WorldWideScience

Sample records for geographic risk modeling

  1. The effect of modifiable risk factors on geographic mortality differentials: a modelling study

    Directory of Open Access Journals (Sweden)

    Stevenson Christopher E

    2012-01-01

    Full Text Available Abstract Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men and 35.6% (women of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%. Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.

  2. Using Geographic Information System-based Ecologic Niche Models to Forecast the Risk of Hantavirus Infection in Shandong Province, China

    Science.gov (United States)

    Wei, Lan; Qian, Quan; Wang, Zhi-Qiang; Glass, Gregory E.; Song, Shao-Xia; Zhang, Wen-Yi; Li, Xiu-Jun; Yang, Hong; Wang, Xian-Jun; Fang, Li-Qun; Cao, Wu-Chun

    2011-01-01

    Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in Shandong Province, China. In this study, we combined ecologic niche modeling with geographic information systems (GIS) and remote sensing techniques to identify the risk factors and affected areas of hantavirus infections in rodent hosts. Land cover and elevation were found to be closely associated with the presence of hantavirus-infected rodent hosts. The averaged area under the receiver operating characteristic curve was 0.864, implying good performance. The predicted risk maps based on the model were validated both by the hantavirus-infected rodents' distribution and HFRS human case localities with a good fit. These findings have the applications for targeting control and prevention efforts. PMID:21363991

  3. Geographic exposure risk of variant Creutzfeldt-Jakob disease in US blood donors: a risk-ranking model to evaluate alternative donor-deferral policies.

    Science.gov (United States)

    Yang, Hong; Huang, Yin; Gregori, Luisa; Asher, David M; Bui, Travis; Forshee, Richard A; Anderson, Steven A

    2017-04-01

    Variant Creutzfeldt-Jakob disease (vCJD) has been transmitted by blood transfusion (TTvCJD). The US Food and Drug Administration (FDA) recommends deferring blood donors who resided in or traveled to 30 European countries where they may have been exposed to bovine spongiform encephalopathy (BSE) through beef consumption. Those recommendations warrant re-evaluation, because new cases of BSE and vCJD have markedly abated. The FDA developed a risk-ranking model to calculate the geographic vCJD risk using country-specific case rates and person-years of exposure of US blood donors. We used the reported country vCJD case rates, when available, or imputed vCJD case rates from reported BSE and UK beef exports during the risk period. We estimated the risk reduction and donor loss should the deferral be restricted to a few high-risk countries. We also estimated additional risk reduction by leukocyte reduction (LR) of red blood cells (RBCs). The United Kingdom, Ireland, and France had the greatest vCJD risk, contributing approximately 95% of the total risk. The model estimated that deferring US donors who spent extended periods of time in these three countries, combined with currently voluntary LR (95% of RBC units), would reduce the vCJD risk by 89.3%, a reduction similar to that achieved under the current policy (89.8%). Limiting deferrals to exposure in these three countries would potentially allow donations from an additional 100,000 donors who are currently deferred. Our analysis suggests that a deferral option focusing on the three highest risk countries would achieve a level of blood safety similar to that achieved by the current policy. © 2016 AABB.

  4. Bayesian geostatistical modelling of malaria and lymphatic filariasis infections in Uganda: predictors of risk and geographical patterns of co-endemicity

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    Pedersen Erling M

    2011-10-01

    Full Text Available Abstract Background In Uganda, malaria and lymphatic filariasis (causative agent Wuchereria bancrofti are transmitted by the same vector species of Anopheles mosquitoes, and thus are likely to share common environmental risk factors and overlap in geographical space. In a comprehensive nationwide survey in 2000-2003 the geographical distribution of W. bancrofti was assessed by screening school-aged children for circulating filarial antigens (CFA. Concurrently, blood smears were examined for malaria parasites. In this study, the resultant malariological data are analysed for the first time and the CFA data re-analysed in order to identify risk factors, produce age-stratified prevalence maps for each infection, and to define the geographical patterns of Plasmodium sp. and W. bancrofti co-endemicity. Methods Logistic regression models were fitted separately for Plasmodium sp. and W. bancrofti within a Bayesian framework. Models contained covariates representing individual-level demographic effects, school-level environmental effects and location-based random effects. Several models were fitted assuming different random effects to allow for spatial structuring and to capture potential non-linearity in the malaria- and filariasis-environment relation. Model-based risk predictions at unobserved locations were obtained via Bayesian predictive distributions for the best fitting models. Maps of predicted hyper-endemic malaria and filariasis were furthermore overlaid in order to define areas of co-endemicity. Results Plasmodium sp. parasitaemia was found to be highly endemic in most of Uganda, with an overall population adjusted parasitaemia risk of 47.2% in the highest risk age-sex group (boys 5-9 years. High W. bancrofti prevalence was predicted for a much more confined area in northern Uganda, with an overall population adjusted infection risk of 7.2% in the highest risk age-group (14-19 year olds. Observed overall prevalence of individual co

  5. A geographical information system-based web model of arbovirus transmission risk in the continental United States of America

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    Sarah K. Konrad

    2012-11-01

    Full Text Available A degree-day (DD model of West Nile virus capable of forecasting real-time transmission risk in the continental United States of America up to one week in advance using a 50-km grid is available online at https://sites. google.com/site/arbovirusmap/. Daily averages of historical risk based on temperatures for 1994-2003 are available at 10- km resolution. Transmission risk maps can be downloaded from 2010 to the present. The model can be adapted to work with any arbovirus for which the temperature-related parameters are known, e.g. Rift Valley fever virus. To more effectively assess virus establishment and transmission, the model incorporates “compound risk” maps and forecasts, which includes livestock density as a parameter.

  6. The preparation of landslide map by Landslide Numerical Risk Factor (LNRF model and Geographic Information System (GIS

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    Ali Mohammadi Torkashvand

    2014-12-01

    Full Text Available One of the risks to threaten mountainous areas is that hillslope instability caused damage to lands. One of the most dangerous instabilities is mass movement and much movement occurs due to slip. The aim of this study is zonation of landslide hazards in a basin of the Ardebil province, the eastern slopes of Sabalan, Iran. Geological and geomorphologic conditions, climate and type of land use have caused susceptibility of this watershed to landslides. Firstly, maps of the main factors affecting landslide occurrence including slope, distance from faults, lithology, elevation and precipitation were prepared and digitized. Then, by using interpretation of aerial photos and satellite images and field views, the ground truth map of landslides was prepared. Each basic layer (factor and landslide map were integrated to compute the numeric value of each factor with the help of a Landslide Numerical Risk Factor (LNRF model and landslide occurrence percent obtained in different units from each of the maps. Finally, with overlapping different data layers, a landslide hazard zonation map was prepared. Results showed that 67.85% of the basin has high instability, 7.76% moderate instability and 24.39% low instability.

  7. Conceptual Model of Dynamic Geographic Environment

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    Martínez-Rosales Miguel Alejandro

    2014-04-01

    Full Text Available In geographic environments, there are many and different types of geographic entities such as automobiles, trees, persons, buildings, storms, hurricanes, etc. These entities can be classified into two groups: geographic objects and geographic phenomena. By its nature, a geographic environment is dynamic, thus, it’s static modeling is not sufficient. Considering the dynamics of geographic environment, a new type of geographic entity called event is introduced. The primary target is a modeling of geographic environment as an event sequence, because in this case the semantic relations are much richer than in the case of static modeling. In this work, the conceptualization of this model is proposed. It is based on the idea to process each entity apart instead of processing the environment as a whole. After that, the so called history of each entity and its spatial relations to other entities are defined to describe the whole environment. The main goal is to model systems at a conceptual level that make use of spatial and temporal information, so that later it can serve as the semantic engine for such systems.

  8. Composing Models of Geographic Physical Processes

    Science.gov (United States)

    Hofer, Barbara; Frank, Andrew U.

    Processes are central for geographic information science; yet geographic information systems (GIS) lack capabilities to represent process related information. A prerequisite to including processes in GIS software is a general method to describe geographic processes independently of application disciplines. This paper presents such a method, namely a process description language. The vocabulary of the process description language is derived formally from mathematical models. Physical processes in geography can be described in two equivalent languages: partial differential equations or partial difference equations, where the latter can be shown graphically and used as a method for application specialists to enter their process models. The vocabulary of the process description language comprises components for describing the general behavior of prototypical geographic physical processes. These process components can be composed by basic models of geographic physical processes, which is shown by means of an example.

  9. Evaluation of Refuge Life Risk using Geographical and Social Grid-Models with Satellite-Based House Ratio and Flood Depth by Tsunami Simulation

    Science.gov (United States)

    Kaneko, D.; Hosoyamada, T.

    2017-12-01

    The authors have developed social and geographical models for evaluating and applying life risk to the Kamakura coast near the south-western part of the metropolitan areas of Tokyo. The coastline close to the seismic center of the South Kanto earthquake is in the riskiest belt in the metropolitan area with a high possibility of house collapse and tsunami run-up. Kamakura is an important historical city, visited by many tourists who are not familiar with seismic dangers. There is a high probability of loss of human life during an evacuation of the city during tsunami waves. To evaluate the distribution of life risk characteristics in the area, models for citizens and sightseers are developed that includes social data such as population density, wooden-house ratio, and geographical evacuation distance and tsunami-flooding depth. The population of Kamakura City is 174,050 and the risk of tsunami evacuation is high in the area from the southern part of Kamakura Station to Zaimokuza block, where the population is approximately 15,310 people. There are about 26,000 tourists visiting this area on weekdays and about 100,000 sightseers visiting the area on Saturdays and Sundays. On weekdays the population per mesh will increase by half of the 2,000 inhabitants. On Saturdays and Sundays the population density will be 4 thousand who will double those of the inhabitants. A disaster prevention hill is proposed as a tsunami countermeasure on the coast of Kamakura City. The hill is covered by pine forest with a high-standard road, evacuation center, and sightseeing parking lots embedded in the hilly bank. In normal times, tourists and citizens use this area as a seaside pine park. Long concrete box structures strengthen the hill inside the mound, which has two levels, the lower equipped with high-standard-width roads on the ground level. The parking areas will resolve daily traffic congestion issues along the Kamakura main streets. The evaluation of over-flooding tsunamis and

  10. Geographic Resolution Issues in RAM Transport Risk Analysis

    International Nuclear Information System (INIS)

    Mills, G.S.; Neuhauser, K.S.

    2000-01-01

    Transport risk analyses based on the RADTRAN code have been met with continual demands for increased spatial resolution of variations in population densities and other parameters employed in the calculation of risk estimates for transport of radioactive material (RAM). With the advent of geographic information systems (GISs) large quantities of data required to describe transport routes, which may extend to hundreds of kilometers, with high resolution (e.g. 1 km segments) can be handled without inordinate expense. This capability has raised a question concerning the maximum resolution of available input data and compatibility with RADTRAN computational models. Quantitative examinations are presented of spatial resolution issues in the calculation of incident-free doses and accident dose risks. For incident-free calculations, the effect of decreasing route-segment length on accuracy, in view of the model employed, is examined, and means of reducing total data input to the RADTRAN calculations, without loss of meaningful resolution of population concentrations, are presented. In the case of accident-risk calculations, the ability to detail population density under very large dispersal plumes permits comparison of plume modelling to actual data. In both types of calculations, meaningful limits to geographic extent are suggested. (author)

  11. Geographically weighted regression model on poverty indicator

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    Slamet, I.; Nugroho, N. F. T. A.; Muslich

    2017-12-01

    In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

  12. Geographically Weighted Logistic Regression Applied to Credit Scoring Models

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    Pedro Henrique Melo Albuquerque

    Full Text Available Abstract This study used real data from a Brazilian financial institution on transactions involving Consumer Direct Credit (CDC, granted to clients residing in the Distrito Federal (DF, to construct credit scoring models via Logistic Regression and Geographically Weighted Logistic Regression (GWLR techniques. The aims were: to verify whether the factors that influence credit risk differ according to the borrower’s geographic location; to compare the set of models estimated via GWLR with the global model estimated via Logistic Regression, in terms of predictive power and financial losses for the institution; and to verify the viability of using the GWLR technique to develop credit scoring models. The metrics used to compare the models developed via the two techniques were the AICc informational criterion, the accuracy of the models, the percentage of false positives, the sum of the value of false positive debt, and the expected monetary value of portfolio default compared with the monetary value of defaults observed. The models estimated for each region in the DF were distinct in their variables and coefficients (parameters, with it being concluded that credit risk was influenced differently in each region in the study. The Logistic Regression and GWLR methodologies presented very close results, in terms of predictive power and financial losses for the institution, and the study demonstrated viability in using the GWLR technique to develop credit scoring models for the target population in the study.

  13. Geographic resolution issues in RAM transportation risk analysis

    International Nuclear Information System (INIS)

    Mills G, Scott; Neuhauser, Sieglinde

    2000-01-01

    Over the years that radioactive material (RAM) transportation risk estimates have been calculated using the RADTRAN code, demand for improved geographic resolution of route characteristics, especially density of population neighboring route segments, has led to code improvements that provide more specific route definition. With the advent of geographic information systems (GISs), the achievable resolution of route characteristics is theoretically very high. The authors have compiled population-density data in 1-kilometer increments for routes extending over hundreds of kilometers without impractical expenditures of time. Achievable resolution of analysis is limited, however, by the resolution of available data. U.S. Census data typically have 1-km or better resolution within densely-populated portions of metropolitan areas but census blocks are much larger in rural areas. Geographic resolution of accident-rate data, especially for heavy/combination trucks, are typically tabulated on a statewide basis. These practical realities cause one to ask what level(s) of resolution may be necessary for meaningful risk analysis of transportation actions on a state or interstate scale

  14. Geographical information modelling for land resource survey

    NARCIS (Netherlands)

    Bruin, de S.

    2000-01-01

    The increasing popularity of geographical information systems (GIS) has at least three major implications for land resources survey. Firstly, GIS allows alternative and richer representation of spatial phenomena than is possible with the traditional paper map. Secondly, digital technology has

  15. Geographical variance in the risk of gastric stump cancer: no increased risk in Japan?

    NARCIS (Netherlands)

    Tersmette, A. C.; Giardiello, F. M.; Offerhaus, G. J.; Tersmette, K. W.; Ohara, K.; Vandenbroucke, J. P.; Tytgat, G. N.

    1991-01-01

    Geographical differences may exist in the risk of gastric stump cancer. Therefore, we performed meta-analysis of literature reports in Japan (n = 3), the USA (n = 4), and Europe (n = 20) on the risk of postgastrectomy cancer. The weighted mean relative risk of stump cancer in Japan was 0.28, 95%

  16. Generalisation of geographic information cartographic modelling and applications

    CERN Document Server

    Mackaness, William A; Sarjakoski, L Tiina

    2011-01-01

    Theoretical and Applied Solutions in Multi Scale MappingUsers have come to expect instant access to up-to-date geographical information, with global coverage--presented at widely varying levels of detail, as digital and paper products; customisable data that can readily combined with other geographic information. These requirements present an immense challenge to those supporting the delivery of such services (National Mapping Agencies (NMA), Government Departments, and private business. Generalisation of Geographic Information: Cartographic Modelling and Applications provides detailed review

  17. Communicating Geographical Risks in Crisis Management: The Need for Research.

    Science.gov (United States)

    French, Simon; Argyris, Nikolaos; Haywood, Stephanie M; Hort, Matthew C; Smith, Jim Q

    2017-10-23

    In any crisis, there is a great deal of uncertainty, often geographical uncertainty or, more precisely, spatiotemporal uncertainty. Examples include the spread of contamination from an industrial accident, drifting volcanic ash, and the path of a hurricane. Estimating spatiotemporal probabilities is usually a difficult task, but that is not our primary concern. Rather, we ask how analysts can communicate spatiotemporal uncertainty to those handling the crisis. We comment on the somewhat limited literature on the representation of spatial uncertainty on maps. We note that many cognitive issues arise and that the potential for confusion is high. We note that in the early stages of handling a crisis, the uncertainties involved may be deep, i.e., difficult or impossible to quantify in the time available. In such circumstance, we suggest the idea of presenting multiple scenarios. © 2017 Society for Risk Analysis.

  18. Geographic delivery models for radiotherapy services

    International Nuclear Information System (INIS)

    Roberts, G.H.; Dunscombe, P.B.; Samant, R.S.

    2002-01-01

    The study described here was undertaken to quantify the societal cost of radiotherapy in idealized urban and rural populations and, hence, to generate a measure of impediment to access. The costs of centralized, distributed comprehensive and satellite radiotherapy delivery formats were examined by decomposing them into institutional, productivity and geographical components. Our results indicate that centralized radiotherapy imposes the greatest financial burden on the patient population in both urban and rural scenarios. The financial burden faced by patients who must travel for radiotherapy can be interpreted as one component of the overall impediment to access. With advances in remote-monitoring systems, it is possible to maintain technical quality while enhancing patient access. However, the maintenance of professional competence will remain a challenge with a distributed service-delivery format. Copyright (2002) Blackwell Science Pty Ltd

  19. Geographical Environment Factors and Risk Assessment of Tick-Borne Encephalitis in Hulunbuir, Northeastern China.

    Science.gov (United States)

    Li, Yifan; Wang, Juanle; Gao, Mengxu; Fang, Liqun; Liu, Changhua; Lyu, Xin; Bai, Yongqing; Zhao, Qiang; Li, Hairong; Yu, Hongjie; Cao, Wuchun; Feng, Liqiang; Wang, Yanjun; Zhang, Bin

    2017-05-26

    Tick-borne encephalitis (TBE) is one of natural foci diseases transmitted by ticks. Its distribution and transmission are closely related to geographic and environmental factors. Identification of environmental determinates of TBE is of great importance to understanding the general distribution of existing and potential TBE natural foci. Hulunbuir, one of the most severe endemic areas of the disease, is selected as the study area. Statistical analysis, global and local spatial autocorrelation analysis, and regression methods were applied to detect the spatiotemporal characteristics, compare the impact degree of associated factors, and model the risk distribution using the heterogeneity. The statistical analysis of gridded geographic and environmental factors and TBE incidence show that the TBE patients mainly occurred during spring and summer and that there is a significant positive spatial autocorrelation between the distribution of TBE cases and environmental characteristics. The impact degree of these factors on TBE risks has the following descending order: temperature, relative humidity, vegetation coverage, precipitation and topography. A high-risk area with a triangle shape was determined in the central part of Hulunbuir; the low-risk area is located in the two belts next to the outside edge of the central triangle. The TBE risk distribution revealed that the impact of the geographic factors changed depending on the heterogeneity.

  20. Modeling the geographical studies with GeoGebra-software

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    Ionica Soare

    2010-01-01

    Full Text Available The problem of mathematical modeling in geography is one of the most important strategies in order to establish the evolution and the prevision of geographical phenomena. Models must have a simplified structure, to reflect essential components and must be selective, structured, and suggestive and approximate the reality. Models could be static or dynamic, developed in a theoretical, symbolic, conceptual or mental way, mathematically modeled. The present paper is focused on the virtual model which uses GeoGebra software, free and available at www.geogebra.org, in order to establish new methods of geographical analysis in a dynamic, didactic way.

  1. Comparison of GARP and Maxent in modelling the geographic ...

    African Journals Online (AJOL)

    A number of presence-only models can be used in the prediction of the geographic distribution of diseases and/or their vectors. The predictive performance of these models differs depending on a number of factors but primarily the modeled species' ecological traits. In this study, the performance of GARP and Maxent, two of ...

  2. Geographic profiling to assess the risk of rare plant poaching in natural areas

    Science.gov (United States)

    Young, J.A.; Van Manen, F.T.; Thatcher, C.A.

    2011-01-01

    We demonstrate the use of an expert-assisted spatial model to examine geographic factors influencing the poaching risk of a rare plant (American ginseng, Panax quinquefolius L.) in Shenandoah National Park, Virginia, USA. Following principles of the analytic hierarchy process (AHP), we identified a hierarchy of 11 geographic factors deemed important to poaching risk and requested law enforcement personnel of the National Park Service to rank those factors in a series of pair-wise comparisons. We used those comparisons to determine statistical weightings of each factor and combined them into a spatial model predicting poaching risk. We tested the model using 69 locations of previous poaching incidents recorded by law enforcement personnel. These locations occurred more frequently in areas predicted by the model to have a higher risk of poaching than random locations. The results of our study can be used to evaluate resource protection strategies and to target law enforcement activities. ?? Springer Science+Business Media, LLC (outside the USA) 2011.

  3. Random-growth urban model with geographical fitness

    Science.gov (United States)

    Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

    2012-12-01

    This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

  4. Geographic Video 3d Data Model And Retrieval

    Science.gov (United States)

    Han, Z.; Cui, C.; Kong, Y.; Wu, H.

    2014-04-01

    Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

  5. An approach for a complex assessment of the geo-ecological risk from natural disasters in a geographic region

    International Nuclear Information System (INIS)

    Zlateva, Plamena; Stoyanov, Krasimir

    2009-01-01

    The paper proposes an approach for a complex assessment of the geo-ecological risk of a certain geographic region on the basis of quantitative and qualitative datum about the potential natural disasters. A fuzzy logic model is designed. The type of the threats, consequences and interdependencies between infrastructure objects are taken into account. The geographic region is considered as a complex system of interconnected and mutually influencing elements. The expected damages are directly and/or indirectly connected with life quality deterioration. Keywords: Risk, Geo-ecological risk, Damages, Threats, Vulnerabilities, Natural disasters

  6. Geographical information system and predictive risk maps of urinary schistosomiasis in Ogun State, Nigeria

    Directory of Open Access Journals (Sweden)

    Solarin Adewale RT

    2008-05-01

    Full Text Available Abstract Background The control of urinary schistosomiasis in Ogun State, Nigeria remains inert due to lack of reliable data on the geographical distribution of the disease and the population at risk. To help in developing a control programme, delineating areas of risk, geographical information system and remotely sensed environmental images were used to developed predictive risk maps of the probability of occurrence of the disease and quantify the risk for infection in Ogun State, Nigeria. Methods Infection data used were derived from carefully validated morbidity questionnaires among primary school children in 2001–2002, in which school children were asked among other questions if they have experienced "blood in urine" or urinary schistosomiasis. The infection data from 1,092 schools together with remotely sensed environmental data such as rainfall, vegetation, temperature, soil-types, altitude and land cover were analysis using binary logistic regression models to identify environmental features that influence the spatial distribution of the disease. The final regression equations were then used in Arc View 3.2a GIS software to generate predictive risk maps of the distribution of the disease and population at risk in the state. Results Logistic regression analysis shows that the only significant environmental variable in predicting the presence and absence of urinary schistosomiasis in any area of the State was Land Surface Temperature (LST (B = 0.308, p = 0.013. While LST (B = -0.478, p = 0.035, rainfall (B = -0.006, p = 0.0005, ferric luvisols (B = 0.539, p = 0.274, dystric nitosols (B = 0.133, p = 0.769 and pellic vertisols (B = 1.386, p = 0.008 soils types were the final variables in the model for predicting the probability of an area having an infection prevalence equivalent to or more than 50%. The two predictive risk maps suggest that urinary schistosomiasis is widely distributed and occurring in all the Local Government Areas (LGAs

  7. [Multicriteria evaluation of environmental risk exposure using a geographic information system in Argentina].

    Science.gov (United States)

    Pietri, Diana De; Dietrich, Patricia; Mayo, Patricia; Carcagno, Alejandro

    2011-10-01

    Develop a spatial model that includes environmental factors posing a health hazard, for application in the Matanza-Riachuelo River Basin (MRB) in Argentina. Multicriteria evaluation procedures were used with geographic information systems to obtain territorial zoning based on the degree of suitability for residence. Variables that characterize the habitability of housing and potential sources of basin pollution were geographically referenced. Health information was taken from the Risk Factor Survey (RFS) to measure the relative risk of living in unsuitable areas (exposed population) compared with suitable areas (unexposed population). Sixty percent of the MRB area is in suitable condition, a situation that affects 40% of residents. The rest of the population lives in unsuitable territory, and 6% live in the basin's most unsuitable conditions. Environmental conditions that are detrimental to health in the unsuitable areas became evident during the interviews through three of the pathologies considered: diarrheal diseases, respiratory diseases, and cancer. A regional analysis that provides valid information to support decisionmaking was obtained. Considering the basin as a unit of analysis allowed the use of a single protocol to undertake comprehensive measurement of the magnitude of risk and, thus, set priorities.

  8. Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

    Science.gov (United States)

    Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

    2017-06-01

    A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

  9. Fuzzy modeling with spatial information for geographic problems

    CERN Document Server

    Petry, Frederick E; Cobb, Maria A

    2005-01-01

    The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and ...

  10. A Framework for Conceptual Modeling of Geographic Data Quality

    DEFF Research Database (Denmark)

    Friis-Christensen, Anders; Christensen, J.V.; Jensen, Christian Søndergaard

    2004-01-01

    Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large...... an object is moving. Empirical performance studies based on a real road network and GPS logs from cars areThe notion of data quality is of particular importance to geographic data. One reason is that such data is often inherently imprecise. Another is that the usability of the data is in large part...... determined by how "good" the data is, as different applications of geographic data require different qualities of the data are met. Such qualities concern the object level as well as the attribute level of the data. This paper presents a systematic and integrated approach to the conceptual modeling...

  11. Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating Malaria.

    Directory of Open Access Journals (Sweden)

    Freya M Shearer

    2016-08-01

    Full Text Available Infection by the simian malaria parasite, Plasmodium knowlesi, can lead to severe and fatal disease in humans, and is the most common cause of malaria in parts of Malaysia. Despite being a serious public health concern, the geographical distribution of P. knowlesi malaria risk is poorly understood because the parasite is often misidentified as one of the human malarias. Human cases have been confirmed in at least nine Southeast Asian countries, many of which are making progress towards eliminating the human malarias. Understanding the geographical distribution of P. knowlesi is important for identifying areas where malaria transmission will continue after the human malarias have been eliminated.A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines.We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.

  12. Geographical point cloud modelling with the 3D medial axis transform

    NARCIS (Netherlands)

    Peters, R.Y.

    2018-01-01

    A geographical point cloud is a detailed three-dimensional representation of the geometry of our geographic environment.
    Using geographical point cloud modelling, we are able to extract valuable information from geographical point clouds that can be used for applications in asset management,

  13. A method for managing re-identification risk from small geographic areas in Canada

    Directory of Open Access Journals (Sweden)

    Neisa Angelica

    2010-04-01

    Full Text Available Abstract Background A common disclosure control practice for health datasets is to identify small geographic areas and either suppress records from these small areas or aggregate them into larger ones. A recent study provided a method for deciding when an area is too small based on the uniqueness criterion. The uniqueness criterion stipulates that an the area is no longer too small when the proportion of unique individuals on the relevant variables (the quasi-identifiers approaches zero. However, using a uniqueness value of zero is quite a stringent threshold, and is only suitable when the risks from data disclosure are quite high. Other uniqueness thresholds that have been proposed for health data are 5% and 20%. Methods We estimated uniqueness for urban Forward Sortation Areas (FSAs by using the 2001 long form Canadian census data representing 20% of the population. We then constructed two logistic regression models to predict when the uniqueness is greater than the 5% and 20% thresholds, and validated their predictive accuracy using 10-fold cross-validation. Predictor variables included the population size of the FSA and the maximum number of possible values on the quasi-identifiers (the number of equivalence classes. Results All model parameters were significant and the models had very high prediction accuracy, with specificity above 0.9, and sensitivity at 0.87 and 0.74 for the 5% and 20% threshold models respectively. The application of the models was illustrated with an analysis of the Ontario newborn registry and an emergency department dataset. At the higher thresholds considerably fewer records compared to the 0% threshold would be considered to be in small areas and therefore undergo disclosure control actions. We have also included concrete guidance for data custodians in deciding which one of the three uniqueness thresholds to use (0%, 5%, 20%, depending on the mitigating controls that the data recipients have in place, the

  14. Modelling Participatory Geographic Information System for Customary Land Conflict Resolution

    Science.gov (United States)

    Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.

    2017-11-01

    Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.

  15. COMPLEMENTARITY OF HISTORIC BUILDING INFORMATION MODELLING AND GEOGRAPHIC INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    X. Yang

    2016-06-01

    Full Text Available In this paper, we discuss the potential of integrating both semantically rich models from Building Information Modelling (BIM and Geographical Information Systems (GIS to build the detailed 3D historic model. BIM contributes to the creation of a digital representation having all physical and functional building characteristics in several dimensions, as e.g. XYZ (3D, time and non-architectural information that are necessary for construction and management of buildings. GIS has potential in handling and managing spatial data especially exploring spatial relationships and is widely used in urban modelling. However, when considering heritage modelling, the specificity of irregular historical components makes it problematic to create the enriched model according to its complex architectural elements obtained from point clouds. Therefore, some open issues limiting the historic building 3D modelling will be discussed in this paper: how to deal with the complex elements composing historic buildings in BIM and GIS environment, how to build the enriched historic model, and why to construct different levels of details? By solving these problems, conceptualization, documentation and analysis of enriched Historic Building Information Modelling are developed and compared to traditional 3D models aimed primarily for visualization.

  16. Case-control geographic clustering for residential histories accounting for risk factors and covariates

    Science.gov (United States)

    2006-01-01

    Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case

  17. Case-control geographic clustering for residential histories accounting for risk factors and covariates

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2006-08-01

    Full Text Available Abstract Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters, Ingham (2 and Jackson (1 counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically

  18. Vector status of Aedes species determines geographical risk of autochthonous Zika virus establishment.

    Directory of Open Access Journals (Sweden)

    Lauren Gardner

    2017-03-01

    Full Text Available The 2015-16 Zika virus pandemic originating in Latin America led to predictions of a catastrophic global spread of the disease. Since the current outbreak began in Brazil in May 2015 local transmission of Zika has been reported in over 60 countries and territories, with over 750 thousand confirmed and suspected cases. As a result of its range expansion attention has focused on possible modes of transmission, of which the arthropod vector-based disease spread cycle involving Aedes species is believed to be the most important. Additional causes of concern are the emerging new links between Zika disease and Guillain-Barre Syndrome (GBS, and a once rare congenital disease, microcephaly.Like dengue and chikungunya, the geographic establishment of Zika is thought to be limited by the occurrence of its principal vector mosquito species, Ae. aegypti and, possibly, Ae. albopictus. While Ae. albopictus populations are more widely established than those of Ae. aegypti, the relative competence of these species as a Zika vector is unknown. The analysis reported here presents a global risk model that considers the role of each vector species independently, and quantifies the potential spreading risk of Zika into new regions. Six scenarios are evaluated which vary in the weight assigned to Ae. albopictus as a possible spreading vector. The scenarios are bounded by the extreme assumptions that spread is driven by air travel and Ae. aegypti presence alone and spread driven equally by both species. For each scenario destination cities at highest risk of Zika outbreaks are prioritized, as are source cities in affected regions. Finally, intercontinental air travel routes that pose the highest risk for Zika spread are also ranked. The results are compared between scenarios.Results from the analysis reveal that if Ae. aegypti is the only competent Zika vector, then risk is geographically limited; in North America mainly to Florida and Texas. However, if Ae

  19. Inferring the risk factors behind the geographical spread and transmission of Zika in the Americas

    Science.gov (United States)

    Bóta, András; Gangavarapu, Karthik; Kraemer, Moritz U. G.; Grubaugh, Nathan D.

    2018-01-01

    Background An unprecedented Zika virus epidemic occurred in the Americas during 2015-2016. The size of the epidemic in conjunction with newly recognized health risks associated with the virus attracted significant attention across the research community. Our study complements several recent studies which have mapped epidemiological elements of Zika, by introducing a newly proposed methodology to simultaneously estimate the contribution of various risk factors for geographic spread resulting in local transmission and to compute the risk of spread (or re-introductions) between each pair of regions. The focus of our analysis is on the Americas, where the set of regions includes all countries, overseas territories, and the states of the US. Methodology/Principal findings We present a novel application of the Generalized Inverse Infection Model (GIIM). The GIIM model uses real observations from the outbreak and seeks to estimate the risk factors driving transmission. The observations are derived from the dates of reported local transmission of Zika virus in each region, the network structure is defined by the passenger air travel movements between all pairs of regions, and the risk factors considered include regional socioeconomic factors, vector habitat suitability, travel volumes, and epidemiological data. The GIIM relies on a multi-agent based optimization method to estimate the parameters, and utilizes a data driven stochastic-dynamic epidemic model for evaluation. As expected, we found that mosquito abundance, incidence rate at the origin region, and human population density are risk factors for Zika virus transmission and spread. Surprisingly, air passenger volume was less impactful, and the most significant factor was (a negative relationship with) the regional gross domestic product (GDP) per capita. Conclusions/Significance Our model generates country level exportation and importation risk profiles over the course of the epidemic and provides quantitative

  20. Trends in the risk of mortality due to cardiovascular diseases in five Brazilian geographic regions from 1979 to 1996

    Directory of Open Access Journals (Sweden)

    Maria de Fátima Marinho de Souza

    2001-12-01

    Full Text Available OBJECTIVE - To analyze the trends in risk of death due to cardiovascular diseases in the northern, northeastern, southern, southeastern, and central western Brazilian geographic regions from 1979 to 1996. METHODS - Data on mortality due to cardiovascular, cardiac ischemic, and cerebrovascular diseases in 5 Brazilian geographic regions were obtained from the Ministry of Health. Population estimates for the time period from 1978 to 1996 in the 5 Brazilian geographic regions were calculated by interpolation with the Lagrange method, based on the census data from 1970, 1980, 1991, and the population count of 1996, for each age bracket and sex. Trends were analyzed with the multiple linear regression model. RESULTS - Cardiovascular diseases showed a declining trend in the southern, southeastern, and northern Brazilian geographic regions in all age brackets and for both sexes. In the northeastern and central western regions, an increasing trend in the risk of death due to cardiovascular diseases occurred, except for the age bracket from 30 to 39 years, which showed a slight reduction. This resulted from the trends of cardiac ischemic and cerebrovascular diseases. The analysis of the trend in the northeastern and northern regions was impaired by the great proportion of poorly defined causes of death. CONCLUSION - The risk of death due to cardiovascular, cerebrovascular, and cardiac ischemic diseases decreased in the southern and southeastern regions, which are the most developed regions in the country, and increased in the least developed regions, mainly in the central western region.

  1. Correlates and geographic patterns of knowledge that physical activity decreases cancer risk.

    Science.gov (United States)

    Ramírez, A Susana; Finney Rutten, Lila J; Vanderpool, Robin C; Moser, Richard P; Hesse, Bradford W

    2013-04-01

    While many lifestyle-related cancer risk factors including tobacco use, poor diet, and sun exposure are well recognized by the general public, the role of physical activity in decreasing cancer risk is less recognized. Studies have demonstrated gender-, race/ethnicity-, and age-based disparities in cancer risk factor knowledge; however, beliefs and geographic factors that may be related to knowledge are under-examined. In this study, we analyzed data from the 2008 Health Information National Trends Survey to determine correlates of knowledge of the relationship between physical activity and reduced cancer risk in the adult US population. We generated geographic information system maps to examine the geographic distribution of this knowledge. Results revealed that there is confusion among US adults about the relationship between physical activity and cancer risk: Respondents who believed that cancer is not preventable had significantly lower odds of knowing that physical activity reduces cancer risk (p physical activity reduces cancer risk (p physical activity guidelines were also significantly more likely to know that physical activity reduces cancer risk (p physical inactivity. Correlates of cancer risk factor knowledge point to opportunities for targeted interventions.

  2. Geographic variance of cardiovascular risk factors among community women: the national Sister to Sister campaign.

    Science.gov (United States)

    Jarvie, Jennifer L; Johnson, Caitlin E; Wang, Yun; Wan, Yun; Aslam, Farhan; Athanasopoulos, Leonidas V; Pollin, Irene; Foody, JoAnne M

    2011-01-01

    There are substantial variations in cardiovascular disease (CVD) risk and outcomes among women. We sought to determine geographic variation in risk factor prevalence in a contemporary sample of U.S. women. Using 2008-2009 Sister to Sister (STS) free heart screening data from 17 U.S. cities, we compared rates of obesity (body mass index [BMI] ≥30 kg/m(2)), hypertension (HTN ≥140/90 mm Hg), low high-density lipoprotein cholesterol (HDL-C cities had higher rates of hyperglycemia and low HDL-C. In a large, community-based sample of women nationwide, this comprehensive analysis shows remarkable geographic variation in risk factors, which provides opportunities to improve and reduce a woman's CVD risk. Further investigation is required to understand the reasons behind such variation, which will provide insight toward tailoring preventive interventions to narrow gaps in CVD risk reduction in women.

  3. Modelling Technology for Building Fire Scene with Virtual Geographic Environment

    Science.gov (United States)

    Song, Y.; Zhao, L.; Wei, M.; Zhang, H.; Liu, W.

    2017-09-01

    Building fire is a risky activity that can lead to disaster and massive destruction. The management and disposal of building fire has always attracted much interest from researchers. Integrated Virtual Geographic Environment (VGE) is a good choice for building fire safety management and emergency decisions, in which a more real and rich fire process can be computed and obtained dynamically, and the results of fire simulations and analyses can be much more accurate as well. To modelling building fire scene with VGE, the application requirements and modelling objective of building fire scene were analysed in this paper. Then, the four core elements of modelling building fire scene (the building space environment, the fire event, the indoor Fire Extinguishing System (FES) and the indoor crowd) were implemented, and the relationship between the elements was discussed also. Finally, with the theory and framework of VGE, the technology of building fire scene system with VGE was designed within the data environment, the model environment, the expression environment, and the collaborative environment as well. The functions and key techniques in each environment are also analysed, which may provide a reference for further development and other research on VGE.

  4. A preliminary geodetic data model for geographic information systems

    Science.gov (United States)

    Kelly, K. M.

    2009-12-01

    Our ability to gather and assimilate integrated data collections from multiple disciplines is important for earth system studies. Moreover, geosciences data collection has increased dramatically, with pervasive networks of observational stations on the ground, in the oceans, in the atmosphere and in space. Contemporary geodetic observations from several space and terrestrial technologies contribute to our knowledge of earth system processes and thus are a valuable source of high accuracy information for many global change studies. Assimilation of these geodetic observations and numerical models into models of weather, climate, oceans, hydrology, ice, and solid Earth processes is an important contribution geodesists can make to the earth science community. Clearly, the geodetic observations and models are fundamental to these contributions. ESRI wishes to provide leadership in the geodetic community to collaboratively build an open, freely available content specification that can be used by anyone to structure and manage geodetic data. This Geodetic Data Model will provide important context for all geographic information. The production of a task-specific geodetic data model involves several steps. The goal of the data model is to provide useful data structures and best practices for each step, making it easier for geodesists to organize their data and metadata in a way that will be useful in their data analyses and to their customers. Built on concepts from the successful Arc Marine data model, we introduce common geodetic data types and summarize the main thematic layers of the Geodetic Data Model. These provide a general framework for envisioning the core feature classes required to represent geodetic data in a geographic information system. Like Arc Marine, the framework is generic to allow users to build workflow or product specific geodetic data models tailored to the specific task(s) at hand. This approach allows integration of the data with other existing

  5. Geographic variation in risk factors for SFG rickettsial and leptospiral exposure in Colombia.

    Science.gov (United States)

    Padmanabha, Harish; Hidalgo, Marylin; Valbuena, Gustavo; Castaneda, Elizabeth; Galeano, Armando; Puerta, Henry; Cantillo, Cesar; Mantilla, Gilma

    2009-10-01

    In order to characterize the patterns of human exposure to spotted fever group (SFG) rickettsial and leptospiral infection, IgG surveys were conducted on 642 residents of ten different areas of the rural district of Necoclí, Colombia. Areas were selected based on forest cover and human settlement pattern, and individual risk factors were elucidated through multivariate logistic models, controlling for variance clustering within communities. Overall, prevalence of high antibody titers indicating previous exposure to SFG rickettsia and leptospira was 29.2% and 35.6%, respectively, and both were most prevalent in the same peri-urban neighborhood. Forest cover .10% demonstrated the strongest independent association with leptospiral exposure, followed by homes with outdoor storage sheds. Isolated rural housing was the only variable independently associated with SFG rickettsia exposure. Community-level variables significantly modified the effects of individual risk factors. For both pathogens the eldest quartile was less exposed in periurban areas although there was no age effect overall for either. Females living in population settlements were more exposed to SFG rickettsiae but there was no sex association in isolated rural houses. Similarly, in sites with forest cover .10%, individuals working at home had higher leptospira seroprevalence, but place of work was not a risk factor in areas of forest cover ,10%. These data suggest that the patterns of maintenance and/or exposure to leptospira and rickettsia vary across different human created landscapes and settlement patterns. While contrasting risk factors may reflect the unique transmission cycles of each pathogen, the observed patterns of geographic variation suggest that both diseases may respond similarly larger scale human-ecological dynamics.

  6. Investigation of Flood Risk Assessment in Inaccessible Regions using Multiple Remote Sensing and Geographic Information Systems

    Science.gov (United States)

    Lim, J.; Lee, K. S.

    2017-12-01

    Flooding is extremely dangerous when a river overflows to inundate an urban area. From 1995 to 2016, North Korea (NK) experienced annual extensive damage to life and property almost each year due to a levee breach resulting from typhoons and heavy rainfall during the summer monsoon season. Recently, Hoeryeong City (2016) experienced heavy rainfall during typhoon Lionrock and the resulting flood killed and injured many people (68,900) and destroyed numerous buildings and settlements (11,600). The NK state media described it as the biggest national disaster since 1945. Thus, almost all annual repeat occurrences of floods in NK have had a serious impact, which makes it necessary to figure out the extent of floods in restoring the damaged environment. In addition, traditional hydrological model is impractical to delineate Flood Damaged Areas (FDAs) in NK due to the inaccessibility. Under such a situation, multiple optical Remote Sensing (RS) and radar RS along with a Geographic Information System (GIS)-based spatial analysis were utilized in this study (1) to develop modelling FDA delineation using multiple RS and GIS methods and (2) to conduct flood risk assessment in NK. Interpreting high-resolution web-based satellite imagery were also implemented to confirm the results of the study. From the study result, it was found that (1) on August 30th, 2016, an area of 117.2 km2 (8.6%) at Hoeryeong City was inundated. Most floods occurred in flat areas with a lower and middle stream order. (2) In the binary logistic regression model applied in this study, the distance from the nearest stream map and landform map variables are important factors to delineate FDAs because these two factors reflect heterogeneous mountainous NK topography. (3) Total annual flood risk of study area is estimated to be ₩454.13 million NKW ($504,417.24 USD, and ₩576.53 million SKW). The risk of the confluence of the Tumen River and Hoeryeong stream appears to be the highest. (4) High resolution

  7. Modeling the Geographic Consequence and Pattern of Dengue Fever Transmission in Thailand.

    Science.gov (United States)

    Bekoe, Collins; Pansombut, Tatdow; Riyapan, Pakwan; Kakchapati, Sampurna; Phon-On, Aniruth

    2017-05-04

    Dengue fever is one of the infectious diseases that is still a public health problem in Thailand. This study considers in detail, the geographic consequence, seasonal and pattern of dengue fever transmission among the 76 provinces of Thailand from 2003 to 2015. A cross-sectional study. The data for the study was from the Department of Disease Control under the Bureau of Epidemiology, Thailand. The quarterly effects and location on the transmission of dengue was modeled using an alternative additive log-linear model. The model fitted well as illustrated by the residual plots and the  Again, the model showed that dengue fever is high in the second quarter of every year from May to August. There was an evidence of an increase in the trend of dengue annually from 2003 to 2015. There was a difference in the distribution of dengue fever within and between provinces. The areas of high risks were the central and southern regions of Thailand. The log-linear model provided a simple medium of modeling dengue fever transmission. The results are very important in the geographic distribution of dengue fever patterns.

  8. Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

    NARCIS (Netherlands)

    P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We

  9. On Modeling Risk Shocks

    OpenAIRE

    Dorofeenko, Victor; Lee, Gabriel; Salyer, Kevin; Strobel, Johannes

    2016-01-01

    Within the context of a financial accelerator model, we model time-varying uncertainty (i.e. risk shocks) through the use of a mixture Normal model with time variation in the weights applied to the underlying distributions characterizing entrepreneur productivity. Specifically, we model capital producers (i.e. the entrepreneurs) as either low-risk (relatively small second moment for productivity) and high-risk (relatively large second moment for productivity) and the fraction of both types is...

  10. Modelling grid losses and the geographic distribution of electricity generation

    DEFF Research Database (Denmark)

    Østergaard, Poul Alberg

    2005-01-01

    In Denmark more than 40% of the electricity consumption is covered by geographically scattered electricity sources namely wind power and local CHP (cogeneration of heat and power) plants. This causes problems in regard to load balancing and possible grid overloads. The potential grid problems...... and methods for solving these are analysed in this article on the basis of energy systems analyses, geographic distribution of consumption and production and grid load-flow analyses. It is concluded that by introducing scattered load balancing using local CHP plants actively and using interruptible loads...

  11. Hazard, Vulnerability and Capacity Mapping for Landslides Risk Analysis using Geographic Information System (GIS)

    Science.gov (United States)

    Sari, D. A. P.; Innaqa, S.; Safrilah

    2017-06-01

    This research analyzed the levels of disaster risk in the Citeureup sub-District, Bogor Regency, West Java, based on its potential hazard, vulnerability and capacity, using map to represent the results, then Miles and Huberman analytical techniques was used to analyze the qualitative interviews. The analysis conducted in this study is based on the concept of disaster risk by Wisner. The result shows that the Citeureup sub-District has medium-low risk of landslides. Of the 14 villages, three villages have a moderate risk level, namely Hambalang, Tajur, and Tangkil, or 49.58% of the total land area. Eleven villages have a low level of risk, namely Pasir Mukti, Sanja, Tarikolot, Gunung Sari, Puspasari, East Karang Asem, Citeureup, Leuwinutug, Sukahati, West Karang Asem West and Puspanegara, or 48.68% of the total land area, for high-risk areas only around 1.74%, which is part of Hambalang village. The analysis using Geographic Information System (GIS) prove that areas with a high risk potential does not necessarily have a high level of risk. The capacity of the community plays an important role to minimize the risk of a region. Disaster risk reduction strategy is done by creating a safe condition, which intensified the movement of disaster risk reduction.

  12. Environmental statistical modelling of mosquito vectors at different geographical scales

    NARCIS (Netherlands)

    Cianci, D.

    2015-01-01

    Vector-borne diseases are infections transmitted by the bite of infected arthropod vectors, such as mosquitoes, ticks, fleas, midges and flies. Vector-borne diseases pose an increasingly wider threat to global public health, both in terms of people affected and their geographical spread. Mosquitoes

  13. Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

    Science.gov (United States)

    Akil, Luma; Ahmad, H Anwar

    2016-03-03

    Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections correlation with socioeconomic status using geographical information system (GIS) and neural network models. In this study, the relevant updated data of foodborne illness for southern states, from 2002 to 2011, were collected and used in the GIS and neural networks models. Data were collected from the Centers for Disease Control and Prevention (CDC), MS state Department of Health and the other states department of health. The correlation between low socioeconomic status and Salmonella infections were determined using models created by several software packages, including SAS, ArcGIS @RISK and NeuroShell. Results of this study showed a significant increase in Salmonella outbreaks in MS during the study period, with highest rates in 2011 (47.84 ± 24.41 cases/100,000; pGIS maps of Salmonella outbreaks in MS in 2010 and 2011 showed the districts with higher rates of Salmonella. Regression analysis and neural network models showed a moderate correlation between cases of Salmonella infections and low socioeconomic factors. Poverty was shown to have a negative correlation with Salmonella outbreaks (R(2)=0.152, p<0.05). Geographic location besides socioeconomic status may contribute to the high rates of Salmonella outbreaks in MS. Understanding the geographical and economic relationship with infectious diseases will help to determine effective methods to reduce outbreaks within low socioeconomic status communities. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  14. Modelling the geographic distribution of wind power and the impact on transmission needs

    DEFF Research Database (Denmark)

    Østergaard, Poul Alberg

    2003-01-01

    Through energy systems modelling, transmission systems modelling and geographical modelling, the article examines the sensitivity of the response of the transmission system to the geographic distributions of wind power and in particular the sensitivity of the results to the accuracy...... of the distributed modelled. The results show that accuracy of the geographic modelling while important for the analysis of specific single transmission lines is not important for the analysis of the general response of the transmission system. The analyses thus corroborate previous analyses that demonstrated...

  15. Living at a Geographically Higher Elevation Is Associated with Lower Risk of Metabolic Syndrome: Prospective Analysis of the SUN Cohort

    Directory of Open Access Journals (Sweden)

    Amaya Lopez-Pascual

    2017-01-01

    Full Text Available Living in a geographically higher altitude affects oxygen availability. The possible connection between environmental factors and the development of metabolic syndrome (MetS feature is not fully understood, being the available epidemiological evidence still very limited. The aim of the present study was to evaluate the longitudinal association between altitude and incidence of MetS and each of its components in a prospective Spanish cohort, The Seguimiento Universidad de Navarra (SUN project. Our study included 6860 highly educated subjects (university graduates free from any MetS criteria at baseline. The altitude of residence was imputed with the postal code of each individual subject residence according to the data of the Spanish National Cartographic Institute and participants were categorized into tertiles. MetS was defined according to the harmonized definition. Cox proportional hazards models were used to assess the association between the altitude of residence and the risk of MetS during follow-up. After a median follow-up period of 10 years, 462 incident cases of MetS were identified. When adjusting for potential confounders, subjects in the highest category of altitude (>456 m exhibited a significantly lower risk of developing MetS compared to those in the lowest tertile (<122 m of altitude of residence [Model 2: Hazard ratio = 0.75 (95% Confidence interval: 0.58–0.97; p for trend = 0.029]. Living at geographically higher altitude was associated with a lower risk of developing MetS in the SUN project. Our findings suggest that geographical elevation may be an important factor linked to metabolic diseases.

  16. Use of Geographic Information Systems for Planning HIV Prevention Interventions for High-Risk Youths

    Science.gov (United States)

    Geanuracos, Catherine G.; Cunningham, Shayna D.; Weiss, George; Forte, Draco; Henry Reid, Lisa M.; Ellen, Jonathan M.

    2007-01-01

    Geographic information system (GIS) analysis is an emerging tool for public health intervention planning. Connect to Protect, a researcher–community collaboration working in 15 cities to reduce HIV infection among youths, developed GIS databases of local health, crime, and demographic data to evaluate the geographic epidemiology of sexually transmitted infections and HIV risk among adolescents. We describe the process and problems of data acquisition, analysis, and mapping in the development of structural interventions, demonstrating how program planners can use this technology to inform and improve planning decisions. The Connect to Protect project’s experience suggests strategies for incorporating public data and GIS technology into the next generation of public health interventions. PMID:17901452

  17. Self-Reported Stroke Risk Stratification: Reasons for Geographic and Racial Differences in Stroke Study.

    Science.gov (United States)

    Howard, George; McClure, Leslie A; Moy, Claudia S; Howard, Virginia J; Judd, Suzanne E; Yuan, Ya; Long, D Leann; Muntner, Paul; Safford, Monika M; Kleindorfer, Dawn O

    2017-07-01

    The standard for stroke risk stratification is the Framingham Stroke Risk Function (FSRF), an equation requiring an examination for blood pressure assessment, venipuncture for glucose assessment, and ECG to determine atrial fibrillation and heart disease. We assess a self-reported stroke risk function (SRSRF) to stratify stroke risk in comparison to the FSRF. Participants from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke) were evaluated at baseline and followed for incident stroke. The FSRF was calculated using directly assessed stroke risk factors. The SRSRF was calculated from 13 self-reported questions to exclude those with prevalent stroke and assess stroke risk. Proportional hazards analysis was used to assess incident stroke risk using the FSRF and SRSRF. Over an average 8.2-year follow-up, 939 of 23 983 participants had a stroke. The FSRF and SRSRF produced highly correlated risk scores ( r Spearman =0.852; 95% confidence interval, 0.849-0.856); however, the SRSRF had higher discrimination of stroke risk than the FSRF (c SRSRF =0.7266; 95% confidence interval, 0.7076-0.7457; c FSRF =0.7075; 95% confidence interval, 0.6877-0.7273; P =0.0038). The 10-year stroke risk in the highest decile of predicted risk was 11.1% for the FSRF and 13.4% for the SRSRF. A simple self-reported questionnaire can be used to identify those at high risk for stroke better than the gold standard FSRF. This instrument can be used clinically to easily identify individuals at high risk for stroke and also scientifically to identify a subpopulation enriched for stroke risk. © 2017 American Heart Association, Inc.

  18. Crafting Disaster Risk Science: Environmental and geographical science sans frontières

    Directory of Open Access Journals (Sweden)

    Ailsa Holloway

    2009-11-01

    Full Text Available In keeping with the University of Cape Town’s commitment to social responsiveness (http://www.socialresponsiveness.uct.ac.za/, this article traces the process that underpinned the development and introduction of a postgraduate programme in Disaster Risk Science (DRS. It foregrounds the programme’s conceptualisation within the Department of Environmental and Geographical Science (EGS at the University of Cape Town (UCT, with particular emphasis on examining how disciplinary and theoretical coherence was balanced with cross-disciplinary application and social responsiveness. The article begins by describing the contextual conditions external to UCT’s formal teaching and learning environment that provided the necessary impetus for the new programme. It also traces the iterative relationship between context and curriculum that occurred over the period 1998–2008. This engagement was facilitated and mediated by the Disaster Mitigation for Sustainable Livelihoods Programme (DiMP, an interfacing research and advocacy unit, located within UCT’s Department of Environmental and Geographical Science. An explanation of subsequent content and sequencing of the postgraduate curriculum then follow. They illustrate the programme’s articulation with South Africa’s newly promulgated disaster management legislation, as well as its relevance and rigour in relation to the complex risk environment of South Africa’s Western Cape. The article specifically applies a transdisciplinary lens to the new programmme, in which Disaster Risk Science is conceptualized as a Mode 2 knowledge, but one that draws theoretically and methodologically on environmental and geographical science as its foundation or Mode 1 domain. It concludes by examining the DRS programme’s positive contributions both to scholarship and local risk management practices as well as the obstacles that constrained the new programme and continue to challenge its institutional sustainability.

