This paper presents an analysis of the stability of equilibrium positions of two artificial satellites system connected by light, flexible and elastic long tether under the combined effect of several classical perturbative forces in elliptical orbit. The tether may be either conducting or non-conducting. In this study, it is assumed to be non-conducting in nature. We have treated the problem with taking five perturbative forces acting simultaneously on the system. Among these perturbations, three perturbations exist due to the Earth’s influences: the geomagnetic field, shadows and oblateness. The other two perturbations are due to the elasticity of the cable and solar light pressure. The effect of air resistance is neglected considering the satellites as high-altitude satellites. To determine the stability of the satellites, the Lyapunov method has been used. The dynamical behaviours of the satellites are represented by differential equations. As anticipated, the Lyapunov method indicates that the equilibrium position is unstable. At last we have neglected the perturbative forces and treated the problem only under the effect of central gravitational field. The stability analysis is then carried graphically, and final conclusions are drawn.

This paper presents a method for solving non-homogeneous linear sequential fractional differential equations (NHLSFDEs) with constant coefficients involving conformable fractional derivatives. For this purpose, the fundamental properties of the conformable derivative and fractional exponential functions are discussed. After this, we determined the particular integrals (PIs) of NHLSFDE in terms of fractional exponential functions, fractional cosine and sine functions. We have demonstrated this developed method with a few examples of NHLSFDEs.

Internet of things (IoT) has incredibly transformed the whole domain of communication process. The extensive dependency on these devices leads to various advanced cyber security threats. IoT devices fall easily into the ambit of malicious threats and are susceptible to vast range of attacks due to their limited computation capabilities and memory constraints. Intrusion Detection Systems (IDSs) are dedicated outstanding frameworks to protect these devices from cyber threats. In this study, a comprehensive review of different AI based IDS applied on IoTs is done. It has been observed that machine learning and deep learning has widely influenced the domain of IoT security. The focus of the research carried out is to earmark the techniques that are performing best on a given data set. Features selection, type of attacks, proposed solutions in solving security menaces are taken into consideration. Further, we have presented DLIIoT, a deep learning based intelligent attack detection in IoT networks by generating precise IoT datasets in Cooja Simulator. Four Deep learning algorithms are utilized and analysed under standard performance criteria metrics such as Precision, Recall, Accuracy and F1-score. It was found that deep learning algorithms have remarkable potential in detecting and recognizing malicious data patterns in IoT networks.

Singular boundary value problems (SBVPs) have become prevalent in scientific applications such as gas dynamics, chemical reactions, and structural mechanics. In review, the numerical approximation of solutions to differential equations serves as a crucial mechanism across various scientific and engineering fields, facilitating the assessment and analysis of complex systems that are not readily solvable through analytical methods. Due to this, the numerical methods are very crucial. As a result, numerical methods are of significant importance. So, the wavelet-based Galerkin method using Fibonacci wavelets for the numerical solution of SBVPs is introduced. The paper also provides illustrative examples to demonstrate the effectiveness and accuracy of the method.

Acoustic and volumetric studies were conducted on aqueous solutions of L-isoleucine in the presence of magnesium nitrate and magnesium sulphate solution at temperatures of 288.15K and 298.15K. Ultrasonic sound waves propagating through these experimental solutions demonstrated a direct association between the different molecular interactions among the solution's constituents, both strong and weak. The rising electrostriction of water molecules around the solute and co-solute ions decreased isothermal compressibility (KT). Significant ion-ion, ion/hydrophilic-hydrophilic, and ion/hydrophobic-hydrophobic interactions happened among various segments of solute and co-solute ions, while ion-solvent interactions dominated. The processes of solvation and ion association brought about the reformation of the water structure. Numerous variables were assessed and highlighted the increased ion-solvent interactions, ion-pair formation, and structure-building capabilities of L-isoleucine in the presence of MgSO4 / Mg(NO3)2.

