工程项目快速投标报价系统与测标模型的研究

结合工程实际，建立具有模糊辩识功能的工程项目快速投标报价系统和测算模型，并对影响投标报价的主要因素作不确定性分析．

Adaptive moving target detection algorithm based on Gaussian mixture model

In order to enhance the reliability of the moving target detection, an adaptive moving target detection algorithm based on the Gaussian mixture model is proposed. This algorithm employs Gaussian mixture distributions in modeling the background of each pixel. As a result, the number of Gaussian distributions is not fixed but adaptively changes with the change of the pixel value frequency. The pixels of the difference image are divided into two parts according to their values. Then the two parts are separately segmented by the adaptive threshold, and finally the foreground image is obtained. The shadow elimination method based on morphological reconstruction is introduced to improve the performance of foreground image＇s segmentation. Experimental results show that the proposed algorithm can quickly and accurately build the background model and it is more robust in different real scenes.

Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks

The distributed passive measurement is an important technology for networkbehavior research. To achieve a consistent measurement, the same packets should be sampled atdistributed measurement points. And in order to estimate the character of traffic statistics, thetraffic sample should be random in statistics. A distributed samplingmask measurement model isintroduced to tackle the difficulty of measuring the full trace of high-speed networks. The keypoint of the model is to choose some bits that are suitable to be sampling mask. In the paper, thebit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we findthat the 16 bits of identification field in IP packet header are fit to the matching field ofsampling mask. Measurement traffic also can be used to analyze the statistical character ofmeasurement sample and the randomicity of the model. At the same time the experiment resultsindicate that the model has a good sampling performance.

Stationarity Intervals of Time-Variant Channel in High Speed Railway Scenario

The non-stationary behavior, caused by the train rmverrent, is the rmin factor for the variation of high speed railway channel. To measure the tirce-variant effect, the parameter of stationarity interval, in which the channel keeps constant or has no great change, is adopted based on Zhengzfiou- Xi＇an （Zhengxi） passenger dedicated line measurement with different train speeds. The stationarity interval is calculated through the definition of Local Region of Stationarity （LRS） under three train ve- locities. Furthermore, the time non-stationary characteristic of high speed pared with five standard railway channel is corn- Multiple-Input MultipleOutput （MIMO） channel models, i.e. Spatial Channel Model （SCM）, extended version of SCM （SCME）, Wireless World Initiative New Radio Phase II （WINNERII）, International Mobile Teleconmnications-Advanced （IMT-Advanced） and WiMAX models which contain the high speed moving scenario. The stationarity interval of real channel is 9 ms in 80% of the cases, which is shorter than those of the standard models. Hence the real channel of high speed railway changes more rapidly. The stationarity intervals of standard models are different due to different modeling methods and scenario def- initions. And the compared results are instructive for wireless system design in high speed railway.

Acoustic emission activity in directly tensile test on marble specimens and its tensile damage constitutive model

For understanding acoustic emission （AE） activity and accumulation of micro-damage inside rock under pure tensile state, the AE signals has been monitored on the test of directly tension on two kinds of marble specimens. A tensile constitutive model was proposed with the damage factor calculated by AE energy rate. The tensile strength of marble was discrete obviously and was sensitive to the inside microdefects and grain composition. With increasing of loading, the tensile stress-strain curve obviously showed nonlinear with the tensile tangent modulus decreasing. In repeated loading cycle, the tensile elastic modulus was less than that in the previous loading cycle because of the generation of micro damage during the prior loading. It means the linear weakening occurring in the specimens. The AE activity was corresponding with occurrence of nonlinear deformation. In the initial loading stage which only elastic deformation happened on the specimens, there were few AE events occurred; while when the nonlinear deformation happened with increasing of loading, lots of AE events were generated. The quantity and energy of AE events were proportionally related to the variation of tensile tangent modulus. The Kaiser effect of AE activity could be clearly observed in tensile cycle loading. Based on the theory of damage mechanics, the damage factor was defined by AE energy rate and the tensile damage constitutive model was proposed which only needed two property constants. The theoretical stress-strain curve was well fitted with the curve plotted with tested datum and the two property constants were easily gotten by the laboratory testing.

SMC-PHD based multi-target track-before-detect with nonstandard point observations model

Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method was proposed to tackle this issue using a nonstandard point observation model. The method was developed from sequential Monte Carlo(SMC)-based probability hypothesis density(PHD) filter, and it was implemented by modifying the original calculation in update weights of the particles and by adopting an adaptive particle sampling strategy. To efficiently execute the SMC-PHD based TBD method, a fast implementation approach was also presented by partitioning the particles into multiple subsets according to their position coordinates in 2D resolution cells of the sensor. Simulation results show the effectiveness of the proposed method for time-varying multi-target tracking using raw observation data.

