Efficient Activation Method of Hardware Trojan Based on Greedy Algorithm

To generate test vector sets that can efficiently activate hardware Trojans and improve probability of the hardware Trojan activation,an efficient hardware Trojan activation method is proposed based on greedy algorithm for combinatorial hardware Trojans. Based on the greedy algorithm and the recursive construction method in the combination test,the method formulates appropriate and useful greedy strategy and generates test vector sets with different combinatorial correlation coefficients to activate hardware Trojans in target circuits. The experiment was carried out based on advanced encryption standard（ AES） hardware encryption circuit,different combinatorial hardware Trojans were implanted in AES as target circuits,the experiment of detecting hardware Trojans in target circuits was performed by applying the proposed method and different combinatorial hardware Trojans in target circuits were activated successfully many times in the experiment. The experimental results showthat the test vector sets generated using the proposed method could effectively activate combinatorial hardware Trojans,improve the probability of the hardware Trojan being activated,and also be applied to practice.

A rapid audio event detection method by adopting 2D-Haar acoustic super feature vector

For accuracy and rapidity of audio event detection in the mass-data audio pro- cessing tasks, a generic method of rapidly recognizing audio event based on 2D-Haar acoustic super feature vector and AdaBoost is proposed. Firstly, it combines certain number of con- tinuous audio frames to be an ＂acoustic feature image＂, secondly, uses AdaBoost.MH or fast Random AdaBoost feature selection algorithm to select high representative 2D-Haar pattern combinations to construct super feature vectors; thirdly, analyzes the commonality and differ- ences between subcategories, then extracts common features and reduces different features to obtain a generic audio event template, which can support the accurate identification of multi- ple sub-classes and detect and locate the specific audio event from the audio stream accurately. Experimental results show that the use of 2D-Haar acoustic feature super vector can make recog- nition accuracy 5% higher than ones that MFCC, PLP, LPCC and other traditional acoustic features yielded, and can make tile training processing 7 20 times faster and the recognition processing 5-10 times faster, it can even achieve an average precision of 93.38%, an average recall of 95.03% under the optimal parameter configuration found by grid method. Above all, it can provide an accurate and fast mass-data processing method for audio event detection.

ON DETECTION OF CHANGE POINTS USING MEAN VECTORS

In this paper,the authors consider the problem of change points within the framework of model selection and propose a procedure for estimating the locations of change points when the number of change points is known.The strong consistency of this procedure is also established. The problem of detecting change points is discussed within the framework of the simultaneous test procedure.The case where the number of change points is unknown will be discussed in another paper.

Auto-normalization algorithm for robotic precision drilling system in aircraft component assembly

A novel approach is proposed to detect the normal vector to product surface in real time for the robotic precision drilling system in aircraft component assembly, and the auto-normalization algorithm is presented based on the detection system. Firstly, the deviation between the normal vector and the spindle axis is measured by the four laser displacement sensors installed at the head of the multi-function end effector. Then, the robot target attitude is inversely solved according to the auto-normalization algorithm. Finally, adjust the robot to the target attitude via pitch and yaw rotations about the tool center point and the spindle axis is corrected in line with the normal vector simultaneously. To test and verify the auto-normalization algorithm, an experimental platform is established in which the laser tracker is introduced for accurate measurement. The results show that the deviations between the corrected spindle axis and the normal vector are all reduced to less than 0.5°, with the mean value 0.32°. It is demonstrated the detection method and the autonormalization algorithm are feasible and reliable.

The technique of detecting the laser-ultrasonic vector displacement with a confocal Fabry-Perot interferometer waves in a plate

Generally, a confocal Fabry-Perot interferometer is only able to detect the out-of-plane component of a displacement field; while the in-plane component often has the information about the material which cannot be found in this out-of-plane component. In this paper, based on a confocal Fabry-Perot interferometer set-up for detecting the out-of-plane component of a laser generated acoustic field, a technique is developed to detect both the out-of-plane and in-plane displacement components simultaneously with a novel two-channel confocal Fabry-Perot interferometer.

Highly sensitive vector magnetic fiber sensor based on hyperbolic metamaterials

Hyperbolic metamaterials(HMMs) are novel artificial materials that excite the surface plasmon resonance(SPR) because of their unique hyperbolic dispersion properties. Herein, to the best of our knowledge, we propose the first HMM-based fiber SPR(HMM-SPR) sensor for vector magnetic detection. By selecting the composite materials and structural parameters of the HMM dispersion management, HMM-SPR sensors can achieve a high refractive index sensitivity of 14.43 μm/RIU. Vector magnetic field detection was performed with the HMM-SPR sensor encapsulated with a magnetic fluid. Compared with other ferrofluidbased magnetic field fiber sensors, the proposed sensor shows pronounced advantages in intensity and direction sensitivity of 1.307 nm/Oe and 7.116 nm/°, respectively. The sensor design approach presented in this paper provides an excellent demonstration of HMM-SPR sensors in various applications.