• Journal of Biomedical Engineering Research
• /
• v.8 no.2
• /
• pp.171-176
• /
• 1987

Wiener filtering method was applied to the dual energy imaging procedure in digital radiography(D.R.). A linear scanning photodiode arrays with 1024 elements(0.6mm H 1.3mm pixel size) were used to obtain chest images in 0.7 sec. For high energy image acquisition, X-ray tube was set at 140KVp, 100mA with a rare-earth phosphor screen. Low energy image was obtained with X-ray tube setting at 70KVp, 150mA. These measured dual energy images are represented in the vector matrix notation as a linear discrete model including the additive random noise. Then, the object images are restored in the minimum mean square error sense using Wiener filtering method in the transformed domain. These restored high and low energy images are used for computation of the basis image decomposition. Then the basis images are linearly combined to produce bone or tissue selective images. Using this process, we could improve the signal to noise ratio characteristics in the material selective images.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.7
• /
• pp.2010-2026
• /
• 2024

This work investigates the hybrid precoder scheme in a millimeter wave (mmWave) multi-user MIMO system. We study a sum rate maximization scheme by jointly designing the digital precoder and the analog precoder. To handle the non-convex problem, a block coordinate descent (BCD) method is formulated, where the digital precoder is solved by a bisection search and the analog precoder is addressed by the penalty dual decomposition (PDD) alternately. Then, we extend the proposed algorithm to the sub-connected schemes. Besides, the proposed algorithm enjoys lower computational complexity when compared with other benchmarks. Simulation results verify the performance of the proposed scheme and provide some meaningful insight.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.25 no.6
• /
• pp.469-476
• /
• 2012

In this paper, a finite element domain decomposition method using local and mixed Lagrange multipliers for a large scal structural analysis is presented. The proposed algorithms use local and mixed Lagrange multipliers to improve computational efficiency. In the original FETI method, classical Lagrange multiplier technique was used. In the dual-primal FETI method, the interface nodes are used at the corner nodes of each sub-domain. On the other hand, the proposed FETI-local analysis adopts localized Lagrange multipliers and the proposed FETI-mixed analysis uses both global and local Lagrange multipliers. The numerical analysis results by the proposed algorithms are compared with those obtained by dual-primal FETI method.

• Journal of applied mathematics & informatics
• /
• v.30 no.5_6
• /
• pp.759-772
• /
• 2012

In this paper, semi-infinite constrained programming, a class of constrained nonsmooth optimization problems, are transformed into unconstrained nonsmooth convex programs under the help of exact penalty function. The unconstrained objective function which owns the primal-dual gradient structure has connection with $\mathcal{VU}$-space decomposition. Then a $\mathcal{VU}$-space decomposition method can be applied for solving this unconstrained programs. Finally, the superlinear convergence algorithm is proved under certain assumption.

• Carbon letters
• /
• v.7 no.4
• /
• pp.277-281
• /
• 2006

In this study, in order to easily provide functional groups on the surface of carbon nanotubes, dual structural multiwalled carbon nanotubes which have crystalline graphite and turbostratic carbon wall were synthesized by modified vertical thermal decomposition method. Synthesized dual structural MWCNTs were characterized by FE-SEM, TGA, HR-TEM, Raman spectroscopy and BET specific surface area analyzer. The average innermost and outermost diameters of the synthesized nanotubes were around 45 and 75 nm, respectively. The large empty inner space and the presence of graphitic carbons on the surface may open potential applications for gas storage and collection of hazardous materials.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.12 no.2
• /
• pp.42-50
• /
• 1987

This objective of this paper is to develop an efficient method with small memory requirement for a feed-mixing problem on a micro computer. First this method uses the decomposition principle to reduce the memory requirement. Next, the decomposition principle is modified to fit the problem. Further four different variations in solving subproblems are designed in order to improve efficiency of the principle. According to the test with respect to the processing time, the best variation is such that the dual simplex method is used, and the optimal basis of a previous subproblem is used as an initial basis, and the master problem is (M +1) dimensional. In general, the convergence of solution becomes slower near the optimal value. This paper introduces a termination criterion for a sufficiently good solution. According to the test, 5%-tolerence is acceptable with respect to the relation between the processing time and optimal value.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.97-104
• /
• 2008

Most of engine control systems for helicopter turboshaft engines are equipped with dual sensors. For the system with dual redundancy, analytic methods are used to detect faults based on the system dynamical model. Helicopter engine dynamics are affected by aerodynamic torque induced from the dynamics of the main rotor. In this paper an engine model including the rotor dynamics is constructed for the T700-GE-700 turboshaft engine powering UH-60 helicopter. The singular value decomposition(SVD) method is applied to the developed model in order to detect sensor faults. The SVD method which do not need an additional computation to generate residual uses the characteristics that the system outputs in direction of the left singular vector if an input is applied in direction of the right singular vector. Simulations show that the SVD method works well in detecting and isolating the sensor faults.

• Current Optics and Photonics
• /
• v.7 no.4
• /
• pp.428-434
• /
• 2023

The compensators used in spectroscopic ellipsometers are usually assumed to be ideal linear waveplates. In reality, however, they are elliptical waveplates, because they are usually made by bonding two or more linear waveplates of different materials with slight misalignment. This induces systematic error when they are modeled as linear waveplates. We propose an improved calibration method based on an optical model that regards an elliptical waveplate as a combination of a circular waveplate (rotator) and a linear waveplate. The method allows elimination of the systematic error, and the residual error of optic axis measurement is reduced to 0.025 degrees in the spectral range of 450-800 nm.

• Journal of Power Electronics
• /
• v.11 no.4
• /
• pp.401-407
• /
• 2011

In order to enhance torque density of five-phase permanent magnetic synchronous motor with third harmonic injection for electric vehicles (EVs) applications, optimum seeking method for injection ratio of third harmonic was proposed adopting theoretical derivation and finite element analysis method, under the constraint of same amplitude for current and air-gap flux. By five-dimension space vector decomposition, the mathematic model in two orthogonal space plane, $d_1-q_1$ and $d_3-q_3$, was deduced. And the corresponding dual-plane vector control method was accomplished to independently control fundamental and third harmonic currents in each vector plane. A five-phase PMSM prototype with quasi-trapezoidal flux pattern and its fivephase voltage source inverter were designed. Also, the dual-plane vector control was digitized in a single XC3S1200E FPGA. Simulation and experimental results prove that using the proposed optimum seeking method, the torque density of five-phase PMSM is enhanced by 20%, without any increase of power converter capacity, machine size and iron core saturation.

• The Journal of Information Technology
• /
• v.3 no.2
• /
• pp.73-85
• /
• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.