• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1217-1227
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• 2018

This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1055-1066
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• 2018

Vegetation indices on the basis of optical characteristics of vegetation can represent various conditions such as canopy biomass and physiological activity. Those have been mostly developed with the large-scaled applications of multi-band optical sensors on-board satellites. However, the sensitivity of vegetation indices for detecting vegetation features will be different depending on the spatial scales. Therefore, in this study, the investigation of photochemical reflectance index (PRI), known as one of useful vegetation indices for detecting photosynthetic ability and vegetation stress, under the three spatial scales was conducted using multi-spectral camera installed in unmanned aerial vehicle (UAV),field spectrometer, and leaf reflectometer. In the leaf scale, diurnal PRI had minimum values at different local-time according to the compass direction of leaf face. It meant that each leaf in some moment had the different degree of light use efficiency (LUE). In early growth stage of crop, $PRI_{leaf}$ was higher than $PRI_{stands}$ and $PRI_{canopy}$ because the leaf scale is completely not governed by the vegetation cover fraction.In the stands and canopy scales, PRI showed a large spatial variability unlike normalized difference vegetation index (NDVI). However, the bias for the relationship between $PRI_{stands}$ and $PRI_{canopy}$ is lower than that in $NDVI_{stands}$ and $NDVI_{canopy}$. Our results will help to understand and utilize PRIs observed at different spatial scales.

• Journal of IKEEE
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• v.23 no.2
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• pp.739-742
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• 2019

In this paper, we propose enhanced DAP(Dose Area Product). The development of enhanced DAP proposed in this paper has optimized the area dose meter that was developed previously. The development of enhanced DAP performed Optimized design of charge integrator and ADC circuit, optimization of line transceiver for RS-485 communication, optimization of display circuit, and optimization of PC-based control program for interlocking and aging. As a result of evaluating the performance of the proposed system in an accredited testing laboratory, Radiation dose dependence and Radiation quality dependence were measured to be 4.2%, which is below ${\pm}15%$ of international standard. Energy range/Tube voltage was confirmed in the range of 30~150kV. The sensitivity difference between sensor field and sensor field area dose sensitivity was measured to be 4.3%, and it was confirmed that it operates normally under ${\pm}15%$ of international standard. In order to measure the reproducibility of the area dosimeter, it was confirmed that it was 0% and it was operated normally at less than 2% of IEC60580 recommendation. Digital resolution was confirmed to be a minimum unit of $0.01{\mu}Gy{\cdot}m^2$ within the error range for the reference dose per hour.

• Korean Journal of Food Science and Technology
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• v.51 no.4
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• pp.348-355
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• 2019

This study investigated the impact of cellulase treatment on the extraction yield of potato starch (PS), and compared the physicochemical properties of PS by conventional (CSE) and enzymatic (ESE) starch extraction. In ESE, the PS extraction yield was predominantly influenced by reaction temperature, time and their interaction, compared to the cellulase concentration. When potatoes were treated for 8 h at $40^{\circ}C$ with 1.5% cellulase, the PS extraction yield was about 3.4-fold higher than that by CSE. Compared to CSE-PS, ESE-PS showed lower total starch contents and higher amylose contents, resulting in lower swelling factors and distorted pasting viscosity profiles accompanied by absence of peak and breakdown viscosities. However, ESE did not affect the gelatinization characteristics of PS. Overall results suggested that ESE can provide the highest yield of PS, and ESE-PS can be a potential starch source for extending the utilization of PS in food industries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.394-405
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• 2019

The purpose of this study is to clarify the concept of the frail elderly and to obtain theoretical evidence. The research method was conducted using the basic principles for conceptual analysis of Walker and Avant(2005). As a Result of a review of the literature about how to utilize the concept of a frail elderly, frail elderly might be in the intermediate state of health and disease. They can be defined as physically vulnerable in the sarcopenia, inflammation, insulin resistance, and preceding advanced disease, lead to hospitalization, falls, disability, and death. The attributes were physiological, psychological, and socio-environmental and economic factors, so they had multidimensional factors. They were required the assist daily living of another person. Also, their attributes had decreased the amount of recovery time and degree, and exhaustion. The attributes of frail elderly consisted of these facts: dynamic process, multidimensional factors, dependency, vulnerability. The frail elderly was a dynamic process that involves the possibility of change to health and disease, and include physical, mental, cognitive, and social environmental factors. In addition, the frail elderly was difficulty in daily life, physical vulnerability and difficulty in adaption. In conclusion, frail elderly as defined by the results of this study will contribute to the foundation of health care systems, including community visiting nursing to understand the level of frail elderly and systemic management to do not go into long term care.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.637-648
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• 2021

