• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.688-695
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• 2017

This paper deals with characteristics analysis of a permanent magnet (PM) linear generator using analytical methods for wave energy harvesting. The wave energy is carried out from the movement of a yo-yo system. A linear generator using permanent magnets to generate a magnetic force itself does not require a separate power supply and has the advantage of simple maintenance. In addition to the use of a rare earth, a permanent magnet having a high-energy density can be miniaturized and lightweight, and can obtain high energy-conversion efficiency. We derived magnetic field solutions produced by the permanent magnet and armature reaction based on 2D polar coordinates and magnetic vector potential. Induced voltage is obtained via arbitrary sinusoidal input. In addition, electrical parameters are obtained, such as back-EMF constant, resistance, and self- and mutual-winding inductances. The space harmonic method used in this paper is confirmed by comparing it with finite element method (FEM) results. These facilitate the characterization of the PM-type linear generator and provide a basis for comparative studies, design optimization, and machine dynamic modeling.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.28-35
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• 2007

Airbone laser altimeters have been utilized for 3D topographic mapping of the earth, moon, and planets with high resolution and accuracy, which is a rapidly growing remote sensing technique that measures the round-trip time emitted laser pulse to determine the topography. The traveling time from the laser scanner to the Earth's surface and back is directly related to the distance of the sensor to the ground. When there are several objects within the travel path of the laser pulse, the reflected laser pluses are distorted by surface variation within the footprint, generating multiple echoes because each target transforms the emitted pulse. The shapes of the received waveforms also contain important information about surface roughness, slope and reflectivity. Waveform processing algorithms parameterize and model the return signal resulting from the interaction of the transmitted laser pulse with the surface. Each of the multiple targets within the footprint can be identified. Assuming each response is gaussian, returns are modeled as a mixture gaussian distribution. Then, the parameters of the model are estimated by LMS Method or EM algorithm However, each response actually shows the skewness in the right side with the slowly decaying tail. For the application to require more accurate analysis, the tail information is to be quantified by an approach to decompose the tail. One method to handle with this problem is proposed in this study.

• Journal of the Korean Geotechnical Society
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• v.27 no.7
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• pp.47-57
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• 2011

The p-y curve has been used to design pile foundations subjected to lateral loading. Although the p-y curve has a large influence on the pile lateral behavior, p-y curves have not been clearly suggested. In this study, the p-y curve of clay was evaluated for drilled shafts in marine deposits by using 3-dimensional numerical analyses. First, the optimization study was performed to properly determine boundary extent, mesh size, and interface stiffness. The numerical modeling in the study was verified by comparing the calculated and the pile loading test results. Then, the p-y curves of single and group piles were evaluated from the parametric study. The selected parameters were pile diameter, pile Young's modulus and pile head fixed condition for a single pile, and pile spacing for group piles. Finally, the p-multiplier was evaluated by comparing the p-y curves of a single pile and group piles. As a result, the p-multiplier at pile spacing of 3D was 0.83, 0.67 and 0.78 for the front, middle, and back row piles, respectively, and showed values similar to those of O'Neill and Reese (1999). For the pile group with pile spacing larger than 60, the group effect can be ignorable.

• Journal of Korean Society of Steel Construction
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• v.19 no.2
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• pp.233-245
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• 2007

Previous finite element studies have shown that AASHTO Standard load distribution factor (LDF) equations appear to be conservative for longer spans and larger girder spacing, but too permissible for short spans and girder spacing. AASHTO LRFD specification defines the distribution factor equation for girder spacing, span length, slab thickness, and longitudinal stiffness. However, this equation requires an iterative procedure to correctly determine the LDF value due to an initially unknown longitudinal stiffness parameter. This study presents a simplified LDF equation for interior and exterior girders of two-span continuous I-girder bridges that does not require an iterative design procedure. The finite element method was used to investigate the effect of girder spacing, span length, slab thickness, slab width, and spacing and size of bracing. The computer program, GTSTRUDL, was used to idealize the bridge superstructures as the eccentric beam model, the concrete slab by quadrilateral shell elements, steel girders by space frame members, and the composite action between these elements by rigid links. The distribution factors obtained from these analyses were compared with those from the AASHTO Standard and LRFD methods. It was observed through the parametric studies that girder spacing, span length, and slab thickness were the dominant parameters compared with others. The LRFD distribution factor for the interior girder was found to be conservative in most cases, whereas the factor for the exterior girder to be unconservative in longer spans. Furthermore, a regression analysis was performed to develop simplified LDF formulas. The formulas developed in this study produced LDF values that are always conservative to those from the finite element method and are generally smaller than the LDF values obtained from the AASHTO LRFD specification. The proposed simplified equation will assist bridge engineers in predicting the actual LDF in two-span continuous I-girder bridges.

• Journal of Pharmaceutical Investigation
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• v.39 no.1
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• pp.29-36
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• 2009

Since the quality of final products is significantly affected by the homogeneity of powder mixture, the powder blending process has been regarded as one of the critical pharmaceutical unit processes, especially for solid dosage forms. Accordingly, the monitoring to determine a blending process' end-point based on a faster and more accurate in-line/on-line analysis has attracted enormous attentions recently. Among various analytical tools, NIR (near-infrared) spectroscopy has been extensively studied for PAT (process analytical technology) system due to its many advantages. In this study, NIR spectroscopy was employed with an optical fiber probe for the in-line monitoring of fluid-bed blending process. The position of the probe, the ratio of binary powder mixture, the powder size differential and the back-flush period of the shaking bag were examined as principal process parameters. During the blending process of lactose and mannitol powders, NIR spectra were collected, corrected, calibrated and analyzed using MSC and PLS method, respectively. The probe position was optimized. A reasonable end-point was predicted as 1,500 seconds based on 5% RSD value. As a consequence, it was demonstrated that the blending process using a fluid-bed processor has several advantages over other methods, and the application of NIRS with an optical fiber probe as PAT system for a fluid-bed blending process could be high feasible.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.42 no.1
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• pp.45-55
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• 2016

Light shows various optical behaviors such as reflection, absorption, and scattering on skin for individuals. In particular, reflection of light from the skin has been widely used as the brightness index of the skin of individuals through the measurement of the physical quantity of spectral reflectance. Therefore, the study of light behavior on skin would be useful for the preparation of new evaluation method in the development stage of make-up products. In this study, multi-dimensional analysis for spectral reflectance behavior of light on individual skin was performed using Kubelka-Munk model. Also, we analyzed the contribution of skin parameters such as skin thickness and hemoglobin, which could affect the spectral reflectance, using above model and literature information. Base on this, we calculated the theoretical reflectance of normal women for visual light, which showed good agreement with the measured reflectance. Our study of light propagation in skin based on Kubelka-Munk model provides useful insight for the development of personalized cosmetic in the near future.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.6-14
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• 2011

The fast growing of the number of users requires the development of reliable communication systems able to provide higher data rates. In order to meet those requirements, techniques such as Multiple Input Multiple Out (MIMO) and Orthogonal Frequency Division multiplexing (OFDM) have been developed in the recent years. In order to combine the benefits of both techniques, the research activity is currently focused on MIMO-OFDM systems. In addition, for a fast wireless channel environment, the data rate and reliability can be optimized by setting the modulation and coding adaptively according to the channel conditions; and using sub-carrier frequency, and power allocation techniques. Depending on how accurate the feedback-based system obtain the channel state information (CSI) and feed it back to the transmitter without delay, the overall system performance would be poor or optimal. In this paper, we propose a Signal to Noise Ratio (SNR) estimation algorithm where the preamble is known for both sides of the transciever. Through simulations made over several channel environments, we prove that our proposed SNR estimation algorithm is more accurate compared with the traditional SNR estimation. Also, We applied AMC on several channel environments using the parameters of IEEE 802.11n, and compared the Throughput performance when using each of the different SNR Estimation Algorithms. The results obtained in the simulation confirm that the proposed algorithm produces the highest Throughput performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.6
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• pp.69-77
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• 2002

To acquire the dynamic response and design the controller of the airship, the longitudinal motion of the airship with respect to the vertical gust, which is the nonlinear system, was studied. The effects of the apparent mass and moment of the airship delay the dynamic response and the settling time, which are slower than those of conventional airplanes. The current object of the airship is designed to cruise at 500~1000m altitude. At that height, the atmospheric conditions are generally unstable by wind gust. In this paper, it has been studied for the case of vertical gust, since the apparent mass effects are dominant in has been studied for the case of vertical gust, since the apparent mass effects are dominant in that plane. In addition to the study of the dynamic responses of the airship, the controller was designed using the PID-controller. When the gust was applied, airship responses were recovered of equilibrium states. However, it takes too ling time for recovery and the speed of airship is reduced. So, the aim in this paper was to fasten the recovery speed and to get back the cruising velocity. The control parameters were determined from the stability mode analysis, and the control inputs were the thrust and the elevator deflection angle.