词的理据与英语词汇习得

语言包括词汇、语法、语音三种成分,其中词汇是最重要的成分。对词汇的成功习得往往成为语言成功习得的关键一环。英语词汇来源复杂,构词手段多样,其词汇浩如烟海,如果没有科学的学习方法做指导,则词汇习得难以卓有成效。从理据的定义、分类以及英语词汇习得三个方面进行阐释,力求为中国英语学习者在英语词汇习得方面提供一些有效策略。

Integrating TM and Ancillary Geographical Data with Classification Trees for Land Cover Classification of Marsh Area

The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjiang Plain, Heilongjiang Province, China. Semi-variograms and Z-test value were calculated to assess the separability of grey-level co-occurrence texture measures to maximize the difference between land cover types. The degree of spatial autocorrelation showed that window sizes of 3×3 pixels and 11×11 pixels were most appropriate for Landsat TM im- age texture calculations. The texture analysis showed that co-occurrence entropy, dissimilarity, and variance texture measures, derived from the Landsat TM spectrum bands and vegetation indices provided the most significant statistical differentiation between land cover types. Subsequently, a Classification and Regression Tree (CART) algorithm was applied to three different combinations of predictors: 1) TM imagery alone (TM-only); 2) TM imagery plus image texture (TM+TXT model); and 3) all predictors including TM imagery, image texture and additional ancillary GIS in- formation (TM+TXT+GIS model). Compared with traditional Maximum Likelihood Classification (MLC) supervised classification, three classification trees predictive models reduced the overall error rate significantly. Image texture measures and ancillary geographical variables depressed the speckle noise effectively and reduced classification error rate of marsh obviously. For classification trees model making use of all available predictors, omission error rate was 12.90% and commission error rate was 10.99% for marsh. The developed method is portable, relatively easy to im- plement and should be applicable in other settings and over larger extents.

New WA-system of kravchenko functions in digital signal processing

On the basis of modified atomic transformations the new WA-systems of Kravchenko functions are constructed.As an example the digital processing of time series of the various physical nature processing is considered.The numerical experiments and physical analysis of the results confirm the efficiency of the proposed WA-systems of Kravchenko functions.

MPPT research based on fuzzy adaptive PID control

In order to improve the efficiency and precision of maximum power point tracking(MPPT)control,a new method is proposed.Based on original MPPT technology of photovoltaic cells,the fuzzy adaptive proportion-integral-differential(PID)control has less fluctuation and higher stability.The simulation circuit using Simulink is established,and output power curves under constant temperature or constant sunlight are obtained.The superiority of the fuzzy PID control method has been proved by means of the simulation results,and it makes the solar system approach maximum power point quickly and smoothly.

Object-tracking robot using ultrasonic sensor and servo motor

This paper proposes a method that rotation angle of servo motor and distance values of ultrasonic sensor are used for tracking an object in real-time while the robot keeps regular distance.Object detection distance widens by using ultrasonic sensors and object recognition,and movement of robot is controlled by angle of servo motor and distance of ultrasonic sensors.Not adopting the existing tracking methods:camera,laser-infrared(LRF)and many ultrasonic sensors,the proposed method proves that it is possible to track object using ultrasonic sensor and servo motor.Trajectory of robot is represented and analysed according to movement of object in limited conditions.

Land Cover Classification with Multi-source Data Using Evidential Reasoning Approach

Land cover classification is the core of converting satellite imagery to available geographic data.However,spectral signatures do not always provide enough information in classification decisions.Thus,the application of multi-source data becomes necessary.This paper presents an evidential reasoning (ER) approach to incorporate Landsat TM imagery,altitude and slope data.Results show that multi-source data contribute to the classification accuracy achieved by the ER method,whereas play a negative role to that derived by maximum likelihood classifier (MLC).In comparison to the results derived based on TM imagery alone,the overall accuracy rate of the ER method increases by 7.66% and that of the MLC method decreases by 8.35% when all data sources (TM plus altitude and slope) are accessible.The ER method is regarded as a better approach for multi-source image classification.In addition,the method produces not only an accurate classification result,but also the uncertainty which presents the inherent difficulty in classification decisions.The uncertainty associated to the ER classification image is evaluated and proved to be useful for improved classification accuracy.

Identifying uncertainty sources in measurements-A methodology

The overall purpose of performing measurements in science is to increase knowledge and document about some physical quantity. The measurand has a true value but, except for straightforward counting situations, the true value can never be fully determined. When a quantity is measured, the outcome depends on the measuring system, the measurement procedure, the skill of the operator, the environment and other effects. In practice the uncertainty on the result may arise from many possible sources, including examples such as incomplete definition, sampling, matrix effects and interferences, environmental couditions, uncertainties of weights and volumetric equipment, reference wtlues, approximations and assump- tions incorporated in the measurement method and procedure, and random wlriation. The objective of the paper is how to identify the sources of uncertainty in measurement and their importance on the result.

