• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.224-224
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• 2016

수문 순환과 물 수지에 관한 연구는 강수량, 지표유출량, 지하수, 토양수분 및 증발산량 등에 대한 관측이 이루어질 때 실제로 규명될 수 있다. 하지만, 수문 순환과 물수지 평가에 중요한 부분을 차지하는 증발산량의 경우 관측값보다 단순한 가정이나 경험식에 의한 추정값을 사용하고 있어 그 자료의 신뢰성에 대해서도 꾸준히 문제가 제기되어 왔다. 따라서, 수문 순환과 물수지의 정량적인 분석을 위해서는 수문 순환 과정에서 상당부분을 차지하는 증발산량의 측정(실측)과 자료의 축척이 필요한 실정이다. 본 연구는 국토교통부의 기초수문자료 구축사업의 일환으로 수행되고 있으며, 수문자료의 다양화 목적을 가지고 에디공분산 기술을 사용하여 증발산량을 직접 관측하고 있다. 관측지점은 한반도의 약 70%를 차지하는 산림지 중 대표적 식생 기능 형태인 혼효림으로 구성된 지점(설마천 관측소, 2007년 8월부터)과, 인위적인 관개가 이루어지는 논경지(청미천 관측소, 2008년 8월부터)에서의 증발산량 측정을 수행하였다. 그 결과 두 지점에서 증발산량의 계절 및 경년 변동 특성을 파악 할 수 있었다. 혼효림(설마천 관측소)에서 산정된 증발산량은 2008년 471.7mm, 2009년 408.4mm, 2010년 489.4mm, 2011년 387.0mm, 2012년 323.3mm, 2013년 293.3mm, 2014년 360.9mm, 2015년 419.6mm이고, 강수량 대비 증발산량은 18.9%~56.2%를 보였다. 논경지(청미천 관측소)에서 산정된 증발산량은 2009년 571.8mm, 2010년 650.6mm, 2011년 523.9mm, 2012년 509.8mm, 2013년 467.9mm 2014년 533.9mm, 2015년 600.5mm이고, 강수량 대비 증발산량은 25.6%~71.4%를 보였다. 강수량 대비 비율의 최대값은 설마천 관측소는 2014년, 청미천 관측소는 2015년에 발생하였다.. 평균 증발산량 비율은 산림지인 설마천 관측소보다 논경지인 청미천 관측소가 평균 15.5%정도 높게 나타났다.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.379-385
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• 2017

This study identifies the optimal tube voltages depending on the changes in the patient's body type for limb tests using a digital radiography (DR) system. For the upper-limp test, the dose area product (DAP) was fixed at $5.06dGy{\ast} cm^2$, and for the lower-limb test, the DAP was fixed at $5.04dGy{\ast} cm^2$. Afterwards, the tube voltage was changed to four different stages and the images were taken three times at each stage. The thickness of the limbs was increased by 10 mm to 30 mm to change in the patient's body type. For a quantitative evaluation, Image J was used to calculate the contrast to noise ratio (CNR) and signal to noise ratio (SNR) among the four groups, according to the tube voltage. For statistical testing, the statistically significant differences were analyzed through the Kruskal-Wallis test at a 95% confidence level. For the qualitative analysis of the images, the pre-determined items were evaluated based on a 5-point Likert scale. In both upper-limb and lower-limb tests, the more the tube voltage increased, the more the CNR and SNR of the images decreased. The test on the changes depending on the patient's body shape showed that the more the thickness increased, the more the CNR and SNR decreased. In the qualitative evaluation on the upper limbs, the more the tube voltage increased, the more score increased to 4.6 at the maximum of 55kV and 3.6 at 40kV, respectively. The mean score for the lower limbs was 4.4, regardless of the tube voltage. The more either the upper or lower limbs got thicker, the more the score generally decreased. The score of the upper limps sharply dropped at 40kV, whereas that of the lower limps sharply dropped at 50kV. For patients with a standard thickness, the optimized images can be obtained when taken at 45kV for the upper limbs, and at 50kV for the lower limbs. However, when the thickness of the patient's limbs increases, it is best to set the tube voltage at 50 kV for the upper limbs and at 55 kV for the lower limbs.

• Journal of the Korean earth science society
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• v.24 no.7
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• pp.614-624
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• 2003

The purpose of this study was to examine the effectiveness of utilizing a concept map as an instructional strategy to promote student achievement through semantical learning in elementary school on volcanoes. To analyze student achievement in understanding the concept of volcano, quantitative and qualitative analyses were performed through a written test for two different groups that were composed of 80 sixth-grade students: a control group that attended class using the conventional strategy and an experimental group that attended class using concept maps. The results of this study were as follows: First, the use of concept maps in class is effective in learning because of the higher understanding of the group that was using concept maps in the achievement assessment. Second, in their post-instructional understandings, no significant differences are shown between middle- and low-ranking students statistically, but a significant difference is shown between high- and low-ranking students or between high- and middle-ranking students. This indicates that the use of concepts maps in a class is more effective for the middle- and low-ranking students than for the high-ranking students. Third, in the repetitions of classes, the students learning with an aid of concept maps became accustomed to structuring the concepts of their learning subject in categories of relationships, hierarchies, cross-links, and examples easily.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.637-644
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• 2012

In a nuclear power plant, fretting wear due to impact motion between U-tubes and support structures located in steam generators can cause serious problems. In order to guarantee the reliability of the steam generator, the damage due to fretting wear should be thoroughly investigated. The purpose of this study is to elucidate the fretting wear mechanism qualitatively and quantitatively. Hence, fretting wear simulation is performed for the environments to which the actual steam generators in nuclear power plants are exposed. Initial experimental results are obtained for various experimental parameters, and the effect of the work rate and temperature on fretting wear is evaluated. In water, the wear coefficients for $90^{\circ}C$, $200^{\circ}C$, and $340^{\circ}C$ are found to be $9.051{\times}10^{-16}\;Pa^{-1}$, $3.009{\times}10^{-15}\;Pa^{-1}$, and $2.235{\times}10^{-15}\;Pa^{-1}$, respectively. It is also found that the wear coefficient at room temperature is larger than that at low temperature in water because of the dynamic viscosity of water.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.29-39
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• 2015

This paper describes a design and implementation of fuzzy-based algorithm for hand-shake state detection and error compensation in the mobile optical image stabilization(OIS) motion detector. Since the gyro sensor output of the OIS motion detector includes inherent error signals, accurate error correction is required for prompt hand-shake error compensation and stable hand-shake state detection. In this research with a little computation overhead of fuzzy-based algorithm, the hand-shake error compensation could be improved by quickly reducing the angle and phase error for the hand-shake frequencies. Further, stability of the OIS system could be enhanced by the hand-shake states of {Halt, Little vibrate, Big vibrate, Pan/Tilt}, classified by subdividing the hand-shake angle. The performance and stability of the proposed algorithm in OIS motion detector is quantitatively and qualitatively evaluated with the emulated hand-shaking of ${\pm}0.5^{\circ}$, ${\pm}0.8^{\circ}$ vibration and 2~12Hz frequency. In experiments, the average error compensation gain of 3.71dB is achieved with respect to the conventional BACF/DCF algorithm; and the four hand-shake states are detected in a stable manner.

• Journal of Service Research and Studies
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• v.9 no.3
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• pp.87-99
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• 2019

Healthcare and data science are often linked through finances as the industry attempts to reduce its expenses with the help of large amounts of data. Data science and medicine are rapidly developing, and it is important that they advance together. Data science is a driving force in transition of healthcare systems from treatment-oriented to preventive care in healthcare 3.0 era. It enables customized precision-based medicine that current healthcare systems cannot facilitate, and discovers more cost-effective treatment. Currently, healthcare big data is in the reality of medical institution, public health, medical academia, pharmaceutical sector as well as insurance agency. With this motivation, the medical college of Soonchunhyang university has performed a 'healthcare data science initiative(HDSI)' since 2014. Most of domestic HDSI programs focus on short-term contents such as mentoring and sharing cases for data science. Therefore, it is difficult to provide education tailored to the level of skills and job competency required at the practical site. Soonchunhyang HDSI implemented specialized strategies for improving resilience and response to changes in the IT education of current healthcare with the emphasis on the need for systematic activation of the practical HDSI. The HDSI has been performed as a part of on industry-academic link program in CK-1. Through quantitative and qualitative analysis, this paper discussed the HDSI process, performance, achievement, and implications.

• Journal of Korea Technology Innovation Society
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• v.12 no.1
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• pp.189-211
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• 2009

The importance of searching the weak signal has been increasingly recognized to cope with rapidly changing circumstances as an environmental analysis technique. This study proposed the NEST process for the searching for the weak signal. The NEST (New & Emerging Signals of Trends) is a micro environmental analysis process based on both quantitative and qualitative method. For this, the weak signal Searching Board is developed and traditional methods as global monitoring, trend analysis, brainstorming and delphi method are implemented to NEST. The NEST process is consists of three stage modules; the global monitoring stage in search of seeds information related to the environmental change, the weak signal analysis stage using the weak signal Tracking Board, and the delphi valuation stage for objectifying the final result. The NEST provides the weak signal of the promising technology which can bring new paradigm and the Up-Coming Trends which can lead new trend in the future. These outputs can be used to select promising technology from firm level to national level. The NEST system can be effectively operated as well as in small group so that small and medium innovative firms can develop and execute their own NEST process individually.

• Economic and Environmental Geology
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• v.52 no.5
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• pp.459-469
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• 2019

We present a quantitative evaluation of density, vesicularity and microtextures for coarse lapilli collected from the Jugam Scoria Deposits, northeastern Ulleung Island. Lapilli from the deposits have modal vesicularities of 61% in the lower part and 67% in the upper part, and vesicle populations dominated by non-interconnected subround vesicles. Clasts of modal vesicularity have margin-parallel zonation, with subaerially quenched rims interpreted to preserve "syn-fragmentation" magmatic textures in microlite-free sideromelane rims, grading "post-fragmentation" tachylitic interiors with vesicle and microlite textures that progressively coarsen from rim to interior. Degassing scenarios are linked to syn-fragmentation vesicle textures to demonstrate that the magmas degassed in dominantly closed systems. And diffusion-controlled cooling rates of trachyandesitic pyroclasts in contact with atmosphere are linked to post-fragmentation evolution of vesicle and microlite textures to infer about transportation and dispersal of the pyroclasts in low shooting jets. These textural analyses show that the Jugam eruptions were strictly applied to the strombolian type, analogous to the hawaiian type among any classical subaerial eruption type.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.25-33
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• 2023

Noise generated during the acquisition and transmission of CT images acts as a factor that degrades image quality. Therefore, noise removal to solve this problem is an important preprocessing process in image processing. In this paper, we remove noise by using a deformable convolutional autoencoder (DeCAE) model in which deformable convolution operation is applied instead of the existing convolution operation in the convolutional autoencoder (CAE) model of deep learning. Here, the deformable convolution operation can extract features of an image in a more flexible area than the conventional convolution operation. The proposed DeCAE model has the same encoder-decoder structure as the existing CAE model, but the encoder is composed of deformable convolutional layers and the decoder is composed of conventional convolutional layers for efficient noise removal. To evaluate the performance of the DeCAE model proposed in this paper, experiments were conducted on CT images corrupted by various noises, that is, Gaussian noise, impulse noise, and Poisson noise. As a result of the performance experiment, the DeCAE model has more qualitative and quantitative measures than the traditional filters, that is, the Mean filter, Median filter, Bilateral filter and NL-means method, as well as the existing CAE models, that is, MAE (Mean Absolute Error), PSNR (Peak Signal-to-Noise Ratio) and SSIM. (Structural Similarity Index Measure) showed excellent results.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.