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Item Determinants of Risk and Resilience among Youth and the Effect of Sensitization Programme(Avinashilingam, 2025-05) Fenny Leferty Kharpuri; Guide - Dr.Ramya BhaskarYouth are the most energetic slice of the population in any country, the future of tomorrow. Youth constitute an integral developmental phase marked by transitioning from childhood to adulthood, characterised by unique cognitive, emotional and social changes. This period encompasses stages of maturation that neither occur in early childhood nor can be delayed until adulthood. It is often expounded by exploring roles and identities, relatively unbound from rigid social expectations, yet progressively shaped by emerging responsibilities and societal norms. Out of the 1.2 billion people living in India, 54 percent are below 24 years of age. Youth lifestyles are of concern. This study examines youth as a formative period that prepares individuals for active participation in the broader social collective. This study explores the concept of risk and resilience among youth. It discusses various factors influencing risk factors and resilience components among the youth. The review of relevant literature highlights the importance of fostering resilience in adolescents and youth involved in various risk factors to support their overall well-being. Understanding the underlying risk factors and process of risk is crucial to the identification of those adolescents and youth who are most in need of early intervention, whereas clarification of protective factors and process of resilience can inform the design of sensitisation and intervention to strengthen those at greatest risk. The primary objective of this study was to assess the prevalence of risk behaviours and levels of resilience among youth, followed by the objectives to analyse the interrelationship between risk and resilience factors, to explore the socio-demographic predictors of risk and resilience and to examine the effect of the sensitisation programme on the risk behaviours and resilience among the youth. In the pursuit of these goals, risk and resilience research has focused on several levels of analysis. An action-based cross-sectional research study was designed to target youth from both urban and rural areas within the Coimbatore jurisdiction, Tamil Nadu. A sample of 1710 youth aged 18-22 years was selected for the study using a simple random sampling technique from the city of Coimbatore, Tamil Nadu state. The self-made demographic questionnaire was used to collect the socio-demographic information. The Youth Risk Behaviour Scale 2019 was administered to study the risk behaviours, and the Resilience questionnaire 2017 was also used to assess the youth’s response to resilience. The study also emphasised the sensitisation programme to be conducted to enhance resilience and reduce risk based on the prevalence of risk factors among the selected youth. A sensitisation programme for the youth after obtaining permission from the college administrators. A total of 184 youth were selected using a controlled randomised selection technique, where 122 youth were taken as the experimental group based on their willingness to participate in the programme, and 62 youth were taken as the control group (waitlist). The sensitisation programme was conducted for 2 weeks (4 days per week), consisting of 16 sessions (2 sessions per day) using validated educational content, through delivering lecturers/awareness, clearing doubts, tailoring messages to the students to make them aware on various topics such as unhealthy and abusive risks, the cycle of addictions, problem solving skills, strengthening protective factors and providing counselling sessions if asked and required. Data was collected from the experimental and control groups after the sensitisation programme (post data), and post data collection was done at two intervals . The first post-data was collected after 10 days of the programme, and follow-up data was collected after a gap of a month. The pre-sensitisation scores were taken from the data collected during the II phase (before sensitisation). The sensitisation programme was conducted by the investigator with the help of a trained clinical psychologist. As part of the research framework and the study objectives, multiple levels of analysis was carried out, where the socio-demographic markers which includes age, gender, educational qualification, type of family, area of residents, parents education and occupation and family annual income served as the independent variables and the dependent variables constituted the risk factors (safety issues, attempting suicide, substance use, sexual behavior and health issues) and resilience components (self-belief, optimism, purposeful direction, adaptability, ingenuity, challenge orientation, emotional regulation and support seeking). Descriptive statistics (frequency and percentage) were used to determine the prevalence of risk behaviours and levels of resilience among youth. Subsequently, canonical correlation analysis was conducted to explore the interrelationship between risk and resilience factors. Multiple linear regression analysis was used to identify the socio- demographic predictors of risk and resilience. To examine the effect and sustainability of the sensitisation programme on the risk behaviours and resilience among the youth, paired sample t test, independent t test and multivariate analysis of variance (MANOVA) were applied. The study depicted that most youth experienced moderate to high levels of risk behaviours such as driving safety issues, bullying, smoking, tobacco use, alcohol, sexual behaviour, body weight, eating habits physical activities and health related issues, and moderate to low levels of resilience in the components of self-belief, optimism, purposeful direction, ingenuity, challenge orientation, emotional regulation, and support seeking. A significant interrelationship emerged between risk behaviours and resilience components, indicating that engagement in risky behaviours tends to reduce resilience, indicating high substance use and health issues, lowers ingenuity, challenge orientation, and adaptability. Conversely, low protective factors in youth increase susceptibility to risky behaviours like lower support seeking increases attempting suicide, and higher self-belief lowers the substance use. Socio-demographic markers were also identified as influential in shaping both risk behaviours and resilience of youth, indicating particularly, the gender and age of the youth, educational and occupational backgrounds of parents, family income, and area of residence were evident in shaping youth direction. These factors were linked to both heightened vulnerability to risk behaviours and reduced resilience capacities. The effectiveness and sustainability of the sensitisation programme in preventing risk and promoting resilience were examined. Findings revealed that participants in the experimental group demonstrated significant improvements in resilience scores and reductions in risk behaviours at both post-test and follow-up stages. In contrast, the control group exhibited minimal or no statistically significant changes across the same measures. The significant differences in mean scores between the experimental and control groups provide strong evidence for the programme’s efficacy. Nonetheless, it is important to note that certain dimensions of resilience did not show substantial improvement in the follow- up phase, underscoring the necessity for ongoing, targeted interventions to support long- term behavioural change and the continued development of youth resilience. Based on the study's findings, several implications emerged for youth, college administrators, educators, parents, families, communities, and policymakers. These stakeholders must actively engage in sensitisation, intervention or awareness programmes to address the resilience and risk factors affecting young people. The study recommends efforts for fostering healthy development, positive mental health, and overall well-being. Early identification of at-risk students is crucial, along with initiatives to strengthen student–teacher relationships, enhance family involvement, and integrate mental health services on campus through accessible counselling. Keywords: Youth, Risk Behaviour, Resilience Components, Sensitisation Programme, Socio-demographic Markers.Item Fantasy and Reality at Crossroads: Exploring Mythical and Mortal Worlds in Select Novels of Rick Riordan(Avinashilingam, 2024-12) Devika Kakkat; Guide - Dr. Chitra SivasubramaniamRick Riordan’s children’s fantasy adventure, Greek mythological retelling series, Percy Jackson and the Olympians, a major popular fiction sensation, has captured a place in mainstream status in the world of literature. A deep dive into the plot and narrative structures of the first five novels in the series, The Lightning Their (2005), The Sea of Monsters (2006), The Titan’s Curse (2007), The Battle of the Labyrinth (2008), and The Last Olympian (2008) using the theories of Julia Kristeva’s Intertextuality, William H. Gass’s Metafiction, Linda Hutcheon’s Historiographic Metafiction, Jean Francois Lyotard’s Incredulity towards metanarratives, the conventional models – Gustav Freytag’s ‘Freytag pyramid’, Northrop Frye’s criticism of myth, John Gardner’s ‘Fichtean Curve’, Tzvetan Todorov’s narrative theory of equilibrium, Vladimir Propp’s narrative structure, Joseph Campbell’s ‘monomyth’ or the Hero’s Journey, John Clute’s structure of fantasy, and Christopher Vogler’s ‘Mythic Structure’ and character functions as identified by Vladimir Propp, Joseph Campbell, Christopher Vogler, and A. J. Greimas’s concept of actants, help to illuminate the elements of fantasy in the plot of the select novels with the potential to be transcribed into the reality of readers, thereby cementing it’s significance among readers of all age groups. The realistic themes represented in its mesmerising armoury of fictional, mythical world like social justice, diversity and inclusivity, ecology, dark themes such as the death and loss of loved ones, psychology, emotions, and contemporary concerns of growing up cements it’s status as a narrative self-portrait and a reviser of grand narrative traditions. The study demonstrates a subversion of the conventional structural and narrative models in the select novels that provide authentic voices which are reflective of true life. It highlights the transformative power of children’s fantasy literature, suggesting alternative ways of thinking through aesthetic and social advocacy that instils the message of living with the awareness of one’s culture.Item Refugeehood Dematerialised: An Analysis of Agency in Select Refugee Narratives(Avinashilingam, 2025-05) N. Lavanya; Guide - Dr. M. Anjum KhanRefugee narratives in English literature encapsulate the extensive problems of the individuals on becoming non- citizens due to several reasons. These narratives examine the factors that lead to statelessness and explores their predicament as refugees, internally displaced persons, asylum seekers or immigrants. The narratives written by refugees themselves or an author with personal interest and proper research on refugees, provide authentic depiction of their ordeal. Further, these literary works advocate for solutions, urging those in power and society at large to take meaningful