• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.47-55
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic continuously influences on the health and well-being of people and communities worldwide. The purpose of this study was to explore the published research articles in the fields of nursing and health during the COVID-19 pandemic. The research design is an exploratory study. Samples are the abstracts of the articles from a literature database, PubMed, that were published from January 1st, 2020 to April 15th, 2021. We used a MeSH term, 'nursing' and "COVID-19" to retrieve articles that are related to COVID-19. Five hundred and fifty-five articles were retrieved. Two hundred and sixteen articles were excluded as they were not met the inclusion criteria. The total number of articles used in this study was three hundred and thirty-nine. The average number of articles published during the data collection period was 21.9. Seven topics were discovered from the abstracts of the articles: COVID-19 management and guidance; Perinatal COVID-19 and breastfeeding; Nurse; Health service and support; Patient care; Research; and Education and experience. This study revealed some interesting topics from the articles related to COVID-19 and provided some sense of research areas that may be interesting and allow us to develop important research questions about nursing science and nursing practice.

• Smart Structures and Systems
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• 제30권4호
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• pp.385-395
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• 2022

Detecting cracks on a concrete structure is crucial for structural maintenance, a crack being an indicator of possible damage. Conventional crack detection methods which include visual inspection and non-destructive equipment, are typically limited to a small region and require time-consuming processes. Recently, to reduce the human intervention in the inspections, various researchers have sought computer vision-based crack analyses: One class is filter-based methods, which effectively transforms the image to detect crack edges. The other class is using deep-learning algorithms. For example, convolutional neural networks have shown high precision in identifying cracks in an image. However, when the objective is to classify not only the existence of crack but also the types of cracks, only a few studies have been reported, limiting their practical use. Thus, the presented study develops an image processing procedure that detects cracks and classifies crack types; whether the image contains a crazing-type, single crack, or multiple cracks. The properties and steps in the algorithm have been developed using field-obtained images. Subsequently, the algorithm is validated from additional 227 images obtained from an open database. For test datasets, the proposed algorithm showed accuracy of 92.8% in average. In summary, the developed algorithm can precisely classify crazing-type images, while some single crack images may misclassify into multiple cracks, yielding conservative results. As a result, the successful results of the presented study show potentials of using vision-based technologies for providing crack information with reduced human intervention.

• Asia pacific journal of information systems
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• 제31권4호
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• pp.543-574
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• 2021

This study focuses on a better understanding of the importance of risk perception in adopting Mobile Payment Systems (MPS) by conducting a systematic literature review. From the social science field (using Scopus and Web of Science database) articles were selected. Overall, forty-four significant pieces were determined using a systematic methodology. In addition to providing a summary of the most used theories used to address perceived risk in MPS this paper also investigates the definition for the perceived risk in MPS literature. The study is performed through the identification of dominant theories used to explain perceived risk in the literature. The article gives a thematic analysis of theories and the relation of perceived risk with behavioural intention. As far as we know, this is the first effort of its kind to give a holistic, systematic literature review in light of perceived risk in MPS. Consequently, it is a crucial first step in establishing a solid theoretical framework involving the constructs of perceived risk and laying the groundwork for future research in this area.

• 정보처리학회논문지A
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• 제10A권5호
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• pp.469-478
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• 2003

