• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.681-689
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• 2019

Web usage pattern discovery is an advanced means by using web log data, and it's also a specific application of data mining technology in Web log data mining. In education Data Mining (DM) is the application of Data Mining techniques to educational data (such as Web logs of University, e-learning, adaptive hypermedia and intelligent tutoring systems, etc.), and so, its objective is to analyze these types of data in order to resolve educational research issues. In this paper, the Web log data of a university are used as the research object of data mining. With using the database OLAP technology the Web log data are preprocessed into the data format that can be used for data mining, and the processing results are stored into the MSSQL. At the same time the basic data statistics and analysis are completed based on the processed Web log records. In addition, we introduced the Apriori Algorithm of Web usage pattern mining and its implementation process, developed the Apriori Algorithm program in Python development environment, then gave the performance of the Apriori Algorithm and realized the mining of Web user access pattern. The results have important theoretical significance for the application of the patterns in the development of teaching systems. The next research is to explore the improvement of the Apriori Algorithm in the distributed computing environment.

• Journal of radiological science and technology
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• v.28 no.4
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• pp.307-315
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• 2005

In the ubiquitous computing environments, ICT industries of current society are developed in enormous growth. Medicine or patients with mobile devices can access at any time, any place. The medical procedures at the patient bedside are out of the scope of current systems, which means that patient record and image data access during the medical visit or the execution, recording and confirmation of the medicine prescriptions, still do not enjoy computerized support. Today, the exchange of medical images and clinical information is well defined by DICOM and HL7 standards. The DICOM independent terminal equipment image access system was developed in which a DICOM Engine acts as the gateway between a PACS DB and user's terminal. Implementation system is compatible with most currently available Integration system models. This paper presents a software technology where the medical and nursing staff will be equipped with any device connected by wire and wireless to a central server that provides access to the electronic patient records and that will actively inform about tasks pending distribution. The prototype described in this article implements a medical images and structured reports server that makes the search and recovery of data stored in the DICOM standard possible.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.493-502
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• 2012

This study aimed to determine the management and environmental factors affecting medical expense reduction. For analysis, medical expenses were divided into hospitalization expenses and outpatient treatment expenses, and the rate of medical expense reduction was classified into initial and final reduction rates. Data were collected through a direct survey among 205 directors of independent health insurance review departments of hospital-level medical institutions in Korea. The results of the study are discussed below: In the analysis, differences in the initial and final reduction rates of hospitalization expenses and outpatient treatment expenses were compared. The results showed that, in hospitalization expenses, the initial and final reduction rates were both significantly affected by the following management factors: number of beds, number of departments, number of personnel reviewing health insurance cases, and total number of employees. Further, in outpatient treatment expenses, the initial and final reduction rates were both affected significantly by the following management factors: management of medical records, number of beds, number of departments, number of personnel reviewing health insurance, and total number of employees. The management factors significantly affecting both the initial and final reduction rates were higher number of beds for hospitalization expenses and electronic medical record management for outpatient treatment expenses. The environmental factors significantly affecting both the initial and final reduction rates of hospitalization expenses were a highly cooperative work environment, better implementation of indicator management systems, and overtime pay. Better implementation of indicator management system and a committee for handling medical expenses had significant effects on the initial reduction rate for outpatient treatment expenses. A highly cooperative work environment, better implementation of indicator management system, and overtime pay had significant effects on the final reduction rate for outpatient treatment expenses.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.430-444
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• 2021

Purpose: This study is an integrated literature review to analyze health problems and social determinants of multicultural adolescents in South Korea. Methods: An integrative review was conducted according to Whittemore & Knafl's guideline. An electronic search that included publications from 2018 to 2020 in the PubMed, EMBASE, Cochrane Library, CINAHL, RISS, and KISS databases was conducted. Of a total of 67 records that were identified, 13 finally met full inclusion criteria. Text network analysis was also conducted to identify keywords network trends using NetMiner program. Results: The health problems of multicultural adolescents were classified into mental health (depression, anxiety, suicide and acculturative stress) and health risk behaviors (smoking, risky drinking, smartphone dependence and sexual behavior). As social determinants affecting the health of multicultural adolescents, the biological factors such as gender, age, and visible minority, and the psychological factors such as acculturative stress, self-esteem, family support, and ego-resiliency were identified. The sociocultural factors were identified as family economic status, residential area, parental education level, and parents' country of birth. As a result of text network analysis, a total of 41 words were identified. Conclusion: Based on these results, mental health and health risk behaviors should be considered as interventions for health promotion of multicultural adolescents. Our findings suggest that further research should be conducted to broaden the scope of health determinants to account for the effects of the physical environment and health care system.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.265-270
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• 2014

Hearing-impaired people have difficulty in hearing, so it is also hard for them to learn letters that represent sound and text that conveys complex and abstract concepts. Therefore it has been natural choice for the hearing-impaired people to use sign language for communication, which employes facial expression, and hands and body motion. However, the major communication methods in daily life are text and speech, which are big obstacles for the hearing-impaired people to access information, to learn and make intellectual activities, and to get jobs. As delivering information via internet become common the hearing-impaired people are experiencing more difficulty in accessing information since internet represents information mostly in text forms. This intensifies unbalance of information accessibility. This paper reports web-based text-to-sign language translating system that helps web designer to use sign language in web page design. Since the system is web-based, if web designers are equipped with common computing environment for internet browsing, they can use the system. The web-based text-to-sign language system takes the format of bulletin board as user interface. When web designers write paragraphs and post them through the bulletin board to the translating server, the server translates the incoming text to sign language, animates with 3D avatar and records the animation in a MP4 file. The file addresses are fetched by the bulletin board and it enables web designers embed the translated sign language file into their web pages by using HTML5 or Javascript. Also we analyzed text used by web pages of public services, then figured out new words to the translating system, and added to improve translation. This addition is expected to encourage wide and easy acceptance of web pages for hearing-impaired people to public services.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.3
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• pp.318-333
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• 2023

The purpose of this study is to analyze changes in dental trauma in children under the age of 12 during the period of Coronavirus Disease 2019 (COVID-19). March 2020, when COVID-19 was officially declared a pandemic by the World Health Organization, was set as the starting point for COVID-19. From March 2018 to February 2020, subjects in the pre-COVID-19 period were classified as the Pre-COVID-19 group, and from March 2020 to March 2022, subjects in the post-COVID-19 period were classified as the COVID-19 group. Information related to trauma was collected through electronic medical records. The number of trauma patients before and after the outbreak of COVID-19 decreased significantly. During the COVID-19 period, there was no significant difference in the male-female ratio or the distribution order of age groups. In the COVID-19 group of permanent teeth, the ratio of trauma caused by personal mobility was higher than trauma caused by sports. In the COVID-19 group of permanent teeth, the ratio of crown fracture with pulp involvement was significantly higher than the ratio of crown fracture without pulp involvement. Changes in trauma patterns caused by COVID-19 were observed more clearly in school-aged children than in preschool children. In a pandemic situation such as COVID-19, it is expected to be used as a good educational basis for knowing that frequent diagnoses can change due to changes in the environment.