• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.927-933
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• 2020

This paper presents a fuel quantity measurement system (FQMS) for an aircraft supplementary fuel tank considering the change of aircraft attitude. The developed FQMS consists of fuel sensors, a signal process unit, an indicator and a software to estimate the fuel quantity from the sensor data. To replicate the change of the roll and pitch attitude on the ground, the test simulator is developed in this work. Using the test simulator, the sensor data at various fuel quantities, roll and pitch angles are automatically measured to build a training data set. The data-driven software to estimate the fuel quantity is then developed using a trilinear interpolation method with the training data set. The developed FQMS is verified by investigating the fuel estimation error of the test data set that we know the true values. Through the test, it is confirmed that the error of the developed FQMS system satisfies the criteria of TSO-C55 document.

• Proceedings of the Korean Society of Food Science and Nutrition Conference
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• 2001.12a
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• pp.52-60
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• 2001

Purpose: We performed a randomized, double-blind, placebo-controlled trial in mild to moderate myopia patients to evaluate the benefit of taking a nutrient supplement containing anthocyanoside oligomers for improving nocturnal visiual function and/or clinical symptoms. Methods: The subjects included have refractive error between -lD(Diopters) $\~$-8D in both eyes, symptoms of decreased night vision and asthenopia based on the scoring result of a pre-structured questionnaire, and abnormal results of mesopic contrast sensitivity(MCS) screening test showing abnormal curve of contrast sensitivity in the middle and high frequency level, between 6.0 and 30.0 CPD(Cycles per degree) at mesopic condition(-2$\~$0 log cd/$m^2$). Total 60 people who qualified the criteria above were enrolled and the subjects were instructed to take the investigational product (anthocyanoside or placebo) twice daily for a 4 week period. The enrolled subjects were investigated for nocturnal vision performance by MCS and clinical symptoms at their first visit and re-evaluated at post-intervention (4 weeks later). MCS was measured and improvement of contrast threshold level according to each CPD was calculated by subtracting initial values from final values. Age, refractive error, and MCS were compared between the placebo and anthocyanoside. Results: After 4 weeks of drug administration 22 of the anthocyanoside group showed symptom improvement compared to 1 of the placebo group (p=0.000). Contrast sensitivity levels according to each CPD before and after drug treatment showed significant improvement in the anthocyanoside group but not in the placebo group. Mean MCS change of anthocyanoside group is 2.41$\pm$1.91 which showed significant improvement compared to -0.40$\pm$2.47 of the placebo group(p=0.000). MCS changes of anthocyanoside group showed significant improvement compared to placebo group in all levels of CPD(p<0.05). During our investigation none of the subjects complained of specific side effects related to anthocyanoside use. Conclusion: Our results show that under careful selection of people with significant symptoms and definite MCS abnormalities, anthocyanoside oligomers may improve the subjective symptoms and objective MCS results.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.782-787
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• 2001

In this paper, we propose an growing and pruning algorithm to design the adaptive structure of modular wavelet neural network(MWNN) with F-projection and geometric growing criterion. Geometric growing criterion consists of estimated error criterion considering local error and angel criterion which attempts to assign wavelet function that is nearly orthogonal to all other existing wavelet functions. There criteria provide a methodology that a network designer can constructs wavelet neural network according to one s intention. The proposed growing algorithm grows the module and the size of modules. Also, the pruning algorithm eliminates unnecessary node of module or module from constructed MWNN to overcome the problem due to localized characteristics of wavelet neural network which is used to modules of MWNN. We apply the proposed constructing algorithm of the adaptive structure of MWNN to approximation problems of 1-D function and 2-D function, and evaluate the effectiveness of the proposed algorithm.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.841-849
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• 2007

This study evaluated the effect of combined rainfall observation of using rain gauge and rain radar. The effect of combined observations is to be evaluated by considering the decrease of measurement error due to combined use of design orthogonal observation methods. As an example, this study evaluated the rain gauge network of the Keum river basin, and showed how the density of rain gauges could be decreased by combining the radar observation. This study applied the researches on sampling error by North and Nakamoto(1989), Yoo et al. (1996) and Yoo (1997), also the simple NFD model for representing the rainfall field. The model parameters were decided using the rainfall characteristics (correlation time and length) estimated using the data collected in the Keum River Basin by 28 rain gauges and the operation rule of radar was assumed arbitrarily. This study considered the rain gauge density criteria provided by WMO(1994) and the rain gauge density installed in the Keum river basin to decrease the rain gauge density under the condition of introducing the radar.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.577-584
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• 2018

