• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.527-532
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• 2021

In this paper, we propose an efficient finite field computation method for Rainbow algorithm, which is the only multivariate quadratic-equation based digital signature among the current US NIST PQC standardization Final List algorithms. Recently, Chou et al. proposed a new efficient implementation method for Rainbow on the Cortex-M4 environment. This paper proposes a new multiplication method over the finite field that can reduce the number of XOR operations by more than 13.7% compared to the Chou et al. method. In addition, a multiplicative inversion over that can be performed by a 4x4 matrix inverse instead of the table lookup method is presented. In addition, the performance is measured by porting the software to which the new method was applied onto RaspberryPI 3B+.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.42.1-42.1
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• 2017

We present the results from an extensive spectroscopic survey of the central region of the nearby galaxy cluster Abell 2199 (A2199) at z=0.03. By combining 775 new redshifts from the MMT/Hectospec observations with the data in the literature, we construct a large sample of 1624 galaxies with measured redshifts at R<30', which redsults in high spectroscopic completeness at $r_{petro,0}$<20.5 (77%). We use these data to study the kinematics and clustering of galaxies, focusing on the comparison with those of the intracluster medium (ICM) from Suzaku X-ray observations. We identify 406 member galaxies of A2199 at R<30' using the caustic technique. The velocity dispersion profile of cluster members appears smoothly connected to the stellar velocity dispersion profile of the cD galaxy. The luminosity function is well fitted with a Schechter function at $M_r$<-15. The radial velocities of cluster galaxies generally agree well with those of the ICM, but there are some regions where the velocity difference between the two is about a few hundred kilometers per second. The cluster galaxies show a hint of global rotation at R<5' with $v_{rot}=300-600kms^{-1}$, but the ICM in the same region does not show such rotation. We apply a friends-of-friends algorithm to the cluster galaxy sample at R<60' and identify 32 group candidates, and examine the spatial correlation between the galaxy groups and X-ray emission. This extensive survey in the central region of A2199 provides an important basis for future studies of interplay among the galaxies, the ICM, and the dark matter in the cluster.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.1
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• pp.46-53
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• 2010

A Compton X-ray backscatter technique has been developed to quantitatively assess impact damage in quasi-isotropic laminated composites made by a drop-weight tester. X-ray backscatter imaging system with a slit-type camera is constructed to obtain a cross-sectional profile of impact-damaged laminated composites from the electron-density variation of the cross section. A nonlinear scattering model based on Boltsman equation is introduced to compute Compton X-ray backscattering field for the defect assessment. An adaptive filter is also used to reduce noises from many sources including quantum noise and irregular distributions of fibers and matrix in composites. Delaminations masked or distorted by the first delamination are detected and characterized effectively by the Compton X-ray backscatter technique, both in width and location, by application of error minimization algorithm.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.3
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• pp.159-167
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• 2005

Quantization effects (QEs), which manifests when the device dimensions are comparable to the de Brogile wavelength, are becoming common physical phenomena in the present micro-/nanometer technology era. While most novel devices take advantage of QEs to achieve fast switching speed, miniature size and extremely small power consumption, the mainstream CMOS devices (with the exception of EEPROMs) are generally suffering in performance from these effects. In this paper, an analytical model accounting for the QEs and poly-depletion effects (PDEs) at the silicon (Si)/dielectric interface describing the capacitance-voltage (C-V) and current-voltage (I-V) characteristics of MOS devices with thin oxides is developed. It is also applicable to multi-layer gate-stack structures, since a general procedure is used for calculating the quantum inversion charge density. Using this inversion charge density, device characteristics are obtained. Also solutions for C-V can be quickly obtained without computational burden of solving over a physical grid. We conclude with comparison of the results obtained with our model and those obtained by self-consistent solution of the $Schr{\ddot{o}}dinger$ and Poisson equations and simulations reported previously in the literature. A good agreement was observed between them.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.673-681
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• 2004

As the use of digital videos is getting popular, there is an increasing demand for efficient browsing and retrieval of video. To support such operations, effective video indexing should be incorporated. One of the most fundamental steps in video indexing is to parse video stream into shots and scenes. Generally, it takes long time to parse a video due to the huge amount of computation in a traditional single computing environment. Previous studies had widely used Round Robin scheduling which basically allocates tasks to each slave for a time interval of one quantum. This scheduling is difficult to adapt in a heterogeneous environment. In this paper, we propose two different parallel parsing algorithms which are Size-Adaptive Round Robin and Dynamic Size-Adaptive Round Robin for the heterogeneous distributed computing environments. In order to show their performance, we perform several experiments and show some of the results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2137-2142
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• 2016

The electrical current generated by heart creates not only electric potential but also a magnetic field. In this study, the signals obtained magnetocardiogram(MCG) using 61 channel superconducting quantum interference device(SQUID) system, and the clinical significance of various feature parameters has been developed MCG. Neural network algorithm was used to perform the classification of ischemic heart disease. The MCG signal was obtained to facilitate the extraction of parameters through a process of pre-processing. The data used to research the normal group 10 and ischemic heart disease group 10 with visible signs of stable angina patients. The available clinical indicators were extracted by characteristic point, characteristic interval parameter, and amplitude ratio parameter. The extracted parameters are determined to analysis the significance and clinical parameters were defined. It is possible to classify ischemic heart disease using the MCG feature parameters as a neural network input.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.545-554
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• 2000

Compton X-ray backscatter technique has been used to quantitatively assess the impact damage in quasi-isotropic laminated composites and to obtain a cross-sectional profile of impact-damaged laminated composites from the density variation of the cross section. An adaptive filter is applied to the Compton backscattering data for the reconstruction and noise reduction from many sources including quantum noise, especially when the SNR(signal-to-noise ratio) of the image is relatively low. A nonlinear reconstruction model is also proposed to overcome distortion of the Compton backscatter image due to attenuation effects, beam hardening, and irregular distributions of the fibers and the matrix in composites. Delaminations masked or distorted by the first few delaminations near the front surface are detected and characterized both in width and location, by application of an error minimization algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.2
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• pp.11-21
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• 2009

The NTRU cryptosystem proposed by Hoffstein et al. in 1990s is a public key cryptosystem based on hard lattice problems. NTRU has many advantages compared to other public key cryptosystems such as RSA and elliptic curve cryptosystems. For example, it guarantees high speed encryption and decryption with the same level of security, and there is no known quantum computing algorithm for speeding up attacks against NTRD. In this paper, we analyze the security of NTRU against the simple power analysis (SPA) attack and the statistical power analysis (STPA) attack such as the correlation power analysis (CPA) attack First, we implement NTRU operations using NesC on a Telos mote, and we show how to apply CPA to recover a private key from collected power traces. We also suggest countermeasures against these attacks. In order to prevent SPA, we propose to use a nonzero value to initialize the array which will store the result of a convolution operation. On the other hand, in order to prevent STPA, we propose two techniques to randomize power traces related to the same input. The first one is random ordering of the computation sequences in a convolution operation and the other is data randomization in convolution operation.