16,132 research outputs found
Foreign Aid in Equatorial Guinea: Macroeconomic Features and Future Challenges
The paper carries out a deep case study of the international aid that Equatorial Guinea receives. This is an extremely interesting country because, not being a failed state, it presents very low indexes in institutional quality. Its oil richness, which began to be exploited by foreign investors in 1996, has meant a structural change of extraordinary interest without the traditional effects of Dutch disease. While in 1989 the country financed 54% of its GDP with ODA, in 1996 this ratio represented only 22% and nowadays barely reaches 0.5% thanks to the enormous growth of foreign investment. The article analyses empirically the predictability of the ODA flows -mainly composed of Spanish funds-, their stability, cyclical behaviour and stabilizing effect on the GDP. The main findings of the study are that the ODA has been a hardly predictable, relatively stable, counter-cyclical flow and that it does have a stabilizing effect on its product. The FDI (Direct Foreign Investment), on the other hand is much more volatile and pro-cyclical, although it shares the stabilizing effect of the ODA. For every million dollars of the FDI, GDP grew 0.1%. Development aid, on the contrary, doesn’t have a statistically significant impact if we consider the time period 1985-2006. But it does in 1985-1995. Every additional million dollars of ODA made the GDP grow 1.3%. The sectoral analysis of ODA revealed that more than 80% of Spanish aid has been invested in social services, especially education (46%) and healthcare (26%), carried out by two NGOs that somehow became accomplices of the social underdevelopment that the Guinean government maintains since its independence. The article concludes with some ideas on how to improve the quality of Spanish ODA, especially proposing a deadline for the aid and a result-based conditionality, like the Aid Efficiency Agenda of Accra suggests.development aid; Dutch disease; stabilization; evaluation; results; volatility
I Know Why You Went to the Clinic: Risks and Realization of HTTPS Traffic Analysis
Revelations of large scale electronic surveillance and data mining by
governments and corporations have fueled increased adoption of HTTPS. We
present a traffic analysis attack against over 6000 webpages spanning the HTTPS
deployments of 10 widely used, industry-leading websites in areas such as
healthcare, finance, legal services and streaming video. Our attack identifies
individual pages in the same website with 89% accuracy, exposing personal
details including medical conditions, financial and legal affairs and sexual
orientation. We examine evaluation methodology and reveal accuracy variations
as large as 18% caused by assumptions affecting caching and cookies. We present
a novel defense reducing attack accuracy to 27% with a 9% traffic increase, and
demonstrate significantly increased effectiveness of prior defenses in our
evaluation context, inclusive of enabled caching, user-specific cookies and
pages within the same website
The value of implementation and the value of information: combined and uneven development
<i>Aim</i>: In a budget-constrained health care system, the decision to invest in strategies to improve the implementation of cost-effective technologies must be made alongside decisions regarding investment in the technologies themselves and investment in further research. This article presents a single, unified framework that simultaneously addresses the problem of allocating funds between these separate but linked activities. <i>Methods</i>: The framework presents a simple 4-state world where both information and implementation can be either at the current level or "perfect". Through this framework, it is possible to determine the maximum return to further research and an upper bound on the value of adopting implementation strategies. The framework is illustrated through case studies of health care technologies selected from those previously considered by the UK National Institute for Health and Clinical Excellence (NICE). <i>Results</i>: Through the case studies, several key factors that influence the expected values of perfect information and perfect implementation are identified. These factors include the maximum acceptable cost-effectiveness ratio, the level of uncertainty surrounding the adoption decision, the expected net benefits associated with the technologies, the current level of implementation, and the size of the eligible population. <i>Conclusions</i>: Previous methods for valuing implementation strategies have not distinguished the value of efficacy research and the value of strategies to change the level of implementation. This framework demonstrates that the value of information and the value of implementation can be examined separately but simultaneously in a single framework. This can usefully inform policy decisions about investment in health care services, further research, and adopting implementation strategies that are likely to differ between technologies
Creating a Relational Distributed Object Store
In and of itself, data storage has apparent business utility. But when we can
convert data to information, the utility of stored data increases dramatically.
It is the layering of relation atop the data mass that is the engine for such
conversion. Frank relation amongst discrete objects sporadically ingested is
rare, making the process of synthesizing such relation all the more
challenging, but the challenge must be met if we are ever to see an equivalent
business value for unstructured data as we already have with structured data.
This paper describes a novel construct, referred to as a relational distributed
object store (RDOS), that seeks to solve the twin problems of how to
persistently and reliably store petabytes of unstructured data while
simultaneously creating and persisting relations amongst billions of objects.Comment: 12 pages, 5 figure
Big Data and the Internet of Things
Advances in sensing and computing capabilities are making it possible to
embed increasing computing power in small devices. This has enabled the sensing
devices not just to passively capture data at very high resolution but also to
take sophisticated actions in response. Combined with advances in
communication, this is resulting in an ecosystem of highly interconnected
devices referred to as the Internet of Things - IoT. In conjunction, the
advances in machine learning have allowed building models on this ever
increasing amounts of data. Consequently, devices all the way from heavy assets
such as aircraft engines to wearables such as health monitors can all now not
only generate massive amounts of data but can draw back on aggregate analytics
to "improve" their performance over time. Big data analytics has been
identified as a key enabler for the IoT. In this chapter, we discuss various
avenues of the IoT where big data analytics either is already making a
significant impact or is on the cusp of doing so. We also discuss social
implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski
(eds.) Big Data Analysis: New algorithms for a new society, Springer Series
on Studies in Big Data, to appea
Readability of Privacy Policies of Healthcare Websites
Health-related personal information is very privacy-sensitive. Online privacy policies inform Website users about the ways their personal information is gathered, processed and stored. In the light of increasing privacy concerns, privacy policies seem to be an important mechanism for increasing customer loyalty. However, in practice, consumers only rarely read privacy policies, possibly due to the common assumption that policies are hard to read. By designing and implementing an automated extraction and readability analysis toolset, we present the first study that provides empirical evidence on readability of over 5,000 privacy policies of health websites and over 1,000 privacy policies of top e-commerce sites. Our results confirm the difficulty of reading current privacy policies. We further show that health websites\u27 policies are more readable than top e-commerce ones, but policies of non-commercial health websites are worse readable than commercial ones. Our study also provides a solid policy text corpus for further research
- …