International Journal of Health Geographics 2011, 10:37, 20 May 2011
Joseph R. Sharkey, Cassandra M. Johnson, Wesley R. Dean, and Scott A. Horel
“Objective: The objective of this study is to examine the relationship between residential exposure to fast-food entrées, using two measures of potential spatial access: proximity (distance to the nearest location) and coverage (number of different locations), and weekly consumption of fast-food meals.
“Methods: Traditional fast-food restaurants and non-traditional fast-food outlets, such as convenience stores, supermarkets, and grocery stores, from the 2006 Brazos Valley Food Environment Project were linked with individual participants (n = 1409) who completed the nutrition module in the 2006 Brazos Valley Community Health Assessment.
“Results: Increased age, poverty, increased distance to the nearest fast food, and increased number of different traditional fast-food restaurants, non-traditional fast-food outlets, or fastfood opportunities were associated with less frequent weekly consumption of fast-food meals. The interaction of gender and proximity (distance) or coverage (number) indicated that the association of proximity to or coverage of fast-food locations on fast-food consumption was greater among women and opposite of independent effects.
“Conclusions: Results provide impetus for identifying and understanding the complex relationship between access to all fast-food opportunities, rather than to traditional fast-food restaurants alone, and fast-food consumption. The results indicate the importance of further examining the complex interaction of gender and distance in rural areas and particularly in fastfood consumption. Furthermore, this study emphasizes the need for health promotion and policy efforts to consider all sources of fast-food as part of promoting healthful food choices. ”
Network Architecture and Information System Security, SAR-SSI 2011
Ahmed AMOKRANE, Yacine CHALLAL, and Amar BALLA
“A Wireless Sensor Network (WSN) is composed of small, low cost and low energy consumption devices called sensors. Those sensors are deployed in a monitored area. They capture measurements related to the monitored phenomenon (temperature, humidity…) and send them through a multi-hop routing to a sink node that delivers them to a Base Station for use and decision making. WSN are used in several ﬁelds ranging from military applications to civilian ones, for security, home automation and health care… Up to now, most of the works focused on designing routing protocols to address energy consumption issue, fault tolerance and security. In this paper, we address the issue of secure management and interrogation of WSN through Internet mainly. In our work, we designed and implemented a generic approach based on Web Services that builds a standardized interface between a WSN and external networks and applications. Our approach uses a gateway that oﬀers a synthesis of Web Services oﬀered by the WSN assuring its interrogation and management. Furthermore, Authentication, Authorization and Accounting mechanism has been implemented to provide security services and a billing system for WSN interrogation. We designed our architecture as a generic framework. Then, we instantiated it for two use cases. Furthermore, we designed and implemented a Service Oriented routing protocol for WSN.”
BMC Public Health 2011, 11:380, Published 24 May 2011
Ching-Lan Cheng, Yi-Chi Chen, Tzu-Ming Liu, and Yea-Huei Kao-Yang
“Background: Geographic Information Systems (GIS) combined with spatial analytical methods could be helpful in examining patterns of drug use. Little attention has been paid to geographic variation of cardiovascular prescription use in Taiwan. The main objective was to use local spatial association statistics to test whether or not the cardiovascular medication-prescribing pattern is homogenous across 352 townships in Taiwan.
“Methods: The statistical methods used were the global measures of Moran’s I and Local Indicators of Spatial Association (LISA). While Moran’s I provides information on the overall spatial distribution of the data, LISA provides information on types of spatial association at the local level. LISA statistics can also be used to identify influential locations in spatial association analysis. The major classes of prescription cardiovascular drugs were taken from Taiwan’s National Health Insurance Research Database (NHIRD), which has a coverage rate of over 97%. The dosage of each prescription was converted into defined daily doses to measure the consumption of each class of drugs. Data were analyzed with ArcGIS and GeoDa at the township level.
“Results: The LISA statistics showed an unusual use of cardiovascular medications in the southern townships with high local variation. Patterns of drug use also showed more low-low spatial clusters (cold spots) than high-high spatial clusters (hot spots), and those low-low associations were clustered in the rural areas.
“Conclusions: The cardiovascular drug prescribing patterns were heterogeneous across Taiwan. In particular, a clear pattern of north-south disparity exists. Such spatial clustering helps prioritize the target areas that require better education concerning drug use.”
CASA Working Paper 166, 23 May 2011
“In this paper, we develop a generic framework for comparing spatial models whose dynamics ranges from comparative static equilibrium structures to fully dynamic models. In the last 40 years, a variety of spatial models have been suggested. Until the mid 1980s, most models were static in structure and tended to embrace detailed mechanisms involving spatial economics and social physics. Typical examples were Land Use Transportation Interaction (LUTI) models that embraced theories of spatial interaction and discrete choice modelling. During this earlier period, the problems of making these models dynamic and more disaggregate was broached but progress was slow largely because of problems in collecting requisite data and problems of increasing the complexity of such models to the point where they could be properly validated in traditional ways. 20 years or more ago, new modelling approaches from very different sources came onto the horizon: in particular, dynamic models based in Cellular Automata (CA) which were largely physical in nature and Agent-Based Models (ABM) providing explicit behavioural processes that often rested alongside these automata. Systems Dynamics Models (SDM), Spatial Econometric Models (SEM) and Micro-simulation Models (MM) all informed the debate. It is tempting to see these models as all being of different genera but here we attempt to see them as part of an integrated whole, introducing a framework for their elaboration and comparison. After the framework is introduced, we review these six model types and choose three – CA, ABM and LUTI models – that we then work up in more detail to illustrate these comparisons. We conclude with the conundrums and paradoxes that beset this field.”