19,036 research outputs found

    BIOMONITORING OF ECOLOGICAL STATE OF THE ENVIRONMENT IN THE ZONE OF INFLUENCE OF THE “CHERVONOGRADSKA” MINE OF THE LVIV-VOLYN COALFIELD

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    Coal mining has a very negative impact on the environment and it requires monitoring studies to assess the degree of environmental pollution

    BIOMONITORING OF ECOLOGICAL STATE OF THE ENVIRONMENT IN THE ZONE OF INFLUENCE OF THE “CHERVONOGRADSKA” MINE OF THE LVIV-VOLYN COALFIELD

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    Coal mining has a very negative impact on the environment and it requires monitoring studies to assess the degree of environmental pollution

    Mining Complex Hydrobiological Data with Galois Lattices

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    We have used Galois lattices for mining hydrobiological data. These data are about macrophytes, that are macroscopic plants living in water bodies. These plants are characterized by several biological traits, that own several modalities. Our aim is to cluster the plants according to their common traits and modalities and to find out the relations between traits. Galois lattices are efficient methods for such an aim, but apply on binary data. In this article, we detail a few approaches we used to transform complex hydrobiological data into binary data and compare the first results obtained thanks to Galois lattices

    Whose Lands? Which Public? Trump\u27s National Monument Proclamations and the Shape of Public-Lands Law

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    President Trump issued a proclamation in December 2017 purporting to remove two million acres in southern Utah from national monument status, radically shrinking the Grand-Staircase Escalante National Monument and splitting the Bears Ears National Monument into two residual protected areas. Whether the President has the power to revise or revoke existing monuments under the Antiquities Act, which creates the national monument system, is a new question of law for a 112-year-old statute that has been used by Presidents from Theodore Roosevelt to Barack Obama to protect roughly fifteen million acres of federal land and hundreds of millions of marine acres. If President Trump’s shrinkages stand, they will be the largest removal of public lands from protected status in U.S. history, and will put the remaining national monuments on the chopping block. This article advances a novel theory showing that the President lacks the power to revise or revoke monuments. The Antiquities Act gives a power only to protect public lands, not to remove them from protection. Arguments developed so far in litigation and scholarship fail to recognize a general feature of public-lands law: It consistently denies the President the power unilaterally to remove lands from statutorily protected categories once they are placed within those categories. The Antiquities Act should be read to be consistent with this field-wide pattern. The article explicates the reasons for this pattern. Generally speaking, public-lands law has been very little theorized; but it needs a theory now. Public-lands law is a field defined by structured normative pluralism. It integrates a range of deeply conflicting public-lands purposes, from mining and drilling to wilderness preservation, across a range of statutes and agencies and acreage totaling nearly a third of the land area of the United States. The asymmetric premise against any Presidential power remove lands from protection is rooted in this structure, specifically the President’s obligation to preserve for Congress the option of protecting lands, and the dangers of hasty or corrupt Presidential action. The article traces these rationales across the history of statutory, executive, and judicial articulations of public-lands law and shows that they apply to the present Antiquities Act dispute. The article also highlights the political and cultural dimension of the dispute: a series of three-way conflicts among “public-lands populists” who seek increased use of and access to public lands (whose agenda the Trump Administration has incorporated into its economic and ethno-national populism), recreationists and environmentalists, and indigenous communities in the Bears Ears region. Conflicts among these groups amount to fights over collective identity--the nature of the “public” that public lands should serve. This dimension of the conflict does not fall outside the doctrinal analysis of the Antiquities Act. Rather, with a clear theoretical view of public-lands law, it is possible to see that these agendas are already integral to the field itself. They are central threads of its pluralism, and their competing claims fit within its structure. An account of the larger field of cultural conflict both enriches the theory of public-lands law and helps to show how the field should resolve the present fight

    Whose Lands? Which Public? Trump\u27s National Monument Proclamations and the Shape of Public-Lands Law

