An uncertain geo-spatial dataset is a collection of geo-spatial objects that do not represent accurately real-world entities. Each object has a confidence value indicating how likely it is for the object to be correct. Uncertain data can be the result of operations such as imprecise integration, incorrect update or inexact querying. A k-route, over an uncertain geo-spatial dataset, is a path th...

This paper aims at providing a survey of recently developed multidimensional methods in the field of spatial data and policy analysis. After a brief methodological introduction, various multidimensional techniques for data analysis are discussed. Much emphasis is placed on the treatment of soft (ordinal or qualitative) data. Next, several multidimensional methods for policy analysis (multi-obje...

For the sake of environmental change monitoring, a huge amount of geospatial and temporal data have been acquired through various networks of monitoring stations. For instance, daily precipitation and air temperature are observed at meteorological stations, and MODIS images are regularly received at satellite ground stations. However, so far these massive raw data from the stations are not full...

Geographical data broadcasting is suitable for many large scale disseminationbased applications due to its independence of number of users, and thus it can serve as an important part of intelligent information infrastructures for modern cities. In broadcast systems, query response time is greatly affected by the order in which data items are being broadcast. However, existing broadcast ordering...

Formal remittance flows to Pakistan have shown noticeable growth over the past decade. Using bilateral remittance data for 23 major source countries, this study examines the external and internal factors driving these remittance flows during the period 2001-2011. We estimate a gravity model for bilateral remittance flows using a variety of panel data techniques suitable to control for unobserve...

Geographical information systems are commonly used for a variety of purposes. Many of them make use of a large database of geographical data, the correctness of which strongly influences the reliability of the system. In this paper, we present an approach to quality maintenance that is based on automatic discovery of non-perfect regularities in the data. The underlying idea is that exceptions t...

one of the methods used in the analysis of data related to diseases, and their underlying reasons is drawing geographical map. mapping diseases is a valuable tool to determine the regions of high rate of infliction requiring therapeutic interventions. the objective of this study was to investigate obesity pattern in iran by drawing geographical maps based on bayesian spatial model to recognize ...

In medical education and clinical care, representations of the patient help health care teams in planning and coordinating patient care, sometimes over geographic distances. This takes forms ranging from telemedicine consultations to using simulations and information and communication technology representations to plan, and at times, perform clinical procedures such as are done in intensive car...

This paper uses the establishment of federal agricultural experiment stations to provide new evidence on the effects of university research on long-term regional development. Our analysis of county-level agricultural census data from 1870 to 2000 reveals that station establishment increased local crop revenue per acre for 30-40 years, but localization effects do not persist to the present day. ...

This paper proposes optimal prediction intervals for the future generalized order statistic (GOS) based on the first GOS (ordinary order statistics, usual record values, -record values) from an exponential population. A conditional argument is considered for obtaining an optimal prediction interval for future GOS. A numerical example illustrates this technique.