• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.83-94
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• 2007

In this paper, we consider a standby redundant structure with a function of switchover processing which may not be not perfect. The switchover processing is governed by a control module whose failure may cause the failure of the whole system. The parameters measuring such an effect of failure of the control module is included in our reliability model. We compute several reliability measures such as reliability function, failure rate, MTBF, mean residual life function, and the steady state availability. We also compare a single unit structure and the redundant structure with regard to those reliability measures. An example is given to illustrate our results.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2E
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• pp.86-99
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• 2010

This paper analyzes the performance of various single channel speech enhancement algorithms when they are applied to automatic speech recognition (ASR) systems as a preprocessor. The functional modules of speech enhancement systems are first divided into four major modules such as a gain estimator, a noise power spectrum estimator, a priori signal to noise ratio (SNR) estimator, and a speech absence probability (SAP) estimator. We investigate the relationship between speech recognition accuracy and the roles of each module. Simulation results show that the Wiener filter outperforms other gain functions such as minimum mean square error-short time spectral amplitude (MMSE-STSA) and minimum mean square error-log spectral amplitude (MMSE-LSA) estimators when a perfect noise estimator is applied. When the performance of the noise estimator degrades, however, MMSE methods including the decision directed module to estimate a priori SNR and the SAP estimation module helps to improve the performance of the enhancement algorithm for speech recognition systems.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1878-1888
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• 1990

In this paper, the input-output interconnection method of the multi-valued signal processing circuit using perfect Shuffle technique and Kronecker product is discussed. Using this method, the design method of circuit of the multi-valued Reed-Muller expansions(MRME) to be used the multi-valued signal processing on finite field GF(p**m) is presented. The proposed input-output interconnection method is shown that the matrix transform is efficient and that the module structure is easy. The circuit design of MRME on FG(p**m) is realized following as` 1) contructing the baisc gates on GF(3) by CMOS T gate, 2) designing the basic cells to be implemented the transform and inverse transform matrix of MRME using these basic gates, 3) interconnecting these cells by the input-output interconnecting method of the multivalued signal processing circuits. Also, the circuit design of the multi-valued signal processing function on GF(3\ulcorner similar to Winograd algorithm of 3x3 array of DFT (discrete fourier transform) is realized by interconnection of Perfect Shuffle technique and Kronecker product. The presented multi-valued signal processing circuits that are simple and regular for wire routing and posses the properties of concurrency and modularity are suitable for VLSI.

• Structural Engineering and Mechanics
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• v.66 no.4
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• pp.495-504
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• 2018

The current study is dedicated to study the thermal effects of wave propagation in beams, reinforced by carbon nanotubes (CNT). Beams, made up of carbon nanotube reinforced composite (CNTRC) are the future materials in various high tech industries. Herein a Winkler elastic foundation is assumed in order to make the model more realistic. Mostly, CNTs are pervaded in cross section of beam, in various models. So, it is tried to use four of the most profitable reconstructions. The homogenization of elastic and thermal properties such as density, Yong's module, Poisson's ratio and shear module of CNTRC beam, had been done by the demotic rule of mixture to homogenize, which gives appropriate traits in such settlements. To make this investigation, a perfect one, various shear deformation theories had been utilized to show the applicability of this theories, in contrast to their theoretical face. The reigning equation had been derived by extended Hamilton principle and the culminant equation solved analytically by scattering relations for propagation of wave in solid bodies. Results had been verified by preceding studies. It is anticipated that current results can be applicable in future studies.

• Progress in Superconductivity and Cryogenics
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• v.9 no.3
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• pp.57-61
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• 2007

The current limiting characteristics of hybrid SFCL with additional power electronic devices was investigated in order to improve operation reliabilities. The hybrid SFCL developed consists of a superconducting trigger (S/T) part, a fast switch (F/S) module and a current limiting (C/L) part. Although hybrid SFCL had shown a excellent current limiting characteristics, this device was rather vulnerable to the residual arc currents which could exist during fast switch operation. This undesirable arc should be extinguished as quickly as possible in order to implement perfect fault current commutation. So, in order to eliminate the residual arcs between fast switch contacts, the power electronic devices (IGBT or GTO) were connected in series between the S/T part and the interrupter of the F/S module. According to the fault tests conducting with an input voltage of $270\;V_{rms}$ and a fault current of $5\;kA_{rms}$, The power electronic devices could perfectly remove the arc generated between the contacts of the interrupter within 4 ms after the fault occurred. From the test analysis, it was confirmed that the hybrid SFCL could enhance the operation reliability by adopting additional power electronic devices.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.36-45
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• 2000

