Applied Mechanics and Materials Vols. 602-605

Abstract: Because of the influence of fog and other inclement weather, traffic’s low visibility and the highway’s traffic accident often occurred, which caused very big loss to people's life and property. For the disaster area, there are no ways to access the information and transmit in time, so establishing a system to eliminate the low visibility has a very important significance of random fog, low visibility caused by traffic accident in short time. The result shows that the system has high precision and reliability.

Abstract: Graphical User Interfaces (GUI) is becoming increasingly important in the software field, while GUI testing is becoming the key issues restricting GUI rapid development. GUI testing mainly serves two goals: to establish confidence in assessment of GUI and find more software defects in GUI testing. For this purpose, any testing method must be better at detecting defects. However, GUI testing is faced with many challenges due to the immense number of event interactions. In this paper, it introduces a Bayesian model guiding the process of GUI testing, discusses the Bayesian model topology and its issues encountered in the modeling process. In the end, a case reveals the validity of the GUI testing model.

Abstract: The interesting point is important features in images, which is frequently used for image registration, scene analysis, object tracking. Many algorithms for detecting the interesting points have been developed up to now. Among them, the Harris interesting point detector is proved most stable against rotation and noise, while it is also very sensitive to scale change. In order to solve this problem, a new multi-scale Harris interesting point detection algorithm is proposed in this paper. The algorithm consists of two main stages. In stage one, we build a multi-scale representation for Harris measure and find candidate interesting points at each scale level. In stage two, a novel measure is defined to measure the stability of each point. Based on the measure, the final interesting point is selected from candidates. The experiments on both optical and sar data sets have shown that, compared with stand Harris interesting point detector and some other multi-scale interesting point detectors, our algorithm is more robust.

Abstract: A portable detection system is designed for solving the problems of too many individual equipment, great difficulty in detection and lack of special detection and repair equipment. This system have the functions of fault detection, fault locating and repair instruction, so its detection functions are better, especially suitable for field work. Through experiments, it is found that the system has the advantages of high degree of automation, openness and quick detection and can adapt to the need of repair.

Abstract: A method for online identifying and processing single variable outliers was proposed based on a three-sliding window-Bayesian method. Generally, the method utilized the characteristic that the flow rate and temperature in metallurgical production do not change suddenly. Based on this characteristic, the research accurately identified outliers and variation of normal working points by analyzing the change of Bayesian posterior probability and conditional probability of the detection data in the three sliding windows.

Abstract: Linear target is the most widely used in remote sensing image. Effective extraction of the linear target can make us reduce a lot of practical work, thus greatly improve the target extraction and identification of timeliness. According to this situation, in the process of building a recognition system, the recognition efficiency can be realized by joining human recognize and identify, combining with the intelligence of computer processing and powerful place. So in this paper, the method based on edge detection and Hough transform algorithm is exploded. Line Extraction and Target Recognition System is developed. The system is realized under Windows operating system. The tool is Visual C++ 6.0 software. The platform is MFC functions. The system is written in C++ language. The characteristics of the system are the strong pertinence and the simple operation. When the system is applied safely, the results are definite and clear.

Abstract: With the development of science and technology, optical images with very high resolution have been able to provide a large amount of information. Therein the road target is the most widely used in optical image. Road target detection and recognition is extremely important for reducing a lot of practical work and greatly improving the efficiency of the target extraction and identification. Aimed at this problem, we propose a road target recognition method based on optical image.The method is realized by joining human recognize and identify, combining with the intelligence of computer processing and powerful place. So in this work, the method based on edge detection and Hough transform algorithm is exploded. The man-machine interactive recognition system (Road Target Extraction and Recognition System) is developed. The system is realized under Windows operating system. The tool is Visual C++ 6.0 software. The platform is MFC functions. The system is written in C++ language. The characteristics of the system are the strong pertinence and the simple operation. When the system is applied safely, the results are definite and clear.

Abstract: This paper describes the fabrication process of the thin film bulk acoustic resonator (FBAR) based on good quality aluminum nitride (AlN) film and the measurement of FBAR by a network analyzer. The AlN film with a highly c-axis orientation and homogeneous surface morphologies is deposited on Bragg reflectors as piezoelectric film by magnetron sputtering. The Bragg reflectors consisted of Ti and W fabricated under the resonator for acoustic isolation improves performance and compatibility of the FBAR and reduces the parasitic resistance of the electrode. The devices are packaged on tube seat and fixed on a high frequency PCB board designed specially for measurement and applications. The FBAR achieved a Q factor of 505 and k²_eff of 3.42% at a resonant frequency of 2.22 GHz. A high sensitivity of 4.79 kHz·cm²/ng is obtained in the FBAR, which is higher than quartz crystal microbalance.

Abstract: Adaptive optics (AO) is the primary means of improving the light transmission quality and easing the optical turbulence in communication. In laser intensity/direct demodulation (IM/DD) optical communication system, the function of AO correction for improving the optical communication performance is analyzed, adaptive optics (AO) compensating effects of atmospheric turbulence is studied by simulation and experiment in our adaptive optics system test bed. And 2.5 GB/s optical communication system performance is improved by AO compensating effects. So signal noise rate (SNR) and bit error rate (BER) of laser communication are improved.

Abstract: According to the need of bridge group network security monitoring, fiber optic sensing technology and internet of things concept are used for the study on bridge structural safety monitoring network platform. From four parts, namely, function goals, service contents, hierarchy model and working environment, the network platform function analysis are finished. Aim at the present situation of bridge safety monitoring systems in Wuhan, a preliminary platform application effect bearing by main interface and navigation menu is introduced.