인터넷상의 정보 검색 엔진들은 웹 로봇을 이용해서 인터넷에 연결되어 있는 수 많은 웹 서버들을 주기적 또는 비주기적으로 방무나여 자체적인 인텍싱 방법에 따라 자료를 추출하고 분류해서 검색 엔진의 기초가 되는 데이터 베이스를 구축하고 변겨아는 작업을 계속하고 있다. 이런 일련의 작업은 인터넷 상에 분산되어 있는 막대한 정보를 쉽고 정확하게 찾을 수 있는 게이트 사이트로서의 역할을 담당하기 위한 전략적인 목적으로 진행되고 있다. 수천만 이상의 웹 사이트들을 상대로 하는 정보 수집은 검색 엔진 사이트 중심으로 기존 데이터의 수정과 삭제 등과 같은 데이터 베이스 유지 관리와 신규 사이트들에 대한 자료 수집 작업이 이루어지고 있다. 이러한 작업은 웹 서버에 대한 사전 지식 없이 정보 추출을 위해 웹 로봇을 실행하므로 인터넷 상에 수많은 요구가 전송되고 이는 인터넷 트래픽을 증가 시키는 원인이 되고 있다. 따라서 웹 서버가 사전에 자신이 공개할 문서에 대한 변경 정보를 웹 로봇에게 통보하고 웹 로봇은 이 정보를 이용해서 웹 서버의 해당 문서에 대한 정보 수집 작업을 한다면 불필요한 인터넷 트래픽을 감소시킬 수 있을 뿐만 아니라 검색 엔진의 정보의 신뢰도도 높아지고 웹 서버의 해당 문서에 대한 정보수집 작업을 한다면 불필요한 인터넷 트래픽을 감소 시킬 수 있을 뿐만 아니라 검색 엔진의 정보의 신뢰도도 높아지고 웹 서버의 시스템 부하와 검색 엔진의 시스템 부하를 줄일 수 있는 효과를 가질 수 있을 것이다. 본 논문에서는 웹 서버상의 웹 문서 파일의 변동 사항을 자동으로 검사하고 변동 사항들을 종합 정리해서 변경 문서에 대한 정보를 통보 받기 원하는 등록된 각 웹 로봇에게 전송하는 검사 통보 시스템을 설계 구현하였다. 웹 로봇을 운영하는 검색 엔진에서는 통보된 요약 정보를 이용해서 웹 서버로부터 해당 문서를 전송 받아 필요로 하는 인덱스 정보를 추출해서 데이터베이스를 구축하는 효율적인 웹 로봇을 설계 구현하였다.

• 보건의료산업학회지
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• 제9권3호
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• pp.175-185
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• 2015

Objectives : This study was did a meta-analysis of emergency room visits decreased effectiveness of self management education interventions in asthma among adult patients with asthma. Methods : A search of the database PubMed resulted in identifying 8,619 studies done between January 1990 and November 2012. STATA version 10.0 was used to analyze the effect size, explore possible causes of heterogeneity, and determine publication bias with a funnel plot. Results : We included 7 cases on emergency room visits decreased effectiveness of self management and education. Asthmatic patients experienced fewer attacks (summary effect size, 0.75; 95% confidence interval [CI], 0.65-0.95). We found that emergency room visits decreased effectiveness of self management and education were associated with statistically significant effects. Conclusions : Based on these finding, self management and education on interventions are necessary to prevent asthmatic attacks in patients and to reduce the severity of the attacks, and self management and education programs are needed in Korea.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.332-338
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• 2009

한의학 통계의 생산, 관리 및 제공은 구체적이고 객관적인 데이터를 활용한 한의학 정책의 수립과 근거에 기반한 한의학 연구를 위해 필수적인 요소이다. 그러나 현재 한방 통계 서비스는 정부와 민간의 유관 단체가 산별적으로 제공하는 상황에서 체계적이고 통합적인 서비스가 이루어지고 있지 않기 때문에 이용자는 신뢰할 수 있으며 유용한 가치를 가진 데이터의 검색, 획득 및 활용에 많은 어려움이 있다. 본 연구는 각 기관에서 생산하는 한의학 관련 통계자료를 분석하여 이용자가 편리하게 이용할 수 있도록 한방 통계를 7가지 분야로 구분하고, 분야별 서비스 통계 항목을 분석하였다. 서비스 이용에 대한 시나리오 설계를 바탕으로 테이블 동적생성기법을 이용하여 데이터베이스를 설계하였으며 Excel Import, Statistics Analysis, Chart Creation, Search Engine의 4개 모듈로 이루어진 시스템을 설계하여 사용자가 원하는 형태의 통계 가공 기능을 제공하는 시스템을 구현하였다. 한방 통계 시스템은 사용자에게 필요한 통계를 검색하고 통계 정보를 획득하는데 많은 유연성을 제공할 것으로 기대된다.