Most relevant weighted filtering with one-step singular correlation recognition

Based on the recognition of one-step singular correlation and the remedying methods obtained before,the correlation properties of the neighborhood pixels and the characteristics of image de-noising were analyzed.A kind of most relevant weighted filtering method based on one-step singular correlation recognition(OSSC-MRWF)was put forward.The simulation experiments were done and the comparison with some commonly used methods under salt-and-pepper noises was made.The results show that the proposed method can not only effectively recognize salt-and-pepper noises and mend up the noise points,but also protect the original information such as the edge details very well.The accuracy and performance indicators are further improved considerably.

A framework of hybrid authentication for link access under MIH environments

A unified hybrid authentication framework was proposed to provide proactive authentication and re-authentication for media independent handover（MIH）-based multi-wireless access. In addition, a specific protocol distributing a hierarchi- cal key after the proactive authentication from key holder to base station has been proposed. The proposed hybrid authenti- cation framework not only performs proaetive authentication with credentials based on Chameleon hashing, which removes the authentication procedures that exchanges messages with a authentication server, but also performs re-authentication with EAP re-authentication protocol（ERP） that distributes the hierarchical key on the basis of the root key generated by the pro- active authentication.

Preparation and characterization of alumina nanoparticles in non-aqueous solution

Nanometer Al2O3powder is prepared by sol-gel method.Trans mission electron microscope(TEM),X-ray diffrac-tion(XRD),ther mal analysis,IR and the grain-testing instructure are used to characterize the particle shape and phase,chemical bonds of hydrous cassiterite andsize distribution after being heated.XRDand TEMshowthat the powder is fibrous γ-Al2O3at800 ℃andsphericalα-Al2O3at1 200℃.The grain-testinginstructure shows that the average particle diameter of γ-Al2O3is36.2nm while that ofα-Al2O3is125.6nm.The IRshows that aluminumstearate is synthesizedin the process of sol-gel.

Information entropy-based estimation of hand and elbow movements using ECoG signals

A method of estimating hand and elbow movements using electrocorticogram （ECoG） signals is proposed. Using multiple channels, surface electromyogram （EMG） signals and ECoG signals were obtained from patients simultaneously. The estimated movements were those to close and then open the hand and those to bend the elbow inward. The patients were encouraged to perform the movements in accordance with their free will instead of after being induced by external stimuli. Surface EMG signals were used to find movement time points, and ECoG signals were used to estimate the movements. To extract the characteristics of the individual movements, the ECoG signals were divided into a total of six bands （the entire band and the ~, 0, a ,fl and 7 bands） to obtain the information entropy, and the maximum likelihood estimation method was used to estimate the movements. The results of the experiment show that the performance averages 74 % when the ECoG of 7 band is used, which is higher than that when other bands are used, and higher estimation success rates are shown in the 7 band than in other bands. The time of the movements is divided into three time sections based on movement time points, and the ＂Before＂ section, which includes the readiness potential, is compared with the ＂Onset＂ section. In the ＂Before＂ section and the ＂Onset＂ section, estimation success rates are 66 % and 65 %, respectively, and thus it is determined that the readiness potential could can be used.

Implementation of motion estimator algorithm with 1/4 pixel accuracy based on FPGA

After research on the motion estimation algorithm in video coding, a motion estimator algorithm with 1/4 pixel ac- curacy is implemented based on fie/d-programmable gate array （FPGA）. The motion estimation algorithm module is made up of the 1[4 pixel interpolation module with serial input and parallel output, the three step search module and the block match- ing module, which can use relatively less Wiener filters for interpolation operation. Experiment results show that the hard- ware design has less consumption of the logical resource, higher stability and lower power consumption.

Balancing control of unicycle robot by using sliding control

This paper discusses about balancing control of unicycle robot.Unicycle robot consists of pitch which acts like inverted pendulum and roll which acts like reaction wheel pendulum.The robot which does not have actuator located in yaw axis is made to derive the simple dynamics.Lagrange equation is applied to deriving dynamic equations.Obtained dynamic equations are used to design the sliding mode control.State variables of the designed control are pitch angle and roll angle.Sliding mode control has chattering problem,which is eliminated by using the sigmoid function as switching function.Finally the control performance and eliminated chattering problem is verified by simulation.

Study on Raman and SERS spectra of filter paper and silica gel plate

Raman spectra and surface-enhanced Raman scattering （SERS） spectra of filter paper and silica gel plate are ob- tained at 785-nm excitation wavelength. The results show that filter paper has thirteen Raman lines in 800 - 1 500 cm 1 and silica gel plate has eight lines in the region of 400 - 1 200 cm-I. The frequencies and Raman active modes are assigned. By comparing their Raman spectra and SERS spectra, we find that the silver colloid could repress the Raman intensities of filter paper and silica gel plate, and reduce their effects on the combination of thin-layer chromatographic （TLC） and SERS. Ac- cording to SERS spectra, the bands at 997 cm 1,1 094 cm I ,1 118 cm-1 ,1 336 cm-1 and 1 378 cm-1 for filter paper and the peak of v l [ SO4] symmetric stretching vibration （--1 017 cm-1 ） for silica gel plate also have high intensities, and those lines should be paid enough attention in TLC-SERS.

Test on methane flame velocity in horizontal tube with obstacles

To test flame propagation velocity of gas explosion in a horizontal tube,a set of flame velocity testing system is designed.The system is composed of two parts:a horizontal tube used for methane burning and a flame detection system.The effect of obstacles on flame propagation velocity of methane explosion is tested.Methane volume density is 10% in the tube.The obstacle is the circular ring,2 mm thick.Its blockage ratios are 40%,50% and 60%,respectively.The number of obstacles put in the tube is 1,3,5 and 7.Experimental results show that the obstacle has obviously accelerating effect on flame wave of gas explosion.As the number and blockage ratios of the obstacles increase,flame accelerating became more obviously.When there are seven obstacles,the maximum average flame velocity reaches over 351.2 m/s.When the blockage ratio of three obstacles is 60%,the maximum average flame velocity is 238.9 m/s.

Bounding box based on probability density for the pedestrian tracking

This paper proposes a pedestrian tracking approach using bounding box based on probability densities.It is generally a difficult task to track features like corner points in outdoor images due to complex environment.To solve this problem,the feature points are projected along X and Y direction separately,and a histogram is constructed for each projection,with horizontal axis as positions and vertical axis as the number of feature points that lie on each position.Finally,the vertical axis is normalized for expression as probability.After histogram is constructed,the probability of each feature point is checked with a threshold.A feature point will be ignored if its probability is lower than a threshold,while the remaining feature points are grouped,based on which a bounding box is made.Kanade-Lucas Tomasi(KLT)algorithm is adopted as the tracking algorithm because it is able to track local features in images robustly.The efficiency of the tracking results using this method is verified in real environment test.

Classification of the mining land cover based on density segmentation

The Datun mining area is the test area in this paper,and the purpose is to obtain the mining land cover classification map in 2003.The data source used in this paper is the Landsat enhanced thematic mapper plus(ETM)remote sensing data.By obtaining the normalized difference vegetation index(NDVI)of the study area,the land cover classification information is extracted using the density segmentation method.Because the results cannot distinguish the construction land and wetland,this paper obtains the humidity information of multi-spectral data through the tasseled cap transformation.From the density segmentation image of humidity information,the construction and wetland types can be clearly distinguished.Finally,combining the two classification maps,the visual interpretation using Landsat ETM fusion image with 15-m resolution helps to get the final classification results.After classification accuracy assessment,the overall accuracy calculated from the classification confusion matrix is 86%.This result can be applied in actual project.

Facial model fitting algorithm based on active appearance model

Active appearance model（AAM） is an efficient useful for the subsequent work such as face detection and method for the localization of facial feature points, which is also facial expression recognition. In this paper, we mainly discuss the AAMs based on principal component analysis （PCA）. We also propose an efficient facial fitting algorithm, which is named inverse compositional image alignment （ICIA）, to eliminate a considerable amount of computation resulting from traditional gradient descent fitting algorithm. Finally, 3D facial curvature is used to initialize the location of facial feature, which helps select the parameters of initial state for the improved AAM.

Study on TRV of circuit breaker in two substation operational ways and its countermeasure

To verify a vacuum breaker's feasibility,when a transformer substation chooses a vacuum circuit breaker,it takes two different actual operational ways to cut off a transformer.This paper,using the power system computer aided design/electro magnetic transient in DC system(PSCAD/EMTDC)software,simulates the substation system and studies transient recovery voltage(TRV)caused by the two different ways which can cut off a with load transformer or a no-load transformer.Simulation and calculation results show that TRV indexes of the first way are much higher than that of the second one,and their TRV indexes are both in a permissible range.The breaker is proved to be available.Besides,this paper proves that paralleling resistance has a good effect when the indexes exceed the standard.The resistance value depends on specific circumstances.

Application of multi-GRNN with a gating network in stock prices forecast

This paper proposes the generalized regression neural network(GRNN)model and multi-GRNN model with a gating network by selecting the data of Shanghai index,the stocks of Shanghai Pudong Development Bank(SPDB),Dongfeng Automobile and Baotou Steel.We analyze the two models using Matlab software to predict the opening price respectively.Through building a softmax excitation function,the multi-GRNN model with a gating network can obtain the best weights.Using the data of the four groups,the average of forecasting errors of 4 groups by GRNN neural model is 0.012 208,while the average of the multi-GRNN models's with a gating network is 0.002 659.Compared with the real data,it is found that the both results predicted by the two models have small mean square prediction errors.So the two models are suitable to be adopted to process a large quantity of data,furthermore the multi-GRNN model with a gating network is better than the GRNN model.