  19. A coregionalization model can assist specification of Geographically Weighted Poisson Regression: Application to an ecological study.

    Science.gov (United States)

    Ribeiro, Manuel Castro; Sousa, António Jorge; Pereira, Maria João

    2016-05-01

    The geographical distribution of health outcomes is influenced by socio-economic and environmental factors operating on different spatial scales. Geographical variations in relationships can be revealed with semi-parametric Geographically Weighted Poisson Regression (sGWPR), a model that can combine both geographically varying and geographically constant parameters. To decide whether a parameter should vary geographically, two models are compared: one in which all parameters are allowed to vary geographically and one in which all except the parameter being evaluated are allowed to vary geographically. The model with the lower corrected Akaike Information Criterion (AICc) is selected. Delivering model selection exclusively according to the AICc might hide important details in spatial variations of associations. We propose assisting the decision by using a Linear Model of Coregionalization (LMC). Here we show how LMC can refine sGWPR on ecological associations between socio-economic and environmental variables and low birth weight outcomes in the west-north-central region of Portugal. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Risk assessment of urban flood disaster in Jingdezhen City based on analytic hierarchy process and geographic information system

    Science.gov (United States)

    Sun, D. C.; Huang, J.; Wang, H. M.; Wang, Z. Q.; Wang, W. Q.

    2017-08-01

    The research of urban flood risk assessment and management are of great academic and practical importance, which has become a widespread concern throughout the world. It’s significant to understand the spatial-temporal distribution of the flood risk before making the risk response measures. In this study, the urban region of Jingdezhen City is selected as the study area. The assessment indicators are selected from four aspects: disaster-causing factors, disaster-pregnant environment, disaster-bearing body and the prevention and mitigation ability, by consideration of the formation process of urban flood risk. And then, a small-scale flood disaster risk assessment model is developed based on Analytic Hierarchy Process(AHP) and Geographic Information System(GIS), and the spatial-temporal distribution of flood risk in Jingdezhen City is analysed. The results show that the risk decreases gradually from the centre line of Changjiang River to the surrounding, and the areas of high flood disaster risk is decreasing from 2010 to 2013 while the risk areas are more concentred. The flood risk of the areas along the Changjiang River is the largest, followed by the low-lying areas in Changjiang District. And the risk is also large in Zhushan District where the population, the industries and commerce are concentrated. The flood risk in the western part of Changjiang District and the north-eastern part of the study area is relatively low. The results can provide scientific support for flood control construction and land development planning in Jingdezhen City.

  1. Exploitation of geographic information system at mapping and modelling of selected soil parameters

    International Nuclear Information System (INIS)

    Palka, B.; Makovnikova, J.; Siran, M.

    2005-01-01

    In this presentation authors describe using of computers and geographic information systems (GIS) at effective use of soil fund, rational exploitation and organization of agricultural soil fund on the territory of the Slovak Republic, its monitoring and modelling. Using and creating of some geographically oriented information systems and databases about soils as well as present trends are discussed

  2. Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

    Science.gov (United States)

    Song, Chao; Kwan, Mei-Po; Zhu, Jiping

    2017-04-08

    An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

  3. Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics

    Directory of Open Access Journals (Sweden)

    Ahmed Seid

    2014-05-01

    Full Text Available Cutaneous leishmaniasis (CL is a neglected tropical disease strongly associated with poverty. Treatment is problematic and no vaccine is available. Ethiopia has seen new outbreaks in areas previously not known to be endemic, often with co-infection by the human immunodeficiency virus (HIV with rates reaching 5.6% of the cases. The present study concerns the development of a risk model based on environmental factors using geographical information systems (GIS, statistical analysis and modelling. Odds ratio (OR of bivariate and multivariate logistic regression was used to evaluate the relative importance of environmental factors, accepting P ≤0.056 as the inclusion level for the model’s environmental variables. When estimating risk from the viewpoint of geographical surface, slope, elevation and annual rainfall were found to be good predictors of CL presence based on both probabilistic and weighted overlay approaches. However, when considering Ethiopia as whole, a minor difference was observed between the two methods with the probabilistic technique giving a 22.5% estimate, while that of weighted overlay approach was 19.5%. Calculating the population according to the land surface estimated by the latter method, the total Ethiopian population at risk for CL was estimated at 28,955,035, mainly including people in the highlands of the regional states of Amhara, Oromia, Tigray and the Southern Nations, Nationalities and Peoples’ Region, one of the nine ethnic divisions in Ethiopia. Our environmental risk model provided an overall prediction accuracy of 90.4%. The approach proposed here can be replicated for other diseases to facilitate implementation of evidence-based, integrated disease control activities.

  4. The global geographical overlap of aflatoxin and hepatitis C: Controlling risk factors for liver cancer worldwide

    Science.gov (United States)

    Palliyaguru, Dushani L.; Wu, Felicia

    2012-01-01

    About 85% of hepatocellular carcinoma (HCC, liver cancer) cases occur in low-income countries, where the risk factors of dietary aflatoxin exposure and chronic hepatitis B and C (HBV and HCV) viral infection are common. While studies have shown synergism between aflatoxin and HBV in causing HCC, much less is known about whether aflatoxin and HCV synergize similarly. From an exposure perspective, we examine whether there is a geographical overlap in populations worldwide exposed to high dietary aflatoxin levels and with high HCV prevalence. While HCV is one of the most important risk factors for HCC in high-income nations (where aflatoxin exposure is low), we find that HCV prevalence is much higher in Africa and Asia, where aflatoxin exposure is also high. However, within a given world region, there are some inconsistencies regarding exposure and cancer risk. Therefore, there is a need to control risk factors such as aflatoxin and hepatitis viruses in a cost-effective manner to prevent global HCC, while continuing to evaluate biological mechanisms by which these risk factors interact to increase HCC risk. PMID:23281740

  5. Andean Condor (Vultur gryphus) in Ecuador: Geographic Distribution, Population Size and Extinction Risk.

    Science.gov (United States)

    Naveda-Rodríguez, Adrián; Vargas, Félix Hernán; Kohn, Sebastián; Zapata-Ríos, Galo

    2016-01-01

    The Andean Condor (Vultur gryphus) in Ecuador is classified as Critically Endangered. Before 2015, standardized and systematic estimates of geographic distribution, population size and structure were not available for this species, hampering the assessment of its current status and hindering the design and implementation of effective conservation actions. In this study, we performed the first quantitative assessment of geographic distribution, population size and population viability of Andean Condor in Ecuador. We used a methodological approach that included an ecological niche model to study geographic distribution, a simultaneous survey of 70 roosting sites to estimate population size and a population viability analysis (PVA) for the next 100 years. Geographic distribution in the form of extent of occurrence was 49 725 km2. During a two-day census, 93 Andean Condors were recorded and a population of 94 to 102 individuals was estimated. In this population, adult-to-immature ratio was 1:0.5. In the modeled PVA scenarios, the probability of extinction, mean time to extinction and minimum population size varied from zero to 100%, 63 years and 193 individuals, respectively. Habitat loss is the greatest threat to the conservation of Andean Condor populations in Ecuador. Population size reduction in scenarios that included habitat loss began within the first 15 years of this threat. Population reinforcement had no effects on the recovery of Andean Condor populations given the current status of the species in Ecuador. The population size estimate presented in this study is the lower than those reported previously in other countries where the species occur. The inferences derived from the population viability analysis have implications for Condor management in Ecuador. This study highlights the need to redirect efforts from captive breeding and population reinforcement to habitat conservation.

  6. Geographical Detector Model for Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia, China

    Directory of Open Access Journals (Sweden)

    Rina Wu

    2016-02-01

    Full Text Available Studying the influencing factors of carbon dioxide emissions is not only practically but also theoretically crucial for establishing regional carbon-reduction policies, developing low-carbon economy and solving the climate problems. Therefore, we used a geographical detector model which is consists of four parts, i.e., risk detector, factor detector, ecological detector and interaction detector to analyze the effect of these social economic factors, i.e., GDP, industrial structure, urbanization rate, economic growth rate, population and road density on the increase of energy consumption carbon dioxide emissions in industrial sector in Inner Mongolia northeast of China. Thus, combining with the result of four detectors, we found that GDP and population more influence than economic growth rate, industrial structure, urbanization rate and road density. The interactive effect of any two influencing factors enhances the increase of the carbon dioxide emissions. The findings of this research have significant policy implications for regions like Inner Mongolia.

  7. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Asymptotic behaviour of a nonlinear model for the geographic diffusion of infections diseases

    International Nuclear Information System (INIS)

    Kirane, M.; Kouachi, S.

    1994-01-01

    In this paper a nonlinear diffusion model for the geographical spread of infective diseases is studied. In addition to proving well-posedness of the associated initial-boundary value problem, the large time behaviour is analyzed. (author). 4 refs

  9. Credit Risk Modeling

    DEFF Research Database (Denmark)

    Lando, David

    Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers...... and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand...

  10. Validity of covariance models for the analysis of geographical variation

    DEFF Research Database (Denmark)

    Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio

    2014-01-01

    1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained att...

  11. A geographical model of radio-frequency power density around mobile phone masts

    International Nuclear Information System (INIS)

    Briggs, David; Beale, Linda; Bennett, James; Toledano, Mireille B.; Hoogh, Kees de

    2012-01-01

    Public concern about possible health effects of EMF radiation from mobile phone masts has led to an increase of epidemiological studies and health risk assessments which, in turn, require adequate methods of exposure estimation. Difficulties in exposure modelling are exacerbated both by the complexity of the propagation processes, and the need to obtain estimates for large study populations in order to provide sufficient statistical power to detect or exclude the small relative risks that might exist. Use of geographical information system (GIS) techniques offers the means to make such computations efficiently. This paper describes the development and field validation of a GIS-based exposure model (Geomorf). The model uses a modified Gaussian formulation to represent spatial variations in power densities around mobile phone masts, on the basis of power output, antenna height, tilt and the surrounding propagation environment. Obstruction by topography is allowed for, through use of a visibility function. Model calibration was done using field data from 151 measurement sites (1510 antenna-specific measurements) around a group of masts in a rural location, and 50 measurement sites (658 antenna-specific measurements) in an urban area. Different parameter settings were found to be necessary in urban and rural areas to obtain optimum results. The calibrated models were then validated against independent sets of data gathered from measurement surveys in rural and urban areas, and model performance was compared with that of two commonly used path-loss models (the COST-231 adaptations of the Hata and Walfisch–Ikegami models). Model performance was found to vary somewhat between the rural and urban areas, and at different measurement levels (antenna-specific power density, total power density), but overall gave good estimates (R 2 = 0.641 and 0.615, RMSE = 10.7 and 6.7 dB m at the antenna and site-level respectively). Performance was considerably better than that of both

  12. Assessing the risk for suicide in schizophrenia according to migration, ethnicity and geographical ancestry.

    Science.gov (United States)

    Hettige, Nuwan C; Bani-Fatemi, Ali; Kennedy, James L; De Luca, Vincenzo

    2017-02-09

    Suicide is a leading cause of mortality among those afflicted by schizophrenia. Previous studies demonstrated that the stressors associated with immigration may lead to an onset of schizophrenia and suicide separately in susceptible individuals. However, no studies have shown whether immigration may lead to suicidal behaviour for individuals with schizophrenia. Our study proposes that an individual's geographical ancestry, ethnicity or migration status may be predictive of suicide risk in schizophrenia. In a sample of 276 participants with schizophrenia spectrum disorders, we conducted cross-sectional assessments to collect clinical information. Self-identified ethnicity and suicide history were collected through self-report questionnaires and interview-based scales. Ancestry was identified using 292 genetic markers from HapMap. Migrants were classified as those who immigrated to Canada during their lifetime. Using a regression analysis, we tested whether a history of migration, ethnicity or geographical ancestry were predictive of a history of suicide attempts. Our analysis failed to demonstrate a significant relationship between suicide history and migration, ethnicity or ancestry. However, ethnicity appears to be significantly associated with the number of psychiatric hospitalizations in our sample. Ethnicity and migration history are not predictive of previous suicide attempts. Ethnicity may be an important demographic factor affecting access to mental health resources and frequency of hospitalizations.

  13. QUALITY INSPECTION AND ANALYSIS OF THREE-DIMENSIONAL GEOGRAPHIC INFORMATION MODEL BASED ON OBLIQUE PHOTOGRAMMETRY

    Directory of Open Access Journals (Sweden)

    S. Dong

    2018-04-01

    Full Text Available In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

  14. Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

    Science.gov (United States)

    Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

    2018-04-01

    In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

  15. A geographic information system forecast model for strategic control of fasciolosis in Ethiopia.

    Science.gov (United States)

    Yilma, J M; Malone, J B

    1998-07-31

    A geographic information system (GIS) forecast model based on moisture and thermal regime was developed to assess the risk of Fasciola hepatica, a temperate species, and its tropical counterpart, Fasciola gigantica, in Ethiopia. Agroecological map zones and corresponding environmental features that control the distribution and abundance of the disease and its snail intermediate hosts were imported from the Food and Agriculture Organization (FAO) Crop Production System Zones (CPSZ) database on east Africa and used to construct a GIS using ATLAS GIS 3.0 software. Base temperatures of 10 degrees C and 16 degrees C were used for F. hepatica and F. gigantica, respectively, to calculate growing degree days in a previously developed climate forecast system that was modified to allow use of monthly climate data values. The model was validated by comparison of risk indices and environmental features to available survey data on fasciolosis. Monthly Fasciola risk indices of four climatic regions in Ethiopia were used to project infection transmission patterns under varying climatic conditions and strategic chemotherapeutic fasciolosis control schemes. Varying degrees of F. hepatica risk occurred in most parts of the country and distinct regional F. hepatica transmission patterns could be identified. In the humid west, cercariae-shedding was predicted to occur from May to October. In the south it occurred from April to May and September to October, depending on the annual abundance of rain. In the north-central and central regions, risk was highest during heavy summer rains and pasture contamination with metacercariae was predicted to occur during August-September, except in wet years, when it may start as early as July and extend up to October. At cooler sites above altitude of 2800 m, completion of an infection cycle may require more than a year. Fasciola gigantica risk was present in the western, southern and north-central regions of the country at altitudes of 1440-2560 m

  16. Spatial distribution and risk factors of influenza in Jiangsu province, China, based on geographical information system

    Directory of Open Access Journals (Sweden)

    Jia-Cheng Zhang

    2014-05-01

    Full Text Available Influenza poses a constant, heavy burden on society. Recent research has focused on ecological factors associated with influenza incidence and has also studied influenza with respect to its geographic spread at different scales. This research explores the temporal and spatial parameters of influenza and identifies factors influencing its transmission. A spatial autocorrelation analysis, a spatial-temporal cluster analysis and a spatial regression analysis of influenza rates, carried out in Jiangsu province from 2004 to 2011, found that influenza rates to be spatially dependent in 2004, 2005, 2006 and 2008. South-western districts consistently revealed hotspots of high-incidence influenza. The regression analysis indicates that railways, rivers and lakes are important predictive environmental variables for influenza risk. A better understanding of the epidemic pattern and ecological factors associated with pandemic influenza should benefit public health officials with respect to prevention and controlling measures during future epidemics.

  17. ABO Blood Type and Stroke Risk: The REasons for Geographic and Racial Differences in Stroke (REGARDS) Study

    Science.gov (United States)

    Zakai, Neil A.; Judd, Suzanne E.; Alexander, Kristine; McClure, Leslie A.; Kissela, Brett M.; Howard, George; Cushman, Mary

    2016-01-01

    Background ABO blood type is an inherited trait associated with coagulation factor levels and vascular outcomes. Objectives To assess the association of blood type with stroke and whether blood type contributes to racial disparities in stroke in the United States. Patients and Methods The REasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited 30,239 participants between 2003-07. Using a case-cohort design, blood type was genotyped in 646 participants with stroke and a 1,104 participant cohort random sample. Cox models adjusting for Framingham stroke risk factors assessed the association of blood type with stroke. Results Over 5.8 years of follow-up, blood types A or B versus type O were not associated with stroke. Blood type AB versus O was associated with an increased risk of stroke (adjusted HR 1.83; 95% CI 1.01, 3.30). The association of blood type AB versus O was greater in those without diabetes (adjusted HR 3.33; 95% CI 1.61, 6.88) than those with diabetes (adjusted HR 0.49; 95% CI 0.17, 1.44) (p-interaction = 0.02). Factor VIII levels accounted for 60% (95% CI 11%, 98%) of the association of AB blood type and stroke risk. Conclusion Blood type AB is associated with an increased risk of stroke that is not attenuated by conventional stroke risk factors and factor VIII levels were associated with 60% of the association. While blood type AB is rare in the U.S. population, it is a significant stroke risk factor and may play an important role in stroke risk in these individuals. PMID:24444093

  18. Geographical distribution of radiation risk unaccountable by direct exposure dose in hiroshima A-bomb victims

    International Nuclear Information System (INIS)

    Tonda, Tetsuji; Satoh, Kenichi; Ohani, Keiko

    2012-01-01

    Death risks due to solid cancer were estimated from region to region where the A-bomb survivors had been actually exposed, to visualize the risk distribution on the map, which resulting in risk regional difference that had been unaccountable by direct exposure dose estimation. Analysis was performed with 3 hazard models of the previous one, + direct exposed dose as a confounding factor and, further, + spatial distance from the explosion point. Subjects were 37,382 A-bomb survivors at Jan. 1, 1970 with known positional coordinate at explosion, followed until Dec. 31, 2009, whose endpoint was set by 4,371 deaths due to cancer except leukemia, cancers of thyroid and breast. Confounding factors in the previous hazard model were sex, age at the exposure, dose and shielding. With the previous model, risk distribution was observed in a concentric circular region around the hypocenter and in an additional west to northwestern suburbs. The latter risk distribution was also seen with the second model in the same region, where dose decreased with -7 powers of the distance. When adjusted with -3 powers of the distance with the third model, the actual risk distribution was found best fitted, indicating the presence of distance-dependent risk. It was suggested that the region exposed to additional dose possibly derived from fallout had been the actual black rainfall area as those regions agreed with each other. (T.T.)

  19. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  20. A growing social network model in geographical space

    Science.gov (United States)

    Antonioni, Alberto; Tomassini, Marco

    2017-09-01

    In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.

  1. Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling

    Directory of Open Access Journals (Sweden)

    Rodrigo Gurgel-Gonçalves

    2012-01-01

    Full Text Available Although Brazil was declared free from Chagas disease transmission by the domestic vector Triatoma infestans, human acute cases are still being registered based on transmission by native triatomine species. For a better understanding of transmission risk, the geographic distribution of Brazilian triatomines was analyzed. Sixteen out of 62 Brazilian species that both occur in >20 municipalities and present synanthropic tendencies were modeled based on their ecological niches. Panstrongylus geniculatus and P. megistus showed broad ecological ranges, but most of the species sort out by the biome in which they are distributed: Rhodnius pictipes and R. robustus in the Amazon; R. neglectus, Triatoma sordida, and T. costalimai in the Cerrado; R. nasutus, P. lutzi, T. brasiliensis, T. pseudomaculata, T. melanocephala, and T. petrocchiae in the Caatinga; T. rubrovaria in the southern pampas; T. tibiamaculata and T. vitticeps in the Atlantic Forest. Although most occurrences were recorded in open areas (Cerrado and Caatinga, our results show that all environmental conditions in the country are favorable to one or more of the species analyzed, such that almost nowhere is Chagas transmission risk negligible.

  2. Modelling social vulnerability in sub-Saharan West Africa using a geographical information system

    Directory of Open Access Journals (Sweden)

    Olanrewaju Lawal

    2015-05-01

    Full Text Available In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs. Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.

  3. Systems-based modeling of generation variability under alternate geographic configurations of photovoltaic (PV) installations in Virginia

    International Nuclear Information System (INIS)

    Collins, Ross D.; Crowther, Kenneth G.

    2011-01-01

    With increased focus on renewable energy in our modern era, it is increasingly important to understand the impact of policies on the performance and reliability of regional energy systems. This research develops a model to understand how geographic dispersion of PV installations impacts the reliability of electricity generated from the total PV network, measured by the variance of the distribution of generated electricity. Using NREL data, beta probability distributions of sunlight (kWh/m 2 /day) in various regions of Virginia are estimated using a fitting method that minimizes the Kolmogorov-Smirnov test statistic. A Monte Carlo simulation model is developed to measure PV electricity generation from multiple centralized and dispersed configurations over 100,000 days of probabilistic sunlight. There is a calculable tradeoff between average generation and generation variability, and increased geographic dispersion of PV installations can decrease this variability. Controlling variable generation through policies that promote efficient PV siting can help provide reliable power, minimizing the need for load-balancing peaking power infrastructure and costly electricity purchases from the grid. Using a tradeoff framework of generation and costs, this paper shows that geographically dispersed generation can mitigate the risk of unreliable solar generation that can significantly impact the end-user costs and make PV infrastructure unattractive. - Highlights: → We model how uncertain sunlight affects generation of different PV systems. → We show that geographically dispersed systems decrease generation variability. → Geographically dispersed PV systems are potentially more costly in the short run. → Controlling variability provides reliable power, which can decrease long-run costs. → Promoting mixes of uncertain energy sources requires assessment of these tradeoffs.

  4. Model Checking Geographically Distributed Interlocking Systems Using UMC

    DEFF Research Database (Denmark)

    Fantechi, Alessandro; Haxthausen, Anne Elisabeth; Nielsen, Michel Bøje Randahl

    2017-01-01

    the relevant distributed protocols. By doing that we obey the safety guidelines of the railway signalling domain, that require formal methods to support the certification of such products. We also show how formal modelling can help designing alternative distributed solutions, while maintaining adherence...

  5. Modeling social networks in geographic space: approach and empirical application

    NARCIS (Netherlands)

    Arentze, T.A.; Berg, van den P.E.W.; Timmermans, H.J.P.

    2012-01-01

    Social activities are responsible for a large proportion of travel demands of individuals. Modeling of the social network of a studied population offers a basis to predict social travel in a more comprehensive way than currently is possible. In this paper we develop a method to generate a whole

  6. Geographic variation of gallbladder cancer mortality and risk factors in Chile: a population-based ecologic study

    Science.gov (United States)

    Andia, Marcelo E.; Hsing, Ann W.; Andreotti, Gabriella; Ferreccio, Catterina

    2010-01-01

    Chile’s gallbladder cancer rates are among the highest in the world, being the first cancer killer among Chilean women. To provide insights into the etiology of gallbladder cancer, we conducted an ecologic study examining the geographical variation of gallbladder cancer and several putative risk factors. The relative risk of dying from gallbladder cancer (relative to the national average mortality rate) between 1985 and 2003 was estimated for each of the 333 Chilean counties, using a hierarchical Poisson regression model, adjusting for age, sex, and geographical location. The risk of gallbladder cancer mortality was analyzed in relation to region (costal, inland, northern, and southern), poverty, Amerindian (Mapuche) population, typhoid fever, and access to cholecystectomy, using logistic regression analysis. There were 27,183 gallbladder cancer deaths, age-sex-adjusted county mortality rates ranging from 8.2 to 12.4 per 100,000 inhabitants, being higher in inland and southern regions; compare to the north-coastal, the northern-inland region had a 10-fold risk odds ratio (OR) (95% of confidence interval (95% CI): 2.4–42.2) and the southern-inland region had a 26-fold risk (OR 95%CI: 6.0–114.2). Independent risk factors for gallbladder cancer were: ethnicity (Mapuche) OR:3.9 (95%CI 1.8–8.7), typhoid fever OR:2.9 (95%CI 1.2–6.9), poverty OR:5.1 (95%CI 1.6–15.9), low access to cholecystectomy OR:3.9 (95%CI 1.5–10.1), low access to hospital care OR:14.2 (95%CI 4.2–48.7) and high urbanization OR:8.0 (95%CI 3.4–18.7). Our results suggest that gallbladder cancer in Chile may be related to both genetic factors and poor living conditions. Future analytic studies are needed to further clarify the role of these factors in gallbladder cancer etiology. PMID:18566990

  7. Landscape Epidemiology Modeling Using an Agent-Based Model and a Geographic Information System

    Directory of Open Access Journals (Sweden)

    S. M. Niaz Arifin

    2015-05-01

    Full Text Available A landscape epidemiology modeling framework is presented which integrates the simulation outputs from an established spatial agent-based model (ABM of malaria with a geographic information system (GIS. For a study area in Kenya, five landscape scenarios are constructed with varying coverage levels of two mosquito-control interventions. For each scenario, maps are presented to show the average distributions of three output indices obtained from the results of 750 simulation runs. Hot spot analysis is performed to detect statistically significant hot spots and cold spots. Additional spatial analysis is conducted using ordinary kriging with circular semivariograms for all scenarios. The integration of epidemiological simulation-based results with spatial analyses techniques within a single modeling framework can be a valuable tool for conducting a variety of disease control activities such as exploring new biological insights, monitoring epidemiological landscape changes, and guiding resource allocation for further investigation.

  8. Geographical Detector-Based Risk Factors Assessment of the Hand-Foot-Mouth Disease in China

    Science.gov (United States)

    Huang, J.

    2017-12-01

    Background: Hand, foot and mouth disease(HFMD) is a common infectious disease, causing thousands of deaths among children in China. This study focused on analyzing the impacts of different populations and different industry structures on HFMD incidence in China. Methods: We collected HFMD cases from 2307 counties during May 2008 in China. The potential risk factors included: monthly mean temperature, monthly mean relative humidity, monthly precipitation, different population density, different industry structures. Geographical detector technique was used to analyze the main and interactive effect of potential risk factors on HFMD incidence. Result: Using risk detector, we found the most serious HFMD incidence mainly located in the Yangtze River delta and the Pearl River delta. When the temperature was high, the incidence of HFMD was also high. This finding indicates that there is a correlation between monthly mean temperature and the incidence of HFMD. Similar analysis was undertaken to analyze the correlation between other variables and the incidence of HFMD using the risk detector. Using factor detector, we found the effect of risk factors on the incidence of HFMD, and this was ranked by PD value as follows: density of children aged 0-9 years (0.25) > tertiary industry (0.23) > GDP (0.20) >middle school student density (0.13) > relative humidity (0.12) >average temperature (0.11) >first industry (0.05). Using ecological detector, we found that child density, tertiary industry, and GDP had a strong effect on the incidence of HFMD. Using interactive detector, we found that the interactive PD value of tertiary industry and child population density was 0.42, which of GDP and tertiary industry was 0.34, that of child population density and GDP was 0.35, and that of average temperature and relative humidity was 0.28. All of these interactive PD values appeared to be higher than any PD value of sole risk factors. The combinations of the above-mentioned risk factors

  9. HTRA1 variant confers similar risks to geographic atrophy and neovascular age-related macular degeneration.

    Science.gov (United States)

    Cameron, D Joshua; Yang, Zhenglin; Gibbs, Daniel; Chen, Haoyu; Kaminoh, Yuuki; Jorgensen, Adam; Zeng, Jiexi; Luo, Ling; Brinton, Eric; Brinton, Gregory; Brand, John M; Bernstein, Paul S; Zabriskie, Norman A; Tang, Shibo; Constantine, Ryan; Tong, Zongzhong; Zhang, Kang

    2007-05-02

    Age-related macular degeneration (AMD) is the most common cause of irreversible visual impairment in the developed world. The two forms of advanced AMD, geographic atrophy (GA) and choroidal neovascularization (wet AMD), represent two types of degenerative processes in the macula that lead to loss of central vision. Soft confluent drusen, characterized by deposits in macula without visual loss are considered a precursor of advanced AMD. A single nucleotide polymorphism, rs11200638, in the promoter of HTRA1 has been shown to increases the risk for wet AMD. However, its impact on soft confluent drusen and GA or the relationship between them is unclear. To better understand the role the HTRA1 polymorphism plays in AMD subtypes, we genotyped an expanded Utah population with 658 patients having advanced AMD or soft confluent drusen and 294 normal controls and found that the rs11200638 was significantly associated with GA. This association remains significant conditional on LOC387715 rs10490924. In addition, rs11200638 was significantly associated with soft confluent drusen, which are strongly immunolabeled with HTRA1 antibody in an AMD eye with GA similar to wet AMD. Two-locus analyses were performed for CFH Y402H variant at 1q31 and the HTRA1 polymorphism. Together CFH and HTRA1 risk variants increase the odds of having AMD by more than 40 times. These findings expand the role of HTRA1 in AMD. Understanding the underlying molecular mechanism will provide an important insight in pathogenesis of AMD.

  10. Design and Establishment of Quality Model of Fundamental Geographic Information Database

    Science.gov (United States)

    Ma, W.; Zhang, J.; Zhao, Y.; Zhang, P.; Dang, Y.; Zhao, T.

    2018-04-01

    In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

  11. Models of Credit Risk Measurement

    OpenAIRE

    Hagiu Alina

    2011-01-01

    Credit risk is defined as that risk of financial loss caused by failure by the counterparty. According to statistics, for financial institutions, credit risk is much important than market risk, reduced diversification of the credit risk is the main cause of bank failures. Just recently, the banking industry began to measure credit risk in the context of a portfolio along with the development of risk management started with models value at risk (VAR). Once measured, credit risk can be diversif...

  12. A Review on Applications of Remote Sensing and Geographic Information Systems (GIS in Water Resources and Flood Risk Management

    Directory of Open Access Journals (Sweden)

    Xianwei Wang

    2018-05-01

    Full Text Available Water is one of the most critical natural resources that maintain the ecosystem and support people’s daily life. Pressures on water resources and disaster management are rising primarily due to the unequal spatial and temporal distribution of water resources and pollution, and also partially due to our poor knowledge about the distribution of water resources and poor management of their usage. Remote sensing provides critical data for mapping water resources, measuring hydrological fluxes, monitoring drought and flooding inundation, while geographic information systems (GIS provide the best tools for water resources, drought and flood risk management. This special issue presents the best practices, cutting-edge technologies and applications of remote sensing, GIS and hydrological models for water resource mapping, satellite rainfall measurements, runoff simulation, water body and flood inundation mapping, and risk management. The latest technologies applied include 3D surface model analysis and visualization of glaciers, unmanned aerial vehicle (UAV video image classification for turfgrass mapping and irrigation planning, ground penetration radar for soil moisture estimation, the Tropical Rainfall Measuring Mission (TRMM and the Global Precipitation Measurement (GPM satellite rainfall measurements, storm hyetography analysis, rainfall runoff and urban flooding simulation, and satellite radar and optical image classification for urban water bodies and flooding inundation. The application of those technologies is expected to greatly relieve the pressures on water resources and allow better mitigation of and adaptation to the disastrous impact of droughts and flooding.

  13. Circulation of HIV antigen in blood according to stage of infection, risk group, age and geographic origin

    NARCIS (Netherlands)

    Goudsmit, J.; Paul, D. A.

    1987-01-01

    Human immunodeficiency virus antigen (HIV-ag) was determined by enzyme immunoassay (EIA) in HIV-antibody (anti-HIV) positive as well as pre-anti-HIV seroconversion sera and the results analysed according to stage of infection, risk group, age and geographic origin. Eleven (19%) of 58 homosexual men

  14. Geographical Detector-Based Identification of the Impact of Major Determinants on Aeolian Desertification Risk.

    Science.gov (United States)

    Du, Ziqiang; Xu, Xiaoming; Zhang, Hong; Wu, Zhitao; Liu, Yong

    2016-01-01

    Arid and semi-arid areas in North China are facing the challenge of a rising aeolian desertification risk (ADR) due to the intertwined effects of complex natural processes and intensified anthropogenic activities. An accurate quantitative assessment of the relationship between ADR and its determinants is beneficial for understanding the driving mechanisms of aeolian desertification and for controlling future desertification. Previous studies have failed to quantify the relative role of determinants driving ADR and have been limited in assessing their interactive impacts. In this study, a spatial variance analysis-based geographical detector methodology is used to quantify the effects of geological, physical, and human factors on the occurrence of ADR in an area characterized by mountains and hills in northern China. It is found that soil type, precipitation, and wind velocity are the major determinants of ADR, which implies that geological and physical elements (e.g., soil attribute) and climatic factors (e.g., precipitation and wind velocity) rather than human activities have played a greater role in the incidence of ADR. Particularly, the results show that the interaction of various determinants causes significant non-linearly enhanced impacts on the ADR. The findings of our study will assist local inhabitants and policy makers in developing measures for wind prevention and sand control to mitigate the effects of desertification in the region.

  15. What to expect from a greater geographic dispersion of wind farms?-A risk portfolio approach

    International Nuclear Information System (INIS)

    Drake, Ben; Hubacek, Klaus

    2007-01-01

    The UK, like many other industrialised countries, is committed to reducing greenhouse gas emissions under the Kyoto Protocol. To achieve this goal the UK is increasingly turning towards wind power as a source of emissions free energy. However, the variable nature of wind power generation makes it an unreliable energy source, especially at higher rates of penetration. Likewise the aim of this paper is to measure the potential reduction in wind power variability that could be realised as a result of geographically dispersing the location of wind farm sites. To achieve this aim wind speed data will be used to simulate two scenarios. The first scenario involves locating a total of 2.7 gigawatts (GW) of wind power capacity in a single location within the UK while the second scenario consists of sharing the same amount of capacity amongst four different locations. A risk portfolio approach as used in financial appraisals is then applied in the second scenario to decide upon the allocation of wind power capacity, amongst the four wind farm sites, that succeeds in minimising overall variability for a given level of wind power generation. The findings of this paper indicate that reductions in the order of 36% in wind power variability are possible as a result of distributing wind power capacity

  16. NATURAL AND ANTHROPIC RISK STUDIES IN FOUR DECADES IN THE GEOGRAPHICAL JOURNAL OF CENTRAL AMERICA (1974 - 2015)

    OpenAIRE

    Quesada-Román, Adolfo

    2017-01-01

    The aim of this work is to identify the influence of the international and national epistemological trends and the techniques in the risk management of disasters (RMD) in Costa Rica. To do this, the journal papers of the Geographical Journal of Central America between 1974 and 2015 were analyzed -114 included topics related to natural and anthropogenic risks. They were classified into eight thematic classes: seismic hazards, volcanic hazards, slope processes hazards, hydrometeorological hazar...

  17. Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

    Science.gov (United States)

    Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

    2017-11-01

    Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.

  18. Determinants of the geographical distribution of endemic giardiasis in Ontario, Canada: a spatial modelling approach.

    Science.gov (United States)

    Odoi, A; Martin, S W; Michel, P; Holt, J; Middleton, D; Wilson, J

    2004-10-01

    Giardiasis surveillance data as well as drinking water, socioeconomic and land-use data were used in spatial regression models to investigate determinants of the geographic distribution of endemic giardiasis in southern Ontario. Higher giardiasis rates were observed in areas using surface water [rate ratio (RR) 2.36, 95 % CI 1.38-4.05] and in rural areas (RR 1.79, 95 % CI 1.32-2.37). Lower rates were observed in areas using filtered water (RR 0.55, 95 % CI 0.42-0.94) and in those with high median income (RR 0.62, 95 % CI 0.42-0.92). Chlorination of drinking water, cattle density and intensity of manure application on farmland were not significant determinants. The study shows that waterborne transmission plays an important role in giardiasis distribution in southern Ontario and that well-collected routine surveillance data could be useful for investigation of disease determinants and identification of high-risk communities. This information is useful in guiding decisions on control strategies.

  19. Geographic differences in the associations between impaired glucose regulation and cardiovascular risk factors among young adults

    DEFF Research Database (Denmark)

    Oya, J.; Vistisen, D.; Christensen, Dirk Lund

    2015-01-01

    AIMS: To assess geographic differences in the association between BMI, blood pressure and lipid levels with impaired glucose regulation among young adults from various geographical regions. METHODS: This was a cross-sectional study including data from 6987 participants aged ≤ 30 years from India,...

  20. Integrating Geographical Information Systems (GIS) with Hydrological Modelling – Applicability and Limitations

    OpenAIRE

    Rajesh VijayKumar Kherde; Dr. Priyadarshi. H. Sawant

    2013-01-01

    The evolution of Geographic information systems (GIS) facilitated the use digital terrain data for topography based hydrological modelling. The use of spatial data for hydrological modelling emerged from the great capability of GIS tools to store and handle the data associated hydro-morphology of the basin. These models utilize the spatially variable terrain data for converting rainfall into surface runoff.Manual map manipulation has always posed difficulty in analysing and designing large sc...

  1. A framework to specify agent-based models in geographic sciences

    OpenAIRE

    Grueau, Cédric; Araújo, João

    2015-01-01

    Agent-Based Modeling (ABM) and simulation have gained popularity in the Geographic Information Systems (GIS) domain. Despite the increasing number of models built by experts and users, it remains challenging for users to specify their models in a manner in which one can understand it. This constraint represents an inhibition to the development and acceptance of the ABM approach. In this paper, we raise the questions that need to be answered in order to cope with ABM specification issues. We r...

  2. Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland.

    Science.gov (United States)

    Skelsey, Peter; Cooke, David E L; Lynott, James S; Lees, Alison K

    2016-11-01

    The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop-growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO 2 emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change-driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective. © 2016 John Wiley & Sons Ltd.

  3. Identifying Geographic Areas at Risk of Soil-transmitted Helminthes Infection Using Remote Sensing and Geographical Information Systems: Boaco, Nicaragua as a Case Study

    Science.gov (United States)

    Moreno, Max J.; Al-Hamdan, Mohammad Z.; Parajon, David G.; Rickman, Douglas L.; Luvall, Jeffrey; Estes, Sue; Podest, Erika

    2011-01-01

    Several types of intestinal nematodes, that can infect humans and specially school-age children living in poverty, develop part of their life cycle in soil. Presence and survival of these parasites in the soil depend on given environmental characteristics like temperature and moisture that can be inferred with remote sensing (RS) technology. Prevalence of diseases caused by these parasitic worms can be controlled and even eradicated with anthelmintic drug treatments and sanitation improvement. Reliable and updated identification of geographic areas at risk is required to implement effective public health programs; to calculate amount of drug required and to distribute funding for sanitation projects. RS technology and geographical information systems (GIS) will be used to analyze for associations between in situ prevalence and remotely sensed data in order to establish RS proxies of environmental parameters that indicate the presence of these parasits. In situ data on helminthisasis will be overlaid over an ecological map derived from RS data using ARC Map 9.3 (ESRI). Temperature, vegetation, and distance to bodies of water will be inferred using data from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat TM and ETM+. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections are determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). This study will demonstrate the importance of an integrated GIS/RS approach to define clusters and areas at risk. Such information will help to the implementation of time and cost efficient control programs and sanitation efforts.

  4. Geographic distribution of risk of death due to homicide in Puerto Rico, 2001-2010.

    Science.gov (United States)

    Zavala-Zegarra, Diego E; López-Charneco, Magdalena; Garcia-Rivera, Enid J; Concha-Eastman, Alberto; Rodriguez, José F; Conte-Miller, María

    2012-11-01

    To raise awareness of the impact of homicides in Puerto Rico based on the findings of the spatial and temporal distribution of homicides and the use of firearms, by age and gender, using reports of interpersonal violent deaths from the Institute of Forensic Science (IFS) headquartered in San Juan, Puerto Rico. This was a descriptive study of all homicide incidents in Puerto Rico reported by the IFS for the period 2001-2010. For each of the 8 542 cases, data analyzed included age, sex, municipality of incident, date of death, and mechanism. Crude sex- and age-specific mortality rates for Puerto Rico and for each municipality per year and for the 10-year period were calculated. Cumulative rate and cumulative risks were estimated and defined as lifetime risk. The relative distribution of cumulative rates for each municipality was categorized into quartiles of highest to lowest risk and displayed as a map. The risk of homicide death among males is 13 times greater than among females. The highest rates were observed among males 20-24 years of age (198.4 homicides per 100 000). In any given year, firearms were used in at least 80% of homicides. The average lifetime risk of homicide death for males is 1 in 34. Young adult males with access to firearms are at greatest risk of homicide in Puerto Rico. Also, highly urbanized municipalities are at highest risk; however, certain non-urban municipalities along the coast also have a very high homicide risk. Top priorities should be applying the WHO "ecological model" for violent injury prevention and establishing a surveillance system that will assist in identifying the role that socioeconomics, illegal firearms trade, and drug trafficking are playing.

  5. Global potential for carbon sequestration. Geographical distribution, country risk and policy implications

    International Nuclear Information System (INIS)

    Benitez, Pablo C.; McCallum, Ian; Obersteiner, Michael; Yamagata, Yoshiki

    2007-01-01

    We have provided a framework for identifying least-cost sites for afforestation and reforestation and deriving carbon sequestration cost curves at a global level in a scenario of limited information. Special attention is given to country risk in developing countries and the sensitivity to spatial datasets. Our model results suggest that within 20 years and considering a carbon price of USD 50/tC, tree-planting activities could offset 1 year of global carbon emissions in the energy sector. However, if we account for country risk considerations-associated with political, economic and financial risks - carbon sequestration is reduced by approximately 60%. With respect to the geography of supply, illustrated by grid-scale maps, we find that most least-cost sites are located in regions of developing countries such as the Sub-Sahara, Southeast Brazil and Southeast Asia. (author)

  6. The distance-decay function of geographical gravity model: Power law or exponential law?

    International Nuclear Information System (INIS)

    Chen, Yanguang

    2015-01-01

    Highlights: •The distance-decay exponent of the gravity model is a fractal dimension. •Entropy maximization accounts for the gravity model based on power law decay. •Allometric scaling relations relate gravity models with spatial interaction models. •The four-parameter gravity models have dual mathematical expressions. •The inverse power law is the most probable distance-decay function. -- Abstract: The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be reasonably explained with the ideas from Euclidean geometry. This results in a dimension dilemma in geographical analysis. Consequently, a negative exponential function was used to replace the inverse power function to serve for a distance-decay function. But a new puzzle arose that the exponential-based gravity model goes against the first law of geography. This paper is devoted for solving these kinds of problems by mathematical reasoning and empirical analysis. New findings are as follows. First, the distance exponent of the gravity model is demonstrated to be a fractal dimension using the geometric measure relation. Second, the similarities and differences between the gravity models and spatial interaction models are revealed using allometric relations. Third, a four-parameter gravity model possesses a symmetrical expression, and we need dual gravity models to describe spatial flows. The observational data of China's cities and regions (29 elements indicative of 841 data points) in 2010 are employed to verify the theoretical inferences. A conclusion can be reached that the geographical gravity model based on power-law decay is more suitable for analyzing large, complex, and scale-free regional and urban systems. This study lends further support to the suggestion that the underlying rationale of fractal structure is entropy maximization. Moreover

  7. The loss of species: mangrove extinction risk and geographic areas of global concern.

    Directory of Open Access Journals (Sweden)

    Beth A Polidoro

    2010-04-01

    Full Text Available Mangrove species are uniquely adapted to tropical and subtropical coasts, and although relatively low in number of species, mangrove forests provide at least US $1.6 billion each year in ecosystem services and support coastal livelihoods worldwide. Globally, mangrove areas are declining rapidly as they are cleared for coastal development and aquaculture and logged for timber and fuel production. Little is known about the effects of mangrove area loss on individual mangrove species and local or regional populations. To address this gap, species-specific information on global distribution, population status, life history traits, and major threats were compiled for each of the 70 known species of mangroves. Each species' probability of extinction was assessed under the Categories and Criteria of the IUCN Red List of Threatened Species. Eleven of the 70 mangrove species (16% are at elevated threat of extinction. Particular areas of geographical concern include the Atlantic and Pacific coasts of Central America, where as many as 40% of mangroves species present are threatened with extinction. Across the globe, mangrove species found primarily in the high intertidal and upstream estuarine zones, which often have specific freshwater requirements and patchy distributions, are the most threatened because they are often the first cleared for development of aquaculture and agriculture. The loss of mangrove species will have devastating economic and environmental consequences for coastal communities, especially in those areas with low mangrove diversity and high mangrove area or species loss. Several species at high risk of extinction may disappear well before the next decade if existing protective measures are not enforced.

  8. The loss of species: mangrove extinction risk and geographic areas of global concern.

    Science.gov (United States)

    Polidoro, Beth A; Carpenter, Kent E; Collins, Lorna; Duke, Norman C; Ellison, Aaron M; Ellison, Joanna C; Farnsworth, Elizabeth J; Fernando, Edwino S; Kathiresan, Kandasamy; Koedam, Nico E; Livingstone, Suzanne R; Miyagi, Toyohiko; Moore, Gregg E; Ngoc Nam, Vien; Ong, Jin Eong; Primavera, Jurgenne H; Salmo, Severino G; Sanciangco, Jonnell C; Sukardjo, Sukristijono; Wang, Yamin; Yong, Jean Wan Hong

    2010-04-08

    Mangrove species are uniquely adapted to tropical and subtropical coasts, and although relatively low in number of species, mangrove forests provide at least US $1.6 billion each year in ecosystem services and support coastal livelihoods worldwide. Globally, mangrove areas are declining rapidly as they are cleared for coastal development and aquaculture and logged for timber and fuel production. Little is known about the effects of mangrove area loss on individual mangrove species and local or regional populations. To address this gap, species-specific information on global distribution, population status, life history traits, and major threats were compiled for each of the 70 known species of mangroves. Each species' probability of extinction was assessed under the Categories and Criteria of the IUCN Red List of Threatened Species. Eleven of the 70 mangrove species (16%) are at elevated threat of extinction. Particular areas of geographical concern include the Atlantic and Pacific coasts of Central America, where as many as 40% of mangroves species present are threatened with extinction. Across the globe, mangrove species found primarily in the high intertidal and upstream estuarine zones, which often have specific freshwater requirements and patchy distributions, are the most threatened because they are often the first cleared for development of aquaculture and agriculture. The loss of mangrove species will have devastating economic and environmental consequences for coastal communities, especially in those areas with low mangrove diversity and high mangrove area or species loss. Several species at high risk of extinction may disappear well before the next decade if existing protective measures are not enforced.

  9. A Geographic Information System approach to modeling nutrient and sediment transport

    Energy Technology Data Exchange (ETDEWEB)

    Levine, D.A. [Automated Sciences Group, Inc., Oak Ridge, TN (United States); Hunsaker, C.T.; Beauchamp, J.J. [Oak Ridge National Lab., TN (United States); Timmins, S.P. [Analysas Corp., Oak Ridge, TN (United States)

    1993-02-01

    The objective of this study was to develop a water quality model to quantify nonpoint-source (NPS) pollution that uses a geographic information system (GIS) to link statistical modeling of nutrient and sediment delivery with the spatial arrangement of the parameters that drive the model. The model predicts annual nutrient and sediment loading and was developed, calibrated, and tested on 12 watersheds within the Lake Ray Roberts drainage basin in north Texas. Three physiographic regions are represented by these watersheds, and model success, as measured by the accuracy of load estimates, was compared within and across these regions.

  10. Application of a random walk model to geographic distributions of animal mitochondrial DNA variation.

    Science.gov (United States)

    Neigel, J E; Avise, J C

    1993-12-01

    In rapidly evolving molecules, such as animal mitochondrial DNA, mutations that delineate specific lineages may not be dispersed at sufficient rates to attain an equilibrium between genetic drift and gene flow. Here we predict conditions that lead to nonequilibrium geographic distributions of mtDNA lineages, test the robustness of these predictions and examine mtDNA data sets for consistency with our model. Under a simple isolation by distance model, the variance of an mtDNA lineage's geographic distribution is expected be proportional to its age. Simulation results indicated that this relationship is fairly robust. Analysis of mtDNA data from natural populations revealed three qualitative distributional patterns: (1) significant departure of lineage structure from equilibrium geographic distributions, a pattern exhibited in three rodent species with limited dispersal; (2) nonsignificant departure from equilibrium expectations, exhibited by two avian and two marine fish species with potentials for relatively long-distance dispersal; and (3) a progression from nonequilibrium distributions for younger lineages to equilibrium distributions for older lineages, a condition displayed by one surveyed avian species. These results demonstrate the advantages of considering mutation and genealogy in the interpretation of mtDNA geographic variation.

  11. Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses.

    Directory of Open Access Journals (Sweden)

    Deverick J Anderson

    Full Text Available The rate of community-acquired Clostridium difficile infection (CA-CDI is increasing. While receipt of antibiotics remains an important risk factor for CDI, studies related to acquisition of C. difficile outside of hospitals are lacking. As a result, risk factors for exposure to C. difficile in community settings have been inadequately studied.To identify novel environmental risk factors for CA-CDI.We performed a population-based retrospective cohort study of patients with CA-CDI from 1/1/2007 through 12/31/2014 in a 10-county area in central North Carolina. 360 Census Tracts in these 10 counties were used as the demographic Geographic Information System (GIS base-map. Longitude and latitude (X, Y coordinates were generated from patient home addresses and overlaid to Census Tracts polygons using ArcGIS; ArcView was used to assess "hot-spots" or clusters of CA-CDI. We then constructed a mixed hierarchical model to identify environmental variables independently associated with increased rates of CA-CDI.A total of 1,895 unique patients met our criteria for CA-CDI. The mean patient age was 54.5 years; 62% were female and 70% were Caucasian. 402 (21% patient addresses were located in "hot spots" or clusters of CA-CDI (p<0.001. "Hot spot" census tracts were scattered throughout the 10 counties. After adjusting for clustering and population density, age ≥ 60 years (p = 0.03, race (<0.001, proximity to a livestock farm (0.01, proximity to farming raw materials services (0.02, and proximity to a nursing home (0.04 were independently associated with increased rates of CA-CDI.Our study is the first to use spatial statistics and mixed models to identify important environmental risk factors for acquisition of C. difficile and adds to the growing evidence that farm practices may put patients at risk for important drug-resistant infections.

  12. Transmission tower classification based on landslide risk map generated by Geographical Information System (GIS) at Cameron Highlands

    International Nuclear Information System (INIS)

    Hazwani N K; Rohayu C O; Fathoni U; Baharuddin, Inz

    2013-01-01

    Transmission tower is usually locates at remote area which is covered by hilly topography. Landslide is mainly occurring at hilly area and causing failure to the tower structure. This phenomenon subsequently will affect the national electricity supply. A landslide risk hazard map is generated using Geographical Information System (GIS). Risk classification is introduced to initiate the monitoring process along Jor-Bintang transmission line, Cameron Highland, Pahang. The classification has been divided into three categories, which are low, medium and high. This method can be applied in slope monitoring activities since all towers have been classified based on their risk level. Therefore, maintenance schedule can be planned smoothly and efficiently.

  13. Transmission tower classification based on landslide risk Map generated by Geographical Information System (GIS) at Cameron Highlands

    International Nuclear Information System (INIS)

    Hazwani N K; Rohayu C O; Fathoni U; Baharuddin, I N Z; Azwin Z A

    2013-01-01

    Transmission tower is usually locates at remote area which is covered by hilly topography. Landslide is mainly occurring at hilly area and causing failure to the tower structure. This phenomenon subsequently will affect the national electricity supply. A landslide risk hazard map is generated using Geographical Information System (GIS). Risk classification is introduced to initiate the monitoring process along Jor-Bintang transmission line, Cameron Highland, Pahang. The classification has been divided into three categories, which are low, medium and high. This method can be applied in slope monitoring activities since all towers have been classified based on their risk level. Therefore, maintenance schedule can be planned smoothly and efficiently.

  14. Exploring geographic distributions of high-risk water, sanitation, and hygiene practices and their association with child diarrhea in Uganda

    Directory of Open Access Journals (Sweden)

    Mitsuaki Hirai

    2016-10-01

    Full Text Available Background: High-risk water, sanitation, and hygiene (WASH practices are still prevalent in most low-income countries. Because of limited access to WASH, children may be put at an increased risk of diarrheal diseases. Objectives: This study aims to 1 develop a new measure of WASH-induced burden, the WASH Resource Index (WRI, and estimate its correlation with child diarrhea and an additive index of high-risk WASH practices; 2 explore the geographic distribution of high-risk WASH practices, child diarrhea, and summary indices at the cluster level; and 3 examine the association between the WRI and child diarrhea at the individual level. Design: A sample of 7,019 children from the Uganda Demographic and Health Survey 2011 were included in this study. Principal component analysis was used to develop a WRI, and households were classified as WASH poorest, poorer, middle, richer, and richest. A hot spot analysis was conducted to assess whether and how high-risk WASH practices and child diarrhea were geographically clustered. A potential association between the WRI and child diarrhea was examined through a nested regression analysis. Results: High-risk WASH practices were clustered at geographically distant regions from Kampala. The 2-week prevalence of child diarrhea, however, was concentrated in Eastern and East Central regions where high-risk WASH practices were not prevalent. At the individual level, none of the high-risk WASH practices were significantly associated with child diarrhea. Being in the highest WASH quintile was, however, significantly associated with 24.9% lower prevalence of child diarrhea compared to being in the lowest quintile (p<0.05. Conclusions: Only a weak association was found between the WRI and child diarrhea in this study. Future research should explore the potential utility of the WRI to examine WASH-induced burden.

