• Journal of the Korean Society for information Management
• /
• v.38 no.4
• /
• pp.199-230
• /
• 2021

This study is to present an analysis and activation plan for the effect of reuse of research data through investigation of researchers and reuse data on reuse of research data. To this end, 178 copies were analyzed based on the distribution and collection of surveys targeting academic researchers in the field of social science in Korea who have experience in calculating new research results by reusing research data. As a result, 1) Most researchers acquire reuse data through systems such as data repositories, data management systems, and research data DBs, and mainly reuse analysis data produced through experiments and observations. In addition, despite being a researcher who successfully reused research data, the awareness of research data sharing was low and did not share it in the face of various problems. 2) The reliability and validity of 10 factors derived through literature review and factor analysis (academic usefulness, research efficiency, researcher concerns, data vulnerability, direct effort, indirect effort, suitability for reuse, data completeness, data usefulness, and social conditions) were verified. 3) As a result of correlation analysis, research efficiency, social conditions showed a quantitative correlation with research data reuse intention, researcher concerns, data vulnerability, and direct effort showed a negative correlation with research data reuse intention. As a result of regression analysis, all of these factors had a significant effect on the intention to reuse research data, and in the order of research efficiency, social conditions, direct efforts, researchers' concerns, and data vulnerability. Based on this, a plan to revitalize the reuse of research data was proposed.

• Journal of Intelligence and Information Systems
• /
• v.3 no.2
• /
• pp.33-55
• /
• 1997

A data model is a diagram that describes the properties of different categories of data and the associations among them within a business or information system. In spite of its importance and usefulness, data modeling activity requires not only a lot of time and effort but also extensive experience and expertise. The data models for similar business areas are analogous to one another. Therefore, it is reasonable to reuse the already-developed data models if the target business area is similar to what we have already analyzed before. In this research, we develop a case-based reasoning system for data model reuse, which we shall call CB-DM Reuser (Case-Based Data Model Reuser). CB-DM Reuse consists of four subsystems : the graphic user interface to interact with end user, the data model management system to build new data model, the case base to store the past data models, and the knowledge base to store data modeling and data model reusing knowledge. We present the functionality of CB-DM Reuser and show how it works on real-life a, pp.ication.

• Journal of Korea Multimedia Society
• /
• v.16 no.6
• /
• pp.735-745
• /
• 2013

The emergence of Web 2.0 technologies, such as blogs and wiki, enable even naive users to easily create and share content on the Web using freely available content sharing tools. Wide availability of almost free data and promiscuous sharing of content through social networking platforms created a content borrowing phenomenon, where the same content appears (in many cases in the form of extensive quotations) in different outlets. An immediate side effect of this phenomenon is that identifying which content is re-used by whom is becoming a critical tool in social network analysis, including expert identification and analysis of information flow. Internet-scale reuse detection, however, poses extremely challenging scalability issues: considering the large size of user created data on the web, it is essential that the techniques developed for content-reuse detection should be fast and scalable. Thus, in this paper, we propose a $qSign_{lsh}$ algorithm, a mechanism for identifying multi-sentence content reuse among documents by efficiently combining sentence-level evidences. The experiment results show that $qSign_{lsh}$ significantly improves the reuse detection speed and provides high recall.

• Journal of the Korea Furniture Society
• /
• v.20 no.1
• /
• pp.31-41
• /
• 2009

In our country, most of the wood resources are imported. We faced a continuous rising of wood price by export country's some conditions and excess rising of transport charge, also a shortage of structural size members. In these situation, recycling or reuse of wood residues and wastes under wood processing industry, building construction and demolition is not a option but a prerequisite. In our country, there is a dearth of data on recycling or reuse of wood residues and wastes, so the investigation on the necessity of recycling or reuse of wood residues and wastes was conducted by using the foreign data and documents. First of all, fields and actual conditions for the domestic wood processing industry were surveyed. Then, kinds and signification of wood residues and wastes were organized. Later, the necessity and the signification of recycling or reuse of wood residues were investigated, and postulations for effective recycling and reuse were suggested. Above all, the necessity of grading standards for reuse or recycling and some important consideration for developing grading standards were emphasized. At last, foreign research tendencies and some applications on recycling or reuse of wood residues and wastes were supplemented.

• Journal of the Korean Society for information Management
• /
• v.37 no.4
• /
• pp.1-26
• /
• 2020

In today's increasingly data-intensive academic environment, data is becoming the foundation of academic communication as a research outcome rather than a research by-product. However, there is a limit to guaranteeing actual data reuse only by expanding the data supply or securing accessibility. In order to overcome this, it is necessary to understand the data reuse behavior and data needs in-depth. Therefore, this study attempted to identify the major data reuse behavior and data needs among researchers. To this end, the authors of KCI papers among the data reuse documents of the Korea Social Science Data Archive (KOSSDA) for the past 3 years were targeted. An in-depth interview was conducted with 12 researchers who accepted the interview. As a result, factors considered when reusing data were personal, economic, technical, and social aspects, and it was found that the data itself was used or contextual information of the data was used depending on the purpose of data reuse. The path to acquiring data is a web-based source of information, and a path through informal communication can also be found. In terms of the data needs, it was found that they prefer English, the United States, and institutional producers. Also they have a clear preference for quantitative data from an interviewer-filled interpersonal interview survey method, rich metadata along with raw data, and data that contains identification information. However, due to the lack of confidence in the value, it is negative for the use of data with controlled access and use, and it is difficult to confirm a clear preference because there is no similar data available for selection in terms of size and freshness.

