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.
In recent years, literary studies have witnessed a remarkable shift towards employing digital technologies, particularly artificial intelligence tools, in analyzing literary texts and exploring their linguistic and semantic structures. This trend has provided researchers with new possibilities for understanding texts in quantitative and qualitative ways that transcend traditional methods based solely on critical reading. The current research aims to introduce professors and students of Arabic to artificial intelligence tools that contribute to the analysis of literary texts, focusing on exploring their mechanisms for studying style, meaning, structure, and emotion. It also seeks to highlight the most prominent challenges facing researchers
... Show MoreRegarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
... Show MoreThe widespread of internet allover the world, in addition to the increasing of the huge number of users that they exchanged important information over it highlights the need for a new methods to protect these important information from intruders' corruption or modification. This paper suggests a new method that ensures that the texts of a given document cannot be modified by the intruders. This method mainly consists of mixture of three steps. The first step which barrows some concepts of "Quran" security system to detect some type of change(s) occur in a given text. Where a key of each paragraph in the text is extracted from a group of letters in that paragraph which occur as multiply of a given prime number. This step cannot detect the ch
... Show MoreMetal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit
... Show MoreThis study provides a systematic and bibliometric review of ASTM F75 cobalt–chromium alloys, focusing on microstructure and the shift from conventional to laser-based manufacturing. Using combined analytical methods, it evaluates microstructure, mechanical properties, corrosion behavior, and biocompatibility. Results show that laser-based techniques such as LPBF and DMLS produce finer grain sizes (1–10 µm vs. 50–200 µm), leading to improved hardness (20–40%) and tensile strength (15–30%). Despite challenges like residual stress and process optimization, these methods show strong potential for high-performance and sustainable applications.
Objectives: To review the failure rates of molar tubes and the effect of molar tube base design, adhesive type, and bonding technique on the failure rates of molar tubes. Data: The revolution of molar bonding greatly impacted fixed orthodontic appliance treatment by reducing chair-side time and improving patient comfort. Even with the many advantages of molar bonding, clinicians sometimes hesitate to use molar tubes due to their failure rates. Sources: Internet sources, such as Pubmed and Google Scholar. Study selection: studies testing the bond failure rate of molar tubes. Conclusions: The failure rate of the molar tubes can be reduced and the bond strength of the molar tubes can be improved by changing the design of the molar tube base
... Show More
Cressa cretica (Shuwwayl) is a halophytic that belongs to Convolvulaceae, naturally grown in the Middle East including Iraq. Traditionally the plant is used as a paste for sore treatment, also it is used for fever, jaundice, and other illness. Regarding nonclinical use it is used as goat, sheep, and camel feed also as an oil source. Flavonoids including quercetin, kamepferol, apigenin, and their glycosides, phenolic acid as chlorogenic acid, and phytosterols mainly ?–sitosterol were the most important phytochemicals that were detected in this halophyte. Crude ethanolic, methanolic extracts and ethyl acetate fraction of the areal parts were used in clinical studies and demonstrated various effe
... Show MoreSpeech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra
When the drawdown pressure amounts to a value below the dew point pressure, a minor droplet of condensate is shaped and accumulated in the close area of wellbore. As the accumulation happens, the saturation of the liquid will grow and a reduction in gas relative permeability will happen, therefore it will affect the productivity. Generally, condensate baking problem in gas wells is being deliberated and studied and numerous techniques have been suggested to solve the problem. The studying of condensate banking dynamics is essential to evaluate the productivity and behavior of the wells of the gas fields.