Automated production system is composed of many complicated techniques and it become a very difficult task to control, monitor and diagnose this compound system. Moreover, it is required to develop an effective diagnosing technique and reduce the diagnosing time while operating the system in parallel under many faults occurring concurrently. This study develops a Modular Artificial Neural Network(MANN) which can perform a diagnosing function of multiple faults with the following steps: 1) Modularizing a complicated system into subsystems. 2) Formulating a hierarchical structure by dividing the subsystem into many detailed elements. 3) Planting an artificial neural network into hierarchical module. The system developed is implemented on workstation platform with $X-Windows^{(r)}$ which provides multi-process, multi-tasking and IPC facilities for visualization of transaction, by applying the software written in $ANSI-C^{(r)}$ together with $MOTIF^{(r)}$ on the fault diagnosis of PI feedback controller reactor. It can be used as a simple stepping stone towards a perfect multiple diagnosing system covering with various industrial applications, and further provides an economical approach to prevent a disastrous failure of huge complicated systems.

• Bulletin of the Korean Mathematical Society
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• v.61 no.1
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• pp.1-12
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• 2024

In this paper, we introduce the notion of Gorenstein (m, n)-flat modules as an extension of (m, n)-flat left R-modules over a ring R, where m and n are two fixed positive integers. We demonstrate that the class of all Gorenstein (m, n)-flat modules forms a Kaplansky class and establish that (𝓖𝓕_m,n(R),𝓖𝓒_m,n(R)) constitutes a hereditary perfect cotorsion pair (where 𝓖𝓕_m,n(R) denotes the class of Gorenstein (m, n)-flat modules and 𝓖𝓒_m,n(R) refers to the class of Gorenstein (m, n)-cotorsion modules) over slightly (m, n)-coherent rings.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.27-34
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• 2005

Iterative detection (ID) has proven to be a near-optimal solution for concatenated Finite State Machines (FSMs) with interleavers over an additive white Gaussian noise (AWGN) channel. When perfect channel state information (CSI) is not available at the receiver, an adaptive ID (AID) scheme is required to deal with the unknown, and possibly time-varying parameters. The basic building block for ID or AID is the soft-input soft-output (SISO) or adaptive SISO (A-SISO) module. In this paper, Reduced State SISO (RS-SISO) algorithms have been applied for complexity reduction of the A-SISO module. We show that serially concatenated CPM (SCCPM) with AID has turbo-like performance over fading ISI channels and also RS-A-SISO systems have large iteration gains. Various design options for RS-A-SISO algorithms are evaluated. Recently developed density evolution technique is used to analyze RS-A-SISO algorithms. We show that density evolution technique that is usually used for AWGN systems is also a good analysis tool for RS-A-SISO systems over frequency-selective fading channels.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.3
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• pp.1-11
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• 1999

It is now common practice to utilize the quadrature RF coils to improve the signal-to-noise ratio (SNR) in the Magnetic Resonance Imaging (MRI) System. In addition, to make such an available SNR improvement, it is mandatory to use a well-designed quadrature coupler, which facilitates a perfect 3-dB coupling and quadrature-phase shift. However, the four ports matching condition has to be well considered during the RF excitation and the signal detection period. This work investigates the effects of such a mismatching condition (especially, due to patient) from the analysis, simulation, and real implementation and firstly proposes dynamic loading technique for a quadrature coupler and transmitting/receiving switch module to minimize a patient mismatching and enhance a system reliability. Also, we designed and implemented the quadrature coupler and transmitting/receiving switch module using microstrip. As a result, the SNR of our MRI system using the microstrip quadrature coupler and transmitting/receiving switch module with dynamic load increases 3 dB compared with the old one using USA quadrature switch. Also, the power capability of quadrature coupler and transmitting/receiving switch module is 5-kw peak power. Considering power loss and reduction of size, we used a RT/duroid 6010 substrate with high permittivity and for simulation we use Compact Software.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.53-59
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• 2022

After the 3rd level autonomous driving vehicle, the 4th and 5th level of autonomous driving technology is trying to maintain the optimal condition of the passengers as well as the perfect driving of the vehicle. However current autonomous driving technology is too dependent on visual information such as LiDAR and front camera, so it is difficult to fully autonomously drive on roads other than designated roads. Therefore this paper proposes a Braking Strength Calculation System (BSCS), in which a vehicle classifies road conditions using data other than visual information and calculates optimal braking strength according to road conditions and driving conditions. The BSCS consists of RCDM (Road Condition Definition Module), which classifies road conditions based on KNN algorithm, and BSCM (Braking Strength Calculation Module), which calculates optimal braking strength while driving based on current driving conditions and road conditions. As a result of the experiment in this paper, it was possible to find the most suitable number of Ks for the KNN algorithm, and it was proved that the RCDM proposed in this paper is more accurate than the unsupervised K-means algorithm. By using not only visual information but also vibration data applied to the suspension, the BSCS of the paper can make the braking of autonomous vehicles smoother in various environments where visual information is limited.