• 한국의류산업학회지
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• 제15권3호
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• pp.381-392
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• 2013

This study analyzed the effects of internet fashion consumer characteristics and shopping motivation on price sensitivity as well as the effect of price sensitivity on negative purchasing behavior. A survey was conducted from August 10 to September 20 in 2012 and 364 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. The characteristics of internet fashion consumers were composed of innovation tendency, impulse buying tendency, information orientation, and variety seeking tendency. Shopping motivation was composed of convenient motivation, social motivation, hedonic motivation, product motivation, and economic motivation. The information orientation and variety seeking tendency of internet fashion consumers influenced the price search. The innovation tendency, impulse buying tendency, and variety seeking tendency of internet fashion consumers influenced the price importance. Convenient motivation, hedonic motivation, and product motivation positively affected the price search; however, social motivation negatively affected the price search. The social motivation, hedonic motivation, and economic motivation of internet fashion consumers positively affected price importance. Price search and price importance influenced the purchasing delay; in addition, price search influenced the switching intention. The results of this study provide useful information for customer management and internet shopping mall marketing strategies.

• 디지털콘텐츠학회 논문지
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• 제19권2호
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• pp.301-307
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• 2018

일반적으로 검색엔진은 이용자가 검색하고자 하는 내용의 정보를 제공하는 사이트를 우선 탐색할 수 있도록 검색결과의 주요내용을 요약하여 이용자에게 제공하고 있다. 본 연구에서는 이용자의 검색 결과 클릭이 검색 엔진에서 제공하는 요약 내용 기반으로 진행되는 것인지 검색결과 배치 순서에 기인한 것인지를 검색 결과 역배열 제시를 통한 실증 연구 결과를 제시하였다. 검색엔진 업체에서 제공하는 API를 활용하여 검색결과를 정배열과 역배열로 제시해 주는 검색사이트를 제작하여 각 이용자들의 검색결과에 대한 클릭 행동을 실제 클릭 순서와 클릭 위치, 클릭 수, 검색결과 내에서의 페이지 간 이동경로 등과 같은 이용자 검색 유형을 분석하였다. 분석 결과 대부분의 이용자들은 검색결과 정배열 또는 역배열 제시와 상관없이 첫 번째와 두 번째 노출된 검색 결과를 우선 클릭하는 이용자가 60% 이상 차지하였다. 이는 검색 결과 요약 내용과 상관없이 검색 결과 배치 순서에 따라 이용자의 정보탐색 우선순위가 결정되는 것으로 확인되었다.

• 전기학회논문지
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• 제58권7호
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• pp.1255-1262
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• 2009

The present study explained the phenomenon that low frequency oscillation is synchronized with discrete data obtained from a wide area system, and a sync search method. When a disturbance occurs in an power system, various controllers operate in order to maintain synchronization. If the system's damping is poor, low frequency oscillations continue for a long time and the oscillations are synchronized with one another at specific frequency. The present study estimated dominant modes, magnitude and phase of signals by applying parameter estimation methods to discrete signals obtained from an power system, and performed sync search among wide area signals by comparing the estimated data. Sync search was performed by selecting those with the same frequency and damping constant from dominant oscillation modes included in a large number of signals, and comparing their magnitude and phase. In addition, we defined sync indexes in order to indicate the degree of sync between areas in a wide area system. Furthermore, we proposed a wide area sync search method by normalizing mode magnitude in discrete data obtained from critical generator of the wide area. By applying the sync search method and sync indexes proposed in this study to two area systems, we demonstrated that sync scanning can be performed for discrete signals obtained from power systems.

• Bioinformatics and Biosystems
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• 제2권2호
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• pp.46-51
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• 2007

In the proteomics research using mass spectrometry, the protein database search gives the protein information from the peptide sequences that show the best match with the tandem mass spectra. The protein sequence database has been a powerful knowledgebase for this protein identification. However, as we accumulate the protein sequence information in the database, the database size gets to be huge. Now it becomes hard to consider all the protein sequences in the database search because it consumes much computing time. For the high-throughput analysis of the proteome, usually we have used the non-redundant refined database such as IPI human database of European Bioinformatics Institute. While the non-redundant database can supply the search result in high speed, it misses the variation of the protein sequences. In this study, we have concerned the proteomics data in the point of protein similarities and used the network analysis tool to build a new analysis method. This method will be able to save the computing time for the database search and keep the sequence variation to catch the modified peptides.

• Mass Spectrometry Letters
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• 제5권1호
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• pp.16-23
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• 2014

Liquid chromatography based mass spectrometry (LC-MS) is a key technology for analyzing highly complex and dynamic proteome samples. With highly accurate and sensitive LC-MS analysis of complex proteome samples, efficient data processing is another critical issue to obtain more information from LC-MS data. A typical proteomic data processing starts with protein database search engine which assigns peptide sequences to MS/MS spectra and finds proteins. Although several search engines, such as SEQUEST and MASCOT, have been widely used, there is no unique standard way to interpret MS/MS spectra of peptides. Each search engine has pros and cons depending on types of mass spectrometers and physicochemical properties of peptides. In this study, we describe a novel data process pipeline which identifies more peptides and proteins by correcting precursor ion mass numbers and unifying multi search engines results. The pipeline utilizes two open-source software, iPE-MMR for mass number correction, and iProphet to combine several search results. The integrated pipeline identified 25% more proteins in mouse epididymal adipose tissue compared with the conventional method. Also the pipeline was validated using control and colitis induced colon tissue. The results of the present study shows that the integrated pipeline can efficiently identify increased number of proteins compared to the conventional method which can be a breakthrough in identification of a potential biomarker candidate.

