![Convex Converts Xrd Data Files Convex Converts Xrd Data Files](http://pd.chem.ucl.ac.uk/pxrd/qa/PDF2-1996s.gif)
The methods of collection, identification, and analysis of biological communities were followed.
![Convex Converts Xrd Data Files Convex Converts Xrd Data Files](https://myscope.training/myscope/images/xrd/eva_01.jpg)
It was proposed to evaluate hydrobiological information (phytoplankton, zooplankton, periphyton, benthic macroinvertebrates, and nekton) in two sampling points in the Lurín River at the height of the Antioquia district, Huarochirí Province, Lima. Keywords: Sustainable construction material, RGPC beams, aggregate replacement, water curing methods, black marble waste aggregate.
#CONVEX CONVERTS XRD DATA FILES CRACK#
The results of this study are analysed and accordingly the behaviour of RGPC beams was investiaged.Experimental results include the load capacity viz., 1st breaking load, final load, and load deformation behaviour, moment to curve behaviour, crack width, crack distance and failure pattern.Overall, this investigation proves that, water curing offers better performance than ambient room temperature. We also considered that, varying concentrations of NaOH. In the produced RGPC beams, the Natural Coarse Aggregate (NCA) is replaced with Black Marble Waste Aggregate (BMWA) and the study was conducted on the beams that has varying percetanges of BMWA typically 0%, 50%, and 100%. For testing pupouse we produced 54 RGPC beams with a size of 150 x 150 with effective span of 750mm. In this study, we considered two curing methods and analysed the flexural behaviour of produced RGPC beams. Hence, we conducted a research study upon developing one such material. In general, these materials have reduced environmental footprint across its lifecycle. Keywords: Predictive Analytics, Fraudulent Claim, Complaint Identification and Visualisation, Decision Tree, Neural Network |Ī key emphasis on environmental sustainability in the global housing and construction industry has given the scope for the production of sustainable construction approchaesand novel construction materials. Artificial Neural Network (ANN) was used in order to foresee the possible failure time of a trained component to predict fraudulent warranty claims and improve customer satisfaction. The aim of this research article is to propose a machine learning-based decision support system, building a data warehouse to data processing, exploration, visualization, identifying complaint patterns and providing survival analytics for the frequent failure components.Decision trees were used to determine the probable time to failure of a chosen component. The major issue facing by the manufacturing industries are travelling between production and latest perception of information technology to make automate with sustainable manufacturing. In current global scenario, new techniques are essential to look into increasingly complex volumes of automobile service data, anticipate product failures, visualize and report product failures and also recommend possible ways to resolve them with sustainable manufacturing system.