  15. Russian and Foreign Experience of Integration of Agent-Based Models and Geographic Information Systems

    Directory of Open Access Journals (Sweden)

    Konstantin Anatol’evich Gulin

    2016-11-01

    Full Text Available The article provides an overview of the mechanisms of integration of agent-based models and GIS technology developed by Russian and foreign researchers. The basic framework of the article is based on critical analysis of domestic and foreign literature (monographs, scientific articles. The study is based on the application of universal scientific research methods: system approach, analysis and synthesis, classification, systematization and grouping, generalization and comparison. The article presents theoretical and methodological bases of integration of agent-based models and geographic information systems. The concept and essence of agent-based models are explained; their main advantages (compared to other modeling methods are identified. The paper characterizes the operating environment of agents as a key concept in the theory of agent-based modeling. It is shown that geographic information systems have a wide range of information resources for calculations, searching, modeling of the real world in various aspects, acting as an effective tool for displaying the agents’ operating environment and allowing to bring the model as close as possible to the real conditions. The authors also focus on a wide range of possibilities for various researches in different spatial and temporal contexts. Comparative analysis of platforms supporting the integration of agent-based models and geographic information systems has been carried out. The authors give examples of complex socio-economic models: the model of a creative city, humanitarian assistance model. In the absence of standards for research results description, the authors focus on the models’ elements such as the characteristics of the agents and their operation environment, agents’ behavior, rules of interaction between the agents and the external environment. The paper describes the possibilities and prospects of implementing these models

  16. Hospital distribution in a metropolitan city: assessment by a geographical information system grid modelling approach

    Directory of Open Access Journals (Sweden)

    Kwang-Soo Lee

    2014-05-01

    Full Text Available Grid models were used to assess urban hospital distribution in Seoul, the capital of South Korea. A geographical information system (GIS based analytical model was developed and applied to assess the situation in a metropolitan area with a population exceeding 10 million. Secondary data for this analysis were obtained from multiple sources: the Korean Statistical Information Service, the Korean Hospital Association and the Statistical Geographical Information System. A grid of cells measuring 1 × 1 km was superimposed on the city map and a set of variables related to population, economy, mobility and housing were identified and measured for each cell. Socio-demographic variables were included to reflect the characteristics of each area. Analytical models were then developed using GIS software with the number of hospitals as the dependent variable. Applying multiple linear regression and geographically weighted regression models, three factors (highway and major arterial road areas; number of subway entrances; and row house areas were statistically significant in explaining the variance of hospital distribution for each cell. The overall results show that GIS is a useful tool for analysing and understanding location strategies. This approach appears a useful source of information for decision-makers concerned with the distribution of hospitals and other health care centres in a city.

  17. Robust geographically weighted regression of modeling the Air Polluter Standard Index (APSI)

    Science.gov (United States)

    Warsito, Budi; Yasin, Hasbi; Ispriyanti, Dwi; Hoyyi, Abdul

    2018-05-01

    The Geographically Weighted Regression (GWR) model has been widely applied to many practical fields for exploring spatial heterogenity of a regression model. However, this method is inherently not robust to outliers. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression model. One of solution to handle the outliers in the regression model is to use the robust models. So this model was called Robust Geographically Weighted Regression (RGWR). This research aims to aid the government in the policy making process related to air pollution mitigation by developing a standard index model for air polluter (Air Polluter Standard Index - APSI) based on the RGWR approach. In this research, we also consider seven variables that are directly related to the air pollution level, which are the traffic velocity, the population density, the business center aspect, the air humidity, the wind velocity, the air temperature, and the area size of the urban forest. The best model is determined by the smallest AIC value. There are significance differences between Regression and RGWR in this case, but Basic GWR using the Gaussian kernel is the best model to modeling APSI because it has smallest AIC.

  18. Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia.

    Science.gov (United States)

    Chammartin, Frédérique; Scholte, Ronaldo G C; Malone, John B; Bavia, Mara E; Nieto, Prixia; Utzinger, Jürg; Vounatsou, Penelope

    2013-05-25

    The prevalence of infection with the three common soil-transmitted helminths (i.e. Ascaris lumbricoides, Trichuris trichiura, and hookworm) in Bolivia is among the highest in Latin America. However, the spatial distribution and burden of soil-transmitted helminthiasis are poorly documented. We analysed historical survey data using Bayesian geostatistical models to identify determinants of the distribution of soil-transmitted helminth infections, predict the geographical distribution of infection risk, and assess treatment needs and costs in the frame of preventive chemotherapy. Rigorous geostatistical variable selection identified the most important predictors of A. lumbricoides, T. trichiura, and hookworm transmission. Results show that precipitation during the wettest quarter above 400 mm favours the distribution of A. lumbricoides. Altitude has a negative effect on T. trichiura. Hookworm is sensitive to temperature during the coldest month. We estimate that 38.0%, 19.3%, and 11.4% of the Bolivian population is infected with A. lumbricoides, T. trichiura, and hookworm, respectively. Assuming independence of the three infections, 48.4% of the population is infected with any soil-transmitted helminth. Empirical-based estimates, according to treatment recommendations by the World Health Organization, suggest a total of 2.9 million annualised treatments for the control of soil-transmitted helminthiasis in Bolivia. We provide estimates of soil-transmitted helminth infections in Bolivia based on high-resolution spatial prediction and an innovative variable selection approach. However, the scarcity of the data suggests that a national survey is required for more accurate mapping that will govern spatial targeting of soil-transmitted helminthiasis control.

  19. A geographic information system-based 3D city estate modeling and simulation system

    Science.gov (United States)

    Chong, Xiaoli; Li, Sha

    2015-12-01

    This paper introduces a 3D city simulation system which is based on geographic information system (GIS), covering all commercial housings of the city. A regional- scale, GIS-based approach is used to capture, describe, and track the geographical attributes of each house in the city. A sorting algorithm of "Benchmark + Parity Rate" is developed to cluster houses with similar spatial and construction attributes. This system is applicable for digital city modeling, city planning, housing evaluation, housing monitoring, and visualizing housing transaction. Finally, taking Jingtian area of Shenzhen as an example, the each unit of 35,997 houses in the area could be displayed, tagged, and easily tracked by the GIS-based city modeling and simulation system. The match market real conditions well and can be provided to house buyers as reference.

  20. The globalization of risk and risk perception: why we need a new model of risk communication for vaccines.

    Science.gov (United States)

    Larson, Heidi; Brocard Paterson, Pauline; Erondu, Ngozi

    2012-11-01

    Risk communication and vaccines is complex and the nature of risk perception is changing, with perceptions converging, evolving and having impacts well beyond specific geographic localities and points in time, especially when amplified through the Internet and other modes of global communication. This article examines the globalization of risk perceptions and their impacts, including the example of measles and the globalization of measles, mumps and rubella (MMR) vaccine risk perceptions, and calls for a new, more holistic model of risk assessment, risk communication and risk mitigation, embedded in an ongoing process of risk management for vaccines and immunization programmes. It envisions risk communication as an ongoing process that includes trust-building strategies hand-in-hand with operational and policy strategies needed to mitigate and manage vaccine-related risks, as well as perceptions of risk.

  1. Custom v. Standardized Risk Models

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-05-01

    Full Text Available We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1 longer horizon risk factors (value, growth, etc. increase noise trades and trading costs; (2 arbitrary risk factors can neutralize alpha; (3 “standardized” industries are artificial and insufficiently granular; (4 normalization of style risk factors is lost for the trading universe; (5 diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building.

  2. A geographically weighted regression model for geothermal potential assessment in mediterranean cultural landscape

    Science.gov (United States)

    D'Arpa, S.; Zaccarelli, N.; Bruno, D. E.; Leucci, G.; Uricchio, V. F.; Zurlini, G.

    2012-04-01

    Geothermal heat can be used directly in many applications (agro-industrial processes, sanitary hot water production, heating/cooling systems, etc.). These applications respond to energetic and environmental sustainability criteria, ensuring substantial energy savings with low environmental impacts. In particular, in Mediterranean cultural landscapes the exploitation of geothermal energy offers a valuable alternative compared to other exploitation systems more land-consuming and visual-impact. However, low enthalpy geothermal energy applications at regional scale, require careful design and planning to fully exploit benefits and reduce drawbacks. We propose a first example of application of a Geographically Weighted Regression (GWR) for the modeling of geothermal potential in the Apulia Region (South Italy) by integrating hydrological (e.g. depth to water table, water speed and temperature), geological-geotechnical (e.g. lithology, thermal conductivity) parameters and land-use indicators. The GWR model can effectively cope with data quality, spatial anisotropy, lack of stationarity and presence of discontinuities in the underlying data maps. The geothermal potential assessment required a good knowledge of the space-time variation of the numerous parameters related to the status of geothermal resource, a contextual analysis of spatial and environmental features, as well as the presence and nature of regulations or infrastructures constraints. We create an ad hoc geodatabase within ArcGIS 10 collecting relevant data and performing a quality assessment. Cross-validation shows high level of consistency of the spatial local models, as well as error maps can depict areas of lower reliability. Based on low enthalpy geothermal potential map created, a first zoning of the study area is proposed, considering four level of possible exploitation. Such zoning is linked and refined by the actual legal constraints acting at regional or province level as enforced by the regional

  3. Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site.

    Science.gov (United States)

    Ndiath, Mansour M; Cisse, Badara; Ndiaye, Jean Louis; Gomis, Jules F; Bathiery, Ousmane; Dia, Anta Tal; Gaye, Oumar; Faye, Babacar

    2015-11-18

    of the district where hotspots are more accurate while low values are mainly found in the centre and in the north. Geographically-weighted regression and OLS showed important risks factors of malaria hotspots in Keur Soce. The outputs of such models can be a useful tool to understand occurrence of malaria hotspots in Senegal. An understanding of geographical variation and determination of the core areas of the disease may provide an explanation regarding possible proximal and distal contributors to malaria elimination in Senegal.

  4. Geographically weighted negative binomial regression applied to zonal level safety performance models.

    Science.gov (United States)

    Gomes, Marcos José Timbó Lima; Cunto, Flávio; da Silva, Alan Ricardo

    2017-09-01

    Generalized Linear Models (GLM) with negative binomial distribution for errors, have been widely used to estimate safety at the level of transportation planning. The limited ability of this technique to take spatial effects into account can be overcome through the use of local models from spatial regression techniques, such as Geographically Weighted Poisson Regression (GWPR). Although GWPR is a system that deals with spatial dependency and heterogeneity and has already been used in some road safety studies at the planning level, it fails to account for the possible overdispersion that can be found in the observations on road-traffic crashes. Two approaches were adopted for the Geographically Weighted Negative Binomial Regression (GWNBR) model to allow discrete data to be modeled in a non-stationary form and to take note of the overdispersion of the data: the first examines the constant overdispersion for all the traffic zones and the second includes the variable for each spatial unit. This research conducts a comparative analysis between non-spatial global crash prediction models and spatial local GWPR and GWNBR at the level of traffic zones in Fortaleza/Brazil. A geographic database of 126 traffic zones was compiled from the available data on exposure, network characteristics, socioeconomic factors and land use. The models were calibrated by using the frequency of injury crashes as a dependent variable and the results showed that GWPR and GWNBR achieved a better performance than GLM for the average residuals and likelihood as well as reducing the spatial autocorrelation of the residuals, and the GWNBR model was more able to capture the spatial heterogeneity of the crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Critical Data Source; Tool or Even Infrastructure? Challenges of Geographic Information Systems and Remote Sensing for Disaster Risk Governance

    Directory of Open Access Journals (Sweden)

    Alexander Fekete

    2015-09-01

    Full Text Available Disaster risk information is spatial in nature and Geographic Information Systems (GIS and Remote Sensing (RS play an important key role by the services they provide to society. In this context, to risk management and governance, in general, and to civil protection, specifically (termed differently in many countries, and includes, for instance: civil contingencies in the UK, homeland security in the USA, disaster risk reduction at the UN level. The main impetus of this article is to summarize key contributions and challenges in utilizing and accepting GIS and RS methods and data for disaster risk governance, which includes public bodies, but also risk managers in industry and practitioners in search and rescue organizations. The article analyzes certain method developments, such as vulnerability indicators, crowdsourcing, and emerging concepts, such as Volunteered Geographic Information, but also investigates the potential of the topic Critical Infrastructure as it could be applied on spatial assets and GIS and RS itself. Intended to stimulate research on new and emerging fields, this article’s main contribution is to move spatial research toward a more reflective stance where opportunities and challenges are equally and transparently addressed in order to gain more scientific quality. As a conclusion, GIS and RS can play a pivotal role not just in delivering data but also in connecting and analyzing data in a more integrative, holistic way.

  6. Model Risk in Portfolio Optimization

    Directory of Open Access Journals (Sweden)

    David Stefanovits

    2014-08-01

    Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.

  7. Application of a geographical information system approach for risk analysis of fascioliasis in southern Espírito Santo state, Brazil.

    Science.gov (United States)

    Martins, Isabella Vilhena Freire; de Avelar, Barbara Rauta; Pereira, Maria Julia Salim; da Fonseca, Adevair Henrique

    2012-09-01

    A model based on geographical information systems for mapping the risk of fascioliasis was developed for the southern part of Espírito Santo state, Brazil. The determinants investigated were precipitation, temperature, elevation, slope, soil type and land use. Weightings and grades were assigned to determinants and their categories according to their relevance with respect to fascioliasis. Theme maps depicting the spatial distribution of risk areas indicate that over 50% of southern Espírito Santo is either at high or at very high risk for fascioliasis. These areas were found to be characterized by comparatively high temperature but relatively low slope, low precipitation and low elevation corresponding to periodically flooded grasslands or soils that promote water retention.

  8. Risk based modelling

    International Nuclear Information System (INIS)

    Chapman, O.J.V.; Baker, A.E.

    1993-01-01

    Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

  9. Advanced model for expansion of natural gas distribution networks based on geographic information systems

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez-Rosado, I.J.; Fernandez-Jimenez, L.A.; Garcia-Garrido, E.; Zorzano-Santamaria, P.; Zorzano-Alba, E. [La Rioja Univ., La Rioja (Spain). Dept. of Electrical Engineering; Miranda, V.; Montneiro, C. [Porto Univ., Porto (Portugal). Faculty of Engineering]|[Inst. de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

    2005-07-01

    An advanced geographic information system (GIS) model of natural gas distribution networks was presented. The raster-based model was developed to evaluate costs associated with the expansion of electrical networks due to increased demand in the La Rioja region of Spain. The model was also used to evaluate costs associated with maintenance and amortization of the already existing distribution network. Expansion costs of the distribution network were modelled in various demand scenarios. The model also considered a variety of technical factors associated with pipeline length and topography. Soil and slope data from previous pipeline projects were used to estimate real costs per unit length of pipeline. It was concluded that results obtained by the model will be used by planners to select zones where expansion is economically feasible. 4 refs., 5 figs.

  10. A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

    Science.gov (United States)

    Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

    2005-01-01

    This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

  11. Modeling of geographical pricing: A game analysis of siberian fuel costs

    Science.gov (United States)

    Sivushina, Anastasiya; Kombu, Anchy; Ryumkin, Valeriy

    2017-11-01

    In the present study, we propose a novel game-theoretic pricing model describing the interaction between producers and retailers of goods in conditions of poor transport infrastructure and sparse geographical distribution of the points of sale. The proposed model generalizes the Stackelberg leadership model for an arbitrary number of leaders and followers. We show that the model always has a Nash and Stackelberg equilibria. We also provide formulas for the equilibrium prices and volume of sales. As an example we model diesel pricing in south Siberia. Our model found no signs of a cartel. The results of this paper can be used by policymakers to inform market regulations aimed at promoting free competition and avoiding monopolies in production and retail of goods.

  12. Indicator 1.07. Number and geographic distribution of forest-associated species at risk of losing genetic variation and locally adapted genotypes

    Science.gov (United States)

    C. H. Flather; M. S Knowles; C. H. Sieg

    2011-01-01

    This indicator provides information on the number and distribution of forest-associated species at risk of losing genetic variation across their geographic range. Comparing a species' current geographic distribution with its historic distribution is the basis for identifying those species whose range has contracted significantly. Human activities are accelerating...

  13. A geographic approach to modelling human exposure to traffic air pollution using GIS. Separate appendix report

    Energy Technology Data Exchange (ETDEWEB)

    Solvang Jensen, S.

    1998-10-01

    A new exposure model has been developed that is based on a physical, single media (air) and single source (traffic) micro environmental approach that estimates traffic related exposures geographically with the postal address as exposure indicator. The micro environments: residence, workplace and street (road user exposure) may be considered. The model estimates outdoor levels for selected ambient air pollutants (benzene, CO, NO{sub 2} and O{sub 3}). The influence of outdoor air pollution on indoor levels can be estimated using average (I/O-ratios. The model has a very high spatial resolution (the address), a high temporal resolution (one hour) and may be used to predict past, present and future exposures. The model may be used for impact assessment of control measures provided that the changes to the model inputs are obtained. The exposure model takes advantage of a standard Geographic Information System (GIS) (ArcView and Avenue) for generation of inputs, for visualisation of input and output, and uses available digital maps, national administrative registers and a local traffic database, and the Danish Operational Street Pollution Model (OSPM). The exposure model presents a new approach to exposure determination by integration of digital maps, administrative registers, a street pollution model and GIS. New methods have been developed to generate the required input parameters for the OSPM model: to geocode buildings using cadastral maps and address points, to automatically generate street configuration data based on digital maps, the BBR and GIS; to predict the temporal variation in traffic and related parameters; and to provide hourly background levels for the OSPM model. (EG)

  14. A geographic approach to modelling human exposure to traffic air pollution using GIS

    Energy Technology Data Exchange (ETDEWEB)

    Solvang Jensen, S.

    1998-10-01

    A new exposure model has been developed that is based on a physical, single media (air) and single source (traffic) micro environmental approach that estimates traffic related exposures geographically with the postal address as exposure indicator. The micro environments: residence, workplace and street (road user exposure) may be considered. The model estimates outdoor levels for selected ambient air pollutants (benzene, CO, NO{sub 2} and O{sub 3}). The influence of outdoor air pollution on indoor levels can be estimated using average (I/O-ratios. The model has a very high spatial resolution (the address), a high temporal resolution (one hour) and may be used to predict past, present and future exposures. The model may be used for impact assessment of control measures provided that the changes to the model inputs are obtained. The exposure model takes advantage of a standard Geographic Information System (GIS) (ArcView and Avenue) for generation of inputs, for visualisation of input and output, and uses available digital maps, national administrative registers and a local traffic database, and the Danish Operational Street Pollution Model (OSPM). The exposure model presents a new approach to exposure determination by integration of digital maps, administrative registers, a street pollution model and GIS. New methods have been developed to generate the required input parameters for the OSPM model: to geocode buildings using cadastral maps and address points, to automatically generate street configuration data based on digital maps, the BBR and GIS; to predict the temporal variation in traffic and related parameters; and to provide hourly background levels for the OSPM model. (EG) 109 refs.

  15. Handbook on advances in remote sensing and geographic information systems paradigms and applications in forest landscape modeling

    CERN Document Server

    Favorskaya, Margarita N

    2017-01-01

    This book presents the latest advances in remote-sensing and geographic information systems and applications. It is divided into four parts, focusing on Airborne Light Detection and Ranging (LiDAR) and Optical Measurements of Forests; Individual Tree Modelling; Landscape Scene Modelling; and Forest Eco-system Modelling. Given the scope of its coverage, the book offers a valuable resource for students, researchers, practitioners, and educators interested in remote sensing and geographic information systems and applications.

  16. Geographical dimensions of risk management : the contribution of spatial planning and Geo-ICT to risk reduction

    NARCIS (Netherlands)

    Neuvel, J.M.M.

    2009-01-01

    Geographical information systems can offer insights into the possibilities for emergency response and the possibilities for self help during a disaster, such as a flooding or explosions. Based on this information, proposed housing areas can be adapted. The building site can be elevated or ‘safe

  17. Wildfire Risk Main Model

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The model combines three modeled fire behavior parameters (rate of spread, flame length, crown fire potential) and one modeled ecological health measure (fire regime...

  18. Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

    Directory of Open Access Journals (Sweden)

    Y. Cao

    2017-09-01

    Full Text Available Most atmospheric models, including the Weather Research and Forecasting (WRF model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studies have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.

  19. A Probabilistic Typhoon Risk Model for Vietnam

    Science.gov (United States)

    Haseemkunju, A.; Smith, D. F.; Brolley, J. M.

    2017-12-01

    Annually, the coastal Provinces of low-lying Mekong River delta region in the southwest to the Red River Delta region in Northern Vietnam is exposed to severe wind and flood risk from landfalling typhoons. On average, about two to three tropical cyclones with a maximum sustained wind speed of >=34 knots make landfall along the Vietnam coast. Recently, Typhoon Wutip (2013) crossed Central Vietnam as a category 2 typhoon causing significant damage to properties. As tropical cyclone risk is expected to increase with increase in exposure and population growth along the coastal Provinces of Vietnam, insurance/reinsurance, and capital markets need a comprehensive probabilistic model to assess typhoon risk in Vietnam. In 2017, CoreLogic has expanded the geographical coverage of its basin-wide Western North Pacific probabilistic typhoon risk model to estimate the economic and insured losses from landfalling and by-passing tropical cyclones in Vietnam. The updated model is based on 71 years (1945-2015) of typhoon best-track data and 10,000 years of a basin-wide simulated stochastic tracks covering eight countries including Vietnam. The model is capable of estimating damage from wind, storm surge and rainfall flooding using vulnerability models, which relate typhoon hazard to building damageability. The hazard and loss models are validated against past historical typhoons affecting Vietnam. Notable typhoons causing significant damage in Vietnam are Lola (1993), Frankie (1996), Xangsane (2006), and Ketsana (2009). The central and northern coastal provinces of Vietnam are more vulnerable to wind and flood hazard, while typhoon risk in the southern provinces are relatively low.

  20. New spatial clustering-based models for optimal urban facility location considering geographical obstacles

    Science.gov (United States)

    Javadi, Maryam; Shahrabi, Jamal

    2014-03-01

    The problems of facility location and the allocation of demand points to facilities are crucial research issues in spatial data analysis and urban planning. It is very important for an organization or governments to best locate its resources and facilities and efficiently manage resources to ensure that all demand points are covered and all the needs are met. Most of the recent studies, which focused on solving facility location problems by performing spatial clustering, have used the Euclidean distance between two points as the dissimilarity function. Natural obstacles, such as mountains and rivers, can have drastic impacts on the distance that needs to be traveled between two geographical locations. While calculating the distance between various supply chain entities (including facilities and demand points), it is necessary to take such obstacles into account to obtain better and more realistic results regarding location-allocation. In this article, new models were presented for location of urban facilities while considering geographical obstacles at the same time. In these models, three new distance functions were proposed. The first function was based on the analysis of shortest path in linear network, which was called SPD function. The other two functions, namely PD and P2D, were based on the algorithms that deal with robot geometry and route-based robot navigation in the presence of obstacles. The models were implemented in ArcGIS Desktop 9.2 software using the visual basic programming language. These models were evaluated using synthetic and real data sets. The overall performance was evaluated based on the sum of distance from demand points to their corresponding facilities. Because of the distance between the demand points and facilities becoming more realistic in the proposed functions, results indicated desired quality of the proposed models in terms of quality of allocating points to centers and logistic cost. Obtained results show promising

  1. Geographic variation in the prevalence of Kaposi sarcoma-associated herpesvirus and risk factors for transmission.

    Science.gov (United States)

    de Sanjose, Silvia; Mbisa, Georgina; Perez-Alvarez, Susana; Benavente, Yolanda; Sukvirach, Sukhon; Hieu, Nguyen Trong; Shin, Hai-Rim; Anh, Pham Thi Hoang; Thomas, Jaiyeola; Lazcano, Eduardo; Matos, Elena; Herrero, Rolando; Muñoz, Nubia; Molano, Monica; Franceschi, Silvia; Whitby, Denise

    2009-05-15

    The aim of the present study was to estimate the prevalence of Kaposi sarcoma-associated herpesvirus (KSHV) in the female general population, to define geographic variation in and heterosexual transmission of the virus. The study included 10,963 women from 9 countries for whom information on sociodemographic characteristics and reproductive, sexual, and smoking behaviors were available. Antibodies against KSHV that encoded lytic antigen K8.1 and latent antigen ORF73 were determined. The range of prevalence of KSHV (defined as detection of any antigen) was 3.81%-46.02%, with significant geographic variation noted. In Nigeria, the prevalence was 46.02%; in Colombia, 13.32%; in Costa Rica, 9.81%; in Argentina, 6.40%; in Ho Chi Minh City, Vietnam, 15.50%; in Hanoi, Vietnam, 11.26%; in Songkla, Thailand, 10%; in Lampang, Thailand, 8.63%; in Korea, 4.93%; and in Spain, 3.65%. The prevalence of KSHV slightly increased with increasing age among subjects in geographic areas where the prevalence of KSHV was high, such as Nigeria and Colombia, and it significantly decreased with increases in the educational level attained by subjects in those areas. KSHV was not statistically associated with age at first sexual intercourse, number of sex partners, number of children, patterns of oral contraceptive use, presence of cervical human papillomavirus DNA, or smoking status. The study provides comparable estimates of KSHV prevalence in diverse cultural settings across 4 continents and provides evidence that sexual transmission of KSHV is not a major source of infection in the general population.

  2. Soil erosion fragility assessment using an impact model and geographic information system

    OpenAIRE

    Jorge,Luiz Alberto Blanco

    2009-01-01

    A study was taken in a 1566 ha watershed situated in the Capivara River basin, municipality of Botucatu, São Paulo State, Brazil. This environment is fragile and can be subjected to different forms of negative impacts, among them soil erosion by water. The main objective of the research was to develop a methodology for the assessment of soil erosion fragility at the various different watershed positions, using the geographic information system ILWIS version 3.3 for Windows. An impact model wa...

  3. Modelling allergenic risk

    DEFF Research Database (Denmark)

    Birot, Sophie

    combines second order Monte-Carlo simulations with Bayesian inferences [13]. An alternative method using second order Monte-Carlo simulations was proposed to take into account the uncertainty from the inputs. The uncertainty propagation from the inputs to the risk of allergic reaction was also evaluated...... countries is proposed. Thus, the allergen risk assessment can be performed cross-nationally and for the correct food group. Then the two probabilistic risk assessment methods usually used were reviewed and compared. First order Monte-Carlo simulations are used in one method [14], whereas the other one......Up to 20 million Europeans suffer from food allergies. Due to the lack of knowledge about why food allergies developed or how to protect allergic consumers from the offending food, food allergy management is mainly based on food allergens avoidance. The iFAAM project (Integrated approaches to Food...

  4. An assessment of the geographical risks of wild and vaccine-derived poliomyelitis outbreaks in Africa and Asia.

    Science.gov (United States)

    O'Reilly, Kathleen M; Lamoureux, Christine; Molodecky, Natalie A; Lyons, Hil; Grassly, Nicholas C; Tallis, Graham

    2017-05-26

    The international spread of wild poliomyelitis outbreaks continues to threaten eradication of poliomyelitis and in 2014 a public health emergency of international concern was declared. Here we describe a risk scoring system that has been used to assess country-level risks of wild poliomyelitis outbreaks, to inform prioritisation of mass vaccination planning, and describe the change in risk from 2014 to 2016. The methods were also used to assess the risk of emergence of vaccine-derived poliomyelitis outbreaks. Potential explanatory variables were tested against the reported outbreaks of wild poliomyelitis since 2003 using multivariable regression analysis. The regression analysis was translated to a risk score and used to classify countries as Low, Medium, Medium High and High risk, based on the predictive ability of the score. Indicators of population immunity, population displacement and diarrhoeal disease were associated with an increased risk of both wild and vaccine-derived outbreaks. High migration from countries with wild cases was associated with wild outbreaks. High birth numbers were associated with an increased risk of vaccine-derived outbreaks. Use of the scoring system is a transparent and rapid approach to assess country risk of wild and vaccine-derived poliomyelitis outbreaks. Since 2008 there has been a steep reduction in the number of wild poliomyelitis outbreaks and the reduction in countries classified as High and Medium High risk has reflected this. The risk of vaccine-derived poliomyelitis outbreaks has varied geographically. These findings highlight that many countries remain susceptible to poliomyelitis outbreaks and maintenance or improvement in routine immunisation is vital.

  5. Modeling the adoption of innovations in the presence of geographic and media influences.

    Directory of Open Access Journals (Sweden)

    Jameson L Toole

    Full Text Available While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial to making more accurate predictions of a social contagion and technology adoption at a city-to-city scale. Using data from the adoption of the popular micro-blogging platform, Twitter, we present a model of adoption on a network that places friendships in real geographic space and exposes individuals to mass media influence. We show that homophily both among individuals with similar propensities to adopt a technology and geographic location is critical to reproducing features of real spatiotemporal adoption. Furthermore, we estimate that mass media was responsible for increasing Twitter's user base two to four fold. To reflect this strength, we extend traditional contagion models to include an endogenous mass media agent that responds to those adopting an innovation as well as influencing agents to adopt themselves.

  6. Modeling the adoption of innovations in the presence of geographic and media influences.

    Science.gov (United States)

    Toole, Jameson L; Cha, Meeyoung; González, Marta C

    2012-01-01

    While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial to making more accurate predictions of a social contagion and technology adoption at a city-to-city scale. Using data from the adoption of the popular micro-blogging platform, Twitter, we present a model of adoption on a network that places friendships in real geographic space and exposes individuals to mass media influence. We show that homophily both among individuals with similar propensities to adopt a technology and geographic location is critical to reproducing features of real spatiotemporal adoption. Furthermore, we estimate that mass media was responsible for increasing Twitter's user base two to four fold. To reflect this strength, we extend traditional contagion models to include an endogenous mass media agent that responds to those adopting an innovation as well as influencing agents to adopt themselves.

  7. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

    Science.gov (United States)

    Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

    2017-07-01

    Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

  8. Case control study of the geographic variability of exposure to disinfectant byproducts and risk for rectal cancer

    Directory of Open Access Journals (Sweden)

    Rogerson Peter A

    2007-05-01

    Full Text Available Abstract Background Levels of byproducts that result from the disinfection of drinking water vary within a water distribution system. This prompted us to question whether the risk for rectal cancer also varies, depending upon one's long term geographic location within the system. Such a geographic distribution in rectal cancer risk would follow naturally from an association between level of byproduct and rectal cancer risk. We assess the effects of estimated geographic variability in exposure to some of the components of the trihalomethane group of disinfectant byproducts (DBPs on the odds ratios and probabilities for rectal cancer in white males in a case control study of 128 cases and 253 controls, conducted in Monroe County, Western New York State, U.S.A. The study was designed around health data initially collected at the University at Buffalo (Department of Social and Preventative Medicine as part of the Upstate New York Diet Study, and trihalomethane (THM data collected from a separate independent study of THMs conducted by Monroe County Department of Health. Case participants were chosen from hospital pathology records. The controls are disease-free white males between 35–90 years old, living in Monroe County, and chosen from control groups for studies from cancer of five other (unrelated sites. Using a combination of case control methodology and spatial analysis, the spatial patterns of THMs and individual measures of tap water consumption provide estimates of the effects of ingestion of specific amounts of some DBPs on rectal cancer risk. Trihalomethane (THM data were used to spatially interpolate levels at the taps of cases and controls, and odds ratios were estimated using logistic regression to assess the effects of estimated THM exposure dose on cancer risk, adjusting for alcohol, dietary beta carotene intake, tap water intake, and total caloric intake. Results Trihalomethane levels varied spatially within the county; although

  9. Model for Determining Geographical Distribution of Heat Saving Potentials in Danish Building Stock

    Directory of Open Access Journals (Sweden)

    Stefan Petrovic

    2014-02-01

    Full Text Available Since the global oil crisis in the 1970s, Denmark has followed a path towards energy independency by continuously improving its energy efficiency and energy conservation. Energy efficiency was mainly tackled by introducing a high number of combined heat and power plants in the system, while energy conservation was predominantly approached by implementing heat saving measures. Today, with the goal of 100% renewable energy within the power and heat sector by the year 2035, reductions in energy demand for space heating and the preparation of domestic hot water remain at the top of the agenda in Denmark. A highly detailed model for determining heat demand, possible heat savings and associated costs in the Danish building stock is presented. Both scheduled and energy-saving renovations until year 2030 have been analyzed. The highly detailed GIS-based heat atlas for Denmark is used as a container for storing data about physical properties for 2.5 million buildings in Denmark. Consequently, the results of the analysis can be represented on a single building level. Under the assumption that buildings with the most profitable heat savings are renovated first, the consequences of heat savings for the economy and energy system have been quantified and geographically referenced. The possibilities for further improvements of the model and the application to other geographical regions have been discussed.

  10. Geographical Information System Model for Potential Mines Data Management Presentation in Kabupaten Gorontalo

    Science.gov (United States)

    Roviana, D.; Tajuddin, A.; Edi, S.

    2017-03-01

    Mining potential in Indonesian is very abundant, ranging from Sabang to Marauke. Kabupaten Gorontalo is one of many places in Indonesia that have different types of minerals and natural resources that can be found in every district. The abundant of mining potential must be balanced with good management and ease of getting information by investors. The current issue is, (1) ways of presenting data/information about potential mines area is still manually (the maps that already capture from satellite image, then printed and attached to information board in the office) it caused the difficulties of getting information; (2) the high cost of maps printing; (3) the difficulties of regency leader (bupati) to obtain information for strategic decision making about mining potential. The goal of this research is to build a model of Geographical Information System that could provide data management of potential mines, so that the investors could easily get information according to their needs. To achieve that goal Research and Development method is used. The result of this research, is a model of Geographical Information System that implemented in an application to presenting data management of mines.

  11. An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

    Science.gov (United States)

    Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

    2018-05-01

    Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

  12. Neighborhood Condition and Geographic Locale in Assessing HIV/STI Risk Among African American Adolescents.

    Science.gov (United States)

    Kerr, Jelani C; Valois, Robert F; Siddiqi, Arjumand; Vanable, Peter; Carey, Michael P; DiClemente, Ralph J; Romer, Daniel; Brown, Larry K; Farber, Naomi B; Salazar, Laura F

    2015-06-01

    Although region and neighborhood condition's effect on HIV/sexually transmitted infection (STI) risk has been studied separately, there is little research examining their interplay. African American adolescents (n = 1,602) from four matched cities in the Northeastern and Southeastern US completed Audio Computer Assisted Self-Interviews and submitted biospecimen samples to detect Sexually Transmitted Infections (chlamydia, gonorrhea, and trichomonas). Logistic and negative binomial regressions determined HIV/STI risk differences by region, neighborhood stress, and stress-region dyads. Northeastern participants demonstrated lower HIV/STI risk while participants from higher stress neighborhoods exhibited greater risk. Relationships between neighborhood condition and ever having anal sex (p use (p partners (p partners than participants in comparable Southeastern neighborhoods (p risk.

  13. Understanding the geographic distribution of tropical cyclone formation for applications in climate models

    Science.gov (United States)

    Tory, Kevin J.; Ye, H.; Dare, R. A.

    2018-04-01

    Projections of Tropical cyclone (TC) formation under future climate scenarios are dependent on climate model simulations. However, many models produce unrealistic geographical distributions of TC formation, especially in the north and south Atlantic and eastern south Pacific TC basins. In order to improve confidence in projections it is important to understand the reasons behind these model errors. However, considerable effort is required to analyse the many models used in projection studies. To address this problem, a novel diagnostic is developed that provides compelling insight into why TCs form where they do, using a few summary diagrams. The diagnostic is developed after identifying a relationship between seasonal climatologies of atmospheric variables in 34 years of ECMWF reanalysis data, and TC detection distributions in the same data. Geographic boundaries of TC formation are constructed from four threshold quantities. TCs form where Emanuel's Maximum Potential Intensity, V_{{PI}}, exceeds 40 {ms}^{{ - 1}}, 700 hPa relative humidity, RH_{{700}}, exceeds 40%, and the magnitude of the difference in vector winds between 850 and 200 hPa, V_{{sh}}, is less than 20 {ms}^{{ - 1}}. The equatorial boundary is best defined by a composite quantity containing the ratio of absolute vorticity (η ) to the meridional gradient of absolute vorticity (β ^{*}), rather than η alone. {β ^*} is also identified as a potentially important ingredient for TC genesis indices. A comparison of detected Tropical Depression (TD) and Tropical Storm (TS) climatologies revealed TDs more readily intensify further to TS where {V_{PI}} is elevated and {V_{sh}} is relatively weak. The distributions of each threshold quantity identify the factors that favour and suppress TC formation throughout the tropics in the real world. This information can be used to understand why TC formation is poorly represented in some climate models, and shows potential for understanding anomalous TC formation

  14. Model of cholera dissemination using geographic information systems and fuzzy clustering means: case study, Chabahar, Iran.

    Science.gov (United States)

    Pezeshki, Z; Tafazzoli-Shadpour, M; Mansourian, A; Eshrati, B; Omidi, E; Nejadqoli, I

    2012-10-01

    Cholera is spread by drinking water or eating food that is contaminated by bacteria, and is related to climate changes. Several epidemics have occurred in Iran, the most recent of which was in 2005 with 1133 cases and 12 deaths. This study investigated the incidence of cholera over a 10-year period in Chabahar district, a region with one of the highest incidence rates of cholera in Iran. Descriptive retrospective study on data of patients with Eltor and NAG cholera reported to the Iranian Centre of Disease Control between 1997 and 2006. Data on the prevalence of cholera were gathered through a surveillance system, and a spatial database was developed using geographic information systems (GIS) to describe the relation of spatial and climate variables to cholera incidences. Fuzzy clustering (fuzzy C) method and statistical analysis based on logistic regression were used to develop a model of cholera dissemination. The variables were demographic characteristics, specifications of cholera infection, climate conditions and some geographical parameters. The incidence of cholera was found to be significantly related to higher temperature and humidity, lower precipitation, shorter distance to the eastern border of Iran and local health centres, and longer distance to the district health centre. The fuzzy C means algorithm showed that clusters were geographically distributed in distinct regions. In order to plan, manage and monitor any public health programme, GIS provide ideal platforms for the convergence of disease-specific information, analysis and computation of new data for statistical analysis. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  15. Geographic information system-coupling sediment delivery distributed modeling based on observed data.

    Science.gov (United States)

    Lee, S E; Kang, S H

    2014-01-01

    Spatially distributed sediment delivery (SEDD) models are of great interest in estimating the expected effect of changes on soil erosion and sediment yield. However, they can only be applied if the model can be calibrated using observed data. This paper presents a geographic information system (GIS)-based method to calculate the sediment discharge from basins to coastal areas. For this, an SEDD model, with a sediment rating curve method based on observed data, is proposed and validated. The model proposed here has been developed using the combined application of the revised universal soil loss equation (RUSLE) and a spatially distributed sediment delivery ratio, within Model Builder of ArcGIS's software. The model focuses on spatial variability and is useful for estimating the spatial patterns of soil loss and sediment discharge. The model consists of two modules, a soil erosion prediction component and a sediment delivery model. The integrated approach allows for relatively practical and cost-effective estimation of spatially distributed soil erosion and sediment delivery, for gauged or ungauged basins. This paper provides the first attempt at estimating sediment delivery ratio based on observed data in the monsoon region of Korea.

  16. Multilevel joint competing risk models

    Science.gov (United States)

    Karunarathna, G. H. S.; Sooriyarachchi, M. R.

    2017-09-01

    Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).

  17. Comparative assessment of spent nuclear fuel transportation routes using risk factors and a geographic information system

    International Nuclear Information System (INIS)

    Toth, D.M.

    1996-01-01

    The assessment of potential alternative routes was simplified through the use of six comparative risk factors evaluated using detailed, route-specific data. The route and environmental attributes varied strongly with location and were developed from national, state, and local sources. The six comparative factors were risk measures of incident-free transportation radiation exposure, radiological accident population exposure, nonradiological accidents, contamination of environmental sensitive areas, environmental justice for minority populations, and environmental justice for low-income populations. An assessment of four real North-Central Florida routes provided a sample implementation of the analysis tools and risk factors. The assessment routes, consisting of common beginning and end locations, included an interstate highway, a rural highway, a mostly urban highway, and a combination interstate highway with rural bypass. This route comparative assessment study predicted that the interstate highway, despite a higher population density, greater traffic volume, and greater number of vehicular fatality accidents, would present the lowest cumulative risk. On the contrary, the rural highway route, characterized as having the lowest population density, minimal vehicle traffic volume, and the lowest percentages of minority and low-income populations, displayed the highest cumulative risk measure. Factors contributing to the high risk for the rural highway route included greater route length, higher vehicular fatality accident rates per vehicle mile traveled, and the close proximity to environmentally sensitive areas. This route comparative assessment study predicted that the interstate highway, despite a higher population density, greater traffic volume, and greater number of vehicular fatality accidents, would present the lowest cumulative risk. On the contrary, the rural highway route, characterized as having the lowest population density, minimal vehicle traffic volume

  18. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  1. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  7. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Risk modelling in portfolio optimization

    Science.gov (United States)

    Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

    2013-09-01

    Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

  10. Models for Pesticide Risk Assessment

    Science.gov (United States)

    EPA considers the toxicity of the pesticide as well as the amount of pesticide to which a person or the environments may be exposed in risk assessment. Scientists use mathematical models to predict pesticide concentrations in exposure assessment.

  11. Feasibility of Close-Range Photogrammetric Models for Geographic Information System

    International Nuclear Information System (INIS)

    2011-01-01

    The objective of this project was to determine the feasibility of using close-range architectural photogrammetry as an alternative three dimensional modeling technique in order to place the digital models in a geographic information system (GIS) at SLAC. With the available equipment and Australis photogrammetry software, the creation of full and accurate models of an example building, Building 281 on SLAC campus, was attempted. After conducting several equipment tests to determine the precision achievable, a complete photogrammetric survey was attempted. The dimensions of the resulting models were then compared against the true dimensions of the building. A complete building model was not evidenced to be obtainable using the current equipment and software. This failure was likely attributable to the limits of the software rather than the precision of the physical equipment. However, partial models of the building were shown to be accurate and determined to still be usable in a GIS. With further development of the photogrammetric software and survey procedure, the desired generation of a complete three dimensional model is likely still feasible.

  12. Development of a risk score for geographic atrophy in complications of the age-related macular degeneration prevention trial.

    Science.gov (United States)

    Ying, Gui-Shuang; Maguire, Maureen G

    2011-02-01

    To develop a risk score for developing geographic atrophy (GA) involving easily obtainable information among patients with bilateral large drusen. Cohort study within a multicenter randomized clinical trial. We included 1052 participants with ≥ 10 large (>125 μm) drusen and visual acuity ≥ 20/40 in each eye. In the Complications of Age-related Macular Degeneration (AMD) Prevention Trial (CAPT), 1 eye of each participant was randomly assigned to laser treatment and the contralateral eye was assigned to observation to evaluate whether laser treatment of drusen could prevent vision loss. Gradings by a reading center were used to identify: CAPT end point GA (total area of GA [>250 μm] > 1 disc area), GA (>175 μm) involving the foveal center (CGA), and GA of any size and location (any GA). Established risk factors (age, smoking status, hypertension, Age-related Eye Disease Study simple severity scale score), both with and without a novel risk factor (night vision score), were used in assigning risk points. The risk scores were evaluated for the ability to discriminate and calibrate GA risk. Development of end point GA, CGA, and any GA. Among 942 CAPT participants who completed 5 years of follow-up and did not have any GA at baseline, 6.8% participants developed CAPT end point GA, 9.6% developed CGA, and 34.4% developed any GA. The 5-year incidence of end point GA in 1 or both eyes of a participant increased with the 15-point GA risk score, from 0.6% for prevention of GA and for clinical assessment of GA risk in early AMD patients. Copyright © 2011 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

  13. Health risks maps. Modelling of air quality as a tool to map health risks

    International Nuclear Information System (INIS)

    Van Doorn, R.; Hegger, C.

    2000-01-01

    Environmental departments consider geographical maps with information on air quality as the final product of a complicated process of measuring, modelling and presentation. Municipal health departments consider such maps a useful starting point to solve the problem whether air pollution causes health risks for citizens. The answer to this question cannot be reduced to checking if threshold limit values are exceeded. Based on the results of measurements and modelling of concentrations of nitrogen dioxide in air, the health significance of air pollution caused by nitrogen dioxide is illuminated. A proposal is presented to map health risks of air pollution by using the results of measurements and modelling of air pollution. 7 refs

  14. Identification of environmental parameters and risk mapping of visceral leishmaniasis in Ethiopia by using geographical information systems and a statistical approach

    Directory of Open Access Journals (Sweden)

    Teshome Tsegaw

    2013-05-01

    Full Text Available Visceral leishmaniasis (VL, a vector-borne disease strongly influenced by environmental factors, has (re-emerged in Ethiopia during the last two decades and is currently of increasing public health concern. Based on VL incidence in each locality (kebele documented from federal or regional health bureaus and/or hospital records in the country, geographical information systems (GIS, coupled with binary and multivariate logistic regression methods, were employed to develop a risk map for Ethiopia with respect to VL based on soil type, altitude, rainfall, slope and temperature. The risk model was subsequently validated in selected sites. This environmental VL risk model provided an overall prediction accuracy of 86% with mean land surface temperature and soil type found to be the best predictors of VL. The total population at risk was estimated at 3.2 million according to the national population census in 2007. The approach presented here should facilitate the identification of priority areas for intervention and the monitoring of trends as well as providing input for further epidemiological and applied research with regard to this disease in Ethiopia.

  15. Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia.

    Science.gov (United States)

    Deribe, Kebede; Cano, Jorge; Newport, Melanie J; Golding, Nick; Pullan, Rachel L; Sime, Heven; Gebretsadik, Abeba; Assefa, Ashenafi; Kebede, Amha; Hailu, Asrat; Rebollo, Maria P; Shafi, Oumer; Bockarie, Moses J; Aseffa, Abraham; Hay, Simon I; Reithinger, Richard; Enquselassie, Fikre; Davey, Gail; Brooker, Simon J

    2015-01-01

    Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues. Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008-2010. The integrated mapping used woreda (district) health offices' reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT) modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence. Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2-51.7) million people (i.e. 43.8%; 95% CI: 25.3-64.8% of Ethiopia's national population) lived in areas environmentally suitable for the occurrence of podoconiosis. Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide programme planning

  16. Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia.

    Directory of Open Access Journals (Sweden)

    Kebede Deribe

    Full Text Available Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues.Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008-2010. The integrated mapping used woreda (district health offices' reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence.Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2-51.7 million people (i.e. 43.8%; 95% CI: 25.3-64.8% of Ethiopia's national population lived in areas environmentally suitable for the occurrence of podoconiosis.Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide

  17. Development of cesium 137 plant uptake predicting model using geographical information systems

    International Nuclear Information System (INIS)

    Lomonos, O.V.

    2002-01-01

    Soil-plant system is a critical component of food chain in processes of Cs 137 migration. In this component it is possible to decrease greatly Cs 137 uptake in food chain. Development of Cs 137 migration model in soil-plant system enable to determine amount of Cs 137 in plant uptake and evaluate agricultural produce accordance with modern ecological requirements. Also this model can help with management of agricultural production. Geographical information systems (GIS) have a wide propagation in radioecology at present time. Models using GIS have several advantages: relative simplicity of evaluation, visualization of evaluated results etc. As a result, plots with possible Cs 137 uptake increasing could be easily discovered. Physical decay, Cs 137 sorption and fixation by soil, Cs 137 vertical migration in soil profile and plant uptake are the main components of the Cs 137 migration model in soil-plant system. Content of biologically available Cs 137 calculated taking into account all of these components. Using GIS with Cs 137 migration model in soil-plant system lets efficiently discover those factors that have major influence on Cs 137 plant uptake increasing. This model improves agricultural production on territories, which polluted by Cs 137

  18. A validation of ground ambulance pre-hospital times modeled using geographic information systems.

    Science.gov (United States)

    Patel, Alka B; Waters, Nigel M; Blanchard, Ian E; Doig, Christopher J; Ghali, William A

    2012-10-03

    Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7-8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a

  19. Modeling renewable energy company risk

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2012-01-01

    The renewable energy sector is one of the fastest growing components of the energy industry and along with this increased demand for renewable energy there has been an increase in investing and financing activities. The tradeoff between risk and return in the renewable energy sector is, however, precarious. Renewable energy companies are often among the riskiest types of companies to invest in and for this reason it is necessary to have a good understanding of the risk factors. This paper uses a variable beta model to investigate the determinants of renewable energy company risk. The empirical results show that company sales growth has a negative impact on company risk while oil price increases have a positive impact on company risk. When oil price returns are positive and moderate, increases in sales growth can offset the impact of oil price returns and this leads to lower systematic risk.

  20. Geographical Research Model of the Relation Between Tourism and Industry on the Framework of Pula

    Directory of Open Access Journals (Sweden)

    Nikola Vojnović

    2002-01-01

    Full Text Available The research gives a proposal of a theoretical research model, and can be the basis of geographical research of the relation between tourism and industry as two opposite human activities and branches of economy. The accent is set on the consideration of their relation in major urban areas, which show a parallel development of tourism and industry of the Second Industrial Revolution, typical for Croatian coastline region. The proposal of the research scheme, from the analysis of the present structure and the quantity, harmony and disharmony of both branches, to the possibility of creating an industrial-tourism region are analyzed in the first part of the work, whereas the results of the initial research are presented in the second part.

  1. Geographical distribution of complement receptor type 1 variants and their associated disease risk.

    Directory of Open Access Journals (Sweden)

    Thaisa Lucas Sandri

    Full Text Available Pathogens exert selective pressure which may lead to substantial changes in host immune responses. The human complement receptor type 1 (CR1 is an innate immune recognition glycoprotein that regulates the activation of the complement pathway and removes opsonized immune complexes. CR1 genetic variants in exon 29 have been associated with expression levels, C1q or C3b binding and increased susceptibility to several infectious diseases. Five distinct CR1 nucleotide substitutions determine the Knops blood group phenotypes, namely Kna/b, McCa/b, Sl1/Sl2, Sl4/Sl5 and KCAM+/-.CR1 variants were genotyped by direct sequencing in a cohort of 441 healthy individuals from Brazil, Vietnam, India, Republic of Congo and Ghana.The distribution of the CR1 alleles, genotypes and haplotypes differed significantly among geographical settings (p≤0.001. CR1 variants rs17047660A/G (McCa/b and rs17047661A/G (Sl1/Sl2 were exclusively observed to be polymorphic in African populations compared to the groups from Asia and South-America, strongly suggesting that these two SNPs may be subjected to selection. This is further substantiated by a high linkage disequilibrium between the two variants in the Congolese and Ghanaian populations. A total of nine CR1 haplotypes were observed. The CR1*AGAATA haplotype was found more frequently among the Brazilian and Vietnamese study groups; the CR1*AGAATG haplotype was frequent in the Indian and Vietnamese populations, while the CR1*AGAGTG haplotype was frequent among Congolese and Ghanaian individuals.The African populations included in this study might have a selective advantage conferred to immune genes involved in pathogen recognition and signaling, possibly contributing to disease susceptibility or resistance.

  2. Geographically weighted lasso (GWL) study for modeling the diarrheic to achieve open defecation free (ODF) target

    Science.gov (United States)

    Arumsari, Nurvita; Sutidjo, S. U.; Brodjol; Soedjono, Eddy S.

    2014-03-01

    Diarrhea has been one main cause of morbidity and mortality to children around the world, especially in the developing countries According to available data that was mentioned. It showed that sanitary and healthy lifestyle implementation by the inhabitants was not good yet. Inadequacy of environmental influence and the availability of health services were suspected factors which influenced diarrhea cases happened followed by heightened percentage of the diarrheic. This research is aimed at modelling the diarrheic by using Geographically Weighted Lasso method. With the existence of spatial heterogeneity was tested by Breusch Pagan, it was showed that diarrheic modeling with weighted regression, especially GWR and GWL, can explain the variation in each location. But, the absence of multi-collinearity cases on predictor variables, which were affecting the diarrheic, resulted in GWR and GWL modelling to be not different or identical. It is shown from the resulting MSE value. While from R2 value which usually higher on GWL model showed a significant variable predictor based on more parametric shrinkage value.

  3. Spatial modelling of assumption of tourism development with geographic IT using

    Directory of Open Access Journals (Sweden)

    Jitka Machalová

    2010-01-01

    Full Text Available The aim of this article is to show the possibilities of spatial modelling and analysing of assumptions of tourism development in the Czech Republic with the objective to make decision-making processes in tourism easier and more efficient (for companies, clients as well as destination managements. The development and placement of tourism depend on the factors (conditions that influence its application in specific areas. These factors are usually divided into three groups: selective, localization and realization. Tourism is inseparably connected with space – countryside. The countryside can be modelled and consecutively analysed by the means of geographical information technologies. With the help of spatial modelling and following analyses the localization and realization conditions in the regions of the Czech Republic have been evaluated. The best localization conditions have been found in the Liberecký region. The capital city of Prague has negligible natural conditions; however, those social ones are on a high level. Next, the spatial analyses have shown that the best realization conditions are provided by the capital city of Prague. Then the Central-Bohemian, South-Moravian, Moravian-Silesian and Karlovarský regions follow. The development of tourism destination is depended not only on the localization and realization factors but it is basically affected by the level of local destination management. Spatial modelling can help destination managers in decision-making processes in order to optimal use of destination potential and efficient targeting their marketing activities.

  4. [Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

    Science.gov (United States)

    Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

    2016-01-01

    To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

  5. Flood Risk Mapping Using Flow Energy Equation and Geographic Information System

    Directory of Open Access Journals (Sweden)

    pourya Javan

    2013-09-01

    Full Text Available Flooding and its damages are not only found uplift water level in a region. In other words, the depth and speed parameters together have determining the level of flood risk at each point. This subject is visible in flooded plain with low height and high speed of 2 meters per second, which damages are extensive. According to the criteria of having both velocity and flow depth in the governing equation to the flows energy, this equation seems appropriate to analysis in this study. Various methods have been proposed for increase accuracy in flood zoning with different return periods and risks associated with it in land border of river. For example, some of these methods are considered factors such as analysis of past flooding in the area affected by floods, hydrological factors and consideration of hydraulic elements affecting in flood zoning (such as flow velocity. This paper investigates the effect of flood zoning by the energy flow in the areas affected by floods. Also risk due to flood based on energy flow in each section of the river is compared by the proposed graphs of hazard interval and other done flood zoning in this field. In this study, the FORDO river has been selected as the case study. This river is part of the rivers located in the city of QOM KAHAK. The characteristics of river in upstream and downstream are mountain, young and stable and adult, respectively. Also this river in different seasons is exposed the flood damage. The proposed method in this study can be improving recognition accuracy of flood risk in areas affected by flood. Also, this method facilitate the identify parts of the river bed, that is affected by severe flooding, for decision making to improve rivers organizing.

