• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.104-112
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• 2012

Recently, the HDR imaging technique that mimics human eye is incorporated with LCD/LED display devices to deal with mismatch between the real world scene and the displayed image. However, HDR image has a veiling glare limit as well as a scale of the local contrast problem. In order to overcome these problems, several color correction methods, CSR(center/surround Retinex), MSR (Multi-Scale Retinex), tone-mapping method, iCAM06 and so on, are proposed. However, these methods have a dominated color throughout the entire resulting image after performing color correction. Accordingly, this paper presents a new color correction method using dynamic cone response function. The proposed color correction method consists of tone-mapping and dynamic cone response. The tone-mapping is obtained by using a linear interpolation between chromatic and achromatic. Thereafter, the resulting image is processed through the dynamic cone response function, which estimates the dynamic responses of human visual system as well as deals with mismatch between the real scene image and the rendered image. The experiment results show that the proposed method yields better performance of color correction over the conventional methods.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.15-25
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• 2008

Ocean-bottom seismometer (OBS) positions are one of the key parameters in an OBS-airgun seismic survey for crustal structure study. To improve the quality of these parameters, we have developed a new method of determining OBS positions, using airgun shot data and bathymetric data in addition to available distance measurements by acoustic transponders. The traveltimes of direct water waves emitted by airgun shots and recorded by OBSs are used as important information for determining OBS locations, in cases where there are few acoustic transponder data (<3 sites). The new method consists of two steps. A global search is performed as the first step, to find nodes of the bathymetric grid that are the closest to explaining the observed direct water-wave traveltimes from airgun shots, and acoustic ranging using a transponder system. The use of precise 2D bathymetric data is most important if the bottom topography near the OBS is extremely rough. The locations of the nodes obtained by the first step are used as initial values for the second step, to avoid falling into local convergence minima. In the second step, a non-linear inverse method is executed. If the OBS internal clock shows large drift, a secondary correction for the OBS internal clock is obtained, as well as the OBS location, as final results by this method. We discuss the error and the influence of each measurement used in the determination of OBS location.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.171-178
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• 1994

The skin friction on single piles was investigated by using an analytical study and a numerical analysis. The emphasis was given to the variation of skin friction on piles based on the load transfer mechanism developed for the consolidation of a surrounding soft clay. Local yield or slip at the pile-soil interface was taken into account by specifying a limiting value of shear stress. The response of a single pile was analyzed and compared to the results of field case study. Based on the results obtained, it is shown that the skin friction on a pile increases as the degree of consolidation increases and the ultimate axial forces result from the long term behavior of clay corresponding to the end of the consolidation. It is also found that the analysis using one-dimensional consolidation theory as well as two or three-dimensional non-linear analysis gives relatively reasonable results.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.346-348
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• 2004

In this rarer, we introduce a new Fuzzy Polynomial Neural Networks (FPNNs)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNs based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNs-like structurenamed Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. In considering the structures of FPNN-like networks such as FPNN and FSPNN, they are almost similar. Therefore they have the same shortcomings as well as the same virtues on structural side. The proposed design procedure for networks' architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IG) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using gas furnace process dataset.

• Ecology and Resilient Infrastructure
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• v.4 no.2
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• pp.83-92
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• 2017

Increased investment in environment-friendly transport vehicles has led to rapid transit of railway tracks, double track program, linear improvements in railway lines, and moving railroad routes into the suburbs. They resulted in fast increase of railway yards. However, as the railroad yards being neglected, urban fine sites have been degraded. Local governments kept seeking ways to utilize the railway yards. In addition, Ministry of land, infrastructure and transport enacted "Guidelines for utilization of railway yards". The Guidelines categorized the railway yards into three types; conservation, utilized, and other sites in order to make efficient use of them. The railway yards have been converted and used for parks, rail bike trails, bike paths, and solar projects. It seems that studies are needed on diverse use of the yards and on post evaluation. This study investigated current uses of railway yards, domestic and foreign, and analyzed for the pertinent conditions on natural and cultural landscape, educational value, location and accessibility, potential for recreational area, and development opportunities. In this study, I proposed a quantitative evaluation method, and to find way to diversify the use of railway yards.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.5-14
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• 1994

