• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.977-980
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• 2015

Beacons have been noted in the core of the recent things Internet. It is also the technology is spreading most rapidly among the things Internet-related communication technologies. Beacon is a data communications technology that provides information that is customized to know the user's location. Using the BLE technology, to grasp the position of such people and goods. In addition to the non-contact method, since it is possible to communicate within the maximum 70m, it has attracted the interest than the NFC. Beacon, guidance for the current coupon, you can use as an advertising platform, such as the provision of product information, it has also been used in the indoor positioning service. Therefore, in this paper, we introduce about whether Case Study beacon is utilized how in the Internet of Things, were analyzed. Beacon exit the smart phone, the date to be used in conjunction with a wearable device, such as Google glasses and smart watch was not far away. Future it is expected or beacons are used everywhere to be expanded.

• Journal of the Korean Geotechnical Society
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• v.34 no.5
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• pp.19-35
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• 2018

The necessity of predicting the spatial information of the site-specific seismic response, which is essential information for the comprehensive earthquake disaster countermeasures, is increasing for the mid-west urban areas where the earthquake-induced damages can be increased due to frequent occurrence of mid-scale earthquake such as 2016 Gyeongju Earthquake and 2017 Pohang Earthquake. Especially, researches on strategic securing of site survey datasets and understanding the site-specific site response characteristics were conducted for Gyeonggi-do, South Korea. In this study, a GIS-based framework for site-specific assessment of site response and induced vulnerable area in Gyeonggi-do, South Korea was proposed. Geo-Data based on GIS platform was constructed for regional estimation of geotechnical characteristics by collecting borehole and land coverage datasets. And the geo-spatial grid information was developed for deriving spatial distribution of geotechnical layer and site response parameters based on the optimization of the geostatistical interpolation method. Accordingly, base information for Improving earthquake preparedness measures was derived as seismic zonation map with administrative sub-units considering the quantitative site effect of Gyeonggi-do.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.1
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• pp.285-310
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• 2020

A significant number of studies have been conducted on user perceptions of archive and record contents for the National Archives of Korea (NAK) and local record centers in the field of archives and records management in Korea. Yet, there has not been such a research on the use of digital archive contents designed for contents creation. Accordingly, this study investigated user perceptions of the use of the contents on the Korea Creative Content Agency (KOCCA)'s Culturing archive designed for creation purposes. A survey was conducted, examining the user's degree of interests, the expected user preference of the use and the expected extent of help by the contents of the archive. For the analyses of the survey data, this study performed one-way ANOVA for the comparative analyses of the means related to the subjects' general characteristics and the perceptions, along with cross-tabulation analyses for the association among the same items and nominal variables related to perceptions. On the basis of these analyses, this study suggests the following: ① to supplement the contents of the archive; ② to design customized interfaces and to enhance the readability; ③ to reinforce site PRs for large portal sites and creators' groups.

• Journal of Korean Home Economics Education Association
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• v.29 no.3
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• pp.89-104
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• 2017

Considering the advent of the Fourth Industrial Revolution, this study examines the changes and influences of intelligent information technology and the role of consumer education in the context of consumption life. The purpose of this study is to provide a theoretical foundation to effectively respond to the future consumption society as an independent consumer by enhancing the understanding of the Fourth Industrial Revolution in terms of consumption life. First, in terms of changes in the consumption paradigm in the Fourth Industrial Revolution, production and consumption are converged by being shared through a comprehensive connection platform in real time. Regarding the meaning of consumption, mental experience is being emphasized; moreover, usage and sharing, rather than ownership, are being highlighted. In terms of major changes in consumption life, the emergence of a more convenient smart consumption life and the possibility of personalized consumption optimized for individual demand are anticipated. Moreover, sustainable eco-friendly consumption is expected to increase further, and rapidly changing consumption trends will experience accelerated progress in consumer-centered changes. Next, the predicted problems in consumption life in the Fourth Industrial Revolution include unequal consumption due to intelligent information technology power center and the use and management of personal information data. Furthermore, ethical concerns related to the introduction of new technologies will become prominent, eventually resulting in issues concerning consumption satisfaction. To effectively respond to these new paradigm changes, consumer education should be value-centered. Ethical aspects of consumption should be considered, and consumption life should include trust and mutual cooperation. Furthermore, consumer education should facilitate creative convergence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.520-527
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• 2019

