• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.671-686
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• 2020

Due to the long training time and high training cost of traditional surgical training methods, the emerging virtual surgical training method has gradually replaced it as the mainstream. However, the virtual surgical system suffers from poor authenticity and high computational cost problems. For overcoming the deficiency of these problems, we propose an optimized model for the local compression deformation of soft tissue. This model uses a simulated annealing algorithm to optimize the parameters of the soft tissue model to improve the authenticity of the simulation. Meanwhile, although the soft tissue deformation is divided into local deformation region and non-deformation region, our proposed model only needs to calculate and update the deformation region, which can improve the simulation real-time performance. Besides, we define a compensation strategy for the "superelastic" effect which often occurs with the mass-spring model. To verify the validity of the model, we carry out a compression simulation experiment of abdomen and human foot and compare it with other models. The experimental results indicate the proposed model is realistic and effective in soft tissue compression simulation, and it outperforms other models in accuracy and real-time performance.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1031-1054
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• 2014

Real-time hybrid simulation (RTHS) of a stacked wood shear wall retrofitted with a rate-dependent seismic energy dissipation device (viscous damper) was conducted at the newly constructed Structural Engineering Laboratory at the University of Alabama. This paper describes the implementation process of the RTHS focusing on the controller scheme development. An incremental approach was adopted starting from a controller for the conventional slow pseudodynamic hybrid simulation and evolving to the one applicable for RTHS. Both benchmark-scale and full-scale tests are discussed to provide a roadmap for future RTHS implementation at different laboratories and/or on different structural systems. The developed RTHS controller was applied to study the effect of a rate-dependent energy dissipation device on the seismic performance of a multi-story wood shear wall system. The test specimen, setup, program and results are presented with emphasis given to inter-story drift response. At 100% DBE the RTHS showed that the multi-story shear wall with the damper had 32% less inter-story drift and was noticeably less damaged than its un-damped specimen counterpart.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.122-122
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• 2017

Recently, environmental problems have become an area of growing interests. In-situ monitoring of water quality is fundamental to most environmental applications. The accurate measurement of nitrate concentrations is fundamental to understanding biogeochemistry in aquatic ecosystems. Several studies have reported that one of the most feasible methods to measure nitrate concentration is the use of Ion Selective-electrodes (ISEs). The ISE application to water monitoring has several advantages, such as direct measurement methodology, high sensitivity, wide measurement range, low cost, and portability. However, the ISE methods may yield inconsistent results where there was a difference in temperature between the calibration and measurement solutions, which is associated with the temperature dependence of ionic activity coefficients in solution. In this study, to investigate the potential of using the combination of a temperature sensor and nitrate ISEs for minimizing the effect of temperature on real-time nitrate sensing in natural water, a prototype of on-site water monitoring system was built, mainly consisting of a sensor chamber, an array of 3 ISEs, an waterproof temperature sensor, an automatic sampling system, and an arduino MCU board. The analog signals of ISEs were obtained using the second-order Sallen-key filter for performing voltage following, differential amplification, and low pass filtering. The performance test of the developed water nitrate sensing system was conducted in a monitoring station of drinking water located in Jeongseon, Kangwon. A temperature compensation method based on two-point normalization was proposed, which incorporated the determination of temperature coefficient values using regression equations relating solution temperature and electrode signal determined in our previous studies.

• Journal of the Korean Ceramic Society
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• v.16 no.3
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• pp.142-154
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• 1979

The effects of microstructures and some additives $(CoO and Al_2O_3$) on the magnetic properties such as initial permeability, $\mu$-T curve, coercive force, and magnetic induction of MnZn ferrites have been studied. The powder was prepared by Hot Petroleum Drying Method. The basic composition of MnZn ferrites was 25.5mole % MnO, 22.0 mole% ZnO, 52.5 mole% $Fe_2O_3$. CoO in a concentration range from 0.05 to 0.5 mole% and $Al_2O_3$ from 2.5 to 7.5 mole% were added. Sintered density increased up to 97.5% of theoretical density. Permeability increased as average grain size increased, and that coercive force decreased as average grian size increased. Magnetic induction increased as sintered density increased. The variation of initial permeability with temperature in a temperature range from 0$^{\circ}$ to $60^{\circ}C$ was lowered (a flatter $\mu-T$ curve) as sintering temperature decreased. The compensation temperature To ofmagnetocrystalline anisotropy constant K1 and initial permeability varied with the species and amount of additives. When 0.05 mole% CoO was added to the basic composition, initial permeability at $15^{\circ}C$ increased from 5200 to 5900. The variation ofinitial permeability with temperature in a temperature range from 0^{\circ}to $60^{\circ}C$ was smaller (a flatter $\mu$-T curve) than that of the basic composition of Mn Zn ferrites. When 2.5 mole% $Al_2O_3$ was added, initial permeability at $15^{\circ}C$ decreased from 5200 to 3000. But the variation of initial permeability with temperature in a temperature range from 0$^{\circ}$to $60^{\circ}C$ was smaller (a flat ter $\mu-T$ curve) than when 0.05 mole% CoO was added. Experimental results showed that the conditions necessary for the occurrence of a very high permeability and a flat $\mu$-T curve were controversial even in a temperature range from $0^{\circ}$to $60^{\circ}C$.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.5
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• pp.82-89
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• 2007