  6. Geographic distribution and mortality risk factors during the cholera outbreak in a rural region of Haiti, 2010-2011.

    Directory of Open Access Journals (Sweden)

    Anne-Laure Page

    2015-03-01

    Full Text Available In 2010 and 2011, Haiti was heavily affected by a large cholera outbreak that spread throughout the country. Although national health structure-based cholera surveillance was rapidly initiated, a substantial number of community cases might have been missed, particularly in remote areas. We conducted a community-based survey in a large rural, mountainous area across four districts of the Nord department including areas with good versus poor accessibility by road, and rapid versus delayed response to the outbreak to document the true cholera burden and assess geographic distribution and risk factors for cholera mortality.A two-stage, household-based cluster survey was conducted in 138 clusters of 23 households in four districts of the Nord Department from April 22nd to May 13th 2011. A total of 3,187 households and 16,900 individuals were included in the survey, of whom 2,034 (12.0% reported at least one episode of watery diarrhea since the beginning of the outbreak. The two more remote districts, Borgne and Pilate were most affected with attack rates up to 16.2%, and case fatality rates up to 15.2% as compared to the two more accessible districts. Care seeking was also less frequent in the more remote areas with as low as 61.6% of reported patients seeking care. Living in remote areas was found as a risk factor for mortality together with older age, greater severity of illness and not seeking care.These results highlight important geographical disparities and demonstrate that the epidemic caused the highest burden both in terms of cases and deaths in the most remote areas, where up to 5% of the population may have died during the first months of the epidemic. Adapted strategies are needed to rapidly provide treatment as well as prevention measures in remote communities.

  7. Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey

    Directory of Open Access Journals (Sweden)

    Vahdettin Demir

    2016-01-01

    Full Text Available In this study, flood hazard maps were prepared for the Mert River Basin, Samsun, Turkey, by using GIS and Hydrologic Engineering Centers River Analysis System (HEC-RAS. In this river basin, human life losses and a significant amount of property damages were experienced in 2012 flood. The preparation of flood risk maps employed in the study includes the following steps: (1 digitization of topographical data and preparation of digital elevation model using ArcGIS, (2 simulation of flood lows of different return periods using a hydraulic model (HEC-RAS, and (3 preparation of flood risk maps by integrating the results of (1 and (2.

  8. Information risk and security modeling

    Science.gov (United States)

    Zivic, Predrag

    2005-03-01

    This research paper presentation will feature current frameworks to addressing risk and security modeling and metrics. The paper will analyze technical level risk and security metrics of Common Criteria/ISO15408, Centre for Internet Security guidelines, NSA configuration guidelines and metrics used at this level. Information IT operational standards view on security metrics such as GMITS/ISO13335, ITIL/ITMS and architectural guidelines such as ISO7498-2 will be explained. Business process level standards such as ISO17799, COSO and CobiT will be presented with their control approach to security metrics. Top level, the maturity standards such as SSE-CMM/ISO21827, NSA Infosec Assessment and CobiT will be explored and reviewed. For each defined level of security metrics the research presentation will explore the appropriate usage of these standards. The paper will discuss standards approaches to conducting the risk and security metrics. The research findings will demonstrate the need for common baseline for both risk and security metrics. This paper will show the relation between the attribute based common baseline and corporate assets and controls for risk and security metrics. IT will be shown that such approach spans over all mentioned standards. The proposed approach 3D visual presentation and development of the Information Security Model will be analyzed and postulated. Presentation will clearly demonstrate the benefits of proposed attributes based approach and defined risk and security space for modeling and measuring.

  9. Cabin Environment Physics Risk Model

    Science.gov (United States)

    Mattenberger, Christopher J.; Mathias, Donovan Leigh

    2014-01-01

    This paper presents a Cabin Environment Physics Risk (CEPR) model that predicts the time for an initial failure of Environmental Control and Life Support System (ECLSS) functionality to propagate into a hazardous environment and trigger a loss-of-crew (LOC) event. This physics-of failure model allows a probabilistic risk assessment of a crewed spacecraft to account for the cabin environment, which can serve as a buffer to protect the crew during an abort from orbit and ultimately enable a safe return. The results of the CEPR model replace the assumption that failure of the crew critical ECLSS functionality causes LOC instantly, and provide a more accurate representation of the spacecraft's risk posture. The instant-LOC assumption is shown to be excessively conservative and, moreover, can impact the relative risk drivers identified for the spacecraft. This, in turn, could lead the design team to allocate mass for equipment to reduce overly conservative risk estimates in a suboptimal configuration, which inherently increases the overall risk to the crew. For example, available mass could be poorly used to add redundant ECLSS components that have a negligible benefit but appear to make the vehicle safer due to poor assumptions about the propagation time of ECLSS failures.

  10. Evaluation of the 3d Urban Modelling Capabilities in Geographical Information Systems

    Science.gov (United States)

    Dogru, A. O.; Seker, D. Z.

    2010-12-01

    Geographical Information System (GIS) Technology, which provides successful solutions to basic spatial problems, is currently widely used in 3 dimensional (3D) modeling of physical reality with its developing visualization tools. The modeling of large and complicated phenomenon is a challenging problem in terms of computer graphics currently in use. However, it is possible to visualize that phenomenon in 3D by using computer systems. 3D models are used in developing computer games, military training, urban planning, tourism and etc. The use of 3D models for planning and management of urban areas is very popular issue of city administrations. In this context, 3D City models are produced and used for various purposes. However the requirements of the models vary depending on the type and scope of the application. While a high level visualization, where photorealistic visualization techniques are widely used, is required for touristy and recreational purposes, an abstract visualization of the physical reality is generally sufficient for the communication of the thematic information. The visual variables, which are the principle components of cartographic visualization, such as: color, shape, pattern, orientation, size, position, and saturation are used for communicating the thematic information. These kinds of 3D city models are called as abstract models. Standardization of technologies used for 3D modeling is now available by the use of CityGML. CityGML implements several novel concepts to support interoperability, consistency and functionality. For example it supports different Levels-of-Detail (LoD), which may arise from independent data collection processes and are used for efficient visualization and efficient data analysis. In one CityGML data set, the same object may be represented in different LoD simultaneously, enabling the analysis and visualization of the same object with regard to different degrees of resolution. Furthermore, two CityGML data sets

  11. Predicting geographic distributions of Phacellodomus species (Aves: Furnariidae in South America based on ecological niche modeling

    Directory of Open Access Journals (Sweden)

    Maria da Salete Gurgel Costa

    2014-08-01

    Full Text Available Phacellodomus Reichenbach, 1853, comprises nine species of Furnariids that occur in South America in open and generally dry areas. This study estimated the geographic distributions of Phacellodomus species in South America by ecological niche modeling. Applying maximum entropy method, models were produced for eight species based on six climatic variables and 949 occurrence records. Since highest climatic suitability for Phacellodomus species has been estimated in open and dry areas, the Amazon rainforest areas are not very suitable for these species. Annual precipitation and minimum temperature of the coldest month are the variables that most influence the models. Phacellodomus species occurred in 35 ecoregions of South America. Chaco and Uruguayan savannas were the ecoregions with the highest number of species. Despite the overall connection of Phacellodomus species with dry areas, species such as P. ruber, P. rufifrons, P. ferrugineigula and P. erythrophthalmus occurred in wet forests and wetland ecoregions.

  12. Integrating remote sensing, geographic information system and modeling for estimating crop yield

    Science.gov (United States)

    Salazar, Luis Alonso

    This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

  13. Geographic scale matters in detecting the relationship between neighbourhood food environments and obesity risk: an analysis of driver license records in Salt Lake County, Utah.

    Science.gov (United States)

    Fan, Jessie X; Hanson, Heidi A; Zick, Cathleen D; Brown, Barbara B; Kowaleski-Jones, Lori; Smith, Ken R

    2014-08-19

    Empirical studies of the association between neighbourhood food environments and individual obesity risk have found mixed results. One possible cause of these mixed findings is the variation in neighbourhood geographic scale used. The purpose of this paper was to examine how various neighbourhood geographic scales affected the estimated relationship between food environments and obesity risk. Cross-sectional secondary data analysis. Salt Lake County, Utah, USA. 403,305 Salt Lake County adults 25-64 in the Utah driver license database between 1995 and 2008. Utah driver license data were geo-linked to 2000 US Census data and Dun & Bradstreet business data. Food outlets were classified into the categories of large grocery stores, convenience stores, limited-service restaurants and full-service restaurants, and measured at four neighbourhood geographic scales: Census block group, Census tract, ZIP code and a 1 km buffer around the resident's house. These measures were regressed on individual obesity status using multilevel random intercept regressions. Obesity. Food environment was important for obesity but the scale of the relevant neighbourhood differs for different type of outlets: large grocery stores were not significant at all four geographic scales, limited-service restaurants at the medium-to-large scale (Census tract or larger) and convenience stores and full-service restaurants at the smallest scale (Census tract or smaller). The choice of neighbourhood geographic scale can affect the estimated significance of the association between neighbourhood food environments and individual obesity risk. However, variations in geographic scale alone do not explain the mixed findings in the literature. If researchers are constrained to use one geographic scale with multiple categories of food outlets, using Census tract or 1 km buffer as the neighbourhood geographic unit is likely to allow researchers to detect most significant relationships. Published by the BMJ

  14. Data model management, with the use of artificial intelligence, for a geographic information system in the energetic sector

    Directory of Open Access Journals (Sweden)

    Nayi Sánchez Fleitas

    2016-09-01

    Full Text Available A Geographic Information System (GIS, named SIGOBE v 3.0, for the electric sector is development. The Integral Management System of the ECIE (SIGECIE and the Integrated Network Management System (SIGERE databases are taxed alfanumeric information. Studies determined the need for a model for data management, contributing to the GIS development, on a conceptual schema domain capable of responding to different user requests, through automatic query as support decision making. To provide the GIS with a conceptual basis an ontology is determined, which will be expressed by logical descriptive, to generate the traits of a case-based reasoning that allows automation of consultations. The final quality of GIS was verified according to the quality standards of the ISO-9126:2002 standard. The proposed model and its functionality contributes to: facilitate decision-making at different levels, perform risk analysis to have the defects of electrical installations, reduce the time of failure to the key areas of the country, organize the travel of trucks more efficiently and locate electrical faults more accurately.

  15. Geographic Names

    Data.gov (United States)

    Minnesota Department of Natural Resources — The Geographic Names Information System (GNIS), developed by the United States Geological Survey in cooperation with the U.S. Board of Geographic Names, provides...

  16. Virtual Geographic Simulation of Light Distribution within Three-Dimensional Plant Canopy Models

    Directory of Open Access Journals (Sweden)

    Liyu Tang

    2017-12-01

    Full Text Available Virtual geographic environments (VGEs have been regarded as an important new means of simulating, analyzing, and understanding complex geological processes. Plants and light are major components of the geographic environment. Light is a critical factor that affects ecological systems. In this study, we focused on simulating light transmission and distribution within a three-dimensional plant canopy model. A progressive refinement radiosity algorithm was applied to simulate the transmission and distribution of solar light within a detailed, three-dimensional (3D loquat (Eriobotrya japonica Lindl. canopy model. The canopy was described in three dimensions, and each organ surface was represented by a set of triangular facets. The form factors in radiosity were calculated using a hemi-cube algorithm. We developed a module for simulating the instantaneous light distribution within a virtual canopy, which was integrated into ParaTree. We simulated the distribution of photosynthetically active radiation (PAR within a loquat canopy, and calculated the total PAR intercepted at the whole canopy scale, as well as the mean PAR interception per unit leaf area. The ParaTree-integrated radiosity model simulates the uncollided propagation of direct solar and diffuse sky light and the light-scattering effect of foliage. The PAR captured by the whole canopy based on the radiosity is approximately 9.4% greater than that obtained using ray tracing and TURTLE methods. The latter methods do not account for the scattering among leaves in the canopy in the study, and therefore, the difference might be due to the contribution of light scattering in the foliage. The simulation result is close to Myneni’s findings, in which the light scattering within a canopy is less than 10% of the incident PAR. Our method can be employed for visualizing and analyzing the spatial distribution of light within a canopy, and for estimating the PAR interception at the organ and canopy

  17. Seasonal and geographical distribution of bacillary dysentery (shigellosis) and associated climate risk factors in Kon Tam Province in Vietnam from 1999 to 2013.

    Science.gov (United States)

    Lee, Hu Suk; Ha Hoang, T T; Pham-Duc, Phuc; Lee, Mihye; Grace, Delia; Phung, Dac Cam; Thuc, Vu Minh; Nguyen-Viet, Hung

    2017-06-21

    Bacillary dysentery (BD) is an acute bacterial infection of the intestine caused by Shigella spp., with clinical symptoms ranging from fever to bloody diarrhoea to abdominal cramps to tenesmus. In Vietnam, enteric bacterial pathogens are an important cause of diarrhoea and most cases in children under 5 years of age are due to Shigella strains. The serogroups S. flexneri and S. sonnei are considered to be the most common. The main objective of this study was to, for the first time, assess the seasonal patterns and geographic distribution of BD in Vietnam, and to determine the climate risk factors associated with the incidence of BD in Kon Tum Province, where the highest rate of bacillary dysentery was observed from 1999 to 2013. The seasonal patterns and geographic distribution of BD was assessed in Vietnam using a seasonal-trend decomposition procedure based on loess. In addition, negative binomial regression models were used to determine the climate risk factors associated with the incidence of BD in Kon Tum Province, from 1999 to 2013. Overall, incidence rates of BD have slightly decreased over time (except for an extremely high incidence in 2012 in the north of Vietnam). The central regions (north/south central coast and central highlands) had relatively high incidence rates, whereas the northwest/east and Red River Delta regions had low incidence rates. Overall, seasonal plots showed a high peak in the mid-rainy reason and a second smaller peak in the early or late rainy season. The incidence rates significantly increased between May and October ("wet season") across the country. In Kon Tum Province, temperature, humidity, and precipitation were found to be positively associated with the incidence of BD. Our findings provide insights into the seasonal patterns and geographic distribution of BD in Vietnam and its associated climate risk factors in Kon Tum Province. This study may help clinicians and the general public to better understand the timings of

  18. A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

    Science.gov (United States)

    Pan, Shaoming; Chong, Yanwen; Zhang, Hang; Tan, Xicheng

    2017-01-01

    A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client's requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users' access behaviors and all tiles' relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users' access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods.

  19. Fuzzy audit risk modeling algorithm

    Directory of Open Access Journals (Sweden)

    Zohreh Hajihaa

    2011-07-01

    Full Text Available Fuzzy logic has created suitable mathematics for making decisions in uncertain environments including professional judgments. One of the situations is to assess auditee risks. During recent years, risk based audit (RBA has been regarded as one of the main tools to fight against fraud. The main issue in RBA is to determine the overall audit risk an auditor accepts, which impact the efficiency of an audit. The primary objective of this research is to redesign the audit risk model (ARM proposed by auditing standards. The proposed model of this paper uses fuzzy inference systems (FIS based on the judgments of audit experts. The implementation of proposed fuzzy technique uses triangular fuzzy numbers to express the inputs and Mamdani method along with center of gravity are incorporated for defuzzification. The proposed model uses three FISs for audit, inherent and control risks, and there are five levels of linguistic variables for outputs. FISs include 25, 25 and 81 rules of if-then respectively and officials of Iranian audit experts confirm all the rules.

  20. Technical note: Modeling primate occlusal topography using geographic information systems technology.

    Science.gov (United States)

    Zuccotti, L F; Williamson, M D; Limp, W F; Ungar, P S

    1998-09-01

    Most functional analyses of primate tooth form have been limited to linear or area measurements. Such studies have offered but a limited glimpse at differences in occlusal relief among taxa. Such differences in dental topography may relate to tooth function and, so, have considerable implications for the inference of diet from fossil teeth. In this article, we describe a technique to model and compare primate molars in three dimensions using Geographic Resources Analysis Support System (GRASS) software. We examine unworn lower second molars of three extant hominoids with known differences in diet (Gorilla gorilla, Pan troglodytes, and Pongo pygmaeus), and two fossil forms, (Afropithecus turkanesis and Dryopithecus laietanus). First, we obtained approximately 400 landmarks on the occlusal surfaces of each tooth using an electromagnetic digitizer. Raster "terrain models" of occlusal surfaces were then created by interpolation of the coordinate data. We used GRASS terrain analysis automated techniques to quantify the volumes and slopes of individual cusps. We also used the GRASS watershed technique to identify the volume of liquid that would accumulate in each tooth's basin (a measure of basin area), and the directions and intensity of drainage over the occlusal surface. In sum, GRASS shows considerable potential for the characterization and comparison of tooth surfaces. Furthermore, techniques described here are not limited to the study of teeth, but may be broadly applicable to studies of skulls, joints, and other biological structures.

  1. A Conceptual Model for Delineating Land Management Units (LMUs Using Geographical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Deniz Gerçek

    2017-06-01

    Full Text Available Land management and planning is crucial for present and future use of land and the sustainability of land resources. Physical, biological and cultural characteristics of land can be used to define Land Management Units (LMUs that aid in decision making for managing land and communicating information between different research and application domains. This study aims to describe the classification of ecologically relevant land units that are suitable for land management, planning and conservation purposes. Relying on the idea of strong correlation between landform and potential landcover, a conceptual model for creating Land Management Units (LMUs from topographic data and biophysical information is presented. The proposed method employs a multi-level object-based classification of Digital Terrain Models (DTMs to derive landform units. The sensitivity of landform units to changes in segmentation scale is examined, and the outcome of the landform classification is evaluated. Landform classes are then aggregated with landcover information to produce ecologically relevant landform/landcover assemblages. These conceptual units that constitute a framework of connected entities are finally enriched given available socio-economic information e.g., land use, ownership, protection status, etc. to generate LMUs. LMUs attached to a geographic database enable the retrieval of information at various levels to support decision making for land management at various scales. LMUs that are created present a basis for conservation and management in a biodiverse area in the Black Sea region of Turkey.

  2. Comprehensive Regional Modeling for Long-Range Planning: Linking Integrated Urban Models and Geographic Information Systems

    OpenAIRE

    Johnston, Robert; de la Barra, Thomas

    2000-01-01

    This study demonstrates the sequential linking of two types of models to permit the comprehensive evaluation of regional transportation and land use policies. First, we operate an integrated urban model (TRANUS), which represents both land and travel markets with zones and networks. The travel and land use projections from TRANUS are outlined, to demonstrate the general reasonableness of the results, as this is the first application of a market-based urban model in the US. Second, the land us...

  3. Geographic origin as a determinant of left ventricular mass and diastolic function - the Cardiovascular Risk in Young Finns Study.

    Science.gov (United States)

    Vähämurto, L; Juonala, M; Ruohonen, S; Hutri-Kähönen, N; Kähönen, M; Laitinen, T; Tossavainen, P; Jokinen, E; Viikari, J; Raitakari, O T; Pahkala, K

    2018-03-01

    Eastern Finns have higher risk of coronary heart disease (CHD) and carotid intima-media thickness than western Finns although current differences in CHD risk factors are minimal. Left ventricular (LV) mass and diastolic function predict future cardiovascular events but their east-west differences are unknown. We examined the association of eastern/western baseline origin with LV mass and diastolic function. The study population included 2045 subjects of the Cardiovascular Risk in Young Finns Study with data from the baseline survey (1980) and the latest follow-up (2011) when echocardiography was performed at the age of 34-49 years. Subjects with eastern baseline origin had in 2011 higher LV mass (139±1.0 vs. 135±1.0 g, p=0.006) and E/e'-ratio indicating weaker LV diastolic function (4.86±0.03 vs. 4.74±0.03, p=0.02) than western subjects. Results were independent of age, sex, area of examination and CHD risk factors such as blood pressure and BMI (LV mass indexed with height: porigin (135±0.9 vs. 131±0.9 ml, p=0.0011) but left atrial end-systolic volume, also indicating LV diastolic function, was not different between eastern and western subjects (43.4±0.5 vs. 44.0±0.5 ml, p=0.45). Most of the subjects were well within the normal limits of these echocardiographic measurements. In our healthy middle-aged population, geographic origin in eastern Finland associated with higher LV mass compared to western Finland. Higher E/e'-ratio suggests that subjects with eastern baseline origin might have higher prevalence of diastolic dysfunction in the future than western subjects.

  4. Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia.

    Science.gov (United States)

    Minale, Amare Sewnet; Alemu, Kalkidan

    2018-05-07

    The main objective of this study was to develop a malaria risk map for Bahir Dar City, Amhara, which is situated south of Lake Tana on the Ethiopian plateau. Rainfall, temperature, altitude, slope and land use/land cover (LULC), as well as proximity measures to lake, river and health facilities, were investigated using remote sensing and geographical information systems. The LULC variable was derived from a 2012 SPOT satellite image by supervised classification, while 30-m spatial resolution measurements of altitude and slope came from the Shuttle Radar Topography Mission. Metrological data were collected from the National Meteorological Agency, Bahir Dar branch. These separate datasets, represented as layers in the computer, were combined using weighted, multi-criteria evaluations. The outcome shows that rainfall, temperature, slope, elevation, distance from the lake and distance from the river influenced the malaria hazard the study area by 35%, 15%, 10%, 7%, 5% and 3%, respectively, resulting in a map showing five areas with different levels of malaria hazard: very high (11.2%); high (14.5%); moderate (63.3%); low (6%); and none (5%). The malaria risk map, based on this hazard map plus additional information on proximity to health facilities and current LULC conditions, shows that Bahir Dar City has areas with very high (15%); high (65%); moderate (8%); and low (5%) levels of malaria risk, with only 2% of the land completely riskfree. Such risk maps are essential for planning, implementing, monitoring and evaluating disease control as well as for contemplating prevention and elimination of epidemiological hazards from endemic areas.

  5. Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment.

    Science.gov (United States)

    Khormi, Hassan M; Kumar, Lalit

    2012-05-01

    An important option in preventing the spread of dengue fever (DF) is to control and monitor its vector (Aedes aegypti) as well as to locate and destroy suitable mosquito breeding environments. The aim of the present study was to use a combination of environmental and socioeconomic variables to model areas at risk of DF. These variables include clinically confirmed DF cases, mosquito counts, population density in inhabited areas, total populations per district, water access, neighbourhood quality and the spatio-temporal risk of DF based on the average, weekly frequency of DF incidence. Out of 111 districts investigated, 17 (15%), covering a total area of 121 km2, were identified as of high risk, 25 (22%), covering 133 km2, were identified as of medium risk, 18 (16%), covering 180 km2, were identified as of low risk and 51 (46%), covering 726 km2, were identified as of very low risk. The resultant model shows that most areas at risk of DF were concentrated in the central part of Jeddah county, Saudi Arabia. The methods used can be implemented as routine procedures for control and prevention. A concerted intervention in the medium- and high-risk level districts identified in this study could be highly effective in reducing transmission of DF in the area as a whole.

  6. Modeling wind energy potential in a data-poor region: A geographic information systems model for Iraq

    Science.gov (United States)

    Khayyat, Abdulkareem Hawta Abdullah Kak Ahmed

    Scope and Method of Study: Most developing countries, including Iraq, have very poor wind data. Existing wind speed measurements of poor quality may therefore be a poor guide to where to look for the best wind resources. The main focus of this study is to examine how effectively a GIS spatial model estimates wind power potential in regions where high-quality wind data are very scarce, such as Iraq. The research used a mixture of monthly and hourly wind data from 39 meteorological stations. The study applied spatial analysis statistics and GIS techniques in modeling wind power potential. The model weighted important human, environmental and geographic factors that impact wind turbine siting, such as roughness length, land use⪉nd cover type, airport locations, road access, transmission lines, slope and aspect. Findings and Conclusions: The GIS model provided estimations for wind speed and wind power density and identified suitable areas for wind power projects. Using a high resolution (30*30m) digital elevation model DEM improved the GIS wind suitability model. The model identified areas suitable for wind farm development on different scales. The model showed that there are many locations available for large-scale wind turbines in the southern part of Iraq. Additionally, there are many places in central and northern parts (Kurdistan Region) for smaller scale wind turbine placement.

  7. Ecological study and risk mapping of leishmaniasis in an endemic area of Brazil based on a geographical information systems approach

    Directory of Open Access Journals (Sweden)

    Alba Valéria Machado da Silva

    2011-11-01

    Full Text Available Visceral leishmaniasis is a vector-borne disease highly influenced by eco-epidemiological factors. Geographical information systems (GIS have proved to be a suitable approach for the analysis of environmental components that affect the spatial distribution of diseases. Exploiting this methodology, a model was developed for the mapping of the distribution and incidence of canine leishmaniasis in an endemic area of Brazil. Local variations were observed with respect to infection incidence and distribution of serological titers, i.e. high titers were noted close to areas with preserved vegetation, while low titers were more frequent in areas where people kept chickens. Based on these results, we conclude that the environment plays an important role in generating relatively protected areas within larger endemic regions, but that it can also contribute to the creation of hotspots with clusters of comparatively high serological titers indicating a high level of transmission compared with neighbouring areas.

  8. Model of MSD Risk Assessment at Workplace

    OpenAIRE

    K. Sekulová; M. Šimon

    2015-01-01

    This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

  9. What are we 'tweeting' about obesity? Mapping tweets with Topic Modeling and Geographic Information System.

    Science.gov (United States)

    Ghosh, Debarchana Debs; Guha, Rajarshi

    2013-01-01

    Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are 'food deserts', 'fast food', and 'childhood obesity'. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as 'childhood obesity and schools', 'obesity prevention', and 'obesity and food habits' are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets.

  10. Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model

    International Nuclear Information System (INIS)

    Druckman, A.; Jackson, T.

    2008-01-01

    Devising policies for a low carbon society requires a careful understanding of energy consumption in different types of households. In this paper, we explore patterns of UK household energy use and associated carbon emissions at national level and also at high levels of socio-economic and geographical disaggregation. In particular, we examine specific neighbourhoods with contrasting levels of deprivation, and typical 'types' (segments) of UK households based on socio-economic characteristics. Results support the hypothesis that different segments have widely differing patterns of consumption. We show that household energy use and associated carbon emissions are both strongly, but not solely, related to income levels. Other factors, such as the type of dwelling, tenure, household composition and rural/urban location are also extremely important. The methodology described in this paper can be used in various ways to inform policy-making. For example, results can help in targeting energy efficiency measures; trends from time series results will form a useful basis for scenario building; and the methodology may be used to model expected outcomes of possible policy options, such as personal carbon trading or a progressive tax regime on household energy consumption

  11. Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks

    Science.gov (United States)

    Horita, Flávio E. A.; Albuquerque, João Porto de; Degrossi, Lívia C.; Mendiondo, Eduardo M.; Ueyama, Jó

    2015-07-01

    Effective flood risk management requires updated information to ensure that the correct decisions can be made. This can be provided by Wireless Sensor Networks (WSN) which are a low-cost means of collecting updated information about rivers. Another valuable resource is Volunteered Geographic Information (VGI) which is a comparatively new means of improving the coverage of monitored areas because it is able to supply supplementary information to the WSN and thus support decision-making in flood risk management. However, there still remains the problem of how to combine WSN data with VGI. In this paper, an attempt is made to investigate AGORA-DS, which is a Spatial Decision Support System (SDSS) that is able to make flood risk management more effective by combining these data sources, i.e. WSN with VGI. This approach is built over a conceptual model that complies with the interoperable standards laid down by the Open Geospatial Consortium (OGC) - e.g. Sensor Observation Service (SOS) and Web Feature Service (WFS) - and seeks to combine and present unified information in a web-based decision support tool. This work was deployed in a real scenario of flood risk management in the town of São Carlos in Brazil. The evidence obtained from this deployment confirmed that interoperable standards can support the integration of data from distinct data sources. In addition, they also show that VGI is able to provide information about areas of the river basin which lack data since there is no appropriate station in the area. Hence it provides a valuable support for the WSN data. It can thus be concluded that AGORA-DS is able to combine information provided by WSN and VGI, and provide useful information for supporting flood risk management.

  12. Modeling the geographic distribution of Ixodes scapularis and Ixodes pacificus (Acari: Ixodidae) in the contiguous United States

    Science.gov (United States)

    Hahn, Micah; Jarnevich, Catherine S.; Monaghan, Andrew J.; Eisen, Rebecca J.

    2016-01-01

    In addition to serving as vectors of several other human pathogens, the black-legged tick, Ixodes scapularis Say, and western black-legged tick, Ixodes pacificus Cooley and Kohls, are the primary vectors of the spirochete (Borrelia burgdorferi ) that causes Lyme disease, the most common vector-borne disease in the United States. Over the past two decades, the geographic range of I. pacificus has changed modestly while, in contrast, the I. scapularis range has expanded substantially, which likely contributes to the concurrent expansion in the distribution of human Lyme disease cases in the Northeastern, North-Central and Mid-Atlantic states. Identifying counties that contain suitable habitat for these ticks that have not yet reported established vector populations can aid in targeting limited vector surveillance resources to areas where tick invasion and potential human risk are likely to occur. We used county-level vector distribution information and ensemble modeling to map the potential distribution of I. scapularis and I. pacificus in the contiguous United States as a function of climate, elevation, and forest cover. Results show that I. pacificus is currently present within much of the range classified by our model as suitable for establishment. In contrast, environmental conditions are suitable for I. scapularis to continue expanding its range into northwestern Minnesota, central and northern Michigan, within the Ohio River Valley, and inland from the southeastern and Gulf coasts. Overall, our ensemble models show suitable habitat for I. scapularis in 441 eastern counties and for I. pacificus in 11 western counties where surveillance records have not yet supported classification of the counties as established.

  13. A conceptual model of the automated credibility assessment of the volunteered geographic information

    International Nuclear Information System (INIS)

    Idris, N H; Jackson, M J; Ishak, M H I

    2014-01-01

    The use of Volunteered Geographic Information (VGI) in collecting, sharing and disseminating geospatially referenced information on the Web is increasingly common. The potentials of this localized and collective information have been seen to complement the maintenance process of authoritative mapping data sources and in realizing the development of Digital Earth. The main barrier to the use of this data in supporting this bottom up approach is the credibility (trust), completeness, accuracy, and quality of both the data input and outputs generated. The only feasible approach to assess these data is by relying on an automated process. This paper describes a conceptual model of indicators (parameters) and practical approaches to automated assess the credibility of information contributed through the VGI including map mashups, Geo Web and crowd – sourced based applications. There are two main components proposed to be assessed in the conceptual model – metadata and data. The metadata component comprises the indicator of the hosting (websites) and the sources of data / information. The data component comprises the indicators to assess absolute and relative data positioning, attribute, thematic, temporal and geometric correctness and consistency. This paper suggests approaches to assess the components. To assess the metadata component, automated text categorization using supervised machine learning is proposed. To assess the correctness and consistency in the data component, we suggest a matching validation approach using the current emerging technologies from Linked Data infrastructures and using third party reviews validation. This study contributes to the research domain that focuses on the credibility, trust and quality issues of data contributed by web citizen providers

  14. The Impact of College Education on Geographic Mobility: Identifying Education Using Multiple Components of Vietnam Draft Risk. NBER Working Paper No. 16463

    Science.gov (United States)

    Malamud, Ofer; Wozniak, Abigail K.

    2010-01-01

    We examine whether higher education is a causal determinant of geographic mobility using variation in college attainment induced by draft-avoidance behavior during the Vietnam War. We use national and state-level induction risk to identify both educational attainment and veteran status among cohorts of affected men observed in the 1980 Census. Our…

  15. Quantile uncertainty and value-at-risk model risk.

    Science.gov (United States)

    Alexander, Carol; Sarabia, José María

    2012-08-01

    This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

  16. Spatiotemporal Modeling of Community Risk

    Science.gov (United States)

    2016-03-01

    Ertugay, and Sebnem Duzgun, “Exploratory and Inferential Methods for Spatio-Temporal Analysis of Residential Fire Clustering in Urban Areas,” Fire ...response in communities.”26 In “Exploratory and Inferential Methods for Spatio-temporal Analysis of Residential Fire Clustering in Urban Areas,” Ceyhan...of fire resources spread across the community. Spatiotemporal modeling shows that actualized risk is dynamic and relatively patterned. Though

  17. Analisis Faktor – Faktor yang Mempengaruhi Jumlah Kejahatan Pencurian Kendaraan Bermotor (Curanmor) Menggunakan Model Geographically Weighted Poisson Regression (Gwpr)

    OpenAIRE

    Haris, Muhammad; Yasin, Hasbi; Hoyyi, Abdul

    2015-01-01

    Theft is an act taking someone else's property, partially or entierely, with intention to have it illegally. Motor vehicle theft is one of the most highlighted crime type and disturbing the communities. Regression analysis is a statistical analysis for modeling the relationships between response variable and predictor variable. If the response variable follows a Poisson distribution or categorized as a count data, so the regression model used is Poisson regression. Geographically Weighted Poi...

  18. Analysis of uncertainty in modeling perceived risks

    International Nuclear Information System (INIS)

    Melnyk, R.; Sandquist, G.M.

    2005-01-01

    Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

  19. Geographical Analysis for Detecting High-Risk Areas for Bovine/Human Rabies Transmitted by the Common Hematophagous Bat in the Amazon Region, Brazil.

    Directory of Open Access Journals (Sweden)

    Fernanda A G de Andrade

    Full Text Available The common hematophagous bat, Desmodus rotundus, is one of the main wild reservoirs of rabies virus in several regions in Latin America. New production practices and changed land use have provided environmental features that have been very favorable for D. rotundus bat populations, making this species the main transmitter of rabies in the cycle that involves humans and herbivores. In the Amazon region, these features include a mosaic of environmental, social, and economic components, which together creates areas with different levels of risk for human and bovine infections, as presented in this work in the eastern Brazilian Amazon.We geo-referenced a total of 175 cases of rabies, of which 88% occurred in bovines and 12% in humans, respectively, and related these cases to a number of different geographical and biological variables. The spatial distribution was analyzed using the Kernel function, while the association with independent variables was assessed using a multi-criterion Analytical Hierarchy Process (AHP technique.The spatiotemporal analysis of the occurrence of rabies in bovines and humans found reduction in the number of cases in the eastern state of Pará, where no more cases were recorded in humans, whereas high infection rates were recorded in bovines in the northeastern part of the state, and low rates in the southeast. The areas of highest risk for bovine rabies are found in the proximity of rivers and highways. In the case of human rabies, the highest concentration of high-risk areas was found where the highway network coincides with high densities of rural and indigenous populations.The high-risk areas for human and bovine rabies are patchily distributed, and related to extensive deforested areas, large herds of cattle, and the presence of highways. These findings provide an important database for the generation of epidemiological models that could support the development of effective prevention measures and controls.

  20. Model risk analysis for risk management and option pricing

    NARCIS (Netherlands)

    Kerkhof, F.L.J.

    2003-01-01

    Due to the growing complexity of products in financial markets, market participants rely more and more on quantitative models for trading and risk management decisions. This introduces a fairly new type of risk, namely, model risk. In the first part of this thesis we investigate the quantitative

  1. Geographic information modeling of Econet of Northwestern Federal District territory on graph theory basis

    Science.gov (United States)

    Kopylova, N. S.; Bykova, A. A.; Beregovoy, D. N.

    2018-05-01

    Based on the landscape-geographical approach, a structural and logical scheme for the Northwestern Federal District Econet has been developed, which can be integrated into the federal and world ecological network in order to improve the environmental infrastructure of the region. The method of Northwestern Federal District Econet organization on the basis of graph theory by means of the Quantum GIS geographic information system is proposed as an effective mean of preserving and recreating the unique biodiversity of landscapes, regulation of the sphere of environmental protection.

  2. Hydrologic connectivity between geographically isolated wetlands and surface water systems: A review of select modeling methods

    Science.gov (United States)

    Heather E. Golden; Charles R. Lane; Devendra M. Amatya; Karl W. Bandilla; Hadas Raanan Kiperwas Kiperwas; Christopher D. Knightes; Herbert. Ssegane

    2014-01-01

    Geographically isolated wetlands (GIW), depressional landscape features entirely surrounded by upland areas, provide a wide range of ecological functions and ecosystem services for human well-being. Current and future ecosystem management and decision-making rely on a solid scientific understanding of how hydrologic processes affect these important GIW services and...

  3. Density-Based Clustering with Geographical Background Constraints Using a Semantic Expression Model

    Directory of Open Access Journals (Sweden)

    Qingyun Du

    2016-05-01

    Full Text Available A semantics-based method for density-based clustering with constraints imposed by geographical background knowledge is proposed. In this paper, we apply an ontological approach to the DBSCAN (Density-Based Geospatial Clustering of Applications with Noise algorithm in the form of knowledge representation for constraint clustering. When used in the process of clustering geographic information, semantic reasoning based on a defined ontology and its relationships is primarily intended to overcome the lack of knowledge of the relevant geospatial data. Better constraints on the geographical knowledge yield more reasonable clustering results. This article uses an ontology to describe the four types of semantic constraints for geographical backgrounds: “No Constraints”, “Constraints”, “Cannot-Link Constraints”, and “Must-Link Constraints”. This paper also reports the implementation of a prototype clustering program. Based on the proposed approach, DBSCAN can be applied with both obstacle and non-obstacle constraints as a semi-supervised clustering algorithm and the clustering results are displayed on a digital map.

  4. Geographic approaches to quantifying the risk environment: a focus on syringe exchange program site access and drug-related law enforcement activities

    Science.gov (United States)

    Cooper, Hannah LF; Bossak, Brian; Tempalski, Barbara; Des Jarlais, Don C.; Friedman, Samuel R.

    2009-01-01

    The concept of the “risk environment” – defined as the “space … [where] factors exogenous to the individual interact to increase the chances of HIV transmission” – draws together the disciplines of public health and geography. Researchers have increasingly turned to geographic methods to quantify dimensions of the risk environment that are both structural and spatial (e.g., local poverty rates). The scientific power of the intersection between public health and geography, however, has yet to be fully mined. In particular, research on the risk environment has rarely applied geographic methods to create neighbourhood-based measures of syringe exchange programs (SEPs) or of drug-related law enforcement activities, despite the fact that these interventions are widely conceptualized as structural and spatial in nature and are two of the most well-established dimensions of the risk environment. To strengthen research on the risk environment, this paper presents a way of using geographic methods to create neighbourhood-based measures of (1) access to SEP sites and (2) exposure to drug-related arrests, and then applies these methods to one setting (New York City). NYC-based results identified substantial cross-neighbourhood variation in SEP site access and in exposure to drug-related arrest rates (even within the subset of neighbourhoods nominally experiencing the same drug-related police strategy). These geographic measures – grounded as they are in conceptualizations of SEPs and drug-related law enforcement strategies – can help develop new arenas of inquiry regarding the impact of these two dimensions of the risk environment on injectors’ health, including exploring whether and how neighbourhood-level access to SEP sites and exposure to drug-related arrests shape a range of outcomes among local injectors. PMID:18963907

  5. Credit Risk Evaluation : Modeling - Analysis - Management

    OpenAIRE

    Wehrspohn, Uwe

    2002-01-01

    An analysis and further development of the building blocks of modern credit risk management: -Definitions of default -Estimation of default probabilities -Exposures -Recovery Rates -Pricing -Concepts of portfolio dependence -Time horizons for risk calculations -Quantification of portfolio risk -Estimation of risk measures -Portfolio analysis and portfolio improvement -Evaluation and comparison of credit risk models -Analytic portfolio loss distributions The thesis contributes to the evaluatio...

  6. Geographical distribution and risk assessment of persistent organic pollutants in golden threads (Nemipterus virgatus) from the northern South China Sea.

    Science.gov (United States)

    Hao, Qing; Sun, Yu-Xin; Xu, Xiang-Rong; Yao, Zi-Wei; Wang, You-Shao; Zhang, Zai-Wang; Luo, Xiao-Jun; Mai, Bi-Xian

    2015-10-01

    Fish are often used as good bioindicators to monitor the occurrence of persistent organic pollutants (POPs) on different scales in recent years. Forty-five golden threads (Nemipterus virgatus) were collected from six sampling sites in the northern South China Sea (SCS) to investigate the geographical distribution of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethane and its metabolites (DDTs). Concentrations of PBDEs, PCBs, and DDTs ranged from 1.3-36.0, 2.3-76.5, 8.3-228 ng/g lipid weight, respectively. The highest PBDEs and DDTs concentrations were found in golden threads from Shantou, owing to the intensive electronic waste recycling activities and rapid development of agriculture. Samples from Haikou had the highest levels of PCBs, probably due to the existence of many shipbuilding yards in the past years. The concentrations of PBDEs and PCBs were found in a decreasing trend from east to west and from north to south, while DDTs concentrations had no obvious trend in the distribution. PCBs were the most prevalent contaminants in Xiamen and Yangjiang, while DDTs were the dominant compounds at the other four sampling sites. Different profiles of POPs at each sampling site may attribute to different pollution sources in the northern SCS. Ratios of (DDD + DDE)/DDTs in golden threads suggested the probability of fresh input of DDT in the northern SCS. The estimated daily intakes of PBDEs, PCBs and DDTs were 0.030-0.069, 0.167-0.258 and 0.105-1.88 ng/kg/day, respectively, which were significantly lower than the acceptable daily intake, suggesting that consumption of golden threads from the northern SCS would not subject the residents in the coastal areas of SCS to significant health risk.

  7. Determination of soil erosion risk in the Mustafakemalpasa River Basin, Turkey, using the revised universal soil loss equation, geographic information system, and remote sensing.

    Science.gov (United States)

    Ozsoy, Gokhan; Aksoy, Ertugrul; Dirim, M Sabri; Tumsavas, Zeynal

    2012-10-01

    Sediment transport from steep slopes and agricultural lands into the Uluabat Lake (a RAMSAR site) by the Mustafakemalpasa (MKP) River is a serious problem within the river basin. Predictive erosion models are useful tools for evaluating soil erosion and establishing soil erosion management plans. The Revised Universal Soil Loss Equation (RUSLE) function is a commonly used erosion model for this purpose in Turkey and the rest of the world. This research integrates the RUSLE within a geographic information system environment to investigate the spatial distribution of annual soil loss potential in the MKP River Basin. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index: The topographic factor was developed from a digital elevation model; the K factor was determined from a combination of the soil map and the geological map; and the land cover factor was generated from Landsat-7 Enhanced Thematic Mapper (ETM) images. According to the model, the total soil loss potential of the MKP River Basin from erosion by water was 11,296,063 Mg year(-1) with an average soil loss of 11.2 Mg year(-1). The RUSLE produces only local erosion values and cannot be used to estimate the sediment yield for a watershed. To estimate the sediment yield, sediment-delivery ratio equations were used and compared with the sediment-monitoring reports of the Dolluk stream gauging station on the MKP River, which collected data for >41 years (1964-2005). This station observes the overall efficiency of the sediment yield coming from the Orhaneli and Emet Rivers. The measured sediment in the Emet and Orhaneli sub-basins is 1,082,010 Mg year(-1) and was estimated to be 1,640,947 Mg year(-1) for the same two sub-basins. The measured sediment yield of the gauge station is 127.6 Mg km(-2) year(-1) but was estimated to be 170.2 Mg km(-2) year(-1). The close match between the sediment amounts estimated using the RUSLE-geographic

  8. Geographic variations in cervical cancer risk in San Luis Potosí state, Mexico: A spatial statistical approach.

    Science.gov (United States)

    Terán-Hernández, Mónica; Ramis-Prieto, Rebeca; Calderón-Hernández, Jaqueline; Garrocho-Rangel, Carlos Félix; Campos-Alanís, Juan; Ávalos-Lozano, José Antonio; Aguilar-Robledo, Miguel

    2016-09-29

    Worldwide, Cervical Cancer (CC) is the fourth most common type of cancer and cause of death in women. It is a significant public health problem, especially in low and middle-income/Gross Domestic Product (GDP) countries. In the past decade, several studies of CC have been published, that identify the main modifiable and non-modifiable CC risk factors for Mexican women. However, there are no studies that attempt to explain the residual spatial variation in CC incidence In Mexico, i.e. spatial variation that cannot be ascribed to known, spatially varying risk factors. This paper uses a spatial statistical methodology that takes into account spatial variation in socio-economic factors and accessibility to health services, whilst allowing for residual, unexplained spatial variation in risk. To describe residual spatial variations in CC risk, we used generalised linear mixed models (GLMM) with both spatially structured and unstructured random effects, using a Bayesian approach to inference. The highest risk is concentrated in the southeast, where the Matlapa and Aquismón municipalities register excessive risk, with posterior probabilities greater than 0.8. The lack of coverage of Cervical Cancer-Screening Programme (CCSP) (RR 1.17, 95 % CI 1.12-1.22), Marginalisation Index (RR 1.05, 95 % CI 1.03-1.08), and lack of accessibility to health services (RR 1.01, 95 % CI 1.00-1.03) were significant covariates. There are substantial differences between municipalities, with high-risk areas mainly in low-resource areas lacking accessibility to health services for CC. Our results clearly indicate the presence of spatial patterns, and the relevance of the spatial analysis for public health intervention. Ignoring the spatial variability means to continue a public policy that does not tackle deficiencies in its national CCSP and to keep disadvantaging and disempowering Mexican women in regard to their health care.

  9. Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata

    Directory of Open Access Journals (Sweden)

    Yu Zou

    2013-07-01

    Full Text Available Reconciling competing desires to build urban models that can be simple and complicated is something of a grand challenge for urban simulation. It also prompts difficulties in many urban policy situations, such as urban sprawl, where simple, actionable ideas may need to be considered in the context of the messily complex and complicated urban processes and phenomena that work within cities. In this paper, we present a novel architecture for achieving both simple and complicated realizations of urban sprawl in simulation. Fine-scale simulations of sprawl geography are run using geographic automata to represent the geographical drivers of sprawl in intricate detail and over fine resolutions of space and time. We use Equation-Free computing to deploy population as a coarse observable of sprawl, which can be leveraged to run automata-based models as short-burst experiments within a meta-simulation framework.

  10. Energy Facility Siting by Means of Environmental Modelling with LANDSAT, Thematic Mapper and Geographic Information System (GIS) Data

    Science.gov (United States)

    1982-01-01

    Currently based on ground and aerial surveys, the land cover data base of the Pennsylvania Power and Light Company is routinely used for modelling the effects of alternative generating plant and transmission line sites on the local and regional environment. The development of a satellite-based geographic information system would facilitate both the preparation of environmental impact statements by power companies and assessment of the data by the Nuclear Regulatory Commission. A cooperative project is planned to demonstrate the methodology for integrating satellite data into an existing geographic information system, d to further evaluate the ability of satellite data in modeling environmental conditions that would be applied in the preparation and assessment of environmental impact statements.

  11. Efficient workload management in geographically distributed data centers leveraging autoregressive models

    Science.gov (United States)

    Altomare, Albino; Cesario, Eugenio; Mastroianni, Carlo

    2016-10-01

    The opportunity of using Cloud resources on a pay-as-you-go basis and the availability of powerful data centers and high bandwidth connections are speeding up the success and popularity of Cloud systems, which is making on-demand computing a common practice for enterprises and scientific communities. The reasons for this success include natural business distribution, the need for high availability and disaster tolerance, the sheer size of their computational infrastructure, and/or the desire to provide uniform access times to the infrastructure from widely distributed client sites. Nevertheless, the expansion of large data centers is resulting in a huge rise of electrical power consumed by hardware facilities and cooling systems. The geographical distribution of data centers is becoming an opportunity: the variability of electricity prices, environmental conditions and client requests, both from site to site and with time, makes it possible to intelligently and dynamically (re)distribute the computational workload and achieve as diverse business goals as: the reduction of costs, energy consumption and carbon emissions, the satisfaction of performance constraints, the adherence to Service Level Agreement established with users, etc. This paper proposes an approach that helps to achieve the business goals established by the data center administrators. The workload distribution is driven by a fitness function, evaluated for each data center, which weighs some key parameters related to business objectives, among which, the price of electricity, the carbon emission rate, the balance of load among the data centers etc. For example, the energy costs can be reduced by using a "follow the moon" approach, e.g. by migrating the workload to data centers where the price of electricity is lower at that time. Our approach uses data about historical usage of the data centers and data about environmental conditions to predict, with the help of regressive models, the values of the

  12. Modelling the ecological vulnerability to forest fires in mediterranean ecosystems using geographic information technologies.

    Science.gov (United States)

    Duguy, Beatriz; Alloza, José Antonio; Baeza, M Jaime; De la Riva, Juan; Echeverría, Maite; Ibarra, Paloma; Llovet, Juan; Cabello, Fernando Pérez; Rovira, Pere; Vallejo, Ramon V

    2012-12-01

    Forest fires represent a major driver of change at the ecosystem and landscape levels in the Mediterranean region. Environmental features and vegetation are key factors to estimate the ecological vulnerability to fire; defined as the degree to which an ecosystem is susceptible to, and unable to cope with, adverse effects of fire (provided a fire occurs). Given the predicted climatic changes for the region, it is urgent to validate spatially explicit tools for assessing this vulnerability in order to support the design of new fire prevention and restoration strategies. This work presents an innovative GIS-based modelling approach to evaluate the ecological vulnerability to fire of an ecosystem, considering its main components (soil and vegetation) and different time scales. The evaluation was structured in three stages: short-term (focussed on soil degradation risk), medium-term (focussed on changes in vegetation), and coupling of the short- and medium-term vulnerabilities. The model was implemented in two regions: Aragón (inland North-eastern Spain) and Valencia (eastern Spain). Maps of the ecological vulnerability to fire were produced at a regional scale. We partially validated the model in a study site combining two complementary approaches that focused on testing the adequacy of model's predictions in three ecosystems, all very common in fire-prone landscapes of eastern Spain: two shrublands and a pine forest. Both approaches were based on the comparison of model's predictions with values of NDVI (Normalized Difference Vegetation Index), which is considered a good proxy for green biomass. Both methods showed that the model's performance is satisfactory when applied to the three selected vegetation types.

  13. The role of geographic information systems inwildlife epidemiology: models of chronic wasting disease in Colorado mule deer

    OpenAIRE

    Farnsworth, Matthew L.; Hoeting, Jennifer A.; Hobbs, N. Thompson; Conner, Mary M.; Burnham, Kenneth P.; Wolfe, Lisa L.; Williams, Elizabeth S.; Theobald, David M.; Miller, Michael W.

    2007-01-01

    The authors present findings from two landscape epidemiology studies of chronic wasting disease (CWD) in northern Colorado mule deer (Odocoileus hemionus). First, the effects of human land use on disease prevalence were explored by formulating a set of models estimating CWD prevalence in relation to differences in human land use, sex and geographic location. Prevalence was higher in developed areas and among male deer suggesting that anthropogenic influences (changes in land use), differences...

  14. Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

    Science.gov (United States)

    Long, Nguyen Phuoc; Lim, Dong Kyu; Mo, Changyeun; Kim, Giyoung; Kwon, Sung Won

    2017-08-17

    Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In this study, we developed a method that employed lipidomics and deep learning to discriminate white rice from Korea to China. A total of 126 white rice of 30 cultivars from different regions were utilized for the method development and validation. By using direct infusion-mass spectrometry-based targeted lipidomics, 17 lysoglycerophospholipids were simultaneously characterized within minutes per sample. Unsupervised data exploration showed a noticeable overlap of white rice between two countries. In addition, lysophosphatidylcholines (lysoPCs) were prominent in white rice from Korea while lysophosphatidylethanolamines (lysoPEs) were enriched in white rice from China. A deep learning prediction model was built using 2014 white rice and validated using two different batches of 2015 white rice. The model accurately discriminated white rice from two countries. Among 10 selected predictors, lysoPC(18:2), lysoPC(14:0), and lysoPE(16:0) were the three most important features. Random forest and gradient boosting machine models also worked well in this circumstance. In conclusion, this study provides an architecture for high-throughput classification of white rice from different geographical origins.

  15. Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia

    OpenAIRE

    Deribe, Kebede; Cano, Jorge; Newport, Melanie J.; Golding, Nick; Pullan, Rachel L.; Sime, Heven; Gebretsadik, Abeba; Assefa, Ashenafi; Kebede, Amha; Hailu, Asrat; Rebollo, Maria P.; Shafi, Oumer; Bockarie, Moses J.; Aseffa, Abraham; Hay, Simon I.

    2015-01-01

    Background\\ud \\ud Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues.\\ud \\ud Methodology\\ud \\ud Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Et...

  16. Environmental modeling and health risk analysis (ACTS/RISK)

    National Research Council Canada - National Science Library

    Aral, M. M

    2010-01-01

    ... presents a review of the topics of exposure and health risk analysis. The Analytical Contaminant Transport Analysis System (ACTS) and Health RISK Analysis (RISK) software tools are an integral part of the book and provide computational platforms for all the models discussed herein. The most recent versions of these two softwa...

  17. Statistical models for competing risk analysis

    International Nuclear Information System (INIS)

    Sather, H.N.

    1976-08-01

    Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined

  18. Risk matrix model for rotating equipment

    Directory of Open Access Journals (Sweden)

    Wassan Rano Khan

    2014-07-01

    Full Text Available Different industries have various residual risk levels for their rotating equipment. Accordingly the occurrence rate of the failures and associated failure consequences categories are different. Thus, a generalized risk matrix model is developed in this study which can fit various available risk matrix standards. This generalized risk matrix will be helpful to develop new risk matrix, to fit the required risk assessment scenario for rotating equipment. Power generation system was taken as case study. It was observed that eight subsystems were under risk. Only vibration monitor system was under high risk category, while remaining seven subsystems were under serious and medium risk categories.

  19. The use of geographical information systems for disaster risk reduction strategies: a case study of Volcan de Colima, Mexico

    Science.gov (United States)

    Landeg, O.

