• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.76-80
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• 2001

Unsteady compressible Euler equation is solved and the high-order, high-resolution numerical solver, physical boundary condition, adaptive nonlinear artificial dissipation model and conformal mapping are applied to computation of steady transonic flow and unsteady acoustics. The acoustic characteristics of axi-symmetric duct and two dimensional straight/S channel are studied and the computation results shows good agreements with linear analysis. In transonic case, local time stepping and canceling-the-residual techniques are used for convergence acceleration. The aspect of flow and acoustics in S-channel and the Pattern of noise radiation is changed by inflow Mach no. and static pressure at fan-face.

• Wind and Structures
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• v.20 no.4
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• pp.565-578
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• 2015

A wind energy assessment is an integrated analysis of the potential of wind energy resources of a particular area. In this work, the wind energy potentials for Mauritius have been assessed using a Computational Fluid Dynamics (CFD) model. The approach employed in this work aims to enhance the assessment of wind energy potentials for the siting of large-scale wind farms in the island. Validation of the model is done by comparing simulated wind speed data to experimental ones measured at specific locations over the island. The local wind velocity resulting from the CFD simulations are used to compute the weighted-sum power density including annual directional inflow variations determined by wind roses. The model is used to generate contour maps of velocity and power, for Mauritius at a resolution of 500 m.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.471-477
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• 2018

As an important key technology using on electronic devices, face recognition has become one of the hottest technology recently. The traditional BP Neural network has a strong ability of self-learning, adaptive and powerful non-linear mapping but it also has disadvantages such as slow convergence speed, easy to be traversed in the training process and easy to fall into local minimum points. So we come up with an algorithm based on BP neural network but also combined with the PCA algorithm and other methods such as the elastic gradient descent method which can improve the original network to try to improve the whole recognition efficiency and has the advantages of both PCA algorithm and BP neural network.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.210-210
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• 2000

In this paper, we have investigated the properties of multi-layer perceptron (MLP) for odour patterns classification and concentration estimation simultaneously. When the MLP may be has a fast convergence speed with small error and excellent mapping ability for classification, it can be possible to use for classification and concentration prediction of volatile chemicals simultaneously. However, the conventional MLP, which is back-Propagation of error based on the steepest descent method, was difficult to use for odour classification and concentration estimation simultaneously, because it is slow to converge and may fall into the local minimum. We adapted the Levenberg-Marquardt(LM) algorithm [4,5] having advantages both the steepest descent method and Gauss-Newton method instead of the conventional steepest descent method for the simultaneous classification and concentration estimation of odours. And, We designed the artificial odour sensing system(Electronic Nose) and applied LM-BP algorithm for classification and concentration prediction of VOC gases.

• Genomics & Informatics
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• v.10 no.3
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• pp.133-144
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• 2012

Genetic admixture in human, the result of inter-marriage among people from different well-differentiated populations, has been extensively studied in the New World, where European colonization brought contact between peoples of Europe, Africa, and Asia and the Amerindian populations. In Asia, genetic admixing has been also prevalent among previously separated human populations. However, studies on admixed populations in Asia have been largely underrepresented in similar efforts in the New World. Here, I will provide an overview of population genomic studies that have been published to date on human admixture in Asia, focusing on population structure and population history.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.41-44
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• 2004

Measurements of streaming potential can provide a means for the detection and quantification of contaminants in groundwater prior to remediation. However, laboratory determinations of specific electrolyte properties are required for an adequate analysis of the hydraulic gradient in complex situations. Data obtained for the King River in Tasmania confirm a linear relationship linking streaming potential data and hydraulic gradients. Laboratory samples at low concentration (0.001M KCl) indicate values in the range 20-80 mV/cm of water pressure, while for higher concentrations (0.01M KCl) values are less than 25 mV/cm. Similar ion concentrations are observed in the King River, consistent with field correlations indicating values for streaming potential close to 15 mV/cm. In-situ fluid samples are required for more detailed analysis of local anomalies that may be associated with variations in recharge and migration of contaminants.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.205-211
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• 2020

In this paper, we propose a modified ORB-SLAM (Oriented FAST and Rotated BRIEF Simultaneous Localization And Mapping) for precise indoor navigation of a mobile robot. The exact posture and position estimation by the ORB-SLAM is not possible all the times for the indoor navigation of a mobile robot when there are not enough features in the environment. To overcome this shortcoming, additional IMU (Inertial Measurement Unit) and encoder sensors were installed and utilized to calibrate the ORB-SLAM. By fusing the global information acquired by the SLAM and the dynamic local location information of the IMU and the encoder sensors, the mobile robot can be obtained the precise navigation information in the indoor environment with few feature points. The superiority of the modified ORB-SLAM was verified to compared with the conventional algorithm by the real experiments of a mobile robot navigation in a corridor environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.94-101
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• 1992

The multilayer perceptron, trained by the error back-propagation learning rule, has been known as a mapping network which can represent arbitrary functions. However depending on the complexity of a function and the initial weights of the multilayer perceptron, the error back-propagation learning may fall into a local minimum or a flat area which may require a long learning time or lead to unsuccessful learning. To solve such difficulties in training the multilayer perceptron by standard error back-propagation learning rule, the paper proposes a learning method which progressively enlarges the learning domain from a small area to the entire region. The proposed method is devised from the investigation on the roles of hidden nodes and connection weights in the multilayer perceptron which approximates a function of one variable. The validity of the proposed method was illustrated through simulations for a function of one variable and a function of two variable with many extremal points.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.1
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• pp.7-17
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• 2010

ITS(Intelligent Transport System) as things are used for Broadcast service using TDMB/TPEG/NAVI rather than personal seamless service. It is attaching weight to Traffic information gathering, Charging, Settlement service. This research is applied to improve DCCP(Datagram Congestion Control Protocol) which has function as protecting data and preserving message boundary. The improving method is like that we solve data trust in UDP because Connection and Transmission overhead in UDP is less than in TCP. We fix the data loss which is generated from unordered delivery section of IP base wireless service by using DCCP protocol. We guarantee of connection with OBE(On-Board Equipment) and reliance about transmission of data by complement to mapping table and multi-hoping. Finally, We evaluate the performance about transmission of IP based data. We constructed a test-bed near research center for this test.

• Water for future
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• v.29 no.4
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• pp.109-118
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• 1996

The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.