Browse
Recent Submissions
Item Effect of E Service Quality on Continued Usage Intention of Customers in Select Private Sector Banks(Avinashiligam, 2025-12) Fathimath Thasleena K; Guide - Dr.P.SanthiGlobally, the banking witnessed a rapid advancement in digital technology, intensifying the digital transformation process and necessitating the development of new technologies or adjustment to current business models (Kaur and Sahni, 2024). Every nation's economic development is significantly impacted by a healthy banking sector. It is crucial for the development of nation’s economy as banks channelise the fund through the society. Digital technology is employed by the banks to provide a range of financial solutions, including online payments, equity and crowd fund raising, peer-to-peer lending, insurance and personal financial management. Financial technologies are changing the whole financial market trading, supervisory and regulatory processes, make financial services more convenient for retail customers (Sathiyavani and Shivani, 2018). Private sector banks are facing tough competition from fintech or digital first payment providers. Therefore, it is essential to their growth and viability to retain clients by providing exceptional e-service quality (Sardar and Anjaria, 2023). In the present day of intense competition and outspoken customers who base their decisions to stay or leave based on both emotional and rational cues, customers continued usage intention is becoming an increasingly important managerial concern. In this context, understanding how e-service quality influences continued usage intention is essential for Private sector banks that wish to sustain customer engagement and loyalty. The present study examines the effect of e-service quality and banking service quality of select Private sector banks on continued usage of customers with mediating role e-service satisfaction and moderating role of customer trust. The study aims to analyze the customer expectation and experience gap of e-service quality and Banking Service Quality offered by the select Private Sector Banks among IT&ITeS employees. The study utilized Cognitive Motivational Relational (CMR) Theory developed by Richard Lazarus (1991) to provide theoretical support for the association between e-service quality and continued usage intention of customers. The locale of the study is Ernakulam district in Kerala, India, a prominent commercial and industrial center in the state of Kerala. Specifically, the study focusses on e-banking users of selected Private sector banks and they become employees of IT&ITeS companies working at Infopark, Ernakulam. Primary data were gathered from 398 customers by using structured questionnaires and the secondary data were collected from research articles, books and government reports. The reliability of the constructs is proved with a Cronbach’s alpha value of above 0.70. The Friedman Mean Rank test was employed to identify the main benefits of using e- services. Paired t test was conducted to measure the gap between customer experience and expectation on e-service quality and banking service quality dimensions. Chi-square test was used to test the association between socio-economic variables and level of e-service satisfaction, level of customer trust and level of continued usage intention. The significant difference between customer experience of e-service quality across socio economic variables were examined by using ANOVA and Tukey’s HSD Post-hoc analysis. Structural Equation Modelling were employed to analyse the effect of E-S-QUAL dimensions and BSQ dimensions on e-service satisfaction and the impact of e- service quality on continued usage intention with mediating role of e-service satisfaction and the moderating role of customer trust. The results reveals that customer experience better service than expectation and no gap was identified relating to ease of use, efficiency, safety, interoperability and service portfolio. While, there is significant gap noted in reliability and responsiveness of e-services. The post-hoc analysis indicates that elder customers and those earning monthly income above ₹ 75000, showing a positive attitude toward all the e-service quality dimensions and banking service quality dimensions as compared to other customer groups. The customers with 2-5 years of experience with bank are having more positive perception on concern to safety, reliability, responsiveness and interoperability of e-services. As the experience increases their concern is shifted towards efficiency, ease of use, service charge, service portfolio and personalized services dimensions. It is found that socio economic variables like age, monthly income, marital status and years of experience with the bank is significantly associated with level of customer trust, e-service satisfaction and continued usage intention of customers.The results of the structural equation modelling clearly demonstrated that e-service quality and banking service quality both have a major role in raising e-service satisfaction, which in turn has a strong positive impact on the intention to continue using the service. Notably, BSQ dimensions has a stronger effect on e-service satisfaction compared to E-S-QUAL dimensions. The partial mediation effect of e-service satisfaction further reveals that the benefits of e-service quality on continued usage intention are channelled significantly through satisfaction, reinforcing the need to focus on user-friendly, fast and responsive digital services. Importantly, customer trust emerged as a critical moderator in the satisfaction–continued usage intention link. The interaction effect proves that customer trust amplifies the influence of satisfaction on continued usage intention. The customers with high trust are more likely to stay loyal, even with moderate satisfaction levels. Keywords: E-Service Quality, Banking Service Quality, Experience and Expectation Gap,E-Service Satisfaction, Customer Trust and Continued Usage Intention.Item Enhancing Favourable Menstrual Attitude using Yoga and Psychoeducation among Adolescent School Girls(Avinashilingam, 2025-05) Srinithi A.M.; Guide - Dr. S. GayatrideviMenstruation is a natural biological process, yet unfavourable attitudes, stigma and psychological distress associated with it continue to affect adolescent girls. Addressing these concerns through holistic interventions can foster a more healthy menstrual attitude, reduce stress and enhance Psychological well-being. This study aimed to evaluate the effectiveness of Yoga, Psychoeducation and a Combined Intervention (Yoga & Psychoeducation) in enhancing favourable menstrual attitudes, reducing perceived stress and improving psychological well-being among adolescent schoolgirls. A before-after- follow-up study was conducted among 91 adolescent school girls in Avinashi, Tiruppur District. Participants were assessed using the Menstrual Attitude Questionnaire, Perceived Stress Scale and Psychological Well-being Scale at three time points, before intervention, after intervention, and at follow-up. The intervention consisted of Yoga in the form of Simplified Physical Exercises, Psychoeducation and a Combined approach, delivered systematically. Data were analyzed using SPSS 30, employing normality testing, descriptive statistics, Mixed ANOVA and Bonferroni post-hoc tests. The findings revealed that the Combined Intervention (Yoga & Psychoeducation) was significantly more effective than either intervention alone in reducing perceived stress, enhancing menstrual attitudes and improving psychological well-being (p < 0.05). While Yoga and Psychoeducation individually showed improvements, the synergistic effect of the Combined Intervention yielded greater and more sustained benefits across all measures. Integrating Yoga and Psychoeducation presents a holistic and effective approach to transforming adolescent girls’ perspectives on menstruation, mitigating stress and fostering psychological well-being. These findings underscore the importance of incorporating mind-body interventions in menstrual health programs to empower young girls with knowledge, resilience and confidence. Keywords : Menstrual Attitude, Yoga, Psychoeducation, Perceived Stress, Psychological Well-being, Adolescent GirlsItem Analytical Study on Social Networking among the Youth(Avinashilingam, 2025-10) Sinjitha V; Guide - Dr.R.Jansi RaniSocial networking sites have gained prominence as powerful digital platforms that have crucial influence on the social, emotional and scholastic development of youth. Social networking platforms have become necessary tools for communication, education and career development. This present study aims to explore the knowledge, attitude and usage patterns of social networking among youth from rural and urban settings, in Thiruvananthapuram district, Kerala. The research incorporates a mixed method design that incorporates quantitative and qualitative approaches based on interview, case studies and awareness programmes. To assess the effectiveness of awareness initiatives, pre test and post test assessments were conducted to measure changes identified in respondents understanding. Among the 600 sample, from student youth and employed youth, 150 samples were fragmented from the rural student youth and 150 samples from rural employed youth. Similarly, 150 samples were selected among urban student youth and 150 from urban employed youth. Among rural student youth, 89 percent demonstrate adequate knowledge of Facebook, 