• Journal of Fashion Business
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• v.10 no.1
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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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• v.9 no.1
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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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• v.12 no.4
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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.

• Journal of Korean Academy of Nursing
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• v.47 no.4
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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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• v.15 no.9
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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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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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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• v.17 no.10
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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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• v.20 no.1
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• pp.8-15
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• 1995

An estimate of a change in radioactivity's circumstances around the nuclear power plant is validated with the results of the radioactivity measurements are compared. In this study, to further enhance the reliability of the results obtained from the environmental radioactivity measurements and analysis around the nuclear power plants that have been carried out up to the present. In the korea standard, there is the technical analysis guide for general stable chemical element's, but there is not the technical analysis guide for the radionuclei. therefore the environmental sample collection, the pretreatment of the sample and radionuclide analysis in the sample, the result's of the environmental radioactivity measurements by each organization, etc. are different. It is not sufficient for the database to forecasting a change in radioactivity's circumstances. A comparative study of collection and pretreatment techniques for the soil sample, the results by comparison, the method of minimizing the relative error are proposed. At one side of sample collection, there are going to considered that the surroundings of sample collection like the lay of the land, the provision of the selection standard for the area and pathway of radionuclide adhesion, the coherence of sample collection, etc.. at another side of pretreatment of the sample and measurement in the case of soil sample, how to do homogeneously the soil particle size and the standard tools, i.e. kinds of meshes, must to be selected.

• Culinary science and hospitality research
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• v.22 no.4
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• pp.277-287
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• 2016

This research was conducted over four weeks from April 1, 2016 until April 30. Data collection was of responses from customers who a self-targeting customers who have visited more than 10 eating out establishments in downtown Seoul. First, a regression analysis was conducted to analyze the effect of activity of the food service industry marketing communications on customer satisfaction. First, advertising, B=0.107 (p<.001), convenient, B=0.093 (p<.05), social B=0.294 (p<.01), PR B=0.334 (p<.001), sales promotion B=0.542 (p<.001), personnel sales each had a significant positive influence (+) on customer satisfaction B=0.111 (p<.01). Secondly, menu selection catering property between marketing communications and customer satisfaction analysis of the impact of human Sales were significantly positive (+) Publicity Department had the effect of (-). In addition, advertising and sales promotion did not have any moderating effect.

• Journal of Industrial Convergence
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• v.18 no.2
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• pp.95-100
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• 2020

Among the customer-oriented data used to comprehend the customer, the user review data has received much attention as it provides insights into customer opinion in a detailed and large-scale manner; many customers have come to rely upon and trust the user reviews. Many application developers are cognizant of the importance of user reviews, so they monitor and respond to these reviews. However, due to the absence of a systematic method, developers have been investing their time and money without clear correlation to the customer satisfaction. Therefore, this paper suggests a systematic method to select user reviews from the application market using the Kano Model that deals with customer satisfaction and service quality, thereby maximizing the customer satisfaction under the given time period and budget. This method is constructed in the following phases: the user review collection and requirement elicitation phase in which the developers collect user reviews from the application market and elicit requirements, the Kano Model application and selection phase in which the Kano Model is applied to the elicited requirements and selection occurs based on the quality type, and the stakeholder review and redefinition phase in which relevant personnel gather to review and redefine requirements from an internal perspective.