• Journal of the Korean earth science society
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• v.45 no.3
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• pp.239-259
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• 2024

In this study, a qualitative meta-analysis was conducted on research papers on earth science education to derive knowledge of students' understanding of specific science topics-greenhouse effect, global warming, and climate change-within the context of collective Pedagogical Content Knowledge (PCK). Twenty-two research papers addressing students' alternative conceptions (misconceptions) about these topics were selected and analyzed for their respective definitions, causes (mechanisms), and impacts. Semantic network analysis and a mental model framework were applied to synthesize the findings. The meta-analysis revealed several key insights: (1) Regarding the greenhouse effect, students often used the terms "greenhouse effect" and "global warming" interchangeably, lacked knowledge about the types of greenhouse gases, and misunderstood their roles. They commonly associated the greenhouse effect with environmental pollution or changes in the ozone layer, failing to recognize its relation to the heat balance between the surface and atmosphere. (2) Concerning global warming, students confused it with sea level rise and linked it to pollution, ozone layer changes, and glacier melting. They understood global warming as a disruption of the heat balance between the surface and atmosphere but had misconceptions about its environmental impacts. (3) In terms of climate change, students used the term interchangeably with global warming, weather change, and climate anomalies. They associated climate change with atmospheric pollution and ozone layer depletion but misunderstood its environmental impacts. As result, three mental models-categorical, mechanistic, and hierarchical misconceptions-were identified as collective PCK. The implications for enhancing earth science teachers' PCK were discussed based on these findings.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.95-114
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• 2020

This paper, a meta-analysis of the effect of the start-up support policy on the start-up performance was conducted to examine the effect of the start-up support policy on the start-up performance of beneficiary companies and to provide theoretical and practical implications to support organizations and practitioners. To this end, 35 papers containing the correlation coefficient, which is a positive statistical value, were selected from the previous studies in academic journals and dissertations published in Korea from 2007 to 2020. In the preceding study of the start-up support policy, the independent variables include funding, education support, facility/equipment support, network support, mentoring support, consulting support, marketing support, management support, technical support, manpower support, and finance as a dependent variable. The effect size of the impact on aptitude and non-financial performance was reviewed. The pattern of the effect size was presented as a forest plot for easy visual understanding, and outliers were verified through sensitivity analysis for small-study-effect data with publication convenience. As a result of analyzing the effect size of the government-supported policy, it was verified that the effect size was generally medium or higher, affecting the entrepreneurial performance. Among the independent variables, the factor that has the greatest effect on startup performance is manpower support, followed by technical support, marketing support, management support, facility/equipment support, education support, mentoring support, funding, network support, and consulting support. It was analyzed that the effect size was large in order. As the 「Small and Medium Business Startup Support Act」 was recently reorganized from the manufacturing industry to digital transformation and smartization on October 8, 2020, the start-up support policy should consider the start-up stage and verify the priorities to organize the budget.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.591-604
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• 2023

This study investigated the impact of elementary science classes using metaverse on the academic achievement, positive experience in science, and digital literacy of elementary school students. In addition, we examined their perceptions. The respondents were derived from two classes in the sixth grade at an elementary school in Gyeonggi-do, who were selected designated as the experimental (n=29 students) and comparative (n=29) groups, respectively. Across five lessons under the "Plant Structure and Function" unit, the experimental group conducted science classes using the metaverse, whereas the comparative group conducted general textbook-based classes. To investigate instructional effects, the study performed ANCOVA using the pre-test score as a covariate, a survey on the perception of students about science classes using metaverse, and conducted interviews with a number of subjects. The result demonstrated that science classes using metaverse exerted no significant effect on scientific academic achievement and digital literacy. However, the study observed a statistically significant effect on science learning emotion which is a sub-element of positive experiences in science. The students were positively aware of science classes using metaverse in terms of interesting and diverse activities, and free expression of inquiry results and perceived the instability of smart devices and network connections as regrettable. Finally, the study posed the implications of the use of metaverse in science classes.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.141-144
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• 2011

