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Fractional approach for mathematical model of phytoplankton-toxic phytoplankton-zooplankton system with Mittag-Leffler kernel
The solution for phytoplankton-toxic phytoplankton-zooplankton system with q-homotopy analysis transform method (q-HATM) is discussed. The projected system exemplifies three components (namely, zooplankton, toxic-phytoplankton as well as phytoplankton) and the corresponding nonlinear ordinary differential equations exemplify the zooplankton feeds on phytoplankton. The projected method is an amalgamation of q-homotopy analysis algorithm and Laplace transform and the derivative associated with the Atangana-Baleanu (AB) operator. The equilibrium points and stability have been discussed with the assistance of the Routh-Hurwitz rule in this work within the frame of generalized calculus. The fixed-point theorem is employed to present the existence and uniqueness of the attained result for the considered model, and we consider five different initial conditions for the projected system. Further, the physical nature of the achieved solution has been captured for fractional order, external force and diverse mass. The achieved consequences explicate that the proposed solution method is highly methodical, easy to implement and accurate to analyze the behavior of the nonlinear system relating to allied areas of science and technology. 2023 World Scientific Publishing Company. -
Fractional MooreGibsonThomson thermoelastic analysis of nonlocal nanobeams under moving heat source with machine learning-assisted predictive modeling
This study presents a comprehensive investigation of thermoelastic wave propagation in nonlocal nanobeams subjected to a moving heat source within the framework of fractional MooreGibsonThomson (MGT) heat conduction theory. The model incorporates nonlocal elasticity to capture size-dependent mechanical behavior and employs a fractional-order formulation to account for thermal memory and finite-speed heat propagation. The coupled governing equations are derived and solved analytically using Laplace transform techniques to obtain the temperature, displacement, and stress distributions. A detailed parametric analysis is performed to examine the effects of fractional order, nonlocal parameter, thermal relaxation time, and source velocity on the thermoelastic response. The results reveal significant modifications in wave attenuation, temperature evolution, and stress distribution due to the combined influence of nonlocality and fractional thermal effects, particularly under moving thermal loads. To enhance computational efficiency and enable rapid prediction of system responses, a machine learning-based surrogate framework is developed using an artificial neural network (ANN). The network is trained on data generated from the present analytical model and is shown to accurately predict thermoelastic fields across a wide range of governing parameters. The ANN predictions exhibit excellent agreement with analytical results, demonstrating its capability as a reliable reduced-order modeling tool. The proposed hybrid analyticalcomputational approach provides new insights into thermoelastic behavior at the nanoscale and offers an efficient predictive framework for heat transfer applications involving moving thermal loads. This study is motivated by the need to address unresolved challenges in modeling thermoelastic behavior at the nanoscale, particularly the simultaneous incorporation of fractional heat conduction, nonlocal elasticity, and moving thermal loads within a unified framework. 2026 Published by Elsevier Ltd. -
Fractional operator-based mathematical model for hydrological cycle analysis with machine learning integration
The most important natural resource for maintaining ecosystems, life, and human civilization is water. Climate patterns, hydrological processes, and energy balance are all impacted by the constant movement of water across different parts of the Earths climate system. A new mathematical model is proposed using a fractional order, and this study investigates the four main elements of the hydrological cycle: atmospheric water, rainfall, surface water, and groundwater. The model uses the Caputo fractional operator to account for memory effects and long-term dependencies in water dynamics. A thorough qualitative and quantitative study examines the systems boundedness, stability, existence, and uniqueness. The AdamsBashforthMoulton (ABM) approach is used for numerical simulations, and it shows improved accuracy, stability, and reduced error metrics compared to traditional methods. Furthermore, bifurcation analysis reveals the systems possible behavior. Data-driven parameter estimation and trend forecasting are achieved by integrating Machine Learning (ML) techniques like the random forest regressor to improve predictive capabilities. Visualization tools such as pair plots, box plots, bar plots, and correlation matrix examines the associations between variables. The suggested method provides a strong framework for hydrological cycle modeling, increasing forecasting accuracy for water resource dynamics and climate-driven hydrological changes. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Fractional p()-Kirchhoff Type Problems Involving Variable Exponent Logarithmic Nonlinearity
In this paper, we investigate a fractional p()-Kirchhoff type problem involving variable exponent logarithmic nonlinearity. With the help of the Nehari manifold approach, the existence and multiplicity of nontrivial weak solutions for the above problem are obtained. The main aspect and challenges of this paper are the presence of double non-local terms and logarithmic nonlinearity. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
Fractional ReactionDiffusion Model: An Efficient Computational Technique for Nonlinear Time-Fractional Schnakenberg Model
