The work presented in this paper is a case study of the southeastern Iraqi Fauqi Oil Field to evaluate both the petrophysical properties and lithology of the Jeribe–Euphrates Formations. Reservoir characterization was performed using well log data, including Gamma Ray (GR), Density (RHOB), Neutron (NPHI), Sonic (DT), Spontaneous Potential (SP), and resistivity logs. Data processing, correction, and interpretation were conducted using Interactive Petrophysics (IP) software. The Gamma Ray method was used to estimate shale volume (Vsh), while porosity was calculated using various methods, with the neutron–density combination providing reliable results. To determine water saturation (Sw), the Archie equation was applied using common

The problem of rapid population growth is one of the main problems effecting countries of the world the reason for this the growth in different environment areas of life commercial, industrial, social, food and educational. Therefore, this study was conducted on the amount of potable water consumed using two models of the two satellite and aerial images of the Kadhimiya District-block 427 and Al-Shu^,laa district-block 450 in Baghdad city for available years in the Secretariat of Baghdad (2005, 2011,2013,2015). Through the characteristics of geographic information systems, which revealed the spatial patterns of urban creep by determining the role and buildings to be created, which appear in the picture for the

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

Buckling and free vibration analysis of laminated rectangular plates with uniform and non uniform distributed in-plane compressive loadings along two opposite edges is performed using the Ritz method. Classical laminated plate theory is adopted. The static component of the applied in- plane loading are assumed to vary according to uniform, parabolic or linear distributions. Initially, the plate membrane problem is solved using the Ritz method; subsequently, using Hamilton’s variational principle, linear homogeneous algebraic equations in terms of unknown are generated, the set of linear algebraic equations can be solved as an Eigen-value problem. Buckling loads for laminated plates with different combinations of bounda

This paper shows the characteristics of temperature and adsorbed (water vapor) mass rate distribution in the adsorber unit which is the key part to any adsorption refrigeration system. The temperature profiles of adsorption/desorption phases (Dynamic Sorption) are measured experimentally under the operating conditions of 90oC hot water temperature, 30oC cooling water temperature, 35oC adsorption temperature and cycle time of 40 min. Based on the temperature profiles, The mass transfer equations for the annulus adsorbent bed are solved to obtain the distribution of adsorption velocity and adsorbate concentration using non-equilibrium
model. The relation between the adsorption velocity with time is investigated during the process of ads

Over the last few years, the interior designer has been given the ability to access many innovative tools for new forms of unprecedented diversity and efficiency. Some design experts have described the new parametric procedures they are introducing to create new interior projects as a radical transformation that carries all the elements of a qualitative shift in interior design. The best of these parametric procedures is the technical capabilities offered by us to create new forms that are different from what has been discussed in everything that has been produced by designers and architects since modernity and even before it to the present time, which returns our design products through a series of computer programs that perform the pro

Objectives: To assess the feasibility and accuracy of a new prototype robotic implant system for the placement of zygomatic implants in edentulous maxillary models. Methods: The study was carried out on eight plastic models. Cone beam computed tomographs were captured for each model to plan the positions of zygomatic implants. The hand-eye calibration technique was used to register the dynamic navigation system to the robotic spaces. A total of 16 zygomatic implants were placed, equally distributed between the anterior and the posterior parts of the zygoma. The placement of the implants (ZYGAN®, Southern Implants) was carried out using an active six-jointed robotic arm (UR3e, Universal Robots) guided by the dynamic navigation coordinate tr

Objectives: To quantify the reproducibility of the drill calibration process in dynamic navigation guided placement of dental implants and to identify the human factors that could affect the precision of this process in order to improve the overall implant placement accuracy. Methods: A set of six drills and four implants were calibrated by three operators following the standard calibration process of NaviDent® (ClaroNav Inc.). The reproducibility of the position of each tip of a drill or implant was calculated in relation to the pre-planned implants’ entry and apex positions. Intra- and inter-operator reliabilities were reported. The effects of the drill length and shape on the reproducibility of the calibration process were also invest

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an