AVR(Automatic Voltage Regulator) of exciter control system in AC generator controls voltage and current according to load and terminal voltage variations in order to remain at the bus voltage. The output characteristics of main generator is dependent on the control performance of AVR. This paper presents the PWM type exciter system with transient response compensator for robust control of load variations. Additional transient response compensator generates compensation signal for load variation. So the proposed excitation control system has fast dynamic response in transient period and can control terminal voltage constantly. The proposed method is verified by the computer simulation and experimental results in prototype generation system.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.369-374
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• 2002

In this paper, we propose the react-time car license plate recognition algorithm using intensity variation and geometric pattern vector. Generally, difference of car license plate region between character and background is more noticeable than other regions. And also, car license plate region usually shows high density values as well as constant intensity variations. Based on these characteristics, we first extract car license plate region using intensity variations. Secondly, lightness compensation process is performed on the considerably dark and brightness input images to acquire constant extraction efficiency. In the proposed recognition step, we first pre-process noise reduction and thinning steps. And also, we use geometric pattern vector to extract features which independent on the size, translation, and rotation of input values. In the experimental results, the proposed method shows better computation times than conventional circular pattern vector and better extraction results regardless of irregular environment lighting conditions as well as noise, size, and location of plate.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1566-1576
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• 2007

Camera pose information from 2D face image is very important for making virtual 3D face model synchronize with the real face. It is also very important for any other uses such as: human computer interface, 3D object estimation, automatic camera control etc. In this paper, we have presented a camera position determination algorithm from a single 2D face image using the relationship between mouth position information and face region boundary information. Our algorithm first corrects the color bias by a lighting compensation algorithm, then we nonlinearly transformed the image into $YC_bC_r$ color space and use the visible chrominance feature of face in this color space to detect human face region. And then for face candidate, use the nearly reversed relationship information between $C_b\;and\;C_r$ cluster of face feature to detect mouth position. And then we use the geometrical relationship between mouth position information and face region boundary information to determine rotation angles in both x-axis and y-axis of camera position and use the relationship between face region size information and Camera-Face distance information to determine the camera-face distance. Experimental results demonstrate the validity of our algorithm and the correct determination rate is accredited for applying it into practice.

• Transactions on Electrical and Electronic Materials
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• v.15 no.2
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• pp.103-111
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• 2014

This paper investigates the output powers of PV modules by predicting three unknown parameters: reverse saturation current, and series and shunt resistances. A theoretical model using the non-uniform physical parameters of solar cells, including the temperature coefficients, voltage, current, series and shunt resistances, is proposed to obtain the I-V characteristics of PV modules. The solar irradiation effect is included in the model to improve the accuracy of the output power. Analytical and Newton methods are implemented in MATLAB to calculate a module output. Experimental data of the non-uniform solar cells for both serial and parallel connections are used to extend the implementation of the model based on the I-V equation of the equivalent circuit of the cells and to extend the application of the model to m by n modules configuration. Moreover, the theoretical model incorporates, for the first time, the variations of series and shunt resistances, reverse saturation current and irradiation for easy implementation in real power generation. Finally, this model can be useful in predicting the degradation of a PV system because of evaluating the variations of series and shunt resistances, which are critical in the reliability analysis of PV power generation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.900-911
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• 2015

In this paper, 3D face recognition model is designed by using Polynomial based RBFNN(Radial Basis Function Neural Network) and PNN(Polynomial Neural Network). Also recognition rate is performed by this model. In existing 2D face recognition model, the degradation of recognition rate may occur in external environments such as face features using a brightness of the video. So 3D face recognition is performed by using 3D scanner for improving disadvantage of 2D face recognition. In the preprocessing part, obtained 3D face images for the variation of each pose are changed as front image by using pose compensation. The depth data of face image shape is extracted by using Multiple point signature. And whole area of face depth information is obtained by using the tip of a nose as a reference point. Parameter optimization is carried out with the aid of both ABC(Artificial Bee Colony) and PSO(Particle Swarm Optimization) for effective training and recognition. Experimental data for face recognition is built up by the face images of students and researchers in IC&CI Lab of Suwon University. By using the images of 3D face extracted in IC&CI Lab. the performance of 3D face recognition is evaluated and compared according to two types of models as well as point signature method based on two kinds of depth data information.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.1
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• pp.33-37
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• 2011

In the fields of display, optics, and energy, it is important to improve micropattern-machining technology for achieving small patterns, large surface areas, and low cost. Unlike flat molds, roll molds have the following advantages: they can be manufactured within a short time, larger surface areas can be obtained, and continuous molding can be achieved. In this study, we aim to investigate the causes for errors in the shapes for a micropattern-machining process, and we show that by compensating the dynamic balance of roll molds, the dimensional accuracy of machined parts can be improved. The experimental results show that dynamic-balance compensation for a roll mold reduced the mass unbalance and the vibrations of the roll mold, and as a result, the dimensional accuracy of machined micropatterns has been improved.