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Kevin Stanley L. Kurt Kreuger Priyasree Bhowmik Narjes Shojaati Alexa Elliott 《International journal of geographical information science》2016,30(9):1853-1872
ABSTRACTIn the past decade society has entered a technological period characterized by handheld computing that supports input and processing from numerous sensors. Today’s mobile phones offer the ability to integrate input from sensors monitoring various external and internal sources (e.g., accelerometer, magnetometer, microphone, GPS, wireless Internet, and Bluetooth). Furthermore, these raw inputs can be integrated and processed in ways that can offer novel representations of human behaviour. As a result, new opportunities to examine and better understand human spatial behaviour are available; one such application is the constant monitoring of a group of people over an extended period of time. Such a research setting lends itself to natural experiments that emerge as a result of regular and on-going observations. We report here on the observation of a natural experiment that took place in the context of a month-long monitoring study of 28 participants using mobile phone-based ubiquitous sensor monitoring. The implications for public health and transportation planning are discussed. 相似文献
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Proper estimation of the spatial distribution of water-table depth is highly important in most groundwater studies. Groundwater depth is measured at specific and limited points and it is estimated for other parts using spatial estimation methods. In this study, two multivariate methods, artificial neural network (ANN) and multiple linear regression (MLR), are examined to estimate water-table depth in an unconfined aquifer located in Shibkooh, Iran. The different ancillary data, including spatial coordinates, digital elevation model (DEM), aquifer bed elevation, specific resistivity and aquifer thickness were used to improve estimates based on these methods. It was proved that performance of the ANN surpasses that of the MLR method. Using the spatial coordinates, the aquifer bed elevation and aquifer thickness resulted in the optimum spatial estimation of the water-table depth. These parameters, directly or indirectly, affect the water-table depth estimation through techniques such as ANN capable of modelling of nonlinear relationships. 相似文献
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在水体工程及河流工程项目规划与设计中,瞬时顶峰流量是需要加以了解的最重要因素之一。本研究的目的是,在估算伊朗法尔斯省西北部Kharestan流域的瞬时顶峰流量时,对人工神经网络法与传统方法的功效进行对比。为此,采用了Jamal Beig水文站25年的日顶峰流量和瞬时顶峰流量数据。在Fuller、Sangal及Fill-Steiner经验方法以及人工神经网络方法的基础上进行了估算,并根据RMSE和R2进行了对比。结果显示,采用人工神经网络法的估算值比经验方法的更为精确,RMSE =13.710,R2= 0.942。这表明人工神经网络法比经验方法的误差更低。 相似文献
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Runoff and sediment yield modeling using SWAT model: case of Wadi Hatab basin,central Tunisia 总被引:1,自引:0,他引:1
This study presents an application of the model Soil and Water Assessment Tool (SWAT) to simulate daily and monthly water flow and sediment fluxes in the Wadi Hatab watershed (2200 km2) located in central Tunisia. The study basin is characterized by a significant climatic contrast, abrupt topography, and soil fragility, resulting thereby in flash floods and important water erosion rates. This alarming situation requires urgent interventions in order to preserve water and soil resources, implying the need for a decision tool for proper integrated management of the watershed. The model was calibrated and validated based on a comparison of simulated and observed flow rates at the basin outlet (hydrometric station Khanguet Zazia), during the periods 1987–1988 and 1989–1990, respectively. The comparison was based not only on visual inspection of the agreement between observed and simulated time series, but also on statistical parameters. Indeed, for the daily time step application, the Nash—Sutcliffe efficiency (NSE) values were 0.52 and 0.61, and the coefficient of determination (R2) was 0.54 and 0.61 for calibration and validation, respectively. As for the monthly time-step application, the obtained NSE values were 0.67 and 0.89 while R2 values were 0.83 and 0.87 for calibration and validation, respectively. This clearly shows the reasonably good agreement between simulated and observed flow rates. In terms of erosion, the model gave sediment yield values ??of 1.15 and 5.37 t/ha/year during the periods of calibration and validation, respectively. 相似文献
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Lack of population genetic structure in the marine nematodes Ptycholaimellus pandispiculatus and Terschellingia longicaudata in beaches of the Persian Gulf,Iran 下载免费PDF全文
Narjes Sahraean Jelle Van Campenhout Annelien Rigaux Hadi Mosallanejad Frederik Leliaert Tom Moens 《Marine Ecology》2017,38(3)
We investigated genetic diversity and population genetic structure of two common benthic nematode species, Ptycholaimellus pandispiculatus and Terschellingia longicaudata, from sandy beaches in the area of Bandar Abbas (Iran), Persian Gulf. Based upon partial mitochondrial cytochrome oxidase c subunit 1 (COI) gene data, 17 and two haplotypes were found for P. pandispiculatus and Te. longicaudata, respectively. Analysis of molecular variance did not reveal a significant population genetic structure for either species. The absence of genetic structuring indicates substantial dispersal and gene flow in our study area. To assess the species structure of Te. longicaudata at a larger geographic scale, we compared 18S rDNA and COI sequences from Iran and the Scheldt Estuary in The Netherlands to ascertain whether they truly belong to the same species. Our data confirmed previous studies that Te. longicaudata likely constitutes a complex of multiple cryptic species, with one of these species having a (near) cosmopolitan distribution. 相似文献
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