基于问题解决的小学数学信息处理方法培养例析

在问题解决的四种能力中,分析问题能力是关键,而信息处理方法是获得分析、解决问题能力的基础。很多课堂对问题信息的处理方法较单一,未形成较系统的策略。文章总结出“列表”“图示”“增减”“架构”等四种信息处理方法,以典型、新颖的案例,从策略层面剖析教学实践效果。

固定化微生物处理含H_2S气体的试验研究

研究海藻酸钠包理固定化微生物颗粒填充床去除气相Ｈ２Ｓ的过程，活性微生物为经Ｓ２－加富驯化的污水厂污泥．填充滴滤塔运行实验表明，除Ｈ２Ｓ外适宜的ｐＨ值和喷淋率分别为１．８—４．０和＞０．１７ｍ３／（ｍ３·ｄ）；最大有效（去除率＞９６％）Ｈ２Ｓ体积负荷为６０００—６５００ｇ／（ｍ３·ｄ）；超过此负荷运行造成的气流阻力上升和去除率下降可通过反冲洗与低负荷（＜２０００ｇ／（ｍ３·ｄ），４ｄ）运行恢复；停气１２ｈ再启动去除率恢复时间＜２６ｈ．

动词类义的抽象原则与方法——动词类义系列研究之二

本文从中文信息处理的角度讨论了动词类义的抽象原则与方法 ,并作具体论述。动词类义的抽象原则与方法具有普遍意义 ,对于其他词性词的类义研究也有借鉴作用。

优化灰色模型在负荷预测中的应用

论述了用优化灰色理论进行电力系统负荷预测的建模过程。通过指数平滑法对原始负荷数据进行预处理 ,把有起伏特性的原始数据序列改造成规律性强的序列 ,再利用优化灰色模型进行预测 ,提高了预测精度 ,该方法简捷实用 ,经实际算例校核证明 。

An adaptive learning rate GMM for background extraction

The rapidness and stability of background extraction from image sequences are incompatible,that is,when a conventional Gaussian mixture models (GMM)is used to rebuild the background,if the background regions of the scene are changed,the extracted background becomes bad until the transition is over. A novel adaptive method is presented to adjust the learning rate of GMM in a Hilbert space. The background extraction is treated as a process of approaching to a certain point in the Hilbert space,so the real-time learning rate can be obtained by calculating the distance between the two adjacent extracted background images,and a judgment method of the stability of background is got too. Compared with conventional GMM,the method has both high rapidness and good stability at the same time,and it can adjust the learning rate online. The experiment shows that it is better than conventional GMM,especially in the transition process of background extraction.

基于多层递阶回归分析的轧钢煤气用量预测

以某钢铁企业为背景,基于煤气用户的历史数据,通过多层递阶回归分析建立相应的消耗预报模型,从而对煤气用量进行预测。首先把统计样本中的各个高相关因子作为回归变量进行线性回归处理,然后以回归系数与预报因子的乘积作为对修正量来进行多层递阶预报。这种多层递阶与回归分析方法,既能较好地体现高相关因子在预报模型中的重要作用,又具有较强的适应性,可提高预报精度。实际工业应用证明了方法的有效性。

Radar target recognition based on micro-Doppler effect

Mechanical vibration of target structures will modulate the phase function of radar backscattering,and will induce the frequency modulation of returned signals from the target. It generates a side bands of the target body Doppler frequency shift,which is helpful for target recognition. Based on this,a micro-Doppler atomic storehouse is built for the target recognition,and four kinds of common classifiers are used separately to perform the classified recognition. The simulation experimental results show that this method has high recognition rate above 90%.

Research on the Informatization Technology of Rural Residential Land Cadastral Data

Using innovative information means to form the digital management sys- tem of rural residential land is the key point to solve the difficult and hot issues in rural residential land management. In view of the diversity, large quantity, and preservation with paper of rural residential land data, a new method for automatic cutting and classification of digital images based on the image data source and us- ing the image processing algorithm and Python programming was proposed in order to achieve rapid and accurate collection and digital storage of rural residential land cadastral data. Using this method, digital image automatic cutting and classification were realized, and the efficiency and accuracy of this method was validated by comparing with the non-support free shooting method and manual image process- ing. The experimental results showed that the efficiency of the data acquisition of the fixed shooting method was 4.24 times of that of the non-support free shooting method with the accuracy rate increasing by 7.1%, and the efficiency of automatic image processing was 35 times of that of manual processing. Based on rapid and accuracy data acquisition, this method realized the automatic processing of digital images, which provided a reference for the research of informatization technology of the whole rural residential land data and has the value of popularization and appli- cation.

Design and Research of Information Processing System Based on Mix Platform

Aim To develop an information processing system with real time processing capability and artistic user interface for the optoelectronic antagonism general measuring system. Methods The A/D board and the multifunctional board communicating with every instruments were designed, data collecting and processing were realized by selecting appropriate software platform. Results Simulating results show the information processing system can operate correctly and dependably, the measuring rules, interactive interface and data handling method were all accepted by the user. Conclusion The designing approach based on the mix platform takes advantages of the two operating systems, the desired performances are acquired both in the real time processing and with the friendly artistic user interface.

