In this work, results from an optical technique (laser speckle technique) for measuring surface roughness was done by using statistical properties of speckle pattern from the point of view of computer image texture analysis. Four calibration relationships were used to cover wide range of measurement with the same laser speckle technique. The first one is based on intensity contrast of the speckle, the second is based on analysis of speckle binary image,  the third is on size of speckle pattern spot, and the latest one is based on characterization of the energy feature of the gray level co-occurrence matrices for the speckle pattern. By these calibration relationships surface roughness of an object surface can be evaluated within the

This project sought to fabricate a flexible gas sensor based on a short functionalized multi-walled carbon nanotubes (f-MWCNTs) network for nitrogen dioxide gas detection. The network was prepared by filtration from the suspension (FFS) method and modified by coating with a layer of polypyrrole conductive polymer (PPy) prepared by the oxidative chemical polymerization to improve the properties of the network. The structural, optical, and morphological properties of the f-MWCNTs and f-MWCNTs/PPy network were studied using X-ray diffraction (XRD), Fourie-transform infrared (FTIR), with an AFM (atomic force microscopy). XRD proved that the structure of f-MWCNTs is unaffected by the synthesis procedure. The FTIR spectra verified the existence o

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 M eV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for each of the element

This study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be comp

    This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr

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.