• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.109-110
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• 2015

Estimation of rebar quantity may be used as an index to evaluate the economic feasibility of structural designs. However, when using the software to estimate the rebar quantity, there may be some limitations such as data loss caused by human errors and estimation delays caused by increased input time, since the information on arrangement of rebar is inserted manually. To solve the problems of such quantity estimation software, it is necessary to develop a method on automatic input/output of structural design information for quantity estimation and an algorithm for accurate estimation of rebar quantity. The purpose of this study is to improve the existing rebar quantity estimation by connecting with the database on information related to rebar estimation and the algorithm for rebar estimation, in order to develop an algorithm to estimate an accurate, net rebar quantity. The study result can be used as basic data for development of software for efficient structural designs and automatic framework estimation of buildings.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.43.4-43
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• 2001

This paper deals with motion identification using artificial neural network (ANN) and its application to automatic ship berthing. As ship motions are expressed by multi-term non-linear model, it is very difficult to find optimal methods for automatic ship berthing especially under environmental disturbances. In this paper, metier identification was used to estimate the effect of environmental disturbances and then the differences between values of identification and state variables are used to estimate the effect of environmental disturbances. A rule based-algorithm using the difference is suggested to cope with the effect of the disturbances. The algorithm adjusts the value of input units of ANN, which control a ship to keep desired route ...

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.21-22
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• 2023

In reinforced concrete constructions, reinforcing bar generates more CO₂ per unit weight than other construction materials. In particular, cutting and bending rebar is the main source of rebar waste in the construction industry. Rebar-cutting waste is inevitable during the construction of a reinforced concrete structure since the rebar is not manufactured as designed. Large amounts of waste can be avoided by utilizing optimal cutting patterns and schedules. This research provides a fundamental analysis of the automatic calculation of column rebar length using BIM-based shape codes to minimize cutting waste to near zero. By employing this approach in practice, it is possible to minimize the rate of rebar-cutting waste, reduce costs, shorten construction duration, and reduce CO₂ emissions. In addition, the development of this research will serve as a clue for the development of BIM-based rebar layout automation algorithms.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.4
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• pp.190-200
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• 1996

Step-by-step time integration methods are widely used for solving structural dynamics problem. One difficult yet critical choice an analyst must make is to decide an appropriate time step size. The choice of time step size has a significant effect on solution accuracy and computational expense. The objective of this research is to derive error estimate for newly developed time integration method and develop automatic time step size control algorithm for structural dynamics. A formula for computing error tolerance is derived based on desired period resolution. An automatic time step size control strategy is proposed based on a normalized local error estimate for the generalized-α method. Numerical examples demonstrate the developed strategy satisfies general design criteria for time step size control algorithm for dynamic problem.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.79-80
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• 2023

Reinforced concrete structures require large amounts of concrete and rebar in the construction stage. Rebar is a major resource for reinforced concrete structures, and generates more CO₂ per unit weight than other materials. To solve this problem, it was confirmed that the cutting waste can be close to zero when the special length of the rebar is calculated in the drawing created after structural design. However, a system for automatically calculating the length of reinforcing bars to efficiently calculate the total amount of reinforcing bars has not been established. Therefore, the objective of this study is a basic study of automatic rebar length estimate algorithm of bearing wall by using BIM-based shape codes built in Revit. The bearing wall rebar can be automatically derived using the developed model. Furthermore, through applying the developed model to the construction field, it will greatly contribute to reducing greenhouse gas emissions by reducing rebar cutting waste.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.595-602
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• 2006

Determinations of conformal map from the unit disk onto a Jordan region are reduced to solve the Theodorsen equation which is an integral equation for the boundary correspondence function. Among numerical conformal maps the Wegmann's method is well known as a Newton efficient one for solving Theodorsen equation. However this method has not so wide class of convergence. We proposed as an improved method for convergence by applying a low frequency filter to the Wegmann's method. In this paper, we investigate error analysis and propose an automatic algorithm based on this analysis.

• ETRI Journal
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• v.43 no.2
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• pp.324-331
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• 2021

Space-based automatic dependent surveillance-broadcast (ADS-B) is an important emerging augmentation of existing ground-based ADS-B systems. In this paper, the problem of space-based ultra-long-range reception processing of ADS-B signals is described. We first introduce a header detection method for accurately determining the pulse position of a weak ADS-B signal. We designed a signal encoding method, shaping method, and fitness function. We then employed a genetic algorithm to perform high-precision frequency and phase estimations of the detected weak signal. The advantage of this algorithm is that it can simultaneously estimate the frequency and phase, meaning a direct coherent demodulation can be implemented. To address the computational complexity of the genetic algorithm, we improved the ratio algorithm for frequency estimation and raised the accuracy beyond that of the original ratio algorithm with only a slight increase in the computational complexity using relatively few sampling points.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.1002-1005
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• 1995

This paper presents an enhanced preprocessing and recognition algorithm for automatic vehicle license plate recognition system. The algorithm first applies horizontal gradient filter followed by thresholding and mathematical morphology operation for preprocessing. The final stage of the preprocessing is the application of connected component analysis in order to estimate the license plate region. For the recognition of the serial numbers of the plates, we developed a very effective algorithm. We call this zerocrossing count algorithm. This paper presents a detail of this algorithm and compare the performance with a template matching algorithm which utilizes correlation coefficient.

• Journal of Ship and Ocean Technology
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• v.6 no.1
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• pp.16-26
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• 2002

In this paper, a motion identification method using neural networks is applied to automatic ship berthing to overcome disturbance effects. Motion identification is used to estimate the effect of environmental disturbance. Two rule-based algorithms have been developed to over-come disturbance. The first rule based-algorithm was designed to overcome lateral disturbance when a ship's lateral speed is affected by it. The second rule-based algorithm was also designed to overcome longitudinal disturbance when a ship's angular velocity is changed by it. Finally, numerical simulations for automatic berthing are carried out, and the suggested control system is proved to be more practical under disturbance circumstances.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.31-39
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• 2010

The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity ($\nu_{int}$) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.