• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.955-961
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• 2010

In this paper, we describe a study of a vehicle detection method based on a Boosting Classifier which uses Histogram of Oriented Gradient (HOG) features and Image Segmentation techniques. An input image is segmented by means of a split and merge algorithm. Then, the two largest segmented regions are removed in order to reduce the search region and speed up processing time. The HOG features are then calculated for each pixel in the search region. In order to detect the vehicle region we used the AdaBoost (adaptive boost) method, which is well known for classifying samples with two classes. To evaluate the performance of the proposed method, 537 training images were used to train and learn the classifier, followed by 500 non-training images to provide the recognition rate. From these experiments we were able to detect the proper image 98.34% of the time for the 500 non-training images. In conclusion, the proposed method can be used for detecting the location of a vehicle in an intelligent vehicle control system.

• Geomechanics and Engineering
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• v.30 no.3
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• pp.259-272
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• 2022

Rockburst is a dynamic, multivariate, and non-linear phenomenon that occurs in underground mining and civil engineering structures. Predicting rockburst is challenging since conventional models are not standardized. Hence, machine learning techniques would improve the prediction accuracies. This study describes decision based uncertainty models to predict rockburst in underground engineering structures using gradient boosting algorithms (GBM). The model input variables were uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), maximum tangential stress (MTS), excavation depth (D), stress ratio (SR), and brittleness coefficient (BC). Several models were trained using different combinations of the input variables and a 3-fold cross-validation resampling procedure. The hyperparameters comprising learning rate, number of boosting iterations, tree depth, and number of minimum observations were tuned to attain the optimum models. The performance of the models was tested using classification accuracy, Cohen's kappa coefficient (k), sensitivity and specificity. The best-performing model showed a classification accuracy, k, sensitivity and specificity values of 98%, 93%, 1.00 and 0.957 respectively by optimizing model ROC metrics. The most and least influential input variables were MTS and BC, respectively. The partial dependence plots revealed the relationship between the changes in the input variables and model predictions. The findings reveal that GBM can be used to anticipate rockburst and guide decisions about support requirements before mining development.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.74-85
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• 2024

Objective: Idiopathic intracranial hypertension (IIH) is a condition of unknown etiology associated with venous sinus stenosis. This study aimed to develop a magnetic resonance venography (MRV)-based radiomics model for predicting a high trans-stenotic pressure gradient (TPG) in IIH patients diagnosed with venous sinus stenosis. Materials and Methods: This retrospective study included 105 IIH patients (median age [interquartile range], 35 years [27-42 years]; female:male, 82:23) who underwent MRV and catheter venography complemented by venous manometry. Contrast enhanced-MRV was conducted under 1.5 Tesla system, and the images were reconstructed using a standard algorithm. Shape features were derived from MRV images via the PyRadiomics package and selected by utilizing the least absolute shrinkage and selection operator (LASSO) method. A radiomics score for predicting high TPG (≥ 8 mmHg) in IIH patients was formulated using multivariable logistic regression; its discrimination performance was assessed using the area under the receiver operating characteristic curve (AUROC). A nomogram was constructed by incorporating the radiomics scores and clinical features. Results: Data from 105 patients were randomly divided into two distinct datasets for model training (n = 73; 50 and 23 with and without high TPG, respectively) and testing (n = 32; 22 and 10 with and without high TPG, respectively). Three informative shape features were identified in the training datasets: least axis length, sphericity, and maximum three-dimensional diameter. The radiomics score for predicting high TPG in IIH patients demonstrated an AUROC of 0.906 (95% confidence interval, 0.836-0.976) in the training dataset and 0.877 (95% confidence interval, 0.755-0.999) in the test dataset. The nomogram showed good calibration. Conclusion: Our study presents the feasibility of a novel model for predicting high TPG in IIH patients using radiomics analysis of noninvasive MRV-based shape features. This information may aid clinicians in identifying patients who may benefit from stenting.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.141-147
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• 2024

Progressive photon mapping is a widely adopted rendering technique that conducts a kernel-density estimation on photons progressively generated from lights. Its hyperparameter, which controls the reduction rate of the density estimation, highly affects the quality of its rendering image due to the bias-variance tradeoff of pixel estimates in photon-mapped results. We can minimize the errors of rendered pixel estimates in progressive photon mapping by estimating the optimal parameters based on gradient-based optimization techniques. To this end, we derived the gradients of pixel estimates with respect to the parameters when performing progressive photon mapping and compared our estimated gradients with finite differences to verify estimated gradients. The gradient estimated in this paper can be applied in an online learning algorithm that simultaneously performs progressive photon mapping and parameter optimization in future work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.88-95
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• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.4
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• pp.9-14
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• 1985

In this research mass of a plane strain two dimensional elastic concrete dam under gravitational and hydrostatic loads is minimized, through shape optimization of the dam cross section. Cross sectional area of the dam is taken as cost function of the optimization problem while constraints on the principal stress distribution and dam thickness are imposed. Shape of the boundary of the model is chosen as design variable. Variational formulation of the optimization problem, the material derivative idea of continuum mechanics, and an adjoint variable method are employed for the shape design sensitivity calculation. Then the gradient projection algorithm is utilized to obtain an optimum design iteratively. Research results fully demonstrate that the theory and procedure adopted are quite efficient and can be applicable to a wide class of practical elastic structural design problems.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1045-1053
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• 2006

We introduce a new method of painterly rendering. Instead of using the gradient direction of the source image to generate a brush stroke, we extract regions that can be drawn in one stroke using MHN filtering followed by identification of connected components, and make a brush stroke from each, based on an approximation to the medial axis. This method results in realistic-looking brush strokes of varying width that have an irregular directions where necessary.

• Journal of Astronomy and Space Sciences
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• v.8 no.1
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• pp.85-98
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• 1991

Geomagnetism was used to control the attitude of the small scientific satellite at low altitude in sun-synchronous orbit. First, we analyzed the telemetry data. The rotation state of the satellite, can be known from the magnitude and variations of the magnetic field which is measured from the 3 axis magnetometer. In axisymmetric case, it is possible to control the attitude of the satellite by changing the rotation velocity of each 3 axis. The algorithm and the program were developed to calculate the supply time of the current operating the magnetorquer. This attitude control can be applied when the satellite is in tumbling motion and after passive control is attained by the Gravity gradient boom.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.340-346
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• 1998

In order to improve the prediction of dynamic behavior in structures, several lower vibration modes from FFT analysis through experiments are used to update the mechanical properties followed by the updated frequencies from numerical analysis. Performance index consists of the sum of error norms between the chosen frequencies and corresponding frequencies from numerical analysis. As an updating process of the natural frequencies, the optimization algorithm based on conjugate gradient method is adopted. The gradient of performance index is calculated using the sensitivity of selected eigenvalues with respect to each design parameter. The mechanical properties of lamina, E$\_$l/, E$\_$2/, .nu.$\_$12/ and G$\_$12/, are design parameters for the updating process. The proposed method is applied to predict the dynamic behavior of composite laminated plates of [0]$\_$8T/ and [.+-.45]$\_$2S/ separately or interchangeably. Also, the mixed case for [0]$\_$8T/ and [.+-.45]$\_$2S/ is exarm'ned to check the possibility for the improved prediction generally. The good agreement is obtained between the measured frequencies and the numerical ones. Based on the results for all the cases studied, the proposed approach has a clear potential in characterizing the mechanical properties of composite lamina.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1281-1287
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• 2013

In order to prevent illegal video copies, many video fingerprints have been developed. Video fingerprints should be robust from various video transformations and have high discriminative powers. In general, video fingerprints are generated from three feature spaces such as luminance, gradient, and DCT coefficients. However, there is a few study for the robustness and discrimination according to feature spaces. Thus, we analyzed the property of each feature space by video copy detion task with the robustness and the discrimination of video fingerprints. We generated three video fingerprints from these feature spaces using a same algorithm. In our test, a video fingerprint. based on DCT coefficient outperformed others because the discrimination of it was higher.