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The Online Advertising Tax

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Book Series: CAMRI Policy Briefs ISBN: 9781911534860 9781911534860 9781911534877 9781911534884 Year: Pages: 33 DOI: 10.16997/book24 Language: English
Publisher: University of Westminster Press
Subject: Law --- Computer Science --- Philosophy --- Media and communication
Added to DOAB on : 2019-01-15 13:34:39
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"Google and Facebook currently control close to two-thirds of global advertising revenue. While dominating the online advertising market, these two companies have thus far avoided paying adequate taxes.

This CAMRI policy brief presents a new policy innovation, the online advertising tax. Considering the key role of user activity and user data for the value of Google and Facebook’s services, it explains how digital advertising companies’ revenues could be taxed based on the respective country in which targeted users are located.

The author reviews existing policy arguments and policy options and sets out practical steps to ensure that tax avoidance by online advertising companies is mitigated. Furthermore, he illustrates how tax revenues could be used to support public service internet platforms."

There is no Software, there are just Services

Authors: ---
Book Series: Digital Cultures ISBN: 9783957960559 9783957960566 Year: DOI: 10.14619/008 Language: English
Publisher: meson press
Subject: Media and communication
Added to DOAB on : 2017-04-23 15:18:20
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Is software dead? Services like Google, Dropbox, Adobe Creative Cloud, or Social Media apps are all-pervasive in our digital media landscape. This marks the (re)emergence of the service paradigm that challenges traditional business and license models as well as modes of media creation and use. The short essays in this edited collection discuss how services shift the notion of software, the cultural technique of programming, conditions of labor as well as the ecology and politics of data and how they influence dispositifs of knowledge.

The Online Advertising Tax as the Foundation of a Public Service Internet

Author:
Book Series: CAMRI Policy Briefs ISBN: 9781911534945 9781911534938 9781911534945 9781911534952 9781911534969 Year: Pages: 102 DOI: 10.16997/book23 Language: English
Publisher: University of Westminster Press
Subject: Philosophy --- Law --- Computer Science --- Political Science --- Media and communication
Added to DOAB on : 2019-01-15 13:34:39
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"Online advertising will soon form the largest share of global advertisement revenues. Google and Facebook netted profits of US $29 billion in 2016. While these two giants control more than 66% of all online advertising revenues complex legal company structures have minimised their tax liabilities. This extended policy report considers where they should be taxed and where the value of their activities is actually created. It argues that tax paid by those platforms should be levied in the country where platform users are located when they click on or view an advertisement. Furthermore, the report examines the practical steps needed to ensure transparent accounting of taxed transactions in order to avoid long term negative effects for media and democracy.

Considering counter-arguments the author makes the case for an online advertising tax alongside a public service Internet strategy that could support other viable platforms and counter the dangers of duopoly or oligopoly and the high risks of financial bubbles in a world where advertising is the Internet's dominant business model."

Voices from the South

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ISBN: 9781928396703 Year: Pages: 292 DOI: 10.4102/aosis.2018.BK79 Language: English
Publisher: AOSIS
Subject: Sociology --- Social Sciences --- Arts in general
Added to DOAB on : 2019-04-05 11:21:03
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This volume captures the status of digital humanities within the Arts in South Africa. The primary research methodology falls within the broader tradition of phenomenological hermeneutics, with a specific emphasis on visual hermeneutics. Some of the tools utilised as part of the visual hermeneutic methods are geographic information system (GIS) mapping, sensory ethnography and narrative pathways. Digital humanities is positioned here as the necessary engagement of the humanities with the pervasive digital culture of the 21st century. It is posited that the humanities and arts, in particular, have an essential role to play in unlocking meaning from scientific, technological and data-driven research. The critical engagement with digital humanities is foregrounded throughout the volume, as this crucial engagement works through images. 

Images (as understood within image studies) are not merely another form of text but always more than text. As such, this book is the first of its kind in the South African scholarly landscape, and notably also a first on the African continent. Its targeted audience include both scholars within the humanities, particularly in the arts and social sciences. Researchers pursuing the new field of digital humanities may also find the ideas presented in this book significant. Several of the chapters analyse the question of dealing with digital humanities through representations of the self as viewed from the Global South. However, it should be noted that self-representation is not the only area covered in this volume. The latter chapters of the book discuss innovative ways of implementing digital humanities strategies and methodologies for teaching and researching in South Africa.

