17 resultados para Data breach notification law

em CentAUR: Central Archive University of Reading - UK


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This article analyses the results of an empirical study on the 200 most popular UK-based websites in various sectors of e-commerce services. The study provides empirical evidence on unlawful processing of personal data. It comprises a survey on the methods used to seek and obtain consent to process personal data for direct marketing and advertisement, and a test on the frequency of unsolicited commercial emails (UCE) received by customers as a consequence of their registration and submission of personal information to a website. Part One of the article presents a conceptual and normative account of data protection, with a discussion of the ethical values on which EU data protection law is grounded and an outline of the elements that must be in place to seek and obtain valid consent to process personal data. Part Two discusses the outcomes of the empirical study, which unveils a significant departure between EU legal theory and practice in data protection. Although a wide majority of the websites in the sample (69%) has in place a system to ask separate consent for engaging in marketing activities, it is only 16.2% of them that obtain a consent which is valid under the standards set by EU law. The test with UCE shows that only one out of three websites (30.5%) respects the will of the data subject not to receive commercial communications. It also shows that, when submitting personal data in online transactions, there is a high probability (50%) of incurring in a website that will ignore the refusal of consent and will send UCE. The article concludes that there is severe lack of compliance of UK online service providers with essential requirements of data protection law. In this respect, it suggests that there is inappropriate standard of implementation, information and supervision by the UK authorities, especially in light of the clarifications provided at EU level.

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The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.

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The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.

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The rapid expansion of the TMT sector in the late 1990s and more recent growing regulatory and corporate focus on business continuity and security have raised the profile of data centres. Data centres offer a unique blend of occupational, physical and technological characteristics compared to conventional real estate assets. Limited trading and heterogeneity of data centres also causes higher levels of appraisal uncertainty. In practice, the application of conventional discounted cash flow approaches requires information about a wide range of inputs that is difficult to derive from limited market signals or estimate analytically. This paper outlines an approach that uses pricing signals from similar traded cash flows is proposed. Based upon ‘the law of one price’, the method draws upon the premise that two identical future cash flows must have the same value now. Given the difficulties of estimating exit values, an alternative is that the expected cash flows of data centre are analysed over the life cycle of the building, with corporate bond yields used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds. Although there are rarely assets that have identical cash flows and some approximation is necessary, the level of appraiser subjectivity is dramatically reduced.

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This paper analyses the appraisal of a specialized form of real estate - data centres - that has a unique blend of locational, physical and technological characteristics that differentiate it from conventional real estate assets. Market immaturity, limited trading and a lack of pricing signals enhance levels of appraisal uncertainty and disagreement relative to conventional real estate assets. Given the problems of applying standard discounted cash flow, an approach to appraisal is proposed that uses pricing signals from traded cash flows that are similar to the cash flows generated from data centres. Based upon ‘the law of one price’, it is assumed that two assets that are expected to generate identical cash flows in the future must have the same value now. It is suggested that the expected cash flow of assets should be analysed over the life cycle of the building. Corporate bond yields are used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds.

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Various studies investigating the future impacts of integrating high levels of renewable energy make use of historical meteorological (met) station data to produce estimates of future generation. Hourly means of 10m horizontal wind are extrapolated to a standard turbine hub height using the wind profile power or log law and used to simulate the hypothetical power output of a turbine at that location; repeating this procedure using many viable locations can produce a picture of future electricity generation. However, the estimate of hub height wind speed is dependent on the choice of the wind shear exponent a or the roughness length z0, and requires a number of simplifying assumptions. This paper investigates the sensitivity of this estimation on generation output using a case study of a met station in West Freugh, Scotland. The results show that the choice of wind shear exponent is a particularly sensitive parameter which can lead to significant variation of estimated hub height wind speed and hence estimated future generation potential of a region.

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Meteorological (met) station data is used as the basis for a number of influential studies into the impacts of the variability of renewable resources. Real turbine output data is not often easy to acquire, whereas meteorological wind data, supplied at a standardised height of 10 m, is widely available. This data can be extrapolated to a standard turbine height using the wind profile power law and used to simulate the hypothetical power output of a turbine. Utilising a number of met sites in such a manner can develop a model of future wind generation output. However, the accuracy of this extrapolation is strongly dependent on the choice of the wind shear exponent alpha. This paper investigates the accuracy of the simulated generation output compared to reality using a wind farm in North Rhins, Scotland and a nearby met station in West Freugh. The results show that while a single annual average value for alpha may be selected to accurately represent the long term energy generation from a simulated wind farm, there are significant differences between simulation and reality on an hourly power generation basis, with implications for understanding the impact of variability of renewables on short timescales, particularly system balancing and the way that conventional generation may be asked to respond to a high level of variable renewable generation on the grid in the future.

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Data from civil engineering projects can inform the operation of built infrastructure. This paper captures lessons for such data handover, from projects into operations, through interviews with leading clients and their supply chain. Clients are found to value receiving accurate and complete data. They recognise opportunities to use high quality information in decision-making about capital and operational expenditure; as well as in ensuring compliance with regulatory requirements. Providing this value to clients is a motivation for information management in projects. However, data handover is difficult as key people leave before project completion; and different data formats and structures are used in project delivery and operations. Lessons learnt from leading practice include defining data requirements at the outset, getting operations teams involved early, shaping the evolution of interoperable systems and standards, developing handover processes to check data rather than documentation, and fostering skills to use and update project data in operations

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The absorption spectra of phytoplankton in the visible domain hold implicit information on the phytoplankton community structure. Here we use this information to retrieve quantitative information on phytoplankton size structure by developing a novel method to compute the exponent of an assumed power-law for their particle-size spectrum. This quantity, in combination with total chlorophyll-a concentration, can be used to estimate the fractional concentration of chlorophyll in any arbitrarily-defined size class of phytoplankton. We further define and derive expressions for two distinct measures of cell size of mixed populations, namely, the average spherical diameter of a bio-optically equivalent homogeneous population of cells of equal size, and the average equivalent spherical diameter of a population of cells that follow a power-law particle-size distribution. The method relies on measurements of two quantities of a phytoplankton sample: the concentration of chlorophyll-a, which is an operational index of phytoplankton biomass, and the total absorption coefficient of phytoplankton in the red peak of visible spectrum at 676 nm. A sensitivity analysis confirms that the relative errors in the estimates of the exponent of particle size spectra are reasonably low. The exponents of phytoplankton size spectra, estimated for a large set of in situ data from a variety of oceanic environments (~ 2400 samples), are within a reasonable range; and the estimated fractions of chlorophyll in pico-, nano- and micro-phytoplankton are generally consistent with those obtained by an independent, indirect method based on diagnostic pigments determined using high-performance liquid chromatography. The estimates of cell size for in situ samples dominated by different phytoplankton types (diatoms, prymnesiophytes, Prochlorococcus, other cyanobacteria and green algae) yield nominal sizes consistent with the taxonomic classification. To estimate the same quantities from satellite-derived ocean-colour data, we combine our method with algorithms for obtaining inherent optical properties from remote sensing. The spatial distribution of the size-spectrum exponent and the chlorophyll fractions of pico-, nano- and micro-phytoplankton estimated from satellite remote sensing are in agreement with the current understanding of the biogeography of phytoplankton functional types in the global oceans. This study contributes to our understanding of the distribution and time evolution of phytoplankton size structure in the global oceans.

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Sea ice friction models are necessary to predict the nature of interactions between sea ice floes. These interactions are of interest on a range of scales, for example, to predict loads on engineering structures in icy waters or to understand the basin-scale motion of sea ice. Many models use Amonton's friction law due to its simplicity. More advanced models allow for hydrodynamic lubrication and refreezing of asperities; however, modeling these processes leads to greatly increased complexity. In this paper we propose, by analogy with rock physics, that a rate- and state-dependent friction law allows us to incorporate memory (and thus the effects of lubrication and bonding) into ice friction models without a great increase in complexity. We support this proposal with experimental data on both the laboratory (∼0.1 m) and ice tank (∼1 m) scale. These experiments show that the effects of static contact under normal load can be incorporated into a friction model. We find the parameters for a first-order rate and state model to be A = 0.310, B = 0.382, and μ0 = 0.872. Such a model then allows us to make predictions about the nature of memory effects in moving ice-ice contacts.

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Using panel data for 111 countries over the period 1982–2002, we employ two indexes that cover a wide range of human rights to empirically analyze whether and to what extent terrorism affects human rights. According to our results,terrorism significantly, but not dramatically, diminishes governments’ respect for basic human rights such as the absence of extrajudicial killings, political imprisonment, and torture. The result is robust to how we measure terrorist attacks, to the method of estimation, and to the choice of countries in our sample. However, we find no effect of terrorism on empowerment rights.

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The maximum 'Depth to Mate' (DTM(k)) data for k-man chess, k = 3-7, is now available: log(maxDTM(k)) demonstrates quasi-linear behaviour. This note predicts maxDTM for 8- to 10-man chess and the two-sigma distributions around these figures. 'Haworth's Law' is the conjecture that maxDTM will continue to demonstrate this behaviour for some time to come. The supporting datafile is a pgn of maxDTM positions, each having a DTM-minimaxing line of play from it to 'mate'.

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The article examines the customary international law credentials of the humanitarian law rules proposed by the International Committee of the Red Cross (ICR) in 2005. It relies on the BIICL/Chatham House analysis as a ‘constructive comment’ on the methodology of the ICRC study and the rules formed as a result of that methodology with respect to the dead and missing as an aid to determination of their customary law status. It shows that most of the rules studied have a customary international lawpedigree which conforms to the conclusions formed on the rules generally in the Wilmshurst and Breau study. However, the rules with respect to return of personal effects, recording location of graves and notification of relatives of access to gravesites do not seem to have even on a majoritarian/deductive approach enough volume of state practice to establish them as customary with respect to civilians.