• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.2
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• pp.91-98
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• 1989

The analysis of a single stereo model is not sufficient in applying for some large structures, therefore the precise coordinate analysis photogrammetric block adjustment method should be considered. The distribution of control points has a great influence on the error characteristics of the block adjustment results. Thus, the unit model method is applied to the photogrammentric adjustment procedure to study error characterestics with different distributions of control points. Through this study, the second order polynomial equations about bridging distance and plane error are developed in block adjustment of terrestrial photogrammetry. Comparing the block adjustment method and a single model method, root mean square error of the block adjustment method is 0.44mm, and a single model method is 1.06mm.

• Smart Structures and Systems
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• v.24 no.2
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• pp.193-207
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• 2019

This study concerns with morphing structures, e.g. as applied in the aerospace industry. A morphing aerofoil structure capable of variable geometry was developed, which was shown to be able to cater for the different aerodynamic requirements at different stages of flight. In this work, the useful and relatively simple method has been applied, which provides a direct method for calculating required morphing shape displacements via finding the most effective bar through calculating bar sensitivity to displacement and calculating set of length actuations for bar assembly to control/adjust shape imperfection of prestressable structural assemblies including complex elements ("macro-elements", e.g., the pantographic element), involving Matrix Condensation. The technique has been verified by experiments on the physical model of an aerofoil shaped morphing pantographic structure. Overall, experimental results agree well with theoretical prediction. Furthermore, the technique of multi-iteration adjustment was presented that effective in eliminating errors that occur in the practical adjustment process itself. It has been demonstrated by the experiments on the physical model of pantographic morphing structure. Finally, the study discusses identification of the most effective bars with the objective of minimal number of actuators or minimum actuation.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.888-890
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• 2003

The objective of this investigation is to establish a simple yet effective block adjustment procedure for the orthorectification of multi-orbit satellite images. The major works of the proposed scheme are: (1) adjustment of satellite‘s orbit accurately, (2) calculation of the error vectors for each tie point using digital terrain model and ray tracing technique, (3) refining the orbit using the Least Squares Filtering technique and (4) generation of the orthophotos. In the process of least squares filtering, we use the residual vectors on ground control points and tie points to collocate the orbit. In orthorectification, we use the indirect method to generate the orthoimage. Test areas cover northern Taiwan. Test images are from SPOT 5 satellite. Experimental results indicate that proposed method improves the relative accuracy significantly.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.452-455
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• 2007

3D stereoscopic viewing of large scale imagery, such as aerial photography and satellite images, needs different parallaxes relative to the display scale. For example, when a viewer sees a stereoscopic image of aerial photography, the optimal parallax of its zoom-in image should be smaller than that of its zoom-out. Therefore, relative parallax adjustment according to the display scale is required. Merely adjusting the spacing between stereo images is not appropriate because the depths of the whole image are either exaggerated or reduced entirely. This paper focuses on the improving stereoscopic viewing with a single remote sensing image and a digital surface model (DSM). We present the parallax adjustment technique to maximize the 3D realistic effect and the visual comfort. For remote sensing data, DSM height value can be regarded as disparity. There are two possible kinds of methods to adjust the relative parallax with a single image performance. One is the DSM compression technique: the other is an adjustment of the distance between the original image and its stereo-mate. In our approach, we carried out a test to evaluate the optimal distance between a single remote sensing image and its stereo-mate, relative to the viewing scale. Several synthetic stereo-mates according to certain viewing scale were created using a parallel projection model and their anaglyphs were estimated visually. The occlusion of the synthetic stereo-mate was restored by the inpainting method using the fields of experts (FoE) model. With the experiments using QuickBird imagery, we could obtain stereoscopic images with optimized parallax at varied display scales.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.473-480
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• 1998

The substructuring pseudodynamic test is a hybrid testing method consisting of a numerical simulation of the earthquake response of an analytical model and a loading test of a specimen. The substructuring pseudodynamic testing technique has been applied to various seismic experiments since it has advantages over the shaking table test to study dynamic behaviors of relatively large scale structures. However, experimental errors are inevitable in substructuring pseudodynamic testing. Some of these errors can be monitored during the test, but, due to limitations in control system, they cannot be eliminated. For example, one cannot control exactly the displacements that are actually imposed on the structures at each time step. This paper focuses on a technique to minimize the cumulative effect of such control errors for MDOF system. For this purpose, the modified posterior adjustment of the time increment from a target value $\Delta$t$_{n}$ to an adjusted value is performed to minimize the effect of the control errors for MDOF system.for MDOF system.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.372-383
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• 2011

Our study was carried out to develop the severity-adjustment model for length of stay in hospital for percutaneous coronary interventions so that we would analysis the factors on the variation in length of stay(LOS). The subjects were 1,011 percutaneous coronary interventions inpatients of the Korean National Hospital Discharge In-depth Injury Survey 2004-2006 data. The data were analyzed using t-test and ANOVA and the severity-adjustment model was developed using data mining technique. After yielding the standardized value of the difference between crude and expected length of stay, we analysed the variation of length of stay for percutaneous coronary interventions. There was variation of LOS in regional differences, size of sickbed and insurance type. The variation of length of stay controlling the case mix or severity of illness can be explained the factors of provider. This supply factors in LOS variations should be more studied for individual practice style or patient management practices and healthcare resources or environment. We expect that the severity-adjustment model using administrative databases should be more adapted in other diseases in practical.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.313-316
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• 2002

In this paper, we present an online scheme for parameter estimation of solar cell, based on the model adjustment technique and a genetic algorithm. The ideal diode model and the diode model with series and shunt resistor are used to estimate their parameters. Simulation works using field data in the form of a VI characteristic curve are carried out to demonstrate the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.80-87
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• 1998

This paper presents and online scheme for fuzzy modelling of nonlinear systems, based on the model adjustment technique and the genetic algorithm technique. The fuzzy model is characterized by fuzzy "if-then" rules which represent locally linear input-output relations whose consequence parts are defined as subsystems of a nonlinear sysem. The discrete-time model for each subsystem is obtained to deal with initalization and unmeasurable signal problems in online estimation and the final output of the fuzzy model is computed from the outputs of the discrete-time models. Then, the parameters of both the premise and consequence parts of the fuzzy model are adjusted by a genetic algorithm. A set of simulation works is carried out to demonstrate the effectiveness of the proposed method.ed method.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.795-797
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• 2005

During the past few years, various traffic-flow forecasting models, i.e. an ARIMA, an ANN, and so on, have been developed to predict more accurate traffic flow. However, these models analyze historical data in an attempt to predict future value of a variable of interest. They make use of the following basic strategy. Past data are analyzed in order to identify a pattern that can be used to describe them. Then this pattern is extrapolated, or extended, into the future in order to make forecasts. This strategy rests on the assumption that the pattern that has been identified will continue into the future. So ARIMA or ANN models with its traditional architecture cannot be expected to give good predictions unless this assumption is valid; The statistical models in particular, the time series models are deficient in the sense that they merely extrapolate past patterns in the data without reflecting the expected irregular and infrequent future events Also forecasting power of a single model is limited to its accurate. In this paper, we compared with an ANN model and ARIMA model and tried to combine an ARIMA model and ANN model for obtaining a better forecasting performance. In addition to combining two models, we also introduced judgmental adjustment technique. Our approach can improve the forecasting power in traffic flow. To validate our model, we have compared the performance with other models. Finally we prove that the proposed model, i.e. ARIMA + ANN + Judgmental Adjustment, is superior to the other model.