Google Earth Engine Applications

Authors: ---
ISBN: 9783038978848 9783038978855 Year: Pages: 420 DOI: 10.3390/books978-3-03897-885-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2019-04-25 16:37:17
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In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Keywords

Google Earth Engine --- NDVI --- vegetation index --- Landsat --- remote sensing --- phenology --- surface reflectance --- cropland mapping --- cropland areas --- 30-m --- Landsat-8 --- Sentinel-2 --- Random Forest --- Support Vector Machines --- segmentation --- RHSeg --- Google Earth Engine --- Africa --- remote sensing --- semi-arid --- ecosystem assessment --- land use change --- image classification --- seasonal vegetation --- carbon cycle --- Google Earth Engine --- crop yield --- gross primary productivity (GPP) --- data fusion --- Landsat --- MODIS --- MODIS --- Random Forest --- pasture mapping --- Brazilian pasturelands dynamics --- Google Earth Engine --- crop classification --- multi-classifier --- cloud computing --- time series --- high spatial resolution --- BACI --- Enhanced Vegetation Index --- Google Earth Engine --- cloud-based geo-processing --- satellite-derived bathymetry --- image composition --- pseudo-invariant features --- sun glint correction --- empirical --- spatial error --- Google Earth Engine --- low cost in situ --- Sentinel-2 --- Mediterranean --- burn severity --- change detection --- Landsat --- dNBR --- RdNBR --- RBR --- composite burn index (CBI) --- MTBS --- lower mekong basin --- landsat collection --- suspended sediment concentration --- online application --- google earth engine --- Landsat --- Google Earth Engine --- protected area --- forest and land use mapping --- machine learning classification --- China --- temporal compositing --- image time series --- multitemporal analysis --- change detection --- cloud masking --- Landsat-8 --- Google Earth Engine (GEE) --- Google Earth Engine --- LAI --- FVC --- FAPAR --- CWC --- plant traits --- random forests --- PROSAIL --- small-scale mining --- industrial mining --- google engine --- image classification --- land-use cover change --- seagrass --- habitat mapping --- image composition --- machine learning --- support vector machines --- Google Earth Engine --- Sentinel-2 --- Aegean --- Ionian --- global scale --- soil moisture --- Soil Moisture Ocean Salinity --- Soil Moisture Active Passive --- Google Earth Engine --- drought --- cloud computing --- remote sensing --- snow hydrology --- water resources --- Google Earth Engine --- user assessment --- MODIS --- snow cover --- flood --- disaster prevention --- emergency response --- decision making --- Google Earth Engine --- land cover --- deforestation --- Brazilian Amazon --- Bayesian statistics --- BULC-U --- Mato Grosso --- spatial resolution --- Landsat --- GlobCover --- SDG --- surface urban heat island --- Geo Big Data --- Google Earth Engine --- global monitoring service --- Google Earth Engine --- web portal --- satellite imagery --- trends --- earth observation --- wetland --- Google Earth Engine --- Sentinel-1 --- Sentinel-2 --- random forest --- cloud computing --- geo-big data --- cloud computing --- big data analytics --- long term monitoring --- data archival --- early warning systems

Tech Giants, Artificial Intelligence and the Future of Journalism

Author:
ISBN: 9781138499973 9781351013758 Year: Language: English
Publisher: Routledge Grant: Knowledge Unlatched - 102683
Subject: Media and communication
Added to DOAB on : 2019-02-26 11:21:02
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This book examines the impact of the "Big Five" technology companies – Apple, Alphabet/Google, Amazon, Facebook and Microsoft – on journalism and the media industries. It looks at the current role of algorithms and artificial intelligence in curating how we consume media and their increasing influence on the production of the news.Exploring the changes that the technology industry and automation have made in the past decade to the production, distribution and consumption of news globally, the book considers what happens to journalism once it is produced and enters the media ecosystems of the internet tech giants – and the impact of social media and AI on such things as fake news in the post-truth age.

Emerging Technology Applications to Promote Physical Activity and Health

Authors: ---
ISBN: 9783038977087 Year: Pages: 176 DOI: 10.3390/books978-3-03897-709-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Sociology --- Social Sciences
Added to DOAB on : 2019-04-05 10:34:31
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As technology becomes an ever-more prevalent part of everyday life, and population-based physical activity programs seek new ways to increase life-long engagement with physical activity, these two ideas have become increasingly linked. This Special Issue attempts to offer a thorough and critical examination of emerging technologies in physical activity and health promotion, considering technological interventions in different contexts (communities, clinics, schools, homes, etc.) among various populations, exploring the challenges of integrating technology into physical activity promotion, and offering solutions for its implementation. This Special Issue aims to take a broadly positive stance toward interactive technology initiatives and, while discussing some negative implications of an increased use of technology, offers practical recommendations for promoting physical activity through various emerging technologies, including, but not limited to: Active video games (exergaming); social media; mobile device apps; health wearables; mobile games, augmented reality games, global positioning and geographic information systems; and virtual reality. Offering a logical and clear critique of emerging technologies in physical activity and health promotion, this Special Issue will provide useful suggestions and practical implications for researchers, practitioners, and educators in the fields of public health, kinesiology, physical activity and health, and healthcare.

