• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.20 no.3
• /
• pp.129-147
• /
• 2009

The ultimate goal of classification systems is to provide tools for information management and services through collocation of information objects in similar topics. The National Research Council for Economics, Humanities, and Social Sciences(NRCS) aims to organize the research products from 23 research institutes. To manage and organize the research products effectively, the standard classification system has been developed in conjunction of users' survey and the Business Reference Model(BRM). Although the standard classification system consists of users' perspectives and the aspects of organizational functions, there are limits to apply the system into classification practices. In this study, the proposed hybrid approach is to combine a clustering approach with 1,884 keywords from the titles of research products between 2007 and 2008. The clustering approach is performed in a heuristic way according to the KDC due to the lack of digital full texts of research products. The results of this study proposed a revised standard classification system for NRCS with 16 headings and 90 sub-headings. The revised standard classification system will play an important role in managing research products effectively.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.3D
• /
• pp.355-362
• /
• 2008

Fast track completion of urgent typhoon damage recovery construction project is becoming crucial for the prevention of the secondary damage from the next year typhoon, prompt psychological stabilization of flood sufferers, the early recovery of damaged infrastructure condition and so forth. As the recovery learning process has been continued for last consecutive typhoons and experts suggested, the keys in attaining the goals of the project (preventative, sustainable, cleaner and fast tracking development) are found to be the early contracting and improved competencies in project management especially during the design phase. It can be presumed that the former is attainable through administrative supports in the form of government guidelines, but the latter necessitates more research efforts. In this regards, this study aims to find a way how to lift up the current level of project management capability facing ever changing project mangement environment of urgent typhoon recovery project. By comparing the current level of application of government guidelines in flooded districts and analyzing the time required for each phase from design contracting to construction starting, several reformative ideas are illustrated in association with the necessity of adopting CM method in the deign phase. It is highly expected that CM application in the design phase can be an effective alternative in overcoming current limits in improving the quality of the project and prevent the delay due to the lack of expertise and professional workers in the owner side.

• The Journal of the Korea Contents Association
• /
• v.22 no.8
• /
• pp.660-670
• /
• 2022

This study was analyzed by applying AMSTAR-2, a methodological quality evaluation tool, to evaluate the quality of domestic meta-analysis papers on rehabilitation interventions for stroke patients. The purpose of this study is to provide guidelines for qualitative improvement of evidence-based practice and meta-analysis research by analyzing the qualitative level of the analyzed research. The literature search was conducted using the Research Information Sharing Service, Korean Medical database, and Korean studies Information Service System. Two authors searched, extracted, and reviewed literature using the keywords 'stroke' and 'meta-analysis'. As a result of the AMSTAR-2 quality evaluation of the final 18 studies, 3 studies (16.67%) were 'Moderate', 8 studies (44.44%) were 'Low', and 7 studies (38.89%) were 'Critically Low'. In future research, scientific and objective data selection and extraction process should be performed. It is expected that interest and efforts to improve the quality of meta-analysis research will continue by referring to the contents analyzed in this study as a way to improve the quality of literature.

• Korean Journal of Social Welfare Studies
• /
• v.42 no.4
• /
• pp.35-59
• /
• 2011

As the long term care insurance for the elderly has been established for 3 years it was noticed that the success of the policy is depending on the care workers. This study is to analyze and evaluate what are the characteristics and factors influencing their job satisfaction. The questionnaire survey was conducted over 291 care workers who are employed at 61nursing home for the elderlyin Jeollanamdo. The survey result is as following. Firstly, 93.5% of workers were female, 78% of them were over 40-50 years old, and 68.7% of them werelower than a high school graduate as their academic background. Secondly, 63.2% were contract-based or temporary employees, 53.3% had a work-related education less than 5 times for the past year, and 79.7% had an annual salary lower than KRW 20 million. Thirdly, the overall job satisfaction was 3.19 on the Likert scale of 5. Also, the job satisfaction was higher for the care workers working and getting paid by home than by company, for full-time workers than temporary workers. In addition, it was found that the more workers have work-related education and the higher their annual salary is, the higher their job satisfaction is. The study evaluated the factor influencing on their job satisfaction and suggested the way to improve it based on the survey analysis.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.41-48
• /
• 2023

In this paper, we propose an analysis of recent trends in the NFT (Non-Fungible Token) industry using topic modeling techniques, focusing on their universal application across various industrial fields. For this study, patent data was utilized to understand industry trends. We collected data on 371 domestic and 454 international NFT-related patents registered in the patent information search service KIPRIS from 2017, when the first NFT standard was introduced, to October 2023. In the preprocessing stage, stopwords and lemmas were removed, and only noun words were extracted. For the analysis, the top 50 words by frequency were listed, and their corresponding TF-IDF values were examined to derive key keywords of the industry trends. Next, Using the LDA algorithm, we identified four major latent topics within the patent data, both domestically and internationally. We analyzed these topics and presented our findings on NFT industry trends, underpinned by real-world industry cases. While previous review presented trends from an academic perspective using paper data, this study is significant as it provides practical trend information based on data rooted in field practice. It is expected to be a useful reference for professionals in the NFT industry for understanding market conditions and generating new items.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.12
• /
• pp.363-370
• /
• 2023

Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.2
• /
• pp.67-79
• /
• 2023

The bounce rate is the rate at which a user leaves immediately after visiting, and this study aimed to find out what attributes of a website affect the bounce rate. Web site evaluation items were defined as a total of 4 items and 27 evaluation attributes, including usability, information, service interaction, and technology, so that they can be commonly applied to venture companies in various industries through prior research. As a result of the study, 6 website attributes that affect the bounce rate were verified to be significant by discriminant analysis and decision tree analysis. Suggestions to reduce the bounce rate of venture business websites through this study are as follows. First, the path name of the website is displayed as mandatory and a pull-down menu function is added to facilitate movement to other pages. Second, it is good to expose core content that can attract users' attention in the form of a banner, and place internal link banners in the right place on sub-pages. Third, external links should be linked to a new window so that they do not leave the current page immediately so that they can be re-entered. Lastly, it is recommended to expose the contact information of the person in charge and consultation function as direct information for communication with customers, but if individual response is difficult, at least the consultation function must be added. These suggestions are expected to be of practical help in various fields such as website development, operation, and marketing. However, in special cases, a high bounce rate may be normal, so it should be considered according to the situation.

• Convergence Security Journal
• /
• v.24 no.2
• /
• pp.89-104
• /
• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Information Systems Review
• /
• v.21 no.4
• /
• pp.125-141
• /
• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.891-899
• /
• 2024

The Fourth Industrial Revolution is centered on a personalized demand fulfillment economy and is all about transformation and flexible processing that can deliver what customers want in real time across space and time. This paper implements the construction and operation of a packaging platform that can instantly procure the required packaging products based on real-time orders and evaluates its performance. The components of customer satisfaction are flexible and dependent on the situation which requires efficient management of enterprise operational processes based on an e-SCM platform. An OMS optimized for these conditions plays an important role in maximizing and differentiating the efficiency of a company's operations and improving its cost advantage. OMS is a system of mass customization that provides efficient MOT(Moment of Truth) logistics services to meet the eco-friendly issues of many individual customers and achieve optimized logistics operation goals to enhance repurchase intentions and sustainable business. OMS precisely analyzes the collected data to support information and decision-making related to efficiency, productivity, cost and provide accurate reports. It uses data visualization tools to express data visually and suggests directions for improvement of the operational process through statistics and prediction analysis.