• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1063-1075
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• 2012

To locate an object accurately in the wireless sensor networks, the distance measure based on time-delay plays an important role. In this paper, we propose a maximum likelihood (ML) time-delay estimation algorithm in multi-path wireless propagation channel. We get the joint probability density function after sampling the frequency domain response of the multi-path channel, which could be obtained by the vector network analyzer. Based on the ML criterion, the time-delay values of different paths are estimated. Considering the ML function is non-linear with respect to the multi-path time-delays, we first obtain the coarse values of different paths using the subspace fitting algorithm, then take them as an initial point, and finally get the ML time-delay estimation values with the pattern searching optimization method. The simulation results show that although the ML estimation variance could not reach the Cramer-Rao lower bounds (CRLB), its performance is superior to that of subspace fitting algorithm, and could be seen as a fine algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.963-969
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• 2000

In this paper, we define two input-output gains of linear periodic time-varying systems. One is the ratio of output with worst-case l2-norm over all inputs with unit 12-norm. It denotes G($\iota_2,\iota_2$.The other is the ratio of output with worst-case RMS value over all inputs with unit RMS value. It denotes G(RMS, RMS) .It is fact that these two gains are equivalent for linear time-invariant system. In this paper, we prove these two gains are also equivalent for linear periodic time-varying system. In addition, the relationship between two method of obtaining the generalized frequency responses for linear periodic time-varying system is derived. Finally, we apply the defined input-output gains to M-channel filter-bank which is multi-rate signal Processing system, used to speech coding. In the filter-bank, generally, aliasing distortion, magnitude distortion, and phase distortion are present. It is shown that these are kept small if the filter-bank is designed by a method that optimizes the gain G($\iota_2,\iota_2$ of an error system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.106-113
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• 2022

The structural safety of the basic design model of the linear actuator for the individual blade pitch control of eVTOL personal aircraft was investigated. Stress analysis based on the finite element method was conducted, and the margin of safety was calculated to examine the structural safety under stall load conditions. Additionally, fatigue analysis was conducted to evaluate the fatigue life of the linear actuators under operating conditions. The load history with the blade pitch angle was calculated using multi-body dynamics analysis, and the static load analysis was used to obtain the stress distribution for the rated load. As a result, it was confirmed that the safety margins exceeded zero, and the fatigue lives of all linear actuator components exceeded 107 cycles, indicating a safe structural range.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.437-445
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• 1999

This paper presents a simple modification technique of finite element model for dynamic analysis of linear/nonlinear structural system subjected to multiple support excitation. For the sake of verification of the proposed method, dynamic responses obtained by the present technique for a couple of linear and nonlinear structural systems were compared with those by a general-purpose structural analysis software which can deal with the multi-support analysis. The method presented in this paper is expected to be used for multiple support excitation analysis by means of a computer code without the capability of modeling the non-synchronous support motion.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.1
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• pp.15-22
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• 2015

Estimating the number of distinct values is really well-known problems in network data measurement and many effective algorithms are suggested. Recent works have built upon technique called Linear Counting to solve the estimation problem for massive sets or spreaders in small memory. Sampling is used to reduce the measurement data, and it is assumed that sampling gives bad effect on the accuracy. In this paper, however, we show that the sampling on multi-set estimation sometimes gives better results for CSE with sampling than for MCSE that examines all the packets without sampling in terms of accuracy and estimation range. To prove this, we presented mathematical analysis, conducted experiment with real data, and compared the results of CSE, MCSE, and CSES.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.488-496
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• 2012

In this paper, the scheme for designing optimal beamforming matrix for interference control is proposed. The optimal beamforming matrix is found though linear combination of interference alignment conditions and renewal of linear combination coefficient. The proposed scheme has advantages that the complexity is reduced and there is no multiplying operation in matrix calculations even if proposed scheme has the form similar to that of existing least square based scheme. The simulation results show that proposed scheme has about 4bps/Hz higher gain than existing least square scheme. Also there is no additional multiplying calculation and increase of matrix size when the number of transmit and receive antennas is increased.

• The KIPS Transactions:PartC
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• v.19C no.4
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• pp.247-252
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• 2012

Network coding has been shown to improve various performance metrics in network systems. However, if network coding is implemented as software a huge time delay may be incurred at encoding/decoding stage so it is imperative for network coding to be parallelized to reduce time delay when encoding/decoding. In this paper, we compare the performance of parallelized decoders for random linear network coding (RLC) and pipeline network coding (PNC), a recent development in order to alleviate problems of RLC. We also compare multi-threaded algorithms on multi-core CPUs and massively parallelized algorithms on GPGPU for PNC/RLC.