최근 무선통신의 발전과 스마트 폰 사용자의 급격한 증가로 인하여 멀티미디어 콘텐츠에 대한 사용이 증가되면서 트래픽 량과 네트워크 속도 증가에 대한 요구가 급속히 증대되고 있다. 이를 위해 LTE, LTE-Advanced, Mobile WiMAX 등 차세대 이동통신 플랫폼 및 연관 기술들이 많이 제안되고 있다. 이에 따라 차세대 이동 통신 프로토콜 개발 단계부터 안정화 단계까지 프로토콜 검증 및 분석을 위한 프로토콜 분석기가 필요하게 되었다. 본 논문에서는 LTE-Advanced 망에서 L3 프로토콜들을 분석할 수 있는 분석기를 제안한다. 제안하는 분석기는 연동 메시지를 XML 메타데이터로 기술하여 분석 시 활용하며, ASN.1 인코딩된 연동 메시지나 바이너리 인코딩된 메시지를 디코딩하여 분석할 수 있는 기법을 적용하였다. 자체 설계된 LTE-Advanced 망과의 연동 테스트를 통해 본 시스템을 검증하였다.

• Journal of Information Management
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• v.34 no.3
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• pp.1-19
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• 2003

Due to rapid internet supply, the increase of electronic resources including network resources, and the appearance of metadate, there has been a sudden change in cataloguing fields. To deal with rapid changes, the related organizations such as IFLA are organizing the research team and revising rules. This study analyzes current trend of cataloguing digital resources, considering recent matters in regards with the revision of ISBD(ER), AACR2R 2002 edition, MARC 21, Dubin Core, KCR4 etc. This research discusses also the questions of how digital resources are organized; automatic indexing, matadata, and MARC format.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.313-318
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• 2007

위치기반서비스에서 사용자의 정확한 위치가 요구되면서 측위와 추적에 대한 연구가 활발히 진행되고 있다. 측위 방법에는 위성기반 방법[1, 2], 로컬네트워크기반 방법[3-6], 센서기반 방법[1, 7, 8, 9]등이 있다. 본 연구에서는 로컬네트워크 중 WLAN (Wireless Local Area Network) 환경의 옥내에서 사용자의 위치를 추적하는 기존의 방법의 정확성을 제고하는 방안을 제안한다. 제안하는 방법은 WLAN 환경에서 RSS를 측정하여 K-NN방식으로 현재 위치를 판단한 다음, 칼만필터를 사용하여 사용자의 위치와 이동경로를 예측한다는 점에서 기존의 방법과 비슷하다. 제안하는 방법의 특징은 도면 정보를 이용하는 것이다. 제안하는 방법은 도면정보로부터 갈림길 영역을 파악하고, 갈림길 영역에서는 측정치에 가중치를 두고 갈림길이 아닌 지역에서는 시스템 모델에 가중치를 두도록 파라메타의 값을 조절한다. 제안하는 방법의 효율성을 실험적으로 증명하기 위한 실험 결과와 분석 내용도 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.165-175
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• 2007

The mobile agent executes a given task by which the agent code moves to the server directly. Therefore, node migration method becomes an important factor which impact on the whole performance of distributed system. In this paper, we propose an adaptive migration path technique of mobile agent using the metadata of naming agent. In this proposed technique, node selection for migration depends on the content of referenced metadata, and the reliability of migrated information is determined by the metadata updating method and cooperative operations of individual agents in multi-agents system. For these, we design the metadata using by the number of hit documents, hit ratio, node processing time and network delay time, and describe the methods for creating, using and updating metadata for which determine the adaptive node migration path of mobile agent according to the cooperation of individual agents and number of hit documents using by designed metadata. And results of evaluated performance for proposed adaptive migration path technique through the proper experiment and analysis gain rate of high effective information earning, because of high hit ratio(72%) about of fathered documents by case of applying metadata move to the 13 nodes. But, in case of non-applying metadata is hit ratio(46%) of gathered documents and rate of effective information earning about of 26 nodes is 36.8%.

• Journal of The Korean Ophthalmological Society
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• v.60 no.2
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• pp.144-151
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• 2019

Purpose: Intravitreal aflibercept, ranibizumab, bevacizumab, and dexamethasone are the most widely used drugs in the treatment of diabetic macular edema (DME). The aim of this study was to compare the efficacy and safety of anti-vascular endothelial growth factors and dexamethasone for the treatment of DME. Methods: There were nine previous systematic reviews on this topic; we updated these high-quality reviews. Seven studies were added to two studies following a literature search. Efficacy outcomes were 1) average improvement in visual acuity, 2) proportion of patients who experienced an improvement in vision (an increase in best-corrected visual acuity (BCVA) of ${\geq}15$ in the Early Treatment Diabetic Retinopathy Study [ETDRS]), and 3) proportion of patients who experienced worsening vision (a decrease in BCVA of ${\geq}15$ in the ETDRS). Safety outcomes included systemic adverse events and ocular-related adverse events. Results: The mean difference in the BCVA for ranibizumab versus bevacizumab treatment was 0.16 (95% confidence interval [CI]: -0.02, 0.34), and that for ranibizumab versus aflibercept was -0.08 (95% CI: -0.26, 0.10). The mean difference in the change of BCVA for aflibercept versus ranibizumab was -0.20 (95% CI: -0.40, -0.01), and that for aflibercept versus bevacizumab was -0.34 (95% CI: -0.53, -0.14). Other efficacy outcomes showed similar trends, and there was no significant difference between treatments. There was also no significant difference in both systemic and ocular adverse events rates between the treatments. Conclusions: In DME patients, the efficacy of aflibercept was found to be higher with respect to BCVA changes compared with ranibizumab or bevacizumab. However, there were no significant difference in terms of visual acuity improvement or visual acuity of more than 15 letters, nor in terms of anti-vascular endothelial growth factors (as a safety outcome).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4697-4706
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• 2010

This paper suggested the optimal operating design method using simulation and ANP(Analytic Network Process) for mass-customization in the automotive component manufacturing industry. For this, first of all, we built the simulation model including various and complex factors in the field, and estimated the meta-model by RSM(Response Surface Method). Secondly using ANP, we calculated the weight of relative importance of evaluation factors gathered from decision makers. And then, we proposed the optimal operation designs by MOGA(Multi-Objective Genetic Algorithm), analyzed results of them. Moreover, by comparing the results with the consequences using AHP(Analytic Hierarchy Process), we showed its superiority of suggested method to the manner using AHP, because it reflects inner, outer dependency, and inter-relation among judgement factors. In conclusion, through this process, we can present the better way to serve mover effective, precise, and accurate information to decision makers when they build operation design for mass-customization system as automotive parts production system.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.414-418
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• 2010

최근 라이프 로그의 수집과 관리에 관련된 연구가 많이 진행 중에 있다. 또 핸드폰 카메라, 디지털 카메라, 캠코더 등의 발전으로 자신의 일상생활을 비디오로 저장하고, 인터넷을 통해 공유하는 사람도 증가하고 있다. 비디오 데이터는 많은 정보를 포함하고 있는 라이프 로그의 한 예로. 동영상의 촬영 및 수집이 활발해짐에 따라 동영상의 메타정보를 생성하고, 이를 이용해 동영상 검색과 관리에 이용하려는 연구들이 진행 중이다. 본 논문에서는 라이프 로그를 수집하고 수집된 동영상과 라이프 로그를 이용하여 의미정보를 추출하는 시스템을 제안한다. 의미정보란 사용자의 행동을 나타내는 정보로써 컴퓨터 사용, 식사, 집안일, 이동, 외출, 독서, 휴식, 일, 기타로 9가지의 의미정보를 추출한다. 제안하는 방법은 사용자로부터 GPS, 가속도센서, 캠코더를 이용해 실제 데이터를 수집하고, 전처리 과정을 통하여 특징을 추출한다. 이때 추출될 특징은 위치정보와 사용자의 상태정보 그리고 영상처리릍 통한 RGB와 HSL 색공간의 요소와 MPEG-7의 EHD(Edge Histogram Descriptor). CLD(Color Layout Descriptor)이다. 추출된 특징으로부터 사람 행동과 같은 불안정한 상황에서 강점을 보이는 확률모델 네트워크인 베이지안 네트워크를 이용하여 의미정보를 추출한다. 제안하는 방법의 유용성을 보이기 위해 실제 데이터를 수집하고 추론하고 10-Fold Cross-validation을 이용하여 데이터를 검증한다.