GNSS based transport infrastructure cluster is to broadcast satellite navigation correction information and integrity information capable of precise positioning for land transport users. This makes it possible to do lane-level positioning reliably. However, in order to provide the lane-level positioning and correction information service nationwide, new station sites selection and to build GNSS stations have a heavy cost and a burden for a considerable period of time. In this paper, we propose the cluster design criteria and national-wide network-based precise positioning for land transportation (NETPPI-LT) cluster design for a cluster-based precise positioning. Furthermore, it is analyzed the precise positioning pre-performance of this cluster design based on the spatial error and verified its suitability as the precise positioning pre-performance of the cluster design.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.127-132
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• 2021

The intravenous injection monitoring system used by medical institutions was developed to remotely provide patients with the amount of intravenous injected and the termination point of the injection. In order to measure the amount of intravenous injection input, the weight or flow rate of the level going out from the inside to outside of the intravenous injection can be observed with a measuring sensor. The criteria for devices that apply herein are accuracy and vigilance. In addition, it is compact and should be easy to use when installing intravenous injection on patients. In medical institutions, the accuracy of the measured values must be high, and economically inexpensive devices are required. In this study, low-cost small-weight-centered load cell sensors were applied, and algorithms were applied to reduce the artefact by external movement by converging with gyro sensors for accuracy of measurements. As a result, it was possible to reduce the error of measurement, thereby improving the accuracy of the intravenous injection monitoring measurement value.

• Atmosphere
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• v.32 no.2
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• pp.149-162
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• 2022

This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation for the period of 1991~2016. Additionally, we evaluated the prediction skill of those variables depending on the combination of the initial dates in the sub-seasonal scale for the dust source region affecting South Korea. The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) from GloSea5-ADAM were compared to that from Synoptic observation and European Centre for medium range weather forecasts reanalysis v5, respectively, based on Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC) as evaluation criteria. In general, the Asian dust and meteorological variables in the source region showed high ACC in the prediction scale within one month. For all variables, the use of the initial dates closest to the prediction month led to the best performances based on MBE, RMSE, and ACC, and the performances could be improved by adjusting the number of ensembles considering the combination of the initial date. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.145-150
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• 2022

The main purpose of this work was to restore the blurry chest CT images by applying a blind deconvolution algorithm. In general, image restoration is the procedure of improving the degraded image to get the true or original image. In this regard, we focused on a blind deblurring approach with chest CT imaging by using digital image processing in MATLAB, which the blind deconvolution technique performed without any whole knowledge or information as to the fundamental point spread function (PSF). For our approach, we acquired 30 chest CT images from the public source and applied three type's PSFs for finding the true image and the original PSF. The observed image might be convolved with an isotropic gaussian PSF or motion blurring PSF and the original image. The PSFs are assumed as a black box, hence restoring the image is called blind deconvolution. For the 30 iteration times, we analyzed diverse sizes of the PSF and tried to approximate the true PSF and the original image. For improving the ringing effect, we employed the weighted function by using the sobel filter. The results was compared with the three criteria including mean squared error (MSE), root mean squared error (RMSE) and peak signal-to-noise ratio (PSNR), which all values of the optimal-sized image outperformed those that the other reconstructed two-sized images. Therefore, we improved the blurring chest CT image by using the blind deconvolutin algorithm for optimal approach.

• Journal of the Korean Geotechnical Society
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• v.23 no.12
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• pp.109-116
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• 2007

This study has reviewed the applicability of displacement measurement by using a digital vision technique based on typical photogrammetric methods. In this study, a series of experimental measurements have been performed in order to improve the accuracy of digital vision measurement by establishing criteria of factors of various vision measurements. It is found that the digital vision measurement tends to show higher accuracy as the image size(resolution) and the focal length become larger and the distance to an object becomes closer. It is also observed that measurement error decreases with processing as many images as possible in various angles. Applicability on high-resolution displacement measurement is proved by applying the digital vision measurement developed in this study to a large scale loading test of concrete lining.

• Steel and Composite Structures
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• v.45 no.2
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.