• Korean Journal of Construction Engineering and Management
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• v.23 no.5
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• pp.56-64
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• 2022

Although pilot projects have been actively carried out from 2017 to present to institutionalize CM at Risk, one of the major tasks for innovation in the construction industry, standards and processes related to Design VE, a key tool for determining GMP in the pre-construction phase, have not yet been established. Therefore, through research and operation status related to CM at Risk and Design VE, and survey on project participants' perception, the problem of the existing design VE process was derived, and the design VE process suitable for the CM at Risk project was proposed. The application plan was proposed in three aspects: Schedule, Cycle, and Process, and the appropriateness and applicability were verified through FGI. The results of this study are expected to be used as basic data on the establishment and legislation of order standards to be made in the future.

• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.135-142
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• 2022

It is impossible to know the amount of pork primal cut by pig carcass grade which is determined only by carcass weight and backfat thickness in the Korean Pig Carcass System. The aim of this study was to investigate the correlation between the pig carcass grade and the amount of pork primal cut estimated with AutoFom III. A total of 419,321 Landrace, Yorkshire, and Duroc (LYD) pigs were graded with the Korean Pig Carcass Grade System. Amounts of belly, neck, loin, tenderloin, spare ribs, shoulder, and ham were estimated with AutoFom III. Regression equations for seven primal cuts according to each grade were derived. There were significant differences among the three carcass grades due to heteroscedasticity variance (p < 0.0001). Three regression equations were derived from AutoFom III estimation of primal cuts according to carcass grades. The coefficient of determination of the regression equation was 0.941 for grade 1⁺, 0.982 for grade 1, and 0.993 for grade 2. Regression equations obtained from this study are suitable for AutoFom III software, a useful tool for the analysis of each pig carcass grade in the Korean Pig Carcass Grade System. The high reliability of predicting the amount of primal cut with AutoFom III is advantageous for the management of slaughterhouses to optimize their product sorting in Korea.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Structural Engineering and Mechanics
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• v.86 no.4
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• pp.473-486
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• 2023

Nowadays, urban centers are increasingly vertical, making architects and engineers look for more efficient tools to analyze the effects of wind on tall buildings. Topology optimization can be used as an efficient tool for the design of bracing systems. Therefore, this work obtained the wind loads that act in the CAARC building, following the Brazilian standard NBR 6123/1988 and using Computational Fluid Dynamics. Four loading situations were considered, using the SIMP and BESO methods to optimize two-dimensional structures. A comparison between the SIMP and BESO methods is presented, showing the differences in the geometry of the solution found by both methods, the percentage variation in the objective function values and the dimensionless processing time. The solutions obtained through the loads obtained by the Brazilian standard are also compared with the numerical solutions obtained by CFD. The results show that the BESO method presented more rigid structures compared to the SIMP method. The bracing structures obtained with the SIMP method always present similar patterns in the distribution and quantity of bars, in contrast to the BESO method where no characteristic topology pattern was observed. It was concluded that even though the structures obtained by the BESO method presented greater stiffness, the SIMP method was less susceptible to the methodology used for the determination of wind loads. Additionally, it was evident the great potential that the combination topology optimization and computational wind engineering have in the design of bracing systems of high functional and aesthetic standards.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.93-93
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• 2020

미래 기후변화로 인해 집중 호우, 가뭄의 발생 빈도가 증가하고, 물 부족, 수질 오염 등으로 인해 합리적인 수자원 계획 및 관리의 중요성이 증가하고 있다. 기후변화는 유역간 물 이동량 뿐만 아니라 유역의 하천 유량 및 수질에 영향을 미치기 때문에, 물 이동량이 많은 유역에서는 기후변화 시나리오를 고려한 하천 유량 및 수질 변화를 정량적으로 평가해야 한다. 만경강 유역(1,602 ㎢)은 하류 지역에 비옥한 평야가 분포되어 있어 농업이 발달한 유역이나, 유역 내 가용 용수가 부족하여 인근에 위치한 금강 용담댐의 발전용수를 공급받아 사용하고 있다. 발달된 농경지로부터 발생되는 비점오염, 축산 점오염원으로 인한 수질 문제가 심각할 뿐만 아니라, 만경강의 수질은 궁극적으로 새만금호에 영향을 미치기 때문에 더욱 엄격한 관리가 필요하다. 따라서, 본 연구에서는 유역간 물이동량, 취수량 등을 고려하여 Soil and Water Assessment Tool(SWAT) 모형을 구축하였다. 2개의 수위-유량 관측소의 일자료와 2개의 수질관측소 월자료를 이용하여 보정(2012~2014) 및 검증(2016~2018)을 수행한 결과 유출량의 평균 Nash-Sutcliffe model Efficiency (NSE)는 0.49 ~ 0.51, SS, T-N, 그리고 T-P에 대한 평균 결정계수(Coefficient of determination, R²)는 0.73, 0.78, 0.72였다. 미래 기후변화에 따른 유역의 수문 및 수질 변화 분석을 위해 증발산량 산정이 가능한 RCP 8.5 기후변화 시나리오에 STARDEX를 활용하여 가장 습윤한 시나리오 및 가장 건조한 기후변화 시나리오를 각각 1개를 선정할 것이다. 선정된 시나리오를 구축된 SWAT 모형에 적용하여 미래 유역간 물이동이 유역의 하천 유량 및 수질에 미치는 영향을 미래 평가기간(S1:2011~2040, S2:2041~2070, S3:2071~2100)으로 구분하여 분석할 것이다.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.226-233
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• 2023

Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.21-32
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• 2008

Flood forecasting is a very important tool as one of nonstructural measures for reduction of flood damages in life and property and its accuracy is also an important factor. However, when we apply the Storage Function Model(SFM) which is mainly used for the flood forecasting system in Korea, the determination of the parameters is very important but it is difficult. So, the parameters have been calibrated by using an empirical formulas and judgement of hydrologist. Hence, in this study we perform the sensitivity analysis to understand the parameter characteristics and establish the ranges of parameters of the SFM. Also we do the parameter calibration by using the optimization techniques and objective functions, and evaluate their performances. Especially, we suggest a method to determine proper parameters by using a objective function which can be obtained from flood events. So, we use the suggested method for parameter estimation and compare the estimated parameters with the previously reported parameters. As a result of the application, the estimated parameters by the suggested method showed better than them from the previously reported parameters.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.124-124
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• 2022

가뭄시 유역 수문량은 하천수/지하수 취·배수, 하·폐수방류량, 용수재이용 등 복잡한 물이용체계에 따른 영향이 크지만 기존 가뭄시 수문량 평가는 이러한 복잡한 물이용체계를 고려하지 않아 정도 높은 예측에 어려움이 있다. 따라서 가뭄시 유력 내 상세물이용체계 및 수문환경특성 인자들의 상호작용 규명을 통한 정도 높은 수문량 평가 기술의 개발이 시급하다. 대하천 주변 광역상수도 공급지역은 가뭄 발생시에도 안정적으로 물이용이 가능하나, 중소하천을 수원으로 하는 하천의 상류지역은 가뭄시 물공급 안정성이 취약하다. 따라서 중소하천을 대상으로 가뭄시 물 공급시설의 효율적 운영, 물부족 위험도 평가, 가용수자원의 최적이용 등 종합적인 대책 마련을 위해서는 신뢰성 높은 수문량(하천유출량 및 수자원가용량) 예측이 필요하다. 가뭄에 따른 중소하천유역의 수문학적 유출거동을 평가하기 위한 해석 모형으로는 국내의 복잡한 유역 수문환경특성을 평가하기 위해 개발된CAT (Catchment hydrologic cycle Assessment Tool)(김현준 등, 2012)을 이용하였다. CAT은 기후변화나 토지이용변화에 따른 유역의 수문환경특성 변동성을 정량적으로 평가하기 위해 개발된 모형이다. CAT은 인위적인 물이용체계 즉, 광역급수, 용수재이용, 지하수 취수, 하천수 취·배수 등을 분석하기 위한 툴을 제공하므로 가뭄시 상세물이용체계에 따른 시·공간적 수문환경특성 분석 및 수문량 평가를 위한 최적의 모형으로 선정하였다. 본 연구에서는 중소하천유역의 수문량 예측기술 실용화 기반을 마련하기 위하여 낙동강, 금강, 영산/섬진강 중권역을 대상으로 정밀 시공간 수문량을 평가하였다. 각 권역별 보정지점을 기준으로 관측유량 자료와 모의자료의 1:1비교를 통해 수문량 예측정확도를 산정하였으며, 모형효율(Nash Sutcliffe Efficiency, NSE) 및 결정계수(Coefficient of Determination, R²)의 권역별 평균은 NSE 72%, R2 79%로 나타났으며, 대부분의 지점에서 70% 이상을 나타내어 환경부 및 지자체의 가뭄시 물관리 정책을 지원하기 위한 실용화 기반을 마련하였다.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.487-497
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• 2023

Penetration rate (PR) and penetration depth (Pe) are crucial parameters for estimating the cost and time required in tunnel construction using tunnel boring machines (TBMs). This study focuses on investigating the impact of rock strength on PR and Pe through full-scale experiments. By conducting controlled tests on rock-like specimens, the study aims to understand the contributions of various ground parameters and machine-operating conditions to TBM excavation performance. An earth pressure balanced (EPB) TBM with a sectional diameter of 3.54 m was utilized in the experiments. The TBM excavated rocklike specimens with varying uniaxial compressive strength (UCS), while the thrust and cutterhead rotational speed were controlled. The results highlight the significance of the interplay between thrust, cutterhead speed, and rock strength (UCS) in determining Pe. In high UCS conditions exceeding 70 MPa, thrust plays a vital role in enhancing Pe as hard rock requires a greater thrust force for excavation. Conversely, in medium-to-low UCS conditions less than 50 MPa, thrust has a weak relationship with Pe, and Pe becomes directly proportional to the cutterhead rotational speed. Furthermore, a strong correlation was observed between Pe and cutterhead torque with a determination coefficient of 0.84. Based on these findings, a predictive model for Pe is proposed, incorporating thrust, TBM diameter, number of disc cutters, and UCS. This model offers a practical tool for estimating Pe in different excavation scenarios. The study presents unprecedented full-scale TBM excavation results, with well-controlled experiments, shedding light on the interplay between rock strength, TBM operational variables, and excavation performance. These insights are valuable for optimizing TBM excavation in grounds with varying strengths and operational conditions.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.191-204
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• 2024

IOT has carried out important function in converting the traditional fitness care corporation. With developing call for in population, traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings. The worldwide is handling devastating developing antique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens. There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized, right blanketed care to prevent and manipulate excessive coronial situations. Many tech orientated packages related to Health Monitoring have been delivered these days as taking advantage of net boom everywhere on globe, manner to improvements in cellular and in IOT generation. Such as optimized indoor networks insurance, community shape, and fairly-low device fee performances, advanced tool reliability, low device energy consumption, and hundreds higher unusual common usual performance in network safety and privacy. Studies have highlighted fantastic advantages of integrating IOT with health care location and as era is improving the rate also cannot be that terrific of a problem. However, many challenges in this new paradigm shift notwithstanding the fact that exist, that need to be addressed. So the out most purpose of this research paper is 3 essential departments: First, evaluation of key elements that drove the adoption and boom of the Internet of factors based totally domestic some distance off monitoring; Second, present fashionable improvement of IOT in home a long manner off monitoring shape and key building gadgets; Third, communicate future very last effects and distinct guidelines of such type a long way off monitoring packages going ahead. Such Research is a wonderful manner in advance now not outstanding in IOT Terminology but in standard fitness care location.