Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

This work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C.  As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power

In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The energy aimed at examining the mode of energy drinks consumption among athletes in
Baghdad and assessing their drinks were spread greatly among the athletes and students. This
study impression toward such drinks. The study sample comprised of 102 mal athletes aged
between 19-27 years and selected randomly .The obtained results showed that football was
most practiced among the test samples at 40.54% based on twice daily .The athletes
consumed one can each day at 41.18% .As the data on energy drinks was supplied from
friends .The prefared period for drinking was before or during exercise .The athletes thought
that there products can provide energy ,vitamins ,tell ale materials ,does not affect
appetite.The most f

Is to obtain competitive advantage legitimate objective pursued by all organizations to achieve, because they live today in environments of rapid change and dynamic in order to meet the demands of the customer changing as well as intense competition between the organizations, which requires them to get the location of competitive markets in order to do this will remain to do the building and strengthening competitive advantage to be able to achieve, but that this feature is not easy and is not only through the identification and use of a successful strategy for a competitive standard and then manage it successfully. Hence the research problem of determining the sources of differentiation strategy and its impact on the dimensions of compe

The subject of this research involves studying adsorption to removal herbicide Atlantis WG from aqueous solutions by bentonite clay. The equilibrium concentration have been determined spectra photometry by using UV-Vis spectrophotometer. The experimental equilibrium sorption data were analyzed by two widely, Langmuir and Freundlish isotherm models. The Langmuir model gave a better fit than Freundlich model The adsorption amount of (Atlantis WG) increased when the temperature and pH decreased. The thermodynamic parameters like ?G, ?H, and ?S have been calculated from the effect of temperature on adsorption process, is exothermic. The kinetic of adsorption process was studied depending on Lagergren ,Morris ? Weber and Rauschenberg equati

Abstract:

                The internal control is the tool through which it is possible to verify and ensure the implementation of tasks in accordance with the established plans and programs and to evaluate the level of performance that is implemented within the different companies.

A guarantee from the supplier with the absence of a specialized technical committee that follows up the stages of implementing the contract and disbursing all amounts of financial dues to the supplier before completing the implementation of the contract and overlooking the non-implementation of some clauses of the contract by the committee in charge of

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i