• 폴리머
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• 제38권1호
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• pp.9-15
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• 2014

Methylene diphenyl diisocyanate(MDI)와 poly(tetramethylene glycol)(PTMG)로부터 양말단에 isocyanate(NCO) 작용기를 가진 polyurethane(PU) prepolymer를 제조한 다음 이를 개시제로 하고 potassium pyrrolidonate를 촉매로 하여 2-pyrrolidone을 음이온 개환중합함으로써 최종적으로 양 끝에 polyamide4(PA4)가 단단한 블록이 되고 PU가 부드러운 블록이 되는 PA4-PU-PA4 형태의 삼블록 공중합체를 합성하였다. 그리고 공중합체내 각각 PA4 블록과 PU 블록의 분자량을 변화시켜 이들의 변화가 여러 가지 성질에 미치는 영향을 확인하였다. 결과적으로 PA4 블록으로 인해 원래의 PU 탄성체보다 용융온도($T_m$)는 크게 상승하였고 PA4 블록의 분자량이 증가함에 따라 초기 탄성률과 인장강도는 크게 증가하였다. 한편, PU 블록의 분자량이 증가되면 파단신율이 증가하였지만 초기 탄성률과 인장강도는 감소하는 전형적인 블록 공중합체형 탄성체의 성질을 나타냈다.

• Bulletin of the Korean Chemical Society
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• 제20권3호
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• pp.314-320
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• 1999

Several bisphosphine- and bisphosphite-substituted Re-imido complexes have been prepared from Re(NPh)(PPh3)2Cl3, 1, and Re(N-C6H3-i-Pr2)2Cl3(py), 4. Compound 1 reacted with trimethyl phosphate (P(OMe)3) to give a mixture of two isomers,mer,trans-Re(NPh)(P(OMe)3)2Cl3, 2, and fac,cis-Re(NPh)(P(OMe)3)2Cl3, 2a. In this reaction, the mer,trans-isomer is a major product. Complex 1 also reacted with triethylphosphine (PEt3) to exclusively give mertrans-Re(NPh)(PEt3)2Cl3, 3. Compound 4 reacted with trimethylphosphine (PMe3) to give mer,trans-Re(N-C6H3-i-Pr2)(PMe3)2Cl3, 5, which was converted to mer-Re(N-C6H3-i-Pr2)(PMe)(OPMe3)Cl3, 6, on exposure to air. Crystallographic data for 2: monoclinic space group P21/n, a = 8.870(2) Å, b = 14.393(3) Å, c = 17.114(4) Å, β = 101.43(2)°, Z = 4, R(wR2) = 0.0521(0.1293). Crystallographic data for 5: orthorhombic space group P212121, a = 11.307(l) Å, b = 11.802(l) Å, c = 19.193(2) Å, Z = 4, R(wR2) = 0.0250(0.0593). Crystallographic data for 6: orthorhombic space group P212121, a = 14.036(4) Å, b = 16.486(5) Å, c = 11.397(3) Å, Z = 4, R(wR2) = 0.0261(0.0630).

• 대한금속재료학회지
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• 제47권8호
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• pp.508-515
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• 2009

Ti-6Al-4V biomaterial is widely used as a bone alternative. However, Ti-6Al-4V ELI alloy suffers from numerous problems such as a high elastic modulus and high toxicity. Therefore, non-toxic biomaterials with low elastic moduli need to be developed. Ti-HA(hydroxyapatite) composites were fabricated in the present work by pulsed current activated sintering (PCAS) at $1000^{\circ}C$ under 60 MPa using mixed Ti and HA powders. The effects of HA content on the physical and mechanical properties of the sintered Ti-HA composites have been investigated. X-ray diffraction(XRD) analysis of the Ti-HA composites, including Ti-40 wt%HA in particular, revealed new phases, $Ti_{2}O$, CaO, $CaTiO_3$, and TixPy, formed by chemical reactions between Ti and HA during sintering. The hardness of the Ti-HA composites decreased with an increase in HA content. The corrosion resistance of these composites was observed to be an excellent candidate as a commercial Ti-6Al-4 V ELI alloy. A Ti-5 wt%HA composite fabricated by PCAS is recommended as a new biomaterial, because it offers good corrosion resistance, compressive strength, wear resistance, and biocompatibility, and a low Young's modulus.

• Animal Bioscience
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• 제35권7호
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• pp.955-963
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• 2022

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

• 대한치과교정학회지
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• 제52권2호
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.118-118
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• 2022

