Safe Harbour or into the storm? EU-US data transfers after the Schrems judgment. Liberty and security in Europe No. 85/November 2015

In its recent Schrems judgment the Luxembourg Court annulled Commission Decision 2000/520 according to which US data protection rules are sufficient to satisfy EU privacy rules regarding EU-US transfers of personal data, otherwise known as the ‘Safe Harbour’ framework. What does this judgment mean and what are its main implications for EU-US data transfers? In this paper the authors find that this landmark judgment sends a strong message to EU and US policy-makers about the need to ensure clear rules governing data transfers, so that people whose personal data is transferred to third countries have sufficient legal guarantees. Without such rules there is legal uncertainty and mistrust. Any future arrangement for the transatlantic transfer of data will therefore need to be firmly anchored in a framework of protection commensurate to the EU Charter of Fundamental Rights and the EU data protection architecture.

Tecnologie per l’analisi in tempo reale di Big Data: prestazioni a confronto

Lo scopo di questo l'elaborato è l'analisi,lo studio e il confronto delle tecnologie per l'analisi in tempo reale di Big Data: Apache Spark Streaming, Apache Storm e Apache Flink. Per eseguire un adeguato confronto si è deciso di realizzare un sistema di rilevamento e riconoscimento facciale all’interno di un video, in maniera da poter parallelizzare le elaborazioni necessarie sfruttando le potenzialità di ogni architettura. Dopo aver realizzato dei prototipi realistici, uno per ogni architettura, si è passati alla fase di testing per misurarne le prestazioni. Attraverso l’impiego di cluster appositamente realizzati in ambiente locale e cloud, sono state misurare le caratteristiche che rappresentavano, meglio di altre, le differenze tra le architetture, cercando di dimostrarne quantitativamente l’efficacia degli algoritmi utilizzati e l’efficienza delle stesse. Si è scelto quindi il massimo input rate sostenibile e la latenza misurate al variare del numero di nodi. In questo modo era possibile osservare la scalabilità di architettura, per analizzarne l’andamento e verificare fino a che limite si potesse giungere per mantenere un compromesso accettabile tra il numero di nodi e l’input rate sostenibile. Gli esperimenti effettuati hanno mostrato che, all’aumentare del numero di worker le prestazioni del sistema migliorano, rendendo i sistemi studiati adatti all’utilizzo su larga scala. Inoltre sono state rilevate sostanziali differenze tra i vari framework, riportando pro e contro di ognuno, cercando di evidenziarne i più idonei al caso di studio.

Rock-magnetic data of ODP Site 105-645 (Appendix)

We present the rock-magnetic stratigraphy for Ocean Drilling Program (ODP) Leg 105, Site 645 (Baffin Bay). Variations in magnetic mineral concentration (X) and particle size (XAKM/X) are used to correlate advanced piston corer (APC) cores from several holes at Site 645. Downsite variations in rock-magnetic parameters and carbonate content are placed within the framework of inferred changes in sedimentation. These results suggest an initiation of Northern Hemisphere ice rafting in Baffin Bay in the early-late Pliocene (approximately 3.4 Ma).

A World that Counts: Mobilising the Data Revolution for Sustainable Development

In September 2015, the UN Member States are expected to commit to an ambitious new set of global goals for a new era of sustainable development. Achieving them will require an unprecedented joint effort on the part of governments at every level, civil society and the private sector, and millions of individual choices and actions. To be realised, the SDGs will require a monitoring and accountability framework and a plan for implementation. A commitment to realise the opportunities of the data revolution should be firmly embedded into the action plan for the SDGs, to support those countries most in need of resources, and to set the world on track for an unprecedented push towards a new world of data for change.

Reconstructing Past Climate by Using Proxy Data and a Linear Climate Model

Thesis (Master's)--University of Washington, 2016-06

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

A Novel Framework for Real-time Traffic Flow Parameter Estimation from Aerial Videos

Thesis (Master's)--University of Washington, 2016-06

Submodular Optimization and Data Processing

Thesis (Ph.D.)--University of Washington, 2016-06

Centromere identification and inactivation on a neo-Y chromosome fusion in threespine stickleback fish (Gasterosteus aculeatus)

Thesis (Ph.D.)--University of Washington, 2016-05

Thinking Local About Self-Driving Cars: a Local Framework for Autonomous Vehicle Development in the United States

Thesis (Master's)--University of Washington, 2016-06

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Fuzzy logic in web data mining for website assessment

This paper proposes a novel application of fuzzy logic to web data mining for two basic problems of a website: popularity and satisfaction. Popularity means that people will visit the website while satisfaction refers to the usefulness of the site. We will illustrate that the popularity of a website is a fuzzy logic problem. It is an important characteristic of a website in order to survive in Internet commerce. The satisfaction of a website is also a fuzzy logic problem that represents the degree of success in the application of information technology to the business. We propose a framework of fuzzy logic for the representation of these two problems based on web data mining techniques to fuzzify the attributes of a website.

Data-driven fuzzy analysis in quantitative mineral resource assessment

The integration of geo-information from multiple sources and of diverse nature in developing mineral favourability indexes (MFIs) is a well-known problem in mineral exploration and mineral resource assessment. Fuzzy set theory provides a convenient framework to combine and analyse qualitative and quantitative data independently of their source or characteristics. A novel, data-driven formulation for calculating MFIs based on fuzzy analysis is developed in this paper. Different geo-variables are considered fuzzy sets and their appropriate membership functions are defined and modelled. A new weighted average-type aggregation operator is then introduced to generate a new fuzzy set representing mineral favourability. The membership grades of the new fuzzy set are considered as the MFI. The weights for the aggregation operation combine the individual membership functions of the geo-variables, and are derived using information from training areas and L, regression. The technique is demonstrated in a case study of skarn tin deposits and is used to integrate geological, geochemical and magnetic data. The study area covers a total of 22.5 km(2) and is divided into 349 cells, which include nine control cells. Nine geo-variables are considered in this study. Depending on the nature of the various geo-variables, four different types of membership functions are used to model the fuzzy membership of the geo-variables involved. (C) 2002 Elsevier Science Ltd. All rights reserved.