• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.7
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• pp.666-674
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• 2015

In this paper, we introduce an adaptive phase-comparison monopulse technique for angle estimation of two targets in the same antenna beam. The proposed method determines a more suitable technique(between conventional phase comparison monopulse technique and Zheng's method) based on interference between two targets in Fourier domain. Consequently, regardless of the interference, angles of each individual target can be accurately estimated by means of the proposed method. In simulations, we assumed that two point targets with same velocity are located in the same antenna beam, and the accuracy improvement of the proposed method is verified by using several simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7B
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• pp.706-718
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• 2002

In bluetooth system, there are two kinds of interference. One is the frequency static interference, for example 802.11 direct sequence, the interferer uses fixed frequency band. Another is frequency dynamic interference, for example other piconets or 802.11 frequency hopping, the interferer uses dynamic frequency channel and cant be estimated. In this paper we introduce a novel solution of hybrid method of Listen-Before-Talk (LBT) and Adaptive Frequency Hopping (AFH) to address the coexistence of bluetooth and Direct Sequence of wireless local area network (WLAN). Before any bluetooth packet transmission, in the turn around time of the current slot, both the sender and receiver sense the channel whether there is any transmission going on or not. If the channel is busy, packet transmission is withdrawn until another chance. This is the LBT in Bluetooth. Because of asymmetry sense ability of WLAN and bluetooth, AFH is introduced to combat the left front-edge packet collisions. In monitor period of AFH, LBT is performed to label the channels with static interference. Then, all the labeled noisy channels are not used in the followed bluetooth frequency hopping. In this way, both the frequency dynamic and frequency static interference are effectively mitigated. We evaluate the solution through packet collision analysis and a detail realistic simulation with IP traffic. It turns out that the hybrid method can combat both the frequency dynamic and frequency static interference. The packet collision analysis shows it almost doubles the maximal system aggregate throughput. The realistic simulation shows it has the least packet loss.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2044-2062
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• 2018

Information theory progression along with the advancements being made in the field of Vehicular Ad hoc NETworks (VANETs) supports the use of coding-aware opportunistic routing for efficient data forwarding. In this work, we propose and investigate an adaptive coding-aware routing scheme in a specific VANET scenario known as a vehicular platoon. Availability of coding opportunities may vary with time and therefore, the accurate identification of available coding opportunities at a specific time is a quite challenging task in the highly dynamic scenario of VANETs. In the proposed approach, while estimating the topology of the network at any time instance, a forwarding vehicle contemplates the composition of multiple unicast data flows to encode the correct data packets that can be decoded successfully at destinations. The results obtained by using OMNeT++ simulator reveal that higher throughput can be achieved with minimum possible packet transmissions through the proposed adaptive coding-aware routing approach. In addition, the proposed adaptive scheme outperforms static transmissions of the encoded packets in terms of coding gain, transmission percentage, and encoded packet transmission. To the best of our knowledge, the use of coding-aware opportunistic routing has not been exploited extensively in available literature with reference to its implications in VANETs.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.818-827
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• 2008

In this paper, we propose a new noise estimation and reduction algorithm for stationary and nonstationary noisy environments. This approach uses an algorithm that classifies the speech and noise signal contributions in time-frequency bins. It relies on the ratio of the normalized standard deviation of the noisy power spectrum in time-frequency bins to its average. If the ratio is greater than an adaptive estimator, speech is considered to be present. The propose method uses an auto control parameter for an adaptive estimator to work well in highly nonstationary noisy environments. The auto control parameter is controlled by a linear function using a posteriori signal to noise ratio(SNR) according to the increase or the decrease of the noise level. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of much more simplicity and light computational load for estimating the stationary and nonstationary noise environments. The proposed algorithm is superior to conventional methods. To evaluate the algorithm's performance, we test it using the NOIZEUS database, and use the segment signal-to-noise ratio(SNR) and ITU-T P.835 as evaluation criteria.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.9-15
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• 2001

This paper describes a new method of Genetic Algorithms for Adaptive Fuzzy Control System. Previous works using a Multi-population Genetic Algorithm have divided chromosome into two components, rule sets and membership functions. However, in this case bad rule sets disturb optimization in good rule sets and membership functions. A new method for a Multi population Genetic Algorithm suggests three components, good rule sets, bad rule sets, and membership functions. To show the effectiveness of this method, fuzzy controller is applied to a Truck Backing Problem. Results of the computer simulation show good adaptation of the proposed method.

