Unified automotive safety technology is the tendency of developing automotive safety technologies. The occupant protection performance of conventional automotive passive safety technology can be further improved by cooperating with active sensors such as millimeter-wave radars and cameras. The view of interest in automotive passive safety technology is nearer than that in active safety technology. A calibration method for radars and cameras was developed using vehicle longitudinal symmetry plane as a datum to more accurately detect and locate in automotive passive safety application. Calibration parameters were obtained, with the coordinate transformation relationship between the two sensors being developed. Validation tests show that the radar and the camera in this method have good measurement accuracy, and the target location can be transformed into picture coordinate accurately. This method can provide reliable data for automotive safety systems.

With the development of finite element method, finite element models become commonly used in the research of automotive safety with debugging and calibrating having great influence on the output accuracy of a finite element model. 14 pedestrian headform impact experiments were made to study the major factors that affect the output of an FE model, with the corresponding FE model being built. During the calibration of the FE model, some methods for FE model structure building have been used, with the sensitive parameters debugging, which leads to the conclusions about effective means for calibration and the sensitive parameters that should be controlled accurately in the FE modeling.

A bionic tube composed of bionic joints, bionic units and bionic inner tubes was developed based on the bamboo structure to improve the crashworthiness and the energy absorption of thin walled tube resistance structures. The finite element method was used to simulate the axial impact with the response surface method used to obtain the optimal structure of the bionic energy-absorbing tube. The results show that the optimal structure of the bionic tube has a thickness of 1mm for the bionic units and a thickness of 0.628mm for the bionic inner tubes, with the specific energy absorption being 157.57kN and 34.33kJ/kg, respectively. These studies provide new methods and ideas for improving crashworthiness energy absorption of thin-walled structures.

Cr-Mo low alloy heat-resistant steel has been widely used in energy, chemicals and other large equipment manufacturing industries by welding. The strength, toughness, creep properties of welding joints are of very strict requirement. But the welding joint consists of the welding metal, fusion, zone, harden area of based metal, and soft zone with significant differences in chemical composition, organization, and performance, with the mechanical behavior of the welding joint showing obvious differences with homogeneous materials, so tests are needed to find the weak links of the welding joint, which can reflect the mechanics characteristics of different zones at the same time. In this paper, a three-point bending test including different zones was made on the narrow-gap multi path/multi layer welding joints of the typical 2.25Cr-1Mo steel, with the secondary crack found near the fusion zone. The fracture surface observation, optical observation, micro-hardness test and numerical simulation were carried out to study what causes the secondary crack. The results show that the fusion zone has some soft ferrites, and the coarse grain zone has some harden martensites, with non-uniform hardness found near the secondary crack. The results of finite-element analysis reveal that stress concentration exists at the boundary with non-uniform hardness, which leads to the secondary crack in the fused zone. The results has are of significance to adjust the matched types of welding joints and the welding technology.

Industrial application needs mesocarbon microbeads (MCMB) with even particle size distribution and good sphericity, while the reaction conditions and raw material property may influence the MCMB property stated above. MCMB was prepared by thermal polymerization with coal tar pitch as the raw material, with the effects of reaction conditions i.e., the temperature, time and pressure, as well as raw material properties including the soft point and quinolone-insoluble (QI) on the particle size distribution and appearance of MCMB being investigated. The results show that within a certain range, the increase of the reaction temperature or reaction time during thermal polymerization helps the grow of MCMB, and the particle size distribution becomes more narrow with granularity becoming homogeneous. Too low pressure makes the light components of the reaction system escape and the system viscosity quickly increase, which is not conducive to gain the spherical appearance. Low soft points of raw materials and small viscosities of the reaction system are helpful for the free motion and fusion of the microbeads growing to MCMB with even particle sizes. The primary QI in the raw material is the core for the formation and growth of MCMB, and if the particle sizes of the primary QI are too different, the size of MCMB will become uneven with MCMB polarized. The MCMB with even particle sizes can be obtained by removing the QI with too large particle sizes in the raw material.