Evaluation of wind vectors observed by HY-2A scatterometer using ocean buoy observations,ASCAT measurements,and numerical model data

The first Chinese microwave ocean environment satellite HY-2A was launched successfully in August, 201 I. This study presents a quality assessment of HY-2A scatterometer （HYSCAT） data based on comparison with ocean buoy data, the Advanced Scatterometer （ASCAT） data, and numerical model data from the National Centers for Environmental Prediction （NCEP）. The in-situ observations include those from buoy arrays operated by the National Data Buoy Center （NDBC） and Tropical Atmosphere Ocean （TAO） project. Only buoys located offshore and in deep water were analyzed. The temporal and spatial collocation windows between HYSCAT data and buoy observations were 30 min and 25 km, respectively. The comparisons showed that the wind speeds and directions observed by HYSCAT agree well with the buoy data. The root-mean-squared errors （RMSEs） of wind speed and direction for the HYSCAT standard wind products are 1.90 m/s and 22.80°, respectively. For the HYSCAT-ASCAT comparison, the temporal and spatial differences were limited to 1 h and 25 km, respectively. This comparison yielded RMSEs of 1.68 m/s for wind speed and 19.1° for wind direction. We also compared HYSCAT winds with reanalysis data from NCEP. The results show that the RMSEs of wind speed and direction are 2.6 m/s and 26°, respectively. The global distribution of wind speed residuals （HYSCAT-NCEP） is also presented here for evaluation of the HYSCAT-retrieved wind field globally. Considering the large temporal and spatial differences of the collocated data, it is concluded that the HYSCAT-retrieved wind speed and direction met the mission requirements, which were 2 rn/s and 20° for wind speeds in the range 2-24 m/s. These encouraging assessment results show that the wind data obtained from HYSCAT will be useful for the scientific community.

An estimation of the penetration rate of rotary drills using the Specific Rock Mass Drillability index

The main purpose of the present study was to provide a practical, convenient drillability prediction model based on rock mass characteristics, geological sampling from blast holes, and drill operational factors. Empirical equations that predict drill penetration rate have been developed using statistical analyses of data from the Sarcheshmeh Copper Mine. Seven parameters of the rock or rock mass, including uniaxial compressive strength （UCS） of the rock, Schmidt hammer hardness value, quartz content, fragment size （dso）, alteration, and joint dip, are included in the model along with two operational parameters of the rotary drill, bit rotational speed and thrust. These parameters were used to predict values of the newly developed Specific Rock Mass Drillability （SRMD） index. Comparing measured SRMD values to those pre- dicted by the multi-parameter linear, or nonlinear, regression models showed good agreement. The cor- relation coefficients were 0.82 and 0.81. resoectively.

Maneuvering target track-before-detect via multiple-model Bernoulli particle filter

Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo(particle) technique. Target detection was accomplished through the estimation of target's existence probability, and the estimate of target state was obtained by combining the outputs of modeldependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter.

Integrating unascertained measurement and information entropy theory to assess blastability of rock mass

Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.

Measuring the influences of supplier selection and supply chain tasks on firm performance among manufacturing firms in India

The primary objective of this research is to empirically probe the various aspects and variables that have been already addressed in the previous literature related to supplier selection criterion, supply effort management and firm performance. Further, this research aims to develop a measurement framework and pragmatically prove the framework through a measurement model. First, a factor structure for various constructs is made and the initial validity is determined from practicing managers and academicians. This research employs survey method and the data is collected from 358 supply chain professionals working in manufacturing firms in India. A measurement model is developed and proved with various tests of reliability and validity. Finally, three major latent constructs were formulated, namely, criterion of supplier selection, supply effort management and firm performance. The factor scores of these latent variables were used for further analysis. A six-stage approach was followed in the analysis of data. Firm performance was regressed against supplier selection criterion and supply effort management. The results indicate that the predictive variable has positive and significant effect on firm performance and they do not have any interaction and multicollinearity effects.

Moving object detection method based on complementary multi resolution background models

A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models were used.The ghost and real static object could be classified by comparing the similarity of the edge images further.In each group,the multi resolution Gaussian mixture models were used and dual thresholds were applied in every resolution in order to get a complete object mask without much noise.The computational color model was also used to depress illustration variations and light shadows.The proposed method was verified by the public test sequences provided by the IEEE Change Detection Workshop and compared with three state-of-the-art methods.Experimental results demonstrate that the proposed method is better than others for all of the evaluation parameters in intermittent object motion sequences.Four and two in the seven evaluation parameters are better than the others in thermal and dynamic background sequences,respectively.The proposed method shows a relatively good performance,especially for the intermittent object motion sequences.

Estimation Methodology of Short-term Natural Rubber Price Forecasting Models

This study developed a short-term econometric model of world natural rubber price Standard Malaysia Rubber Grade 20 （SMR20）. Both single and simultaneous equations were utilized using monthly data from January 1990-December 2008 as estimation period and data from January 2009-June 2009 was used as an ex-ante forecast. The data were tested for unit root and Vector Error Correction and co-integration method was used to estimate the parameters of the model. The models specifications were developed in order to discover the inter-relationships between NR production, consumption and prices of SMR20 and to determine forecast price of SMR20. Comparative analysis between the single-equation specification and simultaneous supply-demand and price equation were made in terms of their estimation accuracy based on RMSE, MAE and （U-Thile） criteria. Ex-ante forecasts was carried out for the period of January 2009-June 2009. The results revealed that the values of the RMSE, MAE and U of simultaneous supply-demand and price equations model were comparatively smaller than the values generated by the single-equation model. These statistics suggest that the simultaneous equation of supply-demand and price model is more accurate and efficient measure in terms of its statistical criteria than the single-equation model in predicting the price of SMR20 in the next 6 months.

