Finite Element Structural Analysis UsingObject-Oriented Techniques

This paper describes the object-oriented implementational method of finite element structural analysis, gives the basic concepts of the object-oriented method and objectoriented programming, develops a complete class hierarchy structure of object-oriented finite element structural analysis, and gives a part C+ + code description.

Reliability Modelling and Analysis of Satellite Propulsion System Based on Reliability Block Diagram and Extended Object-Oriented Petri Net

Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.

Open-Access Framework for Efficient Object-Oriented Development of Video Analysis Software

The increasing use of digital video everyday in a multitude of electronic devices, including mobile phones, tablets and laptops, poses the need for quick development of cross-platform video software. However current approaches to this direction usually require a long learning curve, and their development lacks standardization. This results in software components that are difficult to reuse, and hard to maintain or extend. In order to overcome such issues, we propose a novel object-oriented framework for efficient development of software systems for video analysis. It consists of a set of four abstract components, suitable for the implementation of independent plug-in modules for video acquisition, preprocessing, analysis and output handling. The extensibility of each module can be facilitated by sub-modules specifying additional functionalities. This architecture enables quick responses to changes and re-configurability;thus conforming to the requirements of agile software development practices. Considering the need for platform independency, the proposed Java Video Analysis (JVA) framework is implemented in Java. It is publicly available through the web as open-access software, supported by a growing collection of implemented modules. Its efficiency is empirically validated for the development of a representative video analysis system.

Sediment distribution pattern mapped from the combination of objective analysis and geostatistics in the large shallow Taihu Lake, China

Investigation was made into sediment depth at 723 irregularly scattered measurement points which cover all the regions in Taihu Lake, China. The combination of successive correction scheme and geostatistical method was used to get all the values of recent sediment thickness at the 69×69 grids in the whole lake. The results showed that there is the significant difference in sediment depth between the eastern area and the western region, and most of the sediments are located in the western shore-line and northern regimes but just a little in the center and eastern parts. The notable exception is the patch between the center and Xishan Island where the maximum sediment depth is more than 4.0 m. This sediment distribution pattern is more than likely related to the current circulation pattern induced by the prevailing wind-forcing in Taihu Lake. The numerical simulation of hydrodynamics can strong support the conclusion. Sediment effects on water quality was also studied and the results showed that the concentrations of TP, TN and SS in the western part are obviously larger than those in the eastern regime, which suggested that more nutrients can be released from thicker sediment areas.

OBJECTIVE ANALYSIS OVER INDIAN REGION BY BRATSETH'SSUCCESSIVE CORRECTION SCHEME

Bratseth (1986) has proposed a successive correction scheme for numerical analysis where the solution converges towards the solution obtained by optimum interpolation. This paper presents the results of some experiments carried out over indian reston during summer monsoon period using this Bratseth’s method. The convergence of the method is investigated.

Distributed Parallelization of a Global Atmospheric Data Objective Analysis System

It is difficult to parallelize a subsistent sequential algorithm. Through analyzing the sequential algorithm of a Global Atmospheric Data Objective Analysis System, this article puts forward a distributed parallel algorithm that statically distributes data on a massively parallel processing (MPP) computer. The algorithm realizes distributed parailelization by extracting the analysis boxes and model grid point Iatitude rows with leaped steps, and by distributing the data to different processors. The parallel algorithm achieves good load balancing, high parallel efficiency, and low parallel cost. Performance experiments on a MPP computer arc also presented.

Construction Activity Analysis of Workers Based on Human Posture Estimation Information

Identifying workers’construction activities or behaviors can enable managers to better monitor labor efficiency and construction progress.However,current activity analysis methods for construction workers rely solely on manual observations and recordings,which consumes considerable time and has high labor costs.Researchers have focused on monitoring on-site construction activities of workers.However,when multiple workers are working together,current research cannot accu rately and automatically identify the construction activity.This research proposes a deep learning framework for the automated analysis of the construction activities of multiple workers.In this framework,multiple deep neural network models are designed and used to complete worker key point extraction,worker tracking,and worker construction activity analysis.The designed framework was tested at an actual construction site,and activity recognition for multiple workers was performed,indicating the feasibility of the framework for the automated monitoring of work efficiency.

