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Abbott's Gambit: The 2013 Australian Federal Election

Authors: --- ---
ISBN: 9781925022100 Year: Pages: 436 DOI: 10.26530/OAPEN_515965 Language: English
Publisher: ANU Press
Subject: Political Science
Added to DOAB on : 2015-02-01 11:01:11
License: ANU Press

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This book provides a truly comprehensive analysis of the 2013 federal election in Australia, which brought the conservative Abbott government to power, consigned the fractious Labor Party to the Opposition benches and ended the ‘hung parliament’ experiment of 2010–13 in which the Greens and three independents lent their support to form a minority Labor government.

Keywords

australia --- politics --- voting

Many Faces of Strategic Voting

Authors: --- ---
ISBN: 9780472131020 9780472901128 9780472901128 Year: DOI: 10.3998/mpub.9946117 Language: English
Publisher: University of Michigan Press Grant: Knowledge Unlatched - 102039
Added to DOAB on : 2019-02-05 09:51:01
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Strategic voting is classically defined as “voting for one’s second preferred option to prevent one’s least preferred option from winning when one’s first preference has no chance.” Voters want their votes to be effective, and casting a ballot that will have no influence on an election is undesirable—therefore, some voters cast a strategic ballot when they decide it is useful.This edited volume includes case studies of strategic voting behavior in Israel, Germany, Japan, Belgium, Spain, Switzerland, Canada, and the UK, and provides a conceptual framework for understanding strategic voting behavior in all types of electoral systems.

Electronic Democracy

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ISBN: 9783847400189 9783866495463 Year: DOI: 10.3224/84740018 Language: English
Publisher: Verlag Barbara Budrich Grant: Knowledge Unlatched - 102281
Subject: Political Science
Added to DOAB on : 2019-03-07 11:21:02
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The timely book takes stock of the state of the art and future of electronic democracy, exploring the history and potential of e-democracy in global perspective. Analysing the digital divide, the role of the internet as a tool for political mobilisation, internet Voting and Voting Advice Applications, and other phenomena, this volume critically engages with the hope for more transparency and political participation through e-democracy.

Debating European Citizenship

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Book Series: IMISCOE Research Series ISSN: 2364-4087/2364-4095 ISBN: 9783319899046/9783319899053 Year: Pages: 331 DOI: https://doi.org/10.1007/978-3-319-89905-3 Language: English
Publisher: Springer
Subject: Political Science
Added to DOAB on : 2019-07-24 12:39:28
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This open access book raises crucial questions about the citizenship of the European Union. Is it a new citizenship beyond the nation-state although it is derived from Member State nationality? Who should get it? What rights and duties does it entail? Should EU citizens living in other Member States be able to vote there in national elections? If there are tensions between free movement and social rights, which should take priority? And should the European Court of Justice determine what European citizenship is about or the legislative institutions of the EU or national parliaments? This book collects a wide range of answers to these questions from legal scholars, political scientists, and political practitioners. It is structured as a series of three conversations in which authors respond to each other. This exchange of arguments provides unique depth to the debate.

Migration and Citizenship

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Book Series: IMISCoe Reports ISBN: 9789053568880 Year: Pages: 128 DOI: 10.5117/9789053568880 Language: Undetermined
Publisher: Amsterdam University Press
Subject: Political Science --- Sociology --- History --- Migration
Added to DOAB on : 2011-11-04 00:00:00
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Citizenship is frequently invoked both as an instrument and goal of immigrant integration. Yet, in migration contexts, citizenship also marks a distinction between members and outsiders based on their different relations to particular states. A migration perspective highlights the boundaries of citizenship and political control over entry and exit as well as the fact that foreign residents remain in most countries deprived of core rights of political participation. This book summarizes current theories and empirical research on the legal status and political participation of migrants in European democracies.

Public Choice

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ISBN: 9783039212712 / 9783039212729 Year: Pages: 148 DOI: 10.3390/books978-3-03921-272-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Economics
Added to DOAB on : 2019-12-09 11:49:15
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Interest in politics and the political process—topics that economists consider to be the purview of the sub-field of study known as public choice—appears to be as high as ever. This Special Issue aims to provide a collection of high-quality studies covering many of the varied topics traditionally investigated in the growing field of public choice economics. These include expressive and instrumental voting, checks and balances in the enforcement of rules, electoral disproportionality, foreign aid and political freedom, voting cycles, (in)stability of political ideology, federal spending on environmental goods, pork-barrel and general appropriations spending, politics and taxpayer funding for professional sports arenas, and political scandal and “friends-and-neighbors” voting in general elections. In bringing these topics together in one place, this Special Issue offers a mix of conceptual/formal and empirical studies in public choice economics.

