• 패션비즈니스
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• 제10권1호
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• pp.148-163
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• 2006

The purpose of this study is to examine differences in university students' spatial behavior and time for purchasing weekdays or weekends according to trading areas they use to purchase casual wears. Theoretical background examined trading areas, in Busan, consumers' spatial behavior. An empirical research developed a questionnaire as a measuring tool to conduct a preliminary survey and a main survey. Data collection was implemented with 507 students from four universities in Busan; and for data analysis, descriptive statistics, cross-tabulation analysis, correspondence analysis, and McNemar test were carried out by using the SPSS for Windows 12.0K program. This study obtained the main results as follows: The characteristics of university students' spatial behavior according to trading areas show significant difference in reasons of trading area selection, time slots for visiting. University students who visited the Seomyeon trading area were found to consider comparison-based purchasing and prominence of the trading area, regardless of the time for purchasing weekdays or weekends. As for trading areas around Busan National University, visits were mainly due to accessibility. Students visited trading areas in Nampo-Gwangbok-dong regardless of the time for purchasing in diverse reasons of trading area selection, time slots. As for trading areas around Kyungsung University, students were visited due to accessibility.

• Journal of Information Processing Systems
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• 제9권1호
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.

• Nutrition Research and Practice
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• 제12권4호
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• pp.348-354
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• 2018

BACKGROUND/OBJECTIVES: Obesity is a serious concern worldwide, for which the restaurant industry holds partial responsibility. This study was conducted to estimate restaurant consumers' intention to select healthy menu items and to examine the relationships among behavioral beliefs, past behaviors, attitudes and behavioral intentions, which are known to be major determinants of consumer behaviors. SUBJECTS/METHODS: An online, self-administered survey was distributed for data collection. The study sample consisted of customers who reported having visited casual dining restaurants in the last three months at the time of the survey. Structural equation modeling was used to verify the fit of the proposed research model. RESULTS: Structural equation modeling revealed that the proposed model supports the sequential, mediated (indirect) relationships among behavioral beliefs, past behaviors, attitudes and behavioral intentions toward healthy menu selection. CONCLUSION: This study contributes to the available literature regarding obesity by adding past behaviors, one of the most influential variables involved in prediction of future behaviors of consumers, to the TPB model, enabling a better understanding of restaurant consumers' rational decision process regarding healthy menu choices. The results of this study provide practical implications for restaurant practitioners and government agencies regarding ways to promote healthy menus.

• 대한간호학회지
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• 제47권4호
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• pp.488-498
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• 2017

Purpose: The focus of the study was on the selection-optimization-compensation (SOC) strategy to predict successful aging mediated by dyspnea symptoms in older adults with chronic obstructive pulmonary disease. The model was constructed based on the hypotheses that coping strategy and social support of the elders predict successful aging through the SOC strategies. Methods: Participants were 218 outpatients with chronic obstructive pulmonary disease recruited for the study. Data collection was done from March 25 to September 11, 2015, and analyzed using SPSSWIN 22.0 and AMOS 21.0. Results: The hypothetical model appeared to be fit to the data. Seven of eight hypotheses selected for hypothetical model were statistically significant. The SOC strategy has only significant indirect effects through dyspnea symptoms on successful aging. Coping strategy, social support, SOC strategies and dyspnea symptoms explained 62% of variance in successful aging. Conclusion: The SOC strategies with social support and dyspnea symptoms significantly explained successful aging among patients with chronic obstructive pulmonary disease. Nursing strategies should be focused on social support and coping strategies to optimize SOC strategies so that older adults with chronic obstructive pulmonary disease are able to manage dyspnea symptoms and eventually achieve successful aging.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3120-3137
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• 2021

Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.218-218
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• 2022

Granules-bound starch synthase II (GBSSII), one of the isoforms of granule-bound starch synthase (GBSS), is responsible for amylose synthesis by expressing in non-storage tissues such as leaf, stem, root, and pericarp. Up to date, little is known about this gene functions and basic knowledge of heritable characteristics of this gene, GBSSII. We identified functional haplotypes and performed evolutionary analyses on the GBSSII using 374 rice accessions (320 Korean bred and 54 wild) based on the classified groups. A total of 14 haplotypes were found, and almost all haplotypes (13) were functional, carrying 19 non-synonymous SNPs in two exons (exons 1 and 2). The lowest nucleotide diversity was detected in Tropical japonica (0.00145), while the highest pi-value was in Aus (0.01081), illustrating the signal of this gene evolution. The highest Tajima's D value in Aus (1.6380) indicates GBSSII gene domestication signature under balancing selection, while the lowest Tajima's D value in Temperate japonica (-0.8243) highlights that they were under positive selection, which may be purified due to the excess of rare alleles. The highest genetic differentiation was observed between Tropical japonica and aroma (F_ST = 0.921928). In contrast, the highest interbreed level was detected in Aus-admixture (F_ST = -0.20157). The genetic relatedness between and or among the wild and cultivated subpopulations was revealed through PCA, population structure, and phylogenetic analyses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2658-2681
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• 2023

