Safe drinking water is essential for the present and future generations' health. This study aims to assess drinking water quality in Baghdad's Al-Rusafa neighborhood. Water samples were taken from 32 neighborhoods on this side. The quality of the examined potable water samples differed depending on the water source. This investigation's pH, chlorine, EC, TDS, TSS, Cd, and Pb levels were below acceptable ranges. TDS levels in Al-Mada'in are more significant than acceptable (>600ppm) water levels. Bacteria have polluted six communities (Shigella, Salmonella, Escherichia coli, and Klebsiella). Bacterial quality of drinking water and gram-negative bacteria resistant to chlorine in Baghdad's municipal water supply. Regarding pH, the w

Six house-hold Abyssinian pumps distributed in different villages of Mansoura (Mans-I, Mans-II and Mans-III) and Talkha (Talk-I, Talk-II and Talk-III) cities, Egypt, have been selected for regular seasonal water quality assessment during 2017. Water samples have been collected within the mid-periods of four seasons Standard assessment tools were employed for the integrated water quality assessment including Water Quality Index (WQI) and ISO standard algal toxicity test. WQI displayed remarkable local and seasonal variations with excellent (≥ 90) and good (70 - 89) only recorded for water samples collected from Mans-I pump located in sparsely populated area and far 50 meters only from the eastern (Damietta) branch of Nile River. WQI of

     Municipal solid waste generation, management, and dumping are economic and ecological concerns that metropolitan areas, particularly those in developing nations, must address. This study intended to ascertain the impacts of solid waste on the quality of groundwater around trash dumps located inside and surrounding landfill sites in the city of Erbil. Samples of groundwater, as well as two samples of leachate, were collected from eight wells situated near landfills during the dry and rainy seasons of August 2021 and February 2022. Several physico-chemical parameters, including pH, EC, NO₂, NO₃, alkalinity, HCO₃, Na, Ca, Mg, Cl, SAR, total hardness, and heavy metals, were evaluated in the samples.

The current study a accounts for the climate of the Diyala River Basin in Iraq where the climate is assessed depending on the most wellknown climatic classification. According to these classifications, it has been discovered that the area is located under Three climatic zones. The first zone is the semi humid or moderate, which covers the northern parts of the area. The second zone is the semi –dry climate which spreads over the middle part of the region. The third one, it extends over the southern parts and it is described as being dry .some maps were drawn to show the depth of rain fall for two successive periods. These maps indicate increase in the area of lands affected by the dry climate on account of the lands that used to lie

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

 Monthly variations in Physio-chemical parameters of Al-Garraf water in Waist province, one of the main tributaries of the Tigris River to investigate the water quality of the river from August 2014 to January 2015. The study location situated in the southeastern sector of Iraq and surrounded by wide and fertile agricultural lands. Three stations were selected for collecting  samples monthly, samples were taken each month. Station one is located at 500 m of  the AL - KUT Dam. The second is situated at distance of 15 Km away from the former (Kut- Muwafaqiya) and the latter station is located at 18 Km apart from the second one upon entering the river hand Muwafaqiya.  In the present study fourteen physical and chemical

The present study has examined the spatiotemporal varieties of the demographics of the Shatt Al-Arab River fishes and their relation to some ecological components. The aim is to forecast these groups in the unexplored parts of the waterway with an emphasis on environmental indices of diversity. Three sites in the river were selected as an observation and study of these species, which lasted from March 2019 to February 2020, the study dealt with factors affecting fishes, as Water Temperature (WT), Dissolved Oxygen (DO), Potential Hydrogen Ion (pH), Salinity (Sal), and Transparency (Tra). Gill nets, cast nets, hooks, and hand nets were adopted to collecting fish. The results indicated that the fish population comprises 60 species represent

Thirty water sample of wells, and three samples of springs from the upper most aquifer, as well as four samples from Lesser Zab River in Koi Sanjaq Basin, Erbil governorate of northern Iraq was collected and physically and chemically were analyzed. Physical analysis includes temperature, hydrogen ion concentration (pH), Electrical Conductivity (EC), Total Dissolved Solid (TDS), and Turbidity, whereas the geochemical analysis included concentration determines of the major, minor and trace elements. Chemical classification of the present samples using of chadha diagram explain that ( 95% ) of them located within field 5 and 6 whereas the rest (5%) are located in the field 8. According to Iraqi [9] and WHO [10] standers, most of the samples

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope