2 resultados para Publicly Traded

em CUNY Academic Works


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In recent decades, library associations have advocated for the adoption of privacy and confidentiality policies as practical support to the Library Code of Ethics with a threefold purpose to (1) define and uphold privacy practices within the library, (2) convey privacy practices to patrons and, (3) protect against potential liability and public relations problems. The adoption of such policies has been instrumental in providing libraries with effective responses to surveillance initiatives such as warrantless requests and the USA PATRIOT ACT. Nevertheless, as reflected in recent news stories, the rapid emergence of data brokerage relationships and technologies and the increasing need for libraries to utilize third party vendor services have increased opportunities for data surveillers to access patrons’ personal information and reading habits, which are funneled and made available through multiple online library service platforms. Additionally, the advice that libraries should “contract for the same level of privacy reflected in their privacy policies” is no longer realistic given that the existence of multiple vendor contracts negotiated at arms length is likely to produce varying privacy terms and even varying definitions of what constitutes personal information (PII). These conditions sharply threaten the effectiveness and relevance of library privacy policies and privacy initiatives in that such policies increasingly offer false comfort by failing to reflect privacy weaknesses in the data sharing landscape and vendor contracts when library-vendor contracts fail to keep up with vendor data sharing capabilities. While some argue that library privacy ethics are antiquated and rendered obscure in the current online sharing economy PEW studies point to pronounced public discomfort with increasing privacy erosion. At the same time, new directions in FTC enforcement raise the possibility that public institutions’ privacy policies may serve as swords to unfair or deceptive commercial trade practices – offering the potential of renewed relevance for library privacy and confidentiality policies. This dual coin of public concern and the potential for enhanced FTC enforcement suggests that when crafting privacy polices libraries must now walk the knife’s edge by offering patrons both realistic notice about the limitations of protections the library can ensure while at the same time publicly holding vendors accountable to library privacy ethics and expectations. Potential solutions for how to walk this edge are developed and offered as a subject for further discussion to assist the modification of model policies for both public and academic libraries alike.

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Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed.