• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.113-124
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• 2020

Social movements to improve the performance of buildings through remodeling of aging apartment houses are being captured. To this end, the remodeling construction cost analysis, structural analysis, and political institutional review have been conducted to suggest ways to activate the remodeling. However, although the method of analyzing construction cost for remodeling apartment houses is currently being proposed for research purposes, there are limitations in practical application possibilities. Specifically, In order to be used practically, it is applicable to cases that have already been completed or in progress, but cases that will occur in the future are also used for construction cost analysis, so the sustainability of the analysis method is lacking. For the purpose of this, we would like to suggest an automated estimating method. For the sustainability of construction cost estimates, Deep-Learning was introduced in the estimating procedure. Specifically, a method for automatically finding the relationship between design elements, work types, and cost increase factors that can occur in apartment remodeling was presented. In addition, Monte Carlo Simulation was included in the estimation procedure to compensate for the lack of uncertainty, which is the inherent limitation of the Deep Learning-based estimation. In order to present higher accuracy as cases are accumulated, a method of calculating higher accuracy by comparing the estimate result with the existing accumulated data was also suggested. In order to validate the sustainability of the automated estimates proposed in this study, 13 cases of learning procedures and an additional 2 cases of cumulative procedures were performed. As a result, a new construction cost estimating procedure was automatically presented that reflects the characteristics of the two additional projects. In this study, the method of estimate estimate was used using 15 cases, If the cases are accumulated and reflected, the effect of this study is expected to increase.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.158-163
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• 2012

This study is concerned with the estimation of wind speeds for return period in cellularized district of Busan by the recent meteorological data. Recently standard of the wind load in Busan area is determined by using meteorological wind speed data which is observed on Automated Synoptic Observing System(ASOS) only. Applying the existing basic wind speed that is 40m/s to the construction design of Busan area is inefficient. Because the wind speeds of Busan area show different amounts depend on the location of cellularized district. This research analyze the observed data of wind speeds of cellularized district in Busan based on Automate Weather System(AWA). In addition that we compute regional wind speeds for return period by using Gumbel distribution and study and compare with the existing basic wind speeds after evaluating appropriateness by Hazen's plot method.

• Journal of Biomedical Engineering Research
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• v.17 no.1
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• pp.99-108
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• 1996

Diverse digital filters have been designed previously to eliminate powerline(AC) interference in the electrocardiouam. This paper describes filtering methods which have been developed recursive notch, adaptive, IEF(Incremental Estimation Filter) and proposes a new AIEF(Advanced Incremental Estimation Filter) method. The performances of these filters are compared on artificial signals as well as actual ECG signals with the aid of validated CSE(Common Standards for Quantitative Electrocardiowaphy). AC interference in this database is shown to exhibit two qualities especially relevant to filter design : considerable deviations from a nominal 60Hz frequency and substantial noise at higher harmonics.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.93-96
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• 2010

현재 국내외에서 Building Information Modeling을 적용한 여러 분야의 연구가 활발하게 진행되고 있으며, 일부 국외에서는 3D 기반의 견적을 실제 프로젝트에 반영하고 있다. 반면, 국내 건설 프로젝트에서는 여전히 2D 설계도면과 물량산출 프로그램을 이용하여 견적이 이루어지고 있다. 작업의 신속성 및 정확성을 중요시하는 국내 견적 문화에서는 3D 기반의 물량산출 방식 도입을 부정적으로 바라보는 시각이 있으나, 향후 건설 산업의 경쟁력 확보를 위해서 3D 기반 견적작업이 필요하다. 이에 국외에서 상용화된 견적 시스템을 국내 건설 프로젝트에 적용한 결과, 몇 가지 한계점이 있는 것으로 드러나 국내 견적 방식에 적합한 3D기반의 물량산출 프로그램 개발이 절실한 상황이다. 따라서 본 연구에서는 국내 건설 산업에서의 물량 산출 특성을 반영한 공법기반 견적자동화 시스템 개발 및 검증을 통해 국내 3D 기반의 견적 도입을 앞당기고자 한다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.505-507
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• 2003

This paper describes techniques for the automated creation of geometric 3D models of the urban area us ing two 2D laser scanners and aerial images. One of the laser scanners scans an environment horizontally and the other scans vertically. Horizontal scanner is used for position estimation and vertical scanner is used for building 3D model. Aerial image is used for registration with scan data. Those models can be used for virtual reality, tele-presence, digital cinematography, and urban planning applications. Results are shown with 3D point cloud in urban area.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1915-1923
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• 2011

