A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on

The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an

In this research constructed N2 laser system by use developed method of electric discharge. In this method used four step of electric discharge by using four capacitors, three spark gaps, high tension power supply varying in range from 12kV to 24 kV and three resistors, this method called three stage blumlein circuit. The breakdown time delay of these parallel spark gaps cement strong ultraviolet preionization in the laser channel, thus the result of these amendments the laser output is many doubled and is more increasing than that obtained using the one and two stage blumlein circuits. This system has been designed and operated to give pulse laser with wavelength at 337.1 nm. This laser system can operate without mirrors and optical res

This study involves the investigation of the effect of nitrogen laser with 337.1 nm wavelength on the sensitivity of Staphylococcus aureus bacteria by using local therapeutic due to burns. Thirty six isolate of Staphylococcus aureus bacteria were isolated from 25 patients suffering from sever burns, each isolate of bacteria was irradiated with nitrogen laser at (5, 10, 15 and 30) pulses/second repetition rates for 1, 5, 10, 20 and 30 minutes for each repetition rate. The effects of nitrogen laser on the local therapeutics sensitivity of bacteria were obtained using Kirby Baur method. Changes in the sensitivity of bacteria to local therapeutics (Tetracyclin, Chloramphenicol, Flumizin and Fucidin) occur at high repetition rate(30 pulses/seco

Background: The excessive use and abuse of antibiotics contribute to bacterial resistance, raising the risk of complications and treatment failures. This study investigates adherence to antibiotic prescriptions among Iraqi dental patients, highlighting implications for antimicrobial resistance.Objective: To assess adherence levels and identify factors influencing antibiotic therapy compliance among dental patients.Methods: A cross-sectional survey was conducted in which adult dental patients aged 18 and older, who had been prescribed antibiotics within the past year, participated. The modified Morisky Medication Adherence Scale-8 items was used to evaluate adherence, and data were analyzed with IBM SPSS Statistics software V26.Results: Amon

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete