• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.10-18
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• 2010

This paper presents a optimization of sigmoid activation function parameter using genetic algorithms and pattern recognition analysis in input space of two spirals benchmark problem. To experiment, cascade correlation learning algorithm is used. In the first experiment, normal sigmoid activation function is used to analyze the pattern classification in input space of the two spirals problem. In the second experiment, sigmoid activation functions using different fixed values of the parameters are composed of 8 pools. In the third experiment, displacement of the sigmoid function to determine the value of the three parameters is obtained using genetic algorithms. The parameter values applied to the sigmoid activation functions for candidate neurons are used. To evaluate the performance of these algorithms, each step of the training input pattern classification shows the shape of the two spirals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5904-5927
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• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.395-404
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• 2000

A damage detection and assessment algorithm is developed by measuring accelerations at limited locations of a structure under forced vibrations. The developed algorithm applies a time-domain system identification (SI) method that identifies a structure by solving a linearly constrained nonlinear optimization problem for optimal structural parameters. An equation error of the dynamic equilibrium of motion is minimized to estimate optimal parameters. An adaptive parameter grouping scheme is applied to localize damaged members with sparse measured accelerations. Damage is assessed in a statistical manner by applying a time-windowing technique to the measured time history of acceleration. Displacements and velocities at the measured degrees of freedom (DOF) are computed by integrating the measured accelerations. The displacements at the unmeasured DOF are estimated as additional unknowns to the unknown structural parameters, and the corresponding velocities and accelerations we computed by a numerical differentiation. A numerical simulation study with a truss structure is carried out to examine the efficiency of the algorithm. A data perturbation scheme is applied to determine the thresholds lot damage indices and to compute the damage possibility of each member.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.245-254
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• 2004

This paper deals with the problem of estimating structure and motion from long continuous image sequences, applying the Expectation Maximization algorithm based on extended Kalman smoother to impose the time-continuity of the motion parameters. By repeatedly estimating the state transition matrix of the dynamic equation and the parameters of noise processes in the dynamic and measurement equations, this optimization gives the maximum likelihood estimates of the motion and structure parameters. Practically, this research is essential for dealing with a long video-rate image sequence with partially unknown system equation and noise. The algorithm is implemented and tested for a real image sequence.

• Imaging Science in Dentistry
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• v.49 no.2
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• pp.139-151
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• 2019

Purpose: This study was performed to investigate the effect of exposure parameters on image quality obtained using a cone-beam computed tomography (CBCT) scanner and the relationship between physical factors and clinical image quality depending on the diagnostic task. Materials and Methods: CBCT images of a SedentexCT IQ phantom and a real skull phantom were obtained under different combinations of tube voltage and tube current (Alphard 3030 CBCT scanner, 78-90 kVp and 2-8 mA). The images obtained using a SedentexCT IQ phantom were analyzed technically, and the physical factors of image noise, contrast resolution, spatial resolution, and metal artifacts were measured. The images obtained using a real skull phantom were evaluated for each diagnostic task by 6 oral and maxillofacial radiologists, and each setting was classified as acceptable or unacceptable based on those evaluations. A statistical analysis of the relationships of exposure parameters and physical factors with observer scores was conducted. Results: For periapical diagnosis and implant planning, the tube current of the acceptable images was significantly higher than that of the unacceptable images. Image noise, the contrast-to-noise ratio (CNR), the line pair chart on the Z axis, and modulation transfer function (MTF) values showed statistically significant differences between the acceptable and unacceptable image groups. The cut-off values obtained using receiver operating characteristic curves for CNR and MTF 10 were useful for determining acceptability. Conclusion: Tube current had a major influence on clinical image quality. CNR and MTF 10 were useful physical factors that showed significantly associations with clinical image quality.

• Geomechanics and Engineering
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• v.28 no.4
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• pp.385-396
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• 2022

The accurate determination of the subgrade reaction modulus (K_s) of soil is an important factor for geotechnical engineers. This study estimated the K_s of soft soil improved with floating deep cement mixing (DCM) columns. A novel prediction model was developed that emphasizes the accuracy of identifying the most significant parameters of K_s. Several multi-layer perceptron (MLP) models that were trained using the Levenberg Marquardt (LM) backpropagation method were developed to estimate K_s. The models were trained using a reliable database containing the results of 36 physical modelling tests. The input parameters were the undrained shear strength of the DCM columns, undrained shear strength of soft soil, area improvement ratio and length-to-diameter ratio of the DCM columns. Grey wolf optimization (GWO) was coupled with the MLPs to improve the performance indices of the MLPs. Sensitivity tests were carried out to determine the importance of the input parameters for prediction of K_s. The results showed that both the MLP-LM and MLP-GWO methods showed high ability to predict K_s. However, it was shown that MLP-GWO (R = 0.9917, MSE = 0.28 (MN/m²/m)) performed better than MLP-LM (R =0.9126, MSE =6.1916 (MN/m²/m)). This proves the greater reliability of the proposed hybrid model of MLP-GWO in approximating the subgrade reaction modulus of soft soil improved with floating DCM columns. The results revealed that the undrained shear strength of the soil was the most effective factor for estimation of K_s.

• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.783-791
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• 2000

A multidimensional representation for precipitation, given In the theory proposed by E. Waymire et al. (1984), is used for simulating rainfall in space and time. The model produces moving storms with realistic meso-scale meteorological features in time and space. The first- and second-order statistics derived from observed JX)int gauge data were used to estimate the model parameters based on the Nelder-Mead algorithm of optimization. Then twelve-year traces of rainfall intensities at fixed gage stations were generated at intervals of 1 hours. First- and second-order statistics are evaluated from the above series, which are used for estimating the parameters of one dimensional model of temporal rainfall at a point. As a result from the comparisons of one dimensional model parameters used observed and generated data from multidimensional model, we found that the multidimensional rainfall model generated visually realistic spatial patterns of rainfall as well as realistic temporal hyetographs of rainfall at a point. point.

• Journal of IKEEE
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• v.27 no.4
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• pp.657-667
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• 2023

This paper proposes two-stage optimization framework to re-estimate the photovoltaic (PV) hosting capacity (HC) by improving parameters for voltage controls of the smart inverter. In the first stage, PV HC is estimated considering Volt-Var (VV) and Volt-Watt (VW) controls, aligning with IEEE Std 1547-2018 guidelines. In the second stage, adjust parameters of VV and VW to improve HC. To investigate the performance of the proposed algorithm, simulations conducted using OpenDSS on an IEEE 37-bus system. The results demonstrate that effectively increases PV HC.