Identification of mine waters by statistical multivariate methods
Energy Technology Data Exchange (ETDEWEB)
Mali, N [IGGG, Ljubljana (Slovenia)
1992-01-01
Three water-bearing aquifers are present in the Velenje lignite mine. The aquifer waters have differing chemical composition; a geochemical water analysis can therefore determine the source of mine water influx. Mine water samples from different locations in the mine were analyzed, the results of chemical content and of electric conductivity of mine water were statistically processed by means of MICROGAS, SPSS-X and IN STATPAC computer programs, which apply three multivariate statistical methods (discriminate, cluster and factor analysis). Reliability of calculated values was determined with the Kolmogorov and Smirnov tests. It is concluded that laboratory analysis of single water samples can produce measurement errors, but statistical processing of water sample data can identify origin and movement of mine water. 15 refs.
HSM: Heterogeneous Subspace Mining in High Dimensional Data
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Seidl, Thomas
2009-01-01
Heterogeneous data, i.e. data with both categorical and continuous values, is common in many databases. However, most data mining algorithms assume either continuous or categorical attributes, but not both. In high dimensional data, phenomena due to the "curse of dimensionality" pose additional...... challenges. Usually, due to locally varying relevance of attributes, patterns do not show across the full set of attributes. In this paper we propose HSM, which defines a new pattern model for heterogeneous high dimensional data. It allows data mining in arbitrary subsets of the attributes that are relevant...... for the respective patterns. Based on this model we propose an efficient algorithm, which is aware of the heterogeneity of the attributes. We extend an indexing structure for continuous attributes such that HSM indexing adapts to different attribute types. In our experiments we show that HSM efficiently mines...
Mining Heterogeneous Information Networks by Exploring the Power of Links
Han, Jiawei
Knowledge is power but for interrelated data, knowledge is often hidden in massive links in heterogeneous information networks. We explore the power of links at mining heterogeneous information networks with several interesting tasks, including link-based object distinction, veracity analysis, multidimensional online analytical processing of heterogeneous information networks, and rank-based clustering. Some recent results of our research that explore the crucial information hidden in links will be introduced, including (1) Distinct for object distinction analysis, (2) TruthFinder for veracity analysis, (3) Infonet-OLAP for online analytical processing of information networks, and (4) RankClus for integrated ranking-based clustering. We also discuss some of our on-going studies in this direction.
Lehermeier, Christina; Schön, Chris-Carolin; de Los Campos, Gustavo
2015-09-01
Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to "correct" for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP. Copyright © 2015 by the Genetics Society of America.
Estimating correlation between multivariate longitudinal data in the presence of heterogeneity.
Gao, Feng; Philip Miller, J; Xiong, Chengjie; Luo, Jingqin; Beiser, Julia A; Chen, Ling; Gordon, Mae O
2017-08-17
Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121-0.420) and random slopes (ρ = 0.579, 95% CI: 0.349-0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125).
Tsuboi, Alice; Umetsu, Daiki; Kuranaga, Erina; Fujimoto, Koichi
2017-01-01
Cell populations in multicellular organisms show genetic and non-genetic heterogeneity, even in undifferentiated tissues of multipotent cells during development and tumorigenesis. The heterogeneity causes difference of mechanical properties, such as, cell bond tension or adhesion, at the cell–cell interface, which determine the shape of clonal population boundaries via cell sorting or mixing. The boundary shape could alter the degree of cell–cell contacts and thus influence the physiological consequences of sorting or mixing at the boundary (e.g., tumor suppression or progression), suggesting that the cell mechanics could help clarify the physiology of heterogeneous tissues. While precise inference of mechanical tension loaded at each cell–cell contacts has been extensively developed, there has been little progress on how to distinguish the population-boundary geometry and identify the cause of geometry in heterogeneous tissues. We developed a pipeline by combining multivariate analysis of clone shape with tissue mechanical simulations. We examined clones with four different genotypes within Drosophila wing imaginal discs: wild-type, tartan (trn) overexpression, hibris (hbs) overexpression, and Eph RNAi. Although the clones were previously known to exhibit smoothed or convoluted morphologies, their mechanical properties were unknown. By applying a multivariate analysis to multiple criteria used to quantify the clone shapes based on individual cell shapes, we found the optimal criteria to distinguish not only among the four genotypes, but also non-genetic heterogeneity from genetic one. The efficient segregation of clone shape enabled us to quantitatively compare experimental data with tissue mechanical simulations. As a result, we identified the mechanical basis contributed to clone shape of distinct genotypes. The present pipeline will promote the understanding of the functions of mechanical interactions in heterogeneous tissue in a non-invasive manner. PMID
Huang, Shuangbing; Liu, Changrong; Wang, Yanxin; Zhan, Hongbin
2014-01-01
The effects of various geochemical processes on arsenic enrichment in a high-arsenic aquifer at Jianghan Plain in Central China were investigated using multivariate models developed from combined adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR). The results indicated that the optimum variable group for the AFNIS model consisted of bicarbonate, ammonium, phosphorus, iron, manganese, fluorescence index, pH, and siderite saturation. These data suggest that reductive dissolution of iron/manganese oxides, phosphate-competitive adsorption, pH-dependent desorption, and siderite precipitation could integrally affect arsenic concentration. Analysis of the MLR models indicated that reductive dissolution of iron(III) was primarily responsible for arsenic mobilization in groundwaters with low arsenic concentration. By contrast, for groundwaters with high arsenic concentration (i.e., > 170 μg/L), reductive dissolution of iron oxides approached a dynamic equilibrium. The desorption effects from phosphate-competitive adsorption and the increase in pH exhibited arsenic enrichment superior to that caused by iron(III) reductive dissolution as the groundwater chemistry evolved. The inhibition effect of siderite precipitation on arsenic mobilization was expected to exist in groundwater that was highly saturated with siderite. The results suggest an evolutionary dominance of specific geochemical process over other factors controlling arsenic concentration, which presented a heterogeneous distribution in aquifers. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of Environmental Science and Health, Part A, to view the supplemental file.
Directory of Open Access Journals (Sweden)
Mostafa Nejadhadad
2017-11-01
Full Text Available A geochemical exploration program was applied to recognize the anomalous geochemical haloes at the Ravanj lead mine, Delijan, Iran. Sampling of unweathered rocks were undertaken across rock exposures on a 10 × 10 meter grid (n = 302 as well as the accessible parts of underground mine A (n = 42. First, the threshold values of all elements were determined using the cut-off values used in the exploratory data analysis (EDA method. Then, for further studies, elements with lognormal distributions (Pb, Zn, Ag, As, Cd, Co, Cu, Sb, S, Sr, Th, Ba, Bi, Fe, Ni and Mn were selected. Robustness against outliers is achieved by application of central log ratio transformation to address the closure problems with compositional data prior to principle components analysis (PCA. Results of these analyses show that, in the Ravanj deposit, Pb mineralization is characterized by a Pb-Ba-Ag-Sb ± Zn ± Cd association. The supra-mineralization haloes are characterized by barite and tetrahedrite in a Ba- Th- Ag- Cu- Sb- As- Sr association and sub-mineralization haloes are comprised of pyrite and tetrahedrite, probably reflecting a Fe-Cu-As-Bi-Ni-Co-Mo-Mn association. Using univariate and multivariate geostatistical analyses (e.g., EDA and robust PCA, four anomalies were detected and mapped in Block A of the Ravanj deposit. Anomalies 1 and 2 are around the ancient orebodies. Anomaly 3 is located in a thin bedded limestone-shale intercalation unit that does not show significant mineralization. Drilling of the fourth anomaly suggested a low grade, non-economic Pb mineralization.
Blasting methods for heterogeneous rocks in hillside open-pit mines with high and steep slopes
Chen, Y. J.; Chang, Z. G.; Chao, X. H.; Zhao, J. F.
2017-06-01
In the arid desert areas in Xinjiang, most limestone quarries are hillside open-pit mines (OPMs) where the limestone is hard, heterogeneous, and fractured, and can be easily broken into large blocks by blasting. This study tried to find effective technical methods for blasting heterogeneous rocks in such quarries based on an investigation into existing problems encountered in actual mining at Hongshun Limestone Quarry in Xinjiang. This study provided blasting schemes for hillside OPMs with different heights and slopes. These schemes involve the use of vertical deep holes, oblique shallow holes, and downslope hole-by-hole sublevel or simultaneous detonation techniques. In each bench, the detonations of holes in a detonation unit occur at intervals of 25-50 milliseconds. The research findings can offer technical guidance on how to blast heterogeneous rocks in hillside limestone quarries.
Czech Academy of Sciences Publication Activity Database
Čech, František; Baruník, Jozef
2017-01-01
Roč. 36, č. 1 (2017), s. 181-206 ISSN 0277-6693 R&D Projects: GA ČR GA13-32263S Institutional support: RVO:67985556 Keywords : Multivariate volatility * realized covariance * portfolio optimisation Subject RIV: AH - Economic s OBOR OECD: Economic Theory Impact factor: 0.747, year: 2016 http://library.utia.cas.cz/separaty/2017/E/barunik-0478479.pdf
Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.
Li, Jun; Zhao, Patrick X
2016-01-01
Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.
Multivariate statistical methods and data mining in particle physics (4/4)
CERN. Geneva
2008-01-01
The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.
Multivariate statistical methods and data mining in particle physics (2/4)
CERN. Geneva
2008-01-01
The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.
Multivariate statistical methods and data mining in particle physics (1/4)
CERN. Geneva
2008-01-01
The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.
Rakotondrabe, Felaniaina; Ndam Ngoupayou, Jules Remy; Mfonka, Zakari; Rasolomanana, Eddy Harilala; Nyangono Abolo, Alexis Jacob; Ako Ako, Andrew
2018-01-01
The influence of gold mining activities on the water quality in the Mari catchment in Bétaré-Oya (East Cameroon) was assessed in this study. Sampling was performed within the period of one hydrological year (2015 to 2016), with 22 sampling sites consisting of groundwater (06) and surface water (16). In addition to measuring the physicochemical parameters, such as pH, electrical conductivity, alkalinity, turbidity, suspended solids and CN - , eleven major elements (Na + , K + , Ca 2+ , Mg 2+ , NH 4 + , Cl - , NO 3 - , HCO 3 - , SO 4 2- , PO 4 3- and F - ) and eight heavy metals (Pb, Zn, Cd, Fe, Cu, As, Mn and Cr) were also analyzed using conventional hydrochemical methods, Multivariate Statistical Analysis and the Heavy metal Pollution Index (HPI). The results showed that the water from Mari catchment and Lom River was acidic to basic (5.40water quality, except for nitrates in some wells, which was found at a concentration >50mg NO 3 - /L. This water was found as two main types: calcium magnesium bicarbonate (CaMg-HCO 3 ), which was the most represented, and sodium bicarbonate potassium (NaK-HCO 3 ). As for trace elements in surface water, the contents of Pb, Cd, Mn, Cr and Fe were higher than recommended by the WHO guidelines, and therefore, the surface water was unsuitable for human consumption. Three phenomena were responsible for controlling the quality of the water in the study area: hydrolysis of silicate minerals of plutono-metamorphic rocks, which constitute the geological basement of this area; vegetation and soil leaching; and mining activities. The high concentrations of TSS and trace elements found in this basin were mainly due to gold mining activities (exploration and exploitation) as well as digging of rivers beds, excavation and gold amalgamation. Copyright © 2017 Elsevier B.V. All rights reserved.
Liu, Jun; Hua, Zheng-Shuang; Chen, Lin-Xing; Kuang, Jia-Liang; Li, Sheng-Jin; Shu, Wen-Sheng
2014-01-01
Recent molecular surveys have advanced our understanding of the forces shaping the large-scale ecological distribution of microbes in Earth's extreme habitats, such as hot springs and acid mine drainage. However, few investigations have attempted dense spatial analyses of specific sites to resolve the local diversity of these extraordinary organisms and how communities are shaped by the harsh environmental conditions found there. We have applied a 16S rRNA gene-targeted 454 pyrosequencing approach to explore the phylogenetic differentiation among 90 microbial communities from a massive copper tailing impoundment generating acidic drainage and coupled these variations in community composition with geochemical parameters to reveal ecological interactions in this extreme environment. Our data showed that the overall microbial diversity estimates and relative abundances of most of the dominant lineages were significantly correlated with pH, with the simplest assemblages occurring under extremely acidic conditions and more diverse assemblages associated with neutral pHs. The consistent shifts in community composition along the pH gradient indicated that different taxa were involved in the different acidification stages of the mine tailings. Moreover, the effect of pH in shaping phylogenetic structure within specific lineages was also clearly evident, although the phylogenetic differentiations within the Alphaproteobacteria, Deltaproteobacteria, and Firmicutes were attributed to variations in ferric and ferrous iron concentrations. Application of the microbial assemblage prediction model further supported pH as the major factor driving community structure and demonstrated that several of the major lineages are readily predictable. Together, these results suggest that pH is primarily responsible for structuring whole communities in the extreme and heterogeneous mine tailings, although the diverse microbial taxa may respond differently to various environmental conditions
Zhang, Jun; Yao, Duoxi; Su, Yue
2018-02-01
Under the current situation of energy demand, coal is still one of the major energy sources in China for a certain period of time, so the task of coal mine safety production remains arduous. In order to identify the water source of the mine accurately, this article takes the example from Renlou and Tongting coal mines in the northern Anhui mining area. A total of 7 conventional water chemical indexes were selected, including Ca2+, Mg2+, Na++K+, Cl-, SO4 2-, HCO3 - and TDS, to establish a multivariate matrix model for the source identifying inrush water. The results show that the model is simple and is rarely limited by the quantity of water samples, and the recognition effect is ideal, which can be applied to the control and treatment for water inrush.
Smith, Richard N; Aleksic, Jelena; Butano, Daniela; Carr, Adrian; Contrino, Sergio; Hu, Fengyuan; Lyne, Mike; Lyne, Rachel; Kalderimis, Alex; Rutherford, Kim; Stepan, Radek; Sullivan, Julie; Wakeling, Matthew; Watkins, Xavier; Micklem, Gos
2012-12-01
InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. Freely available from http://www.intermine.org under the LGPL license. g.micklem@gen.cam.ac.uk Supplementary data are available at Bioinformatics online.
Pujiwati, Arie; Nakamura, K.; Watanabe, N.; Komai, T.
2018-02-01
Multivariate analysis is applied to investigate geochemistry of several trace elements in top soils and their relation with the contamination source as the influence of coal mines in Jorong, South Kalimantan. Total concentration of Cd, V, Co, Ni, Cr, Zn, As, Pb, Sb, Cu and Ba was determined in 20 soil samples by the bulk analysis. Pearson correlation is applied to specify the linear correlation among the elements. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied to observe the classification of trace elements and contamination sources. The results suggest that contamination loading is contributed by Cr, Cu, Ni, Zn, As, and Pb. The elemental loading mostly affects the non-coal mining area, for instances the area near settlement and agricultural land use. Moreover, the contamination source is classified into the areas that are influenced by the coal mining activity, the agricultural types, and the river mixing zone. Multivariate analysis could elucidate the elemental loading and the contamination sources of trace elements in the vicinity of coal mine area.
Liu, Pu; Hoth, Nils; Drebenstedt, Carsten; Sun, Yajun; Xu, Zhimin
2017-12-01
Groundwater is an important drinking water resource that requires protection in North China. Coal mining industry in the area may influence the water quality evolution. To provide primary characterization of the hydrogeochemical processes and paths that control the water quality evolution, a complex multi-layer groundwater system in a coal mining area is investigated. Multivariate statistical methods involving hierarchical cluster analysis (HCA) and principal component analysis (PCA) are applied, 6 zones and 3 new principal components are classified as major reaction zones and reaction factors. By integrating HCA and PCA with hydrogeochemical correlations analysis, potential phases, reactions and connections between various zones are presented. Carbonates minerals, gypsum, clay minerals as well as atmosphere gases - CO 2 , H 2 O and NH 3 are recognized as major reactants. Mixtures, evaporation, dissolution/precipitation of minerals and cation exchange are potential reactions. Inverse modeling is finally used, and it verifies the detailed processes and diverse paths. Consequently, 4 major paths are found controlling the variations of groundwater chemical properties. Shallow and deep groundwater is connected primarily by the flow of deep groundwater up through fractures and faults into the shallow aquifers. Mining does not impact the underlying aquifers that represent the most critical groundwater resource. But controls should be taken to block the mixing processes from highly polluted mine water. The paper highlights the complex hydrogeochemical evolution of a multi-layer groundwater system under mining impact, which could be applied to further groundwater quality management in the study area, as well as most of the other coalfields in North China. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Henry Jeremy Bockholt
2010-04-01
Full Text Available A neuroinformatics (NI system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN, database system has been designed and improved through our experience with 200 research studies and 250 researchers from 7 different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining.
Bockholt, Henry J.; Scully, Mark; Courtney, William; Rachakonda, Srinivas; Scott, Adam; Caprihan, Arvind; Fries, Jill; Kalyanam, Ravi; Segall, Judith M.; de la Garza, Raul; Lane, Susan; Calhoun, Vince D.
2009-01-01
A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining. PMID:20461147
An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity
Directory of Open Access Journals (Sweden)
Yu Wang
2014-01-01
Full Text Available Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH, to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same class. After the removal of outliers, relevance of features in each cluster is calculated based on their variations in this cluster. The feature relevance is incorporated into distance calculation for classification. The main advantage of SCCFSH lies in the fact that it is capable of solving a classification problem with feature space heterogeneity in an incremental way, which is favorable for online classification tasks with continuously changing data. Experimental results on a series of data sets and application to a database marketing problem show the efficiency and effectiveness of the proposed approach.
Zong, Nansu; Kim, Hyeoneui; Ngo, Victoria; Harismendy, Olivier
2017-08-01
A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and their targets. Deep learning reveals features of vertices of a large network that can be adapted in accommodating the similarity-based solutions to provide a flexible method of drug-target prediction. We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure. DeepWalk, a deep learning method, is adopted in this study to calculate the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets. This proposed method shows promising results for drug-target association prediction: 98.96% AUC ROC score with a 10-fold cross-validation and 99.25% AUC ROC score with a Monte Carlo cross-validation with LTN. By utilizing DeepWalk, we demonstrate that: (i) this method outperforms other existing topology-based similarity computation methods, (ii) the performance is better for tripartite than with bipartite networks and (iii) the measure of similarity using network topology outperforms the ones derived from chemical structure (drugs) or genomic sequence (targets). Our proposed methodology proves to be capable of providing a promising solution for drug-target prediction based on topological similarity with a heterogeneous network, and may be readily re-purposed and adapted in the existing of similarity-based methodologies. The proposed method has been developed in JAVA and it is available, along with the data at the following URL: https://github.com/zongnansu1982/drug-target-prediction . nazong@ucsd.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.
Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain
2015-10-01
Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.
Directory of Open Access Journals (Sweden)
Khairullah Khan
2014-09-01
Full Text Available Opinion mining is an interesting area of research because of its applications in various fields. Collecting opinions of people about products and about social and political events and problems through the Web is becoming increasingly popular every day. The opinions of users are helpful for the public and for stakeholders when making certain decisions. Opinion mining is a way to retrieve information through search engines, Web blogs and social networks. Because of the huge number of reviews in the form of unstructured text, it is impossible to summarize the information manually. Accordingly, efficient computational methods are needed for mining and summarizing the reviews from corpuses and Web documents. This study presents a systematic literature survey regarding the computational techniques, models and algorithms for mining opinion components from unstructured reviews.
Appels, Willemijn M.; Ireson, Andrew M.; Barbour, S. Lee
2018-02-01
Mine waste rock dumps have highly variable flowpaths caused by contrasting textures and geometry of materials laid down during the 'plug dumping' process. Numerical experiments were conducted to investigate how these characteristics control unsaturated zone flow and transport. Hypothetical profiles of inner-lift structure were generated with multiple point statistics and populated with hydraulic parameters of a finer and coarser material. Early arrival of water and solutes at the bottom of the lifts was observed after spring snowmelt. The leaching efficiency, a measure of the proportion of a resident solute that is flushed out of the rock via infiltrating snowmelt or rainfall, was consistently high, but modified by the structure and texture of the lift. Under high rates of net percolation during snowmelt, preferential flow was generated in coarse textured part of the rock, and solutes in the fine textured parts of the rock remained stagnant. Under lower rates of net percolation during the summer and fall, finer materialswere flushed too, and the spatial variability of solute concentration in the lift was reduced. Layering of lifts leads to lower flow rates at depth, minimizing preferential flow and increased leaching of resident solutes. These findings highlight the limited role of large scale connected geometries on focusing flow and transport under dynamic surface net percolation conditions. As such, our findings agree with recent numerical results from soil studies with Gaussian connected geometries as well as recent experimental findings, emphasizing the dominant role of matrix flow and high leaching efficiency in large waste rock dumps.
Information Mining from Heterogeneous Data Sources: A Case Study on Drought Predictions
Directory of Open Access Journals (Sweden)
Getachew B. Demisse
2017-07-01
Full Text Available The objective of this study was to develop information mining methodology for drought modeling and predictions using historical records of climate, satellite, environmental, and oceanic data. The classification and regression tree (CART approach was used for extracting drought episodes at different time-lag prediction intervals. Using the CART approach, a number of successful model trees were constructed, which can easily be interpreted and used by decision makers in their drought management decisions. The regression rules produced by CART were found to have correlation coefficients from 0.71–0.95 in rules-alone modeling. The accuracies of the models were found to be higher in the instance and rules model (0.77–0.96 compared to the rules-alone model. From the experimental analysis, it was concluded that different combinations of the nearest neighbor and committee models significantly increase the performances of CART drought models. For more robust results from the developed methodology, it is recommended that future research focus on selecting relevant attributes for slow-onset drought episode identification and prediction.
Garcia Nieto, P J; Sánchez Lasheras, F; de Cos Juez, F J; Alonso Fernández, J R
2011-11-15
There is an increasing need to describe cyanobacteria blooms since some cyanobacteria produce toxins, termed cyanotoxins. These latter can be toxic and dangerous to humans as well as other animals and life in general. It must be remarked that the cyanobacteria are reproduced explosively under certain conditions. This results in algae blooms, which can become harmful to other species if the cyanobacteria involved produce cyanotoxins. In this research work, the evolution of cyanotoxins in Trasona reservoir (Principality of Asturias, Northern Spain) was studied with success using the data mining methodology based on multivariate adaptive regression splines (MARS) technique. The results of the present study are two-fold. On one hand, the importance of the different kind of cyanobacteria over the presence of cyanotoxins in the reservoir is presented through the MARS model and on the other hand a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained. The agreement of the MARS model with experimental data confirmed the good performance of the same one. Finally, conclusions of this innovative research are exposed. Copyright © 2011 Elsevier B.V. All rights reserved.
Cobin, P. F.; Oommen, T.; Gierke, J. S.
2013-12-01
The Lake Atitlán watershed is home to approximately 200,000 people and is located in the western highlands of Guatemala. Steep slopes, highly susceptible to landslides during the rainy season, characterize the region. Typically these landslides occur during high-intensity precipitation events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. Different datasets of landslide and non-landslide points across the watershed were used to compare model success at a small scale and regional scale. This study used data from multiple attributes: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The open source software Weka was used for the data mining. Several attribute selection methods were applied to the data to predetermine the potential landslide causative influence. Different multivariate algorithms were then evaluated for their ability to predict landslide occurrence. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The attribute combinations of the most successful models were compared to the attribute evaluator results. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points for the regions selected in the watershed. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.
Isinkaye, Omoniyi Matthew
2018-02-01
The Itakpe abandoned iron-ore mines constitute the largest iron-ore deposits in Nigeria with an estimated reserve of about three million metric tons of ore. The present effort is a part of a comprehensive study to estimate the environmental and radiological health hazards associated with previous mining operations in the study area. In this regard, heavy metals (Fe, Zn, Cu, Cd, Cr, Mn, Pb, Ni, Co and As) and natural radionuclides (U, Th and K) were measured in rock, soil and water samples collected at different locations within the mining sites. Atomic absorption and gamma-ray spectrometry were utilized for the measurements. Fe, Mn, Zn, Cu, Ni, Cd, Cr, Co Pb and As were detected at varying concentrations in rock and soil samples. Cd, Cr, Pb and As were not detected in water samples. The concentrations of heavy metals vary according to the following pattern; rock ˃ soil ˃ water. The mean elemental concentrations of K, U and Th are 2.9%, 0.8 and 1.2 ppm and 1.3%, 0.7 and 1.7 ppm, respectively, for rock and soil samples. Pearson correlation analyses of the results indicate that the heavy metals are mostly negatively correlated with natural radionuclides in the study area. Cancer and non-cancer risks due to heavy metals and radiological hazards due to natural radionuclides to the population living within the vicinity of the abandoned mines are lower than acceptable limits. It can, therefore, be concluded that no significant environmental or radiological health hazard is envisaged.
Introduction to multivariate discrimination
Kégl, Balázs
2013-07-01
Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either
Introduction to multivariate discrimination
International Nuclear Information System (INIS)
Kegl, B.
2013-01-01
Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyper-parameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either
Multivariate statistical assessment of coal properties
Czech Academy of Sciences Publication Activity Database
Klika, Z.; Serenčíšová, J.; Kožušníková, Alena; Kolomazník, I.; Študentová, S.; Vontorová, J.
2014-01-01
Roč. 128, č. 128 (2014), s. 119-127 ISSN 0378-3820 R&D Projects: GA MŠk ED2.1.00/03.0082 Institutional support: RVO:68145535 Keywords : coal properties * structural,chemical and petrographical properties * multivariate statistics Subject RIV: DH - Mining, incl. Coal Mining Impact factor: 3.352, year: 2014 http://dx.doi.org/10.1016/j.fuproc.2014.06.029
Multivariate analysis with LISREL
Jöreskog, Karl G; Y Wallentin, Fan
2016-01-01
This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.
J Olive, David
2017-01-01
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...
2014-01-01
Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as "big data", that is, are huge, heterogeneous, complex, distributed, etc. Data mining is a series of processes which include collecting and accumulating data, modeling phenomena, and discovering new information, and it is one of the most important steps to scientific analysis of the processes of services. Data mining application in services requires a thorough understanding of the characteristics of each service and knowledge of the compatibility of data mining technology within each particular service, rather than knowledge only in calculation speed and prediction accuracy. Varied examples of services provided in this book will help readers understand the relation between services and data mining technology. This book is intended to stimulate interest among researchers and practitioners in the relation between data mining technology and its application to ...
Continuous multivariate exponential extension
International Nuclear Information System (INIS)
Block, H.W.
1975-01-01
The Freund-Weinman multivariate exponential extension is generalized to the case of nonidentically distributed marginal distributions. A fatal shock model is given for the resulting distribution. Results in the bivariate case and the concept of constant multivariate hazard rate lead to a continuous distribution related to the multivariate exponential distribution (MVE) of Marshall and Olkin. This distribution is shown to be a special case of the extended Freund-Weinman distribution. A generalization of the bivariate model of Proschan and Sullo leads to a distribution which contains both the extended Freund-Weinman distribution and the MVE
Methods of Multivariate Analysis
Rencher, Alvin C
2012-01-01
Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life sit
DEFF Research Database (Denmark)
Silvennoinen, Annastiina; Teräsvirta, Timo
This article contains a review of multivariate GARCH models. Most common GARCH models are presented and their properties considered. This also includes nonparametric and semiparametric models. Existing specification and misspecification tests are discussed. Finally, there is an empirical example...
Multivariate Time Series Search
National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...
The United States and the Navajo Nation entered into settlement agreements that provide funds to conduct investigations and any needed cleanup at 16 of the 46 priority mines, including six mines in the Northern Abandoned Uranium Mine Region.
Modeling Covariance Breakdowns in Multivariate GARCH
Jin, Xin; Maheu, John M
2014-01-01
This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation of the conditional covariance matrix from its implied MGARCH dynamics. This is captured through a flexible stochastic component that allows for changes in the conditional variances, covariances and impl...
Data Mining Aplications in Livestock
Directory of Open Access Journals (Sweden)
Feyza ALEV ÇETİN
2016-03-01
Full Text Available Data mining provides discovering the required and applicable knowledge from very large amounts of information collected in one centre. Data mining has been used in the information industry and society. Although many methods of data mining has been used, these techniques has been remarkable in animal husbandry in recent years. For the solution of complex problems in animal husbandry many methods were discussed and developed. Brief information on data mining techniques such as k-means approach, k-nearest neighbor approach, multivariate adaptive regression function (MARS, naive Bayesian classifiers (NBC, artificial neural networks (ANN, support vector machines (SVM, decision trees are given in the study. Some data mining methods are presented and examples of the application of data mining in the field of animal husbandry in the world are provided with this study.
Multivariate Birkhoff interpolation
Lorentz, Rudolph A
1992-01-01
The subject of this book is Lagrange, Hermite and Birkhoff (lacunary Hermite) interpolation by multivariate algebraic polynomials. It unifies and extends a new algorithmic approach to this subject which was introduced and developed by G.G. Lorentz and the author. One particularly interesting feature of this algorithmic approach is that it obviates the necessity of finding a formula for the Vandermonde determinant of a multivariate interpolation in order to determine its regularity (which formulas are practically unknown anyways) by determining the regularity through simple geometric manipulations in the Euclidean space. Although interpolation is a classical problem, it is surprising how little is known about its basic properties in the multivariate case. The book therefore starts by exploring its fundamental properties and its limitations. The main part of the book is devoted to a complete and detailed elaboration of the new technique. A chapter with an extensive selection of finite elements follows as well a...
Applied multivariate statistical analysis
Härdle, Wolfgang Karl
2015-01-01
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added. All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior. All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...
A MULTIVARIATE WEIBULL DISTRIBUTION
Directory of Open Access Journals (Sweden)
Cheng Lee
2010-07-01
Full Text Available A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu and Bhattacharyya. From the survival function, the probability density function, the cumulative probability function, the determinant of the Jacobian Matrix, and the general moment are derived.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger
We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...
DEFF Research Database (Denmark)
Hansen, Michael Adsetts Edberg
Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set...
Multivariate pattern dependence.
Directory of Open Access Journals (Sweden)
Stefano Anzellotti
2017-11-01
Full Text Available When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD: a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS and to the fusiform face area (FFA, using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.
Skopina, Maria; Protasov, Vladimir
2016-01-01
This book presents a systematic study of multivariate wavelet frames with matrix dilation, in particular, orthogonal and bi-orthogonal bases, which are a special case of frames. Further, it provides algorithmic methods for the construction of dual and tight wavelet frames with a desirable approximation order, namely compactly supported wavelet frames, which are commonly required by engineers. It particularly focuses on methods of constructing them. Wavelet bases and frames are actively used in numerous applications such as audio and graphic signal processing, compression and transmission of information. They are especially useful in image recovery from incomplete observed data due to the redundancy of frame systems. The construction of multivariate wavelet frames, especially bases, with desirable properties remains a challenging problem as although a general scheme of construction is well known, its practical implementation in the multidimensional setting is difficult. Another important feature of wavelet is ...
Multivariate calculus and geometry
Dineen, Seán
2014-01-01
Multivariate calculus can be understood best by combining geometric insight, intuitive arguments, detailed explanations and mathematical reasoning. This textbook has successfully followed this programme. It additionally provides a solid description of the basic concepts, via familiar examples, which are then tested in technically demanding situations. In this new edition the introductory chapter and two of the chapters on the geometry of surfaces have been revised. Some exercises have been replaced and others provided with expanded solutions. Familiarity with partial derivatives and a course in linear algebra are essential prerequisites for readers of this book. Multivariate Calculus and Geometry is aimed primarily at higher level undergraduates in the mathematical sciences. The inclusion of many practical examples involving problems of several variables will appeal to mathematics, science and engineering students.
Intelligent multivariate process supervision
International Nuclear Information System (INIS)
Visuri, Pertti.
1986-01-01
This thesis addresses the difficulties encountered in managing large amounts of data in supervisory control of complex systems. Some previous alarm and disturbance analysis concepts are reviewed and a method for improving the supervision of complex systems is presented. The method, called multivariate supervision, is based on adding low level intelligence to the process control system. By using several measured variables linked together by means of deductive logic, the system can take into account the overall state of the supervised system. Thus, it can present to the operators fewer messages with higher information content than the conventional control systems which are based on independent processing of each variable. In addition, the multivariate method contains a special information presentation concept for improving the man-machine interface. (author)
Multivariate rational data fitting
Cuyt, Annie; Verdonk, Brigitte
1992-12-01
Sections 1 and 2 discuss the advantages of an object-oriented implementation combined with higher floating-point arithmetic, of the algorithms available for multivariate data fitting using rational functions. Section 1 will in particular explain what we mean by "higher arithmetic". Section 2 will concentrate on the concepts of "object orientation". In sections 3 and 4 we shall describe the generality of the data structure that can be dealt with: due to some new results virtually every data set is acceptable right now, with possible coalescence of coordinates or points. In order to solve the multivariate rational interpolation problem the data sets are fed to different algorithms depending on the structure of the interpolation points in then-variate space.
Transient multivariable sensor evaluation
Energy Technology Data Exchange (ETDEWEB)
Vilim, Richard B.; Heifetz, Alexander
2017-02-21
A method and system for performing transient multivariable sensor evaluation. The method and system includes a computer system for identifying a model form, providing training measurement data, generating a basis vector, monitoring system data from sensor, loading the system data in a non-transient memory, performing an estimation to provide desired data and comparing the system data to the desired data and outputting an alarm for a defective sensor.
Purchasing Power Parity and Heterogeneous Mean Reversion
C.G. Koedijk (Kees); B. Tims (Ben); M.A. van Dijk (Mathijs)
2005-01-01
textabstractThis paper analyzes the properties of multivariate tests of purchasing power parity (PPP) that fail to take heterogeneity in the speed of mean reversion across real exchange rates into account. We compare the performance of homogeneous and heterogeneous unit root testing methodologies.
Multivariate statistical analysis of major and trace element data for ...
African Journals Online (AJOL)
Multivariate statistical analysis of major and trace element data for niobium exploration in the peralkaline granites of the anorogenic ring-complex province of Nigeria. PO Ogunleye, EC Ike, I Garba. Abstract. No Abstract Available Journal of Mining and Geology Vol.40(2) 2004: 107-117. Full Text: EMAIL FULL TEXT EMAIL ...
Mine drivage in hydraulic mines
Energy Technology Data Exchange (ETDEWEB)
Ehkber, B Ya
1983-09-01
From 20 to 25% of labor cost in hydraulic coal mines falls on mine drivage. Range of mine drivage is high due to the large number of shortwalls mined by hydraulic monitors. Reducing mining cost in hydraulic mines depends on lowering drivage cost by use of new drivage systems or by increasing efficiency of drivage systems used at present. The following drivage methods used in hydraulic mines are compared: heading machines with hydraulic haulage of cut rocks and coal, hydraulic monitors with hydraulic haulage, drilling and blasting with hydraulic haulage of blasted rocks. Mining and geologic conditions which influence selection of the optimum mine drivage system are analyzed. Standardized cross sections of mine roadways driven by the 3 methods are shown in schemes. Support systems used in mine roadways are compared: timber supports, roof bolts, roof bolts with steel elements, and roadways driven in rocks without a support system. Heading machines (K-56MG, GPKG, 4PU, PK-3M) and hydraulic monitors (GMDTs-3M, 12GD-2) used for mine drivage are described. Data on mine drivage in hydraulic coal mines in the Kuzbass are discussed. From 40 to 46% of roadways are driven by heading machines with hydraulic haulage and from 12 to 15% by hydraulic monitors with hydraulic haulage.
Control Multivariable por Desacoplo
Directory of Open Access Journals (Sweden)
Fernando Morilla
2013-01-01
Full Text Available Resumen: La interacción entre variables es una característica inherente de los procesos multivariables, que dificulta su operación y el diseño de sus sistemas de control. Bajo el paradigma de Control por desacoplo se agrupan un conjunto de metodologías, que tradicionalmente han estado orientadas a eliminar o reducir la interacción, y que recientemente algunos investigadores han reorientado con objetivos de solucionar un problema tan complejo como es el control multivariable. Parte del material descrito en este artículo es bien conocido en el campo del control de procesos, pero la mayor parte de él son resultados de varios años de investigación de los autores en los que han primado la generalización del problema, la búsqueda de soluciones de fácil implementación y la combinación de bloques elementales de control PID. Esta conjunción de intereses provoca que no siempre se pueda conseguir un desacoplo perfecto, pero que sí se pueda conseguir una considerable reducción de la interacción en el nivel básico de la pirámide de control, en beneficio de otros sistemas de control que ocupan niveles jerárquicos superiores. El artículo resume todos los aspectos básicos del Control por desacoplo y su aplicación a dos procesos representativos: una planta experimental de cuatro tanques acoplados y un modelo 4×4 de un sistema experimental de calefacción, ventilación y aire acondicionado. Abstract: The interaction between variables is inherent in multivariable processes and this fact may complicate their operation and control system design. Under the paradigm of decoupling control, several methodologies that traditionally have been addressed to cancel or reduce the interactions are gathered. Recently, this approach has been reoriented by several researchers with the aim to solve such a complex problem as the multivariable control. Parts of the material in this work are well known in the process control field; however, most of them are
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger
2011-01-01
We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...
Fürnkranz, Johannes
The World-Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. This chapter provides a brief overview of web mining techniques and research areas, most notably hypertext classification, wrapper induction, recommender systems and web usage mining.
Trybula, Walter J.
1999-01-01
Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…
Robert Leopold; Bruce Rowland; Reed Stalder
1979-01-01
The surface mining process consists of four phases: (1) exploration; (2) development; (3) production; and (4) reclamation. A variety of surface mining methods has been developed, including strip mining, auger, area strip, open pit, dredging, and hydraulic. Sound planning and design techniques are essential to implement alternatives to meet the myriad of laws,...
International Nuclear Information System (INIS)
Lange, G.
1975-01-01
The winning of uranium ore is the first stage of the fuel cycle. The whole complex of questions to be considered when evaluating the profitability of an ore mine is shortly outlined, and the possible mining techniques are described. Some data on uranium mining in the western world are also given. (RB) [de
International Nuclear Information System (INIS)
Moura Neto, C. de; Nair, R.P.K.
1979-08-01
The microscopic study of a cell is meant for the determination of the infinite multiplication factor of the cell, which is given by the four factor formula: K(infinite) = n(epsilon)pf. The analysis of an homogeneous reactor is similar to that of an heterogeneous reactor, but each factor of the four factor formula can not be calculated by the formulas developed in the case of an homogeneous reactor. A great number of methods was developed for the calculation of heterogeneous reactors and some of them are discussed. (Author) [pt
Directory of Open Access Journals (Sweden)
2016-12-01
Full Text Available This paper is on data analysis strategy in a complex, multidimensional, and dynamic domain. The focus is on the use of data mining techniques to explore the importance of multivariate structures; using climate variables which influences climate change. Techniques involved in data mining exercise vary according to the data structures. The multivariate analysis strategy considered here involved choosing an appropriate tool to analyze a process. Factor analysis is introduced into data mining technique in order to reveal the influencing impacts of factors involved as well as solving for multicolinearity effect among the variables. The temporal nature and multidimensionality of the target variables is revealed in the model using multidimensional regression estimates. The strategy of integrating the method of several statistical techniques, using climate variables in Nigeria was employed. R2 of 0.518 was obtained from the ordinary least square regression analysis carried out and the test was not significant at 5% level of significance. However, factor analysis regression strategy gave a good fit with R2 of 0.811 and the test was significant at 5% level of significance. Based on this study, model building should go beyond the usual confirmatory data analysis (CDA, rather it should be complemented with exploratory data analysis (EDA in order to achieve a desired result.
Contract Mining versus Owner Mining
African Journals Online (AJOL)
Owner
mining companies can concentrate on their core businesses while using specialists for ... 2 Definition of Contract and Owner. Mining ... equipment maintenance, scheduling and budgeting ..... No. Region. Amount Spent on. Contract Mining. ($ billion). Percent of. Total. 1 ... cost and productivity data based on a large range.
Multivariable calculus with applications
Lax, Peter D
2017-01-01
This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems to partial derivatives, multiple integrals, Stokes’ and divergence theorems. Students with a background in single variable calculus are guided through a variety of problem solving techniques and practice problems. Examples from the physical sciences are utilized to highlight the essential relationship between calculus and modern science. The symbiotic relationship between science and mathematics is shown by deriving and discussing several conservation laws, and vector calculus is utilized to describe a number of physical theories via partial differential equations. Students will learn that mathematics is the language that enables scientific ideas to be precisely formulated and that science is a source for the development of mathemat...
Multivariate Statistical Process Control
DEFF Research Database (Denmark)
Kulahci, Murat
2013-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...
Applied data mining for business and industry
Giudici, Paolo
2009-01-01
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies a...
Implications of Emerging Data Mining
Kulathuramaiyer, Narayanan; Maurer, Hermann
Data Mining describes a technology that discovers non-trivial hidden patterns in a large collection of data. Although this technology has a tremendous impact on our lives, the invaluable contributions of this invisible technology often go unnoticed. This paper discusses advances in data mining while focusing on the emerging data mining capability. Such data mining applications perform multidimensional mining on a wide variety of heterogeneous data sources, providing solutions to many unresolved problems. This paper also highlights the advantages and disadvantages arising from the ever-expanding scope of data mining. Data Mining augments human intelligence by equipping us with a wealth of knowledge and by empowering us to perform our daily tasks better. As the mining scope and capacity increases, users and organizations become more willing to compromise privacy. The huge data stores of the ‚master miners` allow them to gain deep insights into individual lifestyles and their social and behavioural patterns. Data integration and analysis capability of combining business and financial trends together with the ability to deterministically track market changes will drastically affect our lives.
Multivariate statistical methods a primer
Manly, Bryan FJ
2004-01-01
THE MATERIAL OF MULTIVARIATE ANALYSISExamples of Multivariate DataPreview of Multivariate MethodsThe Multivariate Normal DistributionComputer ProgramsGraphical MethodsChapter SummaryReferencesMATRIX ALGEBRAThe Need for Matrix AlgebraMatrices and VectorsOperations on MatricesMatrix InversionQuadratic FormsEigenvalues and EigenvectorsVectors of Means and Covariance MatricesFurther Reading Chapter SummaryReferencesDISPLAYING MULTIVARIATE DATAThe Problem of Displaying Many Variables in Two DimensionsPlotting index VariablesThe Draftsman's PlotThe Representation of Individual Data P:ointsProfiles o
Frey, Davide; Guerraoui, Rachid; Kermarrec, Anne-Marie; Koldehofe, Boris; Mogensen, Martin; Monod, Maxime; Quéma, Vivien
Gossip-based information dissemination protocols are considered easy to deploy, scalable and resilient to network dynamics. Load-balancing is inherent in these protocols as the dissemination work is evenly spread among all nodes. Yet, large-scale distributed systems are usually heterogeneous with respect to network capabilities such as bandwidth. In practice, a blind load-balancing strategy might significantly hamper the performance of the gossip dissemination.
Multivariate statistics exercises and solutions
Härdle, Wolfgang Karl
2015-01-01
The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether more than 250 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R language. All R codes and data sets may be downloaded via the quantlet download center www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.
Mine Water Treatment in Hongai Coal Mines
Dang Phuong Thao; Dang Vu Chi
2018-01-01
Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine ...
International Nuclear Information System (INIS)
Anon.
1984-01-01
Mine layouts, new machines and techniques, research into problem areas of ground control and so on, are highlighted in this report on extending mine life. The main resources taken into account are coal mining, uranium mining, molybdenum and gold mining
International Nuclear Information System (INIS)
2008-01-01
Full text: The economic and environmental sustainability of uranium mining has been analysed by Monash University researcher Dr Gavin Mudd in a paper that challenges the perception that uranium mining is an 'infinite quality source' that provides solutions to the world's demand for energy. Dr Mudd says information on the uranium industry touted by politicians and mining companies is not necessarily inaccurate, but it does not tell the whole story, being often just an average snapshot of the costs of uranium mining today without reflecting the escalating costs associated with the process in years to come. 'From a sustainability perspective, it is critical to evaluate accurately the true lifecycle costs of all forms of electricity production, especially with respect to greenhouse emissions, ' he says. 'For nuclear power, a significant proportion of greenhouse emissions are derived from the fuel supply, including uranium mining, milling, enrichment and fuel manufacture.' Dr Mudd found that financial and environmental costs escalate dramatically as the uranium ore is used. The deeper the mining process required to extract the ore, the higher the cost for mining companies, the greater the impact on the environment and the more resources needed to obtain the product. I t is clear that there is a strong sensitivity of energy and water consumption and greenhouse emissions to ore grade, and that ore grades are likely to continue to decline gradually in the medium to long term. These issues are critical to the current debate over nuclear power and greenhouse emissions, especially with respect to ascribing sustainability to such activities as uranium mining and milling. For example, mining at Roxby Downs is responsible for the emission of over one million tonnes of greenhouse gases per year and this could increase to four million tonnes if the mine is expanded.'
Data mining methods and applications
Lawrence, Kenneth D; Klimberg, Ronald K
2007-01-01
With today's information explosion, many organizations are now able to access a wealth of valuable data. Unfortunately, most of these organizations find they are ill-equipped to organize this information, let alone put it to work for them. Gain a Competitive Advantage Employ data mining in research and forecasting Build models with data management tools and methodology optimization Gain sophisticated breakdowns and complex analysis through multivariate, evolutionary, and neural net methodsLearn how to classify data and maintain qualityTransform Data into Business Acumen Data Mining Methods and
Multivariate analysis: models and method
International Nuclear Information System (INIS)
Sanz Perucha, J.
1990-01-01
Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis
Model Checking Multivariate State Rewards
DEFF Research Database (Denmark)
Nielsen, Bo Friis; Nielson, Flemming; Nielson, Hanne Riis
2010-01-01
We consider continuous stochastic logics with state rewards that are interpreted over continuous time Markov chains. We show how results from multivariate phase type distributions can be used to obtain higher-order moments for multivariate state rewards (including covariance). We also generalise...
Multivariate analysis methods in physics
International Nuclear Information System (INIS)
Wolter, M.
2007-01-01
A review of multivariate methods based on statistical training is given. Several multivariate methods useful in high-energy physics analysis are discussed. Selected examples from current research in particle physics are discussed, both from the on-line trigger selection and from the off-line analysis. Also statistical training methods are presented and some new application are suggested [ru
Multivariate covariance generalized linear models
DEFF Research Database (Denmark)
Bonat, W. H.; Jørgensen, Bent
2016-01-01
are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...
Ishikawa, Hiroshi
2015-01-01
Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.
A primer of multivariate statistics
Harris, Richard J
2014-01-01
Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why
Mine Water Treatment in Hongai Coal Mines
Dang, Phuong Thao; Dang, Vu Chi
2018-03-01
Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.
Mine Water Treatment in Hongai Coal Mines
Directory of Open Access Journals (Sweden)
Dang Phuong Thao
2018-01-01
Full Text Available Acid mine drainage (AMD is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.
Multivariate and semiparametric kernel regression
Härdle, Wolfgang; Müller, Marlene
1997-01-01
The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...
Network structure of multivariate time series.
Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito
2015-10-21
Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.
Solar Data Mining at Georgia State University
Angryk, R.; Martens, P. C.; Schuh, M.; Aydin, B.; Kempton, D.; Banda, J.; Ma, R.; Naduvil-Vadukootu, S.; Akkineni, V.; Küçük, A.; Filali Boubrahimi, S.; Hamdi, S. M.
2016-12-01
In this talk we give an overview of research projects related to solar data analysis that are conducted at Georgia State University. We will provide update on multiple advances made by our research team on the analysis of image parameters, spatio-temporal patterns mining, temporal data analysis and our experiences with big, heterogeneous solar data visualization, analysis, processing and storage. We will talk about up-to-date data mining methodologies, and their importance for big data-driven solar physics research.
Multivariate Statistical Process Control Charts: An Overview
Bersimis, Sotiris; Psarakis, Stelios; Panaretos, John
2006-01-01
In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as p...
Bell, Peter M.
The Exclusive Economic Zone (EEZ) declared by President Reagan in March 1983 has met with a mixed response from those who would benefit from a guaranteed, 200-nautical-mile (370-km) protected underwater mining zone off the coasts of the United States and its possessions. On the one hand, the U.S. Department of the Interior is looking ahead and has been very successful in safeguarding important natural resources that will be needed in the coming decades. On the other hand, the mining industry is faced with a depressed metals and mining market.A report of the Exclusive Economic Zone Symposium held in November 1983 by the U.S. Geological Survey, the Mineral Management Service, and the Bureau of Mines described the mixed response as: “ … The Department of Interior … raring to go into promotion of deep-seal mining but industrial consortia being very pessimistic about the program, at least for the next 30 or so years.” (Chemical & Engineering News, February 5, 1983).
Multivariate Generalized Multiscale Entropy Analysis
Directory of Open Access Journals (Sweden)
Anne Humeau-Heurtier
2016-11-01
Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.
Surface Mines, Other - Longwall Mining Panels
NSGIC Education | GIS Inventory — Coal mining has occurred in Pennsylvania for over a century. A method of coal mining known as Longwall Mining has become more prevalent in recent decades. Longwall...
DEFF Research Database (Denmark)
van der Aalst, W.M.P.; Rubin, V.; Verbeek, H.M.W.
2010-01-01
Process mining includes the automated discovery of processes from event logs. Based on observed events (e.g., activities being executed or messages being exchanged) a process model is constructed. One of the essential problems in process mining is that one cannot assume to have seen all possible...... behavior. At best, one has seen a representative subset. Therefore, classical synthesis techniques are not suitable as they aim at finding a model that is able to exactly reproduce the log. Existing process mining techniques try to avoid such “overfitting” by generalizing the model to allow for more...... support for it). None of the existing techniques enables the user to control the balance between “overfitting” and “underfitting”. To address this, we propose a two-step approach. First, using a configurable approach, a transition system is constructed. Then, using the “theory of regions”, the model...
Rogowitz, Bernice E.; Rabenhorst, David A.; Gerth, John A.; Kalin, Edward B.
1996-04-01
This paper describes a set of visual techniques, based on principles of human perception and cognition, which can help users analyze and develop intuitions about tabular data. Collections of tabular data are widely available, including, for example, multivariate time series data, customer satisfaction data, stock market performance data, multivariate profiles of companies and individuals, and scientific measurements. In our approach, we show how visual cues can help users perform a number of data mining tasks, including identifying correlations and interaction effects, finding clusters and understanding the semantics of cluster membership, identifying anomalies and outliers, and discovering multivariate relationships among variables. These cues are derived from psychological studies on perceptual organization, visual search, perceptual scaling, and color perception. These visual techniques are presented as a complement to the statistical and algorithmic methods more commonly associated with these tasks, and provide an interactive interface for the human analyst.
Gorunescu, Florin
2011-01-01
The knowledge discovery process is as old as Homo sapiens. Until some time ago, this process was solely based on the 'natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since 'knowledge is power'. The goal of this book is to provide, in a friendly way
International Nuclear Information System (INIS)
Pradel, J.
1981-01-01
In this article mining wastes means wastes obtained during extraction and processing of uranium ores including production of uraniferous concentrates. The hazards for the population are irradiation, ingestion, dust or radon inhalation. The different wastes produced are reviewed. Management of liquid effluents, water treatment, contamined materials, gaseous wastes and tailings are examined. Environmental impact of wastes during and after exploitation is discussed. Monitoring and measurements are made to verify that ICRP recommendations are met. Studies in progress to improve mining waste management are given [fr
Applied multivariate statistics with R
Zelterman, Daniel
2015-01-01
This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the B...
Multivariate stochastic simulation with subjective multivariate normal distributions
P. J. Ince; J. Buongiorno
1991-01-01
In many applications of Monte Carlo simulation in forestry or forest products, it may be known that some variables are correlated. However, for simplicity, in most simulations it has been assumed that random variables are independently distributed. This report describes an alternative Monte Carlo simulation technique for subjectively assesed multivariate normal...
Multivariate Matrix-Exponential Distributions
DEFF Research Database (Denmark)
Bladt, Mogens; Nielsen, Bo Friis
2010-01-01
be written as linear combinations of the elements in the exponential of a matrix. For this reason we shall refer to multivariate distributions with rational Laplace transform as multivariate matrix-exponential distributions (MVME). The marginal distributions of an MVME are univariate matrix......-exponential distributions. We prove a characterization that states that a distribution is an MVME distribution if and only if all non-negative, non-null linear combinations of the coordinates have a univariate matrix-exponential distribution. This theorem is analog to a well-known characterization theorem...
Antunes, Sara Cristina; Pereira, Ruth; Marques, Sérgio Miguel; Castro, Bruno Branco; Gonçalves, Fernando
2011-12-01
European frameworks for the ecological risk assessment (ERA) of contaminated sites integrate information from three lines of evidence: chemical, ecotoxicological, and ecological. Regarding the last one, field observations at the contaminated sites are compared to reference site(s) and the differences recorded are analysed at the light of a cause-effect relationship, taking into account the site-specific contamination. Thus, included in the tier 2 of a site-specific risk assessment that is being carried out in an deactivated uranium mining area, a battery of soil enzyme activities (dehydrogenases, urease, arysulphatase, cellulase, acid phosphate) and potential nitrification were assessed in seven sampling sites (A-D-E-F-G-H-I) at different distances from the mine pit. These parameters have been considered good indicators of impacts on soil microbial communities and, subsequently, on soil functions. Soil enzyme activities were impaired in the most contaminated site (A, near the mine pit), for which a higher degree of risk was determined in the tier 1 of ERA. Three other sites within the mining area (F, G, and D) were discriminated on the basis of their low microbial activity, using uni- and multivariate approaches, and validating what had been previously found with chemical and ecotoxicological lines of evidence. We observed considerable among-site heterogeneity in terms of soil physical and chemical properties, combined with seasonal differences in enzyme activities. Still, the correlation between microbial parameters and soil general physical and chemical parameters was weak. In opposition, significant and negative correlations were found between soil enzyme activities and several metallic elements (Al, Be, Cu, U). These findings suggest a clear correlation between compromised soil function (nutrient recycling) and metal contamination. Such information reinforces the evidence of risks for some sites within the mining area and is an important contribution for the
Metal contamination of agricultural soils in the copper mining areas ...
Indian Academy of Sciences (India)
Soma Giri
2017-06-07
Jun 7, 2017 ... Agricultural soil; heavy metals; copper mining areas; multivariate analysis; ... multivariate statistical analysis. 2. ... sieved through standard sieve of 200 mesh size (Giri ... Pearson's correlation is a bivariate correlation ... is a variation reduction technique in which a num- ... Varimax rotation is applied to all the.
The Multivariate Gaussian Probability Distribution
DEFF Research Database (Denmark)
Ahrendt, Peter
2005-01-01
This technical report intends to gather information about the multivariate gaussian distribution, that was previously not (at least to my knowledge) to be found in one place and written as a reference manual. Additionally, some useful tips and tricks are collected that may be useful in practical ...
A "Model" Multivariable Calculus Course.
Beckmann, Charlene E.; Schlicker, Steven J.
1999-01-01
Describes a rich, investigative approach to multivariable calculus. Introduces a project in which students construct physical models of surfaces that represent real-life applications of their choice. The models, along with student-selected datasets, serve as vehicles to study most of the concepts of the course from both continuous and discrete…
Energy Technology Data Exchange (ETDEWEB)
Kim, Young Shik; Lee, Kyung Woon; Kim, Oak Hwan; Kim, Dae Kyung [Korea Institute of Geology Mining and Materials, Taejon (Korea, Republic of)
1996-12-01
The reducing coal market has been enforcing the coal industry to make exceptional rationalization and restructuring efforts since the end of the eighties. To the competition from crude oil and natural gas has been added the growing pressure from rising wages and rising production cost as the workings get deeper. To improve the competitive position of the coal mines against oil and gas through cost reduction, studies to improve mining system have been carried out. To find fields requiring improvements most, the technologies using in Tae Bak Colliery which was selected one of long running mines were investigated and analyzed. The mining method appeared the field needing improvements most to reduce the production cost. The present method, so-called inseam roadway caving method presently is using to extract the steep and thick seam. However, this method has several drawbacks. To solve the problems, two mining methods are suggested for a long term and short term method respectively. Inseam roadway caving method with long-hole blasting method is a variety of the present inseam roadway caving method modified by replacing timber sets with steel arch sets and the shovel loaders with chain conveyors. And long hole blasting is introduced to promote caving. And pillar caving method with chock supports method uses chock supports setting in the cross-cut from the hanging wall to the footwall. Two single chain conveyors are needed. One is installed in front of chock supports to clear coal from the cutting face. The other is installed behind the supports to transport caved coal from behind. This method is superior to the previous one in terms of safety from water-inrushes, production rate and productivity. The only drawback is that it needs more investment. (author). 14 tabs., 34 figs.
Energy Technology Data Exchange (ETDEWEB)
Patchett, A. [Hitachi Construction Equipment (United Kingdom)
2006-09-15
The article describes various excavators used in the UK by Hall Construction for coal mining and reclamation projects. They include machines from Hitachi Construction Machinery that have been modified with a coal shovel at the front end. The ZX350LC-3, for example incorporates a coal shovel, manufactured by Kocurek, to allow it to work at the rock face and lift coal into road wagons or dump trucks. 5 figs.
International Nuclear Information System (INIS)
Raetsep, A.; Liblik, V.
2004-01-01
The attention is focused on the formation of hydrological and hydrogeological interconnections between the catchment areas of Purtse, Rannapungerja, Puhajoe and Vasavere rivers after closing (in 1997-2002) and flooding the Ahtme, Tammiku, Sompa and Kohtla oil shale underground mines. The multivariate relationship between the changes in mine water amounts directed into the rivers, annual runoff due to mine water inlets, groundwater underground flow, outflow module and other factors (as variables) were studied. A complex of linear regression formulas was derived to calculate the amounts of mine water outputs into the rivers and water distribution in order to regulate the hydrological regime of investigated rivers. (author)
Exploration and Mining Roadmap
Energy Technology Data Exchange (ETDEWEB)
none,
2002-09-01
This Exploration and Mining Technology Roadmap represents the third roadmap for the Mining Industry of the Future. It is based upon the results of the Exploration and Mining Roadmap Workshop held May 10 ñ 11, 2001.
African Journals Online (AJOL)
... in the Ghana mining journal: Geology and Mineral Exploration, Mining, Quarrying, Geomechanics, Groundwater Studies, Hydrocarbon Development, Mineral Processing, Metallurgy, Material Science, Mineral Management Policies, Mineral Economics, Environmental Aspects, Computer Applications and Mining Education.
Earth Data Analysis Center, University of New Mexico — ESRI ArcView shapefile depicting New Mexico coal mines permitted under the Surface Mining Control and Reclamation Act of 1977 (SMCRA), by either the NM Mining these...
International Nuclear Information System (INIS)
Anon.
1984-01-01
The mining of uranium in Australia is criticised in relation to it's environmental impact, economics and effects on mine workers and Aborigines. A brief report is given on each of the operating and proposed uranium mines in Australia
Likelihood estimators for multivariate extremes
Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.
2015-01-01
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
Sparse Linear Identifiable Multivariate Modeling
DEFF Research Database (Denmark)
Henao, Ricardo; Winther, Ole
2011-01-01
and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...
Improved multivariate polynomial factoring algorithm
International Nuclear Information System (INIS)
Wang, P.S.
1978-01-01
A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timing are included
Likelihood estimators for multivariate extremes
Huser, Raphaël
2015-11-17
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
Simulation of multivariate diffusion bridges
DEFF Research Database (Denmark)
Bladt, Mogens; Finch, Samuel; Sørensen, Michael
We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental role in simulation-based likelihood and Bayesian inference for stochastic differential equations. By a novel application of classical coupling methods, the new approach generalizes a previously...... proposed simulation method for one-dimensional bridges to the mulit-variate setting. First a method of simulating approzimate, but often very accurate, diffusion bridges is proposed. These approximate bridges are used as proposal for easily implementable MCMC algorithms that produce exact diffusion bridges...
Essentials of multivariate data analysis
Spencer, Neil H
2013-01-01
""… this text provides an overview at an introductory level of several methods in multivariate data analysis. It contains in-depth examples from one data set woven throughout the text, and a free [Excel] Add-In to perform the analyses in Excel, with step-by-step instructions provided for each technique. … could be used as a text (possibly supplemental) for courses in other fields where researchers wish to apply these methods without delving too deeply into the underlying statistics.""-The American Statistician, February 2015
Multivariate process monitoring of EAFs
Energy Technology Data Exchange (ETDEWEB)
Sandberg, E.; Lennox, B.; Marjanovic, O.; Smith, K.
2005-06-01
Improved knowledge of the effect of scrap grades on the electric steelmaking process and optimised scrap loading practices increase the potential for process automation. As part of an ongoing programme, process data from four Scandinavian EAFs have been analysed, using the multivariate process monitoring approach, to develop predictive models for end point conditions such as chemical composition, yield and energy consumption. The models developed generally predict final Cr, Ni and Mo and tramp element contents well, but electrical energy consumption, yield and content of oxidisable and impurity elements (C, Si, Mn, P, S) are at present more difficult to predict. Potential scrap management applications of the prediction models are also presented. (author)
Aspects of multivariate statistical theory
Muirhead, Robb J
2009-01-01
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "". . . the wealth of material on statistics concerning the multivariate normal distribution is quite exceptional. As such it is a very useful source of information for the general statistician and a must for anyone wanting to pen
Directory of Open Access Journals (Sweden)
Jelenković Rade J.
2014-01-01
Full Text Available Mineral resources are finite and nonrenewable in the sense that their extraction permanently depletes a country's resource inventory. The role of governments should be to manage the exploitation of these resources to maximize the economic benefits to their community, consistent with the need to attract and retain the exploration and development capital necessary to continue to realize these benefits for as long as possible. In designing mineral sector taxation systems, policy makers must carefully seek to balance tax types, rates, and incentives that satisfy the needs of both the nation and the mining investor.
Appalachian mine soil morphology and properties: Effects of weathering and mining method
Energy Technology Data Exchange (ETDEWEB)
Haering, K.C.; Daniels, W.L.; Galbraith, J.M. [Virginia Polytechnic Institute & State University, Blacksburg, VA (United States)
2004-08-01
Surface coal mining and reclamation methods in the Appalachians have changed dramatically since the passage of the Surface Mining Control and Reclamation Act (SMCRA) of 1977 and subsequent improvements in mining and reclamation technology. In this study, 30 pre-SMCRA mine soil profiles (4-20 yr old) were examined and sampled in 1980 and compared with 20 mine soil profiles (8-13 yr old) described in the same area in 2002 after it had been completely remined by modern deep cut methods. Mine soils in both sampling years had high rock fragment content (42-81%), relatively well-developed A horizons, and generally exhibited A-C or A-AC-C horizonation. Although six Bw horizons were described in 1980, only two met all requirements for cambic horizons. The 1980 mine soils developed in overburden dominated by oxidized, preweathered material due to relatively shallow mining cuts. The 1980 mine soils had lower rock fragment content, finer textures, lower pH, and tended to be more heterogeneous in horizonation, morphology, and texture than soils observed in 2002, which had formed primarily in unweathered overburden from deeper cuts. Half the pedons sampled in both years had densic materials within 70 cm of the surface. Four poorly to very poorly drained soil profiles were described in each sampling year containing distinct hydric soil indicators in surface horizons. While older pre-SMCRA mine soils do have many properties in common with newer mine soils, their properties are highly influenced by the fact that they generally have formed in more weathered overburden from higher in the geologic column. Overall, Appalachian mine soils are much more complex in subsoil morphology than commonly assumed, and differential compaction greatly complicates their internal drainage and limits their overall productivity potential.
Multivariate methods for particle identification
Visan, Cosmin
2013-01-01
The purpose of this project was to evaluate several MultiVariate methods in order to determine which one, if any, offers better results in Particle Identification (PID) than a simple n$\\sigma$ cut on the response of the ALICE PID detectors. The particles considered in the analysis were Pions, Kaons and Protons and the detectors used were TPC and TOF. When used with the same input n$\\sigma$ variables, the results show similar perfoance between the Rectangular Cuts Optimization method and the simple n$\\sigma$ cuts. The method MLP and BDT show poor results for certain ranges of momentum. The KNN method is the best performing, showing similar results for Pions and Protons as the Cuts method, and better results for Kaons. The extension of the methods to include additional input variables leads to poor results, related to instabilities still to be investigated.
Acoustic multivariate condition monitoring - AMCM
Energy Technology Data Exchange (ETDEWEB)
Rosenhave, P E [Vestfold College, Maritime Dept., Toensberg (Norway)
1998-12-31
In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.
Acoustic multivariate condition monitoring - AMCM
Energy Technology Data Exchange (ETDEWEB)
Rosenhave, P.E. [Vestfold College, Maritime Dept., Toensberg (Norway)
1997-12-31
In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Stelzer, Robert
Univariate superpositions of Ornstein-Uhlenbeck (OU) type processes, called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behaviour. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness...... of moments. Moreover, the second order moment structure is explicitly calculated, and examples exhibit the possibility of long range dependence. Our supOU processes are defined via homogeneous and factorisable Lévy bases. We show that the behaviour of supOU processes is particularly nice when the mean...... reversion parameter is restricted to normal matrices and especially to strictly negative definite ones.For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation...
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Stelzer, Robert
2011-01-01
Univariate superpositions of Ornstein–Uhlenbeck-type processes (OU), called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behavior. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness of moments....... Moreover, the second-order moment structure is explicitly calculated, and examples exhibit the possibility of long-range dependence. Our supOU processes are defined via homogeneous and factorizable Lévy bases. We show that the behavior of supOU processes is particularly nice when the mean reversion...... parameter is restricted to normal matrices and especially to strictly negative definite ones. For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation of OU...
An Exact Confidence Region in Multivariate Calibration
Mathew, Thomas; Kasala, Subramanyam
1994-01-01
In the multivariate calibration problem using a multivariate linear model, an exact confidence region is constructed. It is shown that the region is always nonempty and is invariant under nonsingular transformations.
Heterogeneity in the WTP for recreational access
DEFF Research Database (Denmark)
Campbell, Danny; Vedel, Suzanne Elizabeth; Thorsen, Bo Jellesmark
2014-01-01
In this study we have addressed appropriate modelling of heterogeneity in willingness to pay (WTP) for environmental goods, and have demonstrated its importance using a case of forest access in Denmark. We compared WTP distributions for four models: (1) a multinomial logit model, (2) a mixed logit...... model assuming a univariate Normal distribution, (3) or assuming a multivariate Normal distribution allowing for correlation across attributes, and (4) a mixture of two truncated Normal distributions, allowing for correlation among attributes. In the first two models mean WTP for enhanced access...... was negative. However, models accounting for preference heterogeneity found a positive mean WTP, but a large sub-group with negative WTP. Accounting for preference heterogeneity can alter overall conclusions, which highlights the importance of this for policy recommendations....
A kernel version of multivariate alteration detection
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack
2013-01-01
Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....
International Nuclear Information System (INIS)
Cheeseman, E.W.
1980-01-01
The international uranium market appears to be currently over-supplied with a resultant softening in prices. Buyers on the international market are unhappy about some of the restrictions placed on sales by the government, and Canadian sales may suffer as a result. About 64 percent of Canada's shipments come from five operating Ontario mines, with the balance from Saskatchewan. Several other properties will be producing within the next few years. In spite of the adverse effects of the Three Mile Island incident and the default by the T.V.A. of their contract, some 3 600 tonnes of new uranium sales were completed during the year. The price for uranium had stabilized at US $42 - $44 by mid 1979, but by early 1980 had softened somewhat. The year 1979 saw the completion of major environmental hearings in Ontario and Newfoundland and the start of the B.C. inquiry. Two more hearings are scheduled for Saskatchewan in 1980. The Elliot Lake uranium mining expansion hearings are reviewed, as are other recent hearings. In the production of uranium for nuclear fuel cycle, environmental matters are of major concern to the industry, the public and to governments. Research is being conducted to determine the most effective method for removing radium from tailings area effluents. Very stringent criteria are being drawn up by the regulatory agencies that must be met by the industry in order to obtain an operating licence from the AECB. These criteria cover seepages from the tailings basin and through the tailings retention dam, seismic stability, and both short and long term management of the tailings waste management area. (auth)
Multivariate strategies in functional magnetic resonance imaging
DEFF Research Database (Denmark)
Hansen, Lars Kai
2007-01-01
We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a `mind reading' predictive multivariate fMRI model....
Energy Technology Data Exchange (ETDEWEB)
Oestensen, A
1983-12-01
The research mine at Kiruna is the first large-scale mining research project sponsored by the Swedish government. Under the leadership of the Swedish Mining Research Foundation, a five-year project involving development of new mining systems and machinery will be carried out in cooperation with the Lulea Institute of Technology and a number of Swedish industrial companies.
Application for trackless mining technique in Benxi uranium mine
International Nuclear Information System (INIS)
Chen Bingguo
1998-01-01
The author narrates the circumstances achieving constructional target in Benxi Uranium Mine under relying on advance of science and technology and adopting small trackless mining equipment, presents the application of trackless mining equipment at mining small mine and complex mineral deposit and discusses the unique superiority of trackless mining technique in development work, mining preparation work and backstoping
Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price
Directory of Open Access Journals (Sweden)
Kaijian He
2016-04-01
Full Text Available Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in benchmark crude oil markets confirm that more diverse heterogeneous data characteristics can be revealed and modeled in the projected time delayed domain. The proposed model demonstrates the superior performance compared to the benchmark models.
International Nuclear Information System (INIS)
Antunes, Sara Cristina; Pereira, Ruth; Marques, Sérgio Miguel; Castro, Bruno Branco; Gonçalves, Fernando
2011-01-01
European frameworks for the ecological risk assessment (ERA) of contaminated sites integrate information from three lines of evidence: chemical, ecotoxicological, and ecological. Regarding the last one, field observations at the contaminated sites are compared to reference site(s) and the differences recorded are analysed at the light of a cause-effect relationship, taking into account the site-specific contamination. Thus, included in the tier 2 of a site-specific risk assessment that is being carried out in an deactivated uranium mining area, a battery of soil enzyme activities (dehydrogenases, urease, arysulphatase, cellulase, acid phosphate) and potential nitrification were assessed in seven sampling sites (A–D–E–F–G–H–I) at different distances from the mine pit. These parameters have been considered good indicators of impacts on soil microbial communities and, subsequently, on soil functions. Soil enzyme activities were impaired in the most contaminated site (A, near the mine pit), for which a higher degree of risk was determined in the tier 1 of ERA. Three other sites within the mining area (F, G, and D) were discriminated on the basis of their low microbial activity, using uni- and multivariate approaches, and validating what had been previously found with chemical and ecotoxicological lines of evidence. We observed considerable among-site heterogeneity in terms of soil physical and chemical properties, combined with seasonal differences in enzyme activities. Still, the correlation between microbial parameters and soil general physical and chemical parameters was weak. In opposition, significant and negative correlations were found between soil enzyme activities and several metallic elements (Al, Be, Cu, U). These findings suggest a clear correlation between compromised soil function (nutrient recycling) and metal contamination. Such information reinforces the evidence of risks for some sites within the mining area and is an important
Multivariate pluvial flood damage models
International Nuclear Information System (INIS)
Van Ootegem, Luc; Verhofstadt, Elsy; Van Herck, Kristine; Creten, Tom
2015-01-01
Depth–damage-functions, relating the monetary flood damage to the depth of the inundation, are commonly used in the case of fluvial floods (floods caused by a river overflowing). We construct four multivariate damage models for pluvial floods (caused by extreme rainfall) by differentiating on the one hand between ground floor floods and basement floods and on the other hand between damage to residential buildings and damage to housing contents. We do not only take into account the effect of flood-depth on damage, but also incorporate the effects of non-hazard indicators (building characteristics, behavioural indicators and socio-economic variables). By using a Tobit-estimation technique on identified victims of pluvial floods in Flanders (Belgium), we take into account the effect of cases of reported zero damage. Our results show that the flood depth is an important predictor of damage, but with a diverging impact between ground floor floods and basement floods. Also non-hazard indicators are important. For example being aware of the risk just before the water enters the building reduces content damage considerably, underlining the importance of warning systems and policy in this case of pluvial floods. - Highlights: • Prediction of damage of pluvial floods using also non-hazard information • We include ‘no damage cases’ using a Tobit model. • The damage of flood depth is stronger for ground floor than for basement floods. • Non-hazard indicators are especially important for content damage. • Potential gain of policies that increase awareness of flood risks
Multivariate pluvial flood damage models
Energy Technology Data Exchange (ETDEWEB)
Van Ootegem, Luc [HIVA — University of Louvain (Belgium); SHERPPA — Ghent University (Belgium); Verhofstadt, Elsy [SHERPPA — Ghent University (Belgium); Van Herck, Kristine; Creten, Tom [HIVA — University of Louvain (Belgium)
2015-09-15
Depth–damage-functions, relating the monetary flood damage to the depth of the inundation, are commonly used in the case of fluvial floods (floods caused by a river overflowing). We construct four multivariate damage models for pluvial floods (caused by extreme rainfall) by differentiating on the one hand between ground floor floods and basement floods and on the other hand between damage to residential buildings and damage to housing contents. We do not only take into account the effect of flood-depth on damage, but also incorporate the effects of non-hazard indicators (building characteristics, behavioural indicators and socio-economic variables). By using a Tobit-estimation technique on identified victims of pluvial floods in Flanders (Belgium), we take into account the effect of cases of reported zero damage. Our results show that the flood depth is an important predictor of damage, but with a diverging impact between ground floor floods and basement floods. Also non-hazard indicators are important. For example being aware of the risk just before the water enters the building reduces content damage considerably, underlining the importance of warning systems and policy in this case of pluvial floods. - Highlights: • Prediction of damage of pluvial floods using also non-hazard information • We include ‘no damage cases’ using a Tobit model. • The damage of flood depth is stronger for ground floor than for basement floods. • Non-hazard indicators are especially important for content damage. • Potential gain of policies that increase awareness of flood risks.
International Nuclear Information System (INIS)
Veiga, Marcello M.; Scoble, Malcolm; McAllister, Mary Louise
2001-01-01
To be considered as sustainable, a mining community needs to adhere to the principles of ecological sustainability, economic vitality and social equity. These principles apply over a long time span, covering both the life of the mine and post-mining closure. The legacy left by a mine to the community after its closure is emerging as a significant aspect of its planning. Progress towards sustainability is made when value is added to a community with respect to these principles by the mining operation during its life cycle. This article presents a series of cases to demonstrate the diverse potential challenges to achieving a sustainable mining community. These case studies of both new and old mining communities are drawn mainly from Canada and from locations abroad where Canadian companies are now building mines. The article concludes by considering various approaches that can foster sustainable mining communities and the role of community consultation and capacity building. (author)
Heterogeneous network architectures
DEFF Research Database (Denmark)
Christiansen, Henrik Lehrmann
2006-01-01
is flexibility. This thesis investigates such heterogeneous network architectures and how to make them flexible. A survey of algorithms for network design is presented, and it is described how using heuristics can increase the speed. A hierarchical, MPLS based network architecture is described......Future networks will be heterogeneous! Due to the sheer size of networks (e.g., the Internet) upgrades cannot be instantaneous and thus heterogeneity appears. This means that instead of trying to find the olution, networks hould be designed as being heterogeneous. One of the key equirements here...... and it is discussed that it is advantageous to heterogeneous networks and illustrated by a number of examples. Modeling and simulation is a well-known way of doing performance evaluation. An approach to event-driven simulation of communication networks is presented and mixed complexity modeling, which can simplify...
Energy Technology Data Exchange (ETDEWEB)
Storrar, C D
1977-01-01
This article sets out the basic concepts of mine valuation, with gold mining receiving more space than base minerals and coal. Sampling practice is given special attention. Chapter headings are methods of investigation, sampling, underground sampling, averaging of underground sampling, diamond-drill sampling, mass and mineral content of ore, organization of a sample office, working costs, mining pay limits, ore reserves, ore accounting, maintenance of grade, forecasting operations and life of mine, statistical mine valuation, state's share of profits and taxation, and financial valuation of mining ventures.
Energy Technology Data Exchange (ETDEWEB)
Davison, I. [Highwall Systems (United States)
2006-09-15
The paper explores the issues facing highwall mining. Based in Chilhowie, Virginia, American Highwall Systems has developed a highwall mining system that will allow the mining of coal seams from 26 in to 10 ft in thickness. The first production model, AH51, began mining in August 2006. Technologies incorporated into the company's mining machines to improve the performance, enhance the efficiency, and improve the reliability of the highwall mining equipment incorporate technologies from many disciplines. Technology as applied to design engineering, manufacturing and fabrication engineering, control and monitoring computer hardware and software has played an important role in the evolution of the American Highwall Systems design concept. 5 photos.
Multivariate refined composite multiscale entropy analysis
International Nuclear Information System (INIS)
Humeau-Heurtier, Anne
2016-01-01
Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.
Heterogeneous Seepage at the Nopal I Uranium Mine, Chihuahua, Mexico
International Nuclear Information System (INIS)
Dobson, Patrick; Dobson, Patrick F.; Cook, Paul J.; Ghezzehei, Teamrat; Rodriguez, J. Alfredo; Garza, Rodrigo de la
2008-01-01
The primary objective of this analogue study is to evaluate flow and transport processes of relevance to the proposed Yucca Mountain repository. Seepage data obtained from this study will be used to constrain flow and transport models being developed for the Nopal I system
Multivariate Regression Analysis and Slaughter Livestock,
AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY
Contract Mining versus Owner Mining – The Way Forward | Suglo ...
African Journals Online (AJOL)
Ghana Mining Journal ... By contracting out one or more of their mining operations, the mining companies can concentrate on their core businesses. This paper reviews ... The general trends in the mining industry show that contract mining will be the way forward for most mines under various circumstances in the future.
Optimization of mining design of Hongwei uranium mine
International Nuclear Information System (INIS)
Wu Sanmao; Yuan Baixiang
2012-01-01
Combined with the mining conditions of Hongwei uranium mine, optimization schemes for hoisting cage, mine drainge,ore transport, mine wastewater treatment, power-supply system,etc are put forward in the mining design of the mine. Optimized effects are analyzed from the aspects of technique, economy, and energy saving and reducing emissions. (authors)
Unsupervised classification of multivariate geostatistical data: Two algorithms
Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques
2015-12-01
With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.
Mining and Risk of Tuberculosis in Sub-Saharan Africa
Basu, Sanjay; McKee, Martin; Lurie, Mark
2011-01-01
Objectives. We estimated the relationship between mining and tuberculosis (TB) among countries in sub-Saharan Africa. Methods. We used multivariate regression to estimate the contribution of mining activity to TB incidence, prevalence, and mortality, as well as rates of TB among people living with HIV, with control for economic, health system, and population confounders. Results. Mining production was associated with higher population TB incidence rates (adjusted b = 0.093; 95% confidence interval [CI] = 0.067, 0.120; with an increase of mining production of 1 SD corresponding to about 33% higher TB incidence or 760 000 more incident cases), after adjustment for economic and population controls. Similar results were observed for TB prevalence and mortality, as well as with alternative measures of mining activity. Independent of HIV, there were significant associations between mining production and TB incidence in countries with high HIV prevalence (≥ 4% antenatal HIV prevalence; HIV-adjusted B = 0.066; 95% CI = 0.050, 0.082) and between log gold mining production and TB incidence in all studied countries (HIV-adjusted B = 0.053; 95% CI = 0.032, 0.073). Conclusions. Mining is a significant determinant of countrywide variation in TB among sub-Saharan African nations. Comprehensive TB control strategies should explicitly address the role of mining activity and environments in the epidemic. PMID:20516372
International Nuclear Information System (INIS)
Anon.
1980-01-01
Known uranium deposits and the companies involved in uranium mining and exploration in Australia are listed. The status of the development of the deposits is outlined and reasons for delays to mining are given
Department of Homeland Security — Mines in the United States According to the Homeland Security Infrastructure Program Tiger Team Report Table E-2.V.1 Sub-Layer Geographic Names, a mine is defined as...
Heterogeneous cellular networks
Hu, Rose Qingyang
2013-01-01
A timely publication providing coverage of radio resource management, mobility management and standardization in heterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentum in industry and the research community, attracting the attention of standardization bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are looking into increasing the capacity and coverage of the cellular networks. This book focuses on recent progresses, covering the related topics including scenarios of heterogeneous network deployment, interference management i
Mining Views : database views for data mining
Blockeel, H.; Calders, T.; Fromont, É.; Goethals, B.; Prado, A.
2008-01-01
We present a system towards the integration of data mining into relational databases. To this end, a relational database model is proposed, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules and decision
Mining Views : database views for data mining
Blockeel, H.; Calders, T.; Fromont, É.; Goethals, B.; Prado, A.; Nijssen, S.; De Raedt, L.
2007-01-01
We propose a relational database model towards the integration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules, decision trees and clusterings, can be
International Nuclear Information System (INIS)
Katam, K.; Sudarsono
1982-01-01
Uranium mine ventilation system aimed basically to control and decreasing the air radioactivity in mine caused by the radon emanating from uranium ore. The control and decreasing the air ''age'' in mine, with adding the air consumption volume, increasing the air rate consumption, closing the mine-out area; using closed drainage system. Air consumption should be 60m 3 /minute for each 9m 2 uranium ore surfaces with ventilation rate of 15m/minute. (author)
Directory of Open Access Journals (Sweden)
Berislav Šebečić
1996-12-01
Full Text Available The way mining was monitored in the past depended on knowledge, interest and the existing legal regulations. Documentary evidence about this work can be found in archives, libraries and museums. In particular, there is the rich archival material (papers and books concerning the work of the one-time Imperial and Royal Mining Captaincies in Zagreb, Zadar, Klagenfurt and Split, A minor part of the documentation has not yet been transferred to Croatia. From mining handbooks and books we can also find out about mining in Croatia. In the context of Austro-Hungary. For example, we can find out that the first governorships in Zagreb and Zadar headed the Ban, Count Jelacic and Baron Mamula were also the top mining authorities, though this, probably from political motives, was suppressed in the guides and inventories or the Mining Captaincies. At the end of the 1850s, Croatia produced 92-94% of sea salt, up to 8.5% of sulphur, 19.5% of asphalt and 100% of oil for the Austro-Hungarian empire. From data about mining in the Split Mining Captaincy, prepared for the Philadephia Exhibition, it can be seen that in the exploratory mining operations in which there were 33,372 independent mines declared in 1925 they were looking mainly for bauxite (60,0%, then dark coal (19,0%, asphalts (10.3% and lignites (62%. In 1931, within the area covered by the same captaincy, of 74 declared mines, only 9 were working. There were five coal mines, three bauxite mines and one for asphalt. I suggest that within state institution, the Mining Captaincy or Authority be renewed, or that a Mining and Geological Authority be set ap, which would lead to the more complete affirmation of Croatian mining (the paper is published in Croatian.
Golomeova, Mirjana; Zendelska, Afrodita; Krstev, Boris; Golomeov, Blagoj; Krstev, Aleksandar
2012-01-01
Water flowing from underground and surface mines and contains high concentrations of dissolved metals is called mine drainage. Mine drainage can be categorized into several basic types by their alkalinity or acidity. Sulfide rich and carbonate poor materials are expected to produce acidic drainage, and alkaline rich materials, even with significant sulfide concentrations, often produce net alkaline water. Mine drainages are dangerous because pollutants may decompose in the environment. In...
DEFF Research Database (Denmark)
Pacheco Cueva, Vladimir
2014-01-01
In this guest article, Vladimir Pacheco, a social scientist who has worked on mining and human rights shares his perspectives on a current campaign against mining in El Salvador – Central America’s smallest but most densely populated country.......In this guest article, Vladimir Pacheco, a social scientist who has worked on mining and human rights shares his perspectives on a current campaign against mining in El Salvador – Central America’s smallest but most densely populated country....
Accumulation of heavy metals by vegetables grown in mine wastes
Energy Technology Data Exchange (ETDEWEB)
Cobb, G.P.; Sands, K.; Waters, M.; Wixson, B.G.; Dorward-King, E.
2000-03-01
Lead, cadmium, arsenic, and zinc were quantified in mine wastes and in soils mixed with mine wastes. Metal concentrations were found to be heterogeneous in the wastes. Iceberg lettuce, Cherry Belle radishes, Roma bush beans, and Better Boy tomatoes were cultivated in mine wastes and in waste-amended soils. Lettuce and radishes had 100% survival in the 100% mine waste treatments compared to 0% and 25% survival for tomatoes and beans, respectively. Metal concentrations were determined in plant tissues to determine uptake and distribution of metals in the edible plant parts. Individual soil samples were collected beneath each plant to assess metal content in the immediate plant environment. This analysis verified heterogeneous metal content of the mine wastes. The four plant species effectively accumulated and translocated lead, cadmium, arsenic, and zinc. Tomato and bean plants contained the four metals mainly in the roots and little was translocated to the fruits. Radish roots accumulated less metals compared to the leaves, whereas lettuce roots and leaves accumulated similar concentrations of the four metals. Lettuce leaves and radish roots accumulated significantly more metals than bean and tomato fruits. This accumulation pattern suggests that consumption of lettuce leaves or radish roots from plants grown in mine wastes would pose greater risks to humans and wildlife than would consumption of beans or tomatoes grown in the same area. The potential risk may be mitigated somewhat in humans, as vegetables grown in mine wastes exhibited stunted growth and chlorosis.
The mining methods at the Fraisse mine
International Nuclear Information System (INIS)
Heurley, P.; Vervialle, J.P.
1985-01-01
The Fraisse mine is one of the four underground mines of the La Crouzille mining divisions of Cogema. Faced with the necessity to mechanize its workings, this mine also had to satisfy a certain number of stringent demands. This has led to concept of four different mining methods for the four workings at present in active operation at this pit, which nevertheless preserve the basic ideas of the methods of top slicing under concrete slabs (TSS) or horizontal cut-and-fill stopes (CFS). An electric scooptram is utilized. With this type of vehicle the stringent demands for the introduction of means for fire fighting and prevention are reduced to a minimum. Finally, the dimensions of the vehicles and the operation of these methods result in a net-to-gross tonnages of close to 1, i.e. a maximum output, combined with a minimum of contamination [fr
CSIR Research Space (South Africa)
Cichowicz, A
1994-01-01
Full Text Available This report discusses the assessment of safety risk and the analysis of Falls Of Ground (FOG) in mines due to seismic events and mining layout during the period of 1991-1992 on a single mine. The multivariate analysis was used to obtain a...
Thearling, Kurt
Data Mining technology allows marketing organizations to better understand their customers and respond to their needs. This chapter describes how Data Mining can be combined with customer relationship management to help drive improved interactions with customers. An example showing how to use Data Mining to drive customer acquisition activities is presented.
International Nuclear Information System (INIS)
Mendoza Delgado, Eva Isolina
2004-01-01
The paper makes a historical recount of the mining legislation in Colombia, it is about the more relevant aspects of the Code of Mines, like they are the title miner, obligations, economic aspects, integration of mining areas and of the benefits contemplated in the law 685 of 2001
International Nuclear Information System (INIS)
Hutchinson, I.P.G.; Ellison, R.D.
1992-01-01
This book reports on mine waste management. Topics covered include: Performance review of modern mine waste management units; Mine waste management requirements; Prediction of acid generation potential; Attenuation of chemical constituents; Climatic considerations; Liner system design; Closure requirements; Heap leaching; Ground water monitoring; and Economic impact evaluation
Mining compressing sequential problems
Hoang, T.L.; Mörchen, F.; Fradkin, D.; Calders, T.G.K.
2012-01-01
Compression based pattern mining has been successfully applied to many data mining tasks. We propose an approach based on the minimum description length principle to extract sequential patterns that compress a database of sequences well. We show that mining compressing patterns is NP-Hard and
International Nuclear Information System (INIS)
Reinsalu, Enno; Toomik, Arvi; Valgma, Ingo
2002-01-01
Estonian mineral resources are deposited in low depth and mining fields are large, therefore vast areas are affected by mining. There are at least 800 deposits with total area of 6,000 km 2 and about the same number of underground mines, surface mines, peat fields, quarries, and sand and gravel pits. The deposits cover more than 10% of Estonian mainland. The total area of operating mine claims exceeds 150 km 2 that makes 0.3 % of Estonian area. The book is written mainly for the people who are living or acting in the area influenced by mining. The observations and research could benefit those who are interested in geography and environment, who follow formation and look of mined-out landscapes. The book contains also warnings for careless people on and under the surface of the mined-out land. Part of the book contains results of the research made in 1968-1993 by the first two authors working at the Estonian branch of A.Skochinsky Institute of Mining. Since 1990, Arvi Toomik continued this study at the Northeastern section of the Institute of Ecology of Tallinn Pedagogical University. Enno Reinsalu studied aftereffects of mining at the Mining Department of Tallinn Technical University from 1998 to 2000. Geographical Information System for Mining was studied by Ingo Valgma within his doctoral dissertation, and this book is one of the applications of his study
Energy Technology Data Exchange (ETDEWEB)
Komissarov, S V
1980-10-01
This article discusses composition of chemical compounds dissolved or suspended in mine waters in various coal basins of the USSR: Moscow basin, Kuzbass, Pechora, Kizelovsk, Karaganda, Donetsk and Chelyabinsk basins. Percentage of suspended materials in water depending on water source (water from water drainage system of dust suppression system) is evaluated. Pollution of mine waters with oils and coli bacteria is also described. Recommendations on construction, capacity of water settling tanks, and methods of mine water treatment are presented. In mines where coal seams 2 m or thicker are mined a system of two settling tanks should be used: in the upper one large grains are settled, in the lower one finer grains. The upper tank should be large enough to store mine water discharged during one month, and the lower one to store water discharged over two months. Salty waters from coal mines mining thin coal seams should be treated in a system of water reservoirs from which water evaporates (if climatic conditions permit). Mine waters from mines with thin coal seams but without high salt content can be treated in a system of long channels with water plants, which increase amount of oxygen in treated water. System of biological treatment of waste waters from mine wash-houses and baths is also described. Influence of temperature, sunshine and season of the year on efficiency of mine water treatment is also assessed. (In Russian)
Mountaintop mining consequences
M.A. Palmer; E.S. Bernhardt; W.H. Schlesinger; K.N. Eshleman; E. Foufoula-Georgiou; M.S. Hendryx; A.D. Lemly; G.E. Likens; O.L. Loucks; M.E. Power; P.S. White; P.R. Wilcock
2010-01-01
There has been a global, 30-year increase in surface mining (1), which is now the dominant driver of land-use change in the central Appalachian ecoregion of the United States (2). One major form of such mining, mountaintop mining with valley fills (MTM/VF) (3), is widespread throughout eastern Kentucky, West Virginia (WV), and southwestern Virginia. Upper elevation...
African Journals Online (AJOL)
Principal Contact. Professor Daniel Mireku-Gyimah Editor-in-Chief University of Mines & Technology Ghana Mining Journal University of Mines & Technology P. O. BOX 237 Tarkwa Ghana Phone: +233 362 20280/20324. Fax: +233 362 20306. Email: dm.gyimah@umat.edu.gh ...
Multivariate Marshall and Olkin Exponential Minification Process ...
African Journals Online (AJOL)
A stationary bivariate minification process with bivariate Marshall-Olkin exponential distribution that was earlier studied by Miroslav et al [15]is in this paper extended to multivariate minification process with multivariate Marshall and Olkin exponential distribution as its stationary marginal distribution. The innovation and the ...
Multivariate multiscale entropy of financial markets
Lu, Yunfan; Wang, Jun
2017-11-01
In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.
Harvesting Information from Heterogeneous Sources
DEFF Research Database (Denmark)
Qureshi, Pir Abdul Rasool; Memon, Nasrullah; Wiil, Uffe Kock
2011-01-01
The abundance of information regarding any topic makes the Internet a very good resource. Even though searching the Internet is very easy, what remains difficult is to automate the process of information extraction from the available online information due to the lack of structure and the diversi...... with performance of our tool with respect to each format. Finally, the different potential applications of the proposed tool are discussed with special emphasis on open source intelligence....... in the sharing methods. Most of the times, information is stored in different proprietary formats, complying with different standards and protocols which makes tasks like data mining and information harvesting very difficult. In this paper, an information harvesting tool (heteroHarvest) is presented...... with objectives to address these problems by filtering the useful information and then normalizing the information in a singular non hypertext format. We also discuss state of the art tools along with the shortcomings and present the results of an analysis carried out over different heterogeneous formats along...
Neurobiological heterogeneity in ADHD
de Zeeuw, P.
2011-01-01
Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heterogeneous disorder clinically. Symptoms take many forms, from subtle but pervasive attention problems or dreaminess up to disruptive and unpredictable behavior. Interestingly, early neuroscientific work on ADHD assumed either a
Heterogeneous Calculation of {epsilon}
Energy Technology Data Exchange (ETDEWEB)
Jonsson, Alf
1961-02-15
A heterogeneous method of calculating the fast fission factor given by Naudet has been applied to the Carlvik - Pershagen definition of {epsilon}. An exact calculation of the collision probabilities is included in the programme developed for the Ferranti - Mercury computer.
Heterogeneous Calculation of ε
International Nuclear Information System (INIS)
Jonsson, Alf
1961-02-01
A heterogeneous method of calculating the fast fission factor given by Naudet has been applied to the Carlvik - Pershagen definition of ε. An exact calculation of the collision probabilities is included in the programme developed for the Ferranti - Mercury computer
HETEROGENEOUS INTEGRATION TECHNOLOGY
2017-08-24
AFRL-RY-WP-TR-2017-0168 HETEROGENEOUS INTEGRATION TECHNOLOGY Dr. Burhan Bayraktaroglu Devices for Sensing Branch Aerospace Components & Subsystems...Final September 1, 2016 – May 1, 2017 4. TITLE AND SUBTITLE HETEROGENEOUS INTEGRATION TECHNOLOGY 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER N/A...provide a structure for this review. The history and the current status of integration technologies in each category are examined and product examples are
International Nuclear Information System (INIS)
Toledo, R.D.
1985-01-01
Basic concepts concerning mining parameters, plan establishment and typical procedure methods applied throughout the physical execution of mining operations are here determined, analyzed and discussed. Technological and economic aspects of the exploration phase are presented as well as general mathematical and statistical methods for estimating, analyzing and representing mineral deposits which are virtually essential for good mining project execution. The characterization of important mineral substances and the basic parameters of mining works are emphasized in conjunction with long, medium and short term mining planning. Finally, geological modelling, ore reserves calculations and final economic evaluations are considered using a hypothetical example in order to consolidate the main elaborated ideas. (D.J.M.) [pt
DEFF Research Database (Denmark)
Raaballe, J.; Grundy, B.D.
2002-01-01
Based on standard option pricing arguments and assumptions (including no convenience yield and sustainable property rights), we will not observe operating gold mines. We find that asymmetric information on the reserves in the gold mine is a necessary and sufficient condition for the existence...... of operating gold mines. Asymmetric information on the reserves in the mine implies that, at a high enough price of gold, the manager of high type finds the extraction value of the company to be higher than the current market value of the non-operating gold mine. Due to this under valuation the maxim of market...
Energy Technology Data Exchange (ETDEWEB)
NONE
2007-08-15
AcuMine is a spin-out company from CRC Mining Australia and the University of Sydney's Australian Centre for Field Robotics (ACFR). Its focus is to provide safety and fatigue management in mining environments. The AcuLine Haul Check system was its first development. Of greater benefit to safety in mines will be the AcuMine Proximity System (APPS) developed to reliably detect and warn drivers when in proximity to other trucks and utility vehicles and to detect personnel near to those heavy vehicles. 6 figs.
Lewis, Dawn E; Chauhan, Ashvini; White, John R; Overholt, Will; Green, Stefan J; Jasrotia, Puja; Wafula, Denis; Jagoe, Charles
2012-10-01
Microorganisms are very sensitive to environmental change and can be used to gauge anthropogenic impacts and even predict restoration success of degraded environments. Here, we report assessment of bauxite mining activities on soil biogeochemistry and microbial community structure using un-mined and three post-mined sites in Jamaica. The post-mined soils represent a chronosequence, undergoing restoration since 1987, 1997, and 2007. Soils were collected during dry and wet seasons and analyzed for pH, organic matter (OM), total carbon (TC), nitrogen (TN), and phosphorus. The microbial community structure was assessed through quantitative PCR and massively parallel bacterial ribosomal RNA (rRNA) gene sequencing. Edaphic factors and microbial community composition were analyzed using multivariate statistical approaches and revealed a significant, negative impact of mining on soil that persisted even after greater than 20 years of restoration. Seasonal fluctuations contributed to variation in measured soil properties and community composition, but they were minor in comparison to long-term effects of mining. In both seasons, post-mined soils were higher in pH but OM, TC, and TN decreased. Bacterial rRNA gene analyses demonstrated a general decrease in diversity in post-mined soils and up to a 3-log decrease in rRNA gene abundance. Community composition analyses demonstrated that bacteria from the Proteobacteria (α, β, γ, δ), Acidobacteria, and Firmicutes were abundant in all soils. The abundance of Firmicutes was elevated in newer post-mined soils relative to the un-mined soil, and this contrasted a decrease, relative to un-mined soils, in proteobacterial and acidobacterial rRNA gene abundances. Our study indicates long-lasting impacts of mining activities to soil biogeochemical and microbial properties with impending loss in soil productivity.
International Nuclear Information System (INIS)
Kharat, Amit T; Singh, Amarjit; Kulkarni, Vilas M; Shah, Digish
2014-01-01
Data mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized software which assesses relationships and agreement in available information. By using similar data analysis tools, radiologists can make informed decisions and predict the future outcome of a particular imaging finding. Data, information and knowledge are the components of data mining. Classes, Clusters, Associations, Sequential patterns, Classification, Prediction and Decision tree are the various types of data mining. Data mining has the potential to make delivery of health care affordable and ensure that the best imaging practices are followed. It is a tool for academic research. Data mining is considered to be ethically neutral, however concerns regarding privacy and legality exists which need to be addressed to ensure success of data mining
Heterogeneous gas core reactor
International Nuclear Information System (INIS)
Han, K.I.
1977-01-01
Preliminary investigations of a heterogeneous gas core reactor (HGCR) concept suggest that this potential power reactor offers distinct advantages over other existing or conceptual reactor power plants. One of the most favorable features of the HGCR is the flexibility of the power producing system which allows it to be efficiently designed to conform to a desired optimum condition without major conceptual changes. The arrangement of bundles of moderator/coolant channels in a fissionable gas or mixture of gases makes a truly heterogeneous nuclear reactor core. It is this full heterogeneity for a gas-fueled reactor core which accounts for the novelty of the heterogeneous gas core reactor concept and leads to noted significant advantages over previous gas core systems with respect to neutron and fuel economy, power density, and heat transfer characteristics. The purpose of this work is to provide an insight into the design, operating characteristics, and safety of a heterogeneous gas core reactor system. The studies consist mainly of neutronic, energetic and kinetic analyses of the power producing and conversion systems as a preliminary assessment of the heterogeneous gas core reactor concept and basic design. The results of the conducted research indicate a high potential for the heterogeneous gas core reactor system as an electrical power generating unit (either large or small), with an overall efficiency as high as 40 to 45%. The HGCR system is found to be stable and safe, under the conditions imposed upon the analyses conducted in this work, due to the inherent safety of ann expanding gaseous fuel and the intrinsic feedback effects of the gas and water coolant
Multivariate meta-analysis: Potential and promise
Jackson, Dan; Riley, Richard; White, Ian R
2011-01-01
The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052
Multivariate statistical methods a first course
Marcoulides, George A
2014-01-01
Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is poin
Exploratory multivariate analysis by example using R
Husson, Francois; Pages, Jerome
2010-01-01
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis.The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the prin
Multivariable control in nuclear power stations
International Nuclear Information System (INIS)
Parent, M.; McMorran, P.D.
1982-11-01
Multivariable methods have the potential to improve the control of large systems such as nuclear power stations. Linear-quadratic optimal control is a multivariable method based on the minimization of a cost function. A related technique leads to the Kalman filter for estimation of plant state from noisy measurements. A design program for optimal control and Kalman filtering has been developed as part of a computer-aided design package for multivariable control systems. The method is demonstrated on a model of a nuclear steam generator, and simulated results are presented
Economics of mine water treatment
Dvořáček, Jaroslav; Vidlář, Jiří; Štěrba, Jiří; Heviánková, Silvie; Vaněk, Michal; Barták, Pavel
2012-01-01
Mine water poses a significant problem in lignite coal mining. The drainage of mine water is the fundamental prerequisite of mining operations. Under the legislation of the Czech Republic, mine water that discharges into surface watercourse is subject to the permission of the state administration body in the water management sector. The permission also stipulates the limits for mine water pollution. Therefore, mine water has to be purified prior to discharge. Although all...
Directional outlyingness for multivariate functional data
Dai, Wenlin; Genton, Marc G.
2018-01-01
The direction of outlyingness is crucial to describing the centrality of multivariate functional data. Motivated by this idea, classical depth is generalized to directional outlyingness for functional data. Theoretical properties of functional
The value of multivariate model sophistication
DEFF Research Database (Denmark)
Rombouts, Jeroen; Stentoft, Lars; Violante, Francesco
2014-01-01
We assess the predictive accuracies of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set of 444 multivariate models that differ in their spec....... In addition to investigating the value of model sophistication in terms of dollar losses directly, we also use the model confidence set approach to statistically infer the set of models that delivers the best pricing performances.......We assess the predictive accuracies of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set of 444 multivariate models that differ...
Multivariate survival analysis and competing risks
Crowder, Martin J
2012-01-01
Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.
Simplicial band depth for multivariate functional data
Ló pez-Pintado, Sara; Sun, Ying; Lin, Juan K.; Genton, Marc G.
2014-01-01
sample of curves. Based on these depths, a sample of multivariate curves can be ordered from the center outward and order statistics can be defined. Properties of the proposed depths, such as invariance and consistency, can be established. A simulation
Ellipsoidal prediction regions for multivariate uncertainty characterization
DEFF Research Database (Denmark)
Golestaneh, Faranak; Pinson, Pierre; Azizipanah-Abarghooee, Rasoul
2018-01-01
, for classes of decision-making problems based on robust, interval chance-constrained optimization, necessary inputs take the form of multivariate prediction regions rather than scenarios. The current literature is at very primitive stage of characterizing multivariate prediction regions to be employed...... in these classes of optimization problems. To address this issue, we introduce a new class of multivariate forecasts which form as multivariate ellipsoids for non-Gaussian variables. We propose a data-driven systematic framework to readily generate and evaluate ellipsoidal prediction regions, with predeﬁned...... probability guarantees and minimum conservativeness. A skill score is proposed for quantitative assessment of the quality of prediction ellipsoids. A set of experiments is used to illustrate the discrimination ability of the proposed scoring rule for potential misspeciﬁcation of ellipsoidal prediction regions...
An Introduction to Applied Multivariate Analysis
Raykov, Tenko
2008-01-01
Focuses on the core multivariate statistics topics which are of fundamental relevance for its understanding. This book emphasis on the topics that are critical to those in the behavioral, social, and educational sciences.
L.R. Arends (Lidia)
2006-01-01
textabstractMeta-analysis may be broadly defined as the quantitative review and synthesis of the results of related but independent studies. For the simple case where meta-analysis concerns only one outcome measure in each study, the statistical methods are well established now. However, in many
Green heterogeneous wireless networks
Ismail, Muhammad; Nee, Hans-Peter; Qaraqe, Khalid A; Serpedin, Erchin
2016-01-01
This book focuses on the emerging research topic "green (energy efficient) wireless networks" which has drawn huge attention recently from both academia and industry. This topic is highly motivated due to important environmental, financial, and quality-of-experience (QoE) considerations. Specifically, the high energy consumption of the wireless networks manifests in approximately 2% of all CO2 emissions worldwide. This book presents the authors’ visions and solutions for deployment of energy efficient (green) heterogeneous wireless communication networks. The book consists of three major parts. The first part provides an introduction to the "green networks" concept, the second part targets the green multi-homing resource allocation problem, and the third chapter presents a novel deployment of device-to-device (D2D) communications and its successful integration in Heterogeneous Networks (HetNets). The book is novel in that it specifically targets green networking in a heterogeneous wireless medium, which re...
Data mining, mining data : energy consumption modelling
Energy Technology Data Exchange (ETDEWEB)
Dessureault, S. [Arizona Univ., Tucson, AZ (United States)
2007-09-15
Most modern mining operations are accumulating large amounts of data on production and business processes. Data, however, provides value only if it can be translated into information that appropriate users can utilize. This paper emphasized that a new technological focus should emerge, notably how to concentrate data into information; analyze information sufficiently to become knowledge; and, act on that knowledge. Researchers at the Mining Information Systems and Operations Management (MISOM) laboratory at the University of Arizona have created a method to transform data into action. The data-to-action approach was exercised in the development of an energy consumption model (ECM), in partnership with a major US-based copper mining company, 2 software companies, and the MISOM laboratory. The approach begins by integrating several key data sources using data warehousing techniques, and increasing the existing level of integration and data cleaning. An online analytical processing (OLAP) cube was also created to investigate the data and identify a subset of several million records. Data mining algorithms were applied using the information that was isolated by the OLAP cube. The data mining results showed that traditional cost drivers of energy consumption are poor predictors. A comparison was made between traditional methods of predicting energy consumption and the prediction formed using data mining. Traditionally, in the mines for which data were available, monthly averages of tons and distance are used to predict diesel fuel consumption. However, this article showed that new information technology can be used to incorporate many more variables into the budgeting process, resulting in more accurate predictions. The ECM helped mine planners improve the prediction of energy use through more data integration, measure development, and workflow analysis. 5 refs., 11 figs.
Multivariable Feedback Control of Nuclear Reactors
Directory of Open Access Journals (Sweden)
Rune Moen
1982-07-01
Full Text Available Multivariable feedback control has been adapted for optimal control of the spatial power distribution in nuclear reactor cores. Two design techniques, based on the theory of automatic control, were developed: the State Variable Feedback (SVF is an application of the linear optimal control theory, and the Multivariable Frequency Response (MFR is based on a generalization of the traditional frequency response approach to control system design.
Application of multivariate splines to discrete mathematics
Xu, Zhiqiang
2005-01-01
Using methods developed in multivariate splines, we present an explicit formula for discrete truncated powers, which are defined as the number of non-negative integer solutions of linear Diophantine equations. We further use the formula to study some classical problems in discrete mathematics as follows. First, we extend the partition function of integers in number theory. Second, we exploit the relation between the relative volume of convex polytopes and multivariate truncated powers and giv...
Isotopes in heterogeneous catalysis
Hargreaves, Justin SJ
2006-01-01
The purpose of this book is to review the current, state-of-the-art application of isotopic methods to the field of heterogeneous catalysis. Isotopic studies are arguably the ultimate technique in in situ methods for heterogeneous catalysis. In this review volume, chapters have been contributed by experts in the field and the coverage includes both the application of specific isotopes - Deuterium, Tritium, Carbon-14, Sulfur-35 and Oxygen-18 - as well as isotopic techniques - determination of surface mobility, steady state transient isotope kinetic analysis, and positron emission profiling.
Cancer heterogeneity and imaging.
O'Connor, James P B
2017-04-01
There is interest in identifying and quantifying tumor heterogeneity at the genomic, tissue pathology and clinical imaging scales, as this may help better understand tumor biology and may yield useful biomarkers for guiding therapy-based decision making. This review focuses on the role and value of using x-ray, CT, MRI and PET based imaging methods that identify, measure and map tumor heterogeneity. In particular we highlight the potential value of these techniques and the key challenges required to validate and qualify these biomarkers for clinical use. Copyright © 2016. Published by Elsevier Ltd.
Moyle, Steve
Collaborative Data Mining is a setting where the Data Mining effort is distributed to multiple collaborating agents - human or software. The objective of the collaborative Data Mining effort is to produce solutions to the tackled Data Mining problem which are considered better by some metric, with respect to those solutions that would have been achieved by individual, non-collaborating agents. The solutions require evaluation, comparison, and approaches for combination. Collaboration requires communication, and implies some form of community. The human form of collaboration is a social task. Organizing communities in an effective manner is non-trivial and often requires well defined roles and processes. Data Mining, too, benefits from a standard process. This chapter explores the standard Data Mining process CRISP-DM utilized in a collaborative setting.
Energy Technology Data Exchange (ETDEWEB)
NONE
2013-02-15
Coal mine sites can have significant effects on local environments. In addition to the physical disruption of land forms and ecosystems, mining can also leave behind a legacy of secondary detrimental effects due to leaching of acid and trace elements from discarded materials. This report looks at the remediation of both deep mine and opencast mine sites, covering reclamation methods, back-filling issues, drainage and restoration. Examples of national variations in the applicable legislation and in the definition of rehabilitation are compared. Ultimately, mine site rehabilitation should return sites to conditions where land forms, soils, hydrology, and flora and fauna are self-sustaining and compatible with surrounding land uses. Case studies are given to show what can be achieved and how some landscapes can actually be improved as a result of mining activity.
