Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other languages like English. The proposed model tackles Arabic Sentiment Analysis (ASA) by using a DL approach. ASA is a challenging field where Arabic language has a rich morphological structure more than other languages. In this work, Long Short-Term Memory (LSTM) as a deep neural network has been used for training the model combined with word embedding as a first hidden layer for features extracting. The results show an accuracy of about 82% is achievable using DL method.
The importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure.
The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts.
The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling exe
... Show MoreThe importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure. The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts. The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling execution safer and more economical by reducin
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
... Show MoreResearchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
... Show MorePorosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to convert the color and grayscale images to binary images. The idea is to accommodate the blue regions entirely with pores and transform it to white in r
... Show MoreAmong many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r
... Show Moreأن الطرق اللامعلمية هي نوع من الطرق الاحصائية الاستدلالية التي يمكن استخدامها للتوصل إلى أستنتاجات لذا كان حرص المؤلف على أصدار هذا الكتاب والذي يعمل على توضيح ( لماذا ؟ ومتى ؟ وكيف ؟ ) تستخدم كل طريقة إحصائية . وبإمكان القاريء سواء أكان أستاذا ً جامعيا ً أو باحثا ً أو طالبا ً في الدراسات العليا ( الماجستير والدكتوراه ) أو طالبا ً في الدراسات الأولية أن يتتبع جميع الخطوات لحساب كل قانون إحصائي وبدءا ً من عملية إدخ
... Show MoreA Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.