Kinneret watershed analysis tool: a cell-based decision tree model for watershed flowand pollutants predictions

2006 ◽  
Vol 53 (10) ◽  
pp. 29-35 ◽  
Author(s):  
A. Preis ◽  
A. Tubaltzev ◽  
A. Ostfeld
Keyword(s):  
Genetic Algorithm ◽  
Lake Kinneret ◽  
Analysis Tool ◽  
Rainfall Time Series ◽  
Tree Model ◽  
Watershed Analysis ◽  
Average Rainfall ◽  
A Cell ◽  
Surface Water Resource ◽  
Series Intensity

This paper presents the methodology and application underlying the Kinneret Watershed Analysis Tool (KWAT), developed for flow and contaminant predictions for Lake Kinneret (the Sea of Galilee) watershed located in northern Israel. Lake Kinneret watershed is about 2,730 km2 (2,070 in Israel, the rest in Lebanon), inhabited by about 200,000 people organized in 25 municipalities, and three cities (the Israeli part). The model aims to predict flow and contaminant transports within the watershed, down to its outlet – Lake Kinneret, the most important surface water resource in Israel. The model is comprised of two sections: quantity and quality. The objective of the quantity section is to tune the values of a vector of coefficients α that multiply the average rainfall time series intensity I(t) (the input) imposed on given sub-sets (i.e., cells) of the basin so as to calibrate their outlet flows Q(t); the quality section then uses these optimal flows Q(t) and the effective optimal rainfall intensities to adjust the values of a vector of coefficients β so as to calibrate the sub-watersheds outlet concentrations C(t). The model uses decision trees coupled with a genetic algorithm for optimally tuning the KWAT coefficients for each of the watershed cells, which taken together comprise the flow and contamination amounts measured at the watershed outlet.

Structural Optimization of Composite Panel with Lamination Parameters and Equivalent Stiffness Laminate Method

2014 ◽  
Vol 496-500 ◽  
pp. 429-435
Author(s):  
Xiao Ping Zhong ◽  
Peng Jin
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Composite Structure ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Composite Panel ◽  
Analysis Tool ◽  
Equivalent Stiffness ◽  
Lamination Parameters ◽  
Design Variables

Firstly, a two-level optimization procedure for composite structure is investigated with lamination parameters as design variables and MSC.Nastran as analysis tool. The details using lamination parameters as MSC.Nastran input parameters are presented. Secondly, with a proper equivalent stiffness laminate built to substitute for the lamination parameters, a two-level optimization method based on the equivalent stiffness laminate is proposed. Compared with the lamination parameters-based method, the layer thicknesses of the equivalent stiffness laminate are adopted as continuous design variables at the first level. The corresponding lamination parameters are calculated from the optimal layer thicknesses. At the second level, genetic algorithm (GA) is applied to identify an optimal laminate configuration to target the lamination parameters obtained. The numerical example shows that the proposed method without considering constraints of lamination parameters can obtain better optimal results.

scholarly journals A rapid and affordable point of care test for antibodies against SARS-CoV-2 based on hemagglutination and artificial intelligence interpretation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vanessa Redecke ◽  
Kazuki Tawaratsumida ◽  
Erin T. Larragoite ◽  
Elizabeth S. C. P. Williams ◽  
Vicente Planelles ◽  
...  
Keyword(s):  
Test Performance ◽  
Learning Algorithm ◽  
Point Of Care ◽  
Method Comparison ◽  
High Specificity ◽  
Turnaround Time ◽  
Analysis Tool ◽  
Point Of Care Test ◽  
Specificity And Sensitivity ◽  
A Cell

AbstractDiagnostic tests that detect antibodies (AB) against SARS-CoV-2 for evaluation of seroprevalence and guidance of health care measures are important tools for managing the COVID-19 pandemic. Current tests have certain limitations with regard to turnaround time, costs and availability, particularly in point-of-care (POC) settings. We established a hemagglutination-based AB test that is based on bi-specific proteins which contain a dromedary-derived antibody (nanobody) binding red blood cells (RBD) and a SARS-CoV-2-derived antigen, such as the receptor-binding domain of the Spike protein (Spike-RBD). While the nanobody mediates swift binding to RBC, the antigen moiety directs instantaneous, visually apparent hemagglutination in the presence of SARS-CoV-2-specific AB generated in COVID-19 patients or vaccinated individuals. Method comparison studies with assays cleared by emergency use authorization demonstrate high specificity and sensitivity. To further increase objectivity of test interpretation, we developed an image analysis tool based on digital image acquisition (via a cell phone) and a machine learning algorithm based on defined sample-training and -validation datasets. Preliminary data, including a small clinical study, provides proof of principle for test performance in a POC setting. Together, the data support the interpretation that this AB test format, which we refer to as ‘NanoSpot.ai’, is suitable for POC testing, can be manufactured at very low costs and, based on its generic mode of action, can likely be adapted to a variety of other pathogens.

