A Human-centric Perspective on Digital Consenting: The Case of GAFAM

According to different legal frameworks such as the European General Data Protection Regulation (GDPR), an end-user's consent constitutes one of the well-known legal bases for personal data processing. However, research has indicated that the majority of end-users have difficulty in understanding what they are consenting to in the digital world. Moreover, it has been demonstrated that marginalized people are confronted with even more difficulties when dealing with their own digital privacy. In this research, we use an enactivist perspective from cognitive science to develop a basic human-centric framework for digital consenting. We argue that the action of consenting is a sociocognitive action and includes cognitive, collective, and contextual aspects. Based on the developed theoretical framework, we present our qualitative evaluation of the consent-obtaining mechanisms implemented and used by the five big tech companies, i.e. Google, Amazon, Facebook, Apple, and Microsoft (GAFAM). The evaluation shows that these companies have failed in their efforts to empower end-users by considering the human-centric aspects of the action of consenting. We use this approach to argue that their consent-obtaining mechanisms violate principles of fairness, accountability and transparency. We then suggest that our approach may raise doubts about the lawfulness of the obtained consent—particularly considering the basic requirements of lawful consent within the legal framework of the GDPR

Research and development of an airborne multispectral scanner to measure fire, terrestrial and atmospheric characteristics (50 channel)

The AB184 Spectrometer and the AC12206 High Temperature Blackbody Reference Source Assembly were both successfully developed during this contract effort. The newly developed hardware provide a means of quantifying the spectral characteristics of high temperature fire scenes

Optimum Currency Area Indices - How Close is the Czech Republic to the Eurozone?

In this paper we provide a survey of the optimum currency area theory, estimate the degree of the explanatory power of the optimum currency area criteria, and also calculate the optimum currency area index in the case of the Czech Republic. The results indicate that the traditional optimum currency area criteria to certain extent explain exchange rate variability. Our results may be interpreted as an attempt to assess the benefit-cost ratio of implementing a common currency for a pair of countries. Our results also suggest that from the point of view of the optimum currency area theory the costs of adopting the euro for the Czech Republic may be relatively low, at least in comparison with other EMU member countries. We conclude that if the European Monetary Union is sustainable, the accession of the Czech Republic should not change it.Convergence, EU/eurozone, exchange rate, optimum currency area theory, transition.

ERM II Membership - the View of the Accession Countries

With EU accession looming, a new chapter has been opened in the debate about the candidate countries' exchange rate strategies. A heated discussion has arisen in relation to ERM2 membership. The experience of the present eurozone members with ERM/ERM2 membership shows that none of them faced a significant challenge in the two-year 'evaluation' period in terms of the exchange rate stability convergence criterion. This could also be attributable to the stability policies prescribed by the Maastricht Treaty. However, for catching-up countries in the run-up to joining the eurozone, given the existing functioning of the mechanism, the ERM2 appears be of little help for ensuring exchange rate stability. The mechanism should be viewed rather as a tool for 'persuading' the markets of the appropriateness of the euro-locking rate. Since the Maastricht rules do not allow downward adjustment of the central parity within the ERM2 for two years before introduction of the euro, the authorities should be familiar with the preferred real exchange rate path prior to entering the mechanism. We conclude that countries could face large costs if they fail to do so.EU/eurozone, convergence, exchange rate, transition.

Continuous Action Recognition Based on Sequence Alignment

Continuous action recognition is more challenging than isolated recognition because classification and segmentation must be simultaneously carried out. We build on the well known dynamic time warping (DTW) framework and devise a novel visual alignment technique, namely dynamic frame warping (DFW), which performs isolated recognition based on per-frame representation of videos, and on aligning a test sequence with a model sequence. Moreover, we propose two extensions which enable to perform recognition concomitant with segmentation, namely one-pass DFW and two-pass DFW. These two methods have their roots in the domain of continuous recognition of speech and, to the best of our knowledge, their extension to continuous visual action recognition has been overlooked. We test and illustrate the proposed techniques with a recently released dataset (RAVEL) and with two public-domain datasets widely used in action recognition (Hollywood-1 and Hollywood-2). We also compare the performances of the proposed isolated and continuous recognition algorithms with several recently published methods

Moving Metadata and Medicine: Migrating a Nursing History Photograph Collection to Digital Commons

The Center for Nursing History of Northeastern Pennsylvania (CNH) at Misericordia University documents the history of nursing and the many nursing schools in the Keystone State\u27s Wyoming Valley. In 2015, the Center received a grant to digitize and host its photograph collection to establish a stable digital environment for this regionally significant collection. This presentation will share some challenges, successes, and lessons learned during the migration of over 500 digital objects from ArtStor Public Collections to the Library\u27s institutional repository on Digital Commons