• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.1
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• pp.64-69
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• 2016

This study was conducted to develop a fast and efficient screening method to determine the quantity of fatty acid in peanut oil for high oleate breeding program. A total of 329 peanut samples were used in this study, 227 of which were considered in the calibration equation development and 102 were utilized for validation, using near infrared reflectance spectroscopy (NIRS). The NIRS equations for all the seven fatty acids had low standard error of calibration (SEC) values, while high R2 values of 0.983 and 0.991 were obtained for oleic and linoleic acids, respectively in the calibration equation. Furthermore, the predicted means of the two main fatty acids in the calibration equation were very similar to the means based on gas chromatography (GC) analysis, ranging from 36.7 to 77.1% for oleic acid and 7.1 to 42.7% for linoleic acid. Based on the standard error of prediction (SEP), bias values, and $R^2$ statistics, the NIRS fatty acid equations were accurately predicted the concentrations of oleic and linoleic acids of the validation sample set. These results suggest that NIRS equations of oleic and linoleic acid can be used as a rapid mass screening method for fatty acid content analysis in peanut breeding program.

• Korean Journal of Health Education and Promotion
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• v.21 no.4
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• pp.15-33
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• 2004

With growing significance of psychological well-being in the worksite, the purpose of this analysis was to overview the empirical studies on worksite stress management and to identity the overall effect of worksite health promotion programs on stress management through meta-analysis. Literature retrieval was conducted on-line first in MEDLINE, EBSCOhost Academic Search Premier, and PSYCHINFO databases in public health, psychology, sociology, and human resource management areas. All studies written in English and published in the peer-reviewed journals during 1990 and 2002 were recruited. Key words used in literature retrieval were 'worksite,' 'intervention,' 'program,' 'work stress,' 'strain,' 'burnout,' 'management,' 'prevention,' 'education,' and 'health promotion.' A total of 18 worksite intervention studies with 48 effect sizes were analyzed and the results were as follows. Approximately 60％ of the studies had quasi-experimental design and were conducted in manufacturing company and public sector. General psychological strains and burnout were frequently used measures of psychological stress. The lecturing and discussion typed intervention and the participatory problem-solving typed intervention were employed more than others in the studies. The average effect (r: pearson's simple correlation coefficient) weighted by sampling error was -0.14 (-0.32 to 0.05). In the conventional category of effects this is a small effect ranging from -0.59 to 0.05. Binomial effect size showed that success rates increased from 43％ without intervention to 57％ after an intervention. Sampling error explained 47.14％ of the observed variance and its effectiveness on stress management were heterogeneous. In regression analysis with suspected moderating factors affecting the worksite interventions, research design was the only significant moderating factor. The studies with quasi-experimental design had greater effects than the studies with experimental design.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.273-279
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• 2014

In this paper, we propose a novel algorithm for three dimensional positioning system and implement a system over indoor wireless channel. A commercial modules are used for mobile and fixed nodes which are product of German company Nanotron Co. This module adopts chirp spread spreading scheme as modulation method to improve the ranging resolution and the module satisfies the IEEE standard 802.15.4a. The distance computation is based on received signal strength(RSS) levels and trilateration method. A testbed was set up to measure and compare the positioning estimation error of the proposed algorithm. The experiments results showed that the accuracy of location estimation was sufficiently good as much as 1m distance error in a wireless environment in an office building.

• Journal of Sensor Science and Technology
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• v.8 no.3
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• pp.219-225
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• 1999

The purpose of this study is to measure such parameters as TMR, OAR, TSF for small beams ranging in size from 12.5mm to 40mm by diode, ionization chamber, film, TLD and to determine proper detectors for the measurement of 6MV small x-ray beams. Diode and film show good results within 2% error for the TMR measurement of the beam as small as beam with diameter 12.5mm. Diode and film have excellent spatial resolution in the OAR measurement and the comparison between two detectors shows the error within 3%. But TMR and OAR can not be measured accurately by the ionization chambers. The TSF by diode and TLD records 0.890.96 for the beams with diameter 12.5mm 40mm. The TSF determined by 0.125cc ionization chamber and markus ionization chamber for the larger beams than the beams with diameter 25mm agrees within 2% comparing with that of diode and TLD.

