Visual Modflow在和田县农业经济新区地下水资源评价中的应用

为全面了解地下水系统受各种激励因素影响后的水动力场和地下水量变化规律,以及为当地地下水资源开发与利用提供科学的指导意见,本次在和田县农业经济新区地下水资源评价中采用可视化标准软件Visnal Modflow实现地下水资源的模拟与预报,通过构建三维非稳定流数值模型,使用迭代方法求解,并根据设计开采量对地下水水位变动做出预测,再基于建模预测结果,结合经济新区地下水资源量确定合理的地下水开采量。

Vehicle Detection Based on Visual Saliency and Deep Sparse Convolution Hierarchical Model

Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification.These types of methods generally have high processing times and low vehicle detection performance.To address this issue,a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed.A visual saliency calculation is firstly used to generate a small vehicle candidate area.The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection.The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group,which outperforms the existing state-of-the-art algorithms.More importantly,high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.

DATA MODEL AND VISUALIZATION OF 3D CITY LANDSCAPE BASED ON INTEGRATED DATABASES

Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.

3D visualization model and key techniques for digital mine

Digital mine is the inevitable outcome of the information processing, and is also a complicated system engineering. Firstly, for the 3D visualization application of the digital mine, the ground and underground integrative visualization framework model was proposed based on the mine entity database. So, the visualization problem was availably resolved, as well as the professional analytical ability was improved. Secondly, aiming at the irregularities, non-uniformity, dynamics of mine entities, mix modeling method based on the entity character was put forward, in which 3D expression of mine entities was realized. Lastly, the 3D visualization project for a copper mine was experimentally studied. Satisfactory results were acquired, and the rationality of visualization model and feasibility of 3D modeling were validated.

A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

Modeling Tracer Flow Characteristics in Different Types of Pores: Visualization and Mathematical Modeling

Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tracer transport,this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport.The visualization results show a faster tracer movement into movable water than it into bound water,and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity.Moreover,the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression.The new model also distinguishes flowing and storage pores,accounting for different tracer transport mechanisms(dispersion,diffusion and adsorption)in different types of pores.The resulting analytical solution better matches with tracer production data than the standard model.The residual sum of squares(RSS)from the new model is 0.0005,which is 100 times smaller than the RSS from the standard model.The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope,whereas the superficial velocity and bound water saturation show a positive correlation.

Experimental investigation on migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats using multidimensional visualized models

Knowledge of migration and retention mechanisms of elastic gel particles(EGPs)in pore-throats is essential for the effective application of EGPs as a smart sweep improvement and profile control agent for enhanced oil recovery(EOR).The matching coefficient(defined as the ratio of particle size to pore-throat size)is used to investigate its influence on migration,retention and profile control performance of EGPs.A 1-D continuous pore-throat visualization model(PTVM),a 2-D heterogeneous PTVM and a 3-D heterogeneous core model were constructed and used to investigate pore-scale migration,retention and controlling mechanism of migration and retention characteristics on EGPs profile control.The results of the 1-D continuous PTVM indicated that while the matching coefficient was in the optimal range(i.e.,0.20-0.32),the EGPs could not only smoothly migrate to the deeper pore-throats,but also form stable retention in the pores to resist the erosion of injected water,which was conducive to the effective indepth profile control.The results of the 2-D heterogeneous PTVM verified that the sweep efficiency in low-permeability regions could be significantly improved by in-depth migration and stable retention of EGPs in the pore-throats with an optimal matching coefficient(0.29),which was much better than that in cases with a smaller matching coefficient(0.17)or an excessive matching coefficient(0.39).Moreover,the NMR displacement experiments of 3-D heterogeneous cores were carried out to simulate the EGPs profile control in actual reservoir porous media.Saturation images and T2 spectrum curves of crude oil showed that EOR in the low-permeability layer was highest(56.1%)using EGPs profile control with an optimal matching coefficient,attributing to the in-depth migration and stable retention of EGPs.

Optimized Modeling Method for Unbalanced Data in High-Level Visual Semantic Concept Classification

To solve the unbalanced data problems of learning models for semantic concepts, an optimized modeling method based on the posterior probability support vector machine （PPSVM） is presented. A neighborbased posterior probability estimator for visual concepts is provided. The proposed method has been applied in a high-level visual semantic concept classification system and the experiment results show that it results in enhanced performance over the baseline SVM models, as well as in improved robustness with respect to high-level visual semantic concept classification.

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.

Traffic danger detection by visual attention model of sparse sampling

A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.

Visualized Analysis Model for Hadoop Business Data

With the social development, we are stepping into an information technology world. In such a world, our life is getting more and more diversified and rich because of e-business. E-business not only provides us convenience but also large amounts of business data. However, how shall we better store, manage and use these business data has become a major field being studied by e-business. With the rapid growth of data volume, the relational database system cannot meet the requirements of the current status. In this paper, focusing on the visualized analysis model of Hadoop business data, it analyzed the business data in terms of the visualized platform, database and analysis model etc. Depending on the analysis, offline-data analysis and data visualization for Hive database will be greatly improved, so that references and suggestions can be provided for the visualized analysis model of Hadoop business data.

From neurogenesis to neuronal regeneration: the amphibian olfactory system as a model to visualize neuronal development in vivo

How do individual neurons develop and how are they in- tegrated into neuronal circuitry？ To answer this question is essential to understand how the nervous system develops and how it is maintained during the adult life. A neural stem cell must go through several stages of maturation, including proliferation, migration, differentiation, and integration, to become fully embedded to an existing neuronal circuit. The knowledge on this topic so far has come mainly from cell culture studies. Studying the development of individual neurons within intact neuronal networks in vivo is inherently difficult. Most neurons are generated form neural stem cells during embryonic and early postnatal development.

Geometrical Modeling by NURBS Surface and RCS Computing by Visualization for Complex Targets

A novel approach to compute the high frequency radar cross-section (RCS) of complex targets is described in this paper.From the three views or the sectional views of the target, target is geometrically modeled by non-uniform rational B-spline (NURBS) parametric surfaces using the software CNFEOV developed by oneself which constructs NURBS representation of complex target from engineering orthographic views. RCS is obtained through PO, PTD, MEC and IBC techniques. When calculating RCS of the target, it is necessary to get the unit normal vector to surface illumi- nated by radar and the value Z which is the distance from the point on the surface to radar. ln this novel approach, the unit normal vector to the surface can be obtained either by the Phong rendering model, in which the color components (RGB) of every pixel on the image are equal to the coordinate components of the normal, or by the NURBS expressions. The value Z can be achieved by software or hardware Z-buffer. The effects of the size of image on the RCS of target are discussed and the correct method is recommended. The RCS of the perfect conducting sphere, cylinder and dihedral as well as the coated cylinder, as some examples, are computed. The accuracy of the method is verified by comparing the numerical results with those obtained by using other methods.

Physical modeling and visualization of soil liquefaction under high confining stress

The mechanisms of seismically-induced liquefaction of granular soils underhigh confining stresses are still not fully understood. Evaluation of these mechanisms is generallybased on extrapolation of observed behavior at shallow depths. Three centrifuge model tests wereconducted at RPI's experimental facility to investigate the effects of confining stresses on thedynamic response of a deep horizontal deposit of saturated sand. Liquefaction was observed at highconfining stresses in each of the tests. A system identification procedure was used to estimate theassociated shear strain and stress time histories. These histories revealed a response marked byshear strength degradation and dilative patterns. The recorded accelerations and pore pressures wereemployed to generate visual animations of the models. These visualizations revealed a liquefactionfront traveling downward and leading to large shear strains and isolation of upper soil layers.

Chromatic and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems

Adaptive mate choice has been accepted as the leading theory to explain the colorful plumage of birds.This theory hypothesizes that conspicuous colors act as signals to advertise the qualities of the owners.However,a dilemma arises in that conspicuous colors may not only attract mates,but also alert predators.The"private channels of communication"hypothesis proposes that some intraspecific signals may not be visible to heterospecific animals because of different visual systems.To better understand the evolution of plumage colors and sexual selection in birds,here we studied the chromatic difference and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems.We found that either the chromatic or achromatic difference among male or female minivets’plumage was consistently higher under conspecific vision than under predator vision for all five studied species of minivets.This result indicated that individual differences in plumage colors of minivets were visible to the conspecific receivers and hidden from potential predators as a result of evolution under predation risk and conspecific communication.However,males were under a higher risk of predation because they were more conspicuous than females to the vision of a nocturnal predator.

A COM-based Framework for Management,Analysis and Visualization of Large Scope Digital Elevation Models

This paper presents a component object model (COM) based framework for managing, analyzing and visualizing massive multi-scale digital elevation models (DEMs). The framework consists of a data management component (DMC), which is based on RDBMS/ORDBMS, a data analysis component (DAC) and a data render component (DRC). DMC can manage massive multi-scale data expressed at various reference frames within a pyramid database and can support fast access to data at variable resolution. DAC integrates many useful applied analytic functions whose results can be overlaid with the 3D scene rendered by DRC. DRC provides view-dependent data paging with the support of the underlying DMC and organizes the potential visible data at different levels into rendering.