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최정인,김원근,이동석,이석원,Choi, Jung-In,Kim, Won-Keun,Lee, Dong-Seok,Lee, Seok-Won 한국터널지하공간학회 2010 한국터널지하공간학회논문집 Vol.12 No.1
국외에서는 대형 대단면 지하공간을 건설할 경우 기존의 이형철근 록볼트와 병행하여 시공이 간편하고 안정성을 확보할 수 있는 케이블볼트를 적용하고 있다. 그러나 국내의 경우 케이블볼트에 대한 인식 부족 및 대형 지하공간의 부재로 인하여 기존에 사용하고 있는 이형철근 록볼트를 계속 사용하고 있으며, 또한 케이블볼트의 성능 평가 및 검증에 대한 연구도 매우 적어 현재 현장 시험시공 수준에서 머무르고 있다. 따라서 본 연구에서는 외국에서 개발된 버튼형 케이블볼트를 수장 보완하여 콘형 케이블볼트를 개발하였다. 개발된 콘형 케이블볼트의 적용성 및 성능 평가를 수행하기 위하여 이형철근 록볼트, 일반(plane) 케이블볼트 그리고 외국에서 다양하게 개선된 케이블볼트 중에서 콘형 케이블볼트와 작용 매커니즘이 비슷한 벌브형 케이블볼트를 함께 사용하여 인발성능을 평가하였다. 실험 결과, 강도 관점에서 (콘형 케이블볼트${\approx}$벌브형 케이블볼트) > 록볼트 > 일반 케이블볼트 순으로 인발강도 값이 크게 산정되었다. 따라서 본 연구에서 개발한 콘형 케이블볼트는 기존에 외국에서 개발된 고성능 케이블볼트와 동등 이상의 성능을 보였으며, 결국 실제 현장에서 지보재로서의 역할을 충분히 수행할 수 있을 것으로 판단된다. The cablebolt which secures a workability and stability has been used in foreign countries as one of supporting materials with rebar rockbolt especially in construction of large underground structures. However, only the rebar rockbolt has been applied up to now to all the constructions of underground structures in Korea due to an absence of recognition of cablebolt and large underground structure projects. Consequently, the research for a performance evaluation and verification of cablebolt is very limited and only the proto-type field tests have been conducted. In this study, the cone-shaped button cablebolt is developed by modifying an existing button cablebolt. To evaluate a performance and applicability of cone-shaped button cablebolt, the laboratory pull tests are conducted and bond capacity is analyzed under a various conditions. The rebar rockbolt, plane cablebolt, and bulb cablebolt which has a similar mechanical behavior with cone-shaped button cablebolt, are also tested and their bond capacities are evaluated and compared with cone-shaped button cablebolt under the same condition. The results show that the bond capacity is in the order of (cone-shaped button cablebolt$\approx$bulb cablebolt) > rockbolt > plane cablebolt. It is found that the bond capacity of cone-shaped button cablebolt developed in this study is at least equivalent with an existing high performance cablebolt developed in foreign countries, therefore the cone-shaped button cablebolt could be used as one of supporting materials for underground structures in construction field.
IoT 오픈 플랫폼 암호기술 현황 및 보안 요구사항 분석
최정인,오윤석,김도원,최은영,서승현,Choi, Jung-In,Oh, Yoon-Seok,Kim, Do-won,Choi, Eun Young,Seo, Seung-Hyun 한국정보처리학회 2018 정보처리학회논문지. 컴퓨터 및 통신시스템 Vol.7 No.7
With the rapid development of IoT(Internet of Things) technology, various convenient services such as smart home and smart city have been realized. However, IoT devices in unmanned environments are exposed to various security threats including eavesdropping and data forgery, information leakage due to unauthorized access. To build a secure IoT environment, it is necessary to use proper cryptographic technologies to IoT devices. But, it is impossible to apply the technologies applied in the existing IT environment, due to the limited resources of the IoT devices. In this paper, we survey the classification of IoT devices according to the performance and analyze the security requirements for IoT devices. Also we survey and analyze the use of cryptographic technologies in the current status of IoT open standard platform such as AllJoyn, oneM2M, IoTivity. Based on the research of cryptographic usage, we examine whether each platform satisfies security requirements. Each IoT open platform provides cryptographic technology for supporting security services such as confidentiality, integrity, authentication an authorization. However, resource constrained IoT devices such as blood pressure monitoring sensors are difficult to apply existing cryptographic techniques. Thus, it is necessary to study cryptographic technologies for power-limited and resource constrained IoT devices in unattended environments.