    Contemporary disaster risk management requires the analysis of vulnerability and hazard exposure, which is imperative at Volcan de Colima (VdC), Mexico, due to the predicted, large-magnitude eruption forecast to occur before 2025. The methods used to gauge social vulnerability included the development and application of proxies to census records, the undertaking of a building vulnerability survey and the spatial mapping of civil and emergency infrastructure. Hazard exposure was assessed using primary modelling of laharic events and the digitalisation of secondary data sources detailing the modelled extent of pyroclastic flows and tephra deposition associated with a large-magnitude (VEI 5) eruption at VdC. The undertaking and analysis of a risk perception survey of the population enabled an understanding of the cognitive behaviour of residents towards the volcanic risk. In comparison to the published hazard map, the GIS analysis highlighted an underestimation of lahar hazard on the western flank of VdC and the regional tephra hazard. Vulnerability analysis identified three communities where social deprivation is relatively high, and those with significant elderly and transient populations near the volcano. Furthermore, recognition of the possibility of an eruption in the near future was found to be low across the study region. These results also contributed to the analysis of emergency management procedures and the preparedness of the regional authorities. This multidisciplinary research programme demonstrates the success of applying a GIS platform to varied integrative spatial and temporal analysis. Furthermore, ascertaining the impact of future activity at VdC upon its surrounding populations permits the evaluation of emergency preparedness and disaster risk reduction strategies.

  20. Developing landscape habitat models for rare amphibians with small geographic ranges: a case study of Siskiyou Mountains salamanders in the western USA

    Science.gov (United States)

    Nobuya Suzuki; Deanna H. Olson; Edward C. Reilly

    2007-01-01

    To advance the development of conservation planning for rare species with small geographic ranges, we determined habitat associations of Siskiyou Mountains salamanders (Plethodon stormi) and developed habitat suitability models at fine (10 ha), medium (40 ha), and broad (202 ha) spatial scales using available geographic information systems data and...

  1. Models for assessing and managing credit risk

    Directory of Open Access Journals (Sweden)

    Neogradi Slađana

    2014-01-01

    Full Text Available This essay deals with the definition of a model for assessing and managing credit risk. Risk is an inseparable component of any average and normal credit transaction. Looking at the different aspects of the identification and classification of risk in the banking industry as well as representation of the key components of modern risk management. In the first part of the essay will analyze how the impact of credit risk on bank and empirical models for determining the financial difficulties in which the company can be found. Bank on the basis of these models can reduce number of approved risk assets. In the second part, we consider models for improving credit risk with emphasis on Basel I, II and III, and the third part, we conclude that the most appropriate model and gives the best effect for measuring credit risk in domestic banks.

  2. RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE

    Directory of Open Access Journals (Sweden)

    Ming-Chang LEE

    2015-07-01

    Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets.  The risk analysis and asset allocation are the key technology of banking and risk management.  The aim of this paper, build a loan portfolio optimization model based on risk analysis.  Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank.  In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm.  This paper solves the highly difficult problem by matrix operation method.  Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space.  It is easy calculation in proposed method.

  3. Concentrations and geographical variations of selected toxic elements in meat from semi-domesticated reindeer (Rangifer tarandus tarandus L.) in mid- and northern Norway: evaluation of risk assessment.

    Science.gov (United States)

    Hassan, Ammar Ali; Brustad, Magritt; Sandanger, Torkjel M

    2012-05-01

    Meat samples (n = 100) from semi-domesticated reindeer (Rangifer tarandus tarandus L.) were randomly collected from 10 grazing districts distributed over four Norwegian counties in 2008 and 2009. The main aim was to study concentrations and geographical variations in selected toxic elements; cadmium (Cd), lead (Pb), arsenic (As), copper (Cu), nickel (Ni) and vanadium (V) in order to assess the risk associated with reindeer meat consumption. Sample solutions were analysed using an inductively coupled plasma high resolution mass spectrometer (ICP-HRMS), whereas analysis of variance (ANOVA) was used for statistical analyses. Geographical variations in element concentrations were revealed, with As and Cd demonstrating the largest geographical differences. No clear geographical gradient was observed except for the east-west downward gradient for As. The As concentrations were highest in the vicinity of the Russian border, and only Cd was shown to increase with age (p < 0.05). Sex had no significant effect on the concentration of the studied elements. The concentrations of all the studied elements in reindeer meat were generally low and considerably below the maximum levels (ML) available for toxic elements set by the European Commission (EC). Thus, reindeer meat is not likely to be a significant contributor to the human body burden of toxic elements.

  4. Offer acceptance practices and geographic variability in allocation model for end-stage liver disease at transplant.

    Science.gov (United States)

    Wey, Andrew; Pyke, Joshua; Schladt, David P; Gentry, Sommer E; Weaver, Tim; Salkowski, Nicholas; Kasiske, Bertram L; Israni, Ajay K; Snyder, Jon J

    2018-04-01

    Offer acceptance practices may cause geographic variability in allocation Model for End-Stage Liver Disease (aMELD) score at transplant and could magnify the effect of donor supply and demand on aMELD variability. To evaluate these issues, offer acceptance practices of liver transplant programs and donation service areas (DSAs) were estimated using offers of livers from donors recovered between January 1, 2016, and December 31, 2016. Offer acceptance practices were compared with liver yield, local placement of transplanted livers, donor supply and demand, and aMELD at transplant. Offer acceptance was associated with liver yield (odds ratio, 1.32; P offer acceptance (r = 0.09; P = 0.50). Additionally, the association between DSA-level donor-to-candidate ratios and aMELD at transplant did not change after adjustment for offer acceptance. The average squared difference in median aMELD at transplant across DSAs was 24.6; removing the effect of donor-to-candidate ratios reduced the average squared differences more than removing the effect of program-level offer acceptance (33% and 15% reduction, respectively). Offer acceptance practices and donor-to-candidate ratios independently contributed to geographic variability in aMELD at transplant. Thus, neither offer acceptance nor donor-to-candidate ratios can explain all of the geographic variability in aMELD at transplant. Liver Transplantation 24 478-487 2018 AASLD. © 2018 by the American Association for the Study of Liver Diseases.

  5. MODELING CREDIT RISK THROUGH CREDIT SCORING

    OpenAIRE

    Adrian Cantemir CALIN; Oana Cristina POPOVICI

    2014-01-01

    Credit risk governs all financial transactions and it is defined as the risk of suffering a loss due to certain shifts in the credit quality of a counterpart. Credit risk literature gravitates around two main modeling approaches: the structural approach and the reduced form approach. In addition to these perspectives, credit risk assessment has been conducted through a series of techniques such as credit scoring models, which form the traditional approach. This paper examines the evolution of...

  6. A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

    Science.gov (United States)

    Zhang, Feng; Xu, Yuetong; Chou, Jarong

    2016-01-01

    The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. PMID:27681730

  7. A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

    Directory of Open Access Journals (Sweden)

    Feng Zhang

    2016-09-01

    Full Text Available The service of sensor device in Emerging Sensor Networks (ESNs is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples.

  8. Use of geographically weighted logistic regression to quantify spatial variation in the environmental and sociodemographic drivers of leptospirosis in Fiji: a modelling study

    Directory of Open Access Journals (Sweden)

    Helen J Mayfield, PhD

    2018-05-01

    Full Text Available Summary: Background: Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR to provide insights into the ecoepidemiology of human leptospirosis in Fiji. Methods: We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1–90 years was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR for each covariate. Findings: The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but

  9. A comparison of models for risk assessment

    International Nuclear Information System (INIS)

    Kellerer, A.M.; Jing Chen

    1993-01-01

    Various mathematical models have been used to represent the dependence of excess cancer risk on dose, age and time since exposure. For solid cancers, i.e. all cancers except leukaemia, the so-called relative risk model is usually employed. However, there can be quite different relative risk models. The most usual model for the quantification of excess tumour rate among the atomic bomb survivors has been a dependence of the relative risk on age at exposure, but it has been shown recently that an age attained model can be equally applied, to represent the observations among the atomic bomb survivors. The differences between the models and their implications are explained. It is also shown that the age attained model is similar to the approaches that have been used in the analysis of lung cancer incidence among radon exposed miners. A more unified approach to modelling of radiation risks can thus be achieved. (3 figs.)

  10. Competing Risks and Multistate Models with R

    CERN Document Server

    Beyersmann, Jan; Schumacher, Martin

    2012-01-01

    This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.

  11. Modeling Research Project Risks with Fuzzy Maps

    Science.gov (United States)

    Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

    2009-01-01

    The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…

  12. Deterrence and Geographical Externalities in Auto Theft

    OpenAIRE

    Marco Gonzalez-Navarro

    2013-01-01

    Understanding the degree of geographical crime displacement is crucial for the design of crime prevention policies. This paper documents changes in automobile theft risk that were generated by the plausibly exogenous introduction of Lojack, a highly effective stolen vehicle recovery device, into a number of new Ford car models in some Mexican states, but not others. Lojack-equipped vehicles in Lojack-coverage states experienced a 48 percent reduction in theft risk due to deterrence effects. H...

  13. Risk Modelling for Passages in Approach Channel

    Directory of Open Access Journals (Sweden)

    Leszek Smolarek

    2013-01-01

    Full Text Available Methods of multivariate statistics, stochastic processes, and simulation methods are used to identify and assess the risk measures. This paper presents the use of generalized linear models and Markov models to study risks to ships along the approach channel. These models combined with simulation testing are used to determine the time required for continuous monitoring of endangered objects or period at which the level of risk should be verified.

  14. Modeling for operational event risk assessment

    International Nuclear Information System (INIS)

    Sattison, M.B.

    1997-01-01

    The U.S. Nuclear Regulatory Commission has been using risk models to evaluate the risk significance of operational events in U.S. commercial nuclear power plants for more seventeen years. During that time, the models have evolved in response to the advances in risk assessment technology and insights gained with experience. Evaluation techniques fall into two categories, initiating event assessments and condition assessments. The models used for these analyses have become uniquely specialized for just this purpose

  15. MATHEMATICAL RISK ANALYSIS: VIA NICHOLAS RISK MODEL AND BAYESIAN ANALYSIS

    Directory of Open Access Journals (Sweden)

    Anass BAYAGA

    2010-07-01

    Full Text Available The objective of this second part of a two-phased study was to explorethe predictive power of quantitative risk analysis (QRA method andprocess within Higher Education Institution (HEI. The method and process investigated the use impact analysis via Nicholas risk model and Bayesian analysis, with a sample of hundred (100 risk analysts in a historically black South African University in the greater Eastern Cape Province.The first findings supported and confirmed previous literature (KingIII report, 2009: Nicholas and Steyn, 2008: Stoney, 2007: COSA, 2004 that there was a direct relationship between risk factor, its likelihood and impact, certiris paribus. The second finding in relation to either controlling the likelihood or the impact of occurrence of risk (Nicholas risk model was that to have a brighter risk reward, it was important to control the likelihood ofoccurrence of risks as compared with its impact so to have a direct effect on entire University. On the Bayesian analysis, thus third finding, the impact of risk should be predicted along three aspects. These aspects included the human impact (decisions made, the property impact (students and infrastructural based and the business impact. Lastly, the study revealed that although in most business cases, where as business cycles considerably vary dependingon the industry and or the institution, this study revealed that, most impacts in HEI (University was within the period of one academic.The recommendation was that application of quantitative risk analysisshould be related to current legislative framework that affects HEI.

  16. Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches

    Directory of Open Access Journals (Sweden)

    Romano Ngui

    2014-05-01

    Full Text Available Soil-transmitted helminth (STH infections in Malaysia are still highly prevalent, especially in rural and remote communities. Complete estimations of the total disease burden in the country has not been performed, since available data are not easily accessible in the public domain. The current study utilised geographical information system (GIS to collate and map the distribution of STH infections from available empirical survey data in Peninsular Malaysia, highlighting areas where information is lacking. The assembled database, comprising surveys conducted between 1970 and 2012 in 99 different locations, represents one of the most comprehensive compilations of STH infections in the country. It was found that the geographical distribution of STH varies considerably with no clear pattern across the surveyed locations. Our attempt to generate predictive risk maps of STH infections on the basis of ecological limits such as climate and other environmental factors shows that the prevalence of Ascaris lumbricoides is low along the western coast and the southern part of the country, whilst the prevalence is high in the central plains and in the North. In the present study, we demonstrate that GIS can play an important role in providing data for the implementation of sustainable and effective STH control programmes to policy-makers and authorities in charge.

  17. Korean risk assessment model for breast cancer risk prediction.

    Science.gov (United States)

    Park, Boyoung; Ma, Seung Hyun; Shin, Aesun; Chang, Myung-Chul; Choi, Ji-Yeob; Kim, Sungwan; Han, Wonshik; Noh, Dong-Young; Ahn, Sei-Hyun; Kang, Daehee; Yoo, Keun-Young; Park, Sue K

    2013-01-01

    We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk. Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail's equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort. The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (pKorean women, especially urban women.

  18. Geographical variation of overweight, obesity and related risk factors: Findings from the European Health Examination Survey in Luxembourg, 2013-2015.

    Science.gov (United States)

    Samouda, Hanen; Ruiz-Castell, Maria; Bocquet, Valery; Kuemmerle, Andrea; Chioti, Anna; Dadoun, Frédéric; Kandala, Ngianga-Bakwin; Stranges, Saverio

    2018-01-01

    The analyses of geographic variations in the prevalence of major chronic conditions, such as overweight and obesity, are an important public health tool to identify "hot spots" and inform allocation of funding for policy and health promotion campaigns, yet rarely performed. Here we aimed at exploring, for the first time in Luxembourg, potential geographic patterns in overweight/obesity prevalence in the country, adjusted for several demographic, socioeconomic, behavioural and health status characteristics. Data came from 720 men and 764 women, 25-64 years old, who participated in the European Health Examination Survey in Luxembourg (2013-2015). To investigate the geographical variation, geo-additive semi-parametric mixed model and Bayesian modelisations based on Markov Chain Monte Carlo techniques for inference were performed. Large disparities in the prevalence of overweight and obesity were found between municipalities, with the highest rates of obesity found in 3 municipalities located in the South-West of the country. Bayesian approach also underlined a nonlinear effect of age on overweight and obesity in both genders (significant in men) and highlighted the following risk factors: 1. country of birth for overweight in men born in a non-European country (Posterior Odds Ratio (POR): 3.24 [1.61-8.69]) and women born in Portugal (POR: 2.44 [1.25-4.43]), 2. low educational level (secondary or below) for overweight (POR: 1.66 (1.06-2.72)] and obesity (POR:2.09 [1.05-3.65]) in men, 3. single marital status for obesity in women (POR: 2.20 [1.24-3.91]), 4.fair (men: POR: 3.19 [1.58-6.79], women: POR: 2.24 [1.33-3.73]) to very bad health perception (men: POR: 15.01 [2.16-98.09]) for obesity, 5. sleeping more than 6 hours for obesity in unemployed men (POR: 3.66 [2.02-8.03]). Protective factors highlighted were: 1. single marital status against overweight (POR: [0.60 (0.38-0.96)]) and obesity (POR: 0.39 [0.16-0.84]) in men, 2. the fact to be widowed against overweight in

  19. BETR-World: a geographically explicit model of chemical fate: application to transport of α-HCH to the Arctic

    International Nuclear Information System (INIS)

    Toose, L.; Woodfine, D.G.; MacLeod, M.; Mackay, D.; Gouin, J.

    2004-01-01

    The Berkeley-Trent (BETR)-World model, a 25 compartment, geographically explicit fugacity-based model is described and applied to evaluate the transport of chemicals from temperate source regions to receptor regions (such as the Arctic). The model was parameterized using GIS and an array of digital data on weather, oceans, freshwater, vegetation and geo-political boundaries. This version of the BETR model framework includes modification of atmospheric degradation rates by seasonally variable hydroxyl radical concentrations and temperature. Degradation rates in all other compartments vary with seasonally changing temperature. Deposition to the deep ocean has been included as a loss mechanism. A case study was undertaken for α-HCH. Dynamic emission scenarios were estimated for each of the 25 regions. Predicted environmental concentrations showed good agreement with measured values for the northern regions in air, and fresh and oceanic water and with the results from a previous model of global chemical fate. Potential for long-range transport and deposition to the Arctic region was assessed using a Transfer Efficiency combined with estimated emissions. European regions and the Orient including China have a high potential to contribute α-HCH contamination in the Arctic due to high rates of emission in these regions despite low Transfer Efficiencies. Sensitivity analyses reveal that the performance and reliability of the model is strongly influenced by parameters controlling degradation rates. - A geographically explicit multi-compartment model is applied to the transport of α-HCH to the Arctic, showing Europe and the Orient are key sources

  20. The effects of photovoltaic electricity injection into microgrids: Combination of Geographical Information Systems, multicriteria decision methods and electronic control modeling

    International Nuclear Information System (INIS)

    Roa-Escalante, Gino de Jesús; Sánchez-Lozano, Juan Miguel; Faxas, Juan-Gabriel; García-Cascales, M. Socorro; Urbina, Antonio

    2015-01-01

    Highlights: • Geographical Information Systems can be used as a support to classify the viable locations for photovoltaic facilities. • Multicriteria decision methods are useful tools to choose the optimal locations for photovoltaic systems. • Variations of photovoltaic power injected into the grid have been calculated for the optimum locations. • Grid stabilization can be achieved within 500 ms with electronic control strategies. - Abstract: This article presents a model to calculate the impact on the grid of the injection of electricity generated from photovoltaic systems. The methodology combines the use of Geographical Information System tools to classify the optimal locations for the installation of photovoltaic systems with the calculation of the impact into microgrids of the electricity generated in such locations. The case study is focused on Murcia region, in South-east Spain, and on medium size photovoltaic systems. The locations have been selected from a Geographical Information System database including several parameters, and evaluated and classified using a fuzzy version of the multicriteria decision method called Technique for Order Preference by Similarity to Ideal Solution. In order to obtain the weights for the criteria used in the evaluation, the Analytic Hierarchy Process has been used. Finally, using meteorological data from a small set of possible locations, the impact on the grid arising from the injection of power generated from photovoltaic systems that are connected to the grid via a module implementing different control electronic strategies has been calculated. Different electronic control strategies have been modeled to demonstrate that stabilization of the electrical parameters of a microgrid can be obtained within 500 ms in all cases, even when a relatively large power surge, or slower variations, are injected into the grid from the medium size photovoltaic systems

  1. Hierarchical Distributed-Lag Models: Exploring Varying Geographic Scale and Magnitude in Associations Between the Built Environment and Health.

    Science.gov (United States)

    Baek, Jonggyu; Sanchez-Vaznaugh, Emma V; Sánchez, Brisa N

    2016-03-15

    It is well known that associations between features of the built environment and health depend on the geographic scale used to construct environmental attributes. In the built environment literature, it has long been argued that geographic scales may vary across study locations. However, this hypothesized variation has not been systematically examined due to a lack of available statistical methods. We propose a hierarchical distributed-lag model (HDLM) for estimating the underlying overall shape of food environment-health associations as a function of distance from locations of interest. This method enables indirect assessment of relevant geographic scales and captures area-level heterogeneity in the magnitudes of associations, along with relevant distances within areas. The proposed model was used to systematically examine area-level variation in the association between availability of convenience stores around schools and children's weights. For this case study, body mass index (weight kg)/height (m)2) z scores (BMIz) for 7th grade children collected via California's 2001-2009 FitnessGram testing program were linked to a commercial database that contained locations of food outlets statewide. Findings suggested that convenience store availability may influence BMIz only in some places and at varying distances from schools. Future research should examine localized environmental or policy differences that may explain the heterogeneity in convenience store-BMIz associations. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  2. Transmission risk assessment of invasive fluke Fascioloides magna using GIS-modelling and multicriteria analysis methods

    Directory of Open Access Journals (Sweden)

    Juhásová L.

    2017-06-01

    Full Text Available The combination of multicriteria analysis (MCA, particularly analytic hierarchy process (AHP and geographic information system (GIS were applied for transmission risk assessment of Fascioloides magna (Trematoda; Fasciolidae in south-western Slovakia. Based on the details on F. magna life cycle, the following risk factors (RF of parasite transmission were determined: intermediate (RFIH and final hosts (RFFH (biological factors, annual precipitation (RFAP, land use (RFLU, flooded area (RFFA, and annual mean air temperature (RFAT (environmental factors. Two types of risk analyses were modelled: (1 potential risk analysis was focused on the determination of the potential risk of parasite transmission into novel territories (data on F. magna occurrence were excluded; (2 actual risk analysis considered also the summary data on F. magna occurrence in the model region (risk factor parasite occurrence RFPO included in the analysis. The results of the potential risk analysis provided novel distribution pattern and revealed new geographical area as the potential risk zone of F. magna occurrence. Although the actual risk analysis revealed all four risk zones of F. magna transmission (acceptable, moderate, undesirable and unacceptable, its outputs were significantly affected by the data on parasite occurrence what reduced the informative value of the actual transmission risk assessment.

  3. A Critical Review of the Integration of Geographic Information System and Building Information Modelling at the Data Level

    Directory of Open Access Journals (Sweden)

    Junxiang Zhu

    2018-02-01

    Full Text Available The benefits brought by the integration of Building Information Modelling (BIM and Geographic Information Systems (GIS are being proved by more and more research. The integration of the two systems is difficult for many reasons. Among them, data incompatibility is the most significant, as BIM and GIS data are created, managed, analyzed, stored, and visualized in different ways in terms of coordinate systems, scope of interest, and data structures. The objective of this paper is to review the relevant research papers to (1 identify the most relevant data models used in BIM/GIS integration and understand their advantages and disadvantages; (2 consider the possibility of other data models that are available for data level integration; and (3 provide direction on the future of BIM/GIS data integration.

  4. Geographically Weighted Regression Model with Kernel Bisquare and Tricube Weighted Function on Poverty Percentage Data in Central Java Province

    Science.gov (United States)

    Nugroho, N. F. T. A.; Slamet, I.

    2018-05-01

    Poverty is a socio-economic condition of a person or group of people who can not fulfil their basic need to maintain and develop a dignified life. This problem still cannot be solved completely in Central Java Province. Currently, the percentage of poverty in Central Java is 13.32% which is higher than the national poverty rate which is 11.13%. In this research, data of percentage of poor people in Central Java Province has been analyzed through geographically weighted regression (GWR). The aim of this research is therefore to model poverty percentage data in Central Java Province using GWR with weighted function of kernel bisquare, and tricube. As the results, we obtained GWR model with bisquare and tricube kernel weighted function on poverty percentage data in Central Java province. From the GWR model, there are three categories of region which are influenced by different of significance factors.

  5. ISM Approach to Model Offshore Outsourcing Risks

    Directory of Open Access Journals (Sweden)

    Sunand Kumar

    2014-07-01

    Full Text Available In an effort to achieve a competitive advantage via cost reductions and improved market responsiveness, organizations are increasingly employing offshore outsourcing as a major component of their supply chain strategies. But as evident from literature number of risks such as Political risk, Risk due to cultural differences, Compliance and regulatory risk, Opportunistic risk and Organization structural risk, which adversely affect the performance of offshore outsourcing in a supply chain network. This also leads to dissatisfaction among different stake holders. The main objective of this paper is to identify and understand the mutual interaction among various risks which affect the performance of offshore outsourcing.  To this effect, authors have identified various risks through extant review of literature.  From this information, an integrated model using interpretive structural modelling (ISM for risks affecting offshore outsourcing is developed and the structural relationships between these risks are modeled.  Further, MICMAC analysis is done to analyze the driving power and dependency of risks which shall be helpful to managers to identify and classify important criterions and to reveal the direct and indirect effects of each criterion on offshore outsourcing. Results show that political risk and risk due to cultural differences are act as strong drivers.

  6. Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

    Science.gov (United States)

    Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

    2017-03-01

    Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

  7. Population Structure in the Model Grass Brachypodium distachyon Is Highly Correlated with Flowering Differences across Broad Geographic Areas

    Directory of Open Access Journals (Sweden)

    Ludmila Tyler

    2016-07-01

    Full Text Available The small, annual grass (L. Beauv., a close relative of wheat ( L. and barley ( L., is a powerful model system for cereals and bioenergy grasses. Genome-wide association studies (GWAS of natural variation can elucidate the genetic basis of complex traits but have been so far limited in by the lack of large numbers of well-characterized and sufficiently diverse accessions. Here, we report on genotyping-by-sequencing (GBS of 84 , seven , and three accessions with diverse geographic origins including Albania, Armenia, Georgia, Italy, Spain, and Turkey. Over 90,000 high-quality single-nucleotide polymorphisms (SNPs distributed across the Bd21 reference genome were identified. Our results confirm the hybrid nature of the genome, which appears as a mosaic of -like and -like sequences. Analysis of more than 50,000 SNPs for the accessions revealed three distinct, genetically defined populations. Surprisingly, these genomic profiles are associated with differences in flowering time rather than with broad geographic origin. High levels of differentiation in loci associated with floral development support the differences in flowering phenology between populations. Genome-wide association studies combining genotypic and phenotypic data also suggest the presence of one or more photoperiodism, circadian clock, and vernalization genes in loci associated with flowering time variation within populations. Our characterization elucidates genes underlying population differences, expands the germplasm resources available for , and illustrates the feasibility and limitations of GWAS in this model grass.

  8. Virulence Studies of Different Sequence Types and Geographical Origins of Streptococcus suis Serotype 2 in a Mouse Model of Infection

    Directory of Open Access Journals (Sweden)

    Jean-Philippe Auger

    2016-07-01

    Full Text Available Multilocus sequence typing previously identified three predominant sequence types (STs of Streptococcus suis serotype 2: ST1 strains predominate in Eurasia while North American (NA strains are generally ST25 and ST28. However, ST25/ST28 and ST1 strains have also been isolated in Asia and NA, respectively. Using a well-standardized mouse model of infection, the virulence of strains belonging to different STs and different geographical origins was evaluated. Results demonstrated that although a certain tendency may be observed, S. suis serotype 2 virulence is difficult to predict based on ST and geographical origin alone; strains belonging to the same ST presented important differences of virulence and did not always correlate with origin. The only exception appears to be NA ST28 strains, which were generally less virulent in both systemic and central nervous system (CNS infection models. Persistent and high levels of bacteremia accompanied by elevated CNS inflammation are required to cause meningitis. Although widely used, in vitro tests such as phagocytosis and killing assays require further standardization in order to be used as predictive tests for evaluating virulence of strains. The use of strains other than archetypal strains has increased our knowledge and understanding of the S. suis serotype 2 population dynamics.

  9. Geographical accessibility and spatial coverage modeling of the primary health care network in the Western Province of Rwanda

    Directory of Open Access Journals (Sweden)

    Huerta Munoz Ulises

    2012-09-01

    Full Text Available Abstract Background Primary health care is essential in improving and maintaining the health of populations. It has the potential to accelerate achievement of the Millennium Development Goals and fulfill the “Health for All” doctrine of the Alma-Ata Declaration. Understanding the performance of the health system from a geographic perspective is important for improved health planning and evidence-based policy development. The aims of this study were to measure geographical accessibility, model spatial coverage of the existing primary health facility network, estimate the number of primary health facilities working under capacity and the population underserved in the Western Province of Rwanda. Methods This study uses health facility, population and ancillary data for the Western Province of Rwanda. Three different travel scenarios utilized by the population to attend the nearest primary health facility were defined with a maximum travelling time of 60 minutes: Scenario 1 – walking; Scenario 2 – walking and cycling; and Scenario 3 – walking and public transportation. Considering these scenarios, a raster surface of travel time between primary health facilities and population was developed. To model spatial coverage and estimate the number of primary health facilities working under capacity, the catchment area of each facility was calculated by taking into account population coverage capacity, the population distribution, the terrain topography and the travelling modes through the different land categories. Results Scenario 2 (walking and cycling has the highest degree of geographical accessibility followed by Scenario 3 (walking and public transportation. The lowest level of accessibility can be observed in Scenario 1 (walking. The total population covered differs depending on the type of travel scenario. The existing primary health facility network covers only 26.6% of the population in Scenario 1. In Scenario 2, the use of a bicycle

  10. Decision making support of the management of technogenically contaminated territories basing on risk analysis with use of geographic information technology

    International Nuclear Information System (INIS)

    Yatsalo, B.I.; Demin, V.F.

    2002-01-01

    Overall questions of decision making support of the contaminated territories management on a basis of risk assessment were considered. Characteristics and possibilities of the applied geoinformation system of decision making support PRANA developed for the risk control and rehabilitation of contaminated territories are demonstrated. The PRANA system involves estimations of all fundamental characteristics of risk during analysis of results and contaminated territories management [ru

  11. Concordance for prognostic models with competing risks

    DEFF Research Database (Denmark)

    Wolbers, Marcel; Blanche, Paul; Koller, Michael T

    2014-01-01

    The concordance probability is a widely used measure to assess discrimination of prognostic models with binary and survival endpoints. We formally define the concordance probability for a prognostic model of the absolute risk of an event of interest in the presence of competing risks and relate i...

  12. Why operational risk modelling creates inverse incentives

    NARCIS (Netherlands)

    Doff, R.

    2015-01-01

    Operational risk modelling has become commonplace in large international banks and is gaining popularity in the insurance industry as well. This is partly due to financial regulation (Basel II, Solvency II). This article argues that operational risk modelling is fundamentally flawed, despite efforts

  13. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    Science.gov (United States)

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  14. Methodological issues in cardiovascular epidemiology: the risk of determining absolute risk through statistical models

    Directory of Open Access Journals (Sweden)

    Demosthenes B Panagiotakos

    2006-09-01

    Full Text Available Demosthenes B Panagiotakos, Vassilis StavrinosOffice of Biostatistics, Epidemiology, Department of Dietetics, Nutrition, Harokopio University, Athens, GreeceAbstract: During the past years there has been increasing interest in the development of cardiovascular disease functions that predict future events at individual level. However, this effort has not been so far very successful, since several investigators have reported large differences in the estimation of the absolute risk among different populations. For example, it seems that predictive models that have been derived from US or north European populations  overestimate the incidence of cardiovascular events in south European and Japanese populations. A potential explanation could be attributed to several factors such as geographical, cultural, social, behavioral, as well as genetic variations between the investigated populations in addition to various methodological, statistical, issues relating to the estimation of these predictive models. Based on current literature it can be concluded that, while risk prediction of future cardiovascular events is a useful tool and might be valuable in controlling the burden of the disease in a population, further work is required to improve the accuracy of the present predictive models.Keywords: cardiovascular disease, risk, models

  15. Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

    Science.gov (United States)

    Astuti Thamrin, Sri; Taufik, Irfan

    2018-03-01

    Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

  16. Calculating excess lifetime risk in relative risk models

    International Nuclear Information System (INIS)

    Vaeth, M.; Pierce, D.A.

    1990-01-01

    When assessing the impact of radiation exposure it is common practice to present the final conclusions in terms of excess lifetime cancer risk in a population exposed to a given dose. The present investigation is mainly a methodological study focusing on some of the major issues and uncertainties involved in calculating such excess lifetime risks and related risk projection methods. The age-constant relative risk model used in the recent analyses of the cancer mortality that was observed in the follow-up of the cohort of A-bomb survivors in Hiroshima and Nagasaki is used to describe the effect of the exposure on the cancer mortality. In this type of model the excess relative risk is constant in age-at-risk, but depends on the age-at-exposure. Calculation of excess lifetime risks usually requires rather complicated life-table computations. In this paper we propose a simple approximation to the excess lifetime risk; the validity of the approximation for low levels of exposure is justified empirically as well as theoretically. This approximation provides important guidance in understanding the influence of the various factors involved in risk projections. Among the further topics considered are the influence of a latent period, the additional problems involved in calculations of site-specific excess lifetime cancer risks, the consequences of a leveling off or a plateau in the excess relative risk, and the uncertainties involved in transferring results from one population to another. The main part of this study relates to the situation with a single, instantaneous exposure, but a brief discussion is also given of the problem with a continuous exposure at a low-dose rate

  17. Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors.

    Science.gov (United States)

    He, Jinwei; Ge, Miao; Wang, Congxia; Jiang, Naigui; Zhang, Mingxin; Yun, Pujun

    2014-07-01

    The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X1), annual duration of sunshine (X2), annual mean air temperature (X3), annual mean relative humidity (X4), annual precipitation amount (X5), annual air temperature range (X6) and annual mean wind speed (X7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging's method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.

  18. Factors affecting CO_2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model

    International Nuclear Information System (INIS)

    Xu, Bin; Lin, Boqiang

    2017-01-01

    China is currently the world's largest emitter of carbon dioxide. Considered as a large agricultural country, carbon emission in China’s agriculture sector keeps on growing rapidly. It is, therefore, of great importance to investigate the driving forces of carbon dioxide emissions in this sector. The traditional regression estimation can only get “average” and “global” parameter estimates; it excludes the “local” parameter estimates which vary across space in some spatial systems. Geographically weighted regression embeds the latitude and longitude of the sample data into the regression parameters, and uses the local weighted least squares method to estimate the parameters point–by–point. To reveal the nonstationary spatial effects of driving forces, geographically weighted regression model is employed in this paper. The results show that economic growth is positively correlated with emissions, with the impact in the western region being less than that in the central and eastern regions. Urbanization is positively related to emissions but produces opposite effects pattern. Energy intensity is also correlated with emissions, with a decreasing trend from the eastern region to the central and western regions. Therefore, policymakers should take full account of the spatial nonstationarity of driving forces in designing emission reduction policies. - Highlights: • We explore the driving forces of CO_2 emissions in the agriculture sector. • Urbanization is positively related to emissions but produces opposite effect pattern. • The effect of energy intensity declines from the eastern region to western region.

  19. Geographical variations in the prevalence and management of cardiovascular risk factors in outpatients with CAD: Data from the contemporary CLARIFY registry.

    Science.gov (United States)

    Ferrari, Roberto; Ford, Ian; Greenlaw, Nicola; Tardif, Jean-Claude; Tendera, Michal; Abergel, Hélène; Fox, Kim; Hu, Dayi; Shalnova, Svetlana; Steg, Ph Gabriel

    2015-08-01

    To determine the current prevalence and control of major cardiovascular risk factors in stable CAD outpatients worldwide. We analysed variations in cardiovascular risk factors in stable CAD outpatients from CLARIFY, a 5-year observational longitudinal cohort study, in seven geographical zones (Western/Central Europe; Canada/South Africa/Australia/UK; Eastern Europe; Central/South America; Middle East; East Asia; and India). Patient presentation (N=32,954, mean age 64.2 years, 78% male) varied between zones, as did prevalence of risk factors (all p Asia) to 42% (Middle East), raised blood pressure from 28% (Central/South America and East Asia) to 48% (Eastern Europe), raised LDL cholesterol from 24% (Canada/South Africa/Australia/UK) to 65% (Eastern Europe), elevated heart rate (≥70 bpm) from 38% (Western/Central Europe) to 78% (India), diabetes from 17% (Eastern Europe) to 60% (Middle East), and smoking from 6% (Central/South America) to 19% (Eastern Europe). Aspirin and lipid-lowering drugs were widely used everywhere (≥84% and ≥88%, respectively). Rates of risk factor control varied geographically (all p Asia), controlled LDL cholesterol and dyslipidaemia from 32% (Eastern Europe) to 75% (Canada/South Africa/Australia/UK), heart rate <70 bpm from 22% (India) to 62% (Western/Central Europe), and heart rate ≤60 bpm in angina patients from 2% (India) to 29% (Canada/South Africa/Australia/UK and Central/South America). Prevalence and control of major cardiovascular risk factors in stable CAD vary markedly worldwide. Many stable CAD outpatients are being treated suboptimally. © The European Society of Cardiology 2014.

  20. East meets West: the influence of racial, ethnic and cultural risk factors on cardiac surgical risk model performance.

    Science.gov (United States)

    Soo-Hoo, Sarah; Nemeth, Samantha; Baser, Onur; Argenziano, Michael; Kurlansky, Paul

    2018-01-01

    To explore the impact of racial and ethnic diversity on the performance of cardiac surgical risk models, the Chinese SinoSCORE was compared with the Society of Thoracic Surgeons (STS) risk model in a diverse American population. The SinoSCORE risk model was applied to 13 969 consecutive coronary artery bypass surgery patients from twelve American institutions. SinoSCORE risk factors were entered into a logistic regression to create a 'derived' SinoSCORE whose performance was compared with that of the STS risk model. Observed mortality was 1.51% (66% of that predicted by STS model). The SinoSCORE 'low-risk' group had a mortality of 0.15%±0.04%, while the medium-risk and high-risk groups had mortalities of 0.35%±0.06% and 2.13%±0.14%, respectively. The derived SinoSCORE model had a relatively good discrimination (area under of the curve (AUC)=0.785) compared with that of the STS risk score (AUC=0.811; P=0.18 comparing the two). However, specific factors that were significant in the original SinoSCORE but that lacked significance in our derived model included body mass index, preoperative atrial fibrillation and chronic obstructive pulmonary disease. SinoSCORE demonstrated limited discrimination when applied to an American population. The derived SinoSCORE had a discrimination comparable with that of the STS, suggesting underlying similarities of physiological substrate undergoing surgery. However, differential influence of various risk factors suggests that there may be varying degrees of importance and interactions between risk factors. Clinicians should exercise caution when applying risk models across varying populations due to potential differences that racial, ethnic and geographic factors may play in cardiac disease and surgical outcomes.

  1. A methodology for modeling regional terrorism risk.

    Science.gov (United States)

    Chatterjee, Samrat; Abkowitz, Mark D

    2011-07-01

    Over the past decade, terrorism risk has become a prominent consideration in protecting the well-being of individuals and organizations. More recently, there has been interest in not only quantifying terrorism risk, but also placing it in the context of an all-hazards environment in which consideration is given to accidents and natural hazards, as well as intentional acts. This article discusses the development of a regional terrorism risk assessment model designed for this purpose. The approach taken is to model terrorism risk as a dependent variable, expressed in expected annual monetary terms, as a function of attributes of population concentration and critical infrastructure. This allows for an assessment of regional terrorism risk in and of itself, as well as in relation to man-made accident and natural hazard risks, so that mitigation resources can be allocated in an effective manner. The adopted methodology incorporates elements of two terrorism risk modeling approaches (event-based models and risk indicators), producing results that can be utilized at various jurisdictional levels. The validity, strengths, and limitations of the model are discussed in the context of a case study application within the United States. © 2011 Society for Risk Analysis.

  2. Geographical Tatoos

    Directory of Open Access Journals (Sweden)

    Valéria Cazetta

    2014-08-01

    Full Text Available The article deals with maps tattooed on bodies. My interest in studying the corporeality is inserted in a broader project entitled Geographies and (in Bodies. There is several published research on tattoos, but none in particular about tattooed maps. However some of these works interested me because they present important discussions in contemporary about body modification that helped me locate the body modifications most within the culture than on the nature. At this time, I looked at pictures of geographical tattoos available in several sites of the internet.

  3. Entrepreneural adaptation processes. An industry-geographic working model, illustrated by the example of Saarbergwerke AG

    International Nuclear Information System (INIS)

    Doerrenbaecher, P.

    1992-01-01

    The study has two goals: Solutions based in industrial geography and chronogeography are to be synthesized in order to develop a model of entrepreneurial adaptation processes. On the basis of this model, the development of Saarbergwerke AG in the first phase of the coal crisis (1957-1962) is reconstructed as an entrepreneurial adaptation process. (orig.) [de

  4. An analytical model for the performance of geographical multi-hop broadcast

    NARCIS (Netherlands)

    Klein Wolterink, W.; Heijenk, G.; Berg, J.L. van den

    2012-01-01

    In this paper we present an analytical model accurately describing the behaviour of a multi-hop broadcast protocol. Our model covers the scenario in which a message is forwarded over a straight road and inter-node distances are distributed exponentially. Intermediate forwarders draw a small random

  5. BETR global - A geographically-explicit global-scale multimedia contaminant fate model

    International Nuclear Information System (INIS)

    MacLeod, Matthew; Waldow, Harald von; Tay, Pascal; Armitage, James M.; Woehrnschimmel, Henry; Riley, William J.; McKone, Thomas E.; Hungerbuhler, Konrad

    2011-01-01

    We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15 o x 15 o grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5). - Two new software implementations of the Berkeley-Trent Global Contaminant Fate Model are available. The new model software is illustrated using a case study of the global fate of decamethylcyclopentasiloxane (D5).

  6. Application of Geographic Information System (GIS) to Model the Hydrocarbon Migration: Case Study from North-East Malay Basin, Malaysia

    Science.gov (United States)

    Rudini; Nasir Matori, Abd; Talib, Jasmi Ab; Balogun, Abdul-Lateef

    2018-03-01

    The purpose of this study is to model the migration of hydrocarbon using Geographic Information System (GIS). Understanding hydrocarbon migration is important since it can mean the difference between success and failure in oil and gas exploration project. The hydrocarbon migration modeling using geophysical method is still not accurate due to the limitations of available data. In recent years, GIS has emerged as a powerful tool for subsurface mapping and analysis. Recent studies have been carried out about the abilities of GIS to model hydrocarbon migration. Recent advances in GIS support the establishment and monitoring of prediction hydrocarbon migration. The concept, model, and calculation are based on the current geological situation. The spatial data of hydrocarbon reservoirs is determined by its geometry of lithology and geophysical attributes. Top of Group E horizon of north-east Malay basin was selected as the study area due to the occurrence of hydrocarbon migration. Spatial data and attributes data such as seismic data, wells log data and lithology were acquired and processed. Digital Elevation Model (DEM) was constructed from the selected horizon as a result of seismic interpretation using the Petrel software. Furthermore, DEM was processed in ArcGIS as a base map to shown hydrocarbon migration in north-east Malay Basin. Finally, all the data layers were overlaid to produce a map of hydrocarbon migration. A good data was imported to verify the model is correct.

  7. Application of Geographic Information System (GIS to Model the Hydrocarbon Migration: Case Study from North-East Malay Basin, Malaysia

    Directory of Open Access Journals (Sweden)

    Rudini

    2018-01-01

    Full Text Available The purpose of this study is to model the migration of hydrocarbon using Geographic Information System (GIS. Understanding hydrocarbon migration is important since it can mean the difference between success and failure in oil and gas exploration project. The hydrocarbon migration modeling using geophysical method is still not accurate due to the limitations of available data. In recent years, GIS has emerged as a powerful tool for subsurface mapping and analysis. Recent studies have been carried out about the abilities of GIS to model hydrocarbon migration. Recent advances in GIS support the establishment and monitoring of prediction hydrocarbon migration. The concept, model, and calculation are based on the current geological situation. The spatial data of hydrocarbon reservoirs is determined by its geometry of lithology and geophysical attributes. Top of Group E horizon of north-east Malay basin was selected as the study area due to the occurrence of hydrocarbon migration. Spatial data and attributes data such as seismic data, wells log data and lithology were acquired and processed. Digital Elevation Model (DEM was constructed from the selected horizon as a result of seismic interpretation using the Petrel software. Furthermore, DEM was processed in ArcGIS as a base map to shown hydrocarbon migration in north-east Malay Basin. Finally, all the data layers were overlaid to produce a map of hydrocarbon migration. A good data was imported to verify the model is correct.

  8. A Network Model of Credit Risk Contagion

    Directory of Open Access Journals (Sweden)

    Ting-Qiang Chen

    2012-01-01

    Full Text Available A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

  9. BETR Global - A geographically explicit global-scale multimedia contaminant fate model

    Energy Technology Data Exchange (ETDEWEB)

    Macleod, M.; Waldow, H. von; Tay, P.; Armitage, J. M.; Wohrnschimmel, H.; Riley, W.; McKone, T. E.; Hungerbuhler, K.

    2011-04-01

    We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15{sup o} x 15{sup o} grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5).

  10. Expert judgement models in quantitative risk assessment

    Energy Technology Data Exchange (ETDEWEB)

    Rosqvist, T. [VTT Automation, Helsinki (Finland); Tuominen, R. [VTT Automation, Tampere (Finland)

    1999-12-01

    Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed.

  11. Expert judgement models in quantitative risk assessment

    International Nuclear Information System (INIS)

    Rosqvist, T.; Tuominen, R.

    1999-01-01

    Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed

  12. Risk modelling study for carotid endarterectomy.

    Science.gov (United States)

    Kuhan, G; Gardiner, E D; Abidia, A F; Chetter, I C; Renwick, P M; Johnson, B F; Wilkinson, A R; McCollum, P T

    2001-12-01

    The aims of this study were to identify factors that influence the risk of stroke or death following carotid endarterectomy (CEA) and to develop a model to aid in comparative audit of vascular surgeons and units. A series of 839 CEAs performed by four vascular surgeons between 1992 and 1999 was analysed. Multiple logistic regression analysis was used to model the effect of 15 possible risk factors on the 30-day risk of stroke or death. Outcome was compared for four surgeons and two units after adjustment for the significant risk factors. The overall 30-day stroke or death rate was 3.9 per cent (29 of 741). Heart disease, diabetes and stroke were significant risk factors. The 30-day predicted stroke or death rates increased with increasing risk scores. The observed 30-day stroke or death rate was 3.9 per cent for both vascular units and varied from 3.0 to 4.2 per cent for the four vascular surgeons. Differences in the outcomes between the surgeons and vascular units did not reach statistical significance after risk adjustment. Diabetes, heart disease and stroke are significant risk factors for stroke or death following CEA. The risk score model identified patients at higher risk and aided in comparative audit.

  13. Extending the formal model of a spatial data infrastructure to include volunteered geographical information

    CSIR Research Space (South Africa)

    Cooper, Antony K

    2011-07-01

    Full Text Available , Information and Computational Viewpoints of the Reference Model for Open Distributed Processing (RM-ODP). We identified six stakeholders: Policy Maker, Producer, Provider, Broker, Value-added Reseller and End User. The Internet has spawned the development...

  14. Prevalence of chronic obstructive pulmonary disease and variation in risk factors across four geographically diverse resource-limited settings in Peru.

    Science.gov (United States)

    Jaganath, Devan; Miranda, J Jaime; Gilman, Robert H; Wise, Robert A; Diette, Gregory B; Miele, Catherine H; Bernabe-Ortiz, Antonio; Checkley, William

    2015-03-18

    It is unclear how geographic and social diversity affects the prevalence of chronic obstructive pulmonary disease (COPD). We sought to characterize the prevalence of COPD and identify risk factors across four settings in Peru with varying degrees of urbanization, altitude, and biomass fuel use. We collected sociodemographics, clinical history, and post-bronchodilator spirometry in a randomly selected, age-, sex- and site-stratified, population-based sample of 2,957 adults aged ≥35 years (median age was 54.8 years and 49.3% were men) from four resource-poor settings: Lima, Tumbes, urban and rural Puno. We defined COPD as a post-bronchodilator FEV1/FVC Peru was not uniform and, unlike other settings, was not predominantly explained by tobacco smoking. This study emphasizes the role of biomass fuel use, and highlights pulmonary tuberculosis as an often neglected risk factor in endemic areas.

  15. [Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

    Science.gov (United States)

    Zhang, Ling Yu; Liu, Zhao Gang

    2017-12-01

    Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

  16. Competing Risks Copula Models for Unemployment Duration

    DEFF Research Database (Denmark)

    Lo, Simon M. S.; Stephan, Gesine; Wilke, Ralf

    2017-01-01

    The copula graphic estimator (CGE) for competing risks models has received little attention in empirical research, despite having been developed into a comprehensive research method. In this paper, we bridge the gap between theoretical developments and applied research by considering a general...... class of competing risks copula models, which nests popular models such as the Cox proportional hazards model, the semiparametric multivariate mixed proportional hazards model (MMPHM), and the CGE as special cases. Analyzing the effects of a German Hartz reform on unemployment duration, we illustrate...

  17. Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

    Science.gov (United States)

    Rodhouse, Thomas J.; Ormsbee, Patricia C.; Irvine, Kathryn M.; Vierling, Lee A.; Szewczak, Joseph M.; Vierling, Kerri T.

    2012-01-01

    Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species–energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients.

  18. Risk Monitoring through Traceability Information Model

    OpenAIRE

    Juan P. Zamora; Wilson Adarme; Laura Palacios

    2012-01-01

    This paper shows a traceability framework for supply risk monitoring, beginning with the identification, analysis, and evaluation of the supply chain risk and focusing on the supply operations of the Health Care Institutions with oncology services in Bogota, Colombia. It includes a brief presentation of the state of the art of the Supply Chain Risk Management and traceability systems in logistics operations, and it concludes with the methodology to integrate the SCRM model with the traceabili...

  19. Criterion of Semi-Markov Dependent Risk Model

    Institute of Scientific and Technical Information of China (English)

    Xiao Yun MO; Xiang Qun YANG

    2014-01-01

    A rigorous definition of semi-Markov dependent risk model is given. This model is a generalization of the Markov dependent risk model. A criterion and necessary conditions of semi-Markov dependent risk model are obtained. The results clarify relations between elements among semi-Markov dependent risk model more clear and are applicable for Markov dependent risk model.

  20. Vertical Integration of Geographic Information Sciences: A Recruitment Model for GIS Education

    Science.gov (United States)

    Yu, Jaehyung; Huynh, Niem Tu; McGehee, Thomas Lee

    2011-01-01

    An innovative vertical integration model for recruiting to GIS education was introduced and tested following four driving forces: curriculum development, GIS presentations, institutional collaboration, and faculty training. Curriculum development was a useful approach to recruitment, student credit hour generation, and retention-rate improvement.…

  1. Research-Based Program Development: Refining the Service Model for a Geographic Alliance

    Science.gov (United States)

    Rutherford, David J.; Lovorn, Carley

    2018-01-01

    Research conducted in 2013 identified the perceptions that K-12 teachers and administrators hold with respect to: (1) the perceived needs in education, (2) the professional audiences that are most important to reach, and (3) the service models that are most effective. The specific purpose of the research was to refine and improve the services that…

  2. Extending Geographic Weights of Evidence Models for Use in Location Based Services

    Science.gov (United States)

    Sonwalkar, Mukul Dinkar

    2012-01-01

    This dissertation addresses the use and modeling of spatio-temporal data for the purposes of providing applications for location based services. One of the major issues in dealing with spatio-temporal data for location based services is the availability and sparseness of such data. Other than the hardware costs associated with collecting movement…

  3. A Geographic Approach to Modelling Human Exposure to Traffic Air Pollution using GIS

    DEFF Research Database (Denmark)

    Jensen, S. S.

    on gender and age from the Central Population Register (CPR); the number of employees from the Central Business Register (CER); standardised time-activity profiles for the different age groups in the residence and workplace microenvironments; and meteorological parameters (hourly). The exposure model...

  4. To assess and control global change in agriculture through ecosystem models integrated into geographic information systems

    International Nuclear Information System (INIS)

    Ponti, L.; Iannetta, M.; Gutierrez, A.P.

    2015-01-01

    The transfer of ENEA PBDM (physiologically based demographic models) GIS technology, represents an opportunity to address global change in agriculture on an ecological basis in a local context, be able to provide European governmental agencies the necessary scientific basis for developing effective policies for adaptation to global change, including climate change [it

  5. Effects of Geographic Diversification on Risk Pooling to Mitigate Drought-Related Financial Losses for Water Utilities

    Science.gov (United States)

    Baum, Rachel; Characklis, Gregory W.; Serre, Marc L.

    2018-04-01

    As the costs and regulatory barriers to new water supply development continue to rise, drought management strategies have begun to rely more heavily on temporary conservation measures. While these measures are effective, they often lead to intermittent and unpredictable reductions in revenues that are financially disruptive to water utilities, raising concerns over lower credit ratings and higher rates of borrowing for this capital intensive sector. Consequently, there is growing interest in financial risk management strategies that reduce utility vulnerabilities. This research explores the development of financial index insurance designed to compensate a utility for drought-related losses. The focus is on analyzing candidate hydrologic indices that have the potential to be used by utilities across the US, increasing the potential for risk pooling, which would offer the possibility of both lower risk management costs and more widespread implementation. This work first analyzes drought-related financial risks for 315 publicly operated water utilities across the country and examines the effectiveness of financial contracts based on several indices both in terms of their correlation with utility revenues and their spatial autocorrelation across locations. Hydrologic-based index insurance contracts are then developed and tested over a 120 year period. Results indicate that risk pooling, even under conditions in which droughts are subject to some level of spatial autocorrelation, has the potential to significantly reduce the cost of managing financial risk.

  6. Risk management model of winter navigation operations

    International Nuclear Information System (INIS)

    Valdez Banda, Osiris A.; Goerlandt, Floris; Kuzmin, Vladimir; Kujala, Pentti; Montewka, Jakub

    2016-01-01

    The wintertime maritime traffic operations in the Gulf of Finland are managed through the Finnish–Swedish Winter Navigation System. This establishes the requirements and limitations for the vessels navigating when ice covers this area. During winter navigation in the Gulf of Finland, the largest risk stems from accidental ship collisions which may also trigger oil spills. In this article, a model for managing the risk of winter navigation operations is presented. The model analyses the probability of oil spills derived from collisions involving oil tanker vessels and other vessel types. The model structure is based on the steps provided in the Formal Safety Assessment (FSA) by the International Maritime Organization (IMO) and adapted into a Bayesian Network model. The results indicate that ship independent navigation and convoys are the operations with higher probability of oil spills. Minor spills are most probable, while major oil spills found very unlikely but possible. - Highlights: •A model to assess and manage the risk of winter navigation operations is proposed. •The risks of oil spills in winter navigation in the Gulf of Finland are analysed. •The model assesses and prioritizes actions to control the risk of the operations. •The model suggests navigational training as the most efficient risk control option.

  7. A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic Data

    DEFF Research Database (Denmark)

    Guillot, Gilles; Rena, Sabrina; Ledevin, Ronan

    2012-01-01

    Recognition of evolutionary units (species, populations) requires integrating several kinds of data such as genetic or phenotypic markers or spatial information, in order to get a comprehensive view concerning the dierentiation of the units. We propose a statistical model with a double original...... advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography; and (ii) it allows one to analyze genetic and phenotypic data within a unied model and inference framework, thus...... an intricate case of inter- and intra-species dierentiation based on an original data-set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Geneland....

