Applied Mechanics and Materials Vols. 128-129

Abstract: In order to study the performance of Sasobit warm mix asphalt and the influence of aging, complex shear modulus G* and phase angle δ of Sasobit warm mix asphalt are tested by Dynamic Shear Rheometer （DSR） at different aging phase, to analyze the effects of Sasobit to the performance and the aging of 70^# and SBS asphalt. The results show that with the increasing of the dosage of Sasobit, the value of G*/sinδ can be increased at different aging phase, the change in the phase angle has the same trend; the degree of Long-term aging of warm-matrix asphalt is larger than modified asphalt's. This may be related to the interaction of Sasobit and modifier.

Abstract: Using the Dynamic Shear Rheometer (DSR) to do the dynamic viscoelastic properties test for asphalt mortar which added Sasobit, to analyze the G*/sinδ trends of asphalt mortar and warm mix asphalt mortar, then to get the high temperature stability of warm mix asphalt mortar. The results indicate that following the increasing of filler-bitumen ratio the G*/sinδ value of warm asphalt mortar is decreased when the temperature is the same; The G*/sinδ value of asphalt mortar with Sasobit than not, show that Sasobit can be increased the high temperature stability of asphalt mortar.

Abstract: A new method for workpiece surface roughness measuring system based on machine vision technology was designed. A Charge-coupled Device （CCD） camera was used to take workpiece surface image. Then median filtering, image enhancement and image binarization techniques were used for image preprocessing. And then useful information was extracted from image characteristic parameters. The surface roughness of cutting workpiece was calculated out. Researching emphasis was focused on the hardware design and software programming of the main two parts, image acquisition module and image processing module. This measuring system was used to measure cutting workpiece surface roughness, and perform very well.

Abstract: Wireless sensor networks (WSNs) are vulnerable to a variety of malicious attacks, especially the packet dropping attack, making security an important research field. Since prevention based techniques are less helpful for guarding against inside attacks, intrusion detection (ID) techniques are indispensable to provide advanced protection. This paper proposes an innovative cellular ID framework for packet dropping attack, which takes the deployment of passive listening nodes into consideration. Performance evaluation made in VisualSense demonstrates its high detection accuracy.

Abstract: ion: In gas difference absorption detecting system, the output electric signal is very faint and submerged in the background noise. In order to extract the faint signal covered by the background noise, we design the detective circuit aiming at how to restrain the noise and improve SNR of the system. In this paper, the detection circuit centering lock-in amplifier which reference signal frequency is automaticly followed is designed. The circuit adopts synchronization cumulating and locked loop technic, carries out frequency and phase aotomatic follow to the measuring signal by a locked loop circuit. The circuit not only avoids the tache taking reference signai from the modulator then adjusting the phase shif, but also improving signal-to-noise ratio more by synchronization cumulation.

Abstract: Adaptive notch filters (ANF) are known have non-absolute convergence problems which will lead to precision reduction in long-playing frequency tracking. In this paper, we propose an improved ANF based on Steiglitz-McBride method (SMM) for Coriolis mass flowmeter (CMF) whose frequency, amplitude and phase are time-varying based on the random walk model. An monitor is designed to monitor whether the frequency is estimated rightly or the ANF just filters noise. If the frequency of CMF’s signal is missed, we will modify the parameters and restart the ANF to resume the search for the correct frequency again. The particular algorithm of the improved ANF is also put forward. Simulations have verified the effectiveness of the presented method in tracking CMF’s frequency, which shows superior performance comparing to the primary SMM based ANF.

Abstract: In this paper, a natural image compression method is proposed based on independent component analysis (ICA) and visual saliency detection. The proposed compression method learns basis functions trained from data using ICA to transform the image at first; and then sets percentage of the zero coefficient number in the total transforming coefficients. After that, transforming coefficients are sparser which indicates further improving of compression ratio. Next, the compression method performance is compared with the discrete cosine transform (DCT). Evaluation through both the usual PSNR and Structural Similarity Index (SSIM) measurements showed that proposed compression method is more robust to DCT. And finally, we proposed a visual saliency detection method to detect automatically the important region of image which is not or low compressed while the other regions are highly compressed. Experiment shows that the method can guarantee the quality of important region effectively.

Abstract: In this paper, we proposed left-right hidden Markov models (HMMs) combination with k-means threshold of Likelihood ratio test (LRT) to identify the start and end of the speech. This method builds two models of non-speech and speech but not two states, i.e. each model could conclude several states. In the experiments we present the Voice Activity Detection (VAD) results between two states hidden semi-Markov model (HSMM) and proposed algorithm. We also compare accuracy and robust between the k-means threshold and the adaptive threshold in high signal to noise rate in the background noise. It presents that k-means threshold is more effective than the adaptive threshold and the proposed method also make a better performance than two states HSMM based VAD, especially in the low signal-to-noise ratio (SNR) environment.

Abstract: That the control objectives of active power filter are diversified is an import measure to improve application efficiency of active power filter. This paper puts forward a new referenced signal detection method based on generalized orthogonal transformation, and expatiates of the basic theory of generalized orthogonal transformation and detection principles and their realization methods of all kinds of referenced signals. Finally, simulative results are given. Theory analysis and simulative results show validity of the proposed detection method.

Abstract: The paper proposes a novel corner detection algorithm based on classical Susan model. The improvement is given from two aspects. One is the choice of the self-adaptive threshold. The other is that we present a rotate coordinate system to find all possible corner points. Experiment result shows that the modified algorithm is robust and of high efficiency.