• Journal of Life Science
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• v.10 no.1
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• pp.52-60
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• 2000

Up to now, there have been done much efforts in regard to nitrate reductase activity (NRA) of dicotyledonous herbs and important crop monocotyledons, but few to wild plants having canopy structure such as Carex. The objective of the present study are to determine: a) the optimum in vivo NR assay conditions for leaf samples of Carex species, b) changes of NRA according to section within leaf and leaf ages, c) diurnal variations. Optimized assay media of each Carex species were determined. NRA of C. rostrata adapted to oligotrophic habitats is readily saturated at lower substrate concentration than those of C. distans and C. gracilis, adapted to meso- and eutrophic habitats, respectively. All Carex species investigated have higher NRA in leaves than in roots. NRA of all species showed maximal values at the middle section of each leaf and in the youngest fully expanded leaves. Compared to C. gracilis, NR in leaves of C. distans was adapted readily to the light period. On the whole, Carex showed rather delayed diurnal variation. Even if the in vivo nitrate reductase assay based on nitrite estimation does not give an accurate estimation of total nitrate reduced, it still serves as a useful tool to find out relative differences in varying environmental conditions. Additionally, in vivo RNA measurements are helpful to understand nitrate reduction and basic nitrogen metabolism of Carex species having different canopy structure.

• Journal of Ginseng Research
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• v.41 no.4
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• pp.463-468
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• 2017

Background: Both Panax ginseng Meyer and Panax quinquefolius are obligate shade-loving plants whose natural habitats are broadleaved forests of Eastern Asia and North America. Panax species are easily damaged by photoinhibition when they are exposed to high temperatures or insufficient shade. In this study, a cytohistological study of the leaf structures of two of the most well-known Panax species was performed to better understand the physiological processes that limit photosynthesis. Methods: Leaves of ginseng plants grown in soil and hydroponic culture were sectioned for analysis. Leaf structures of both Panax species were observed using a light microscope, scanning electron microscope, and transmission electron microscope. Results: The mesostructure of both P. ginseng and P. quinquefolius frequently had one layer of non-cylindrical palisade cells and three or four layers of spongy parenchymal cells. P. quinquefolius contained a similar number of stomata in the abaxial leaf surface but more tightly appressed enlarged grana stacks than P. ginseng contained. The adaxial surface of the epidermis in P. quinquefolius showed cuticle ridges with a pattern similar to that of P. ginseng. Conclusion: The anatomical leaf structure of both P. ginseng and P. quinquefolius shows that they are typical shade-loving sciophytes. Slight differences in chloroplast structure suggests that the two different species can be authenticated using transmission electron microscopy images, and light-resistant cultivar breeding can be performed via controlling photosynthesis efficiency.

• Journal of Biosystems Engineering
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• v.32 no.4
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• pp.256-262
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• 2007

Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.

• Journal of the Korea Computer Graphics Society
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• v.21 no.5
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• pp.1-10
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• 2015

This study proposes a method of developing authoring tool that can easily and intuitively generate diverse digital leaves that compose virtual landscape. The main system of the proposed authoring tool consists of deformation method for the contour of leaf blade based on image warping, procedural modeling of leaf vein and visualization method based on mathematical model that expresses the color and brightness of leaves. First, the proposed authoring tool receives leaf input image and searches for contour information on the leaf blades. It then designs leaf blade deformation method that can generate diverse shapes of leaf blades in an intuitive structure using feature-based image warping. Based on the computed leaf blade contour, the system implements the generalized procedural modeling method suitable for the authoring tool that generates natural vein patterns appropriate for the leaf blade shape. Finally, the system applies visualization function that can express color and brightness of leaves and their changes over time using a mathematical model based on convolution sums of divisor functions. This paper provides texture support function so that the digital leaves that were generated using the proposed authoring tool can be used in a variety of three-dimensional digital contents field.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.261-273
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• 2004

Advances in information and communication technologies have been creating new classes of applications in the area of databases. For example, in moving object databases, which track positions of a lot of objects, or stream databases, which process data streams from a lot of sensors, data Processed in such database systems are usually changed very rapidly and continuously. However, traditional database systems have a problem in processing these rapidly and continuously changing data because they suppose that a data item stored in the database remains constant until It is explicitly modified. The problem becomes more serious in the R-tree, which is a typical index structure for multidimensional data, because modifying data in the R-tree can generate cascading node splits or merges. To process frequent updates more efficiently, we propose a novel update technique for the R-tree, which we call the leaf-update technique. If a new value of a data item lies within the leaf MBR that the data item belongs, the leaf-update technique changes the leaf node only, not whole of the tree. Using this leaf-update manner and the leaf-access hash table for direct access to leaf nodes, the proposed technique can reduce update cost greatly. In addition, the leaf-update technique can be adopted in diverse variants of the R-tree and various applications that use the R-tree since it is based on the R-tree and it guarantees the correctness of the R-tree. In this paper, we prove the effectiveness of the leaf-update techniques theoretically and present experimental results that show that our technique outperforms traditional one.

