• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.103-108
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• 2011

Recently reported asynchronous-optical-sampling terahertz (THz) time-domain spectroscopy enables high-resolution spectroscopy due to a long time-delay window. However, a long-lasting tail signal following the main pulse is often measured in a time-domain waveform, resulting in spectral fluctuation above a background noise level on a high-resolution THz amplitude spectrum. Here, we adopt the wavelet power spectrum estimation technique (WPSET) to effectively remove the spectral fluctuation without sacrificing spectral features. Effectiveness of the WPSET is verified by investigating a transmission spectrum of water vapor.

• Korean Journal of Computational Design and Engineering
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• v.7 no.2
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• pp.102-109
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• 2002

This paper presents a method for automatic generating of check sheet to measure deep-drawn sheet metal. By using polyhedral model of CAD, the proposed procedure calculates measuring points automatically. The results of measure are exported to MS-Excel. The proposed method is implemented by API functions and C language using SPEED plus CAD/CAM system and MS-Window OLE.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1041-1041
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• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.917-922
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• 2018

In the conventional interchannel interference self-cancellation (ICI-SC) schemes, the length of sampling window is the same as the symbol length of orthogonal frequency division multiplexing (OFDM). Thus, the number of complex operations to compute the interference coefficient of each subchannel is significantly increased. To solve this problem, we present an approximated mathematical model for the coefficients of ICI-SC schemes. Based on the proposed approximation, we analyze mean squared error (MSE) and computational complexity of the ICI-SC schemes with the length of sampling window. As a result, the presented approximation has an error of less than 0.01% on the MSE compared to the original equation. When the number of subchannels is 1024, the number of complex computations for the interference coefficients is reduced by 98% or more. Since the computational complexity can be remarkably reduced without sacrificing the self-cancellation capability, it is considered that the proposed approximation is very useful to develop an algorithm for the ICI-SC scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1051-1060
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• 2014

In this paper, performance of an orthogonal frequency division multiplexing (OFDM) system in an impulsive noise environment is analyzed. Here, it is verified that performance of the OFDM system with window nonlinearity, which is one of the impulsive noise mitigation algorithms, is dependent on the over-sampling rate and the size of window. With respect to the variation of those parameters, we also provide an appropriate region of threshold values that control amplitudes of the sampled waveform of received signals. As a result, a new combination of parameters which improves error performance of OFDM system in an impulsive noise environment as compared to the previously reported parameters is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.771-778
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• 2002

We investigate the design of an interpolation filter of a MF-TDMA demodulator which is applied to DVB-RCS. If sampling is not synchronized to the data symbols, timing adjustment in digital receiver must be performed by interpolation. It is impossible that conventional sinc interpolation filter coefficients are actually extended to infinity. We propose a Kaiser window interpolation filter and a sinc interpolation filter using th Kaiser window. Simulation results show that the performance improvement is realized by employing the proposed interpolation filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.1-18
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• 2014

Over the past years RFID/SN has been an elementary technology in a diversity of applications for the ubiquitous environments, especially for Internet of Things. However, one of obstacles for widespread deployment of RFID technology is the inherent unreliability of the RFID data streams by tag readers. In particular, the problem of false readings such as lost readings and mistaken readings needs to be treated by RFID middleware systems because false readings ultimately degrade the quality of application services due to the dirty data delivered by middleware systems. As a result, for the higher quality of services, an RFID middleware system is responsible for intelligently dealing with false readings for the delivery of clean data to the applications in accordance with the tag reading environment. One of popular techniques used to compensate false readings is a sliding window filter. In a sliding window scheme, it is evident that determining optimal window size intelligently is a nontrivial important task in RFID middleware systems in order to reduce false readings, especially in mobile environments. In this paper, for the purpose of reducing false readings by intelligent window adaption, we propose a new adaptive RFID data cleaning scheme based on window sliding for a single tag. Unlike previous works based on a binomial sampling model, we introduce the weight averaging. Our insight starts from the need to differentiate the past readings and the current readings, since the more recent readings may indicate the more accurate tag transitions. Owing to weight averaging, our scheme is expected to dynamically adapt the window size in an efficient manner even for non-homogeneous reading patterns in mobile environments. In addition, we analyze reading patterns in the window and effects of decreased window so that a more accurate and efficient decision on window adaption can be made. With our scheme, we can expect to obtain the ultimate goal that RFID middleware systems can provide applications with more clean data so that they can ensure high quality of intended services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2614-2632
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• 2015

A multiple symbol detection (MSD) algorithm is proposed relying on soft information for ultra-wideband systems, where differential space-time block code is employed. The proposed algorithm aims to calculate a posteriori probabilities (APP) of information symbols, where a forward and backward message passing mechanism is implemented based on the BCJR algorithm. Specifically, an MSD metric is analyzed and performed for serving the APP model. Furthermore, an autocorrelation sampling is employed to exploit signals dependencies among different symbols, where the observation window slides one symbol each time. With the aid of the bidirectional message passing mechanism and the proposed sampling approach, the proposed MSD algorithm achieves a better detection performance as compared with the existing MSD. In addition, when the proposed MSD is exploited in conjunction with channel decoding, an iterative soft-input soft-output MSD approach is obtained. Finally, simulations demonstrate that the proposed approaches improve detection performance significantly.

• Journal of Environmental Health Sciences
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• v.21 no.4
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• pp.56-62
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• 1995

Recently, the traffic noise around residences and schools has become a serious social problem with the increase of the amount of transportation. This study was performed to investigate the sound proof efficiency of windows for traffic noise. The results were as follows 1) The traffic noise in 19 sites among 22 sampling sites was higher value than 65 dB(A) being roadside environment standard level in the daytime when all windows were opened, while the noise in 22 sampling sites was transmitted below standard level when all windows were closed. 2) The transmission loss of sound level at single window and double windows were 10~25 dB(A) and 11~29 dB(A) respectively. 3) The transmission loss of sound level at sampled school with sound proof pannel was 7~8 dB (A), which was lower 2~7 dB(A) than the theoretical value of the influence assessment . 4) The construction cost of double windows was lower 28% even if include the cost of setting up air conditioner for the summer season and the power consuming cost for its operation than that of sound proof pannel for traffic noise. 5) The effect of transmission loss of windows was more influenced by airtight than materials of windows.