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.
The present study investigates the relation between the biliteral and triliteral roots which is the introduction to comprehend the nature of the Semitic roots during its early stage of development being unconfirmed to a single pattern. The present research is not meant to decide on the question of the biliteral roots in the Semitic languages, rather it is meant to confirm the predominance of the triliteral roots on these languages which refers, partially, to analogy adopted by the majority of linguists. This tendency is frequently seen in the languages which incline to over generalize the triliteral phenomenon, i. e., to transfer the biliteral roots to the triliteral room, that is, to subject it to the predominant pattern regarding the r
... Show MoreThe precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
... Show MoreThe purpose of the current investigation is to distinguish between working memory ( ) in five patients with vascular dementia ( ), fifteen post-stroke patients with mild cognitive impairment ( ), and fifteen healthy control individuals ( ) based on background electroencephalography (EEG) activity. The elimination of EEG artifacts using wavelet (WT) pre-processing denoising is demonstrated in this study. In the current study, spectral entropy ( ), permutation entropy ( ), and approximation entropy ( ) were all explored. To improve the classification using the k-nearest neighbors ( NN) classifier scheme, a comparative study of using fuzzy neighbourhood preserving analysis with -decomposition ( ) as a dimensionality reduction technique an
... Show MoreThis article is devoted to the cognitive study of ironic metonymy in Russian and Arabic. Metonymy and irony have traditionally been seen as parallel linguistic phenomena. But their formation and interpretation are based on different cognitive mechanisms. At the formal and functional level, metonymy and irony have a number of significant differences. Metonymy is an artistic technique, the mechanism of which is based on obvious, easily traced connections between objects and phenomena of the surrounding world. Irony is a satirical technique or a rhetorical figure that is used to create a certain artistic image, aimed at forming the hidden meaning of the statement. A native speaker intuitively feels the difference between metonymy and i
... Show MoreShadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit
... Show MoreThis study was set out to investigate factors affecting labor productivity on construction in the north of Iraq (Kurdistan) and to rank all the factors based on engineers, contractors, and designer’s opinions. 76 factors were analyzed based on previous literature and a pilot study. Next, by using online Google Form, a questionnaire form was created and sent to people who have experience in the construction industry. Afterward, the questionnaire form was sent to targeted people by email and social media apps. Factors were divided into nine groups “Management, Technical and Technology, Human and Workforce, Leadership, Motivation, Safety, Time, Material and Equipment, and External”. However, 202 respondents participated in this study,
... Show MoreThe current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.
The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri
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