• Advances in concrete construction
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• v.10 no.6
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• pp.479-488
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• 2020

The experimental and numerical works were carried out on high performance fiber reinforced concrete (HPFRC) with w/cm ratios ranging from 0.25 to 0.40, fiber volume fraction (Vf)=0-1.5% and 10% silica fume replacement. Improvements in compressive and flexural strengths obtained for HPFRC are moderate and significant, respectively, Empirical equations developed for the compressive strength and flexural strength of HPFRC as a function of fiber volume fraction. A relation between flexural strength and compressive strength of HPFRC with R=0.78 was developed. Due to the complex mix proportions and non-linear relationship between the mix proportions and properties, models with reliable predictive capabilities are not developed and also research on HPFRC was empirical. In this paper due to the inadequacy of present method, a back propagation-neural network (BP-NN) was employed to estimate the 28-day compressive strength of HPFRC mixes. BP-NN model was built to implement the highly non-linear relationship between the mix proportions and their properties. This paper describes the data sets collected, training of ANNs and comparison of the experimental results obtained for various mixtures. On statistical analyses of collected data, a multiple linear regression (MLR) model with R2=0.78 was developed for the prediction of compressive strength of HPFRC mixes, and average absolute error (AAE) obtained is 6.5%. On validation of the data sets by NNs, the error range was within 2% of the actual values. ANN model has given the significant degree of accuracy and reliability compared to the MLR model. ANN approach can be effectively used to estimate the 28-day compressive strength of fibrous concrete mixes and is practical.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.511-518
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• 2023

Accurate ranging is one of the key factors in the test and evaluation process of underwater vehicles. In particular, when estimating range using Time of Arrival (ToA) values, signals such as Linear Frequency Modulation (LFM), a chirp signal, are highly applicable due to their correlated nature. However, in a Doppler shift environment with mobility, measurement errors may occur due to the range-Doppler coupling effect. In this paper, we propose a signal that compensates for the distance-Doppler coupling effect to reduce the measurement error of the arrival time value. The proposed signal is constructed by superimposing two types of LFM signals, and the range-Doppler coupling effect can be minimized. Through simulations, it is confirmed that the proposed signal is a way to compensate for the distance-Doppler coupling effect in the distance estimation of underwater mobile bodies, reducing the measurement error of the arrival time value.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1225-1228
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• 2006

A total of 1,367 first lactation records of daughters of 81 sires, having 5 or more progeny were used to evaluate sires by 3 different methods viz., least squares (LS), best linear unbiased prediction (BLUP) and derivative free restricted maximum likelihood (DFREML) method. The highest and lowest overall average breeding value of sires for first lactation 305 days or less milk yield was obtained by BLUP (1,520.72 kg) and LS method (1,502.22 kg), respectively. The accuracy, efficiency and stability of different sire evaluation methods were compared to judge their effectiveness. The error variance of DFREML method was lowest ($191,112kg^2$) and its coefficient of determination of fitting the model was highest (33.39%) revealing that this method of sire evaluation was most efficient and accurate as compared to other methods. However, the BLUP method was most stable amongst all the methods having coefficient of variation (%) very near to unadjusted data (18.72% versus 19.89%). The higher rank correlations (0.7979 to 0.9568) between different sire evaluation methods indicated that there was higher degree of similarity of ranking sires by different methods ranging from about 80 to 96 percent. However, the DFREML method seemed to be the most effective sire evaluation method as compared to other methods for the present set of data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.253-270
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• 2013

To achieve accurate localization information, complex algorithms that have high computational complexity are usually implemented. In addition, many of these algorithms have been developed to overcome several limitations, e.g., obstruction interference in multi-path and non-line-of-sight (NLOS) environments. However, localization systems those have complex design experience latency when operating multiple mobile nodes occupying various channels and try to compensate for inaccurate distance values. To operate multiple mobile nodes concurrently, we propose a localization system with both low complexity and high accuracy and that is based on a chirp spread spectrum (CSS) radio. The proposed localization system is composed of accurate ranging values that are analyzed by simple linear regression that utilizes a Big-$O(n^2)$ of only a few data points and an algorithm with a self-calibration feature. The performance of the proposed localization system is verified by means of actual experiments. The results show a mean error of about 1 m and multiple mobile node operation in a $100{\times}35m^2$ environment under NLOS condition.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.355-369
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• 2018

LiDAR (Light Detection And Ranging) strip adjustment is process to improve geo-referencing of the ALS (Airborne Laser Scanner) strips that leads to seamless LiDAR data. Multiple strips are required to collect data over the large areas, thus the strips are overlapped in order to ensure data continuity. The LSA (LiDAR Strip Adjustment) consists of identifying corresponding features and minimizing discrepancies in the overlapping strips. The corresponding features are utilized as control features to estimate transformation parameters. This paper applied SURF (Speeded Up Robust Feature) to identify corresponding features. To improve determination of the corresponding feature, false matching points were removed by applying three schemes: (1) minimizing distance of the SURF feature vectors, (2) selecting reliable matching feature with high cross-correlation, and (3) reflecting geometric characteristics of the matching pattern. In the strip adjustment procedure, corresponding points having large residuals were removed iteratively that could achieve improvement of accuracy of the LSA eventually. Only a few iterations were required to reach reasonably high accuracy. The experiments with simulated and real data show that the proposed method is practical and effective to airborne LSA. At least 80 % accuracy improvement was achieved in terms of RMSE (Root Mean Square Error) after applying the proposed schemes.