CIS数据质量控制

本篇根据GIS具体应用实例。

A Preliminary Analysis of Phylogenetic Relationships in Cymbidium (Orchidaceae) Based on nrITS Sequence Data

The infrageneric classification currently in use for Cymbidium is based on gross morphology, with emphasis on the number of pollinia and state of fusion between lip and column. The sequences of nrDNA regions of 27 species and 3 cultivars of Cymbidium and 3 outgroup species ( Eulophia graminea, Geodorum densiflorum, Amitostigma pinguiculum) were analyzed using PCR amplification and direct DNA sequencing. The phylogenetic trees generated from maximum parsimony analysis, however, show that the existing division among three subgenera (subgen. Cymbidium , subgen. Cyperorchis and subgen. Jensoa ) should be evaluated with more data. Subgenus Cyperorchis was not a monophyletic group, with the unexpected nesting of C. dayanum (subgen. Cymbidium ) within it; subgenus Jensoa also appeared paraphyletic, with C. lancifolium being the sister group to the remainder of the genus; species of subgen. Cymbidium appeared polyphyletic, being split into several clades and intermixed with the main subgen. Cyperorchis and subgen. Jensoa clades, respectively. However, because of the insufficiency of informative characters of ITS sequences, some of the clades identified, especially the major lineages of Cymbidium , received relatively low support; sectional delimitations were also not clear within each subgenus. Further study is needed for achieving a robust phylogeny of Cymbidium .

Measuring technical efficiency of Chinese nonferrous metals enterprises on a background of industry consolidation

Since 2009, Chinese nonferrous metals industry has been carried out industry consolidation with strong support by the central government. This work examined technical efficiency of Chinese nonferrous metals firms and its change during the period of 2007 and 2011. Based on financial data from nonferrous metals listed companies, technical efficiency of nonferrous metal minerals mining firms and nonferrous metal smelting, pressing and processing firms was estimated respectively using the data envelopment analysis （DEA） method. It was found that, in both sectors, number of pure technical and scale inefficient firms dominated over efficient ones. Overall, their technical and scale efficiency tended to be very low after 2009. In particular, efficiency scores of nonferrous metal smelting, pressing and processing firms fluctuated greatly during the research period. And a limited number of large leading firms were able to maintain 100% efficiency score in the industry, while efficiency of most of other leading firms has declined since 2009.

The algorithm of 3D multi-scale volumetric curvature and its application

To fully extract and mine the multi-scale features of reservoirs and geologic structures in time/depth and space dimensions, a new 3D multi-scale volumetric curvature （MSVC） methodology is presented in this paper. We also propose a fast algorithm for computing 3D volumetric curvature. In comparison to conventional volumetric curvature attributes, its main improvements and key algorithms introduce multi-frequency components expansion in time-frequency domain and the corresponding multi-scale adaptive differential operator in the wavenumber domain, into the volumetric curvature calculation. This methodology can simultaneously depict seismic multi-scale features in both time and space. Additionally, we use data fusion of volumetric curvatures at various scales to take full advantage of the geologic features and anomalies extracted by curvature measurements at different scales. The 3D MSVC can highlight geologic anomalies and reduce noise at the same time. Thus, it improves the interpretation efficiency of curvature attributes analysis. The 3D MSVC is applied to both land and marine 3D seismic data. The results demonstrate that it can indicate the spatial distribution of reservoirs, detect faults and fracture zones, and identify their multi-scale properties.

Matrix Generator (MG): a Program for Creating 0/1 Matrix from Sized DNA Fragments

A computer program called Matrix Generator (MG) was developed for transforming sized DNA fragments into a presence/absence data matrix. Dynamic computation was run to avoid errors introduced using fixed-bin-width arithmetic. MG can be used with bin sized fragments from AFLP, ISSR, RAPD, RFLP, and other molecular markers. The accuracy of MG was tested using fAFLP data of Abelia and the results show that MG results in higher resolution of taxa and is more reliable than programs of the similar usage.

WEIGHTED ALGORITHM FOR FINGERPRINTING RELATIONAL DATABASES

The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm.

Estimation of As and Cu Contamination in Agricultural Soils Around a Mining Area by Reflectance Spectroscopy:A Case Study

Concentrations of Iron (Fe), As, and Cu in soil samples from the fields near the Baoshan Mine in Hunan Province, China, were analyzed and soil spectral reflectance was measured with an ASD FieldSpec FR spectroradiometer (Analytical Spectral Devices, Inc., USA) under laboratory condition. Partial least square regression (PLSR) models were constructed for predicting soil metal concentrations. The data pre-processing methods, first and second derivatives (FD and SD), baseline correction (BC), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR), were used for the spectral reflectance data pretreatments. Then, the prediction results were evaluated by relative root mean square error (RRMSE) and coefficients of determination (R 2 ). According to the criteria of minimal RRMSE and maximal R 2 , the PLSR models with the FD pretreatment (RRMSE = 0.24, R 2 = 0.61), SNV pretreatment (RRMSE = 0.08, R 2 = 0.78), and BC-pretreatment (RRMSE = 0.20, R 2 = 0.41) were considered as the final models for predicting As, Fe, and Cu, respectively. Wavebands at around 460, 1 400, 1 900, and 2 200 nm were selected as important spectral variables to construct final models. In conclusion, concentrations of heavy metals in contaminated soils could be indirectly assessed by soil spectra according to the correlation between the spectrally featureless components and Fe; therefore, spectral reflectance would be an alternative tool for monitoring soil heavy metals contamination.

Quality Assessment of Attribute Data in GIS Based on Simple Random Sampling

On the basis of the principles of simple random sampling, the statistical model of rate of disfigurement (RD) is put forward and described in detail. According to the definition of simple random sampling for the attribute data in GIS, the mean and variance of the RD are deduced as the characteristic value of the statistical model in order to explain the feasibility of the accuracy measurement of the attribute data in GIS by using the RD. Moreover, on the basis of the mean and variance of the RD, the quality assessment method for attribute data of vector maps during the data collecting is discussed. The RD spread graph is also drawn to see whether the quality of the attribute data is under control. The RD model can synthetically judge the quality of attribute data, which is different from other measurement coefficients that only discuss accuracy of classification.

Choosing meaningful structure data for improving web search

In order to improve the quality of web search,a new query expansion method by choosing meaningful structure data from a domain database is proposed.It categories attributes into three different classes,named as concept attribute,context attribute and meaningless attribute,according to their semantic features which are document frequency features and distinguishing capability features.It also defines the semantic relevance between two attributes when they have correlations in the database.Then it proposes trie-bitmap structure and pair pointer tables to implement efficient algorithms for discovering attribute semantic feature and detecting their semantic relevances.By using semantic attributes and their semantic relevances,expansion words can be generated and embedded into a vector space model with interpolation parameters.The experiments use an IMDB movie database and real texts collections to evaluate the proposed method by comparing its performance with a classical vector space model.The results show that the proposed method can improve text search efficiently and also improve both semantic features and semantic relevances with good separation capabilities.

QoS Evaluation for Web Service Recommendation

Web service recommendation is one of the most important fi elds of research in the area of service computing. The two core problems of Web service recommendation are the prediction of unknown Qo S property values and the evaluation of overall Qo S according to user preferences. Aiming to address these two problems and their current challenges, we propose two efficient approaches to solve these problems. First, unknown Qo S property values were predicted by modeling the high-dimensional Qo S data as tensors, by utilizing an important tensor operation, i.e., tensor composition, to predict these Qo S values. Our method, which considers all Qo S dimensions integrally and uniformly, allows us to predict multi-dimensional Qo S values accurately and easily. Second, the overall Qo S was evaluated by proposing an efficient user preference learning method, which learns user preferences based on users' ratings history data, allowing us to obtain user preferences quantifiably and accurately. By solving these two core problems, it became possible to compute a realistic value for the overall Qo S. The experimental results showed our proposed methods to be more efficient than existing methods.