  8. Water quality control in Third River Reservoir (Argentina using geographical information systems and linear regression models

    Directory of Open Access Journals (Sweden)

    Claudia Ledesma

    2013-08-01

    Full Text Available Water quality is traditionally monitored and evaluated based upon field data collected at limited locations. The storage capacity of reservoirs is reduced by deposits of suspended matter. The major factors affecting surface water quality are suspended sediments, chlorophyll and nutrients. Modeling and monitoring the biogeochemical status of reservoirs can be done through data from remote sensors. Since the improvement of sensors’ spatial and spectral resolutions, satellites have been used to monitor the interior areas of bodies of water. Water quality parameters, such as chlorophyll-a concentration and secchi disk depth, were found to have a high correlation with transformed spectral variables derived from bands 1, 2, 3 and 4 of LANDSAT 5TM satellite. We created models of estimated responses in regard to values of chlorophyll-a. To do so, we used population models of single and multiple linear regression, whose parameters are associated with the reflectance data of bands 2 and 4 of the sub-image of the satellite, as well as the data of chlorophyll-a obtained in 25 selected stations. According to the physico-chemical analyzes performed, the characteristics of the water in the reservoir of Rio Tercero, correspond to somewhat hard freshwater with calcium bicarbonate. The water was classified as usable as a source of plant treatment, excellent for irrigation because of its low salinity and low residual sodium carbonate content, but unsuitable for animal consumption because of its low salt content.

  9. Integration of a Hydrological Model within a Geographical Information System: Application to a Forest Watershed

    Directory of Open Access Journals (Sweden)

    Dimitris Fotakis

    2014-03-01

    Full Text Available Watershed simulation software used for operational purposes must possess both dependability of results and flexibility in parameter selection and testing. The UBC watershed model (UBCWM contains a wide spectrum of parameters expressing meteorological, geological, as well as ecological watershed characteristics. The hydrological model was coupled to the MapInfo GIS and the software created was named Watershed Mapper (WM. WM is endowed with several features permitting operational utilization. These include input data and basin geometry visualization, land use/cover and soil simulation, exporting of statistical results and thematic maps and interactive variation of disputed parameters. For the application of WM two hypothetical scenarios of forest fires were examined in a study watershed. Four major rainfall events were selected from 12-year daily precipitation data and the corresponding peak flows were estimated for the base line data and hypothetical scenarios. A significant increase was observed as an impact of forest fires on peak flows. Due to its flexibility the combined tool described herein may be utilized in modeling long-term hydrological changes in the context of unsteady hydrological analyses.

  10. Spatial Modeling of Tsunami Impact in Manado City using Geographic Information System

    Science.gov (United States)

    Kumaat, J. C.; Kandoli, S. T. B.; Laeloma, F.

    2018-02-01

    Manado City is a coastal area in the shape of a bay. Manado Bay is a water body that protrudes in the area of Manado City where the condition of this region is likely to have a tsunami threat. Manado Bay is home to several rivers such as Tondano River has a geological history of both land and sea. There are several active faults, such as in the sea, subduction of subplate in the north of the island, Mayu mountain plate, and Sangihe plate east of North Sulawesi. The purpose of this study is divided into two parts: General purpose is to describe GIS-based disaster mitigation that can be done to minimize disaster risk if Tsunami disaster occurs in coastal area of Manado Bay, while special purpose consists of 3 parts, namely: 1. mapping of zone- Tsunami vulnerability zone of Manado Bay; 2. mapping the distance and time of the scenario of the Manado Bay Tsunami evacuation route; 3. mapping of the number of buildings and roads exposed to the Manado Bay Tsunami. Data collection techniques use secondary data collection techniques. Secondary data comes from related institutions or institutions, libraries, or individual archives. The data collection is also continued by direct observation. Direct observation is meant by direct observation by using a checklist for secondary data adjustment and then the determination of coordinate point with Global Position System (GPS) at some tsunami location.

  11. Inferring the past and present connectivity across the range of a North American leaf beetle: combining ecological niche modeling and a geographically explicit model of coalescence.

    Science.gov (United States)

    Dellicour, Simon; Fearnley, Shannon; Lombal, Anicée; Heidl, Sarah; Dahlhoff, Elizabeth P; Rank, Nathan E; Mardulyn, Patrick

    2014-08-01

    The leaf beetle Chrysomela aeneicollis occurs across Western North America, either at high elevation or in small, isolated populations along the coast, and thus has a highly fragmented distribution. DNA sequence data (three loci) were collected from five regions across the species range. Population connectivity was examined using traditional ecological niche modeling, which suggested that gene flow could occur among regions now and in the past. We developed geographically explicit coalescence models of sequence evolution that incorporated a two-dimensional representation of the hypothesized ranges suggested by the niche-modeling estimates. We simulated sequence data according to these models and compared them to observed sequences to identify most probable scenarios regarding the migration history of C. aeneicollis. Our results disagreed with initial niche-modeling estimates by clearly rejecting recent connectivity among regions, and were instead most consistent with a long period of range fragmentation, extending well beyond the last glacial maximum. This application of geographically explicit models of coalescence has highlighted some limitations of the use of climatic variables for predicting the present and past range of a species and has explained aspects of the Pleistocene evolutionary history of a cold-adapted organism in Western North America. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

  12. A model-based risk management framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune

    2002-08-15

    The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

  13. Equality in Maternal and Newborn Health: Modelling Geographic Disparities in Utilisation of Care in Five East African Countries.

    Directory of Open Access Journals (Sweden)

    Corrine W Ruktanonchai

    Full Text Available Geographic accessibility to health facilities represents a fundamental barrier to utilisation of maternal and newborn health (MNH services, driving historically hidden spatial pockets of localized inequalities. Here, we examine utilisation of MNH care as an emergent property of accessibility, highlighting high-resolution spatial heterogeneity and sub-national inequalities in receiving care before, during, and after delivery throughout five East African countries.We calculated a geographic inaccessibility score to the nearest health facility at 300 x 300 m using a dataset of 9,314 facilities throughout Burundi, Kenya, Rwanda, Tanzania and Uganda. Using Demographic and Health Surveys data, we utilised hierarchical mixed effects logistic regression to examine the odds of: 1 skilled birth attendance, 2 receiving 4+ antenatal care visits at time of delivery, and 3 receiving a postnatal health check-up within 48 hours of delivery. We applied model results onto the accessibility surface to visualise the probabilities of obtaining MNH care at both high-resolution and sub-national levels after adjusting for live births in 2015.Across all outcomes, decreasing wealth and education levels were associated with lower odds of obtaining MNH care. Increasing geographic inaccessibility scores were associated with the strongest effect in lowering odds of obtaining care observed across outcomes, with the widest disparities observed among skilled birth attendance. Specifically, for each increase in the inaccessibility score to the nearest health facility, the odds of having skilled birth attendance at delivery was reduced by over 75% (0.24; CI: 0.19-0.3, while the odds of receiving antenatal care decreased by nearly 25% (0.74; CI: 0.61-0.89 and 40% for obtaining postnatal care (0.58; CI: 0.45-0.75.Overall, these results suggest decreasing accessibility to the nearest health facility significantly deterred utilisation of all maternal health care services. These

  14. Equality in Maternal and Newborn Health: Modelling Geographic Disparities in Utilisation of Care in Five East African Countries.

    Science.gov (United States)

    Ruktanonchai, Corrine W; Ruktanonchai, Nick W; Nove, Andrea; Lopes, Sofia; Pezzulo, Carla; Bosco, Claudio; Alegana, Victor A; Burgert, Clara R; Ayiko, Rogers; Charles, Andrew Sek; Lambert, Nkurunziza; Msechu, Esther; Kathini, Esther; Matthews, Zoë; Tatem, Andrew J

    2016-01-01

    Geographic accessibility to health facilities represents a fundamental barrier to utilisation of maternal and newborn health (MNH) services, driving historically hidden spatial pockets of localized inequalities. Here, we examine utilisation of MNH care as an emergent property of accessibility, highlighting high-resolution spatial heterogeneity and sub-national inequalities in receiving care before, during, and after delivery throughout five East African countries. We calculated a geographic inaccessibility score to the nearest health facility at 300 x 300 m using a dataset of 9,314 facilities throughout Burundi, Kenya, Rwanda, Tanzania and Uganda. Using Demographic and Health Surveys data, we utilised hierarchical mixed effects logistic regression to examine the odds of: 1) skilled birth attendance, 2) receiving 4+ antenatal care visits at time of delivery, and 3) receiving a postnatal health check-up within 48 hours of delivery. We applied model results onto the accessibility surface to visualise the probabilities of obtaining MNH care at both high-resolution and sub-national levels after adjusting for live births in 2015. Across all outcomes, decreasing wealth and education levels were associated with lower odds of obtaining MNH care. Increasing geographic inaccessibility scores were associated with the strongest effect in lowering odds of obtaining care observed across outcomes, with the widest disparities observed among skilled birth attendance. Specifically, for each increase in the inaccessibility score to the nearest health facility, the odds of having skilled birth attendance at delivery was reduced by over 75% (0.24; CI: 0.19-0.3), while the odds of receiving antenatal care decreased by nearly 25% (0.74; CI: 0.61-0.89) and 40% for obtaining postnatal care (0.58; CI: 0.45-0.75). Overall, these results suggest decreasing accessibility to the nearest health facility significantly deterred utilisation of all maternal health care services. These results

  15. Residents in a high radon potential geographic area: Their risk perception and attitude toward testing and mitigation

    International Nuclear Information System (INIS)

    Ferng, S.F.; Lawson, J.K.

    1996-01-01

    Boone County, Indiana was identified by the EPA as one of the high radon potential geographic areas. Health education campaigns are needed to prevent resident's unnecessary radon exposure. In order to design suitable programs, a questionnaire mail survey was conducted to measure socio-demographic characteristics of County resident's knowledge about radon, attitude toward radon testing and mitigation, support of education campaigns, and the best media to deliver radon education campaigns. A stratified random sampling method was applied for a total of 400 samples. The number of samples from each township/city was a proportion of their taxable parcels. The survey return rate was 39.8%. The data were analyzed by Epi Info and SPSS. The statistical significant level was set at α = 0.05. The results showed that resident's knowledge about radon was at a relatively superficial level. There was no association identified between the knowledge of radon and gender, age, family income, or education, except that females more frequently believed in false effects caused by radon. A significant correlation between radon knowledge and home radon tests was observed. Also found in this study was that respondents with better knowledge about diseases caused by radon had more confidence in radon mitigation actions. Newspaper was chosen by respondents as the most favorite media to deliver radon health education campaigns. Health education campaigns for the residents of Boone County might be conducted by local governments and/or other organizations

  16. The air emissions risk assessment model (AERAM)

    International Nuclear Information System (INIS)

    Gratt, L.B.

    1991-01-01

    AERAM is an environmental analysis and power generation station investment decision support tool. AERAM calculates the public health risk (in terms of the lifetime cancers) in the nearby population from pollutants released into the air. AERAM consists of four main subroutines: Emissions, Air, Exposure and Risk. The Emission subroutine uses power plant parameters to calculate the expected release of the pollutants. A coal-fired and oil-fired power plant are currently available. A gas-fired plant model is under preparation. The release of the pollutants into the air is followed by their dispersal in the environment. The dispersion in the Air Subroutine uses the Environmental Protection Agency's model, Industrial Source Complex-Long Term. Additional dispersion models (Industrial Source Complex - Short Term and Cooling Tower Drift) are being implemented for future AERAM versions. The Expose Subroutine uses the ambient concentrations to compute population exposures for the pollutants of concern. The exposures are used with corresponding dose-response model in the Risk Subroutine to estimate both the total population risk and individual risk. The risk for the dispersion receptor-population centroid for the maximum concentration is also calculated for regulatory-population purposes. In addition, automated interfaces with AirTox (an air risk decision model) have been implemented to extend AERAM's steady-state single solution to the decision-under-uncertainty domain. AERAM was used for public health risks, the investment decision for additional pollution control systems based on health risk reductions, and the economics of fuel vs. health risk tradeoffs. AERAM provides that state-of-the-art capability for evaluating the public health impact airborne toxic substances in response to regulations and public concern

  17. Assess and control global change in agriculture through ecosystem models integrated in geographic information systems

    International Nuclear Information System (INIS)

    Ponti, Luigi; Gutierrez, Andrew Paul; Iannetta, Massimo

    2015-01-01

    ENEA has created, in collaboration with the University of California at Berkeley, the Global Change Biology project that, for the first time, has made available in Europe a technology that can be It used to interpret and effectively manage change Global agriculture. The aim of the project was to provide tools to summarize, manage and analyze data Ecological on the effects of global change in agricultural systems, using traditional Mediterranean crops (Eg. Vineyards and olive) as model systems (http: // cordis.europa.eu/project/rcn/89728_en.html). [it

  18. Remote sensing, geographical information systems, and spatial modeling for analyzing public transit services

    Science.gov (United States)

    Wu, Changshan

    Public transit service is a promising transportation mode because of its potential to address urban sustainability. Current ridership of public transit, however, is very low in most urban regions, particularly those in the United States. This woeful transit ridership can be attributed to many factors, among which poor service quality is key. Given this, there is a need for transit planning and analysis to improve service quality. Traditionally, spatially aggregate data are utilized in transit analysis and planning. Examples include data associated with the census, zip codes, states, etc. Few studies, however, address the influences of spatially aggregate data on transit planning results. In this research, previous studies in transit planning that use spatially aggregate data are reviewed. Next, problems associated with the utilization of aggregate data, the so-called modifiable areal unit problem (MAUP), are detailed and the need for fine resolution data to support public transit planning is argued. Fine resolution data is generated using intelligent interpolation techniques with the help of remote sensing imagery. In particular, impervious surface fraction, an important socio-economic indicator, is estimated through a fully constrained linear spectral mixture model using Landsat Enhanced Thematic Mapper Plus (ETM+) data within the metropolitan area of Columbus, Ohio in the United States. Four endmembers, low albedo, high albedo, vegetation, and soil are selected to model heterogeneous urban land cover. Impervious surface fraction is estimated by analyzing low and high albedo endmembers. With the derived impervious surface fraction, three spatial interpolation methods, spatial regression, dasymetric mapping, and cokriging, are developed to interpolate detailed population density. Results suggest that cokriging applied to impervious surface is a better alternative for estimating fine resolution population density. With the derived fine resolution data, a multiple

  19. Modelling nonpoint source pollution of MUDA river basin using GIS (Geographic Information System)

    International Nuclear Information System (INIS)

    Nyon Yong Chik; Taher Buyong

    2000-01-01

    The management of our rivers is under increasing pressure to conserve and sustain as it remains the focus of human civilization and subjected to increasing demand from man and its activities. Integrated river basin management represents comprehensive form of terrestrial water resources management while GIS is a promising tool to be used in the management strategy. In efforts to display the true capabilities of GIS in analysing nonpoint source pollution (NPS), an assessment of NPS was carried out at MUDA river basin using Arc View 3.0 Spatial Analyst. Expected Mean Concentration (EMC) which is associated with land use was used to predict the amount of pollutants constituents. A runoff grid was then processed to model the flow domain. Finally, the modelling of the pollutant loads downstreams towards the basin outlet is achieved by flow direction and accumulation analysis of the product of EMC and runoff grid. A user interface was programmed to display each application data theme via a pop-up window. In addition, users will be able to enter EMG values for the corresponding land use through an application dialog developed in Visual Basic. (Author)

  20. Interface between the model of quality QUALZE and a geographic information system

    International Nuclear Information System (INIS)

    Betancur, T; Sierra C, J.H.

    1998-01-01

    For the decision making related to the adequate utilization of a natural resource, is required count on versatile mechanisms that permit a rapid access the information related to the conditions of the system on the one which is intended to act, so that they could be analyzed and be designed political of managing and control that guarantee the preservation of the resource. A model is a design tool that permits to represent the simplified way reality and if is built of adequate way possesses a value predictive enormously useful for the managing of a natural resource. The water, essential element for the life, it has suffered deterioration in its quality, on account of man activities that they have established the irrational use of the water. The principal objective of the mathematical current models of water is to produce a tool that has the capacity to simulate the hydrological behavior and the quality of an aquatic system. The power to simulate the behavior of a water current permits to predict the changes that will have, when vary the element exhausts that affect its conditions

  1. [A model list of high risk drugs].

    Science.gov (United States)

    Cotrina Luque, J; Guerrero Aznar, M D; Alvarez del Vayo Benito, C; Jimenez Mesa, E; Guzman Laura, K P; Fernández Fernández, L

    2013-12-01

    «High-risk drugs» are those that have a very high «risk» of causing death or serious injury if an error occurs during its use. The Institute for Safe Medication Practices (ISMP) has prepared a high-risk drugs list applicable to the general population (with no differences between the pediatric and adult population). Thus, there is a lack of information for the pediatric population. The main objective of this work is to develop a high-risk drug list adapted to the neonatal or pediatric population as a reference model for the pediatric hospital health workforce. We made a literature search in May 2012 to identify any published lists or references in relation to pediatric and/or neonatal high-risk drugs. A total of 15 studies were found, from which 9 were selected. A model list was developed mainly based on the ISMP one, adding strongly perceived pediatric risk drugs and removing those where the pediatric use was anecdotal. There is no published list that suits pediatric risk management. The list of pediatric and neonatal high-risk drugs presented here could be a «reference list of high-risk drugs » for pediatric hospitals. Using this list and training will help to prevent medication errors in each drug supply chain (prescribing, transcribing, dispensing and administration). Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

  2. Mercury concentrations in Northwest Atlantic winter-caught, male spiny dogfish (Squalus acanthias): A geographic mercury comparison and risk-reward framework for human consumption.

    Science.gov (United States)

    St Gelais, Adam T; Costa-Pierce, Barry A

    2016-01-15

    Mercury (Hg) contamination testing was conducted on winter-caught male spiny dogfish (Squalus acanthias) in southern New England and results compared to available data on Hg concentrations for this species. A limited risk-reward assessment for EPA (eicosapentanoic acid) and DHA (docosahexanoic acid) lipid concentrations of spiny dogfish was completed in comparison with other commonly consumed marine fish. Mean Hg concentrations were 0.19 ppm (±0.30) wet weight. In comparison, mean Hg concentrations in S. acanthias varied geographically ranging from 0.05 ppm (Celtic Sea) to 2.07 ppm (Crete, Mediterranean Sea). A risk-reward assessment for Hg and DHA+EPA placed S. acanthias in both "low-risk, high-reward" and "high-risk, high-reward" categories for consumption dependent on locations of the catch. Our results are limited and are not intended as consumption advisories but serve to illustrate the need for making more nuanced, geo-specific, consumption guidance for spiny dogfish that is inclusive of seafood traceability and nutritional benefits. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Geographic information system for SILMU and the modelling of soil carbon flows

    International Nuclear Information System (INIS)

    Alm, J.; Lempinen, R.

    1994-01-01

    Integration of the various research themes incorporated as a single programme is a demanding task both scientifically and technically. To provide a tool for regionally based analysis and display of the results, a general purpose research database was configured in the GIS laboratory of the university of Joensuu, starting in 1992. In addition of the database system itself, a service node for GIS analysis and other possible uses of regional data was also established. The database can be used to store various background datasets, such as land use, soil maps, topography and regionally interpolated 1961-1990 climate parameters. These data can be combined and connected to other datasets and models provided by any SILMU research group

  4. Model for Determining Geographical Distribution of Heat Saving Potentials in Danish Building Stock

    DEFF Research Database (Denmark)

    Petrovic, Stefan; Karlsson, Kenneth Bernard

    2014-01-01

    Since the global oil crisis in the 1970s, Denmark has followed a path towards energy independency by continuously improving its energy efficiency and energy conservation. Energy efficiency was mainly tackled by introducing a high number of combined heat and power plants in the system, while energy...... conservation was predominantly approached by implementing heat saving measures. Today, with the goal of 100% renewable energy within the power and heat sector by the year 2035, reductions in energy demand for space heating and the preparation of domestic hot water remain at the top of the agenda in Denmark....... A highly detailed model for determining heat demand, possible heat savings and associated costs in the Danish building stock is presented. Both scheduled and energy-saving renovations until year 2030 have been analyzed. The highly detailed GIS-based heat atlas for Denmark is used as a container for storing...

  5. Use of geographically weighted logistic regression to quantify spatial variation in the environmental and sociodemographic drivers of leptospirosis in Fiji: a modelling study.

    Science.gov (United States)

    Mayfield, Helen J; Lowry, John H; Watson, Conall H; Kama, Mike; Nilles, Eric J; Lau, Colleen L

    2018-05-01

    Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR) to provide insights into the ecoepidemiology of human leptospirosis in Fiji. We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1-90 years) was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month) on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR) for each covariate. The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but GWLR also detected spatial variation in the effect of each

  6. Ecological models and pesticide risk assessment: current modeling practice.

    Science.gov (United States)

    Schmolke, Amelie; Thorbek, Pernille; Chapman, Peter; Grimm, Volker

    2010-04-01

    Ecological risk assessments of pesticides usually focus on risk at the level of individuals, and are carried out by comparing exposure and toxicological endpoints. However, in most cases the protection goal is populations rather than individuals. On the population level, effects of pesticides depend not only on exposure and toxicity, but also on factors such as life history characteristics, population structure, timing of application, presence of refuges in time and space, and landscape structure. Ecological models can integrate such factors and have the potential to become important tools for the prediction of population-level effects of exposure to pesticides, thus allowing extrapolations, for example, from laboratory to field. Indeed, a broad range of ecological models have been applied to chemical risk assessment in the scientific literature, but so far such models have only rarely been used to support regulatory risk assessments of pesticides. To better understand the reasons for this situation, the current modeling practice in this field was assessed in the present study. The scientific literature was searched for relevant models and assessed according to nine characteristics: model type, model complexity, toxicity measure, exposure pattern, other factors, taxonomic group, risk assessment endpoint, parameterization, and model evaluation. The present study found that, although most models were of a high scientific standard, many of them would need modification before they are suitable for regulatory risk assessments. The main shortcomings of currently available models in the context of regulatory pesticide risk assessments were identified. When ecological models are applied to regulatory risk assessments, we recommend reviewing these models according to the nine characteristics evaluated here. (c) 2010 SETAC.

  7. A model of the European electricity market. What can we learn from a geographical expansion to EU20?

    International Nuclear Information System (INIS)

    Lise, W.; Hobbs, B.F.

    2005-09-01

    This paper presents the static computational game theoretic COMPETES (COmprehensive Market Power in Electricity Transmission and Energy Simulator) model version 2.0. This model can be used to study various policy question regarding economic and environmental effects of a fully opened European electricity market. The COMPETES model can take strategic interaction among electricity producing firms into account. The strategic behaviour of generation companies can be reflected in the conjectures each company holds regarding the supply response of rival companies. These response functions simulate expectations concerning how rivals will change their electricity sales when prices change; these expectations determine the perceived profitability of capacity withholding and other strategies. In addition, COMPETES can solve the market outcome under price and quantity competition. COMPETES can also represent different systems of transmission pricing, among them fixed transmission tariffs, congestion-based pricing of physical transmission, and auction pricing of interface capacity between countries. CO2 costs can be brought in as an exogenous variable. In this paper the COMPETES model is calibrated to twenty European countries, EU20 for short, namely Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Hungary, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, UK/England and Wales. These countries have been chosen because they are geographically adjoined, their electricity networks are well connected (UCTE, Nord Pool, UK), they are members of the European Union (except for Norway and Switzerland) and data is quite reliable (which would for instance not be the case for the Balkan countries). The level of detail in the COMPETES model is quite extensive. The model contains various characteristics of 7531 power plants in the EU20 area (acquired from the database on World Energy Power Plants). These

  8. Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

    Science.gov (United States)

    Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

    2013-02-01

    Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local

  9. Quantifying geographic variation in the climatic drivers of midcontinent wetlands with a spatially varying coefficient model.

    Science.gov (United States)

    Roy, Christian

    2015-01-01

    The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012). I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult.

  10. Quantifying geographic variation in the climatic drivers of midcontinent wetlands with a spatially varying coefficient model.

    Directory of Open Access Journals (Sweden)

    Christian Roy

    Full Text Available The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012. I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult.

  11. Maxent modeling for predicting the potential geographical distribution of two peony species under climate change.

    Science.gov (United States)

    Zhang, Keliang; Yao, Linjun; Meng, Jiasong; Tao, Jun

    2018-09-01

    Paeonia (Paeoniaceae), an economically important plant genus, includes many popular ornamentals and medicinal plant species used in traditional Chinese medicine. Little is known about the properties of the habitat distribution and the important eco-environmental factors shaping the suitability. Based on high-resolution environmental data for current and future climate scenarios, we modeled the present and future suitable habitat for P. delavayi and P. rockii by Maxent, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results showed that the moderate and high suitable areas for P. delavayi and P. rockii encompassed ca. 4.46×10 5 km 2 and 1.89×10 5 km 2 , respectively. Temperature seasonality and isothermality were identified as the most critical factors shaping P. delavayi distribution, and UVB-4 and annual precipitation were identified as the most critical for shaping P. rockii distribution. Under the scenario with a low concentration of greenhouse gas emissions (RCP2.6), the range of both species increased as global warming intensified; however, under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of P. delavayi decreased while P. rockii increased. Overall, our prediction showed that a shift in distribution of suitable habitat to higher elevations would gradually become more significant. The information gained from this study should provide a useful reference for implementing long-term conservation and management strategies for these species. Copyright © 2018. Published by Elsevier B.V.

  12. SAS macro programs for geographically weighted generalized linear modeling with spatial point data: applications to health research.

    Science.gov (United States)

    Chen, Vivian Yi-Ju; Yang, Tse-Chuan

    2012-08-01

    An increasing interest in exploring spatial non-stationarity has generated several specialized analytic software programs; however, few of these programs can be integrated natively into a well-developed statistical environment such as SAS. We not only developed a set of SAS macro programs to fill this gap, but also expanded the geographically weighted generalized linear modeling (GWGLM) by integrating the strengths of SAS into the GWGLM framework. Three features distinguish our work. First, the macro programs of this study provide more kernel weighting functions than the existing programs. Second, with our codes the users are able to better specify the bandwidth selection process compared to the capabilities of existing programs. Third, the development of the macro programs is fully embedded in the SAS environment, providing great potential for future exploration of complicated spatially varying coefficient models in other disciplines. We provided three empirical examples to illustrate the use of the SAS macro programs and demonstrated the advantages explained above. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  13. Modelling the sequential geographical exploitation and potential collapse of marine fisheries through economic globalization, climate change and management alternatives

    Directory of Open Access Journals (Sweden)

    Gorka Merino

    2011-07-01

    Full Text Available Global marine fisheries production has reached a maximum and may even be declining. Underlying this trend is a well-understood sequence of development, overexploitation, depletion and in some instances collapse of individual fish stocks, a pattern that can sequentially link geographically distant populations. Ineffective governance, economic considerations and climate impacts are often responsible for this sequence, although the relative contribution of each factor is contentious. In this paper we use a global bioeconomic model to explore the synergistic effects of climate variability, economic pressures and management measures in causing or avoiding this sequence. The model shows how a combination of climate-induced variability in the underlying fish population production, particular patterns of demand for fish products and inadequate management is capable of driving the world’s fisheries into development, overexploitation, collapse and recovery phases consistent with observations. Furthermore, it demonstrates how a sequential pattern of overexploitation can emerge as an endogenous property of the interaction between regional environmental fluctuations and a globalized trade system. This situation is avoidable through adaptive management measures that ensure the sustainability of regional production systems in the face of increasing global environmental change and markets. It is concluded that global management measures are needed to ensure that global food supply from marine products is optimized while protecting long-term ecosystem services across the world’s oceans.

  14. Lung cancer risk models from experimental animals

    International Nuclear Information System (INIS)

    Gilbert, E.S.

    1988-03-01

    The objective of this paper is to present analyses of data based on methods that adequately account for time-related factors and competiting risks, and that yield results that are expressed in a form comparable to results obtained from recent analyses of epidemiological studies of humans exposed to radon and radon daughters. These epidemiological analyses have modeled the hazard, or age-specific death rates, as a function of factors such as dose and dose rate, time from exposure, and time from cessation of exposure. The starting point for many of the analyses of human data has been the constant relative risk modeling which the age-specific death rates are assumed to be a function of cumulative dose, and the risks due to exposure are assumed to be proportional to the age-specific baseline death rates. However, departures from this initial model, such as dependence of risks on age at risk and/or time from exposure, have been investigated. These analyses have frequently been based on a non-parametric model that requires minimal assumptions regarding the baseline risks and their dependence on age

  15. Quantitative occupational risk model: Single hazard

    International Nuclear Information System (INIS)

    Papazoglou, I.A.; Aneziris, O.N.; Bellamy, L.J.; Ale, B.J.M.; Oh, J.

    2017-01-01

    A model for the quantification of occupational risk of a worker exposed to a single hazard is presented. The model connects the working conditions and worker behaviour to the probability of an accident resulting into one of three types of consequence: recoverable injury, permanent injury and death. Working conditions and safety barriers in place to reduce the likelihood of an accident are included. Logical connections are modelled through an influence diagram. Quantification of the model is based on two sources of information: a) number of accidents observed over a period of time and b) assessment of exposure data of activities and working conditions over the same period of time and the same working population. Effectiveness of risk reducing measures affecting the working conditions, worker behaviour and/or safety barriers can be quantified through the effect of these measures on occupational risk. - Highlights: • Quantification of occupational risk from a single hazard. • Influence diagram connects working conditions, worker behaviour and safety barriers. • Necessary data include the number of accidents and the total exposure of worker • Effectiveness of risk reducing measures is quantified through the impact on the risk • An example illustrates the methodology.

  16. Conceptual models for cumulative risk assessment.

    Science.gov (United States)

    Linder, Stephen H; Sexton, Ken

    2011-12-01

    In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive "family" of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects.

  17. Evaluation Models for E-Learning Platform in Riyadh City Universities (RCU with Applied of Geographical Information System (GIS

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    Abdulaziz I. Alharrah

    2014-12-01

    Full Text Available E-learning that integrates digital knowledge content, network and information technology has become an emerging learning method. As the e-learning platform approach is becoming an important tool to allow the flexibility and quality requested by such a kind of learning process. There is a new kind of problem faced by organizations consisting in the selection of the most suitable e-learning platform. This paper proposes evaluation model for E-Learning platform in Riyadh City universities (RCU with Applied Geographic Information System (GIS. The E-Learning platform solution selection is a multiple criteria decision-making problem that needs to be addressed objectively taking into consideration the relative weights of the criteria for any organization. We formulate the quoted multi criteria problem as a decision hierarchy to be solved using GIS. AGIS-based evaluation index system and web-based evaluating platform were established. In this paper we will show the general evaluation strategy and some obtained results using our model to evaluate some existing commercial platforms.The results of evaluation model are outlined as follows: Total weights of the proposed framework in management feature is 20.25/25, in collaborative feature is 9.2/10, in adaption learning path is 6.8/10 and in interactive learning object is 5/5. The total weights of all features are 41.25/50. In this study an evaluation model was applied on Riyadh City universities like KSU, IMAMU, NAUSS, YU and FU. Then, the results were compared with each other. The total weighs of KSU was 41. While the total weights of FU, IMAMU, YU and NAUSS was 40, 37, 36 and 32, respectively. Evaluation process shows that the proposed framework satisfied the objectives with applied GIS.

  18. Fuzzy logic model to quantify risk perception

    International Nuclear Information System (INIS)

    Bukh, Julia; Dickstein, Phineas

    2008-01-01

    The aim of this study is a quantification of public risk perception towards the nuclear field so as to be considered in decision making whenever the public involvement is sought. The proposed model includes both qualitative factors such as familiarity and voluntariness and numerical factors influencing risk perception, such as probability of occurrence and severity of consequence. Since part of these factors can be characterized only by qualitative expressions and the determination of them are linked with vagueness, imprecision and uncertainty, the most suitable method for the risk level assessment is Fuzzy Logic, which models qualitative aspects of knowledge and reasoning processes without employing precise quantitative analyses. This work, then, offers a Fuzzy-Logic based mean of representing the risk perception by a single numerical feature, which can be weighted and accounted for in decision making procedures. (author)

  19. Lifestyle-based risk model for fall risk assessment

    OpenAIRE

    Sannino, Giovanna; De Falco, Ivanoe; De Pietro, Guiseppe

    2016-01-01

    Purpose: The aim of this study was to identify the explicit relationship between life-style and the risk of falling under the form of a mathematical model. Starting from some personal and behavioral information of a subject as, e.g., weight, height, age, data about physical activity habits, and concern about falling, the model would estimate the score of her/his Mini-Balance Evaluation Systems (Mini-BES) test. This score ranges within 0 and 28, and the lower its value the more likely the subj...

  20. Healthy lifestyle factors and risk of cardiovascular events and mortality in treatment-resistant hypertension: the Reasons for Geographic and Racial Differences in Stroke study.

    Science.gov (United States)

    Diaz, Keith M; Booth, John N; Calhoun, David A; Irvin, Marguerite R; Howard, George; Safford, Monika M; Muntner, Paul; Shimbo, Daichi

    2014-09-01

    Few data exist on whether healthy lifestyle factors are associated with better prognosis among individuals with apparent treatment-resistant hypertension, a high-risk phenotype of hypertension. The purpose of this study was to assess the association of healthy lifestyle factors with cardiovascular events, all-cause mortality, and cardiovascular mortality among individuals with apparent treatment-resistant hypertension. We studied participants (n=2043) from the population-based Reasons for Geographic and Racial Differences in Stroke (REGARDS) study with apparent treatment-resistant hypertension (blood pressure ≥140/90 mm Hg despite the use of 3 antihypertensive medication classes or the use of ≥4 classes of antihypertensive medication regardless of blood pressure control). Six healthy lifestyle factors adapted from guidelines for the management of hypertension (normal waist circumference, physical activity ≥4 times/week, nonsmoking, moderate alcohol consumption, high Dietary Approaches to Stop Hypertension diet score, and low sodium-to-potassium intake ratio) were examined. A greater number of healthy lifestyle factors were associated with lower risk for cardiovascular events (n=360) during a mean follow-up of 4.5 years. Multivariable-adjusted hazard ratios [HR (95% confidence interval)] for cardiovascular events comparing individuals with 2, 3, and 4 to 6 versus 0 to 1 healthy lifestyle factors were 0.91 (0.68-1.21), 0.80 (0.57-1.14), and 0.63 (0.41-0.95), respectively (P-trend=0.020). Physical activity and nonsmoking were individual healthy lifestyle factors significantly associated with lower risk for cardiovascular events. Similar associations were observed between healthy lifestyle factors and risk for all-cause and cardiovascular mortality. In conclusion, healthy lifestyle factors, particularly physical activity and nonsmoking, are associated with a lower risk for cardiovascular events and mortality among individuals with apparent treatment

  1. Determinants of Dentists' Geographic Distribution.

    Science.gov (United States)

    Beazoglou, Tryfon J.; And Others

    1992-01-01

    A model for explaining the geographic distribution of dentists' practice locations is presented and applied to particular market areas in Connecticut. Results show geographic distribution is significantly related to a few key variables, including demography, disposable income, and housing prices. Implications for helping students make practice…

  2. Seroprevalence of feline immunodeficiency virus and feline leukaemia virus in Australia: risk factors for infection and geographical influences (2011–2013

    Directory of Open Access Journals (Sweden)

    Mark E Westman

    2016-05-01

    Full Text Available Objectives Our aim was to: (i determine the current seroprevalence of feline immunodeficiency virus (FIV and feline leukaemia virus (FeLV in three large cohorts of cats from Australia; and (ii investigate potential risk factors for retroviral infection. Methods Cohort 1 (n = 2151 for FIV, n = 2241 for FeLV consisted of cats surrendered to a shelter on the west coast of Australia (Perth, Western Australia [WA]. Cohort 2 (n = 2083 for FIV, n = 2032 for FeLV consisted of client-owned cats with outdoor access recruited from around Australia through participating veterinary clinics. Cohort 3 (n = 169 for FIV, n = 166 for FeLV consisted of cats presenting to Murdoch University Veterinary Hospital for a variety of reasons. Fresh whole blood was collected and tested using a commercially available point-of-care lateral flow ELISA kit that detects p27 FeLV antigen and antibodies to FIV antigens (p15 and p24 (cohorts 1 and 2, or one of two lateral flow immunochromatography kits that detect p27 antigen and antibodies to FIV antigen (p24 and/or gp40 (cohort 3. Data recorded for cats in cohort 2 included signalment, presenting complaint and postcode, allowing investigation of risk factors for FIV or FeLV infection, as well as potential geographical ‘hot spots’ for infection. Results The seroprevalence of FIV was 6% (cohort 1, 15% (cohort 2 and 14% (cohort 3, while the seroprevalence of FeLV was 1%, 2% and 4% in the same respective cohorts. Risk factors for FIV infection among cats in cohort 2 included age (>3 years, sex (male, neutering status (entire males and location (WA had a significantly higher FIV seroprevalence compared with the Australian Capital Territory, New South Wales and Victoria. Risk factors for FeLV infection among cats in cohort 2 included health status (‘sick’ and location (WA cats were approximately three times more likely to be FeLV-infected compared with the rest of Australia. No geographical hot spots of FIV infection were

  3. Comparison of height-diameter models based on geographically weighted regressions and linear mixed modelling applied to large scale forest inventory data

    Energy Technology Data Exchange (ETDEWEB)

    Quirós Segovia, M.; Condés Ruiz, S.; Drápela, K.

    2016-07-01

    Aim of the study: The main objective of this study was to test Geographically Weighted Regression (GWR) for developing height-diameter curves for forests on a large scale and to compare it with Linear Mixed Models (LMM). Area of study: Monospecific stands of Pinus halepensis Mill. located in the region of Murcia (Southeast Spain). Materials and Methods: The dataset consisted of 230 sample plots (2582 trees) from the Third Spanish National Forest Inventory (SNFI) randomly split into training data (152 plots) and validation data (78 plots). Two different methodologies were used for modelling local (Petterson) and generalized height-diameter relationships (Cañadas I): GWR, with different bandwidths, and linear mixed models. Finally, the quality of the estimated models was compared throughout statistical analysis. Main results: In general, both LMM and GWR provide better prediction capability when applied to a generalized height-diameter function than when applied to a local one, with R2 values increasing from around 0.6 to 0.7 in the model validation. Bias and RMSE were also lower for the generalized function. However, error analysis showed that there were no large differences between these two methodologies, evidencing that GWR provides results which are as good as the more frequently used LMM methodology, at least when no additional measurements are available for calibrating. Research highlights: GWR is a type of spatial analysis for exploring spatially heterogeneous processes. GWR can model spatial variation in tree height-diameter relationship and its regression quality is comparable to LMM. The advantage of GWR over LMM is the possibility to determine the spatial location of every parameter without additional measurements. Abbreviations: GWR (Geographically Weighted Regression); LMM (Linear Mixed Model); SNFI (Spanish National Forest Inventory). (Author)

  4. Forecasting the regional distribution and sufficiency of physicians in Japan with a coupled system dynamics-geographic information system model.

    Science.gov (United States)

    Ishikawa, Tomoki; Fujiwara, Kensuke; Ohba, Hisateru; Suzuki, Teppei; Ogasawara, Katsuhiko

    2017-09-12

    In Japan, the shortage of physicians has been recognized as a major medical issue. In our previous study, we reported that the absolute shortage will be resolved in the long term, but maldistribution among specialties will persist. To address regional shortage, several Japanese medical schools increased existing quota and established "regional quotas." This study aims to assist policy makers in designing effective policies; we built a model for forecasting physician numbers by region to evaluate future physician supply-demand balances. For our case study, we selected Hokkaido Prefecture in Japan, a region displaying disparities in healthcare services availability between urban and rural areas. We combined a system dynamics (SD) model with geographic information system (GIS) technology to analyze the dynamic change in spatial distribution of indicators. For Hokkaido overall and for each secondary medical service area (SMSA) within the prefecture, we analyzed the total number of practicing physicians. For evaluating absolute shortage and maldistribution, we calculated sufficiency levels and Gini coefficient. Our study covered the period 2010-2030 in 5-year increments. According to our forecast, physician shortage in Hokkaido Prefecture will largely be resolved by 2020. Based on current policies, we forecast that four SMSAs in Hokkaido will continue to experience physician shortages past that date, but only one SMSA would still be understaffed in 2030. The results show the possibility that diminishing imbalances between SMSAs would not necessarily mean that regional maldistribution would be eliminated, as seen from the sufficiency levels of the various SMSAs. Urgent steps should be taken to place doctors in areas where our forecasting model predicts that physician shortages could occur in the future.

  5. Geographic information systems-based expert system modelling for shoreline sensitivity to oil spill disaster in Rivers State, Nigeria

    Directory of Open Access Journals (Sweden)

    Olanrewaju Lawal

    2017-07-01

    Full Text Available In the absence of adequate and appropriate actions, hazards often result in disaster. Oil spills across any environment are very hazardous; thus, oil spill contingency planning is pertinent, supported by Environmental Sensitivity Index (ESI mapping. However, a significant data gap exists across many low- and middle-income countries in aspect of environmental monitoring. This study developed a geographic information system (GIS-based expert system (ES for shoreline sensitivity to oiling. It focused on the biophysical attributes of the shoreline with Rivers State as a case study. Data on elevation, soil, relative wave exposure and satellite imageries were collated and used for the development of ES decision rules within GIS. Results show that about 70% of the shoreline are lined with swamp forest/mangroves/nympa palm, and 97% have silt and clay as dominant sediment type. From the ES, six ranks were identified; 61% of the shoreline has a rank of 9 and 19% has a rank of 3 for shoreline sensitivity. A total of 568 km out of the 728 km shoreline is highly sensitive (ranks 7–10. There is a clear indication that the study area is a complex mixture of sensitive environments to oil spill. GIS-based ES with classification rules for shoreline sensitivity represents a rapid and flexible framework for automatic ranking of shoreline sensitivity to oiling. It is expected that this approach would kick-start sensitivity index mapping which is comprehensive and openly available to support disaster risk management around the oil producing regions of the country.

  6. Geographically Weighted Regression Models in Estimating Median Home Prices in Towns of Massachusetts Based on an Urban Sustainability Framework

    Directory of Open Access Journals (Sweden)

    Yaxiong Ma

    2018-03-01

    Full Text Available Housing is a key component of urban sustainability. The objective of this study was to assess the significance of key spatial determinants of median home price in towns in Massachusetts that impact sustainable growth. Our analysis investigates the presence or absence of spatial non-stationarity in the relationship between sustainable growth, measured in terms of the relationship between home values and various parameters including the amount of unprotected forest land, residential land, unemployment, education, vehicle ownership, accessibility to commuter rail stations, school district performance, and senior population. We use the standard geographically weighted regression (GWR and Mixed GWR models to analyze the effects of spatial non-stationarity. Mixed GWR performed better than GWR in terms of Akaike Information Criterion (AIC values. Our findings highlight the nature and spatial extent of the non-stationary vs. stationary qualities of key environmental and social determinants of median home price. Understanding the key determinants of housing values, such as valuation of green spaces, public school performance metrics, and proximity to public transport, enable towns to use different strategies of sustainable urban planning, while understanding urban housing determinants—such as unemployment and senior population—can help modify urban sustainable housing policies.

  7. A State-of-the-Art Review on the Integration of Building Information Modeling (BIM and Geographic Information System (GIS

    Directory of Open Access Journals (Sweden)

    Xin Liu

    2017-02-01

    Full Text Available The integration of Building Information Modeling (BIM and Geographic Information System (GIS has been identified as a promising but challenging topic to transform information towards the generation of knowledge and intelligence. Achievement of integrating these two concepts and enabling technologies will have a significant impact on solving problems in the civil, building and infrastructure sectors. However, since GIS and BIM were originally developed for different purposes, numerous challenges are being encountered for the integration. To better understand these two different domains, this paper reviews the development and dissimilarities of GIS and BIM, the existing integration methods, and investigates their potential in various applications. This study shows that the integration methods are developed for various reasons and aim to solve different problems. The parameters influencing the choice can be summarized and named as “EEEF” criteria: effectiveness, extensibility, effort, and flexibility. Compared with other methods, semantic web technologies provide a promising and generalized integration solution. However, the biggest challenges of this method are the large efforts required at early stage and the isolated development of ontologies within one particular domain. The isolation problem also applies to other methods. Therefore, openness is the key of the success of BIM and GIS integration.

  8. Modelling of chosen selectable factors of the develop of tourism with geographic IT and fuzzy sets using

    Directory of Open Access Journals (Sweden)

    Jitka Machalová

    2011-01-01

    Full Text Available The tourism is the significant tool of prosperity not only of the well-known touristic regions, but it is significant potential developing element of not so developed provincial regions. Develop and placements of tourism are dependent on factors (conditions that influence its use in concrete regions. These factors are classified into selectable, localisation, and realisation (localisation and realisation factors issue was published as a part of solution of the research plan of FBE No. MSM 6215648904, part 03. The selectable factors determine the possibilities of the region to develop tourism in demand function. The landscape character and the environment appertain to these objective presumptions. But these presumptions were subjective perceived. The aim of this paper is to make methodology of evaluation of introduced selectable factors. Geographic information technology will be use for spatial modelling. Theory of fuzzy sets, with its ability to catch the vagueness, will be use for defining of fuzzygeoelements and for the making several fuzzylayers. The fuzzylayers will be come into map algebra for whole formulation of these selectable factors. The methodology will be verified on territory micro region Babi lom (south of Moravia.

  9. Geographic Access Modeling of Emergency Obstetric and Neonatal Care in Kigoma Region, Tanzania: Transportation Schemes and Programmatic Implications.

    Science.gov (United States)

    Chen, Yi No; Schmitz, Michelle M; Serbanescu, Florina; Dynes, Michelle M; Maro, Godson; Kramer, Michael R

    2017-09-27

    Access to transportation is vital to reducing the travel time to emergency obstetric and neonatal care (EmONC) for managing complications and preventing adverse maternal and neonatal outcomes. This study examines the distribution of travel times to EmONC in Kigoma Region, Tanzania, using various transportation schemes, to estimate the proportion of live births (a proxy indicator of women needing delivery care) with poor geographic access to EmONC services. The 2014 Reproductive Health Survey of Kigoma Region identified 4 primary means of transportation used to travel to health facilities: walking, cycling, motorcycle, and 4-wheeled motor vehicle. A raster-based travel time model was used to map the 2-hour travel time catchment for each mode of transportation. Live birth density distributions were aggregated by travel time catchments, and by administrative council, to estimate the proportion of births with poor access. Of all live births in Kigoma Region, 13% occurred in areas where women can reach EmONC facilities within 2 hours on foot, 33% in areas that can be reached within 2 hours only by motorized vehicles, and 32% where it is impossible to reach EmONC facilities within 2 hours. Over 50% of births in 3 of the 8 administrative councils had poor estimated access. In half the councils, births with poor access could be reduced to no higher than 12% if all female residents had access to motorized vehicles. Significant differences in geographic access to EmONC in Kigoma Region, Tanzania, were observed both by location and by primary transportation type. As most of the population may only have good EmONC access when using mechanized or motorized vehicles, bicycles and motorcycles should be incorporated into the health transportation strategy. Collaboration between private transportation sectors and obstetric service providers could improve access to EmONC services among most populations. In areas where residents may not access EmONC facilities within 2 hours

  10. Risk Measurement and Risk Modelling Using Applications of Vine Copulas

    Directory of Open Access Journals (Sweden)

    David E. Allen

    2017-09-01

    Full Text Available This paper features an application of Regular Vine copulas which are a novel and recently developed statistical and mathematical tool which can be applied in the assessment of composite financial risk. Copula-based dependence modelling is a popular tool in financial applications, but is usually applied to pairs of securities. By contrast, Vine copulas provide greater flexibility and permit the modelling of complex dependency patterns using the rich variety of bivariate copulas which may be arranged and analysed in a tree structure to explore multiple dependencies. The paper features the use of Regular Vine copulas in an analysis of the co-dependencies of 10 major European Stock Markets, as represented by individual market indices and the composite STOXX 50 index. The sample runs from 2005 to the end of 2013 to permit an exploration of how correlations change indifferent economic circumstances using three different sample periods: pre-GFC (January 2005–July 2007, GFC (July 2007– September 2009, and post-GFC periods (September 2009–December 2013. The empirical results suggest that the dependencies change in a complex manner, and are subject to change in different economic circumstances. One of the attractions of this approach to risk modelling is the flexibility in the choice of distributions used to model co-dependencies. The practical application of Regular Vine metrics is demonstrated via an example of the calculation of the VaR of a portfolio made up of the indices.

  11. Modeling species’ realized climatic niche space and predicting their response to global warming for several western forest species with small geographic distributions

    Science.gov (United States)

    Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston

    2010-01-01

    The Random Forests multiple regression tree was used to develop an empirically based bioclimatic model of the presence-absence of species occupying small geographic distributions in western North America. The species assessed were subalpine larch (Larix lyallii), smooth Arizona cypress (Cupressus arizonica ssp. glabra...

  12. Crossing physical simulations of snow conditions and a geographic model of ski area to assess ski resorts vulnerability

    Science.gov (United States)

    François, Hugues; Spandre, Pierre; Morin, Samuel; George-Marcelpoil, Emmanuelle; Lafaysse, Matthieu; Lejeune, Yves

    2016-04-01

    In order to face climate change, meteorological variability and the recurrent lack of natural snow on the ground, ski resorts adaptation often rely on technical responses. Indeed, since the occurrence of episodes with insufficient snowfalls in the early 1990's, snowmaking has become an ordinary practice of snow management, comparable to grooming, and contributes to optimise the operation of ski resorts. It also participates to the growth of investments and is associated with significant operating costs, and thus represents a new source of vulnerability. The assessment of the actual effects of snowmaking and of snow management practices in general is a real concern for the future of the ski industry. The principal model use to simulate snow conditions in resorts, Ski Sim, has also been moving this way. Its developers introduced an artificial input of snow on ski area to complete natural snowfalls and considered different organisations of ski lifts (lower and upper zones). However the use of a degree-day model prevents them to consider the specific properties of artificial snow and the impact of grooming on the snowpack. A first proof of concept in the French Alps has shown the feasibility and the interest to cross the geographic model of ski areas and the output of the physically-based reanalysis of snow conditions SAFRAN - Crocus (François et al., CRST 2014). Since these initial developments, several ways have been explored to refine our model. A new model of ski areas has been developed. Our representation is now based on gravity derived from a DEM and ski lift localisation. A survey about snow management practices also allowed us to define criteria in order to model snowmaking areas given ski areas properties and tourism infrastructures localisation. We also suggest to revisit the assessment of ski resort viability based on the "one hundred days rule" based on natural snow depth only. Indeed, the impact of snow management must be considered so as to propose

  13. Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L. Using Herbarium Data and a Maximum Entropy Model

    Directory of Open Access Journals (Sweden)

    Guoqing Li

    2014-11-01

    Full Text Available Black locust (Robinia pseudoacacia L. is a tree species of high economic and ecological value, but is also considered to be highly invasive. Understanding the global potential distribution and ecological characteristics of this species is a prerequisite for its practical exploitation as a resource. Here, a maximum entropy modeling (MaxEnt was used to simulate the potential distribution of this species around the world, and the dominant climatic factors affecting its distribution were selected by using a jackknife test and the regularized gain change during each iteration of the training algorithm. The results show that the MaxEnt model performs better than random, with an average test AUC value of 0.9165 (±0.0088. The coldness index, annual mean temperature and warmth index were the most important climatic factors affecting the species distribution, explaining 65.79% of the variability in the geographical distribution. Species response curves showed unimodal relationships with the annual mean temperature and warmth index, whereas there was a linear relationship with the coldness index. The dominant climatic conditions in the core of the black locust distribution are a coldness index of −9.8 °C–0 °C, an annual mean temperature of 5.8 °C–14.5 °C, a warmth index of 66 °C–168 °C and an annual precipitation of 508–1867 mm. The potential distribution of black locust is located mainly in the United States, the United Kingdom, Germany, France, the Netherlands, Belgium, Italy, Switzerland, Australia, New Zealand, China, Japan, South Korea, South Africa, Chile and Argentina. The predictive map of black locust, climatic thresholds and species response curves can provide globally applicable guidelines and valuable information for policymakers and planners involved in the introduction, planting and invasion control of this species around the world.

  14. Risk assessment of trace metal-polluted coastal sediments on Hainan Island: A full-scale set of 474 geographical locations covering the entire island.

    Science.gov (United States)

    Li, Feng; Lin, Ze-Feng; Wen, Jia-Sheng; Wei, Yan-Sha; Gan, Hua-Yang; He, Hai-Jun; Lin, Jin-Qin; Xia, Zhen; Chen, Bi-Shuang; Guo, Wen-Jie; Tan, Cha-Sheng; Cai, Hua-Yang

    2017-12-15

    Hainan Island is the second largest island and one of the most famous tourist destinations in China, but sediment contamination by trace metals in coastal areas is a major issue. However, full-scale risk assessments of trace metal-polluted coastal sediments are lacking. In this study, coastal surface sediments from 474 geographical locations covering almost the entire island were collected to identify risk-related variables. Controlling factors and possible sources of trace metals were identified, and the toxicity effects were carefully evaluated. Our results suggest that trace-metal pollution in coastal sediments, which was mainly caused by Pb, Zn and Cu emissions, has primarily resulted from industrial sewage and shipping activities and has threatened the offshore ecosystem of Hainan Island and warrants extensive consideration. This is the first study that has systematically investigated trace metal-polluted coastal sediments throughout the entirety of Hainan Island and provides solid evidence for sustainable marine management in the region. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  16. Risk considerations related to lung modeling

    International Nuclear Information System (INIS)

    Masse, R.; Cross, F.T.

