• Tunnel and Underground Space
• /
• v.20 no.2
• /
• pp.97-104
• /
• 2010

The materials failure relation $\ddot{\Omega}=A{(\dot{\Omega})}^\alpha$ where $\Omega$ is a measurable quantity such as displacement and the dot superscript is the time derivative, may be used to analyze the accelerating creep of materials. Coefficients, A and $\alpha$, are determined by fitting given data sets. In this study, it is tried to predict the failure time of tunnel using the materials failure relation. Four fitting techniques of applying the materials failure relation are attempted to forecast a failure time. Log velocity versus log acceleration technique, log time versus log velocity technique, inverse velocity technique are based on the linear least squares fits and non-linear least squares technique utilizes the Levenberg-Marquardt algorithm. Since the log velocity versus log acceleration technique utilizes a logarithmic representation of the materials failure relation, it indicates the suitability of the materials failure relation applied to predict a failure time of tunnel. A linear correlation between log velocity and log acceleration appears satisfactory(R=0.84) and this represents that the materials failure relation is a suitable model for predicting a failure time of tunnel. Through comparing the real failure time of tunnel with the predicted failure times from four curve fittings, it is shown that the log time versus log velocity technique results in the best prediction.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.23 no.2
• /
• pp.43-50
• /
• 2019

Purpose The principle of nuclear medicine test is divided into two main categories: competition(radioimmunoassay, RIA) and noncompetitive reaction(Immunoradiometric assay, IRMA). It is known that the curve fitting method, which is commonly used in inspection field, uses Spline interpolation in RIA method and Linear interpolation method in IRMA method. Among them, the insulin test using the IRMA test showed a significant difference, especially at low concentrations, despite the same algorithm of linear interpolation between fully automated radio immunoassay analyzers. In this study, we aim to obtain results from applying two different of algorithm using fully automated radio immunoassay analyzers including Gamma pro, Gamma 10, Cobra, and SR300. Materials and Methods A total of 30 test samples were selected for the test of TSH, ferritin, C-peptide, and insulin serum levels. Test was performed by IRMA method. We compared the difference in the results of applying the linear interpolation method and the spline interpolation method to Gamma Pro, Gamma 10, Cobra, and SR300 equipment. Results Two-way ANOVA was used for statistical analysis. The significance level was applied as P <0.05. The results of TSH, ferritin, C-peptide, and insulin tests were compared between the fully automated radio immunoassay analyzers. There was a significant difference between ferritin, C-peptide, and insulin serum levels(P<0.001). TSH didn't show any significant different between the devices(P=0.29). In the difference between linear and spline interpolation, there was no significant difference between insulin test(P=0.08), TSH test(P=0.81), and Ferritin test(P=0.06). However, C-peptide test showed a significant difference(P=0.03). Especially, the insulin test showed significant difference in lower ranges. As a result of comparing and analyzing the difference between the two interpolation methods, the devices in the low concentration group showed significant difference(P<0.001). Conclusion In case of new equipment in the laboratory it is necessary to recognize that there is a difference in the curve fitting method for each automated radio immunoassay analyzers in the low concentration area when the principle of inspection is IRMA method.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.1
• /
• pp.16-22
• /
• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.

• Geophysics and Geophysical Exploration
• /
• v.15 no.2
• /
• pp.85-91
• /
• 2012

Multiple Lapse Time Window (MLTW) analysis for obtaining intrinsic attenuation value require numerous data without directional bias to compensate focal mechanism. The first window of MLTW, therefore, shows large deviation in fitting smoothed theoretical curve. The information on the focal mechanism may reduce burdens of number and distribution. This study combined algorithm of computing focal mechanism to DSMC method by Yoshimoto (2000). However, the MLTW method based on the numerous data was not applicable to this study, because of the limited data to the almost same fault plane solution. This study showed that the available data was too insufficient to construct smoothed theoretical curve, although the deviation of the first window was improved. Instead of conventional solution by more data, the study seems to be needed for new constraints to obtain smoothed curve.

• The Journal of the Korea Contents Association
• /
• v.6 no.11
• /
• pp.302-309
• /
• 2006

This paper propose a practical algorithm to reuse and expand the objects. This algorithm is based on the Motion Path Modification rules. We focus on reusing of the existing motions for synthesizing new motions for the objects. Both the linear and the nonlinear curve-fitting algorithm are applied to modify an animation by keyframe interpolation and to make the motion appear realistic. We also proposes a framework of the scenario-based 3D image synthesizing system that allows common users, who envision a scenario in their minds, to realize it into segments of a cool animation. The framework is useful in building a 3D animation in game programming with a limited set of 3D objects.

• Journal of Computational Design and Engineering
• /
• v.1 no.3
• /
• pp.202-212
• /
• 2014

To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components' accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components' accuracy by comparing each component's point cloud data scanned by laser scanners and the ship's design data formatted in CAD cannot be processed efficiently when (1) extract components from point cloud data include irregular obstacles endogenously, or when (2) registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles' shadows. The ICP (Iterative Closest Point) algorithm conducts a registration of the two sets of data after the proper registration's direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.3
• /
• pp.68-74
• /
• 2001

A lane detection based on a road model or feature all needs correct acquirement of information on the lane in an image. It is inefficient to implement a lane detection algorithm through the full range of an image when it is applied to a real road in real time because of the calculating time. This paper defines two (other proper terms including"modes") for detecting lanes on a road. First is searching mode that is searching the lane without any prior information of a road. Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It allows to extract accurately and efficiently the edge candidate points of a lane without any unnecessary searching. By means of inverse perspective transform which removes the perspective effect on the edge candidate points, we transform the edge candidate information in the Image Coordinate System(ICS) into the plan-view image in the World Coordinate System(WCS). We define a linear approximation filter and remove faulty edge candidate points by using it. This paper aims at approximating more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.e fitting.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.18 no.2
• /
• pp.172-179
• /
• 2006

This study developed a program for detecting charged refrigerant amount in system air-conditioner. System air-conditioner is an air-conditioning system with multiple indoor units. Due to the complexity of the system, it is more difficult to detect the refrigerant amount charged in the system air-conditioner than in a general single air-conditioner. Experiments were performed for a 6 HP outdoor unit with 3 indoor units in a psychrometric calorimeter. The experimental amount of the charged refrigerant was ranged from $60\%\;to\;140\%\;with\;10\%$ increasement. Fuzzy algorithm was employed for detecting the charged refrigerant amount in the system air-conditioner. The experimental data were used for curve-fitting for the general ranges of indoor and outdoor temperature conditions. Membership function was determined for the whole ranges of experimentally measured data and rule-bases were defined for each charged refrigerant amount. Developed program successfully predicted the measured data within $10\%$ resolution range.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.18 no.4
• /
• pp.376-386
• /
• 2013

This paper proposes an improved Maximum Power Point Tracking method and design methods of unmanned solar vehicle system by parts of hardware, unmanned driving control and power conversion. The hardware design is offered on the weight reduction and structural reliability by using structural analysis software. The technique of curve fitting is applied to unmanned control system due to minimizing the vehicle's behavior. Furthermore, lateral controller applying actuator dynamics is robust enough to prevent performance degradation by measurement noise regarding position and heading angle. The power conversion system contains battery charger system and tapped-inductor boost converter. In the battery charger system, variable step-size MPPT is conducted for quick response of maximum power point tracking. The validity of the proposed algorithm are verified by simulations and experiments.

• Proceedings of the KIPE Conference
• /
• 2003.07a
• /
• pp.299-303
• /
• 2003

This paper deals with the frequency sensing methods at HVDC system. The objects of frequency information in HVDC system areto fire a valve and to control a frequency of AC network. Conventionally, there are two methods to measure a frequency of AC network. The first method is to draw out from the synchronous machine and the second method is from AC network. Two methods have advantages and disadvantage each other. For the extreme case of a receiving system of zero inertia (no generation), synchronous machine is essential. In this situation, the frequency information received from the synchronous machine shaft. However, the speed of synchronous machine is oscillated when a disturbance in AC network occurs, and HVDC may be oscillated due to an oscillation speed. To solve this drawback, in this paper, new frequency sensing method is proposed. A proposed method that is use a modified curve-fitting algorithm, has a robust characteristics against a harmonics and unbalanced faults. Consequently, A proposed method is verified by PSCAD/EMTDC Program and experimental test.