• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.181-189
• /
• 2022

The purpose of this study is to investigate the innovation of business model and the effectiveness of the data-driven model. the main concepts and policies related to the data economy are reviewed, and implications are drawn through the analysis of data-based convergence service creation cases. This study identified the existing data-driven business model of the creation of MyData service industry in the financial industry and concept of the data economy. According to the empirical analysis result, this study confirmed that t considering the mobile environment and consumer acceptance of data portability, the ripple effect of the implementation of My Data on the financial industry is expected to be significant.

• The Korean Journal of Archival Studies
• /
• no.55
• /
• pp.275-305
• /
• 2018

The advent of e-government following the information revolution has affected public records systems. Records management should now be changed into an environment for establishing a national records management system based on the Internet of things (IoT), cloud, big data, and mobile (ICBM), and it is time to make a fresh start toward a next-generation records management system that responds to changes in the environment. Ultimately, it is time for a records management system that ensures a proper way of dealing with new environmental changes. It has been nearly 20 years since the Public Records Management Act was enacted in 1999, and its complete amendment was made in 2006 so that electronic records could be efficiently managed. When recompliance management needs to be rechecked, a full redesign is required to enable the current legal system to respond to the new circumstances in the present day. Therefore, this study is intended to suggest ways to improve the new records management legal system as the environment changes over the next generation and lay the legal groundwork for innovation in the national records management system.

• Journal of Information Processing Systems
• /
• v.12 no.4
• /
• pp.711-723
• /
• 2016

With the rapid development of both ubiquitous computing and the mobile internet, big data technology is gradually penetrating into various applications, such as smart traffic, smart city, and smart medical. In particular, smart medical, which is one core part of a smart city, is changing the medical structure. Specifically, it is improving treatment planning for various diseases. Since multiple treatment plans generated from smart medical have their own unique treatment costs, pollution effects, side-effects for patients, and so on, determining a sustainable strategy for treatment planning is becoming very critical in smart medical. From the sustainable point of view, this paper first presents a three-dimensional evaluation model for representing the raw medical data and then proposes a sustainable strategy for treatment planning based on the representation model. Finally, a case study on treatment planning for the group of "computer autism" patients is then presented for demonstrating the feasibility and usability of the proposed strategy.

• Journal of Fashion Business
• /
• v.22 no.6
• /
• pp.70-82
• /
• 2018

In modern society, the means of sharing information has expanded from existing personal computers and mobile devices to a variety of smart devices rapidly increasing information production. Recently, curations have extended to online businesses. There has been wide use of curation services in the cosmetics curation market. In this study, focuses on factors which cosmetics curators have in mind. In relation to the impact of cosmetics curation quality properties on usability, the effects of the medium of satisfaction and confidence are to be verified. For this study, a survey of 378 women in their 20s and 40s who had experience with curations was done and the collected data were analyzed using SPSS 23.0 and AMOS 23.0 statistics programs. The results showed that information quality and personalization quality of cosmetics curation service were important factors affecting customer satisfaction. Personalization quality also had a positive effect on trust. System quality has a positive impact on trust and further influence on intention to use. This indicates that the trust on the curation service depends on the stability of system. However, design quality was found to have no significant effect on satisfaction and trust. In future, the research related to application and utilization of big data-based cosmetic curation will be further expanded.

• Fashion & Textile Research Journal
• /
• v.23 no.6
• /
• pp.790-798
• /
• 2021

With digital technology innovation, increased data access and mobile network use by consumers, products and services are changing toward pursuing differentiated values for personalization, and personalized markets are rapidly emerging in the fashion industry. This study aims to identify trends in digital customized automation technology by deriving types of digital customizing and analyzing cases by type, and to present directions for the development of digital customizing processes and the use of technology in the future. As a research method, a literature study for a theoretical background, a case study for classification and analysis of types was conducted. The results of the study are as follows. The types of digital customizing can be classified into three types: 'cooperative customization', 'selective composition and combination', 'transparent suggestion', and automation technologies shown in each type include 3D printing, 3D virtual clothing, robot mannequin, human automatic measurement program, AR-based fitting service, big data, and AI-based curation function. With the development of digital automation technology, the fashion industry environment is also changing from existing manufacturing-oriented to consumer-oriented, and the production process is rapidly changing with IT and artificial intelligence-based automation technology. The results of this study hope that digital customized automation technology will meet various needs of personalization and customization and present the future direction of digital fashion technology, where fashion brands will expand based on the spread of digital technology.

