• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.225-227
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• 2003

Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.

• 한국도로학회:학술대회논문집
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• 2008.10a
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• pp.93-102
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• 2008

An energy based crack growth model is developed in this study to simulate the propagation of top-down cracking in asphalt pavements. A viscoelastic fracture mechanics approach, generalized J integral, is employed to model the crack growth of asphalt concrete. Laboratory fatigue crack propagation tests for three different asphalt mixtures are performed at various load levels, frequencies and temperatures. Disk-shaped specimens with a proper loading fixture and crack growth monitoring system are selected for the tests. It is observed from the tests that the crack propagation model based on the generalized J integral is independent of load levels and frequencies, while the traditional Paris' law model based on stress intensity factor is dependent of loading frequencies. However, both models are unable to take care of the temperature dependence of the mixtures. The fatigue crack propagation model proposed in this study has a good agreement between experimental and predicted crack growth lives, which implies that the energy based J integral could be a better parameter to describe fatigue crack propagation of viscoelastic materials such as asphalt mixtures.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.292-298
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• 2019

Mobile-based software development methodology has been vigorously researched from using object-oriented development methodology and component-based development methodology previous structural developing methodology. There are two types of OS in mobile platform which are android and iOS. There is a problem that the application to be developed is developed depending on the device type. To resolve this problem, first, the system structure and design method should be managed effectively. Second, a basic design guide that can be commonly adapted to the each project is required. In this paper, we define a mobile cross platform meta model based on MDA-development methodology, focusing on reusability, portability and interoperability about non - dependent part of the mobile platform. If the proposed meta-model is applied to manage the related information and all the types of Mobile-Apps become available through independent mobile app development process, henceforward, it will be much of help establishing formulaic mobile-app developmental methodology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.1
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• pp.25-34
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• 2004

Common Criteria(CC, ISO/IEC 15408) is an international standard for evaluation of Information Suity Systems(ISS). There need a suitable evidence of estimation of evaluation cost in an evaluation facility under the CC-based evaluation and assurance scheme. In this paper, we propose an evaluation effort model, which is based not only on assurance-level but also on product-type of ISS, by means of real experience of real evaluators, use-ratio concept and the Function Point of security function. The model is based not on a real evaluation environment of evaluation facility, but on CC, public PPs and product specific STs. Our result might be used as a basic model for estimation of evaluation cost and time of ISS in an CC-based evaluation and assurance scheme.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.371-388
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• 2021

A novel flexibility-based beam-foundation model for inelastic analyses of beams resting on foundation is presented in this paper. To model the deformability of supporting foundation media, the Winkler-Pasternak foundation model is adopted. Following the derivation of basic equations of the problem (strong form), the flexibility-based finite beam-foundation element (weak form) is formulated within the framework of the matrix virtual force principle. Through equilibrated force shape functions, the internal force fields are related to the element force degrees of freedom. Tonti's diagrams are adopted to present both strong and weak forms of the problem. Three numerical simulations are employed to assess validity and to show effectiveness of the proposed flexibility-based beam-foundation model. The first two simulations focus on elastic beam-foundation systems while the last simulation emphasizes on an inelastic beam-foundation system. The influences of the adopted foundation model to represent the underlying foundation medium are also discussed.

• Geomechanics and Engineering
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• v.29 no.5
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• pp.487-496
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• 2022

Most of the pile's vertical static load tests in construction sites are the proof load tests, which is difficult to accurately estimate the ultimate bearing capacity and analyze the reliability of piles. Therefore, a reliability analysis method based on the proof load-settlement (Q-s) data is proposed in this study. In this proposed method, a simple ultimate limit state function based on the hyperbolic model is established, where the random variables of reliability analysis include the model factor of the ultimate bearing capacity and the fitting parameters of the hyperbolic model. The model factor M = R_uR / R_uP is calculated based on the available destructive Q-s data, where the real value of the ultimate bearing capacity (R_uR) is obtained by the complete destructive Q-s data; the predicted value of the ultimate bearing capacity (R_uP) is obtained by the proof Q-s data, a part of the available destructive Q-s data, that before the predetermined load determined by the pile test report. The results demonstrate that the proposed method can easy and effectively perform the reliability analysis based on the proof Q-s data.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.120-120
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• 2020

Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

• Geomechanics and Engineering
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• v.36 no.4
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• pp.381-390
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• 2024

The introduction of bio-based materials has been recommended in the geotechnical engineering field to reduce environmental pollutants such as heavy metals and greenhouse gases. However, bio-treated soil methods face limitations in field application due to short research periods and insufficient verification of engineering performance, especially when compared to conventional materials like cement. Therefore, this study aimed to develop a machine learning model for predicting the unconfined compressive strength, a representative soil property, of biopolymer-based soil treatment (BPST). Four machine learning algorithms were compared to determine a suitable model, including linear regression (LR), support vector regression (SVR), random forest (RF), and neural network (NN). Except for LR, the SVR, RF, and NN algorithms exhibited high predictive performance with an R² value of 0.98 or higher. The permutation feature importance technique was used to identify the main factors affecting the strength enhancement of BPST. The results indicated that the unconfined compressive strength of BPST is affected by mean particle size, followed by biopolymer content and water content. With a reliable prediction model, the proposed model can present guidelines prior to laboratory testing and field application, thereby saving a significant amount of time and money.

• Steel and Composite Structures
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• v.52 no.4
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• pp.475-485
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• 2024

The mechanical behavior of the steel tube encased high-strength concrete (STHC) composite walls under constant axial load and cyclically increasing lateral load was studied. Conclusions are drawn based on experimental observations, grey evolutionary algorithm and finite element (FE) simulations. The use of steel tube wall panels improved the load capacity and ductility of the specimens. STHC composite walls withstand more load cycles and show more stable hysteresis performance than conventional high strength concrete (HSC) walls. After the maximum load, the bearing capacity of the STHC composite wall was gradually reduced, and the wall did not collapse under the influence of the steel pipe. For analysis of the bending capacity of STHC composite walls based on artificial intelligence tools, an analysis model is proposed that takes into account the limiting effect of steel pipes. The results of this model agree well with the test results, indicating that the model can be used to predict the bearing capacity of STHC composite walls. Based on a reasonable material constitutive model and the limiting effect of steel pipes, a finite element model of the STHC composite wall was created. The finite elements agree well with the experimental results in terms of hysteresis curve, load-deformation curve and peak load.