再论电子商务的本质

电子商务的本质是以信息处理为基础的、强化信息价值的商务活动。Internet是EB的基础,高效率低成本的信息处理、传递是EB的根本.电子商务活动中,商务信息的智能处理使信息价值的深化,同时衍生出新的信息商品。

Multi-sensor systems and information processing of mobile robot in uncertain environments

The PBJ- 01 robot is a kind of mobile robot featuring six wheels and two swing arms which can help it to fit many terrains. The robot has a sophisticated sensor system, which includes ultrasonic sensors, tentacle sensors and a vision sensor. The PBJ- 01 adopts behavior-based reactive control architecture in which the key part is an object recognition system based on a fuzzy neural network. Simulation validates that this system can conclude the obstacle type from the sensor data, and help the robot decide whether to negotiate or to avoid obstacles.

RESEARCH ON 3 D RANGE SENSOR SYSTEM

The structure of 3 D range sensor system for unmanned vehicle is introduced.Several key technologies are described in detail.The ultrasonic signal is processed from different angles.Image edges are extracted by the multiple scale method.Image noises are recognized and cleared by using multilayer forward neural network with fuzzy logic.The method of information fusion for multiple sensors is discussed.This paper also gives some ultrasonic signal curves and image results.

Method for eliminating zero-order image in digital holography

For eliminating the zero-order image in digital holography, a new method using the differential of the hologram intensity instead of the hologram itself for numerical reconstruction is proposed. This method is based on digital image processing. By analyzing the spatial spectrum of the off-axis digital hologram, it theoretically proves that the zero-order image can be effectively eliminated by differential before reconstruction. Then, the detected hologram is processed in the program with differential and reconstruction. Both the theoretical analysis and digital reconstruction results show that it can effectively eliminate the large bright spot in the center of the reconstructed image caused by the zero-order image, improve the image quality significantly, and render a better contrast of the reconstructed image. This method is very simple and convenient due to no superfluous optical elements and requiring only one time record.

Probabilistic Teleportation of a Four-Particle Entangled W State

In this paper, two schemes for teleporting an unknown four-particle entangled W state is proposed. In the first scheme, two partial entangled four-particle states are used as quantum channels, while in the second scheme,four non-maximally entangled particle pairs are considered as quantum channels. It is shown that the teleportation can be successfully realized with certain probability, for both schemes, if a receiver adopts some appropriate unitary transformations. It is also shown that the successful probabilities of these two schemes are different.

Optical polarization imaging for underwater target detection with non-scatter background

For conventional optical polarization imaging of underwater target,the polarization degree of backscatter should be pre-measured by averaging the pixel intensities in the no target region of the polarization images,and the polarization property of the target is assumed to be completely depolarized.When the scattering background is unseen in the field of view or the target is polarized,conventional method is helpless in detecting the target.An improvement is to use lots of co-polarization and cross polarization detection components.We propose a polarization subtraction method to estimate depolarization property of the scattering noise and target signal.And experiment in a quartz cuvette container is performed to demonstrate the effectiveness of the proposed method.The results show that the proposed method can work without scattering background reference,and further recover the target along with smooth surface for polarization preserving response.This study promotes the development of optical polarization imaging systems in underwater environments.

Vision based terrain reconstruction for planet rover using a special binocular bundle adjustment

This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.

BOOTSTRAPPING FOR EXTRACTING RELATIONS FROM LARGE CORPORA

A new approach of relation extraction is described in this paper. It adopts a bootstrap- ping model with a novel iteration strategy, which generates more precise examples of specific relation. Compared with previous methods, the proposed method has three main advantages: first, it needs less manual intervention; second, more abundant and reasonable information are introduced to represent a relation pattern; third, it reduces the risk of circular dependency occurrence in bootstrapping. Scalable evaluation methodology and metrics are developed for our task with comparable techniques over TianWang 100G corpus. The experimental results show that it can get 90% precision and have excellent expansibility.

Feature extraction for target identification and image classification of OMIS hyperspectral image

In order to combine feature extraction operations with specific hyperspectral remote sensing information processing objectives,two aspects of feature extraction were explored. Based on clustering and decision tree algorithm,spectral absorption index (SAI),continuum-removal and derivative spectral analysis were employed to discover characterized spectral features of different targets,and decision trees for identifying a specific class and discriminating different classes were generated. By combining support vector machine (SVM) classifier with different feature extraction strategies including principal component analysis (PCA),minimum noise fraction (MNF),grouping PCA,and derivate spectral analysis,the performance of feature extraction approaches in classification was evaluated. The results show that feature extraction by PCA and derivate spectral analysis are effective to OMIS (operational modular imaging spectrometer) image classification using SVM,and SVM outperforms traditional SAM and MLC classifiers for OMIS data.

FUZZY PRINCIPAL COMPONENT ANALYSIS AND ITS KERNEL-BASED MODEL

Principal Component Analysis(PCA)is one of the most important feature extraction methods,and Kernel Principal Component Analysis(KPCA)is a nonlinear extension of PCA based on kernel methods.In real world,each input data may not be fully assigned to one class and it may partially belong to other classes.Based on the theory of fuzzy sets,this paper presents Fuzzy Principal Component Analysis(FPCA)and its nonlinear extension model,i.e.,Kernel-based Fuzzy Principal Component Analysis(KFPCA).The experimental results indicate that the proposed algorithms have good performances.