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.

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

            In this work, the adsorption of crystal violet dye from aqueous solution on charcoal and rice husk has been investigated, where the impact of variable factors (contact time; the dosage of adsorbent, pH, temperature, and ionic strength) have been studied. It has been found that charcoal and rice husk have an appropriate adsorption limit with regards to the expulsion of crystal violet dye from fluid arrangements. The harmony adsorption is for all intents and purposes accomplished in 45 min for charcoal and 60 min for rice husk. The amount of crystal violet dye adsorbed (0.4 g of charcoal and 0.5 g of rice husk) increased with an increasing pH and the value of 11 is the best

This work is aiming to study and compare the removal of lead (II) from simulated wastewater by activated carbon and bentonite as adsorbents with particle size of 0.32-0.5 mm. A mathematical model was applied to describe the mass transfer kinetic.

The batch experiments were carried out to determine the adsorption isotherm constants for each adsorbent, and five isotherm models were tested to choose the best fit model for the experimental data. The pore, surface diffusion coefficients and mass transfer coefficient were found by fitting the experimental data to a theoretical model. Partial differential equations were used to describe the adsorption in the bulk and solid phases. These equations were simplified and the

Background: Medicinal plants that possess antimicrobial and antioxidant properties have garnered significant attention for their role in maintaining food quality, improving safety, and impeding spoilage. They also can aid in controlling food contamination risks and augmenting the nutritional value of foods. Objective: The study aimed to obtain botanical extracts possessing antimicrobial capabilities and use them to inhibit the growth of molds and yeasts. Additionally, these extracts are aimed at prolonging product shelf life by harnessing their antioxidant attributes. Methods: Several microorganisms, including E. coli and Pseudomonas, were subjected to testing. Ethanolic alcohol, chloroform, and essential oil extracts were prepared;

Both of the species Typha domengensis and Phragmites communis among the most important plant endemic in flora of Iraq from monocotyledon. Due to the similarity of the two species with each other in many morphological characteristics such as the environment where they live and the form of leaves and type of leaf venation and type of stomata….ets, also both of species belong to monocots plant therefore this research work was conducted find anatomical differences that have the same as taxonomic value to help distinguishing between both species under study. Through this research, we found great importance to the anatomical characteristics which we reached by studying the roots, stems and leaves sections f