Papers by Dr. Srinivasarao Thota
RASÄ€YAN Journal of Chemistry, 2025
This article presents a novel repetitive procedure to work out non-linear equations commonly enco... more This article presents a novel repetitive procedure to work out non-linear equations commonly encountered in chemical systems, such as reaction kinetics and thermodynamic equilibria. The algorithm combines exponential decay and derivative-based adjustments to iteratively refine solutions, making it highly effective for optimizing reaction rates and determining equilibrium concentrations in complex chemical reactions. We demonstrate the algorithm's applicability in solving reaction rate optimization problems and chemical equilibrium equations, where traditional analytical solutions are often impractical. The algorithm's robustness and precision are highlighted through examples, including the optimization of a second-order reaction rate and the determination of equilibrium concentrations in a system governed by mass action laws. Results indicate that the algorithm converges rapidly to high-precision solutions, offering a powerful tool for chemists to model and analyze chemical processes. This method holds significant potential for broad applications in reaction modeling, material science, and computational chemistry.
International Journal of Optimization and Control: Theories & Applications, 2025
Nonlinear phenomena are prevalent in numerous fields, including economics, engineering, and natur... more Nonlinear phenomena are prevalent in numerous fields, including economics, engineering, and natural sciences. Computational science continues to advance through the development of novel numerical schemes and the refinement of existing ones. Ideally, these numerical systems should offer both high-order convergence and computational efficiency. This article introduces a new threestep algorithm for solving nonlinear scalar equations, aiming to meet these criteria. The proposed approach requires six function evaluations per iteration and achieves ninth-order convergence. To demonstrate the efficiency of the technique, various numerical examples are shown. Implementations of the method are available in both Maple and Python, and it can be readily adapted for use in other computational environments.
Computational Methods for Differential Equations, 2025
In developing countries, the agricultural industry is pivotal in economic development and sustain... more In developing countries, the agricultural industry is pivotal in economic development and sustaining rural livelihoods. However, one of the major challenges to achieving food security globally is crop losses due to pests. Pest control is a vital practice for safeguarding crops; it is often complicated by the need to balance pest reduction with the associated costs of operations, as well as the potential impacts on the environment and human health. This delicate balance is crucial for sustainable agriculture and long-term food security. In this paper, a mathematical model is developed to quantify the complex biological processes involved in the biological control of pests through prey-predator mechanisms. We provide trajectory analysis in the research discussion analysis.
Sigma Journal of Engineering and Natural Sciences, 2025
The digital era has witnessed a significant rise in misinformation, underscoring the urgent need ... more The digital era has witnessed a significant rise in misinformation, underscoring the urgent need for effective tools to distinguish factual news from fabricated content. This study proposes a novel methodology for fake news detection that leverages quantum entanglement to facilitate multimodal fusion of textual, visual, and acoustic data. The quantum entanglement algorithm offers significant advantages in managing high-dimensional data by enabling efficient feature optimization through quantum computing encodings integrated with neural network architectures. The existing quantum circuits for text, visual, and audio would co-occur while witnessing the message from humans to machines with the machines acting as quantum computers integrated with neural networks, specifically designed for fake news detection. The results generated from our method demonstrate significantly improved fake news detection accuracy, and increased accuracy in the noise simulation, and the system is resilient to adversarial methods, all in contrast to typical methods. The proposed Quantum Encoding with Multimodal Fusion (QEMF) framework surpasses existing approaches by offering as it suggests promising future directions to tackle fake news across the web. The system, in a scientific manner, performs a variety of strict pre-processing techniques to all textual data such as tokenization, stemming, and lemmatization, along with sophisticated image pre-processing to all visual data. It uses the latest extracting features, i.e., Glove for text embedding, and conventional convolutional networks, like VGG16, for visual data. The feature representation is significantly enriched through quantum encoding, while the capability of QCNNs to identify the most salient and discriminative features enhances accuracy and ensures robustness against noise and adversarial interference. Furthermore, the system's real-time detection capability and its scalability position it as a powerful tool in combating misinformation within the evolving bio-informational ecosystem.
