Permeability is an essential parameter in reservoir characterization because it is determined hydrocarbon flow patterns and volume, for this reason, the need for accurate and inexpensive methods for predicting permeability is important. Predictive models of permeability become more attractive as a result.

   A Mishrif reservoir in Iraq's southeast has been chosen, and the study is based on data from four wells that penetrate the Mishrif formation. This study discusses some methods for predicting permeability. The conventional method of developing a link between permeability and porosity is one of the strategies. The second technique uses flow units and a flow zone indicator (FZI) to predict the permeability of a rock mass u

Energy is one of the components of the national security of countries and is of particular importance to the industrialized countries, including Germany. Energy policy includes many areas and has an impact on various sectors such as the environment, climate, agriculture and others. During the past few years, Germany has witnessed many transformations, the most important of which is the energy transition towards renewable energy, and it was strengthened in the strategy that was It was developed in 2010, which aims to achieve a long-term energy transformation, and sales of the German energy technology sector have evolved from 2010 to 2020, and this issue is related on the other hand to the concept of energy security and because of its strateg

Abstract: The aim of the present work is to measure radon concentration in wood. Solid state nuclear track detectors of type CR – 39 was used as measurement device. Eight different samples of imported and local wood were collected from markets. Samples were grinded, dried in order to measure radon concentrations in it. Cylindrical diffusion tube was used as detection technique. Results show that the higher concentration was in Iraqi sample 1 which recorded (14.02 ± 0.9) Bq / m3, while the less was in Emirates Sample which recorded (5.35 ± 1.2) Bq / m3. From the present work, all wood samples were with lowest concentrations of radon gas than other building materials.

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

A cantilevered piezoelectric beam with a tip mass at its free end is a common energy harvester configuration. This paper introduces a new principle of designing such a harvester which increases the generated voltage without changing the natural frequency of the harvester: The attraction force between two permanent magnets is used to add stiffness to the system. This magnetic stiffening counters the effect of the tip mass on the natural frequency. Three setups incorporating piezoelectric bimorph cantilevers of the same type in different mechanical configurations are compared theoretically and experimentally to investigate the feasibility of this principle. Theoretical and experimental results show that magnetically stiffe

Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

The research aims to clarify the COBIT5 framework for IT governance and to develop of a criterion based on Balanced Scorecard that contributes in measuring the performance of IT governance. To achieve these goals, the researchers adopted the deductive approach in the design of balanced scorecard to measure the IT governance at the Bank of Baghdad that was chosen because it relied heavily on IT.

The research has reached a number of conclusions, the most important of which is that the performance of IT department in the Bank of Baghdad falls within the good level that requires constant monitoring, the most committed items of Balanced Scorecard by the Bank were customer, internal operation, growth and finally the financial item; IT

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt