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피우미 사우미야 쿠마라테나,조영열 (사) 한국생물환경조절학회 2024 생물환경조절학회지 Vol.33 No.1
이 연구에서는 Inception V3, SqueezeNet(local), VGG-16, Painters 및 DeepLoc의 다섯 가지 인공지능(AI) 모델을 사용하여 차나무 잎의 병해를 분류하였다. 여덟 가지 이미지 카테고리를 사용하였는데, healthy, algal leaf spot, anthracnose, bird’s eye spot, brown blight, gray blight, red leaf spot, and white spot였다. 이 연구에서 사용한 소프트웨어는 데이터 시각적 프로그래밍을 위한 파이썬 라이브러리로 작동하는 Orange3였다. 이는 데이터를 시각적으로조작하여 분석하기 위한 워크플로를 생성하는 인터페이스를 통해 작동되었다. 각 AI 모델의 정확도로 최적의 AI 모델을 선택하였다. 모든 모델은 Adam 최적화, ReLU 활성화 함수, 은닉 레이어에 100개의 뉴런, 신경망의 최대 반복횟수가 200회, 그리고 0.0001 정규화를 사용하여 훈련되었다. Orange3 기능을 확장하기 위해 새로운 이미지 분석Add-on을 설치하였다. 훈련 모델에서는 이미지 가져오기(import image), 이미지 임베딩(image embedding), 신경망(neural network), 테스트 및 점수(test and score), 혼동 행렬(confusion matrix) 위젯이 사용되었으며, 예측에는 이미지 가져오기(import image), 이미지 임베딩(image embedding), 예측(prediction) 및 이미지 뷰어(image viewer) 위젯이 사용되었다. 다섯 AI 모델[Inception V3, SqueezeNet(로컬), VGG-16, Painters 및 DeepLoc]의 신경망 정밀도는 각각 0.807, 0.901, 0.780, 0.800 및 0.771이었다. 결론적으로 SqueezeNet(local) 모델이 차나무 잎 이미지를 사용하여 차병해 탐색을 위한 최적 AI 모델로 선택되었으며, 정확도와 혼동 행렬을 통해 뛰어난 성능을 보였다. In this study, five artificial intelligence (AI) models: Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc were used to classify tea leaf diseases. Eight image categories were used: healthy, algal leaf spot, anthracnose, bird’s eye spot, brown blight, gray blight, red leaf spot, and white spot. Software used in this study was Orange 3 which functions as a Python library for visual programming, that operates through an interface that generates workflows to visually manipulate and analyze the data. The precision of each AI model was recorded to select the ideal AI model. All models were trained using the Adam solver, rectified linear unit activation function, 100 neurons in the hidden layers, 200 maximum number of iterations in the neural network, and 0.0001 regularizations. To extend the functionality of Orange 3, new add-ons can be installed and, this study image analytics add-on was newly added which is required for image analysis. For the training model, the import image, image embedding, neural network, test and score, and confusion matrix widgets were used, whereas the import images, image embedding, predictions, and image viewer widgets were used for the prediction. Precisions of the neural networks of the five AI models (Inception v3, SqueezeNet (local), VGG-16, Painters, and DeepLoc) were 0.807, 0.901, 0.780, 0.800, and 0.771, respectively. Finally, the SqueezeNet (local) model was selected as the optimal AI model for the detection of tea diseases using tea leaf images owing to its high precision and good performance throughout the confusion matrix.
Kim-Ngan T. Tran,쿠마라벨 아쇽 쿠마,정재훈,홍순호 한국생물공학회 2022 Biotechnology and Bioprocess Engineering Vol.27 No.2
L-serine is a non-essential amino acid which has a wide range of applications and plays an important role as a building block for growing cells. L-serine microbial development is considered a difficult activity due to Lserine's central role in cellular metabolism with 2 main degradation pathways. A novel strategy is needed to overcome the L-serine degradation pathway and low Lserine tolerance of Escherichia coli for efficient L-serine production. A synthetic protein scaffold between SerB and EamA was introduced in this study to physically combine the two enzymes. Through this strategy, the L-serine production is more efficient than in competing pathways. By the introduction of a synthetic protein scaffold without metabolic pathway engineering or addition of glycine, 1.8 g/L of L-serine was produced at pH7 and 37°C. By fermentation, 9.4 g/L of serine was produced at a yield of 0.34 mol/mol glucose. These results suggest that the carbon flux was successfully directed to the L-serine secretion pathway without knocking out a competing pathway or adding expensive glycine.
Impact of the Synthetic Scaffold Strategy on the Metabolic Pathway Engineering
Kim-Ngan T. Tran,쿠마라벨 아쇽 쿠마,홍순호 한국생물공학회 2023 Biotechnology and Bioprocess Engineering Vol.28 No.3
For the development of the efficient bio-refinery process or biochemical producer, metabolic engineering has become an attractive choice recently. However, engineered metabolic pathways often suffer from flux imbalances due to a lack of corresponding regulatory mechanisms associated with natural metabolism. The interaction among different enzymes within a metabolic pathway plays an important role in regulating the efficiency of metabolic processes. Consequently, the creation of protein scaffolds has helped with the spatial co-localization of proteins in metabolic engineering. Research on protein scaffolds indicated scaffold systems may enhance metabolic productivity further. In this review, the specificity, selectivity, and regulatory mechanisms of protein-protein interactions are discussed in the context of the important effects that they exert on various biological processes.
