A Stochastic Optimization Method to Estimate the Spatial Distribution of a Pathogen from a Sample

Information on the spatial distribution of plant disease can be utilized to implement efficient and spatially targeted disease management interventions. We present a pathogen-generic method to estimate the spatial distribution of a plant pathogen using a stochastic optimization process which is epidemiologically motivated. Based on an initial sample, the method simulates the individual spread processes of a pathogen between patches of host to generate optimized spatial distribution maps. The method was tested on data sets of Huanglongbing of citrus and was compared with a kriging method from the field of geostatistics using the well-established kappa statistic to quantify map accuracy. Our method produced accurate maps of disease distribution with kappa values as high as 0.46 and was able to outperform the kriging method across a range of sample sizes based on the kappa statistic. As expected, map accuracy improved with sample size but there was a high amount of variation between different random sample placements (i.e., the spatial distribution of samples). This highlights the importance of sample placement on the ability to estimate the spatial distribution of a plant pathogen and we thus conclude that further research into sampling design and its effect on the ability to estimate disease distribution is necessary.

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Selection of a semivariogram model in the study of spatial distribution of soil moisture

Journal of Water and Land Development ◽

10.1515/jwld-2017-0080 ◽

2017 ◽

Vol 35 (1) ◽

pp. 161-166 ◽

Cited By ~ 3

Author(s):

Radomir Obroślak ◽

Oleksandr Dorozhynskyy

Keyword(s):

Spatial Distribution ◽

Soil Moisture ◽

Gaussian Model ◽

Soil Surface ◽

Exponential Model ◽

Kriging Method ◽

Semivariogram Model ◽

The Individual ◽

Nearest Points ◽

Selection Of

AbstractThe paper presents a selection of a semivariogram model in the study of spatial variability of soil moisture in a loess agricultural catchment. Soil moisture tests were carried out in the Moszenki village, 15 km northwest of Lublin. Soil moisture measurements were performed at two dates at 104 points, located on a rectangular surface measuring 700 × 1200 m. These points were laid out in the corners of a grid of squares with sides 100 m. In addition, 6 measurements were made at a distance of less than 100 m from the nearest points. Soil moisture was measured in the soil surface (0–5 cm). ArcGis software with Geostatistical Analyst extension was used for modelling semivariograms. In both terms, five models of semivariograms were used: stable, circular, spherical, exponential and Gaussian. Kriging was used for the estimation of soil moisture values. Among the semivariogram models analyzed in this study, the largest errors in the determined values of soil moisture relative to the empirical data were observed for the exponential model, and the smallest for the Gaussian model. However, it should be emphasized that the values of the analysed errors for the individual semivariogram models were similar. Application of the ordinary kriging method for interpolation of spatial distribution of soil moisture yields good results, but it has to be kept in mind that the final shape of the spatial distribution is influenced by the choice of the semivariance function model.

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Análise espacial da mosca-negra em sistema agroflorestal de citros

Comunicata Scientiae ◽

10.14295/cs.v6i3.408 ◽

2015 ◽

Vol 6 (3) ◽

pp. 350

Author(s):

Anderson Gonçalves Silva ◽

Paulo Roberto Silva Farias ◽

Arlindo Leal Boiça Junior ◽

Bruno Gonçaves Lima ◽

Nara Helena Tavares da Ponte ◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Dependence ◽

Spherical Model ◽

Sampling Point ◽

Kriging Method ◽

Citrus Orchard ◽

Black Fly ◽

Distribution Maps ◽

Experimental Area ◽

Aleurocanthus Woglumi

The aim of this study was to characterize the spatial distribution of citrus black fly (Aleurocanthus woglumi) in citrus orchard in agroforestry plantation in Pará State, Brazil. The experimental area is located in Capitão Poço, Northeastern Pará. Twelve samples were taken monthly where the presence or absence of the pest in the experimental area were evaluated. From each sampling point (plant) we obtained the value of the variable and the coordinates (latitude and longitude). By the parameters of semivariogram models the surveys were interpolated by kriging method which provided us spatial distribution maps of the areas of higher and lower infestation of the black fly. The results showed that the spatial distribution of black fly takes place predominantly in clusters with spatial dependence described by the spherical model, forming clusters from 15.5 to 34 m (range of the model).

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Limitations of Predicting Substrate Classes on a Sedimentary Complex but Morphologically Simple Seabed

Remote Sensing ◽

10.3390/rs12203398 ◽

2020 ◽

Vol 12 (20) ◽

pp. 3398 ◽

Cited By ~ 1

Author(s):

Markus Diesing ◽

Peter J. Mitchell ◽

Eimear O’Keeffe ◽

Giacomo O. A. Montereale Gavazzi ◽

Tim Le Bas

Keyword(s):