Energy Technology Data Exchange (ETDEWEB)
Matlak, E S; Kochegarova, L V; Zaslavskaya, I Yu
1980-10-01
Taking into account the negative influence of mine waters with suspended matter on the natural environment on the surface, the maximum treatment of mine water underground, is proposed. It is noted that full treatment of mine water, using conventional filtration methods, would be rather expensive, but a limited treatment of mine water is possible. Such treated mine water can be used in dust suppression and fire fighting systems. Mine water treated underground should be free of any odor, with pH level ranging from 6 to 9.5, with suspended matter content not exceeding 50 mg/l and coli-titre not less than 300 cm$SUP$3. It is suggested that water treatment to produce water characterized by these parameters is possible and economical. Recommendations on construction of underground sedimentation tanks and channels, and a hydraulic system of cleaning sedimentation tanks are proposed. The settling would be stored underground in abandoned workings. (2 refs.) (In Russian)
Weinstein, Lawrence; Radano, Todd A; Jack, Timothy; Kalina, Philip; Eberhardt, John S
2009-09-16
This paper explores the use of machine learning and Bayesian classification models to develop broadly applicable risk stratification models to guide disease management of health plan enrollees with substance use disorder (SUD). While the high costs and morbidities associated with SUD are understood by payers, who manage it through utilization review, acute interventions, coverage and cost limitations, and disease management, the literature shows mixed results for these modalities in improving patient outcomes and controlling cost. Our objective is to evaluate the potential of data mining methods to identify novel risk factors for chronic disease and stratification of enrollee utilization, which can be used to develop new methods for targeting disease management services to maximize benefits to both enrollees and payers. For our evaluation, we used DecisionQ machine learning algorithms to build Bayesian network models of a representative sample of data licensed from Thomson-Reuters' MarketScan consisting of 185,322 enrollees with three full-year claim records. Data sets were prepared, and a stepwise learning process was used to train a series of Bayesian belief networks (BBNs). The BBNs were validated using a 10 percent holdout set. The networks were highly predictive, with the risk-stratification BBNs producing area under the curve (AUC) for SUD positive of 0.948 (95 percent confidence interval [CI], 0.944-0.951) and 0.736 (95 percent CI, 0.721-0.752), respectively, and SUD negative of 0.951 (95 percent CI, 0.947-0.954) and 0.738 (95 percent CI, 0.727-0.750), respectively. The cost estimation models produced area under the curve ranging from 0.72 (95 percent CI, 0.708-0.731) to 0.961 (95 percent CI, 0.95-0.971). We were able to successfully model a large, heterogeneous population of commercial enrollees, applying state-of-the-art machine learning technology to develop complex and accurate multivariate models that support near-real-time scoring of novel payer
Visual Analytics for Heterogeneous Geoscience Data
Pan, Y.; Yu, L.; Zhu, F.; Rilee, M. L.; Kuo, K. S.; Jiang, H.; Yu, H.
2017-12-01
Geoscience data obtained from diverse sources have been routinely leveraged by scientists to study various phenomena. The principal data sources include observations and model simulation outputs. These data are characterized by spatiotemporal heterogeneity originated from different instrument design specifications and/or computational model requirements used in data generation processes. Such inherent heterogeneity poses several challenges in exploring and analyzing geoscience data. First, scientists often wish to identify features or patterns co-located among multiple data sources to derive and validate certain hypotheses. Heterogeneous data make it a tedious task to search such features in dissimilar datasets. Second, features of geoscience data are typically multivariate. It is challenging to tackle the high dimensionality of geoscience data and explore the relations among multiple variables in a scalable fashion. Third, there is a lack of transparency in traditional automated approaches, such as feature detection or clustering, in that scientists cannot intuitively interact with their analysis processes and interpret results. To address these issues, we present a new scalable approach that can assist scientists in analyzing voluminous and diverse geoscience data. We expose a high-level query interface that allows users to easily express their customized queries to search features of interest across multiple heterogeneous datasets. For identified features, we develop a visualization interface that enables interactive exploration and analytics in a linked-view manner. Specific visualization techniques such as scatter plots to parallel coordinates are employed in each view to allow users to explore various aspects of features. Different views are linked and refreshed according to user interactions in any individual view. In such a manner, a user can interactively and iteratively gain understanding into the data through a variety of visual analytics operations. We
Treatment of mine-water from decommissioning uranium mines
International Nuclear Information System (INIS)
Fan Quanhui
2002-01-01
Treatment methods for mine-water from decommissioning uranium mines are introduced and classified. The suggestions on optimal treatment methods are presented as a matter of experience with decommissioned Chenzhou Uranium Mine
Implementation of Paste Backfill Mining Technology in Chinese Coal Mines
Chang, Qingliang; Zhou, Huaqiang; Bai, Jianbiao
2014-01-01
Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application. PMID:25258737
International Nuclear Information System (INIS)
Fallon, M.
1982-01-01
In July 1978 the then Union Corporation (which is a wholly-owned Subsidiary of the larger Gencor Group) announced its intention to develop Beisa mine in the Orange Free State. They started up a medium sized uranium mine with gold as a by-product. The main idea was for the processing of uranium. The planning of the uranium recovery plant, the actual mining, and the recovery and extraction of uranium are discussed
Uranium mining in Saskatchewan
International Nuclear Information System (INIS)
Scales, M.
2006-01-01
The mines of northern Saskatchewan make Canada the worlds leading uranium producer in Canada supplied 29% of global demand, or 11.60 million tonnes of the metal in 2004. Here are two bright ideas - how to mine an orebody by neither pit nor underground method, and how to mine high-grade ore without miners - that Cogema and Cameco are pursuing in the Athabasca Basin
Szathmary , Laszlo; Napoli , Amedeo; Valtchev , Petko
2007-01-01
site de la conférence : http://ictai07.ceid.upatras.gr/; International audience; We describe here a general approach for rare itemset mining. While mining literature has been almost exclusively focused on frequent itemsets, in many practical situations rare ones are of higher interest (e.g., in medical databases, rare combinations of symptoms might provide useful insights for the physicians). Based on an examination of the relevant substructures of the mining space, our approach splits the ra...
Goyal, S.
2018-01-01
This chapter shows that networks can have large and differentiated effects on behavior and then argues that social and economic pressures facilitate the formation of heterogenous networks. Thus networks can play an important role in understanding the wide diversity in human behaviour and in economic outcomes.
Heterogeneous Computing in Economics
DEFF Research Database (Denmark)
Dziubinski, M.P.; Grassi, S.
2014-01-01
This paper shows the potential of heterogeneous computing in solving dynamic equilibrium models in economics. We illustrate the power and simplicity of C++ Accelerated Massive Parallelism (C++ AMP) recently introduced by Microsoft. Starting from the same exercise as Aldrich et al. (J Econ Dyn...
Heterogeneity of Dutch rainfall
Witter, J.V.
1984-01-01
Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the
Directory of Open Access Journals (Sweden)
Saeed Balouchi
2013-01-01
Full Text Available Fractured reservoirs contain about 85 and 90 percent of oil and gas resources respectively in Iran. A comprehensive study and investigation of fractures as the main factor affecting fluid flow or perhaps barrier seems necessary for reservoir development studies. High degrees of heterogeneity and sparseness of data have incapacitated conventional deterministic methods in fracture network modeling. Recently, simulated annealing (SA has been applied to generate stochastic realizations of spatially correlated fracture networks by assuming that the elastic energy of fractures follows Boltzmann distribution. Although SA honors local variability, the objective function of geometrical fracture modeling is defined for homogeneous conditions. In this study, after the introduction of SA and the derivation of the energy function, a novel technique is presented to adjust the model with highly heterogeneous data for a fractured field from the southwest of Iran. To this end, the regular object-based model is combined with a grid-based technique to cover the heterogeneity of reservoir properties. The original SA algorithm is also modified by being constrained in different directions and weighting the energy function to make it appropriate for heterogeneous conditions. The simulation results of the presented approach are in good agreement with the observed field data.
Heterogeneous chromium catalysts
2005-01-01
The present invention relates to a heterogeneous chromium catalyst system for the polymerisation of ethylene and/or alpha olefins prepared by the steps of: (a) providing a silica-containing support, (b) treating the silica-containing support with a chromium compound to form a chromium-based
Why does heterogeneity matter?
K.B. Pierce
2007-01-01
This is a review of the book "Ecosystem function in heterogeneous landscapes" published in 2005. The authors are G. Lovett, C. Jones, M.G. Turner, and K.C. Weathers. It was published by Springer, New York. The book is a synthesis of the 10th Gary conference held at the Institute of Ecosystem Studies in Millbrook, New York, in 2003.
Heterogeneity and option pricing
Benninga, Simon; Mayshar, Joram
2000-01-01
An economy with agents having constant yet heterogeneous degrees of relative risk aversion prices assets as though there were a single decreasing relative risk aversion pricing representative agent. The pricing kernel has fat tails and option prices do not conform to the Black-Scholes formula.
Energy Technology Data Exchange (ETDEWEB)
Haslam, R
1988-04-01
This paper discusses the benefits resulting from mutual cooperation and information exchange between the UK and USA coal industries. The aim of this cooperation is to promote safe and efficient extraction and profitable use of coal. Advanced mining technologies and mechanisation of the coal mines are some of the results of research cooperation between British Coal and the US Bureau of Mines. In addition, Britain has studied and put into good use the management styles, working practices and pay structure, and mining engineering adopted in the USA.
International Nuclear Information System (INIS)
Hunkin, G.G.
1980-01-01
The field of application of in-situ solution mining of uranium is described and areas of competition with open pit and underground mining identified. The influence of high interest rates and dollar inflation on present values and rate of return is shown to be minimized by low capitalization and short construction lead times typical of in-situ leaching ventures. A scheme of three major project account divisions is presented and basic parameters necessary for mine planning are listed. 1979 cost ranges and useful methods of estimation of capital and operating costs are given for the in-situ uranium mining method
Energy Technology Data Exchange (ETDEWEB)
G, Litvinskiy G; Babyuk, G V; Yakovenko, V A
1981-01-07
Mining face equipment includes drilling advance wells, drilling using explosives on the contour bore holes, loading and transporting the crushed mass, drilling reinforcement shafts, injecting reinforcement compounds and moving the timber. Camouflet explosives are used to form relaxed rock stress beyond the mining area to decrease costs of reinforcing the mining area by using nonstressed rock in the advance well as support. The strengthening solution is injected through advanced cementing wells before drilling the contour bores as well as through radial cementing wells beyond the timbers following loading and transport of the mining debris. The advance well is 50-80 m.
International Nuclear Information System (INIS)
Ramsey, L.J.
1985-01-01
The history of the mines in the vicinity of Jackymov, a small town in Central Europe is given. These mines have been worked for several hundred years and from them has been brought forth a variety of products including silver, uranium and radium, the latter being isolated from Jackymov pitch-blende and identified by Marie Curie. The health effects of the miners mining radioactive ores are briefly discussed. The development of Jackymov as a spa resort using the mine water containing radium is also described. (U.K.)
International Nuclear Information System (INIS)
Floeter, W.
1976-01-01
In this report uranium mining and milling are reviewed. The fuel cycle, different types of uranium geological deposits, blending of ores, open cast and underground mining, the mining cost and radiation protection in mines are treated in the first part of this report. In the second part, the milling of uranium ores is treated, including process technology, acid and alkaline leaching, process design for physical and chemical treatment of the ores, and the cost. Each chapter is clarified by added figures, diagrams, tables, and flowsheets. (HK) [de
Energy Technology Data Exchange (ETDEWEB)
Hall, C.J.
1981-01-01
This book on mine ventilation covers psychometrics, airflow through roadways and ducts, natural ventilation, fans, instruments, ventilation surveys, auxiliary ventilation, air quality, and planning and economics.
Responsible Mining: A Human Resources Strategy for Mine Development Project
Sampathkumar, Sriram (Ram)
2012-01-01
Mining is a global industry. Most mining companies operate internationally, often in remote, challenging environments and consequently frequently have respond to unusual and demanding Human Resource (HR) requirements. It is my opinion that the strategic imperative behind success in mining industry is responsible mining. The purpose of this paper is to examine how an effective HR strategy can be a competitive advantage that contributes to the success of a mining project in the global mining in...
Mining engineer requirements in a German coal mine
Energy Technology Data Exchange (ETDEWEB)
Rauhut, F J
1985-10-01
Basic developments in German coal mines, new definitions of working areas of mining engineers, and groups of requirements in education are discussed. These groups include: requirements of hard-coal mining at great depth and in extended collieries; application of process technology and information systems in semi-automated mines; thinking in processes and systems; organizational changes; future requirements of mining engineers; responsibility of the mining engineer for employees and society.
Heterogeneous Materials I and Heterogeneous Materials II
International Nuclear Information System (INIS)
Knowles, K M
2004-01-01
In these two volumes the author provides a comprehensive survey of the various mathematically-based models used in the research literature to predict the mechanical, thermal and electrical properties of hetereogeneous materials, i.e., materials containing two or more phases such as fibre-reinforced polymers, cast iron and porous ceramic kiln furniture. Volume I covers linear properties such as linear dielectric constant, effective electrical conductivity and elastic moduli, while Volume II covers nonlinear properties, fracture and atomistic and multiscale modelling. Where appropriate, particular attention is paid to the use of fractal geometry and percolation theory in describing the structure and properties of these materials. The books are advanced level texts reflecting the research interests of the author which will be of significant interest to research scientists working at the forefront of the areas covered by the books. Others working more generally in the field of materials science interested in comparing predictions of properties with experimental results may well find the mathematical level quite daunting initially, as it is apparent that the author assumes a level of mathematics consistent with that taught in final year undergraduate and graduate theoretical physics courses. However, for such readers it is well worth persevering because of the in-depth coverage to which the various models are subjected, and also because of the extensive reference lists at the back of both volumes which direct readers to the various source references in the scientific literature. Thus, for the wider materials science scientific community the two volumes will be a valuable library resource. While I would have liked to see more comparison with experimental data on both ideal and 'real' heterogeneous materials than is provided by the author and a discussion of how to model strong nonlinear current--voltage behaviour in systems such as zinc oxide varistors, my overall
Sustainable Mining Environment: Technical Review of Post-mining Plans
Directory of Open Access Journals (Sweden)
Restu Juniah
2017-12-01
Full Text Available The mining industry exists because humans need mining commodities to meet their daily needs such as motor vehicles, mobile phones, electronic equipment and others. Mining commodities as mentioned in Government Regulation No. 23 of 2010 on Implementation of Mineral and Coal Mining Business Activities are radioactive minerals, metal minerals, nonmetallic minerals, rocks and coal. Mineral and coal mining is conducted to obtain the mining commodities through production operations. Mining and coal mining companies have an obligation to ensure that the mining environment in particular after the post production operation or post mining continues. The survey research aims to examine technically the post-mining plan in coal mining of PT Samantaka Batubara in Indragiri Hulu Regency of Riau Province towards the sustainability of the mining environment. The results indicate that the post-mining plan of PT Samantaka Batubara has met the technical aspects required in post mining planning for a sustainable mining environment. Postponement of post-mining land of PT Samantaka Batubara for garden and forest zone. The results of this study are expected to be useful and can be used by stakeholders, academics, researchers, practitioners and associations of mining, and the environment.
Multivariate Max-Stable Spatial Processes
Genton, Marc G.
2014-01-06
Analysis of spatial extremes is currently based on univariate processes. Max-stable processes allow the spatial dependence of extremes to be modelled and explicitly quantified, they are therefore widely adopted in applications. For a better understanding of extreme events of real processes, such as environmental phenomena, it may be useful to study several spatial variables simultaneously. To this end, we extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. In particular, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extremevalue, the Schlather extremal-Gaussian and extremal-t, and the BrownResnick models. Inferential aspects of those models based on composite likelihoods are developed. We present results of various Monte Carlo simulations and of an application to a dataset of summer daily temperature maxima and minima in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case. Based on joint work with Simone Padoan and Huiyan Sang.
Multivariate Max-Stable Spatial Processes
Genton, Marc G.
2014-01-01
Analysis of spatial extremes is currently based on univariate processes. Max-stable processes allow the spatial dependence of extremes to be modelled and explicitly quantified, they are therefore widely adopted in applications. For a better understanding of extreme events of real processes, such as environmental phenomena, it may be useful to study several spatial variables simultaneously. To this end, we extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. In particular, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. Then, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extremevalue, the Schlather extremal-Gaussian and extremal-t, and the BrownResnick models. Inferential aspects of those models based on composite likelihoods are developed. We present results of various Monte Carlo simulations and of an application to a dataset of summer daily temperature maxima and minima in Oklahoma, U.S.A., highlighting the utility of working with multivariate models in contrast to the univariate case. Based on joint work with Simone Padoan and Huiyan Sang.
Heterogeneous recurrence monitoring and control of nonlinear stochastic processes
Energy Technology Data Exchange (ETDEWEB)
Yang, Hui, E-mail: huiyang@usf.edu; Chen, Yun [Complex Systems Monitoring, Modeling and Analysis Laboratory, University of South Florida, Tampa, Florida 33620 (United States)
2014-03-15
Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., values and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system.
An architecture for implementation of multivariable controllers
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Stoustrup, Jakob
1999-01-01
Browse > Conferences> American Control Conference, Prev | Back to Results | Next » An architecture for implementation of multivariable controllers 786292 searchabstract Niemann, H. ; Stoustrup, J. ; Dept. of Autom., Tech. Univ., Lyngby This paper appears in: American Control Conference, 1999....... Proceedings of the 1999 Issue Date : 1999 Volume : 6 On page(s): 4029 - 4033 vol.6 Location: San Diego, CA Meeting Date : 02 Jun 1999-04 Jun 1999 Print ISBN: 0-7803-4990-3 References Cited: 7 INSPEC Accession Number: 6403075 Digital Object Identifier : 10.1109/ACC.1999.786292 Date of Current Version : 06...... august 2002 Abstract An architecture for implementation of multivariable controllers is presented in this paper. The architecture is based on the Youla-Jabr-Bongiorno-Kucera parameterization of all stabilizing controllers. By using this architecture for implementation of multivariable controllers...
A MULTIVARIATE ANALYSIS OF CROATIAN COUNTIES ENTREPRENEURSHIP
Directory of Open Access Journals (Sweden)
Elza Jurun
2012-12-01
Full Text Available In the focus of this paper is a multivariate analysis of Croatian Counties entrepreneurship. Complete data base available by official statistic institutions at national and regional level is used. Modern econometric methodology starting from a comparative analysis via multiple regression to multivariate cluster analysis is carried out as well as the analysis of successful or inefficacious entrepreneurship measured by indicators of efficiency, profitability and productivity. Time horizons of the comparative analysis are in 2004 and 2010. Accelerators of socio-economic development - number of entrepreneur investors, investment in fixed assets and current assets ratio in multiple regression model are analytically filtered between twenty-six independent variables as variables of the dominant influence on GDP per capita in 2010 as dependent variable. Results of multivariate cluster analysis of twentyone Croatian Counties are interpreted also in the sense of three Croatian NUTS 2 regions according to European nomenclature of regional territorial division of Croatia.
Simplicial band depth for multivariate functional data
López-Pintado, Sara
2014-03-05
We propose notions of simplicial band depth for multivariate functional data that extend the univariate functional band depth. The proposed simplicial band depths provide simple and natural criteria to measure the centrality of a trajectory within a sample of curves. Based on these depths, a sample of multivariate curves can be ordered from the center outward and order statistics can be defined. Properties of the proposed depths, such as invariance and consistency, can be established. A simulation study shows the robustness of this new definition of depth and the advantages of using a multivariate depth versus the marginal depths for detecting outliers. Real data examples from growth curves and signature data are used to illustrate the performance and usefulness of the proposed depths. © 2014 Springer-Verlag Berlin Heidelberg.
Multivariate generalized linear mixed models using R
Berridge, Damon Mark
2011-01-01
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...
A MATLAB companion for multivariable calculus
Cooper, Jeffery
2001-01-01
Offering a concise collection of MatLab programs and exercises to accompany a third semester course in multivariable calculus, A MatLab Companion for Multivariable Calculus introduces simple numerical procedures such as numerical differentiation, numerical integration and Newton''s method in several variables, thereby allowing students to tackle realistic problems. The many examples show students how to use MatLab effectively and easily in many contexts. Numerous exercises in mathematics and applications areas are presented, graded from routine to more demanding projects requiring some programming. Matlab M-files are provided on the Harcourt/Academic Press web site at http://www.harcourt-ap.com/matlab.html.* Computer-oriented material that complements the essential topics in multivariable calculus* Main ideas presented with examples of computations and graphics displays using MATLAB * Numerous examples of short code in the text, which can be modified for use with the exercises* MATLAB files are used to implem...
Mining and Integration of Environmental Data
Tran, V.; Hluchy, L.; Habala, O.; Ciglan, M.
2009-04-01
The project ADMIRE (Advanced Data Mining and Integration Research for Europe) is a 7th FP EU ICT project aims to deliver a consistent and easy-to-use technology for extracting information and knowledge. The project is motivated by the difficulty of extracting meaningful information by data mining combinations of data from multiple heterogeneous and distributed resources. It will also provide an abstract view of data mining and integration, which will give users and developers the power to cope with complexity and heterogeneity of services, data and processes. The data sets describing phenomena from domains like business, society, and environment often contain spatial and temporal dimensions. Integration of spatio-temporal data from different sources is a challenging task due to those dimensions. Different spatio-temporal data sets contain data at different resolutions (e.g. size of the spatial grid) and frequencies. This heterogeneity is the principal challenge of geo-spatial and temporal data sets integration - the integrated data set should hold homogeneous data of the same resolution and frequency. Thus, to integrate heterogeneous spatio-temporal data from distinct source, transformation of one or more data sets is necessary. Following transformation operation are required: • transformation to common spatial and temporal representation - (e.g. transformation to common coordinate system), • spatial and/or temporal aggregation - data from detailed data source are aggregated to match the resolution of other resources involved in the integration process, • spatial and/or temporal record decomposition - records from source with lower resolution data are decomposed to match the granularity of the other data source. This operation decreases data quality (e.g. transformation of data from 50km grid to 10 km grid) - data from lower resolution data set in the integrated schema are imprecise, but it allows us to preserve higher resolution data. We can decompose the
Multivariable nonlinear analysis of foreign exchange rates
Suzuki, Tomoya; Ikeguchi, Tohru; Suzuki, Masuo
2003-05-01
We analyze the multivariable time series of foreign exchange rates. These are price movements that have often been analyzed, and dealing time intervals and spreads between bid and ask prices. Considering dealing time intervals as event timing such as neurons’ firings, we use raster plots (RPs) and peri-stimulus time histograms (PSTHs) which are popular methods in the field of neurophysiology. Introducing special processings to obtaining RPs and PSTHs time histograms for analyzing exchange rates time series, we discover that there exists dynamical interaction among three variables. We also find that adopting multivariables leads to improvements of prediction accuracy.
CSIR Research Space (South Africa)
Green, JJ
2012-04-01
Full Text Available of threedimensional cameras (SR 4000 and XBOX Kinect) and a thermal imaging sensor (FLIR A300) in order to create 3d thermal models of narrow mining stopes. This information can be used in determining the risk of rockfall in an underground mine, which is a major...
Cementitious backfill in mining
Energy Technology Data Exchange (ETDEWEB)
Taute, A; Spice, J; Wingrove, A C [Van Niekerk, Kleyn Edwards (South Africa)
1993-03-01
This article describes the need for increased usage of backfill material in mining and presents some of the considerations for use of cemented materials. Laboratory test results obtained using a variety of cementitious binders and mine tailings are presented. 3 figs., 1 tab.
Mining Department computer systems
Energy Technology Data Exchange (ETDEWEB)
1979-09-01
Describes the main computer systems currently available, or being developed by the Mining Department of the UK National Coal Board. They are primarily for the use of mining and specialist engineers, but some of them have wider applications, particularly in the research and development and management statistics fields.
Aalst, van der W.M.P.; Alves De Medeiros, A.K.; Weijters, A.J.M.M.; Ciardo, G.; Darondeau, P.
2005-01-01
The topic of process mining has attracted the attention of both researchers and tool vendors in the Business Process Management (BPM) space. The goal of process mining is to discover process models from event logs, i.e., events logged by some information system are used to extract information about
Ghana - Mining and Development
Mohan, P.C.
2004-01-01
The objectives of the project ($9.37 million, 1996-2001) were to (a) enhance the capacity of the mining sector institutions to carry out their functions of encouraging and regulating investments in the mining sector in an environmentally sound manner and (b) support the use of techniques and mechanisms that will improve productivity, financial viability and reduce the environmental impact of ...
Northeast Church Rock Mine, a former uranium mine 17 miles northeast of Gallup, NM in the Pinedale Chapter of the Navajo Nation. EPA is working with NNEPA to oversee cleanup work by United Nuclear Corporation, a company owned by General Electric (GE).
Distributed genetic process mining
Bratosin, C.C.; Sidorova, N.; Aalst, van der W.M.P.
2010-01-01
Process mining aims at discovering process models from data logs in order to offer insight into the real use of information systems. Most of the existing process mining algorithms fail to discover complex constructs or have problems dealing with noise and infrequent behavior. The genetic process
Information and Heterogeneous Beliefs
DEFF Research Database (Denmark)
Christensen, Peter Ove; Qin, Zhenjiang
2014-01-01
In an incomplete market with heterogeneous prior beliefs, we show public information can have a substantial impact on the ex ante cost of capital, trading volume, and investor welfare. The Pareto effcient public information system is the system enjoying the maximum ex ante cost of capital...... and the maximum expected abnormal trading volume. Imperfect public information increases the gains-to-trade based on heterogeneously updated posterior beliefs. In an exchange economy, this leads to higher growth in the investors' certainty equivalents and, thus, a higher equilibrium interest rate, whereas the ex...... ante risk premium is unaffected by the informativeness of the public information system. Similar results are obtained in a production economy, but the impact on the ex ante cost of capital is dampened compared to the exchange economy due to welfare improving reductions in real investments to smooth...
Micromechanics of heterogeneous materials
Buryachenko, Valeriy
2007-01-01
Here is an accurate and timely account of micromechanics, which spans materials science, mechanical engineering, applied mathematics, technical physics, geophysics, and biology. The book features rigorous and unified theoretical methods of applied mathematics and statistical physics in the material science of microheterogeneous media. Uniquely, it offers a useful demonstration of the systematic and fundamental research of the microstructure of the wide class of heterogeneous materials of natural and synthetic nature.
International Nuclear Information System (INIS)
1991-01-01
The second 'African Mining' conference was held in June 1991, and followed the first event held in May 1987. That full four-year period was characterized by substantial changes in the political and economic climate of many countries in both hemispheres. The results of many of these changing facets of our industry are described in the papers in African Mining'91. Many of the papers deal with advances in technology, which is the main reason for the meeting. There are 37 papers under the headings general, mining, metallurgy and geology and exploration. Most papers are concerned with gold, copper and mineral mining. One paper concerning uranium mining operations in Namibia is indexed separately. (author)
Percolation in Heterogeneous Media
International Nuclear Information System (INIS)
Vocka, Radim
1999-01-01
This work is a theoretical reflection on the problematic of the modeling of heterogeneous media, that is on the way of their simple representation conserving their characteristic features. Two particular problems are addressed in this thesis. Firstly, we study the transport in porous media, that is in a heterogeneous media which structure is quenched. A pore space is represented in a simple way - a pore is symbolized as a tube of a given length and a given diameter. The fact that the correlations in the distribution of pore sizes are taken into account by a construction of a hierarchical network makes possible the modeling of porous media with a porosity distributed over several length scales. The transport in the hierarchical network shows qualitatively different phenomena from those observed in simpler models. A comparison of numerical results with experimental data shows that the hierarchical network gives a good qualitative representation of the structure of real porous media. Secondly, we study a problem of the transport in a heterogeneous media which structure is evolving during the time. The models where the evolution of the structure is not influenced by the transport are studied in detail. These models present a phase transition of the same nature as that observed on the percolation networks. We propose a new theoretical description of this transition, and we express critical exponents describing the evolution of the conductivity as a function of fundamental exponents of percolation theory. (author) [fr
Calculus of multivariate functions: it's application in business | Awen ...
African Journals Online (AJOL)
Multivariate functions can be applied to situations in business organizations like ... of capital invested in the plant, the size of the labour force and the cost of raw ... of multivariate functions and has considered types of multivariate differentiation ...
Dynamic heterogeneity in life histories
DEFF Research Database (Denmark)
Tuljapurkar, Shripad; Steiner, Uli; Orzack, Steven Hecht
2009-01-01
or no fixed heterogeneity influences this trait. We propose that dynamic heterogeneity provides a 'neutral' model for assessing the possible role of unobserved 'quality' differences between individuals. We discuss fitness for dynamic life histories, and the implications of dynamic heterogeneity...... generate dynamic heterogeneity: life-history differences produced by stochastic stratum dynamics. We characterize dynamic heterogeneity in a range of species across taxa by properties of the Markov chain: the entropy, which describes the extent of heterogeneity, and the subdominant eigenvalue, which...... distributions of lifetime reproductive success. Dynamic heterogeneity contrasts with fixed heterogeneity: unobserved differences that generate variation between life histories. We show by an example that observed distributions of lifetime reproductive success are often consistent with the claim that little...
Multivariate Analysis of Industrial Scale Fermentation Data
DEFF Research Database (Denmark)
Mears, Lisa; Nørregård, Rasmus; Stocks, Stuart M.
2015-01-01
Multivariate analysis allows process understanding to be gained from the vast and complex datasets recorded from fermentation processes, however the application of such techniques to this field can be limited by the data pre-processing requirements and data handling. In this work many iterations...
Multivariate Option Pricing Using Dynamic Copula Models
van den Goorbergh, R.W.J.; Genest, C.; Werker, B.J.M.
2003-01-01
This paper examines the behavior of multivariate option prices in the presence of association between the underlying assets.Parametric families of copulas offering various alternatives to the normal dependence structure are used to model this association, which is explicitly assumed to vary over
Fully conditional specification in multivariate imputation
van Buuren, S.; Brand, J. P.L.; Groothuis-Oudshoorn, C. G.M.; Rubin, D. B.
2006-01-01
The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the
Multivariate ordination statistics workshop with R slides
Strack, Michael
2015-01-01
2-hour workshop given at Macquarie University Department of Biological Sciences, 4 November 2015. Workshop was an introduction to the family of techniques falling under multivariate ordination, using the R language and drawing heavily from the book "Numerical Ecology with R" by Borcard et. al (2012).
Multivariate Analysis of Schools and Educational Policy.
Kiesling, Herbert J.
This report describes a multivariate analysis technique that approaches the problems of educational production function analysis by (1) using comparable measures of output across large experiments, (2) accounting systematically for differences in socioeconomic background, and (3) treating the school as a complete system in which different…
Multivariate Discrete First Order Stochastic Dominance
DEFF Research Database (Denmark)
Tarp, Finn; Østerdal, Lars Peter
This paper characterizes the principle of first order stochastic dominance in a multivariate discrete setting. We show that a distribution f first order stochastic dominates distribution g if and only if f can be obtained from g by iteratively shifting density from one outcome to another...
Multivariate Time Series Decomposition into Oscillation Components.
Matsuda, Takeru; Komaki, Fumiyasu
2017-08-01
Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.
Ranking multivariate GARCH models by problem dimension
M. Caporin (Massimiliano); M.J. McAleer (Michael)
2010-01-01
textabstractIn the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. The two most widely known and used are the Scalar BEKK model of Engle and Kroner (1995) and Ding and Engle (2001), and the DCC model of Engle (2002). Some recent research has begun to
Radioecological challenges for mining
Energy Technology Data Exchange (ETDEWEB)
Vesterbacka, P.; Ikaeheimonen, T.K.; Solatie, D. [Radiation and Nuclear Safety Authority (Finland)
2014-07-01
In Finland, mining became popular in the mid-1990's when the mining amendments to the law made the mining activities easier for foreign companies. Also the price of the minerals rose and mining in Finland became economically profitable. Expanding mining industry brought new challenges to radiation safety aspect since radioactive substances occur in nearly all minerals. In Finnish soil and bedrock the average crystal abundance of uranium and thorium are 2.8 ppm and 10 ppm, respectively. It cannot be predicted beforehand how radionuclides behave in the mining processes which why they need to be taken into account in mining activities. Radiation and Nuclear Safety Authority (STUK) has given a national guide ST 12.1 based on the Finnish Radiation Act. The guide sets the limits for radiation doses to the public also from mining activities. In general, no measures to limit the radiation exposure are needed, if the dose from the operation liable to cause exposure to natural radiation is no greater than 0.1 mSv per year above the natural background radiation dose. If the exposure of the public may be higher than 0.1 mSv per year, the responsible party must provide STUK a plan describing the measures by which the radiation exposure is to be kept as low as is reasonably achievable. In that case the mining company responsible company has to make a radiological baseline study. The baseline study must focus on the environment that the mining activities may impact. The study describes the occurrence of natural radioactivity in the environment before any mining activities are started. The baseline study lasts usually for two to three years in natural circumstances. Based on the baseline study measurements, detailed information of the existing levels of radioactivity in the environment can be attained. Once the mining activities begin, it is important that the limits are set for the wastewater discharges to the environment and environmental surveillance in the vicinity of
Genetic heterogeneity of retinitis pigmentosa
Hartono, Hartono
2015-01-01
Genetic heterogeneity is a phenomenon in which a genetic disease can be transmitted by several modes of inheritance. The understanding of genetic heterogeneity is important in giving genetic counselling.The presence of genetic heterogeneity can be explained by the existence of:1.different mutant alleles at a single locus, and2.mutant alleles at different loci affecting the same enzyme or protein, or affecting different enzymes or proteins.To have an overall understanding of genetic heterogene...
Ideate about building green mine of uranium mining and metallurgy
International Nuclear Information System (INIS)
Shi Zuyuan
2012-01-01
Analysing the current situation of uranium mining and metallurgy; Setting up goals for green uranium mining and metallurgy, its fundamental conditions, Contents and measures. Putting forward an idea to combine green uranium mining and metallurgy with the state target for green mining, and keeping its own characteristics. (author)
International Nuclear Information System (INIS)
2016-01-01
The annual report of the Saarland Upper Mining Authority provides an insight into the activities of mining authorities. Especially, the development of the black coal mining, safety and technology of mining as well as the correlation between mining and environment are stressed.
Bindler, Richard; Yu, Ruilian; Hansson, Sophia; Classen, Neele; Karlsson, Jon
2012-08-07
In Central Sweden an estimated 80% of the lakes contain fish exceeding health guidelines for mercury. This area overlaps extensively with the Bergslagen ore region, where intensive mining of iron ores and massive sulfide ores occurred over the past millennium. Although only a few mines still operate today, thousands of mineral occurrences and mining sites are documented in the region. Here, we present data on long-term mercury pollution in 16 sediment records from 15 lakes, which indicate that direct release of mercury to lakes and watercourses was already significant prior to industrialization (mines. Although the timing and magnitude of the historical increases in mercury are heterogeneous among lakes, the data provide unambiguous evidence for an incidental release of mercury along with other mining metals to lakes and watercourses, which suggests that the present-day problem of elevated mercury concentrations in the Bergslagen region can trace its roots back to historical mining.
Heterogeneous chromatin target model
International Nuclear Information System (INIS)
Watanabe, Makoto
1996-01-01
The higher order structure of the entangled chromatin fibers in a chromosome plays a key role in molecular control mechanism involved in chromosome mutation due to ionizing radiations or chemical mutagens. The condensed superstructure of chromatin is not so rigid and regular as has been postulated in general. We have proposed a rheological explanation for the flexible network system ('chromatin network') that consists of the fluctuating assembly of nucleosome clusters linked with supertwisting DNA in a chromatin fiber ('Supertwisting Particulate Model'). We have proposed a 'Heterosensitive Target Model' for cellular radiosensitivity that is a modification of 'Heterogeneous Target Model'. The heterogeneity of chromatin target is derived from the highly condensed organization of chromatin segments consist of unstable and fragile sites in the fluctuating assembly of nucleosome clusters, namely 'supranucleosomal particles' or 'superbeads'. The models have been principally supported by our electron microscopic experiments employing 'surface - spreading whole - mount technique' since 1967. However, some deformation and artifacts in the chromatin structure are inevitable with these electron microscopic procedures. On the contrary, the 'atomic force microscope (AFM)' can be operated in liquid as well as in the air. A living specimen can be examined without any preparative procedures. Micromanipulation of the isolated chromosome is also possible by the precise positional control of a cantilever on the nanometer scale. The living human chromosomes were submerged in a solution of culture medium and observed by AFM using a liquid immersion cell. The surface - spreading whole - mount technique was applicable for this observation. The particulate chromatin segments of nucleosome clusters were clearly observed within mitotic human chromosomes in a living hydrated condition. These findings support the heterogeneity of chromatin target in a living cell. (J.P.N.)
International Nuclear Information System (INIS)
Anon.
1981-01-01
Mining in South Africa to this present day has not been a case of dramatic development, rather a steady technical progress, assisted by a rising product market price. Prominent men in the mining industry look at the future in terms of that logical development. Coverage is given to gold, mine unionization, coal, rock bursts, ventilation, uranium and ocean mining
International Nuclear Information System (INIS)
Wood, J.T.
1977-01-01
The Jackpile--Paquate Mines of the Anaconda Company are on the Laguna Indian Reservation midway between Grants and Albuquerque, New Mexico. The open pit mining of uranium ore at those mines is conducted in three separate operations (stripping, mining, and ore haul)
Australian uranium mining policy
International Nuclear Information System (INIS)
Fisk, B.
1985-01-01
Australian government policy is explained in terms of adherence to the Non-Proliferation Treaty. Two alleged uncertainties are discussed: the future of Australian mining industry as a whole -on which it is said that Australian uranium mines will continue to be developed; and detailed commercial policy of the Australian government - on which it is suggested that the three-mines policy of limited expansion of the industry would continue. Various aspects of policy, applying the principles of the NPT, are listed. (U.K.)
Energy Technology Data Exchange (ETDEWEB)
Sprouls, M.W.
1994-10-01
Peabody Western Coal Co. is the owner of Black Mesa and Kayenta coal opencast mines, both sited on Hopi and Navajo lands. 93% of the employees are native American, mostly Navajo. Kayenta is the larger and extracts coal with draglines. Sulphur content is high so the coal has to be analyzed and carefully blended before use. Black Mesa also uses draglines, here quality control is not as important as it is at Kayenta. Coal is transported to power stations using slurry pipelines. Both mines are heavily involved in land reclamation, leaving a landscape that makes better grazing than it did before mining. 2 figs.
Kolb, Thomas; Klotsa, Daphne
Active systems are composed of self-propelled (active) particles that locally convert energy into motion and exhibit emergent collective behaviors, such as fish schooling and bird flocking. Most works so far have focused on monodisperse, one-component active systems. However, real systems are heterogeneous, and consist of several active components. We perform molecular dynamics simulations of multi-component active matter systems and report on their emergent behavior. We discuss the phase diagram of dynamic states as well as parameters where we see mixing versus segregation.
International Nuclear Information System (INIS)
Ding Fulong; Ding Dexin; Ye Yongjun
2010-01-01
Mining operation in the existed mining area at a uranium mine is near completion and it is necessary to mine the No.3 uranium ore body in another mining area at the mine. This paper, based on the geological conditions, used analogical method for analyzing the feasible methods and the low cost and high efficiency mining method was suggested for the No.3 ore body in the independent mining area at the uranium mine. (authors)
Power Estimation in Multivariate Analysis of Variance
Directory of Open Access Journals (Sweden)
Jean François Allaire
2007-09-01
Full Text Available Power is often overlooked in designing multivariate studies for the simple reason that it is believed to be too complicated. In this paper, it is shown that power estimation in multivariate analysis of variance (MANOVA can be approximated using a F distribution for the three popular statistics (Hotelling-Lawley trace, Pillai-Bartlett trace, Wilk`s likelihood ratio. Consequently, the same procedure, as in any statistical test, can be used: computation of the critical F value, computation of the noncentral parameter (as a function of the effect size and finally estimation of power using a noncentral F distribution. Various numerical examples are provided which help to understand and to apply the method. Problems related to post hoc power estimation are discussed.
Directional outlyingness for multivariate functional data
Dai, Wenlin
2018-04-07
The direction of outlyingness is crucial to describing the centrality of multivariate functional data. Motivated by this idea, classical depth is generalized to directional outlyingness for functional data. Theoretical properties of functional directional outlyingness are investigated and the total outlyingness can be naturally decomposed into two parts: magnitude outlyingness and shape outlyingness which represent the centrality of a curve for magnitude and shape, respectively. This decomposition serves as a visualization tool for the centrality of curves. Furthermore, an outlier detection procedure is proposed based on functional directional outlyingness. This criterion applies to both univariate and multivariate curves and simulation studies show that it outperforms competing methods. Weather and electrocardiogram data demonstrate the practical application of our proposed framework.
Multivariate max-stable spatial processes
Genton, Marc G.; Padoan, S. A.; Sang, H.
2015-01-01
Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extremal-Gaussian and extremal-t, and the Brown–Resnick models. We develop inference for the models based on composite likelihoods. We present results of Monte Carlo simulations and an application to daily maximum wind speed and wind gust.
Multivariate Process Control with Autocorrelated Data
DEFF Research Database (Denmark)
Kulahci, Murat
2011-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control and monitoring. This new high dimensional data...... often exhibit not only cross-‐correlation among the quality characteristics of interest but also serial dependence as a consequence of high sampling frequency and system dynamics. In practice, the most common method of monitoring multivariate data is through what is called the Hotelling’s T2 statistic....... In this paper, we discuss the effect of autocorrelation (when it is ignored) on multivariate control charts based on these methods and provide some practical suggestions and remedies to overcome this problem....
Prospective surveillance of multivariate spatial disease data
Corberán-Vallet, A
2012-01-01
Surveillance systems are often focused on more than one disease within a predefined area. On those occasions when outbreaks of disease are likely to be correlated, the use of multivariate surveillance techniques integrating information from multiple diseases allows us to improve the sensitivity and timeliness of outbreak detection. In this article, we present an extension of the surveillance conditional predictive ordinate to monitor multivariate spatial disease data. The proposed surveillance technique, which is defined for each small area and time period as the conditional predictive distribution of those counts of disease higher than expected given the data observed up to the previous time period, alerts us to both small areas of increased disease incidence and the diseases causing the alarm within each area. We investigate its performance within the framework of Bayesian hierarchical Poisson models using a simulation study. An application to diseases of the respiratory system in South Carolina is finally presented. PMID:22534429
Multivariate max-stable spatial processes
Genton, Marc G.
2015-02-11
Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extremal-Gaussian and extremal-t, and the Brown–Resnick models. We develop inference for the models based on composite likelihoods. We present results of Monte Carlo simulations and an application to daily maximum wind speed and wind gust.
Multivariate Approaches to Classification in Extragalactic Astronomy
Directory of Open Access Journals (Sweden)
Didier eFraix-Burnet
2015-08-01
Full Text Available Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still largely in use, together with numerous mono- or bivariate classifications most often made by eye. However, a classification must be driven by the data, and sophisticated multivariate statistical tools are used more and more often. In this paper we review these different approaches in order to situate them in the general context of unsupervised and supervised learning. We insist on the astrophysical outcomes of these studies to show that multivariate analyses provide an obvious path toward a renewal of our classification of galaxies and are invaluable tools to investigate the physics and evolution of galaxies.
Regression Models For Multivariate Count Data.
Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei
2017-01-01
Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.
Security Measures in Data Mining
Anish Gupta; Vimal Bibhu; Rashid Hussain
2012-01-01
Data mining is a technique to dig the data from the large databases for analysis and executive decision making. Security aspect is one of the measure requirement for data mining applications. In this paper we present security requirement measures for the data mining. We summarize the requirements of security for data mining in tabular format. The summarization is performed by the requirements with different aspects of security measure of data mining. The performances and outcomes are determin...
A short note on multivariate dependence modeling
Czech Academy of Sciences Publication Activity Database
Bína, V.; Jiroušek, Radim
2013-01-01
Roč. 49, č. 3 (2013), s. 420-432 ISSN 0023-5954 Grant - others:GA ČR(CZ) GAP403/12/2175 Program:GA Institutional support: RVO:67985556 Keywords : multivariate distribution * dependence * copula Subject RIV: IN - Informatics, Computer Science Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2014/MTR/jirousek-0427848.pdf
Multivariate Welch t-test on distances
Alekseyenko, Alexander V.
2016-01-01
Motivation: Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method...
Multivariate fractional Poisson processes and compound sums
Beghin, Luisa; Macci, Claudio
2015-01-01
In this paper we present multivariate space-time fractional Poisson processes by considering common random time-changes of a (finite-dimensional) vector of independent classical (non-fractional) Poisson processes. In some cases we also consider compound processes. We obtain some equations in terms of some suitable fractional derivatives and fractional difference operators, which provides the extension of known equations for the univariate processes.
On Multivariate Methods in Robust Econometrics
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 21, č. 1 (2012), s. 69-82 ISSN 1210-0455 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : least weighted squares * heteroscedasticity * multivariate statistics * model selection * diagnostics * computational aspects Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.561, year: 2012 http://www.vse.cz/pep/abstrakt.php?IDcl=411
Precision Index in the Multivariate Context
Czech Academy of Sciences Publication Activity Database
Šiman, Miroslav
2014-01-01
Roč. 43, č. 2 (2014), s. 377-387 ISSN 0361-0926 R&D Projects: GA MŠk(CZ) 1M06047 Institutional support: RVO:67985556 Keywords : data depth * multivariate quantile * process capability index * precision index * regression quantile Subject RIV: BA - General Mathematics Impact factor: 0.274, year: 2014 http://library.utia.cas.cz/separaty/2014/SI/siman-0425059.pdf
The evolution of multivariate maternal effects.
Directory of Open Access Journals (Sweden)
Bram Kuijper
2014-04-01
Full Text Available There is a growing interest in predicting the social and ecological contexts that favor the evolution of maternal effects. Most predictions focus, however, on maternal effects that affect only a single character, whereas the evolution of maternal effects is poorly understood in the presence of suites of interacting traits. To overcome this, we simulate the evolution of multivariate maternal effects (captured by the matrix M in a fluctuating environment. We find that the rate of environmental fluctuations has a substantial effect on the properties of M: in slowly changing environments, offspring are selected to have a multivariate phenotype roughly similar to the maternal phenotype, so that M is characterized by positive dominant eigenvalues; by contrast, rapidly changing environments favor Ms with dominant eigenvalues that are negative, as offspring favor a phenotype which substantially differs from the maternal phenotype. Moreover, when fluctuating selection on one maternal character is temporally delayed relative to selection on other traits, we find a striking pattern of cross-trait maternal effects in which maternal characters influence not only the same character in offspring, but also other offspring characters. Additionally, when selection on one character contains more stochastic noise relative to selection on other traits, large cross-trait maternal effects evolve from those maternal traits that experience the smallest amounts of noise. The presence of these cross-trait maternal effects shows that individual maternal effects cannot be studied in isolation, and that their study in a multivariate context may provide important insights about the nature of past selection. Our results call for more studies that measure multivariate maternal effects in wild populations.
The evolution of multivariate maternal effects.
Kuijper, Bram; Johnstone, Rufus A; Townley, Stuart
2014-04-01
There is a growing interest in predicting the social and ecological contexts that favor the evolution of maternal effects. Most predictions focus, however, on maternal effects that affect only a single character, whereas the evolution of maternal effects is poorly understood in the presence of suites of interacting traits. To overcome this, we simulate the evolution of multivariate maternal effects (captured by the matrix M) in a fluctuating environment. We find that the rate of environmental fluctuations has a substantial effect on the properties of M: in slowly changing environments, offspring are selected to have a multivariate phenotype roughly similar to the maternal phenotype, so that M is characterized by positive dominant eigenvalues; by contrast, rapidly changing environments favor Ms with dominant eigenvalues that are negative, as offspring favor a phenotype which substantially differs from the maternal phenotype. Moreover, when fluctuating selection on one maternal character is temporally delayed relative to selection on other traits, we find a striking pattern of cross-trait maternal effects in which maternal characters influence not only the same character in offspring, but also other offspring characters. Additionally, when selection on one character contains more stochastic noise relative to selection on other traits, large cross-trait maternal effects evolve from those maternal traits that experience the smallest amounts of noise. The presence of these cross-trait maternal effects shows that individual maternal effects cannot be studied in isolation, and that their study in a multivariate context may provide important insights about the nature of past selection. Our results call for more studies that measure multivariate maternal effects in wild populations.
Geometric noise reduction for multivariate time series.
Mera, M Eugenia; Morán, Manuel
2006-03-01
We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.
Preliminary Multivariable Cost Model for Space Telescopes
Stahl, H. Philip
2010-01-01
Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. Previously, the authors published two single variable cost models based on 19 flight missions. The current paper presents the development of a multi-variable space telescopes cost model. The validity of previously published models are tested. Cost estimating relationships which are and are not significant cost drivers are identified. And, interrelationships between variables are explored
International Nuclear Information System (INIS)
Boopathy, P.V.; Rathinavel, R.
1993-01-01
Mining activities at lignite areas around Neyveli are described. Measures taken to safeguard the environment from despoliation of land, air pollution, noise pollution and effluents are described. (M.G.B.)
International Nuclear Information System (INIS)
Rose, H.J.M.
1982-01-01
Radiation in mines is primarily associated with, but not restricted to, the exploitation of uranium bearing orebodies. The intent of this chapter is to convey some aspects of radiation control in the mining industry, the behaviour of the parent radon and its daughter products. An attempt was made to demonstrate that anything less than complete diligence by the ventilation personnel could result in rapid deterioration of the mine environment, and consequently high exposure rates. When the maximum annual exposure limit is 4,0 WLM (Working level month exposure) the ventilation official is not allowed the privilege of making an error. Ventilation planning in uranium mines is of prime importance and is very much a group involvement
Energy Technology Data Exchange (ETDEWEB)
1979-01-01
This article looks at the pump industry as a whole, its historical links with the mining industry, their parallel develop ment, and at the individual manufacturers and pumps, services and auxillary products they have to offer.
Mucherino, Antonio; Pardalos, Panos M
2009-01-01
Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given. Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ©2009.
National Research Council Canada - National Science Library
Fripp, Jon
2000-01-01
.... Acid mine drainage (AMD) can have severe impacts to aquatic resources, can stunt terrestrial plant growth and harm wetlands, contaminate groundwater, raise water treatment costs, and damage concrete and metal structures...
Automatic identification in mining
Energy Technology Data Exchange (ETDEWEB)
Puckett, D; Patrick, C [Mine Computers and Electronics Inc., Morehead, KY (United States)
1998-06-01
The feasibility of monitoring the locations and vital statistics of equipment and personnel in surface and underground mining operations has increased with advancements in radio frequency identification (RFID) technology. This paper addresses the use of RFID technology, which is relatively new to the mining industry, to track surface equipment in mine pits, loading points and processing facilities. Specific applications are discussed, including both simplified and complex truck tracking systems and an automatic pit ticket system. This paper concludes with a discussion of the future possibilities of using RFID technology in mining including monitoring heart and respiration rates, body temperatures and exertion levels; monitoring repetitious movements for the study of work habits; and logging air quality via personnel sensors. 10 refs., 5 figs.
International Nuclear Information System (INIS)
Razykov, Z.A; Gusakov, E.G.; Marushenko, A.A.; Botov, A.Yu.; Yunusov, M.M.
2002-12-01
The book describes location laws, the main properties of geological structure and industrial perspectives for known uranium mines of the Republic of Tajikistan. Used methods of industrial processing of uranium mines are described. The results of investigations of technological properties of main types of uranium ores and methods of industrial processing of some of them are shown. Main properties of uranium are shortly described as well as problems, connected with it, which arise during exploitation, mining and processing of uranium ores. The main methods of solution of these problems are shown. The book has interest for specialists of mining, geological, chemical, and technological fields as well as for students of appropriate universities. This book will be interested for usual reader, too, if they are interested in mineral resources of their country [ru
Bigham, Jerry M.; Cravotta, Charles A.
2016-01-01
Acid mine drainage (AMD) consists of metal-laden solutions produced by the oxidative dissolution of iron sulfide minerals exposed to air, moisture, and acidophilic microbes during the mining of coal and metal deposits. The pH of AMD is usually in the range of 2–6, but mine-impacted waters at circumneutral pH (5–8) are also common. Mine drainage usually contains elevated concentrations of sulfate, iron, aluminum, and other potentially toxic metals leached from rock that hydrolyze and coprecipitate to form rust-colored encrustations or sediments. When AMD is discharged into surface waters or groundwaters, degradation of water quality, injury to aquatic life, and corrosion or encrustation of engineered structures can occur for substantial distances. Prevention and remediation strategies should consider the biogeochemical complexity of the system, the longevity of AMD pollution, the predictive power of geochemical modeling, and the full range of available field technologies for problem mitigation.
Scalable Frequent Subgraph Mining
Abdelhamid, Ehab
2017-01-01
Given an input graph, the Frequent Subgraph Mining (FSM) task finds all subgraphs with frequencies exceeding a given threshold. FSM is crucial for graph analysis, and it is an essential building block in a variety
National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...
International Nuclear Information System (INIS)
Rahall, N.J.
1991-05-01
This paper examines the efficacy of the Department of the Interior's Office of Surface Mining Reclamation and Enforcement's (OSMRE) efforts to implement the federally assisted coal mine subsidence insurance program. Coal mine subsidence, a gradual settling of the earth's surface above an underground mine, can damage nearby land and property. To help protect property owners from subsidence-related damage, the Congress passed legislation in 1984 authorizing OSMRE to make grants of up to $3 million to each state to help the states establish self-sustaining, state-administered insurance programs. Of the 21 eligible states, six Colorado, Indiana, Kentucky, Ohio, West Virginia, and Wyoming applied for grants. This paper reviews the efforts of these six states to develop self-sustaining insurance programs and assessed OSMRE's oversight of those efforts
Bayesian Inference of a Multivariate Regression Model
Directory of Open Access Journals (Sweden)
Marick S. Sinay
2014-01-01
Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.
Gaber, Mohamed Medhat; Zaslavsky, Arkady; Krishnaswamy, Shonali
Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).
Ankita Guhe; Shruti Deshmukh; Bhagyashree Borekar; Apoorva Kailaswar; Milind E.Rane
2012-01-01
Geological circumstances of mine seem to be extremely complicated and there are many hidden troubles. Coal is wrongly lifted by the musclemen from coal stocks, coal washeries, coal transfer and loading points and also in the transport routes by malfunctioning the weighing of trucks. CIL —Coal India Ltd is under the control of mafia and a large number of irregularities can be contributed to coal mafia. An Intelligent Coal Mine Security System using data acquisition method utilizes sensor, auto...
Xu, Guandong
2013-01-01
Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest advances in newly emerging information services. It explores the extension of well-studied algorithms and approaches into these new research arenas.
International Nuclear Information System (INIS)
Francois, Y.; Pradel, J.; Zettwoog, P.; Dumas, M.
1975-01-01
In the first part of the paper the authors describe the ventilation of French mines in terms of the primary ventilation system, which brings the outside air close to the working places using the overall structure of the mine to form the airways, and the secondary ventilation system, which is for the distribution of the primary air or for the ventilation of the development drifts and blind tunnels. Brief mention is made of the French regulations on the ventilation of mines in general and uranium mines in particular. The authors describe the equipment used and discuss the installed capacities and air flow per man and per working place. The difficulties encountered in properly ventilating various types of working places are mentioned, such as sub-level development drifts, reinforced stopes, and storage chambers with an artificial crown. The second part of the paper is devoted to computer calculations of the primary ventilation system. It is explained why the Commissariat a l'energie atomique has found it necessary to make these calculations. Without restating the mathematical theories underlying the methods employed, the authors demonstrate how simple measuring instruments and a small-size computer can be used to solve the ventilation problems arising in French mines. Emphasis is given to the layout of the ventilation system and to air flow and negative pressure measurements at the base of the mine. The authors show how calculations can be applied to new heading operations, a change in resistance, the replacement or addition of a ventilator, and a new air inlet or outlet. The authors come to the conclusion that since ventilation is at present the most reliable way of avoiding the pollution of mines, a thorough knowledge of the capabilities in this respect can often help improve working conditions. Despite the progress made, however, constant surveillance of the ventilation systems in uranium mines by a separate team with no responsibility for production problems is
Energy Technology Data Exchange (ETDEWEB)
1986-11-01
In 1982 surveys of the mining industry revealed no applications of robotics existed and none were planned. This report provides a general overview of automation in the mining industry since this point in time. Roof control electronics, gas monitoring, jumbo drill automation, remote and sensor- controlled continuous miners, automated trolley trucks, roof bolting and screening machines are examples of technology available today. The report concludes with recommendations as to six potential research areas. 25 refs.
International Nuclear Information System (INIS)
Francois, Y.; Pradel, J.; Zettwoog, P.; Dumas, M.
1975-01-01
In the first part of the paper the authors describe the ventilation of French mines in terms of the primary ventilation system, which brings the outside air close to the working places using the overall structure of the mine to form the airways, and the secondary ventilation system, which is for the distribution of the primary air or for the ventilation of the development drifts and blind tunnels. Brief mention is made of the French regulations on the ventilation of mines in general and uranium mines in particular. The authors describe the equipment used and discuss the installed capacities and air flow per man and per working place. The difficulties encountered in properly ventilating various types of working places are mentioned, such as sublevel development drifts, reinforced stopes, and storage chambers with an artificial crown. The second part of the paper is devoted to computer calculations of the primary ventilation system. It is explained why the Commissariat a l'energie atomique has found it necessary to make these calculations. Without restating the mathematical theories underlying the methods employed, the authors demonstrate how simple measuring instruments and a small-size computer can be used to solve the ventilation problems arising in French mines. Emphasis is given to the layout of the ventilation system and to air flow and negative pressure measurements at the base of the mine. The authors show how calculations can be applied to new heading operations, a change in resistance, the replacement or addition of a ventilator, and a new air inlet or outlet. The authors come to the conclusion that since ventilation is at present the most reliable way of avoiding the pollution of mines, a thorough knowledge of the capabilities in this respect can often help improve working conditions. Despite the progress made, however, constant surveillance of the ventilation systems in uranium mines by a separate team with no responsibility for production problems is
Weiss, Gary M.
Rare cases are often the most interesting cases. For example, in medical diagnosis one is typically interested in identifying relatively rare diseases, such as cancer, rather than more frequently occurring ones, such as the common cold. In this chapter we discuss the role of rare cases in Data Mining. Specific problems associated with mining rare cases are discussed, followed by a description of methods for addressing these problems.
CSIR Research Space (South Africa)
Ritchken, E
2017-10-01
Full Text Available mechanisms that will entrench the collaboration. The Phakisa had the task of developing collaborative solutions in response to the mining cluster challenges. • Operates through threat • Company focus • Objective is to comply • Company acts... in relative isolation. • Focus on ticking boxes • Focus on individual, easy to measure, projects of limited ambition • Funding through mining company balance sheet. • Creativity unlocked in finding loop- holes in compliance framework – does...
Atkins, Patrick R.; Bayliss, Chris; Ward, Sam
In 1990, the International Aluminum Institute began a program to report on the bauxite mining and rehabilitation activities of the worldwide industry. A survey process was initiated and reports were published in 1992, 2000 and 2004. The most recent report includes extensive data on mines representing over 70% of the world's output of bauxite and includes a more detailed focus on the social and economic as well as the environmental performance of the industry.
DEFF Research Database (Denmark)
Bladt, Mogens; Nielsen, Bo Friis
2012-01-01
Laplace transform. In a longer perspective stochastic and statistical analysis for MVME will in particular apply to any of the previously defined distributions. Multivariate gamma distributions have been used in a variety of fields like hydrology, [11], [10], [6], space (wind modeling) [9] reliability [3......Numerous definitions of multivariate exponential and gamma distributions can be retrieved from the literature [4]. These distribtuions belong to the class of Multivariate Matrix-- Exponetial Distributions (MVME) whenever their joint Laplace transform is a rational function. The majority...... of these distributions further belongs to an important subclass of MVME distributions [5, 1] where the multivariate random vector can be interpreted as a number of simultaneously collected rewards during sojourns in a the states of a Markov chain with one absorbing state, the rest of the states being transient. We...
International mining forum 2004, new technologies in underground mining, safety in mines proceedings
Energy Technology Data Exchange (ETDEWEB)
Jerzy Kicki; Eugeniusz Sobczyk (eds.)
2004-01-15
The book comprises technical papers that were presented at the International Mining Forum 2004. This event aims to bring together scientists and engineers in mining, rock mechanics, and computer engineering, with a view to explore and discuss international developments in the field. Topics discussed in this book are: trends in the mining industry; new solutions and tendencies in underground mines; rock engineering problems in underground mines; utilization and exploitation of methane; prevention measures for the control of rock bursts in Polish mines; and current problems in Ukrainian coal mines.
AN APPLICATION OF FUNCTIONAL MULTIVARIATE REGRESSION MODEL TO MULTICLASS CLASSIFICATION
Krzyśko, Mirosław; Smaga, Łukasz
2017-01-01
In this paper, the scale response functional multivariate regression model is considered. By using the basis functions representation of functional predictors and regression coefficients, this model is rewritten as a multivariate regression model. This representation of the functional multivariate regression model is used for multiclass classification for multivariate functional data. Computational experiments performed on real labelled data sets demonstrate the effectiveness of the proposed ...
Schwering, P.B.W.; Lensen, H.A.; Broek, S.P. van den; Hollander, R.J.M. den; Mark, W. van der; Bouma, H.; Kemp, R.A.W.
2009-01-01
In a harbor environment threats like explosives-packed rubber boats, mine-carrying swimmers and divers must be detected in an early stage. This paper describes the integration and use of a heterogeneous multiple camera system with panoramic observation capabilities for detecting these small vessels
Directory of Open Access Journals (Sweden)
CLAUDIA ELENA DINUCĂ
2011-01-01
Full Text Available The World Wide Web became one of the most valuable resources for information retrievals and knowledge discoveries due to the permanent increasing of the amount of data available online. Taking into consideration the web dimension, the users get easily lost in the web’s rich hyper structure. Application of data mining methods is the right solution for knowledge discovery on the Web. The knowledge extracted from the Web can be used to raise the performances for Web information retrievals, question answering and Web based data warehousing. In this paper, I provide an introduction of Web mining categories and I focus on one of these categories: the Web structure mining. Web structure mining, one of three categories of web mining for data, is a tool used to identify the relationship between Web pages linked by information or direct link connection. It offers information about how different pages are linked together to form this huge web. Web Structure Mining finds hidden basic structures and uses hyperlinks for more web applications such as web search.
International Nuclear Information System (INIS)
Beer, G.
2006-01-01
The newest Slovak brown coal mine - Bana Zahorie is in crisis. Despite the fact that experts believe that along with Bana Novaky, it has the most potential. The owners have started its liquidation. One of the walls has collapsed and another part flooded. Nobody was hurt, but some equipment is still underground. The mine had already lost equipment in the past. During an accident in 2000, equipment worth several tens of millions was destroyed. 'After the accident, mining had to be stopped and from a technical point of view that was the end of the joint stock company, Bana Zahorie Cary. The company could not raise the funds necessary to recover from the accident,' stated the Director of the mine, Jan Palkovic. But he stressed that only the joint stock company is in liquidation, the mine is still being ventilated and the water is being pumped out. But the company management still does not want to specify who will become the new owner of the lignite deposits in Zahorie. The Director promised to publish more details within several weeks. All competencies and mining rights of the former Bana Zahorie are being transferred to a new company - joint stock company Bana Cary. (author)
Energy Technology Data Exchange (ETDEWEB)
Hood, M.; Hatherly, P.; Gurgenci, H. [Centre for Mining Technology and Equipment (Australia)
1999-10-01
New technology in open-pit and underground hard rock mining in 2015 is anticipated in this article, based on a paper presented to the 1998 invitation symposium - 'Technology - Australia's future: new technology for traditional industry', held in Freemantle, WA, 24-25 November 1998. It is expected that essential mining operations of rock breakage and transport and ore processing will still exist but the use of drills, shovels/LHDs and trucks is likely to be replaced by continuous, intelligent, automated mining systems. Rock blasting models need to be fed data on rock properties at each blasthole for high accuracy. The authors believe that in 2015 measurements of rock properties will be a routine part of the drilling process. Blasthole drills will be fitted with a range of mechanical and geophysical sensors. New, non-explosive methods of rock breaking such as oscillating disc cutting, may be available. Mining automation will improve safety and productivity, perhaps with the automation of dragline swing LHDs and trucks may be able to drive themselves, with operators monitoring and intervening when necessary. Performance and machine condition data may be applied to improve equipment design. Australian mining stands to gain by these advances in mining technology. 1 fig., 3 photos.
International Nuclear Information System (INIS)
Tejera Oliver, J. L.
2009-01-01
Mining activities are carried out by the older man and have provided resources, since ancient times, for their development and progress. With the discovery of fire will show the first metals that have marked the civilizations of copper, bronze and iron, and is the prehistory of the Stone Age tools that man has made from the exploitation of quarries first. The industrial revolution of the nineteenth century is linked to coal and steel, and could not conceiver of todays society without oil and gas, without silicon and coltan. But the mines are often aggressive and, despite their need and what they contribute to the development are answered by the societies where are made. during recent years there has been growing international efforts to try to make the minimum requirements of sustainable exploitation (European Directives, GMI, GRI, etc.) In AENOR, and within the Technical Committee of Standardization 22 Mining and Explosives, chaired by AITEMIN, was established the subcommittee 3, chaired by IGME, where, with the participation of all stake holders, have developed some standards on sustainable mining management sustainable mining that will be a tool available to mining companies to demonstrate their sustainable use to Society. (Author)
Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes
Yang, Hui; Tang, Ming; Gross, Thilo
2015-08-01
One of the famous results of network science states that networks with heterogeneous connectivity are more susceptible to epidemic spreading than their more homogeneous counterparts. In particular, in networks of identical nodes it has been shown that network heterogeneity, i.e. a broad degree distribution, can lower the epidemic threshold at which epidemics can invade the system. Network heterogeneity can thus allow diseases with lower transmission probabilities to persist and spread. However, it has been pointed out that networks in which the properties of nodes are intrinsically heterogeneous can be very resilient to disease spreading. Heterogeneity in structure can enhance or diminish the resilience of networks with heterogeneous nodes, depending on the correlations between the topological and intrinsic properties. Here, we consider a plausible scenario where people have intrinsic differences in susceptibility and adapt their social network structure to the presence of the disease. We show that the resilience of networks with heterogeneous connectivity can surpass those of networks with homogeneous connectivity. For epidemiology, this implies that network heterogeneity should not be studied in isolation, it is instead the heterogeneity of infection risk that determines the likelihood of outbreaks.
Large epidemic thresholds emerge in heterogeneous networks of heterogeneous nodes.
Yang, Hui; Tang, Ming; Gross, Thilo
2015-08-21
One of the famous results of network science states that networks with heterogeneous connectivity are more susceptible to epidemic spreading than their more homogeneous counterparts. In particular, in networks of identical nodes it has been shown that network heterogeneity, i.e. a broad degree distribution, can lower the epidemic threshold at which epidemics can invade the system. Network heterogeneity can thus allow diseases with lower transmission probabilities to persist and spread. However, it has been pointed out that networks in which the properties of nodes are intrinsically heterogeneous can be very resilient to disease spreading. Heterogeneity in structure can enhance or diminish the resilience of networks with heterogeneous nodes, depending on the correlations between the topological and intrinsic properties. Here, we consider a plausible scenario where people have intrinsic differences in susceptibility and adapt their social network structure to the presence of the disease. We show that the resilience of networks with heterogeneous connectivity can surpass those of networks with homogeneous connectivity. For epidemiology, this implies that network heterogeneity should not be studied in isolation, it is instead the heterogeneity of infection risk that determines the likelihood of outbreaks.
Use of Markov chains for forecasting labor requirements in black coal mines
Energy Technology Data Exchange (ETDEWEB)
Penar, L.; Przybyla, H.
1987-01-01
Increasing mining depth, deterioration of mining conditions and technology development are causes of changes in labor requirements. In mines with stable coal output these changes in most cases are of a qualitative character, in mines with an increasing or decreasing coal output they are of a quantitative character. Methods for forecasting personnel needs, in particular professional requirements, are discussed. Quantitative and qualitative changes are accurately described by heterogenous Markov chains. A structure consisting of interdependent variables is the subject of a forecast. Changes that occur within the structure of time units is the subject of investigations. For a homogenous Markov chain probabilities of a transition from the i-state to the j-state are determined (the probabilities being time independent). For a heterogenous Markov chain probabilities of a transition from the i-state to the j-state are non-conditioned. The method was developed for the ODRA 1325 computers. 8 refs.
Hidden Markov latent variable models with multivariate longitudinal data.
Song, Xinyuan; Xia, Yemao; Zhu, Hongtu
2017-03-01
Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.
Heterogeneous gas core reactor
International Nuclear Information System (INIS)
Diaz, N.J.; Dugan, E.T.
1983-01-01
A heterogeneous gas core nuclear reactor is disclosed comprising a core barrel provided interiorly with an array of moderator-containing tubes and being otherwise filled with a fissile and/or fertile gaseous fuel medium. The fuel medium may be flowed through the chamber and through an external circuit in which heat is extracted. The moderator may be a fluid which is flowed through the tubes and through an external circuit in which heat is extracted. The moderator may be a solid which may be cooled by a fluid flowing within the tubes and through an external heat extraction circuit. The core barrel is surrounded by moderator/coolant material. Fissionable blanket material may be disposed inwardly or outwardly of the core barrel
Heterogeneity in Waardenburg syndrome.
Hageman, M J; Delleman, J W
1977-01-01
Heterogeneity of Waardenburg syndrome is demonstrated in a review of 1,285 patients from the literature and 34 previously unreported patients in five families in the Netherlands. The syndrome seems to consist of two genetically distinct entities that can be differentiated clinically: type I, Waardenburg syndrome with dystopia canthorum; and type II, Waardenburg syndrome without dystopia canthorum. Both types have an autosomal dominant mode of inheritance. The incidence of bilateral deafness in the two types of the syndrome was found in one-fourth with type I and about half of the patients with type II. This difference has important consequences for genetic counseling. Images Fig. 7 Fig. 8 Fig. 9 PMID:331943
Quantifying hidden individual heterogeneity
DEFF Research Database (Denmark)
Steiner, Ulrich; Lenart, Adam; Vaupel, James W.
Aging is assumed to be driven by the accumulation of damage or some other aging factor which shapes demographic patterns, including the classical late age mortality plateaus. However to date, heterogeneity in these damage stages is not observed. Here, we estimate underlying stage distributions...... and stage dynamics, based on observed survival patterns of isoclonal bacteria. Our results reveal demographic dynamics being dominated by low damage stages and transmission of damage from mother to daughters is low. Still, our models are too simplistic and deterministic. Explaining the observed data...... requires more stochastic processes as our current models includes. We are only at the beginning of understanding the diverse mechanism behind aging and the shaping of senescence....
DEFF Research Database (Denmark)
Kovács, Erika R.; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani
2014-01-01
Heterogeneity amongst devices and desired service are commonly seen as a source of additional challenges for setting up an efficient multi-layer multicast service. In particular, devices requiring only the base layer can become a key bottleneck to the performance for other devices. This paper...... studies the case of a wireless multi-layer multicast setting and shows that the judicious use of network coding allows devices with different computational capabilities to trade-off processing complexity for an improved quality of service. As a consequence, individual devices can determine their required...... effort, while bringing significant advantages to the system as a whole. Network coding is used as a key element to reduce signaling in order to deliver the multicast service. More importantly, our proposed approach focuses on creating some structure in the transmitted stream by allowing inter-layer...
Time varying, multivariate volume data reduction
Energy Technology Data Exchange (ETDEWEB)
Ahrens, James P [Los Alamos National Laboratory; Fout, Nathaniel [UC DAVIS; Ma, Kwan - Liu [UC DAVIS
2010-01-01
Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the
Interconnecting heterogeneous database management systems
Gligor, V. D.; Luckenbaugh, G. L.
1984-01-01
It is pointed out that there is still a great need for the development of improved communication between remote, heterogeneous database management systems (DBMS). Problems regarding the effective communication between distributed DBMSs are primarily related to significant differences between local data managers, local data models and representations, and local transaction managers. A system of interconnected DBMSs which exhibit such differences is called a network of distributed, heterogeneous DBMSs. In order to achieve effective interconnection of remote, heterogeneous DBMSs, the users must have uniform, integrated access to the different DBMs. The present investigation is mainly concerned with an analysis of the existing approaches to interconnecting heterogeneous DBMSs, taking into account four experimental DBMS projects.
Multivariate linear models and repeated measurements revisited
DEFF Research Database (Denmark)
Dalgaard, Peter
2009-01-01
Methods for generalized analysis of variance based on multivariate normal theory have been known for many years. In a repeated measurements context, it is most often of interest to consider transformed responses, typically within-subject contrasts or averages. Efficiency considerations leads...... to sphericity assumptions, use of F tests and the Greenhouse-Geisser and Huynh-Feldt adjustments to compensate for deviations from sphericity. During a recent implementation of such methods in the R language, the general structure of such transformations was reconsidered, leading to a flexible specification...
New multivariable capabilities of the INCA program
Bauer, Frank H.; Downing, John P.; Thorpe, Christopher J.
1989-01-01
The INteractive Controls Analysis (INCA) program was developed at NASA's Goddard Space Flight Center to provide a user friendly, efficient environment for the design and analysis of control systems, specifically spacecraft control systems. Since its inception, INCA has found extensive use in the design, development, and analysis of control systems for spacecraft, instruments, robotics, and pointing systems. The (INCA) program was initially developed as a comprehensive classical design analysis tool for small and large order control systems. The latest version of INCA, expected to be released in February of 1990, was expanded to include the capability to perform multivariable controls analysis and design.
Multivariate Analysis for the Processing of Signals
Directory of Open Access Journals (Sweden)
Beattie J.R.
2014-01-01
Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or
Multivariable dynamic calculus on time scales
Bohner, Martin
2016-01-01
This book offers the reader an overview of recent developments of multivariable dynamic calculus on time scales, taking readers beyond the traditional calculus texts. Covering topics from parameter-dependent integrals to partial differentiation on time scales, the book’s nine pedagogically oriented chapters provide a pathway to this active area of research that will appeal to students and researchers in mathematics and the physical sciences. The authors present a clear and well-organized treatment of the concept behind the mathematics and solution techniques, including many practical examples and exercises.
Multivariable adaptive control of bio process
Energy Technology Data Exchange (ETDEWEB)
Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique
1995-12-31
This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.
Topics in multivariate approximation and interpolation
Jetter, Kurt
2005-01-01
This book is a collection of eleven articles, written by leading experts and dealing with special topics in Multivariate Approximation and Interpolation. The material discussed here has far-reaching applications in many areas of Applied Mathematics, such as in Computer Aided Geometric Design, in Mathematical Modelling, in Signal and Image Processing and in Machine Learning, to mention a few. The book aims at giving a comprehensive information leading the reader from the fundamental notions and results of each field to the forefront of research. It is an ideal and up-to-date introduction for gr
Data mining in Cloud Computing
Directory of Open Access Journals (Sweden)
Ruxandra-Ştefania PETRE
2012-10-01
Full Text Available This paper describes how data mining is used in cloud computing. Data Mining is used for extracting potentially useful information from raw data. The integration of data mining techniques into normal day-to-day activities has become common place. Every day people are confronted with targeted advertising, and data mining techniques help businesses to become more efficient by reducing costs.Data mining techniques and applications are very much needed in the cloud computing paradigm. The implementation of data mining techniques through Cloud computing will allow the users to retrieve meaningful information from virtually integrated data warehouse that reduces the costs of infrastructure and storage.
Methane emissions from coal mining
International Nuclear Information System (INIS)
Boyer, C.M.; Kelafant, J.R.; Kuuskraa, V.A.; Manger, K.C.; Kruger, D.
1990-09-01
The report estimates global methane emissions from coal mining on a country specific basis, evaluates the technologies available to degasify coal seams and assesses the economics of recovering methane liberated during mining. 33 to 64 million tonnes were liberated in 1987 from coal mining, 75 per cent of which came from China, the USSR, Poland and the USA. Methane emissions from coal mining are likely to increase. Emission levels vary between surface and underground mines. The methane currently removed from underground mines for safety reasons could be used in a number of ways, which may be economically attractive. 55 refs., 19 figs., 24 tabs
Multivariate and Spatial Visualisation of Archaeological Assemblages
Directory of Open Access Journals (Sweden)
Martin Sterry
2018-05-01
Full Text Available Multivariate analyses, in particular correspondence analysis (CA, have become a standard exploratory tool for analysing and interpreting variance in archaeological assemblages. While they have greatly helped analysts, they unfortunately remain abstract to the viewer, all the more so if the viewer has little or no experience with multivariate statistics. A second issue with these analyses can arise from the detachment of archaeological material from its geo-referenced location and typically considered only in terms of arbitrary classifications (e.g. North Europe, Central Europe, South Europe instead of the full range of local conditions (e.g. proximity to other assemblages, relationships with other spatial phenomena. This article addresses these issues by presenting a novel method for spatially visualising CA so that these analyses can be interpreted intuitively. The method works by transforming the resultant bi-plots of the CA into colour maps using the HSV colour model, in which the similarity and difference between assemblages directly corresponds to the similarity and difference of the colours used to display them. Utilising two datasets – ceramics from the excavations of the Roman fortress of Vetera I, and terra sigillata forms collected as part of 'The Samian Project' – the article demonstrates how the method is applied and how it can be used to draw out spatial and temporal trends.
Particulate characterization by PIXE multivariate spectral analysis
International Nuclear Information System (INIS)
Antolak, Arlyn J.; Morse, Daniel H.; Grant, Patrick G.; Kotula, Paul G.; Doyle, Barney L.; Richardson, Charles B.
2007-01-01
Obtaining particulate compositional maps from scanned PIXE (proton-induced X-ray emission) measurements is extremely difficult due to the complexity of analyzing spectroscopic data collected with low signal-to-noise at each scan point (pixel). Multivariate spectral analysis has the potential to analyze such data sets by reducing the PIXE data to a limited number of physically realizable and easily interpretable components (that include both spectral and image information). We have adapted the AXSIA (automated expert spectral image analysis) program, originally developed by Sandia National Laboratories to quantify electron-excited X-ray spectroscopy data, for this purpose. Samples consisting of particulates with known compositions and sizes were loaded onto Mylar and paper filter substrates and analyzed by scanned micro-PIXE. The data sets were processed by AXSIA and the associated principal component spectral data were quantified by converting the weighting images into concentration maps. The results indicate automated, nonbiased, multivariate statistical analysis is useful for converting very large amounts of data into a smaller, more manageable number of compositional components needed for locating individual particles-of-interest on large area collection media
Peramalan Multivariate untuk Menentukan Harga Emas Global
Directory of Open Access Journals (Sweden)
David Christian
2016-12-01
Full Text Available Gold is one of the most enticing commodities and a very popular way of investing. Gold’s price is allegedly influenced by another factors such as US Dollar, oil’s price, inflation rate, and stock exchange so that its model is not only affected by its value. The aim of this research is to determine the best forecasting model and influencing factors to gold’s price. This research reviews the univariate modeling as a benchmark and comparison to the multivariate one. Univariate time series is modeled using the ARIMA model which indicates that the fluctuation of the gold prices are following the white noise. Gold’s multivariate modeling is built using the Vector Error Correction Model with oil’s price, US Dollar and Dow Jones indices, and inflation rate as its predictors. Research’s result shows that the VECM model has been able to model the gold’s price well and all factors investigated are influencing gold’s price. US Dollar and oil’s price are negatively correlated with gold’s price as the inflation rate is positively correlated. Dow Jones Index is positively correlated with gold’s price only at its first two periods
Crane cabins' interior space multivariate anthropometric modeling.
Essdai, Ahmed; Spasojević Brkić, Vesna K; Golubović, Tamara; Brkić, Aleksandar; Popović, Vladimir
2018-01-01
Previous research has shown that today's crane cabins fail to meet the needs of a large proportion of operators. Performance and financial losses and effects on safety should not be overlooked as well. The first aim of this survey is to model the crane cabin interior space using up-to-date crane operator anthropometric data and to compare the multivariate and univariate method anthropometric models. The second aim of the paper is to define the crane cabin interior space dimensions that enable anthropometric convenience. To facilitate the cabin design, the anthropometric dimensions of 64 crane operators in the first sample and 19 more in the second sample were collected in Serbia. The multivariate anthropometric models, spanning 95% of the population on the basis of a set of 8 anthropometric dimensions, have been developed. The percentile method was also used on the same set of data. The dimensions of the interior space, necessary for the accommodation of the crane operator, are 1174×1080×1865 mm. The percentiles results for the 5th and 95th model are within the obtained dimensions. The results of this study may prove useful to crane cabin designers in eliminating anthropometric inconsistencies and improving the health of operators, but can also aid in improving the safety, performance and financial results of the companies where crane cabins operate.
MULTIVARIATE ACCOUNTING IN INTERNATIONAL FINANCIAL REPORTING STANDARDS
Directory of Open Access Journals (Sweden)
V. V. IEVDOKYMOV
2017-03-01
Full Text Available The necessity of the research on the basis of the positivist model of scientific knowledge is proved. The value of the conceptual framework in the process of bookkeeping selection is analyzed. The differences of the accounting selection adjustment procedure in US GAAP and IFRS are considered. The role and importance of the qualitative characteristics of financial reporting in the implementation of accounting selection are substantiated. The structure of the qualitative characteristics of financial reporting and their limitations under the Conceptual Framework for the preparation and presentation of financial statements are examined. The correlation between the accounting rules and alternatives adopted in US GAAP and IAS / IFRS is analyzed. The necessity to discuss the issue of the feasibility of «rule-oriented» or «principle-oriented» accounting model in the context of multivariate concept is studied. The authors prove the necessity of the application of institutional theory to solve the problems of accounting opportunism that arises when using the concept of multivariate accounting in International Financial Reporting Standards.
Fuzzy multivariable control of domestic heat pumps
International Nuclear Information System (INIS)
Underwood, C.P.
2015-01-01
Poor control has been identified as one of the reasons why recent field trials of domestic heat pumps in the UK have produced disappointing results. Most of the technology in use today uses a thermostatically-controlled fixed speed compressor with a mechanical expansion device. This article investigates improved control of these heat pumps through the design and evaluation of a new multivariable fuzzy logic control system utilising a variable speed compressor drive with capacity control linked through to evaporator superheat control. A new dynamic thermal model of a domestic heat pump validated using experimental data forms the basis of the work. The proposed control system is evaluated using median and extreme daily heating demand profiles for a typical UK house compared with a basic thermostatically-controlled alternative. Results show good tracking of the heating temperature and superheat control variables, reduced cycling and an improvement in performance averaging 20%. - Highlights: • A new dynamic model of a domestic heat pump is developed and validated. • A new multivariable fuzzy logic heat pump control system is developed/reported. • The fuzzy controller regulates both plant capacity and evaporator superheat degree. • Thermal buffer storage is also considered as well as compressor cycling. • The new controller shows good variable tracking and a reduction in energy of 20%.
Boosted Multivariate Trees for Longitudinal Data
Pande, Amol; Li, Liang; Rajeswaran, Jeevanantham; Ehrlinger, John; Kogalur, Udaya B.; Blackstone, Eugene H.; Ishwaran, Hemant
2017-01-01
Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing P-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data. PMID:29249866
Estimating uncertainty in multivariate responses to selection.
Stinchcombe, John R; Simonsen, Anna K; Blows, Mark W
2014-04-01
Predicting the responses to natural selection is one of the key goals of evolutionary biology. Two of the challenges in fulfilling this goal have been the realization that many estimates of natural selection might be highly biased by environmentally induced covariances between traits and fitness, and that many estimated responses to selection do not incorporate or report uncertainty in the estimates. Here we describe the application of a framework that blends the merits of the Robertson-Price Identity approach and the multivariate breeder's equation to address these challenges. The approach allows genetic covariance matrices, selection differentials, selection gradients, and responses to selection to be estimated without environmentally induced bias, direct and indirect selection and responses to selection to be distinguished, and if implemented in a Bayesian-MCMC framework, statistically robust estimates of uncertainty on all of these parameters to be made. We illustrate our approach with a worked example of previously published data. More generally, we suggest that applying both the Robertson-Price Identity and the multivariate breeder's equation will facilitate hypothesis testing about natural selection, genetic constraints, and evolutionary responses. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
Colombia, mining country. Vision a year 2019
International Nuclear Information System (INIS)
2006-01-01
Scope of the state action for the mining sector, the performance of the mining sector, regional perceptions of mining development, construction of a long-term vision for the mining sector, the action plan and goals follow-up
Safety Research and Experimental Coal Mines
Federal Laboratory Consortium — Safety Research and Experimental Coal MinesLocation: Pittsburgh SiteThe Safety Research Coal Mine and Experimental Mine complex is a multi-purpose underground mine...
An Optimization Routing Algorithm for Green Communication in Underground Mines
Directory of Open Access Journals (Sweden)
Heng Xu
2018-06-01
Full Text Available With the long-term dependence of humans on ore-based energy, underground mines are utilized around the world, and underground mining is often dangerous. Therefore, many underground mines have established networks that manage and acquire information from sensor nodes deployed on miners and in other places. Since the power supplies of many mobile sensor nodes are batteries, green communication is an effective approach of reducing the energy consumption of a network and extending its longevity. To reduce the energy consumption of networks, all factors that negatively influence the lifetime should be considered. The degree constraint minimum spanning tree (DCMST is introduced in this study to consider all the heterogeneous factors and assign weights for the next step of the evaluation. Then, a genetic algorithm (GA is introduced to cluster sensor nodes in the network and balance energy consumption according to several heterogeneous factors and routing paths from DCMST. Based on a comparison of the simulation results, the optimization routing algorithm proposed in this study for use in green communication in underground mines can effectively reduce the network energy consumption and extend the lifetimes of networks.
Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study.
Directory of Open Access Journals (Sweden)
Binod Neupane
Full Text Available In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between end points. However, under random-effects assumption the multivariate estimation is more complex (as it involves estimation of more parameters simultaneously than univariate estimation, and sometimes can produce unrealistic parameter estimates. Usefulness of multivariate approach to meta-analysis of the effects of a genetic variant on two or more correlated traits is not well understood in the area of genetic association studies. In such studies, genetic variants are expected to roughly maintain Hardy-Weinberg equilibrium within studies, and also their effects on complex traits are generally very small to modest and could be heterogeneous across studies for genuine reasons. We carried out extensive simulation to explore the comparative performance of multivariate approach with most commonly used univariate inverse-variance weighted approach under random-effects assumption in various realistic meta-analytic scenarios of genetic association studies of correlated end points. We evaluated the performance with respect to relative mean bias percentage, and root mean square error (RMSE of the estimate and coverage probability of corresponding 95% confidence interval of the effect for each end point. Our simulation results suggest that multivariate approach performs similarly or better than univariate method when correlations between end points within or between studies are at least moderate and between-study variation is similar or larger than average within-study variation for meta-analyses of 10 or more genetic studies. Multivariate approach produces estimates with smaller bias and RMSE especially for the end point that has randomly or informatively missing summary data in some individual studies, when
Heterogeneity: multilingualism and democracy
Directory of Open Access Journals (Sweden)
Hans-Jürgen Krumm
2004-01-01
Full Text Available Linguistic diversity and multilingualism on the part of individuals are aprerequisite and a constitutive condition of enabling people to live togetherin a world of growing heterogeneity. Foreign language teaching plays animportant part in democratic education because it can be seen as a trainingin respecting otherness and developing an intercultural, non-ethnocentricperception and attitude. This is all the more important because of the neces-sity of integrating children from migrant families into school life.My article argues that language education policy has to take this per-spective into account, i.e., of establishing a planned diversification so thatpupils (and their parents will not feel satisfied with learning English only,but also become motivated to learn languages of their own neighbourhood,such as migrant and minority languages. However, in order to make use ofthe linguistic resources in the classroom, relating it to the democratic impetusof foreign language education, it is necessary to revise existing languagepolicies and to develop a multilingual perspective for all educational institutions.
Heterogeneous burnable poisons:
International Nuclear Information System (INIS)
Leiva, Sergio; Agueda, Horacio; Russo, Diego
1989-01-01
The use of materials possessing high neutron absorption cross-section commonly known as 'burnable poisons' have its origin in BWR reactors with the purpose of improving the efficiency of the first fuel load. Later on, it was extended to PWR to compensate of initial reactivity without infringing the requirement of maintaining a negative moderator coefficient. The present tendency is to increase the use of solid burnable poisons to extend the fuel cycle life and discharge burnup. There are two concepts for the burnable poisons utilization: 1) heterogeneously distributions in the form of rods, plates, etc. and 2) homogeneous dispersions of burnable poisons in the fuel. The purpose of this work is to present the results of sinterability studies, performed on Al 2 O 3 -B 4 C and Al 2 O 3 -Gd 2 O 3 systems. Experiments were carried on pressing at room temperature mixtures of powders containing up to 5 wt % of B 4 C or Gd 2 O 3 in Al 2 O 3 and subsequently sintering at 1750 deg C in reducing atmosphere. Evaluation of density, porosity and microstructures were done and a comparison with previous experiences is shown. (Author) [es
Heterogeneity of protein hormones
Energy Technology Data Exchange (ETDEWEB)
Rosselin, G; Bataille, D; Laburthe, M; Duran-Garcia, S [Institut National de la Sante et de la Recherche Medicale (INSERM), Hopital Saint-Antoine, 75 - Paris (France)
1975-12-01
Radioimmunoassay measures antigenic determinants of hormonal molecules in the plasmas and tissues. These estimations carried out after fractionation in biological fluids, have revealed several immunological forms of the same hormone. The main problem is in the relationship of the various immunoreactive forms to the same hormonal sequence. The similar immunoreactive forms of high molecular weight usually have low biological activity and suggest the presence of prohormone; the suggestion of prohormonal nature depends on the chronology of the incorporation of labelled leucine and enzymatic transformation of prohormone with low biological into active hormone. The forms with high molecular weight and similar immunological activity may be of another nature. Thus, it has been shown that the biosynthetic nature of a compound such as big big insulin in the rat is doubtful owing to the absence of specific incorporation of labelled leucine into the immunoprecipitate of this fraction. The significance of low molecular weight form is still little known. An example of these forms is supplied by the existence of an alpha sub-unit of gonadotrophin present in the plasma of menopausal women. The interest of analytical methods by radio-receptor, simulation of cyclase activity in the identification of biological activity of immunoreactive forms, is discussed in relation to immunological forms ofenteroglucagon. An unusual aspect of the evolutive and adaptative character of hormonal heterogeneity is given by the gastro-intestinal hormones.
Parsing Heterogeneous Striatal Activity
Directory of Open Access Journals (Sweden)
Kae Nakamura
2017-05-01
Full Text Available The striatum is an input channel of the basal ganglia and is well known to be involved in reward-based decision making and learning. At the macroscopic level, the striatum has been postulated to contain parallel functional modules, each of which includes neurons that perform similar computations to support selection of appropriate actions for different task contexts. At the single-neuron level, however, recent studies in monkeys and rodents have revealed heterogeneity in neuronal activity even within restricted modules of the striatum. Looking for generality in the complex striatal activity patterns, here we briefly survey several types of striatal activity, focusing on their usefulness for mediating behaviors. In particular, we focus on two types of behavioral tasks: reward-based tasks that use salient sensory cues and manipulate outcomes associated with the cues; and perceptual decision tasks that manipulate the quality of noisy sensory cues and associate all correct decisions with the same outcome. Guided by previous insights on the modular organization and general selection-related functions of the basal ganglia, we relate striatal activity patterns on these tasks to two types of computations: implementation of selection and evaluation. We suggest that a parsing with the selection/evaluation categories encourages a focus on the functional commonalities revealed by studies with different animal models and behavioral tasks, instead of a focus on aspects of striatal activity that may be specific to a particular task setting. We then highlight several questions in the selection-evaluation framework for future explorations.
Energy Technology Data Exchange (ETDEWEB)
Shimada, S
1986-01-01
Statistics are given on: 1) Australian dependence on imported raw materials in 1980; 2) production levels in the different mining fields in 1981; 3) trends in the production of minerals over the years 1961-1981. The role of the mining industry in the Australian economy is outlined, and brief details given of its structure. Further statistics are given regarding trends in the production of coal, iron, salt, lead and zinc during the period 1961-1981, together with details of the number of people employed in these industries. Operations at some of the principal mines (coal, iron ore and salt) are outlined and 1983 production figures for all mineral resources are given. 18 refs., 21 figs., 5 tabs.
International Nuclear Information System (INIS)
Janecka, V.; Nemec, V.; Bradka, S.; Placek, V.; Sulovsky, P.
1992-01-01
The proceedings contain 30 contributions, out of which 9 have been inputted in INIS. They are concerned with uranium mines and mills in the Czech Republic. The impacts of the mining activities and of the mill tailings on the environment and the population are assessed, and it is concluded that the radiation hazard does not exceed that from natural background. Considerable attention is paid to the monitoring of the surroundings of mines and mills and to landscaping activities. Proposed technologies for the purification of waste waters from the chemical leaching process are described. Ways to eliminate environmental damage from abandoned tailings settling ponds are suggested. (M.D.). 18 tabs., 21 figs., 43 refs
Chattamvelli, Rajan
2015-01-01
DATA MINING METHODS, Second Edition discusses both theoretical foundation and practical applications of datamining in a web field including banking, e-commerce, medicine, engineering and management. This book starts byintroducing data and information, basic data type, data category and applications of data mining. The second chapterbriefly reviews data visualization technology and importance in data mining. Fundamentals of probability and statisticsare discussed in chapter 3, and novel algorithm for sample covariants are derived. The next two chapters give an indepthand useful discussion of data warehousing and OLAP. Decision trees are clearly explained and a new tabularmethod for decision tree building is discussed. The chapter on association rules discusses popular algorithms andcompares various algorithms in summary table form. An interesting application of genetic algorithm is introduced inthe next chapter. Foundations of neural networks are built from scratch and the back propagation algorithm is derived...
Auxiliary mine ventilation manual
International Nuclear Information System (INIS)
Workplace Safety North
2010-01-01
An adequate ventilation system is needed for air quality and handling in a mine and is comprised of many different pieces of equipment for removing contaminated air and supplying fresh air and thereby provide a satisfactory working environment. This manual highlights auxiliary ventilation systems made up of small fans, ducts, tubes, air movers, deflectors and additional air flow controls which distribute fresh air delivered by the primary system to all areas. A review of auxiliary ventilation is provided. Design, operation and management issues are discussed and guidelines are furnished. This manual is limited to underground hard rock operations and does not address directly other, specific auxiliary systems, either in underground coal mines or uranium mines.
Auxiliary mine ventilation manual
Energy Technology Data Exchange (ETDEWEB)
Workplace Safety North
2010-07-01
An adequate ventilation system is needed for air quality and handling in a mine and is comprised of many different pieces of equipment for removing contaminated air and supplying fresh air and thereby provide a satisfactory working environment. This manual highlights auxiliary ventilation systems made up of small fans, ducts, tubes, air movers, deflectors and additional air flow controls which distribute fresh air delivered by the primary system to all areas. A review of auxiliary ventilation is provided. Design, operation and management issues are discussed and guidelines are furnished. This manual is limited to underground hard rock operations and does not address directly other, specific auxiliary systems, either in underground coal mines or uranium mines.
DEFF Research Database (Denmark)
Hansen, T.
The purpose of this Ph.D. thesis is twofold: The first purpose is to devise a new method for application of multivariable controllers in boiler control systems in which they act as optional process optimizing extensions to conventional control systems and in such a way that the safety measures...... mentioned, the concept is applicable to new as well as existing plants. The seccond purpose is to suggest specific methods for experimental modelling and multivariable controller design which are possible to use under the conceptual framework, implement them and test them in a boiler application....
Worldwide ISL Uranium Mining Outlook
International Nuclear Information System (INIS)
Boytsov, A.; Stander, S.; Martynenko, V.
2014-01-01
Contents: • ISL uranium production historical review and current status; • ISL versus conventional mining; • Acid versus alkaline ISL; • ISL cost considerations; • Principal criteria and parameters for ISL mining; • ISL production forecast and resources availability
The South African mining industry
International Nuclear Information System (INIS)
Langton, G.
1982-01-01
This paper covers six of the many mining and associated developments in South Africa. These are: (1) Deep level gold mining at Western Deep Levels Limited - (2) Palabora Mining Company Limited - SA's unique copper mine - (3) Production of steel and vanadium-rich slag at Highveld Steel and Vanadium Corporation - (4) Coal mining at Kriel and Kleinkopje Collieries - (5) A mass mining system for use below the Gabbro Sill at Premier Diamond Mine - (6) Uranium production - joint metallurgical scheme- Orange Free State Gold Mines. - For publication in this journal the original paper has been summarised. Should any reader wish to have the full text in English he should write to the author at the address below. (orig.) [de
Construction over abandoned mine workings
Energy Technology Data Exchange (ETDEWEB)
Healy, P R; Head, J M
1984-01-01
Guidance is given for engineers involved with the planning and development of sites previously undermined for coal and other minerals. Past methods of mining employed in Britain are described, and their short- and long-term effects on surface stability are assessed. Where modern methods of mining are relevant, or where structural design techniques for the surface effects of mining can be applied, these are included for illustration and completeness. Additional objectives over and above those for conventional site investigations are identified, and details are provided for the planning and execution of a mining investigation. Techniques for consolidation of old mine workings and remedial measures for mine shafts are described. Foundation design options are included for cases where expected ground movements can be accommodated. A comprehensive guide to sources of information on previous mining is presented, together with an example of a specification suitable for the consolidation of old shallow mine workings. (50 refs.)
Swedish mines. Underground exploitation methods
International Nuclear Information System (INIS)
Paucard, A.
1960-01-01
Between 1949 and 1957, 10 engineers of the Mining research and exploitation department of the CEA visited 17 Swedish mines during 5 field trips. This paper presents a compilation of the information gathered during these field trips concerning the different underground mining techniques used in Swedish iron mines: mining with backfilling (Central Sweden and Boliden mines); mining without backfilling (mines of the polar circle area). The following techniques are described successively: pillar drawing and backfilled slices (Ammeberg, Falun, Garpenberg, Boliden group), sub-level pillar drawing (Grangesberg, Bloettberget, Haeksberg), empty room and sub-level pillar drawing (Bodas, Haksberg, Stripa, Bastkarn), storage chamber pillar drawing (Bodas, Haeksberg, Bastkarn), and pillar drawing by block caving (ldkerberget). Reprint of a paper published in Revue de l'Industrie Minerale, vol. 41, no. 12, 1959 [fr
Personal continuous route pattern mining
Institute of Scientific and Technical Information of China (English)
Qian YE; Ling CHEN; Gen-cai CHEN
2009-01-01
In the daily life, people often repeat regular routes in certain periods. In this paper, a mining system is developed to find the continuous route patterns of personal past trips. In order to count the diversity of personal moving status, the mining system employs the adaptive GPS data recording and five data filters to guarantee the clean trips data. The mining system uses a client/server architecture to protect personal privacy and to reduce the computational load. The server conducts the main mining procedure but with insufficient information to recover real personal routes. In order to improve the scalability of sequential pattern mining, a novel pattern mining algorithm, continuous route pattern mining (CRPM), is proposed. This algorithm can tolerate the different disturbances in real routes and extract the frequent patterns. Experimental results based on nine persons' trips show that CRPM can extract more than two times longer route patterns than the traditional route pattern mining algorithms.
Quantifying spatial heterogeneity from images
International Nuclear Information System (INIS)
Pomerantz, Andrew E; Song Yiqiao
2008-01-01
Visualization techniques are extremely useful for characterizing natural materials with complex spatial structure. Although many powerful imaging modalities exist, simple display of the images often does not convey the underlying spatial structure. Instead, quantitative image analysis can extract the most important features of the imaged object in a manner that is easier to comprehend and to compare from sample to sample. This paper describes the formulation of the heterogeneity spectrum to show the extent of spatial heterogeneity as a function of length scale for all length scales to which a particular measurement is sensitive. This technique is especially relevant for describing materials that simultaneously present spatial heterogeneity at multiple length scales. In this paper, the heterogeneity spectrum is applied for the first time to images from optical microscopy. The spectrum is measured for thin section images of complex carbonate rock cores showing heterogeneity at several length scales in the range 10-10 000 μm.
CSIR Research Space (South Africa)
Green, JJ
2011-07-01
Full Text Available International Conference of CAD/CAM, Robotics & Factories of the Future (CARs&FOF 2011) 26-28 July 2-11, Kuala Lumpur, Malaysia Mining Robotics Sensors Perception Sensors on a Mine Safety Platform Green JJ1, Hlophe K2, Dickens J3, Teleka R4, Mathew Price5...-28 July 2-11, Kuala Lumpur, Malaysia visualization in confined, lightless environments, and thermography for assessing the safety and stability of hanging walls. Over the last decade approximately 200 miners have lost their lives per year in South...
CSIR Research Space (South Africa)
Monchusi, B
2012-10-01
Full Text Available stream_source_info Monchusi_2012.pdf.txt stream_content_type text/plain stream_size 1953 Content-Encoding ISO-8859-1 stream_name Monchusi_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Novel Mining Methods 4th... 2012 Slide 12 CSIR mine safety platform AR Drone Differential time-of-flight beacon Sampling ? CSIR 2012 Slide 13 Reef Laser-Induced Breakdown Spectroscopy (LIBS) head Scan X-Y Laser/Spectrometer/Computer Rock Breaking ? CSIR 2012 Slide...
Brown, Meta S
2014-01-01
Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business''s entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn''t take a data scientist to gain
Mena, Jesus
2013-01-01
With today's consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire.Data Mining Mobile Devices defines the collection of machine-sensed environmental data pertaining to human social behavior. It explains how the integration of data mining and machine learning can enable the modeling of conversation context, proximity sensing, and geospatial location throughout large communities of mobile users
A STUDY OF TEXT MINING METHODS, APPLICATIONS,AND TECHNIQUES
R. Rajamani*1 & S. Saranya2
2017-01-01
Data mining is used to extract useful information from the large amount of data. It is used to implement and solve different types of research problems. The research related areas in data mining are text mining, web mining, image mining, sequential pattern mining, spatial mining, medical mining, multimedia mining, structure mining and graph mining. Text mining also referred to text of data mining, it is also called knowledge discovery in text (KDT) or knowledge of intelligent text analysis. T...
Models and Inference for Multivariate Spatial Extremes
Vettori, Sabrina
2017-12-07
The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical
MIDAS: Regionally linear multivariate discriminative statistical mapping.
Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos
2018-07-01
Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the
2010-07-01
... SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Maps § 77.1200 Mine...) The location of railroad tracks and public highways leading to the mine, and mine buildings of a permanent nature with identifying names shown; (k) Underground mine workings underlying and within 1,000...
WIRELESS MINE WIDE TELECOMMUNICATIONS TECHNOLOGY
International Nuclear Information System (INIS)
Zvi H. Meiksin
2002-01-01
Two industrial prototype units for through-the-earth wireless communication were constructed and tested. Preparation for a temporary installation in NIOSH's Lake Lynn mine for the through-the-earth and the in-mine system were completed. Progress was made in the programming of the in-mine system to provide data communication. Work has begun to implement a wireless interface between equipment controllers and our in-mine system
WIRELESS MINE WIDE TELECOMMUNICATIONS TECHNOLOGY
Energy Technology Data Exchange (ETDEWEB)
Zvi H. Meiksin
2002-04-01
Two industrial prototype units for through-the-earth wireless communication were constructed and tested. Preparation for a temporary installation in NIOSH's Lake Lynn mine for the through-the-earth and the in-mine system were completed. Progress was made in the programming of the in-mine system to provide data communication. Work has begun to implement a wireless interface between equipment controllers and our in-mine system.
Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity.
Balluff, B; Hanselmann, M; Heeren, R M A
2017-01-01
One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research. © 2017 Elsevier Inc. All rights reserved.
Classification of adulterated honeys by multivariate analysis.
Amiry, Saber; Esmaiili, Mohsen; Alizadeh, Mohammad
2017-06-01
In this research, honey samples were adulterated with date syrup (DS) and invert sugar syrup (IS) at three concentrations (7%, 15% and 30%). 102 adulterated samples were prepared in six batches with 17 replications for each batch. For each sample, 32 parameters including color indices, rheological, physical, and chemical parameters were determined. To classify the samples, based on type and concentrations of adulterant, a multivariate analysis was applied using principal component analysis (PCA) followed by a linear discriminant analysis (LDA). Then, 21 principal components (PCs) were selected in five sets. Approximately two-thirds were identified correctly using color indices (62.75%) or rheological properties (67.65%). A power discrimination was obtained using physical properties (97.06%), and the best separations were achieved using two sets of chemical properties (set 1: lactone, diastase activity, sucrose - 100%) (set 2: free acidity, HMF, ash - 95%). Copyright © 2016 Elsevier Ltd. All rights reserved.
Multivariate Functional Data Visualization and Outlier Detection
Dai, Wenlin; Genton, Marc G.
2017-01-01
This article proposes a new graphical tool, the magnitude-shape (MS) plot, for visualizing both the magnitude and shape outlyingness of multivariate functional data. The proposed tool builds on the recent notion of functional directional outlyingness, which measures the centrality of functional data by simultaneously considering the level and the direction of their deviation from the central region. The MS-plot intuitively presents not only levels but also directions of magnitude outlyingness on the horizontal axis or plane, and demonstrates shape outlyingness on the vertical axis. A dividing curve or surface is provided to separate non-outlying data from the outliers. Both the simulated data and the practical examples confirm that the MS-plot is superior to existing tools for visualizing centrality and detecting outliers for functional data.
Multivariate Functional Data Visualization and Outlier Detection
Dai, Wenlin
2017-03-19
This article proposes a new graphical tool, the magnitude-shape (MS) plot, for visualizing both the magnitude and shape outlyingness of multivariate functional data. The proposed tool builds on the recent notion of functional directional outlyingness, which measures the centrality of functional data by simultaneously considering the level and the direction of their deviation from the central region. The MS-plot intuitively presents not only levels but also directions of magnitude outlyingness on the horizontal axis or plane, and demonstrates shape outlyingness on the vertical axis. A dividing curve or surface is provided to separate non-outlying data from the outliers. Both the simulated data and the practical examples confirm that the MS-plot is superior to existing tools for visualizing centrality and detecting outliers for functional data.
Lectures in feedback design for multivariable systems
Isidori, Alberto
2017-01-01
This book focuses on methods that relate, in one form or another, to the “small-gain theorem”. It is aimed at readers who are interested in learning methods for the design of feedback laws for linear and nonlinear multivariable systems in the presence of model uncertainties. With worked examples throughout, it includes both introductory material and more advanced topics. Divided into two parts, the first covers relevant aspects of linear-systems theory, the second, nonlinear theory. In order to deepen readers’ understanding, simpler single-input–single-output systems generally precede treatment of more complex multi-input–multi-output (MIMO) systems and linear systems precede nonlinear systems. This approach is used throughout, including in the final chapters, which explain the latest advanced ideas governing the stabilization, regulation, and tracking of nonlinear MIMO systems. Two major design problems are considered, both in the presence of model uncertainties: asymptotic stabilization with a “...
Multivariate approach to matrimonial mobility in Catalonia.
Calafell, F; Hernández, M
1993-10-01
Matrimonial mobility in Catalonia was studied using 1986 census data. Comarca (a geographic division) of birth was used as the population unit, and a measure of affinity (a statistical distance) between comarques in spouse geographic origin was defined. This distance was analyzed with multivariate methods drawn from numerical taxonomy to detect any discontinuities in matrimonial mobility and gene flow between comarques. Results show a three-level pattern of gene flow in Catalonia: (1) a strong endogamy within comarques; (2) a 100-km matrimonial circle around every comarca; and (3) the capital, Barcelona, which attracts migrants from all over Catalonia. The regionalization in matrimonial mobility follows the geographically clear-cut groups of comarques almost exactly.
Nonparametric Bayes Modeling of Multivariate Categorical Data.
Dunson, David B; Xing, Chuanhua
2012-01-01
Modeling of multivariate unordered categorical (nominal) data is a challenging problem, particularly in high dimensions and cases in which one wishes to avoid strong assumptions about the dependence structure. Commonly used approaches rely on the incorporation of latent Gaussian random variables or parametric latent class models. The goal of this article is to develop a nonparametric Bayes approach, which defines a prior with full support on the space of distributions for multiple unordered categorical variables. This support condition ensures that we are not restricting the dependence structure a priori. We show this can be accomplished through a Dirichlet process mixture of product multinomial distributions, which is also a convenient form for posterior computation. Methods for nonparametric testing of violations of independence are proposed, and the methods are applied to model positional dependence within transcription factor binding motifs.
Some developments in multivariate image analysis
DEFF Research Database (Denmark)
Kucheryavskiy, Sergey
be up to several million. The main MIA tool for exploratory analysis is score density plot – all pixels are projected into principal component space and on the corresponding scores plots are colorized according to their density (how many pixels are crowded in the unit area of the plot). Looking...... for and analyzing patterns on these plots and the original image allow to do interactive analysis, to get some hidden information, build a supervised classification model, and much more. In the present work several alternative methods to original principal component analysis (PCA) for building the projection......Multivariate image analysis (MIA), one of the successful chemometric applications, now is used widely in different areas of science and industry. Introduced in late 80s it has became very popular with hyperspectral imaging, where MIA is one of the most efficient tools for exploratory analysis...
Multivariate analysis of data in sensory science
Naes, T; Risvik, E
1996-01-01
The state-of-the-art of multivariate analysis in sensory science is described in this volume. Both methods for aggregated and individual sensory profiles are discussed. Processes and results are presented in such a way that they can be understood not only by statisticians but also by experienced sensory panel leaders and users of sensory analysis. The techniques presented are focused on examples and interpretation rather than on the technical aspects, with an emphasis on new and important methods which are possibly not so well known to scientists in the field. Important features of the book are discussions on the relationship among the methods with a strong accent on the connection between problems and methods. All procedures presented are described in relation to sensory data and not as completely general statistical techniques. Sensory scientists, applied statisticians, chemometricians, those working in consumer science, food scientists and agronomers will find this book of value.
FACT. Multivariate extraction of muon ring images
Energy Technology Data Exchange (ETDEWEB)
Noethe, Maximilian; Temme, Fabian; Buss, Jens [Experimentelle Physik 5b, TU Dortmund, Dortmund (Germany); Collaboration: FACT-Collaboration
2016-07-01
In ground-based gamma-ray astronomy, muon ring images are an important event class for instrument calibration and monitoring of its properties. In this talk, a multivariate approach will be presented, that is well suited for real time extraction of muons from data streams of Imaging Atmospheric Cherenkov Telescopes (IACT). FACT, the First G-APD Cherenkov Telescope is located on the Canary Island of La Palma and is the first IACT to use Silicon Photomultipliers for detecting the Cherenkov photons of extensive air showers. In case of FACT, the extracted muon events are used to calculate the time resolution of the camera. In addition, the effect of the mirror alignment in May 2014 on properties of detected muons is investigated. Muon candidates are identified with a random forest classification algorithm. The performance of the classifier is evaluated for different sets of image parameters in order to compare the gain in performance with the computational costs of their calculation.
Validation of models with multivariate output
International Nuclear Information System (INIS)
Rebba, Ramesh; Mahadevan, Sankaran
2006-01-01
This paper develops metrics for validating computational models with experimental data, considering uncertainties in both. A computational model may generate multiple response quantities and the validation experiment might yield corresponding measured values. Alternatively, a single response quantity may be predicted and observed at different spatial and temporal points. Model validation in such cases involves comparison of multiple correlated quantities. Multiple univariate comparisons may give conflicting inferences. Therefore, aggregate validation metrics are developed in this paper. Both classical and Bayesian hypothesis testing are investigated for this purpose, using multivariate analysis. Since, commonly used statistical significance tests are based on normality assumptions, appropriate transformations are investigated in the case of non-normal data. The methodology is implemented to validate an empirical model for energy dissipation in lap joints under dynamic loading
Advanced event reweighting using multivariate analysis
International Nuclear Information System (INIS)
Martschei, D; Feindt, M; Honc, S; Wagner-Kuhr, J
2012-01-01
Multivariate analysis (MVA) methods, especially discrimination techniques such as neural networks, are key ingredients in modern data analysis and play an important role in high energy physics. They are usually trained on simulated Monte Carlo (MC) samples to discriminate so called 'signal' from 'background' events and are then applied to data to select real events of signal type. We here address procedures that improve this work flow. This will be the enhancement of data / MC agreement by reweighting MC samples on a per event basis. Then training MVAs on real data using the sPlot technique will be discussed. Finally we will address the construction of MVAs whose discriminator is independent of a certain control variable, i.e. cuts on this variable will not change the discriminator shape.
Multivariate Markov chain modeling for stock markets
Maskawa, Jun-ichi
2003-06-01
We study a multivariate Markov chain model as a stochastic model of the price changes of portfolios in the framework of the mean field approximation. The time series of price changes are coded into the sequences of up and down spins according to their signs. We start with the discussion for small portfolios consisting of two stock issues. The generalization of our model to arbitrary size of portfolio is constructed by a recurrence relation. The resultant form of the joint probability of the stationary state coincides with Gibbs measure assigned to each configuration of spin glass model. Through the analysis of actual portfolios, it has been shown that the synchronization of the direction of the price changes is well described by the model.
New mine projects, positive outlook
Energy Technology Data Exchange (ETDEWEB)
M. Cremer
2006-12-15
Speaking on the first day at the Mining 2006 Resources Convention the Deputy Director General, Mining and Petroleum gave an optimistic outlook for mining in 2007 based on the number of new projects under consideration or construction. The convention was held in early November in Brisbane, Queensland, Australia. 3 figs., 1 photo.
Process mining : overview and opportunities
Aalst, van der W.M.P.
2012-01-01
Over the last decade, process mining emerged as a new research ¿eld that focuses on the analysis of processes using event data. Classical data mining techniques such as classi¿cation, clustering, regression, association rule learning, and sequence/episode mining do not focus on business process
Studies in frequent tree mining
Knijf, De J.
2008-01-01
Employing Data mining techniques for structured data is particularly challenging, because it is commonly assumed that the structure of the data encodes part of its semantics. As a result are classical data mining techniques insufficient to analyze and mine these data. In this thesis we develop
Review of South American mines
International Nuclear Information System (INIS)
Anon.
1984-01-01
A general overview is presented of the mining activity and plans for South America. The countries which are presented are Columbia, Argentina, Brazil, Venezuela, Chile, Peru, and Bolivia. The products of the mines include coal, bauxite, gold, iron, uranium, copper and numerous other minor materials. A discussion of current production, support and processing facilities, and mining strategies is also given
in remediating acid mine drainage
African Journals Online (AJOL)
The management and treatment of contaminated mine water is one of the most urgent problems facing the South African mining industry. The cost advantage of permeable reactive barriers (PRBs) has seen their increased application as means of passively treating mine drainage. A PRB is built by placing a reactive material ...
Heterogeneity of reward mechanisms.
Lajtha, A; Sershen, H
2010-06-01
The finding that many drugs that have abuse potential and other natural stimuli such as food or sexual activity cause similar chemical changes in the brain, an increase in extracellular dopamine (DA) in the shell of the nucleus accumbens (NAccS), indicated some time ago that the reward mechanism is at least very similar for all stimuli and that the mechanism is relatively simple. The presently available information shows that the mechanisms involved are more complex and have multiple elements. Multiple brain regions, multiple receptors, multiple distinct neurons, multiple transmitters, multiple transporters, circuits, peptides, proteins, metabolism of transmitters, and phosphorylation, all participate in reward mechanisms. The system is variable, is changed during development, is sex-dependent, and is influenced by genetic differences. Not all of the elements participate in the reward of all stimuli. Different set of mechanisms are involved in the reward of different drugs of abuse, yet different mechanisms in the reward of natural stimuli such as food or sexual activity; thus there are different systems that distinguish different stimuli. Separate functions of the reward system such as anticipation, evaluation, consummation and identification; all contain function-specific elements. The level of the stimulus also influences the participation of the elements of the reward system, there are possible reactions to even below threshold stimuli, and excessive stimuli can change reward to aversion involving parts of the system. Learning and memory of past reward is an important integral element of reward and addictive behavior. Many of the reward elements are altered by repeated or chronic stimuli, and chronic exposure to one drug is likely to alter the response to another stimulus. To evaluate and identify the reward stimulus thus requires heterogeneity of the reward components in the brain.
Energy Technology Data Exchange (ETDEWEB)
Bogdan, A. [Helsinki Univ. (Finland). Dept. of Physics
1994-12-31
The classical theory of heterogenous ice nucleation is reviewed in detail. The modelling of ice nucleation in the adsorbed water films on natural particles by analogous ice nucleation in adsorbed water films on the walls of porous media is discussed. Ice nucleation in adsorbed films of purewater and the HNO{sub 3}/H{sub 2}0 binary system on the surface of porous aerosol (SiO{sub 2}) was investigated using the method of NMR spectroscopy. The median freezing temperature and freezing temperature region were shown to be highly sensitive both to the average thickness of the adsorbed films and to the amount of adsorbed nitric acid. The character of the ice phase formation tends to approach that of bulk liquid with increasing adsorbed film thickness. Under the given conditions the thickness of the adsorbed films decreases with an increasing amount of adsorbed nitric acid molecules The molar concentration of nitric acid in the adsorbed films is very small (of the order of 10{sup -}3 10{sup -}2 (M/l)). Nitric acid molecules tend to adsorb on the surface of aerosol to a greater extent than in subsequent layers. The concentration is greatest in layers situated close to the surface and sharply decreases with the distance from the surface. The difference between the median freezing temperatures for adsorbed pure water and for the binary system was found to be about 9 K for films of equal thickness. This is about 150 times greater than the difference between the median freezing temperatures of bulk pure water and a solution with the same concentration of nitric acid. (orig.)
Heterogeneous dissipative composite structures
Ryabov, Victor; Yartsev, Boris; Parshina, Ludmila
2018-05-01
The paper suggests mathematical models of decaying vibrations in layered anisotropic plates and orthotropic rods based on Hamilton variation principle, first-order shear deformation laminated plate theory (FSDT), as well as on the viscous-elastic correspondence principle of the linear viscoelasticity theory. In the description of the physical relationships between the materials of the layers forming stiff polymeric composites, the effect of vibration frequency and ambient temperature is assumed as negligible, whereas for the viscous-elastic polymer layer, temperature-frequency relationship of elastic dissipation and stiffness properties is considered by means of the experimentally determined generalized curves. Mitigation of Hamilton functional makes it possible to describe decaying vibration of anisotropic structures by an algebraic problem of complex eigenvalues. The system of algebraic equation is generated through Ritz method using Legendre polynomials as coordinate functions. First, real solutions are found. To find complex natural frequencies of the system, the obtained real natural frequencies are taken as input values, and then, by means of the 3rd order iteration method, complex natural frequencies are calculated. The paper provides convergence estimates for the numerical procedures. Reliability of the obtained results is confirmed by a good correlation between analytical and experimental values of natural frequencies and loss factors in the lower vibration tones for the two series of unsupported orthotropic rods formed by stiff GRP and CRP layers and a viscoelastic polymer layer. Analysis of the numerical test data has shown the dissipation & stiffness properties of heterogeneous composite plates and rods to considerably depend on relative thickness of the viscoelastic polymer layer, orientation of stiff composite layers, vibration frequency and ambient temperature.
Derivatives of Multivariate Bernstein Operators and Smoothness with Jacobi Weights
Directory of Open Access Journals (Sweden)
Jianjun Wang
2012-01-01
Full Text Available Using the modulus of smoothness, directional derivatives of multivariate Bernstein operators with weights are characterized. The obtained results partly generalize the corresponding ones for multivariate Bernstein operators without weights.
Regularized multivariate regression models with skew-t error distributions
Chen, Lianfu; Pourahmadi, Mohsen; Maadooliat, Mehdi
2014-01-01
We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both
Graphics for the multivariate two-sample problem
International Nuclear Information System (INIS)
Friedman, J.H.; Rafsky, L.C.
1981-01-01
Some graphical methods for comparing multivariate samples are presented. These methods are based on minimal spanning tree techniques developed for multivariate two-sample tests. The utility of these methods is illustrated through examples using both real and artificial data
Multivariate Receptor Models for Spatially Correlated Multipollutant Data
Jun, Mikyoung; Park, Eun Sug
2013-01-01
The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air
Marshall-Olkin multivariate semi-logistic distribution and minification ...
African Journals Online (AJOL)
Olkin multivariate logistic distribution (MO-ML) are introduced and studied. Various characterizations properties of Marshall-Olkin multivariate semi-logistic distribution are investigated and studied. First order autoregressive minification processes ...
Scale and shape mixtures of multivariate skew-normal distributions
Arellano-Valle, Reinaldo B.; Ferreira, Clé cio S.; Genton, Marc G.
2018-01-01
We introduce a broad and flexible class of multivariate distributions obtained by both scale and shape mixtures of multivariate skew-normal distributions. We present the probabilistic properties of this family of distributions in detail and lay down
A direction of developing a mining method and mining complexes
Energy Technology Data Exchange (ETDEWEB)
Gabov, V.V.; Efimov, I.A. [St. Petersburg State Mining Institute, St. Petersburg (Russian Federation). Vorkuta Branch
1996-12-31
The analyses of a mining method as a main factor determining the development stages of mining units is presented. The paper suggests a perspective mining method which differs from the known ones by following peculiarities: the direction selectivity of cuts with regard to coal seams structure; the cutting speed, thickness and succession of dusts. This method may be done by modulate complexes (a shield carrying a cutting head for coal mining), their mining devices being supplied with hydraulic drive. An experimental model of the module complex has been developed. 2 refs.
Energy Technology Data Exchange (ETDEWEB)
Goergen, H; Stoll, R D; Vriesen, R D; Welzenberg, B
1981-01-01
The dictionary reflects the latest technical developments in the vocabulary of mining methods and the mining industry. Volume I of the dictionary is English to German, Volume II German to English. 36,000 entries are included.
75 FR 17529 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines
2010-04-06
... High-Voltage Continuous Mining Machine Standard for Underground Coal Mines AGENCY: Mine Safety and... of high-voltage continuous mining machines in underground coal mines. It also revises MSHA's design...-- Underground Coal Mines III. Section-by-Section Analysis A. Part 18--Electric Motor-Driven Mine Equipment and...
Internet technologies in the mining industry. Towards unattended mining systems
Energy Technology Data Exchange (ETDEWEB)
Krzykawski, Michal [FAMUR Group, Katowice (Poland)
2009-08-27
Global suppliers of longwall systems focus mainly on maximising the efficiency of the equipment they manufacture. Given the fact that, since 2004, coal demand on world markets has been constantly on the increase, even during an economic downturn, this endeavour seems fully justified. However, it should be remembered that maximum efficiency must be accompanied by maximum safety of all underground operations. This statement is based on the belief that the mining industry, which exploits increasingly deep and dangerous coal beds, faces the necessity to implement comprehensive IT systems for managing all mining processes and, in the near future, to use unmanned mining systems, fully controllable from the mine surface. The computerisation of mines is an indispensable element of the development of the world mining industry, a belief which has been put into practice with e-mine, developed by the FAMUR Group. (orig.)
Mining Together : Large-Scale Mining Meets Artisanal Mining, A Guide for Action
World Bank
2009-01-01
The present guide mining together-when large-scale mining meets artisanal mining is an important step to better understanding the conflict dynamics and underlying issues between large-scale and small-scale mining. This guide for action not only points to some of the challenges that both parties need to deal with in order to build a more constructive relationship, but most importantly it sh...
Mining frequent binary expressions
Calders, T.; Paredaens, J.; Kambayashi, Y.; Mohania, M.K.; Tjoa, A.M.
2000-01-01
In data mining, searching for frequent patterns is a common basic operation. It forms the basis of many interesting decision support processes. In this paper we present a new type of patterns, binary expressions. Based on the properties of a specified binary test, such as reflexivity, transitivity
Energy Technology Data Exchange (ETDEWEB)
Gualdron, R; Camacho, R [Intercor, Barranquilla (Colombia). Environmental Engineering Division
1993-10-01
This article describes the rehabilitation of dumps and backfill areas at the world's largest export coal mine, El Cerrejon Zone Norte, in Northern Colombia. The rehabilitation process includes the preparation of surfaces and slopes, the placement of topsoil and the revegetation and reforestation of the prepared areas. 8 photos.
Peek, N.; Combi, C.; Tucker, A.
2009-01-01
Objective: To introduce the special topic of Methods of Information in Medicine on data mining in biomedicine, with selected papers from two workshops on Intelligent Data Analysis in bioMedicine (IDAMAP) held in Verona (2006) and Amsterdam (2007). Methods: Defining the field of biomedical data
Sosa Landeo, Milagros
2017-01-01
This thesis documents as well as questions how the presence of large mining operations in Andean regions of Peru alters social and natural landscapes. Taking conflicts over water as a useful entry-point for the analysis, it explores and unravels the dilemmas and challenges faced by the main
Energy Technology Data Exchange (ETDEWEB)
Sikora, W [Politechnika Slaska, Gliwice (Poland). Instytut Mechanizacji Gornictwa
1989-06-01
Discusses thin seam mining in Poland and its prospects. There were 194 working faces in coal seams to 1.5 m thick in Poland in 1988. Of them, 115 fell on faces with powered supports, 79 on faces with SHC-40 and Valent props; 108 shearer loaders and 45 coal plows were used for longwall mining of thin coal seams. Drilling and blasting was used to mine 21 working faces. Longwall faces in seams to 1.0 m thick gave 2.0% coal output, faces in coal seams 1.01-1.5 m thick gave 12.2% of daily coal output of underground mining. Structure of daily coal output of faces in thin seams was the following: 52 faces below 300 t/day, 42 from 301-500 t/day, 63 from 501 to 1,000 t/day, 17 faces above 1,000 t/day. Prospects for increasing coal output of faces in thin seams are discussed. 7 refs.
Aggarwal, Charu C
2014-01-01
Proposes numerous methods to solve some of the most fundamental problems in data mining and machine learning Presents various simplified perspectives, providing a range of information to benefit both students and practitioners Includes surveys on key research content, case studies and future research directions
Mei, Qiaozhu
2009-01-01
With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the…
International Nuclear Information System (INIS)
Crouch, K.M.
1976-01-01
The requirements of the law which must be met in order to create title to an unpatented mining claim and the procedures which should be followed when an attempt is made to determine the title to the claim is acceptable are reviewed
Leemans, I.B.; Broomhall, Susan
2017-01-01
Digital emotion research has yet to make history. Until now large data set mining has not been a very active ﬁeld of research in early modern emotion studies. This is indeed surprising since ﬁrst, the early modern ﬁeld has such rich, copyright-free, digitized data sets and second, emotion studies
Vreeken, J.
2009-01-01
The discovery of patterns plays an important role in data mining. A pattern can be any type of regularity displayed in that data, such as, e.g. which items are typically sold together, which genes are mostly active for patients of a certain disease, etc, etc. Generally speaking, finding a pattern is
International Nuclear Information System (INIS)
Davies, W.
1997-01-01
Energy Resource of Australia (ERA) is a public company with 68% of its shares owned by the Australian company North Limited. It is currently operating one major production centre - Ranger Mine which is 260 kilometres east of Darwin, extracting and selling uranium from the Ranger Mine in the Northern Territory to nuclear electricity utilities in Japan, South Korea, Europe and North America. The first drum of uranium oxide from Ranger was drummed in August 1981 and operations have continued since that time. ERA is also in the process of working towards obtaining approvals for the development of a second mine - Jabiluka which is located 20 kilometres north of Ranger. The leases of Ranger and Jabiluka adjoin. The Minister for the Environment has advised the Minister for Resources and Energy that there does not appear to be any environmental issue which would prevent the preferred Jabiluka proposal from proceeding. Consent for the development of ERA's preferred option for the development of Jabiluka is being sought from the Aboriginal Traditional Owners. Ranger is currently the third largest producing uranium mine in the world producing 4,237 tonnes of U 3 O 8 in the year to June 1997
The Grants Mineral Belt was the focus of uranium extraction and production activities from the 1950s until the late 1990s. EPA is working with state, local, and federal partners to assess and address health risks and environmental effects of the mines
Mueller, Rob; Murphy, Gloria
2010-01-01
This slide presentation describes a competition to design a lunar robot (lunabot) that can be controlled either remotely or autonomously, isolated from the operator, and is designed to mine a lunar aggregate simulant. The competition is part of a systems engineering curriculum. The 2010 competition winners in five areas of the competition were acknowledged, and the 2011 competition was announced.
Klein, Robert; Tischler, Judith S; Mühling, Martin; Schlömann, Michael
2014-01-01
Caused by the oxidative dissolution of sulfide minerals, mine waters are often acidic and contaminated with high concentrations of sulfates, metals, and metalloids. Because the so-called acid mine drainage (AMD) affects the environment or poses severe problems for later use, treatment of these waters is required. Therefore, various remediation strategies have been developed to remove soluble metals and sulfates through immobilization using physical, chemical, and biological approaches. Conventionally, iron and sulfate-the main pollutants in mine waters-are removed by addition of neutralization reagents and subsequent chemical iron oxidation and sulfate mineral precipitation. Biological treatment strategies take advantage of the ability of microorganisms that occur in mine waters to metabolize iron and sulfate. As a rule, these can be grouped into oxidative and reductive processes, reflecting the redox state of mobilized iron (reduced form) and sulfur (oxidized form) in AMD. Changing the redox states of iron and sulfur results in iron and sulfur compounds with low solubility, thus leading to their precipitation and removal. Various techniques have been developed to enhance the efficacy of these microbial processes, as outlined in this review.
Multivariate Pareto Minification Processes | Umar | Journal of the ...
African Journals Online (AJOL)
Autoregressive (AR) and autoregressive moving average (ARMA) processes with multivariate exponential (ME) distribution are presented and discussed. The theory of positive dependence is used to show that in many cases, multivariate exponential autoregressive (MEAR) and multivariate autoregressive moving average ...
Multivariate semi-logistic distribution and processes | Umar | Journal ...
African Journals Online (AJOL)
Multivariate semi-logistic distribution is introduced and studied. Some characterizations properties of multivariate semi-logistic distribution are presented. First order autoregressive minification processes and its generalization to kth order autoregressive minification processes with multivariate semi-logistic distribution as ...
Multivariable biorthogonal continuous--discrete Wilson and Racah polynomials
International Nuclear Information System (INIS)
Tratnik, M.V.
1990-01-01
Several families of multivariable, biorthogonal, partly continuous and partly discrete, Wilson polynomials are presented. These yield limit cases that are purely continuous in some of the variables and purely discrete in the others, or purely discrete in all the variables. The latter are referred to as the multivariable biorthogonal Racah polynomials. Interesting further limit cases include the multivariable biorthogonal Hahn and dual Hahn polynomials
A model-based approach to studying changes in compositional heterogeneity
Baeten, L.; Warton, D.; Calster, van H.; Frenne, De P.; Verstraeten, G.; Bonte, D.; Bernhardt-Romermann, M.; Cornelis, R.; Decocq, G.; Eriksson, O.; Hommel, P.W.F.M.
2014-01-01
1. Non-random species loss and gain in local communities change the compositional heterogeneity between communities over time, which is traditionally quantified with dissimilarity-based approaches. Yet, dissimilarities summarize the multivariate species data into a univariate index and obscure the
Physics Mining of Multi-Source Data Sets
Helly, John; Karimabadi, Homa; Sipes, Tamara
2012-01-01
Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.
Data mining in healthcare: decision making and precision
Directory of Open Access Journals (Sweden)
Ionuţ ŢĂRANU
2016-05-01
Full Text Available The trend of application of data mining in healthcare today is increased because the health sector is rich with information and data mining has become a necessity. Healthcare organizations generate and collect large volumes of information to a daily basis. Use of information technology enables automation of data mining and knowledge that help bring some interesting patterns which means eliminating manual tasks and easy data extraction directly from electronic records, electronic transfer system that will secure medical records, save lives and reduce the cost of medical services as well as enabling early detection of infectious diseases on the basis of advanced data collection. Data mining can enable healthcare organizations to anticipate trends in the patient's medical condition and behaviour proved by analysis of prospects different and by making connections between seemingly unrelated information. The raw data from healthcare organizations are voluminous and heterogeneous. It needs to be collected and stored in organized form and their integration allows the formation unite medical information system. Data mining in health offers unlimited possibilities for analyzing different data models less visible or hidden to common analysis techniques. These patterns can be used by healthcare practitioners to make forecasts, put diagnoses, and set treatments for patients in healthcare organizations.
Imaging metabolic heterogeneity in cancer.
Sengupta, Debanti; Pratx, Guillem
2016-01-06
As our knowledge of cancer metabolism has increased, it has become apparent that cancer metabolic processes are extremely heterogeneous. The reasons behind this heterogeneity include genetic diversity, the existence of multiple and redundant metabolic pathways, altered microenvironmental conditions, and so on. As a result, methods in the clinic and beyond have been developed in order to image and study tumor metabolism in the in vivo and in vitro regimes. Both regimes provide unique advantages and challenges, and may be used to provide a picture of tumor metabolic heterogeneity that is spatially and temporally comprehensive. Taken together, these methods may hold the key to appropriate cancer diagnoses and treatments in the future.
International Nuclear Information System (INIS)
Pimiento, Elkin Vargas
1998-01-01
In order to obtain the best social and environmental results from mining activities, different solutions, which involve a variety of perspectives, have been proposed. These include the worldwide perspective based in the economy globalization paradigms; the regional perspective, focused in the integration of countries; the national perspective, which emphasizes the natural assets and development options, and finally a local perspective is incorporated to account for the participation of directly affected communities. Within this framework, the mining industry is requested to develop both technological and managerial tools appropriate to evaluate, optimize and communicate the social and environmental performance and output of its related activities, mainly in the developing countries. On the other hand, the governments have been committed to implement regulatory actions, of command and control type, based on an environmental legislation in line with the above mentioned perspectives and also to use economical instruments as a mean to accomplish environmental objectives. In Colombia the direct regulation methods have been traditionally used to prevent the environmental deterioration produced by mining activities, however, since the 1991 political constitution and the law 99 of 1993, the communities' participation and economical instruments were incorporated. A historic summary of the environmental legislation in our country from the early 70's up to now, showing its implications in mining is presented. Then a favorable tendency is indicated in the environmental improvement of the national extractive industry, accomplished as a result of the implementation of new strategies to minimize the impact of mining on the environment and to improve the well being of local communities
Technologies for Decreasing Mining Losses
Valgma, Ingo; Väizene, Vivika; Kolats, Margit; Saarnak, Martin
2013-12-01
In case of stratified deposits like oil shale deposit in Estonia, mining losses depend on mining technologies. Current research focuses on extraction and separation possibilities of mineral resources. Selective mining, selective crushing and separation tests have been performed, showing possibilities of decreasing mining losses. Rock crushing and screening process simulations were used for optimizing rock fractions. In addition mine backfilling, fine separation, and optimized drilling and blasting have been analyzed. All tested methods show potential and depend on mineral usage. Usage in addition depends on the utilization technology. The questions like stability of the material flow and influences of the quality fluctuations to the final yield are raised.
Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald
2017-12-01
An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.
Ecosystem Health Assessment of Mining Cities Based on Landscape Pattern
Yu, W.; Liu, Y.; Lin, M.; Fang, F.; Xiao, R.
2017-09-01
Ecosystem health assessment (EHA) is one of the most important aspects in ecosystem management. Nowadays, ecological environment of mining cities is facing various problems. In this study, through ecosystem health theory and remote sensing images in 2005, 2009 and 2013, landscape pattern analysis and Vigor-Organization-Resilience (VOR) model were applied to set up an evaluation index system of ecosystem health of mining city to assess the healthy level of ecosystem in Panji District Huainan city. Results showed a temporal stable but high spatial heterogeneity landscape pattern during 2005-2013. According to the regional ecosystem health index, it experienced a rapid decline after a slight increase, and finally it maintained at an ordinary level. Among these areas, a significant distinction was presented in different towns. It indicates that the ecosystem health of Tianjijiedao town, the regional administrative centre, descended rapidly during the study period, and turned into the worst level in the study area. While the Hetuan Town, located in the northwestern suburb area of Panji District, stayed on a relatively better level than other towns. The impacts of coal mining collapse area, land reclamation on the landscape pattern and ecosystem health status of mining cities were also discussed. As a result of underground coal mining, land subsidence has become an inevitable problem in the study area. In addition, the coal mining subsidence area has brought about the destruction of the farmland, construction land and water bodies, which causing the change of the regional landscape pattern and making the evaluation of ecosystem health in mining area more difficult. Therefore, this study provided an ecosystem health approach for relevant departments to make scientific decisions.
Economic impact of world mining
International Nuclear Information System (INIS)
Walser, G.
2002-01-01
Mining plays a vital role in the economic development of many countries. The emerging economies are now major players in the production and availability of key commodities such as copper (70%), bauxite (40%), iron ore and precious metals. Mining also has a positive impact on the economy of many countries. Another impact of mining can be measured in terms of employment opportunities and income generation. Commercial scale mining provides employment and skills transfer to more than 2 million workers. The multiplier effect increases this benefit by a factor of between 2 and 5. The World Bank Mining Department has carried out an in-depth study on economic and social impact of mining at the community level in Chile, Peru, Bolivia, Papua New Guinea and Mali. This study demonstrates that there are substantial social and economic benefits to the community. The most positive cases are related to the growth of local small- and micro-enterprise activities. However, mining remains controversial, as true sustainable development is not only a matter of financial flows. Mining has also been associated with a number of economic and social problems. As a result there are questions about the sustainability of the economic outcome of mining. The contribution of mining to sustainable development needs to be considered in terms of economic and technical viability, ecological sustainability and social equity. To achieve this, governments, mining companies and local communities must work together to address these issues. (author)
Service mining framework and application
Chang, Wei-Lun
2014-01-01
The shifting focus of service from the 1980s to 2000s has proved that IT not only lowers the cost of service but creates avenues to enhance and increase revenue through service. The new type of service, e-service, is mobile, flexible, interactive, and interchangeable. While service science provides an avenue for future service researches, the specific research areas from the IT perspective still need to be elaborated. This book introduces a novel concept-service mining-to address several research areas from technology, model, management, and application perspectives. Service mining is defined as "a systematical process including service discovery, service experience, service recovery, and service retention to discover unique patterns and exceptional values within the existing services." The goal of service mining is similar to data mining, text mining, or web mining, and aims to "detect something new" from the service pool. The major difference is the feature of service is quite distinct from the mining targe...
Energy Technology Data Exchange (ETDEWEB)
McCloskey, G
1986-07-01
A comprehensive review of new steam coal mines being planned or developed worldwide. It shows that at least 20 major mines with a combined annual output of 110 million tonnes per annum, could add their coal to world markets in the next 10 years. The review highlights: substantial activity in Australia with at least four major mines at advanced planning stages; a strengthening of the South American export industry with 4 major mines operating in 10 years compared with just one today; no major export mines being developed in the traditional US mining areas; and the emergence of Indonesia as a major steam coal producer/exporter. The review also shows a reduction in cost/output ratios, and also the proximity of the new mines to existing infrastructure (e.g. export terminals, rail links).
Method for statistical data analysis of multivariate observations
Gnanadesikan, R
1997-01-01
A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte
Viscous fingering with permeability heterogeneity
International Nuclear Information System (INIS)
Tan, C.; Homsy, G.M.
1992-01-01
Viscous fingering in miscible displacements in the presence of permeability heterogeneities is studied using two-dimensional simulations. The heterogeneities are modeled as stationary random functions of space with finite correlation scale. Both the variance and scale of the heterogeneities are varied over modest ranges. It is found that the fingered zone grows linearly in time in a fashion analogous to that found in homogeneous media by Tan and Homsy [Phys. Fluids 31, 1330 (1988)], indicating a close coupling between viscous fingering on the one hand and flow through preferentially more permeable paths on the other. The growth rate of the mixing zone increases monotonically with the variance of the heterogeneity, as expected, but shows a maximum as the correlation scale is varied. The latter is explained as a ''resonance'' between the natural scale of fingers in homogeneous media and the correlation scale
Tumor Heterogeneity and Drug Resistance
International Nuclear Information System (INIS)
Kucerova, L.; Skolekova, S.; Kozovska, Z.
2015-01-01
New generation of sequencing methodologies revealed unexpected complexity and genomic alterations linked with the tumor subtypes. This diversity exists across the tumor types, histologic tumor subtypes and subsets of the tumor cells within the same tumor. This phenomenon is termed tumor heterogeneity. Regardless of its origin and mechanisms of development it has a major impact in the clinical setting. Genetic, phenotypic and expression pattern diversity of tumors plays critical role in the selection of suitable treatment and also in the prognosis prediction. Intratumoral heterogeneity plays a key role in the intrinsic and acquired chemoresistance to cytotoxic and targeted therapies. In this review we focus on the mechanisms of intratumoral and inter tumoral heterogeneity and their relationship to the drug resistance. Understanding of the mechanisms and spatiotemporal dynamics of tumor heterogeneity development before and during the therapy is important for the ability to design individual treatment protocols suitable in the given molecular context. (author)
Aggregation Algorithms in Heterogeneous Tables
Directory of Open Access Journals (Sweden)
Titus Felix FURTUNA
2006-01-01
Full Text Available The heterogeneous tables are most used in the problem of aggregation. A solution for this problem is to standardize these tables of figures. In this paper, we proposed some methods of aggregation based on the hierarchical algorithms.
Homogenisation of heterogeneous viscoplastic materials.
Sluis, van der O.; Schreurs, P.J.G.; Meijer, H.E.H.; Anderson, P.D.; Kruijt, P.G.M.
1999-01-01
Heterogeneous materials have been used extensively in the past few decades, since their mechanical properties, such as strength, stiffness and toughness are being improved continuously. Experimental work has clearly demonstrated the significant influence of the micromechanical phenomena on the
Multivariate meta-analysis: a robust approach based on the theory of U-statistic.
Ma, Yan; Mazumdar, Madhu
2011-10-30
Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.
2015-05-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Multivariate Welch t-test on distances.
Alekseyenko, Alexander V
2016-12-01
Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method, however, suffers from loss of power and type I error inflation in the presence of heteroscedasticity and sample size imbalances. We develop a solution in the form of a distance-based Welch t-test, [Formula: see text], for two sample potentially unbalanced and heteroscedastic data. We demonstrate empirically the desirable type I error and power characteristics of the new test. We compare the performance of PERMANOVA and [Formula: see text] in reanalysis of two existing microbiome datasets, where the methodology has originated. The source code for methods and analysis of this article is available at https://github.com/alekseyenko/Tw2 Further guidance on application of these methods can be obtained from the author. alekseye@musc.edu. © The Author 2016. Published by Oxford University Press.
Multivariate sensitivity to voice during auditory categorization.
Lee, Yune Sang; Peelle, Jonathan E; Kraemer, David; Lloyd, Samuel; Granger, Richard
2015-09-01
Past neuroimaging studies have documented discrete regions of human temporal cortex that are more strongly activated by conspecific voice sounds than by nonvoice sounds. However, the mechanisms underlying this voice sensitivity remain unclear. In the present functional MRI study, we took a novel approach to examining voice sensitivity, in which we applied a signal detection paradigm to the assessment of multivariate pattern classification among several living and nonliving categories of auditory stimuli. Within this framework, voice sensitivity can be interpreted as a distinct neural representation of brain activity that correctly distinguishes human vocalizations from other auditory object categories. Across a series of auditory categorization tests, we found that bilateral superior and middle temporal cortex consistently exhibited robust sensitivity to human vocal sounds. Although the strongest categorization was in distinguishing human voice from other categories, subsets of these regions were also able to distinguish reliably between nonhuman categories, suggesting a general role in auditory object categorization. Our findings complement the current evidence of cortical sensitivity to human vocal sounds by revealing that the greatest sensitivity during categorization tasks is devoted to distinguishing voice from nonvoice categories within human temporal cortex. Copyright © 2015 the American Physiological Society.
Multivariate volume visualization through dynamic projections
Energy Technology Data Exchange (ETDEWEB)
Liu, Shusen [Univ. of Utah, Salt Lake City, UT (United States); Wang, Bei [Univ. of Utah, Salt Lake City, UT (United States); Thiagarajan, Jayaraman J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bremer, Peer -Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States)
2014-11-01
We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization. We assume that the complex, high-dimensional data in the attribute space can be well-represented through a collection of low-dimensional linear subspaces, and embed the data points in a variety of 2D views created as projections onto these subspaces. Through dynamic projections, we present animated transitions between different views to help the user navigate and explore the attribute space for effective transfer function design. Our framework not only provides a more intuitive understanding of the attribute space but also allows the design of the transfer function under multiple dynamic views, which is more flexible than being restricted to a single static view of the data. For large volumetric datasets, we maintain interactivity during the transfer function design via intelligent sampling and scalable clustering. As a result, using examples in combustion and climate simulations, we demonstrate how our framework can be used to visualize interesting structures in the volumetric space.
Scattering amplitudes from multivariate polynomial division
Energy Technology Data Exchange (ETDEWEB)
Mastrolia, Pierpaolo, E-mail: pierpaolo.mastrolia@cern.ch [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Muenchen (Germany); Dipartimento di Fisica e Astronomia, Universita di Padova, Padova (Italy); INFN Sezione di Padova, via Marzolo 8, 35131 Padova (Italy); Mirabella, Edoardo, E-mail: mirabell@mppmu.mpg.de [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Muenchen (Germany); Ossola, Giovanni, E-mail: GOssola@citytech.cuny.edu [New York City College of Technology, City University of New York, 300 Jay Street, Brooklyn, NY 11201 (United States); Graduate School and University Center, City University of New York, 365 Fifth Avenue, New York, NY 10016 (United States); Peraro, Tiziano, E-mail: peraro@mppmu.mpg.de [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Muenchen (Germany)
2012-11-15
We show that the evaluation of scattering amplitudes can be formulated as a problem of multivariate polynomial division, with the components of the integration-momenta as indeterminates. We present a recurrence relation which, independently of the number of loops, leads to the multi-particle pole decomposition of the integrands of the scattering amplitudes. The recursive algorithm is based on the weak Nullstellensatz theorem and on the division modulo the Groebner basis associated to all possible multi-particle cuts. We apply it to dimensionally regulated one-loop amplitudes, recovering the well-known integrand-decomposition formula. Finally, we focus on the maximum-cut, defined as a system of on-shell conditions constraining the components of all the integration-momenta. By means of the Finiteness Theorem and of the Shape Lemma, we prove that the residue at the maximum-cut is parametrized by a number of coefficients equal to the number of solutions of the cut itself.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.; Kleiber, William
2015-01-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Multivariate Heteroscedasticity Models for Functional Brain Connectivity
Directory of Open Access Journals (Sweden)
Christof Seiler
2017-12-01
Full Text Available Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI. We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.
Hierarchical multivariate covariance analysis of metabolic connectivity.
Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J
2014-12-01
Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).
Data-driven modeling of background and mine-related acidity and metals in river basins
International Nuclear Information System (INIS)
Friedel, Michael J.
2014-01-01
A novel application of self-organizing map (SOM) and multivariate statistical techniques is used to model the nonlinear interaction among basin mineral-resources, mining activity, and surface-water quality. First, the SOM is trained using sparse measurements from 228 sample sites in the Animas River Basin, Colorado. The model performance is validated by comparing stochastic predictions of basin-alteration assemblages and mining activity at 104 independent sites. The SOM correctly predicts (>98%) the predominant type of basin hydrothermal alteration and presence (or absence) of mining activity. Second, application of the Davies–Bouldin criteria to k-means clustering of SOM neurons identified ten unique environmental groups. Median statistics of these groups define a nonlinear water-quality response along the spatiotemporal hydrothermal alteration-mining gradient. These results reveal that it is possible to differentiate among the continuum between inputs of background and mine-related acidity and metals, and it provides a basis for future research and empirical model development. The trained self-organizing map is used to determine upstream hydrothermal alteration (AS – acid sulfate; PROP – propylitic, PROP-V – propylitic veins, QSP – quartz-sericite-pyrite, WSP – weak-sericite-pyrite; Mining activity: MINES) from water-quality measurements in the Animas river basin, Colorado, USA. The white hexagons are sized proportional to the number of water-quality samples associated with that SOM neuron. Highlights: • We model surface-water quality response using a self-organizing map and multivariate statistics. • Applying Davies–Bouldin criteria to k-means clusters defines ten environmental response groups. • The approach differentiates between background and mine-related acidity and metals. -- These results reveal that it is possible to differentiate among the continuum between inputs of background and mine-related acidity and metals
Li, Yanming; Nan, Bin; Zhu, Ji
2015-06-01
We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.
On Design Mining: Coevolution and Surrogate Models.
Preen, Richard J; Bull, Larry
2017-01-01
Design mining is the use of computational intelligence techniques to iteratively search and model the attribute space of physical objects evaluated directly through rapid prototyping to meet given objectives. It enables the exploitation of novel materials and processes without formal models or complex simulation. In this article, we focus upon the coevolutionary nature of the design process when it is decomposed into concurrent sub-design-threads due to the overall complexity of the task. Using an abstract, tunable model of coevolution, we consider strategies to sample subthread designs for whole-system testing and how best to construct and use surrogate models within the coevolutionary scenario. Drawing on our findings, we then describe the effective design of an array of six heterogeneous vertical-axis wind turbines.
Maione, Camila; Barbosa, Rommel Melgaço
2018-01-24
Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.
International Nuclear Information System (INIS)
Rawlings., D.E.; Silver, S.
1995-01-01
Microbes are playing increasingly important roles in commercial mining operations, where they are being used in the open-quotes bioleachingclose quotes of copper, uranium, and gold ores. Direct leaching is when microbial metabolism changes the redox state of the metal being harvested, rendering it more soluble. Indirect leaching includes redox chemistry of other metal cations that are then coupled in chemical oxidation or reduction of the harvested metal ion and microbial attack upon and solubilization of the mineral matrix in which the metal is physically embedded. In addition, bacterial cells are used to detoxify the waste cyanide solution from gold-mining operations and as open-quotes absorbantsclose quotes of the mineral cations. Bacterial cells may replace activated carbon or alternative biomass. With an increasing understanding of microbial physiology, biochemistry and molecular genetics, rational approaches to improving these microbial activities become possible. 40 refs., 3 figs
Dardzinska, Agnieszka
2013-01-01
We are surrounded by data, numerical, categorical and otherwise, which must to be analyzed and processed to convert it into information that instructs, answers or aids understanding and decision making. Data analysts in many disciplines such as business, education or medicine, are frequently asked to analyze new data sets which are often composed of numerous tables possessing different properties. They try to find completely new correlations between attributes and show new possibilities for users. Action rules mining discusses some of data mining and knowledge discovery principles and then describe representative concepts, methods and algorithms connected with action. The author introduces the formal definition of action rule, notion of a simple association action rule and a representative action rule, the cost of association action rule, and gives a strategy how to construct simple association action rules of a lowest cost. A new approach for generating action rules from datasets with numerical attributes...
Ontario's uranium mining industry
International Nuclear Information System (INIS)
Runnalls, O.J.C.
1981-01-01
This report traces the Ontario uranium mining industry from the first discovery of uranium north of Sault Ste. Marie through the uranium boom of the 1950's when Elliot Lake and Bancroft were developed, the cutbacks of the 1960s, the renewed enthusiasm in exploration and development of the 1970s to the current position when continued production for the domestic market is assured. Ontario, with developed mines and operational expertise, will be in a position to compete for export markets as they reopen. The low level of expenditures for uranium exploration and the lack of new discoveries are noted. The report also reviews and places in perspective the development of policies and regulations governing the industry and the jurisdictional relationships of the Federal and Provincial governments
Directory of Open Access Journals (Sweden)
Nicolas Houy
2016-12-01
Full Text Available This article deals with the mining incentives in the Bitcoin protocol. The mining process is used to confirm and secure transactions. This process is organized as a speed game between individuals or firms – the miners – with different computational powers to solve a mathematical problem, bring a proof of work, spread their solution and reach consensus among the Bitcoin network nodes with it. First, we define and specify this game. Second, we analytically find its Nash equilibria in the two-player case. We analyze the parameters for which the miners would face the proper incentives to fulfill their function of transaction processors in the current situation. Finally, we study the block space market offer.
Realtime mine ventilation simulation
International Nuclear Information System (INIS)
McDaniel, K.H.
1997-01-01
This paper describes the development of a Windows based, interactive mine ventilation simulation software program at the Waste Isolation Pilot Plant (WIPP). To enhance the operation of the underground ventilation system, Westinghouse Electric Corporation developed the program called WIPPVENT. While WIPPVENT includes most of the functions of the commercially available simulation program VNETPC and uses the same subroutine to calculate airflow distributions, the user interface has been completely rewritten as a Windows application with screen graphics. WIPPVENT is designed to interact with WIPP ventilation monitoring systems through the sitewise Central monitoring System. Data can be continuously collected from the Underground Ventilation Remote Monitoring and Control System (e.g., air quantity and differential pressure) and the Mine Weather Stations (psychrometric data). Furthermore, WIPPVENT incorporates regulator characteristic curves specific to the site. The program utilizes this data to create and continuously update a REAL-TIME ventilation model. This paper discusses the design, key features, and interactive capabilities of WIPPVENT
Mine Waste Disposal and Managements
Energy Technology Data Exchange (ETDEWEB)
Cheong, Young-Wook; Min, Jeong-Sik; Kwon, Kwang-Soo [Korea Institute of Geology Mining and Materials, Taejon (KR)] (and others)
1999-12-01
This research project deals with: Analysis and characterization of mine waste piles or tailings impoundment abandoned in mining areas; Survey of mining environmental pollution from mine waste impounds; Modelling of pollutants in groundwater around tailings impoundment; Demonstration of acid rock drainage from coal mine waste rock piles and experiment of seeding on waste rock surface; Development of a liner using tailings. Most of mine wastes are deposited on natural ground without artificial liners and capping for preventing contamination of groundwater around mine waste piles or containments. In case of some mine waste piles or containments, pollutants have been released to the environment, and several constituents in drainage exceed the limit of discharge from landfill site. Metals found in drainage exist in exchangeable fraction in waste rock and tailings. This means that if when it rains to mine waste containments, mine wastes can be pollutant to the environment by release of acidity and metals. As a result of simulation for hydraulic potentials and groundwater flow paths within the tailings, the simulated travel paths correlated well with the observed contaminant distribution. The plum disperse, both longitudinal and transverse dimensions, with time. Therefore liner system is a very important component in tailings containment system. As experimental results of liner development using tailings, tailings mixed with some portion of resin or cement may be used for liner because tailings with some additives have a very low hydraulic conductivity. (author). 39 refs.
Energy Technology Data Exchange (ETDEWEB)
NONE
1964-01-15
Safety in mining radioactive ores, and in milling and treating them, has been a serious preoccupation for some thirty years. Much earlier than this, however, a high incidence of lung cancer had been reported among the miners of the Erzgebirge mountains in the German-Czechoslovak border region (places familiar under the names of Schneeberg and St. Joachims thai). Investigations into deaths from radium poisoning began at these mines in 1937, and the results seemed to indicate a causal connection between the radioactive substances and the development of lung cancer and other diseases. These matters were discussed in Vienna at the symposium on Radiological Health and Safety in Nuclear Materials Mining and Milling, 26-31 August 1963. The symposium was organized by IAEA and co-sponsored by ILO and WHO; some 70 papers were presented. The purpose of the meeting was to collect and compare the very widely scattered research results and practical experience in this field. One conclusion which emerged was that the milling of uranium ore involves no unusual problem. Provided standard controls - as applied to the treatment of other minerals - are strictly enforced, exposure to radiation can be kept to a minimum. In the actual mining of uranium, the problems are only beginning to be clearly defined, but it seems to be well established that exposure of miners to excessive levels of radon will have most serious consequences. In a complicated pattern there are many factors at work, ranging from the physical behaviour of sundry radioactive substances to the personal histories of individual miners. The need for considerably more research was stressed throughout the discussions.
International Nuclear Information System (INIS)
1964-01-01
Safety in mining radioactive ores, and in milling and treating them, has been a serious preoccupation for some thirty years. Much earlier than this, however, a high incidence of lung cancer had been reported among the miners of the Erzgebirge mountains in the German-Czechoslovak border region (places familiar under the names of Schneeberg and St. Joachims thai). Investigations into deaths from radium poisoning began at these mines in 1937, and the results seemed to indicate a causal connection between the radioactive substances and the development of lung cancer and other diseases. These matters were discussed in Vienna at the symposium on Radiological Health and Safety in Nuclear Materials Mining and Milling, 26-31 August 1963. The symposium was organized by IAEA and co-sponsored by ILO and WHO; some 70 papers were presented. The purpose of the meeting was to collect and compare the very widely scattered research results and practical experience in this field. One conclusion which emerged was that the milling of uranium ore involves no unusual problem. Provided standard controls - as applied to the treatment of other minerals - are strictly enforced, exposure to radiation can be kept to a minimum. In the actual mining of uranium, the problems are only beginning to be clearly defined, but it seems to be well established that exposure of miners to excessive levels of radon will have most serious consequences. In a complicated pattern there are many factors at work, ranging from the physical behaviour of sundry radioactive substances to the personal histories of individual miners. The need for considerably more research was stressed throughout the discussions.
International Nuclear Information System (INIS)
Mackay, G.A.
1978-01-01
Western world requirements for uranium based on increasing energy consumption and a changing energy mix, will warrant the development of Australia's resources. By 1985 Australian mines could be producing 9500 tonnes of uranium oxide yearly and by 1995 the export value from uranium could reach that from wool. In terms of benefit to the community the economic rewards are considerable but, in terms of providing energy to the world, Australias uranium is vital
Special survey: mining industry
International Nuclear Information System (INIS)
Preece, H.
1981-01-01
South Africa is now the world's second biggest producer of non-oil minerals after the United States and far ahead of Canada and Australia, according to the author. South Africa's economic growth prospects over the 1980's are inevitably crucially dependent on the mining industry. The production and economics of various minerals are discussed, with special reference to gold, coal, diamonds, uranium, platinum, manganese, copper and asbestos
Dealing with spatial heterogeneity
Marsily, Gh.; Delay, F.; Gonçalvès, J.; Renard, Ph.; Teles, V.; Violette, S.
2005-03-01
Heterogeneity can be dealt with by defining homogeneous equivalent properties, known as averaging, or by trying to describe the spatial variability of the rock properties from geologic observations and local measurements. The techniques available for these descriptions are mostly continuous Geostatistical models, or discontinuous facies models such as the Boolean, Indicator or Gaussian-Threshold models and the Markov chain model. These facies models are better suited to treating issues of rock strata connectivity, e.g. buried high permeability channels or low permeability barriers, which greatly affect flow and, above all, transport in aquifers. Genetic models provide new ways to incorporate more geology into the facies description, an approach that has been well developed in the oil industry, but not enough in hydrogeology. The conclusion is that future work should be focused on improving the facies models, comparing them, and designing new in situ testing procedures (including geophysics) that would help identify the facies geometry and properties. A world-wide catalog of aquifer facies geometry and properties, which could combine site genesis and description with methods used to assess the system, would be of great value for practical applications. On peut aborder le problème de l'hétérogénéité en s'efforçant de définir une perméabilité équivalente homogène, par prise de moyenne, ou au contraire en décrivant la variation dans l'espace des propriétés des roches à partir des observations géologiques et des mesures locales. Les techniques disponibles pour une telle description sont soit continues, comme l'approche Géostatistique, soit discontinues, comme les modèles de faciès, Booléens, ou bien par Indicatrices ou Gaussiennes Seuillées, ou enfin Markoviens. Ces modèles de faciès sont mieux capables de prendre en compte la connectivité des strates géologiques, telles que les chenaux enfouis à forte perméabilité, ou au contraire les faci
Multivariate statistical analysis of wildfires in Portugal
Costa, Ricardo; Caramelo, Liliana; Pereira, Mário
2013-04-01
Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).
Multivariate spatial condition mapping using subtractive fuzzy cluster means.
Sabit, Hakilo; Al-Anbuky, Adnan
2014-10-13
Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining.
Samms, Kevin O.
2015-01-01
The Data Mining project seeks to bring the capability of data visualization to NASA anomaly and problem reporting systems for the purpose of improving data trending, evaluations, and analyses. Currently NASA systems are tailored to meet the specific needs of its organizations. This tailoring has led to a variety of nomenclatures and levels of annotation for procedures, parts, and anomalies making difficult the realization of the common causes for anomalies. Making significant observations and realizing the connection between these causes without a common way to view large data sets is difficult to impossible. In the first phase of the Data Mining project a portal was created to present a common visualization of normalized sensitive data to customers with the appropriate security access. The tool of the visualization itself was also developed and fine-tuned. In the second phase of the project we took on the difficult task of searching and analyzing the target data set for common causes between anomalies. In the final part of the second phase we have learned more about how much of the analysis work will be the job of the Data Mining team, how to perform that work, and how that work may be used by different customers in different ways. In this paper I detail how our perspective has changed after gaining more insight into how the customers wish to interact with the output and how that has changed the product.
Nemati, Hamid R.; Barko, Christopher D.
Many organizations today possess substantial quantities of business information but have very little real business knowledge. A recent survey of 450 business executives reported that managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. To reverse this trend, businesses of all sizes would be well advised to adopt Organizational Data Mining (ODM). ODM is defined as leveraging Data Mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage. ODM has helped many organizations optimize internal resource allocations while better understanding and responding to the needs of their customers. The fundamental aspects of ODM can be categorized into Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the key distinction between ODM and Data Mining. In this chapter, we introduce ODM, explain its unique characteristics, and report on the current status of ODM research. Next we illustrate how several leading organizations have adopted ODM and are benefiting from it. Then we examine the evolution of ODM to the present day and conclude our chapter by contemplating ODM's challenging yet opportunistic future.
International Nuclear Information System (INIS)
Darmody, R.G.; Hetzler, R.T.; Simmons, F.W.
1992-01-01
Longwall coal mining in southern Illinois occurs beneath some of the best agricultural land in the U.S. This region is characterized by highly productive, nearly level, and somewhat poorly drained soils. Subsidence from longwall mining causes changes in surface topography which alters surface and subsurface hydrology. These changes can adversely affect agricultural land by creating wet or ponded areas that can be deleterious to crop production. While most subsided areas show little impact from subsidence, some areas experience total crop failure. Coal companies are required by law to mitigate subsidence damage to cropland. The objective of this paper is to test the effectiveness of mitigation in restoring grain yields to their pre-mined levels. The research was conducted on sites selected to represent conventional mitigation techniques on the predominate soils in the area. Corn (Zea mays L.) and soybean [Glycine max.(L.) Merr] yields in 1988, 1989, 1990, and 1991 from mitigated areas were compared to yields from nearby undisturbed areas
Energy Technology Data Exchange (ETDEWEB)
Breuer, H
1978-01-01
This report summarizes the information gained from research carried out under the five-year programme (1971-1976) relating to health in mines. This programme concentrates on technical means of dust control, and the various aspects of this topic are reviewed. The purpose of the epidemiology of pneumoconiosis is to determine the origin and development of this endemic disease with a view to formulating a policy of worker protection. The constituents of dust and their possible influences are studied. Measuring and determining the characteristics of dusts are the subject of the second group of research projects. Prevention techniques have been proposed, tried out and developed, thus providing the mining industry with a set of dust control methods. water infusion, dedusting on coal-getting and heading machines, control of dust produced by caving, etc. A chapter devoted to iron ore mines discusses means of protection against noxious emissions from Diesel engines and explosives. (Editions available in English, in German, in French, in Italian, and in Dutch)
Alday, Josu G; Zaldívar, Pilar; Torroba-Balmori, Paloma; Fernández-Santos, Belén; Martínez-Ruiz, Carolina
2016-07-01
The characterization of suitable microsites for tree seedling establishment and growth is one of the most important tasks to achieve the restoration of native forest using natural processes in disturbed sites. For that, we assessed the natural Quercus petraea forest expansion in a 20-year-old reclaimed open-cast mine under sub-Mediterranean climate in northern Spain, monitoring seedling survival, growth, and recruitment during 5 years in three contrasting environments (undisturbed forest, mine edge, and mine center). Seedling density and proportion of dead branches decreased greatly from undisturbed forest towards the center of the mine. There was a positive effect of shrubs on Q. petraea seedling establishment in both mine environments, which increase as the environment undergoes more stress (from the mine edge to the center of the mine), and it was produced by different shrub structural features in each mine environment. Seedling survival reduction through time in three environments did not lead to a density reduction because there was a yearly recruitment of new seedlings. Seedling survival, annual growth, and height through time were greater in mine sites than in the undisturbed forest. The successful colonization patterns and positive neighbor effect of shrubs on natural seedlings establishment found in this study during the first years support the use of shrubs as ecosystem engineers to increase heterogeneity in micro-environmental conditions on reclaimed mine sites, which improves late-successional Quercus species establishment.
Mining technology and policy issues 1983
International Nuclear Information System (INIS)
Anon.
1983-01-01
This book presents conference papers on advances in mineral processing, coal mining, communications for mining executives, environmental laws and regulations, exploration philosophy, exploration technology, government controls and the environment, management, mine finance, minerals availability, mine safety, occupational health, open pit mining, the precious metals outlook, public lands, system improvements in processing ores, and underground mining. Topics considered include coal pipelines and saline water, an incentive program for coal mines, sandwich belt high-angle conveyors, the development of a mining company, regulations for radionuclides, contracts for western coal production for Pacific Rim exports, and the control of radon daughters in underground mines
Optimal Control of Heterogeneous Systems with Endogenous Domain of Heterogeneity
International Nuclear Information System (INIS)
Belyakov, Anton O.; Tsachev, Tsvetomir; Veliov, Vladimir M.
2011-01-01
The paper deals with optimal control of heterogeneous systems, that is, families of controlled ODEs parameterized by a parameter running over a domain called domain of heterogeneity. The main novelty in the paper is that the domain of heterogeneity is endogenous: it may depend on the control and on the state of the system. This extension is crucial for several economic applications and turns out to rise interesting mathematical problems. A necessary optimality condition is derived, where one of the adjoint variables satisfies a differential inclusion (instead of equation) and the maximization of the Hamiltonian takes the form of “min-max”. As a consequence, a Pontryagin-type maximum principle is obtained under certain regularity conditions for the optimal control. A formula for the derivative of the objective function with respect to the control from L ∞ is presented together with a sufficient condition for its existence. A stylized economic example is investigated analytically and numerically.
Imouraren mining exploitation : Complementary studies Synthetic report Volum B - Mines
International Nuclear Information System (INIS)
1980-01-01
The object of the current study is to determine the main technical characteristics of the reference project of a mine that can supply the necessary ore quantity at a production of 3000 tonnes uranium per year, along 10 years. The project is one of the possible solutions for exploiting the mine. The current study permits to establish : investment and functioning cost estimation, overall project of the mining exploitation program, necessary strength estimation, average ore grades evaluation and variations of these grades, utilities needs, production vizing program, main exploitation methods and necessary materials. Reference project study of the mine serves as base to the economics studies and studies optimization [fr
Long, K.R.
1995-01-01
Modern mining law, by facilitating socially and environmentally acceptable exploration, development, and production of mineral materials, helps secure the benefits of mineral production while minimizing environmental harm and accounting for increasing land-use competition. Mining investments are sunk costs, irreversibly tied to a particular mineral site, and require many years to recoup. Providing security of tenure is the most critical element of a practical mining law. Governments owning mineral rights have a conflict of interest between their roles as a profit-maximizing landowner and as a guardian of public welfare. As a monopoly supplier, governments have considerable power to manipulate mineral-rights markets. To avoid monopoly rent-seeking by governments, a competitive market for government-owned mineral rights must be created by artifice. What mining firms will pay for mineral rights depends on expected exploration success and extraction costs. Landowners and mining firms will negotlate respective shares of anticipated differential rents, usually allowing for some form of risk sharing. Private landowners do not normally account for external benefits or costs of minerals use. Government ownership of mineral rights allows for direct accounting of social prices for mineral-bearing lands and external costs. An equitable and efficient method is to charge an appropriate reservation price for surface land use, net of the value of land after reclamation, and to recover all or part of differential rents through a flat income or resource-rent tax. The traditional royalty on gross value of production, essentially a regressive income tax, cannot recover as much rent as a flat income tax, causes arbitrary mineral-reserve sterilization, and creates a bias toward development on the extensive margin where marginal environmental costs are higher. Mitigating environmental costs and resolving land-use conflicts require local evaluation and planning. National oversight ensures
Mining highly stressed areas, part 2.
CSIR Research Space (South Africa)
Johnson, R
1995-12-01
Full Text Available A questionnaire related to mining at great depth and in very high stress conditions has been completed with the assistance of mine rock mechanics personnel on over twenty mines in all mining districts, and covering all deep level mines...
2010-07-01
... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Mining wastes. 6.7 Section 6... DISPOSAL SITES IN UNITS OF THE NATIONAL PARK SYSTEM § 6.7 Mining wastes. (a) Solid waste from mining includes but is not limited to mining overburden, mining byproducts, solid waste from the extraction...
Maryati, Sri; Shimada, Hideki; Hamanaka, Akihiro; Sasaoka, Takashi; Matsui, Kikuo
2012-01-01
Coal mining industry gives many benefits for Indonesia including contribution in total Indonesian GDP. Most of coal mines in Indonesia are open pit mining method which disturbs large area of land. One of open pit mining impact is damage land and related to soil erosion occurrences it will degrade land by top soil loses. Indonesia Government has issued mine closure regulation to encourage mining industry provide post mining land use. Determination of post mining land use should be considering ...
Data mining for bioinformatics applications
Zengyou, He
2015-01-01
Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research.
Mine waters: Acidic to circumneutral
Nordstrom, D. Kirk
2011-01-01
Acid mine waters, often containing toxic concentrations of Fe, Al, Cu, Zn, Cd, Pb, Ni, Co, and Cr, can be produced from the mining of coal and metallic deposits. Values of pH for acid mine waters can range from –3.5 to 5, but even circumneutral (pH ≈ 7) mine waters can have high concentrations of As, Sb, Mo, U, and F. When mine waters are discharged into streams, lakes, and the oceans, serious degradation of water quality and injury to aquatic life can ensue, especially when tailings impoundments break suddenly. The main acid-producing process is the exposure of pyrite to air and water, which promotes oxidative dissolution, a reaction catalyzed by microbes. Current and future mining should plan for the prevention and remediation of these contaminant discharges by the application of hydrogeochemical principles and available technologies, which might include remining and recycling of waste materials.
Coal mine subsidence and structures
International Nuclear Information System (INIS)
Gray, R.E.
1988-01-01
Underground coal mining has occurred beneath 32 x 10 9 m 2 (8 million acres) of land in the United States and will eventually extend beneath 162 x 10 9 m 2 (40 million acres). Most of this mining has taken place and will take place in the eastern half of the United States. In areas of abandoned mines where total extraction was not achieved, roof collapse, crushing of coal pillars, or punching of coal pillars into softer mine floor or roof rock is now resulting in sinkhole or trough subsidence tens or even hundreds of years after mining. Difference in geology, in mining, and building construction practice between Europe and the United States preclude direct transfer of European subsidence engineering experience. Building damage cannot be related simply to tensile and compressive strains at the ground surface. Recognition of the subsidence damage role played by ground-structure interaction and by structural details is needed
DEFF Research Database (Denmark)
Gidofalvi, Gyozo; Pedersen, Torben Bach
2005-01-01
Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based Services (LBS). To achieve high quality for such services, spatio-temporal data mining techniques...... are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms...... the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed....
Organizational heterogeneity of vertebrate genomes.
Frenkel, Svetlana; Kirzhner, Valery; Korol, Abraham
2012-01-01
Genomes of higher eukaryotes are mosaics of segments with various structural, functional, and evolutionary properties. The availability of whole-genome sequences allows the investigation of their structure as "texts" using different statistical and computational methods. One such method, referred to as Compositional Spectra (CS) analysis, is based on scoring the occurrences of fixed-length oligonucleotides (k-mers) in the target DNA sequence. CS analysis allows generating species- or region-specific characteristics of the genome, regardless of their length and the presence of coding DNA. In this study, we consider the heterogeneity of vertebrate genomes as a joint effect of regional variation in sequence organization superimposed on the differences in nucleotide composition. We estimated compositional and organizational heterogeneity of genome and chromosome sequences separately and found that both heterogeneity types vary widely among genomes as well as among chromosomes in all investigated taxonomic groups. The high correspondence of heterogeneity scores obtained on three genome fractions, coding, repetitive, and the remaining part of the noncoding DNA (the genome dark matter--GDM) allows the assumption that CS-heterogeneity may have functional relevance to genome regulation. Of special interest for such interpretation is the fact that natural GDM sequences display the highest deviation from the corresponding reshuffled sequences.
Organizational heterogeneity of vertebrate genomes.
Directory of Open Access Journals (Sweden)
Svetlana Frenkel
Full Text Available Genomes of higher eukaryotes are mosaics of segments with various structural, functional, and evolutionary properties. The availability of whole-genome sequences allows the investigation of their structure as "texts" using different statistical and computational methods. One such method, referred to as Compositional Spectra (CS analysis, is based on scoring the occurrences of fixed-length oligonucleotides (k-mers in the target DNA sequence. CS analysis allows generating species- or region-specific characteristics of the genome, regardless of their length and the presence of coding DNA. In this study, we consider the heterogeneity of vertebrate genomes as a joint effect of regional variation in sequence organization superimposed on the differences in nucleotide composition. We estimated compositional and organizational heterogeneity of genome and chromosome sequences separately and found that both heterogeneity types vary widely among genomes as well as among chromosomes in all investigated taxonomic groups. The high correspondence of heterogeneity scores obtained on three genome fractions, coding, repetitive, and the remaining part of the noncoding DNA (the genome dark matter--GDM allows the assumption that CS-heterogeneity may have functional relevance to genome regulation. Of special interest for such interpretation is the fact that natural GDM sequences display the highest deviation from the corresponding reshuffled sequences.
International Nuclear Information System (INIS)
Lebecka, J.
1996-01-01
The article describes purification of radium containing water in coal mines. Author concludes that water purification is relatively simple and effective way to decrease environmental pollution caused by coal mining. The amount of radium disposed with type A radium water has been significantly decreased. The results of investigations show that it will be soon possible to purify also type B radium water. Article compares the amounts of radium disposed by coal mines in 1990, 1995 and forecast for 2000
Predicting rock bursts in mines
Spall, H.
1979-01-01
In terms of lives lost, rock bursts in underground mines can be as hazardous as earthquakes on the surface. So it is not surprising that fo the last 40 years the U.S Bureau of Mines has been using seismic methods for detecting areas in underground mines where there is a high differential stress which could lead to structural instability of the rock mass being excavated.
Text Mining Applications and Theory
Berry, Michael W
2010-01-01
Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning
76 FR 63238 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines
2011-10-12
... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... Agency's proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in... proposed rule for Proximity Detection Systems on Continuous Mining Machines in Underground Coal Mines. Due...
30 CFR 77.1712 - Reopening mines; notification; inspection prior to mining.
2010-07-01
... to mining. 77.1712 Section 77.1712 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... prior to mining. Prior to reopening any surface coal mine after it has been abandoned or declared... an authorized representative of the Secretary before any mining operations in such mine are...
30 CFR 819.21 - Auger mining: Protection of underground mining.
2010-07-01
... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Auger mining: Protection of underground mining. 819.21 Section 819.21 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... STANDARDS-AUGER MINING § 819.21 Auger mining: Protection of underground mining. Auger holes shall not extend...
76 FR 70075 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines
2011-11-10
... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in Underground Coal... Detection Systems for Continuous Mining Machines in Underground Coal Mines. MSHA conducted hearings on...
Determination of sulfamethoxazole and trimethoprim mixtures by multivariate electronic spectroscopy
Cordeiro, Gilcélia A.; Peralta-Zamora, Patricio; Nagata, Noemi; Pontarollo, Roberto
2008-01-01
In this work a multivariate spectroscopic methodology is proposed for quantitative determination of sulfamethoxazole and trimethoprim in pharmaceutical associations. The multivariate model was developed by partial least-squares regression, using twenty synthetic mixtures and the spectral region between 190 and 350 nm. In the validation stage, which involved the analysis of five synthetic mixtures, prediction errors lower that 3% were observed. The predictive capacity of the multivariate model...
Web Mining and Social Networking
Xu, Guandong; Li, Lin
2011-01-01
This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal s
Sentiment Analysis and Opinion Mining
Liu, Bing
2012-01-01
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions
Data mining applications in healthcare.
Koh, Hian Chye; Tan, Gerald
2005-01-01
Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these mounds of data into useful information for decision making. This article explores data mining applications in healthcare. In particular, it discusses data mining and its applications within healthcare in major areas such as the evaluation of treatment effectiveness, management of healthcare, customer relationship management, and the detection of fraud and abuse. It also gives an illustrative example of a healthcare data mining application involving the identification of risk factors associated with the onset of diabetes. Finally, the article highlights the limitations of data mining and discusses some future directions.
Golden prospects for uranium mine
International Nuclear Information System (INIS)
Anon.
1980-01-01
Beisa Mines Ltd, a wholly-owned subsidiary of Union Corporation, looks a born winner. Although only due for completion in 1982 it can already boast several 'firsts' in the mining industry. It is, of course, the first mine in South Africa to be developed as a primary producer of uranium with gold as a by-product. Its No. 1 Ventilation Shaft is also the smallest diameter shaft in SA to use a rocker-arm shovel loader for rock removal. Moreover, Beisa will be the first mine to use the revolutionary carbon-in-pulp process on a large scale
Mine water treatment in Donbass
Energy Technology Data Exchange (ETDEWEB)
Azarenkov, P A; Anisimov, V M; Krol, V A
1980-10-01
About 2,000,000 m$SUP$3 of mine water are discharged by coal mines yearly to surface waters in the Donbass. Mine water in the region is rich in mineral salts and suspended matter (coal and rock particles). The DonUGI Institute developed a system of mine water treatment which permits the percentage of suspended matter to be reduced to 1.5 mg/l. The treated mine water can be used in fire fighting and in dust suppression systems in coal mines. A scheme of the water treatment system is shown. It consists of the following stages: reservoir of untreated mine water, chamber where mine water is mixed with reagents, primary sedimentation tanks, sand filters, and chlorination. Aluminium sulphate is used as a coagulation agent. To intensify coagulation polyacrylamide is added. Technical specifications of surface structures in which water treatment is carried out are discussed. Standardized mine water treatment systems with capacities of 600 m$SUP$3/h, with 900, 1200, 1500, 1800 and 2100 m$SUP$3/h capacities are used. (In Russian)
How to measure genetic heterogeneity
International Nuclear Information System (INIS)
Yamada, Ryo
2009-01-01
Genetic information of organisms is coded as a string of four letters, A, T, G and C, a sequence in macromolecules called deoxyribonucleic acid (DNA). DNA sequence offers blueprint of organisms and its heterogeneity determines identity and variation of species. The quantitation of this genetic heterogeneity is fundamental to understand biology. We compared previously-reported three measures, covariance matrix expression of list of loci (pair-wise r 2 ), the most popular index in genetics, and its multi-dimensional form, Ψ, and entropy-based index, ε. Thereafter we proposed two methods so that we could handle the diplotypic heterogeneity and quantitate the conditions where the number of DNA sequence samples is much smaller than the number of possible variants.
Heterogeneity in Preferences and Productivity
DEFF Research Database (Denmark)
Gørtz, Mette
This paper discusses the determinants of the retirement decision and the implications of retirement on economic well-being. The main contribution of the paper is to formulate the role of individual heterogeneity explicitly. We argue that individual heterogeneity in 1) productivity of market work...... choices of expenditure, household production and leisure for people in and around retirement. The unobserved individual heterogeneity factor is isolated by comparing cross-sectional evidence and panel data estimates of the effects of retirement on consumption and time allocation. Based on cross......-section data, we can identify a difference in consumption due to retirement status, but when the panel nature of the data is exploited, the effect of retirement on consumption is small and insignificant. Moreover, the analyses point at a large positive effect of retirement on household production. Our results...
Multivariate Bonferroni-type inequalities theory and applications
Chen, John
2014-01-01
Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade. The emergence of new bounding approaches pushes the conventional definitions of optimal inequalities and demands new insights into linear and Fréchet optimality. The book explores these advances in bounding techniques with corresponding innovative applications. It presents the method of linear programming for multivariate bounds, multivariate hybrid bounds, sub-Markovian bounds, and bounds using Hamil
Multivariate methods in nuclear waste remediation: Needs and applications
International Nuclear Information System (INIS)
Pulsipher, B.A.
1992-05-01
The United States Department of Energy (DOE) has developed a strategy for nuclear waste remediation and environmental restoration at several major sites across the country. Nuclear and hazardous wastes are found in underground storage tanks, containment drums, soils, and facilities. Due to the many possible contaminants and complexities of sampling and analysis, multivariate methods are directly applicable. However, effective application of multivariate methods will require greater ability to communicate methods and results to a non-statistician community. Moreover, more flexible multivariate methods may be required to accommodate inherent sampling and analysis limitations. This paper outlines multivariate applications in the context of select DOE environmental restoration activities and identifies several perceived needs
Multivariate statistics high-dimensional and large-sample approximations
Fujikoshi, Yasunori; Shimizu, Ryoichi
2010-01-01
A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic
Job Heterogeneity and Coordination Frictions
DEFF Research Database (Denmark)
Kennes, John; le Maire, Daniel
We develop a new directed search model of a frictional labor market with a continuum of heterogenous workers and firms. We estimate two versions of the model - auction and price posting - using Danish data on wages and productivities. Assuming heterogenous workers with no comparative advantage, we...... the job ladder, how the identification of assortative matching is fundamentally different in directed and undirected search models, how our theory accounts for business cycle facts related to inter-temporal changes in job offer distributions, and how our model could also be used to identify...