In petroleum reservoir engineering, history matching refers to the calibration process in which a reservoir simulation model is validated through matching simulation outputs with the measurement of observed data. A traditional history matching technique is performed manually by engineering in which the most uncertain observed parameters are changed until a satisfactory match is obtained between the generated model and historical information. This study focuses on step by step and trial and error history matching of the Mishrif reservoir to constrain the appropriate simulated model. Up to 1 January 2021, Buzurgan Oilfield, which has eighty-five producers and sixteen injectors and has been under production for 45 years when it started

Evaluation of the Serum Level of Interleukin-6 in Patients Undergoing Surgical Removal of Impacted Mandibular Third Molars, Hussain A Taher*, Salwan Y Bede

In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

As the leading cause of dementia, Alzheimer's disease (AD) is among the most prevalent progressive neurodegenerative diseases globally. The primary indicators of Alzheimer's disease consist of progressive memory impairment together with intellectual decline. Dementia cases from Alzheimer's disease constitute 50-60% of the total, while projections show these numbers will increase from 55 to 151 million by 2050. The development and enhancement of innovative therapeutic agents represent an absolute necessity for treating this medical condition.In this review, we will focus on synthesizing new promising therapeutic agents by many researchers that may improve some of the drawbacks of available drugs that only gave supportive care to Alzheimer's

The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages