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. This study comprehensively analyzes different FS approaches based on optimization algorithms for TC. We begin by introducing the primary phases involved in implementing TC. Subsequently, we explore a wide range of FS approaches for categorizing text documents and attempt to organize the existing works into four fundamental approaches: filter, wrapper, hybrid, and embedded. Furthermore, we review four optimization algorithms utilized in solving text FS problems: swarm intelligence-based, evolutionary-based, physics-based, and human behavior-related algorithms. We discuss the advantages and disadvantages of state-of-the-art studies that employ optimization algorithms for text FS methods. Additionally, we consider several aspects of each proposed method and thoroughly discuss the challenges associated with datasets, FS approaches, optimization algorithms, machine learning classifiers, and evaluation criteria employed to assess new and existing techniques. Finally, by identifying research gaps and proposing future directions, our review provides valuable guidance to researchers in developing and situating further studies within the current body of literature.
The aim of the current research is to reveal the effect of using brain-based learning theory strategies on the achievement of Art Education students in the subject of Teaching Methods. The experimental design with two equal experimental and control groups was used. The experimental design with two independent and equal groups was used, and the total of the research sample was (60) male and female students, (30) male and female students represented the experimental group, and (30) male and female students represented the control group. The researcher prepared the research tool represented by the cognitive achievement test consisting of (20) questions, and it was characterized by honesty and reliability, and the experiment lasted (6) weeks
... Show MoreRecently, the development of the field of biomedical engineering has led to a renewed interest in detection of several events. In this paper a new approach used to detect specific parameter and relations between three biomedical signals that used in clinical diagnosis. These include the phonocardiography (PCG), electrocardiography (ECG) and photoplethysmography (PPG) or sometimes it called the carotid pulse related to the position of electrode.
Comparisons between three cases (two normal cases and one abnormal case) are used to indicate the delay that may occurred due to the deficiency of the cardiac muscle or valve in an abnormal case.
The results shown that S1 and S2, first and second sound of the
... Show MoreThis study aims to employ modern spatial simulation models to predict the future growth of Al-Najaf city for the year 2036 by studying the change in land use for the time period (1986-2016) because of its importance in shaping future policy for the planning process and decision-making process and ensuring a sustainable urban future, using Geographical information software programs and remote sensing (GIS, IDRISI Selva) as they are appropriate tools for exploring spatial temporal changes from the local level to the global scale. The application of the Markov chain model, which is a popular model that calculates the probability of future change based on the past, and the Cellular Automa
The Financial systems can be classified into two types. The first is the market–oriented, which is applied in United States and United Kingdom. While the second is bank-oriented as in Japan and Germany.
This study tries to explain the reasons which make some countries adopt the first one instead of the second, and the contrary. So the study consists of three sections. The first deals with the concept of financial system and it are functions. The second displays the indicators which are used to classify the financial systems, while the third one is devoted to the factors that determine the type of financial system .These sections followed by some conclusions.
Many water supplies are now contaminated by anthropogenic sources such as domestic and agricultural waste, as well as manufacturing activities, the public's concern about the environmental effects of wastewater contamination has grown. Several traditional wastewater treatment methods, such as chemical coagulation, adsorption, and activated sludge, have been used to eliminate pollution; however, there are several drawbacks, most notably high operating costs, because of its low operating and repair costs, the usage of aerobic waste water treatment as a reductive medium is gaining popularity. Furthermore, it is simple to produce and has a high efficacy and potential to degrade pollu
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In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreTraumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
... Show MoreIn recent decades, drug modification is no longer unusual in the pharmaceutical world as living things are evolving in response to environmental changes. A non-steroidal anti-inflammatory drug (NSAID) such as aspirin is a common over-the-counter drug that can be purchased without medical prescription. Aspirin can inhibit the synthesis of prostaglandin by blocking the cyclooxygenase (COX) which contributes to its properties such as anti-inflammatory, antipyretic, antiplatelet and etc. It is also being considered as a chemopreventive agent due to its antithrombotic actions through the COX’s inhibition. However, the prolonged use of aspirin can cause heartburn, ulceration, and gastro-toxicity in children and adults. This review article hi
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