Kisu Park;Chanseok Ryu ;Yeseong Kang;Eunri Kim;Jongchan Jeong;Jinki Park
Korean Journal of Remote Sensing
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v.39
no.5_1
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pp.521-535
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2023
When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.
Kim, Jeong-Soon;Song, Mi-Hee;Choi, Jae-Eul;Lee, Hee-Bong;Ahn, Sang-Nag
Korean Journal of Food Science and Technology
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v.40
no.6
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pp.603-610
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2008
The principal objective of current study was to evaluate the potential of near infrared reflectance spectroscopy (NIRS) as a non-destructive method for the prediction of the amylose and protein contents of un-hulled and brown rice in broad-based calibration models. The average amylose and protein content of 75 rice accessions were 20.3% and 7.1%, respectively. Additionally, the range of amylose and protein content were 16.6-24.5% and 3.8-9.3%, respectively. In total, 79 rice germplasms representing a wide range of chemical characteristics, variable physical properties, and origins were scanned via NIRS for calibration and validation equations. The un-hulled and brown rice samples evidenced distinctly different patterns in a wavelength range from 1,440 nm to 2,400 nm in the original NIR spectra. The optimal performance calibration model could be obtained by MPLS (modified partial least squares) using the first derivative method (1:4:4:1) for un-hulled rice and the second derivative method (2:4:4:1) for brown rice. The correlation coefficients $(r^2)$ and standard error of calibration (SEC) of protein and amylose contents for the un-hulled rice were 0.86, 2.48, and 0.84, 1.13, respectively. The $r^2$ and SEC of protein and amylose content for brown rice were 0.95, 1.09 and 0.94, 0.42, respectively. The results of this study suggest that the NIRS technique could be utilized as a routine procedure for the quantification of protein and amylose contents in large accessions of un-hulled rice germplasms.
Corner block with anchor bolt(CBA) joint method used in knock-down type table furniture manufacturing can reduce the packing and transporting cost. Unfortunately. it also has the disastrous defect to be loosend and unstable during the service life mainly due to fatigue and creep(repeated and prolonged loading). So 22 joint groups constructed were tested to evaluate the effect of some design factors related to the size of side rail(apron). block attachment to side rail. and the number of anchor bolt as well as the effect of the type of corner block(mitered type vs. rectangular type) Usable strength from the stiffness coefficients of each joint group were analysed with SPSS /PC+ and described as the criteria of CBA joint construction. The conclusions were as follows: The height of side rail(50, 75 and 100 mm) and the addition of polyvinyl acetate(PVAc) emulsion in the corner block attactment to side rail had the effect on raising the usable strength of CBA joint with remarkable high significance. And the effect of 2 - anchor bolts was also superior to that of 1 - bolt significantly. However. the thickness of side rail(22 mm vs. 25 mm) had no effect on the strengthening the table joint rigidity. Mitered type corner block joint appeared to he recommendable for CBA jointed table construction rather than the rectangular type one regardless of the method of block attachment to side rail. The best result identified from Duncan's multiple comparison was in the construction with 25 mm thick and 100 mm height of side rail fastened using 2 - anchor bolts in mitered type corner block. But it would be reasonable to use 22 mm thick & 75 mm high side rail and mitered corner block with PVAc emulsion & 2 bolts considering the productivity and production cost down in the MDF furniture manufacturing industries.
Polyethylene pipes has useful benefits which are anti-corrosive and flexible material, so it is used to gas pipes but also class 3 water pipes of nuclear power plant, process pipes of petrochemical plant and chemical plant. So the usage of polyethylene pipes is widely increased. But it has been limited for the usage of polyethylene, because it can not be directly detected to fusion joints by using non destructive evaluation. Polyethylene pipes are connected by two methods, one is butt fusion and the other is electrofusion. Butt fusion is widely used to connecting the pipes. It is proposed to method for determining the reliability of joints in this study that is detection of the melt flow zone at fusion joints. In this study, middle density polyethylene is used, outside diameter of the test specimen is 225mm and thickness is 20.5mm. Speed of ultrasonic of this test specimen is 2,200m/s. Test specimens were fabricated by varying the heating time which means from 0% to 130% applying time through heating plate to polyethylene for detecting melt flow zone. Also 4 additional test specimens were made, one was made that not scrapping attached surface of pipes but applying 100% of the proper heating time and the others were made to include of soil, gravel and vinly tape paper at fusion joints, that were also applied 100% of proper heating time. Ultrasonic testing to measure the melt flow zone of 20 test specimens was conducted by using 3.5MHz and 5.0MHz ultrasonic probes and melt flow zone measuring was conducted to three times at different point to one specimen. To differentiate the melt flow zone signal, post image processing was equally conducted to all test results and image levels, contrast, sharpen, threshold were adopted to all teat results and the test results were displayed gray scale. From the results, for the shorter heating times the reflection area of multiple echo have been increased, so the data was obtained from the position where it can be eliminated as much as possible. At 80% of proper heating time(168 sec.), the signal of melt flow zone was obtained clearly, so measuring could be conducted. From 7% of proper heating time(15 sec.) to shorter heating times. we could not obtain the signal because test specimen was not fused. From the result, we can verify that measuring of melt flow zone by using phased array ultrasonic imaging method is possible. And we can verify to complete and incomplete butt fusion by measuring the melt flow zone.
Journal of the Korea Institute of Building Construction
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v.22
no.6
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pp.651-662
/
2022
The electrochemical impedance spectroscopy(EIS) method was used to evaluate the concrete deterioration process related to chloride-induced steel corrosion with various corrosion levels(initiation, rust propagation and acceleration periods). The impressed current technique, with four total current levels of 0C, 13C, 65C and 130C, was used to accelerate steel corrosion in concrete cylinder samples with w/c ratio of 0.4, 0.5, and 0.6, immersed in a 0.5M NaCl solution. A series of EIS measurements was performed to monitor concrete deterioration during the accelerated corrosion test in this study. Some critical parameters of the equivalent circuit were obtained through the EIS analysis. It was observed that the charge transfer resistance(Rc) dropped sharply as the impressed current increased from 0C to 13C, indicating a value of approximately 10kΩcm2. However, the sensitivity of Rc significantly decreased when the impressed current was further increased from 13C to 130C after corrosion of steel had been initiated. Meanwhile, the double-layer capacitance value(Cdl) linearly increased from 50×10-6μF/cm2 to 250×10-6μF/cm2 as the impressed current in creased from 0C to 130C. The results in this study showed that monitoring Cdl is an effective measurement parameter for evaluating the progress of internal concrete damages(de-bonding between steel and concrete, micro-cracks, and surface-breaking cracks) induced by steel corrosion. The findings of this study provide a fundamental basis for developing an embedded sensor and signal interpretation method for monitoring concrete deterioration due to steel corrosion at various corrosion levels.
Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.
This paper is concerned with estimating equations of leaf area(A) obtained from linear measurements - leaf length(L) and leaf width(W) - on the leaves of 13 species composing a natural mixed stand in Mt. Jiri. This method is known to be rapid and non-destructive in estimating leaf area. The equation of A=bLW is frequently used in rough and rapid estimation. Each species in this study has its own coefficient b according to its geometrical leaf shape. The range of coefficients of 13 species was 0.579 to 0.717. This means that the relationship A=2/3LW is suitable to most broad leaf species in a natural mixed stand in Mt. Jiri. When more precise estimation of leaf area is needed, full regression equation is used. In this study, the form of ${\log}A=b_0+b_1{\log}LW$ was the most precise estimation equation in 8 species. In addition to this, the form of $A=b_0+b_1LW$ and $A=b_0+b_1L^2+b_2W^2$ were founded to be suitable for estimation of leaf area. In comparision of these two forms, the determination coefficient were about the same, but the F-value of the former was greater than that of the latter. Therefore, the use of the former seems to be more reliable and practical.
Kang, Kyeong-Suk;Ryu, Chan-Seok;Jang, Si-Hyeong;Kang, Ye-Seong;Jun, Sae-Rom;Park, Jun-Woo;Song, Hye-Young;Lee, Su Hwan
Korean Journal of Agricultural and Forest Meteorology
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v.21
no.4
/
pp.317-326
/
2019
Salinity which is often detected on reclaimed land is a major detrimental factor to crop growth. It would be advantageous to develop an approach for assessment of salinity and drought damages using a non-destructive method in a large landfills area. The objective of this study was to examine applicability of the decision tree classifier using imagery for classifying for spring potatoes (Solanum tuberosum) damaged by salinity or drought at vegetation growth stages. We focused on comparing the accuracies of OA (Overall accuracy) and KC (Kappa coefficient) between the simple reflectance and the band ratios minimizing the effect on the light unevenness. Spectral merging based on the commercial band width with full width at half maximum (FWHM) such as 10 nm, 25 nm, and 50 nm was also considered to invent the multispectral image sensor. In the case of the classification based on original simple reflectance with 5 nm of FWHM, the selected bands ranged from 3-13 bands with the accuracy of less than 66.7% of OA and 40.8% of KC in all FWHMs. The maximum values of OA and KC values were 78.7% and 57.7%, respectively, with 10 nm of FWHM to classify salinity and drought damages of spring potato. When the classifier was built based on the band ratios, the accuracy was more than 95% of OA and KC regardless of growth stages and FWHMs. If the multispectral image sensor is made with the six bands (the ratios of three bands) with 10 nm of FWHM, it is possible to classify the damaged spring potato by salinity or drought using the reflectance of images with 91.3% of OA and 85.0% of KC.
Ground-based optical sensing over the crop canopy provides information on the mass of plant body which reflects the light, as well as crop nitrogen content which is closely related to the greenness of plant leaves. This method has the merits of being non-destructive real-time based, and thus can be conveniently used for decision making on application of nitrogen fertilizers for crops standing in fields. In the present study relationships among leaf nitrogen content of rice canopy, crop growth status, and Normalized Difference Vegetation Index (NDVI) values were investigated. We measured Green normalized difference vegetation index($gNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$) and NDVI($({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$) were measured by using two different active sensors (Greenseeker, NTech Inc. USA). The study was conducted in the years 2005-06 during the rice growing season at the experimental plots of National Institute of Agricultural Science and Technology located at Suwon, Korea. The experiments carried out with randomized complete block design with the application of four levels of nitrogen fertilizers (0, 70, 100, 130kg N/ha) and same amount of phosphorous and potassium content of the fertilizers. gNDVI and rNDVI increased as growth advanced and reached to maximum values at around early August, G(NDVI) were a decrease in values of observed with the crop maturation. gNDVI values and leaf nitrogen content were highly correlated at early July in 2005 and 2006. On the basis of this finding we attempted to estimate the leaf N contents using gNDVI data obtained in 2005 and 2006. The determination coefficients of the linear model by gNDVI in the years 2005 and 2006 were 0.88 and 0.94, respectively. The measured and estimated leaf N contents using gNDVI values showed good agreement ($R^2=0.86^{***}$). Results from this study show that gNDVI values represent a significant positive correlation with leaf N contents and can be used to estimate leaf N before the panicle formation stage. gNDVI appeared to be a very effective parameter to estimate leaf N content the rice canopy.
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