A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Аннотация

    в статье рассматриваются проблемы преподавания русской литературы в иракской аудитории.. Использование литературы в преподавании иностранного языка, как правило, имеет две цели. Первая-чисто лингвистическая .. Вторая цель, однако, ассоциируется больше с экстралингвистикой  и представляет собой ознакомление студентов с различными аспектами русской жизни, культуры,

Sustainable development (SD) is an improvement that meets present needs but jeopardizes the ability of new populations to do the same. It is vital to acquaint EFL students with the terminology and idiomatic expressions of this discipline. Nowadays, sustainable development and the environment have been prioritized in every aspect of life. Since culture and the teaching of Foreign language English cannot be separated, the English language becomes the mean of communication in health, economics, education, and politics. Thus, integrating sustainable development goals within language learning and teaching is very important. This descriptive quantitative study aims to investigate the perception of EFL pre-service teachers of sustainable develo

Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

Abstract

The aim of the current research is to extract the psychometric properties of Philip Carter's tests (for mental agility) according to the classical measurement theory. To achieve these goals, the researcher took a number of scientific steps to analyze Philip Carter's tests (for mental agility) according to the classical measurement theory. The researcher translated Philip Carter's (mental agility) tests from English into Arabic and then he translated them conversely. For the purpose of statistical analysis of paragraphs of the Philip Carter tests (mental agility) to extract the psychometric properties, the tests were applied to a sample of (1000) male and female students who were selected by cluster sampl

Objective of the study was to rate and analyze the physical fitness of female students from Iraq and Russia to find similarities, differences and regularities. Sampled for the study were 44 female non-sporting students: 20 students from Pedagogical University in Bagdad; and 24 students from Russian State University of Physical Education, Sport, Youth and Tourism in Moscow. The study was designed to obtain the joints flexibility, coordination, speed-strength and static endurance rates. The Iraqi students were tested with higher coordination abilities than their Russian peers, whilst the latter were ranked higher in the speed-strength, shoulder joints and spine flexibility tests, albeit lower than their Iraqi peers in the hip flexibility test