Optimization of well placement plays a considerable role in the production and maximizing the net present value of the investment of oil field developments. However, the application of the optimization techniques in well placement developments is so complicated because many decision variables, objective functions, and constraints are involved in the well placement optimization case. Furthermore, many computational techniques; conventional and non-conventional, have been utilized to optimize well placement operations. This study displays the advancement of the optimization methods applied in the well placement. Subsequently, the study assorted the applied optimization methods, and it demonstrates the restriction and the range of implementati

The demand for electronic -passport photo ( frontal facial) images has grown rapidly. It now extends to Electronic Government (E-Gov) applications such as social benefits driver's license, e-passport, and e-visa . With the COVID 19 (coronavirus disease ), facial (formal) images are becoming more widely used and spreading quickly, and are being used to verify an individual's identity, but unfortunately that comes with insignificant details of constant background which leads to huge byte consumption that affects storage space and transmission, where the optimal solution that aims to curtail data size using compression techniques that based on exploiting image redundancy(s) efficiently.

Image Fusion is being used to gather important data from such an input image array and to place it in a single output picture to make it much more meaningful & usable than either of the input images. Image fusion boosts the quality and application of data. The accuracy of the image that has fused depending on the application. It is widely used in smart robotics, audio camera fusion, photonics, system control and output, construction and inspection of electronic circuits, complex computer, software diagnostics, also smart line assembling robots. In this paper provides a literature review of different image fusion techniques in the spatial domain and frequency domain, such as averaging, min-max, block substitution, Intensity-Hue-Saturation(IH

This research is divided into a process of classifying and filtering most of the studies that dealt with sustainable professional development and dividing them into several sections to determine the categories for which sustainable professional development is measured, which categories did not address it, the extent to which the samples deal with and their number of the target variable, as well as the variables that suit sustainable professional development and the variables that did not Study it yet. And also the quality of studies in terms of the methodology used so that there is a reference for every researcher who intends to study sustainable professional development with studies, their characteristics, categories, tools and methodology

This article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss

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Hydatid cystic or cystic echinococcosis disease remains a major challenge due to its medical and veterinary importance and its widespread spread all over the world as well as the economic losses caused by this disease, whether for humans or farm animals. Echinococcus granulosus is the causative agent for this disease, targeting the liver and lungs primarily and in varying proportions of the rest of the body. This disease is characterized by the non-appearance of pathological symptoms for long periods as its appearance depends on the size, number and site of the cysts formed and the type of organ infected and surgery is still the most effective solution for the disposal of hydatid cysts. Dogs and the rest of Canidae family represent the fina

Optimization of gas lift plays a substantial role in production and maximizing the net present value of the investment of oil field projects. However, the application of the optimization techniques in gas lift project is so complex because many decision variables, objective functions and constraints are involved in the gas lift optimization problem. In addition, many computational ways; traditional and modern, have been employed to optimize gas lift processes. This research aims to present the developing of the optimization techniques applied in the gas lift. Accordingly, the research classifies the applied optimization techniques, and it presents the limitations and the range of applications of each one to get an acceptable level of accura

Objectives: Although the Frankfort Horizontal (FH) and sella-nasion were routinely used as craniofacial reference planes, the inter-individual orientations were changeable when related to true horizontal (HOR). Natural head position (NHP) is a reproducible, standardized position, with the head in an upright posture and eyes focused on a point in the distance at eye level so that the visual axis is horizontal. The natural head position has importance in anthropological as well as in orthodontic fields, as this position has a relatively fixed relationship to the true horizontal and vertical planes. However, NHP is clinically not simple and it takes long time to be recorded, in addition to a deficiency in the tools utilized in the NHP and l

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p