• Bulletin of the Korean Space Science Society
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• 2003.10a
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• pp.48-48
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• 2003

A precision orbit determination (POD) system of low Earth orbiter using the GPS dual frequency measurements has been developed. It is an option of KOMPSAT-2 POD process system. In this research, the orbit determination using the real dual frequency carrier phase measurements of the SAC-C satellite was conducted to verify KOMPSAT-2 POD system reliability. The SAC-C satellite is an international cooperative mission between NASA, the Argentine Commission on Space Activities (CONAE), Centre National d'Etudes Spatiales (CNES or the French Space Agency), Instituto Nacional De Pesquisas Espaciais (Brazilian Space Agency), Danish Space Research Institute, and Agenzia Spaziale Italiana (Italian Space Agency). The SAC-C was launched at November 21, 2000. The altitude of SAC-C is 702 km and it carries a TurboRogue III GPS and four high gain antennas developed by the JPL. The receiver is able to generate the dual frequency code and carrier phase data. Double-differenced carrier phase measurements were formed using 25 IGS stations. The data were sampled at 30 seconds interval. Fully dynamic approach was adopted for POD. The POD results were compared with those of JPL using GOA n software. The comparison verifies that deci-meter level 3D position accuracy of low Earth orbiting satellite could be achieved. The POD system has been developed successfully.

• Earthquakes and Structures
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• v.8 no.5
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• pp.1215-1240
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• 2015

In this paper, the Theory of Plastic Mechanism Control (TPMC) is applied to the seismic design of dual systems composed by moment-resisting frames and Chevron braced frames. The application of TPMC is aimed at the design of dual systems able to guarantee, under seismic horizontal forces, the development of a collapse mechanism of global type. This design goal is of primary importance in seismic design of structures, because partial failure modes and soft-storey mechanisms have to be absolutely prevented due to the worsening of the energy dissipation capacity of structures and the resulting increase of the probability of failure during severe ground motions. With reference to the examined structural typology, diagonal and beam sections are assumed to be known quantities, because they are, respectively, designed to withstand the whole seismic actions and to withstand vertical loads and the net downward force resulting from the unbalanced axial forces acting in the diagonals. Conversely column sections are designed to assure the yielding of all the beam ends of moment-frames and the yielding and the buckling of tensile and compressed diagonals of the V-Braced part, respectively. In this work, a detailed designed example dealing with the application of TPMC to moment frame-chevron brace dual systems is provided with reference to an eight storey scheme and the design procedure is validated by means of non-linear static analyses aimed to check the actual pattern of yielding. The results of push-over analyses are compared with those obtained for the dual system designed according to Eurocode 8 provisions.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.5
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• pp.41-51
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• 2010

For safe seismic evaluation and design, it is necessary to predict the plastic deformation demands of members. In the present study, a quick and reasonable method for the evaluation of member plastic deformations of dual systems was developed on the basis of results of elastic analysis, without using nonlinear analysis. Plastic deformations of beams, columns, and walls are functions of member stiffness, story drift ratio, and moment redistribution determined from elastic analysis. For dual systems with rigid connections between walls and beams, an increase in the plastic deformations of beams due to the rocking effect was considered. The proposed method was applied to 8-story dual systems and the predicted plastic deformations were compared with the results of nonlinear analysis. The results showed that the proposed method accurately predicted the member plastic deformations with simple calculations, but that for the accurate evaluation of member plastic deformations, the inelastic story drift ratio must also be predicted with accuracy. The proposed method can be applied to both the performance-based seismic design of new structures and the seismic evaluation of existing structures.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1015-1026
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• 2018

