In this work, porous silicon gas sensor hs been fabricated on n-type crystalline silicon (c-Si) wafers of (100) orientation denoted by n-PS using electrochemical etching (ECE) process at etching time 10 min and etching current density 40 mA/cm2. Deposition of the catalyst (Cu) is done by immersing porous silicon (PS) layer in solution consists of 3ml from (Cu) chloride with 4ml (HF) and 12ml (ethanol) and 1 ml (H2O2). The structural, morphological and gas sensing behavior of porous silicon has been studied. The formation of nanostructured silicon is confirmed by using X-ray diffraction (XRD) measurement as well as it shows the formation of an oxide silicon layer due to chemical reaction. Atomic force microscope for PS illustrates that the p

This research is about the resources and the way of al-Waqidi in his
researching of al-sira of the Prophet. And what happened in the first of Islam.
This research is about the documents which al-Waqidi had it. Some of it,
which he had visited, was the places, especially the periods which the events had took
place in. He was asking those whom were contemporary to the happenings, from the
sons of al-Sahaba and al-Tabi’een.
Also this research is lightening on the new studies that gave this historian a
good respect during his work, in which he could gave the reality about his authorship.
The research is trying to draw real way of al-Waqidi and what were reported by him,
especially the documents, and what he had s

Imagination as a Path to Reality

New speaker identification test’s feature, extracted from the differentiated form of the wave file, is presented. Differentiation operation is performed by an operator similar to the Laplacian operator. From the differentiated record’s, two parametric measures have been extracted and used as identifiers for the speaker; i.e. mean-value and number of zero-crossing points.

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.