This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

A security system can be defined as a method of providing a form of protection to any type of data. A sequential process must be performed in most of the security systems in order to achieve good protection. Authentication can be defined as a part of such sequential processes, which is utilized in order to verify the user permission to entree and utilize the system. There are several kinds of methods utilized, including knowledge, and biometric features. The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field. EEG has five major wave patterns, which are Delta, Theta, Alpha, Beta and Gamma. Every wave has five features which are amplitude, wavelength, period, speed and frequency. The linear

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an

Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

Rap songs often feature artists who utilize explicit language to convey feelings such as happiness, sorrow, and anger, reflecting audience expectations and trends within the music industry. This study intends to conduct a socio-pragmatic analysis of explicit, derogatory, and offensive language in the songs of the American artist Doja Cat, employing Hughes’ (1996) Swearing Word Theory, Jay’s (1996) Taboo Words Theory, Luhr’s (2002) classification of social factors for sociolinguistic examination, Salager’s (1997) categories of hedges for pragmatic assessment, and Austin’s (1965, 1989) theory of speech acts. The researchers collected the data using the AntConc corpus analysis tool. The data shows the singer’s frequent use

Silybum marianum, from which silymarin (SM) is extracted, is a medicinal herb. In the Biopharmaceutics Classification System, it is of the class II type, meaning it is almost completely insoluble in water. It has a number of therapeutic properties, including anti-inflammatory as well as properties that promote wound healing.

This research target is to promote the dissolution and solubility of SM by employing a technique called solid dispersion and then incorporating the formula of solid dispersion into a topical gel that can be used for wound healing.

Solid dispersion is a technique used to enhance solubility and dissolve pharmaceuticals that are not water-soluble. This method is widely used because of its low cos

A simple and rapid high performance liquid chromatographic with fluorescence detection method for the determination of the aflatoxin B1, B2, G1 and G2 in peanuts, rice and chilli was developed. The sample was extracted using acetonitrile:water (90:10, v/v%) and then purified by using ISOLUTE multimode solid phase extraction. After the pre-column derivatisation, the analytes were separated within 3.7 min using Chromolith performance RP-18e (100–4.6 mm) monolithic column. To assess the possible effects of endogenous components in the food items, matrix-matched calibration was used for the quantification and validation. The recoveries of aflatoxins that were spiked into food samples were 86.38–104.5% and RSDs were <4.4%. The method was