Associated ZH and WH Production in Left-Right Twin Higgs Model at LHC

At the CERN large hadron collider （LHC）, production of the Higgs boson in association with Z or W bosons provides a dramatic experimental signal for detecting the standard model （SM） Higgs boson. In this paper, we consider the contributions of the left-right twin Higgs （LRTH） model to the processes qq＇ --~ Z（W）H. Our numerical results show that, in the favorable parameter spaces, the cross sections deviate distinctly from the predictions of the SM. The possible signals of the LRTH model can be detected via these processes at the LHC experiments.

A metrics suite for coupling measurement of software architecture

To better evaluate the quality of software architecture,a metrics suite is proposed to measure the coupling of software architecture models,in which CBC is used to measure the coupling between components,CBCC is used to measure the coupling of transferring message between components,CBCCT is used to measure the coupling of software architecture,WCBCC is used to measure the coupling of transferring message with weight between components,and WCBCCT is used to measure the coupling of message transmission with weight in the whole software architecture. The proposed algorithm for the coupling metrics is applied to the design of serve software architecture. Analysis of an example validates the feasibility of this metrics suite.

Enhancing pose accuracy of space robot by improved differential evolution

Due to the intense vibration durirLg launching and rigorous orbital temperature environment, the kinematic parameters of space robot may be largely deviated from their nominal parameters. The disparity will cause the real pose （including position and orientation） of the end effector not to match the desired one, and further hinder the space robot from performing the scheduled mission. To improve pose accuracy of space robot, a new self-calibration method using the distance measurement provided by a laser-ranger fixed on the end-effector is proposed. A distance-measurement model of the space robot is built according to the distance from the starting point of the laser beam to the intersection point at the declining plane. Based on the model, the cost function about the pose error is derived. The kinematic calibration is transferred to a non-linear system optimization problem, which is solved by the improved differential evolution （DE） algoritlun. A six-degree of freedom （6-DOF） robot is used as a practical simulation example, and the simulation results show： 1） A significant improvement of pose accuracy of space robot can be obtained by distance measurement only; 2） Search efficiency is increased by improved DE; 3） More calibration configurations may make calibration results better.

Characterization of Water Production and Its Implication to Forest Management

Nowadays, forests are being managed for multiple uses. The basic requirement of multiple use forestry is to identify and quantify forest values and to determine management objectives. The priorities of management objectives, however, must be decided. In this study, a model predicting water production for multi-objective forest management was developed. The model was based on data from permanent sample plots. The data were gathered from 132 sample plots. Approximately 80% of the observations were used for model development and 20% for validation. The model was designed for even-aged forests, as well as for forests with mixed and pure species composition. The explicatory variable in the model was number of trees. All parameter estimates were found highly significant （P 〈 0.001） in predicting water production. The model fit and validation tests were fairly good. The water production model presented in this study was considered to have an appropriate level of reliability. planning, but, it should be limited to the conditions for which the data It can be used in the overall multi-objective forest management were gathered.

Measuring Effectiveness of COCOMO I and COCOMO II Using a Case Study

There are several software estimation models such as Line of Code, Function Point and COnstructive COst MOdel （COCOMO）. The original COCOMO model is one of the most widely practiced and popular among the software development community because of its flexible usage. It is a suite of models i.e., COnstructive Cost MOdel I and COnstructive Cost MOdel II. in this paper, we are evaluating the both models, to find out the level of efficiency they present and how they can be tailored to the needs of modem software development projects. We are applying COCOMO models on a case study of an e-commerce application that is built using Hyper Text Markup Language （HTML） and JavaScript. We will also shed light on the different components of each model, and how their Cost Drivers effect on the accuracy of cost estimations for software development projects.

Path-Following Based on Nonlinear Model Predictive Control with Adaptive Path Preview

This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.

Study on the onset temperature of a standing-wave thermoacoustic engine based on circuit network theory

Onset mechanism is one of the most fundamental issues in thermoacoustic field.However,the onset conditions and the phenomena happening in the onset process have not been well explained theoretically.In this paper,a novel model based on the circuit network analogy is proposed to predict the onset temperature of a standing-wave thermoacoustic engine.The activity and instability criteria are proposed to be the onset criteria in the model.The influences of the porosity of the heat exchanger and the stack,and the length of the resonant tube on the onset temperature are analyzed.The calculated results are in agreement with the experimental results,which indicates that the activity and instability criteria can be used to predict the onset conditions of a thermoacoustic engine.