Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy they got. Deep Learning (DL) and Machine Learning (ML) models were used to enhance text classification for Arabic language. Remarks for future work were concluded.
This work aims at finding out the impact of teaching types blended learning strategies on academic students` achievement. A review of related literature indicates that almost no study has ever attempted to focus specifically on the effect of the different kinds of blended learning strategies on EFL students` achievement in the educational research writing, and the present study attempts to fill this gap. The study focused on the students at the Master's degree in Educational Research Writing in the first semester of the academic year 2020/2021. The sample has selected from the college of Education Ibn-Rushd (18) students. Material has been designed for the Master candidates’ participants of the study was divided into two groups: one an e
... Show MoreThe current research aims to investigate the effect of a specimen of Daniel in the acquisition of concepts for the Arabic language curricula material to the students of the third phase of the Faculty of Basic Education Department of Arabic Language. The sample consists of (93) applications and a student of (47) students in the Division (A), which represents the experimental group which studied the use of a specimen of Daniel, and (46) students in the Division (B), which represents the control group, which studied the traditional way. The subject of unified two groups, which subjects the Arabic language curricula which includes six chapters.
The duration of the experiment is a full semester. The researchers also prepared a tool for mea
Abu Firas al- Hamdani is one of the most prominent abbasid poets Who characterized their poetry with high artistic quality especially in his Romyate which blended the quality of feelings of grief, sorrow, longing and nostalgia that makes sensitive self conflict that stems with time from one hand and with place on the other hand. Because we are dealing with a poet lived west spatial coercive which it has been hurt him within a time conflict swinging between despair and some times patience and hope other times between the present and his painful reality also between the past and the beautiful times.
This researcher is to stand on this Romyat by monitoring effectiveness of the poetic text based on conflict between the presenc
The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura
... Show MoreProducts’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers. In this research, we pr
... Show MoreProducts’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.
 
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The aim of the current research is to prepare an integrated learning program based on mathematics standards for the next generation of the NYS and to investigate its impact on the development of the teaching performance of middle school mathematics teachers and the future thinking skills of their students. To achieve the objectives of the research, the researcher prepared a list of mathematics standards for the next generation, which were derived from a list of standards. He also prepared a list of the teaching competencies required for middle school mathematics teachers in light of the list of standards, as well as clarified the foundations of the training program and its objectives and the mathematical
... Show MoreSoftware-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
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