• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.12-21
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• 2008

As the usage of computer systems is increasing in our lives, the reliability and safely of these systems need to be thoroughly checked through the verification techniques. As a basic formalism for several modeling methods, the finite state machine (FSM) is widely used in specification and verification of system models. And there is a technique for ing internal events of FSM in order to effectively analyze the system. However, this technique does not handle the state explosion problem since it can be applied after completely generating all the state space of the system. In this research, we provide a new approach for efficiently representing concurrent properties of FSM, the slice model and provide an efficient transition reduction method based on the slice model. Our approach is effective in time and space perspective since it is peformed by partially generating the needed system states while the existing abstraction technique can be applied to all the system states.

• Smart Structures and Systems
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• v.33 no.6
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• pp.449-463
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• 2024

Automated crack detection is crucial for structural health monitoring and post-earthquake rapid damage detection. However, realizing high precision automatic crack detection in the absence of corresponding manual labeling presents a formidable challenge. This paper presents a novel crack segmentation transfer learning method and a novel crack segmentation model called Swin-CrackFormer. The proposed method facilitates efficient crack image style transfer through a meticulously designed data preprocessing technique, followed by the utilization of a GAN model for image style transfer. Moreover, the proposed Swin-CrackFormer combines the advantages of Transformer and convolution operations to achieve effective local and global feature extraction. To verify the effectiveness of the proposed method, this study validates the proposed method on three unlabeled crack datasets and evaluates the Swin-CrackFormer model on the METU dataset. Experimental results demonstrate that the crack transfer learning method significantly improves the crack segmentation performance on unlabeled crack datasets. Moreover, the Swin-CrackFormer model achieved the best detection result on the METU dataset, surpassing existing crack segmentation models.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.89-98
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• 2004

The amount of rice yield reduction due to inundation should be estimated to analyse economic efficiency of the farmland drainage improvement projects because those projects are generally promoted to mitigate flood inundation damage to rice in Korea. Estimation of rice yield reduction will also provide information on the flood risk performance to farmers. This study presented the relationships between inundated durations and rice yield reduction rates for different rice growth stages from the observed data collected from 1966 to 2000 in Korea, and developed the rice yield reduction estimation model (RYREM). RYREM was applied to the test watershed for estimating the rice yield reduction rates and the amount of expected average annual rice yield reduction by the rainfalls with 48 hours duration, 10, 20, 50, 100, 200 years return periods.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.51-55
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• 2006

An adaptive tracking controller is presented for the vibration reduction of flexible manipulator employed in hazardous area by combining input shaping technique with sliding-mode control. The combined approach appears to be robust in the presence of severe disturbance and unknown parameter which will be estimated by least-square method in real time. In a maneuver strategy, it is found that a hybrid trajectory with a combination of low frequency mode and rigid-body mode results in better performance and is more efficient than the traditional rigid body trajectory alone which many researchers have employed. The feasibility of the adaptive tracking control approach is demonstrated by applying it to the simplified model of robot system. For the applications of the proposed technique to realistic systems, several requirements are discussed such as control stability and large system order resulted from finite element modeling.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.268-276
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• 2008

In highway construction projects, concrete pavement productivity has been challenged with constructors and decision-makers; at present there are few methods available to accurately evaluate the factors impacting on it. Any inefficient method to analyze it leads to the excessive schedule, higher rehabilitation costs, shorter service life, and reduction of ride quality. To implement these negative outcomes, constructors or decision-makers need a systematic tool that can be used to categorize the factors related to construction productivity. This paper applies multiple regression technique for productivity analysis of the Jointed Plane Concrete Pavement (JPCP), identifies the significant factors, and provides a predictive model assisting in monitoring and managing the productivity of the JPCP construction process. The completed and progressive projects are employed to derive and assess the proposed model. The results are analyzed to illustrate its capabilities.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.427-434
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• 2002

In Korea, there are recently many attempts to expand a temporary soil nailing system into a permanent soil nailing system since the first construction in 1993. In the downtown area, it is important that the relaxation of the ground is minimized in the ground excavation works. Due to these problems, soil nailing systems are often used the flexible facing such as shotcrete rather than the rigid facing such as SCW, CIP, and jet grout types in Korea. The soil nailing systems with rigid facings are used greatly however it is insufficient researches for design and analysis of soil nailing systems with rigid facings. In this study, various laboratory model tests are carried out to examining the influence the rigidity of facings on the global safety of soil nailing system, failure loads, displacement behaviour, axial force acting on the nails, and distribution of earth pressure. Also, the parametric studies are carried out for the typical section of soil nailed walls according to thickness of concrete facings and internal friction angle of soil using the numerical technique as shear strength reduction technique.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.1-5
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• 2012

Data reduction has been used widely in data mining for convenient analysis. Principal component analysis (PCA) and factor analysis (FA) methods are popular techniques. The PCA and FA reduce the number of variables to avoid the curse of dimensionality. The curse of dimensionality is to increase the computing time exponentially in proportion to the number of variables. So, many methods have been published for dimension reduction. Also, data augmentation is another approach to analyze data efficiently. Support vector machine (SVM) algorithm is a representative technique for dimension augmentation. The SVM maps original data to a feature space with high dimension to get the optimal decision plane. Both data reduction and augmentation have been used to solve diverse problems in data analysis. In this paper, we compare the strengths and weaknesses of dimension reduction and augmentation for classification and propose a classification method using data reduction for classification. We will carry out experiments for comparative studies to verify the performance of this research.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.47-61
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• 1996

An ATM switch must deal with various kinds of input sources having different traffic characteristics and it must guarantee very small value of cel loss probability, about 10$^{8}$ -10$^{12}$ , to deal with loss-sensitive traffics. In order to estimate such a rate event probability with simulation procedure, a variance reduction technique is essential for obtaining an appropriate level of precision with reduced cost. In this paper, we propose a hybrid simulation technique to achieve reduction of variance of cell loss probability estimator, where hybrid means the combination of analytical method and simulation procedure. A discrete time queueing model with multiple input sources and a finite shared buffer is considered, where the arrival process at an input source and a finite shared buffer is considered, where the arrival process at an input source is governed by an Interrupted Bernoulli Process and the service rate is constant. We deal with heterogeneous input sources as well as homogeneous case. The performance of the proposed hybrid simulation estimator is compared with those of the raw simulation estimator and the importance sampling estimator in terms of variance reduction ratios.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.2 s.257
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• pp.221-230
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• 2007

An iterated improved reduced system (IIRS) procedure combined with sub-structuring scheme for nonclassically damped structural systems is presented. For dynamic analysis of such systems, complex eigenproperties are required to incorporate properly the nonclassical damping effect. In complex structural systems, the equations of motion are written in the state space from. Thus, the number of degrees of freedom of the new equations of motion and the size of the associated eigenvalue problem required to obtain the complex eigenvalues and eigenvectors are doubled. Iterated IRS method is an efficient reduction technique because the eigenproperties obtained in each iteration step improve the condensation matrix in the next iteration step. However, although this reduction technique reduces the size of problem drastically, it is not efficient to apply this technique to a single domain finite element model with degrees of freedom over several thousands. Therefore, for a practical application of the reduction method, accompanying sub-structuring scheme is necessary. In the present study, iterated IRS method combined with sub-structuring scheme for nonclssically damped structures is developed. Numerical examples demonstrate the convergence and the efficiency of a newly developed scheme.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.559-568
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• 2017

Objective: The aim of this study is to investigate the effective managerial factors influencing dose reduction of the nozzle dam installation and removal tasks ranking within top 3 in viewpoint of average collective dose of nuclear power plant maintenance job. Background: International Commission on Radiation Protection (ICRP) recommended to reduce unnecessary dose and to minimize the necessary dose on the participants of maintenance job in radiation fields. Method: Seven sessions of nozzle dam installation and removal task logs yielded a multiple regression model with collective dose as a dependent variable and work time, number of participants, space doses before and after shield as independent variables. From the sessions in which a significant reduction in collective dose occurred, the effective managerial factors were elicited. Results: Work time was the most important factor contributing to collective dose reduction of nozzle dam installation and removal task. Introduction of new technology in nozzle dam design or maintenance job is the most important factor for work time reduction. Conclusion: With extended task logs and big data processing technique, the more accurate prediction model illustrating the relationship between collective dose reduction and effective managerial factors would be developed. Application: The effective managerial factors will be useful to reduce collective dose of decommissioning tasks as well as regular preventive maintenance tasks for a nuclear power plant.