A FORMAL REPRESENTATION FOR FEATURE-BASED DESIGN

Feature based design has been regarded as a promising approach for CAD/CAM integration.This paper aims to establish a domain independent representation formalism for feature based design in three aspects: formal representation,design process model and design algorithm.The implementing scheme and formal description of feature taxonomy,feature operator,feature model validation and feature transformation are given in the paper.The feature based design process model suited for either sequencial or concurrent engineering is proposed and its application to product structural design and process plan design is presented. Some general design algorithms for developing feature based design system are also addressed.The proposed scheme provides a formal methodology elementary for feature based design system development and operation in a structural way.

Boost-Phase ballistic missile trajectory estimation with ground based radar

A conditional boost-phase trajectory estimation method based on ballistic missile （BM） information database and classification is developed to estimate and predict boos-phase BM trajectory. The main uncertain factors to describe BM dynamics equation are reduced to the control law of trajectory pitch angle in boost-phase. After the BM mass at the beginning of estimation, the BM attack angle and the modification of engine thrust denoting BM acceleration are modeled reasonably, the boost-phase BM trajectory estimation with ground based radar is well realized. The validity of this estimation method is testified by computer simulation with a typical example.

A Feature-Based Parametric Product Modeling System in CIMS Environment

This paper proposes an approach of developing the feature based parametric product modeling system which is suitable for integrated engineering design in CIMS environment.The architecture of ZD--MCADII and the characteristics of its each module are introduced in detail. ZD--MCADII’s product data is managed by an object--oriented database management system OSCAR, and the product model is built according to the standard STEP. The product design is established on a unified product model, and all the product data are globally associated in ZD--MCADII. ZD--MCADII provides various design features to facilitate the product design, and supports the integrity of CAD, CAPP and CAM.

Probabilistic analysis for the response of nonlinear base isolation system under the ground excitation induced by high dam flood discharge

According to theoretical analysis, a general characteristic of the ground vibration induced by high dam flood discharge is that the dominant frequency ranges over several narrow frequency bands, which is verified by observations from the Xiangjiaba Hydropower Station. Nonlinear base isolation is used to reduce the structure vibration under ground excitation and the advantage of the isolation application is that the low-frequency resonance problem does not need to be considered due to its excitation characteristics, which significantly facilitate the isolation design. In order to obtain the response probabilistic distribution of a nonlinear system, the state space split technique is modified. As only a few degrees of freedom are subjected to the random noise, the probabilistic distribution of the response without involving stochastic excitation is represented by the δ function. Then, the sampling property of the δ function is employed to reduce the dimension of the Fokker-Planck-Kolmogorov （FPK） equation and the low-dimensional FPK equation is solvable with existing methods. Numerical results indicate that the proposed approach is effective and accurate. Moreover, the response probabilistic distributions are more reasonable and scientific than the peak responses calculated by conventional time and frequency domain methods.

A Preliminary Global Analysis of Remotely Sensed Radiation Characteristics of Ground Features:Ⅱ. Result Discussion

Based on the L,B and V statistics of the 106 ground feature groups or the 769 ground feature class units in the world presented in the part I of the paper,the distribution of the world ground features on the axes of L,B and V,in the planes of L-B,L-V and B-V and in the space of L-B-V was discussed.And the typical numerical characteristics of the various ground features were also summarized.

Extended state observer-based control with an adjustable parameter for a large ground-based telescope

The high-precision requirements will always be constrained due to the complicated operating conditions of the ground-based telescope. Owing to various internal and external disturbances, it is necessary to study a control method, which should have a good ability on disturbance rejection and a good adaptability on system parameter variation. The traditional proportional-integral(PI) controller has the advantage of simple and easy adjustment, but it cannot deal with the disturbances well in different situations. This paper proposes a simplified active disturbance rejection control law, whose debugging is as simple as the PI controller, and with better disturbance rejection ability and parameter adaptability. It adopts a simplified second-order extended state observer(ESO) with an adjustable parameter to accommodate the significant variation of the inertia during the different design stages of the telescope. The gain parameter of the ESO can be adjusted online with a recursive least square estimating method once the system parameter has changed significantly. Thus, the ESO can estimate the total disturbances timely and the controller will compensate them accordingly. With the adjustable parameter of the ESO, the controller can always achieve better performance in different applications of the telescope. The simulation and experimental verification of the control law was conducted on a 1.2-meter ground based telescope. The results verify the necessity of adjusting the parameter of the ESO, and demonstrate better disturbance rejection ability in a large range of speed variations during the design stages of the telescope.

GENERATIVE CAPP APPROACH BASED ON RESOURCE MODEL AND FEATURE MODEL

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Feature Selection for Image Classification Based on a New Ranking Criterion

In this paper, a feature selection method combining the reliefF and SVM-RFE algorithm is proposed. This algorithm integrates the weight vector from the reliefF into SVM-RFE method. In this method, the reliefF filters out many noisy features in the first stage. Then the new ranking criterion based on SVM-RFE method is applied to obtain the final feature subset. The SVM classifier is used to evaluate the final image classification accuracy. Experimental results show that our proposed relief- SVM-RFE algorithm can achieve significant improvements for feature selection in image classification.

Long-term gravity changes in Chinese mainland from GRACE and ground-based gravity measurements

A long-term （9 years） gravity change in Chinese mainland is obtained on the basis of observation of the ground-based national gravity network. The result shows several features that may be related to sore, large-scale groundwater pumping in North China, glacier-water flow and storage in Tianshan region, and pre seismic gravity changes of the 2008 MsS. 0 Wenchuan earthquake, which are spatially similar to co-seismi, changes but reversed in sign. These features are also shown in the result of the satellite-based GRACE obser vation, after a height effect is corrected with GPS data.

Image block feature vectors based on a singular-value information metric and color-texture description

In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.

0-10 KM TEMPERATURE AND HUMIDITY PROFILES RETRIEVAL FROM GROUND-BASED MICROWAVE RADIOMETER

Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.

DIMENSION VARIATION OF FEATURE-BASED MODEL BY OPERATING DIRECTLY ON B-REP

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Study on the feature selection and classifica－tion effect of precursory data of ground tilt

Using the view point of nonlinear science and the method of selecting numerical features of pattern recognition for reference, the physical and numerical features of precursory ground tilt data are synthetically employed. The dynamic changes of data series are described with the numerical features in multi dimensional space and their distributive relations instead of an unique factor. The relationship between the ground tilt data and earthquake is examined through recognition and classification.

Seismic Response of Base-Isolated Structures underMulti-component Ground Motion Excitation

An analysis of a base-isolated structure for multi-component random ground motion is presented. The mean square respond of the system is Obtained under different parametric variations. The effectiveness of main parameters and the torsional component during an earthquake is quantified with the help of the response ratio and the root mean square response with and without base isolation. It is observed that the base isolation has considerable influence on the response and the effect of the torsional component is not ignored.

Feature-based and objectoriented product information model for welding structure

Product information model for welding structure plays an important role for the integration of welding CAD/CAPP/CAM. However, existing CAD modeling systems are not capable of providing enough information for subsequent manufacturing activities such as CAPP and CAM. A new design approach using feature technique and object oriented programming method is put forward in this paper in order to create the product information model of welding structure. With this approach, the product information model is able to effectively support computer aided welding process planning, fixturing, assembling, path planning of welding robot and other manufacturing activities. The feature classification and representing scheme of welding structure are discussed. A prototype system is developed based on feature and object oriented programming. Its structure and functions are given in detail.