A family of dual-DC-input (DI) dual-buck inverters (DBIs) is proposed by employing a DI switching cell as the input of traditional DBIs. Three power ports, i.e. a low voltage DC input port, a high voltage DC input port and an AC output port, are provided by the proposed DI-DBIs. A low voltage DC source, whose voltage is lower than the peak amplitude of the AC side voltage, can be directly connected to the DI-DBI. This supplies power to the AC side in single-stage power conversion. When compared with traditional DBI-based two-stage DC/AC power systems, the conversion stages are reduced, and the power rating and power losses of the front-end Boost converter of the DI-DBI are reduced. In addition, five voltage-levels are generated with the help of the two DC input ports, which is a benefit in terms of reducing the voltage stresses and switching losses of switches. The topology derivation method, operation principles, modulation strategy and characteristics of the proposed inverter are analyzed in-depth. Experimental results are provided to verify the effectiveness and feasibility of the proposed DI-DBIs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3554-3570
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• 2021

With the rapid development of the Chinese water project, the safety monitoring of dams is urgently needed. Many drawbacks exist in dams, such as high monitoring costs, a limited equipment service life, long-term monitoring difficulties. MEMS sensors have the advantages of low cost, high precision, easy installation, and simplicity, so they have broad application prospects in engineering measurements. This paper designs intelligent monitoring based on the collaborative measurement of dual MEMS sensors. The system first determines the endpoint coordinates of the sensor array by the coordinate transformation relationship in the monitoring system and then obtains the dam settlement according to the endpoint coordinates. Next, this paper proposes a dual-MEMS sensor collaborative measurement algorithm that builds a mathematical model of the dual-sensor measurement. The monitoring system realizes mutual compensation between sensor measurement data by calculating the motion constraint matrix between the two sensors. Compared with the single-sensor measurement, the dual-sensor measurement algorithm is more accurate and can improve the reliability of long-term monitoring data. Finally, the experimental results show that the dam subsidence monitoring system proposed in this paper fully meets the engineering monitoring accuracy needs, and the dual-sensor collaborative measurement system is more stable than the single-sensor monitoring system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.5
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• pp.18-24
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• 2010

This paper propose a dual-layer beam-forming technique for MIMO-OFDM systems. Dual-layer beam-forming is a capacity enhancing technique to transmit two streams of source data with more than two transmit and receive antennas. Beamforming is a technique to enhance the link-level performances gain using antenna array with the small inter element distance. The proposed scheme can obtain both high capacity of spatial multiplexing and antenna array gain of beamforming for MIMO-OFDM systems. Therefore, it provides better BER performance than the traditional spatial multiplexing and beamforming techniques under the same simulation environment.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Korean Management Science Review
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• v.29 no.3
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• pp.81-89
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• 2012

Since introduced by Vining and Myers in 1990, the concept of dual response approach based on response surface methodology has widely been investigated and adopted for the purpose of robust design. Separately estimating mean and variance responses, dual response approach may take advantages of optimization modeling for finding optimum settings of input factors. Explicitly assuming functional relationship between responses and input factors, however, it may not work well enough especially when the behavior of responses are poorly represented. A sufficient number of experimentations are required to improve the precision of estimations. This study proposes an alternative to dual response approach in which additional experiments are not required. An artificial neural network has been applied to model relationships between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Training, validating, and testing a neural network with empirical process data, an artificial data based on the neural network may be generated and used to estimate response functions without performing real experimentations. A drug formulation example from pharmaceutical industry has been investigated to demonstrate the procedures and applicability of the proposed approach.

• The Journal of Information Systems
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• v.25 no.3
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• pp.197-215
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• 2016

Purpose This study aims to investigate the factors that influence decision making in relation to providing personal information on the internet with respect to the integration of the privacy calculus theory and protection motivation theory based on the dual-calculus model proposed by Li(2012). Design/methodology/approach The privacy calculus theory and protection motivation theory have been applied to explain privacy behavior to a certain degree but few studies have been conducted to explain privacy behavior based on the integration of these two theories. Although Li(2012) proposed the dual-calculus model, he only proposed its framework and did not carry out an empirical study. Therefore, this study proposes a research model that integrates these two theories and examines the relationship between the two theories through an empirical study. Findings According to the results of empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between coping appraisal and privacy risk in the risk calculus process. Thus, the results verify that external threat played a decisive role in increasing the risk level of a consumer's privacy. It can be discussed the ways to enhance the privacy behavior of consumer on the internet through these findings.