• Transactions of Materials Processing
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• v.21 no.3
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• pp.207-214
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• 2012

High temperature deformation behavior of a $Ni_{30}Fe_{53}Co_{17}$ alloy, with its extraordinary low coefficient of thermal expansion less than $10{\times}10^{-6}K^{-1}$ at temperatures ranging from room temperature to 673K, was investigated by conducting a series of compression tests. From an empirical processing map, the appropriate working temperature-strain rate combination for optimum forming was deduced to be in the ~1373K, $10^{-2}s^{-1}$ region. This region has a relatively high power dissipation efficiency, greater than 0.36. Furthermore, open die forging of a 100mm diameter billets was performed to confirm the variation of thermo-physical properties in relation to microstructure. The coefficient of thermal expansion was found to increase considerably with increasing the open die forging temperature and decreasing the cooling rate, which in turn provides a drastic increase in the average grain size.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.531-540
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• 2004

Development of Web service application requires the interoperability between various heterogeneous systems, extensibility to allow modification of business environment not of user interface, maintainability, flexibility and reusability As the properties of CBD (Component Based Development) have gradually become clear, attention has started to turn the smooth technology and methodology to solve the existing problems and issues the dynamic responds for the distributed web environments. In this paper, we identify some of the major architectural affecting CBD and describe the Design and Implementation of Security Framework for Application Server with Components. We identify the candidate components, model it using UML and layer it on the architecture. The frameworks will Provide the various security functions, such as incorporating with legacy security systems, supporting of J2EE, JAAS and Kerberos and assisting in increasing the tailorability of component.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.609-618
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• 2006

This paper presents the lateral control of an autonomous vehicle by using a look-ahead sensing system. In look-ahead sensing by an absolute positioning system, a reference lane, constructed by straight lanes or circular lanes, was switched by a segment switching algorithm. To cope with sensor noise and modeling uncertainty, a robust LMI-based $H_{\infty}$ lateral controller was designed by the feedback of lateral offset and yaw angle error at the vehicle look-ahead. In order to verify the safety and the performance of lateral control, a scaled-down vehicle was developed and the location of the vehicle was detected by using an ultrasonic local positioning system. In the mechatronic scaled-down vehicle, the lateral model and parameters are verified and estimated by a J-turn test. For the lane change and reference lane tracking, the lateral controllers are used experimentally. The experimental results show that the $H_{\infty}$ controller is robust and has better performance compared with look-down sensing.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.735-743
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• 2010

A new Fuzzy sliding mode controller is proposed to improve the cornering performance of the four wheel hybrid vehicles. The Fuzzy sliding mode control is applied for the control of rear motor and EHB (Electro-Hydraulic Brake) to improve the cornering performance. The modeling of the automobile is simplified that each of the two wheels is modeled as two degrees of freedom object and the friction coefficient between the wheel and the ground is assumed to be constant. The output of the Fuzzy sliding mode algorithm is the direct yaw moment for the rear wheels, which compensates for the slip angle. Through the simulations using ADAMS and MATLAB Simulink, the cornering performance of the proposed algorithm is compared to the conventional PID to show the superiority of the proposed algorithm. In the simulation experiments, the J-Turn and single lane change are used for each of the Fuzzy sliding mode algorithm and PID controller with the optimal gains which are tuned empirically.

• JSTS:Journal of Semiconductor Technology and Science
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• v.3 no.1
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• pp.21-26
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• 2003

4H-SiC Schottky rectifiers were exposed to pure Ar discharges in a planar coil Inductively Coupled Plasma system, as a function of source power, of chuck power and process pressure. The reverse breakdown voltage ($V_B$) decreased as a result of plasma exposure due to the creation of surface defects associated with the ion bombardment. The magnitude of the decrease was a function of both ion flux and ion energy. The forward turn-on voltage ($V_F$), on-state resistance ($R_{ON}$) and diode ideality factor (n) all increased after plasma exposure. The changes in all of the rectifier parameters were minimized at low power, high pressure plasma conditions.

• Journal of the Korean institute of surface engineering
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• v.38 no.2
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• pp.60-64
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• 2005

The ICP-CVD (inductively coupled plasma chemical vapor deposition) process was applied to the deposition of $TiB_2$ films. For plasma generation, 13.56 MHz r.f. power was supplied to 2-turn Cu coil placed inside chamber. And the gas mixture of $TiCl_4,\;BCl_3,\;H_2$ and Ar was used for $TiB_2$ deposition. $TiB_2$ films with high hardness (<40 GPa) were obtained at extremely low deposition temperature $(250^{\circ}C)$, and the films hardness increased with ICP power and gas flow ratio of $TiCl_4/BCl_3$. The film structure was changed from (100) preferred orientation to random orientation with increasing RF power. It is supposed that the enhanced hardness of films was caused by a strong Ti-B chemical bonding of stoichiometric $TiB_2$ films and film densification induced by high density plasma.

• Journal of Magnetics
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• v.10 no.4
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• pp.145-148
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• 2005

Effect of vacuum annealing on the microstructures and magnetic properties of $Fe_{84}Si_6B_{10}$ films has been investigated as a function of annealing temperature. X-ray diffraction and transmission electron microscopy were employed to analyze crystallization behavior of the films. Permeability of the films was measured at various frequencies by one-turn coil method. When the films were annealed below 673 K, the coercivity of the films did not change a lot (${\~}$1500 A/m) although the grain size of a crystalline phase in the partially crystallized films increased gradually up to about 16 nm. It then increased rapidly as the films became almost fully crystalline mostly with $\alpha$-(Fe,Si) phase at and above 723 K. On the other hand, the electrical resistivity of the films decreased monotonically with the increase of annealing temperature. The permeabilities of the films annealed at 473${\~}$673 K were all over 1000, showing the optimum value of 3500 at 523 K, and almost constant up to 300 MHz. However, those of the as-deposited and fully crystallized films were lower than 1000 and unstable at the same frequency range.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.145-150
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• 1993

It is an important component of the diagnosis to research the morphological changes of EMG in pathological conditions. In order to provide an EMG signal resulting from a predetermined neuromuscular pathophysiology, we have initially developed a mathmatical model of electromyographic interference pattern(IP). It can be used to study the variation of the IP resulting from morphological and electrophysiological changes occurring in disease states, because the model computes the IP from the underlying fiber and muscle structure. We performed quantative analysis or the model output, focusing on IPs resulting from simulations of dystrophic fiber loss and the MU denervation and reinnervation typical of neuropathies. To discribe the characteristics of IPs associated with these pathologies, a set of frequency domain discriptors, activity, mobility, and complexity were used, as well as several measures of the spectral density function. These discriptors demonstrate distinct patterns of variation corresponding to morphological changes observed in disease states, and closely with results obtained from the classical method, turn/amp technique.

• Progress in Superconductivity and Cryogenics
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• v.21 no.1
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• pp.10-14
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• 2019

Radio-frequency (RF) amplifiers based on direct current (DC) superconducting quantum interference device (SQUID) have low-noise performance for precision physics experiments. Gain curves of SQUID RF amplifiers depend on several parameters of the SQUID and operation conditions. We are developing SQUID RF amplifiers for application to measure very weak RF signals from ultra-low-temperature high-magnetic-field microwave cavity in axion search experiments. In this study, we designed, fabricated and characterized SQUID RF amplifiers with different SQUID parameters, such as number of input coil turn, shunt resistance value of the junction and coupling capacitance in the input coil, and compared the results.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.106-118
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• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.