76 percent were capable of profile creation and 88 percent used these platforms primarily for communication. Furthermore, 84 percent recognized social networking as a source of knowledge development and 64 percent employed it for educational purposes. The study also revealed that 87 percent of rural youth reported improvement in language proficiency, 73 percent in personal calibre and 83 percent in photography and creative skills. Meanwhile, 81 percent refrained from chatting with strangers. Among urban youth, a higher proportion 61 percent spend time on online games, whereas 79 percent of employed youth believed that social networking has enhanced their employment opportunities. The analysis highlights a vital association between the location of youth and their levels of social networking knowledge, emotional and behavioural responses and overall attitudes. The findings affirmed that potential of social networking sites to promote youth empowerment and socio economic development. The study concluded that structured education and awareness programmes can guide youth toward responsible, productive and balanced use of social networking. Furthermore, the increasing internet accessibility in rural regions is helping bridge the digital divide, facilitating equal participation in the nation’s development process. The study faced challenges due to COVID-19–related restrictions, which constrained fieldwork, participant interaction, and the inclusion of respondents beyond one district and age group. Key words: Youth, Social Networking, Rural Students, Rural Employed, Urban Students, Urban Employed,Item Evaluation of banks’ and customers’ perception towards the adoption of sustainable banking practices in the select indian commercial banks(Avinashilingam, 2025-12) Sina E. S.; Guide - Dr.D.VennilaThe integration of sustainable practices into business operations and investment decisions depicts a commitment to a sustainable future. This validates a climate-focused initiative, namely the Net-Zero. India is striving to address climate change and achieve Net Zero by 2070 by promoting responsible consumption and a low-carbon strategy. Indian banks are geared up to play a leading role in facilitating this transition, with an unwavering commitment to sustainability. Although sustainability adoption and its opportunities have been widely studied across advanced and emerging economies, research focusing specifically on the Indian banking sector remains limited. In particular, the relationship between environmental concerns and banks’ commitment to sustainability has not been thoroughly explored. Moreover, many existing studies overlook a holistic perspective that considers both banks and their customers, creating a population gap. From a methodological standpoint, while some frameworks have been proposed, little empirical research has applied Structural Equation Modelling (SEM) to examine perceived environmental commitment, behavioural intention, and actual use of sustainable banking practices by customers in the Indian context. Conceptually, most literature highlights external drivers such as regulatory pressures and market demand, but there is limited understanding of how the perceptions of banks and customers influence sustainability-related decision-making. This study aims to address these gaps by theoretically and empirically investigating the factors shaping the intention to adopt sustainability in banking operations. The objectives of this study are to analyse the sustainable banking practices adopted by Indian commercial banks, the factors influencing the customer’s behavioural intention to use and actual use of sustainable banking practices, the benefits and challenges faced by each group. The research employs a quantitative approach, utilising a well-structured questionnaire from 850 bank branches and 1150 customers across India, determined through a proportionate sampling technique. Grounded in the TAM and VBN, the study uses Structural Equation Modelling to analyse the structural relationship of the independent variables: perceived ease of use, perceived usefulness, and perceived environmental commitment on the dependent variable: behavioural intention to use and actual use of sustainable banking practices. The results depict that Indian banks have increasingly adopted sustainability in their operations. Commonly adopted practices include digital banking and e-statements to reduce paper usage, financing green projects and renewable energy sectors, green building certifications for bank branches and solar-powered ATMs. Public sector banks focus more on regulatory compliance, while private sector banks are leading in voluntary green initiatives. Compared to public sector banks, Private sector banks tend to be more proactive and innovative in adopting green policies. The access to green financial products (like loans for EVs or solar panels), energy-efficient purchases and investments led to a sense of contribution to environmental sustainability. Customers report limited awareness, lack of proper education in sustainable banking practices and digital divide (especially in rural areas), concerns over data privacy and digital transaction safety and scepticism about bank motives. Customers perceive benefits such as convenience, a secure and paperless banking experience, and alignment with personal environmental values. Banks face barriers such as high initial investment in technology and green infrastructure, a lack of standardised policies, high implementation costs, and inadequate training of employees. Absence of unified sustainable banking guidelines is also a challenge faced by the banks. Both banks and customers express the need for better incentives and clearer communication of sustainable practices. The adoption and reporting of sustainable banking practices increases brand image, customer satisfaction, data security and customer privacy. Banks can take initiatives on financial inclusion and community development,product innovation with ESG consideration, sustainable business strategy, sustainable financing framework for the Bank’s issuance of sustainable instruments.” Keywords: Adoption of sustainable banking practices, Customers’ perception, Indian Commercial Banking Sector, Structural Equation ModellingItem Trembling Tenors of Life: A Psycho-social Approach to Trauma in Select Arab and Iranian Women Writings in English(Avinashilingam, 2025-01) Kavitha P K; Guide - Dr. S. KalamaniTrembling Tenors of Life: A Psycho-social Approach to Trauma in Select Arab and Iranian Women Writings in English Scheherazade, the legendary storyteller of One Thousand and One Nights, used her voice and stories to resist death, a metaphor for how Arab and Iranian women writers today use literature to fight silencing and marginalisation. Just as Scheherazade’s tales ensured her survival, these contemporary writers employ storytelling to navigate the complex realities of trauma, identity, and resistance in their lives. Arab and Iranian women writers, such as Azar Nafisi, Basma Abdel Aziz, and Jokha Alharthi, face immense challenges in gaining visibility within a literary world, long dominated by Western narratives and perspectives. Despite this, their works have emerged as powerful contributions to global literature, providing critical insights into the intersections of gender, trauma, and socio-political resistance. The present thesis analyses Azar Nafisi’s Reading Lolita in Tehran, Basma Abdel Aziz’s The Queue, and Jokha Alharthi’s Celestial Bodies, focusing on how the characters are traumatised by both personal and political contexts, shaping the identity and resilience of female protagonists in contemporary Arab and Iranian literature based on the broader historical and socio-political forces at play, such as the Iranian Revolution and the Arab Spring. The research applies trauma theories of Cathy Caruth, Shoshana Felman, Dori Laub and several other theorists to investigate how women’s experiences of trauma are portrayed and processed in these narratives. The thesis explores whether the responses to trauma in these texts are gender-specific, focusing on how women navigate societal expectations related to class, politics, and gender roles. It also analyses how literature, fine arts and crafts can help in alleviating the mental agony the women have due to ix trauma experienced in their lives. These creative outlets become essential for the characters’ survival, offering not only relief from mental anguish but also a method for reclaiming agency in a society that seeks to control their narratives. Through the lens of postcolonial theory of trauma studies in literature, it also examines how these female writers resist and rewrite the Western-dominated literary landscape, creating space for indigenous voices that challenge colonial and patriarchal narratives. Nafisi’s Reading Lolita in Tehran presents a poignant reflection on how trauma, particularly the trauma of living under an oppressive regime, impacts the intellectual and emotional lives of Iranian women. The personal trauma of these women is mirrored by the collective trauma of a society undergoing profound political repression. Similarly, Aziz’s The Queue examines the psychological toll of living under an authoritarian military regime in post-Arab Spring Egypt. It speaks of the role of silence and invisibility imposed on citizens in authoritarian contexts; challenging the assumption that trauma is always voiced. Alharthi’s Celestial Bodies offers a deep exploration of both domestic and transgenerational trauma passed down through families and former slaves in Oman. The novel intricately weaves together the lives of people especially women across generations, examining how colonial legacies, slavery, and socio-political transformation affect their identity and resilience. Ultimately, the thesis reveals how contemporary Arab and Iranian women writers not only reflect the trauma of their societies but also craft alternative spaces for healing and empowerment. The study contributes to a broader understanding of how literature and arts serve as vital tools for resisting trauma, reclaiming identity, and creating change in both personal and political contexts.Item Performance Efficient Methods to Handle Zero Day Attacks in Cloud Environment(Avinashilingam, 2026-01) Swathy Akshaya M; Guide - Dr.G.PadmavathiA zero-day attack is a type of cyber-attack that exploits a previously unknown vulnerability in a software application or a system. These attacks are called "zero-day" because the software developer has zero days to address the vulnerability since it has just been discovered. The term zero-day attack refers to a single or specific instance of an attack exploiting a newly discovered vulnerability, whereas zero-day attacks refers to multiple instances of such attacks or the general concept of attacks exploiting zero-day vulnerabilities. Zero-day attacks have become a significant cybersecurity concern as attackers continuously exploit previously unknown vulnerabilities, causing severe consequences such as data breaches, financial losses, and reputational damage. Although vulnerability identification can be performed using techniques such as code analysis, vulnerability scanning, penetration testing, and threat intelligence, traditional detection approaches remain largely dependent on signature-based and reactive mechanisms, making them ineffective against unknown and evolving threats. These limitations are further amplified in dynamic cloud environments, where increased system complexity, shared infrastructure, and large-scale network traffic expand the attack surface and hinder accurate real-time monitoring. Existing methods also suffer from high false positive rates, limited adaptability, inadequate behavioral learning, and increased computational overhead, reducing their effectiveness in large-scale deployments. To address these challenges, this research proposes a proactive, intelligent, and adaptive multi-phase framework for predicting, identifying, and detecting zero-day attacks. The proposed methodology integrates Machine Learning (ML), Deep Learning (DL), probabilistic modeling, game theory, and optimization techniques to enable behavior-driven predictive security. By moving beyond signature-based detection and learning attacker behaviors and system vulnerabilities, the framework enhances detection accuracy, minimizes false alarms, and provides scalable real-time protection suitable for dynamic cloud computing environments. The proposed research outlines a four-phase methodology for predicting zero-day attacks by combining machine learning and deep learning techniques. The first phase employs an Enhanced BPNN with CloudSim simulator to map the attack paths. In subsequent phases, data is systematically preprocessed, feature selection is performed, and multiple ML (Machine Learning) / DL (Deep Learning) models are trained and evaluated, followed by a comparative analysis of results across approaches. The objective is to proactively suggest performance efficient methods to identify and predict previously unseen (zero-day) threats, enabling organizations to detect attacks before they manifest. This approach proves to enhance the accuracy and reliability of intrusion detection systems by leveraging both traditional machine learning and advanced deep neural network methods, ultimately improving protection of digital assets through early, learned prediction of emerging threats. The research is conducted using a combination of simulation and real-world data to evaluate the proposed models performance. The simulation is performed using CloudSim, synthetic datasets Dataset 1 (Path Dataset) and Dataset 2 (Attack Dataset) is obtained from actual zero- day attack. The results of the comparative analysis will provide insights into the effectiveness of the proposed methodology and its potential for practical applications in cyber security. The core contribution of the research for Phase 1 is dedicated to identify the potential paths through which a zero-day attack can infiltrate the system. This phase traces the attack path in the cloud environment using a Probabilistic Graph Approach combined with an Enhanced Back Propagation Neural Network (BPNN), supported by Improved Decision Trees (DT) and Weighted K-Means clustering. Outcomes include improved accuracy by 3.01%, precision by 2.63%, recall by 2.27%, and F1 score by 2.34% compared to Bayesian, Scalable Bayesian, and Probabilistic Bayesian models. Phase 2 employs a hybrid method of Game Theory based on the Nash Equilibrium and an Adaptive Gaming Model based on a Modified Bi-Directional Long Short-Term Memory (LSTM) network to predict zero-day attacks. It enhances the ability to predict the potential zero day threats within the system through enhanced accuracy prediction, system performance and improved communication between security components achieving up to 11.4% higher accuracy, 11.3% higher precision, 5.5% higher recall, and 5.4% higher F1-score compared to DT, SVM, GNB, and Logistic Regression. Phase 3 propose a Residual Network integrated Deep Convolutional Zero-Day Adversarial Safety Network, designed for live zero-day attacks. It uses deep learning over the cloud communication network traffic analyzing and detecting events given in Dataset 1 (Path Dataset) and Dataset 2 (Attack Dataset) for real-time anomalies. Advanced convolutional layers and residual connections enhance generalization and classification up to 12.4% higher accuracy, 10.2% higher precision, 9.1% higher recall, and 9.2% higher F1- score over HMM, and up to 9.7% higher accuracy and 10.8% higher recall and ensure faster learning to identify zero-day attacks effectively compared to Bayesian GNN, BERT, TransVAE, and HADE-SVM models. Phase 4 presents an OLFFOA-optimized hybrid deep learning model. This comparative analysis allows for evaluating different models to determine the most efficient and accurate approach for zero-day attack prediction. The model achieves up to 98.1% accuracy, 95.2% precision, 94.4% recall, and 94.8% F1-score on Dataset 2, outperforming ResNet50, CNN-LSTM, and Bi-LSTM individually by 1.9% – 3.1%. The results show improved recognition rates, fewer false positives, and minimized time complexity, thus making the prediction models credible and scalable. Overall, this research work recommends performance efficient methods to handle zero-day attacks in cloud environment. The results are evident when tested with simulated dataset and benchmark dataset in zero-day attack. The anticipated research impact contributes to the development in enabling proactive, intelligent, and adaptive cloud security mechanisms, while the practical implication of this work supports real-world deployment in cloud infrastructures for early threat prediction, resilient intrusion detection, and enhanced security reliability in dynamic and large-scale environments.Item Parent’s Knowledge, Attitudes and Practice on Pre-requisite Skills for Children with Autism and its Influence on Parents Mental Health and Self-efficacy- A Sensitization Study(Avinashilingam, 2025-08) SeemaSaikia; Guide - Dr. RamyaBhaskarAutism Spectrum Disorder (ASD) is a complex neurodevelopmental condition that requires intensive and continuous care, where parents play a vital role in both management and day-to-day support. Parents serve not only as primary caregivers but also as consistent facilitators of their child’s learning and socialisation, making them critical partners in intervention processes. Nevertheless, the present study has focused on the Knowledge, Attitude, and Practice (KAP) of parents of children with autism on pre-requisite skills. These pre-requisite skills, which include social, communication, and self- help abilities, are essential for children to progress in learning and independence, leading towards vocational development. Without a clear understanding and effective practice of these skills at home, interventions often lose continuity and efficacy. Thus, the present study was undertaken with the objective of assessing the KAP of parents regarding pre-requisite skills, while also evaluating the effect of a sensitization programme designed to enhance parental knowledge, attitude, and practice in this domain. In addition to KAP, the study also addressed a crucial but often overlooked dimension: the mental health of parents themselves and their self- efficacy. Parenting a child with autism is stressful and emotionally taxing, often contributing to poor mental health outcomes and reduced self-efficacy among parents. In recognition of this challenge, the study simultaneously aimed to assess parents’ mental health and self-efficacy, while examining the impact of the sensitization programme on these parameters as well. The study was conducted in Coimbatore, Tamil Nadu.Out of the 16 special schools shortlisted for the present study, only 5 schools accepted to be a part of the research, and 143 parents of children with autism consented to participate. The study followed an action-based