It is very helpful to be able to predict different kinds of intermolecular interaction and the strength of the connection between the solute and solvent with thermo-acoustical and volumetric data. Protein and salts are two types of nutrients that are abundant in the human body. This study has examined a number of volumetric and thermo-acoustical properties of C6H9N3O2+H2O and C6H9N3O2+H2O+K2SO4 systems' attributes. With ultrasonic velocities (U) and densities (ρ) of 0.02 – 0.2 mol-kg-1 concentration of protein (C6H9N3O2) in water and 0.1 mol-kg-1 concentration of aqueous potassium salt. The novelty of this tactic is that it exhibits biological and technical applications by observing the pattern of interaction between the protein and salt molecules, which will assist to build more effective future solutions.

The concept of Virtual Power Plant (VPP) emerges as a pivotal advancement in power systems engineering, aiming to enhance the integration of renewable energy sources into the power market. This research delves into the challenges faced by Distributed Energy Resources (DERs), such as power losses, voltage variations, and revenue losses in the distribution network, hindering the effective participation of small-scale renewable energy sources in the power market. Furthermore, the research addresses the challenge of poor dynamic response in VPPs attributed to dynamic loads and DER characteristics. To mitigate this, a Proportional Resonant (PR) controller is proposed to enhance the dynamic performance of the VPP. Comparative analysis with the conventional Fractional Order Proportional Integral Derivative (FOPID) controller reveals the superiority of the PR controller. The PR-controlled VPP exhibits improved dynamic performance with a lower settling time of 0.49 seconds and a reduced steady-state error of 2.78 compared to the FOPID controller. The investigations extend to the comparison of voltage, real power, and reactive power between the FOPID and PR controllers. The results underscore the superior response of the PR-controlled VPP, showcasing its efficacy in achieving faster responses and minimizing spikes in voltage and power variables.

The absence of a generalized method for solving Diophantine equations having more unknowns than a number of equations is a challenge for researchers in different fields. The presence of the Diophantine equation is reported in the study of the Hydrogen spectrum, quantum Hall effect, chemistry, cryptography, etc. Some special types of Diophantine equations could be addressed with the help of Catalan’s conjecture and Congruence theory. The Diophantine equation 3x + 15y =z2 is addressed in this paper to find the solution(s) in positive integers. It is found that the equation has only two solutions of (x,y,z) as (1,0,2) and (0,1,4) in non-negative integers.

In this paper, The Friedmann-Robertson-walker (FRW) cosmological model with bulk viscosity is investigated in the f(R) theory of gravitation. For the Power and Exponential expansion, the field equations are solved. The functional form of the function f(R) such as f(R) =R+αR2 is chosen for investigation. It is found that the bulk viscosity coefficient reacts similarly to the energy density; the model is viable only for K=-1 , which represents an open universe. The Phantom field potential and scalar field are obtained.

Vibrational and electronic analyses were conducted for quinoxaline utilizing FT-IR, FT – Raman, and UV–Vis–NIR techniques. Infrared intensities, Raman scattering data, vibrational wavenumbers, molecular geometry, and optimal structure were determined using the Density Functional Theory/ Becke's three-parameter exchange functional with the Lee-Yang-Parr correlation functional (DFT/B3LYP) method with a 6–31G** basis set. Electron localization and delocalization were examined through highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO–LUMO) analysis, while Molecular Electrostatic Potential (MEP) analyses were undertaken to identify potential electrophilic, nucleophilic, and radical attacks. The electron affinity, electronegativity, chemical potential, ionization potential, electrophilicity and hardness, softness, stability of the compound were characterized via FMO (Frontier Molecular Orbital) studies. Nonlinear optical (NLO) characterizations involved the determination of dipole moment, polarizability, and first–order hyperpolarizability. Additionally, Molecular Docking analysis of quinoxaline was carried out to know its binding orientation, affinity, and activity.