• 기호학연구
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• no.54
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• pp.177-203
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• 2018

On this study, we analyzed the movie With gods's narrative structure. This movie makes most people who has seen it feel deeply moved. We think that people can get deep feeling from a film at last after people who has seen the movie accept a context, story, and a message of the movie gladly. We focused on a special system in this movie With gods that can make give an ordinary message and big touch to people. Also we focused on every episodes of every space in a movie, and someone who moved freely between the spaces. A repetitive form and repetitive contents in a narrative become a special code itself -repetitiveness- for people and make them do auto-communication. Specifically, an information, the movie's repetitiveness, out of people become a special code for them, and then that make people bring memory and new information by themselves. Watching movie, people can look back up on life with every trial in the movie. In short, a repetitiveness and an auto-communication are a special system in the movie, that can make deeply touched.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.325-339
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• 2021

The purpose of the study is to examine sports-related cognitive functions through a systematic review and to suggest effective instruments to measure the cognitive functions. The present study was conducted based on the systematic review and meta-analysis protocol-the PRISMA. Of 429 articles searched through keywords from 2008 to 2020, 45 articles that met the selection criteria were analyzed. It was revealed that athletes had better cognitive functions than non-athletes, that the higher the sports expertise was, the higher the cognitive functions, and that there were differences in cognitive functions according to the sport types. The primary cognitive functions related to sports performance summarized as executive functions (inhibition ability, cognitive flexibility), information processing speed, spatial ability, and attention. As tasks for measuring each cognitive function, a stop signal task for inhibition ability, a design flexibility task for cognitive flexibility, a simple and choice reaction time test for information processing, a mental rotation task for spatial ability, and an attention network test for attention are appropriate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.291-298
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• 2022

Recently developed drones are inexpensive and very convenient to operate. As a result, the production and utilization of spatial information using drones are increasing. However, most drones acquire images with a low-cost global navigation satellite system (GNSS) and an inertial measurement unit (IMU). Accordingly, the accuracy of the initial location and rotation angle elements of the image is low. In addition, because these drones are small and light, they can be greatly affected by wind, making it difficult to maintain a certain overlap, which degrades the positioning accuracy. Therefore, in this study, images are taken at different times in order to analyze the positioning accuracy according to changes in certain exterior orientation parameters. To do this, image processing was performed with Pix4D Mapper and the accuracy of the results was analyzed. In order to analyze the variation of the accuracy according to the exterior orientation parameters in detail, the exterior orientation parameters of the first processing result were used as meta-data for the second processing. Subsequently, the amount of change in the exterior orientation parameters was analyzed by in a strip-by-strip manner. As a result, it was proved that the changes of the Omega and Phi values among the rotation elements were related to a decrease in the height accuracy, while changes in Kappa were linked to the horizontal accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.115-127
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• 2024

The recent increase in digital audio media has greatly expanded the size and diversity of sound data, which has increased the importance of sound data analysis in the digital forensics process. However, the lack of standardized procedures and guidelines for sound data analysis has caused problems with the consistency and reliability of analysis results. The digital environment includes a wide variety of audio formats and recording conditions, but current audio forensic methodologies do not adequately reflect this diversity. Therefore, this study identifies Life-Cycle-based sound data elemental technologies and provides overall guidelines for sound data analysis so that effective analysis can be performed in all situations. Furthermore, the identified elemental technologies were analyzed for use in the development of digital forensic techniques for sound data. To demonstrate the effectiveness of the life-cycle-based sound data elemental technology identification system presented in this study, a case study on the process of developing an emergency retrieval technology based on sound data is presented. Through this case study, we confirmed that the elemental technologies identified based on the Life-Cycle in the process of developing digital forensic technology for sound data ensure the quality and consistency of data analysis and enable efficient sound data analysis.

• Journal of The Korean Association For Science Education
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• v.34 no.5
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• pp.499-510
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• 2014

