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

         The studying trying to determine the role of  Strategic Intelligence on the Process of Green Manufacturing  of  Sample of Mineral water factories at Dahuk city.  The study submit a theoretical frame of Strategic Intelligence and Green Manufacturing, a supposed sample, had been set to reverye   the nature of the relations and effect in the study  Varity, the study  depend on group of the main and branch concurring with the relations and effect between the Strategic Intelligence and Green Manufacturing to answer the following questions about research to problems:

 What are the relationships and effects between stra

In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of em

The most significant water supply, which is the basis of agriculture, industry and human and wildlife needs, is the river. In order to determine its suitability for drinking purposes, this study aims to measure the Water Quality Index (WQI) of the Tigris River in the Salah Al-Din Province (center of Tikrit), north of Baghdad. For ten (9) physio-chemical parameters, namely turbidity, total suspended sediments, PH, electrical conductivity, total dissolved solids, alkalinity, chloride, nitrogen as nitrate, sulphate, and then transported for examination to the laboratory, water samples were collected from 13 locations along the Tigris river. Using the weighted arithmetic index method, the WQI was measured and found to be 105,87 in up-stream, wh

Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an