• Investigative Magnetic Resonance Imaging
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• v.24 no.3
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• pp.95-122
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• 2020

In this article, we evaluated the performance of radiofrequency (RF) coils in terms of the signal-to-noise ratio (S/N) and homogeneity of magnetic resonance images when used for ultrahigh-frequency (UHF) 7T magnetic resonance imaging (MRI). High-quality MRI can be obtained when these two basic requirements are met. However, because of the dielectric effect, 7T magnetic resonance imaging still produces essentially a non-uniform magnetic flux (|B₁|) density distribution. In general, heterogeneous and homogeneous RF coils may be designed using electromagnetic (EM) modeling. Heterogeneous coils, which are surface coils, are used in consideration of scalability in the |B₁| region with a high S/N as multichannel loop coils rather than selecting a single loop. Loop coils are considered state of the art for their simplicity yet effective |B₁|-field distribution and intensity. In addition, combining multiple loop coils allows phase arrays (PA). PA coils have gained great interest for use in receiving signals because of parallel imaging (PI) techniques, such as sensitivity encoding (SENSE) and generalized autocalibrating partial parallel acquisition (GRAPPA), which drastically reduce the acquisition time. With the introduction of a parallel transmit coil (pTx) system, a form of transceiver loop arrays has also been proposed. In this article, we discussed the applications and proposed designs of loop coils. RF homogeneous coils for volume imaging include Alderman-Grant resonators, birdcage coils, saddle coils, traveling wave coils, transmission line arrays, composite right-/left-handed arrays, and fusion coils. In this article, we also discussed the basic operation, design, and applications of these coils.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.430-439
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• 2011

In this paper, we design a digital predistortion(DPD) for linearity enhancement of RF power amplifier operating in 900 MHz band. We verify improvement of linearity by comparing the proposed DPD using tanh as a nonlinear indexing function and the DPD using linear indexing function based on signal amplitude. The digital predistortion is realized by look-up table(LUT) method, and the Saleh model is employed for power amplifier modeling, then a commercial power amplifier module is used for measurement. The LUT has 256 tables, and the NLMS(Normalized Least Mean Square) algorithm was utilized for an adaptive algorithm for estimation. As a result, we improve the ACLR(Adjacent Channel Leakage Ratio) by around 15 dB.

• Journal of Biosystems Engineering
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• v.41 no.2
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• pp.108-115
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• 2016

Purpose: Radio frequency (RF) heating is a promising thawing method, but it frequently causes undesirable problems such as non-uniform heating. This can occur because of the food shape, component distribution, and initial temperature differences between food parts. In this study, RF heating was applied to the thawing of cylindrically shaped pork sirloin by changing the shape of electrodes and the surrounding temperature. Methods: Curved electrodes were utilized to increase the thawing uniformity of cylindrically shaped frozen meat. Pork sirloin in the shape of a half-circle column was frozen in a deep freezer at $-70^{\circ}C$ and then thawed by RF heating with flat and curved electrodes. In order to prevent fast defrosting of the food surface by heat transfer from air to the food, the temperature of the thawing chamber was varied by -5, -10, and $-20^{\circ}C$. The temperature values of the frozen pork sirloin during RF thawing were measured using fiber-optic thermo sensors. Results: After multiple applications of curved electrodes resembling the food shape, and a cooled chamber at $-20^{\circ}C$ the half-cylindrically shaped meat was thawed without surface burning, and the temperature values of each point were similarly increased. However, with the parallel electrode, the frozen meat was partially burned by RF heating and the temperature values of center were overheated. The uniform heating rate and heat transfer prevention from air to the food were crucial factors for RF thawing. In this study, these crucial factors were accomplished by using a curved electrode and lowering the chamber temperature. Conclusions: The curved shape of the electrode and the equipotential surface calculated from the modeling of the parallel capacitor showed the effect of uniform heating of cylindrically shaped frozen food. Moreover, the low chamber temperature was effective on the prevention of the surface burning during RF thawing.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.393-396
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• 1999

A circuit model of silicon substrate coupling for CMOS RF-IC design is developed. Its characteristics are analyzed by using a simple RC mesh model in order to investigate substrate coupling. The coupling effects due to the substrate were characterized with substrate resistivity, oxide thickness, substrate thickness. and physical distance. Thereby the silicon substrate effects are analytically investigated and verified with simulation. The analysis and simulation of the model have excellent agreements with MEDICI(2D device simulator) simulation results.

