实验数据处理中非线性拟合的VB软件

本软件为高等教育出版社出版的《物理化学实验》一书配套开发,针对物理化学实验数据处理工作中的非线性问题,以Visual Basic 6．0作为开发工具,采用高斯-牛顿法对待定系数进行拟合,通过最大泡压法测定液体表面张力的具体实例,阐述了利用VB编程求解非线性模型从而得到更准确、更科学的实验结果的方法。     

Management of multidimensional discrete data

Spatial database management involves two main categories of data: vector and raster data. The former has received a lot of in-depth investigation; the latter still lacks a sound framework. Current DBMSs either regard raster data as pure byte sequences where the DBMS has no knowledge about the underlying semantics, or they do not complement array structures with storage mechanisms suitable for huge arrays, or they are designed as specialized systems with sophisticated imaging functionality, but no general database capabilities (e.g., a query language). Many types of array data will require database support in the future, notably 2-D images, audio data and general signal-time series (1-D), animations (3-D), static or time-variant voxel fields (3-D and 4-D), and the ISO/IEC PIKS (Programmer's Imaging Kernel System) BasicImage type (5-D). In this article, we propose a comprehensive support ofmultidimensional discrete data (MDD) in databases, including operations on arrays of arbitrary size over arbitrary data types. A set of requirements is developed, a small set of language constructs is proposed (based on a formal algebraic semantics), and a novel MDD architecture is outlined to provide the basis for efficient MDD query evaluation.     

An analysis of expression data using a support vector machine and dimensional reduction methods

Gene expression data are expected to be a significant aid in the development of efficient cancer diagnosis and classification platforms. However, gene expression data are high-dimensional and the number of samples is small in comparison to the dimensions of the data. Furthermore, the data are inherently noisy. Therefore, in order to improve the accuracy of the classifiers, we would be better off reducing the dimensionality of the data. As a method of dimensionality reduction, there are two previous proposals: feature selection and dimensionality reduction. Feature selection is a feedback method which incorporate the classifier algorithm in the future selection process. Dimensionality reduction refers to algorithms and techniques which create new attributes as combinations of the original attributes in order to reduce the dimensionality of a data set. In this article, we compared the feature selection methods and the dimensionality reduction methods, and verified the effectiveness of both types. For the feature selection methods we used one previously known method and three proposed methods, and for the dimensionality reduction methods we used one previously known method and one proposed method. From an experiment using a benchmark data set, we confirmed the effectiveness of our proposed method with each type of dimensional reduction method.     

数据平滑处理算法的编程

本文所写的程序是为了我所试验所用的电源控制的测试工作,是对电压值进行平滑处理。只要给出时间递增量就能计算出平滑处理后的电压值。在本文中我们使用了抛物线平滑处理方法,该处理方法我们将基于组件对象模型COM(Component Object Module)来实现,在客户端程序里在对该组件方法进行调用。经实践证明该方法有很好的平滑效果。     

数据平滑处理算法的编程

本文所写的程序是为了我所试验所用的电源控制的测试工作，是对电压值进行平滑处理。只要给出时间递增量就能计算出平滑处理后的电压值。在本文中我们使用了抛物线平滑处理方法，该处理方法我们将基于组件对象模型COM（Component Object Module）来实现，在客户端程序里在对该组件方法进行调用。经实践证明该方法有很好的平滑效果。     

Spatially consistent nearest neighbor imputation of forest stand data

This study suggests a method for improving spatial consistency in the estimation of forest stand data. Traditional nearest neighbor imputation can preserve between-variable consistency within a unit, but not between geographically nearby units. The lack of spatial consistency may cause problems when data are used for purposes of forestry planning or scenario analysis. In spatially consistent nearest neighbor imputation, adjacent units are considered in the estimation. The first step of the method is a k-Nearest Neighbor imputation. Secondly, based on the initial imputation an optimization algorithm, Simulated Annealing, is applied in order to reach certain spatial variation targets. The proposed method was tested in a case study where tree stem volume data were imputed to each unit (pixel) of forest stands, using satellite digital numbers as carrier data. The spatial variation measures used were between-pixel correlation and short-range variance. In addition, accuracy of the estimated stand level mean volume was used as a target in order to avoid drifts in mean volume during the optimization. The method was successful in three out of four stands where it resulted in imputations corresponding exactly to the target spatial variation measures. In the fourth stand it was not possible to find an exact solution. However, in this case the two spatial variation targets were reached whereas the mean stem volume was slightly overestimated (stem volume of 375 m³ ha^− 1 rather than 336 m³ ha^− 1).     

一种同质的多传感数据融合新算法

提出一种同质的多传感数据融合新算法,充分利用了所得信息,克服了融合过程中必须依赖于多传感数据之间关系阀值的人为经验设置问题。并把新算法应用于测控装置中,计算结果表明:新算法能对多传感数据进行有效融合,提高了抗扰动性,保证融合结果有较好的精度和高可靠性。     

一种Xml数据文件压缩加密算法研究

本文研究了数据文件传输交换过程中的压缩加密算法,针对xml数据文件设计了一种混合压缩算法,算法简单高效,极大提高了系统数据交换的效率。     

The common vector approach and its comparison with other subspace methods in case of sufficient data

This paper presents an application of the common vector approach (CVA), an approach mainly used for speech recognition problems when the number of data items exceeds the dimension of the feature vectors. The calculation of a unique common vector for each class involves the use of principal component analysis. CVA and other subspace methods are compared both theoretically and experimentally. TI-digit database is used in the experimental study to show the practical use of CVA for the isolated word recognition problems. It can be concluded that CVA results are higher in terms of recognition rates when compared with those of other subspace methods in training and test sets. It is also seen that the consideration of only within-class scatter in CVA gives better performance than considering both within- and between-class scatters in Fisher’s linear discriminant analysis. The recognition rates obtained for CVA are also better than those obtained with the HMM method.     

A new vector field distance transform and its application to mesh processing from 3D scanned data

In this paper we define a new 3D vector field distance transform to implicitly represent a mesh surface. We show that this new representation is more accurate than the classic scalar field distance transform by comparing both representations with an error metric evaluation. The widely used marching cube triangulation algorithm is adapted to the new vector field distance transform to correctly reconstruct the resulting explicit surface. In the reconstruction process of 3D scanned data, the useful mesh denoising operation is extended to the new vector field representation, which enables adaptive and selective filtering features. Results show that mesh processing with this new vector field representation is more accurate than with the scalar field distance transform and that it outperforms previous mesh filtering algorithms. Future work is discussed to extend this new vector field representation to other mesh useful operations and applications.     

实验室基因分型数据中心和数据处理平台

分子生物学研究方法的快速发展给综合性遗传研究实验室的实验和数据管理工作提出了严峻的挑战.针对基因分型实验室的特点和需求,对基于SNP实验流程的信息管理系统进行了扩展和升级,在原有LIMS系统所包括的3个SNP分型实验管理模块的基础上,扩展到包括多类基因分型实验的8个实验管理模块,并增加了数据处理、报表展示等模块,完善了数据查询、导出功能,为遗传基因分型实验数据管理与分析提供更全面的支持.本文简要介绍系统的框架结构、设计实现和主要功能.     

基于惩罚和修复混合策略的约束处理方法

约束处理是约束优化的关键问题,特别是非线性约束的处理一直缺少特别有效的解决方法,将惩罚函数法与修复策略结合使用,可以有效地避免迭代过程中大量非可行解的产生,使得约束优化问题在惩罚函数和修复算子的协同作用下收敛于全局最优,较好地解决了在遗传算法约束优化问题中单独使用惩罚和修复方法时一些难以解决的问题。基于随机方向法构造的修复算子作用效果显著,采用多个测试函数对算法进行检验,均能较好地收敛于可行域中的最优解,验证了算法的可靠性。     

Regional scale prospecting for non-sulphide zinc deposits using ASTER data and different spectral processing methods

ABSTRACT

The Ravar-Kuhbanan-Bahabad belt (RKBB) in Central Iran contains several carbonate-hosted non-sulphide Zn (zinc)-Pb (lead) deposits. The Gujer Zn mine area located in the middle of the RKBB was selected as the case study. Due to its large extent, dolomitic envelope in carbonate host rocks can be considered as a more appropriate exploratory target than small Zn-rich gossans or blind karst filling ore. Based on previous studies, the occurrence of red sandstone as a candidate of supplying metal for mineralization and evaporate as sulphate source for mineralized liquids in the vicinity of carbonate rocks can be important exploratory key in the RKBB. Non-sulphide Zn deposits were formed through oxidation of primary Mississippi Valley-type (MVT) deposits in the study area. Remote sensing studies were undertaken using visible to near-infrared (VNIR) and shortwave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with the objective of lithological mapping. Five traverse lines containing a total of 81 samples were designed and followed with subsequent chemical analysis, thin section studies, and spectroscopy to verify the results. Two types of carbonates, namely, magnesian dolomite as host rock and surrounding calcitic limestone, were realized through using magnesium oxide (MgO) to calcium oxide (CaO) ratio. Based on spectroscopy studies, calcite and dolomite showed distinct absorption features at 2.35 µm and 2.32 µm, respectively, in ASTER band 8 while a shoulder at 2.25 µm was seen in ASTER band 7 for dolomite. Three image processing methods including spectral angle mapper (SAM), linear spectral unmixing (LSU), and mixture-tuned matched-filtering (MTMF) were applied to separate dolomite and limestone. The accuracy of image classification was numerically estimated using a confusion matrix. Limestone with the accuracy of 95.83% was more precisely enhanced using MTMF method compared to SAM and LSU methods. Highest accuracy of 75% for dolomite was obtained through using LSU method. Red sandstone and evaporate units were classified using MTMF and SAM/LSU methods, respectively. Rock units with the highest accuracy were selected and simply overlain on an image of ASTER in a GIS platform to create the potential map of the study area. Results showed that ASTER data can be successfully used to prepare a potential map for regional scale prospecting for carbonate-hosted non-sulphide Zn-Pb deposits in geological setting and climate condition similar to the RKBB.     

Analogy retrieval and processing with distributed vector representations

Holographic reduced representations (HRRs) are a method for encoding nested relational structures in fixed-width vector representations. HRRs encode relational structures as vector representations in such a way that the superficial similarity of the vectors reflects both superficial and structural similarity of the relational structures. HRRs also support a number of operations that could be very useful in psychological models of human analogy processing: fast estimation of superficial and structural similarity via a vector dot-product; finding corresponding objects in two structures; and chunking of vector representations. Although similarity assessment and discovery of corresponding objects both theoretically take exponential time to perform fully and accurately, with HRRs one can obtain approximate solutions in constant time. The accuracy of these operations with HRRs mirrors patterns of human performance on analog retrieval and processing tasks.     

智能系统的交流测量方法

本文介绍了智能系统测量交流量的几种方法．给出典型电路，并对微机交流算法进行理论推导。     

位置自动检测与数据处理

介绍一种以位置敏感器件 (positionsensitivedetector,PSD )为核心构成的位置自动检测系统 ,分析了输出信号与位置参数的关系 ,论述了微机位置数据处理系统的硬件组成与软件功能。最后给出系统的主要参数。     

Notes on terrorism and data processing

Terrorism relies on mindless violence to achieve its objectives. Historically it has been employed as a conscious strategy to retain or achieve power by both purportedly legitimate governmental bodies and their opponents. Modern terrorists have begun to refocus their efforts on disruption of the social fabric. Terrorists have failed to recognize the role of DP in perpetuating the social/economic structure, but there have been isolated acts of terrorist violence directed at computer facilities since February 1969. There are many vulnerabilities in DP that terrorists could exploit for their own ends.     

Segmentation methods of fruit image based on color difference

Fruit image segmentation issue on color difference between mature fruits and backgrounds under natural illumination condition is an important and difficult content of fruit-harvesting robot vision. Some studies concerning fruit image segmentation have been presented in the last few years. However, these studies are focused on particular fruit and different from segmentation results. In this paper, four kinds of segmentation methods are presented and applied into fruit image segmentation. The tests show that these methods can segment successful several kinds of fruits image, such as apple, tomato, strawberry, persimmon and orange. Dynamic threshold segmentation method has better performance and least cost time than extended Otsu method, improved Otsu combined with genetic arithmetic and adaptive segmentation method based on LVQ network. Meanwhile, it has satisfactory effect upon fruit image under natural illumination condition. Adaptive segmentation method based on LVQ network can only be applied into balanced color instance of particular fruit, and it isn＇t adapt to be applied into real-time occasion because of high cost time.