Community detection in complex networks by density-based clustering

We proposed a method to find the community structure in a complex network by density-based clustering. Physical topological distance is introduced in density-based clustering for determining a distance function of specific influence functions. According to the distribution of the data, the community structures are uncovered. The method keeps a better connection mode of the community structure than the existing algorithms in terms of modularity, which can be viewed as a basic characteristic of community detection in the future. Moreover, experimental results indicate that the proposed method is efficient and effective to be used for community detection of medium and large networks.     

Preliminary results for the design,fabrication,and performance of a backside-illuminated avalanche drift detector

The detection of low-level light is a key technology in various experimental scientific studies. As a photon detector, the silicon photomultiplier （SiPM） has gradually become an alternative to the photomultiplier tube （PMT） in many applications in high-energy physics, astroparticle physics, and medical imaging because of its high photon detection efficiency （PDE）, good resolution for single-photon detection, insensitivity to magnetic field, low operating voltage, compactness, and low cost. However, primarily because of the geometric fill factor, the PDE of most SiPMs is not very high; in particular, for those SiPMs with a high density of micro cells, the effective area is small, and the bandwidth of the light response is narrow. As a building block of the SiPM, the concept of the backside-illuminated avalanche drift detector （ADD） was first proposed by the Max Planck Institute of Germany eight years ago; the ADD is promising to have high PDE over the full energy range of optical photons, even ultraviolet light and X-ray light, and because the avalanche multiplication region is very small, the ADD is beneficial for the fabrication of large-area SiPMs. However, because of difficulties in design and fabrication, no significant progress had been made, and the concept had not yet been verified. In this paper, preliminary results in the design, fabrication, and performance of a backside-illuminated ADD are reported; the difficulties in and limitations to the backside-illuminated ADD are analyzed.     

Numerical analysis of the resonance mechanism of the lumped parameter system model for acoustic mine detection

The method of numerical analysis is employed to study the resonance mechanism of the lumped parameter system model for acoustic mine detection. Based on the basic principle of the acoustic resonance technique for mine detection and the characteristics of low-frequency acoustics, the “soil-mine” system could be equivalent to a damping “mass-spring” resonance model with a lumped parameter analysis method. The dynamic simulation software, Adams, is adopted to analyze the lumped parameter system model numerically. The simulated resonance frequency and anti-resonance frequency are 151 Hz and 512 Hz respectively, basically in agreement with the published resonance frequency of 155 Hz and anti-resonance frequency of 513 Hz, which were measured in the experiment. Therefore, the technique of numerical simulation is validated to have the potential for analyzing the acoustic mine detection model quantitatively. The influences of the soil and mine parameters on the resonance characteristics of the soil–mine system could be investigated by changing the parameter setup in a flexible manner.     

偏振成像探测技术发展现状及关键技术

考虑偏振成像探测技术在目标探测中具有独特优势,本文介绍了偏振成像探测技术的概念,概括了国外偏振成像探测技术的研究历程和发展现状。基于上述描述,针对偏振成像探测的关键技术进行了深入的讨论,包括目标偏振特性、信道环境下的偏振传输特性和偏振成像目标全偏振图像的获取等。最后总结了该研究领域存在的主要问题,归纳了偏振成像探测技术的发展趋势。     

基于数字图像处理技术的树脂眼镜镜片缺陷检测研究

通过设计的镜片自动检测光学硬件系统,给出了树脂镜片精细杂质图像处理措施,将图像差分法应用于镜片图像边缘的去除;同时解决了镜片检测灰尘影响的问题;另外运用改进型的归一法解决杂质计数问题,为自动化分级分拣系统的研发提供重要的数据支持,为镜片缺陷检测系统的后续分级分拣的数字控制模块提供了可操作性。该检测系统检测精度为0.03 mm、速度为1片/s,检测误差控制在5%。     

A bubble detection technique based on light intensity and Mie scattering theory for spinning solution

A novel bubble detection technique based on light intensity and Mie scattering theory for spinning solution is presented theoretically and experimentally. With the light intensity in every direction, the particle or bubble size distribution can be calculated with the Mie scattering theory. The light intensity distribution in every direction, corresponding to the light intensity received by every assumed annulus of the detector has been calculated theoretically. According to the light intensity distribution, the size distribution of bubbles can be deduced. A series of standardized polystyrene micro-sphere (with 7 μm diameter) solution has been used not only as sample for experiments and calibration, but also as the bubbles in the glycerin. Theoretical and experimental results show that the technique can be used for bubble detection, in order to improve the traditional bubble detection scheme, and to lower production costs.     

A recursive color image edge detection method using Green's function approach

In this paper, an extended version of image edge detector using Green's function approach is proposed for detection of edges in the color vector space field. In the proposed method, the relationship between the Red, Green and Blue components is considered to design a differential operator for detection of edges in color images. By using the proposed operator, partial derivatives of all components of color image can simultaneously affect on the edge detection process. Therefore the proposed method can preserve the vector nature of color images during the edge processing stages. Also, the proposed method is compared both quantitatively and qualitatively with other color edge detectors. Experimental results show that the proposed method can efficiently preserve the edges even when the color images corrupted with different levels of noise.     

Algorithms of target detection on hyperspectral imagery

With the development of airborne and spaceborne remote sensing from the 1980s, as a new and growing technology, hyperspectral imaging is widely used in different fields, such as military investigation, battlefield information acquisition, environmental monitoring, mineral exploration and public security. Because of the unique characteristic of acquiring spectral and spatial information simultaneously, it brings the hyperspectral detection advantages when dealing with target detection problem under complex conditions. Target detecting models of hyperspectral image are established, including the target subspace model and the probability statistical model. And several algorithms are introduced, which are based on original spectral features, sub-space projection and probability statistical model separately. Comparison shows that if the background includes fault objectives, GLRT is the best algorithm, and its SINR is the largest; on condition of anomaly target detection, LPTD is the best, and have a quite high SINR.     

Stochastic resonance in multi-scale bistable array

This Letter explores a new mechanism of stochastic resonance (SR) that is induced by the multi-scale noise decomposed from the input signal, which is promising in signal detection and processing under heavy background noise. The input signal is firstly decomposed to multi-scale signals by orthogonal wavelet transform. Then, the approximate signal, which contains the driving signal, is processed by an uncoupled parallel bistable array with the detailed signal of each scale as the internal noise. At last, a SR mechanism combining the effects of colored noise and array SR is proposed. The simulation results show that a high quality output signal can be obtained by the new mechanism. The proposed model is more adaptive to input signal with high noise intensity than single bistable SR system, which can be seen from the signal-to-noise ratio curves and average noise intensity curves.     

激光诱导击穿光谱技术的研究与应用新进展

激光诱导击穿光谱技术(LIBS)是一种近年来随着激光技术和光谱检测技术的发展而兴起的对元素定性和定量分析的光谱技术。详细介绍了LIBS技术最新的研究发展情况,以及在冶金、环境污染检测、生物医学、植物学、空间探索等领域的最新应用进展。