• Journal of Bio-Environment Control
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• v.25 no.3
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• pp.146-152
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• 2016

Due to complicate canopy structures of Irwin mangoes grown in greenhouses, it is difficult to determine their growth parameters accurately. Leaf area, leaf fresh weight, and leaf dry weight are widely used as indicators to diagnose the tree growth. Therefore, it is necessary to establish models that can non-destructively estimate these growth indicators. The objective of this study was to establish regression models to estimate leaf area, leaf fresh weight, and leaf dry weight of Irwin mangoes (Mangifera indica L. cv. Irwin) by using leaf length, leaf width, petiole length, and SPAD value. The input values of leaf length, leaf width, petiole length, and SPAD value of 6-year old Irwin mangoes were measured, and the corresponding output values of leaf area, leaf fresh weight, and leaf dry weight were also measured. After 14 models were selected among the existing models, coefficients of the models were estimated by regression analysis. Three models with higher $R^2$ and lower RMSE values selected. In validation the $R^2$ values for the selected models were 0.967, 0.743, and 0.567 in the leaf area, leaf fresh weight, and leaf dry weight models, respectively. It is concluded that this models will be helpful to conveniently diagnose the growth of the Irwin mango.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.8-16
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• 2022

In this paper, we propose a method of reconstructing the file system to obtain digital forensics information from the APFS file system when meta information that can know the structure of the file system is deleted due to partial damage to the disk. This method is to reconstruct the tree structure of the file system by only retrieving the B-tree node where file/directory information is stored. This method is not a method of constructing nodes based on structural information such as Container Superblock (NXSB) and Volume Checkpoint Superblock (APSB), and B-tree root and leaf node information. The entire disk cluster is traversed to find scattered B-tree leaf nodes and to gather all the information in the file system to build information. It is a method of reconstructing a tree structure of a file/directory based on refined essential data by removing duplicate data. We demonstrate that the proposed method is valid through the results of applying the proposed method by generating numbers of user files and directories.

• KSBB Journal
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• v.28 no.6
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• pp.356-365
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• 2013

The novel Aloe gels were prepared with dewatering and impregnation by soaking (DIS) processing of Aloe vera leaf slice at four different temperatures (25, 35, 45 and $55^{\circ}C$), using dehydration solution of 40% (w/v) polyethylene glycol (PEG4000). The PEG-impregnation to Aloe vera leaf slice during DIS was observed depending on immersion temperature, and the PEG-impregnated Aloe vera gel (PEG-i-AVG) obtained was characterized using $^1H$ NMR, FT-IR, GPC, XRD and TGA. The PEG-i-AVG had the higher levels of Aloe bioactives (glucomannan and O-acetyl contents) and better quality indices by $^1H$ NMR and FT-IR spectroscopy than those of native Aloe gel. Also, the obtained Aloe gel maintained the bimodal patterns in higher molecular weight region by GPC indicating no degradation of polysaccharide from native Aloe gel. The result observed by SEM confirmed a surface modification by forming the porous structure, and TGA result exhibited better thermal stability than that of native Aloe gel. XRD result revealed that the crystalline structure in Aloe gel was led by incorporation of PEG. Significant decrease of %insolubility and high enhancement of water solubility index were observed, respectively, and highly ordered conformation such as a helix structure was also indicated by Congo red reaction. We concluded that the modification effect for enhancing function of native Aloe gel was successfully obtained by DIS process using PEG as a dehydrating agent. These results suggested that this DIS process had a high potential for developing a new minimally processed product from Aloe vera leaf.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.6
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• pp.771-780
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• 2010

This paper describes the design process of a six-component force/torque (F/T) sensor. The new six-component F/T sensor having leaf spring ends has been developed using a cross beam structure as the basic sensing element. Fundamental strain analysis of both ends fixed beam having a leaf spring structure is performed by finite element analysis. In order to obtain similar output sensing strains from the six component loads and minimize coupling strains, the optimal location of strain gages is determined and the strain gages are connected so that the bridge circuits with four strain gages would be balanced. Using leaf spring ends instead of rigid fixed ends, remarkable increment in output sensing strain can be achieved for two component forces. Several modifications in design result in a similar sensing strain of approximately $400\;{\mu}m/m$ for the six-component forces and moments, and a reduced coupling strain of $0\;{\mu}m/m$ between the forces and moments.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1250-1257
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• 2020

The early detection of diseases is important in agriculture because diseases are major threats of reducing crop yield for farmers. The shape and color of plant leaf are changed differently according to the disease. So we can detect and estimate the disease by inspecting the visual feature in leaf. This study presents a vision-based leaf classification method for detecting the diseases of tomato crop. ResNet-50 model was used to extract the visual feature in leaf and classify the disease of tomato crop, since the model showed the higher accuracy than the other ResNet models with different depths. We propose a new ensemble approach using several DCNN classifiers that have the same structure but have been trained at different ranges in the DCNN layers. Experimental result achieved accuracy of 97.19% for PlantVillage dataset. It validates that the proposed method effectively classify the disease of tomato crop.