• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4483-4501
• /
• 2015

In this paper, we investigate a security transmission scheme at the physical layer for cooperative wireless relay networks in the presence of a passive eavesdropper. While the security scheme has been previously investigated with perfect channel state information(CSI) in the presence of a passive eavesdropper, this paper focuses on researching the robust cooperative relay beamforming mechanism for wireless relay networks which makes use of artificial noise (AN) to confuse the eavesdropper and increase its uncertainty about the source message. The transmit power used for AN is maximized to degrade the signal-to-interference-plus-noise-ratio (SINR) level at the eavesdropper, while satisfying the individual power constraint of each relay node and worst-case SINR constraint at the desired receiver under a bounded spherical region for the norm of the CSI error vector from the relays to the destination. Cooperative beamforming weight vector in the security scheme can be obtained by using S-Procedure and rank relaxation techniques. The benefit of the proposed scheme is showed in simulation results.

• ETRI Journal
• /
• v.38 no.1
• /
• pp.70-80
• /
• 2016

This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.689-694
• /
• 2004

To increase accurateness and reliability of the evaluation of power tool vibration transmitted to an operator, it is necessary to measure grip and feed forces during the measurement of hand-transmitted vibration. In the study a system was invented to measure the vibration and the grip and/or feed force, which consists of a measurement handle and a PC with data acquisition system and the software. Strain gauges and an accelerometer were mounted on the handle for the simultaneous measurement of the forces and the vibration. The program in the system makes it possible to monitor the grip and feed force during the tool operation so that the operator keeps the applying forces within the pre-determined range. Investigating the vibration total values, frequency-weighted root mean square accelerations at the handle, obtained at various conditions with control of the grip and feed force showed more consistency than those measured without force control. By using the system the experimenter can reduce uncertainty of the measured vibration.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.20 no.10
• /
• pp.976-982
• /
• 2010

This paper proposes a novel type of pressure control mechanism which can apply to vehicle ABS (anti-lock braking system) utilizing the piezoactuator based valve system associated with the pressure modulator. As a first step, a flapper-nozzle of a pneumatic valve system is devised by integrating the piezoacuator to the flexible beam structure. The dynamic modeling of the valve system is then undertaken and subsequently the governing equation of pressure control is derived considering the pressure modulator. A sliding mode controller is designed in order to achieve accurate pressure tracking control in the presence of actuator uncertainty as well as input pressure variation. It is shown through computer simulation that an accurate pressure tracking for sinusoidal motion whose magnitude is 40 bar is achieved by utilizing the proposed pressure control mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.6
• /
• pp.3121-3143
• /
• 2019

Segmentation plays an important role in the field of image processing and computer vision. Intuitionistic fuzzy C-means (IFCM) clustering algorithm emerged as an effective technique for image segmentation in recent years. However, standard fuzzy C-means (FCM) and IFCM algorithms are sensitive to noise and initial cluster centers, and they ignore the spatial relationship of pixels. In view of these shortcomings, an improved algorithm based on IFCM is proposed in this paper. Firstly, we propose a modified non-membership function to generate intuitionistic fuzzy set and a method of determining initial clustering centers based on grayscale features, they highlight the effect of uncertainty in intuitionistic fuzzy set and improve the robustness to noise. Secondly, an improved nonlinear kernel function is proposed to map data into kernel space to measure the distance between data and the cluster centers more accurately. Thirdly, the local spatial-gray information measure is introduced, which considers membership degree, gray features and spatial position information at the same time. Finally, we propose a new measure of intuitionistic fuzzy entropy, it takes into account fuzziness and intuition of intuitionistic fuzzy set. The experimental results show that compared with other IFCM based algorithms, the proposed algorithm has better segmentation and clustering performance.

• Structural Monitoring and Maintenance
• /
• v.8 no.4
• /
• pp.379-402
• /
• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1603-1623
• /
• 2020

Multiple Mobile Robots System (MMRS) has shown many attractive features in lots of real-world applications that motivate their rapid and wide diffusion. In MMRS, the Cooperative Localization (CL) is the basis and premise of its high-performance task. However, the statistical characteristics of the system noise should be already known in traditional CL algorithms, which is difficult to satisfy in actual MMRS because of the numerous of disturbances form the complex external environment. So the CL accuracy will be reduced. To solve this problem, an improved Adaptive Active Cooperative Localization (A²CL) algorithm based on information optimization strategy for MMRS is proposed in this manuscript. In this manuscript, an adaptive information fusion algorithm based on the variance component estimation under Extended Kalman filter (VCEKF) method for MMRS is introduced firstly to enhance the robustness and accuracy of information fusion by estimating the covariance matrix of the system noise or observation noise in real time. Besides, to decrease the effect of observation uncertainty on CL accuracy further, an observation optimization strategy based on information theory, the Model Predictive Control (MPC) strategy, is used here to maximize the information amount from observations. And semi-physical simulation experiments were carried out to verity the A²CL algorithm's performance finally. Results proved that the presented A²CL algorithm based on information optimization strategy for MMRS cannot only enhance the CL accuracy effectively but also have good robustness.

• Structural Engineering and Mechanics
• /
• v.75 no.4
• /
• pp.519-527
• /
• 2020

Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system's dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system's dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system's dynamic responses with fuzzy variables.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2010.05a
• /
• pp.43-43
• /
• 2010

Presently, there is the dilemma of uncertainty with respect to the evaluation of sound and vibration based on the fact that there is obviously no agreement upon appropriate methods to measure the "truth" concerning the acceptance of sound and vibration. To evaluate properly physical and perception data in sound and vibration it is necessary to implement new methods and innovative approaches to understand the input of human response in sound design. Fortunately, an elaborate dialogue of the usefulness and applicability of those approaches is in progress. Moreover, the need of using and combining perception and physical data in order to comprehend the process of human perception and evaluation sufficiently is widely accepted. However, still the question remains how the goal of an adequate combination can be achieved. Clearly, themultidimensional human perception cannot be easily reduced to singular numbers. Moreover, factors, among others the meaning of the sound, the composition of the diverse sound sources, the listener's attitude, expectations and experiences, are significant parameters which have to be considered to comprehend the different perceptions and evaluations with regard to specific stimuli. Taking under consideration the physical, psychological, and cognitive dimensions as well as the integration of aspects of design require partially various new approaches. While binaural measurement and analysis technologies and psycho-acoustics are well established as they are proved to be valuable auxiliary tools; it has not been achieved to develop generally acceptable measurement units concerning sound quality. Consequently, there is a need for new approaches and methods which make it possible to comprehend sufficiently the process of perception and evaluation. Going with people's mind will be one solution for the future; thisconcept will be introduced based on the development in sound design.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.9C
• /
• pp.922-927
• /
• 2009

Utilization problem of the limited spectrum is the one of the most important issues in wireless communication systems. Cognitive radio technique which is finding and utilizing frequency holes is also one of those techniques. Specially, the spectrum sensing technique to detect the primary user signal is a core technology in cognitive radio area. In this paper, we propose the spectrum sensing algorithm using Bussgang theorem. The proposed algorithm calculates the statistical difference between the Gaussian noise and the primary user signal by applying Bussgang theorem to the received signal. The algorithm is not affected by noise uncertainty and can detect the primary user signal in the very low SNR environment. We evaluate the algorithm through computer simulations with 12 ATSC A/74 DTV signal captures based on IEEE 802.22 WRAN and formulate the sensing threshold for the proposed scheme.