scholarly journals The Use of Fractal Features from the Periphery of Cell Nuclei as a Classification Tool

1999 ◽  
Vol 19 (1) ◽  
pp. 21-37 ◽  
Author(s):  
Birgitte Nielsen ◽  
Fritz Albregtsen ◽  
Håvard E. Danielsen
Keyword(s):  
Normal Liver ◽  
Analysis Tool ◽  
Cell Nuclei ◽  
Bhattacharyya Distance ◽  
Prior Probabilities ◽  
Hepatocellular Carcinomas ◽  
Transmission Electron ◽  
Mouse Liver Cell ◽  
A Cell ◽  
Classification Tool

A polygonization‐based method is used to estimate the fractal dimension and several new scalar lacunarity features from digitized transmission electron micrographs (TEM) of mouse liver cell nuclei. The fractal features have been estimated in different segments of 1D curves obtained by scanning the 2D cell nuclei in a spiral‐like fashion called “peel‐off scanning”. This is a venue to separate estimates of fractal features in the center and periphery of a cell nucleus. Our aim was to see if a small set of fractal features could discriminate between samples from normal liver, hyperplastic nodules and hepatocellular carcinomas. The Bhattacharyya distance was used to evaluate the features. Bayesian classification with pooled covariance matrix and equal prior probabilities was used as the rule for classification. Several single fractal features estimated from the periphery of the cell nuclei discriminated samples from the hyperplastic nodules and hepatocellular carcinomas from normal ones. The outer 25–30% of the cell nuclei contained important texture information about the differences between the classes. The polygonization‐based method was also used as an analysis tool to relate the differences between the classes to differences in the chromatin structure.

scholarly journals Reliable Shape Optimization of Structures Subjected to Transient Dynamic Loading Using Genetic Algorithms

2005 ◽  
Vol 12 (6) ◽  
pp. 407-424 ◽  
Author(s):  
Sabyasachi Chand ◽  
Anjan Dutta
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Genetic Algorithms ◽  
Shape Optimization ◽  
Analysis Tool ◽  
Time Step ◽  
Transient Dynamic ◽  
Boundary Definition ◽  
Automatic Mesh ◽  
Shape Changes

This paper presents a reliable method of solution of two dimensional shape optimization problems subjected to transient dynamic loads using Genetic Algorithms. Boundary curves undergoing shape changes have been represented by B-splines. Automatic mesh generation and adaptive finite element analysis modules are integrated with Genetic algorithm code to carry out the shape optimization. Both space and time discretization errors are evaluated and appropriate finite element mesh and time step values as obtained iteratively are adopted for accurate dynamic response. Two demonstration problems have been solved, which show convergence to the optimal solution with number of generations. The boundary curve undergoing shape optimization shows smooth shape changes. The combinations of automatic mesh generator with proper boundary definition capabilities, analysis tool with error estimation and Genetic algorithm as optimization engine have been observed to behave as a satisfactory shape optimization environment to deal with real engineering problems.

Genetic algorithm approach for solving a cell formation problem in cellular manufacturing

2009 ◽  
Vol 36 (3) ◽  
pp. 6598-6604 ◽  
Author(s):  
Iraj Mahdavi ◽  
Mohammad Mahdi Paydar ◽  
Maghsud Solimanpur ◽  
Armaghan Heidarzade
Keyword(s):  
Genetic Algorithm ◽  
Cellular Manufacturing ◽  
Cell Formation ◽  
Cell Formation Problem ◽  
Formation Problem ◽  
A Cell ◽  
Genetic Algorithm Approach

Objective Optimization of Weather Radar Networks for Low-Level Coverage Using a Genetic Algorithm

2012 ◽  
Vol 29 (6) ◽  
pp. 807-821 ◽  
Author(s):  
James M. Kurdzo ◽  
Robert D. Palmer
Keyword(s):  
Genetic Algorithm ◽  
Lifetime Cost ◽  
Optimization Technique ◽  
Weather Radar ◽  
The United States ◽  
Analysis Tool ◽  
Low Level ◽  
Mountainous Regions ◽  
Radar Network ◽  
Radar Networks

Abstract The current Weather Surveillance Radar-1988 Doppler (WSR-88D) radar network is approaching 20 years of age, leading researchers to begin exploring new opportunities for a next-generation network in the United States. With a vast list of requirements for a new weather radar network, research has provided various approaches to the design and fabrication of such a network. Additionally, new weather radar networks in other countries, as well as networks on smaller scales, must balance a large number of variables in order to operate in the most effective way possible. To offer network designers an objective analysis tool for such decisions, a coverage optimization technique, utilizing a genetic algorithm with a focus on low-level coverage, is presented. Optimization is achieved using a variety of variables and methods, including the use of climatology, population density, and attenuation due to average precipitation conditions. A method to account for terrain blockage in mountainous regions is also presented. Various combinations of multifrequency radar networks are explored, and results are presented in the form of a coverage-based cost–benefit analysis, with considerations for total network lifetime cost.

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