This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

     In this study,  has been discussed the issue of non-interest income and its impact on the Iraqi banking sector profit for the period between (2008-2017) as it was the main objective of the study is to find the relationship between the non-interest income and the profits of the banking sector in order to know  the size of the sector's dependence on non-interest income As well as an analysis of its profitability compared to selected countries, And to test hypotheses, the financial ratios and some statistical tests to determine the stability of the time series such as the test (Correlegram , Dickey -Fuller (depending on the statistical program (E-Views V8) and a simple linear regression method by (Minitab

Abstract:

               The aim of the research is to evaluate the practice of banking departments for strategic foresight represented by its dimensions (environmental scanning, future vision, scenarios, reconfiguration) and its relationship to the organizational brilliance represented by dimensions (brilliance of leadership, brilliance of service and innovation, brilliance of knowledge, brilliance of employees), as the research was applied in A number of private Iraqi commercial banks represented by (Baghdad, Iraqi Investment, Iraqi Middle East Investment, Commercial Gulf, Ashur International Investment, Al Mansour Investment, Via Iraq Invest

This study examined the adsorption behavior of anionic dye (orange G) from aqueous solution onto the raw and activated a mixture of illite, kaolinite and chlorite clays from area of Zorbatiya (east of Iraq).The chemical treatment involved alkali and acid activation. The alkali activation obtained by treated the raw clay (RC) with 5M NaOH (ACSO) and the acid activation founded by treated it with 0.25M HCl (ACH) and 0.25M  (ACS). The thermal treatment carried out by calcination the produce activated clay at 750^oC for acid activation and 105^oC for alkali activation. Batch

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

      This research investigates the type and the significant relationship between roaming management and self-efficacy and its impact on excellence in providing hotel service. To achieve this, the applied approach was adopted through  A questionnaire was designed and developed for the collected data. It has consisted of three parts. The firsts section included nine questions to measure the dimensions of management by roaming. The second section includes nine questions to measure the effectiveness of the two employees. The last section includes   12   questions to measure the excellence of the hotel service. The research sample included  43  employees' responding to this

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

        This research shows Ibn Battuta's approach in his book Ibn Battuta's Journey that is called "Tuhfet Al-Anzar fi Ghera'ib Al-Amsar wa Eaja'ib-Al-Asfar", which explore the urban aspects of shops, markets, palaces, houses, mosques, monasteries and other antiquities within its pages, whether in terms of the site or in terms of studying it and the plans that explained the basis for the art and architecture of these cities, the intellectual dimensions in their civilizational history are clarified

Each of the languages ​​possesses a set of phenomena that researchers in its sciences should stop at to explain the secrets of this language, including the phenomenon of idiomatic expression. Perhaps this phenomenon may constitute an obstacle to non-native speakers of the language or even the native speakers themselves. The Arabic language is full of these expressions, Which needs us to dedicate its own studies to it so that we can collect it in a dictionary that includes and collects it with explanation and interpretation of its semantics