This paper is about an experiment of speaker-independent automatic Korean spoken words recognition using Multi-Layered Perceptron and Error Back-propagation algorithm. The object words are 50 citynames of D.D.D local numbers. 43 of those are 2 syllables and the rest 7 are 3 syllables. The words were not segmented into syllables or phonemes, and some feature components extracted from the words in equal gap were applied to the neural network. That led independent result on the speech duration, and the PARCOR coefficients calculated from the frames using linear predictive analysis were employed as feature components. This paper tried to find out the optimum conditions through 4 differerent experiments which are comparison between total and pre-classified training, dependency of recognition rate on the number of frames and PAROCR order, recognition change due to the number of neurons in the hidden layer, and the comparison of the output pattern composition method of output neurons. As a result, the recognition rate of $89.6\%$ is obtaimed through the research.

• Journal of Power Electronics
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• v.14 no.2
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• pp.271-281
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• 2014

Fluctuating wind conditions necessitate the use of a variable speed wind turbine (VSWT) with a AC/DC/AC converter scheme in order to harvest the maximum power from the wind and to decouple the synchronous generator voltage and frequency from the grid voltage and frequency. In this paper, a combination of a three phase diode bridge rectifier (DBR) and a modified topology of the diode clamped multilevel inverter (DCMLI) has been considered as an AC/DC/AC converter. A control strategy has been proposed for the DCMLI to achieve the objective of grid interface of a wind power system together with local load compensation. A novel fixed frequency current control method is proposed for the DCMLI based on the level shifted multi carrier PWM for achieving the required control objectives with equal and uniform switching frequency operation for better control and thermal management with the modified DCMLI. The condition of the controller gain is derived to ensure the operation of the DCMLI at the fixed frequency of the carrier. The converter current injected into the distribution grid is controlled in accordance with the wind power availability. In addition, load compensation is performed as an added facility in order to free the source currents being fed from the grid of harmonic distortion, unbalance and a low power factor even though the load may be unbalanced, non-linear and of a poor power factor. The results are validated using PSCAD/EMTDC simulation studies.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.477-486
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• 2008

Facial expression, which changes face geometry, usually has an adverse effect on the performance of a face recognition system. To improve the face recognition rate, we propose a normalization method of facial expression to diminish the difference of facial expression between probe and gallery faces. Two approaches are used to facial expression modeling and normalization from single still images using a generic facial muscle model without the need of large image databases. The first approach estimates the geometry parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF(Radial Basis Function) based interpolation and warping to normalize the facial muscle model as unexpressed face according to the given expression. As a preprocessing stage for face recognition, these approach could achieve significantly higher recognition rates than in the un-normalized case based on the eigenface approach, local binary patterns and a grey-scale correlation measure.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.731-744
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• 2007

A method for dynamic analysis and design calculation of a Powertrain Mounting System(PMS) including Hydraulic Engine Mounts(HEM) is developed with the aim of controlling powertrain motion and reducing low-frequency vibration in pitch and bounce modes. Here the pitch mode of the powertrain is defined as the mode rotating around the crankshaft of an engine for a transversely mounted powertrain. The powertrain is modeled as a rigid body connected to rigid ground by rubber mounts and/or HEMs. A mount is simplified as a three-dimensional spring with damping elements in its Local Coordinate System(LCS). The relation between force and displacement of each mount in its LCS is usually nonlinear and is simplified as piecewise linear in five ranges in this paper. An equation for estimating displacements of the powertrain center of gravity(C.G.) under static or quasi-static load is developed using Newton's second law, and an iterative algorithm is presented to calculate the displacements. Also an equation for analyzing the dynamic response of the powertrain under ground and engine shake excitations is derived using Newton's second law. Formulae for calculating reaction forces and displacements at each mount are presented. A generic PMS with four rubber mounts or two rubber mounts and two HEMs are used to validate the dynamic analysis and design calculation methods. Calculated displacements of the powertrain C.G. under static or quasi-static loads show that a powertrain motion can meet the displacement limits by properly selecting the stiffness and coordinates of the tuning points of each mount in its LCS using the calculation methods developed in this paper. Simulation results of the dynamic responses of a powertrain C.G. and the reaction forces at mounts demonstrate that resonance peaks can be reduced effectively with HEMs designed on the basis of the proposed methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.433-436
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• 2004

In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.