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Physical Unclonable Function and OAuth 2.0 Based Secure Authentication Scheme for Internet of Medical Things
With ubiquitous computing and penetration of high-speed data networks, the Internet of Medical Things (IoMT) has found widespread application. Digital healthcare helps medical professionals monitor patients and provide services remotely. With the increased adoption of IoMT comes an increased risk profile. Private and confidential medical data is gathered across various IoMT devices and transmitted to medical servers. Privacy breach or unauthorized access to personal medical data has far-reaching consequences. However, heterogeneity, limited computational resources, and lack of standardization in authentication schemes prevent a robust IoMT security framework. This paper introduces a secure lightweight authentication and authorization scheme. The use of the Physical Unclonable Function (PUF) reduces pressure on computational resources and establishes the authenticity of the IoMT. The use of OAuth 2.0 open standard for authorization allows interoperability between different vendors. The resilience of the model to impersonation and replay attacks is analyzed. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Zero Trust-Based Adaptive Authentication using Composite Attribute Set
Rapid evolution of internet-oriented applications has increased the threats to confidential data. Single-factor authentication approaches are no longer sufficient to ensure user credibility. Multi-factor authentication schemes are also not tamper-proof. A Zero Trust, adaptive authentication-based approach that uses the user's past behavior can offer protection in this scenario. This paper proposes a system that collects a composite attribute set that includes the user behavior, attributes of the application through which the user is requesting access, and the device used. The enhanced collection allows the creation of detailed context that allows granular variance calculation and risk score. 2021 IEEE. All Rights Reserved. -
A JSON Web Signature Based Adaptive Authentication Modality for Healthcare Applications
In the era of fast internet-centric systems, the importance of security cannot be stressed more. However, stringent and multiple layers of security measures tend to be a hindrance to usability. This even prompts users to bypass multi-factor authentication schemes recommended by enterprises. The need to balance security and usability gave rise to Adaptive authentication. This system of utilizing the user's behavioral context and earlier access patterns is gaining popularity. Continuously analyzing the user's request patterns and attributes against an established contextual profile helps maintain security while challenging the user only when required. This paper proposes an Open standards based authentication modality that can seamlessly integrate with an Adaptive Authentication system. The proposed authentication modality uses JavaScript Object Notation(JSON), JSON Web Signature(JWS) and supports a means of verifying the authenticity of the requesting client. The proposed authentication modality has been formally verified using Scyther and all the claims have been validated. 2022 IEEE. -
Portrayal of cricket in bollywood movies from 2011-2016 /
Movies and cricket are two of the big entertainment and revenue generating industries in India. The first feature film in India can be dated back to 1913 while cricket had its emergence in the 16th century itself. Cricket can also be seen in movies in recent years. This study focuses on films which were released between the years 2011 and 2016 which have depicted cricket in them. The study uses the Representation theory by Stuart Hall as a theoretical framework. -
Processor implemented method for watermarking and cyber protection of deep learning models /
Patent Number: 202141013761, Applicant: Dr. C Kailasanathan.
The present invention relates to processor implemented method for watermarking and cyber protection of deep learning models. The objective of the present invention is to solve the problems in the prior art related to technologies of cyber security in communication and processing of block chain data. -
An IOT based self phased analysis of adverse effects in covid recovered patients /
Patent Number: 2021101599, Applicant: Jasmine Selvakumari Jeya I. -
System method for crop and fertilizer recommendation through soil nutrient monitoring using cyber physical system and machine learning /
Patent Number: 202141022914, Applicant: Dr. Ajith Danti.
