scholarly journals Imputation of confidential data sets with spatial locations using disease mapping models

2014 ◽  
Vol 33 (11) ◽  
pp. 1928-1945 ◽  
Author(s):  
Thais Paiva ◽  
Avishek Chakraborty ◽  
Jerry Reiter ◽  
Alan Gelfand
Keyword(s):  
Disease Mapping ◽  
Data Sets ◽  
Confidential Data ◽  
Spatial Locations ◽  
Mapping Models

Approximate cross-validatory predictive checks in disease mapping models

2003 ◽  
Vol 22 (10) ◽  
pp. 1649-1660 ◽  
Author(s):  
E. C. Marshall ◽  
D. J. Spiegelhalter
Keyword(s):  
Disease Mapping ◽  
Mapping Models

scholarly journals Time-lapse monitoring of fluid-induced geophysical property variations within an unstable earthwork using P-wave refraction

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. EN17-EN27 ◽  
Author(s):  
Paolo Bergamo ◽  
Ben Dashwood ◽  
Sebastian Uhlemann ◽  
Russell Swift ◽  
Jonathan E. Chambers ◽  
...  
Keyword(s):  
Time Lapse ◽  
P Wave ◽  
Data Sets ◽  
Time Intervals ◽  
Total Period ◽  
Seismic Properties ◽  
Wave Refraction ◽  
Regular Time ◽  
Spatial Locations ◽  
Spatial Regularization

A significant portion of the UK’s transportation system relies on a network of geotechnical earthworks (cuttings and embankments) that were constructed more than 100 years ago, whose stability is affected by the change in precipitation patterns experienced over the past few decades. The vulnerability of these structures requires a reliable, cost- and time-effective monitoring of their geomechanical condition. We have assessed the potential application of P-wave refraction for tracking the seasonal variations of seismic properties within an aged clay-filled railway embankment, located in southwest England. Seismic data were acquired repeatedly along the crest of the earthwork at regular time intervals, for a total period of 16 months. P-wave first-break times were picked from all available recorded traces, to obtain a set of hodocrones referenced to the same spatial locations, for various dates along the surveyed period of time. Traveltimes extracted from each acquisition were then compared to track the pattern of their temporal variability. The relevance of such variations over time was compared with the data experimental uncertainty. The multiple set of hodocrones was subsequently inverted using a tomographic approach, to retrieve a time-lapse model of [Formula: see text] for the embankment structure. To directly compare the reconstructed [Formula: see text] sections, identical initial models and spatial regularization were used for the inversion of all available data sets. A consistent temporal trend for P-wave traveltimes, and consequently for the reconstructed [Formula: see text] models, was identified. This pattern could be related to the seasonal distribution of precipitation and soil-water content measured on site.

Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease-Mapping Models

Biometrics ◽  
2006 ◽  
Vol 62 (4) ◽  
pp. 1197-1206 ◽  
Author(s):  
Brian J. Reich ◽  
James S. Hodges ◽  
Vesna Zadnik
Keyword(s):  
Fixed Effects ◽  
Disease Mapping ◽  
Mapping Models ◽  
Residual Smoothing

On fitting spatio-temporal disease mapping models using approximate Bayesian inference

2014 ◽  
Vol 23 (6) ◽  
pp. 507-530 ◽  
Author(s):  
María Dolores Ugarte ◽  
Aritz Adin ◽  
Tomas Goicoa ◽  
Ana Fernandez Militino
Keyword(s):  
Bayesian Inference ◽  
Disease Mapping ◽  
Spatio Temporal ◽  
Approximate Bayesian ◽  
Mapping Models ◽  
Approximate Bayesian Inference

RSSMSO Rapid Similarity Search on Metric Space Object Stored in Cloud Environment

2016 ◽  
Vol 6 (3) ◽  
pp. 33-49 ◽  
Author(s):  
Raghavendra S. ◽  
Nithyashree K. ◽  
Geeta C.M. ◽  
Rajkumar Buyya ◽  
Venugopal K. R. ◽  
...  
Keyword(s):  
Service Provider ◽  
Similarity Search ◽  
Low Cost ◽  
Real Data ◽  
Data Transformation ◽  
Third Party ◽  
Data Sets ◽  
Outsourced Data ◽  
Search Service ◽  
Confidential Data

