Advanced Materials Research Vols. 108-111

Abstract: Relevance Vector Machine (RVM) is a novel kernel method based on Sparse Bayesian, which has many advantages such as its kernel functions without the restriction of Mercer’s conditions, the relevance vectors automatically determined and fewer parameters. In view of the actual situation that the corresponding space curved surface which expressed the characteristics of pressure fluctuation is too complex to be analyzed, the RVM regression model for describing the characteristics which is nonlinear relationship among pressure fluctuation value，unit rotation and unit discharge is established，and it is applied to hydropower station. Comparing with Support Vector Machine (SVM), the experimental results show the final RVM model achieved is sparser, the prediction precision is higher and the prediction values are in better agreement with the real values.

Abstract: Since more power consumption results in more failures and degradations in system performance, reliability, and power bills, it has been a critical problem for not only large scale server system but also personal computers (PCs). Though much literature has focused on energy management and power budgeting for server systems, power consumption of PCs does not attain sufficient attentions fairly. In this paper an online power measurement and prediction framework is proposed and used to save more energy considering the PC as a whole controlled system. The framework includes parts such as power measurement unit, power prediction unit and a simple execution unit of power reduction decisions. A hardware-software joint prototype is implemented based on an intelligent digital multimeter. Experiments on a desktop PC and a laptop show that PC with the framework can save more power consumptions than that of the PCs without this framework.

Abstract: The voids in the mineral aggregate (VMA) is considered to be the most important mix design parameter which affects the durability of the asphalt concrete mix. This has traditionally been addressed during mix design by meeting a minimum voids in the mineral aggregate (VMA) requirement, based solely upon the nominal maximum aggregate size without regard to other significant aggregate-related properties. The goal of this study is to determine the validity of the minimum VMA requirement versus nominal maximum aggregate size required in Marshall volumetric mix design. Specimens were compacted using the Superpave Gyratory Compactor (SGC), conventionally tested for bulk and maximum theoretical specific gravities and physically tested using the thiaxial creep test system under a repeated load confined configuration to identify the transition state from sound to unsound. AC-20 was classified in the light of fine, dense and coarse gradation. The AC-20C, AC-20D and AC-20F asphalt mixtures were tested as the object of study. The results clearly demonstrate that the volumetric conditions of an VMA mixture at the stable unstable threshold are influenced by a composite measure of the aggregate size gradation .The currently defined VMA criterion, while significant, is seen to be insufficient by itself to correctly differentiate sound from unsound mixtures. Under current specifications, many otherwise sound mixtures are subject to rejection solely on the basis of failing to meet the VMA requirement. Based on the laboratory data and analysis, a new paradigm to volumetric mix design is proposed that explicitly accounts for aggregate gradation factors.

Abstract: In intelligent transportation systems (ITS) for urban highway-nets, the data of traffic flow is very important to control and lead to traffic. According to chromatic aberration between vehicles and road surfaces in images caught from moving vehicles, a new method is proposed to analyze on-line traffic states based on video detection technique. firstly video for 10 frame/second sampling, difference operation of same region of two neighbored image is used to detect moving vehicle very quickly on measurement strap; secondly the result of difference was grayed ,horizontal projection and adaptive threshold methods are adopted to recognize moving vehicle and type of vehicle by statistical analysis, which is very expedient, accurate and quick. The results of experiments show that the correct recognition rate of this system reaches up to 96%.And the combination of phase control of road control, which can intelligent lead to traffic by on-line and satisfies the requirements of practical application.

Abstract: In the event of a new version of financial markets, realistic counterfeit money, and only rely on manufacturers to upgrade the software in order to re-identify the class counter counterfeit money, proposed to establish a banknote counter self-learning system. The article mainly describes the specific implementation method of banknote counter being on line self-learning ability, through establishing feature vector template database of banknotes, using the template matching algorithm to identify genuine and fake of banknotes. Experiments show that the smart banknote counter designed in the method has self-learning abilities for fake banknotes, can implement specific anti-counterfeiting, being greatly increase accuracy of identification falsity.

Abstract: Series of large scaled model test has been carried out to examine the reinforcement mechanism of deep buried piles. Testing tools including rigid load cells, the earth pressure cells and data collecting systems are employed to measure the anti-thrust received by deep buried piles and the slope thrust of the slope on piles top. On the basis of the variation process of measured data, the time and the location of slide surface in the slope is determined, and the maximal anti-sliding force upward to the piles top could be gained by the data of earth pressure cells. Then the failure form process is analyzed with the anti-sliding length of the piles changed. The relationship between the sliding force received by the piles and that supplied by the slope on piles top is analyzed to supply scientific demonstration for the design method of slope reinforced by the deeply buried piles.

Abstract: Image fusion has become an important and powerful technique for image analysis and computer vision. This paper presents a novel multiresolution image fusion method, which is based on wavelet transform combing with an effective fusion scheme. The main contribution of this research is that by considering the physical meaning of the wavelet coefficients, a selection scheme that treats the coefficients in different ways is proposed. This scheme selects the coefficients in the high frequency bands by a wavelet entropy based strategy, while selects the coefficients in the low frequency band by a variance based strategy. The performance of the proposed fusion method is compared with several existing fusion techniques. Comparison results show that the proposed method can effectively fuse the images with less error.

Abstract: The implementation and application of manufacturing execution system (MES) is an important way to improve the management level and realize information management for automobile parts manufacturing enterprises. System selection is the basis and prerequisite for MES implementation. Analytic hierarchy process (AHP) is applied in MES system selection in this paper based on the analysis of the MES system selection decision-making problem for automobile parts manufacturing enterprises. Firstly, the MES system selection decision indicators are established from the aspects of system technology performance, system suitability, quality of services and input-output of the MES system. On the basis, three solutions for MES system is analyzed and evaluated by AHP approach. The study of this paper provided a feasible solution for MES system selection decision-making.

Abstract: With the increase in the size of government investment projects, an increasing number of uncertain factors are involved and the risks are increasingly complex, the project risks can accurately describe and measure the project will directly affect the investment decision-making and project management. To this end, respectively, analyze two-dimensional method and multi-dimensional method and Put forward a three-dimensional description method, describing project risk thoroughly from the probability, losses as well as manageability. On this basis the risk function is established, and finally an example is given. The results showed that three-dimensional structure not only take into account both qualitative and quantitative, at the same time taking into account the subjectivity and objectivity of risk, a more accurate reflection of the true face of government investment project risk.

Abstract: A method for parameterized modeling for 3D animation role was proposed. Feature parameters are determined according to anthropometrical approach and theory. Combined axial deformation technique in computer graphics, modeling system that is realized in this study provides very intuitive input interface. Additionally, this method also has the advantage of simple operation and quick modeling.