Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discriminate the polarity of sentiments. This paper proposes a hybrid method of linguistic and statistical features along with classification methods for Arabic sentiment analysis. Linguistic features contains stemming and POS tagging, while statistical contains the TF-IDF. A benchmark dataset of Arabic tweets have been used in the experiments. In addition, three classifiers have been utilized including SVM, KNN and ME. Results showed that SVM has outperformed the other classifiers by obtaining an f-score of 72.15%. This indicates the usefulness of using SVM with the proposed hybrid features.
My study here is about the (possible for itself) features especially in the (Alashaira) opinion, also I touch to the other logicians opinions, I clarified these features concisely in the preface to be clear in front of the reader, I made it in two studies and five subjects.I talked about the meaning of the existence in the ((possible for itself) theme, and I clarified its types in the logicians and the philosophers' opinions, through which the existence and the nonexistence are equal in it, as it cannot be existed nor be nonsexist unless with a separated reason, and there is no necessity to oblige its existence, or its nonexistence is impossible.Then I talked about the outweighing of the (possible for itself) as one side of the exi
... Show MoreGraphic design constitutes the human necessity for the design action, so there is no design achievement that is not considered in its founding project and its final realization as a response to a specific necessity. As a result of knowledge, which is the product of experience and is the result of applied science, design is based on observation, study and development, leading to the main goal, which is the utilitarian and aesthetic function that is put into the final consideration of design, and drug packaging design has an important role in all marketing fields, as companies compete with each other to attract the largest number Possible from consumers in a way that guarantees them material profit, and in order to achieve this, it always
... Show More* مشكلة البحث والحاجة اليه:
تأتي أهمية هذا العلم وقوته ومدى الحاجة اليه لكل الناس وخاصة اللذين يريدون أن يغيروا عاداتهم السيئة ويأثروا في غيرهم ، أذ اكد المفكرون والقادة والمصلحون ورجال التربية أنه يجب على الإنسان ان يكون مثابراً ومجتهداً ومتقناً لعمله ، ومنظماً لوقته الى اخر القائمة الطويلة من مفردات الجودة ولم يقولوا كيف يمكن للانسان ان يفعل ذلك ؟ أن علم الهندسة النفسية استطاع ان يجيب. 
... Show MoreAPDBN Rashid, Southern African Linguistics and Applied Language Studies, 2023
Arab translators have always paid great attention to the translation of the Persian literary genres, in particular, contemporary Iranian novels. They have always translated for the most prominent Iranian novelists such as Jalal Al Ahmad, Sadiq Hidayat, Mahmoud Dowlatabadi, Bozorg Alavi, Ismail Fasih, Houshang Golshiri, Gholam-Hossein Saedi, Simin Daneshvar, Sadiq Chubak, Samad Behrangi and others that have succeeded in perfectly picturing the Iranian society.
Within the perspectives of Arab translators and by using the descriptive - analytical approach, the present study provides an analytical study of the translation into Arabic some of the modern Persian novels. Moreove
... Show MoreIn this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot
... Show MoreIn high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri
... Show MoreAbstract
Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia
... Show MoreIn recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
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