EFFECT OF TROPICAL CYCLONE PRECIPITATION ON ALLEVIATING THE DROUGHT SITUATION IN THE SOUTHEAST COASTAL REGIONS OF CHINA DURING SUMMER AND AUTUMN:USING THE IMPROVED OBJECTIVE SYNOPTIC ANALYSIS TECHNIQUE

To quantitatively study the role of tropical cyclone precipitation(TCP) on alleviating the drought in the southeast coastal region of China(SCR) during summer and autumn,the objective synoptic analysis technique(OSAT),improved for consistency and rationality,was used to separate the TCP data on the summers and autumns of 1963-2005 on the basis of daily precipitation data from stations and tropical cyclone best track data.After defining the season drought index,the actual drought distribution and the assumed drought distribution without TCP were acquired.The results showed that within 1 000 km from the southeast coastline of China,TCP accounted for 11.3%of natural precipitation(NP).Without TCP,the drought index in the SCR during summer would have increased from 0.2 to 0.6 or even above 1.0 in some regions whereas the drought index during autumn would have increased from 0.4 to 0.6 or above 1.2 in some regions.The impact of TCP on drought decreases progressively from the southeast coastline to the inland regions.The TCP proportion(TCPP) showed a significant negative correlation with the drought index in many regions of the southeast,and the significant region is wider in autumn than in summer.TCP relieved the drought most significantly within a range of 0-500 km from the southeast coastline.This drought relief showed different characteristics for the interannual variability in summer and autumn,and the cross wavelet transform indicated that the impact of TCP on drought mainly lies in 2-4-year time scales.In particular,there was a significant effect during the summers of 1977-1985 and in the autumns following that of 1985.Therefore,TCP has indeed largely alleviated drought in the SCR during summer and autumn.

Structural failure analysis with CMS-based ground motion selection using innovative cost function and weight factors

The selection and scaling of ground motion records is considered a primary and essential task in performing structural analysis and design.Conventional methods involve using ground motion models and a conditional spectrum to select ground motion records based on the target spectrum.This research demonstrates the influence of adopting different weighted factors for various period ranges during matching selected ground motions with the target hazard spectrum.The event data from the Next Generation Attenuation West 2(NGA-West 2)database is used as the basis for ground motion selection,and hazard de-aggregation is conducted to estimate the event parameters of interest,which are then used to construct the target intensity measure(IM).The target IMs are then used to select ground motion records with different weighted vector-valued objective functions.The weights are altered to account for the relative importance of IM in accordance with the structural analysis application of steel moment resisting frame(SMRF)buildings.Instead of an ordinary objective function for the matching spectrum,a novel model is introduced and compared with the conventional cost function.The results indicate that when applying the new cost function for ground motion selection,it places higher demands on structures compared to the conventional cost function.Moreover,submitting more weights to the first-mode period of structures increases engineering demand parameters.Findings demonstrate that weight factors allocated to different period ranges can successfully account for period elongation and higher mode effects.

Multivariate Objective Analysis of Wind and Height Fields in the Tropics

The commollly used objective analysis scheme(Scheme-A) for the analysis Of wind and geopotential height smoothen the divergent component of the wind which is rather important in the tropics,specifically over convective regions.To overcome this deficiellcy, a new analysis SCheme in which divergent component is included in the statistical model of the wind forecast errors,has been proposed by Daley(1985).Following this scheme,a new set of correlahon functions of forecast errors for the indian region during monsoon season which are suitable for analysing the tropical wind are obtained.This analysis scheme(Scheme--B) as well as Scheme-A were used to make analyses for the period from 4 July to & July 1979(12 GMT) at 850,700 and 200 hpa levels over an area bounded by l.875'N to 39.375'N and 41.250'E to 108.750'E and subsequently divergent component,velocity potential are computed for both schemes.Results from both these schemes show that in the monsoon depression region the velocity potential and divergence have increased in the later case(Scheme-B).This suggests that the divergent component has been enhanced in Scheme-B and that the objechve of this study is realized to some extent.

Object-Oriented Design for FDTD Visual Scientific Computing

A scheme for general purposed FDTD visual scientific computing software is introduced in this paper using object-oriented design (OOD) method. By abstracting the parameters of FDTD grids to an individual class and separating from the iteration procedure, the visual software can be adapted to more comprehensive computing problems. Real-time gray degree graphic and wave curve of the results can be achieved using DirectX technique. The special difference equation and data structure in dispersive medium are considered, and the peculiarity of parameters in perfectly matched layer are also discussed.

Neutron activation method in the analysis of environmental objects

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An Objective Analysis Method for Surface Residual Current Field in the East China Seas

Since the volume transport across the pycnocline is much smaller than that in the mixed layer, the current in the mixed layer can be regarded as non-divergent. An objective analysis method is deduced based on this hypothesis. The linear combination method is used to solve the non-divergent component of the current field of an ocean basin containing islands,which is equivalent to a mathematical problem of solving a Poisson equation in a multi-connected domain. The method is applied to the Bohai Sea, the Yellow Sea and the East China Sea (ECS). The modeled result is consistent with the current maps constructed by other oceanographers.

Some Experiments with Multivariate Objective Analysis Scheme of Heights and Winds Using Optimum Interpolation

A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. The height-height correlations calculated using daily data of four July months (1976-1979), are used to derive the other autocorrelations and cross-correlations assuming geostropic relationship. A Gaussian function is used to model the autocorrelation function. Since the scheme is multivariate the regression coefficients (weights) are matrix.Near the equator, the geostrophic approximation relating mass and wind is decoupled in a way similar to Bergman (1979). The objective analyses were made over Indian and adjoining region for 850, 700, 500, 300 and 200 hPa levels for the period from 4 July to 8 July 1979, 12 GMT. The analyses obtained using multivariate optimum interpolation scheme depict the synoptic situations satisfactorily. The analyses were also compared with the FGGE analyses (from ECMWF) and also with the station observations by computing the root mean square (RMS) errors and the RMS errors are comparable with those obtained in other similar studies.

Construction of Vertical Wind Profile from Satellite-Derived Winds for Objective Analysis of Wind Field

During summer Monex-79, a variety of observing systems viz. research ships, research aircrafts, constant pressure balloons and geostationary satellite etc. were deployed, besides the regular conventional observations. The purpose of these additional systems was to make the best possible data for the studies on various aspects of monsoon circulation. The present study is aimed at the construction of vertical wind profile using cloud motion vectors obtained from GOES (I-O) satellite and to examine whether the constructed wind profiles improves the representation of the monsoon system, flow pattern etc. in the objective analysis. For this purpose, climatological normals of the wind field are considered as the initial guess and the objective analyses of the wind field are made with, first using only data from conventional observations over land areas, subsequently including the constructed winds from cloud motion vectors. These analyses are then compared with the standard analyses of wind field obtained from Quick Look Atlas by T. N. Krishnamurti et al. (1979).It is inferred that satellite estimated mean wind profiles show good agreement with the mean wind profiles of the research ships with RMS errors less than 5 mps below 500 hPa and less than 8 mps above 500 hPa. It is further inferred that the inclusion of constructed winds shows a positive impact on the objective analysis and improvement is seen to be more marked in the data-sparse region of the Arabian sea. Analyses which include the constructed winds show better agreement with the standard analysis, than the analyses obtained using only conventional winds. Thus, results of our study suggest that the wind profiles constructed using cloud motion vectors are of potential use in objective analysis to depict the major circulation features over the Indian region.

Needs Analysis And Objectives Setting in Curriculum Designing——with Special

On the basis of a detailed introduction to the concept of language learners’needs, this paper illustrates the importance of needs analysis, both pre course analysis and ongoing analysis, in curriculum designing. By doing so, teachers can not only collect factual information for the purpose of setting broad goals related to language content; but also gather information about learners which can be used to guide the learning process once it’s under way. Learners, on the other hand, can be aware of their own learning under the direction of the specified objectives.

Object-based Analysis for Extraction of Dominant Tree Species

As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species,we tested the highly hot method-object-based analysis. Based on the ALOS image data,we combined multi-resolution in e Cognition software and fuzzy classification algorithm. Through analyzing the segmentation results,we basically extract the spruce,the pine,the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects,and with the help of GLCM,we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0. 837.

Geographic Object-Based Image Analysis of Changes in Land Cover in the Coastal Zones of the Red River Delta (Vietnam)

The majority of the population and economic activity of the northern half of Vietnam is clustered in the Red River Delta and about half of the country’s rice production takes place here. There are significant problems associated with its geographical position and the intensive exploitation of resources by an overabundant population (population density of 962 inhabitants/km2). Some thirty years after the economic liberalization and the opening of the country to international markets, agricultural land use patterns in the Red River Delta, particularly in the coastal area, have undergone many changes. Remote sensing is a particularly powerful tool in processing and providing spatial information for monitoring land use changes. The main methodological objective is to find a solution to process the many heterogeneous coastal land use parameters, so as to describe it in all its complexity, specifically by making use of the latest European satellite data (Sentinel-2). This complexity is due to local variations in ecological conditions, but also to anthropogenic factors that directly and indirectly influence land use dynamics. The methodological objective was to develop a new Geographic Object-based Image Analysis (GEOBIA) approach for mapping coastal areas using Sentinel-2 data and Landsat 8. By developing a new segmentation, accuracy measure, in this study was determined that segmentation accuracies decrease with increasing segmentation scales and that the negative impact of under-segmentation errors significantly increases at a large scale. An Estimation of Scale Parameter (ESP) tool was then used to determine the optimal segmentation parameter values. A popular machine learning algorithms (Random Forests-RFs) is used. For all classifications algorithm, an increase in overall accuracy was observed with the full synergistic combination of available data sets.

Kernel principal component analysis network for image classification

In order to classify nonlinear features with a linear classifier and improve the classification accuracy, a deep learning network named kernel principal component analysis network（ KPCANet） is proposed. First, the data is mapped into a higher-dimensional space with kernel principal component analysis to make the data linearly separable. Then a two-layer KPCANet is built to obtain the principal components of the image. Finally, the principal components are classified with a linear classifier. Experimental results showthat the proposed KPCANet is effective in face recognition, object recognition and handwritten digit recognition. It also outperforms principal component analysis network（ PCANet） generally. Besides, KPCANet is invariant to illumination and stable to occlusion and slight deformation.