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Dynamical analysis of fractional yellow fever virus model with efficient numerical approach
In this paper, we have projected the theoretical and numerical investigation of the mathematical model representing the yellow fever virus transmission from infected mosquitoes to humans or vise-versa through mosquito bites in the framework of the Caputo derivative. Theoretical aspects of the dynamics of susceptible individuals, exposed individuals, infected individuals, toxic infected individuals, recovered and immune individuals, and susceptible mosquitoes and infected mosquitoes have been analyzed by using the theory of fractional calculus such as boundedness, uniqueness and existence of the solutions. Sufficient conditions for the global stability of the virus-free point of equilibrium are inspected. T validate the theoretical results numerical analysis is performed using the generalized Adams-Bashforth-Moultan method. 2023, Eudoxus Press, LLC. All rights reserved. -
Dynamics of a fractional epidemiological model with disease infection in both the populations
In order to depict a situation of possible spread of infection from prey to predator, a fractional-order model is developed and its dynamics is surveyed in terms of boundedness, uniqueness, and existence of the solutions. We introduce several threshold parameters to analyze various points of equilibrium of the projected model, and in terms of these threshold parameters, we have derived some conditions for the stability of these equilibrium points. Global stability of axial, predator-extinct, and disease-free equilibrium points are investigated. Novelty of this model is that fractional derivative is incorporated in a system where susceptible predators get the infection from preys while predating as well as from infected predators and both infected preys and predators do not reproduce. The occurrences of transcritical bifurcation for the proposed model are investigated. By finding the basic reproduction number, we have investigated whether the disease will become prevalent in the environment. We have shown that the predation of more number of diseased preys allows us to eliminate the disease from the environment, otherwise the disease would have remained endemic within the prey population. We notice that the fractional-order derivative has a balancing impact and it assists in administering the co-existence among susceptible prey, infected prey, susceptible predator, and infected predator populations. Numerical computations are conducted to strengthen the theoretical findings. 2021 Author(s). -
Fractional Approach for Belousov-Zhabotinsky Reactions Model with Unified Technique
The Belousov-Zhabotinsky reaction model represents chemical oscillators that exhibit periodic vibrations as a result of complex physic-chemical phenomena. The non-linear behaviour exhibited by Belousov-Zhabotinsky model is the cause of Turing patterns, birth of spiral waves, rise of limit cycle attractors, and deterministic chaos in many chemical reaction processes. Due to these noteworthy characteristics, in this paper, we have analyzed mathematical Belousov-Zhabotinsky model by a novel numerical approach q-Homotopy analysis transformation method. To interpret new observations, we have incorporated Caputo fractional derivative in the model. The numerical result are presented graphically and concerning the absolute error of solutions. With the help of the homotopy parameter curve, we have projected the convergence region with reference to diverse values of fractional derivative. This work establishes that the projected numerical algorithm is a well-organized tool to analyze the multifaceted coupled partial differential equation representing Belousov-Zhabotinsky type reactions. 2024 NSP Natural Sciences Publishing Cor. -
Laguerre polynomial-based operational matrix of integration for solving fractional differential equations with non-singular kernel
The Atangana-Baleanu derivative and the Laguerre polynomial are used in this analysis to define a new computational technique for solving fractional differential equations. To serve this purpose, we have derived the operational matrices of fractional integration and fractional integro-differentiation via Laguerre polynomials. Using the derived operational matrices and collocation points, we reduce the fractional differential equations to a system of linear or nonlinear algebraic equations. For the error of the operational matrix of the fractional integration, an error bound is derived. To illustrate the accuracy and the reliability of the projected algorithm, numerical simulation is presented, and the nature of attained results is captured in diverse order. Finally, the achieved consequences enlighten that the solutions obtained by the proposed scheme give better convergence to the actual solution than the results available in the literature. 2021 The Author(s). -
Analysis of a Fractional Stage-Structured Model With CrowleyMartin Type Functional Response by Lagrange Polynomial Based Method
The dynamics of a stage-structured predator-prey system that replicates interactions between two densities of prey and predator populations were investigated in this work. The adult predator population and the juvenile predator are the two compartments that make up the predator population in the model. The predator relies on both prey and juvenile predator, which is another element of the paradigm that can be termed cannibalism. CrowleyMartin type functional denotes the nature of the interaction between prey and adult predators, while Holling type-I functional response denotes the nature of contact between juvenile and adult predators. The concept of memory is introduced in the form of the Caputo fractional derivative to reflect the complicated dynamics of interaction among the species. As a result, the model is able to incorporate all relevant historical information about the occurrence, from its inception to the desired time, into its calculations. We have also investigated the boundedness and existence and uniqueness of solutions to the proposed model. The condition of existence and stability of various points of equilibrium are investigated. The numerical simulations are performed by using the Lagrange polynomial-based method which is novel in the field of mathematical biology. Simulations have been accomplished to examine the significance of parameters related to cannibalism, the conversion rate from prey to adult predator, harvesting of an adult predator, and growth rate of juvenile predators on the overall behavior of the system. The noteworthy performance of the fractional operator on the anticipated predator-prey models dynamical behavior is well demonstrated by numerical results. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Dynamics of the Dadras-Momeni System in the Frame of the Caputo-Fabrizio Fractional Derivative
Investigation of chaos in dynamical systems is one of the most fascinating issues that has received a lot of attention across a variety of scientific domains. One such dynamical system which generates two, three, and four-scroll chaotic attractors with a single parameter change, is the novel Dadras-Momeni system. In this study, we have analyzed the Dadras-Momeni system in the frame of the Caputo-Fabrizio fractional derivative. Theoretical aspects such as boundedness, existence, and uniqueness of solutions are presented. A detailed analysis is presented regarding the stability of points of equilibrium. To regulate chaos in this fractional-order system with unpredictable dynamics, a sliding mode controller is developed and the global stability of the system with control law is established. Later, we introduced uncertainties and external disturbances to the controlled system, and the condition of global stability is derived. To perform numerical simulation we have identified certain values of the parameters where the system exhibits chaotic behavior. Then the theoretical claims about the influence of the controller on the system are established with the help of numerical simulations. 2023 Taylor & Francis Group, LLC. -
Unleashing economic potential: decoding the FDI-economic growth nexus in G-15 economies amidst unique host country traits
This study examined the impacts of ForeignDirectInvestment (FDI) on economic growth across top the five G-15 countries over a period of 33years, while considering the influence of key host country traits, namely macroeconomic stability, financial development, human capital, and trade openness. The selection of these variables was firmly supported by both theoretical foundations and empirical studies that highlight their significant role in shaping the FDIgrowth interconnection. Panel data derived from World Bank Indicators, spanning the period from 1989 to 2021, were analyzed using a feasible generalized least squares method (FGLS), a rigorous approach, including descriptive statistics, correlation analysis, cross-sectional dependence tests, unit root tests, and multiple regression models. By exploring the interconnection between FDI and the characteristics of the host country, this study sheds light on how these factors collectively contributed to economic growth in the G-15 economies. Descriptive statistics indicated a favorable trend in economic growth, with an average of 3.470 and a standard deviation of 4.289. Correlation analysis revealed significant positive relationships between Economic Growth and Gross Capital Formation, Human Capital, and Liquid Liabilities. Conversely, FDI, Inflation, and Trade Openness displayed insignificant positive correlations with Economic Growth. The findings also demonstrated that favorable host country traits magnified the impact of FDI on economic growth. Specifically, increased Financial Development, Human Capital, and Trade Openness enhanced the positive effects of FDI on economic growth. However, Inflation had a dampening effect on the growth factor. Policymakers in G-15 countries should give precedence to developing strong financial markets, promoting trade liberalization, and investing in human capital to optimize the advantages of FDI. This research addresses a critical gap in the literature as limited empirical work has been conducted on the FDIgrowth relationships specific to the G-15 economies, which hold substantial influence in the global investment landscape and showcase remarkable economic growth. By employing rigorous panel data methodology and a long-term dataset, we provides original insights into the interaction between FDI and host country characteristics, contributing to the existing body of knowledge. The Japan Section of the Regional Science Association International 2024. -