Natural gas is green and efficient energy which is widely used in industrial production and daily life. Daily gas load forecasting is helpful for scientifically and rationally supplying. Therefore, the forecasting results are beneficial to practical work. A forecasting model for daily gas loads was developed based on support vector machine theory. The gas load data of a North-China city were taken as a sample to verify the forecasting accuracy, with the main factors that affect the daily gas load as well as their effects on model accuracies being discussed. Several data normalization methods were used with the forecasting accuracy based on normalization methods analyzed. The developed model performs well with the error less than 5% for the through-year data, and less than 2% for the heating period data. The discussion about forecasting accuracies in this paper may be helpful for similar problems.

This study analyzes the reasons for the low reusability of current HLA federates and extends the RTI framework to improve the federate reusability. The extension framework is implemented by adding a self-adapting middle mapping layer to the standard HLA/RTI framework to manage the mapping between the fixed SOM of the federate and the FOM of the federation for various reuse scenarios. The key to the mapping layer is the construction of the mapping model. This paper presents a meta-model for the message mapping operator which can dynamically construct the mapping model. The extension of the RTI framework with the self-adapting middle mapping layer effectively promotes the federate reusability, so a former federate can join a new federation and run correctly. Tests show that this extension framework is feasible and effective.

3-D scanned face registration is the foundation and the prerequisite for 3-D faces statistical learning. To solve the problem of registering these digital points accurately, a 3-D faces registration method was developed using a non-rigid iterative closet point (ICP) algorithm combined with elastic deformation. By using the sparse 3-D feature vertices, the method fits high-resolution 3-D template meshes (3-D template faces) to 3-D face range scans (3-D target faces) through deformations step by step. This deformation process can be formulated as an optimization problem for the affine transformation at each vertex of the template face. In addition, this algorithm accelerates the registration process without sacrificing the registration accuracy by introducing elastic deformation. On this basis, a head missing data completion method for 3-D faces, combining the elastic deformation and the proposed 3-D registration, was developed to enhance the reality and the completeness of the 3-D face models. The experimental results show that this method is more robust than a widely used face completion method.

How to automatically generate linguistic descriptions of spatial relations between spatial objects in image or video is one of the important tasks in linguistic scene description and image understanding. This paper presents the concept and the representation of detail spatial relations, and proposes the linguistic description method of detail spatial relations under different reference frames to solve the problem that the past linguistic descriptions methods of spatial relations only consider the overall spatial relations. Excellent experimental results from synthetic image examples show that the linguistic descriptions of detail spatial relations are consistent with human cognition and description habits.

A hybrid prediction model was established to implement the time series forecasting of traffic accident statistical index based on the ARIMA model and the SVR model. The ARIMA model was used to complete the linear fitting of original time series, with the residual error of the ARIMA model then transformed into fuzzy information granulation particles made up of Low, R and Up. An SVR model was developed to describe the seasonal trend of the residual error with Low, R and Up as input. The predicted value of the ARIMA model was fixed based on the SVR regression result of the seasonal residual error, with the predicted value of the hybrid model being calculated. Empirical research results show that the accuracy of the hybrid model is higher than that of the single ARIMA model and that the seasonal trends of empirical time series are precisely represented by fuzzy information granulation particles.

In the support vector machine (SVM) method, the membership function has a vital infection on the classification of samples. Due to the limitation of the function own condition, this method cannot effectively distinguish the noise and outliers samples. A fuzzy support vector machine (FSVM) was developed based on the dual membership method to solve the problem. The method uses the characteristics of a specifically medical image to map the membership function which has been obtained from the method of degree membership to two different sides, mapping the membership function to obtain the membership function which can more effectively analyze the specific sample. The improved fuzzy support vector method was used to classify benign and malignant of the pulmonary nodule. The parameters inversion shows that the developed method distinguishes the noise and outlier samples more effectively, compared with the traditional fuzzy support vector machine method, and solves the over-fitting problem of traditional methods. Therefore, the results illustrate the robustness to anti-noise property and the effective classification ability of the developed method.

In this paper, a recommender method based on data was developed, which includes friend recommender and application recommender. According to the friend relationship and interaction behavior, a trust computing method was proposed, with a more authentic social network then constructed with the obtained trust. The cohesive subgroup and existing friend information was employed to divide the constructed social network. Based on the work mentioned above, an improved friend recommender and application method was proposed with the similarity of users in the community being differentiated with the similarity of the user out of the community. The improved method can obtain more nearest neighbors and enhance the accuracy of friend recommender and application recommender.

Based on the cooperative game theory, this paper analyzes the demand characteristics of port logistics chain cloud service network, and describes the process of formation of the port logistics chain cloud service network through fair bidding and tendering. The logistics chain cloud service organization strategy was designed including public cloud centralized decision with private cloud compensation designed, which guarantees the benefit equilibrium of port logistics chain members. The multiple agent parallel computing framework was established for port logistics chain cloud service, with the stable and efficient cloud genetic algorithm applied to the implementation process of logistics chain resource selection and collaborative computation. A test example shows that the designed model and algorithm have more effective operability, and can be taken as a reference for port logistics chain's cloud service organization.

On the basis of the estimated urban residents' preference parameters for different urban public services from Hedonic housing price analysis, a construction method for public service quality integrated index was proposed and applied to supply-demand matching analysis of public services in Beijing. Single indexes of three typical urban public services were measured using the potential model, with estimated parameters of urban residents' preferences then obtained based on a large sample of households and their housing price information from 2010 Beijing Urban Household Survey. An integrated quality index of Beijing public services was constructed and compared with resident population density, focusing on the supply and demand matching analysis for 129 streets in downtown Beijing. The results show that the outside region, south area and streets with dense population of Beijing are suffering from serious problem of inadequate supply of public services. The supply-demand matching indices of 87% streets in the south area (45 out of 52) are lower than the average (9.05), and only 5 streets out of the most densely populated 17 streets (more than 30 000 people/km²) have larger matching indices than the average.

IPO (initial public offerings) overpricing has become an important phenomenon in current Chinese stock market. The concept of pricing deviation ratio was introduced to measure IPO pricing efficiency. The data of A-share IPOs from 2005 to 2011 were used to examine how shareholders' characteristics affect the IPO pricing efficiency. Analyses show that foreign ownership is associated with higher IPO pricing efficiency, with state ownership and venture capital ownership being associated with lower IPO pricing efficiency. The results also show that the IPO pricing efficiency is positively correlated with the founder ownership and the ownership that directors on the board hold. Further analysis indicates that the IPO pricing efficiency reduction caused by the state ownership comes from the conservative pricing strategy, while VC backed companies' pricing strategy is more aggressive. The IPO pricing efficiency is examined from the perspective of ownerships' characteristics in this paper, which provides a new way to understand and enhance the IPO pricing efficiency in China.

In China, one of the main purposes of the reform in October 2010 is to reduce the price earnings ratio of initial public offerings (IPO) in small- and medium-sized board and second board market according to totally market-oriented rules, however the effect is not obvious. Focusing on this problem, the authors found that the IPO price earnings ratio stays high while relative inquiries tend to be rationalized after the reform. Therefore, two models were developed i.e., the return analysis model of participation in IPO allocation and the simulation analysis model of relationship between the over-subscription rate and IPO price earnings ratio. Analyses show that the regulation reasons resulting in the high IPO price lie in the insufficiency of inquiry restrictions and the deficiency of pricing restrictions on the basis of the two models. Reform methods are elaborated to strengthen inquiry restrictions by increasing inquiry institutions' cost of quoting high price and pricing ones by increasing managing underwriters' risks resulting from the high IPO price earnings ratio.

The popularity of social networks puts forward new challenges on the user's privacy protection. In this paper, the methods of human dynamics and statistical physics were used to study the relationship of user's network behaviors and user's privacy value. Current domestic popular social networking sites, Renren and Sina Weibo, were used as the research objects, with the user's actual data then obtained and a privacy quantitative model proposed. The results show that the user's behaviors on the network have an important impact on the value of privacy. Renren's sharing behavior in the user's geographic location has great impact on privacy, while Sina microblogging sending private messages has the greatest impact on the value of privacy. Conclusions of this study have theoretical and practical significance.