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An AI-Driven Framework for Computational Literary Analysis: Bridging English Literature and Technology
Artificial Intelligence is emerging to be significantly used in the field of digital humanities, yet the focus of achieving interpretability and predictive level of performance simultaneously in the field of literary analysis is challenging. This paper highlights the study of a newly proposed effective model that is the Interpretable and Pedagogical Artificial Intelligence Framework (IPAF), a novel model that is designed for the analysis of poetry, prose and drama, while suitable outputs are provided by the model that are explainable in the field of education and literature research. The traditional models, such as the Random Forest, XG Boost and the Light BGM model, were used as base learners and have been integrated into the IPAF model by using Term Frequency-Inverse Document Frequency (TF-IDF) and the BERT embedding towards feature-level representations. The evaluation of this framework is carried out by utilising standard levels of classification metrics such as precision, accuracy level, F1 score and the SHAP-based explainability, which is applied for identifying the significant features of text that are influencing predictions. The results show that the IPAF model significantly outperforms the existing baseline models, by achieving a model with high accuracy, stability and robustness, that provides actionable insights towards educators and literary researchers. The interpretability of the framework allows users towards linking the computational outputs of the model alongside stylistic and theme-based patterns, by bridging the need for qualitative analysis along critical understanding of the literature. The future scope of the work extends the IPAF model to explore multi-modal levels of literary analysis by integrating data for audio, text and image together for digital archives for the further enhancement of cross-genre interpretation and applications of pedagogy. 2025 IEEE. -
Next Gen Text Mining in English Literature: A Machine Learning Approach for Narrative and Stylistic Analysis
This paper presents a research work that is novel in nature, based on a new machine learning framework that focuses on a computational analysis in the field of English literature. This research uniquely aims at focusing on an intersection based on stylistic patterns and narrative structures. The newly proposed model is termed the 'Next Gen Text Mining Framework', which leverages transformer-based models (such as GPT, BERT), along with sentiment trajectory-based modeling, network analysis, and clustering algorithms for extracting stylistic features and latent semantics from the text on a large scale. A meticulously used re-processing type pipelining framework modifies and prepares the data for the model ingestion. The multi-modal approach used in this framework enables the experimental analysis of different models across various diverse corpora in the literature that demonstrate stability, superior accuracy, and robustness when compared to the traditional models, in tasks like the authorship attribution, sentimental trajectory mapping, and the theme-based classification. The proposed framework bridges the gap between distant and close reading practices, enhancing the pedagogically based engagements and translating the computational insights into interpretative forms for research and teaching. This research highlights a scalable and replicable framework model that is a transformative tool when a large-scale inquiry in literature is considered and sets a foundation towards multi-modal, future, cross-lingual, and multidisciplinary-based applications. 2025 IEEE. -
Identity and access management for IOT devices
Identity and Access Management (IAM) for Internet of Things (IoT) devices is crucial in safeguarding the security and integrity of interconnected systems. This critical analysis explores the unique challenges and solutions associated with IAM in the context of IoT environments. IoT devices, characterized by their diverse types and widespread deployment, present significant complexities in managing identities and controlling access. Traditional IAM frameworks often fall short when applied to the dynamic and distributed nature of IoT networks, where devices frequently interact autonomously and may lack standardization. The analysis identifies key issues such as scalability, interoperability, and real-time authentication. It highlights the need for advanced IAM solutions that can handle the vast number of devices, support diverse protocols, and ensure robust security measures. Emerging technologies, including blockchain and AI-driven authentication, offer promising avenues for enhancing IAM in IoT contexts. Blockchain can provide decentralized, tamper-proof identity management, while AI can enhance real-time threat detection and adaptive access control. The review underscores the importance of developing IAM frameworks that are both flexible and scalable to address the evolving security requirements of IoT environments. By addressing these challenges, organizations can better secure their IoT infrastructure and mitigate risks associated with unauthorized access and identity breaches. 2026 Elsevier Inc. All rights reserved.. -