Similarity measure design and similarity computation for discrete fuzzy data

The similarity computations for fuzzy membership function pairs were carried out.Fuzzy number related knowledge was introduced,and conventional similarity was compared with distance based similarity measure.The usefulness of the proposed similarity measure was verified.The results show that the proposed similarity measure could be applied to ordinary fuzzy membership functions,though it was not easy to design.Through conventional results on the calculation of similarity for fuzzy membership pair,fuzzy membership-crisp pair and crisp-crisp pair were carried out.The proposed distance based similarity measure represented rational performance with the heuristic point of view.Furthermore,troublesome in fuzzy number based similarity measure for abnormal universe of discourse case was discussed.Finally,the similarity measure computation for various membership function pairs was discussed with other conventional results.

Volatility forecasting in Chinese nonferrous metals futures market

This paper seeks to model and forecast the Chinese nonferrous metals futures market volatility and allows new insights into the time-varying volatility of realized volatility and leverage effects using high-frequency data.The LHAR-CJ model is extended and the empirical research on copper and aluminum futures in Shanghai Futures Exchange suggests the dynamic dependencies and time-varying volatility of realized volatility,which are captured by long memory HAR-GARCH model.Besides,the findings also show the significant weekly leverage effects in Chinese nonferrous metals futures market volatility.Finally,in-sample and out-of-sample forecasts are investigated,and the results show that the LHAR-CJ-G model,considering time-varyingvolatility of realized volatility and leverage effects,effectively improves the explanatory power as well as out-of sample predictive performance.

Developing a mathematical assessment model for blasting patterns management: Sungun copper mine

Blasting is one of the most important operations in the mining projects that has effective role in the whole operation physically and economically. Unsuitable blasting pattern may lead to unwanted events such as poor fragmentation, back break and fly rock. Multi attribute decision making(MADM) can be useful method for selecting the most appropriate blasting pattern among previously performed patterns. In this work, initially, from various already performed patterns, efficient and inefficient patterns are determined using data envelopment analysis(DEA). In the second step, after weighting impressive attributes using experts' opinion, elimination Et choice translating reality(ELECTRE) was used for ranking the efficient patterns and recognizing the most appropriate pattern in the Sungun Copper Mine, Iran. According to the obtained results, blasting pattern with the hole diameter of 15.24 cm, burden of 3 m, spacing of 4 m and stemming of 3.2 m has selected as the best pattern and has selected for future operation.

Heavy metals adsorption by banana peels micro-powder: Equilibrium modeling by non-linear models

In this study the copper and lead adsorption efficiency onto banana peels powder was investigated. The agroindustrial waste recovery represents one of the Circular Economy pillars. In the view of the synthesis of an environmentally friendly adsorbent material, the powder was used without any preliminary chemical or thermal activation, but only after simple washing, drying and grinding. The bio-adsorbent was characterized by the FTIR technique and tested in batch mode on synthetic aqueous solutions containing Pb and Cu in the range 10–90 mg·L^(-1). A selection of two(Langmuir, Freundlich) and three(Sips, Redlich–Peterson, Koble–Corrigan) parameter isotherm models was chosen to fit adsorption equilibrium data by non-linear regression procedure. The best fit isotherm model was selected relying on the error function with the lowest average percentage error(APE) value, among those characterized by the highest R^2 values. As expected, the three-parameter models are found to better represent both metals bio-adsorption, with APE and R^2 values always lower and higher, respectively, than the corresponding values obtained for the two-parameter models.

Volatility-volume relationship of Chinese copper and aluminum futures market

Following Bessembinder and Seguins,trading volume is separated into expected and unexpected components.Meanwhile,realized volatility is divided into continuous and discontinuous jump components.We make the empirical research to investigate the relationship between trading volume components and various realized volatility using1min high frequency data of Shanghai copper and aluminum futures.Moreover,the asymmetry of volatility-volume relationship is investigated.The results show that there is strong positive correlation between volatility and trading volume when realized volatility and its continuous component are considered.The relationship between trading volume and discontinuous jump component is ambiguous.The expected and unexpected trading volumes have positive influence on volatility.Furthermore,the unexpected trading volume,which is caused by arrival of new information,has a larger influence on price volatility.The findings also show that an asymmetric volatility-volume relationship indeed exists,which can be interpreted by the fact that trading volume has more explanatory power in positive realized semi-variance than negative realized semi-variance.The influence of positive trading volume shock on volatility is larger than that of negative trading volume shock,which reflects strong arbitrage in Chinese copper and aluminum futures markets.

The effects of attributes and buyer regret on overall satisfaction

The current study represents an attempt at exploring product attribute, service attribute evaluation, and buyer regret influence overall satisfaction in the buyer decision context. The data used in the project were collected as part of a large study of buyer regret. The sampling frame consisted of automobile purchases in Taiwan We have collected yield 600 questionnaires, by screening out 44 questionnaires, including those missing value or incomplete answer, and finally a usable sample of 556 questionnaires were utilized in this study. The results reinforce the finding form early research that the concept of buyer regret plays an important role for automobile purchases in the buyer decision. Results show that higher evaluations of service and product attributes lead to less buyer regret, and lower buyer regret will likely to increase overall satisfaction. Specifically, the finding indicates that buyer regret mediates the effects of the attributes on overall satisfactions. Implications for marketing theory and practitioners are discussed, and possible directions for future research are sketched.

Thermodynamic assessment of Mg-Ga binary system

In order to obtain the thermodynamic description of the Mg-Ga binary system,the thermodynamic assessment of the system was carried out using the CALPHAD method through Thermo-calc software package based on the evaluation of all available experimental data from the published literature.The solution phases,including liquid,hcp(Mg) and orthorhombic(Ga),were described by the substitutional solution model,of which the excess Gibbs energies were expressed with the Redlich-Kister polynomial.Meanwhile,all intermetallic compounds,Mg5Ga2,Mg2Ga,MgGa,MgGa2 and Mg2Ga5,were modeled as stoichiometric compounds.A set of self-consistent thermodynamic parameters formulating the Gibbs energies of various phases in the Mg-Ga binary system were obtained finally.The much better agreement is achieved between the calculated results and the reported experimental data.

Design of small-area multi-bit antifuse-type 1 kbit OTP memory

A multi-bit antifuse-type one-time programmable （OTP） memory is designed, which has a smaller area and a shorter programming time compared with the conventional single-bit antifuse-type OTP memory. While the conventional antifuse-type OTP memory can store a bit per cell, a proposed OTP memory can store two consecutive bits per cell through a data compression technique. The 1 kbit OTP memory designed with Magnachip 0.18 μm CMOS （complementary metal-oxide semiconductor） process is 34% smaller than the conventional single-bit antifuse-type OTP memory since the sizes of cell array and row decoder are reduced. And the programming time of the proposed OTP memory is nearly 50% smaller than that of the conventional counterpart since two consecutive bytes can be compressed and programmed into eight OTP cells at once. The layout area is 214 μm× 327 μ,, and the read current is simulated to be 30.4 μA.

First record of genera Rutilaria and Trigonium(Bacillariophyta) and 11 diatom taxa(species and varieties) in South China Sea

Diatom taxa in samples collected from the uppermost 1-cm sediment of the South China Sea （SCS） during cruises in 2000, 2001, and 2007 were investigated. Among them, two genera, Rutilaria and Trigoniurn, and 11 marine taxa （species and varieties） were described for the first time in China. The 11 taxa, Rutilaria radiata, Asterolampra grevillei, Biddulphia turrigera, Cocconeis cyclophora var. decora, Cocconeis ocellata, Dictyoneis rnarginata, Entogonia davyana, Tryblionella campechiana, Plagiogramma kinkeri, Plagiogramma nankoorense and Trigonium cf. contumax, were mainly extant species, although Rutilaria radiata and Entogonia davyana are fossils. Available data show that these species are mainly present in the eastern and western Pacific Ocean and the Indian Ocean. A large number of taxa newly recorded in this study were previously reported in the Philippines. The presence of these taxa in both locations is likely a result of seawater exchange in the SCS through the Bashi Channel Taxonomic descriptions, habitats, and distributions of each diatom taxon are provided herein.

Study of River Water Environment Simulation on WebGIS

Along with economic development, river pollution has become a serious phenomenon. It＇s rational to simulate variation of pollutants by using water quality model. Thus, relevant departments could take appropriate measures to improve the water environment. However, the traditional image of mathematical modeling is not intuitive. The advantage of WebGIS is the ability of visualization on web browser by the combination ofgeospatial data and pollution attribute data.