• ETRI Journal
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• v.26 no.4
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• pp.307-314
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• 2004

The application of a discrete pseudomorphic high electron mobility transistor (p-HEMT) as a grounded switch allows for the development of low cost phase shifters and phase modulators operating in a Ku band. This fills the gap in the development of phase control devices comprising p-i-n diodes and microwave monolithic integrated circuits (MMICs). This paper describes a discrete p-HEMT characterization and modeling in switching mode as well as the development of a low-cost four-bit phase shifter and direct quadrature phase shift keying (QPSK) modulator. The developed devices operate in a Ku band with parameters comparable to commercially available MMIC counterparts. Both of them are CMOS compatible and have no power consumption. The parameters of the QPSK modulator are very close to the requirements of available standards for satellite earth stations.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.895-898
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• 1999

Recently, small signal modeling of CMOS device becomes more difficult because the design rule goes into deep submicron. De-embedding of substrate parameters is important in order to use CMOS devices at RF frequencies. In this paper, we suggest a new de-embedding model with refined physical meaning and accuracy. In GaAs IC’s, the substrate is almost an insulator but Si substrate has the semiconducting characteristics. It offers some troubles if it is treated like GaAs substrate. The conducting substrate is modeled with five resistances, which leads to very accurate modeling so long as the pad layout is symmetrical. Frequency range is up to 39㎓ and fitting accuracy is as small as 0.00037 on least square errors.

• Journal of information and communication convergence engineering
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• v.1 no.1
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• pp.6-11
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• 2003

In general, standard TCP/IP (transmission control protocol-internet protocol), which is called TCP/IP, is using as the communication basis protocol between any collections of networks that is connected. In this paper, using this TCP/IP implementation of remote control system and suitable program for long distance communication is proposed. This system can make system, which basic Ethernet and TCP/IP used system, to mini modeling, so all module that is using here can be used. Therefore, intention of this paper is to reduce expenses, to effective manage for plant and to increase of productivity as linking each plant of several factory to TCP/IP and Ethernet, and then many control plant and manager minimize the needed course.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2327-2329
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• 2005

In this paper, we identify the memory effects of the RF high-power base station amplifiers with Vector Signal Analyzer (VSA). It is found that the model of power- amplifier using Tapped Delayed Neural - Networks with back-propagation algorithm shows very accurate modeling performance. Based on this behavioral modeling, we conducted inverse compensation process which also uses Neural Networks.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.11
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• pp.831-836
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• 2010

In this paper, Plasma Enhanced Chemical Vapor Deposition (PECVD) $SiO_2$ film properties are modeled using statistical analysis and neural networks. For systemic analysis, Box-Behnken's 3 factor design of experiments (DOE) with response surface method are used. For characterization, deposited film thickness and film stress are considered as film properties and three process input factors including plasma RF power, flow rate of $N_2O$ gas, and flow rate of 5% $SiH_4$ gas contained at $N_2$ gas are considered for modeling. For film thickness characterization, regression based model showed only 0.71% of root mean squared (RMS) error. Also, for film stress model case, both regression model and neural prediction model showed acceptable RMS error. For sensitivity analysis, compare to conventional fixed mid point based analysis, proposed sensitivity analysis for entire range of interest support more process information to optimize process recipes to satisfy specific film characteristic requirements.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.87-94
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• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.