• Journal of Navigation and Port Research
• /
• v.46 no.5
• /
• pp.458-470
• /
• 2022

As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.

• International Journal of Advanced Culture Technology
• /
• v.11 no.2
• /
• pp.345-357
• /
• 2023

This research investigates the relationship between the information quality, service quality, and system quality of lodging apps and the users' expectations, level of satisfaction, and intent to continue using them. For this objective, 418 respondents participated in a survey. To evaluate the hypotheses, the collected data were examined using SPSS 22.0 and AMOS 22.0 statistical software. This study constructed a model using information quality, service quality, system quality, expectancy, satisfaction, and intention to continue using the pre- and post-use relationship of users of accommodation applications. The results of testing the hypotheses indicated that system quality had no significant effect on expectancy, system quality and service quality had no significant effect on satisfaction, and all other hypotheses had significant effects. The conclusion of this research is that the app's system quality, including access speed, access barriers, and privacy, does not satisfy pre- and post-use expectations. In addition, the system quality and service quality of the application have little effect on the app's satisfaction. The information quality of the application has a considerable impact on expectation confirmation and satisfaction, expectation confirmation has an impact on satisfaction, and expectation confirmation and satisfaction have an impact on intention to continue using.

• Ecology and Resilient Infrastructure
• /
• v.7 no.3
• /
• pp.171-180
• /
• 2020

With the increase in industrialization and urbanization, scarcity of space for leisure life has become an important issue. Opportunities such as natural scenery and ecological experiences provided by waterfront spaces around streams are fundamental factors in the development of the community and creation of a hydrophilic park. In the past, on-site surveys have been conducted using human resources to quantify the number of river visitors, but the accuracy of the results was not sufficient owing to limitations in expenses, manpower, space, and time. In this study, to overcome this problem, we estimated the number of visitors using the location information related to hydrophilic parks. The study areas were Samrak Ecological Park and Daejeo Ecological Park located downstream of the Nakdong River. We compared and analyzed the pattern of the visitors by using the large communication data and the visiting pattern based on GPS location information. The GPS location information is based on Google Popular Times and Kakao visitor data. When the GPS location data were used, the pattern for weekday and weekend visitors was clearer than when the large communication data were used. Therefore, it is expected to be similar to the result of GPS location information if the number of visitors is extracted under the condition of precision of pCELL size and residence time of 30 minutes or more when using future communication big data. In addition, if revisions such as the Personal Information Protection Act are made to extract more accurate data, by estimating the number of visitors based on GPS data, more accurate indicators of the number of visitors can be derived.

• International Journal of Computer Science & Network Security
• /
• v.22 no.6
• /
• pp.230-240
• /
• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.5
• /
• pp.605-612
• /
• 2019

Traditionally, travel demand forecasts have been conducted based on the data collected by a survey of individual travel behavior, and their limitations such as the accuracy of travel demand forecasts have been also raised. In recent, advancements in information and communication technologies are enabling new datasets in travel demand forecasting research. Such datasets include data from global positioning system (GPS) devices, data from mobile phone signalling, and data from call detail record (CDR), and they are used for reducing the errors in travel demand forecasts. Based on these background, the objective of this study is to assess the feasibility of CDR as a base data for travel demand forecasts. To perform this objective, CDR data collected for Daegu Metropolitan area for four days in April including weekdays and weekend days, 2017, were used. Based on these data, we analyzed the correlation between CDR and travel demand by travel survey data. The result showed that there exists the correlation and the correlation tends to be higher in discretionary trips such as non-home based business, non-home based shopping, and non-home based other trips.