• Investigative Magnetic Resonance Imaging
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• v.8 no.1
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• pp.1-8
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• 2004

Purpose : Information about electrical activity inside the brain during fMRl scans is very useful in monitoring physiological function of the patient or locating the spatial position of the activated region in the brain. However, many additional noises appear in the EEG signal acquired during the MRI scan. Gradient induced noise is the biggest one among the noises. In this work, we propose a gradient noise reduction method using the independent component analysis (ICA) method. Materials and Methods : We used a 29-channel MR-compatible EEG measurement system and a 3.0 Tesla MRI system. We measured EEG signals on a subject lying inside the magnet during EPI scans. We selectively removed the gradient noise from the measured EEG signal using the ICA method. We compared the results with the ones obtained with conventional averaging method and PCA method. Results : All the noise reduction methods including the averaging and PCA methods were effective in removing the noise in some extent. However, the proposed ICA method was found to be superior to the other methods. Conclusion : Gradient noise in EEG signals acquired during fMRI scans can be effectively reduced by the ICA method. The noise-reduced EEG signal can be used in fMRI studies of epileptic patients or combinatory studies of fMRI and EEG.

• 전기의세계
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• v.21 no.3
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• pp.48-52
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• 1972

The application of pontryagin's Maximum Principle to the optimal control eventually leads to the problem of solving the two point boundary value problem. Most of problems have been related to their own special factors, therfore it is very hard to recommend the best method of deriving their optimal solution among various methods, such as iterative Runge Kutta, analog computer, gradient method, finite difference and successive approximation by piece-wise linearization. The gradient method has been applied to the optimal control of two point boundary value problem in the power systems. The most important thing is to set up some objective function of which the initial value is the function of terminal point. The next procedure is to find out any global minimum value from the objective function which is approaching the zero by means of gradient projection. The algorithm required for this approach in the relevant differential equations by use of the Runge Kutta Method for the computation has been established. The usefulness of this approach is also verified by solving some examples in the paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2754-2768
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• 2013

Video fingerprints generated from global features are usually vulnerable against general geometric transformations. In this paper, a novel video fingerprinting algorithm is proposed, in which a new spatio-temporal gradient is designed to represent the spatial and temporal information for each frame, and a new partition scheme, based on concentric circle and rings, is developed to resist the attacks efficiently. The centroids of spatio-temporal gradient orientations (CSTGO) within the circle and rings are then calculated to generate a robust fingerprint. Our experiments with different attacks have demonstrated that the proposed approach outperforms the state-of-the-art methods in terms of robustness and discrimination.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.247-249
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• 1995

A new localized imaging technique of reduced imaging time using a locally-linear gradient is proposed. Since most fast MR imaging methods need the whole k-space data corresponding to the whole imaging area, there are limitations in reducing the minimum imaging time. The imaging method proposed in this paper uses a specially-made gradient coil generating a local ramp-shape field and uniform field outside of the imaging area. Conventional imaging sequences can be used without any RF/gradient pulse sequence modifications. The proposed localized imaging technique has been implemented on a 2.0 Tesla whole-body system at KAIST and the imaging results show the utility of the proposed technique.

• 한국생물공학회:학술대회논문집
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• 2002.04a
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• pp.539-542
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• 2002

We propose new encoding method for numerical data in DNA using temperature gradient. To represent numerical values in DNA sequences, we introduce melting temperature. Since DNA strands representing smaller values have a lower Tm, they tend to denature with ease and also easily amplified by denaturation temperature gradient PCR. We also implement a local search molecular algorithm using temperature gradient, which is contrasted to conventional exhaustive search molecular algorithms. The proposed methods are verified by solving an instance of the travelling salesman problem. We could effectively amplify the correct solutions and the use of temperature gradient made the detection of solutions easier.

• The KSFM Journal of Fluid Machinery
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• v.2 no.1 s.2
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• pp.29-34
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• 1999

To develop the efficient numerical optimization method for the design of an airfoil, an evaluation of various methods coupled with two-dimensional Naviev-Stokes analysis is presented. Simplex method and Hook-Jeeves method we used as direct search methods, and steepest descent method, conjugate gradient method and DFP method are used as indirect search methods and are tested to determine the search direction. To determine the moving distance, the golden section method and cubic interpolation method are tested. The finite volume method is used to discretize two-dimensional Navier-Stokes equations, and SIMPLEC algorithm is used for a velocity-pressure correction method. For the optimal design of two-dimensional airfoil, maximum thickness, maximum ordinate of camber line and chordwise position of maximum ordinate are chosen as design variables, and the ratio of drag coefficient to lift coefficient is selected as an objective function. From the results, it is found that conjugate gradient method and cubic interpolation method are the most efficient for the determination of search direction and the moving distance, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.14-17
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• 1995

Various methods and techniques have been proposed for solving optimization problems; the methods have been applied to various practical problems. However the methods have demerits. The demerits which should be covered are, for example, falling into local minima, or, a slow convergence speed to optimal points. In this paper, Likelihood Search Method (L.S.M.) is proposed for searching for a global optimum systematically and effectively in a single framework, which is not a combination of different methods. The L.S.M. is a sort of a random search method (R.S.M.) and thus can get out of local minima. However exploitation of gradient information makes the L.S.M. superior in convergence speed to the commonly used R.S.M..

• Journal of Korean Society of Water and Wastewater
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• v.10 no.4
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• pp.85-93
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• 1996

This study is to make a comparison between the node method and the pipeline method for the analysis of the water distribution systems. For these purposes, the two methods were applied to a pipeline system in series, an artificial distribution network and a real distribution network. The results are as follows. 1. The difference between the results of the two methods was increased with the increase of the hydraulic gradient and the length between two adjacent nodes. 2. When all pipe lengths between two adjacent nodes were larger than 200~300m and have the steep hydraulic gradient, it was found that the results of the two methods showed high differences. 3. The difference between the results of the two methods were negligible in the case of the real distribution system in which only 12% whole pipelines were longer than 30m and the longest pipe length was 850m.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.90-99
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• 2021

Recently, studies on wearable devices in ubiquitous computing environments have increased and the technology collecting user's activities to provide services has received great attention. We have compared the step counting methods according to sensor molding methods in case of counting steps by using the piezoelectric sensor. We have classified the cases which could result from the course of molding the internal module of a smart shoe as follows: (i) the module is unmolded, (ii) molded but only to the extent that a sensor is fixed or (iii) molded to the extent that a sensor is not moved. Moreover, we have made comparison to verify which algorithm should be used to increase the accuracy of counting steps by the respective cases. Based on the comparison result, we have confirmed that the accuracy of counting steps is higher when using gradient value rather than when using threshold value. In the case of no molding and small molding under the condition of using gradient value, it was turned out to be 100% accuracy for step counting.