Calendar anomalies in the Indian stock markets: Monsoon effect
This paper deals with identifying the presence of monsoon effect in the Indian stock market using EGARCH model as well as the impact on the volatility of returns of the selected indices during the monsoon months in India. Daily time series data of closing price of four major indices i.e. Nifty 50, Nifty Smallcap 100, Nifty Midcap 100 and Nifty 500 over a period of sixteen years (April 2002 to March 2018) were collected and analysed. The results substantiate the fact that monsoon effect is present in the Indian equity market. The returns of Nifty 50 and Nifty 500 indices during the month of September were significantly higher. There was also a significant increase in the volatility during the month of September. No significant change was detected during the monsoon months for Midcap 100 and Nifty Smallcap 100. Monsoon effect was found in indices tracking top performing 50 stocks and 500 stocks listed in NSE. Hence, it can be inferred that monsoon effect is present in the Indian stock market. 2019, Allied Academies. -
An Intelligent Business Automation with Conversational Web Based Build Operate Transfer (BOT)
The field of AI chatbots with voice help capabilities has seen significant advancements recently because to the usage of NLP (Natural Language Processing), NLG (Natural Language Generation), and (DNN) Deep Neural Networks. Using the expanding skills of chatbots, which are assisted by AI and ML technologies, a variety of business challenges may be handled. Profitability is one of the most crucial features of a business. This is only achievable if top-level management is aware of the company's costs, revenues, and human resource performance. In this case, an AI-powered chatbot with voice help may be utilised to evaluate corporate data and provide a report. The Bot knows the meaning of words and responds to them thanks to the wordnet in the corpus. Corpus is basically a dictionary for ChatBot. Top management may ask the Bot anything, and the Bot will quickly undertake exploratory data analysis and create a report. The Bot first understands the data using feature selection and then performs exploratory data analysis. After the EDA technique, Bot activates the voice recognition mode to understand the question and give answers. The Bot can use a male or female voice (depending on the developer). Then BOT provides a data table and visualisations for better understanding. 2020 Copyright for this paper by its authors. -
An Intelligent Stock Market Automation with Conversational Web Based Build Operate Transfer (BOT)
Zerodha, Upstox, Angel Broking, Groww, etc. Such companies have the most significant users of traders/investors in the equity share market. Their trust is based on their ease of use, less time-consuming process, and accurate graphs and charts of real-Time data. But what if such companies had an algorithm that could predict the future prices of any share? Not just based on historical data but also on sentimental data? This project aims to build a speech recognition chatbot like Alexa Google, which will use Recurring Neural Network-Long Short-Term Memory (RNNLSTM) and Natural Language Processing (NLP) to predict future intra-day prices. 2022 IEEE. -
Using service learning to fuel multi-disciplinary research in Indian HEIs: A novel approach
The current work proposes a novel approach that can allow Indian HEIs to offer service-learning-based curricula while enhancing the institutional research output. The proposed model suggests a unique linkage between existing volunteer and academic departments at institutions of higher education such that data already being generated through existing outreach programs can be utilised for meaningful social science research. The proposed model thus utilizes existing resources already available with an institution to bolster research output, enhances the institutional capacity to include a pedagogical approach with proven benefits, and facilitates institutional compliance with regulatory directives mandating the inclusion of Service-learning-based courses at UG and PG levels. 2024, IGI Global. All rights reserved. -
Importance of Genetic Model in Huntingtons Disease
Huntingtons disease (HD) is the first defect-mapped autosomal-dominant, progressive neurodegenerative disorder with a distinct phenotype found in 1983, which contributed to the concept of human genome project. Thus, the search for genetic defects pioneered various mapping and gene study technological prototypes that culminated in identification of distinct disorders. Huntingtons disease has many symptoms, including chorea and dystonia, incoordination, cognitive decline and dementia, and behavioral difficulties. This disease can manifest any time over the age of 30 years, with the first sign and symptom being behavioral changes, which might include lack of emotions, periods of aggression, excitement, and anger. HD duration varies, ranging from 10 to 25 years or more depending on the individual. It is caused by a single gene defect on chromosome number 4, wherein a person requires only a single copy of the defected gene to show the symptoms; that is, a person with parent with the HD gene has a 50% chance of suffering. The disease becomes prominent in a human being as a result of mutations in a gene called Huntington that is located on the p arm (short arm) of chromosome 4 (4p 16.3). This chapter discusses the genetic model of Huntingtons disease and its importance. An increase in the normal number of repeat CAG (cytosine, adenine, and guanine) segments, (i.e. > 35 CAG) is seen in the Huntington (HTT) mutation that causes the disease. The severity of the disease depends on the sized expansion (i.e. increasing CAG repeats will accelerate the age of onset of the disease). Continuing studies of genetic modifiers-genes whose natural polymorphic variation contribute to the alteration and development of the D gene-offers to open new gateways for early diagnosis by unlocking the biochemical changes that occur years before diagnosis, thereby providing validated target protein and pathways for rational therapeutic interventions. This is also added as a section in this chapter. 2025 selection and editorial matter, Sachchida Nand Rai, Sandeep Singh, Santosh Kumar Singh. -
A Hybrid Framework for Detecting Hallucinations in Large Language Model Outputs
With Large Language Models (LLMs) continuously growing, they are on a path to replace the search engines soon. No matter how powerful they get, there is a certain level of uncertainty because they tend to hallucinate. Hallucination here refers to generate factually incorrect data, this can include making up names, generating false links and fabricating stories. This makes it extremely difficult to trust large language models. Existing papers provide solutions which are either not monetarily feasible or lack capabilities to build a robust hallucination detector. This paper aims to build a low resource hallucination detector which combines multiple heuristic signals like semantic similarity, self-consistency, external grounding via Wikipedia, NER overlap, flexible numerical check and a quantized LLM Falcon-7b. This eliminates the need to train the model from scratch. Upon evaluating with an input dataset of 50 questions the model was able to achieve an accuracy of 88%. 2025 IEEE. -
AI-Driven Real-Time Decision Making at the Edge: Overcoming Latency, Bandwidth, and Scalability Challenges for Smarter Data-Intensive Applications in Healthcare, Manufacturing, and Smart Cities
Aim and Purpose: This chapter explores the crucial role of artificial intelligence (AI) in enabling real-time decision-making at the edge, particularly within data-intensive applications. It aims to identify and address fundamental challengessuch as latency, limited bandwidth, and scalabilitythat frequently hinder the efficient deployment of AI models near data sources. The objective is to propose a coherent and implementable framework to mitigate these obstacles, thereby facilitating the development of intelligent, responsive systems. The chapter emphasizes the transformative potential of edge AI across three key sectors: healthcare, manufacturing, and smart cities, illustrating how localized intelligence can enhance performance, efficiency, and autonomy in time-sensitive environments. Methodology: We adopt a comprehensive methodological approach that includes studying optimization techniques such as model compression, quantization, and distributed inference. Special attention is given to federated learning, which supports collaborative training without the need to transfer raw dataenhancing both privacy and scalability. The examination of edge-optimized hardware accelerators (e.g., NPUs, FPGAs) and streamlined software frameworks will highlight their role in overcoming processing bottlenecks and ensuring low-latency performance. Limitations: Despite the promise of edge AI, challenges persist. These include limited processing and energy resources, security vulnerabilities, and device heterogeneity. Managing updates and maintaining consistency across distributed systems complicate widespread implementation further. Applications and Novelty: This chapters novelty lies in its integrated focus on practical, real-world applications of edge AI in healthcare, manufacturing, and smart cities. By presenting targeted solutions to known constraints, it contributes a practical, implementation-ready perspective to the growing body of edge AI research. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
RL-Based Online Mutation Strategy Selection Techniques inDifferential Evolution: A Study
In recent years, reinforcement learning (RL)-based online mutation strategy selection techniques have emerged as a principled learning framework for balancing exploration and exploitation in Differential Evolution. Several state-of-the-art (SOTA) DE variants have been proposed that utilize online mutation strategy selection to improve the performance of the canonical DE algorithm. This paper presents a comprehensive review of such DE variants and studies multi-armed bandit formulations for online mutation strategy selection in DE. It systematically categorizes existing DE variants based on their utilization of RL algorithms. The Author(s) 2026. -
Use of popular paintings in advertising /
Western paintings are constantly been in multiple mediums used because of its high recall value; these paintings have had a huge impact on global advertisement by multiple companies to promote their products and services. These popular western paintings have been the source of inspiration for various reason, the age old classic paintings have been deconstructed analysed and meanings have derived. -
Vicarious Trauma in Law Students: Role of Gender, Personality, and Social Support
Law student trainees are exposed to trauma-related work which puts them at higher risk of being adversely affected by it. Since they are not directly related to the event, their distress goes unnoticed. The repetitive account of traumatic instances leads to traumatization of their own which is referred to as vicarious traumatization. The purpose of this paper was to delve into the degree to which the role of gender, personality, and social support impact law students vulnerability to vicarious trauma. For the current research, exploratory design was utilized. All one hundred and twenty participants were selected using purposive sampling. Self-report measures were employed to investigate social support, personality traits, and vicarious trauma in sixty male and sixty female law students. The results revealed that female law students and those law students who are high on Neuroticism and low on Extraversion are more vulnerable to experiencing vicarious trauma. Implications for trainees and educators are discussed and suggestions are provided for future research. 2021 International Journal of Criminal Justice Sciences. All Rights Reserved. -
Changing climate and its impacts on the dynamics of future malaria transmission over certain endemic regions in India
As climate change plays a major role in evaluating the malaria disease over India, it is highly relevant to assess the spatio-temporal variability of malaria transmission dynamics over different climatic zones in India using modelling studies. In this study, VECTRI (vector-borne disease community model of the International Centre for Theoretical Physics, Trieste) model is simulated to predict the future malaria transmission dynamics over four major climatological zones of India, forced with the different climatic parameters such as temperature and rainfall and non-climatic parameter such as population density. The climate data is obtained from multi model mean of different CMIP6 global climate models under the SSP5-8.5 scenario. Results indicate that there is an overall decrease in EIR (Entomological Inoculation Rate) values of 10 to 30% are seen over most of the Indian regions with an increase in temperature about 4 to 5C and rainfall about 10 to 40%, by end of the century (2080s) when compared with the baseline period (19852014). However, few exceptions are seen over few parts of western and peninsular region where increase in EIR values are seen. This decrease (increase) in EIR values which describes the intensity of malaria transmission is predominantly controlled by temperature and rainfall during summer (winter) monsoon seasons. Such results from the VECTRI model may be useful for policymakers towards various malaria disease control programs in India and this may provide a basis for climate change impact assessments on malaria risk at a regional scale. The Author(s) 2025. -
Optimal Disassembly Sequence Generation Using Tool Information Matrix
Just as the assembly sequence plays an important role in the early part of the product, the disassembly sequence plays an important part in the final stage of the product. The disassembly sequence determines how efficiently the product can be recycled or it can be disassembled for maintenance purposes. In this study, the disassembly sequence is generated using the Tool Information Matrix (TIM) and the contact relations. In this study the feasible sequences are generated using the TIM and contact relations, afterward, the time required is considered as a fitness equation for generating the optimal disassembly sequence. The proposed methodology is applied to 10-part crankshaft assembly to test the performance in generating the optimal disassembly sequences. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Impact of the Internet on Human Life a Data-Driven Analysis Using Machine Learning and Statistical Correlations
These days Internet is became an essential part of human life and affects various domains which includes education, business, social interactions, mental health. It pushes the society ahead through increasing innovations, amplifying learning techniques, connecting people across the globe and access to vast resources which makes it a valuable tool in this modern society. But it comes with problems such as Internet addiction, sleeping disorders, health complications. This abstract discusses about dual impact of Internet uses, focusing on its significant benefits and possible dangers. Hence, there is need to manage use of Internet so one can make use of its benefits at the same time reducing the affects which are caused by Internet on human life. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.