cross-sectional design by adopting a purposive sampling technique. The study was also approved by the Institutional Human Ethics Committee of the University (approval No. IHEC/19-20/HD/46).For the present study, four assessment scales were chiefly used, such as a self-developed tool to elicit socio-demographic profile of parents of children with autism, which includes the gender of parents, qualification, occupation, family income, number of siblings, types of family, and area of residence. ALikert scale consisting of 35 items each was developed by the researcher to assess the Knowledge, Attitude and Practices (KAP) of parents towards pre-requisite skills. The items covered the aspects of scheduling, attention, socialisation, self-control, self-advocacy, safety, communication, and imitation. The tool was tested for reliability and validity. Face validity and content validity were done, and the feedback and suggestions from subject experts were considered and incorporated to further refine the scales.The reliability was tested using Cronbach's alpha reliability test, with scores of 0.94 for knowledge, 0.84 for attitude, and 0.79 for practice,showing an excellent, very good, and good reliability of the scales, respectively. Validity was tested using principle component analysis (PCA) where the sampling adequacy was also found to be adequate for KAP with 0.760, 0.846, and 0.645, respectively and Bartlett’s test of Sphericity showed the significant level with cumulative percentage of 69.240 for knowledge, 69.652 for attitude, and 69.201 for practices, which were in the acceptable ranges. Standardised tools such as Mental Health Inventory (MHI) by Jagdish and Srivastava 2005, and Early Intervention Parents Self- Efficacy Scale (EIPSES) by Guimond, Wilcox, &Lamorey2008, were utilized to assess parents’ mental health and self-efficacy.The baseline findings of the study revealed that parents of children with autism demonstrated average to low levels of knowledge, unfavourable attitudes, and low to average levels of practice regarding pre-requisite skills. This indicated that while some awareness existed, a lack of comprehensive understanding and consistent application remained barriers to supporting children effectively. Parents’ mental health levels were found to be poor to very poor, highlighting the significant emotional strain and stress endured by families. Self-efficacy levels were also reported to be average to low, reflecting a lack of confidence among parents in their ability to handle the complex and demanding requirements of raising a child with ASD. These findings underscored the need for sensitization/interventions that simultaneously address both skill-based awareness and the psychosocial challenges parents face.A sensitization programme was planned and conducted, specifically designed for this research, aimed at equipping parents with an improved understanding of pre-requisite skills and strategies to effectively support their children in everyday situations. Of the larger pool, 30 parents were placed in the experimental group and another 30 in the control group for the sensitization component of the study.Statistical analyses revealed that paired t-tests demonstrated meaningful differences between pre- and post-test scores when compared with the control group, showing small to medium effect size in knowledge and attitude, as well as practice, respectively. These findings suggest that while knowledge improved modestly, the programme was particularly effective in reshaping parental attitudes and practice areas. Repeated measures – ANOVA was conducted to examine the sustainability showed that there was no significant variance in the experimental group’s post-test scores and follow-up scores. This was observed both at the first follow-up (after a 10-day interval) and the second follow-up (after a month’s interval), indicating that the improvements were largely retained. However, a slight decline was observed across follow-ups, implying reinforcement over time is necessary. In terms of parental mental health and self-efficacy, the experimental group showed significant improvements compared to the control group, with medium effect sizes, indicating meaningful changes in the mental health state and self-efficacy levels of parents. Repeated measures - ANOVA again confirmed that these improvements were largely sustained across follow-up assessments, although some minor declines were evident, indicating consistent reinforcement and long-term support mechanisms are necessary for enduring impact. The findings from this study carry important implications, highlighting the critical need to focus on parents not only as caregivers but also as individuals who require knowledge, skills, emotional resilience, and confidence to manage the demands of raising a child with ASD. Training programmes should therefore be designed to be holistic, integrating both informational and psychosocial support elements. The study points to policy and practice implications. There is a strong case for embedding parent sensitization and support programmes within the infrastructure of special schools and community health systems. Policymakers and practitioners should consider establishing formalized parent training modules as a routine part of early intervention services. In conclusion,this study demonstrates that while parents of children with autism often begin with limited knowledge and confidence, when parents are supported with knowledge, attitude, practice, mental health care, and self-efficacy, the outcomes can be transformative for both children and parents contributing to better developmental outcomes for children with autism and a healthier, more resilient family system. Keywords- Autism, Parents, Pre-requisite skills, Mental health, Self-efficacy, SensitizationItem Effect of High Intensity Interval Training Aerobic Training and Concurrent Training on Selected Physical Physiological and Skill Performance Variables among Football Players(Avinashilingam, 2025-07) Eswari S; Guide - Dr.T.ShanmugavalliThe aim of this study was to investigate the effects of High-Intensity Interval Training (HIIT), Aerobic Training (AT), Concurrent Training (CHAT) and Control group (CG) on selected physical, physiological, and skill performance variables among football players. Football demands a high level of fitness, combining speed, agility, endurance, and technical proficiency. To identify the most effective training method, the following objectives were formulated: To examine the effects of HIIT on selected performance variables; To assess the influence of aerobic training on physical and skill outcomes; To evaluate the combined effects of HIIT and AT (concurrent training); and to compare the effectiveness of these three training methods.Hundred intercollegiate male football players aged 18–21 years, with at least two years of playing experience, were randomly divided into four equal groups (n=25 each): Group I (HIIT), Group II (AT), Group III (CHAT), and Group IV (CG). The intervention lasted for Twelve weeks, with each group undergoing its respective training protocol three days per week under controlled conditions. Physical variables assessed included Muscular strength, Muscular endurance, Speed, Power, Agility and Cardiovascular Endurance; physiological variables included heart rate and VO₂ max; and skill performance variables included, passing, kicking, dribbling and shooting. Pre- and post-test data were collected, and Analysis of Covariance (ANCOVA) was employed to analyze the results, controlling for pre-test differences. The significance level was set at p < 0.05. All four groups showed statistically significant improvements in most measured variables. However, the Concurrent Training group (CHAT) demonstrated the most comprehensive enhancement across all physical, physiological, and skill performance domains, with several variables reaching high statistical significance. In conclusion, Concurrent Training, which combines the strengths of both HIIT and aerobic training methods, was found to be the most effective in enhancing overall football performance. Keywords : High-Intensity Interval Training, Aerobic Training, Concurrent Training, Football, Physical Fitness, Skill Performance, VO₂ max, ANCOVA, Objectives.Item Exploring the Dasya Bhakti from the selected Dasa Sahityas(Avinashilingam, 2025-12) Sajitha Suku. B; Guide - Dr.V.Janaka Maya DeviWorship began in primitive times where early humans used simple rituals to connect it with natural elements like the Sun, Fire, Water and many more. Overtime, worship took on a variety of forms with the change of living situations and society.Man developed different kinds of approaches to express their devotion and connect with the God. Navavidhabhakti, or the nine methods of devotion, which was mentioned in Srimad Bhagavata Purana is a significant sighting that made worship more personalised and inclusive. These paths of devotion supported the devotees to choose a suitable approach of worship that worked best for them. Nine types of devotion which makes up Navavidhabhakti are Sravanam, Keertanam, Smaranam, Padasevanam, Archanam, Vandanam, Dasyam, Sakhyam, and Atmanivedanam. Among these, Dasya Bhakti is unique that emphasizes humbleness, obedience, service and surrender to the Supreme. Dasya Bhakti incorporates aspects of all other seven bhaktis within itself, thus making it a comprehensive and all-inclusive form of worship.The lyrics of several types of Compositions expressively convey Dasya Bhakti. However, the dedication of servitude to God is most deeply emphasized and beautifully portrayed in Haridasa Sahitya, written by Haridasa saints who adhered to Dvaita Vedanta. These compositions mainly highlight the servant-master connection using simple language, making spiritual lessons understandable to the common people. This thesis is entitled as ‘Exploring the Dasya Bhakti from the selected Dasa Sahityas’, which includes five chapters excluding Introduction and Conclusion. The first chapter serves as an introduction to the evolution of worship started from the nature worship prevailed from the primitive period till the modern period, including the evolution of Navavidhabhakti. The second chapter details the uniqueness and servitude mode of Dasya Bhakti and the core connection of Dasyam with the Haridasa Sahitya composed by Haridasa saints. The third chapter details the elaborated life sketch of Sripadaraja, Vyasaraja, Vadiraja, Purandaradasa, Kanakadasa and Vijayadasa and chapter four is a detailed lyrical analysis of the selected Compositions of the above selected Haridasas, to bring out the core Dasalakshanas [characteristic features of Dasyam] depicted in the lyrics. The fifth chapter analyses selected six compositions of the selected Haridasas, each with one musical aspect. Only a few aspects of musical analysis have been carried out on selected compositions because the primary emphasis of this thesis is to reveal Dasalakshanas through lyrical analysis. The aim of this thesis is to explore eighteen significant Dasalakshanas, which authentically represent the fundamental dasa qualities (qualities of a soulful devotee), by lyrically analysing selected eighteen compositions (Haridasa Sahitya), composed by selected six Haridasas. Each of these Dasalakshanas provides insightful advice for developing a urposeful and well-rounded living in the present.Item Effectiveness of Reiki and Existential Therapy in Managing Body Pain Intensity and Insomnia Among Women(Avinashilingam, 2025-07) Sathya M; Guide - Dr. S. GayatrideviWomen play a vital role in every culture and are multifaceted. Being a woman is a disguised blessing. They face problems or challenges in their day to day life either socially or physically. Body pain and Insomnia are the remnants of this age of high demand and stress. Reiki and Existential Therapy is an integrated model of noninvasive alternative therapy and psychotherapy that has the potential to reduce symptoms of insomnia, pain and improve holistic well-being. A total of 124 participants aged 36-64 were selected by purposive sampling, with 30 participants in the Reiki intervention group, 31 in the Existential therapy group, 32 in the integrated therapy group and 31 in waitlist control group who were randomly assigned. The research design is Before, After and Follow-up with Waitlist Control Group Design (Randomized Control Trial method). A mixed method approach was used for pain and insomnia assessment among the participants. Assessments were done using the Brief Pain Inventory (Cleeland, 1994) and Regensburg Insomnia Scale (RIS) (Croenlein 2013). Intervention to the three experimental groups was given over a period of three months with 18 sessions. Pain and insomnia were reassessed after the intervention, and a follow-up was also done after 3 months using the same tools. The data was analyzed using the Design Expert Software version 13 for Response Surface Methodology (RSM) for process optimization, SPSS 29 for repeated measures MANOVA and Atlas ti 25 for qualitative analysis. Results revealed that Reiki and Existential therapy (integrated intervention model) is more effective in reducing the levels of Pain and insomnia among women. Interventions to overcome pain and insomnia can significantly improve the well-being and overall mental health of women. Keywords: Pain, Insomnia, Middle Adulthood Women, Reiki, Existential TherapyItem Classification of Diabetic Retinopathy Stages Using Deep Learning Architectures(Avinashilingam, 2025-08) Santhiya Lakshmi K; Guide - Dr. B. SARGUNAMDiabetic Retinopathy (DR) is a progressive microvascular complication of diabetes and a leading cause of vision impairment and blindness worldwide. Early detection and accurate classification of DR are essential for timely medical intervention and prevention of severe visual deterioration. Traditional diagnostic approaches rely on manual grading by ophthalmologists, which is time-consuming, labor-intensive, and susceptible to inter- observer variability. Recent advancements in Deep Learning (DL) have demonstrated significant potential in automating DR classification; however, existing models face challenges related to overfitting, computational complexity, and generalization across diverse datasets. This research aims to develop a robust and computationally efficient DR classification system capable of accurately detecting all four stages of DR like normal, mild, moderate and severe while addressing these challenges. The proposed methodology follows a three step approach to enhance model performance and adaptability. In the first phase, Transfer Learning (TL) is employed to fine-tune state-of-the-art pretrained models, particularly EfficientNetV2L, using the Asia Pacific Tele-Ophthalmology Society (APTOS) dataset. The objective is to utilize deep feature extraction capabilities while ensuring improved generalization. Data augmentation and scaling techniques are incorporated to mitigate overfitting and enhance model robustness. In the second phase, a custom Convolutional Neural Network (CNN) architecture is designed to optimize feature extraction and computational efficiency. The architecture incorporates structured convolutional layers, batch normalization, and dropout mechanisms to enhance learning stability while reducing the risk of overfitting. In the third phase, a hybrid model is developed by integrating the EfficientNetV2L with the custom CNN architecture, thereby utilising the strengths of both architectures. Extensive hyperparameter tuning is performed, including learning rate scheduling, dropout regularization, batch size optimization, and adaptive optimization using Adam optimizer, to ensure efficient training and convergence. The hybrid model is designed to provide a balance between high classification accuracy and computational feasibility, facilitating its deployment in clinical applications.The proposed system is evaluated using key performance metrics, including accuracy, precision, recall, F1-score, and computational complexity (trainable parameters).The hybrid model (EfficientNetV2L + Custom CNN Model) achieves the highest classification accuracy of 94%, with a precision of 94%, recall of 93%, and F1-score of 94%, utilizing 441,087 trainable parameters. Comparative analysis with benchmark models demonstrates the superiority of the proposed approach, with EfficientNetV2L achieving 92% accuracy, the Custom CNN Model reaching 88% accuracy, while conventional architectures such as VGG16 (85%), ResNet-50 (87%), InceptionV3 (89%), and DenseNet121 (90%) exhibit relatively lower performance. These findings confirm the effectiveness of the hybrid approach in achieving state-of-the-art classification accuracy while maintaining computational performance. The developed hybrid model is evaluated against an existing architecture that integrates DenseNet121, Xception, and EfficientNetB3, comprising 2,361,860 trainable parameters. The existing model achieves an accuracy of 75%, precision of 73%, recall of 75%, and an F1 score of 71%. In contrast, the proposed model, with only 441,087 parameters, demonstrates superior performance achieving a 19% increase in accuracy, 21% in precision, 18% in recall, and 23% in F1 score highlighting its effectiveness despite a significantly reduced parameter count. This research contributes to the advancement of automated DR classification by integrating fine-tuned pretrained models with a lightweight custom CNN, resulting in a scalable, efficient, and clinically viable diagnostic framework. The system is validated using clinical data to ensure its applicability in practical healthcare settings, particularly in resource-constrained environments where access to high-end computational resources is limited. The proposed model has the potential to significantly enhance early DR detection, improve diagnostic consistency, and ultimately contribute to better patient outcomes in ophthalmic disease management.Item Creating Awareness on Organic Waste Management Practices among Selected Rural Households(Avinashilingam, 2024-07) Vinothini R; Guide - Manimozhi KThis study investigates the impact of a training program on organic farming practices among rural households in selected areas, aiming to enhance health, reduce environmental pollution, and promote sustainable agricultural practices. The research methodology involved conducting household surveys, implementing training sessions, and evaluating the program's outcomes. The household survey gathered demographic data and insights into current agricultural practices and organic waste management. Findings highlighted diverse farming practices and challenges such as pest attacks and diseases, exacerbated by the heavy use of chemical fertilizers and pesticides. Organic waste management practices also revealed significant gaps in disposal methods and environmental awareness among rural communities. The training program focused on educating farmers about organic farming techniques, including composting and natural pest control methods. Evaluation of the training's impact showed notable improvements in farmers' knowledge and attitudes towards organic farming. Statistical analysis indicated significant changes in knowledge scores post-training, suggesting a substantial increase in understanding organic practices among participants. The adoption of organic practices post-training was another key outcome assessed. Results demonstrated a marked increase in the adoption of composting, organic growth boosters, and natural pest and disease management methods. This adoption was supported by economic benefits derived from reduced input costs and improved crop yields, contributing to rural household prosperity. Challenges identified during the study included logistical constraints in conducting widespread training and limitations in transportation for field visits. Despite these challenges, the training program succeeded in reaching a significant number of farmers and effecting meaningful changes in agricultural practices. The findings underscore the importance of targeted training programs in promoting sustainable agriculture and improving rural livelihoods. The study contributes valuable insights into the efficacy of educational interventions in transitioning farmers towards organic farming practices. Recommendations include scaling up similar training initiatives, addressing logistical barriers, and enhancing community awareness on environmental stewardship and waste management.Item A Hybrid Machine Learning approach for Detecting Intentional and Unintentional Insider Threats with Mitigation through Behavioral Biometrics and User Profiling Mechanism(Avinashilingam, 2025-07) Asha S; Guide - Dr. D. ShanmugapriyaInsider threat is a potential threat to an organization that results in financial and reputation losses while exposing sensitive information. Past research extensively focused on external threats, and overlooked on both intentional and unintentional insider threats.Several researchers majorly focused on detecting such insider activities but fail to mitigate both intentional and unintentional insider threats. Few challenges such as mishandling imbalanced dataset and fail to incorporate feature engineering techniques, limited mitigation strategies are encountered. This research employs a hybrid machine learning approach to identify insider threats and incorporated behavioural biometrics with user profiling to mitigate both intentional and unintentional insiders effectively. A methodology comprising of three phases is proposed. It consist of Preprocessing and Insider Detection (P&ID) in Phase I, Unintentional Insider Mitigation (UIM) in Phase II, and Intentional Insider Mitigation (IIM) in Phase III. P&ID consist of two layers - Preprocessing, and Insider Detection. In Layer 1, log data is preprocessed using data integration, encoding and tuned the nearmiss-2 sampling technique to obtain a balanced data to diminish the class imbalance problem. In Layer 2, a hybrid B-SVM combining Support Vector Machines (SVM) and Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) is applied. It classifies users into genuine, intentional insiders, and unintentional insiders. The proposed method achieved a 99.15% detection accuracy, with a low misclassification rate of 0.85% for detecting both intentional and unintentional insider threats. Once unintentional insiders are detected, the unintentional insiders are mitigated in UIM phase. UIM phase consist of two layers – Feature engineering, and Core behavior identification. In Layer 1, Clonal Kernel Principal Component Analysis (CKPCA) is proposed for feature engineering. CKPCA integrates population subset selection, kernel mean embedding, and dimensionality reduction to improve feature representation. These features are further analyzed using Deep Belief Networks (DBN) in Layer 2 that achieved 99.84% authentication accuracy and a 0.15% Equal Error Rate (EER) of 0.15%. This phase significantly minimizes false alarms and ensures a reliable mitigation process for unintentional insiders. In IIM phase, the detected intentional insiders are mitigated using user profiling mechanism based on their authentication outcome. IIM phase consist of three layers – Data pre-processing, Model training and evaluation, and User profiling. In Layer 1, data pre-processing is done using label encoding and train-test split. In layer 2, Decision tree is modeled to categorize users low-risk and high-risk. In Layer 3, Low-risk users with legitimate activities are profiled into the Allowlist, while users displaying malicious intent with high-risk are placed on the Denylist. This adaptive profiling ensures that intentional threats are neutralized without affecting genuine users. The methodology was validated using two datasets namely the CERT Insider Threat Dataset and the CIC Darknet Dataset. P&ID detected 8 intentional and one unintentional insider among 250,078 daily logs using CERT Dataset. P&ID is validated with darknet dataset, detected 4,783 intentional-Darknet users and 68 unintentional- Darknet users where (VPN: 42) (Tor: 21) (NonVPN: 5) among 134,305 daily activities. UIM mitigated one unintentional insider as an intentional insider using CERT log activities. UIM mitigated 68 unintentional-Darknet users as 64 Intentional-Darknet and 4 benign users using darknet dataset. IIM profiled 57 genuine users in Allowlist and 8 intentional insiders in Denylist using CERT dataset. Using CIC Darknet dataset, the IIM profiled 5063 benign users in Allowlist and 4847 Intentional-Darknet users in Denylist. This study offers a practical and highly effective solution for insider threats in environments where user log data is analyzed. By combining hybrid machine learning models with behavioral biometrics and user profiling, the approach ensures accurate detection and mitigation of both intentional and unintentional threats. This approach can be applied in any environment where user log is prevalent.Item Genomic and epidemiological profile of cervical cancer patients - identifying risk factors, pathways and novel variants through integrated survey and whole exome sequencing strategies(Avinashilingam, 2025-01) Sudha B; Guide - Dr. S. SumathiCervical cancer is a serious global health concern in Tamil Nadu, India. It significantly affects rural women due to their fewer facilities and lesser knowledge regarding healthcare. The study was designed to examine cervical cancer's sociodemographic, clinical, and genetic aspects, thereby identifying existing knowledge gaps, enhancing clinical perception, and determining molecular targets for precision medicine. The socio-demographic assessment revealed poor awareness of the symptoms, preventive measures, and immunization, the most severe deficit in rural areas. Clinical profile analysis of cervical cancer patients from Sri Ramakrishna Hospital, Coimbatore, Tamil Nadu, revealed that middle-aged rural women were the most affected and squamous cell carcinoma is the predominant subtype. The advanced stage of diagnosis was typical, with the prevalent symptoms being abdominal pain and post-menopausal bleeding. It also proved that cisplatin combination therapy is effective enough to change survival results. Considering the dominance of squamous cell cervical cancer, we have tried to profile the mutational patterns from biopsy samples using whole exome sequencing. Genomic analysis of 37 detrimental mutations found in critical genes and confirmation of novel variants in genes like POM121C, PRICKLE1, and GLIS3 by Sanger sequencing revealed bioinformatic dysregulated pathways like Hippo and TGF-beta signaling pathways, highlighting the molecular complexity of the disease and potential targets for precision treatment. Despite the limitations of having insufficient biopsy samples, the study calls for immediate improvement in public awareness, early detection strategies, and genomic-based therapy tailored to individual needs. These results offer crucial insight into the clinical and molecular landscape of cervical cancer and pave the way for precision medicine approaches to reduce mortality rates among affected populations.Item Exploring Neutrosophic Set Variants: Investigating Topological Insights, Approximation Spaces and Decision-Making Approaches(Avinashilingam, 2025-08) Bhuvaneshwari S; Guide - Dr. C.Antony Crispin SweetyList of Notations and Abbreviations : FS Fuzzy Set IVFS Interval Valued Fuzzy Set IFS Intuitionistic Fuzzy Set NS Neutrosophic Set SVNS Single Valued Neutrosophic Set TFS Temporal Fuzzy Set TIFS Temporal Intuitionistic Fuzzy Set PFS Pythagorean Fuzzy Set SFS Spherical Fuzzy Set PNS Pythagorean Neutrosophic Set NSS Neutrosophic Spherical Set FNS Fermatean Neutrosophic Set FTNS Fermatean Temporal Neutrosophic Set IVFNS Interval Valued Fermatean Neutrosophic Set FNCS Fermatean Neutrosophic Cubic Set PNT Pythagorean Neutrosophic Topology PNP Pythagorean Neutrosophic Point PNTS Pythagorean Neutrosophic Topological Space PNN Pythagorean Neutrosophic Neighbourhood PNOS Pythagorean Neutrosophic Open Set PNCS Pythagorean Neutrosophic Closed Set NST Neutrosophic Spherical Topology NSTS Neutrosophic Spherical Topological Space NSP Neutrosophic Spherical Point NSN Neutrosophic Spherical Neighbourhood NSOS Neutrosophic Spherical Open Set NSCS Neutrosophic Spherical Closed Set FNT Fermatean Neutrosophic Topology FNTS Fermatean Neutrosophic Topological Space FNP Fermatean Neutrosophic Point FNN Fermatean Neutrosophic Neighbourhood FNOS Fermatean Neutrosophic Open Set FNCS Fermatean Neutrosophic Closed Set BT-FNS Bitopologies of Fermatean Neutrosophic Set BT-FNSubs Bitopologies of Fermatean Neutrosophic Subsets FTNS Fermatean Temporal Neutrosophic Set FNGO Fermatean Neutrosophic Gradation of Openness FNGC Fermatean Neutrosophic Gradation of Closedness gp- map Gradation preserving map In-BTF Category of all-inclusive BT-FNSubs and continuous functions FNr-top Category of rth graded FNTSs and gp-maps FT-NTS Fermatean Temporal Neutrosophic Topological Spaces SFT-NT Fermatean Temporal Neutrosophic Topology in Šostak’s sense CFT-NT Fermatean temporal neutrosophic topology in Chang’s sense LFT-NT Fermatean Temporal neutrosophic topology in Lowen’s sense FTN- closed Fermatean Temporal Neutrosophic closed FTNRS Fermatean Temporal Neutrosophic Rough Set FNRAS Fermatean Neutrosophic Rough Approximation Space FN-r Fermatean Neutrosophic relation LT Linguistic Term MCDM Multi-Criteria Decision-Making CODAS Combinative Distance-Based Assessment ÐϺ Decision Maker SWAM Spherical Weighted Arithmetic Mean SWGM Spherical Weighted Geometric Mean FWAM Fermatean Weighted Arithmetic Mean FWGM Fermatean Weighted Geometric Mean D-Mx Decision Matrix NS D-Mx Neutrosophic Spherical Decision Matrix FN D-Mx Fermatean Neutrosophic Decision Matrix PIS Positive Ideal Solution NIS Negative Ideal Solution SF Score Function AC Accuracy Function TMNSDM Tangent Metric Neutrosophic Spherical Distance Measure TMFNDM Tangent Metric Fermatean Neutrosophic Distance Measure TOPSIS Technique for Order Preference by Similarity to Ideal Solution ED Euclidean distance N-ED Normalized Euclidean Distance HD Hamming Distance N-HD Normalized Hamming Distance SMSVND Sine Metric Single- Valued Neutrosophic Distance : The scope of this thesis is to explore some of the existing neutrosophic variants and introduce some new types of neutrosophic variants. The notion of extended Pythagorean neutrosophic set, neutrosophic spherical set, and Fermatean neutrosophic set has been examined and the concepts of topology, rough set, operators, and measures has been developed and analysed. The idea of the proposed logic is extended to define Fermatean neutrosophic cubic set to manage high levels of uncertainty and vagueness and also to introduce Fermatean temporal neutrosophic set to deal with time moments. Further, the thesis combines rough set concept with Fermatean temporal neutrosophic set to construct a new class of rough set called Fermatean temporal neutrosophic rough set. A new class of aggregation operators for neutrosophic variant has been developed and used in a COmbinative Distance-based ASsessment (CODAS) evaluation method. Furthermore, tangent metric neutrosophic spherical distance measure and tangent metric Fermatean neutrosophic distance measure are formulated and applied to the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Illustrative examples have been provided to validate and compare the defined aggregation operators and distance measures.Item Antioxidant Potential of Cucurbita Pepo L Pumpkin Seed Extract in the treatment of Stress Induced Male Infertility An in Vivo Study(Avinashilingam, 2025-01) Amrutha B Nair; Guide - Rajeswari P.AInfertility is a growing global health concern, with male factors contributing to nearly 50% of reported cases. Environmental toxicants such as lead are known to impair male reproductive function primarily through oxidative stress. Pumpkin (Cucurbita pepo L.) seeds, often discarded as biowaste, are rich in bioactive compounds and possess potential antioxidant properties. However, their role in stress-induced male infertility remains inadequately explored. The present study investigated the ameliorative effects of C. pepo seed aqueous extract against lead acetate induced reproductive toxicity in male Wistar rats. The study was conducted in five phases involving nutritional and antinutritional profiling, phytochemical and chromatographic analyses, in vitro antioxidant assays, acute oral toxicity evaluation, and an in vivo experimental study. Thirty rats were divided into five groups: control, lead acetate (30 mg/kg bw), seed extract alone (1000 mg/kg bw), lead acetate with low-dose extract (100 mg/kg bw), and lead acetate with high-dose extract (1000 mg/kg bw). Oral administration was carried out intermittently (15th, 30th and 45th days) for a duration of 45 days. The parameters such as body weight and individual organ weight measurements, sperm parameters, hormonal assays, serum and testis antioxidant assays, and histopathology analysis of reproductive organs were carried out using established methodologies. Lead acetate exposure resulted in significant reductions in body and individual organ weights, sperm count, motility, viability, reproductive hormone levels (FSH, LH and testosterone) and antioxidant enzyme levels (SOD, GPx, catalase) along with increased sperm abnormalities, semen pH, lipid peroxidation (MDA), and histopathological alterations in reproductive organ tissues. Co-administration of C. pepo seed extract, particularly at the higher dose, significantly ameliorated these alterations in a dose-dependent manner. The key finding of this research was that the C. pepo seed extract treatment has mitigated lead induced toxicity and exhibited significant improvement in their reproductive potential owing to the antioxidant property of their phytochemical components. Keywords: Male Infertility, Oxidative Stress, Lead Acetate, Cucurbita pepo L. Seeds, Antioxidant PotentialItem Acquisition and adoption of Digital Competency among Women Entrepreneurs in the Informal Sector(Avinashilingam, 2025-07) Mary Treasa C P; Guide - Dr. P .ShanthiDigital competency has emerged as a critical requirement for business development, sustained growth, and long-term competitiveness across sectors. The ability to navigate digital tools and platforms enhances operational efficiency, facilitates access to broader markets, strengthens customer engagement, and improves financial and administrative management. In this context, Digital skills serve as a vital indicator of an individual’s capacity to remain competitive, adapt to technological advancements, and leverage innovation for sustainable business outcomes. In the absence of adequate digital proficiency, many face the risk of exclusion from mainstream economic activities. The present study examines the influence of core antecedents, namely digital competency, performance expectancy, effort expectancy, social influence, and facilitating conditions, on behavioural intention, and how these factors contribute to the actual usage of technology in business operations. The study adopts the Unified Theory of Acceptance and Use of Technology (UTAUT) as its theoretical framework, which effectively captures the interplay between these constructs and their impact on technology adoption. The study is both descriptive and analytical. The locale of the study is Palakkad district in Kerala, India, which was purposively selected due to its prominence for largely informal micro-enterprises. Primary data were collected from a sample of 240 informal women entrepreneurs using a structured questionnaire, and the internal consistency of the instrument was confirmed with a Cronbach’s alpha value exceeding 0.70, indicating acceptable reliability. In addition, secondary sources such as government reports, published research articles, and institutional databases were utilized to complement and contextualize the findings. Targeted Digital competency intervention addresses the digital skill gap by systematically enhancing individual abilities in preparing training modules across key dimensions of digital competency and business applications for business operations. Moreover, technology adoption is closely linked to behavioural factors of technology adoption. Rank analysis was employed to identify the most significant challenges to technology adoption. To assess whether a significant mean difference existed in digital competency levels of women in the informal sector before and after the training intervention, the Wilcoxon Signed-Rank Test was applied. Additionally, the Kruskal-Wallis Test and the Mann-Whitney U Test were used to examine significant differences in digital competency across various socio-demographic and business profile variables of the respondents. The Structural Equation Modelling (SEM) was conducted to evaluate the influence of key antecedents of behavioural intention on the actual use of technology The result indicated that digital competency was found to be significantly influenced by performance expectancy, indicating that enhanced digital skills improve perceptions of technology’s usefulness in business operations. This perception of performance expectancy, in turn, had a strong positive impact on behavioural intention to adopt technology. Social influence also emerged as a significant predictor of behavioural intention, emphasising the role of peer support and community validation in shaping technology adoption decisions. Furthermore, both digital competency and behavioural intention significantly contributed to the actual use of technology in business, confirming their pivotal roles in the adoption process. Behavioural intention was also identified as a key mediator between social influence and actual technology usage. On the other hand, Digital competency did not influence effort expectancy, suggesting that users still perceive new technologies as requiring effort despite increased digital proficiency. Effort expectancy and facilitating conditions did not significantly affect behavioural intention, indicating that ease of use and external support were less influential in determining intent to adopt technology. The sustained technology adoption is more closely tied to internal factors such as digital competency and perceived performance benefits than to structural or external enablers alone. Keywords: Women Entrepreneurs, Technology Adoption, Digital Competency, Behavioural Intention, Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Actual Usage.Item Exploring Entrepreneurship as a Coping Strategy for Mothers of Visually Challenged Children(Avinashilingam, 2025-08) Nirmala Fousta. A; Guide - Dr. Rymala MathenExploring Entrepreneurship as a Coping Strategy for Mothers of Visually Challenged Children :Mothers of visually challenged children face persistent emotional, social, and economic challenges arising from intensive caregiving responsibilities, societal stigma, financial insecurity, and limited institutional support. These stressors often lead to elevated parenting stress, reduced self-esteem, and diminished personal and social well-being. The present study investigates the effectiveness of entrepreneurship as a coping strategy to alleviate stress and enhance the overall quality of life of mothers of visually challenged children. Anchored in Resource Management Theory, the study conceptualises time, energy, and financial resources as critical constraints and examines how these can be effectively reorganised through life skills development and entrepreneurial engagement. A mixed-methods research design was adopted, and the study was conducted in Chennai, Tamil Nadu, across four systematic phases. Phase I, a cross-sectional survey, comprised a total sample of 423 mothers of visually challenged children drawn from eight special schools and organisations to assess socio-economic characteristics, factors leading to stress, parenting stress levels, and personal and social well-being. Phase II employed a pre-test and post-test intervention design with a sub-sample of 50 mothers, who participated in a structured Life Skills Training (LST) and handskills training programme focusing on stress management, decision-making, positive thinking, and income-generating skills. Phase III involved 20 trained mothers who established and operated a small-scale vending enterprise on the school campus (St. Louis Thai Store), while Phase IV evaluated the impact of entrepreneurship and satisfaction levels through detailed case studies of 10 mothers. Data were analysed using descriptive statistics, independent and paired ttests, one-way ANOVA, and correlation analysis to examine differences and relationships between socio-demographic variables, stress factors, parenting stress, and personal and social well-being. The findings revealed statistically significant differences at the 1 per cent level, indicating that socio-demographic variables significantly influenced stress and well-being outcomes. Post-intervention results demonstrated a significant reduction in parenting stress and substantial improvement in life skills, emotional resilience, self-confidence, decision-making ability, financial independence, and personal and social well-being among the mothers. The study further establishes that entrepreneurship, when supported through structured training,institutional backing, and community-based frameworks, functions not only as a viable economic intervention but also as a powerful psychosocial coping mechanism.The integration of livelihood creation with emotional and social support contributed to enhanced resilience, improved caregiving capacity, and sustainable empowerment of mothers of visually challenged children. The study recommends the incorporation of inclusive livelihood initiatives, school-based entrepreneurial models, and supportive policy frameworks to promote the long-term well-being and socioeconomic security of caregivers of children with disabilities. Keywords: Coping strategy, Entrepreneurship, Life skills training, Mothers of visually challenged children, Parenting stress, Quality of life, Resource management,Visual impairment.Item A Neo-Marxist Study of the Select Retellings of Mahabharata(Avinashilingam, 2024-03) Kushma Kumari T V; Guide - Dr. A. VijayaraniMyth is a dynamic and man-made belief to maintain the culture of a society. It is revisited and altered according to the necessity of people and acts as a guiding source for people. The retellings of Mahabharata fascinate the researchers to apply literary theories and experiment it from different points of view. The present study is an attempt to explore on the retellings of Mahabharata by Devudtt Pattanaik (Jaya: an Illustrated Retelling of Mahabharata), Anand Neelakantan (Ajaya: Roll of the Dice), Kavita Kane (Karna’s Wife: the Outcast’s Queen) and Ashutosh Nadkar (Shakuni: Master of the Game) by applying a Neo-Marxian concepts ‘Theory of Cultural Hegemony’ and ‘Role of Intellectuals’ by Antonio Gramsci. The researcher has taken both male and female characters from the chosen primary texts to discuss about the cultural domination prevailed during the ancient time and has also highlighted on the functional solution enumerated by Gramsci with the aid of the characters. The study explicates on the retellings of Mahabharata with certain aspects from Gramsci’s ‘Theory of Cultural Hegemony’ and ‘Role of Intellectuals’. Elucidates on the purpose of retelling of Mahabharata by critically analysing the selected texts and elaborates on the cultural aspects from them. The study also draws attention to the culture based dominations, capitalist ideologies and gives a practical solution for domination in accordance with Gramsci. The area of research is relevant in this present scenario to highlight the cultural hegemony which still exists among the Indians in different forms. The work is significant as it can relate the issues depicted by the authors of the selected retellings of Mahabharata with our current society.Item Mapping Gender and Violence: Assault, Abuse and Trauma in Select Plays of Indian Women Writers(Avinashilingam, 2025-05) Isai Arasi T; Guide - Dr. S. Christina RebeccaMapping Gender and Violence: Assault, Abuse and Trauma in Select Plays of Indian Women Writers : Violence against women constitutes a significant concern in contemporary India.This issue is rooted in patriarchal beliefs that perpetuate power and gender inequalities.The present research examines various forms of violence as depicted in selected plays by Indian women writers, organized into seven chapters, including an introduction and a conclusion. The introduction delineates the evolution of theatrical works and the emergence of Indian women playwrights, emphasizing their contributions to both society and literature. It also addresses contemporary themes and the impact of select playwrights on the theatrical landscape. Chapter II, titled “Gender and Trauma: Theoretical Framework,” analyses how power dynamics related to gender lead to the subjugation and exploitation of women. This chapter explores how the research utilises the concepts of objectification and trauma theory to examine the exploitation of women’s bodies and its impact on their psyche. It employs objectification to illustrate the perception of women as objects valued primarily for their physical appearance, rather than their intrinsic worth. Additionally, trauma theory is integrated to explore the psychological effects experienced by victims, emphasizing trauma as a significant event that disrupts normal coping mechanisms. Chapter III concentrates on child sexual abuse, specifically analysing Dina Mehta’s play Getting Away With Murder, which highlights the power imbalances that facilitate such abuse, particularly against young girls. This chapter further underscores how societal gender disparities contribute to the prevalence of sexual abuse and discusses the coping mechanisms that victims employ to address their trauma, which often extends into later stages of development. Chapter IV investigates the interplay between power dynamics, gender bias, and domestic violence, utilising Poile Sengupta’s play Mangalam to illustrate the objectification and mistreatment of women by family members. The chapter assesses the psychological effects of domestic violence on women and examines their coping strategies to endure the traumatic experiences inherent in their situations. Chapter V addresses the critical issue of gang rape within the context of Manjula Padmanabhan’s play Lights Out, emphasizing the objectification and violation of women’s bodies by perpetrators. It highlights the pervasive fear instilled in women by such acts and their profound impact on victims’ lives, while also considering the perspective of a witness reflecting on the victim’s suffering. Chapter VI explores the grim realities of women in cyberspace, as portrayed in Anupama Chandrasekhar’s play Free Outgoing. It underscores the severe repercussions of revenge pornography on victims and their families, jeopardizing their future. Moreover, this chapter critically examines societal tendencies to perpetuate gender bias. The conclusion posits that societal transformation is essential to eradicate violence against women, achievable through education that reveals the socially constructed nature of gender norms and emphasizes the importance of male respect for women and their emotions. Furthermore, robust familial and social support systems are crucial for victims, equipping them with the emotional resources necessary to cope with trauma and reclaim their voices.