Spatial Distribution ◽

Current Data ◽

Habitat Mapping ◽

Benthic Habitat ◽

Sediment Types ◽

Benchmark Datasets ◽

Mixed Sediments ◽

The Individual ◽

Supervised Classification Methods ◽

Map Accuracy

The ocean floor, its species and habitats are under pressure from various human activities. Marine spatial planning and nature conservation aim to address these threats but require sufficiently detailed and accurate maps of the distribution of seabed substrates and habitats. Benthic habitat mapping has markedly evolved as a discipline over the last decade, but important challenges remain. To test the adequacy of current data products and classification approaches, we carried out a comparative study based on a common dataset of multibeam echosounder bathymetry and backscatter data, supplemented with groundtruth observations. The task was to predict the spatial distribution of five substrate classes (coarse sediments, mixed sediments, mud, sand, and rock) in a highly heterogeneous area of the south-western continental shelf of the United Kingdom. Five different supervised classification methods were employed, and their accuracy estimated with a set of samples that were withheld. We found that all methods achieved overall accuracies of around 50%. Errors of commission and omission were acceptable for rocky substrates, but high for all sediment types. We predominantly attribute the low map accuracy regardless of mapping approach to inadequacies of the selected classification system, which is required to fit gradually changing substrate types into a rigid scheme, low discriminatory power of the available predictors, and high spatial complexity of the site relative to the positioning accuracy of the groundtruth equipment. Some of these issues might be alleviated by creating an ensemble map that aggregates the individual outputs into one map showing the modal substrate class and its associated confidence or by adopting a quantitative approach that models the spatial distribution of sediment fractions. We conclude that further incremental improvements to the collection, processing and analysis of remote sensing and sample data are required to improve map accuracy. To assess the progress in benthic habitat mapping we propose the creation of benchmark datasets.

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High Speed Information Network Planning using Stochastic Optimization Method

Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l'ACSI ◽

10.29173/cais741 ◽

2013 ◽

Author(s):

Ki-Sang Song ◽

Arun K. Somani

Keyword(s):

Stochastic Optimization ◽

Network Design ◽

Multimedia Information ◽

High Speed ◽

Minimum Cost ◽

Optimization Method ◽

Multimedia Communication ◽

Network Design Problem ◽

Information Network ◽

Traffic Characteristics

From the 1994 CAIS Conference: The Information Industry in Transition McGill University, Montreal, Quebec. May 25 - 27, 1994.Broadband integrated services digital network (B-ISDN) based on the asynchronous transmission mode (ATM) is becoming reality to provide high speed, multi bit rate multimedia communications. Multimedia communication network has to support voice, video and data traffics that have different traffic characteristics, delay sensitive or loss sensitive features have to be accounted for designing high speed multimedia information networks. In this paper, we formulate the network design problem by considering the multimedia communication requirements. A high speed multimedia information network design alogrithm is developed using a stochastic optimization method to find good solutions which meet the Quality of Service (QoS) requirement of each traffic class with minimum cost.

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Adolescent Trials Network for HIV-AIDS Scale It Up Program: Protocol for a Rational and Overview (Preprint)

10.2196/preprints.11204 ◽

2018 ◽

Author(s):

Sylvie Naar ◽

Jeffrey T Parsons ◽

Bonita F Stanton

Keyword(s):

Implementation Science ◽

Large Body ◽

Hiv Infections ◽

Self Management ◽

Management Interventions ◽

Hiv Research ◽

The Individual ◽

Youth Living With Hiv ◽

Living With Hiv ◽

Hiv Aids

BACKGROUND The past 30 years have witnessed such significant progress in the prevention and treatment of HIV/AIDS that an AIDS-free generation and the end to the global AIDS epidemic are ambitious, but achievable, national and global goals. Despite growing optimism, globally, youth living with HIV are markedly less likely to receive antiretroviral therapy than adults (23% vs 38%). Furthermore, marked health disparities exist regarding HIV infection risk, with young men of color who have sex with men disproportionately affected. A large body of research has identified highly impactful facilitators of and barriers to behavior change. Several efficacious interventions have been created that decrease the rate of new HIV infections among youth and reduce morbidity among youth living with HIV. However, full benefits that should be possible based on the tools and interventions currently available are yet to be realized in youth, in large part, because efficacious interventions have not been implemented in real-world settings. Scale It Up (SIU) primarily aims to assemble research teams that will ultimately bring to practice evidence-based interventions that positively impact the youth HIV prevention and care cascades, and in turn, advance the fields of implementation science and self-management science. OBJECTIVE This paper aims to describe the structure of the U19-SIU and the effectiveness-implementation hybrid trials, as well as other center-wide protocols and initiatives, implemented within SIU. METHODS SIU will achieve its aims through 4 individual primary protocols, 2 center-wide protocols, and 3 cross-project initiatives. RESULTS SIU was funded by National Institute for Child Health and Human Development (U19HD089875) and began in October 2016. As of November 2018, 6 SIU protocols have launched at least the first phase of work (ATN 144 SMART: Sequential Multiple Assignment Randomized Trial; ATN 145 YMHP: Young Men’s Health Project; ATN 146 TMI: Tailored Motivational Interviewing Intervention; ATN 153 EPIS: Exploration, Preparation, Implementation, Sustainment model; ATN 154 CM: Cascade Monitoring; ATN 156 We Test: Couples' Communication and HIV Testing). Further details can be found in the individual protocol papers. CONCLUSIONS To date, the youth HIV research portfolio has not adequately advanced the important care area of self-management. SIU protocols and initiatives address this broad issue by focusing on evaluating the effectiveness and implementation of self-management interventions. SIU is highly innovative for 5 primary reasons: (1) our research framework expands the application of “self-management”; (2) the 4 primary protocols utilize innovative hybrid designs; (3) our Analytic Core will conduct cost-effectiveness analyses of each intervention; (4) across all 4 primary protocols, our Implementation Science Core will apply implementation scales designed to assess inner and outer context factors; and (5) we shall advance understanding of the dynamics between provider and patient through analysis of recorded interactions. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/11204

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