In order to support the establishment of a farming plan, it is important to preemptively evaluate crop changes and to provide precise information. Therefore, it is necessary to provide customized information suitable for decision-making by farming stage through scientific and continuous monitoring using drones. This study was carried out to support the establishment of the farming plan for ground vegetable. The cultivation management map of each information was obtained from preliminary study. Three cultivation management maps include 'field emergence map', 'stress map' and 'productivity map' reflected spatial variation in the plantation by providing information in units of plants based on 3-dimensions. Application fields of the cultivation management map can be summarized as follows: detect miss-planted, replanting decision, fertilization, weeding, pest control, irrigation schedule, market quality evaluation, harvest schedule, etc.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.556-561
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• 2020

The aging and declining agricultural population in the modern society requires improvement of the agricultural environment and is one of the representative problems. And since most of the work systems always require a transport work, the ratio of labor consumed in the transport work is very high. Accordingly, many types of transport vehicles are being developed and sold, and in the early days, most of them are powered transport vehicles using fossil fuels. However, it is paying attention to next-generation eco-friendly energy such as hydrogen, fuel cells, solar power, and bio due to the strengthening of international environmental regulations such as global warming and the Convention on Climate Change and the depletion of fossil fuels. Therefore, in this study, the ultimate goal is to develop an eco-friendly, easy-to-operate, safe agricultural electric vehicle that replaces fossil fuels. It was designed with a focus on controlling a wide range of vehicle speeds and securing stability of electric agricultural vehicles. Considering the performance and design, it is composed of a frame, a driving part, a steering part, and a controller system, and we are going to review and manufacture each part. It is believed that the manufactured electric vehicle for agriculture can be easily and conveniently operated in an agricultural society where young manpower is scarce, and can be helpful to the agricultural society through high efficiency.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.46 no.4
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• pp.371-382
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• 2020

There have been continuous attempts to quantify sensory attributes of cosmetic products by measuring relevant physical properties. The most representative method to evaluate stickiness is to measure axial force using texture analyzer. Stickiness is known to correlate with AUC which abbreviates area under curve in the obtained axial force curve as a function of time. Recently, Normandie University research group developed in vivo stickiness evaluation method considering the characteristics of skin along with established evaluation method[8]. Based on the study, we tried to optimize in vivo stickiness evaluation method especially for cosmetic creams. The experiment was carried out on 5 different facial creams products by changing the amount and the times of rolling of creams, and the shape and material of probes. Based on the results of the sensory evaluation, the most consistent conditions were established as the optimal evaluation method. As a result, applying 70 μL of cream and rubbing 10 times for 7 s inside the 3.4 cm circle were judged to be suitable. As for the probes, spherical metallic probe was more proper due to its reproducibility. We conducted the settled method on 10 subjects to check its validity. Although the absolute values of AUC differed depending on the individuals, the AUC values were all ranked the same. Finally, for the standardization of stickiness of AUC, polyvinylpyrrolidone (PVP) was set as a reference material and we measured AUC of its aqueous solution by changing concentration. Then, the degree of stickiness recognition for 5 different creams was surveyed to check the correlation between AUC and stickiness.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.547-554
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• 2021

In order to quickly and accurately diagnose pneumonia on a chest X-ray image, different batch sizes of 4, 8, 16, and 32 were applied to the same Xception deep learning model, and modeling was performed 3 times, respectively. As a result of the performance evaluation of deep learning modeling, in the case of modeling to which batch size 32 was applied, the results of accuracy, loss function value, mean square error, and learning time per epoch showed the best results. And in the accuracy evaluation of the Test Metric, the modeling applied with batch size 8 showed the best results, and the precision evaluation showed excellent results in all batch sizes. In the recall evaluation, modeling applied with batch size 16 showed the best results, and for F1-score, modeling applied with batch size 16 showed the best results. And the AUC score evaluation was the same for all batch sizes. Based on these results, deep learning modeling with batch size 32 showed high accuracy, stable artificial neural network learning, and excellent speed. It is thought that accurate and rapid lesion detection will be possible if a batch size of 32 is applied in an automatic diagnosis study for feature extraction and classification of pneumonia in chest X-ray images using deep learning in the future.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.2
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• pp.202-210
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• 2022

Recently with the advance in digital dentistry, the fabrication of dentures using computer-aided design and computer-aided manufacturing (CAD-CAM) is on the rise. The denture designed through a CAD software can be produced in a 3-dimensional manufacturing process. This process includes a subtractive processing method such as milling and an additive processing method such as 3D printing and in which it can be applied efficiently in more complex structures. In this case, complete dentures were fabricated using Stereolithography (SLA)-based 3D printing to shorten the production time and interval of visits in patient with physical disabilities due to cerebral infarction. For definitive impression, the existing interim denture was digitally replicated and used as an individual tray. The definitive impression obtained with polyvinyl siloxane impression material was including information about the inclination and length of the maxillary anterior teeth, vertical dimension, and centric relation. In addition, facial scan data with interim denture was obtained so that it can be used as a reference in determination of the occlusal plane and in arrangement of artificial teeth during laboratory work. Artificial teeth were arranged through a CAD program, and a gingival festooning was performed. The definitive dentures were printed by SLA-based 3D printer using a FDA-approved liquid photocurable resin. The denture showed adequate retention, support, and stability, and results were satisfied functionally and aesthetically.