• Journal of Distribution Science
• /
• v.15 no.4
• /
• pp.59-67
• /
• 2017

Purpose - This study's aims are to examine the effects of airline service quality on brand image, brand attitude and reuse intention and the mediating roles of brand image and brand attitude in the relationship between airline service quality and reuse intention. Research design, data and methodology - A total of 500 questionnaire copies were distributed and 474 were used for the empirical study after excluding some empirical inappropriate or unusable ones. To analyze the collected data, the SPSS/WIN 22.0 statistical package was used. Results - The result of analysis showed that all the intangible, tangible and human elements of the airline service quality positively influenced on brand image and brand attitude and did not directly influence on reuse intention. However, brand image and brand attitude played mediating roles in the relationship between all the service quality elements and reuse intention. Conclusions - This means that airlines need to develop service quality, which is differentiated and provides special feelings for customers and work out improvement strategies for positive brand images and attitudes, since customers choose and reuse airlines, based on brand images and attitudes, which are perceived and formed through the experience of airline service quality and word of mouth.

• Journal of IKEEE
• /
• v.25 no.4
• /
• pp.664-671
• /
• 2021

This paper proposes a GPGPU structure that can reduce the number of operations and memory access by effectively applying a data reuse method to a convolutional neural network(CNN). Convolution is a two-dimensional operation using kernel and input data, and the operation is performed by sliding the kernel. In this case, a reuse method using an internal register is proposed instead of loading kernel from a cache memory until the convolution operation is completed. The serial operation method was applied to the convolution to increase the effect of data reuse by using the principle of GPGPU in which instructions are executed by the SIMT method. In this paper, for register-based data reuse, the kernel was fixed at 4×4 and GPGPU was designed considering the warp size and register bank to effectively support it. To verify the performance of the designed GPGPU on the CNN, we implemented it as an FPGA and then ran LeNet and measured the performance on AlexNet by comparison using TensorFlow. As a result of the measurement, 1-iteration learning speed based on AlexNet is 0.468sec and the inference speed is 0.135sec.

• International Journal of Contents
• /
• v.18 no.2
• /
• pp.81-93
• /
• 2022

The purpose of this study was to identify the structural causation between the service quality of lifelong education, city brand equity, and intention to reuse. For this study, the case of lifelong education in Osan, wherein local governments are leading efforts to promote lifelong education, was selected as the subject. A structured offline survey as well as an online survey were conducted to collect data from citizens of Osan who participated in lifelong education at least once. The results show that lifelong education service quality and city brand equity have a significant positive impact on intention to reuse, and that service quality has a significant positive impact on intention to reuse through city brand equity. The significance of this study lies in the revelation of the mediating impact of city brand equity, in the relationship between the service quality of lifelong education and individuals' intention to reuse lifelong education. This study also contributes establishing lifelong education service policies to increase the intention to reuse lifelong education.

• Journal of IKEEE
• /
• v.25 no.1
• /
• pp.229-233
• /
• 2021

NPU in an embedded environment performs deep learning algorithms with few hardware resources. By using a technique that reuses data, deep learning algorithms can be efficiently computed with fewer resources. In previous studies, data is reused using a shifter in ScratchPad for data reuse. However, as the ScratchPad's bandwidth increases, the shifter also consumes a lot of resources. Therefore, we present a data reuse technique using the Buffer Round Robin method. By using the Buffer Round Robin method presented in this paper, the chip area could be reduced by about 4.7% compared to the conventional method.

• Journal of Information Technology Applications and Management
• /
• v.17 no.2
• /
• pp.71-90
• /
• 2010

Electronic learning(or e-learning) has created hype for companies, universities, and other educational institutions. It has led to the phenomenal growth in the use of web-based learning and experimentation with multimedia, video conferencing, and internet-based technologies. Many researchers are interested in the factors that affect to the performance of e-learning or e-learning services. In this sense, this study is aimed at proposing e-learning system reuse prediction models in which e-learner intention to reuse influence factors(i.e., system accessibility, system stability, information clarity, information validity, self-regulated efficacy, computer self-efficacy, perceived usefulness, perceived ease of use, flow, and parental expectation) affect e-learner intention to reuse positively. A web survey was conducted for the full members of the e-learning education institute A in Seoul, Republic of Korea, an exclusive e-learning company that provides real time video lectures via the desktop conferencing system. The web survey was conducted for 20 days from November 5, 2009, through the e-learning web site of the company A. In this study, three data mining techniques were used : the multivariate discriminant analysis, CART, and C5.0 algorithm. This study was conducted to provide the e-learning service providers, e-learning operators, and contents developers with marketing and management strategies for improving the e-learning service companies, based on the data mining analysis results.