Determination the Curve Number Catchment by Using GIS and Remote Sensing

In recent years, geographic information systems (GIS) and remote sensing using has increased to estimate runoff catchment. In this research, runoff curve number maps for captive catchment of Tehran by helping GIS and also remote sensing which based on factors such as vegetation, lands using, group of soil hydrology and hydrological conditions were obtained. Runoff curve numbers map was obtained by combining these maps in ARC GIS and SCS table. To evaluate the accuracy of the results, the maximum flow rate of flood which was obtained from curve numbers, was compared with the measured maximum flood rate at the watershed outlet and correctness of curve numbers were approved

Determination the Curve Number Catchment by Using GIS and Remote Sensing

In recent years, geographic information systems (GIS) and remote sensing using has increased to estimate runoff catchment. In this research, runoff curve number maps for captive catchment of Tehran by helping GIS and also remote sensing which based on factors such as vegetation, lands using, group of soil hydrology and hydrological conditions were obtained. Runoff curve numbers map was obtained by combining these maps in ARC GIS and SCS table. To evaluate the accuracy of the results, the maximum flow rate of flood which was obtained from curve numbers, was compared with the measured maximum flood rate at the watershed outlet and correctness of curve numbers were approved

Determination the Curve Number Catchment by Using GIS and Remote Sensing

In recent years, geographic information systems (GIS) and remote sensing using has increased to estimate runoff catchment. In this research, runoff curve number maps for captive catchment of Tehran by helping GIS and also remote sensing which based on factors such as vegetation, lands using, group of soil hydrology and hydrological conditions were obtained. Runoff curve numbers map was obtained by combining these maps in ARC GIS and SCS table. To evaluate the accuracy of the results, the maximum flow rate of flood which was obtained from curve numbers, was compared with the measured maximum flood rate at the watershed outlet and correctness of curve numbers were approved

SyMPox: An Automated Monkeypox Detection System Based on Symptoms Using XGBoost

Monkeypox is a zoonotic disease. About 87000 cases of monkeypox were confirmed by the World Health Organization until 10th June 2023. The most prevalent methods for identifying this disease are image-based recognition techniques. Still, they are not too fast and could only be available to a few individuals. This study presents an independent application named SyMPox, developed to diagnose Monkeypox cases based on symptoms. SyMPox utilizes the robust XGBoost algorithm to analyze symptom patterns and provide accurate assessments. Developed using the Gradio framework, SyMPox offers a user-friendly platform for individuals to assess their symptoms and obtain reliable Monkeypox diagnoses

Estimation of coliform contamination rate and impact of environmental factor on bacterial quality of tube well water supplies in Khorramdarreh County, Iran

In this study, the presence of fecal coliforms in tube wells of Khorramdarreh County, Iran, and impact of environmental factors on quantity and quality of these organisms were evaluated. In a cross-sectional survey, 76 tube well water samples from March to September 2010 were tested to determine presence of fecal coliforms, by measuring the most probable number (MPN), and identification of three enteric bacteria namely, Escherichia coli, Klebsiella sp. and Salmonella sp. Out of 76 wells, 24 (31.57%) and 25 (32.89%) wells showed presence of fecal coliforms, during rainy and dry seasons, respectively. In contrast to seasonal changes, depth of the wells showed significant correlation with type of isolated bacterial indices (P = 0.0005). On the other hand, depth of the well and seasonal variations did not show any significant correlation with fecal coliform contamination rate. The level of bacterial contamination of tube wells, in terms of presence of fecal coliforms is alarming. This was only an indicative study, and therefore, appropriate studies are required to determine the extent, risk factors and nature of the problem.Keywords: Fecal coliforms, tube well, E.coli, Klebsiella sp., Salmonella sp

A Scheduling Algorithm to Maximize Storm Throughput in Heterogeneous Cluster

In the most popular distributed stream processing frameworks (DSPFs), programs are modeled as a directed acyclic graph. This model allows a DSPF to benefit from the parallelism power of distributed clusters. However, choosing the proper number of vertices for each operator and finding an appropriate mapping between these vertices and processing resources have a determinative effect on overall throughput and resource utilization; while the simplicity of current DSPFs' schedulers leads these frameworks to perform poorly on large-scale clusters. In this paper, we present the design and implementation of a heterogeneity-aware scheduling algorithm that finds the proper number of the vertices of an application graph and maps them to the most suitable cluster node. We start to scale up the application graph over a given cluster gradually, by increasing the topology input rate and taking new instances from bottlenecked vertices. Our experimental results on Storm Micro-Benchmark show that 1) the prediction model estimate CPU utilization with 92% accuracy. 2) Compared to default scheduler of Storm, our scheduler provides 7% to 44% throughput enhancement. 3) The proposed method can find the solution within 4% (worst case) of the optimal scheduler which obtains the best scheduling scenario using an exhaustive search on problem design space