• Journal of The Korean Association For Science Education
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• v.38 no.5
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• pp.739-751
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• 2018

The purpose of this study is to identify the differences of argumentation discourses for Socio-Scientific Issues in the types of decision-making and personality traits of pre-service biology teachers. For this study, SSI discussion topics were selected according to four types of decision making: logical reasoning, suggestion of complement, emotional base, and internal conflict. Three groups were constructed based on personality traits such as extroversion, acceptability, and integrity. Each three group used the workbook specially developed and freely used the smart device for discussion. A recorder and a camcorder were used to record each group, their behavior was recorded and the written materials during the discussion were collected for the results. Using Walton's analysis framework, the collected data analyzed in terms of the source of utterance, the process of dialogue shift, and the critical movements that can judge the reasoning of utterance. As a result of the study, it was confirmed that the decision-making type of SSI topics and learners' personalities were influential in the decision-making process of SSI small group discussions. This research shows that there is a need to develop instructional materials considering decision-making types and learners' personality types of students as well as pre-service teachers for SSI discussion.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.73-80
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• 2012

Recently, medical equipments are developed and used for diagnosis or studies. In addition, demand of techniques which automatically deal with three dimensional medical images obtained from the medical equipments is growing. One of the techniques is automatic bone segmentation which is expected to enhance the diagnosis efficiency of osteoporosis, fracture, and other bone diseases. Although various researches have been proposed to solve it, they are unable to be used in practice since a size of the medical data is large and there are many low contrast boundaries with other tissues. In this paper, we present a fast and accurate automatic framework for bone segmentation based on multi-resolutions. On a low resolution step, a position of the bone is roughly detected using constrained branch and mincut which find the optimal template from the training set. Then, the segmentation and the registration are iteratively conducted on the multiple resolutions. To evaluate the performance of the proposed method, we make an experiment with femur and tibia from 50 test knee magnetic resonance images using 100 training set. The proposed method outperformed the constrained branch and mincut in aspect of segmentation accuracy and implementation time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.581-590
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• 2022

It is important to create a decent pedestrian space in order to realize a public space that can ultimately improve the quality of life based on guaranteeing people's right to move while also enhancing urban activity. The goal of this study is to develop a pedestrian path evaluation system in order to lay the foundation for data construction leading to the creation of such elegant walking space. First, a basic system was established in keeping with factors and the space, and this system was used as the basic framework of the study. The trends identified in the literature can be divided into eight categories, denoted here as: Walking safety policy, Walking focused plan, Recognition transition, Transportaion system, Activity-linked walking, Facility utilization walking, Nature and history linked walking and Content convergence walking. The macro- and micro-indices and factors mentioned in related studies were synthesized and classified, and the basis for universality and differentiation was established by integrating them. Next, according to the basic composition of the walking system, Walking potential and slope safety in the Safety category, Basic walking connectivity and Traffic linkage in the Efficiency category, Walking arrangement and Rest convenience in the Health category, and Resource connectivity and Activity abundance in the Comfortability category macro evaluation system of the eight categories were established and a corresponding measurement method was developed.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.221-233
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• 2021

The purpose of this study is to analyze the effects of determinants of innovation performance on innovation performance in industry-research institute(IR) cooperation for researchers of government-funded research institutes in Daedeok Innopolis. We reviewed the existing literature on the determinants of innovation performance through cooperation, and established a conceptual framework to analyze the combinatorial effect of the determinants of innovation performance on innovation performance in IR cooperation. Data for empirical analysis were collected through a questionnaire survey targeting researchers at a government-funded research institute in Daedeok Innopolis. The fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the combined effect of determinants of innovation performance. The fsQCA results show that the configuration of high motivation, high trust, high commitment and high satisfaction of researchers of government-funded research institutes improve innovation performance. On the other hand, it shows that the configuration of high motivation, high trust, low commitment and low satisfaction of the researcher improves innovation performance.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.343-376
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• 2022

Continuing education for professionals is the most basic requirement for continuous professional development. The enhancement of the professionalism of librarians will also be possible through the establishment of a systematic continuing education strategy of the national level. In this study, we tried to derive a strategy for continuing education for librarians in Korea by analyzing the internal and external environment of national institutions that are the center of continuing education for librarians. To this end, we proposed a complex framework of PEST-3Cs-SWOT as a systematic environmental analysis methodology and tried to apply it. For PEST analysis, literature related to library, librarian, and librarian education was extensively reviewed, and for 3Cs analysis, in-depth interviews with internal employees, questionnaire data analysis on the demand survey of training subjects, and case studies of similar institutions in Korea and abroad were conducted. Based on this, SWOT analysis was conducted, and finally, 4 strengths-opportunity strategic tasks, 5 weaknesses-opportunity strategic tasks, 5 strength-threat strategic tasks, and 3 weaknesses-threat strategic tasks were derived. This study will be meaningful in that it presents strategic tasks for continuing education institutions in Korea, and at the same time suggests and applies a complex analysis methodology that can be applied to tasks similar to development plans and strategy establishment.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.161-170
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• 2010