The purpose of this research is to understand interactive learning during docent-led tours in a science museum focusing on scaffolding. We developed a scaffolding framework by collating the work of other researchers in related fields. The results show that scaffolding included three dimensions: purpose, interaction, and domain. The purpose dimension, divided into six categories, is related to the intention of the scaffolder and what the scaffolding are for: strategic, social, procedural, conceptual, verbal, and metacognitive. The interaction dimension reflects students' interaction with the scaffolder in two ways: dynamic (situation specific) and static (planned in advance). The domain dimension is related to two contents: domain-general and domain-specific (such as science). The scaffolding framework was applied to dynamic interactions between docents and visitors. The data was collected from elementary school students' family visits with the guidance of two docents at the Seodaemun Museum of Natural History. The data collected consisted of surveys, interviews, video-recordings, and transcripts. The analysis shows that five guiding contexts and scaffolding phases were recognized; 1) strategic scaffolding in a poorly illustrated exhibit; 2) conceptual scaffolding in a thoroughly explanative exhibit; 3) verbal scaffolding in misleading interpretation; 4) procedural scaffolding in a manipulative exhibit; and 5) metacognitive scaffolding with inaccurate content. In addition, the results show that the docents used the dynamic and static scaffolding synthetically so that the docent-led tour was effective. In conclusion, this study presents the usefulness of understanding visitors' science learning through the scaffolding framework, as well as the how docents can scaffold actively.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Proceedings of the Korean Society of Dyers and Finishers Conference
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• 2011.03a
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• pp.29-29
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• 2011

아라미드 섬유는 열에 강한 튼튼한 방향족 폴리아마이드 섬유이다. 아마이드는 "85%이상의 아미드(CO-NH)기가 두 개의 방향족 고리에 직접 연결된 합성 폴리아미드로부터 제조된 섬유"로 정의된다. 아라미드 섬유는 크게 파라계와 메타계로 대별되는데 본 연구에서 사용한 파라계 아라미드는 인장강도, 강인성, 내열성이 뛰어나며 고강력 고탄성률을 지니고 있다. 일반적인 유기 섬유와는 다른 우수한 성질을 바탕으로 부직포, UD laminatig, staple 등의 형태로 크게 섬유보강 고무 복합재료 등의 각종 복합재료, 로프, 케이블, 방탄방호용과 같은 산업자재의 용도로 자동차, 우주항공, 정보통신, 국방, 등 다양한 관련 산업분야에서 사용이 확대되고 있는 고부가 소재이며 가격대비 성능비가 우수하기 때문에 세계적으로 산업용 섬유 및 초고성능 섬유시장에서 비중이 증가될 것으로 예상되고 있다. 본 연구에서는 Para-Aramid 필라멘트를 이용하여 ATY를 생산할 때 제조공정조건에 따른 ATY 물성을 알아보고 고강도를 요구하는 방화복, 고무 보강용 섬유 등의 소재에 맞는 ATY 사가공 최적공정조건을 도출하여 체계화된 data-base를 구축하여 생산성 향상 및 품질개선과 함께 산업자재용 직물개발에 응용하고자 한다. 아라미드를 ATY로 제조할 경우, 표면에 생기는 loop로 인하여 타소재와 접착시, 접착제 담지 성능이 향상되어 접착력이 상승되는 반면, 아라미드 ATY가 기존의 아라미드의 물성보다 저하되는 약점을 가지고 있으므로 이를 보완하기 위해 본 연구에서는 ATY 제조공정에서 중요 공정인자인 사속, heater 온도, over feed ratio를 변화시켜 시료를 제조하여 이들의 물성을 분석하여 최적의 물성을 갖는 ATY 사가공 공정을 도출함으로써 물성이 저하되는 문제를 보완 가능할 것으로 기대된다. 물성분석은 강신도, 초기탄성률을 각각 측정하여 인장특성을 확인하였으며, 습열수축률과 건열수축률을 측정하여 시료의 열수축률에 대해 측정을 하였다. 표면의 루프 발현 정도를 보기 위하여 Crimp Rigidity(CR%), 형태 불안정성(instability)등을 측정하였으며, 영상 현미경 시스템을 사용하여 ${\times}40$ 배율로 표면특성을 측정하였다.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.121-132
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• 2011

A healthcare system is a type of medical information system that performs early detection and prevention in diseases by checking one's health condition periodically. Such a healthcare system is based on the signal obtained from the body. However, the developed existing system represents certain differences in the storage and description of vital signs according to medicare devices and the evaluation method of the system. It brings some disadvantages, such as lacks in the interoperability between systems, increases in the development cost of systems, and absence of a unified system. Thus, this study develops a healthcare system based on a meta model. For establishing this objective, this study describes and stores vital sign data based on the standard meta model of HL7 and applies OCL, which is a mathematical specification language, for defining wellness indexes and extracting data in order to evaluate health risk appraisals in health. In addition, this study implements components based on OSGi and assemble them in order to easily extend various devices and systems. By describing vital data based on the meta model, it represents some advantages that it makes possible to ensure the interoperability between systems and introduce the standardization of the evaluation method of health conditions through defining the wellness index using OCL. Also, it provides dear specifications.