为减少高校实验安全事故发生,本文依据美国麻省理工学院安全文件相关的规定,具体分析了美国高校两起实验安全事故中导师实验安全责任落实不足的问题.依据职业健康安全管理体系标准(IOS 45001),本文讨论了实验操作研究生如何及时发现实验安全风险出现失控,采取措施进行自我保护的问题.

笔者认为,企业应按策划部署,突出主次,按部就班、持续有效地抓好安全,避免时紧时松. 首先,企业应该认识到“抓安全”就是在“促生产”.安全是生产的有机组成部分,不可分割.如果生产没有安全保障,就很可能会引发事故,造成人员伤亡等损失,并迫使生产被停止.因此,只要有生产,就要抓安全.同时,安全需要投入必要的人力、物力,还要占用人员的时间,虽然看起来好像“耽误”了生产,在和生产抢资源,但当企业安全责有效落实,安全真正有效保障后,必然会使事故率大大降低,并大幅减少事故损失,提高生产效率.

A three-dimensional environment perception camera based on structured light and panoramic vision is proposed. A panoramic camera is designed to satisfy the single-viewpoint constraint by combining a hyperbolic reflector and common perspective zoom lens. A near-infrared ray laser is used to project structured light patterns to the environment for a panoramic camera. The camera includes a charge-coupled device sensor, which has a wide sensitivity spectrum such that it can receive near-infrared light and visible light at the same time. We propose a new method of calibrating the panoramic camera and laser light plane to calculate the point cloud more precisely. Finally, we conduct an experiment to evaluate the performance of the camera.

On the basis of analyzing the disadvantage of other structural accelerometer, three-axis high g MEMS piezoresistive accelerometer was put forward in order to apply to the high-shock test field. The accelerometer's structure and working principle were discussed in details. The simulation results show that three-axis high shock MEMS accelerometer can bear high shock. After bearing high shock impact in high-shock shooting test, three-axis high shock MEMS accelerometer can obtain the intact metrical information of the penetration process and still guarantee the accurate precision of measurement in high shock load range, so we can not only analyze the law of stress wave spreading and the penetration rule of the penetration process of the body of the missile, but also furnish the testing technology of the burst point controlling. The accelerometer has far-ranging application in recording the typical data that projectile penetrating hard target and furnish both technology guarantees for penetration rule and defend engineering.

Aiming at the problem lied in existed methods which cannot suppress grille background completely, a novel method of vehicle-logo accurate localization was proposed. Firstly color invariants and prior information are used for fast localizing license plate in RGB color space directly; and then process fine localization of the vehicle-logo based on coarsely localized results. Background noises are secondarily suppressed based on gradient angle histogram analysis and local self-adaptive threshold treatment. Numerous experiments show that this method possesses not only high accuracy but also high robustness in localization, as compared to classic template matching. Besides, the proposed method satisfies the requirement of real-time performance.

Extracting a license plate is an important stage in automatic vehicle identification. The degradation of images and the computation intense make this task difficult. In this paper, a robust and fast license plate detection based on the fusion of color and edge feature is proposed. Based on the dichromatic reflection model, two new color ratios computed from the RGB color model are introduced and proved to be two color invariants. The global color feature extracted by the new color invariants improves the method's robustness. The local Sobel edge feature guarantees the method's accuracy. In the experiment, the detection performance is good. The detection results show that this paper's method is robust to the illumination, object geometry and the disturbance around the license plates. The method can also detect license plates when the color of the car body is the same as the color of the plates. The processing time for image size of 1000x1000 by pixels is nearly 0.2s. Based on the comparison, the performance of the new ratios is comparable to the common used HSI color model.