• 한국식품영양학회지
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• 제22권2호
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• pp.261-271
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• 2009

Deep sea water exists at depths of over 200m under the sea. As no sunlight reaches it, photosynthesis does not take place within it, and it contains no organic matter. In addition, its temperature is maintained at a stable low level throughout the year, so it does not get mixed with the sea water on the surface. It contains a large amount of nutritious salts, whose cleanness is maintained. It is a marine resource that has matured for a long period of time. Research into deep sea water, which started in the 1970s, has been made around the whole world, including the USA and Japan. In Korea, research has been active in this area since 2000. As there has been a good amount of research into industrial applications for deep sea water, since 1993, patents for the relevant technologies have been applied. This paper intends to provide a resource to researchers of deep sea water, by summarizing of all domestic deep sea water-related patents applied with Korean Intellectual Property Office from 1993 to 2008. This research was conducted using a computer and KIPRIS Database owned by the Korea Institute of Patent Information. 'Deep sea water' was used as the search keyword. A total of 222 Korean patents relating to deep sea water have been registered on the basis of IPC. Of these, 126 patents relate to the manufacturing and the treatment of foods, foodstuffs, or non-alcoholic beverages(A23L), while 50 patents relate to the production for medical, dental, or cosmetic purposes(A61K). 38 patents relate to water purification, treatment of wastewater, sewage and sludge (C02F), while 8 patents relate to fishery and farming(A01K). In summary, it was found that studies for the practical use of deep sea water have been conducted in relation to the manufacturing and the treatment of foods, foodstuffs, beverages, and cosmetics.

• 정보처리학회논문지D
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• 제10D권3호
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• pp.531-540
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• 2003

에너지 사용의 급증으로 인해 환경오염, 지구 온난화 현상, 오일 파동의 문제가 발생되고 있다. 이를 해결하기 위해 태양 에너지, 풍력, 소수력 등과 같은 대체에너지에 대한 관심이 매우 높아지고 있다. 미국, 유럽, 일본에서는 대체에너지원의 정보를 체계적으로 관리하고 활용하기 위한 시스템 개발에 많은 노력을 하고 있다. 그러나 국내에서는 아직 대체에너지 정보 시스템이 효과적으로 구축되지 못하고 있다. 따라서 이 논문에서는 일사량 에너지 데이터를 저장 및 관리하는 대체에너지 정보 시스템을 제안한다. 이 시스템은 ArcView GIS를 이용하여 구현되었으며, 다양한 시공간 질의를 사용한 데이터 검색이 가능하도록 하였다. 아울러 사용자는 질의 결과를 챠트, 그래프, 등고선과 같은 형태로 확인할 수 있다. 구현된 시스템은 ArcIMS를 이용하여 인터넷 웹 서비스를 제공한다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권1호
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• pp.433-439
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• 2014

We attempted to develop an indicator combining incidence with mortality rates (single measure of cancer burden, SMCB) and to compare the magnitudes of cancer burden by world region. The SMCB was used to measure the size of cancer burden summarizing the incidence and mortality. The incidence and mortality were divided in equivalent forms and were split. The criteria dividing the size of cancer burden were used as the maximum incidence and mortality by men and women according to the world database, and the value corresponding to 10% of each maximum was set as the cut-off value. In SMCB, the size of cancer burden was highest for men with lung cancer (SMCB=18) and for women with breast cancer (SMCB=14) in MDR (more developed regions) compared to the size of burden in LDR (lower developed regions) (lung, SMCB=11, breast, SMCB=8). For men, the size of cancer burden by region was highest in EURO (SMCB=18, lung), followed by WPRO (SMCB=16, lung), PAHO (SMCB=14, prostate), AFRO (SMCB=8, prostate) and SEARO (SMCB=7, lung). Moreover, for women, the size of cancer burden was greatest in EURO (SMCB=14, breast), followed by PAHO (SMCB=13, breast), AFRO (SMCB=11, cervix uteri), EMRO (SMCB=9, breast) or SEARO (SMCB=8, cervix uteri) and WPRO (SMCB=7, lung). The summary indicator will help to provide a priority setting for reducing cancer burden in health policy.

• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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• pp.2893-2900
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• 2014

Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.