over the last decade or so, artificial neural networks (anns) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. however, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. for this reason, this study aims at de...

background: heavy metals in aquatic systems usually interfere with many beneficial uses of water. divalent nickel is a commonly occurring toxic metal in natural ecosystems due to the effluent of refineries, electroplating, and casting industries. in aquatic environments, nickel appears as ni (ii) and ni0. despite the high reported toxicity for ni (ii), ni0 is only slightly toxic. various method...

Short cycle time prediction is a well-documented problem in complex-process manufacturing such as semiconductor manufacturing. In general, the amount of production in wafer fabrication is dependent on bottleneck facilities. In this paper, we compare scheduling methods to increase the production of the wafer fabrication. We model the process based on DEVS (Discrete Event System)/SES (System Enti...

The objective of this paper is to present a modeling procedure, based on the use of statistical methods, to develop predictive models for Information Technology (IT) capacity planning. The goal of these models is to be able to predict IT variables’ behaviour, using initial inputs provided by high-level business explanatory variables. The modelling process consists in two main sequences, explora...

While the area of process automation in semiconductor manufacturing has many issues in common with process automation and enactment in business processes, the nature of the semiconductor manufacturing process introduces a number of challenging new issues. Among these issues is the need to not only automate the process but also to continuously control and optimize it. Furthermore the semantics o...

Nanoparticles classified in 4 overall groups containing: Metallic nanoparticles, ceramic nanoparticles, polymeric nanoparticles and semiconductor nanoparticles. These nanoparticles are used in some biomedical applications such as carrying medicine and photographing agents. With attention to different criteria which are both qualitative and quantitative, selecting the most suitable nanoparticles...

A UHV atomic hydrogen-cracking cell has been constructed to produce atomic hydrogen in order to perform in-situ cleaning of semiconductor samples. The cell was calibrated and tested with the objective of cleaning the III-V semiconductor samples such as GaAs. Mass spectroscopy studies during the atomic hydrogen cleaning of the GaAs samples revealed the chemical process of the hydrogen cleaning. ...

Nanoparticles classified in 4 overall groups containing: Metallic nanoparticles, ceramic nanoparticles, polymeric nanoparticles and semiconductor nanoparticles. These nanoparticles are used in some biomedical applications such as carrying medicine and photographing agents. With attention to different criteria which are both qualitative and quantitative, selecting the most suitable nanoparticles...

_ This paper presents some of the techniques used to introduce simulation of semiconductor fabrication processes to undergraduate electrical engineering students at the American University of Sharjah. Students use Silvaco Athena process simulator and Atlas device simulator to perform experiments on semiconductor fabrication processes. Simulation results are compared with the theoretically expec...

The performance of the manufacturing process in each of these areas determines the overall manufacturability of the process. As device geometries are reduced, understanding and minimizing the sources of process-induced defects is critical to achieving and maintaining high device yields. This paper presents comprehensive the investigating a novel metrology on semiconductor process module integra...