Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).

In this research, a sensor for chemical solutions was designed and formed using optical fiber-based on a surface Plasmon resonance technology. A single-mode optical fiber with three different diameters (25, 45 and 65) µm was used, respectively.  The second layer of the low refractive fiber was replaced by gold, which was electrically deposited at 40 µm thickness. For each of the three types of optical fiber, different saline concentrations (different index of refraction) were used to evaluate the performance of the refractive index sensor (chemical sensor) by measuring its sensitivity and resolutions. The highest values we could get for these two parameters were 240mm/RIU, and 6*10^-5 RIU respectively, when the diameter of a

Tin dioxide (SnO2) were mixed with (TiO2 and CuO) with concentration ratio (50, 60, 70, 80 and 90) wt% films deposited on single crystal Si and glass substrates at (523 K) by spray pyrolysis technique from aqueous solutions containing tin (II) dichloride Dihydrate (SnCl2, 2H2O), dehydrate copper chloride (CuCl2.2H2O) and Titanium(III) chloride (TiCl3) with molarities (0.2 M). The results of electrical properties and analysis of gas sensing properties of films are presented in this report. Hall measurement showed that films were n-type converted to p- type as titanium and copper oxide added at (50) % ratio. The D.C conductivity measurements referred that there are two mechanisms responsible about the conductivity, hence it possess two act

This work focuses on the preparation of pure nanocrystalline SnO2 and SnO2:Cu thin films on cleaned glass substrates utilizing a sol-gel spin coating and chemical bath deposition (CBD) procedures. The primary aim of this study is to investigate the possible use of these thin films in the context of gas sensor applications. The films underwent annealing in an air environment at a temperature of 500 ^◦C for duration of 60 minutes. The thickness of the film that was deposited may be estimated to be around 300 nm. The investigation included an examination of the structural, optical, electrical, and sensing characteristics, which were explored across various preparation circumstances, specifically focusing on varied

The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge