• The Journal of Korean society of community based occupational therapy
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• v.10 no.3
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• pp.1-13
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• 2020

Objective : The purpose of this study is to present an analysis model in developing an inclusive response for safety hazards and disaster preventive information system for vulnerable people to the disaster including persons with disabilities, and those with specific needs. Methods : In this study, the persona analysis method is used to analyze fictitious characters that correspond to various characteristics such as age, disability, environment, occupation, etc. in terms of the scenario of some particular disaster subjects. Based on the user's communication problems derived from the persona analysis, focused group interview and ICF based analysis were implemented to identify needs and arbitration methods. Results : The needs from persona analysis and ICF-based communication items analysis identifies the factors that make each fictitious character difficult in terms of communication in obtaining the benefits consistent with the purpose of the service. The study derives service requirements that can provide arbitration or facilitation methods to increase communication ability of the users. Conclusion : Through the persona analysis method, difficulties that could occur when receiving disaster information using communication devices were identified and analyzed in conjunction with communication problems described in the ICF. In building information services for the prevention of safety hazards and disasters, this study presented a model that uses the persona analysis method and the ICF classification system to derive user requirements for accessible information system.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.135-142
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• 2020

In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.146-160
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• 2020

In the 4th industrial revolution, research on solving urban problems using ICT technology is emerging. Representatively, research is being conducted mainly focusing on smart cities. 3D geo-spatial. Various case studies on smart cities are being conducted to solve urban problems, and in order to effectively implement smart cities, it is implemented on the basis of a digital twin interconnecting physical and virtual environments. To implement a digital twin, the concept of space is essential, and spatial information that composes the real world is also essential. Therefore, in order to implement the digital twin, this study conducted a study on the construction and modeling of 3D geo-spatial information based on the national spatial information establishment regulations and the international standard CityGML for buildings, water facilities, and transportation facilities in Jeonju. In Jeonju, the research area, the LOD was defined, and the possibility of digital twin based on geo-spatial information was determined through data collection, analysis, and construction for each detail. In this study, it is meaningful that a plan to construct geo-spatial information for the implementation of a digital twin is presented, and the result of the construction is modeled as an urban standard model. The results of study are expected to be used as reference for detailed construction plans and standard establishment by governments and local governments promoting smart city and digital twin construction in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.340-347
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• 2016

Since the 1970s, manufacturing has been one of the key driving forces that has led to Korea's economic growth. However, this growth rate has been reduced significantly since the 2000s, and shows that revenues and employment are steadily decreasing. In addition, while manufacturing investment in Korea has dropped sharply, the United States, Germany, Japan, and other major countries have increased investment in manufacturing. These countries have promoted manufacturing innovation strategies that include the convergence of information and communications technologies (ICT) and manufacturing. For manufacturing innovation, it is important for time and cost savings required for product development to be achieved by changes in the production process, especially product design. Modeling and simulation (M&S) is a process that replaces physical product design, mockup making, and testing, with virtual product creation (modeling) and engineering analysis (simulation). In this paper, we analyze the economic ripple effect of supercomputing M&S using an input-output model technique based on the input-output tables published by the Bank of Korea. When we set the M&S budget (about US$16 million for the last 10 years) of the Korea Institute of Science and Technology Information (KISTI) as input coefficients, the effect on production inducement, value-added inducement, and employment inducement was analyzed to be US$24 million, US$13.4 million, and 267, respectively.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.188-194
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• 2023

This study aimed to derive the basic wood density, one of several carbon emission factors, for carbon accounting of bamboo forests in Korea. Bamboo is mainly distributed in Jeollanam-do and Gyeongsangnam-do provinces, and 101 sample trees were selected for each of the three species (Phyllostachys nigra var. henonis, P. bambusoides, and P. pubescens). The basic wood density derivation used the KS F 2098 method. The measurements showed that the basic wood density was 0.83 g/cm³ for P. nigra var. henonis, 0.81 g/cm³ for P. bambusoides, and 0.72 g/cm³ for P. pubescens. However, the bamboo distribution area in Korea is not very large, and P. pubescens grows in one area only. Therefore, the basic wood density that can be applied to bamboo was 0.79 g/cm³. Evaluation of the uncertainty of the extracted basic wood density showed a very low value of 1.61%, which confirmed the reliability of the basic wood density derived from this analysis. The basic wood density, biomass expansion factor, and root-to-shoot ratio were used to calculate the carbon storage capacity of one bamboo plant and expanded to calculate the capacity for a hectare of bamboo. Carbon storage and absorption of bamboo were calculated by applying a carbon-emission factor, such as the basic wood density. These study results are expected to contribute to the carbon-neutral policy and forest management direction in Korea.

• Korean Journal of Environmental Biology
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• v.31 no.4
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• pp.233-242
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• 2013

Cyanobacteria (blue-green algae) are not only the first oxygenic organisms on earth but also the foremost primary producers in aquatic environment. Massive growth of cyanobacteria, in eutrophic waters, usually changes the water colour to green and is called as algal (cyanobacterial) bloom or green tide. Cyanobacterial blooms are a result of high levels of primary production by certain species such as Microcystis sp., Anabaena sp., Oscillatoria sp., Aphanizomenon sp. and Phormidium sp. These cyanobacterial species can produce hepatotoxins or neurotoxins as well as malodorous compounds like geosmin and 2-methylisoborneol (MIB). In order to solve the nationwide problem of hazardous cyanobacterial blooms in Korea, the following technically and strategically sound approaches need to be developed. 1) As a long-term strategy, reduction of the nutrients such as phosphorus and nitrogen in our water bodies to below permitted levels. 2) As a short term strategy, field application of combination of already established bloom remediation techniques. 3) Development of emerging convergence technologies based on information and communication technology (ICT), environmental technology (ET) and biotechnology (BT). 4) Finally, strengthening education and creating awareness among students, public and industry for effective reduction of pollution discharge. Considering their ecological roles, a complete elimination of cyanobacteria is not desirable. Hence a holistic approach mentioned above in combination to addressing the issue from a social perspective with cooperation from public, government, industry, academic and research institutions is more pragmatic and desirable management strategy.

• Journal of Information Management
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• v.36 no.4
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• pp.117-136
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• 2005

'IT skills framework' provides a common reference model for the identification of the skills needed to develop effective information system making use of information and communications technologies. It is a simple and logical two-dimensional framework consisting of areas of work on axis and levels of responsibility on the other. It uses a common language and a sensible, logical structure that can be adapted for the HRD(human resources development) For example (1) gather labour market intelligence coherently and consistently (2) quantify the skill requirements of the ICT market (3) set up the career path for IT workers and so on.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.4
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• pp.75-93
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• 2016

This study aims at analyzing the relationship between team characteristic and innovation performance. The mediating effect of creative climate on the team characteristic and innovation performance is also measured. Based upon literature review, individual creative characteristics, team diversity, team cohesion, task characteristics are presented as antecedents of team characteristic. Creative climate affects the creative behavior and innovative performance. Creative climate is measured as the Team Climate Inventory (TCI) proposed by Anderson & West (1998) including goal, participative-autonomy and innovative-support. Data were collected from 186 survey responses (54 Teams) out of total 462 (69 teams) from the R&D department of a major ICT firm in Korea. Empirical results show the diversity, cohesion, job characteristic, individual creative characteristic have a positive effect on the creative climate and innovation performance. The participative-autonomy climate factor appears to mediate the relationship between team characteristic (diversity, cohesion, job and individual characteristics) and innovation performance. However, the mediating effects of goals and innovative-support factors were not significant statistically. It was confirmed that the organization can contribute to improve the team innovation performance by facilitating a autonomy and participative climate as well as fostering the team characteristic.

• Journal of Korean Society for Quality Management
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• v.45 no.3
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• pp.463-481
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• 2017

Purpose: This study provide the matching mechanism between startup and business incubator to enhance managerial performance of business incubator. In addition, we propose the differentiation strategy for business incubator based on the needs of startups. Methods: In order to carry out the research, we surveyed 216 startups who already have invested in venture capitals and angel investors and currently residing in business incubator and 30 venture capitals and angel investors. Based on survey results, we develop a business incubator capability table matching startup with business incubator. Results: Satisfaction and importance of the supporting programs varied depending on the startup experience and startup lifecycle. As a result, we recommended a R&D center for machinery/material, bio/medical and electric/electronics startups and individual office for ICT and knowledge service startups. In addition, we suggested a differentiation strategy to BI in university specialized for machinery/material, privately operated BI for electric/electronic, (local)government, R&D center and individual office for knowledge service respectively. Conclusion: In this study, business incubator capability table is applied to match startup with business incubator and it could be applied to evaluate the current status of business incubator. Furthermore, it will help to establish a future strategic direction for business incubator.