BMC Research Notes, 2025
Objective Detecting small, faraway objects in real-time surveillance is challenging due to limite... more Objective Detecting small, faraway objects in real-time surveillance is challenging due to limited pixel representation, affecting classifier performance. Deep Learning (DL) techniques generate feature maps to enhance detection, but conventional methods suffer from high computational costs. To address this, we propose Multi-Scale Region-wise Pixel Analysis with GAN for Tiny Object Detection (MSRP-TODNet). The model is trained and tested on VisDrone VID 2019 and MS-COCO datasets. First, images undergo twofold pre-processing using Improved Wiener Filter (IWF) for artifact removal and Adjusted Contrast Enhancement Method (ACEM) for blurring correction. The Multi-Agent Reinforcement Learning (MARL) algorithm splits the pre-processed image into four regions, analyzing each pixel to generate feature maps. These are processed by the Enhanced Feature Pyramid Network (EFPN), which merges them into a single feature map. Finally, a Generative Adversarial Network (GAN) detects objects with bounding boxes. Results Experimental results on the DOTA dataset demonstrate that MSRP-TODNet outperforms existing state-ofthe-art methods. Specifically, it achieves an mAP @0.5 of 84.2%,
Journal of Nonlinear Modeling and Analysis, 2025
The invention of highly active antiretroviral treatment (HAART) revolutionalized the treatment of... more The invention of highly active antiretroviral treatment (HAART) revolutionalized the treatment of HIV and brought hope to millions of individuals living with the virus. However, the eradication of HIV has proved difficult owing to many factors including accessibility and treatment compliance, particularly among many individuals in low income countries. Thus, we developed a model in terms of a system of nonlinear ordinary differential equations to assess the influence of inaccessibility of treatment and noncompliance with treatment guidelines by the HIV infectives who are aware of their status on the spread of HIV. The model was studied qualitatively and quantitatively using the theory of reproductive ratio and the software Maple respectively. The results of the analysis showed that early detection, treatment accessibility and treatment compliance by the majority of the infectives who know their status are crucial to the minimization of HIV incidence and prevalence.
F1000Research, 2025
Background Matrix Chain Multiplication (MCM) is a fundamental problem in computational mathematic... more Background Matrix Chain Multiplication (MCM) is a fundamental problem in computational mathematics and computer science, often encountered in scientific computing, graphics, and machine learning. Traditional MCM optimization techniques use Dynamic Programming (DP) with Memoization to determine the optimal parenthesization for minimizing the number of scalar multiplications. However, standard matrix multiplication still operates in O(n 3) time complexity, leading to inefficiencies for large matrices. Methods In this paper, we propose a hybrid optimization technique that integrates Strassen's algorithm into MCM to further accelerate matrix multiplication. Our approach consists of two key phases: (i) matrix chain order optimization, using a top-down memoized DP approach, we compute the best multiplication sequence, and (ii) hybrid multiplication strategy, we selectively apply Strassen's algorithm for large matrices (n ≥ 128), reducing the complexity from O(n 3) to O(n 2.81), while using standard multiplication for smaller matrices to avoid recursive overhead. We evaluate the performance of our hybrid method through computational experiments comparing execution time, memory usage, and numerical accuracy against traditional MCM and Strassen's standalone multiplication.
Computational Methods for Differential Equations, 2025
The basic necessities of life are food, shelter and clothing. Food is more necessary because the ... more The basic necessities of life are food, shelter and clothing. Food is more necessary because the existence of life depends on food. In order to foster global food security, integrated pest management (IPM), an environmentallyfriendly program, was designed to maintain the density of pest population in the equilibrium level below the economic damage. For years, mathematics has been an ample tool to solve and analyze various real-life problems in science, engineering, industry and so on but the use of mathematics to quantify ecological phenomena is relatively new. While efforts have been made to study various methods of pest control, the extent to which pests' enemies as well as natural treatment can reduce crop damage is new in the literature. Based on this, deterministic mathematical models are designed to investigate the prey-predator dynamics on a hypothetical crop field in the absence or presence of natural treatment. The existence and uniqueness of solutions of the models are examined using Derrick and Grossman's theorem. The equilibria of the models are derived and the stability analysed following stability principle of differential equations and Bellman and Cooke's theorem. The theoretical results of the models are justified by a means of numerical simulations based on a set of reasonable hypothetical parameter values. Results from the simulations reveal that the presence of pests' enemies on a farm without application of natural treatment may not avert massive crop destruction. It is also revealed that the application of natural treatment may not be enough to keep the density of the pest population below the threshold of economic damage unless the rate of application of natural treatment exceeds the growth rate of the pest.
WSEAS TRANSACTIONS on SYSTEMS, 2025
This work aims to contribute insights into the dynamics of tobacco smoking models concerning snuf... more This work aims to contribute insights into the dynamics of tobacco smoking models concerning snuffing users, and to assess the efficacy of different operators namely the Atangana-Baleanu fractional and fractal-fractional (FF) operators. We utilized fixed-point results to evaluate the existence and uniqueness of solutions for the model. Subsequently, we introduced a novel fractal-fractional concept by incorporating the AB fractional operator into the tobacco smoking model. Two numerical techniques are employed to address both the fractional and FF models. Graphical representations of numerical results are provided for the model encompassing a broad spectrum of fractional order values. Furthermore, we conducted a comparative analysis of the operators utilizing numerical schemes, accommodating diverse fractional order values.
Modelling LCR-Circuit into Integro-Differential Equation Using Variational Iteration Method and GRU-Based Recurrent Neural Network
IEEE Xplore, 2025
This investigation incorporates digital numerical methods with neural networks for resolving an L... more This investigation incorporates digital numerical methods with neural networks for resolving an LCR circuit that shades the integro-differential equation. The variational iteration technique is needed to tackle numerical troubles. The One-Hidden Layer Gated Recurrent Unit (GRU) in a Recurrent Neural Network (RNN) is utilized to model and predict dynamic systems. This eidetic procedure is used as an example in the methodology of imaging dynamic systems and the development of the hybrid method. The advantage of this new tool is that it can be utilized in various contexts, especially in those areas where complex and continuous processes are frequent.
Scientific Reports, 2024
Distributed denial of service (DDoS) attack is one of the most hazardous assaults in cloud comput... more Distributed denial of service (DDoS) attack is one of the most hazardous assaults in cloud computing or networking. By depleting resources, this attack renders the services unavailable to end users and leads to significant financial and reputational damage. Hence, identifying such threats is crucial to minimize revenue loss, market share, and productivity loss and enhance the brand reputation. In this study, we implemented an effective intrusion detection system using deep learning approach. The suggested framework includes three phases: Data pre-processing, Data balancing, and Classification. First, we prepare the valid data, which is helpful for further processing. Then, we balance the given pre-processed data by Conditional generative adversarial network (CGAN), and as a result, we can minimize the bias towards the majority classes. Finally, we distinguish whether the traffic is attack or benign using a stacked sparse denoising autoencoder (SSDAE) with a firefly-black widow (FA-BW) hybrid optimization algorithm. All these experiments are validated through the CICDDoS2019 dataset and compared with well-received techniques. From these findings, we observed that the proposed strategy detects DDoS attacks significantly more accurately than other approaches. Based on our findings, this study highlights the crucial role played by advanced deep learning techniques and hybrid optimization algorithms in strengthening cybersecurity against DDoS attacks.
International Journal of Applied Mathematics, 2024
This study presents a symbolic approach for solving second order boundary value problems with Sti... more This study presents a symbolic approach for solving second order boundary value problems with Stieltjes boundary conditions (integral, differential, and generic boundary conditions). The proposed symbolic method computes the Green’s operator and the Green’s function of the provided boundary value problem on the level of operators by applying the algebra of integro-differential operators. The suggested algorithm will aid in implementing manual calculations in mathematical software programs like Mathematica, Matlab, Singular, Scilab, Maple and others.
Journal For Basic Sciences/Fangzhi Gaoxiao Jichukexue Xuebao, 2024
In this paper, we present a new hybrid root-finding algorithm/method to solve the given nonlinear... more In this paper, we present a new hybrid root-finding algorithm/method to solve the given nonlinear equations. The basic idea of the proposed algorithm is the combination of regula-falsi algorithm and exponential method. The proposed algorithm converges faster than some existing methods and derivative-free. Couple examples are presented to demonstrate the proposed method. Maple and Microsoft excel implementations are discussed with sample computations. We can use the proposed algorithm to implement in the mathematical software tools such as Mathematica, Scilab, MATLAB etc.
WSEAS Transactions on Biology and Biomedicine, 2024
This paper presents a critical review of numerical methods for solving a wide variety of interfac... more This paper presents a critical review of numerical methods for solving a wide variety of interface problems emphasizing the immersed finite element method (IFEM). It is found in the literature that most of the researchers considered the well-known methods with some modifications, however limited number of research articles proposed new algorithms. Apart from the algorithm, this study highlights the wide range of applications of interface problems specifically in biomedical, heat-transfer and turbo-machinery. Different numerical methods for interface problems with their major finding are listed in tabulated form at the end.
BMC Research Notes, 2024
Objective This article introduces a novel approach called Digital Weighted Multi Criteria Decisio... more Objective This article introduces a novel approach called Digital Weighted Multi Criteria Decision Making (DWM-CDM) that employs interval valued fuzzy sets to select the best contractor for building projects. The contractor is chosen based on the pre-qualification and bid evaluation phases. In the first phase, the distance between the actual and required skills of the significant criteria is determined, and it is then converted into digital weighted distances to identify the maximum number of criteria related to the specific project of each contractor. The second step ranks the best contractor based on the bid price and digital weighted distances. Results The suggested technique integrates the pre-qualification and bid review phases to address project award delays and other restrictions. Finally, a real-world application is addressed to demonstrate the applicability of the proposed approach to any type of interval valued fuzzy inputs.
International Journal of Networked and Distributed Computing, 2024
As e-commerce has grown gradually online item assessments have emerged as a key source of consume... more As e-commerce has grown gradually online item assessments have emerged as a key source of consumer data. That stated, there are problems with the consistency and fictitiousness of the evaluations because there are numerous fake or fraudulent ones. These misleading assessments are generated during the investigation in an attempt to mislead customers about the nature of a real advantage, compromising their ability to make a predetermined decision and damaging the reputations of businesses. A cutting-edge interrogation department revealed that quantum machine learning (QML) could manage a huge amount of machine-trained data and could convey almost emotional choices in the context of inaccurate checks. It is truly beneficial in obtaining reviews for things that are incorrect. Opinion, generating trends, interpersonal relationships, and assessing fatigue is merely a few of the attributes. Tests conducted utilizing the Amazon fraudulent review. The dataset demonstrates that QML tactics outperform conventional knowledge acquisition procedures in errands, including the place of fraudulent reviews. The delicacy and tolerance of incorrect review distinguishing evidence can be significantly advanced, although QML is still in its early stages of development. Both our proposed model and model pass rigorous conventional machine learning algorithms testing with a remarkable level of accuracy. An article introduces a unique approach to fraudulent review detection and brings in the QNN algorithm as a solution. A deep learning model, such as this one, has an 86% accuracy rate in quantum computer implementation, which is an impressive level of innovation, especially if it comes with successful results. Involvement in these cutting-edge technologies promises significant benefits in battling the problem of false identities on the Web. In our case, the experimental results demonstrate that our QNN algorithm, which can accurately identify fake reviews, will become a key weapon for suppressing various forms of fraudulence on emerging digital technology platforms.