In this article, the q-homotopy analysis transform method (q-HATM) is committed to finding the solutions and analyzing the gathered results for the nonlinear fractional-order reactiondiffusion systems such as the fractional Schnakenberg model. These models are well known for the modelling of morphogen in developmental biology. The efficiency and reliability of the q-HATM, which is the proper mixture of Laplace transform and q-HAM, always keep it in a better position in comparison with many other analytical techniques. By choosing a precise value for the auxiliary parameter ?, one can modify the region of convergence of the series solution. In the current framework, the investigation of the Schnakenberg models is implemented with exciting results. The acquired results guarantee that the considered method is very satisfying and scrutinizes the complex nonlinear issues that arise in the arena of science and technology. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Fractional study of a novel hyper-chaotic model involving single non-linearity
The applications of hyperchaotic systems (HCSs) can be widely seen in diverse fields associated with engineering due to their complicated dynamics, randomness, and high delicacy and sensibility. In the present work, we aim to investigate a new hyper-chaotic system involving a single non-linearity under the fractional CaputoFabrizio (CF) derivative for the first time. In fact, there is no previous study using fractional derivatives in this system. A new mathematical system using a fractional-order operator will be designed with the novel operator. The CaputoFabrizio non-integer operator is aimed to be employed to capture complex nature. In order to solve the extracted dynamical system, a quadratic numerical scheme is applied. This study contains stability and convergence sections for the considered method. Moreover, numerical results of the problem under various values of fractional orders and different values of initial conditions (ICs) are provided to show the performance of the suggested scheme. Figures of solutions for each dependent variable can be observed. 2022 The Author(s) -
Fragile foundation: Tourism, culture, and environmental stability in Joshimath and Kedarnath
This study aims to explore the ecological and cultural challenges in the delicate ecosystems of Joshimath and Kedarnath. A mixed method approach was adopted. Primary data was collected through semi-structured interviews with 35 tourists to look at the perception of environmental degradation and cultural influences. Content analysis of secondary data, including media reports and academic articles add contextual insights to the issue. The findings suggest that overcrowding and rapid construction works are increasing the environmental instability in both the sites; leading to natural disasters like floods, landslides, avalanches, etc. The tourists are disappointed due to overcrowding, and the threats it brings to the cultural and natural heritage. The study, thus highlights the urgent need for responsible tourism and much stricter developmental control measures. This study highlights that without immediate interventions, these fragile ecosystems are left with the threat of suffering from irreversible damages infringing upon their environmental significance and cultural values. 2025, IGI Global Scientific Publishing. All rights reserved. -
Fragile freedoms and the decline of human rights in global democracies
Indias slide to 161 out of 180 countries in the 2023 Press Freedom Index by Reporters Without Borders (RSF) highlights mounting concerns about media suppression. Journalists critical of the government increasingly face defamation, sedition, and terrorism charges, creating a chilling effect on dissent. -
Fragile pillars of food security: exploring the challenges of availability, accessibility, and quality for global food regime; [Pilares freis da seguran alimentar: explorao dos desafios de disponibilidade, acessibilidade e qualidade para o regime alimentar global]
Hunger is a critical issue impacting a greater part of the world. Food distribution systems are failing millions of people, thereby leading to the crisis of food security. Various international declarations, like the UDHR and the ICESCR, have designated food and basic nutrition as integral elements of human rights. Therefore, provision for adequate and affordable food to all has become the dominant value for relevant regulatory and policy regimes. The problem is particularly sensitive to war-like events as is revealed by troubling statistics emerging against the backdrop of Covid-19, Russia-Ukraine War, and Israel-Hamas crisis. All these recent events have increased global food security concerns. This paper evaluates the fragile nature of food security in its multidisciplinary dimension. The methodology undertaken is a combination of quantitative and qualitative analytical mechanisms to explore the multidimensional issues of food insecurity. A systematic approach has been taken to identify food availability, food accessibility, food utilization, and environmental vulnerability as the intrinsic obstacles to any regulatory intervention. In this context, the paper analyses challenges to food accessibility as the core problem of right to food and food sovereignty regimes. It signifies the connection between the structural notion of accessibility and the legal concept of right to food through food sovereignty. It analyses the causal linkages between the problem of food security and other fundamental policy challenges, like poverty, unemployment, and social inequality. The international nature of the crisis is also manifested in the classic developed-developing nations divide. It, consequently, highlights the structural inefficiencies of the powerful international bodies, like the WTO, the World Bank, and the IMF. The comprehensive nature of the problem is explored through the idea of food sovereignty, which signifies the cultural sensitivity of food and nutrition. Food insecurity is not merely a productivity problem. The paper, therefore, suggests a consumer-centric model of food distribution and accessibility as an optimal and practical model for public policy and regulations. 2024 Centro Universitario de Brasilia. All rights reserved. -
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Frames of Isolation: A Reading Through HIV/AIDS Documentaries