For the development of load and resistance factor design, reliability analysis is required to calibrate resistance factors in the framework of reliability theory. The distribution of measured-to-predicted pile resistance ratio was obrained based on only the results of load tests conducted to failure for the assessment of uncertainty regarding pile resistance and used in the conventional reliability analysis. In other words, successful pile load test (piles resisted twice their design loads without failure) results were discarded, and therefore, were not reflected in the reliability analysis. In this paper, a new systematic method based on Bayesian theory is used to update reliability indices of driven steel pipe piles by adding more proof pile load test results, even not conducted to failure, to the prior distribution of pile resistance ratio. Fifty seven static pile load tests performed to failure in Korea were compiled for the construction of prior distribution of pile resistance ratio. The empirical method proposed by Meyerhof is used to calculate the predicted pile resistance. Reliability analyses were performed using the updated distribution of pile resistance ratio. The challenge of this study is that the distribution updates of pile resistance ratio are possible using the load test results even not conducted to failure, and that Bayesian updates are most effective when limited data are available for reliability analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.301-310
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• 2006

Typically, we needs enormous national budget for the flood control project and so the project usually has big influence on the national economy. Therefore, the reliable estimation of flood damage is the key issue for the economic analysis of the flood control project. This study aims to provide a GIS based technique for distributed flood damage estimation. We consider two aspects of engineering and economic sides, which are the inundation analysis and MD-FDA (Multi-Dimensional Flood Damage Analysis), for the flood damage assessment. We propose the analysis framework and data processing using GIS for assessing flood damages. The proposed methodology is applied to the flood control channel project for flood disaster prevention in Mokgamcheon/Dorimcheon streams and this study presents the detailed GIS database and the assessment results of flood damages. This study may have the worth in improving practical usability of MD-FDA and also providing research direction for combining economic side with the engineering aspect. Also this distributed technique will help decision-making in evaluating the feasibility of flood damage reduction programs for structural and nonstructural measures.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.408-416
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• 2023

The IUCN Red List of Ecosystems serves as a global standard for assessing and identifying ecosystems at high risk of biodiversity loss, providing scientific evidence necessary for effective ecosystem management and conservation policy formulation. The IUCN Red List of Ecosystems has been designated as a key indicator (A.1) for Goal A of the Kunming-Montreal Global Biodiversity Framework. The assessment of the Red List of Ecosystems discerns signs of ecosystem collapse through specific criteria: reduction in distribution (Criterion A), restricted distribution (Criterion B), environmental degradation (Criterion C), changes in biological interaction (Criterion D), and quantitative estimation of the risk of ecosystem collapse (Criterion E). Since 2014, the IUCN Red List of Ecosystems has been evaluated in over 110 countries, with more than 80% of the assessments conducted in terrestrial and inland water ecosystems, among which tropical and subtropical forests are distributed ecosystems under threat. The assessment criteria are concentrated on spatial signs (Criteria A and B), accounting for 68.8%. There are three main considerations for applying the Red List of Ecosystems assessment domestically: First, it is necessary to compile applicable terrestrial ecosystem types within the country. Second, it must be determined whether the spatial sign assessment among the Red List of Ecosystems categories can be applied to the various small-scale ecosystems found domestically. Lastly, the collection of usable time series data (50 years) for assessment must be considered. Based on these considerations, applying the IUCN Red List of Ecosystems assessment domestically would enable an accurate understanding of the current state of the country's unique ecosystem types, contributing to global efforts in ecosystem conservation and restoration.

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

• Information Systems Review
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• v.20 no.1
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• pp.41-59
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• 2018

This study analyzed the factors that affect acceptance of online direct marketing in agricultural companies. Empirical analysis was conducted using the research model based on the individual's technology acceptance model (TAM) and the information technology adoption models in organizations. These models have four dimensions: 1) technology characteristics, which include perceived usefulness and perceived ease of use of TAM 2) CEO characteristics, which including the innovativeness and IT capability of CEOs; 3) organizational readiness, which include financial, technological, and human resources capabilities and 4) environment and external pressure, which include government support and changes to the Internet environment. These concepts were empirically tested. A total of 209 valid data were collected through questionnaires and analyzed using confirmatory factor analysis and path analysis through the application of structural equation modeling. Results show that perceived usefulness, IT capability of CEOs, and changes to the Internet environment have significant effects on the adoption intention of online direct marketing. However, perceived ease of use, CEO innovativeness, government support, and the variables of organizational readiness dimension did not have significant effects on adoption intention. This study suggests practical implications for adoption of online direct marketing in agricultural companies.