• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.495-503
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• 2012

It is necessary to perform the precise analysis of unsteady flow for effective design of the side-weir detention basin installed in the river. Generally, the HEC-RAS program, which is a 1D unsteady numerical model, is mostly used to simulate the unsteady flow for rivers. However, it is difficult to have confidence of unsteady flow results simulated by HEC-RAS due to the lack of experimental data and field monitoring data for the channel with a side-weir detention basin. Therefore, the purpose of this study is to validate or verify the simulation results calculated by HEC-RAS through the experiments for the open channel with a side-weir detention basin using specially-designed unsteady discharge-supply system. The experimental cases included unsteady flows in the straight channel with and without a side-weir detention basin. Especially, for the case with a detention basin, the experiment was performed to consider only the free flow condition over the side-weir. The study results showed that values of water level and discharge obtained from HEC-RAS coincided reasonably with experimental results with the maximum error of 3% for water level and 1% for discharge in the case of the flow without the side-weir detention basin and 4% for water level and 2% for discharge with the side-weir detention basin.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.114-123
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• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

• The Journal of Korean Society for Radiation Therapy
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• v.19 no.1
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• pp.43-49
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• 2007

Purpose: The aim of this study was the clinical implementation of IGRT using KV CBCT for setup correction in radiation therapy. Materials and Methods: We selected 9 patients (3 patient for each region; head, body, pelvis)and acquired 135 CBCT images with CLINAC iX (Varian medical system, USA). During the scan, the required time was measured. We analyzed the result in 3 direction; vertical, longitudinal, lateral. Results: The mean setup errors at the couch position of vertical, lateral, and longitudinal direction were 0.07, 0.12, and 0.1 cm in the head region, 0.3, 0.26, and 0.22 cm in the body region, 0.21, 0.18, and 0.15 cm in the pelvis region respectively. The mean time required for CBCT was $6{\sim}7$ minute. Conclusion: The CBCT on the LINAC provides the capacity for soft tissue imaging in the treatment position and real time monitoring during treatment delivery. With presented workflow, the setup correction within reasonable time for more accurate radiation therapy is possible. And it's image can be very useful for adaptive radiation therapy(ART) in the future with improved image quality.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.2
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• pp.109-115
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• 2006

Understanding characteristics of claypan soils has long been an issue for researchers and farmers because the high-clay subsoil has a pronounced effect on grain crop productivity. The claypan restricts water infiltration and storage within the crop root zone, but these effects are not uniform within fields. Conventional techniques of identifying claypan soil characteristics require manual probing and analysis which can be quite expensive; an expense most farmers are unwilling to pay. On the other hand, farmers would be very interested if this information could be obtained with easy-to-use field sensors. Two examples of sensors that show promise for helping in claypan soil characterization are soil profile strength sensing and bulk soil apparent electrical conductivity (ECa). Little has been reported on claypan soils relating the combined information from these two sensors with grain crop yield. The objective of this research was to identify the relationships of sensed profile soil strength and soil EC with nine years of crop yield (maize and soybean) from a claypan soil field in central Missouri. A multiple-probe (five probes on 19-cm spacing) cone penetrometer was used to measure soil strength and an electromagnetic induction sensor was used to measure soil EC at 55 grid site locations within a 4-ha research field. Crop yields were obtained using a combine equipped with a yield monitoring system. Soil strength at the 15 to 45 cm soil depth were significantly correlated to crop yield and ECa. Estimated crop yields from apparent electrical conductivity and soil strength were validated with an independent data set. Using measurements from these two sensors, standard error rates for estimating yield ranged from 9 to 16%. In conclusion, these results showed that the sensed profile soil strength and soil EC could be used as a measure of the soil productivity for grain crop production.

• Journal of Navigation and Port Research
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• v.33 no.10
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• pp.671-678
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• 2009

Recently, there have been some researches in the equipment fault detection based on shock and vibration information. Most research of them is based on shock and vibration monitoring to determine the equipment fault or not. Different with engine fault detection based on shock and vibration information we focus on detection of engine for boat and system control. First, it use the duplicated-checking method for shock and vibration information to determine the engine fault or not. If there is a fault happened, we use the integral to determine the error engine shock wave width and detect the fault area. On the other hand, we use the engine trend analysis and standard of safety engine to implement the shock and vibration information database. Our simulation results show that the probability of engine fault determination is 98% and the probability of engine fault detection is 72%

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.125-131
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• 2014

The purpose of this study is to verify the utility of reflected photoplethysmography sensor using two green light emitting diodes that influenced by ambient light. Recently it has been studied that green light emitting diode is suitable for light source of reflected photoplethysmography sensor at low temperature and high temperature. Another study showed that, green light is better for monitoring heart rate during motion than led light. However, it has a bad characteristic about ambient light noise. To verify the utility of reflected photoplethysmography sensor using green light emitting diode, this study measures the photoplethysmography signal that is distorted by ambient light and will propose a solution. This study has two parts of research method. One is measurement system that composed sensor and board. The sensor is made up PE-foam and Non-woven fabric for flexible sensor. The photoplethysmography signal is measured by measurement board that composed high-pass filter, low-pass filter and amplifier. Ambient light source is light bulb and white light emitting diode that has three steps brightness. Photoplethysmography signal is measured with lead II electrocardiography signal at the same time and it is measured at the finger and radial artery for 1 minute, 1000 Hz sampling rate. The lead II electrocardiography signal is a standard signal for heart rate and photoplethysmography signal that measured at the finger is a standard signal for waveform. The test is repeated 3 times using three sensor. The data is processed by MATLAB to verify the utility by comparing the correlation coefficient score and heart rate. The photoplethysmography sensor using two green light emitting diodes is shown better utility than using one green light emitting diode and red light emitting diode at the ambient light. The waveform and heart rate that measured by two green light emitting diodes are more identical than others. The amount of electricity used is less than red light emitting diode and error peak detectability factor is the lowest.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.324-339
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• 2021

In this study, we determined the correlation between the wave characteristics and the change in the area of Haeundae Beach, conducted regression analysis between the wave characteristics and the change in beach area, and derived a formula for calculating the change in beach area. The change in beach area was calculated by applying the derived formula to wave observation data corresponding to a period of approximately 10 months, and the formula was subsequently validated by comparing the obtained results with the observed area. It is found that the error associated with the formula for calculating the change in beach area ranges from 1.5 m to 2.7 m based on the average beach width, and the correlation coefficient corresponding to the observed area ranges from 0.91 to 0.94. Furthermore, it is observed that the change in beach area is af ected by the wave direction in the western zone, wave height in the central zone, and wave height and wave period in the eastern zone. These results can contribute to understanding the impact of a coastal improvement project on the beach area fluctuation characteristics of Haeundae Beach and the ef ectiveness of such a coastal improvement project. By applying the aforementioned derived formula to highly accurate wave prediction data, the change in beach area can be calculated and incorporated for predicting significant long-term changes in beach areas. Furthermore, such a prediction can be considered as the basis for making decisions while establishing preemptive countermeasure policies to prevent coastal erosion.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Korean Journal of Plant Resources
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• v.35 no.4
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• pp.471-501
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• 2022

This study was carried out on 455 forest wetlands of south Korea for which an inventory was established through value evaluation and grade. Correlation analysis was conducted to find out the correlation between the types and grades of forest wetlands and 23 evaluation factors in four categories: vegetation and landscape, material circulation and hydraulics·hydrology, humanities and social landscape, and disturbance level. Through the improvement of types and grades of forest wetlands, it is possible to secure basic data that can be used in setting up conservation measures by preparing standards necessary for future forest wetland conservation and restoration, and to found a systematic monitoring system. First, between the type of forest wetland and size and accessibility showed a positive correlation, but the remaining items were analyzed to have negative or no correlation. In particular, it was found that there was no negative correlation or no correlation with the grades of forest wetland. Moreover, it was found that there was a very strong negative correlation with the weighted four category items. Thus, it is judged that improvement is necessary because there is an error in the weight or adjust the evaluation criteria of the value evaluation item, add an item that can increase objectivity. Especially, in the case of forest wetlands, the ecosystem service function due to biodiversity is the largest, so evaluation items should be improved in consideration of this. Therefore, it can be divided into five categories: uniqueness and rarity (15%), wildlife habitat (15%), vegetation and landscape (35%), material cycle·hydraulic hydrology (30%), and humanities and social landscape (5%). It will be possible to propose weights that can increase effectiveness.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.141-152
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• 2020

The rapid on-site measurement of hydroponic nutrients allows for the more efficient use of crop fertilizers. This paper reports on the development of an embedded on-site system consisting of multiple ion-selective electrodes (ISEs) for the real-time measurement of the concentrations of macronutrients in hydroponic solutions. The system included a combination of PVC ISEs for the detection of NO₃, K, and Ca ions, a cobalt-electrode for the detection of H₂PO₄, a double-junction reference electrode, a solution container, and a sampling system consisting of pumps and valves. An Arduino Due board was used to collect data and to control the volume of the sample. Prior to the measurement of each sample, a two-point normalization method was employed to adjust the sensitivity followed by an offset to minimize potential drift that might occur during continuous measurement. The predictive capabilities of the NO₃ and K ISEs based on PVC membranes were satisfactory, producing results that were in close agreement with the results of standard analyzers (R² = 0.99). Though the Ca ISE fabricated with Ca ionophore II underestimated the Ca concentration by an average of 55%, the strong linear relationship (R² > 0.84) makes it possible for the embedded system to be used in hydroponic NO₃, K, and Ca sensing. The cobalt-rod-based phosphate electrodes exhibited a relatively high error of 24.7±9.26% in the phosphate concentration range of 45 to 155 mg/L compared to standard methods due to inconsistent signal readings between replicates, illustrating the need for further research on the signal conditioning of cobalt electrodes to improve their predictive ability in hydroponic P sensing.