The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

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

339 individuals , were sorted from 22 samples collected from three sites in Tigris River including , Al- Sarafiya district (S1), Al- Jaderiyah district (S2) and Al-Za'afaraniya district (S3), in addition to one site in the irrigation canal of the Al- Jaderiyah campus of the University of Baghdad (S4) , and in Al- Jeish canal(S5) east Baghdad. The sorting results revealed that the highest number of individuals of 102 was recorded at S4, whereas the lowest number of 24 individuals was recorded at S2. Regarding the sites, site S4 was the richest site with 30% of the total number represented 16 species, while each of S3 and S5 had 8 species only with 17.11% and 28.60% of the total individuals number respectively. The values of Jaccared Sim

In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

Objectives: The research aims to demonstrate the integration between Quantum Computing (QC) and Predictive Analysis (PA) and their role in reducing costs while achieving Sustainable Development Goals (SDGs). The study addresses the inefficiencies in calculating and measuring product costs under traditional systems and examines how QC and PA can enhance cost reduction and product quality to better meet customer needs. Additionally, the research seeks to strengthen the theoretical framework with practical applications, illustrating how this integration improves a company’s competitive position while promoting social, environmental, and economic sustainability.   Methods: The study employs a descriptive analytical approach, focusi