• Geotechnical Engineering
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• v.8 no.4
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• pp.41-50
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• 1992

In general, the conceptual lumped-parameter groundwater flow model to predict the groundwater fluctuations in hillside slopes has unknown model parameters to be estimated from the known input -output data. The purpose of this study is to estimate the optimal model parameters of the groundwater flow model developed by authors. The Mazilnum A Posteriori( MAP) estimation method is utilized for this purpose and it is applied to a site which shows the typical landslide in Korea. The result of application shows tllat the 반AP estimation method can estimate the unknown parameters properly well. The groundwater model developed along with estimation technique applied in this paper will be used for assessing risk of landslides.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.417-422
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• 2005

This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.621-633
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• 2002

This paper provides some functional equations and parametric expressions of f-essential maps on the projective plane, on the torus and on the Klein bottle with the size as a parameter and gives their explicit formulae for exact enumeration further.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.2
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• pp.115-121
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• 2000

This paper presents reducing method of profile error on a mechanical tuning for multi-spindle control of NC machine tools. To reduce the profile error in the feed drive system, it is useful to adopt same transfer function of multi spindle machine tools. By selecting the correction vector of servo rigidity and natural vibration on JK map, multi spindle control can be tuned by mechanical parameters with small profile error.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2276-2283
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• 2018

A 50kW-4000rpm interior permanent magnet synchronous machine (IPMSM) applied to the high-performance electric vehicle (EV) is introduced in this paper. The main work of this paper is that a 2-D T-type lumped-parameter thermal network (LPTN) model is presented for IPMSM temperature rise calculation. Thermal conductance matrix equation is generated based on calculated thermal resistance and loss. Thus the temperature of each node is obtained by solving thermal conductance matrix. Then a 3-D liquid-solid coupling model is built to compare with the 2-D T-type LPTN model. Finally, an experimental platform is established to verify the above-mentioned methods, which obtains the measured efficiency map and current wave at rated load case and overload case. Thermocouple PTC100 is used to measure the temperature of the stator winding and iron core, and the FLUKE infrared-thermal-imager is applied to measure the surface temperature of IPMSM and controller. Test results show that the 2-D T-type LPTN model have a high accuracy to predict each part temperature.

• Journal of Power System Engineering
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• v.21 no.2
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• pp.20-26
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• 2017

This study was carried out to investigate the effect of precipitate on the high temperature deformation stability of incoloy 825 alloy. $Cr_{23}C_6$ carbide was precipitated under $950^{\circ}C$, but was not detected over $1,000^{\circ}C$. Most of the precipitation consist of $Cr_{23}C_6$ carbide. Strain-rate sensitivity was the highest in 0.01/s and the lowest in 10/s. Strain-rate sensitivity was decreased sharply below $950^{\circ}C$. In the temperature between $850^{\circ}C{\sim}1,150^{\circ}C$, plastic instable area did not exist. It showed the lowest Ziegler Parameter value of 0.06 Ziegler Parameter was the lowest as 0.06 at $850^{\circ}C$ with 10s-1 of strain. The highest Ziegler Parameter value(0.43) was found in plastic deformation at $1,050^{\circ}C$ with 0.01s-1 of strain. It tends to have an higher resistance to the high temperature deformation under $950^{\circ}C$, due to the precipitation.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.90.1-90.1
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• 2011

We are developing empirical space weather (geomagnetic storms, solar proton events, and solar flares) forecast models based on solar information. These models have been set up with the concept of probabilistic forecast using historical events. Major findings can be summarized as follows. First, we present a concept of storm probability map depending on CME parameters (speed and location). Second, we suggested a new geoeffective CME parameter, earthward direction parameter, directly observable from coronagraph observations, and demonstrated its importance in terms of the forecast of geomagnetic storms. Third, the importance of solar magnetic field orientation for storm occurrence was examined. Fourth, the relationship among coronal hole-CIR-storm relationship has been investigated, Fifth, the CIR forecast based on coronal hole information is possible but the storm forecast is challenging. Sixth, a new solar proton event (flux, strength, and rise time) forecast method depending on flare parameters (flare strength, duration, and longitude) as well as CME parameter (speed, angular width, and longitude) has been suggested. Seventh, we are examining the rates and probability of solar flares depending on sunspot McIntosh classification and its area change (as a proxy of flux change). Our results show that flux emergence greatly enhances the flare probability, about two times for flare productive sunspot regions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.3
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• pp.656-663
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• 1990

To investigate the optimum design conditions of Stirling Engines at the preliminary design stage, comparative study between adoabatoc analysis based on an approximate analytical solution to the Ideal Adiabatic Model and the existing isothermal analysis has been carried out. The optimum phase angle obtained from adiabatic analysis to achieve the maximum work with given combination of design parameters is greater than that from isothermal analysis, while the optimum swept volume ratio is smaller. Effect of variation in the temperature ratio on the work parameter is proved to be stronger in adiabatic analysis. On the contrary, the work parameter by adiabatic analysis is less sensitive to a change in the dead volume ratio. Especially in adiabatic analysis there exists the optimum dead volume ratio maximizing the work parameter, which may provide a lower limit of it. Considering that the adiabatic model is more reasonable, signifiant differences between two methods lead to the conclusion that adiabatic analysis is preferable to isothermal one for the preliminary design of Stirling Engines.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Broadcast Engineering
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• v.8 no.3
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• pp.268-277
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• 2003

In this paper, we propose a new video watermarking method exploiting the human visual system (HVS) to find effective locations. in the video frames which make the watermark robust and imperceptible simultaneously. In particular, we propose a new HVS-optimized weighting map for hiding the watermark by considering HVS in three different aspects : frequency, spatial, and motion masking effects. The global masking map is modeled by combining the frequency masking, the spatial masking, and the motion masking. In this paper, we use a watermark which is generated by the bitwise exclusive-OR operation between a logo image and a random sequence. The amount of watermarks is weighted by a control parameter. Furthermore, we embed the watermark in the uncompressed video sequence for the general watermarking method available to various coding schemes. Simulation results show that the watermark is imperceptible and the proposed method is good for watermark capacity. It is also demonstrated that the proposed method is robust against various attacks, such as MPEG coding, MPEG re-encoding, and frame attacks.