoperability issues in projects. The developed library would be open to the public, however the continuous update and maintenance would be necessary.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.97-104
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• 2022

European integration processes have acted as a catalyst for the emergence of a new type of educational environment, which is characterized by competent flexibility of specialists. Therefore, the article focuses on professional training of teachers in the context of European integration processes using information technology and the search for innovative methods of training specialists. One of the educational priorities in Europe is to create a new model of a teacher who has an academic education, knows innovative methods, is able to perform functions and tasks efficiently and professionally, adequately, quickly and correctly respond to changes and innovations. The tasks facing education in the European dimension are formulated. The main trends in the education of teachers in modern Europe are described: the need to deepen and expand subject training programs in pedagogical institutions of Higher Education, which will allow autonomy of activity, awareness of responsibility for independent creative decisions, create favorable conditions for the development of professionalism through the use of Information Technology and the search for innovative methods of training specialists. At the present stage, various models of teacher training are being developed based on the University and practical concept using information technology and searching for innovative methods of training specialists. On this basis, two different theories of perception of teacher education were formed: as preparation of teachers for work throughout their professional career; as preparation for the first years of professional work, which is periodically repeated in the process of continuous professional training and improvement. Among the advantages that the use of Information Technology and the search for innovative methods of training specialists to implement the learning process, it is worth mentioning the following: simultaneous use of several channels of perception of the student or student in the learning process, thanks to which the integration of information processed by different sensory organs is achieved; the ability to simulate complex real experiments; visualization of abstract information by dynamic representation of processes, etc.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.121-138
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• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.539-551
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• 1996

In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.