Feature-Based Aggregation and Deep Reinforcement Learning:A Survey and Some New Implementations

In this paper we discuss policy iteration methods for approximate solution of a finite-state discounted Markov decision problem, with a focus on feature-based aggregation methods and their connection with deep reinforcement learning schemes. We introduce features of the states of the original problem, and we formulate a smaller "aggregate" Markov decision problem, whose states relate to the features. We discuss properties and possible implementations of this type of aggregation, including a new approach to approximate policy iteration. In this approach the policy improvement operation combines feature-based aggregation with feature construction using deep neural networks or other calculations. We argue that the cost function of a policy may be approximated much more accurately by the nonlinear function of the features provided by aggregation, than by the linear function of the features provided by neural networkbased reinforcement learning, thereby potentially leading to more effective policy improvement.

Seismic Responses of Asymmetric Base-Isolated Structures under Near-Fault Ground Motion

An inter-story shear model of asymmetric base-isolated structures incorporating deformation of each isolation bearing was built, and a method to simultaneously simulate bi-directional near-fault and far-field ground motions was proposed. A comparative study on the dynamic responses of asymmetric base-isolated structures under near-fault and far-field ground motions were conducted to investigate the effects of eccentricity in the isolation system and in the superstructures, the ratio of the uncoupled torsional to lateral frequency of the superstructure and the pulse period of near-fault ground motions on the nonlinear seismic response of asymmetric base-isolated structures. Numerical results show that eccentricity in the isolation system makes asymmetric base-isolated structure more sensitive to near-fault ground motions, and the pulse period of near-fault ground motions plays an import role in governing the seismic responses of asymmetric base-isolated structures.

Experimental validation of a signal-based approach for structural earthquake damage detection using fractal dimension of time frequency feature

This article extends a signal-based approach formerly proposed by the authors, which utilizes the fractal dimension of time frequency feature （FDTFF） of displacements, for earthquake damage detection of moment resist frame （MRF）, and validates the approach with shaking table tests. The time frequency feature （TFF） of the relative displacement at measured story is defined as the real part of the coefficients of the analytical wavelet transform. The fractal dimension （FD） is to quantify the TFF within the fundamental frequency band using box counting method. It is verified that the FDTFFs at all stories of the linear MRF are identical with the help of static condensation method and modal superposition principle, while the FDTFFs at the stories with localized nonlinearities due to damage will be different from those at the stories without nonlinearities using the reverse-path methodology. By comparing the FDTFFs of displacements at measured stories in a structure, the damage-induced nonlinearity of the structure under strong ground motion can be detected and localized. Finally shaking table experiments on a 1：8 scale sixteen-story three-bay steel MRF with added frictional dampers, which generate local nonlinearities, are conducted to validate the approach.

Fast Image Retrieval of Textile Industrial Accessory Based on Multi-Feature Fusion

A hierarchical retrieval scheme of the accessory image database is proposed based on textile industrial accessory contour feature and region feature. At first smallest enclosed rectangle[1] feature (degree of accessory coordination) is used to filter the image database to decouple the image search scope. After the accessory contour information and region information are extracted, the fusion multi-feature of the centroid distance Fourier descriptor and distance distribution histogram is adopted to finish image retrieval accurately. All the features above are invariable under translation, scaling and rotation. Results from the test on the image database including 1,000 accessory images demonstrate that the method is effective and practical with high accuracy and fast speed.

PRODUCT IMAGE RETRIEVAL BASED ON CO-FEATURES OF THE OBJECT

In this paper, we propose a product image retrieval method based on the object contour corners, image texture and color. The product image mainly highlights the object and its background is very simple. According to these characteristics, we represent the object using its contour, and detect the corners of contour to reduce the number of pixels. Every corner is described using its approximate curvature based on distance. In addition, the Block Difference of Inverse Probabilities (BDIP) and Block Variation of Local Correlation (BVLC) texture features and color moment are extracted from image's HIS color space. Finally, dynamic time warping method is used to match features with different length. In order to demonstrate the effect of the proposed method, we carry out experiments in Mi-crosoft product image database, and compare it with other feature descriptors. The retrieval precision and recall curves show that our method is feasible.