Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO₄), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

This research involves design and simulation of GaussianFSK transmitter in UHF band using direct modulation of ΣΔ  fractional-N synthesizer with the following specifications:

Frequency range (869.9– 900.4) MHz, data rate 150kbps, channel spacing (500 kHz), Switching time 1 µs, & phase noise @10 kHz = -85dBc.

New circuit techniques have been sought to allow increased integration of radio transmitters and receivers, along with new radio architectures that take advantage of such techniques. Characteristics such as low power operation, small size, and low cost have become the dominant design criteria by which these systems are judged.

A direct modulation by ΣΔ  fractional-N synthesizer is proposed

Background: Saliva plays an important role in oral health. Several salivary proteins are involved in the antimicrobial defence mechanism and are able to eliminate or inhibit bacterial growth in the oral cavity. Secretory IgA (SIgA) is one of the principal antibodies present in saliva, could help oral immunity by preventing microbial adherence, neutralizing enzymes and toxins. The aim of this study was to investigate the relationship between salivary Streptococcus Mutans (SM) count and S IgA in stimulated whole saliva in children with primary dentition compared to those with permanent teeth in relation to some oral hygiene parameters. Material and methods: Stimulated whole saliva was collected from 50 children (25 with primary dentation and