• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.433-442
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• 2005

An increase In traffic has a large Influence on the performance of a total network. Therefore, traffic management has become an important issue of network management. In this paper, we propose a new routing algorithm that attempts to analyze network conditions using time series prediction models and to propose predictive optimal routing decisions. Traffic congestion is assumed when the predicting result is bigger than the permitted bandwidth. By collecting traffic in real network, the predictable model is obtained when it minimizes statistical errors. In order to predict network traffic based on time series models, we assume that models satisfy a stationary assumption. The stationary assumption can be evaluated by using ACF(Auto Correlation Function) and PACF(Partial Auto Correlation Function). We can obtain the result of these two functions when it satisfies the stationary assumption. We modify routing oaths by predicting traffic in order to avoid traffic congestion through experiments. As a result, Predicting traffic and balancing load by modifying paths allows us to avoid path congestion and increase network performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.123-129
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• 2015

The Kalman filter has been widely used in the kinematic GPS positioning due to its flexibility and efficiency in computational points of view. At the same time, the relative positioning technique also provided the high precision positioning results by removing the systematic errors in the measurements significantly. However, the positioning quality may be degraded following to longer in baseline length. For this case, it is required that the remaining atmospheric effects, such as double-difference ionospheric delay and zenith wet delay, should be properly modeled by examining the characteristics of the stochastic processes. In general, atmospheric effects are estimated with the assumption of random walk, or the first-order Gauss-Markov stochastic process, which requires the precise modeling on the corresponding process noises. Therefore, we determined and provided the parameters for modelling the process noises for atmospheric effects. The auto-correlation functions are empirically determined at first, and then the parameters are extracted from the empirical auto-correlation function. In fact, the test results can be either applied directly, or used as guidance values for the modeling of process noises in the kinematic GPS positioning.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.49-60
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• 1995

This paper is a study on the design and implementation of the Korean Text-to-Speech system which is used for a small and simple system. In this paper, a parameter synthesis method is chosen for speech syntheiss method, we use PARCOR(PARtial autoCORrelation) coefficient which is one of the LPC analysis. And we use phoneme for synthesis unit which is the basic unit for speech synthesis. We use PARCOR, pitch, amplitude as synthesis parameter of voice, we use residual signal, PARCOR coefficients as synthesis parameter of unvoice. In this paper, we could obtain the 60% intelligibility by using the residual signal as excitation signal of unvoiced sound. The result of synthesis experiment, synthesis of a word unit is available. The controlling of phoneme duration is necessary for synthesizing of a sentence unit. For setting up the synthesis system, PC 486, a 70[Hz]-4.5[KHz] band pass filter for speech input/output, amplifier, and TMS320C30 DSP board was used.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.837-848
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• 2012

This study has conducted the economic effects of R&D investment in the IT industry using multi-regression analysis with three independent variables; capital stock, labor input and R&D stock. In this study, the IT industry has been categorized into three sub-industries; broadcasting communication appliances, information appliances and electronic components industry. Our analysis has found that auto-correlation shows considerable levels whereas figures of t-value and R-square show significant levels among all the IT sub-industries. Meanwhile, the values of R&D stock in the information appliances industry and that of labor input coefficients in the electronic components industry were minus, thus multi-collinearity was suspected. We have solved the problems regarding auto-correlation and multi-collinearity through Cochrane-Orcutt estimation and principal components analysis. This paper has derived the implications that R&D investment in the broadcasting communication industry is much more influential than any other IT sub-industry.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1124-1131
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• 2008

In this paper, we propose a timing synchronization scheme and its hardware architecture of the next generation IEEE 802.11n wireless LAN standard which is based on MIMO-OFDM technique. Proposed timing synchronization method takes two steps which consist of two modified auto-correlators. For coarse timing synchronization, a sliding window differentiator is used after a conventional auto-correlation in order to avoid plateau problem. The conjugate symmetry property of L-LTS is utilized for the simplification of fine timing synchronization. Since cross-correlation based methods are not required, the computational complexity and the number of multipliers can be reduced. In order to reduce the hardware complexity, we have used sign multipliers. Based on simulation results, the proposed method outperforms a conventional method. The proposed scheme can be applied to IEEE 802.11n systems and can easily be expanded to frequency synchronization scheme.

• Water for future
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• v.26 no.3
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• pp.113-124
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• 1993

This study aims at the evaluation of the stationary distribution and the emptiness passage time for the effectiveness of water utility in the Keumgang estuary reservoir by two-step transition model. It was taken discrete Markovian correlated inflows for the joint probability of inflows and storage, and was used binomial distribution for inflows distribution. As the results, it was decreased from 0.952 to 0.904 the emptiness probability of the reservoir stationary distribution during 1952-1980, and from 0.900 to 0.829 during 1981-1989, and the average emptiness passage time was increased from 23 days to 37 days during 1952-1980, and from 29 days to 61 days during 1981-1989 at low state of storage. From this, it is found that the emptiness passage time is varied with the increase of the inflows auto-correlation coefficient in the Keumgang estuary reservoir. Therefore, it is understood that auto-correlation coefficient must be taken into consideration for the evaluation of water utility in a small reservoir at drought time.

• Journal of Environmental Policy
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• v.7 no.1
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• pp.101-118
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• 2008

In this study, we estimate the labor demand function of environmental industry with environmental industry survey of Ministry of Environment. To do this, we apply the panel estimation technique. We follow the widely accepted estimation methods: panel generalized least square, panel generalized least square with heteroskedasticity/auto-correlation, random effect model and random effect model with auto-correlation. On the average, each industry is estimated at the elasticity of sales on labor demand from 0.193 to 0.259. It means that the increase of sales by 214billion won can create around $1,600{\sim}2,300$ jobs, and this is merely a direct effect. So when we consider the whole effect of labor demand increase including indirect derived job creation, the labor demand increase will be higher than this. So it is desirable for the government to support the development of environmental industry for sustainable development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.224-229
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• 1999

In the field of speech recognition, the research area can be classified into the following two categories: one which is concerned with the development of phoneme-level recognition system, the other with the efficiency of word-level recognition system. The resonable phoneme-level recognition system should detect the phonemic boundaries appropriately and have the improved recognition abilities all the more. The traditional LPC methods detect the phoneme boundaries using Itakura-Saito method which measures the distance between LPC of the standard phoneme data and that of the target speech frame. The MFCC methods which treat spectral transitions as the phonemic boundaries show the lack of adaptability. In this paper, we present new speech recognition system which uses auto-correlation method in the phonemic boundary detection process and the multi-layered Feed-Forward neural network in the recognition process respectively. The proposed system outperforms the traditional methods in the sense of adaptability and another advantage of the proposed system is that feature-extraction part is independent of the recognition process. The results show that frame-unit phonemic recognition system should be possibly implemented.

• Journal of Soil and Groundwater Environment
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• v.7 no.1
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• pp.3-14
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• 2002

We analyzed hydrologic time-series data obtained from a fractured aquifer in Wonju and a porous shallow aquifer in Uiwang area. Auto-correlation, spectral density, and cross-correlation functions were used for the analyses. Water level at a shallow well in Wonju was weakly auto-correlated and it was sensitive to direct infiltration from rainfall through soil zone while that at a well screened in the fractured zone showed a relative stability to an outer stress (rainfall), which was derived from a delayed transmission of recharge stress through a fracture network from a remote area. Characteristics of time-series data in Uiwang area were similar to those in the fractured zone in Wonju. This was caused by a regional recharge from a distant area rather than a direct infiltration. This study demonstrated a usefulness of time series analyses for identification of recharge mechanism.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.1
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• pp.165-174
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• 2010

In this paper, a two-phase structural health monitoring system using acceleration response signatures are presented to firstly alarm the change in structural condition and to secondly detect the changed location for full-scale concrete girder bridges. Firstly, Mihocheon Bridge which is a two-span continuous concrete girder bridge is selected as the target structure. The dynamic response features of Mihocheon Bridge are extracted by forced vibration test using bowling ball. Secondly, the damage alarming occurrence and the damage localization techniques are selected to design two-phase structural health monitoring system for Mihocheon Bridge. As the damage alarming techniques, auto-regressive model using time-domain signatures, correlation coefficient of frequency response function and frequency response ratio assurance criterion are selected. As the damage localization technique, modal strain energy-based damage index method is selected. Finally, the feasibility of two-phase structural health monitoring systems is evaluated from static loading tests using a dump truck.