Caliber mortar projectiles and bombs are now tend to use the laser fuze because of its high accuracy in distance measurement, the strong ability to resist electromagnetic interference, the high angular resolution and the good concealment. Otherwise, the microlaser can bring about some alluring benefits. For instance, it can generate high quality laser beam, which has small divergence angle and high power. So, This paper summarizes some key factors which have impacts on the output of LD-pumped passively Q-switched subnanosecond microlasers, including the initial transmission of the absorber, the reflection of output coupler, the length of the cavity and the radius of the pumping laser beam, and gives the conclusion of the simulation based on the variation of the density of the reversal particle in the resonant cavity derived from the oscillation equation of the LD-pumped passively Q-switched Cr4+:YAG/ Nd:YAG laser, which provides the basis for the design of the passive Q-switched micro lasers which have high power, high repetition frequency and narrow pulse width.

In traditional pulsed laser fuze systems, the emission and receiving optical systems are independent, causing a blind area, and they have little capacity to resist cloud and interference. To solve these problems, a polarized laser fuze without blind area was designed based on the polarized property of laser. For the new laser fuze, a polarized beam splitter was used to realize a mode in which the emitter and receiver use the same aperture. At the same time, its anti-interference capacity was improved by using a nanosecond laser as emitting source. An experimental system was established, in which 1064 nm polarized laser with pulse duration of 1 ns was used, and a photodetector was used as the receiver. The echo characteristics of different objects within the range of 1 m were obtained.

A method,named steered response power phase-transform weighed(SRP-PHAT),is one of the most popular approaches for the microphone array sound source localization.The problem that the computation of SRP-PHAT is so expensive that it can't locate the sound source in real time is focused.Some efficient improvement approach such as traction(SRC),coarse-to-fine region contraction(CFRC),stochastic particle filtering(SPF),and so on are analyzed.Improvement methods for SRP-PHAT are summarized.

The steered response power-phase transform algorithm (SRP-PHAT) has been widely utilized for robust sound source localization for indoor environment. Searching space clustering algorithm (SSC) is the improved version of SRP-PHAT, in which the computational complexity could be greatly reduced via the space division and clustering. However, SSC has to frequently perform the space division and clustering when the positions of microphone arrays are changed, which will induce additional computational complexity. In this paper, we proposed a coarse-to-fine region contraction SSC (CFRC-SSC) method to reduce the computational complexity of SSC for the sound source localization algorithm. The coarse level SSC with limited computational complexity will contract the whole searching space to several candidate spaces with limited size, which will reduce the searching volume for fine level SSC without omitting the actual sound source localization. Simulation results demonstrate that the proposed CFRC-SSC show a lower computational complexity in terms of SRP function evaluation times and space clustering calculation times compared to SSC.

For accurate texture description,with the advantage of directional channel selection in dual-tree complex wavelet packet transform,the adaptive probabilistic texture model is used. With the maximum likelihood classification method,an approach which combines the best description of each texture is proposed.By this approach,the correct rate of classification increases from 85% to 93%.

The probabilistic adaptive texture model based on best wavelet packet basis has excellence in more accurate texture description which differentiates various textures by optimizing wavelet packet basis.An adaptive texture description based neighbourhood segmentation method is studied in the paper,the major and minor relationship of the impacts the probabilistic adaptive texture model and the neighbourhood segmentation method has respectively on the segmentation is analyzed through the experiment.The experimental result shows that it is the neighbourhood based segmentation method which mainly contributes to the good performance(with less than 1.34% error rate) whereas the probabilistic model contributes less.This conclusion is helpful for method's improvement.

An implementation of iris recognition on a hybrid opto-electronic volume holographic system is introduced in this paper. Wavelet Packet (WP) decomposition is used to generate the eigen images. The WP nodes combination with the highest recognition rate is obtained through exhuastive search. The time-consuming stages of eigen image generation and storage are completed preliminarily, and due to its multi-channel and high parallelism ability, the feature extraction is performed in real time with the help of volume holographic correlation. The correlation results detected by CCD are post-processed in a computer. Recognition rates can be further improved if window of proper size and the normalization technique are used. The recognition rate of computer simulation can reach 98%, while the highest rate in experiment is 91%. Experiment results demonstrate the feasibility of the iris recognition implementation scheme, and provide some foundation for future development.

