Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and identifying variants. A patient's HIV strain can be classified as susceptible or resistant to 17 different treatments. The FGD-MCNN transforms DNA genotype and HIV data into mathematical metrics, providing valuable insights into treatment-resistant HIV strains through pooling analysis. With remarkable accuracy, the FGD-MCNN deep learning system predicts HIV medication resistance using behavioral and genome-wide data from the HIV database. DNA patterns can be classified as resistant or susceptible by 17 antiretroviral drugs, providing valuable information for treatment planning and medical judgment. The model's parameter values illustrate the connections between neurons and the complex webs observed in the data have been examined. This study improves treatment effectiveness and expands the knowledge of HIV/AIDS.
Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a
... Show MoreBiomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS
... Show MoreIn this paper, a methodology is presented for determining the stress and strain in structural concrete sections, also, for estimating the ultimate combination of axial forces and bending moments that produce failure. The structural concrete member may have a cross-section with an arbitrary configuration, the concrete region may consist of a set of subregions having different characteristics (i.e., different grades of concretes, or initially identical, but working with different stress-strain diagrams due to the effect of indirect reinforcement or the effect of confinement, etc.). This methodology is considering the tensile strain softening and tension stiffening of concrete in additio
A study of characteristics of the lubricant oils and the physical properties is essential to know the quality of lubricant oils. The parameters that lead to classify oils have been studied in this research. Three types of multi-grades lubricant oils were applied under changing temperatures from 25 oC to 78oC to estimate the physical properties and mixture compositions. Kinematic viscosity, viscosity gravity constant and paraffin (P), naphthenes (N) and aromatics (A) (PNA) analysis are used to predict the composition of lubricants oil. Kinematic viscosity gives good behaviors and the oxidation stability for each lubricant oils. PNA analysis predicted fractions of paraffin (XP), naphthenes (XN),
... Show MoreThe present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake
... Show MoreSchiff bases (SBs) represent multipurpose ligands that can be prepared from the concentration of prime amines with carbonyl clusters. Creation of SB transition metal compounds via as ligands has opportunity of attaining coordination complexes of abnormal arrangement and stability. These transition metal compounds have extraordinary attention as a consequence of their dynamic portion in metalloenzymes and as biomimetic prototypical complexes as a result of their proximity to usual enzymes and proteins. These complexes are imperative in medicinal disciplines owing to their widespread range of biological actions. They mostly exhibit organic actions involving antifungal, antibacterial, antitumor, antidiabetic, herbicidal, antiproliferative, ant
... Show MoreSchiff bases (SBs) represent multipurpose ligands that can be prepared from the concentration of prime amines with carbonyl clusters. Creation of SB transition metal compounds via as ligands has opportunity of attaining coordination complexes of abnormal arrangement and stability. These transition metal compounds have extraordinary attention as a consequence of their dynamic portion in metalloenzymes and as biomimetic prototypical complexes as a result of their proximity to usual enzymes and proteins. These complexes are imperative in medicinal disciplines owing to their widespread range of biological actions. They mostly exhibit organic actions involving antifungal, antibacterial, antitumor, antidiabetic, herbicidal, antiproliferative, ant
... Show MoreConventional dosage forms for topical and transdermal drug delivery have several disadvantages related mainly to its poor skin permeation and patient compliance. Many approaches have been developed to improve these dosage forms. Film forming drug delivery systems represents a recent advancement in this field. It provides improved patient compliance with enhanced skin permeation of drugs. In its simplest form, these consist of a polymeric solution, usually in a supersaturated state, in a suitable solvent. A plasticizer is usually added to improve the flexibility and enhance the tensile strength to the film. It is also possible to control and sustain the drug release from the films by controlling the polymeric content, concentration o
... Show MoreThis paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi