Applied Mechanics and Materials Vols. 556-562

Abstract: This report investigates a segment treatment method of long term integration. In this paper, the authors design a velocity template detector (VTD) which is combined with the hybrid coherent-incoherent integration to detect radar dim targets. Unlike most of the existing long term integration methods which are complex-algorithm and huge-computation, the proposed method is simple and easy to achieve, which is of great practical significance.

Abstract: In this paper, an improved object detection method based on SURF (Speed-Up Robust Feature) is presented. SURF is a widely used method in computer vision. But it’s still not efficient enough to apply in real-time applications, such as real time object tracking. To reduce the time cost, the traditional descriptor of SURF is altered. Triangle and diagonal descriptor is adopted to replace the Haar wavelet calculation. Then dual matching approach based on FLANN is employed. Thus matching errors can be cut down. Besides, the traditional SURF does not give the accurate region of the target. To restrict the area, clustering analysis is used which is promoted from K-WMeans. Experimental work demonstrates the proposed approach achieve better effect than traditional SURF in real scenarios.

Abstract: Multiple-input multiple output (MIMO) radar has been widespread concern in the domestic and foreign researchers. Bistatic radar draws on the great success of MIMO technology in the communications field, and it has many advantages over conventional radar. The direction angles estimations of bistatic MIMO radar are researched. To contrast traditional radar DOA estimates, the direction vector of the bistatic MIMO radar is the Knonecker plot of the emission vector and reception vector, that two-dimensional direction angles is estimated. To solve this problem, the principle of bistatic MIMO radar signal model is in-depthly researched.By proposing Capon dimensionality reduction method, the two-dimensional directions of the dual-based MIMO radar are estimated, and computer simulation is to verify the effectiveness of the method.

Abstract: Spectrum sensing is a key technology to reliably detect spectrum holes in multi-dimensions for cognitive radio networks. In this paper, a joint spatial-temporal spectrum sensing scheme is proposed. First of all, the secondary users (SUs) located inside the primary exclusive region (PER) perform temporal sensing. When the primary user (PU) is present, the SUs located outside the PER perform spatial spectrum sensing. The proposed method can improve the spectrum utilization by exploiting both temporal and spatial spectrum holes. The achievable throughput for the secondary network of joint spatial-temporal sensing is higher than that of pure temporal sensing. Simulation results demonstrate the effectiveness of the proposed approach.

Abstract: Spectrum sensing is critical for cognitive radio networks as it allows a secondary user to find spectrum holes for opportunistic reuse. In this paper, an improved maximum-minimum eigenvalue detection method is proposed for a cognitive user equipped with a single receiving antenna. The proposed method utilizes the temporal smoothing technique to form a virtual multiple antennas structure. At the same time, the jackknifing resampling strategy is employed to improve the detection performance. Simulation results are presented to verify the effectiveness of the proposed method.

Abstract: Traditional datacenter temperature monitoring method is to install some temperature sensors which are unable to cover all areas completely, so there are some problems about local hot spot. The method is aiming to find out the position of potential hazard which may exist in the data center on the basis of data center thermal environment evaluation method and characteristics of air distribution. By applying this method into the wireless sensor network monitoring system, it brings a meaningful improvement of the monitoring system.

Abstract: A Lithium niobate (LiNbO₃) based integrated optical E-field sensor with an optical waveguide Mach-Zehnder interferometer (MZI) and a tapered antenna has been designed and fabricated for measurement of pulsed E-field. Experimental results demonstrate that the minimum detectable E-field of the sensor is 10 kV/m. The linear relationship between the sensor input and output is better while the input E-fields varied from 10 kV/m to 370 kV/m. Besides, from the fitting curve it can be calculated that the maximum detectable E-field of the sensor is approximately equal to 1000 kV/m.

Abstract: Compared with the intrusion detection based on pattern matching, the method which is based on model checking can detect the complex attacks. But all of the existing algorithms are used to detect some specific types of attacks. So, we firstly use the projection temporal logic (PTL) formulae to set up formal sub-models respectively for the five kinds of attackers, the four kinds of attack processes and the eight kinds of attack effects. According to their universal relationship and the semantic relation of variety of PTL logic operators, we obtain the above sub-models together, thus, the universal model described by PTL formula for universal attack is formed. On this base, we implement an intrusion detection method based on projection temporal logic for detecting all types of attacks. Compared with the existing methods, the detecting ability of the new method is more comprehensive.

Abstract: As the great development of digital photography and relevant post-processing technology, digital image forgery becomes easily in terms of operating thus may be improperly utilized in news photography in which any forgery is strictly prohibited or the other scenario, for instance, as an evidence in the court. Therefore, digital image forgery detection technique is needed. In this paper, attention has been focused on copy-move forgery that one region is copied and then pasted onto other zones to create duplication or cover something in an image. A novel method based on HSV color space feature is proposed and experimental result will be given and it shows the effectiveness and accurateness of proposed methodology.

Abstract: A recognition method based on Wavelet Packet Decomposition - Common Spatial Patterns (WPD-CSP) and Kernel Fisher Support Vector Machine (KF-SVM) is developed and used for EEG recognition in motor imagery brain–computer interfaces (BCIs). The WPD-CSP is used for feature extraction and KF-SVM is used for classification. The presented recognition method includes the following steps: (1) some important EEG channels are selected. The 'haar' wavelet basis is used to take wavelet packet decomposition. And some decomposed sub-bands related with motor imagery for each EEG channel are reconstructed to obtain the relevant frequency information. (2) A six-dimensional feature vector is obtained by the CSP feature extraction to the reconstructed signal. And then the within-class scatter is calculated based on the feature vector. (3) The scatter is added into the radical basis function to construct a new kernel function. The obtained new kernel is integrated into the SVM to act as its kernel function. To evaluate effectiveness of the proposed WPD-CSP + KF-SVM method, the data from the 2008 international BCI competition are processed. A preliminary result shows that the proposed classification algorithm can well recognize EEG data and improve the EEG recognition accuracy in motor imagery BCIs.