• 농업과학연구
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• 제48권1호
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• pp.179-189
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• 2021

Plants need essential mineral elements to favorably develop and to complete their life cycle. Despite the irreplaceable roles of microelements, they are often ignored due to the relative importance of macroelements with their influence on crop growth and development. We focused on the changes in primary metabolites in the leaves and roots of bell pepper plants under 6 microelements-deficient conditions: Copper (Cu), Zinc (Zn), Iron (Fe), Manganese (Mn), Boron (B) and Molybdenum (Mo). Bell pepper plants were grown in hydroponic containers, and individual elements were adjusted to 1/10-strength of Hoagland nutrient solution. A remarkable perturbation in the abundance of the primary metabolites was observed for the Fe and B and the Mn and B deficiencies in the leaves and roots, respectively. The metabolites with up-accumulation in the Fe-deficient leaves were glucose, fructose, xylose, glutamine, asparagine and serine. In contrast, the Mn deficiency also resulted in a higher accumulation of glucose, fructose, xylose, galactose, serine, glycine, β-alanine, alanine and valine in the roots. The B deficiency noticeably accumulated alanine, valine and phenylalanine in the roots while it showed a substantial decrease in glucose, fructose and xylose. These results show that the primary metabolism could be seriously disturbed due to a microelement deficiency, and the alteration may be either the specific or adaptive responses of bell pepper plants.

• Journal of Ecology and Environment
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• 제45권2호
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• pp.78-87
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• 2021

Background: To understand shade and wind effects on seedling traits of common reed (Phragmites australis), we conducted a mesocosm experiment manipulating day length (10 h daytime a day as open canopy conditions or 6 h daytime a day as partially closed canopy conditions) and wind speed (0 m/s as windless conditions or 4 m/s as windy conditions). Results: Most values of functional traits of leaf blades, culms, and biomass production of P. australis were higher under long day length. In particular, we found sole positive effects of long day length in several functional traits such as internode and leaf blade lengths and the values of above-ground dry weight (DW), rhizome DW, and total DW. Wind-induced effects on functional traits were different depending on functional traits. Wind contributed to relatively low values of chlorophyll contents, angles between leaf blades, mean culm height, and maximum culm height. In contrast, wind contributed to relatively high values of culm density and below-ground DW. Conclusions: Although wind appeared to inhibit the vertical growth of P. australis through physiological and morphological changes in leaf blades, it seemed that P. australis might compensate the inhibited vertical growth with increased horizontal growth such as more numerous culms, indicating a highly adaptive characteristic of P. australis in terms of phenotypic plasticity under windy environments.

• Journal of Multimedia Information System
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• 제8권2호
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• pp.79-84
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• 2021

Detecting brain tumors of different sizes is a challenging task. This study aimed to identify brain tumors using detection algorithms. Most studies in this area use segmentation; however, we utilized detection owing to its advantages. Data were obtained from 64 patients and 11,200 MR images. The deep learning model used was RetinaNet, which is based on ResNet152. The model learned three different types of pre-processing images: normal, general histogram equalization, and contrast-limited adaptive histogram equalization (CLAHE). The three types of images were compared to determine the pre-processing technique that exhibits the best performance in the deep learning algorithms. During pre-processing, we converted the MR images from DICOM to JPG format. Additionally, we regulated the window level and width. The model compared the pre-processed images to determine which images showed adequate performance; CLAHE showed the best performance, with a sensitivity of 81.79%. The RetinaNet model for detecting brain tumors through deep learning algorithms demonstrated satisfactory performance in finding lesions. In future, we plan to develop a new model for improving the detection performance using well-processed data. This study lays the groundwork for future detection technologies that can help doctors find lesions more easily in clinical tasks.

• International Journal of Industrial Entomology and Biomaterials
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• 제43권2호
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• pp.37-44
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• 2021

Mulberry silkworm is classified into uni, bi and multivoltine based on the frequency of diapause incidence. The variation in the incidence of diapause in bivoltine silkworm provides a unique opportunity to study the process of evolution of adaptive plasticity towards seasonal variations. The diapause expression in bivoltine silkworm is highly variable and is determined by environmental factors experienced by the maternal generation. Diapause in natural populations is functionally associated with the overwintering mechanism that facilitates survival in harsh winter conditions. In contrast, under standard commercial rearing conditions, the domesticated bivoltine silkworm is known to enter diapause in every generation. This paper presents a short review of the literature dealing with the role of temperature, photoperiod, diapause hormone and its receptor in diapause induction. Also, we briefly review the incidence of non-diapause eggs in bivoltine silkworm under controlled conditions.

• Structural Engineering and Mechanics
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• 제80권6호
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• pp.711-726
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• 2021

This paper presents a multiple parameters-based recursive methodology for the reliability quantification of civil structures subjected to meteorological disasters. Recognizing the challenge associated with characterizing at a single stroke all the meteorological disasters that may hit a structure during its service life, the proposed methodology by contrast features a multiparameter recursive mechanism to describe the meteorological demand of the structure. The benefit of the arrangements is that the essentially inevitable deviation of the practically observed meteorological data from those in the existing model can be mitigated in an adaptive manner. In particular, the implications of potential climate change to the relevant reliability of civil structures are allowed for. The application of the formulated methodology of recursive reliability quantification is illustrated by first considering the reliability quantification of a linear shear frame against simulated strong wind loads. A parametric study is engaged in this application to examine the effect of some hyperparameters in the configured hierarchical model. Further, the application is extended to a nonlinear hysteretic shear frame involving some field-observed cyclone data, and the incompleteness of the relevant structural diagnosis data that may arise in reality is taken into account. Also investigated is another application scenario where the reliability of a building envelope is assessed under hailstone impacts, and the emphasis is to demonstrate the recursive incorporation of newly obtained meteorological data.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.119-126
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• 2024

Disease caused by the coronavirus (COVID-19) is sweeping the globe. There are numerous methods for identifying this disease using a chest imaging. Computerized Tomography (CT) chest scans are used in this study to detect COVID-19 disease using a pretrain Convolutional Neural Network (CNN) ResNet50. This model is based on image dataset taken from two hospitals and used to identify Covid-19 illnesses. The pre-train CNN (ResNet50) architecture was used for feature extraction, and then fully connected layers were used for classification, yielding 97%, 96%, 96%, 96% for accuracy, precision, recall, and F1-score, respectively. When combining the feature extraction techniques with the Back Propagation Neural Network (BPNN), it produced accuracy, precision, recall, and F1-scores of 92.5%, 83%, 92%, and 87.3%. In our suggested approach, we use a preprocessing phase to improve accuracy. The image was enhanced using the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm, which was followed by cropping the image before feature extraction with ResNet50. Finally, a fully connected layer was added for classification, with results of 99.1%, 98.7%, 99%, 98.8% in terms of accuracy, precision, recall, and F1-score.

• IMMUNE NETWORK
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• 제22권4호
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• pp.32.1-32.20
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• 2022

Sjögren syndrome (SS) is a chronic autoimmune disorder that primarily targets the salivary and lacrimal glands. The pathology of these exocrine glands is characterized by periductal focal lymphocytic infiltrates, and both T cell-mediated tissue injury and autoantibodies that interfere with the secretion process underlie glandular hypofunction. In addition to these adaptive mechanisms, multiple innate immune pathways are dysregulated, particularly in the salivary gland epithelium. Our understanding of the pathogenetic mechanisms of SS has substantially improved during the past decade. In contrast to viral infection, bacterial infection has never been considered in the pathogenesis of SS. In this review, oral dysbiosis associated with SS and evidence for bacterial infection of the salivary glands in SS were reviewed. In addition, the potential contributions of bacterial infection to innate activation of ductal epithelial cells, plasmacytoid dendritic cells, and B cells and to the breach of tolerance via bystander activation of autoreactive T cells and molecular mimicry were discussed. The added roles of bacteria may extend our understanding of the pathogenetic mechanisms and therapeutic approaches for this autoimmune exocrinopathy.

• 대한전자공학회논문지SP
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• 제44권2호
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• pp.116-125
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• 2007

본 논문에서는 군대 주둔지 교도소 전략적 산업구조물 등 중요한 지역의 보안을 위한 조명환경 적응적인 실시간 영상 감시 시스템을 제안한다. 제안하는 시스템은 밝은 환경에서 뿐만 아니라 객체 판별이 어려운 어두운 환경에서도 객체 추출이 추적이 가능하도록 구현하며 그 절차는 다음과 같다. 첫 번째 단계에서는 입력 영상의 분포를 판별하여 전처리 여부를 판단하고 입력 영상이 어두워 객체 탐지가 어렵다고 판단되는 경우에는 Multi-scale Reinex Color Restoration (MSRCR) 과정을 거처 보정된 입력 영상을 얻는다. 두 번째 단계인 객체 정보 획득 과정에서는 정확한 객체의 추출을 위해 보정된 배경영상과 입력 영상과의 차영상을 이용하여 객체를 탐지하고 이진화 및 모폴로지 등 기본적인 영상처리 작업을 통하여 정확하게 객체를 추출한다. 마지막 단계에서는 추출된 객체의 중심점을 이용하여 좀 더 정확하게 객체를 추적할 수 있도록 한다. 실험 결과에서 제안하는 시스템은 어두운 환경에서 객체의 빠른 움직임에도 불구하고 효율적인 객체 탐지 및 추적을 수행한다.

• 대한디지털의료영상학회논문지
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• 제16권2호
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• pp.9-14
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• 2014

Purpose: The purpose of this study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying Filtered Back Projection(FBP), the existing test method, and Adaptive Statistical Iterative Reconstruction(ASIR) with different values of tube voltage during the Low Dose Computed Tomography(LDCT). Materials and Methods: With the image reconstruction method as basis, Chest Phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of Tube Voltage (100kVp, 120kVp). For image evaluation, Back ground noise, Signal to Noise ratio(SNR) and Contrast to Noise ratio(CNR) were measured, and, for dose evaluation, CTDIvol and DLP were measured respectively. The statistical analysis was tested with SPSS(ver. 22.0), followed by ANOVA Test conducted after normality test and homogeneity test. (p<0.05). Results: In terms of image evaluation, there was no outstanding difference in Ascending Aorta(AA) SNR and Infraspinatus Muscle(IM) SNR with the different values of ASIR application(p<0.05), but a significant difference with the different amount of tube voltage(p>0.05). Also, there wasn't noticeable change in CNR with ASIR and different amount of Tube Voltage (p<0.05). However, in terms of dose evaluation, CTDIvol and DLP showed contrasting results(p<0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120kVp were 2.6mGy with No-ASIR and 2.17mGy with 20%-ASIR respectively, decreased by 0.43mGy, and the values with 100kVp were 1.61mGy with No-ASIR and 1.34mGy with 20%-ASIR, decreased by 0.27mGy. In terms of DLP, the measured values with 120kVp were $103.21mGy{\cdot}cm$ with No-ASIR and $85.94mGy{\cdot}cm$ with 20%-ASIR, decreased by $17.27mGy{\cdot}cm$(about 16.7%), and the values with 100kVp were $63.84mGy{\cdot}cm$ with No-ASIR and $53.25mGy{\cdot}cm$ with 20%-ASIR, a decrease by $10.62mGy{\cdot}cm$(about 16.7%). Conclusion: At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise. For the future, through the result of the experiment, it is considered that the method above would be recommended for follow-up patients or those who get health checkup as long as there is no interference on the process of diagnosis due to the characteristics of Low Dose examination.

• 한국환경생태학회지
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• 제35권4호
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• pp.398-407
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• 2021

한반도해송숲의 지형환경, 기상조건, 토양 이화학적 성질과 곰솔의 생육상태를 조사해, 이곳 곰솔의 수세약화 원인을 찾아내고자 했다. 곰솔의 수세가 불량하거나 고사한 지역(수세불량지)과 대조구로서 곰솔의 생육상황이 양호한 지역(수세양호지)으로 나눠 조사했다. 그 결과, 수세불량지의 입목밀도는 수세양호지보다 유의적으로 높았지만, 수관폭은 반대로 수세양호지에서 더 넓었다. 고사목 개체수와 입목밀도는 서로 부(-)의 상관관계를 보였고, 또 입목밀도와 흉고직경·수고·수관고(crown height)·수관폭 사이에서는 부(-)의 상관관계를 보였다. 즉, 입목밀도가 높으면 개체의 수관이 겹쳐 하부 가지가 죽어 수관고와 수관폭이 작아졌다. 이에 엽량 감소에 따른 광합성량이 줄어들어 수고와 직경의 생장량이 적어졌다고 본다. 이로 인해 수세가 약해지면서 해안사구라서 수분·양분의 부족과 강한 조풍 등의 환경압이 가중되어 해안가 근처의 곰솔이 대규모로 죽은 것으로 판단된다. 한반도해송숲의 고사목 발생과 수세약화 원인은 복합적이지만, 곰솔 생장에 따른 적정한 입목밀도 관리 부족이라는 내부요인을 제1 요인으로 꼽을 수 있다. 또 곰솔 생육에 불리한 토양조건과 조풍, 강풍 등의 환경압을 제2 요인이라고 볼 수 있다.