The excavation damaged zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. In this paper, a methodology was examined for computing...

In the present study, the effect of banana peel and bagasse particle additives on the friction and wear behavior of multi-ingredient friction material nanocomposites have been investigated. In order to develop optimized properties of friction nanocomposite, the type and content of natural additives were changed beside the constant amount of other constituents such as alumina nanoparticle and ot...

Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...

An imperative requirement of a modern machining system is to detect tool wear while maintain the surface quality product. Vibration signatures emanating during with single point cutting have proven be good indicators for tool’s health. The current research undertaken utilizes vibration turning EN9 and EN24 steel alloy predict life using Artificial Neural Network (ANN). During initial meager exp...

In the present work, dicationic imidazolium-based ionic liquids (ILs) were investigated as multi-functional coatings on a zirconia (ZrO₂) surface to prevent biofilm formation and enhance the wear performance of zirconia while maintaining the material's compatibility with host cells. ILs containing phenylalanine and methionine were synthesized and deposited on zirconia. Intermolecular interactio...

Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear debris analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self-organizing maps. This is achieved using relationship measurements...

in this study the wavelet neural network (wnn) and artificial neural network (ann) were used to simulate barley breakage percentage in combine harvester. the models have been trained using the same data conditions. air temperature, thresher cylinder speed, distance between thresher cylinder and concave (back and forth) and the percentage of barely moisture were as the input variables. the resul...

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

abstract: this paper represents a novel use of artificial neural networks in medical science. the proposed technique involves training a multi layer perceptron (mlp) (a kind of artificial neural network) with a bp learning algorithm to recognize a pattern for the diagnosing and prediction of five blood disorders, through the results of blood tests from h1 machine. the blood test parameters and ...

The aim of this study was to determine how representative wear scars of simulator-tested polyethylene (PE) inserts compare with retrieved PE inserts from total knee replacement (TKR). By means of a nonparametric self-organizing feature map (SOFM), wear scar images of 21 postmortem- and 54 revision-retrieved components were compared with six simulator-tested components that were tested either in...