This paper involves a cloud computing environment in which the dataowner outsource the similarity search service to a third party service provider. Privacy of the outsourced data is important because they may be confidential data. The data should be made available to the authorized client groups, but not to be revealed to the service provider in which the data is stored. Given this scenario, the paper presents a technique called RSSMSO which has build phase, query phase, data transformation and search phase. The build phase and the query phase are about uploading the data and querying the data respectively; the data transformation phase transforms the data before submitting it to the service provider for similarity queries on the transformed data; search phase involves searching similar object with respect to query object. The RSSMSO technique provides enhanced query accuracy with low communication cost. Experiments have been carried out on real data sets which exhibits that the proposed work is capable of providing privacy and achieving accuracy at a low cost in comparison with FDH

Random disclosure in confidential statistical databases

2020 ◽  
pp. 1-13
Author(s):  
Rainer Lenz ◽  
Tim Hochgürtel
Keyword(s):  
Real World ◽  
Data File ◽  
Data Sets ◽  
Statistical Disclosure Control ◽  
Random Assignment ◽  
National Legislation ◽  
Disclosure Control ◽  
Privacy Requirements ◽  
Confidential Data ◽  
Statistical Disclosure

As part of statistical disclosure control National Statistical Offices can only deliver confidential data being sufficiently protected meeting national legislation. When releasing confidential microdata to users, data holders usually apply what are called anonymisation methods to the data. In order to fulfil the privacy requirements, it is possible to measure the level of privacy of some confidential data file by simulating potential data intrusion scenarios matching publicly or commercially available data with the entire set of confidential data, both sharing a non-empty set of variables (quasi-identifiers). According to real world microdata, incompatibility between data sets and not unique combinations of quasi-identifiers are very likely. In this situation, it is nearly impossible to decide whether or not two records refer to the same underlying statistical unit. Even a successful assignment of records may be a fruitless disclosure attempt, if a rationale data intruder would keep distance from that match. The paper lines out that disclosure risks estimated thus far are overrated in the sense that revealed information is always a combination of both, systematically derived results and non-negligible random assignment.

scholarly journals An Autoregressive Disease Mapping Model for Spatio-Temporal Forecasting

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 384
Author(s):  
Francisca Corpas-Burgos ◽  
Miguel A. Martinez-Beneito
Keyword(s):  
Time Series ◽  
Disease Mapping ◽  
Mortality Data ◽  
Data Sets ◽  
Modeling Tools ◽  
Polynomial Fit ◽  
Proposed Model ◽  
Temporal Models ◽  
Temporal Model ◽  
Spatio Temporal

One of the more evident uses of spatio-temporal disease mapping is forecasting the spatial distribution of diseases for the next few years following the end of the period of study. Spatio-temporal models rely on very different modeling tools (polynomial fit, splines, time series, etc.), which could show very different forecasting properties. In this paper, we introduce an enhancement of a previous autoregressive spatio-temporal model with particularly interesting forecasting properties, given its reliance on time series modeling. We include a common spatial component in that model and show how that component improves the previous model in several ways, its predictive capabilities being one of them. In this paper, we introduce and explore the theoretical properties of this model and compare them with those of the original autoregressive model. Moreover, we illustrate the benefits of this new model with the aid of a comprehensive study on 46 different mortality data sets in the Valencian Region (Spain) where the benefits of the new proposed model become evident.

scholarly journals Provable Security for Outsourcing Database Operations

2010 ◽  
Vol 4 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Sergei Evdokimov ◽  
Matthias Fischmann ◽  
Oliver Günther
Keyword(s):  
Service Providers ◽  
Security And Privacy ◽  
Data Sets ◽  
Database Outsourcing ◽  
Confidential Data ◽  
Encryption Schemes ◽  
Database Operations ◽  
Definition Of ◽  
Database Service ◽  
Privacy Risks

Database outsourcing has become popular in recent years, although it introduces substantial security and privacy risks. In many applications, users may not want to reveal their data even to a generally trusted database service provider. Several researchers have proposed encryption schemes, such as privacy homomorphisms, that allow service providers to process confidential data sets without learning too much about them. In this paper, the authors discuss serious flaws of these solutions. The authors then present a new definition of security for homomorphic database encryption schemes that avoids these flaws and show that it is difficult to build a privacy homomorphism that complies with this definition. As a practical compromise, the authors present a relaxed variant of the security definition and discuss arising security implications. They present a new method to construct encryption schemes for exact selects and prove that the resulting schemes satisfy this notion.

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