The present invention relates to system and Method for crop and fertilizer recommendation through soil nutrient monitoring using cyber physical system and machine learning. The objective of the present invention is to solve the problems in the prior art technologies of crop and fertilizer recommendation based on soil nutrient, soil type and agriculture field location. -
Mythistorical Construction of Divinity and Femininity in Early Mohiniyattam Manuals
The history of Indian classical dances has been shaped by nation-building ideologies that constructed a culturally sanctioned past. For Mohiniyattam, a classical dance from Kerala, dance manuals have constructed a religious and gendered narrative, often relying on myths to comprehend its fragmented history. This paper explores the mythistorical narratives in the dance manuals of four early Mohiniyattam practitioners: Kalamandalam Kalyanikutty Amma, Kalamandalam Sathyabhama, Dr. Kanak Rele, and Bharati Shivaji. Through textual analysis and contextual interpretation, we explain how mythistorical accounts of divinity and femininity shape the sociocultural and bodily dynamics of the performance and the performer. 2026 Taylor & Francis Group, LLC. -
Nature metaphors in Kalyanikutty Ammas Mohiniyattam body aesthetics
Mohiniyattam is a classical dance tradition from the state of Kerala in India, which is bestowed with a feminine identity. Scholars have theorised this feminine identity as self-enforced, constructed and regional. Unique to Mohiniyattam is the inherent relationship with nature. Nature association can be observed in the tradition of Kalamandalam Kalyanikutty Amma, one of the revivalists of Mohiniyattam. This paper will closely read the dance manual Mohiniyattam: Charithravum Aattaprakaaravum by Kalyanikutty Amma, focussing on Ammas use of nature metaphor for body movement. Dance theorist Sondra Fraleighs ideation of the lived and poetic body will be used to understand the experience and expression of nature as a movement quality. Further, Kavya Krishnas theorisation of gender performativity in Mohiniyattam and the discussions on regionality and naturality in movement will bring into effect an ecofeminist reading of Ammas dance aesthetics. This paper will also examine the metaphorical nomenclature that constructs nature as a feminine quality in the body movements and aesthetics of Mohiniyattam. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Nature metaphors in Kalyanikutty Ammas Mohiniyattam body aesthetics
Mohiniyattam is a classical dance tradition from the state of Kerala in India, which is bestowed with a feminine identity. Scholars have theorised this feminine identity as self-enforced, constructed and regional. Unique to Mohiniyattam is the inherent relationship with nature. Nature association can be observed in the tradition of Kalamandalam Kalyanikutty Amma, one of the revivalists of Mohiniyattam. This paper will closely read the dance manual Mohiniyattam: Charithravum Aattaprakaaravum by Kalyanikutty Amma, focussing on Ammas use of nature metaphor for body movement. Dance theorist Sondra Fraleighs ideation of the lived and poetic body will be used to understand the experience and expression of nature as a movement quality. Further, Kavya Krishnas theorisation of gender performativity in Mohiniyattam and the discussions on regionality and naturality in movement will bring into effect an ecofeminist reading of Ammas dance aesthetics. This paper will also examine the metaphorical nomenclature that constructs nature as a feminine quality in the body movements and aesthetics of Mohiniyattam. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Bridging the Rural Digital Divide: Machine-Learning-Driven Predictive Modeling of Digital Literacy Program Outcomes
The research project performed multiple regression model evaluations to assess how effective digital literacy schemes are in rural education settings. Training program achievements relied on predicted educational proficiency scores while program evaluation relied on both comprehensive participant demographic details and process training statistics. Our study examined numerous regression approaches from basic Linear Regression forms through advanced Random Forest and Gradient Boosting models and concluded with complex methods including Stacking and XGBoost. The research analyzed prediction accuracy and model explanatory power using Mean Squared Error (MSE) and Rsquared (R2) values during the evaluation process. Multiple feature applications were the best fit for the deterministic ensemble techniques which exhibited superior performance but alternatively different analytical models displayed stable prediction results. This research proposes educational method advancement through machine learning approaches capable of creating custom solutions targeting rural user requirements. This study delivers key information to stakeholders in its combined study of digital education enhancements and sophisticated learning evaluation data analysis techniques. 2025 IEEE. -
Bridging the Rural Digital Divide: Machine-Learning-Driven Predictive Modeling of Digital Literacy Program Outcomes
The research project performed multiple regression model evaluations to assess how effective digital literacy schemes are in rural education settings. Training program achievements relied on predicted educational proficiency scores while program evaluation relied on both comprehensive participant demographic details and process training statistics. Our study examined numerous regression approaches from basic Linear Regression forms through advanced Random Forest and Gradient Boosting models and concluded with complex methods including Stacking and XGBoost. The research analyzed prediction accuracy and model explanatory power using Mean Squared Error (MSE) and Rsquared (R2) values during the evaluation process. Multiple feature applications were the best fit for the deterministic ensemble techniques which exhibited superior performance but alternatively different analytical models displayed stable prediction results. This research proposes educational method advancement through machine learning approaches capable of creating custom solutions targeting rural user requirements. This study delivers key information to stakeholders in its combined study of digital education enhancements and sophisticated learning evaluation data analysis techniques. 2025 IEEE. -
Smart Autonomous Robot for Efficient Hospitality Service
The hospitality industry is constantly striving to deliver excellent guest experience in the form of timely service and quality food. However, increasing customer expectations have been challenging the industry in the form of workload management, the recruitment of skilled personnel, and the management of operating expenses. Faced with these challenges, companies are embracing state-of-the-art technologies, and mobile robots have been viewed as a potential solution. This paper presents the concept design of a state-of-the-art autonomous robot for food delivery in hospitality establishments. Inspired by robots such as Amazon's Kiva Robots, the robot uses camera modules, path finding algorithms, and sensors to navigate through dynamic spaces while avoiding furniture and moving guests. Unlike warehouse robots, restaurant robots need to learn to adapt to uncertain environments while maintaining the friendly ambiance. By automating routine tasks such as food delivery, the robot allows staff to focus on delivering personalized customer service. Its technical features consist of environmental monitoring camera modules, path-finding algorithm sensors for obstacles detection. It adapts to dynamic environmental conditions for efficiency and safety. Innovation increases operational efficiency, saves labor costs, and improves food quality. 2025 IEEE. -
Behind the Fallout: Environmental Strategy and Innovation Gone Awry
Innovation and environmental strategy play vital roles in addressing the issues of ecological preservation and sustainability. This chapter explores the complicated nature of these concepts, along with their benefits and risks. It also aims to uncover practical lessons from its identified failures. The chapter provides an overview of innovation and environmental strategy, emphasizing their importance in today's environmental and business landscapes. It also explores the central theme of the study: the failure of innovation and environmental strategy to address the challenges of sustainability. Secondly, the chapter explores the various causes of environmental strategy malfunctions. Through a combination of case studies and analysis, it is possible to learn about the common traps, such as poor execution and resource limitations. Thirdly, the chapter focuses on the relationship between innovation and the environment, shedding light on its potential and also the obstacles it encounters in case studies of unsuccessful approaches. The impact of regulation and environmental policy on corporate strategy is explored in the fourth section, which considers how such changes can affect existing approaches, offering practical insights through case studies. Next, the importance of collaboration and communication is emphasized, in which case studies show how poor stakeholder engagement can affect the outcome of an environmental strategy. The sixth section of the chapter tackles the technological issues that can arise when implementing an environmental strategy. It delves into the cases where technological obstacles have resulted in failures. Next, the effect of culture on environmental initiatives is explored. This shows how short-term thinking and resistance to change can either hinder or support initiatives. The eighth section focuses on improving environmental strategies. It offers suggestions on identifying and rectifying issues with such approaches, emphasizing the significance of learning from failures and continuous improvement. Finally, there is a summary of the chapter's findings and a comprehensive overview. This emphasizes how important it is to learn from failures in environmental approaches, offering suggestions for future research. 2026 selection and editorial matter, Sonal Trivedi, Balamurugan Balusamy, Krishnaraj Nagappan, Dinesh Krishnan Subramaniam and Daniel Arockiam; individual chapters, the contributors. All rights reserved. -
Provably Adaptive Trust Dynamics in Context-Aware Zero-Trust Systems: A Formal Framework for Continuous Verification
Zero-Trust (ZT) requires continuous, context-aware evaluation of authentication and authorization decisions. This paper introduces Zero-Trust Hybrid Adaptive Authentication (ZeTHAA), a continuous authentication and authorization framework integrating contextual attributes, authentication strength, behavioral evidence, and retry dynamics. ZeTHAA utilizes a probabilistic risk model and dual-policy thresholds to partition outcomes into allow, step-up, and block regions, enabling precise control over security-usability trade-offs. The system introduces a global admissibility predicate to distinguish hard violations from probabilistic soft violations. Attribute importance is dynamically derived from entropy and Beta-posterior distribution, enabling robust cold-start initialization and online recalibration. ZeTHAA presents a unified composite attack surface covering credential compromise, attribute forgery, and post-grant hijacking, modeling retry behavior with exponential risk escalation and temporal decay. A large-scale synthetic dataset capturing realistic authentication flows, adversarial and temporal patterns, was used to evaluate ZeTHAA against heuristic, logistic regression, random forest, XGBoost, and isolation forest baselines. ZeTHAA produced a more expressive risk distribution and significantly higher attack detection and efficiency while minimizing user friction. ZeTHAA outperformed baseline models, with Recall and Area Under the Curve (AUC) exceeding 79% and 15.1%, respectively. F1-Score showed increases of 48%-147%, with efficiency boost of 20-65%, while reducing the cost per attack by up to 39.6%. Benchmarks against frameworks from Dasu et al. and Matiushin et al. showed a 57.5% lead in F1-Score, more than double increase in detection rate, while blocking 70.78% more attacks. Additional analysis shows that ZeTHAA provides a mathematically grounded foundation for Zero-Trust systems, aligns with NIST standards, offering improved security guarantees and adaptive enforcement. 2013 IEEE. -
Biowaste-Derived, Highly Efficient, Reusable Carbon Nanospheres for Speedy Removal of Organic Dyes from Aqueous Solutions
The current work explores the adsorptive efficiency of carbon nanospheres (CNSs) derived from oil palm leaves (OPL) that are a source of biowaste. CNSs were synthesized at 400, 600, 800 and 1000 C, and those obtained at 1000 C demonstrated maximum removal efficiency of ~91% for malachite green (MG). Physicochemical and microscopic characteristics were analysed by FESEM, TEM, FTIR, Raman, TGA and XPS studies. The presence of surface oxygen sites and the porosity of CNSs synergistically influenced the speed of removal of MG, brilliant green (BG) and Congo red (CR) dyes. With a minimal adsorbent dosage (1 mg) and minimum contact time (10 min), and under different pH conditions, adsorption was efficient and cost-effective (nearly 99, 91 and 88% for BG, MG and CR, respectively). The maximum adsorption capacities of OPL-based CNSs for BG were 500 and 104.16 mg/g for MG and 25.77 mg/g for CR. Adsorption isotherms (Freundlich, Langmuir and Temkin) and kinetics models (pseudo-first-order, pseudo-second-order and Elovich) for the adsorption processes of all three dyes on the CNSs were explored in detail. BG and CR adsorption the Freundlich isotherm best, while MG showed a best fit to the Temkin model. Adsorption kinetics of all three dyes followed a pseudo-second-order model. A reusability study was conducted to evaluate the effectiveness of CNSs in removing the MG dye and showed ~92% efficiency even after several cycles. Highly efficient CNSs with surface oxygen groups and speedy removal of organic dyes within 10 min by CNSs are highlighted in this paper. 2022 by the authors. -
Acid Orange-7 uptake on spherical-shaped nanocarbons
Acid-dyes, typically used in textile productions, could infer poisoning harmful effects on the environment as well as on human health, if not properly treated during their disposal. Henceforth, there is an absolute necessity to achieve new efficient low-cost techniques to remove these dyes from industrial chemical waste. Here, the leaves of oil palm, which are abundant in tropical countries, were used as precursor in the development of carbon nanospheres (adsorbent) to remove hazardous acid Orange-7 (AO-7) dye (C16H11N2NaO4S). The removal efficacy of spherical-shaped nanocarbons was investigated as a function of contact period, by varying their dose (0.5, 1, 1.5, 2 and 2.5mg), pH (acidic, native and basic), and initial AO-7 concentration (10, 15, 20, 25 and 30?M). Amazingly, the oil palm leavesbased carbon nanospheres removed acid-dye up to an efficiency of about 99%. Pseudo second-order kinetics governs the adsorption mechanism and the RedlichPeterson isotherm model fits well to the adsorption results, with regression co-efficient close to unity. This study suggests the importance of natural biowaste-based carbon nanoparticles in sustainable recycling, within the worldwide demanded circular economy. The Author(s) 2021. -
Fast and effective removal of textile dyes from the wastewater using reusable porous nano-carbons: a study on adsorptive parameters and isotherms