• 정보처리학회 논문지
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• 제13권7호
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• pp.311-318
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• 2024

인공지능과 인터넷의 발전으로 인한 데이터의 증가로 데이터 관리의 중요성이 부각되고 있는 상황에서, 데이터 검색과 메모리 공간의 효율적 활용이 매우 중요한 시대가 도래하였다. 본 연구에서는 메타데이터를 기반으로 데이터 구조를 분석하여 검색 속도와 메모리 효율을 최적화하는 방안을 연구한다. 연구방법으로는 사진 이미지의 메타데이터를 활용하여 배열, 연결리스트, 딕셔너리, 이진 트리, 그래프의 데이터 구조에 대한 성능을 시간적, 공간적 복잡도를 중심으로 비교하고 분석하였다. 실험을 통해 대규모의 이미지 데이터를 다루는 상황에서 딕셔너리 구조는 수집속도에서, 그래프 구조는 검색 속도에서 가장 우수한 성능을 보여주는 것을 확인할 수 있었다. 본 논문의 결과는 이미지 데이터 검색 속도와 메모리 효율을 최적화하기 위한 데이터 구조를 선택하는데 실용적인 가이드라인을 제시할 것으로 기대한다.

• 한국수자원학회논문집
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• 제39권10호
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• pp.855-866
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• 2006

본 연구에서는 유역 수문자료를 효율적으로 관리할 수 있는 수문자료관리시스템(HDMS)을 개발하였으며 경기도 화성시에 위치한 발안시험유역을 대상으로 시스템의 적용성을 보여주었다. MySQL 5.0을 사용하여 관계형 데이테베이스를 설계하였으며, MS-Visual Basic 6.0을 이용하여 윈도우 기반의 시스템을 개발하였다. HDMS는 자료검색시스템, 자료관리시스템, 자료분석시스템으로 구성되었다. 자료검색시스템과 자료관리시스템은 자료검색, 자료저장, 자료갱신, 자료추출의 기능을 제공하며, 자료분석시스템은 저장된 자료로부터 다양한 수문통계정보를 제공하며, 자료의 정확성 및 품질을 분석하고 평가한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2840-2861
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• 2020

The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.

• 방송공학회논문지
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• 제26권4호
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• pp.390-397
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• 2021

디지털 트윈 기술을 다양한 산업 분야에 응용함에 따라 대용량 데이터를 효과적으로 처리하기 위한 기술들이 필요하다. 본 논문에서는 지하 공동구 관리를 위한 대용량 데이터를 고속 검색하고 효과적인 전달을 위한 맞춤형 서비스 방안에 대해 논한다. 제안하는 방안은 크게 두 가지로 방대한 데이터를 효율적으로 검색하고 축약해서 보여주기 위한 고속 검색 데이터 생성 방법과 맞춤형 정보 서비스 분할 방법에 대해 제안한다. 고속 검색 데이터 생성에서는 지하 공동구 내 센서들에 의해 수집되는 시계열 분석을 위한 동기화 과정에 대해 구성과 데이터 축약에 따른 부가정보 방안에 대해서 논한다. 사용자 맞춤형 서비스 방법에서는 평상시와 재난 시의 사용자 유형을 정의하고 그에 따른 서비스하는 방법에 대해 논한다. 본 연구를 통해 재난 상황에서 대용량 데이터를 효과적으로 검색하고 서비스 받을 수 있는 지하 공동구 관리를 위한 데이터 생성과 서비스 모델에 대한 체계성을 갖출 수 있을 것으로 예상된다.

• 한국의류산업학회지
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• 제12권6호
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• pp.745-754
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• 2010

This study is to find return factors when modern consumers purchase goods from an internet shopping mall and then to analyze the characteristics of complaints act and information search behavior. Subjects of research are 245 men and women, who have experience with more than one return in internet fashion shopping mall, in their twenties. The data were analyzed by using Factor analysis, Cronbach's analysis, one-way ANOVA, Duncan test as a post identification, Pearson's correlation analysis and multiple regression analysis. The results of this study are that male and female consumers in their 20s are mainly aware of the return factors: impulse buying, product status, deliver service, service after purchase, hype and comfortableness. And complains behavior often conduct public action, private action, nonaction. Information search behaviors for risk reduction when they purchase are product comparison, oral information search, neutral marketing information search, and service information search. The return factor from the internet fashion shopping had the greatest impact on public action and deliver services factor was a big complaint. In addition, impulse buying & Hype affect private action and non-action is influenced by impulse purchase. The consumer types by the return factors in internet fashion shopping mall are classified into the return group by deliver service, the return group by complex factors, and the return group by product status. Furthermore, there are significant differences in complaining behavior among these groups. In the information search behavior for reduction of risk factors, the return group by complex factors did more active information search behavior than the other groups. The return group by deliver service searched oral information and the return group by product status explored the neutral marketing information.