The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

Abstract

The research Compared two methods for estimating fourparametersof the compound exponential Weibull - Poisson distribution which are the maximum likelihood method and the Downhill Simplex algorithm. Depending on two data cases, the first one assumed the original data (Non-polluting), while the second one assumeddata contamination. Simulation experimentswere conducted for different sample sizes and initial values of parameters and under different levels of contamination. Downhill Simplex algorithm was found to be the best method for in the estimation of the parameters, the probability function and the reliability function of the compound distribution in cases of natural and contaminateddata.

Reduction of noise and vibration in spur gear experimentally by using asymmetric teeth profiles with tip relief was presented. Both of classical (symmetric) and asymmetric (with and without tip relief) spur gears are used in this work. Gear test rig was constructed to achieve torsional vibration measuring, and two modified cutters are designed and manufactured to achieve tooth profile modifications. First to cut asymmetric gear tooth with pressure angles (14.5^o/25 ^o) without tip relief for loaded and unloaded tooth sides respectively, and second to cut asymmetric gear tooth with pressure angles (14.5^o/25 ^o) for loaded and unloaded tooth sides respectively with tip relief to ach

This study was conducted in fruit production lathe house of the Department Of Horticulture And Landscape Gardening, in the station (B), College Of Agricultural Engineering Sciences, University Of Baghdad, Al-Jaadria for 8 months, began from 1/3/2019 to 1/9/2019 to investigate the responses of C35 Citrus rootstock to influence of foliar spraying of zinc and irrigation with smoking-water at 2 years old saplings. the study included two factors, first factor was three concentrations of Zinc Element Z0(0 mg.l-1), Z1(50 mg.l-1) and Z2(75 mg.l-1) that sprays at leave. The second factor was watering saplings with smoke-water in three concentrations S0(0 vol.vol-1), S1(0.1 vol.vol-1) and (0.2vol.vol-1), and their interaction. The experiment was fact

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of