• Journal of Biosystems Engineering
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• v.40 no.1
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• pp.89-93
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• 2015

Purpose: Machine vision-based image processing methods can be useful for estimating the fresh weight of plants. This study analyzes the ability of two different image processing methods, i.e., morphological and pixel-value analysis methods, to measure the fresh weight of lettuce grown in a closed hydroponic system. Methods: Polynomial calibration models are developed to relate the number of pixels in images of leaf areas determined by the image processing methods to actual fresh weights of lettuce measured with a digital scale. The study analyzes the ability of the machine vision- based calibration models to predict the fresh weights of lettuce. Results: The coefficients of determination (> 0.93) and standard error of prediction (SEP) values (< 5 g) generated by the two developed models imply that the image processing methods could accurately estimate the fresh weight of each lettuce plant during its growing stage. Conclusions: The results demonstrate that the growing status of a lettuce plant can be estimated using leaf images and regression equations. This shows that a machine vision system installed on a plant growing bed can potentially be used to determine optimal harvest timings for efficient plant growth management.

• Korean Journal of Computational Design and Engineering
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• v.17 no.1
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• pp.35-44
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• 2012

Many automobile manufacturers are doing experiment on manufacturing environments by using an augmented reality technology. However, system layout and process simulation by using the virtual reality technology have been performed actively more than by using the augmented reality technology in practical use so far. Existing automobile assembly by using the augmented reality requires the precise calibrating work after setting the robot because the existing augmented reality system for the automobile assembly system configuration does not include the end tip deflection and the robot joints deflection due to the heavy weight of product and gripper. Because the robot is used mostly at the automobile assembly, the deflection problem of the robot joint and the product in the existing augmented reality system need to be improved. Moreover camera lens calibration has to be performed precisely to use augmented reality. In order to improve this problem, this paper introduces a method of the software based calibration to apply the augmented reality effectively to the automobile assembly system. On the other hand, the camera lens calibration module and the direct compensation module of the virtual object displacement for the augmented reality were designed and implemented. Furthermore, the developed automobile assembly system oriented AR-system was verified by the practical test.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.5-10
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• 2014

It is possible for the nation's largest flowmeter calibration system in K-water to calibrate flow rate up to $2,700m^3/h$ and diameter 800mm. However, the calibration and measurement capability of K-water's system is not satisfied in comparison with other developed countries. In this study, we find the dominant factors related to the uncertainty of weight and time measurement for gravimetric flowmeter calibration system. As a results of improving the system, the combined standard uncertainty has been improved $1.099{\times}10^{-3}$ to $2.332{\times}10^{-4}$. So calibration and measurement capability got 0.08 percent of the relative expanded uncertainty for maximum flow rate using the coverage factor(k=2).

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.479-489
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• 2002

The case which applies two-phase sampling to stratification and nonresponse problem, it is a poweful and effective technique. In this paper we study the calibration estimator and its variance estimator for the population total using two-phase sampling method according to the of auxiliary information for population and sample having strong correlation with an interested variable in unit nonresponse situation. The auxiliary information that available both at first-phase and second-phase sampling can be used to improve weights by the calibration procedure. A weight which corresponds to the product of sampling weights and response probability is calculated at each phase of sampling.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.155-162
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• 2006

Deflections of jointed concrete pavements at test road are monitored during 48 hours. And methods of calibration with respect to curling deflections are suggested. Relations between deflection ratio of center to joint at test time and deflection ratio of center at test time to center at reference time are described by regression. From deflections at test time, deflections transformed to reference time which gives minimum deflections in a day are estimated through regression curves and concluded to propose as a alternative method of curling calibration with more data accumulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.877-878
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• 2012

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1512-1512
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• 2001

