Class-based Rough Approximation with Dominance Principle

Dominance-based Rough Set Approach (DRSA), as the extension of Pawlak's Rough Set theory, is effective and fundamentally important in Multiple Criteria Decision Analysis (MCDA). In previous DRSA models, the definitions of the upper and lower approximations are preserving the class unions rather than the singleton class. In this paper, we propose a new Class-based Rough Approximation with respect to a series of previous DRSA models, including Classical DRSA model, VC-DRSA model and VP-DRSA model. In addition, the new class-based reducts are investigated.Comment: Submitted to IEEE-GrC201

Research on Rough Set Model Based on Golden Ratio

AbstractHow to make decision with pre-defined preference-ordered criteria also depends on the environment of the problem. Dominance rough set model is suitable for preference analysis and probabilistic rough set introduces probabilistic approaches to rough sets. In this paper, new dominance rough set rough set models are given by taking golden ratio into account. Also, we present steps to make decision using new dominance rough set models

Representativeness of the European Social Partner Organisations: Textiles and Clothing Sector

This study provides information designed to aid sectoral social dialogue in the textile and clothing sector. The study is divided into three parts: a summary of the sector’s economic background; an analysis of the social partner organisations in all the EU Member States, including their membership, role in collective bargaining, social dialogue and public policy, and national and European affiliations; and an analysis of relevant European organisations, particularly their membership composition and capacity to negotiate. The aim of EIRO studies on representativeness is to identify the relevant national and supranational social partner organisations in the field of industrial relations in selected sectors. The impetus for these studies comes from the European Commission’s desire to recognise the representative social partner organisations to be consulted under the provisions of the Treaty on the Functioning of the European Union (TFEU)

Evolutionary and Functional Relationships in the Truncated Hemoglobin Family

Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends.Fil: Bustamante, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; ArgentinaFil: Radusky, Leandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Biológica; ArgentinaFil: Boechi, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; ArgentinaFil: Estrin, Dario Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Inorgánica, Analítica y Química Física; ArgentinaFil: Ten Have, Arjen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; ArgentinaFil: Marti, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Cálculo; Argentin

A rough set-based association rule approach implemented on exploring beverages product spectrum

[[abstract]]When items are classified according to whether they have more or less of a characteristic, the scale used is referred to as an ordinal scale. The main characteristic of the ordinal scale is that the categories have a logical or ordered relationship to each other. Thus, the ordinal scale data processing is very common in marketing, satisfaction and attitudinal research. This study proposes a new data mining method, using a rough set-based association rule, to analyze ordinal scale data, which has the ability to handle uncertainty in the data classification/sorting process. The induction of rough-set rules is presented as method of dealing with data uncertainty, while creating predictive if—then rules that generalize data values, for the beverage market in Taiwan. Empirical evaluation reveals that the proposed Rough Set Associational Rule (RSAR), combined with rough set theory, is superior to existing methods of data classification and can more effectively address the problems associated with ordinal scale data, for exploration of a beverage product spectrum.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

CML: Evolution and design.

A retrospective view of the design and evolution of Chemical Markup Language (CML) is presented by its original authors.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Sustainable Commodity Use

This open access book examines the governance and legal landscape of the global commodity sector. For that purpose, the author conceptualises both Global Commodity Governance (GCG) as well as Transnational Commodity Law (TCL). He defines the key terms of Global Commodity Governance, delineates the underlying legal framework of Transnational Commodity Law, and assesses the effectiveness of Transnational Commodity Law in fostering a functional commodity sector. “Sustainable Commodity Use” is based on a comprehensive analysis of over 250 international agreements, standards, and guiding documents. The author distils the main findings into a conceptualisation of Transnational Commodity Law and provides the reader with a succinct overview of its normative configurations as well as regulatory gaps. Moreover, he elaborates a taxonomy of International Commodity Agreements. In addition, an outline of the normative substance of Transnational Commodity Law features in an appendix to the main text. The author concludes by making concrete suggestions on how rules regulating commodity activities de lege ferenda could and should be designed to improve the effectiveness of law regulating transnational commodity activity. In doing so, he demonstrates the application of the sustainable use principle as the overall objective and purpose of Transnational Commodity Law and discusses International Commodity Agreements as future regulatory instruments. This book may assist lawmakers, practitioners, civil society advocates, and academics worldwide in developing a legal framework for sustainable global commodity activity