• Steel and Composite Structures
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• v.21 no.3
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• pp.679-688
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• 2016

Structural design of a composite beam is influenced by two main factors, strength and ductility. For the design to be effective for a composite beam, say an RC slab and a steel I beam, the shear strength of the composite beam and ductility have to carefully estimate with the help of displacements between the two members. In this investigation the shear strengths of steel-concrete composite beams was analyzed based on the respective variable parameters. The methodology used by ANFIS (Adaptive Neuro Fuzzy Inference System) has been adopted for this purpose. The detection of the predominant factors affecting the shear strength steel-concrete composite beam was achieved by use of ANFIS process for variable selection. The results show that concrete compression strength has the highest influence on the shear strength capacity of composite beam.

• ETRI Journal
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• v.34 no.2
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• pp.190-198
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• 2012

An adaptive correlation noise model (CNM) construction algorithm is proposed in this paper to increase the efficiency of parity bits for correcting errors of the side information in transform domain Wyner-Ziv (WZ) video coding. The proposed algorithm introduces two techniques to improve the accuracy of the CNM. First, it calculates the mean of direct current (DC) coefficients of the original WZ frame at the encoder and uses it to assist the decoder to calculate the CNM parameters. Second, by considering the statistical property of the transform domain correlation noise and the motion characteristic of the frame, the algorithm adaptively models the DC coefficients of the correlation noise with the Gaussian distribution for the low motion frames and the Laplacian distribution for the high motion frames, respectively. With these techniques, the proposed algorithm is able to make a more accurate approximation to the real distribution of the correlation noise at the expense of a very slight increment to the coding complexity. The simulation results show that the proposed algorithm can improve the average peak signal-to-noise ratio of the decoded WZ frames by 0.5 dB to 1.5 dB.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.813-821
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• 2000

In this paper, we developed modeling of tension and speed dynamics for a two-drum winder in a three span continuous web transport system which had not been previously. Dynamic modeling of the time-varying nonlinear system was derived by considering the effect of the radii and mass moment of inertia in the unwinder and the two-drum winder through winding up the web. After linearizing it, we designed with a variable-gain a PID controller for tension control and a PI controller for speed. Simulation is carried out with the variation of radii and moment of inertia at high speed for the proposed tension control system with the two-drum winder and the variavle-gain a PID controller. Results show good performance of tension control during the speed change speed at a start-up and stop.

• Smart Structures and Systems
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• v.15 no.1
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• pp.169-189
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• 2015

Convergence difficulty and available complete measurement information have been considered as two primary challenges for the identification of large-scale engineering structures. In this paper, a time domain substructural identification approach by combining a weighted adaptive iteration (WAI) algorithm and an extended Kalman filter method with a weighted global iteration (EFK-WGI) algorithm was proposed for simultaneous identification of physical parameters of concerned substructures and unknown external excitations applied on it with limited response measurements. In the proposed approach, according to the location of the unknown dynamic loadings and the partially available structural response measurements, part of structural parameters of the concerned substructure and the unknown loadings were first identified with the WAI approach. The remaining physical parameters of the concerned substructure were then determined by EFK-WGI basing on the previously identified loadings and substructural parameters. The efficiency and accuracy of the proposed approach was demonstrated via a 20-story shear building structure and 23 degrees of freedom (DOFs) planar truss model with unknown external excitation and limited observations. Results show that the proposed approach is capable of satisfactorily identifying both the substructural parameters and unknown loading within limited iterations when both the excitation and dynamic response are partially unknown.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.233-245
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• 2008

In this work, a new adaptive weighted mean filter is proposed for preserving image details while effectively suppressing impulse noise. The proposed filter is based on a noise pixel detection-estimation strategy. All the pixels are first detected using an impulse noise detector. Then the detected noise pixels are replaced with the output of the weighted mean filter over adaptive working window according to the rate of corrupted neighborhood pixels, while noise-free pixels are left unaltered. We compare the proposed filter to other existing filters in the qualitative measure and quantitative measures such as PSNR and MAE as well as computation time to verify the capability of the proposed filter. Extensive simulations show that the proposed filter performs better than other filters in impulse noise suppression and detail preservation without increasing of running time.