In edge computing scenarios, IoT end devices play a crucial role in relaying and forwarding data to significantly improve IoT network performance. However, traditional routing mechanisms are not applicable to this scenario due to differences in network size and environment. Therefore, it becomes crucial to establish an effective and reliable data transmission path to ensure secure communication between devices. In this paper, we propose a trusted path selection strategy that comprehensively considers multiple attributes, such as link stability and edge cooperation, and selects a stable and secure data transmission path based on the link life cycle, energy level, trust level, and authentication status. In addition, we propose the Stability-based On-demand Multipath Distance Vector (STAOMDV) protocol based on the Ad hoc AOMDV protocol. The STAOMDV protocol implements the collection and updating of link stability attributes during the route discovery and maintenance process. By integrating the STAOMDV protocol with the proposed path selection strategy, a dependable and efficient routing mechanism is established for IoT networks in edge computing scenarios. Simulation results validate that the proposed STAOMDV model achieves a balance in network energy consumption and extends the overall network lifespan.

• Journal of Radiation Protection and Research
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• 제20권1호
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• pp.8-15
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• 1995

환경방사능 분석기술은 원자력시설의 가동중 정상 및 비정상 상태시 이상판단과 지역특성에 따른 주변환경 방사능의 특성 및 거동파악 등을 하는데 필요한 기술로 원전 가동전, 후 환경방사능량을 비교함으로서 방사능 오염 및 변화상황을 파악할 수 있다. 국내에는 현재 관련법에 따라 규제기관 및 관련기관에 의해 환경감시가 계속되어오고 있으나 분석기술에 대한 한국규격이 없으므로 분석절차가 서로 상이하고 분석결과의 상대오차율이 커서 환경방사선 감시결과에 대한 신뢰성이 떨어지고 있다. 따라서 토양시료에 대한 감마핵종 분석에 한정하여 기수행된 측정방법 및 결과 둥을 비교분석하므로서 원전주변 환경방사능 감시목적에 적합한 분석기술의 신뢰도 향상 및 상대오차율 최소화 방안을 도출하였다

• 한국조리학회지
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• 제22권4호
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• pp.277-287
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• 2016

본 연구는 2016년 3월 1일부터 3월 30일에 이르는 약 30일간 조사기간을 두어 실시하였고, 자료 수집은 서울 시내 외식업소 10여 군데에 대해 이용하는 고객들을 대상으로 방문하는 고객에게 자기기입식으로 응답하게 하였다. 첫째, 외식산업의 마케팅 커뮤니케이션 활동이 소비자들의 고객 만족도에 영향을 분석하기 위해 회귀분석을 실시했다. 그 결과, 첫째, 광고는 B=0.107(p<.001), 편리는 B=0.093(p<.05), 사교는 B=0.294(p<.01), 홍보는 B=0.334(p<.001), 판매촉진은 B=0.542(p<001), 인적판매는 B=0.111(p<.01)로 하위 변수 모두 고객 만족도에 유의적인 정(+)의 영향력이 있었다. 둘째, 외식 마케팅 커뮤니케이션과 고객만족도간의 메뉴 선택속성에 관해 조절효과를 검증은 분석 결과, 인적판매는 유의적인 정(+)의 영향력이 있었고, 홍보는 부(-)의 영향력이 있었다. 그리고 광고, 판매촉진은 아무런 조절효과가 없었다.

• 산업융합연구
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• 제18권2호
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• pp.95-100
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• 2020

소비자를 파악하기 위해 활용되고 있는 사용자 중심 데이터 중 사용자 리뷰 데이터는 다량으로 상세하게 소비자의 의견을 파악할 수 있다는 장점으로 인해 주목받고 있으며 많은 소비자들이 사용자 리뷰에 의존하고 신뢰하고 있다. 많은 어플리케이션 개발사들은 중요성을 인지하고 사용자 리뷰를 관찰 및 대응하고 있지만 체계적인 방법의 부재로 고객의 만족과 관계없이 시간과 비용을 투자하고 있다. 따라서, 본 논문에서는 주어진 시간과 비용에서 고객의 만족을 최대화 시킬 수 있도록 고객 만족과 서비스 품질을 다루는 카노 모델을 이용하여 어플리케이션 마켓에서 사용자 리뷰들을 선별하는 체계적인 방법을 제안하였다. 본 방법은 어플리케이션 마켓에서 사용자 리뷰들을 수집하고 요구사항을 도출하는 사용자 리뷰 수집 및 요구사항 도출 단계, 도출된 요구사항에 카노 모델을 적용하고 품질 유형으로 선별하는 카노 모델 적용 및 선별 단계, 그리고 관련자들이 모여 내부적인 측면에서 요구사항 검토 및 재정의하는 이해관계자들과 검토 및 재정의 단계로 구성되었다.