지속적인 학문의 발전을 위해서는 선행연구에 대한 재현성이 무엇보다도 중요하다고 할 수 있다. 하지만 컴퓨터와 소프트웨어의 급속한 발달로 인한 컴퓨터 환경의 다양화, 분석 소프트웨어의 지속적 최신화로 인해서 최근 구축된 모델도 짧게는 몇 달, 길게는 1~2년후면 다양한 에러로 인하여 재현성이 불가능해지고 있다. 이러한 재현성의 극복을 위해서 온라인을 통한 데이터와 소스코드의 공유의 필요성이 제시되고 있으나, 실제로는 개인마다 컴퓨터 환경, 버전, 소프트웨어 설치에 필요한 라이브러리의 버전 또는 디렉토리 등이 달라 단순히 온라인을 통한 데이터와 소스코드의 공유만으로 재현성을 개선하기는 힘든 것이 현실이다. 따라서 이러한 컴퓨터 모델링 환경의 공유는 과거의 형태와 같이 데이터, 소스코드와 매뉴얼의 공유만으로 불가능하다고 할 수 있다. 따라서 본 연구에서는 수자원 모델링의 재현성 개선을 위해 1) 온라인 저장소, 2) 클라우드기반 JupyterHub 모델링 환경과 3) 모델 APIs 3개의 핵심 구성요소를 제시하고, 최근 미국에서 개발된SUMMA(Structure for Unifying Multiple Modeling Alternative) 수자원 모델에 적용하여 재현성 달성을 위한 3개의 핵심 구성요소의 필요성과 용이성을 검증하였다. 첫 번째, 데이터와 모델의 온라인 공유는 FAIR(Findable, Accessible, Interoperable, Reusable) 원칙으로 개발된 수자원분야의 대표적인 온라인 저장소인 HydroShare를 활용하여 모델입력자료를 메타데이터와 함께 공유하였다. 두 번째, HydroShare에서 Web App의 형태로 제공되는 클라우드기반 JupyterHub환경인 CUAHSI JupyterHub(CJH)와 일루노이대학에서 제공하는 CyberGIS-Jupyter for water JupyterHub(CJW)환경에 수자원모델링 환경을 컨테이너(Docker) 환경을 통해 구축·공유하였다. 마지막으로, 클라우드에서 수자원모델의 효율적 이용을 위해 Python기반의SUMMA모델 API인 pySUMMA를 개발·공유하였다. 이와같이 구축된 3개의 핵심 구성요소를 이용하여 2015년 Water Resources Research에 게재된 SUMMA 논문의 9개 Test Cases 중에서 5개를 누구나 쉽게 재현할 수 있음을 증명하였다. 재현성의 중요성에 대한 인식의 증가로 Open과 Transparent Hydrology에 대한 요구가 증대되고 있으며, 이를 위해서 클라우드 기반의 모델링 환경구축 및 제공이 확대되고 있다. 본 연구에서 제시한 HydroShare와 같은 온라인 저장소, CJH와 CJW와 같은 클라우드기반 모델링환경, 모델의 효율적 이용을 위한 모델 APIs는 급속도로 발달하고 있는 컴퓨터 및 소프트웨어 환경에서 핵심구성요소이며, 연구의 재현성 개선을 통해 수자원공학 발전에 기여할 것으로 기대된다.

• 산업경영시스템학회지
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• 제46권3호
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• ALGAE
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• 제38권4호
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• pp.283-294
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• 2023

Previous research indicated that free-living sporangial filament keep hollow morph under high-culture density and form bipartite cells under low-culture density, while the following conchospore release was inhibited by high light. Here, we further explored the molecular bases of these affects caused by light and culture density using a transcriptome analysis. Many differentially expressed genes (DEGs) related to carbon dioxide concentration and fixation, photosynthesis, chlorophyll synthesis and nitrogen absorption were upregulated under high-light conditions compared with low-light conditions, indicating the molecular basis of rapid vegetative growth under the former. The stress response- and ion transport-related DEGs, as well as the gene encoding the vacuole formation-brefeldin A-inhibited guanine nucleotide exchange protein (BIG, py05721), were highly expressed under high-density conditions, indicating the molecular basis of the hollow morph of free-living sporangial filaments under high-culture density conditions. Additionally, the brefeldin A treatment indicated that the hollow morph was directly influenced by vacuole formation-related vesicle traffic. Others DEGs related to cell wall components, zinc-finger proteins, ASPO1527, cell cycle and cytoskeleton were highly expressed in the low density with low-light group, which might be related to the formation and release of conchospores. These results provide a deeper understanding of sporangial filaments in Neopyropia yezoensis and related species.

• 한국농공학회논문집
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• 제66권4호
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• pp.27-39
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• 2024

Soil texture is determined by the proportions of sand, silt, and clay within the soil, which influence characteristics such as porosity, water retention capacity, electrical conductivity (EC), and pH. Traditional classification of soil texture requires significant sample preparation including oven drying to remove organic matter and moisture, a process that is both time-consuming and costly. This study aims to explore an alternative method by developing an AI model capable of predicting soil texture from images of pre-sorted soil samples using computer vision and deep learning technologies. Soil samples collected from agricultural fields were pre-processed using sieve analysis and the images of each sample were acquired in a controlled studio environment using a smartphone camera. Color distribution ratios based on RGB values of the images were analyzed using the OpenCV library in Python. A convolutional neural network (CNN) model, built on PyTorch, was enhanced using Digital Image Processing (DIP) techniques and then trained across nine distinct conditions to evaluate its robustness and accuracy. The model has achieved an accuracy of over 80% in classifying the images of pre-sorted soil samples, as validated by the components of the confusion matrix and measurements of the F1 score, demonstrating its potential to replace traditional experimental methods for soil texture classification. By utilizing an easily accessible tool, significant time and cost savings can be expected compared to traditional methods.

• 한국인터넷방송통신학회논문지
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• 제24권1호
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• pp.17-22
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• 2024

본 논문은 딥러닝을 기반으로 한 가상 피팅 기능을 갖춘 중고 의류 거래 시스템의 구현을 소개한다. 제안된 시스템은 사용자가 중고 의류를 온라인으로 시각적으로 착용하고 핏을 확인할 수 있는 기능을 제공한다. 이를 위해, 합성곱(CNN) 알고리즘을 사용하여 사용자의 신체 형상과 의류의 디자인을 고려한 가상 착용 모습을 생성한다. 이를 통해 구매자는 온라인에서 실제로 의류를 입기 전에 핏을 미리 확인할 수 있으며, 이는 구매 결정에 도움을 준다. 또한, 판매자는 시스템을 통해 정확한 의류 사이즈와 핏을 제시할 수 있어 구매자의 만족도를 높일 수 있다. 본 논문은 CNN 모델의 학습 절차, 시스템의 구현 방법, 사용자 피드백 등을 자세히 다루고, 실험 결과를 통해 제안된 시스템의 유효성을 입증한다.