To introduce wavelet packet transform into optical transform and improve the recognition performance of optical iris recognition, optical wavelet packet transform is proposed based on the analysis of the necessary condition for optical wavelet transform. Using the eigen-image based correlation recognition method and replacing the entropy criterion with the identification rate for iris recognition, the joint best wavelet packet bases for the whole image bank are chosen. Corresponding eigen images are generated. To further improve the performance of optical iris recognition, an optical wavelet packet filter is designed through linearly combining these wavelet packet bases. The filter is inserted in a volume holographic opto-electronic hybrid iris recognition system for feature extraction. The wavelet packet features extracted are correlated with the eigen images stored in the photorefractive crystal. The correlation results are captured and transferred to a computer for post processing. In simulation, the mother wavelet, Db4, is utilized. Four wavelet packet bases are selected. The filter can obviously improve the identification rate from 90. 91% to 95. 45%. This result not only proves the efficiency of the filter designed but also shows that the capacity of optical information processing is enhanced after the introduction of wavelet packet transform into optics.

The analysis and improvement of the dual multichannel iris recognition system are provided.After obtaining the relation between the local region channels and identification rate,the two directional channel separation and the optimization of local region channel are discussed.The influences of wavelet filter channels on the recognition performance are studied.Based on the conclusion of filter channel selection,wavelet packet channels are introduced for better performance.The relative Weighted Euclidean Distance(WED) classifier is proposed as an improvement of the classifier.

The wavelet and harmonic filtering method suggested by Zalevsky and Ouzieli is introduced in this paper and adopted in our volume holographic image recognition system. This composite filter combines several scaled versions of the cascaded wavelet and harmonic filter, obtaining high discrimination ability and wide dynamic range of rotation and scale deformations. Optical experiments are conducted to demonstrate the validity and practicability of the algorithm. To the best of our knowledge, this is the first report of using this algorithm in a volume holographic system. Moreover, the separate correlation approach proposed in this paper greatly simplifies the manufacturing process and reduces the cost of the system.

For improving optical wavelet transform(OWT),optical separable wavelet transform(OSWT) is proposed.Based on the analysis of the necessary condition for OWT,using the cascade algorithm and 2D separable wavelet transform scheme,discrete approximation sequence of scaling and wavelet functions was computed for optical implementation.The advantages of OSWT are described via comparison with OWT and 2D discrete separable wavelet transform.

Based on the cascade algorithm and the theory of 2-D separable wavelet transform, 2-D approximations of scaling and wavelet basis functions are computed and used in optical wavelet transform. The optical transform using these separable wavelet bases can be called optical separable wavelet transform. And the selection of mother wavelets is extended. Unlike 2-D discrete separable wavelet transform, optical separable wavelet transform does not have limitation on direction selectivity. Linearly combining multiple directional channels as a superposition filter, the transform of these bases can be fulfilled simultaneously and the transform results can be synthesized on the output plane. In this paper, 2-D scaling and wavelet basis functions of a biorthogonal wavelet, bior2.6, are calculated. Four directional channels combine into an oriented optical filter to increase the extracted feature energy in high frequency band. And simulation results are presented.

For optical iris recognition, the eigen-images correlation recognition method is modified. The 2-D separable approximations of wavelet packet bases are constructed with the help of the cascade algorithm. Expanding the scale of basis selection, mutli-mother multi-vanishing moment joint best bases are chosen from the basis set of 25 mother wavelets including the mothers constructed by the lifting scheme. Using the corresponding eigen-images generated and the post-processing method based on statistic features, optical experiment is implemented. The experimental result agrees with the simulation result.

采用层叠算法,计算小波包基函数的离散逼近序列.改进特征图像相关识别方法,选用识别能力评价指标,利用图像和小波包基函数相关的直接变换优点改进最优基选择,提出多母小波多消失矩最优基.生成最优基的特征图像,采用体全息相关识别系统实现虹膜的光学识别,实验取得较好的效果.设计、制作多母小波多消失矩最优基光学小波包灰阶滤波器以进一步提升识别率.检测表明,滤波器符合设计要求.实验表明,该滤波器可有效提高识别率.