Review on microbially synthesized nanoparticles: a potent biocontrol agent against Aedes species of mosquito
Aedes aegypti is a principal vector of dengue, chikungunya and Zika illnesses worldwide. Because effective vaccinations or medications for the prevention and/or treatment for these illnesses are not available, vector management has been embraced as the primary method of reducing their transmission. The strategy that is often used for controlling Aedes populations is chemical insecticides; however, despite their efficiency, extensive usage of these pesticides has resulted in high operating costs, the establishment of resistant populations and undesirable non-target impacts. Therefore, the use of nanoparticles derived from multiple synthesis processes as new insecticides has recently attracted the interest of researchers. This study provides an overview of the current understanding concerning the method of action of nanoparticles against mosquitoes. Metal nanoparticles strongly influence antioxidant and detoxifying enzymes in insects, causing oxidative stress and cell death. These nanoparticles similarly inhibited acetylcholinesterase activity. Metal-based nanoparticles can potentially bind to S and P units in proteins and nucleic acids respectively resulting in decreased membrane permeability, organelle and enzyme denaturation which leads to cell death. Furthermore, they upregulate and downregulate critical insect genes, lower protein synthesis and gonadotrophin release, resulting in developmental and reproductive failure. This review critically examines insect nanotoxicology research trends and highlights the ecotoxicological effects of practical usage of nanoparticles as insecticides. 2022 World Research Association. All rights reserved. -
Influence of gravity modulation on the initiation of Rayleigh-Bard convection in ferro-nanofluids
The study investigates the influence of sinusoidal (sine wave) and non-sinusoidal (square wave, triangular wave, and sawtooth wave) gravity modulation on Rayleigh-Bard Convection in ferro-nanofluids (FNF) using both linear and nonlinear stability analyses. Controlled fluid systems are important in application situations, and hence, we have considered gravity modulation approach to control. The linear analysis based on the Venezian method is performed to determine the Rayleigh number of the problem, while the nonlinear analysis is carried out by solving the non-autonomous Lorenz equations to evaluate the heat transfer coefficient through the Nusselt number. Free-free and rigid-rigid boundary conditions for both upper and lower plates are considered along with isothermal and iso-nano concentration conditions. The purpose of the present study is to investigate the influence of initiation of convection and heat transfer in FNFs. This research focuses on analyzing the effects of various dimensionless parameters on the onset of convection and heat transfer. The results indicate that the magnetization parameters destabilize the system and enhance heat transfer. Among the four wave forms considered, square wave gravity modulation is found to facilitate greater heat transport compared to other forms of gravity modulation. In addition, the presence of ferro-nanoparticles advances the initiation of convection and enhances heat transfer. The novelty of this study lies in analyzing unconsidered aspects of gravity modulation, together with magnetic effects and nanoparticles, on the onset of convection and heat transfer in FNFs using both linear and nonlinear stability approaches. 2025 Author(s). -
POST-LISTING PRICING PERFORMANCE OF INITIAL PUBLIC OFFERS: INSIGHTS FROM INDIA
The objective of this study is to investigate short-run performance and whether the IPOs are over-priced or under-priced in various window periods. This study applies one-sample t-tests, capital asset pricing models, and market-adjusted excess return to quantify the short-term pricing performance as well as the risk and return of initial public offerings and market indices. The study investigates the claim that post-listing initial public offerings (IPOs) guarantee short-term gains. The twelve months following the listing, in particular, have seen the biggest gains. According to reports, investors who buy shares in IPOs get strong returns in this period. The market-adjusted initial returns for the IPOs registered on the National Stock Exchange between January 2019 and December 2020 have been found to be roughly 44%, per this analysis. 2024 Published by Faculty of Engineering. -
Exploring the use of mobile phones by children with intellectual disabilities: experiences from Haryana, India