In this study, the technical level and competence of Chungbuk region manufactures were diagnosed and implications for efficiency improvement of cooperation with local universities were derived. The results are as follow. First, in Chungbuk area, 75% of the skilled workers are medium-skilled and high skilled workers. And the life cycle of production products was found to have entered middle/old age. In addition, the industries were overestimating its technology capabilities, including marketing and sales technology, and management technology. Therefore, local universities should develop differentiated program such as technology transfer and commercialization support so that companies can nurture new industries and it is necessary to improve understanding of reality and future prediction ability through various education and seminars. Second, universities in Chungbuk province have failed to meet the practical demands of industry by providing general educational programs such as lifelong education curriculum, rather than the practical training required by industry. First of all, industries needed the practical training programs such as human resource empowerment, technical education and workers' retraining for local industry development. In addition, industries were expected to provide relevant knowledge and infrastructure such as testing, analysis, participation in technology development such as commissioning and joint research. Therefore, universities should prepare customized Industry-Academia Cooperation Programs through industry demand survey in planning. Also, it is necessary to establish various connection points with industry to ensure that industry-academia cooperation will continue and achieve results. Third, the technology of the industries in Chungbuk province was found to be very unrelated to the next generation regional strategic industries. This is not shared vision between industry and local government, Industry-Academia Cooperation Programs will serve as a platform to organize various community entities. Universities will be able to play a key role in between industries and local governments.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.123-138
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• 2022

In order to improve ScienceON as a customized portal for MZ generation, this study investigated the characteristics of MZ generation's use of information portals and the demand for ScienceON to derive ways to improve ScienceON. To this end, a survey was conducted on Generation MZ who had experience using ScienceON, and the direction of improvement of ScienceON was derived. The ScienceON improvement plan proposed in this study is as follows. First, it is necessary to derive a plan to be familiar with the MZ generation for the MZ generation seeking familiarity and convenience. Second, it is necessary to improve the portal, such as arranging intuitive menus and providing convenient information, and various ways such as improving design and UI and reorganizing functions provided by ScienceON are needed. Third, it is necessary to promote the spread of Science ON by providing content through various platforms such as SNS and YouTube. In the future, as interest in the MZ generation continues to increase, analysis studies on the characteristics and demand of the MZ generation are expected to increase. Therefore, this study can be used as basic data for research on MZ generation, and it is expected that it can be used as a reference for the demand for information search and services of MZ generation.

• Information Systems Review
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• v.23 no.3
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• pp.51-75
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• 2021

Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.11-21
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• 2024

This study explores the use of virtual reality (VR) technology to identify and label key segments of the golf swing. To address the limitations of existing VR devices, we developed a platform to collect kinematic data from various VR devices using the OpenVR SDK (Software Development Kit) and SteamVR, and developed a semi-automated labeling technique to identify and label temporal changes in kinematic behavior through LSTM (Long Short-Term Memory)-based time series data analysis. The experiment consisted of 80 participants, 20 from each of the following age groups: teenage, young-adult, middle-aged, and elderly, collecting data from five swings each to build a total of 400 kinematic datasets. The proposed technique achieved consistently high accuracy (≥0.94) and F1 Score (≥0.95) across all age groups for the seven main phases of the golf swing. This work aims to lay the groundwork for segmenting exercise data and precisely assessing athletic performance on a segment-by-segment basis, thereby providing personalized feedback to individual users during future education and training.

• Journal of Nutrition and Health
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• v.53 no.5
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• pp.547-561
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• 2020

Purpose: This study was conducted to segment the delivery food market and to develop customized products and services. Methods: This study analyzed 636 responses collected from customers who ordered delivery food. Statistical analyses were conducted using the SPSS program (ver. 25.0) for frequency analysis, χ²-test, one-way analysis of variance, factor analysis, and cluster analysis. Results: Four factors were extracted by exploratory factor analysis (safety-orientation, convenience-orientation, taste-orientation, and economy-orientation) to explain the consumers' food-related lifestyles. The results of cluster analysis indicated that the 'low-interest group', 'convenience and economy-oriented group', and 'gourmet and economy-oriented group' should be regarded as the target segments. Characteristic analysis of each cluster showed that lowinterest group had higher rates of married (67.1%) and living with family (85.4%) than other clusters. The convenience and the economy-oriented group had higher rates of living alone (28.9%) than others. The gourmet and the economy-oriented group had a higher percentage of unmarried (62.0%) than the others. In addition, the average age of convenience and economy-oriented group (32.3 years) and gourmet and economy-oriented group (32.5 years) were significantly lower than the safety seeker (40.0 years) (p < 0.001). Difference analysis of the consumption practice according to the cluster, revealed significant differences in the order frequency (p < 0.001), main day to order (p < 0.05), source of information about delivery food (p < 0.001), order method (p < 0.001), and co-consumer (p < 0.01). In addition, the convenience and the economy-oriented group had significantly higher overall satisfaction than the others (p < 0.001). Conclusion: These findings suggest that customer segmentation based on a food-related lifestyle can be used to build a successful marketing strategy. Therefore, restaurant managers and delivery platform operators should consider developing products and services according to the segmentation to maximize customer satisfaction.