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Through the investigation of bridges along Shanghai Suzhou Creek, we find a lot of problems. Firstly, Bridge layout is unreasonable. Secondly, mobiles occupy the main traffic volume. Thirdly, slow-traffic and lingering space isn’t comfortable. This study proposes the bridge planning and design idea oriented by slow-traffic and lingering space. Learning from overseas experiences, we put forward the bridge layout suggestions for Suzhou Creek from three aspects. First is to construct the reasonable distance between slow-traffic and lingering bridges. Second is to build the bridge system suitable for fast and slow-traffic. The last is to connect the cross-river attracted sources and bridges. Based on the above, we propose the bridges layout suggestion plan of Suzhou Creek.

Electrical discharge grinding is part of the most widely used methods to machine polycrystalline cubic boron nitride cutting tool. Polycrystalline cubic boron nitride compact samples processed in domestic with different grain size are the research object. Electrode running speed, peak current, and pulse width are selected as the main process parameters. The material removal volume and electrode loss set as the evaluation index of productive efficiency; workpiece surface roughness value sets as an evaluation standard of processing quality. Through electrical discharge grinding experiments, combined with scanning electron microscopy observation, energy spectrum analyzer and roughness tester, the influences of the main process parameters on electrical discharge grinding are analyzed, polycrystalline cubic boron nitride compact electrical discharge grinding technics & mechanism are summarized.

This paper presents a new method for detecting lead pollution in rice by analyzing hyperspectral data. First, preprocessing method is used to remove the outliers which deviate so much from other hyperspectral data. Then, dimensionality-reduced data are made by using discrete wavelet transform. Finally, linear discriminant analysis is utilized to extract the feature which characterizes polluted and unpolluted rice. The experimental result based on the proposed method shows the good performance in detecting lead pollution in rice.

In order to describe the time-delays and faults on continuous nonlinear descriptor system using T-S fuzzy model, an observer is proposed to estimate system states, actuator and sensor faults. A fuzzy state feedback controller is constructed for faults compensations. On the basic of Lyapunov stability theory, the proposed robust fault-tolerant control method ensures the closed-loop system to be robust stability even as faults occur. The actuator and sensor faults can be diagnosed and estimated in 0.2 seconds. The performance of the proposed design method is effective in simulations.

This paper presents a new method for detecting lead pollution in rice by using hyperspectral data. First, some transform methods are used to generate relatively independent datasets on hyperspectral data. Then, the kernel discriminant analysis is utilized to extract features from each represented dataset. Finally, new fused features are made by combining aforementioned features serially. The experimental result based on the proposed method shows the good performance in detecting lead pollution in rice.

This paper presents importance of skin texture information in face recognition. To this end, we perform the illumination normalization on face image in order to extract texture information unaffected by illumination variation. And then apply mask image on each illumination normalized face image to obtain the corresponding texture data, which hardly contain the shape information. Face recognition experiments are carried out by using texture data. Experimental results on Yale face database B and CMU PIE database show that the texture information has considerable ability to distinguish subjects in face recognition.

This paper presents a new illumination normalization method for robust face recognition under varying lighting conditions. In the proposed method, the illumination component is estimated by applying nonlocal total variation model in the logarithmic domain, and then the reflectance component is obtained based on reflectance model. The proposed method restrains the halo effect effectively while preserves the adequate texture information on the reflectance images. As an illumination invariant facial features, the reflectance images are directly utilized for face recognition. Experimental results on Yale face database B and CMU PIE database show that the performance of proposed method is robust and reliable in illumination invariant face recognition.