Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Background Parkinson’s disease (PD) is currently the fastest-growing neurological disorder in the world. Patients with PD face numerous challenges in managing their chronic condition, particularly in countries with scarce healthcare infrastructure. Objective This qualitative study aimed to delve into neurologists’ perspectives on challenges and gaps in the Iraqi healthcare system that influence the management of PD, as well as strategies to mitigate these obstacles. Method Semi-structured interviews were conducted with neurologists from five different Iraqi provinces, working in both hospitals and private neurology clinics, between November 2024 and January 2025. A thematic analysis approach was employed to identify the main challenge

The aim of the research is to identify the international accounting standards and accounting standards for Islamic banks, and to analyze the most important problems in the application of Islamic accounting standards, as well as to analyze some of the principles and methods used in the application of accounting standards in Islamic banks. The research was built on three hypotheses, the first being (there is a tangible impact on the application of international accounting standards for banks’ management of liquidity, achieving profits, maintaining property rights and fulfilling their obligations), and the second (the bank facing obstacles using Islamic accounting standards, as it is expected that when using Islamic accounting standar

Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA