• Title/Summary/Keyword: Prediction Ratio

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Deep Learning-based SISR (Single Image Super Resolution) Method using RDB (Residual Dense Block) and Wavelet Prediction Network (RDB 및 웨이블릿 예측 네트워크 기반 단일 영상을 위한 심층 학습기반 초해상도 기법)

  • NGUYEN, HUU DUNG;Kim, Eung-Tae
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.703-712
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    • 2019
  • Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.

Prediction of calcium and phosphorus requirements for pigs in different bodyweight ranges using a meta-analysis

  • Jeon, Se Min;Hosseindoust, Abdolreza;Ha, Sang Hun;Kim, Tae Gyun;Mun, Jun Young;Moturi, Joseph;Lee, SuHyup;Choi, Yo Han;Lee, Sang Deok;Sa, Soo Jin;Kim, Jin Soo
    • Journal of Animal Science and Technology
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    • v.63 no.4
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    • pp.827-840
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    • 2021
  • Several studies have focused on Ca and P requirements for pigs. These requirements are estimated from their retention and bone formation. However, modern pig breeds have different responses to dietary Ca and P than traditional breeds, and their requirements are expected to change on an annual basis. Besides individual Ca and P needs, the Ca to P ratio (Ca/P) is an important factor in determining requirements. This study aimed to implement a linear and quadratic regression analysis to estimate Ca and P requirements based on average daily gain (ADG), apparent total tract digestibility (ATTD) of Ca (ATTD-Ca), ATTD of P (ATTD-P), and crude protein (CP) digestibility. Results show that Ca/P had linear and quadratic effects on ADG in the phytase-supplemented (PS) group in both the 6-11 kg and 11-25 kg categories. In the latter category, the CP digestibility was linearly increased in response to increasing Ca/P in the without-phytase (WP) group. In the 25-50 kg category, there was a linear response of ADG and linear and quadratic responses of CP digestibility to Ca/P in the PS group, while a linear and quadratic increase in CP digestibility and a quadratic effect on ATTD-Ca were observed in the WP group. In the 50-75 kg category, Ca/P had significant quadratic effects on ADG in the PS and WP groups, along with significant linear and quadratic effects on ATTD-Ca. In addition, Ca/P had significant quadratic effects on ATTD-P and led to a significant linear and quadratic increase in the CP digestibility in the WP group. In the 75-100 kg category, analysis showed a significant decrease in ATTD-Ca and ATTD-P in the PS and WP groups; in the latter, ATTD-P and ATTD-Ca were linearly decreased by increasing Ca/P. In conclusion, our equations predicted a higher Ca/P in the 6-25 kg bodyweight categories and a lower Ca/P in the 50-100 kg category than that recommended in the literature.

A Study on the Influence of Elderly Household Characteristics on Housing Consumption according to Public Pension Receipt (중·고령자 가구의 소득의 특성이 주택소비규모에 미치는 영향: 공적연금수령유무를 중심으로)

  • Jung, Sang Joon;Lee, Chang Moo;Shin, Hye Young
    • Korea Real Estate Review
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    • v.28 no.1
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    • pp.105-114
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    • 2018
  • According to Statistics Korea, South Korea has entered the realm of the "aging society" with the rapid development of the country's population. Researchers anticipate that the extremely high (73%) ratio of real estate property to total assets for mid-age to aged households in South Korea that do not have a fixed income may cause serious problems in the future. For example, the real estate market in South Korea may be bombarded with properties listed for sale, causing the average property price to drop due to the abundant supply. Although this prediction may be reasonable, this concept has excluded the idea of pension (which is crucial as it can be considered a consistent and fixed income) due to the limited amount of available data thereon; as such, it is important to include this factor to improve the pertinent research. Thus, this research was conducted using the data from the $3^{rd}$ and $5^{th}$ Korea Retirement and Income Study. For the study results, it was found that variables such as net asset, gender, education, and number of family members have the same impact as that found in the previous studies. To extend from here, two new factors were introduced: the existence of pensions and the amount of pension received by a household. From there, it was found that the existence of a consistent and fixed income such as a pension has led to an increase in housing consumption, the area of interest of the authors.

