At present, the manufacturing enterprises are extending to the service industry, and product service system(PSS) is developing rapidly as a new manufacturing system mode. The background of PSS was analyzed, in view of the demand of users for the service, the product innovation through the service from enterprise, the demand for the difference competition, the demand for the protection of surroundings, and the role of information and web technology. The development of relative theory and practice of PSS was summarized. The characteristics of various product services were analyzed. The theories of PSS were researched, which include: the theory and method for the management of lifecycle of product services, the optimization theory for organization and process of PSS et al. The key technologies were studied, such as: the product design for the product services, the technology of mining the user demand for the product services, the technology of product maintaining service, the technology of collection information of product services, the humanness technology of product services, et al. The function and characteristics of some PSS were summarized.

In order to analytizing neurons release pattern of the primary motor cortex of rats accurately and predicting corresponding body movement, the activities of the neurons ensemble spike activities in rats primary motor cortex and the forelimb pressure were recorded simultaneously in the experiment. K-means and principal component analysis were used to classification of neurons, then the partial least squares was used to analyze the relations between the neurons activities of the primary motor cortex of the rat and the forelimb motion parameters, and the results were compared with Wiener filter and Kalman filter. The experimental results indicate that the activities of neurons ensembles began a trend of increase 0.6 second before lever pressing, Which hints the neurons distributed activities of the primary motor cortex in rats can be used to analysis and prediction its forelimb movement and the correlation coefficient between the predicted value and real pressure value is more than 085 using the partial least squares, with a better decoding results than those using the Wiener filtering and Kalman filtering．

An all digital architecture was presented to realize the logarithm modeled automatic gain control (AGC) loop based on field programmable gates array (FPGA) platform. The architecture is mainly made up of four modules, including envelope detector, coordinator rotation digital computer (CORDIC) based iterative realization of effective hyperbolic function, infinite impulse response (IIR) based loop filter, and reconfigurable control logic generator. Envelope detector can meet the filter performance requirement only with finite impulse response (FIR) filter of low order. Symmetric coefficient based transposed architecture reduces the number of multipliers in filter to the half. By approximation to analog integrator and suitable process, IIR based filter can simplify the architecture of digital integrator. The logarithm convertor is easy to be realized by CORDIC based iterative hyperbolic function processor. The architecture can also output with random precision, and realize the compromise of circuit resources and speed, which overcomes the high demand for random access memory (RAM) in traditional algorithms. With fully parallel pipeline architecture, the maximum working clock can achieve 206 MHz. Finally, the realization results based on the FPGA processor and the hardware simulation were given. Experimental results were consistent well with the theoretical analysis．

The porous materials with low dielectric constant are suitable for the applications in integrated circuits. From the aspects of composition and structure, preparation method and dielectric properties, this work introduced the porous low-dielectric-constant materials with different matrix such as inorganic materials, organic materials, inorganic and organic composite separately, whose dielectric constants can be reduced to 1.99, 1.50, 1.99, respectively. The using temperature of the porous low-dielectric-constant materials with organic matrix can reach 450 ℃. The flexural strength of the porous low-dielectric-constant materials with inorganic matrix can reach 136 MPa. The introduction of cave into the materials leads to the decrease of mechanical properties and the increase of dielectric loss. The effort to get a low-dielectric-constant and improve the above properties can broaden the application scope of the porous materials．

A Web image retrieval method was proposed which combines textual terms extracted from Web documents and image contents in order to improve Web image retrieval. Web image contents were translated into image annotations by the improved automatic image annotation model. Then the technology of term similarity measurement, as the metric form of semantic information, was applied to weighting image annotations. These annotations and some terms extracted from Web documents were introduced into Web image retrieval under the framework of Bayesian inference network which has an inherent fusion capability of multiple information sources. Experimental results show that the method improves image retrieval to some extent by combining Web image contents and terms in Web documents．

Considering that research on vibratory stress relief (VSR) is limited in the low frequency ranges at present, the changing pattern of residual stress in the material under the condition of high-frequency-exciting was studied. Using the microcosmic dynamics theory, the relationship among particles inside the structural part was considered as a multiple-degree-of-freedom damping system, and the eliminating course of residual stress was analyzed when the part suffered from high-frequency resonance. Comparing the mode of the specimen at the higher frequency with the mode at the lower frequency, the effect of stress homogenization at the higher-frequency-exciting was presented. The feasibility of high frequency VSR was studied by the means of experimental methods, and the results of relieving and homogenizing residual stress were given under various exciting frequencies. The final results showed that high frequency VSR had good effects in relieving and homogenizing residual stress．

In view of the shortcomings of the network transmission and browser rendering in current BIM and GIS integration schemes, 3D Tiles in the GIS domain was chosen as the research object considering that it is more suitable to be loaded on webpages; the method was proposed to convert IFC to 3D Tiles for BIM models and to load BIM data quickly on Web; meanwhile, the integrated solution was analyzed to show BIM-GIS data massively on Web. The IFC data was taken as the starting point and splits BIM data according to the building component categories, and the geometry information and the semantic attributes were obtained. The geometry information file was converted by the intermediate format and finally encapsulated with the semantic attribute file to form 3D Tiles data with BIM semantic attributes. The coordinate conversion, data mapping, spatial index and levels of detail (LOD) hierarchical division are completed during the conversion process to ensure fast and efficient rendering interaction of BIM data and geographical feature data in the 3D WebGIS framework.

Shadow pixels in images can lead to the uncertainty of image content, which is harmful to computer vision tasks. Therefore, shadow detection is often used as a preprocessing step of computer vision algorithm. A shadow detection network was proposed by combining semantic information contained in input images and correlation between pixels. Pre-trained deep network ResNeXt101 was used as feature extraction front-end module to extract semantic information of the image. The baseline structure of the network was built to up-sample feature layers, encouraged by the design idea of U-Net. Non-local operations were added before the output layer to provide global information for each pixel and establish the relationship between pixels. At the same time, an attention generation module and an attention fusion module were developed to further improve shadow detection accuracy. Two common shadow detection datasets named SBU and UCF were utilized for verification. Experiment results showed that the proposed network outperformed previous methods in both visual effect and objective indicator. The proposed network showed 14.4% reduction on SBU and 14.9% reduction on UCF for the balance error rate, compared with the state-of-the-art framework.

A prediction method of rockmass parameters was proposed based on tunnelling process of tunnel boring machine (TBM) in order to solve the problem that the rockmass parameters of tunnel face was obtained difficultly in real time during TBM construction. The variation of tunnelling parameters in the TBM construction process was analyzed supported by water supply project from Songhua River in Jilin Province. A database was established which included the tunnelling parameters of TBM and rockmass parameters, and the correlation between the rockmass parameters and the tunnelling parameters of TBM was deduced. A new relational model between rockmass and TBM was constructed based on the stepwise regression algorithm and the clustering algorithm. The uniaxial compressive strength (UCS) of rock, volumetric joint count and surrounding rockmass classification were predicted by monitoring the tunnelling parameters of TBM. The rock parameters of tunnel face in the limestone and granite strata were predicted and compared with the actual values. Results indicated that the predicted UCS and volumetric joint count had an estimated maximum error of 18%, and the evaluated comprehensively surrounding rockmass classification accorded well with the actual state of rockmass, which verified the accuracy of the research results.