완전제어형 식물공장에서 재배되는 프렌치매리골드의 화아분화를 위한 최적의 광주기 구명
곽나영,성보현,피우미 사우미야 쿠마라테나,조영열 (사) 한국생물환경조절학회 2024 생물환경조절학회지 Vol.33 No.1
작물을 재배하는 데 필요한 여러 가지 환경 조건 중 광은 개화와 밀접한 연관이 있다. 본 연구는 식용화, 매리골드 화아분화에 영향을 주는 최적의 광주기를 구명하여 완전제어형 식물공장에서 효율적으로 재배하기 위해 진행되었다. 실험에 사용된 광주기는 4, 8, 12, 16시간, 총 4가지로 설정하였다. 매리골드 ‘듀란고 레드’ 종자를 우레탄 스펀지에 파종한 직후부터광주기를 처리하였다. 화아분화는 꽃봉오리가 약 2mm 이상일 때 화아분화가 되었다고 정의하였고, 2-3일 간격으로 조사하였다. 생육 조사는 지상부의 생체중, 건물중, 초장, 엽면적을 조사하였다. 최적의 광주기는 식물체의 50%가 화아분화 된 날을 기준으로 정의하였다. 4시간 처리구에서는 식물체가 제대로 자라지 못하며 화아도 형성되지 않았다. 8시간 이상의 처리구에서부터 식물체가 정상적으로 생장하고 화아분화가 이루어졌지만, 8시간 처리구는 12시간 이상의 처리구에 비해 화아분화가 더디게 일어났다. 반면에 12시간 처리구와 16 시간 처리구는 서로 유의하지 않은 결과를 보였다. 모든 생육조사 항목에서 16시간 광주기 처리구가 가장 높은 값을 나타냈으나 지상부의 건물중과 엽면적을 제외한 나머지 항목에서12시간 처리구와 유의하지 않았다. 실험 결과에 따르면, 8시간 광주기에서도 화아분화가 일어났지만, 화아형성까지의 시간이 12시간 이상의 광주기일 때보다 더 많이 소요되었으며, 식물체의 생육 또한 12시간 이상의 광주기를 조사받은 식물체보다 낮게 나타났다. 본 실험에서 에너지 소비량을 고려한최적의 매리골드 ‘듀란고 레드’의 광주기는 12시간으로 판단된다. Among the various environmental conditions necessary for growing crops, light is closely related to the anthesis. This study aimed to determine the optimal photoperiod affecting floral differentiation in an edible flower, marigold, to efficiently cultivate the crops in a closed-type plant factory. The experiment was conducted with photoperiods of 4, 8, 12, and 16 hours. French marigold (Tagetes patula L.) ‘Durango Red’ seeds were sown in polyurethane sponges, and the photoperiod treatments were applied immediately. The extent of floral differentiation was examined at 2-3 day intervals, defined as the visible appearance of flower buds at least 2 mm in size. The growth parameters such as shoot fresh weight and dry weight, height, and leaf area were measured. The optimal photoperiod was determined based on the days when the floral differentiation had occurred in 50% of the total plants. In the 4-hour treatment, proper growth and flower buds did not appear. From the 8-hour treatment, the plant grew normally, and floral differentiation occurred, however, the 8-hour treatment showed the slowest floral differentiation compared to the 12 hours treatments or more. The 12- and 16-hour treatments didn’t show significant differences in floral differentiation. While the 16-hour treatment exhibited the highest results in all growth parameters, it was not significantly different from the 12-hour treatment except for shoot dry weight and leaf area. According to the results, 8 hours of photoperiod induced floral differentiation. However, more time was required for flower bud formation, and plant growth was significantly lower compared to photoperiods of 12 hours or more. Considering the energy consumption and its growth, the optimal photoperiod for marigold was 12 hours.
공구 형상에 따른 CFRP의 가공결함 제거에 관한 연구
박기문(Ki Moon Park),고태조(Tae Jo Ko),위전(Zhen Yu),띠루말라이 쿠마란(Thirumalai Kumaran S) 한국기계가공학회 2017 한국기계가공학회지 Vol.16 No.4
CFRP(Carbon Fiber Reinforced Plastics) has many industrial applications due to its low weight and high strength properties. Due to its superior properties, for example, excellent resistance to fatigue wear, corrosion, and breakage from fatigue, it has been widely applicable to aircraft, automotive, and medical industries and so on. The main machining for CFRP is drilling, and route milling. In case of drilling, the machining defects such as the delamination of each layer, uncut fiber, resin burning, spalling, and exit burrs are inevitable. The issue to remove such kind of defects is necessary to make CFRP parts successful. From this point of view, this paper investigates the removal effectiveness of machining defects existing at exit region with different type of tool geometries. Consequently, based on the experiments, the tool geometry is most impact factor to remove uncut fiber or resin.