WSEAS Transactions on Mathematics, 2024
The initiative of this paper is to present the Runge Kutta Type technique for the development of ... more The initiative of this paper is to present the Runge Kutta Type technique for the development of mathematical solutions to the problems concerning to ordinary differential equation of order six of structure v'''' = f (u, v, v′) denoted as RKSD with initial conditions. The three and four stage Runge-Kutta methods with order conditions up to order seven (RKSD7) have been designed to evaluate global and local truncated errors for the ordinary differential equation of order six. The framework and evaluation of equations with their results are well established to obtain the effectiveness of RK method towards implicit function satisfying the required initial conditions and for obtaining zero-stability of RKSD7 in terms of their accuracy with maximum precision under minimal processing.
BMC Research Notes, 2023
Objective In this paper, we develop a new root-finding algorithm to solve the given non-linear eq... more Objective In this paper, we develop a new root-finding algorithm to solve the given non-linear equations. The proposed root-finding algorithm is based on the exponential method. This algorithm is derivative-free and converges fast. Results Several numerical examples are presented to illustrate and validation of the proposed methods. Microsoft Excel and Maple implementation of the proposed algorithm is presented with sample computations.
F1000Research, 2023
Background: In this paper, we focus on an efficient and easy method for solving the given system ... more Background: In this paper, we focus on an efficient and easy method for solving the given system of differential-algebraic equations (DAEs) of second order.
Methods: The approximate solutions are computed rapidly and efficiently with the help of a semi-analytical method known as Adomian decomposition method (ADM). The logic of this method is simple and straightforward to understand.
Results: To demonstrate the proposed method, we presented several examples and the computations are compared with the exact solutions to show the efficient. One can employ this logic to different mathematical software tools such as Maple, SCILab, Mathematica, NCAlgebra, Matlab etc. for the problems in real life applications.
Conclusions: In this paper, we offered a method for solving the given system of second-order nonlinear DAEs with aid of the ADM. We shown that the proposed method is simple and efficient, also one can obtain the approximate solutions quickly using this method. A couple of examples are discussed for illustrating this method and graphical and mathematical assessments are discussed with the analytical solutions of the given problems.
Information Sciences Letters, 2023
In this paper, we present a three-dimensional numerical analysis of friction stir welding on an a... more In this paper, we present a three-dimensional numerical analysis of friction stir welding on an alumunium butt joint. A thin sheet of aluminum marking material was embedded into the 6061-aluminum alloy panel and its rear weld path. The positions after friction stir welding were investigated by metallographic techniques. Looking at the visualized material flow pattern, a three-dimensional model was developed to numerically simulate the temperature profile and plastic effects. The calculated velocity profile for plastic flow in the immediate vicinity of the tool generally agrees with the visualized results. Increasing the tool speed while maintaining a constant tool feed rate increases the material flow near the pin. The shape and size of the predicted weld zone match the experimentally measured ones.
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Papers by Dr. Srinivasarao Thota
Methods: The approximate solutions are computed rapidly and efficiently with the help of a semi-analytical method known as Adomian decomposition method (ADM). The logic of this method is simple and straightforward to understand.
Results: To demonstrate the proposed method, we presented several examples and the computations are compared with the exact solutions to show the efficient. One can employ this logic to different mathematical software tools such as Maple, SCILab, Mathematica, NCAlgebra, Matlab etc. for the problems in real life applications.
Conclusions: In this paper, we offered a method for solving the given system of second-order nonlinear DAEs with aid of the ADM. We shown that the proposed method is simple and efficient, also one can obtain the approximate solutions quickly using this method. A couple of examples are discussed for illustrating this method and graphical and mathematical assessments are discussed with the analytical solutions of the given problems.