7 resultados para Fraudulent conveyance

em Digital Commons at Florida International University


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Acoustic velocity meter (AVM) sites, located both distant and adjacent to canal water control structures, were constructed and calibrated in L-31W borrow canal and Canal 111 (C-111) to measure canal water velocity. Data were used to compute monthly discharge volumes and overall water budgets for several canal reaches from August 1994 to May 1996. The water budgets indicated extensive aquifer inflows in L-31W associated, in part, with S-332 pump station return flows. Canal and groundwater piezometer data showed 5 distinct hydrologic scenarios (distinguished by the direction and magnitude of hydraulic gradients) in the important Frog Pond area on the eastern boundary of the Everglades National Park. Most of the water lost from C-111 was via surface water losses near the outlet of the system, close to Florida Bay. The distribution of flows during the study suggest an alteration of the present South Dade Conveyance System modification plan to improve water deliveries to Taylor Slough and the Eastern Panhandle of the Everglades National Park. ^

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In broad terms — including a thief's use of existing credit card, bank, or other accounts — the number of identity fraud victims in the United States ranges 9-10 million per year, or roughly 4% of the US adult population. The average annual theft per stolen identity was estimated at $6,383 in 2006, up approximately 22% from $5,248 in 2003; an increase in estimated total theft from $53.2 billion in 2003 to $56.6 billion in 2006. About three million Americans each year fall victim to the worst kind of identity fraud: new account fraud. Names, Social Security numbers, dates of birth, and other data are acquired fraudulently from the issuing organization, or from the victim then these data are used to create fraudulent identity documents. In turn, these are presented to other organizations as evidence of identity, used to open new lines of credit, secure loans, “flip” property, or otherwise turn a profit in a victim's name. This is much more time consuming — and typically more costly — to repair than fraudulent use of existing accounts. ^ This research borrows from well-established theoretical backgrounds, in an effort to answer the question – what is it that makes identity documents credible? Most importantly, identification of the components of credibility draws upon personal construct psychology, the underpinning for the repertory grid technique, a form of structured interviewing that arrives at a description of the interviewee’s constructs on a given topic, such as credibility of identity documents. This represents substantial contribution to theory, being the first research to use the repertory grid technique to elicit from experts, their mental constructs used to evaluate credibility of different types of identity documents reviewed in the course of opening new accounts. The research identified twenty-one characteristics, different ones of which are present on different types of identity documents. Expert evaluations of these documents in different scenarios suggest that visual characteristics are most important for a physical document, while authenticated personal data are most important for a digital document. ^

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With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

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A pivotal component of hydrological restoration of the Florida Everglades is the improvement of water conveyance to Everglades National Park by the degradation of the current network of canals, roadways and levees. The Tamiami Trail (L29) road/canal complex represents a major barrier to natural water flows into the park and a variety of modification options for flow improvement are currently being explored, including the installation of spreader swales immediately downstream of culverts conveying water under Tamiami Trail from the L29 canal into Everglades National Park. In this study, we evaluated water column chemistry and wet-season diatom community structure to provide baseline information for use in future monitoring activities related to the proposed Tamiami Trail modifications. Water chemistry showed pronounced fluctuations in response to precipitation and anthropogenically mediated hydrological events. Differences in water quality variables among sites were dampened during periods of inundation, and became more pronounced during periods of low canal stage, suggesting the importance of small-scale mechanisms related to isolation of habitat patches. Diatom assemblages were unexpectedly speciose (127 taxa in 40 samples) compared to typical Everglades assemblages, and spatially heterogeneous in sites associated with concentric areas of dense vegetation immediately downstream of culverts. We also observed significant compositional dissimilarities among transects, indicating that culvert pool and north transect assemblages were substantially influenced by propagule input from the canal and areas to the north, while south transect sites were compositionally similar to typical sawgrass prairie diatom communities. Central transect sites were compositionally intermediate to their north and south counterparts. We propose that the position and spatial extent of this “transitional assemblage” is a sensitive indicator of subtle environmental change related to Tamiami Trail modifications.

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Estuarine productivity is highly dependent on the freshwater sources of the estuary. In Florida Bay, Taylor Slough was historically the main source of fresh water. Beginning in about 1960, and culminating with the completion of the South Dade Conveyance System in 1984, water management practice began to change the quantity and distribution of flow from Taylor Slough into Northeastern Florida Bay. These practices altered salinity and hydrologic parameters that had measurable negative impacts on vertebrate fauna and their habitats. Here, I review those impacts from published and unpublished literature and anecdotal observations. Almost all vertebrates covered in this review have shown some form of population decline since 1984; most of the studies implicate declines in food resources as the main stressor on their populations. My conclusion is that the diversion of fresh water resulted in an ecological cascade starting with hydrologic stresses on primary then secondary producers culminating in population declines at the top of the food web.

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In broad terms — including a thief's use of existing credit card, bank, or other accounts — the number of identity fraud victims in the United States ranges 9-10 million per year, or roughly 4% of the US adult population. The average annual theft per stolen identity was estimated at $6,383 in 2006, up approximately 22% from $5,248 in 2003; an increase in estimated total theft from $53.2 billion in 2003 to $56.6 billion in 2006. About three million Americans each year fall victim to the worst kind of identity fraud: new account fraud. Names, Social Security numbers, dates of birth, and other data are acquired fraudulently from the issuing organization, or from the victim then these data are used to create fraudulent identity documents. In turn, these are presented to other organizations as evidence of identity, used to open new lines of credit, secure loans, “flip” property, or otherwise turn a profit in a victim's name. This is much more time consuming — and typically more costly — to repair than fraudulent use of existing accounts. This research borrows from well-established theoretical backgrounds, in an effort to answer the question – what is it that makes identity documents credible? Most importantly, identification of the components of credibility draws upon personal construct psychology, the underpinning for the repertory grid technique, a form of structured interviewing that arrives at a description of the interviewee’s constructs on a given topic, such as credibility of identity documents. This represents substantial contribution to theory, being the first research to use the repertory grid technique to elicit from experts, their mental constructs used to evaluate credibility of different types of identity documents reviewed in the course of opening new accounts. The research identified twenty-one characteristics, different ones of which are present on different types of identity documents. Expert evaluations of these documents in different scenarios suggest that visual characteristics are most important for a physical document, while authenticated personal data are most important for a digital document.

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With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.