Purpose: Covid-induced lockdowns have increased the importance of technology in education. Though access to technology as well as availability of the internet remain a major concern for a lot of children in the global south, children with intellectual disabilities are disadvantaged even more as most of the e-content is developed keeping in mind the average learner. Materials and methods: Unstructured interviews were conducted with children with intellectual disabilities studying in government schools in Haryana as well as their teachers and parents. Thematic analysis of the interviews was conducted to understand the use-patterns of mobile phones by children with intellectual disabilities. Results: Findings suggest that these children are learning to use mobile phones on their own or with some support and are able to navigate the complexities of these smartphones quite well. They use these devices mostly for their entertainment. This paper then reflects on the need and strategies to develop these technologies in ways that they can be used as effective tools for teaching children with intellectual disabilities, especially in the inclusive education system in developing countries. Conclusion: The paper reflects on the need to develop technology and tools using flexible and exploratory designs to enhance the learning processes for children with intellectual disabilities from the lower income strata.IMPLICATIONS FOR REHABILITATION This study highlights the importance of being able to use mobile phones by children with intellectual disabilities belonging to low income families. Following this, the article argues for designing of mobile phones suitable for use by children with intellectual disabilities using playfulness and explorations, and Building e-content keeping the elements of playfulness and exploration which can enhance the learnings of this group of students which is often ignored. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Data- Driven Insights for Decision- Making in the Stock Market by Using Meta- Analyses
The stock market structure is complex, dynamic, and continually evolving. This makes it harder for investors to make smart decisions. Using data-driven insights to inform investment decisions has become increasingly prevalent in recent years. This research study focused on two main parameters: investors behavioral biases and initial public offering (IPO) pricing. Forty-five past studies from 2010 to 2022 were analyzed using meta-analyses. The study initially delves into the difficulties investors face in choosing suitable stock market investments. It then covers the various types of data that are available to investors. The paper proceeds to examine the techniques for analyzing stock market data. Finally, the article concludes by discussing the advantages of implementing data-based insights in investment decision-making. 2025 CRC Press. -
Design of Grovers Algorithm over 2, 3 and 4-Qubit Systems in Quantum Programming Studio
In this paper, we design and analyse the Circuit for Grovers Quantum Search Algorithm on 2, 3 and 4-qubit systems, in terms of number of gates, representation of state vectors and measurement probability for the state vectors. We designed, examined and simulated the quantum circuit on IBM Q platform using Quantum Programming Studio. We present the theoretical implementation of the search algorithm on different qubit systems. We observe that our circuit design for 2 and 4-qubit systems are precise and do not introduce any error while experiencing a small error to our design of 3-qubit quantum system. 2022 Polish Academy of Sciences. All rights reserved. -
A collaborative defense protocol against collaborative attacks in wireless mesh networks
Wireless mesh network is an evolving next generation multi-hop broadband wireless technology. Collaborative attacks are more severe at the transport layer of such networks where the transmission control protocol's three-way handshake process is affected with the intention to bring the network down by denying its services. In this paper, we propose a novel collaborative defense protocol (CDP) which uses a handshake-based verification process and a collaborative flood detection and reaction process to effectively carry out the defense. This protocol presents a group of monitors that collaboratively entail in defending the attack; thus reduces the burden on a single monitor. Moreover, this paper proposes a novel transport layer post-connection flooding attack that occurs after establishing a TCP connection and we show that CDP can detect and mitigate this attack. The CDP protocol has been implemented in Java and its performance has been evaluated using essential metrics. We show that CDP is efficient and reliable and it can identify the attack before any major damage has occurred. Copyright 2021 Inderscience Enterprises Ltd. -
Iodine promoted synthesis of pyrido[2?,1?:2,3]imidazo[4,5-c]quinoline derivatives via oxidative decarboxylation of phenylacetic acid
An unprecedented and efficient molecular iodine promoted domino protocol for the synthesis of N polycyclic pyrido[2?,1?:2,3]imidazo[4,5-c]quinolines were reported from phenylacetic acid and 2-(imidazoheteroaryl)anilines. This methodology was also extended for the preparation of benzo[4?,5?]thiazolo [2?,3?:2,3]imidazo[4,5-c]isoquinolines in good yields. However, this protocol proceeds via a sequential decarboxylation of phenylacetic acid with I2/DMSO system followed by Pictet-Spengler cyclization in good yields. 2022 Taylor & Francis Group, LLC. -
Iodine Mediated Oxidative Cross-Coupling of Benzo[d]Imidazo[2,1-b]Thiazoles with Ethylbenzene: An Unprecedented Approach of C3-Dicarbonylation
A versatile approach of iodine mediated C3-dicarbonylation of benzo[d]imidazo[2,1-b]thiazoles (IBTs) with ethylbenzene has been reported. The reaction conditions were optimized by screening in various solvents, catalysts, and oxidants. The reaction is compatible with various substrates and was successfully demonstrated to offer moderate to good yields. 2022 Taylor & Francis Group, LLC. -
Engineering CoMn2O? nanofibers: Enhancing one-dimensional electrode materials for high-performance supercapacitors
One-dimensional CoMn2O4 nanofibers were developed via the electrospinning method, offers a novel approach for designing electrode materials for energy storage device -supercapacitors. Field emission scanning electron microscopy (FESEM) with EDX confirmed the highly porous CoMn2O4 phase with desired composition. Elemental mapping studies confirmed uniform distribution of Co, Mn, and O elements throughout the nanofibers.Electrochemical studies underscored the crucial role of structural voids and spacing in enhancing energy storage capacity, establishing CoMn2O4 as a promising electrode material. Specific energy and power studies yielded remarkable results of 93.84 Whr/kg and 55.20 kW/kg, respectively. Additionally, specific capacitance determination returned 937.42 F/g, indicating exceptional charging and discharging performance over 1000 cycles with 93.3 % capacitance retention. Moreover, the flexible symmetric supercapacitor is expected to demonstrate exceptional flexibility and electrochemical stability, achieving a specific energy of 232 Wh/kg and a specific power of 84 kW/kg at a current density of 1 mA/cm. These findings advance our understanding of CoMn2O4 nanofibers and offer insights into developing efficient and stable energy storage systems for diverse applications. 2025 Elsevier B.V. -
One dimensional NiMn2O4 nanofibrous architectures for symmetric supercapacitor device
In this study, NiMn2O4 nanofibers are synthesized using an electrospinning method. The NiMn2O4 nanofiber films, coated on stainless-steel substrates, are electrochemically characterized in different electrolytes, including KCl, KOH, NaOH, and Na2SO4. The study explores how the choice of electrolyte influences the specific capacitance, galvanostatic charge-discharge behavior, cycle stability, and capacitance retention of the NiMn2O4 nanofiber electrodes. NiMn2O4 electrodes in KOH exhibit superior performance at a scan rate of 5 mV/s, with an areal capacitance of 2125 F/g. The higher capacitance in KOH is attributed to its high ionic conductivity and efficient ion mobility. Additionally, the NiMn2O4 nanofiber electrodes demonstrate excellent cycle stability, with 76.38 % capacitance retention in 1 M KOH. These results suggest that 1D NiMn2O4 nanofiber electrodes deliver superior electrochemical performance in KOH compared to other aqueous electrolytes, highlighting their potential for future electrochemical energy storage applications. Furthermore, the flexible symmetric supercapacitor device shows excellent flexibility and electrochemical stability, with specific energy of 660 Wh/kg and specific power of 140 kW/kg obtained at a current density of 2 mA/cm2. These findings indicate that 1D NiMn2O4 nanofibers, particularly in 1 M KOH, are promising candidates for high-performance supercapacitor applications, paving the way for advancements in electrochemical energy storage devices. 2025 Elsevier B.V. -
Engineering CoMn2O? nanofibers: Enhancing one-dimensional electrode materials for high-performance supercapacitors
One-dimensional CoMn2O4 nanofibers were developed via the electrospinning method, offers a novel approach for designing electrode materials for energy storage device -supercapacitors. Field emission scanning electron microscopy (FESEM) with EDX confirmed the highly porous CoMn2O4 phase with desired composition. Elemental mapping studies confirmed uniform distribution of Co, Mn, and O elements throughout the nanofibers.Electrochemical studies underscored the crucial role of structural voids and spacing in enhancing energy storage capacity, establishing CoMn2O4 as a promising electrode material. Specific energy and power studies yielded remarkable results of 93.84 Whr/kg and 55.20 kW/kg, respectively. Additionally, specific capacitance determination returned 937.42 F/g, indicating exceptional charging and discharging performance over 1000 cycles with 93.3 % capacitance retention. Moreover, the flexible symmetric supercapacitor is expected to demonstrate exceptional flexibility and electrochemical stability, achieving a specific energy of 232 Wh/kg and a specific power of 84 kW/kg at a current density of 1 mA/cm. These findings advance our understanding of CoMn2O4 nanofibers and offer insights into developing efficient and stable energy storage systems for diverse applications. 2025 Elsevier B.V. -
Study of Transport Characteristics using Impedance Spectroscopy and Memristor Property Analysis of Protonated Polyaniline-WO3 Nanocomposite
Polyaniline-WO3 nanocomposite was synthesized through in-situ chemical polymerization. The structural properties are studied by using XRD and FESEM characterization. The XRD results confirmed the presence of crystalline WO3 nanoparticles in the polymer nanocomposite structure. FESEM images confirmed the sheet-like structure with heterojunction of WO3 nanoparticles and polyaniline matrix. The transport properties of the synthesized nanocomposites are studied using impedance spectroscopy analysis. The complex impedance analysis conducted using the Nyquist plot and equivalent circuit model of the nanocomposites are simulated using ZSimpWin software. The major conduction mechanism in the material is found to be grain boundary effect and the grain boundary conduction parameters are calculated. The polyaniline-WO3 nanocomposite with WO3 doping concentration of 15% has exhibited better sensing characteristics towards the target VOC (Volatile Organic Compound) 3-Carene, a breath-based biomarker for malaria. The memristor sensor model of the polyaniline nanocomposite with 15% of WO3 is simulated using MATLAB-Simulink. The pinched hysteresis loop obtained confirmed the memristor properties of the material. 2022, Universiti Malaysia Perlis. All rights reserved. -
Exploring the Nexus: An in-depth analysis of brand activism's influence on consumer behaviour
This study delves into the intricate relationship between brand activism and consumer behavior, aiming to unravel the nuanced dynamics that underlie contemporary market influences. Employing a comprehensive analysis, the authors investigate how brands' engagement with social and environmental causes resonates with consumers, shaping their attitudes, preferences, and ultimately, their purchasing decisions. The research employs a multi-faceted approach, combining qualitative and quantitative methodologies to capture the depth and breadth of brand activism's impact. By examining real-world examples and conducting surveys, the authors seek to discern patterns and correlations that illuminate the mechanisms through which brand activism leaves an indelible mark on the modern consumer landscape. The findings promise to provide valuable insights for marketers, businesses, and scholars alike, offering a deeper understanding of the evolving interplay between corporate values, social responsibility, and consumer choices in today's dynamic marketplace. 2024, IGI Global. All rights reserved. -
Testing for the Bidirectional Relationship Between FDI in Services and Trade in Services: Evidence from Emerging Economies
We examine the two-way links between foreign direct investments (FDI) in services and trade in services for 26 emerging economies from 2003 to 2015 using sectoral and sectoral disaggregated FDI data. Within a multivariate framework, we use panel unit root tests, recently developed heterogeneous panel cointegration and panel vector error correction model (VECM). Our results confirmed the cointegrating relationship between trade in services, FDI in services, financial services FDI and nonfinancial services FDI. We find the existence of long-run unidirectional causality from trade in services to FDI in services. However, the disaggregated analysis shows a bidirectional link between nonfinancial services FDI and trade in services in the short run. Still, there is no causality between financial services FDI and trade in services both in the short run and long run. The result also shows the evidence of unidirectional causality running from trade in services to nonfinancial services FDI in the long run. It implies that sectoral decomposition matters in the FDItrade nexus in emerging economies. JEL Codes: G20, F14, G20, F23 2022 Indian Institute of Foreign Trade. -
Are the determinants of foreign direct investment the same within the service sector? Evidence from bootstrap based bias corrected fixed effects model
Using sectoral as well as subsectoral foreign direct investments (FDI) data, we explore the determinants of FDI in services at both sectoral and sub-sector levels of 25 emerging economies for the period 19992016. We employ a bootstrap-based bias-corrected fixed effects model to analyze whether FDI's determinants vary within the service sector. Our results show that market size, market potential, natural resources endowments, and agglomeration effects are positively associated with the FDI in services and its subsectoral levels. The sectoral disaggregated analysis shows that the variables that attract FDI in services do not vary much from financial to nonfinancial services. This study suggests that there is no need for a separate theory for explaining FDI determinants in financial and nonfinancial services though some modifications are to be made. Before making modifications, we have to consider the salient features of service sector FDI, such as intangibility, inseparability, perishability, heterogeneity, and commercial presence. 2021 John Wiley & Sons Ltd. -
AI-Enabled Brand-to-Generic Medication Recommendation System for Pharmacy: Addressing Consumer Brand-Name Bias
In countries like India, many people choose branded medicines over equally effective generic options, which drives up healthcare costs. This paper introduces a smart recommendation system that can tell whether a medication query is about a brand-name or a generic drug. It then offers more affordable alternatives based on the active ingredients. By using natural language processing and retrieval-augmented generation (RAG) with a detailed medicine database, the system accurately classifies and recommends options. Its conversational interface mimics a real pharmacy interaction, helping users make informed choices while saving money. Tests show the system responds quickly, usually within 7 seconds, and provides accurate answers over 80 % of the time for straightforward queries. Ultimately, this tool addresses the information gaps about generic drugs and branded ones and is easy to use for both consumers and pharmacists. 2026 IEEE.