Voter en Grèce, à Rome et en Gaule : Pratiques, lieux et finalités

Authors: --- --- --- --- et al.
ISBN: 9782356681782 DOI: 10.4000/books.momeditions.6411 Language: French
Publisher: MOM Éditions
Subject: History
Added to DOAB on : 2019-12-06 13:15:38
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Dans ses aspects aussi bien théoriques que matériels, le système du vote dans les mondes grec et romain a depuis longtemps été exploré au sein d’études plus générales sur les institutions ou les différents types de régimes politiques. Il n’a cependant jamais fait l’objet de publications réunissant à la fois les témoignages textuels et les résultats des fouilles archéologiques, dans l’optique d’une compréhension globale de cette pratique. De ce constat est né le projet d’une synthèse portant sur les modalités, les lieux et les finalités du vote en Grèce, à Rome et en Gaule, dans une perspective comparatiste. Menée dans le cadre d’un programme de recherche interdisciplinaire soutenu par l’université Lumière Lyon 2 et la Maison de l’Orient et de la Méditerranée, cette recherche a suscité, selon les régions et les périodes concernées, des questionnements spécifiques mais elle a aussi fait émerger des points de convergence. La collaboration de chercheurs issus de plusieurs disciplines – l’histoire, la philologie et l’archéologie – a permis de cerner la pratique du vote à travers ses implications politiques, ses modalités procédurales et la place qui lui a été réservée dans l’espace civique par les différentes sociétés antiques qui l’ont mise en œuvre. Le présent ouvrage, qui présente une synthèse sur chacune des aires géographiques étudiées et rassemble vingt et une contributions issues de séminaires ou de journées d’études qui se sont tenus à Lyon, à la Maison de l’Orient et de la Méditerranée, de la fin de l’année 2012 au printemps 2014, propose une approche inédite de l’acte de vote dans l’Antiquité.

From the Renaissance to the Modern World

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ISBN: 9783906980362 9783906980355 Year: Pages: VIII, 128 DOI: 10.3390/books978-3-906980-35-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Added to DOAB on : 2014-07-01 11:06:23
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On November 11 and 12, 2011, a symposium held at the University of North Carolina in Chapel Hill honored John M. Headley, Emeritus Professor of History. The organizers, Professor MelissaBullard—Headley’s colleague in the department of history at that university—along with ProfessorsPaul Grendler (University of Toronto) and James Weiss (Boston College), as well as Nancy GraySchoonmaker, coordinator of the Program in Medieval and Early Modern Studies—assembled presenters, respondents, and dozens of other participants from Western Europe and North America to celebrate the career of their prolific, versatile, and influential colleague whose publications challenged and often changed the ways scholars think about Martin Luther, Thomas More, the Habsburg empire,early modern Catholicism, globalization, and multiculturalism.This special issue contains the major papers delivered at the symposium, revised to take account of colleagues’ suggestions at the conference and thereafter. John O’Malley studies the censorship ofsacred art with special reference to Michelangelo’s famed “Last Judgment” and the Council of Trent.John Martin sifts Montaigne’s skepticism about contemporaneous strategies for self-disclosure andself-discipline. Stressing the significance of grammar, Constantin Fasolt helps us recapture theRenaissance’s and the early modern religious reformations’ disagreements with antiquity. RonaldWitt’s reappraisal of humanist historiography probes Petrarch’s perspectives on ancient Rome. JohnMcManamon includes tales of theft and market manipulation in his study of the early moderncollection and circulation of books and manuscripts, the commodification of study. To “nuance” John Headley’s conclusions about “the Europeanization of the world,” Jerry Bentley repossesses the influence of other than European societies on several European theorists of human rights. Kate Lowe’s remarks on the reconstruction of race in the Renaissance explores the effects of a critical mistranslation on what being black was taken to mean by Europeans. David Gilmartin introduces readers to the shape of democracy in nineteenth- and twentieth-century India, as well as to the understandings of popular sovereignty that affected elections, suggesting strides that scholars might take “toward a worldwide history of voting”.The remarkable range of these contributions comes close to reflecting the range of ProfessorHeadley’s interests and achievements, which James M. Weiss maps in his tribute, identifying“unifying themes” in Headley’s work.

Learning to Understand Remote Sensing Images

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ISBN: 9783038976844 / 9783038976851 Year: Volume: 1 Pages: 426 DOI: 10.3390/books978-3-03897-685-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
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With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Learning to Understand Remote Sensing Images

Author:
ISBN: 9783038976981 / 9783038976998 Year: Volume: 2 Pages: 376 DOI: 10.3390/books978-3-03897-699-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

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