아사이베리를 첨가한 샐러드드레싱의 품질특성 및 항산화활성
최정인,정해정,Choi, Jeong-In,Chung, Hai-Jung 한국식생활문화학회 2017 한국식생활문화학회지 Vol.32 No.5
This study was conducted to evaluate the quality characteristics and antioxidant activities of salad dressing prepared with acaiberry powder (0, 1, 3, and 5%). The pH and titratable acidity increased as the acaiberry powder increased. The sugar content showed no significant differences between samples. The viscosity was lowest in the controls and increased with increasing amounts of the acaiberry powder. The lightness and yellowness values decreased, while the redness values increased with increasing amounts of acaiberry powder. The total polyphenol content ranged from 10.26-45.19 mg GAE/100 g, increasing with increased acaiberry powder levels. The antioxidant activities measured via DPPH radical scavenging activity, reducing power and FRAP also increased with increasing acaiberry powder concentrations. Finally, a consumer acceptance test revealed that up to 3% acaiberry powder could be added to salad dressing to provide high antioxidant activity without sacrificing sensory quality.
물질의 상태 분류에 대한 과학교사와 머신러닝 모델의 분류 결과의 비교 분석
최정인(Jung-In Choi),백성혜(Seoung-Hey Paik) 학습자중심교과교육학회 2023 학습자중심교과교육연구 Vol.23 No.4
목적 본 연구는 물질의 상태 분류에 대한 초⋅중등 과학교사들인 연구 참여자들과 개발된 머신러닝 모델의 분류 결과를 비교 분석하여 분류의 결과가 불일치하는 상황의 원인을 확인하고, 그 결과를 토대로 물질의 상태 분류 학습에 줄 수 있는 교육적 함의를 찾고자 하였다. 방법 이를 위하여 중부권 소재 사범대학의 교육대학원에 재학 중인 초⋅중등 과학교사 31명을 대상으로 물질의 상태 분류 활동을 수행하고 의사결정 트리 알고리즘을 적용한 머신러닝 모델을 구축하였다. 그리고 정확도, F1-score, 정밀도, 재현율 등 모델의 성능 평가를 실시하였다. 결과 개발된 물질의 상태 분류 머신러닝 모델의 분류 정확도는 0.820, F1-score는 0.820, 정밀도는 0.826, 재현율은 0.820으로 나타났다. 또한 과학교사들이 분류한 결과와 머신러닝 모델의 분류 결과가 불일치하는 정도는 순물질이나 균일 혼합물보다 불균일 혼합물에서 크게 나타났다. 이러한 불일치는 연구 참여자들이 물질의 상태를 분류할 때 거시적 관점과 미시적 관점의 분류기준을 일관적으로 적용하지 않거나, 특정 물질은 특정 상태라는 개념을 미리 가지고 물질의 상태를 분류하기 때문에 나타나는 현상으로 분석되었다. 그리고 의사결정 트리 알고리즘의 시각화를 통해 학습 상태를 드러내는 도구로서의 유용성을 확인하였다. 결론 연구 결과를 토대로, 선행연구에서 지적한 학생들의 물질의 상태 분류 과정에서 드러나는 혼란의 원인을 찾아볼 수 있었으며, 머신러닝은 효과적인 학습상태 진단도구가 될 수 있으므로 이를 활용할 수 있도록 교사교육이 필요함을 제안하였다. Objectives This study compares and analyzes state classification results of matter between developed machine learning model and research participants who are elementary and middle school science teachers, identifies the cause of the situation in which classification results are inconsistent. And based on the results, we tried to find educational implications that can help learn state classification of matter. Methods For 31 elementary and middle school science teachers enrolled in the Graduate School of Education at the College of Education located in the central region, matter classification activities were performed and a decision tree algorithm was applied to the machine learning model. And the effectiveness of the program was confirmed through model performance evaluation such as accuracy, F1-score, precision, recall. Results The classification accuracy of developed machine learning model for classifying state of matter was 0.820, the F1-score was 0.820, the precision was 0.826 and the recall was 0.820. In addition, the degree of discrepancy between the classification results of science teachers and the classification results of the decision tree algorithm was larger in heterogeneous mixtures than in pure matters or homogeneous mixtures. This discrepancy was analyzed as a phenomenon that occurs because science teachers do not consistently apply the classification criteria from the macroscopic and microscopic perspectives or do have the concept that a specific matter is a specific state in advance when classifying the state of matter. Based on the results of these studies, the cause of confusion revealed in the process of classifying the state of matter pointed out in previous studies was found. Conclusions Based on the research results, it was possible to find the cause of confusion revealed in the process of classifying the state of matter of students pointed out in previous studies, and since machine learning can be an effective tool for diagnosing learning conditions, it is suggested that teacher training is needed to utilize it.
최정인(Jeong-in Choi),임흥빈(Heung-bin Im),정은희(Eun-hee Jung),김태열(Tae-yuel Kim),손영금(Yeong-geum Son),고순미(Sun-mi Ko),이호정(Ho-jung Lee),오조교(Jo-gyo Oh) 한국환경보건학회 2018 한국환경보건학회지 Vol.44 No.4
Objectives: A lake is a place used by many people, and compared to rivers it is easy for them to become polluted. The water quality in lakes and reservoirs has been worsening recently. The purpose of this study is to evaluate the water pollution characteristics of major lakes in northern Gyeonggi-do Province. Methods: Six lakes were selected as major lakes and were evaluated in terms of water pollution characteristics and eutrophication (as defined by results for COD<sub>Mn</sub>, TOC, SS, Chl-a, T-N and T-P) over one year (from December 2016 through November 2017) in northern Gyeonggi-do Province. Results: The annual average COD<sub>Mn</sub> was found to be 3.1 mg/L in Onam, 3.6 mg/L in Sanjeong, 4.7 mg/L in Gisan, 4.8 mg/L in Ilsan, and 6.1 mg/L in Jangja. The results of the Korean trophic state index (TSI<sub>KO</sub>) value indicated a eutrophic state (TSI<sub>KO</sub> 59.0) in Jangja lake. The other lakes were classified as being in a mesotrophic state (TSI<sub>KO</sub> of 38.1 in Sanjeong, 40.2 in Ilsan, 41.9 in Onam, 46.1 in Gisan, and 47.8 in Gomo). Conclusions: Ilsan Lake’s water quality is being well maintained. Sanjeong, Onam, and Gisan are appropriate for use as agricultural water. Jangja lake requires efforts for water quality improvement and to prevent the nflow of non-point pollutant sources.
최정인 ( Jung In Choi ),백성혜 ( Seoung Hye Paik ) 한국과학교육학회 2015 한국과학교육학회지 Vol.35 No.2
The purpose of this study is to find the point for improvement through the comparative analysis of the 2007 & 2009 revised science curriculum, and the NGSS of the United States with Bloom`s revised taxonomy. The results of the analysis confirmed that the revised curriculum in 2009 compared to the revised curriculum in 2007 has expanded the type of cognitive process and knowledge, which promote a higher level thinking. However, the revised curriculum in 2009 has been biased to the type of specific cognitive process and knowledge in cognitive process dimension and knowledge dimension as compared to the NGSS of the United States. In the revised curriculum in 2009, the type of cognitive process such as ‘analyze,’ ‘evaluate,’ ‘create,’ and the type of knowledge such as ‘meta-cognitive knowledge’ have been treated inattentively. In addition, through comparative analysis, it was identified that the type of cognitive process and knowledge that were neglected in achievement standards were not dealt with in the learning objective of teachers` guides, either. The revised curriculum should consist of achievement standards in comparison to the previous curriculum to reflect better the goals of science education. Therefore, it is necessary to create an achievement standards including various types of cognitive processes and knowledge by improving the method of statement of achievement standards of science curriculum.
물질의 상태 분류에 대한 머신러닝 기반 교사교육 프로그램의 교육적 효과
최정인(Jung-In Choi),백성혜(Seoung-Hey Paik) 학습자중심교과교육학회 2023 학습자중심교과교육연구 Vol.23 No.2
목적 본 연구에서는 초·중등 과학교사를 대상으로 물질의 상태 분류에 대한 머신러닝 기반 교사교육 프로그램을 개발 및 실행하여 물질의 상태 분류 머신러닝 모델을 구축하였다. 그리고 모델의 평가 및 과학교사들의 경험을 질적 분석하여 프로그램의 효과성 및 과학수업에 머신러닝을 적용하는 것에 대한 과학교사들의 인식을 확인하고자 하였다. 방법 이를 위하여 중부권 소재의 사범대학의 교육대학원에 재학 중인 초·중등 과학교사 31명을 대상으로 총 3회의 물질의 상태 분류 활동을 수행하고 의사결정트리 알고리즘을 적용한 머신러닝 모델로 구축하였다. 그리고 정확도, F1-score 등 모델 성능 평가를 통해 프로그램의 효과성을 확인하였다. 또한 과학교사들이 머신러닝의 적용에 대해 갖는 생각을 질적 분석하였다. 결과 총 3회의 물질의 상태 분류 활동 동안 구축된 모델의 성능 평가 결과 정확도, F1-score 등의 값이 정적으로 증가하여 물질의 상태 분류에 대한 머신러닝 기반 교사교육 프로그램의 교육적 효과가 있는 것으로 판단되었다. 그리고 연구 참여자들의 머신러닝 모델 생성을 위한 데이터를 분석한 결과, 지식에 근거한 연역적 사고과정을 통해 물질의 상태를 분류하는 경우가 있음이 드러났다. 머신러닝 모델의 분류 성능을 비교한 결과 미시적 분류 기준보다는 거시적 분류 기준이 더 큰 영향을 주었으며, 물질의 사례별 연구 참여자와 머신러닝 모델의 분류 결과를 비교하였을 때 혼합물의 경우 불일치도가 증가하였다. 또한 질적 연구 분석을 통해 연구 참여자들이 머신러닝의 적용에 대해 갖는 생각을 ‘과학 개념의 생성 과정 체험’, ‘인지갈등’, ‘의사소통’ 등 9개의 주제로 도출하였다. 결론 머신러닝을 과학교육의 탐구학습 방안으로 교사교육에 적극 도입하여야 하며, 머신러닝 기반 교육 프로그램을 토대로 귀납적 사고와 같은 과학적 추론 과정을 제대로 반영할 수 있는 교과서 등의 교육 자료가 개발되어야 하겠다. 그리고 혼합물을 물질의 상태 분류 학습에 포함시켜야 하는가에 대한 과학적 관점에서의 논의가 필요하다. Objectives In this study, a machine learning-based teacher education program for classifying the state of matter was developed and implemented for elementary and secondary science teachers and machine learning model for state classification of matter was established. And by analyzing the model evaluation and the experience of science teachers qualitatively, it was attempted to confirm the effectiveness of the program and the perception of science teachers about the application of machine learning to science classes. Methods For 31 elementary and middle school science teachers enrolled in the Graduate School of Education at the College of Education located in the central region, a total of three matter classification activities were performed and a decision tree algorithm was applied to the machine learning model. And the effectiveness of the program was confirmed through model performance evaluation such as accuracy and F1-score. In addition, we qualitatively analyzed the thoughts of science teachers on the application of machine learning. Results TAs a result of evaluating the performance of the built model during a total of 3 state of matter classification activities, it was determined that the accuracy and F1-score values increased statically, resulting in the educational effect of the Machine Learning-Based Teacher Education Program on the Classifying State of Matter. And as a result of analyzing the data of the study participants, it was revealed that there are cases in which the states of matter are classified through a deductive thinking process based on knowledge. As a result of comparing evaluation indicators of the machine learning models, the macroscopic classification criteria had a greater effect than the microscopic classification criteria. And when the classification results between the machine learning model and the research participants for various examples were compared, in the case of mixtures, the degree of inconsistency increased. In addition, through qualitative research analysis, the thoughts of science teachers on the application of machine learning were derived into nine topics, including ‘experience the process of creating science concepts’, ‘cognitive conflict’, and ‘communication’. Conclusions Machine learning should be actively introduced into teacher education as an inquiry-learning method of science education. And educational materials such as textbooks that can properly reflect scientific reasoning processes such as inductive thinking should be developed based on machine learning-based education programs. And it is necessary to discuss from a scientific point of view whether mixtures should be included in the learning of Classifying State of Matter.
IP 공유기 기반 W-PAN(Wireless Personal Area Network) 인증 제어기술 개발
최정인(Jung-In Choi),이선숙(Sun-Sook Lee),이하경(Ha-Kyung Lee),이준형(Jun-Hyeong Lee),정정수(Jung-Su Jeong),용환승(Hwan-Seung Young) 한국컴퓨터정보학회 2013 한국컴퓨터정보학회 학술발표논문집 Vol.21 No.2
본 논문에서는 W-PAN 환경에서 IP공유기를 표준설계하고 구현하며 효율적인 실시간 사용자 웹기반 인증 기법을 연구하였다. 또한 W-PAN Device & Service Application 인증과 접근, 권한제어를 위한 인증 Client 모듈과 Server 모듈, Supplicant를 개발하고 제안하였다. 이를 통해 IP 공유기 기반 환경에서의 W-PAN 환경에서 인증 제어 솔루션에 대한 개발로 생산되는 단말기의 서비스 품질을 향상시키고 무선 접속 기술을 표준화 할 수 있다. 또한 유해한 트래픽을 검색하고 보호하는 안정적인 시스템 관리가 가능해졌다. W-PAN Device와 Service Application 인증, 접근 및 권한 제어를 위한 인증 시스템의 플랫폼 구축으로 향후 관련 기술의 통합과 융합 기술을 적용할 수 있는 능력을 확보하였다.
중학생의 과학 학습 환경에 대한 인식과 메타인지와의 관련성
최정인 ( Jung In Choi ),여성희 ( Sung Hee Yeau ),심규철 ( Kew Cheol Shim ),소금현 ( Keum Hyun So ) 경북대학교 중등교육연구소 2012 중등교육연구 Vol.60 No.1
The purpose of this study was to explore a relationship between middle school students` perceptions of science learning environment and their meta-cognition. Subjects were 231 boys and girls in a middle school in Gyeonggi-do. The results of this study were as follows; First, Meaningful correlation statistically were found between students` perceptions of science learning environment and their meta-cognition(p<.01). The highest level of correlation was reported between ``Personal relevance``, ``Science inquiry`` and meta-cognition(p<.01). Second, the upper group students who perceived positively about ``Personal relevance``, ``Science inquiry``, ``Autonomous participation``, ``Student-student interaction`` and ``Teacher Support`` scored higher in meta-cognition than middle group and lower group students(p<.01).