    1989-01-01

    Improved lung models provide a more accurate assessment of dose from inhalation exposures and, therefore, more accurate dose-response relationships for risk evaluation and exposure limitation. Epidemiological data for externally irradiated persons indicate that the numbers of excess respiratory tract carcinomas differ in the upper airways, bronchi, and distal lung. Neither their histogenesis and anatomical location nor their progenitor cells are known with sufficient accuracy for accurate assessment of the microdosimetry. The nuclei of sensitive cells generally can be assumed to be distributed at random in the epithelium, beneath the mucus and tips of the beating cilia and cells. In stratified epithelia, basal cells may be considered the only cells at risk. Upper-airway tumors have been observed in both therapeutically irradiated patients and in Hiroshima-Nagasaki survivors. The current International Commission on Radiological Protection Lung-Model Task Group proposes that the upper airways and lung have a similar relative risk coefficient for cancer induction. The partition of the risk weighting factor, therefore, will be proportional to the spontaneous death rate from tumors, and 80% of the weighting factor for the respiratory tract should be attributed to the lung. For Weibel lung-model branching generations 0 to 16 and 17 to 23, the Task Group proposes an 80/20 partition of the risk, i.e., 64% and 16%, respectively, of the total risk. Regarding risk in animals, recent data in rats indicate a significantly lower effectiveness for lung-cancer induction at low doses from insoluble long-lived alpha-emitters than from Rn daughters. These findings are due, in part, to the fact that different regions of the lung are irradiated. Tumors in the lymph nodes are rare in people and animals exposed to radiation.44 references

  17. Modeling foreign exchange risk premium in Armenia

    Czech Academy of Sciences Publication Activity Database

    Poghosyan, T.; Kočenda, E.; Zemčík, Petr

    2008-01-01

    Roč. 44, č. 1 (2008), s. 41-61 ISSN 1540-496X R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : foreign exchange risk premium * Armenia * affine term structure models Subject RIV: AH - Economics Impact factor: 0.611, year: 2008

  18. Modeling foreign exchange risk premium in Armenia

    Czech Academy of Sciences Publication Activity Database

    Poghosyan, Tigran; Kočenda, Evžen; Zemčík, P.

    2008-01-01

    Roč. 44, č. 1 (2008), s. 41-61 ISSN 1540-496X R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:MSM0021620846 Keywords : foreign exchange risk premium * Armenia * affine term structure models Subject RIV: AH - Economics Impact factor: 0.611, year: 2008

  19. A Probabilistic Asteroid Impact Risk Model

    Science.gov (United States)

    Mathias, Donovan L.; Wheeler, Lorien F.; Dotson, Jessie L.

    2016-01-01

    Asteroid threat assessment requires the quantification of both the impact likelihood and resulting consequence across the range of possible events. This paper presents a probabilistic asteroid impact risk (PAIR) assessment model developed for this purpose. The model incorporates published impact frequency rates with state-of-the-art consequence assessment tools, applied within a Monte Carlo framework that generates sets of impact scenarios from uncertain parameter distributions. Explicit treatment of atmospheric entry is included to produce energy deposition rates that account for the effects of thermal ablation and object fragmentation. These energy deposition rates are used to model the resulting ground damage, and affected populations are computed for the sampled impact locations. The results for each scenario are aggregated into a distribution of potential outcomes that reflect the range of uncertain impact parameters, population densities, and strike probabilities. As an illustration of the utility of the PAIR model, the results are used to address the question of what minimum size asteroid constitutes a threat to the population. To answer this question, complete distributions of results are combined with a hypothetical risk tolerance posture to provide the minimum size, given sets of initial assumptions. Model outputs demonstrate how such questions can be answered and provide a means for interpreting the effect that input assumptions and uncertainty can have on final risk-based decisions. Model results can be used to prioritize investments to gain knowledge in critical areas or, conversely, to identify areas where additional data has little effect on the metrics of interest.

  20. Issues in Value-at-Risk Modeling and Evaluation

    NARCIS (Netherlands)

    J. Daníelsson (Jón); C.G. de Vries (Casper); B.N. Jorgensen (Bjørn); P.F. Christoffersen (Peter); F.X. Diebold (Francis); T. Schuermann (Til); J.A. Lopez (Jose); B. Hirtle (Beverly)

    1998-01-01

    textabstractDiscusses the issues in value-at-risk modeling and evaluation. Value of value at risk; Horizon problems and extreme events in financial risk management; Methods of evaluating value-at-risk estimates.

  1. Modeling inputs to computer models used in risk assessment

    International Nuclear Information System (INIS)

    Iman, R.L.

    1987-01-01

    Computer models for various risk assessment applications are closely scrutinized both from the standpoint of questioning the correctness of the underlying mathematical model with respect to the process it is attempting to model and from the standpoint of verifying that the computer model correctly implements the underlying mathematical model. A process that receives less scrutiny, but is nonetheless of equal importance, concerns the individual and joint modeling of the inputs. This modeling effort clearly has a great impact on the credibility of results. Model characteristics are reviewed in this paper that have a direct bearing on the model input process and reasons are given for using probabilities-based modeling with the inputs. The authors also present ways to model distributions for individual inputs and multivariate input structures when dependence and other constraints may be present

  2. Model based risk assessment - the CORAS framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.

    2004-04-15

    Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)

  3. Mechanistic modeling for mammography screening risks

    International Nuclear Information System (INIS)

    Bijwaard, Harmen

    2008-01-01

    Full text: Western populations show a very high incidence of breast cancer and in many countries mammography screening programs have been set up for the early detection of these cancers. Through these programs large numbers of women (in the Netherlands, 700.000 per year) are exposed to low but not insignificant X-ray doses. ICRP based risk estimates indicate that the number of breast cancer casualties due to mammography screening can be as high as 50 in the Netherlands per year. The number of lives saved is estimated to be much higher, but for an accurate calculation of the benefits of screening a better estimate of these risks is indispensable. Here it is attempted to better quantify the radiological risks of mammography screening through the application of a biologically based model for breast tumor induction by X-rays. The model is applied to data obtained from the National Institutes of Health in the U.S. These concern epidemiological data of female TB patients who received high X-ray breast doses in the period 1930-1950 through frequent fluoroscopy of their lungs. The mechanistic model that is used to describe the increased breast cancer incidence is based on an earlier study by Moolgavkar et al. (1980), in which the natural background incidence of breast cancer was modeled. The model allows for a more sophisticated extrapolation of risks to the low dose X-ray exposures that are common in mammography screening and to the higher ages that are usually involved. Furthermore, it allows for risk transfer to other (non-western) populations. The results have implications for decisions on the frequency of screening, the number of mammograms taken at each screening, minimum and maximum ages for screening and the transfer to digital equipment. (author)

  4. Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.

    Directory of Open Access Journals (Sweden)

    Ente J J Rood

    Full Text Available Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.

  5. An investigation by LA-ICP-MS of possum tooth enamel as a model for identifying childhood geographical locations of historical and archaeological human remains from New Zealand

    International Nuclear Information System (INIS)

    Cameron, N.E.; Balks, M.; Littler, R.; Manley-Harris, M.; Te Awekotuku, N.

    2012-01-01

    LA-ICP-MS (laser ablation-inductively coupled plasma-mass spectrometry) has been used to analyse enamel from the teeth of brushtail possum (Trichosurus vulpecula) in order to model a method for identifying the childhood geographical origin of human remains within New Zealand. The model application of the method is promising for establishing locations of historical and archaeological human remains, including preserved heads, upoko tuhi. (author). 30 refs., 5 figs., 6 tabs.

  6. Challenges of Modeling Flood Risk at Large Scales

    Science.gov (United States)

    Guin, J.; Simic, M.; Rowe, J.

    2009-04-01

    algorithm propagates the flows for each simulated event. The model incorporates a digital terrain model (DTM) at 10m horizontal resolution, which is used to extract flood plain cross-sections such that a one-dimensional hydraulic model can be used to estimate extent and elevation of flooding. In doing so the effect of flood defenses in mitigating floods are accounted for. Finally a suite of vulnerability relationships have been developed to estimate flood losses for a portfolio of properties that are exposed to flood hazard. Historical experience indicates that a for recent floods in Great Britain more than 50% of insurance claims occur outside the flood plain and these are primarily a result of excess surface flow, hillside flooding, flooding due to inadequate drainage. A sub-component of the model addresses this issue by considering several parameters that best explain the variability of claims off the flood plain. The challenges of modeling such a complex phenomenon at a large scale largely dictate the choice of modeling approaches that need to be adopted for each of these model components. While detailed numerically-based physical models exist and have been used for conducting flood hazard studies, they are generally restricted to small geographic regions. In a probabilistic risk estimation framework like our current model, a blend of deterministic and statistical techniques have to be employed such that each model component is independent, physically sound and is able to maintain the statistical properties of observed historical data. This is particularly important because of the highly non-linear behavior of the flooding process. With respect to vulnerability modeling, both on and off the flood plain, the challenges include the appropriate scaling of a damage relationship when applied to a portfolio of properties. This arises from the fact that the estimated hazard parameter used for damage assessment, namely maximum flood depth has considerable uncertainty. The

  7. Risk analysis: divergent models and convergent interpretations

    Science.gov (United States)

    Carnes, B. A.; Gavrilova, N.

    2001-01-01

    Material presented at a NASA-sponsored workshop on risk models for exposure conditions relevant to prolonged space flight are described in this paper. Analyses used mortality data from experiments conducted at Argonne National Laboratory on the long-term effects of external whole-body irradiation on B6CF1 mice by 60Co gamma rays and fission neutrons delivered as a single exposure or protracted over either 24 or 60 once-weekly exposures. The maximum dose considered was restricted to 1 Gy for neutrons and 10 Gy for gamma rays. Proportional hazard models were used to investigate the shape of the dose response at these lower doses for deaths caused by solid-tissue tumors and tumors of either connective or epithelial tissue origin. For protracted exposures, a significant mortality effect was detected at a neutron dose of 14 cGy and a gamma-ray dose of 3 Gy. For single exposures, radiation-induced mortality for neutrons also occurred within the range of 10-20 cGy, but dropped to 86 cGy for gamma rays. Plots of risk relative to control estimated for each observed dose gave a visual impression of nonlinearity for both neutrons and gamma rays. At least for solid-tissue tumors, male and female mortality was nearly identical for gamma-ray exposures, but mortality risks for females were higher than for males for neutron exposures. As expected, protracting the gamma-ray dose reduced mortality risks. Although curvature consistent with that observed visually could be detected by a model parameterized to detect curvature, a relative risk term containing only a simple term for total dose was usually sufficient to describe the dose response. Although detectable mortality for the three pathology end points considered typically occurred at the same level of dose, the highest risks were almost always associated with deaths caused by tumors of epithelial tissue origin.

  8. NEPR Geographic Zone Map 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geographic zone map was created by interpreting satellite and aerial imagery, seafloor topography (bathymetry model), and the new NEPR Benthic Habitat Map...

  9. Risk management model in road transport systems

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2016-08-01

    The article presents the results of a study of road safety indicators that influence the development and operation of the transport system. Road safety is considered as a continuous process of risk management. Authors constructed a model that relates the social risks of a major road safety indicator - the level of motorization. The model gives a fairly accurate assessment of the level of social risk for any given level of motorization. Authors calculated the dependence of the level of socio-economic costs of accidents and injured people in them. The applicability of the concept of socio-economic damage is caused by the presence of a linear relationship between the natural and economic indicators damage from accidents. The optimization of social risk is reduced to finding the extremum of the objective function that characterizes the economic effect of the implementation of measures to improve safety. The calculations make it possible to maximize the net present value, depending on the costs of improving road safety, taking into account socio-economic damage caused by accidents. The proposed econometric models make it possible to quantify the efficiency of the transportation system, allow to simulate the change in road safety indicators.

  10. Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

    Science.gov (United States)

    Ji, Zexuan; Chen, Qiang; Niu, Sijie; Leng, Theodore; Rubin, Daniel L

    2018-01-01

    To automatically and accurately segment geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images by constructing a voting system with deep neural networks without the use of retinal layer segmentation. An automatic GA segmentation method for SD-OCT images based on the deep network was constructed. The structure of the deep network was composed of five layers, including one input layer, three hidden layers, and one output layer. During the training phase, the labeled A-scans with 1024 features were directly fed into the network as the input layer to obtain the deep representations. Then a soft-max classifier was trained to determine the label of each individual pixel. Finally, a voting decision strategy was used to refine the segmentation results among 10 trained models. Two image data sets with GA were used to evaluate the model. For the first dataset, our algorithm obtained a mean overlap ratio (OR) 86.94% ± 8.75%, absolute area difference (AAD) 11.49% ± 11.50%, and correlation coefficients (CC) 0.9857; for the second dataset, the mean OR, AAD, and CC of the proposed method were 81.66% ± 10.93%, 8.30% ± 9.09%, and 0.9952, respectively. The proposed algorithm was capable of improving over 5% and 10% segmentation accuracy, respectively, when compared with several state-of-the-art algorithms on two data sets. Without retinal layer segmentation, the proposed algorithm could produce higher segmentation accuracy and was more stable when compared with state-of-the-art methods that relied on retinal layer segmentation results. Our model may provide reliable GA segmentations from SD-OCT images and be useful in the clinical diagnosis of advanced nonexudative AMD. Based on the deep neural networks, this study presents an accurate GA segmentation method for SD-OCT images without using any retinal layer segmentation results, and may contribute to improved understanding of advanced nonexudative AMD.

  11. Construction of Site Risk Model using Individual Unit Risk Model in a NPP Site

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Ho Gon; Han, Sang Hoon [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    Since Fukushima accident, strong needs to estimate site risk has been increased to identify the possibility of re-occurrence of such a tremendous disaster and prevent such a disaster. Especially, in a site which has large fleet of nuclear power plants, reliable site risk assessment is very emergent to confirm the safety. In Korea, there are several nuclear power plant site which have more than 6 NPPs. In general, risk model of a NPP in terms of PSA is very complicated and furthermore, it is expected that the site risk model is more complex than that. In this paper, the method for constructing site risk model is proposed by using individual unit risk model. Procedure for the development of site damage (risk) model was proposed in the present paper. Since the site damage model is complicated in the sense of the scale of the system and dependency of the components of the system, conventional method may not be applicable in many side of the problem.

  12. Value at Risk models for Energy Risk Management

    OpenAIRE

    Novák, Martin

    2010-01-01

    The main focus of this thesis lies on description of Risk Management in context of Energy Trading. The paper will predominantly discuss Value at Risk and its modifications as a main overall indicator of Energy Risk.

  13. Research about social, curricular and geographical transversality of a teaching and learning history model based on ojbects as primary sources and classroom museums

    Directory of Open Access Journals (Sweden)

    Glória Solé

    2017-01-01

    Full Text Available The article’s starting point is the problem of perception and understanding of history –which is essential to create a critical citizenship- by future citizens (primary school students as well as future educators (teachers training university students. The article proposes two models of teaching and learning history and its development in two case studies adapted to different ages and geographical contexts (case 1: teachers training degree students of a Spanish university and case 2: Portuguese primary education pupils. Results of the development of the teaching and learning model in both contexts are presented at the same time that the social, curricular and geographical transversality of the model proposed is exposed.

  14. Crop insurance: Risks and models of insurance

    Directory of Open Access Journals (Sweden)

    Čolović Vladimir

    2014-01-01

    Full Text Available The issue of crop protection is very important because of a variety of risks that could cause difficult consequences. One type of risk protection is insurance. The author in the paper states various models of insurance in some EU countries and the systems of subsidizing of insurance premiums by state. The author also gives a picture of crop insurance in the U.S., noting that in this country pays great attention to this matter. As for crop insurance in Serbia, it is not at a high level. The main problem with crop insurance is not only the risks but also the way of protection through insurance. The basic question that arises not only in the EU is the question is who will insure and protect crops. There are three possibilities: insurance companies under state control, insurance companies that are public-private partnerships or private insurance companies on a purely commercial basis.

  15. Latitude, sunshine, and human lactase phenotype distributions may contribute to geographic patterns of modern disease: the inflammatory bowel disease model

    Directory of Open Access Journals (Sweden)

    Szilagyi A

    2014-05-01

    Full Text Available Andrew Szilagyi,1 Henry Leighton,2 Barry Burstein,3 Xiaoqing Xue41Division of Gastroenterology, Department of Medicine, Jewish General Hospital, 2Department of Atmospheric and Oceanic Sciences, 3Department of Medicine, Jewish General Hospital, 4Department of Emergency Medicine, Jewish General Hospital, McGill University, Montreal, QC, CanadaAbstract: Countries with high lactase nonpersistence (LNP or low lactase persistence (LP populations have lower rates of some “western” diseases, mimicking the effects of sunshine and latitude. Inflammatory bowel disease (IBD, ie, Crohn's disease and ulcerative colitis, is putatively also influenced by sunshine. Recent availability of worldwide IBD rates and lactase distributions allows more extensive comparisons. The aim of this study was to evaluate the extent to which modern day lactase distributions interact with latitude, sunshine exposure, and IBD rates. National IBD rates, national distributions of LP/LNP, and population-weighted average national annual ultraviolet B exposure were obtained, estimated, or calculated from the literature. Negative binomial analysis was used to assess the relationship between the three parameters and IBD rates. Analyses for 55 countries were grouped in three geographic domains, ie, global, Europe, and non-Europe. In Europe, both latitude and ultraviolet B exposure correlate well with LP/LNP and IBD. In non-Europe, latitude and ultraviolet B exposure correlate weakly with LP/LNP, but the latter retains a more robust correlation with IBD. In univariate analysis, latitude, ultraviolet B exposure, and LP/LNP all had significant relationships with IBD. Multivariate analysis showed that lactase distributions provided the best model of fit for IBD. The model of IBD reveals the evolutionary effects of the human lactase divide, and suggests that latitude, ultraviolet B exposure, and LP/LNP mimic each other because LP/LNP follows latitudinal directions toward the equator

  16. Improvement of the projection models for radiogenic cancer risk

    International Nuclear Information System (INIS)

    Tong Jian

    2005-01-01

    Calculations of radiogenic cancer risk are based on the risk projection models for specific cancer sites. Improvement has been made for the parameters used in the previous models including introductions of mortality and morbidity risk coefficients, and age-/ gender-specific risk coefficients. These coefficients have been applied to calculate the radiogenic cancer risks for specific organs and radionuclides under different exposure scenarios. (authors)

  17. ABO and Rhesus blood groups and risk of endometriosis in a French Caucasian population of 633 patients living in the same geographic area.

    Science.gov (United States)

    Borghese, Bruno; Chartier, Mélanie; Souza, Carlos; Santulli, Pietro; Lafay-Pillet, Marie-Christine; de Ziegler, Dominique; Chapron, Charles

    2014-01-01

    The identification of epidemiological factors increasing the risk of endometriosis could shorten the time to diagnosis. Specific blood groups may be more common in patients with endometriosis. We designed a cross-sectional study of 633 Caucasian women living in the same geographic area. Study group included 311 patients with histologically proven endometriosis. Control group included 322 patients without endometriosis as checked during surgery. Frequencies of ABO and Rhesus groups in the study and control groups were compared using univariate and multivariate analyses. We observed a higher proportion of Rh-negative women in the study group, as compared to healthy controls. Multivariate analysis showed that Rh-negative women are twice as likely to develop endometriosis (aOR = 1.90; 95% CI: 1.20-2.90). There was no significant difference in ABO group distribution between patients and controls. There was no difference when taking into account either the clinical forms (superficial endometriosis, endometrioma, and deep infiltration endometriosis) or the rAFS stages. Rh-negative women are twice as likely to develop endometriosis. Chromosome 1p, which contains the genes coding for the Rhesus, could also harbor endometriosis susceptibility genes.

  18. Health risk assessment of heavy metals via dietary intake of five pistachio (Pistacia vera L.) cultivars collected from different geographical sites of Iran.

    Science.gov (United States)

    Taghizadeh, Seyedeh Faezeh; Davarynejad, Gholamhossein; Asili, Javad; Nemati, Seyed Hossein; Rezaee, Ramin; Goumenou, Marina; Tsatsakis, Aristides M; Karimi, Gholamreza

    2017-09-01

    Pistachio is an important horticultural product and Iran is considered as a main pistachio producing country. Assessment of heavy metals in this export fruit is crucial for protecting public health against toxic heavy metals. The concentration of selected heavy metals in soil, water and five pistachio cultivars from four geographical regions of Iran were measured. Although none of the elements were detected in water irrigation, infield metal content in the soil had good correlation with that of pistachio. The highest amounts of Al, As, Co, Ni and Se were reported in samples collected from Sarakhs, Iran. Considering both cultivar and region effects on selected heavy metals concentration, Kaleghoochi cultivar from Sarakhs site showed the highest amount of Al, As, Ni and Se. The maximum concentration of Hg was found in Akbari cultivar collected from Damghan. In the Akbari and the Ahmad aghaei cultivars collected from Sarakhs and Damghan cultivation zones, respectively, the highest amount of Co were observed. Based on our results, the HI value for the consumers of Iranian pistachio was 0.066. It seems that the levels of heavy metals in these pistachio samples pose no risk to consumers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Risk assessment model for development of advanced age-related macular degeneration.

    Science.gov (United States)

    Klein, Michael L; Francis, Peter J; Ferris, Frederick L; Hamon, Sara C; Clemons, Traci E

    2011-12-01

    To design a risk assessment model for development of advanced age-related macular degeneration (AMD) incorporating phenotypic, demographic, environmental, and genetic risk factors. We evaluated longitudinal data from 2846 participants in the Age-Related Eye Disease Study. At baseline, these individuals had all levels of AMD, ranging from none to unilateral advanced AMD (neovascular or geographic atrophy). Follow-up averaged 9.3 years. We performed a Cox proportional hazards analysis with demographic, environmental, phenotypic, and genetic covariates and constructed a risk assessment model for development of advanced AMD. Performance of the model was evaluated using the C statistic and the Brier score and externally validated in participants in the Complications of Age-Related Macular Degeneration Prevention Trial. The final model included the following independent variables: age, smoking history, family history of AMD (first-degree member), phenotype based on a modified Age-Related Eye Disease Study simple scale score, and genetic variants CFH Y402H and ARMS2 A69S. The model did well on performance measures, with very good discrimination (C statistic = 0.872) and excellent calibration and overall performance (Brier score at 5 years = 0.08). Successful external validation was performed, and a risk assessment tool was designed for use with or without the genetic component. We constructed a risk assessment model for development of advanced AMD. The model performed well on measures of discrimination, calibration, and overall performance and was successfully externally validated. This risk assessment tool is available for online use.

  20. Applied socio-hydrology using volunteer geographic information (VGI) to integrate ecosystem-based adaptation (EbA) and disaster risk reduction (DRR)

    Science.gov (United States)

    Mendiondo, Eduardo; Taffarello, Denise; Mohor, Guilherme; Guzmán, Diego; Câmara de Freitas, Clarissa; Fava, Maria Clara; Restrepo, Camilo; Abreu, Fernando; Batalini, Marina; Lago, Cesar; Abe, Narumi; Rosa, Altair

    2017-04-01

    Socio-hydrology proposes to understand coupled human-water systems by conceptualizing its components to be dynamically connected by bi-directional feedbacks. For practical purposes, especially in developing countries of South America, socio-hydrology does integrate practical, empirical and theoretical fundamentals from citizens' knowledge and culture. This contribution shows South American examples of how volunteer geographic information (VGI) can help socio-hydrology to integrate emerging aspects with heavy feedbacks, exploding uncertainties and relevant scales of socio-hydrological scales. Here we select examples at different scales of using VGI to link aspects of ecosystem-based adaptation (EbA) and disaster risk reduction (DRR). On the one hand, we show some learning cases of EbA/VGI linked to socio-hydrology also related with water valuation, both monetary and non-monetary, under scenarios of changing conditions of land-use and land cover changes of strategic water supply systems in subtropical biomes. This example brings a bridge of VGI and EbA towards Disaster Risk Reduction (DRR) through water topics of securitization, insurance, smart cities and sustainable urban drainage systems (SUDS). Thus, on the other hand, we also depict how VGI support applied elements for socio-hydrology on South American urban areas, capable of policy actions for DRR through SUDS at human-impacted biomes under extremes of droughts, floods and pollution. We here recommend yardsticks of learning conditions from these real examples of using VGI's knowledge and culture biases for a more resilient socio-hydrology, in order to create opportunities for theoretical, conceptual and applied nature of EbA and DRR with viable alliances from IAHS/Panta Rhei with UN/Sendai/DRR Framework and UN/Sustainable Development Goals. From these examples, however, seem plausible co-evolutionary dynamics with stakeholders if local-scale constraints, from sociopolitical nature, institutions' policies and

  1. Human Plague Risk: Spatial-Temporal Models

    Science.gov (United States)

    Pinzon, Jorge E.

    2010-01-01

    This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

  2. A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

    Science.gov (United States)

    Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

    2018-01-01

    Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

  3. Geographic analysis of shigellosis in Vietnam.

    Science.gov (United States)

    Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Park, Jin-Kyung; von Seidlein, Lorenz; Clemens, John

    2008-12-01

    Geographic and ecological analysis may provide investigators useful ecological information for the control of shigellosis. This paper provides distribution of individual Shigella species in space, and ecological covariates for shigellosis in Nha Trang, Vietnam. Data on shigellosis in neighborhoods were used to identify ecological covariates. A Bayesian hierarchical model was used to obtain joint posterior distribution of model parameters and to construct smoothed risk maps for shigellosis. Neighborhoods with a high proportion of worshippers of traditional religion, close proximity to hospital, or close proximity to the river had increased risk for shigellosis. The ecological covariates associated with Shigella flexneri differed from the covariates for Shigella sonnei. In contrast the spatial distribution of the two species was similar. The disease maps can help identify high-risk areas of shigellosis that can be targeted for interventions. This approach may be useful for the selection of populations and the analysis of vaccine trials.

  4. Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model.

    Science.gov (United States)

    Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun

    2018-06-01

    The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Model of Axiological Dimension Risk Management

    Directory of Open Access Journals (Sweden)

    Kulińska Ewa

    2016-01-01

    Full Text Available It was on the basis of the obtained results that identify the key prerequisites for the integration of the management of logistics processes, management of the value creation process, and risk management that the methodological basis for the construction of the axiological dimension of the risk management (ADRM model of logistics processes was determined. By taking into account the contribution of individual concepts to the new research area, its essence was defined as an integrated, structured instrumentation aimed at the identification and implementation of logistics processes supporting creation of the value added as well as the identification and elimination of risk factors disturbing the process of the value creation for internal and external customers. The base for the ADRM concept of logistics processes is the use of the potential being inherent in synergistic effects which are obtained by using prerequisites for the integration of the management of logistics processes, of value creation and risk management as the key determinants of the value creation.

  6. Electricity market pricing, risk hedging and modeling

    Science.gov (United States)

    Cheng, Xu

    In this dissertation, we investigate the pricing, price risk hedging/arbitrage, and simplified system modeling for a centralized LMP-based electricity market. In an LMP-based market model, the full AC power flow model and the DC power flow model are most widely used to represent the transmission system. We investigate the differences of dispatching results, congestion pattern, and LMPs for the two power flow models. An appropriate LMP decomposition scheme to quantify the marginal costs of the congestion and real power losses is critical for the implementation of financial risk hedging markets. However, the traditional LMP decomposition heavily depends on the slack bus selection. In this dissertation we propose a slack-independent scheme to break LMP down into energy, congestion, and marginal loss components by analyzing the actual marginal cost of each bus at the optimal solution point. The physical and economic meanings of the marginal effect at each bus provide accurate price information for both congestion and losses, and thus the slack-dependency of the traditional scheme is eliminated. With electricity priced at the margin instead of the average value, the market operator typically collects more revenue from power sellers than that paid to power buyers. According to the LMP decomposition results, the revenue surplus is then divided into two parts: congestion charge surplus and marginal loss revenue surplus. We apply the LMP decomposition results to the financial tools, such as financial transmission right (FTR) and loss hedging right (LHR), which have been introduced to hedge against price risks associated to congestion and losses, to construct a full price risk hedging portfolio. The two-settlement market structure and the introduction of financial tools inevitably create market manipulation opportunities. We investigate several possible market manipulation behaviors by virtual bidding and propose a market monitor approach to identify and quantify such

  7. Modelling of spatial prediction of fire ignition risk in the Antalya-Manavgat district

    Directory of Open Access Journals (Sweden)

    Coşkun Okan Güney

    2016-07-01

    Full Text Available The aim of this study was to present the fire ignition risk for Manavgat-Antalya District to enable the planning of firefighting sources in a more qualified way. From sites within the study area, where forest fires broke out or not during the past five years, we obtained geographical coordinates, climate data, topographical data and variables like bedrock, stand types, settlement areas, roads and power lines and prepared them with geographical information systems. For all variables we performed Wilcoxon rank-sum test, interspecific correlation analysis and logistic regression analysis and obtained 4 different models. When ROC analysis was applied to these models, model 4 was determined as the most significant model and therefore used to prepare the fire ignition risk map for the Manavgat-Antalya District. According to this map, ignition risk within the study area was highest in and around settlement areas where roads and power lines concentrate and Turkish red pine is distributed, but it was lowest afar of settlement areas without roads and where species apart from Turkish red pine are distributed. According to the results some suggestions were made.

  8. Pesticide exposure and hepatocellular carcinoma risk: A case-control study using a geographic information system (GIS) to link SEER-Medicare and California pesticide data.

    Science.gov (United States)

    VoPham, Trang; Brooks, Maria M; Yuan, Jian-Min; Talbott, Evelyn O; Ruddell, Darren; Hart, Jaime E; Chang, Chung-Chou H; Weissfeld, Joel L

    2015-11-01

    Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is associated with low survival. U.S. studies examining self-reported pesticide exposure in relation to HCC have demonstrated inconclusive results. We aimed to clarify the association between pesticide exposure and HCC by implementing a novel data linkage between Surveillance, Epidemiology, and End Results (SEER)-Medicare and California Pesticide Use Report (PUR) data using a geographic information system (GIS). Controls were frequency-matched to HCC cases diagnosed between 2000 and 2009 in California by year, age, race, sex, and duration of residence in California. Potential confounders were extracted from Medicare claims. From 1974 to 2008, pounds (1 pound represents 0.45 kg) of applied organophosphate, organochlorine, and carbamate pesticides provided in PURs were aggregated to the ZIP Code level using area weighting in a GIS. ZIP Code exposure estimates were linked to subjects using Medicare-provided ZIP Codes to calculate pesticide exposure. Agricultural residents were defined as living in ZIP Codes with a majority area intersecting agricultural land cover according to the 1992, 2001, and 2006 National Land Cover Database (NLCD) rasters. Multivariable conditional logistic regression was used to estimate the association between pesticide exposure and HCC. Among California residents of agriculturally intensive areas, previous annual ZIP Code-level exposure to over 14.53 kg/km(2) of organochlorine pesticides (75(th) percentile among controls) was associated with an increased risk of HCC after adjusting for liver disease and diabetes (adjusted odds ratio [OR] 1.87, 95% confidence interval [CI] 1.17, 2.99; p=0.0085). ZIP Code-level organochlorines were significantly associated with an increased risk of HCC among males (adjusted OR 2.76, 95% CI 1.58, 4.82; p=0.0004), but not associated with HCC among females (adjusted OR 0.83, 95% CI 0.35, 1.93; p=0.6600) (interaction p=0.0075). This is

  9. Measures of Kidney Disease and the Risk of Venous Thromboembolism in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study.

    Science.gov (United States)

    Cheung, Katharine L; Zakai, Neil A; Folsom, Aaron R; Kurella Tamura, Manjula; Peralta, Carmen A; Judd, Suzanne E; Callas, Peter W; Cushman, Mary

    2017-08-01

    Kidney disease has been associated with venous thromboembolism (VTE) risk, but results conflict and there is little information regarding blacks. Prospective cohort study. 30,239 black and white adults 45 years or older enrolled in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study 2003 to 2007. Estimated glomerular filtration rate (eGFR) using the combined creatinine-cystatin C (eGFR cr-cys ) equation and urinary albumin-creatinine ratio (ACR). The primary outcome was adjudicated VTE, and secondary outcomes were provoked and unprovoked VTE, separately. Mortality was a competing-risk event. During 4.6 years of follow-up, 239 incident VTE events occurred over 124,624 person-years. Cause-specific HRs of VTE were calculated using proportional hazards regression adjusted for age, sex, race, region of residence, and body mass index. Adjusted VTE HRs for eGFR cr-cys of 60 to <90, 45 to <60, and <45 versus ≥90mL/min/1.73m 2 were 1.28 (95% CI, 0.94-1.76), 1.30 (95% CI, 0.77-2.18), and 2.13 (95% CI, 1.21-3.76). Adjusted VTE HRs for ACR of 10 to <30, 30 to <300, and ≥300 versus <10mg/g were 1.14 (95% CI, 0.84-1.56), 1.15 (95% CI, 0.79-1.69), and 0.64 (95% CI, 0.25-1.62). Associations were similar for provoked and unprovoked VTE. Single measurement of eGFR and ACR may have led to misclassification. Smaller numbers of events may have limited power. There was an independent association of low eGFR (<45 vs ≥90mL/min/1.73m 2 ) with VTE risk, but no association of ACR and VTE. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  10. Regional scale ecological risk assessment: using the relative risk model

    National Research Council Canada - National Science Library

    Landis, Wayne G

    2005-01-01

    ...) in the performance of regional-scale ecological risk assessments. The initial chapters present the methodology and the critical nature of the interaction between risk assessors and decision makers...

  11. A spatial mean-variance MIP model for energy market risk analysis

    International Nuclear Information System (INIS)

    Yu, Zuwei

    2003-01-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets

  12. A spatial mean-variance MIP model for energy market risk analysis

    International Nuclear Information System (INIS)

    Zuwei Yu

    2003-01-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets. (author)

  13. A spatial mean-variance MIP model for energy market risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zuwei Yu [Purdue University, West Lafayette, IN (United States). Indiana State Utility Forecasting Group and School of Industrial Engineering

    2003-05-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets. (author)

  14. A spatial mean-variance MIP model for energy market risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Zuwei [Indiana State Utility Forecasting Group and School of Industrial Engineering, Purdue University, Room 334, 1293 A.A. Potter, West Lafayette, IN 47907 (United States)

    2003-05-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets.

  15. NGNP Risk Management Database: A Model for Managing Risk

    International Nuclear Information System (INIS)

    Collins, John

    2009-01-01

    To facilitate the implementation of the Risk Management Plan, the Next Generation Nuclear Plant (NGNP) Project has developed and employed an analytical software tool called the NGNP Risk Management System (RMS). A relational database developed in Microsoft(reg s ign) Access, the RMS provides conventional database utility including data maintenance, archiving, configuration control, and query ability. Additionally, the tool's design provides a number of unique capabilities specifically designed to facilitate the development and execution of activities outlined in the Risk Management Plan. Specifically, the RMS provides the capability to establish the risk baseline, document and analyze the risk reduction plan, track the current risk reduction status, organize risks by reference configuration system, subsystem, and component (SSC) and Area, and increase the level of NGNP decision making.

  16. NGNP Risk Management Database: A Model for Managing Risk

    Energy Technology Data Exchange (ETDEWEB)

    John Collins

    2009-09-01

    To facilitate the implementation of the Risk Management Plan, the Next Generation Nuclear Plant (NGNP) Project has developed and employed an analytical software tool called the NGNP Risk Management System (RMS). A relational database developed in Microsoft® Access, the RMS provides conventional database utility including data maintenance, archiving, configuration control, and query ability. Additionally, the tool’s design provides a number of unique capabilities specifically designed to facilitate the development and execution of activities outlined in the Risk Management Plan. Specifically, the RMS provides the capability to establish the risk baseline, document and analyze the risk reduction plan, track the current risk reduction status, organize risks by reference configuration system, subsystem, and component (SSC) and Area, and increase the level of NGNP decision making.

  17. Characteristics of Black Men Who Have Sex With Men in Baltimore, Philadelphia, and Washington, D.C.: Geographic Diversity in Socio-Demographics and HIV Transmission Risk.

    Science.gov (United States)

    German, Danielle; Brady, Kathleen; Kuo, Irene; Opoku, Jenevieve; Flynn, Colin; Patrick, Rudy; Park, Ju Nyeong; Adams, Joella; Carroll, Makeda; Simmons, Ron; Smith, Carlton R; Davis, Wendy W

    2017-07-01

    Baltimore, Philadelphia, and Washington, DC are geographically proximate cities with high HIV prevalence, including among black men who have sex with men (BMSM). Using data collected among BMSM in CDC's National HIV Behavioral Surveillance project, we compared socio-demographic characteristics, HIV risk behaviors, and service utilization to explore similarities and differences that could inform local and regional HIV intervention approaches. BMSM were recruited through venue time location sampling, June-December, 2011. Participants completed identical socio-behavioral surveys and voluntary HIV testing. Analyses were conducted among the full sample and those aged 18-24. Participants included 159 (DC), 364 (Baltimore), and 331 (Philadelphia) eligible BMSM. HIV prevalence was 23.1% (DC), 48.0% (Baltimore), 14.6% (Philadelphia) with 30.6%, 69.0%, 33.3% unrecognized HIV infection, respectively. Among BMSM 18-24, HIV prevalence was 11.1% (DC), 38.9% (Baltimore), 9.6% (Philadelphia) with unrecognized HIV infection 0.0%, 73.8%, 60.0% respectively. Compared with the other 2 cities, Baltimore participants were less likely to identify as gay/homosexual; more likely to report unemployment, incarceration, homelessness, sex exchange; and least likely to use the internet for partners. DC participants were more likely to have a college degree and employment. Philadelphia participants were more likely to report gay/homosexual identity, receptive condomless anal sex, having only main partners, and bars/clubs as partner meeting places. Sexually transmitted disease testing was universally low. Analyses showed especially high HIV prevalence among BMSM in Baltimore including among young BMSM. Socio-demographic characteristics and HIV infection correlates differed across cities but unrecognized HIV infection and unknown partner status were universally high.

  18. A study on the use and modeling of geographical information system for combating forest crimes: an assessment of crimes in the eastern Mediterranean forests.

    Science.gov (United States)

    Pak, Mehmet; Gülci, Sercan; Okumuş, Arif

    2018-01-06

    This study focuses on the geo-statistical assessment of spatial estimation models in forest crimes. Used widely in the assessment of crime and crime-dependent variables, geographic information system (GIS) helps the detection of forest crimes in rural regions. In this study, forest crimes (forest encroachment, illegal use, illegal timber logging, etc.) are assessed holistically and modeling was performed with ten different independent variables in GIS environment. The research areas are three Forest Enterprise Chiefs (Baskonus, Cinarpinar, and Hartlap) affiliated to Kahramanmaras Forest Regional Directorate in Kahramanmaras. An estimation model was designed using ordinary least squares (OLS) and geographically weighted regression (GWR) methods, which are often used in spatial association. Three different models were proposed in order to increase the accuracy of the estimation model. The use of variables with a variance inflation factor (VIF) value of lower than 7.5 in Model I and lower than 4 in Model II and dependent variables with significant robust probability values in Model III are associated with forest crimes. Afterwards, the model with the lowest corrected Akaike Information Criterion (AIC c ), and the highest R 2 value was selected as the comparison criterion. Consequently, Model III proved to be more accurate compared to other models. For Model III, while AIC c was 328,491 and R 2 was 0.634 for OLS-3 model, AIC c was 318,489 and R 2 was 0.741 for GWR-3 model. In this respect, the uses of GIS for combating forest crimes provide different scenarios and tangible information that will help take political and strategic measures.

  19. Integrated source-risk model for radon: A definition study

    International Nuclear Information System (INIS)

    Laheij, G.M.H.; Aldenkamp, F.J.; Stoop, P.

    1993-10-01

    The purpose of a source-risk model is to support policy making on radon mitigation by comparing effects of various policy options and to enable optimization of counter measures applied to different parts of the source-risk chain. There are several advantages developing and using a source-risk model: risk calculations are standardized; the effects of measures applied to different parts of the source-risk chain can be better compared because interactions are included; and sensitivity analyses can be used to determine the most important parameters within the total source-risk chain. After an inventory of processes and sources to be included in the source-risk chain, the models presently available in the Netherlands are investigated. The models were screened for completeness, validation and operational status. The investigation made clear that, by choosing for each part of the source-risk chain the most convenient model, a source-risk chain model for radon may be realized. However, the calculation of dose out of the radon concentrations and the status of the validation of most models should be improved. Calculations with the proposed source-risk model will give estimations with a large uncertainty at the moment. For further development of the source-risk model an interaction between the source-risk model and experimental research is recommended. Organisational forms of the source-risk model are discussed. A source-risk model in which only simple models are included is also recommended. The other models are operated and administrated by the model owners. The model owners execute their models for a combination of input parameters. The output of the models is stored in a database which will be used for calculations with the source-risk model. 5 figs., 15 tabs., 7 appendices, 14 refs

  20. Automating risk analysis of software design models.

    Science.gov (United States)

    Frydman, Maxime; Ruiz, Guifré; Heymann, Elisa; César, Eduardo; Miller, Barton P

    2014-01-01

    The growth of the internet and networked systems has exposed software to an increased amount of security threats. One of the responses from software developers to these threats is the introduction of security activities in the software development lifecycle. This paper describes an approach to reduce the need for costly human expertise to perform risk analysis in software, which is common in secure development methodologies, by automating threat modeling. Reducing the dependency on security experts aims at reducing the cost of secure development by allowing non-security-aware developers to apply secure development with little to no additional cost, making secure development more accessible. To automate threat modeling two data structures are introduced, identification trees and mitigation trees, to identify threats in software designs and advise mitigation techniques, while taking into account specification requirements and cost concerns. These are the components of our model for automated threat modeling, AutSEC. We validated AutSEC by implementing it in a tool based on data flow diagrams, from the Microsoft security development methodology, and applying it to VOMS, a grid middleware component, to evaluate our model's performance.

  1. Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

    Science.gov (United States)

    Fernandes, R.; Braunschweig, F.; Lourenço, F.; Neves, R.

    2016-02-01

    The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area - the Portuguese continental shelf - with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns ("hot spots") or developing sensitivity analysis to specific conditions, whereas real

  2. Nuclear power investment risk economic model

    International Nuclear Information System (INIS)

    Houghton, W.J.; Postula, F.D.

    1985-12-01

    This paper describes an economic model which was developed to evaluate the net costs incurred by a utility due to an accident induced outage at a nuclear power plant. During such an outage the portion of the plant operating costs associated with power production are saved; however, the owning utility faces a sizable expense as fossil fuels are burned as a substitute for the incapacitated nuclear power. Additional expenses are incurred by the utility for plant repair and if necessary, decontamination costs. The model makes provision for mitigating these costs by sales of power, property damage insurance payments, tax write-offs and increased rates. Over 60 economic variables contribute to the net cost uncertainty. The values of these variables are treated as uncertainty distributions and are used in a Monte carlo computer program to evaluate the cost uncertainty (investment risk) associated with damage which could occur from various categories of initiating accidents. As an example, results of computations for various levels of damage associated with a loss of coolant accident are shown as a range of consequential plant downtime and unrecovered cost. A typical investment risk profile is shown for these types of accidents. Cost/revenue values for each economic factor are presented for a Three Mile Island - II type accident, e.g., uncontrolled core heatup. 4 refs., 6 figs., 3 tabs

  3. Model-based mitigation of availability risks

    NARCIS (Netherlands)

    Zambon, E.; Bolzoni, D.; Etalle, S.; Salvato, M.

    2007-01-01

    The assessment and mitigation of risks related to the availability of the IT infrastructure is becoming increasingly important in modern organizations. Unfortunately, present standards for risk assessment and mitigation show limitations when evaluating and mitigating availability risks. This is due

  4. Model-Based Mitigation of Availability Risks

    NARCIS (Netherlands)

    Zambon, Emmanuele; Bolzoni, D.; Etalle, Sandro; Salvato, Marco

    2007-01-01

    The assessment and mitigation of risks related to the availability of the IT infrastructure is becoming increasingly important in modern organizations. Unfortunately, present standards for Risk Assessment and Mitigation show limitations when evaluating and mitigating availability risks. This is due

  5. ISM Approach to Model Offshore Outsourcing Risks

    OpenAIRE

    Kumar, Sunand; Sharma, Rajiv Kumar; Chauhan, Prashant

    2014-01-01

    [EN] In an effort to achieve a competitive advantage via cost reductions and improved market responsiveness, organizations are increasingly employing offshore outsourcing as a major component of their supply chain strategies. But as evident from literature number of risks such as Political risk, Risk due to cultural differences, Compliance and regulatory risk, Opportunistic risk and Organization structural risk, which adversely affect the performance of offshore outsourcing in a supply chain ...

  6. Geographical information systems

    DEFF Research Database (Denmark)

    Möller, Bernd

    2004-01-01

    The chapter gives an introduction to Geographical Information Systems (GIS) with particular focus on their application within environmental management.......The chapter gives an introduction to Geographical Information Systems (GIS) with particular focus on their application within environmental management....

  7. GIS modeling for canine dirofilariosis risk assessment in central Italy

    Directory of Open Access Journals (Sweden)

    Michele Mortarino

    2008-05-01

    Full Text Available A survey was conducted in an area of central Italy in order to study the prevalence of Dirofilaria immitis and D. repens in dogs. Blood samples were collected from 283 dogs and examined using a modified Knott’s technique. In addition, in order to detect D. immitis occult infection, 203 serum samples were also analysed for D. immitis antigen detection. The results were analyzed in order to evaluate the behavioural and attitudinal risk factors. A geographical information system (GIS for the study area was constructed, utilizing the following data layers: administrative boundaries, elevation, temperature, rainfall and humidity. Microfilariae were detected in 32 of the 283 dogs surveyed, constituting a total Dirofilaria prevalence of 11.3%. In particular, 20 dogs (7.1% were positive for D. immitis and 12 dogs (4.2% for D. repens microfilariae. One case of D. immitis occult infection was also detected. Choroplethic municipal maps were drawn within the GIS in order to display the distribution of each Dirofilaria species in the study area. Statistical analysis showed a significant association between Dirofilaria infection and animal attitude (hunting/truffle dogs showed a higher prevalence compared to guard/pet dogs. A higher prevalence was also recorded in 2 to 5-years old dogs. Furthermore a GIS-based modelling of climatic data, collected from 5 meteorological stations in the study area, was performed to estimate the yearly number of D. immitis generations in the mosquito vector. The results of the model as depicted by GIS analysis was highly concordant with the territorial distribution of positive dogs and showed that D. immitis spreading is markedly influenced by season. The potential transmission period in the study area was found to be confined to summer months with a peak in July and August, as expected for a temperate region where summer season is the most favourable period for the parasite.

  8. Do the risk factors for type 2 diabetes mellitus vary by location? A spatial analysis of health insurance claims in Northeastern Germany using kernel density estimation and geographically weighted regression

    Directory of Open Access Journals (Sweden)

    Boris Kauhl

    2016-11-01

    Full Text Available Abstract Background The provision of general practitioners (GPs in Germany still relies mainly on the ratio of inhabitants to GPs at relatively large scales and barely accounts for an increased prevalence of chronic diseases among the elderly and socially underprivileged populations. Type 2 Diabetes Mellitus (T2DM is one of the major cost-intensive diseases with high rates of potentially preventable complications. Provision of healthcare and access to preventive measures is necessary to reduce the burden of T2DM. However, current studies on the spatial variation of T2DM in Germany are mostly based on survey data, which do not only underestimate the true prevalence of T2DM, but are also only available on large spatial scales. The aim of this study is therefore to analyse the spatial distribution of T2DM at fine geographic scales and to assess location-specific risk factors based on data of the AOK health insurance. Methods To display the spatial heterogeneity of T2DM, a bivariate, adaptive kernel density estimation (KDE was applied. The spatial scan statistic (SaTScan was used to detect areas of high risk. Global and local spatial regression models were then constructed to analyze socio-demographic risk factors of T2DM. Results T2DM is especially concentrated in rural areas surrounding Berlin. The risk factors for T2DM consist of proportions of 65–79 year olds, 80 + year olds, unemployment rate among the 55–65 year olds, proportion of employees covered by mandatory social security insurance, mean income tax, and proportion of non-married couples. However, the strength of the association between T2DM and the examined socio-demographic variables displayed strong regional variations. Conclusion The prevalence of T2DM varies at the very local level. Analyzing point data on T2DM of northeastern Germany’s largest health insurance provider thus allows very detailed, location-specific knowledge about increased medical needs. Risk factors

  9. Geographic Media Literacy

    Science.gov (United States)

    Lukinbeal, Chris

    2014-01-01

    While the use of media permeates geographic research and pedagogic practice, the underlying literacies that link geography and media remain uncharted. This article argues that geographic media literacy incorporates visual literacy, information technology literacy, information literacy, and media literacy. Geographic media literacy is the ability…

  10. Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy

    Directory of Open Access Journals (Sweden)

    Goria Sarah

    2009-05-01

    Full Text Available Abstract Background We conducted an ecological study in four French administrative departments and highlighted an excess risk in cancer morbidity for residents around municipal solid waste incinerators. The aim of this paper is to show how important are advanced tools and statistical techniques to better assess weak associations between the risk of cancer and past environmental exposures. Methods The steps to evaluate the association between the risk of cancer and the exposure to incinerators, from the assessment of exposure to the definition of the confounding variables and the statistical analysis carried out are detailed and discussed. Dispersion modelling was used to assess exposure to sixteen incinerators. A geographical information system was developed to define an index of exposure at the IRIS level that is the geographical unit we considered. Population density, rural/urban status, socio-economic deprivation, exposure to air pollution from traffic and from other industries were considered as potential confounding factors and defined at the IRIS level. Generalized additive models and Bayesian hierarchical models were used to estimate the association between the risk of cancer and the index of exposure to incinerators accounting for the confounding factors. Results Modelling to assess the exposure to municipal solid waste incinerators allowed accounting for factors known to influence the exposure (meteorological data, point source characteristics, topography. The statistical models defined allowed modelling extra-Poisson variability and also non-linear relationships between the risk of cancer and the exposure to incinerators and the confounders. Conclusion In most epidemiological studies distance is still used as a proxy for exposure. This can lead to significant exposure misclassification. Additionally, in geographical correlation studies the non-linear relationships are usually not accounted for in the statistical analysis. In studies of

  11. THE MODEL FOR RISK ASSESSMENT ERP-SYSTEMS INFORMATION SECURITY

    Directory of Open Access Journals (Sweden)

    V. S. Oladko

    2016-12-01

    Full Text Available The article deals with the problem assessment of information security risks in the ERP-system. ERP-system functions and architecture are studied. The model malicious impacts on levels of ERP-system architecture are composed. Model-based risk assessment, which is the quantitative and qualitative approach to risk assessment, built on the partial unification 3 methods for studying the risks of information security - security models with full overlapping technique CRAMM and FRAP techniques developed.

  12. A numerical 4D Collision Risk Model

    Science.gov (United States)

    Schmitt, Pal; Culloch, Ross; Lieber, Lilian; Kregting, Louise

    2017-04-01

    With the growing number of marine renewable energy (MRE) devices being installed across the world, some concern has been raised about the possibility of harming mobile, marine fauna by collision. Although physical contact between a MRE device and an organism has not been reported to date, these novel sub-sea structures pose a challenge for accurately estimating collision risks as part of environmental impact assessments. Even if the animal motion is simplified to linear translation, ignoring likely evasive behaviour, the mathematical problem of establishing an impact probability is not trivial. We present a numerical algorithm to obtain such probability distributions using transient, four-dimensional simulations of a novel marine renewable device concept, Deep Green, Minesto's power plant and hereafter referred to as the 'kite' that flies in a figure-of-eight configuration. Simulations were carried out altering several configurations including kite depth, kite speed and kite trajectory while keeping the speed of the moving object constant. Since the kite assembly is defined as two parts in the model, a tether (attached to the seabed) and the kite, collision risk of each part is reported independently. By comparing the number of collisions with the number of collision-free simulations, a probability of impact for each simulated position in the cross- section of the area is considered. Results suggest that close to the bottom, where the tether amplitude is small, the path is always blocked and the impact probability is 100% as expected. However, higher up in the water column, the collision probability is twice as high in the mid line, where the tether passes twice per period than at the extremes of its trajectory. The collision probability distribution is much more complex in the upper end of the water column, where the kite and tether can simultaneously collide with the object. Results demonstrate the viability of such models, which can also incorporate empirical

  13. Estimating internal exposure risks by the relative risk and the National Institute of Health risk models

    International Nuclear Information System (INIS)

    Mehta, S.K.; Sarangapani, R.

    1995-01-01

    This paper presents tabulations of risk (R) and person-years of life lost (PYLL) for acute exposures of individual organs at ages 20 and 40 yrs for the Indian and Japanese populations to illustrate the effect of age at exposure in the two models. Results are also presented for the organ wise nominal probability coefficients (NPC) and PYLL for individual organs for the age distributed Indian population by the two models. The results presented show that for all organs the estimates of PYLL and NPC for the Indian population are lower than those for the Japanese population by both models except for oesophagus, breast and ovary by the relative risk (RR) model, where the opposite trend is observed. The results also show that the Indian all-cancer values of NPC averaged over the two models is 2.9 x 10 -2 Sv -1 , significantly lower than the world average value of 5x10 -2 Sv -1 estimated by the ICRP. (author). 9 refs., 2 figs., 2 tabs

  14. An assessment of geographical distribution of different plant functional types over North America simulated using the CLASS-CTEM modelling framework

    Science.gov (United States)

    Shrestha, Rudra K.; Arora, Vivek K.; Melton, Joe R.; Sushama, Laxmi

    2017-10-01

    The performance of the competition module of the CLASS-CTEM (Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model) modelling framework is assessed at 1° spatial resolution over North America by comparing the simulated geographical distribution of its plant functional types (PFTs) with two observation-based estimates. The model successfully reproduces the broad geographical distribution of trees, grasses and bare ground although limitations remain. In particular, compared to the two observation-based estimates, the simulated fractional vegetation coverage is lower in the arid southwest North American region and higher in the Arctic region. The lower-than-observed simulated vegetation coverage in the southwest region is attributed to lack of representation of shrubs in the model and plausible errors in the observation-based data sets. The observation-based data indicate vegetation fractional coverage of more than 60 % in this arid region, despite only 200-300 mm of precipitation that the region receives annually, and observation-based leaf area index (LAI) values in the region are lower than one. The higher-than-observed vegetation fractional coverage in the Arctic is likely due to the lack of representation of moss and lichen PFTs and also likely because of inadequate representation of permafrost in the model as a result of which the C3 grass PFT performs overly well in the region. The model generally reproduces the broad spatial distribution and the total area covered by the two primary tree PFTs (needleleaf evergreen trees, NDL-EVG; and broadleaf cold deciduous trees, BDL-DCD-CLD) reasonably well. The simulated fractional coverage of tree PFTs increases after the 1960s in response to the CO2 fertilization effect and climate warming. Differences between observed and simulated PFT coverages highlight model limitations and suggest that the inclusion of shrubs, and moss and lichen PFTs, and an adequate representation of permafrost will help improve

  15. An assessment of geographical distribution of different plant functional types over North America simulated using the CLASS–CTEM modelling framework

    Directory of Open Access Journals (Sweden)

    R. K. Shrestha

    2017-10-01

    Full Text Available The performance of the competition module of the CLASS–CTEM (Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model modelling framework is assessed at 1° spatial resolution over North America by comparing the simulated geographical distribution of its plant functional types (PFTs with two observation-based estimates. The model successfully reproduces the broad geographical distribution of trees, grasses and bare ground although limitations remain. In particular, compared to the two observation-based estimates, the simulated fractional vegetation coverage is lower in the arid southwest North American region and higher in the Arctic region. The lower-than-observed simulated vegetation coverage in the southwest region is attributed to lack of representation of shrubs in the model and plausible errors in the observation-based data sets. The observation-based data indicate vegetation fractional coverage of more than 60 % in this arid region, despite only 200–300 mm of precipitation that the region receives annually, and observation-based leaf area index (LAI values in the region are lower than one. The higher-than-observed vegetation fractional coverage in the Arctic is likely due to the lack of representation of moss and lichen PFTs and also likely because of inadequate representation of permafrost in the model as a result of which the C3 grass PFT performs overly well in the region. The model generally reproduces the broad spatial distribution and the total area covered by the two primary tree PFTs (needleleaf evergreen trees, NDL-EVG; and broadleaf cold deciduous trees, BDL-DCD-CLD reasonably well. The simulated fractional coverage of tree PFTs increases after the 1960s in response to the CO2 fertilization effect and climate warming. Differences between observed and simulated PFT coverages highlight model limitations and suggest that the inclusion of shrubs, and moss and lichen PFTs, and an adequate representation of

  16. Modeling of groundwater potential of the sub-basin of Siriri river, Sergipe state, Brazil, based on Geographic Information System and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Washington Franca Rocha

    2011-08-01

    Full Text Available The use of Geographic Information System (GIS and Remote Sensing for modeling groundwater potential give support for the analysis and decision-making processes about water resource management in watersheds. The objective of this work consisted in modeling the groundwater water potential of Siriri river sub-basin, Sergipe state, based on its natural environment (soil, land use, slope, drainage density, lineament density, rainfall and geology using Remote Sensing and Geographic Information System as an integration environment. The groundwater potential map was done using digital image processing procedures of ENVI 4.4 software and map algebra of ArcGIS 9.3®. The Analytical Hierarchy Method was used for modeling the weights definition of the different criteria (maps. Loads and weights of the different classes were assigned to each map according to their influence on the overall objective of the work. The integration of these maps in a GIS environment and the AHP technique application allowed the development of the groundwater potential map in five classes: very low, low, moderate, high, very high. The average flow rates of wells confirm the potential of aquifers Sapucari, Barriers and Maruim since they are the most exploited in this sub-basin, with average flows of 78,113 L/h, 19,332 L/h and 12,085 L/h, respectively.

  17. A Simple Model to Rank Shellfish Farming Areas Based on the Risk of Disease Introduction and Spread.

    Science.gov (United States)

    Thrush, M A; Pearce, F M; Gubbins, M J; Oidtmann, B C; Peeler, E J

    2017-08-01

    The European Union Council Directive 2006/88/EC requires that risk-based surveillance (RBS) for listed aquatic animal diseases is applied to all aquaculture production businesses. The principle behind this is the efficient use of resources directed towards high-risk farm categories, animal types and geographic areas. To achieve this requirement, fish and shellfish farms must be ranked according to their risk of disease introduction and spread. We present a method to risk rank shellfish farming areas based on the risk of disease introduction and spread and demonstrate how the approach was applied in 45 shellfish farming areas in England and Wales. Ten parameters were used to inform the risk model, which were grouped into four risk themes based on related pathways for transmission of pathogens: (i) live animal movement, (ii) transmission via water, (iii) short distance mechanical spread (birds) and (iv) long distance mechanical spread (vessels). Weights (informed by expert knowledge) were applied both to individual parameters and to risk themes for introduction and spread to reflect their relative importance. A spreadsheet model was developed to determine quantitative scores for the risk of pathogen introduction and risk of pathogen spread for each shellfish farming area. These scores were used to independently rank areas for risk of introduction and for risk of spread. Thresholds were set to establish risk categories (low, medium and high) for introduction and spread based on risk scores. Risk categories for introduction and spread for each area were combined to provide overall risk categories to inform a risk-based surveillance programme directed at the area level. Applying the combined risk category designation framework for risk of introduction and spread suggested by European Commission guidance for risk-based surveillance, 4, 10 and 31 areas were classified as high, medium and low risk, respectively. © 2016 Crown copyright.

  18. Geographic patterns of at-risk species: A technical document supporting the USDA Forest Service Interim Update of the 2000 RPA Assessment

    Science.gov (United States)

    Curtis H. Flather; Michael S. Knowles; Jason McNees

    2008-01-01

    This technical document supports the Forest Service's requirement to assess the status of renewable natural resources as mandated by the Forest and Rangeland Renewable Resources Planning Act of 1974. It updates past reports on the trends and geographic patterns of species formally listed as threatened or endangered under the Endangered Species Act of 1973. We...

  19. Proliferation Risk Characterization Model Prototype Model - User and Programmer Guidelines

    Energy Technology Data Exchange (ETDEWEB)

    Dukelow, J.S.; Whitford, D.

    1998-12-01

    A model for the estimation of the risk of diversion of weapons-capable materials was developed. It represents both the threat of diversion and site vulnerability as a product of a small number of variables (two to eight), each of which can take on a small number (two to four) of qualitatively defined (but quantitatively implemented) values. The values of the overall threat and vulnerability variables are then converted to threat and vulnerability categories. The threat and vulnerability categories are used to define the likelihood of diversion, also defined categorically. The evaluator supplies an estimate of the consequences of a diversion, defined categorically, but with the categories based on the IAEA Attractiveness levels. Likelihood and Consequences categories are used to define the Risk, also defined categorically. The threat, vulnerability, and consequences input provided by the evaluator contains a representation of his/her uncertainty in each variable assignment which is propagated all the way through to the calculation of the Risk categories. [Appendix G available on diskette only.

  20. Two agricultural production data libraries for risk assessment models

    International Nuclear Information System (INIS)

    Baes, C.F. III; Shor, R.W.; Sharp, R.D.; Sjoreen, A.L.

    1985-01-01

    Two data libraries based on the 1974 US Census of Agriculture are described. The data packages (AGDATC and AGDATG) are available from the Radiation Shielding Information Center (RSIC), Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831. Agricultural production and land-use information by county (AGDATC) or by 1/2 by 1/2 degree longitude-latitude grid cell (AGDATG) provide geographical resolution of the data. The libraries were designed for use in risk assessment models that simulate the transport of radionuclides from sources of airborne release through food chains to man. However, they are also suitable for use in the assessment of other airborne pollutants that can affect man from a food ingestion pathway such as effluents from synfuels or coal-fired power plants. The principal significance of the data libraries is that they provide default location-specific food-chain transport parameters when site-specific information are unavailable. Plant food categories in the data libraries include leafy vegetables, vegetables and fruits exposed to direct deposition of airborne pollutants, vegetables and fruits protected from direct deposition, and grains. Livestock feeds are also tabulated in four categories: pasture, grain, hay, and silage. Pasture was estimated by a material balance of cattle and sheep inventories, forage feed requirements, and reported harvested forage. Cattle (Bos spp.), sheep (Ovis aries), goat (Capra hircus), hog (Sus scrofa), chicken (Gallus domesticus), and turkey (Meleagris gallopavo) inventories or sales are also tabulated in the data libraries and can be used to provide estimates of meat, eggs, and milk production. Honey production also is given. Population, irrigation, and meteorological information are also listed

  1. Bankruptcy risk model and empirical tests

    Science.gov (United States)

    Podobnik, Boris; Horvatic, Davor; Petersen, Alexander M.; Urošević, Branko; Stanley, H. Eugene

    2010-01-01

    We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor—the debt-to-asset ratio R—in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market crashes, implying that firms go bankrupt with larger values of R. Based on the Zipf analysis, we employ Bayes’s theorem and relate the conditional probability that a bankrupt firm has a ratio R with the conditional probability of bankruptcy for a firm with a given R value. For 2,737 bankrupt firms, we demonstrate size dependence in assets change during the bankruptcy proceedings. Prepetition firm assets and petition firm assets follow Zipf distributions but with different exponents, meaning that firms with smaller assets adjust their assets more than firms with larger assets during the bankruptcy process. We compare bankrupt firms with nonbankrupt firms by analyzing the assets and liabilities of two large subsets of the US economy: 2,545 Nasdaq members and 1,680 New York Stock Exchange (NYSE) members. We find that both assets and liabilities follow a Pareto distribution. The finding is not a trivial consequence of the Zipf scaling relationship of firm size quantified by employees—although the market capitalization of Nasdaq stocks follows a Pareto distribution, the same distribution does not describe NYSE stocks. We propose a coupled Simon model that simultaneously evolves both assets and debt with the possibility of bankruptcy, and we also consider the possibility of firm mergers. PMID:20937903

  2. A multi-model analysis of risk of ecosystem shifts under climate change

    International Nuclear Information System (INIS)

    Warszawski, Lila; Ostberg, Sebastian; Frieler, Katja; Lucht, Wolfgang; Schaphoff, Sibyll; Buechner, Matthias; Piontek, Franziska; Friend, Andrew; Keribin, Rozenn; Rademacher, Tim Tito; Beerling, David; Lomas, Mark; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B; Kahana, Ron; Ito, Akihiko; Nishina, Kazuya; Kleidon, Axel; Pavlick, Ryan

    2013-01-01

    Climate change may pose a high risk of change to Earth’s ecosystems: shifting climatic boundaries may induce changes in the biogeochemical functioning and structures of ecosystems that render it difficult for endemic plant and animal species to survive in their current habitats. Here we aggregate changes in the biogeochemical ecosystem state as a proxy for the risk of these shifts at different levels of global warming. Estimates are based on simulations from seven global vegetation models (GVMs) driven by future climate scenarios, allowing for a quantification of the related uncertainties. 5–19% of the naturally vegetated land surface is projected to be at risk of severe ecosystem change at 2 ° C of global warming (ΔGMT) above 1980–2010 levels. However, there is limited agreement across the models about which geographical regions face the highest risk of change. The extent of regions at risk of severe ecosystem change is projected to rise with ΔGMT, approximately doubling between ΔGMT = 2 and 3 ° C, and reaching a median value of 35% of the naturally vegetated land surface for ΔGMT = 4 °C. The regions projected to face the highest risk of severe ecosystem changes above ΔGMT = 4 °C or earlier include the tundra and shrublands of the Tibetan Plateau, grasslands of eastern India, the boreal forests of northern Canada and Russia, the savanna region in the Horn of Africa, and the Amazon rainforest. (letter)

  3. Using geographic information systems

    International Nuclear Information System (INIS)

    Winsor, R.W.

    1997-01-01

    A true Geographic Information System (GIS) is a computer mapping system with spatial analysis ability and cartographic accuracy that will offer many different projections. GIS has evolved to become an everyday tool for a wide range of users including oil companies, worldwide. Other systems are designed to allow oil and gas companies to keep their upstream data in the same format. Among these are the Public Petroleum Data Model developed by Gulf Canada, Digitech and Applied Terravision Systems of Calgary, the system developed and marketed by the Petrotechnical Open Software Corporation in the United States, and the Mercury projects by IBM. These have been developed in an effort to define an industry standard. The advantages and disadvantages of open and closed systems were discussed. Factors to consider when choosing a GIS system such as overall performance, area of use and query complexity, were reviewed. 3 figs

  4. Geographical information system based model of land suitability for good yield of rice in prachuap khiri khan province, thailand

    International Nuclear Information System (INIS)

    Hussain, W.; Sohaib, O.

    2012-01-01

    Correct assessment of land is a major issue in agricultural sector to use possible capability of any land, to raise cultivation and production of rice. Geographical Information System (GIS) provides broad techniques for suitable land classifications. This study is GIS based on land suitability analysis for rice farming in Prachuap Khiri Khan Province, Thailand, where the main livelihood of people is rice farming. This analysis was conducted considering the relationship of rice production with various data layers of elevation, slope, soil pH, rainfall, fertilizer use and land use. ArcView GIS 3.2 software is used to consider each layer according to related data to weight every coefficient, ranking techniques are used. It was based on determining correlation of rice production and these variables. This analysis showed a positive correlation with these variables in varying degrees depending on the magnitude and quality of these factors. By combining both data layers of GIS and weighted linear combination, various suitable lands have been developed for cultivation of rice. Integrated suitable assessment map and current land were compared to find suitable land in Prachuap Khiri Khan Province of Thailand. As a result of this comparison, we get a land which is suitable for optimum utilization for rice production in Prachuap Khiri Khan Province. (author)

  5. Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

    Science.gov (United States)

    Cibula, William G.; Nyquist, Maurice O.

    1987-01-01

    An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

  6. Modeling issues in nuclear plant fire risk analysis

    International Nuclear Information System (INIS)

    Siu, N.

    1989-01-01

    This paper discusses various issues associated with current models for analyzing the risk due to fires in nuclear power plants. Particular emphasis is placed on the fire growth and suppression models, these being unique to the fire portion of the overall risk analysis. Potentially significant modeling improvements are identified; also discussed are a variety of modeling issues where improvements will help the credibility of the analysis, without necessarily changing the computed risk significantly. The mechanistic modeling of fire initiation is identified as a particularly promising improvement for reducing the uncertainties in the predicted risk. 17 refs., 5 figs. 2 tabs

  7. A Knowledge-Based Model of Audit Risk

    OpenAIRE

    Dhar, Vasant; Lewis, Barry; Peters, James

    1988-01-01

    Within the academic and professional auditing communities, there has been growing concern about how to accurately assess the various risks associated with performing an audit. These risks are difficult to conceptualize in terms of numeric estimates. This article discusses the development of a prototype computational model (computer program) that assesses one of the major audit risks -- inherent risk. This program bases most of its inferencing activities on a qualitative model of a typical bus...

  8. Enhanced leak detection risk model development

    Energy Technology Data Exchange (ETDEWEB)

    Harron, Lorna; Barlow, Rick; Farquhar, Ted [Enbridge Pipelines Inc., Edmonton, Alberta (Canada)

    2010-07-01

    Increasing concerns and attention to pipeline safety have engaged pipeline companies and regulatory agencies to extend their approaches to pipeline integrity. The implementation of High Consequence Areas (HCAs) has especially had an impact on the development of integrity management protocols (IMPs) for pipelines. These IMPs can require that a risk based assessment of integrity issues be applied to specific HCA risk factors. This paper addresses the development of an operational risk assessment approach for pipeline leak detection requirements for HCAs. A detailed risk assessment algorithm that includes 25 risk variables and 28 consequence variables was developed for application to all HCA areas. This paper describes the consultative process that was used to workshop the development of this algorithm. Included in this description is how the process addressed various methods of leak detection across a wide variety of pipelines. The paper also looks at development challenges and future steps in applying operation risk assessment techniques to mainline leak detection risk management.

  9. Adequacy of relative and absolute risk models for lifetime risk estimate of radiation-induced cancer

    International Nuclear Information System (INIS)

    McBride, M.; Coldman, A.J.

    1988-03-01

    This report examines the applicability of the relative (multiplicative) and absolute (additive) models in predicting lifetime risk of radiation-induced cancer. A review of the epidemiologic literature, and a discussion of the mathematical models of carcinogenesis and their relationship to these models of lifetime risk, are included. Based on the available data, the relative risk model for the estimation of lifetime risk is preferred for non-sex-specific epithelial tumours. However, because of lack of knowledge concerning other determinants of radiation risk and of background incidence rates, considerable uncertainty in modelling lifetime risk still exists. Therefore, it is essential that follow-up of exposed cohorts be continued so that population-based estimates of lifetime risk are available

  10. Sigmoidal response model for radiation risk

    International Nuclear Information System (INIS)

    Kondo, Sohei

    1995-01-01

    From epidemiologic studies, we find no measurable increase in the incidences of birth defects and cancer after low-level exposure to radiation. Based on modern understanding of the molecular basis of teratogenesis and cancer, I attempt to explain thresholds observed in atomic bomb survivors, radium painters, uranium workers and patients injected with Thorotrast. Teratogenic injury induced by doses below threshold will be completely eliminated as a result of altruistic death (apoptosis) of injured cells. Various lines of evidence obtained show that oncomutations produced in cancerous cells after exposure to radiation are of spontaneous origin and that ionizing radiation acts not as an oncomutation inducer but as a tumor promoter by induction of chronic wound-healing activity. The tissue damage induced by radiation has to be repaired by cell growth and this creates opportunity for clonal expansion of a spontaneously occurring preneoplastic cell. If the wound-healing error model is correct, there must be a threshold dose range of radiation giving no increase in cancer risk. (author)

  11. A comparative review of radiation-induced cancer risk models

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung Hee; Kim, Ju Youl [FNC Technology Co., Ltd., Yongin (Korea, Republic of); Han, Seok Jung [Risk and Environmental Safety Research Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2017-06-15

    With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies. This review can be used as a basis for developing a Korean cancer risk model in the future.

  12. Modelling desertification risk in the north-west of Jordan using geospatial and remote sensing techniques

    Directory of Open Access Journals (Sweden)

    Jawad T. Al-Bakri

    2016-03-01

    Full Text Available Remote sensing, climate, and ground data were used within a geographic information system (GIS to map desertification risk in the north-west of Jordan. The approach was based on modelling wind and water erosion and incorporating the results with a map representing the severity of drought. Water erosion was modelled by the universal soil loss equation, while wind erosion was modelled by a dust emission model. The extent of drought was mapped using the evapotranspiration water stress index (EWSI which incorporated actual and potential evapotranspiration. Output maps were assessed within GIS in terms of spatial patterns and the degree of correlation with soil surficial properties. Results showed that both topography and soil explained 75% of the variation in water erosion, while soil explained 25% of the variation in wind erosion, which was mainly controlled by natural factors of topography and wind. Analysis of the EWSI map showed that drought risk was dominating most of the rainfed areas. The combined effects of soil erosion and drought were reflected on the desertification risk map. The adoption of these geospatial and remote sensing techniques is, therefore, recommended to map desertification risk in Jordan and in similar arid environments.

  13. Geographic information system for Long Island: An epidemiologic systems approach to identify environmental breast cancer risks on Long Island. Phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Barancik, J.I.; Kramer, C.F.; Thode, H.C. Jr.

    1995-12-01

    BNL is developing and implementing the project ``Geographic Information System (GIS) for Long Island`` to address the potential relationship of environmental and occupational exposures to breast cancer etiology on Long Island. The project is divided into two major phases: The four month-feasibility project (Phase 1), and the major development and implementation project (Phase 2). This report summarizes the work completed in the four month Phase 1 Project, ``Feasibility of a Geographic Information System for Long Island.`` It provides the baseline information needed to further define and prioritize the scope of work for subsequent tasks. Phase 2 will build upon this foundation to develop an operational GIS for the Long Island Breast Cancer Study Project (LIBCSP).

  14. Geographic information system for Long Island: An epidemiologic systems approach to identify environmental breast cancer risks on Long Island. Phase 1

    International Nuclear Information System (INIS)

    Barancik, J.I.; Kramer, C.F.; Thode, H.C. Jr.

    1995-01-01

    BNL is developing and implementing the project ''Geographic Information System (GIS) for Long Island'' to address the potential relationship of environmental and occupational exposures to breast cancer etiology on Long Island. The project is divided into two major phases: The four month-feasibility project (Phase 1), and the major development and implementation project (Phase 2). This report summarizes the work completed in the four month Phase 1 Project, ''Feasibility of a Geographic Information System for Long Island.'' It provides the baseline information needed to further define and prioritize the scope of work for subsequent tasks. Phase 2 will build upon this foundation to develop an operational GIS for the Long Island Breast Cancer Study Project (LIBCSP)

  15. Tutorial in biostatistics: competing risks and multi-state models

    NARCIS (Netherlands)

    Putter, H.; Fiocco, M.; Geskus, R. B.

    2007-01-01

    Standard survival data measure the time span from some time origin until the occurrence of one type of event. If several types of events occur, a model describing progression to each of these competing risks is needed. Multi-state models generalize competing risks models by also describing

  16. European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

    Science.gov (United States)

    Haylock, M. R.

    2011-10-01

    Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961-2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed. The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.

  17. European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

    Directory of Open Access Journals (Sweden)

    M. R. Haylock

    2011-10-01

    Full Text Available Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961–2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed.

    The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.

  18. Airports Geographic Information System -

    Data.gov (United States)

    Department of Transportation — The Airports Geographic Information System maintains the airport and aeronautical data required to meet the demands of the Next Generation National Airspace System....

  19. Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

    Science.gov (United States)

    Amirpour Haredasht, Sara; Polson, Dale; Main, Rodger; Lee, Kyuyoung; Holtkamp, Derald; Martínez-López, Beatriz

    2017-06-07

    Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight. The model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124). The result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

  20. Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

    Science.gov (United States)

    Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

    2015-01-01

    Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.

  1. Mixed geographically weighted regression (MGWR) model with weighted adaptive bi-square for case of dengue hemorrhagic fever (DHF) in Surakarta

    Science.gov (United States)

    Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.

    2017-06-01

    MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.

  2. Including investment risk in large-scale power market models

    DEFF Research Database (Denmark)

    Lemming, Jørgen Kjærgaard; Meibom, P.

    2003-01-01

    Long-term energy market models can be used to examine investments in production technologies, however, with market liberalisation it is crucial that such models include investment risks and investor behaviour. This paper analyses how the effect of investment risk on production technology selection...... can be included in large-scale partial equilibrium models of the power market. The analyses are divided into a part about risk measures appropriate for power market investors and a more technical part about the combination of a risk-adjustment model and a partial-equilibrium model. To illustrate...... the analyses quantitatively, a framework based on an iterative interaction between the equilibrium model and a separate risk-adjustment module was constructed. To illustrate the features of the proposed modelling approach we examined how uncertainty in demand and variable costs affects the optimal choice...

  3. Coloring geographical threshold graphs

    Energy Technology Data Exchange (ETDEWEB)

    Bradonjic, Milan [Los Alamos National Laboratory; Percus, Allon [Los Alamos National Laboratory; Muller, Tobias [EINDHOVEN UNIV. OF TECH

    2008-01-01

    We propose a coloring algorithm for sparse random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Here, we analyze the GTG coloring algorithm together with the graph's clique number, showing formally that in spite of the differences in structure between GTG and RGG, the asymptotic behavior of the chromatic number is identical: {chi}1n 1n n / 1n n (1 + {omicron}(1)). Finally, we consider the leading corrections to this expression, again using the coloring algorithm and clique number to provide bounds on the chromatic number. We show that the gap between the lower and upper bound is within C 1n n / (1n 1n n){sup 2}, and specify the constant C.

  4. Risk communication: a mental models approach

    National Research Council Canada - National Science Library

    Morgan, M. Granger (Millett Granger)

    2002-01-01

    ... information about risks. The procedure uses approaches from risk and decision analysis to identify the most relevant information; it also uses approaches from psychology and communication theory to ensure that its message is understood. This book is written in nontechnical terms, designed to make the approach feasible for anyone willing to try it. It is illustrat...

  5. Risk assessment and modeling of technical solutions for filtrations earth dams

    Directory of Open Access Journals (Sweden)

    Michael Álvarez González

    2017-12-01

    Full Text Available The paper presents the evaluation and the analysis of three types of filter geometry to evaluate the filtration risk in Zaza Reservoir, taking as starting point the historic characteristics of the fluctuation of water levels inside the earth dam. The work is based on the experience of a multidisciplinary team and previous research with bi-dimensional models, using the Finite Elements Method for the solution of basic engineering problems. Also, the results of the installation of a new filter system with a geospatial index are evaluated (under criteria of threats, vulnerability, and risk with spatial visualization data in a Geographical Information System for thematic maps generation, that represent how much the water level varies inside the dam according to the different filters evaluated.

  6. Assessing the cumulative impacts of geographically isolated wetlands on watershed hydrology using the SWAT model coupled with improved wetland modules.

    Science.gov (United States)

    Lee, S; Yeo, I-Y; Lang, M W; Sadeghi, A M; McCarty, G W; Moglen, G E; Evenson, G R

    2018-06-07

    Despite recognizing the importance of wetlands in the Coastal Plain of the Chesapeake Bay Watershed (CBW) in terms of ecosystem services, our understanding of wetland functions has mostly been limited to individual wetlands and overall catchment-scale wetland functions have rarely been investigated. This study is aimed at assessing the cumulative impacts of wetlands on watershed hydrology for an agricultural watershed within the Coastal Plain of the CBW using the Soil and Water Assessment Tool (SWAT). We employed two improved wetland modules for enhanced representation of physical processes and spatial distribution of riparian wetlands (RWs) and geographically isolated wetlands (GIWs). This study focused on GIWs as their hydrological impacts on watershed hydrology are poorly understood and GIWs are poorly protected. Multiple wetland scenarios were prepared by removing all or portions of the baseline GIW condition indicated by the U.S. Fish and Wildlife Service National Wetlands Inventory geospatial dataset. We further compared the impacts of GIWs and RWs on downstream flow (i.e., streamflow at the watershed outlet). Our simulation results showed that GIWs strongly influenced downstream flow by altering water transport mechanisms in upstream areas. Loss of all GIWs reduced both water routed to GIWs and water infiltrated into the soil through the bottom of GIWs, leading to an increase in surface runoff of 9% and a decrease in groundwater flow of 7% in upstream areas. These changes resulted in increased variability of downstream flow in response to extreme flow conditions. GIW loss also induced an increase in month to month variability of downstream flow and a decrease in the baseflow contribution to streamflow. Loss of all GIWs was shown to cause a greater fluctuation of downstream flow than loss of all RWs for this study site, due to a greater total water storage capacity of GIWs. Our findings indicate that GIWs play a significant role in controlling hydrological

  7. A coupled human and landscape conceptual model of risk and resilience in mountain communities

    Science.gov (United States)

    Ramirez, Jorge; Haisch, Tina; Martius, Olivia; Mayer, Heike; Ifejika Speranza, Chinwe; Keiler, Margreth

    2017-04-01

    Recent extreme natural disasters have focused the attention of the global community to society's vulnerability to these events. Simultaneously these natural disasters occur within a broader social and physical context that is interconnected and may include social upheavals, economic crises, and climate change. While progress has been made to mitigate and adapt to natural hazards, much of the existing research lacks interdisciplinary approaches that equally consider both natural and social processes. More importantly, this lack of integration between approaches remains a major challenge in developing disaster risk management plans for communities. In this study we focus on European Alpine communities that face numerous human and environmental risks and differ regarding their ability to cope with these risks and develop resilience. Herein we present a conceptual model of mountain communities exposed to socio-economic (e.g. economic downturn) and biophysical (e.g. floods) "shocks". We identify system boundaries, structure, components, and processes required to describe both human and landscape systems for mountain communities. More importantly we determine feedbacks within and between both systems. The purpose of the model is to investigate which shocks overcome the buffering capacity of mountain communities, and determine which shocks have a greater effect on mountain communities. Socioeconomic, climate, and hazard 'shock' scenarios have been developed for communities with different geographic sizes. Examples of inputs for the model and methods required to test the model are provided. Guided by the model and scenarios we discuss potential outcomes regarding community resilience.

  8. Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools

    Science.gov (United States)

    O'Donnell, Michael S.; Aldridge, Cameron L.; Doherty, Kevin E.; Fedy, Bradley C.

    2015-01-01

    With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.

  9. Stochastic models in risk theory and management accounting

    NARCIS (Netherlands)

    Brekelmans, R.C.M.

    2000-01-01

    This thesis deals with stochastic models in two fields: risk theory and management accounting. Firstly, two extensions of the classical risk process are analyzed. A method is developed that computes bounds of the probability of ruin for the classical risk rocess extended with a constant interest

  10. Hydrological simulation of Sperchios River basin in Central Greece using the MIKE SHE model and geographic information systems

    Science.gov (United States)

    Paparrizos, Spyridon; Maris, Fotios

    2017-05-01

    The MIKE SHE model is able to simulate the entire stream flow which includes direct and basic flow. Many models either do not simulate or use simplistic methods to determine the basic flow. The MIKE SHE model takes into account many hydrological data. Since this study was directed towards the simulation of surface runoff and infiltration into saturated and unsaturated zone, the MIKE SHE is an appropriate model for reliable conclusions. In the current research, the MIKE SHE model was used to simulate runoff in the area of Sperchios River basin. Meteorological data from eight rainfall stations within the Sperchios River basin were used as inputs. Vegetation as well as geological data was used to perform the calibration and validation of the physical processes of the model. Additionally, ArcGIS program was used. The results indicated that the model was able to simulate the surface runoff satisfactorily, representing all the hydrological data adequately. Some minor differentiations appeared which can be eliminated with the appropriate adjustments that can be decided by the researcher's experience.

  11. Geographical Inequalities and Social and Environmental Risk Factors for Under-Five Mortality in Ghana in 2000 and 2010: Bayesian Spatial Analysis of Census Data.

    Science.gov (United States)

    Arku, Raphael E; Bennett, James E; Castro, Marcia C; Agyeman-Duah, Kofi; Mintah, Samilia E; Ware, James H; Nyarko, Philomena; Spengler, John D; Agyei-Mensah, Samuel; Ezzati, Majid

    2016-06-01

    Under-five mortality is declining in Ghana and many other countries. Very few studies have measured under-five mortality-and its social and environmental risk factors-at fine spatial resolutions, which is relevant for policy purposes. Our aim was to estimate under-five mortality and its social and environmental risk factors at the district level in Ghana. We used 10% random samples of Ghana's 2000 and 2010 National Population and Housing Censuses. We applied indirect demographic methods and a Bayesian spatial model to the information on total number of children ever born and children surviving to estimate under-five mortality (probability of dying by 5 y of age, 5q0) for each of Ghana's 110 districts. We also used the census data to estimate the distributions of households or persons in each district in terms of fuel used for cooking, sanitation facility, drinking water source, and parental education. Median district 5q0 declined from 99 deaths per 1,000 live births in 2000 to 70 in 2010. The decline ranged from 40% in southern districts, where it had been lower in 2000, exacerbating existing inequalities. Primary education increased in men and women, and more households had access to improved water and sanitation and cleaner cooking fuels. Higher use of liquefied petroleum gas for cooking was associated with lower 5q0 in multivariate analysis. Under-five mortality has declined in all of Ghana's districts, but the cross-district inequality in mortality has increased. There is a need for additional data, including on healthcare, and additional environmental and socioeconomic measurements, to understand the reasons for the variations in mortality levels and trends.

  12. Geographical Inequalities and Social and Environmental Risk Factors for Under-Five Mortality in Ghana in 2000 and 2010: Bayesian Spatial Analysis of Census Data.

    Directory of Open Access Journals (Sweden)

    Raphael E Arku

    2016-06-01

    Full Text Available Under-five mortality is declining in Ghana and many other countries. Very few studies have measured under-five mortality-and its social and environmental risk factors-at fine spatial resolutions, which is relevant for policy purposes. Our aim was to estimate under-five mortality and its social and environmental risk factors at the district level in Ghana.We used 10% random samples of Ghana's 2000 and 2010 National Population and Housing Censuses. We applied indirect demographic methods and a Bayesian spatial model to the information on total number of children ever born and children surviving to estimate under-five mortality (probability of dying by 5 y of age, 5q0 for each of Ghana's 110 districts. We also used the census data to estimate the distributions of households or persons in each district in terms of fuel used for cooking, sanitation facility, drinking water source, and parental education. Median district 5q0 declined from 99 deaths per 1,000 live births in 2000 to 70 in 2010. The decline ranged from 40% in southern districts, where it had been lower in 2000, exacerbating existing inequalities. Primary education increased in men and women, and more households had access to improved water and sanitation and cleaner cooking fuels. Higher use of liquefied petroleum gas for cooking was associated with lower 5q0 in multivariate analysis.Under-five mortality has declined in all of Ghana's districts, but the cross-district inequality in mortality has increased. There is a need for additional data, including on healthcare, and additional environmental and socioeconomic measurements, to understand the reasons for the variations in mortality levels and trends.

  13. Operational risk quantification and modelling within Romanian insurance industry

    Directory of Open Access Journals (Sweden)

    Tudor Răzvan

    2017-07-01

    Full Text Available This paper aims at covering and describing the shortcomings of various models used to quantify and model the operational risk within insurance industry with a particular focus on Romanian specific regulation: Norm 6/2015 concerning the operational risk issued by IT systems. While most of the local insurers are focusing on implementing the standard model to compute the Operational Risk solvency capital required, the local regulator has issued a local norm that requires to identify and assess the IT based operational risks from an ISO 27001 perspective. The challenges raised by the correlations assumed in the Standard model are substantially increased by this new regulation that requires only the identification and quantification of the IT operational risks. The solvency capital requirement stipulated by the implementation of Solvency II doesn’t recommend a model or formula on how to integrate the newly identified risks in the Operational Risk capital requirements. In this context we are going to assess the academic and practitioner’s understanding in what concerns: The Frequency-Severity approach, Bayesian estimation techniques, Scenario Analysis and Risk Accounting based on risk units, and how they could support the modelling of operational risk that are IT based. Developing an internal model only for the operational risk capital requirement proved to be, so far, costly and not necessarily beneficial for the local insurers. As the IT component will play a key role in the future of the insurance industry, the result of this analysis will provide a specific approach in operational risk modelling that can be implemented in the context of Solvency II, in a particular situation when (internal or external operational risk databases are scarce or not available.

  14. Risk Modeling Approaches in Terms of Volatility Banking Transactions

    Directory of Open Access Journals (Sweden)

    Angelica Cucşa (Stratulat

    2016-01-01

    Full Text Available The inseparability of risk and banking activity is one demonstrated ever since banking systems, the importance of the topic being presend in current life and future equally in the development of banking sector. Banking sector development is done in the context of the constraints of nature and number of existing risks and those that may arise, and serves as limiting the risk of banking activity. We intend to develop approaches to analyse risk through mathematical models by also developing a model for the Romanian capital market 10 active trading picks that will test investor reaction in controlled and uncontrolled conditions of risk aggregated with harmonised factors.

  15. Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

    Science.gov (United States)

    Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

    2017-10-01

    Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

  16. Calibration plots for risk prediction models in the presence of competing risks

    DEFF Research Database (Denmark)

    Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

    2014-01-01

    A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks...... prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves...

  17. Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

    Science.gov (United States)

    2015-02-01

    Computational and Information Sciences Directorate Battlefield Environment Division (ATTN: RDRL- CIE -M) White Sands Missile Range, NM 88002-5501 8. PERFORMING...meteorological parameters, which became our focus. We found that elevation accounts for a significant portion of the variance in the model error. The...found that elevation accounts for a significant portion of the variance in the model error of surface temperature and relative humidity predictions

  18. The protection against nuclear risks under the international nuclear liability law: the geographical and technical scope of the international conventions on third party liability for nuclear damage

    International Nuclear Information System (INIS)

    Kissich, S.J.

    2001-10-01

    This Ph.D.-research deals with the International Conventions on Third Party Liability for Nuclear Damage. In 1960, the Paris Convention was established with the aim of providing a special uniform nuclear third party liability regime for Western Europe. This Convention was supplemented in 1963 by the Brussels Supplementary Convention. Also in 1963, the Vienna Convention, which aimed to establish a world-wide system based on the same principles as the Paris Convention, was adopted. A further Convention was adopted in 1971 to ensure that nuclear third party liability law and not maritime law would apply to carriage of nuclear materials by sea. In 1988, the Paris and Vienna Conventions have been linked by the adoption of a Joint Protocol. In 1997, the process of amending the 1963 Vienna Convention was successfully concluded and a Convention on Supplementary Compensation was adopted. This Ph.D.-research consists of seven chapters: following an introduction, the second chapter gives a general view of the existing international legal sources. The third chapter describes the international civil nuclear liability law concept and its leading principles. The main element of this work is the question of the technical and geographical scope of the international nuclear liability conventions (chapter IV and V). The conventions are only applicable to nuclear incidents, which occur in a nuclear installation or incidental to the carriage or storage of nuclear material. The nuclear damage must arise out of the radioactive properties of nuclear substances which are also defined by legal terms. In addition, the scope of the conventions is limited by the nature of the installations. The geographical scope of application is established by the provisions on geographical coverage. Only the 1963 Vienna Convention does not contain any specific provision dealing with the territorial scope of its application. The geographical scope determines where the nuclear incident or the nuclear damage

  19. The study of the risk management model of construction project

    International Nuclear Information System (INIS)

    Jiang Bo; Feng Yanping; Liu Changbin

    2010-01-01

    The paper first analyzed the development of the risk management of construction project and the risk management processes, and then briefly introduced the risk management experience of foreign project management. From the project management by objectives point of view, the greatest risk came from the lack of clarity of the objectives in the project management, which led to the project's risk emergence. In the analysis of the principles of the project objectives identification and risk allocation, the paper set up a project management model which insurance companies involved in the whole process of the project management, and simply analyzed the roles of insurance company at last. (authors)

  20. Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures.

    Science.gov (United States)

    Klenk, Jochen; Becker, Clemens; Palumbo, Pierpaolo; Schwickert, Lars; Rapp, Kilan; Helbostad, Jorunn L; Todd, Chris; Lord, Stephen R; Kerse, Ngaire

    2017-11-01

    Falls are a major cause of injury and disability in older people, leading to serious health and social consequences including fractures, poor quality of life, loss of independence, and institutionalization. To design and provide adequate prevention measures, accurate understanding and identification of person's individual fall risk is important. However, to date, the performance of fall risk models is weak compared with models estimating, for example, cardiovascular risk. This deficiency may result from 2 factors. First, current models consider risk factors to be stable for each person and not change over time, an assumption that does not reflect real-life experience. Second, current models do not consider the interplay of individual exposure including type of activity (eg, walking, undertaking transfers) and environmental risks (eg, lighting, floor conditions) in which activity is performed. Therefore, we posit a dynamic fall risk model consisting of intrinsic risk factors that vary over time and exposure (activity in context). eHealth sensor technology (eg, smartphones) begins to enable the continuous measurement of both the above factors. We illustrate our model with examples of real-world falls from the FARSEEING database. This dynamic framework for fall risk adds important aspects that may improve understanding of fall mechanisms, fall risk models, and the development of fall prevention interventions. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

  1. Risk matrix model applied to the outsourcing of logistics' activities

    Directory of Open Access Journals (Sweden)

    Fouad Jawab

    2015-09-01

    Full Text Available Purpose: This paper proposes the application of the risk matrix model in the field of logistics outsourcing. Such an application can serve as the basis for decision making regarding the conduct of a risk management in the logistics outsourcing process and allow its prevention. Design/methodology/approach: This study is based on the risk management of logistics outsourcing in the field of the retail sector in Morocco. The authors identify all possible risks and then classify and prioritize them using the Risk Matrix Model. Finally, we have come to four possible decisions for the identified risks. The analysis was made possible through interviews and discussions with the heads of departments and agents who are directly involved in each outsourced activity. Findings and Originality/value: It is possible to improve the risk matrix model by proposing more personalized prevention measures according to each company that operates in the mass-market retailing. Originality/value: This study is the only one made in the process of logistics outsourcing in the retail sector in Morocco through Label’vie as a case study. First, we had identified as thorough as we could all possible risks, then we applied the Risk Matrix Model to sort them out in an ascending order of importance and criticality. As a result, we could hand out to the decision-makers the mapping for an effective control of risks and a better guiding of the process of risk management.

  2. A Process Model for Assessing Adolescent Risk for Suicide.

    Science.gov (United States)

    Stoelb, Matt; Chiriboga, Jennifer

    1998-01-01

    This comprehensive assessment process model includes primary, secondary, and situational risk factors and their combined implications and significance in determining an adolescent's level or risk for suicide. Empirical data and clinical intuition are integrated to form a working client model that guides the professional in continuously reassessing…

  3. Tests of control in the Audit Risk Model : Effective? Efficient?

    NARCIS (Netherlands)

    Blokdijk, J.H. (Hans)

    2004-01-01

    Lately, the Audit Risk Model has been subject to criticism. To gauge its validity, this paper confronts the Audit Risk Model as incorporated in International Standard on Auditing No. 400, with the real life situations faced by auditors in auditing financial statements. This confrontation exposes

  4. Multivariate operational risk: dependence modelling with Lévy copulas

    OpenAIRE

    Böcker, K. and Klüppelberg, C.

    2015-01-01

    Simultaneous modelling of operational risks occurring in different event type/business line cells poses the challenge for operational risk quantification. Invoking the new concept of L´evy copulas for dependence modelling yields simple approximations of high quality for multivariate operational VAR.

  5. Radiation risk estimation based on measurement error models

    CERN Document Server

    Masiuk, Sergii; Shklyar, Sergiy; Chepurny, Mykola; Likhtarov, Illya

    2017-01-01

    This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.

  6. Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory

    NARCIS (Netherlands)

    Anagnostou, I.; Sourabh, S.; Kandhai, D.

    2018-01-01

    Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of

  7. Comparison of additive (absolute) risk projection models and multiplicative (relative) risk projection models in estimating radiation-induced lifetime cancer risk

    International Nuclear Information System (INIS)

    Kai, Michiaki; Kusama, Tomoko

    1990-01-01

    Lifetime cancer risk estimates depend on risk projection models. While the increasing lengths of follow-up observation periods of atomic bomb survivors in Hiroshima and Nagasaki bring about changes in cancer risk estimates, the validity of the two risk projection models, the additive risk projection model (AR) and multiplicative risk projection model (MR), comes into question. This paper compares the lifetime risk or loss of life-expectancy between the two projection models on the basis of BEIR-III report or recently published RERF report. With Japanese cancer statistics the estimates of MR were greater than those of AR, but a reversal of these results was seen when the cancer hazard function for India was used. When we investigated the validity of the two projection models using epidemiological human data and animal data, the results suggested that MR was superior to AR with respect to temporal change, but there was little evidence to support its validity. (author)

  8. Statistical and RBF NN models : providing forecasts and risk assessment

    OpenAIRE

    Marček, Milan

    2009-01-01

    Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...

  9. Modeling the distribution of Schistosoma mansoni and host snails in Uganda using satellite sensor data and Geographical Information Systems

    DEFF Research Database (Denmark)

    Stensgaard, Anna-Sofie; Jørgensen, A; Kabatereine, N B

    2005-01-01

    The potential value of MODIS satellite sensor data on Normalized Difference Vegetation Index (NDVI) and land surface temperatures (LST) for describing the distribution of the Schistosoma mansoni-"Biomphalaria pfeifferi"/Biomphalaria sudanica parasite-snail system in inland Uganda, were tested...... by developing annual and seasonal composite models, and iteratively analysing for their relationship with parasite and snail distribution. The dry season composite model predicted an endemic area that produced the best fit with the distribution of schools with > or =5% prevalence. NDVI values of 151-174, day...

  10. Risk Estimation for Lung Cancer in Libya: Analysis Based on Standardized Morbidity Ratio, Poisson-Gamma Model, BYM Model and Mixture Model

    Science.gov (United States)

    Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

    2017-03-01

    Cancer is the most rapidly spreading disease in the world, especially in developing countries, including Libya. Cancer represents a significant burden on patients, families, and their societies. This disease can be controlled if detected early. Therefore, disease mapping has recently become an important method in the fields of public health research and disease epidemiology. The correct choice of statistical model is a very important step to producing a good map of a disease. Libya was selected to perform this work and to examine its geographical variation in the incidence of lung cancer. The objective of this paper is to estimate the relative risk for lung cancer. Four statistical models to estimate the relative risk for lung cancer and population censuses of the study area for the time period 2006 to 2011 were used in this work. They are initially known as Standardized Morbidity Ratio, which is the most popular statistic, which used in the field of disease mapping, Poisson-gamma model, which is one of the earliest applications of Bayesian methodology, Besag, York and Mollie (BYM) model and Mixture model. As an initial step, this study begins by providing a review of all proposed models, which we then apply to lung cancer data in Libya. Maps, tables and graph, goodness-of-fit (GOF) were used to compare and present the preliminary results. This GOF is common in statistical modelling to compare fitted models. The main general results presented in this study show that the Poisson-gamma model, BYM model, and Mixture model can overcome the problem of the first model (SMR) when there is no observed lung cancer case in certain districts. Results show that the Mixture model is most robust and provides better relative risk estimates across a range of models. Creative Commons Attribution License

  11. Forecasting risk along a river basin using a probabilistic and deterministic model for environmental risk assessment of effluents through ecotoxicological evaluation and GIS.

    Science.gov (United States)

    Gutiérrez, Simón; Fernandez, Carlos; Barata, Carlos; Tarazona, José Vicente

    2009-12-20

    This work presents a computer model for Risk Assessment of Basins by Ecotoxicological Evaluation (RABETOX). The model is based on whole effluent toxicity testing and water flows along a specific river basin. It is capable of estimating the risk along a river segment using deterministic and probabilistic approaches. The Henares River Basin was selected as a case study to demonstrate the importance of seasonal hydrological variations in Mediterranean regions. As model inputs, two different ecotoxicity tests (the miniaturized Daphnia magna acute test and the D.magna feeding test) were performed on grab samples from 5 waste water treatment plant effluents. Also used as model inputs were flow data from the past 25 years, water velocity measurements and precise distance measurements using Geographical Information Systems (GIS). The model was implemented into a spreadsheet and the results were interpreted and represented using GIS in order to facilitate risk communication. To better understand the bioassays results, the effluents were screened through SPME-GC/MS analysis. The deterministic model, performed each month during one calendar year, showed a significant seasonal variation of risk while revealing that September represents the worst-case scenario with values up to 950 Risk Units. This classifies the entire area of study for the month of September as "sublethal significant risk for standard species". The probabilistic approach using Monte Carlo analysis was performed on 7 different forecast points distributed along the Henares River. A 0% probability of finding "low risk" was found at all forecast points with a more than 50% probability of finding "potential risk for sensitive species". The values obtained through both the deterministic and probabilistic approximations reveal the presence of certain substances, which might be causing sublethal effects in the aquatic species present in the Henares River.

  12. Development of a LiDAR derived digital elevation model (DEM) as Input to a METRANS geographic information system (GIS).

    Science.gov (United States)

    2011-05-01

    This report describes an assessment of digital elevation models (DEMs) derived from : LiDAR data for a subset of the Ports of Los Angeles and Long Beach. A methodology : based on Monte Carlo simulation was applied to investigate the accuracy of DEMs ...

  13. The complex model of risk and progression of AMD estimation

    Directory of Open Access Journals (Sweden)

    V. S. Akopyan

    2012-01-01

    Full Text Available Purpose: to develop a method and a statistical model to estimate individual risk of AMD and the risk for progression to advanced AMD using clinical and genetic risk factors.Methods: A statistical risk assessment model was developed using stepwise binary logistic regression analysis. to estimate the population differences in the prevalence of allelic variants of genes and for the development of models adapted to the population of Moscow region genotyping and assessment of the influence of other risk factors was performed in two groups: patients with differ- ent stages of AMD (n = 74, and control group (n = 116. Genetic risk factors included in the study: polymorphisms in the complement system genes (C3 and CFH, genes at 10q26 locus (ARMS2 and HtRA1, polymorphism in the mitochondrial gene Mt-ND2. Clinical risk factors included in the study: age, gender, high body mass index, smoking history.Results: A comprehensive analysis of genetic and clinical risk factors for AMD in the study group was performed. Compiled statis- tical model assessment of individual risk of AMD, the sensitivity of the model — 66.7%, specificity — 78.5%, AUC = 0.76. Risk factors of late AMD, compiled a statistical model describing the probability of late AMD, the sensitivity of the model — 66.7%, specificity — 78.3%, AUC = 0.73. the developed system allows determining the most likely version of the current late AMD: dry or wet.Conclusion: the developed test system and the mathematical algorhythm for determining the risk of AMD, risk of progression to advanced AMD have fair diagnostic informative and promising for use in clinical practice.

  14. Adoption of Building Information Modelling in project planning risk management

    Science.gov (United States)

    Mering, M. M.; Aminudin, E.; Chai, C. S.; Zakaria, R.; Tan, C. S.; Lee, Y. Y.; Redzuan, A. A.

    2017-11-01

    An efficient and effective risk management required a systematic and proper methodology besides knowledge and experience. However, if the risk management is not discussed from the starting of the project, this duty is notably complicated and no longer efficient. This paper presents the adoption of Building Information Modelling (BIM) in project planning risk management. The objectives is to identify the traditional risk management practices and its function, besides, determine the best function of BIM in risk management and investigating the efficiency of adopting BIM-based risk management during the project planning phase. In order to obtain data, a quantitative approach is adopted in this research. Based on data analysis, the lack of compliance with project requirements and failure to recognise risk and develop responses to opportunity are the risks occurred when traditional risk management is implemented. When using BIM in project planning, it works as the tracking of cost control and cash flow give impact on the project cycle to be completed on time. 5D cost estimation or cash flow modeling benefit risk management in planning, controlling and managing budget and cost reasonably. There were two factors that mostly benefit a BIM-based technology which were formwork plan with integrated fall plan and design for safety model check. By adopting risk management, potential risks linked with a project and acknowledging to those risks can be identified to reduce them to an acceptable extent. This means recognizing potential risks and avoiding threat by reducing their negative effects. The BIM-based risk management can enhance the planning process of construction projects. It benefits the construction players in various aspects. It is important to know the application of BIM-based risk management as it can be a lesson learnt to others to implement BIM and increase the quality of the project.

  15. Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

    Science.gov (United States)

    Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

    2018-01-12

    Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

  16. Investigation on circular asymmetry of geographical distribution in cancer mortality of Hiroshima atomic bomb survivors based on risk maps: analysis of spatial survival data

    International Nuclear Information System (INIS)

    Tonda, Tetsuji; Satoh, Kenichi; Otani, Keiko; Ohtaki, Megu; Sato, Yuya; Maruyama, Hirofumi; Kawakami, Hideshi; Tashiro, Satoshi; Hoshi, Masaharu

    2012-01-01

    While there is a considerable number of studies on the relationship between the risk of disease or death and direct exposure from the atomic bomb in Hiroshima, the risk for indirect exposure caused by residual radioactivity has not yet been fully evaluated. One of the reasons is that risk assessments have utilized estimated radiation doses, but that it is difficult to estimate indirect exposure. To evaluate risks for other causes, including indirect radiation exposure, as well as direct exposure, a statistical method is described here that evaluates risk with respect to individual location at the time of atomic bomb exposure instead of radiation dose. In addition, it is also considered to split the risks into separate risks due to direct exposure and other causes using radiation dose. The proposed method is applied to a cohort study of Hiroshima atomic bomb survivors. The resultant contour map suggests that the region west to the hypocenter has a higher risk compared to other areas. This in turn suggests that there exists an impact on risk that cannot be explained by direct exposure. (orig.)

  17. Investigation on circular asymmetry of geographical distribution in cancer mortality of Hiroshima atomic bomb survivors based on risk maps: analysis of spatial survival data

    Energy Technology Data Exchange (ETDEWEB)

    Tonda, Tetsuji; Satoh, Kenichi; Otani, Keiko; Ohtaki, Megu [Hiroshima University, Department of Environmetrics and Biometrics, Research Institute for Radiation Biology and Medicine (Japan); Sato, Yuya [Hiroshima University, Division of Radiation Information Registry, Research Institute for Radiation Biology and Medicine (Japan); Maruyama, Hirofumi; Kawakami, Hideshi [Hiroshima University, Department of Epidemiology, Research Institute for Radiation Biology and Medicine (Japan); Tashiro, Satoshi [Hiroshima University, Division of Radiation Information Registry, Research Institute for Radiation Biology and Medicine (Japan); Hiroshima University, Department of Cellular Biology, Research Institute for Radiation Biology and Medicine (Japan); Hoshi, Masaharu [Hiroshima University, Department of Radiation Biophysics, Research Institute for Radiation Biology and Medicine (Japan)

    2012-05-15

    While there is a considerable number of studies on the relationship between the risk of disease or death and direct exposure from the atomic bomb in Hiroshima, the risk for indirect exposure caused by residual radioactivity has not yet been fully evaluated. One of the reasons is that risk assessments have utilized estimated radiation doses, but that it is difficult to estimate indirect exposure. To evaluate risks for other causes, including indirect radiation exposure, as well as direct exposure, a statistical method is described here that evaluates risk with respect to individual location at the time of atomic bomb exposure instead of radiation dose. In addition, it is also considered to split the risks into separate risks due to direct exposure and other causes using radiation dose. The proposed method is applied to a cohort study of Hiroshima atomic bomb survivors. The resultant contour map suggests that the region west to the hypocenter has a higher risk compared to other areas. This in turn suggests that there exists an impact on risk that cannot be explained by direct exposure. (orig.)

  18. Estimation of value at risk and conditional value at risk using normal mixture distributions model

    Science.gov (United States)

    Kamaruzzaman, Zetty Ain; Isa, Zaidi

    2013-04-01

    Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

  19. A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

    Directory of Open Access Journals (Sweden)

    Xiaoxiao Ji

    2017-02-01

    Full Text Available This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1 formulation of risk assessment hierarchy; (2 representation of both qualitative and quantitative information; (3 elicitation of attribute weights and information reliabilities; (4 aggregation of assessment information using the ER rule and (5 quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

  20. Risk Decision Making Model for Reservoir Floodwater resources Utilization

    Science.gov (United States)

    Huang, X.

    2017-12-01

    Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

  1. Managing risks in business model innovation processes

    DEFF Research Database (Denmark)

    Taran, Yariv; Boer, Harry; Lindgren, Peter

    2010-01-01

    Companies today, in some industries more than others, invest more capital and resources just to stay competitive, develop more diverse solutions, and increasingly start thinking more radically when considering their business models. However, despite the understanding that business model (BM...