• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.13-18
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• 2019

This paper analyzes the signal acquisition performance of the legacy GNSS spreading codes and a polyphase code. The code length and chip rate of a polyphase code are assumed to be same as those of the GPS L1 C/A and Galileo E1C codes. The autocorrelation and cross correlation characteristics are analyzed. In addition, a way to calculate a more accurate probability of false alarm for a code with sidelobe non-zero auto-correlation function is proposed. Finally, we estimate the probability of detection and the mean acquisition time for a given signal strength and the probability of false alarm.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1431-1436
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• 2018

We study the scaling of the price fluctuation in the Korean housing market. From the numerical analysis, we show that the normalized return distribution of the housing price, P(r), has a fat-tail and is well approximated by a power-law, $P(r){\sim}r^{-({\alpha}+1)}$, with ${\alpha}{\simeq}3$ for the whole data set. However, if we divide the data into groups based on the trading patterns, then the value of ${\alpha}$ for positive tail and negative tail can be different depending on the trading patterns. We also find that the autocorrelation function of the housing price decays much slower than that of the stock exchange markets, which shows a unique feature of the housing market distinguished from the other financial systems.

• Journal of KIISE:Information Networking
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• v.29 no.5
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• pp.553-561
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• 2002

We present a novel service discipline, called linear service discipline, to serve multiple QoS queues sharing a resource and analyze its properties. The linear server makes the output traffic and the queueing dynamics of individual queues as a linear function of its input traffic. In particular, if input traffic is Gaussian, the distributions of queue length and output traffic are also Gaussian with their mean and variance being a function of input mean and input power spectrum (equivalently, autocorrelation function of input). Important QoS measures including buffer overflow probability and queueing delay distribution are also expressed as a function of input mean and input power spectrum. This study explores a new direction for network-wide traffic management based on linear system theories by letting us view the queueing process at each node as a linear filter.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.194-200
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• 2012

In this paper we analyze the code sequence generating algorism defined on $GF(2^n)$ proposed by S.Bostas and V.Kumar[7] and derive the implementation functions of code sequence generator using Boolean functions which can map the vector space $F_2^n$ of all binary vectors of length n, to the finite field with two elements $F_2$. We find the code sequence generating boolean functions based on two kinds of the primitive polynomials of degree, n=5 and n=7 from trace function. We then design and implement the code sequence generators using these functions, and produce two code sequence groups. The two groups have the period 31 and 127 and the magnitudes of out of phase(${\tau}{\neq}0$) autocorrelation and crosscorrelation functions {-9, -1, 7} and {-17, -1, 15}, satisfying the period $L=2^n-1$ and the correlation functions $R_{ij}({\tau})=\{-2^{(n+1)/2}-1,-1,2^{(n+l)/2}-1\}$ respectively. Through these results, we confirm that the code sequence generators using boolean functions are designed and implemented correctly.

• Journal of Distribution Science
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• v.12 no.2
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• Journal of radiological science and technology
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• v.32 no.1
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• pp.17-24
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• 2009

Noise evaluation for an image has been performed by root mean square (RMS) granularity, autocorrelation function (ACF), and Wiener spectrum. RMS granularity stands for standard deviation of photon data and ACF is acquired by integration of 1 D function of distance variation. Fourier transform of ACF results in noise power spectrum which is called Wiener spectrum in image quality evaluation. Wiener spectrum represents noise itself. In addition, along with MTF, it is an important factor to produce detective quantum efficiency (DQE). The proposed evaluation method using Wiener spectrum is expected to contribute to educate the concept of Wiener spectrum in educational organizations, choose the appropriate imaging detectors for clinical applications, and maintain image quality in digital imaging systems.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.44-50
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• 2007

In this paper generating algorithms of the conventional chaos code sequences and a new chaos code sequence derived from the real and imaginary parts of FFT of one chaos code sequence, and the time-frequency function characteristics of generated code sequences to measure the signal resolution, are considered. And two chaos based QCSK digital communication systems-one with two different chaos code sequences, the other with FFT of one chaos code sequence-are analyzed in AWGN and fading communication channels. After analyzing the correlation functions of such sequences, the delta-like autocorrelation and near zero crosscorrelation functions of them are very suitable for chaos based spread spectrum communication systems, is verified. Through evaluating the performance of two chaos based QCSK systems above using Monte-Carlo simulation, the improvement of performance in the latter QCSK system compare favorably with that of the former system, is shown.

• Fire Science and Engineering
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• v.28 no.2
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• pp.69-75
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• 2014

This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.187-192
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• 2015

Underwater acoustic communication channels have very complex channel characteristics caused by time-varying sea surface, submarine topography, sound speed, and geometry between transmitter and receiver. Especially, the channel has time-variance and doppler effect due to wind and sea current. We have to recognize the channel state and apply it to communication technique for increasing transmission efficiency in the underwater acoustic channel. In this paper, we present the frame recursive modulation and demodulation method using ambiguity function and autocorrelation function to estimate the doppler frequency. Furthermore, we conducted the simulation and sea experiment to evaluate the performance of the proposed method. When the channel coding technique was not used, the bit error rate performance of the proposed method was improved about 32 % compared with conventional method.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.143-151
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• 2020

The digital content's security and authentication are important in the field of digital content application. There are some methods to perform the authentication. The digital watermarking is one of authentication methods. Paper presents a digital watermark authentication method that works in the application of digital image. The proposed watermark has the triple status information and performs the embedding and the detection without original Content. When authenticating the owner information of digital content, an autocorrelation function is used. In addition, a spread spectrum method is used to be adaptive to the signal of the original content in the frequency domain(DWT Domain). Therefore, the possibility of errors occurring in the detection of hidden information was reduced. it also has a advantage what Watermarking in DWT has faster embedding and detection time than other transformation domains(DFT, DCT, etc.). if it has a an image of size N=mXm, the computational amount can be reduced from O(N·logN) to O(N). The particular advantage is that it can hide more information(bits) per bit.