In order to detect and process underground vibration signal, this paper presents a system with the combination of software and hardware. The hardware part consists of sensor, memory chips, USB, etc. , which is responsible for capturing original signals from sensors. The software part is a virtual oscilloscope based on LabWindows/CVI （C vitual instrument）, which not only has the functions of traditional oscilloscope but also can analyze and process vibration signals in special ways. The experimental results show that the designed system is stable, reliable and easy to be operated, which can meet practical requirements.
The signal processing technology based on material with negative refractive index provides researchers with the latest ideas. As a new nondestructive bio-photonic technology, photoacoustic tomography is a kind of imaging method based on the differences of optical absorption within the biological organization However, photoacoustic tomography by the scanning sensor or by the sensors array at present has its inherent disadvantages that may lead to poor real-time performance and high cost in the imaging process. The characteristics of acoustic lens with negative refractive index such as focusing, filtering and directional control on acoustic wave, are very suitable for solving the problem in photoacoustic tomography. With an analysis on the nega-tive quality response of acoustic lens and the advantages of negative refractive imaging, we proposed an approach using the lens to change the current photoacoustic imaging methods. The experiment showed that the imaging effectiveness of photoacoustic tomography by the designed lens is very impressive that the pressure distribution of the absorber is basically consistent with the image of the absorber. In addition, the result of 0. 6 times wavelength in the experimental image is demonstrated on sub-wave-length photoacoustic imaging through the lens designed in this work.
HAN Jian-ningGUI Zhi-guoWEN Ting-dunTIAN Er-mingYANG PengZHANG Quan
Although many classical IP geolocation algorithms are suitable to rich-connected networks, their performances are seriously affected in poor-connected networks with weak delay-distance correlation. This paper tries to improve the performances of classical IP geolocation algorithms by finding rich-connected sub-networks inside poor-connected networks. First, a new delay-distance correlation model （RTD-Corr model） is proposed. It builds the relationship between delay-distance correlation and actual network factors such as the tortuosity of the network path and the ratio of propagation delay. Second, based on the RTD-Corr model and actual network characteristics, this paper discusses about how to find rich-connected networks inside China Intemet which is a typical actual poor-connected network. Then we find rich-connected sub-networks of China Intemet through a large-scale network measurement which covers three major ISPs and thirty provinces. At last, based on the founded rich-connected sub-networks, we modify two classical IP geolocation algorithms and the experiments in China Intemet show that their accuracy is significantly increased.
The conventional X-ray gray weighted image fusion method based on variable energy cannot characterize the phys- ical properties of complicated objects correctly, therefore, the gray correction method of X-ray fusion image based on neural network is proposed. The conventional method acquires 12 bit images on variable energy, and then fuses the images in a tra- ditional way. While the new method takes the fusion image as the input of neural network simulation system and takes the acquired 16 bit image as the output of neural network. The X-ray image physical characteristic model based on neural net- work is obtained through training. And then it takes steel ladder block as the test object to verify the feasibility of the mod- el. In the end, the gray curve of output image is compared with the gray curve of 16 bit real image. The experiment results show that this method can fit the nonlinear relationship between the fusion image and the real image, and also can expand the scope of application of low dynamic image acquisition equipment.
Real-time detection for object size has now become a hot topic in the testing field and image processing is the core algorithm. This paper focuses on the processing and display of the collected dynamic images to achieve a real-time image pro- cessing for the moving objects. Firstly, the median filtering, gain calibration, image segmentation, image binarization, cor- ner detection and edge fitting are employed to process the images of the moving objects to make the image close to the real object. Then, the processed images are simultaneously displayed on a real-time basis to make it easier to analyze, understand and identify them, and thus it reduces the computation complexity. Finally, human-computer interaction （HCI）-friendly in- terface based on VC ＋＋ is designed to accomplish the digital logic transform, image processing and real-time display of the objects. The experiment shows that the proposed algorithm and software design have better real-time performance and accu- racy which can meet the industrial needs.
