This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. Howev

Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

KE Sharquie, AF Hameed, AA Noaimi, Indian Journal of Pathology and Microbiology, 2016 - Cited by 12

Subcutaneous vascularization has become a new solution for identification management over the past few years. Systems based on dorsal hand veins are particularly promising for high-security settings. The dorsal hand vein recognition system comprises the following steps: acquiring images from the database and preprocessing them, locating the region of interest, and extracting and recognizing information from the dorsal hand vein pattern. This paper reviewed several techniques for obtaining the dorsal hand vein area and identifying a person. Therefore, this study just provides a comprehensive review of existing previous theories. This model aims to offer the improvement in the accuracy rate of the system that was shown in previous studies and

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D