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이차함수에서 두 변량사이의 관계 인식 및 표현의 발달 과정 분석: 민선의 경우를 중심으로
이동근 ( Dong Gun Lee ),문민정 ( Min Joung Moon ),신재홍 ( Jaehong Shin ) 한국수학교육학회 2015 수학교육 Vol.54 No.4
The aim of this qualitative case study is twofold: 1) to analyze how an eleventh-grader, Min-Seon, conceive and represent a pattern of change between two varying quantities in a quadratic functional situation, and 2) further to help her form a concept of ``derivative`` as a tool to express the relationship with employing a concept of ``rate of change.`` The result indicates that Min-Seon was able to construct graphs of piecewise functions that take average rates of change as range of the functions, and managed to conjecture the derivative of a quadratic function, y=x ^{2}. In conclusion, we argue that covariational approach could not only facilitate students`` construction of an initial function concept, but also support their understanding of the concept of ``derivative.``
재사용이 가능한 나노복합재료 Fe<sub>3</sub>O<sub>4</sub>-ACCS-Ag의 제조 및 항균 특성 평가
심재홍,김해원,김진원,서영석,오세강,조민,박정희,오병택,Shim, Jaehong,Kim, Hea-Won,Kim, Jin-Won,Seo, Young-Seok,Oh, Sae-Gang,Cho, Min,Park, Junghee,Oh, Byung-Taek 한국지하수토양환경학회 2015 지하수토양환경 Vol.20 No.3
In this study, Fe<sub>3</sub>O<sub>4</sub>-ACCS-Ag nanoparticles (NPs) were successfully synthesized using silica extracted from corn cob ash. The synthesized Fe<sub>3</sub>O<sub>4</sub>-ACCS-Ag NPs were characterized using X-ray diffraction (XRD), scanning electron microscopyenergy dispersive X-ray spectroscopy (SEM-EDX), transmission electron microscopy (TEM) and fourier transform infrared spectroscopy (FTIR). In addition, the potential application of Fe<sub>3</sub>O<sub>4</sub>-ACCS-Ag NPs as an antibacterial material in water disinfection was investigated using Escherichia coli ATCC 8739 as model bacteria. The antibacterial activity of synthesized composite material showed 99.9% antibacterial effect within 20 min for the tested bacteria. From this experiment, the synthesized Fe<sub>3</sub>O<sub>4</sub>-ACCS-Ag nanocomposites also hold magnetic properties and could be easily recovered from the water solution for its reuse. The reused nanocomposites presented the decreasing antibacterial efficiencies with the reuse cycle but the composite used three times still killed 90% of bacteria in 20 min.
History and Trends of Data Education in Korea - KISTI Data Education Based on 2001-2019 Statistics
( Jaehong Min ),( Sunggeun Han ),( Bu-young Ahn ) 한국인터넷정보학회 2020 인터넷정보학회논문지 Vol.21 No.6
Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI’s data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees’ interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.
Efficient Deduplication Techniques for Modern Backup Operation
Jaehong Min,Daeyoung Yoon,Youjip Won IEEE 2011 IEEE Transactions on Computers Vol.60 No.6
<P>In this work, we focus on optimizing the deduplication system by adjusting the pertinent factors in fingerprint lookup and chunking, the factors which we identify as the key ingredients of efficient deduplication. For efficient fingerprint lookup, we propose fingerprint management scheme called LRU-based Index Partitioning. For efficient chunking, we propose Incremental Modulo-K(INC-K) algorithm which is optimized Rabin's algorithm where we significantly reduce the number of arithmetic operations exploiting the algebraic nature of modulo arithmetic. LRU-based Index Partitioning uses the notion of tablet and enforces access locality of the fingerprint lookup in storing fingerprints. We maintain tablets with LRU manner to exploit temporal locality of the fingerprint lookup. To preserve access correlation across the tablets, we apply prefetching in maintaining tablet list. We propose Context-aware chunking to maximize chunking speed and deduplication ratio. We develop prototype backup system and performed comprehensive analysis on various factors and their relationship: average chunk size, chunking speed, deduplication ratio, tablet management algorithms, and overall backup speed. By increasing the average chunk size from 4 KB to 10 KB, chunking time increases by 34.3 percent, deduplication ratio decreases by 0.66 percent and the overall backup speed increases by 50 percent (from 51.4 MB/sec to 77.8 MB/sec).</P>
A Study on the Process Design for the Gasification of Industrial Waste by using Aspen Plus
( Jaehong Min ),( Dong-ju Kim ),( Youngsik Yoon ),( Na-rang Kim ),( Yong Taek Lim ),( Jae Hoi Gu ) 한국폐기물자원순환학회(구 한국폐기물학회) 2015 한국폐기물자원순환학회 3RINCs초록집 Vol.2015 No.-
The synthesis gas can be produced from the industrial waste with gasification process. The gasification model has been designed by using Aspen Plus software in this study. The main purpose of this paper was to optimize the best schematic gasification process by using Aspen Plus simulation program and to determine the effects various parameters on syngas composition such as temperature, input oxidant condition. The system consists of two reactors, which are partial combustion and gasification process to react some waste particles with oxygen iteratively. From the result, it can be investigated that as the amount of oxidant to partial combustion increases, the temperature increases and the produced amount of CO and H<sub>2</sub> also increase. The Cold gas efficiency is dependent on the amount of carbon dioxide in this process. The simulation results are compared with the experimental data from the two reactors to define optimized process model for pilot scale system. The simulation results are in good agreement with pilot-scale experimental data. Therefore this schematic process can be applied to expect results in various conditions.
감귤 착과량 추정을 위한 초분광 데이터 분류 정확도 평가
김재홍 ( Jaehong Kim ),박요섭 ( Yosup Park ),좌재호 ( Jaeho Joa ),권순화 ( Soonhwa Kwon ) 한국농업기계학회 2022 한국농업기계학회 학술발표논문집 Vol.27 No.2
감귤 노지 재배의 과학적 근거를 기반으로 한 농작체계의 지능화 및 효율화가 절실히 요구되고 있다. 감귤의 생산량 추정을 위한 기초자료 수집은 한정된 조사인력이 약 22,000ha에 이르는 방대한 면적을 조사하기에 시간이 오래 걸릴 뿐만 아니라 담당직원은 조사인력의 부족으로 격무에 시달리고 있는 실정이다. 또한 조사인력은 관행적으로 직접 관측조사에 의존하며, 일관되지 않은 데이터수집이 이뤄지고 있다. 과수 수확량의 정확한 예측은 수확 후 관리와 마케팅 계획 등에 있어서 필수 요소 중 하나인데, 과수 재배자는 노동력 산출 및 저장 계획의 근거로 중간도매인들은 포장재와 운반비용 산출 등에 활용됨으로 무엇보다 높은 신뢰성이 요구된다 (Wulfsohn et al. 2012). 농업 엔지니어링 기술 최적화와 농업 관리 관행의 표준화의 결합이 절실히 요구되는 가운데 (Leilei et al. 2022), 본 연구는 드론에서 얻은 초분광 영상 데이터를 이용하여 감귤의 열매 수확량을 빠르고 정확하게 예측하는 기초연구로서, 감귤 과실의 분류를 대표적인 감독자분류인 머신러닝 기반의 SVM(Support Vector Machine) 방식, 딥러닝 기반의 ANN(Artificial Neural Network) 방식, CNN(Convolution Neural Network) 방식의 이미지 분석 알고리즘의 분류 정확도를 평가하였다.
민재홍 ( Min Jaehong ) 한국중국언어학회 2017 중국언어연구 Vol.0 No.68
“Jianyuju”(`N₁ + V₁ + N₂ + V₂`) is a predicate type that arouses people`s constant discussion. In Modern Chinese “Jianyuju” means a sentence with its object plays as subject of the second verb simultaneously. This “Jianyuju” pattern is commonly used in our daily life. However this language phenomenon is not aroused due attention in the process of teaching Chinese to foreigners as a second language, which results many errors of its uses of foreign students. The second chapter is the distinction of “Jianyuju”, analyzed similar sentence of “Jianyuju” with syntactic, semantic and pragmatic distinction. The third chapter are the reasons of error analysis, analyzed tha reasons of the occurrence of errors. They are the target language knowledge`s negative migration, Chinese pivotal sentence itself is complicated and difficult to learn, the negative transfer of native language, communication strategies of the learners, teachers influence on grammar point explanation is not clear enough. The conclusion part is the summary of the results of the paper.