Keywords

anxiety --- depression --- exercise --- mental health --- virtual reality --- senior citizens --- perceived environmental factor --- recreational physical activity --- screen based sedentary behavior --- pedometers --- accelerometers --- measurement --- physical activity levels --- active video games --- motor activity --- intelligence quotient --- young children --- physical activity --- quality of life --- social cognitive theory --- wearable technology --- real-time physical activity --- wearable technology --- fitness --- Fitbits --- breast cancer --- mammogram --- mobile phone-based health intervention --- mHealth --- app --- health navigator --- Korean American immigrant women --- Autism --- autism spectrum disorder --- augmented reality --- technology --- Google Glass --- social communication --- safety --- smartglasses --- digital health --- Amazon --- Amazon Web Services --- Google --- sedentary behaviour --- air quality --- socio-ecological model --- wrist-worn activity tracker --- active video games --- cardiorespiratory fitness --- locomotor skills --- motor skill competence --- musculoskeletal fitness --- object control skills --- active video game --- accelerometry --- physical activity assessment --- epoch --- placement site --- heart rate --- preoperative anxiety --- virtual reality game --- preoperative experience --- active video game --- light physical activity --- moderate-to-vigorous physical activity --- sedentary behavior --- sex difference --- active video gaming --- serious games --- physical activity --- physical exercise --- sedentary behavior --- narrative review

Flood Forecasting Using Machine Learning Methods

Authors: --- ---
ISBN: 9783038975489 Year: Pages: 376 DOI: 10.3390/books978-3-03897-549-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-03-08 11:42:05
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This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Water

Keywords

data scarce basins --- runoff series --- data forward prediction --- ensemble empirical mode decomposition (EEMD) --- stopping criteria --- method of tracking energy differences (MTED) --- deep learning --- convolutional neural networks --- superpixel --- urban water bodies --- high-resolution remote-sensing images --- monthly streamflow forecasting --- artificial neural network --- ensemble technique --- phase space reconstruction --- empirical wavelet transform --- hybrid neural network --- flood forecasting --- self-organizing map --- bat algorithm --- particle swarm optimization --- flood routing --- Muskingum model --- machine learning methods --- St. Venant equations --- rating curve method --- nonlinear Muskingum model --- hydrograph predictions --- flood routing --- Muskingum model --- hydrologic models --- improved bat algorithm --- Wilson flood --- Karahan flood --- flood susceptibility modeling --- ANFIS --- cultural algorithm --- bees algorithm --- invasive weed optimization --- Haraz watershed --- ANN-based models --- flood inundation map --- self-organizing map (SOM) --- recurrent nonlinear autoregressive with exogenous inputs (RNARX) --- ensemble technique --- artificial neural networks --- uncertainty --- streamflow predictions --- sensitivity --- flood forecasting --- extreme learning machine (ELM) --- backtracking search optimization algorithm (BSA) --- the upper Yangtze River --- deep learning --- LSTM network --- water level forecast --- the Three Gorges Dam --- Dongting Lake --- Muskingum model --- wolf pack algorithm --- parameters --- optimization --- flood routing --- flash-flood --- precipitation-runoff --- forecasting --- lag analysis --- random forest --- machine learning --- flood prediction --- flood forecasting --- hydrologic model --- rainfall–runoff, hybrid & --- ensemble machine learning --- artificial neural network --- support vector machine --- natural hazards & --- disasters --- adaptive neuro-fuzzy inference system (ANFIS) --- decision tree --- survey --- classification and regression trees (CART), data science --- big data --- artificial intelligence --- soft computing --- extreme event management --- time series prediction --- LSTM --- rainfall-runoff --- flood events --- flood forecasting --- data assimilation --- particle filter algorithm --- micro-model --- Lower Yellow River --- ANN --- hydrometeorology --- flood forecasting --- real-time --- postprocessing --- machine learning --- early flood warning systems --- hydroinformatics --- database --- flood forecast --- Google Maps

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