For automated guidance control of a magnetically guided-all wheel steered vehicle, it is necessary to have information about position and orientation of the vehicle, and deviations from the reference path in real time. The magnet reference system considered here consists of three magnetic sensors mounted on the vehicle and magnetic markers, which are non-equidistantly buried in the road. This paper presents an observer to estimate such position and orientation at the center of gravity of the vehicle. This algorithm is based on the simple kinematic model of vehicle and uses the data of wheel velocity, steering angle, and the discrete measurements of marker positions. Since this algorithm requires the exact values of initial states, we have also proposed an algorithm of determining the initial position and orientation from the 16 successive magnet pole data, which are given by the magnetic measurement system(MMS). The proposed algorithm is capable of continuing to estimate for the case that the magnetic sensor fail to measure up to three successive magnets. It is shown through experimental data that the proposed algorithm works well within permissible error range.

• Journal of Welding and Joining
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• v.27 no.3
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• pp.67-72
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• 2009

The flux cored arc welding (FCAW) process is one of the most frequently employed and important welding process due to high productivity and excellent workability. The process is performed either as an automated process or as a semi-automatic process. In FCAW process, welding voltage has been considered as a qualitative indication of arc length. But it is necessary to let welding operators know, maintain and manage the arc length directly by estimating and displaying it. In this study, to develop arc length estimation technique, we measured a welding circuit resistance($R_sc$) and then we calculated welding circuit voltage drop($V_sc$). Also, we measured arc peak voltage($V_ap$). By subtracting $V_sc$ from $V_arc$, we can easily calculate net arc voltage drop($V_arc$). Consequently, we suggested arc length estimating equation and basic algorithm by regressive analyzing the relationship between net arc voltage drop($V_arc$) and real arc length(Larc) measured by high speed camera. Therefore, arc length can be predicted by just monitoring welding current and voltage.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.294-295
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• 2018

Nowadays, the construction industry utilizes 3D models in the designing process, on which research is being conducted to establish an automated system for project cost estimation in connection with information related to construction such as material unit costs and wages, beyond the level of design interference review and construction quantity estimation. In this process, the project cost is estimated in connection with unit price data after takeoff the quantity based on the 3D model attributes and data types. A way to reduce cost and risk would be first developing prototypes of some of essential buildings and works, comparing and validating the outcomes, and then extending to the whole scope, because estimates differ on the basis of the scope and level of 3D design models as well as the data accuracy. This study analyzes case studies of project cost estimation by computing the quantity on the basis of 3D model in the construction industry and explores methodologies and management measures applicable for estimating nuclear power plant construction project costs.

• Journal of Animal Science and Technology
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• v.61 no.3
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• pp.122-137
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• 2019

Methane, one of the important greenhouse gas, has a higher global warming potential than that of carbon dioxide. Agriculture, especially livestock, is considered as the biggest sector in producing anthropogenic methane. Among livestock, ruminants are the highest emitters of enteric methane. Methanogenesis, a continuous process in the rumen, carried out by archaea either with a hydrogenotrophic pathway that converts hydrogen and carbon dioxide to methane or with methylotrophic pathway, which the substrate for methanogenesis is methyl groups. For accurate estimation of methane from ruminants, three methods have been successfully used in various experiments under different environmental conditions such as respiration chamber, sulfur hexafluoride tracer technique, and the automated head-chamber or GreenFeed system. Methane production and emission from ruminants are increasing day by day with an increase of ruminants which help to meet up the nutrient demands of the increasing human population throughout the world. Several mitigation strategies have been taken separately for methane abatement from ruminant productions such as animal intervention, diet selection, dietary feed additives, probiotics, defaunation, supplementation of fats, oils, organic acids, plant secondary metabolites, etc. However, sustainable mitigation strategies are not established yet. A cumulative approach of accurate enteric methane measurement and existing mitigation strategies with more focusing on the biological reduction of methane emission by direct-fed microbials could be the sustainable methane mitigation approaches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.5-7
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• 2021

Motion capture data files for pose estimation may have inaccurate data depending on the surrounding environment and the degree of movement, so it is necessary to correct it. In the past, inaccurate data was restored with post-processing by people, but recently various kind of neural networks such as LSTM and R-CNN are used as automated method. However, since neural network-based data restoration methods require a lot of computing resource, this paper proposes a method that reduces computing resource and maintains data restoration rate compared to neural network-based method. The proposed method automatically restores inaccurate motion capture data by using posture measurement data (c3d). As a result of the experiment, data restoration rates ranged from 89% to 99% depending on the degree of inaccuracy of the data.