    Get PDF
    President Trump issued a proclamation in December 2017 purporting to remove two million acres in southern Utah from national monument status, radically shrinking the Grand-Staircase Escalante National Monument and splitting the Bears Ears National Monument into two residual protected areas. Whether the President has the power to revise or revoke existing monuments under the Antiquities Act, which creates the national monument system, is a new question of law for a 112-year-old statute that has been used by Presidents from Theodore Roosevelt to Barack Obama to protect roughly fifteen million acres of federal land and hundreds of millions of marine acres. If President Trump’s shrinkages stand, they will be the largest removal of public lands from protected status in U.S. history, and will put the remaining national monuments on the chopping block. This article advances a novel theory showing that the President lacks the power to revise or revoke monuments. The Antiquities Act gives a power only to protect public lands, not to remove them from protection. Arguments developed so far in litigation and scholarship fail to recognize a general feature of public-lands law: It consistently denies the President the power unilaterally to remove lands from statutorily protected categories once they are placed within those categories. The Antiquities Act should be read to be consistent with this field-wide pattern. The article explicates the reasons for this pattern. Generally speaking, public-lands law has been very little theorized; but it needs a theory now. Public-lands law is a field defined by structured normative pluralism. It integrates a range of deeply conflicting public-lands purposes, from mining and drilling to wilderness preservation, across a range of statutes and agencies and acreage totaling nearly a third of the land area of the United States. The asymmetric premise against any Presidential power remove lands from protection is rooted in this structure, specifically the President’s obligation to preserve for Congress the option of protecting lands, and the dangers of hasty or corrupt Presidential action. The article traces these rationales across the history of statutory, executive, and judicial articulations of public-lands law and shows that they apply to the present Antiquities Act dispute. The article also highlights the political and cultural dimension of the dispute: a series of three-way conflicts among “public-lands populists” who seek increased use of and access to public lands (whose agenda the Trump Administration has incorporated into its economic and ethno-national populism), recreationists and environmentalists, and indigenous communities in the Bears Ears region. Conflicts among these groups amount to fights over collective identity--the nature of the “public” that public lands should serve. This dimension of the conflict does not fall outside the doctrinal analysis of the Antiquities Act. Rather, with a clear theoretical view of public-lands law, it is possible to see that these agendas are already integral to the field itself. They are central threads of its pluralism, and their competing claims fit within its structure. An account of the larger field of cultural conflict both enriches the theory of public-lands law and helps to show how the field should resolve the present fight

    Ecomining as a pattern of integrated approach towards sustainable mining

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    This paper briefly describes the Educational Project “EcoMining: Development of Integrated PhD Program for Sustainable Mining & Environmental Activities” (2019–2022), which is being implemented between Dnipro University of Technology (DUT, Ukraine) and Technical University Bergakademie Freiberg (TU BAF, Germany) under support of German Academic Exchange Service (DAAD)

    Methods of Hierarchical Clustering

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    We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations that are available in R and other software environments. We look at hierarchical self-organizing maps, and mixture models. We review grid-based clustering, focusing on hierarchical density-based approaches. Finally we describe a recently developed very efficient (linear time) hierarchical clustering algorithm, which can also be viewed as a hierarchical grid-based algorithm.Comment: 21 pages, 2 figures, 1 table, 69 reference

    Compressive Mining: Fast and Optimal Data Mining in the Compressed Domain

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    Real-world data typically contain repeated and periodic patterns. This suggests that they can be effectively represented and compressed using only a few coefficients of an appropriate basis (e.g., Fourier, Wavelets, etc.). However, distance estimation when the data are represented using different sets of coefficients is still a largely unexplored area. This work studies the optimization problems related to obtaining the \emph{tightest} lower/upper bound on Euclidean distances when each data object is potentially compressed using a different set of orthonormal coefficients. Our technique leads to tighter distance estimates, which translates into more accurate search, learning and mining operations \textit{directly} in the compressed domain. We formulate the problem of estimating lower/upper distance bounds as an optimization problem. We establish the properties of optimal solutions, and leverage the theoretical analysis to develop a fast algorithm to obtain an \emph{exact} solution to the problem. The suggested solution provides the tightest estimation of the L2L_2-norm or the correlation. We show that typical data-analysis operations, such as k-NN search or k-Means clustering, can operate more accurately using the proposed compression and distance reconstruction technique. We compare it with many other prevalent compression and reconstruction techniques, including random projections and PCA-based techniques. We highlight a surprising result, namely that when the data are highly sparse in some basis, our technique may even outperform PCA-based compression. The contributions of this work are generic as our methodology is applicable to any sequential or high-dimensional data as well as to any orthogonal data transformation used for the underlying data compression scheme.Comment: 25 pages, 20 figures, accepted in VLD

    Energy Efficiency Prediction using Artificial Neural Network

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    Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%
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