The University of Cordoba conducts since 1991 a breeding program to obtain new olive cultivars from intraspecific crosses. The objective is to obtain new early bearing and high-quality cultivars. In plant breeding, many seedlings must be tested to increased the chance of getting desirable genotypes. Therefore, fast, cheap and accurate methods of analysis are necessary. The conventional laboratory techniques are costly and time-consuming. Near Infrared Spectroscopy (NIRS) can satisfy the characteristics requested by plant breeders and offers many advantages such as the simultaneous analysis of many traits and cheap cost. The objective of this work was to asses the performance of NIRS to estimate oil fruit components (fruit weight, flesh moisture, flesh/stone ratio and oil flesh content in dry weight basis) and fatty acid composition in olive fruit. Genotypes from reciprocal crosses between ‘Arbequina’, ‘Frantoio’ and ‘Picual’ cultivars have been used in this study. A total of 287 samples, each from a single plant, were scanned using a DA-7000 Diode Array VIS/NIR Analysis System (Perten Instruments), which covers the visible and NIR range from 400-1700 nm. All samples were analysed for fatty acid composition (gas chromatography) and 220 for oil fruit components (oil content by nuclear magnetic resonance), 70% and 30% of samples were randomly assign for the calibration and validation sets respectively. The preliminary results shows that calibration for palmitic, oleic and linoleic acids were highly accurate with calibration and validation values of $r^2$ from 0.85 to 0.95 and 0.76 to 0.91 respectively. Calibration for palmitoleic and estearic acids were less accurate, probably because of the narrow range of variability available for these fatty acids. For the oil fruit components, calibration were high accurate for flesh moisture and oil flesh content in dry weight basis ($r^2$ higher than 0.90 in both calibration and validation sets) and less accurate for the other characteristics evaluated. The first results obtained indicate that NIRS analysis could be an ideal technique to reduce the cost, time and chemical wasted necessary to evaluate a large number of genotypes and it is accurate enough to use for pre-selecting genotypes in a breeding program.

• International Journal of Railway
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• v.9 no.1
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• pp.1-9
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• 2016

In order to achieve a comprehensive utilization of railway networks, it is necessary to accurately assess the timetable indicators that effect the train operation. This paper describes the parameter calibration for two timetable indicators: scheduled running time and scheduled dwell time. For the scheduled running time, an existing model is employed and the single timetable parameter (percentage of minimum running time) in that model is optimized. For the scheduled dwell time, two intrinsic characteristics: the significance of stations and the average headway at each station are proposed firstly to form a new model, and the corresponding timetable parameters (the weight of the significance and the weight of the average headway) are calibrated subsequently. The Floyd Algorithm is used to obtain the connectivity among stations, which represents the significance of the stations. A case study is conducted in a light rail transportation system with 17 underground stations. The results of this research show that the optimal value of the scheduled running time parameter can be automatically determined, and the proposed model for the scheduled dwell time works well with a high coefficient of determination and low relative root mean square error through the leave-one-out validation.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.2
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• pp.133-141
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• 2011

In this study, different calibration approaches for reduced sulfur compounds (RSCs) were investigated by using thermal desorption coupled with gas chromatography (GC) and pulsed flame photometric detection (PFPD). To evaluate the effects of calibration procedures, gaseous standards of 4 RSCs ($H_2S$, $CH_3SH$, DMS, and DMDS) prepared at 10 ppm level were analyzed at 7 loading injection volumes (40, 60, 80, 100, 160, 240, and 320 ${\mu}L$). The results were then compared with calibration curves made with the Z (zero offset) and N (non-zero offset) method. The concentrations of unknown samples were then quantified by using R (ratio) method in which the slope values are compared between standards and samples. Secondly, in A (average) method, results obtained from a multi-point analysis of unknown samples were also averaged to extract representative values for each sample. Results of both experiments showed that analytical error of low molecular weight components (such as $H_2S$ and $CH_3SH$) was greatly expanded with the Z method. In conclusion, the combined application of N-A method was the more realistic approach to reduce biases in the quantification of RSCs.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.95-104
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• 2020

The purpose of this study is to develop a pipe type soil sampler that can easily collect soil cross section servey and soil samples to conduct ecological environment surveys while minimizing ecological disturbance in the area subject to soil survey. Furthermore, this study develop the exponential type estimation specific weight formula (ESWF) that uses pipe type soil sampler to easily carry out soil cross section survey and soil sample while estimating the specific weight of the area using water content and soil sample length variation ratio (SLVRs) and to obtain apparent specific gravity, hardness, and max. porosity which are used as growth of corps and ecological environment index. The calibration results of ESWF showed a high degree of significance, with NSE for actual specific weight (γ₀) and calibration estimation specific weight (γ_ec) 0.95, R² for 0.954, and RMSE for 0.051. The verification results of ESWF showed a high significance, with NSE for actual specific weight (γ₀) and verification estimation specific weight (γ_ev) 0.881, R² for 0.978, and RMSE for 0.055.