Quantification of Chloride Diffusivity in Steady State Condition in Concrete with Fly Ash Considering Curing and Crack Effect (재령 및 균열효과를 고려한 플라이애시 콘크리트의 정상상태 염화물 확산 특성의 정량화)

  • Yoon, Yong-Sik;Cheon, Ju-Hyun;Kwon, Seung-Jun
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.7 no.2
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    • pp.109-115
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    • 2019
  • In case of the cracks in concrete, the penetration of deterioration ions such as chloride ions in to cracks is accelerated. According to the penetration of chloride ions, structural and durability problems to RC(Reinforced Concrete) structures are caused. In this study, the accelerated chloride diffusion coefficient which is in steady state is evaluated for 2 year aged normal and high strength FA(Fly Ash) concrete, after a range of crack depths are induced up to 1.0 mm in 56 aged day. Considering crack effect by linear regression analysis, high strength concrete has slightly less increasing ratio of diffusion coefficient by crack than normal strength concrete, and diffusion coefficient increases non-linearly as crack width is increased. Also, In two types of concrete, crack effect decrease as the curing period increase. In the case of quantifying crack and curing effect by using exponential function form, the coefficients of determination are higher than those of linear regression analysis. Under steady state, it is thought that there is not a high correlation between the crack effect and the curing effect, and considering the two independent effects, it is believed that reasonable prediction equation for diffusion of concrete with crack can be proposed.

Prediction of the human in vivo antiplatelet effect of S- and R-indobufen using population pharmacodynamic modeling and simulation based on in vitro platelet aggregation test

  • Noh, Yook-Hwan;Han, Sungpil;Choe, Sangmin;Jung, Jin-Ah;Jung, Jin-Ah;Hwang, Ae-Kyung;Lim, Hyeong-Seok
    • Translational and Clinical Pharmacology
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    • v.26 no.4
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    • pp.160-165
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    • 2018
  • Indobufen ($Ibustrin^{(R)}$), a reversible inhibitor of platelet aggregation, exists in two enantiomeric forms in 1:1 ratio. Here, we characterized the anti-platelet effect of S- and R-indobufen using response surface modeling using $NONMEM^{(R)}$ and predicted the therapeutic doses exerting the maximal efficacy of each enantioselective S- and R-indobufen formulation. S- and R-indobufen were added individually or together to 24 plasma samples from drug-naïve healthy subjects, generating 892 samples containing randomly selected concentrations of the drugs of 0-128 mg/L. Collagen-induced platelet aggregation in platelet-rich plasma was determined using a Chrono-log Lumi-Aggregometer. Inhibitory sigmoid $I_{max}$ model adequately described the anti-platelet effect. The S-form was more potent, whereas the R-form showed less inter-individual variation. No significant interaction was observed between the two enantiomers. The anti-platelet effect of multiple treatments with 200 mg indobufen twice daily doses was predicted in the simulation study, and the effect of S- or R-indobufen alone at various doses was predicted to define optimal dosing regimen for each enantiomer. Simulation study predicted that 200 mg twice daily administration of S-indobufen alone will produce more treatment effect than S-and R-mixture formulation. S-indobufen produced treatment effect at lower concentration than R-indobufen. However, inter-individual variation of the pharmacodynamic response was smaller in R-indobufen. The present study suggests the optimal doses of R-and S-enantioselective indobufen formulations in terms of treatment efficacy for patients with thromboembolic problems. The proposed methodology in this study can be applied to the develop novel enantio-selective drugs more efficiently.

Development of Productivity Prediction Model according to Choke Size and Gas Injection Rate by using ANN(Artificial Neural Network) at Oil Producer (오일 생산정에서 쵸크사이즈와 가스주입량에 따른 생산성 예측 인공신경망 모델 개발)

  • Han, Dong-kwon;Kwon, Sun-il
    • Journal of the Korean Institute of Gas
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    • v.22 no.6
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    • pp.90-103
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    • 2018
  • This paper presents the development of two ANN models which can predict an optimum production rate by controlling choke size in oil well, and gas injection rate in gas-lift well. The input data was solution gas-oil ratio, water cut, reservoir pressure, and choke size or gas injection rate. The output data was wellhead pressure and production rate. Firstly, a range of each parameters was decided by conducting sensitive analysis of input data for onshore oil well. In addition, 1,715 sets training data for choke size decision model and 1,225 sets for gas injection rate decision model were generated by nodal analysis. From the results of comparing between the nodal analysis and the ANN on the same reservoir system showed that the correlation factors were very high(>0.99). Mean absolute error of wellhead pressure and oil production rate was 0.55%, 1.05% with the choke size model, respectively. And the gas injection rate model showed the errors of 1.23%, 2.67%. It was found that the developed models had been highly accurate.

Development of maintenance cost estimation method considering bridge performance changes (교량 성능변화를 고려한 유지관리비용 추계분석 방법 개발)

  • Sun, Jong-Wan;Lee, Huseok;Park, Kyung-Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.12
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    • pp.717-724
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    • 2018
  • To prepare for the explosive increase in maintenance costs of bridges according to the aging of infrastructure, future maintenance costs of bridges should be predicted. For this purpose, the management status of bridges was investigated and modeled as the upper limit of the performance level and the target management level according to the life cycle. This paper proposes methodologies and procedures for estimating the bridge maintenance costs using two models and existing cost and performance prediction models that consist of unit repair cost model according to the safety score, performance degradation model of bridges, unit reconstruction cost, and average reconstruction time. To verify the applicability, future maintenance costs can be forecasted for specific management agency considering the number of bridges, degree of aging, and current management status. As a result, it is possible to obtain the maintenance cost and safety level of an individual bridge level for each year. In addition, by summing them up to the agency level, the average safety score, ratio of the safety level, inspection costs, repair costs, and reconstruction costs can be obtained. In a further study, the changes in maintenance costs can be analyzed according to the changes in the target management levels using the developed method. The optimal management level can be suggested by reviewing the results.

A Study of Hazard Analysis and Monitoring Concepts of Autonomous Vehicles Based on V2V Communication System at Non-signalized Intersections (비신호 교차로 상황에서 V2V 기반 자율주행차의 위험성 분석 및 모니터링 컨셉 연구)

  • Baek, Yun-soek;Shin, Seong-geun;Ahn, Dae-ryong;Lee, Hyuck-kee;Moon, Byoung-joon;Kim, Sung-sub;Cho, Seong-woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.222-234
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    • 2020
  • Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

Analysis of Hydraulic Fracture Geometry by Considering Stress Shadow Effect during Multi-stage Hydraulic Fracturing in Shale Formation (셰일저류층의 다단계 수압파쇄에서 응력그림자 효과를 고려한 균열형태 분석)

  • Yoo, Jeong-min;Park, Hyemin;Wang, Jihoon;Sung, Wonmo
    • Journal of the Korean Institute of Gas
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    • v.25 no.1
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    • pp.20-29
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    • 2021
  • During multi-stage fracturing in a low permeable shale formation, stress interference occurs between the stages which is called the "stress shadow effect(SSE)". The effect may alter the fracture propagation direction and induce ununiform geometry. In this study, the stress shadow effect on the hydraulic fracture geometry and the well productivity were investigated by the commercial full-3D fracture model, GOHFER. In a homogeneous reservoir model, a multi-stage fracturing process was performed with or without the SSE. In addition, the fracturing was performed on two shale reservoirs with different geomechanical properties(Young's modulus and Poisson's ratio) to analyze the stress shadow effect. In the simulation results, the stress change caused by the fracture created in the previous stage switched the maximum/minimum horizontal stress and the lower productivity L-direction fracture was more dominating over the T-direction fracture. Since the Marcellus shale is more brittle than more dominating over the T-direction fracture. Since the Marcellus shale is more brittle than the relatively ductile Eagle Ford shale, the fracture width in the former was developed thicker, resulting in the larger fracture volume. And the Marcellus shale's Young's modulus is low, the stress effect is less significant than the Eagle Ford shale in the stage 2. The stress shadow effect strongly depends on not only the spacing between fractures but also the geomechanical properties. Therefore, the stress shadow effect needs to be taken into account for more accurate analysis of the fracture geometry and for more reliable prediction of the well productivity.

Development of suspended solid concentration measurement technique based on multi-spectral satellite imagery in Nakdong River using machine learning model (기계학습모형을 이용한 다분광 위성 영상 기반 낙동강 부유 물질 농도 계측 기법 개발)

  • Kwon, Siyoon;Seo, Il Won;Beak, Donghae
    • Journal of Korea Water Resources Association
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    • v.54 no.2
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    • pp.121-133
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    • 2021
  • Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.