Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the IRF algorithm. It optimizes feature importance weights during training and improves the model's ability to detect intrusions in cloud environments accurately. The proposed detection model is implemented in Python software. In the findings assessment phase, we effectively assessed the performance of our proposed DB-IRF in detecting earthquake incidents across multiple evaluation metrics such as Accuracy (97.5%), Precision (97.96%), F1 Score (98.48%) and Recall (97.85%). We also conducted a comparison analysis with other conventional methodologies. Our experimental results demonstrate the capability and reliability of the recommended framework.
Clobetasol propionate (CP) is a super potent corticosteroid widely used to treat various skin disorders such as atopic dermatitis and psoriasis. However, its utility for topical application is hampered due to its common side effects, such as skin atrophy, steroidal acne, hypopigmentation, and allergic contact dermatitis. Microsponge is a unique three-dimensional microstructure particle with micro and nano-meters-wide cavities, which can encapsulate both hydrophilic and lipophilic drugs providing increased efficacy and safety. The aim of the current study is to prepare and optimize clobetasol-loaded microsponges. The emulsion solvent diffusion method is used for the preparation of ethylcellulose (EC)-based microsponges. The impact of
... Show MoreThe inhibitory behavior of L-Cysteine (Cys) and its derivatives towards iron corrosion through density functional theory (DFT) was investigated. The current research study undertakes a rigorous evaluation of global as well as local reactivity descriptors of the Cys in protonated as well as neutral forms and the changes in reactivity after the combination of Cys into di- and tripeptides. The inhibitory effect of di- and tri-peptides increases since, in the molecular structure, the number of reaction centers increase. We computed the adsorption energies (Eads) and low energy complexes with most stability for the adsorption of small peptides and Cys amino acids onto the surfaces of Fe (1 1 1). We found that the adsorption of tri-peptides onto
... Show MoreIn the current work, aromatic amines and alkyl halides have been converted to the corresponding azides 2a‒d and 4a-d by the reaction with sodium nitrite and sodium azide respectively for amines and sodium azide for halides. Then, dipropargyl ether derivative of D-mannose 8 has been synthesized from diacetone mannose that has been obtained by the treatment of D-mannose (5) with dry acetone in the presence of sulfuric acid. Then, aldol condensation has been used to prepare diol 7 from the mannose diacetonide 6. The reaction of compound 7 with propargyl bromide in alkaline media has been afforded dipropargyl
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show MoreThe rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreDue to the importance of the extraction process in many engineering and medical industries, in addition to great interest in medicinal plants, in this research, microwave-assisted extraction has been applied to extract some active compounds from Rosmarinus officinalis leaves. The optimal extraction conditions were then determined by calculating the ratio and extraction efficiency. The process has also been described through kinetic study by applying five kinetic models, the Hyperbolic diffusion model, Power low model, the First order reaction model, Elovich's model, and Fick's second law diffusion model and determining their compatibility with the studies operation, and determining the kinetic constants for each model. The result
... Show MoreBackground: the primary objective for many researches carried out in dental implantology was to reduce the period needed for functional implant loading, simvastatin (cholesterol lowering medication) had many pleiotropic effects, one of which was increasing bone density around titanium implants (1) and subsequently establishing faster osseointegrated dental implants (2,3). This study aims to reduce the period of time needed to establish secondary stability of dental implant measured in ISQ (Implant Stability Quotient) by investigating the effect of orally administered simvastatin on bone. Materials and methods: simvastatin tablets (40mg/day for three months) were administered orally for 11 healthy women aged (40-51) years old who received 1
... Show MoreGiven the paucity and toxicity of available drugs for leishmaniasis, coupled with the advent of drug resistance, the discovery of new therapies for this neglected tropical disease is recognised as being of the utmost urgency. As such antimicrobial peptides (AMPs) have been proposed as promising compounds against the causative Leishmania species, insect vector-borne protozoan parasites. Here the AMP temporins A, B and 1Sa have been synthesised and screened for activity against Leishmania mexicana insect stage promastigotes and mammalian stage amastigotes, a significant cause of human cutaneous disease. In contrast to previous studies with other species the activity of these AMPs against L. mexicana amastigotes was low. This suggests that ama
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