In the present study, recyclable porous nano-carbons (PNCs) were used to remove textile dyes (mainly methylene blue, methyl orange, and rhodamine B) from an aqueous environment. Due to their high surface area and mesoporous nature, PNCs exhibited extremely fast and efficient adsorption behavior. PNCs synthesized at an elevated temperature of 1000 C are used in batch experiments, as they showed maximum dye removal with high surface area. Batch mode was used to optimize operational parameters such as initial dye concentration, contact time, adsorbent dose and pH as a function of time. Within ~7 minutes of treatment, PNCs achieved a maximum removal efficacy of ~99 percent for methylene blue. The recyclability of PNCs was investigated, and it retained its efficiency even after seven cycles. The efficacy of PNCs in treating industrial water contaminated with methylene blue dye was assessed. Different adsorption isotherms were carried out to determine maximum amount of dye that can be adsorbed on to surface of PNCs. The maximum adsorption capacity attained using Langmuir isotherm for methylene blue was around 1216.54 mg g-1. Adsorption kinetics were applied on experimental data to identify the rate of adsorption. It was confirmed that novel onion peel-based porous PNCs were successful in removing methylene blue dye effectively with short duration in comparison with other dyes mainly rhodamine B and methyl orange. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
ALLEVIATION OF POVERTY THROUGH PANCHAYAT RAJ INSTITUTIONS: A CRITICAL STUDY OF CHALLENGES AND PROSPECTS IN KARNATAKA, INDIA; [REDUO DA POBREZA ATRAV DE INSTITUIES PANCHAYAT RAJ: UM ESTUDO CRICO DOS DESAFIOS E PERSPECTIVAS EM KARNATAKA, DIA]
Purpose: The purpose of this paper is to: Analyse the role of Panchayat Raj Institutions (PRIs) in alleviating poverty in Karnataka, India. Identify the challenges faced by PRIs in implementing poverty alleviation programs. Explore potential solutions to overcome these challenges and improve program effectiveness. Provide recommendations for strengthening the role of PRIs in poverty alleviation efforts. Theoretical reference: This paper draws on several theoretical frameworks, including: heories of poverty alleviation, focusing on the role of local governance and community participation. Theories of decentralization and the devolution of power to local governments. Theories of social justice and equity, emphasizing the need to address the root causes of poverty. Theories of sustainable development, highlighting the importance of integrating economic, social, and environmental considerations. Method: This research is primarily a doctrinal study, relying on a variety of primary and secondary sources: Primary Sources: Statutory enactments: Constitution of India, 1950, Central Government Schemes implemented by PRIs, The Karnataka Gram Swaraj and Panchayat Raj Act, 1993. Policy documents: National Rural Development Policy, Karnataka State Rural Development Policy, Poverty alleviation scheme guidelines. Secondary Sources: Statistical analysis: Government reports and data sets, Research reports and surveys, Research publications: Peer-reviewed articles and books on poverty alleviation, local governance, and development. Case studies: Examples of successful poverty alleviation programs implemented by PRIs. Results: This research identified several key challenges faced by PRIs in implementing poverty alleviation programs in Karnataka: Corruption: Misuse of funds and resources hinders the effectiveness of programs and prevents benefits from reaching the intended beneficiaries. Caste: Deep-rooted social inequalities limit access to resources and opportunities for marginalized communities. Lack of awareness: Many people remain unaware of available schemes and benefits, leading to underutilization of resources. Limited capacity: PRIs often lack the necessary skills and resources to effectively plan, implement, and monitor programs. Lack of coordination: Poor coordination between different levels of government and stakeholders can lead to delays, duplication of efforts, and inefficient resource allocation. Despite these challenges, the research also identified several promising practices and potential solutions: Transparency and accountability: Initiatives like social audits and public hearings can improve transparency and hold PRI officials accountable for program outcomes. Community participation: Engaging communities in program design and decision-making can ensure programs are relevant and address local needs. Capacity building: Training programs can equip PRI officials with the necessary skills and knowledge to manage programs effectively. Technology and innovation: Utilizing technology can enhance program efficiency, data management, and communication with beneficiaries. Partnerships: Collaborations with NGOs, civil society organizations, and private sector can contribute resources, expertise, and innovation. Conclusion: PRIs play a crucial role in alleviating poverty in India. While they face numerous challenges, there are also promising solutions and opportunities for improvement. By investing in capacity building, promoting transparency, fostering community participation, and embracing technology and innovation, PRIs can be empowered to become more effective agents of poverty alleviation in Karnataka and beyond. 2024 ANPAD - Associacao Nacional de Pos-Graduacao e Pesquisa em Administracao. All rights reserved.