The question is: how can a documentary create social impact on its audience and, in turn, on society? Film critics and social scientists have considered this question since the inception of documentary filmmaking. Moreover, in the context of disseminating knowledge about infectious diseases, particularly during the HIV/AIDS epidemic, documentaries played a significant role in educating the public about the disease. Following the epidemic, documentaries were used to understand the disease and to witness the lives of people living with the virus. This article further extends the discourse of documentary studies by critically analysing two specific HIV/AIDS documentaries, 5B (2018) and Desert Migration (2015). This analysis provides insight into how the frames of the moving image capture the isolated spaces occupied by people with HIV/AIDS. For this study, Edward Branigans concept of frames is adopted to explore the essence of isolation. This is achieved by examining frames captured by the filmmakers through the camera lens, with a focus on the immediate surroundings of the person being interviewed. The article terms these frames Frames of Isolation, as the images reflect the spatial and emotional isolation associated with the virus. 2025 House of the Book of Science. All rights reserved. -
Framework based on IoT, AI, and blockchain for smart access to government agricultural schemes
Agriculture plays an important part in most countries, such as India. A survey says that 54.6% of the total labor force of India is engaged in agriculture and its connected activities. The government is announcing many schemes to facilitate agriculture and support farmers. But most of the farmers are from poor families and are not able to reach the government schemes when they are really in need. Also, it is required to observe and measure the inter and intra-field variability in crops to enjoy the complete benefits of government schemes. This can be done with the advancements in the field of the Internet of Things. Information related to the impact of natural calamities on the agricultural field, malfunctions in the machinery used for cropping, yielding level, and health status of crops can be measured using the technology of IoT (Internet of Things) and analyzed using AI (Artificial Intelligence). Blockchain plays a critical role in replacing traditional means of data storage and exchanging agricultural data with a more trustworthy, immutable, transparent, and decentralized approach. By keeping all the transactions related to government schemes in blockchain, the possible crimes in the form of false data by the intermediate dealers acting between the farmers and the government can be addressed. This, in turn, allows useful government schemes to reach the farmer in time. We propose to develop a theoretical model using IoT, AI, and blockchain, which can assist the farmers in benefitting from the appropriate schemes announced by the government in time and achieving precise agriculture. 2024 Bentham Science Publishers. All rights reserved. -
Framework for a smart E-Procurement system for ship building
The research aims to improve the shipbuilding process by reducing the time required for building a vessel through adoption of lean in the procurement management process. The research identifies the AS-IS process for procurement, uses Value Stream Mapping to identify different actions, identifies the root causes for administrative lead time with the help of fish bone diagram and proposes a framework for e-procurement system. It was found that lack of proper communication and visibility between the processes can increase the lead time for purchase order creation for different materials. The use of a smart e-procurement system can improve the visibility of the process across various departments and with the suppliers. This can improve the efficiency of the shipbuilding process, reducing the time required for manufacturing a vessel. 2024 by IGI Global. All rights reserved. -
Framework for automatic examination paper generation system /
International Journal Of Computer Science And Technology, Vol.6, Issue 1, pp.128-130, ISSN No: 0976-8491 (Online) 2229-4333 (Pint). -
Framework for Controlling Interference and Power Consumption on Femto-Cells In-Wireless System
Utilization of femto-cells is one of the cost effective solution to increase the internal network connectivity and coverage. However, there are various impediment in achieving so which has caused a consistent research work evolving out with solution. Review of existing literature shows that maximum focus was given for energy problems in cellular network and not much on problems that roots out from interference. Therefore, the proposed system has presented a very simple and novel approach where the problems associated with interference and energy in using large groups of femto-cells are addressed. Adopting analytical research methodology, the proposed model offers on-demand utilization of the selective femto-cells on the basis of the traffic demands. The study outcome shows that proposed system offers better performance in contrast to existing approach. Springer Nature Switzerland AG 2019. -
Framework for proactive visualization of text based narrative using NLP
Language is an essential mode, not only for human communicationbut also for thinking. A story is conveyed or a report of an incident is being told, humans perceive the conveyed information in the form of visual insights. The increasing advancements in the field of artificial intelligence can help with the same in machines. This paper reflects on the internalization of stories from a cognitive perspective and outlines a scalable framework for supporting the visualization of narrative text data. This paper leverages natural language processing (NLP), probabilistic modelling of discourse knowledge, information extraction of narrative components (who, where, when, what) and the narrative visualization. The graphics knowledge base storage structure has been redesigned to obviate the necessity of having a larger database for all graphics entity. With the developed framework, any user can input unrestricted natural language for the dynamic generation of animated scenes. This provides users with direct visual output in response to their natural language input. This tool can potentially impact the way humans interact with computers and expand a completely new way of understanding conversations. 2020 IJSTR. -
Framework for Sustainable Energy Management using Smart Grid Panels Integrated with Machine Learning and IOT based Approach.
Maintaining a consistent supply of power is essential for the well-being of the economy, the public, and one's own health. The generation of energy, as well as its distribution, monitoring, and management, are all undergoing fundamental changes as a result of the implementation of a smart grid (SG), which is authorised to include communication technology and sensors into power systems. There are a lot of problems that need to be fixed before the interoperability of the smart grid can be determined. The integration of renewable energy sources and smart grid technology market size and energy management is a sustainable solution to the problem of energy demand management. The importance work quickly toward the development of an efficient Energy Management Model (EMM) that integrates smart grids and renewable energy sources. When it comes to the modelling of complex and non-linear data, machine learning (ML), Internet of Things (IoT) approaches often perform better than statistical models. So, utilizing a machine learning approach for the EMM is a good option since it simplifies the EMM by generating a single trained model to anticipate its performance characteristics across all conditions. This may be accomplished via the use of an EMM created using an ML method. It was recommended that a certain flexibility sample be used as a control mechanism for incursion into the smart grid. The outcomes of the experiment indicate that the demand-side management (DSM) device is more resistant to infiltration and is enough to lower the energy usage of the smart grid. 2024, Ismail Saritas. All rights reserved. -
Framework to analyze customer's feedback in smartphone industry using opinion mining
In the present age, cellular phones are the largest selling products in the world. Big Data Analytics is a method used for examining large and varied data, which we know as big data. Big data analytics is very useful for understanding the world of cellphone business. It is important to understand the requirements, demands, and opinions of the customer. Opinion Mining is getting more important than ever before, for performing analysis and forecasting customer behavior and preferences. This study proposes a framework about the key features of cellphones based on which, customers buy them and rate them accordingly. This research work also provides balanced and well researched reasons as to why few companies enjoy dominance in the market, while others do not make as much of an impact. 2018 Institute of Advanced Engineering and Science. All rights reserved. -
Framework to analyze customer's feedback in smartphone industry using opinion mining
In the present age cellular phones are the largest selling products in the world. Big Data Analytics is a method used for examining large and varied data, which we know as big data. Big data analytics is very useful for understanding the world of cellphone business. It is important to understand the requirements, demands, and opinions of the customer. Opinion Mining is getting more important than ever before, for performing analysis and forecasting customer behavior and preferences. This study proposes a framework about the key features of cellphones based on which, customers buy them and rate them accordingly. This research work also provides balanced and well researched reasons as to why few companies enjoy dominance in the market, while others do not make as much of an impact 2018 Institute of Advanced Engineering and Science. All rights resented. -
Framing and control for sustainability of industries
Purpose: The paper attempts to frame the challenge of managing the transition to a sustainable economy by way of a conceptual model consisting of a zero-footprint regulatory regime and a sustainability fund. Design/methodology/approach: A conceptual model of the sustainable industrial revolution has been developed based on the learnings from industries such as originators (mining), farming, pharmaceuticals, pesticides and chemicals and long-lasting artefacts against an overall perspective. Findings: It is suggested to have an institutional structural mechanism in place to ensure that footprint is minimized through recycling including refurbishing, resale or transformation. This includes management of recycling businesses through execution of a zero-waste regulatory regime that will build and use a sustainability fund. Research limitations/implications: The limitations of the paper are arising out of the topic being an issue of gigantic proportions with immense complexity. An attempt has been made to bring out the inescapability and the imperative of a sustainable industrial revolution. Practical implications: This paper presents practical aspects such as collusion between trash and recycling businesses, land use and social aspects of criticality of public support. If implemented, the suggested model can make a paradigm shift in the way firms, industry and governments can handle the challenge of sustainability. Originality/value: The value of this conceptual paper lies in an attempt to extend the learning organization framework to the concept of a regulatory model for sustainability that is not limited to the definition of a firm but stands extended to industries and to the economics, land use and demographics of the planet. 2021, Emerald Publishing Limited.