steps toward improving the lives of refugees. As a result, the present thesis scrutinises seven such refugee narratives: A Land of Permanent Goodbyes by Atia Abawi, The Boat People by Sharon Bala, First, They Erased Our Name by Habiburahman, Little Daughter by Zoya Phan, City of Thorns by Ben Rawlence, How Dare the Sun Rise by Sandra Uwiringiyimana, and The Milk of Birds by Sylvia Whitman, which includes memoirs, biographies and fiction. The thesis makes a modest attempt to investigate into refugee crisis with special focus on human agency. It uses Hannah Arendt’s theoretical concept, namely, ‘statelessness,’ ‘right to have rights,’ ‘banality of evil’ and ‘plurality’. The thesis identifies that refugeehood remains a profound challenge, stripping individuals of their political, social, cultural, economic, legal, and bodily agency. It critically examines the erosion of these forms of agency and explores refugees’ resilience through the assertion of autonomy and through their continuing struggle for survival in the face of systemic and enduring adversity with the help of political theories of Hannah Arendt. It also tries to contemplate on few possible solutions for alleviating the hardships of refugees all over the world.Item Unveiling the Anticariogenic Properties of Medicinal Plants and Development of a Polyherbal Dentifrice(Avinashilingam, 2025-01) Gaayathiri Devi E; Guide - Dr. M. K. NishaDental caries, a prevalent multifactorial infection, results from the interaction between acid-producing microorganisms and a diet high in carbohydrates. This study harnesses the potential of a polyherbal remedy that offers a holistic approach to promote overall dental health and combat tooth decay with its natural antibacterial properties. To identify effective oral agents twelve plant extracts, Achyranthes aspera root (AAR), Acalypha indica leaf (AIL), Azadirachta indica leaf (AZL), Abrus precatorius leaf (APL), Barleria cuspidata leaf (BCL), Euphorbia hirta leaf (EHL),Ficus benghalensis prop root (FBP), Piper betle leaf (PBL), Psidium guajava leaf (PGL), Pongamia pinnata leaf (PPL), Tridax procumbens leaf (TPL), and Solanum virginianum fruit (SVF) traditionally used by local tribal populations in Thottakombai Hill, Erode district of Tamil Nadu, were studied. Methanol extracts of AAR, BCL, EHL, FBP, PBL, PGL, PPL, TPL, and SVF demonstrated a higher phytochemical content and exhibited stronger DPPH radical scavenging activity than other plants. Furthermore, clinical plaque isolates, such as Streptococcus mutans (SMU), Streptococcus salivarius (SSA), Streptococcus oralis (SOS), Streptococcus parasanguinis (SPSA), Klebsiella pneumoniae (KP), Pseudomonas aeruginosa (PA), Acinetobacter baumannii (AB), and Candida albicans (CA) were significantly susceptible to AAR, BCL, EHL, FBP, PGL, and SVF. Hence, further investigation of phytocompounds from these six plants through molecular docking studies revealed a high binding affinity for glucosyltransferase-C, a key virulence factor synthesized by SMU. Consequently, all six plants were optimized for the development of a polyherbal dentifrice (PHDF) in toothpowder tablet form. The PHDF demonstrated low toxicity, and showed the presence of essential minerals proving its safe use. Furthermore, PHDF effectively reduced the pH, and hydrophobicity of SMU, thereby eradicating its biofilm formation and outperforming marketed standards. The network pharmacological approach provided valuable insights into PHDF’s mechanism of action, highlighting its potential as a promising natural remedy for the prevention and treatment of dental caries. Thus, this study validates the formulation’s strong effect against oral pathogens and suggests a novel, comprehensive approach to oral health care.Item Exploring the Anti-Cancer Potential of Rhododendron arboreum Sm. in Gastric Cancer using In Vitro and In Vivo Models(Avinashilingam, 2025-04) Yangchen Dolma Kom; Guide - Dr. R. KarthiyayiniIntroduction: Rhododendron arboreum Sm. is an evergreen small tree that belongs to the family Ericaceae, that has been traditionally used to treat various human ailments. This proposed study focused on exploring the phytochemical composition, antioxidant activity and anticancer potential of R. arboreum, particularly against gastric cancer. Methodology :The qualitative and quantitative phytochemical analysis of R. arboreum leaves and flowers were conducted using standard methods. Functional groups were identified and characterized by FT-IR, NMR and GC-MS. Antioxidant capacity was evaluated using DPPH, ABTS, H2O2, LPO and FRAP assays. Cytotoxic effects on AGS gastric cancer cells were measured by MTT assay. In vivo analysis, the gastric cancer was induced in C57BL/6 mice with AGS cells, followed by oral treatment with R. arboreum extracts and standard drug for eight weeks. Post-treatment, histopathological and biochemical analyses were performed. In silico studies, the SwissADME predicted the ADME properties and drug-likeness of active compounds. Network pharmacology identified target proteins linked to gastric cancer with PPI networks analysed via STRING and Cytoscape. Functional enrichment highlighted key pathways using DAVID and ShinyGO. Molecular docking and molecular dynamics simulations confirmed stable binding of bioactive compounds to cancer-related proteins, supporting their therapeutic potential. Results : The proposed work involved a comprehensive analysis of aqueous, methanol, ethanol, acetone, chloroform and petroleum ether extracts of leaves and flowers showed the presence of diverse bioactive compounds. In quantitative analysis, the methanol extracts of both leaf and flower were significantly higher when compared to ethanol and acetone. Exploring the Anti-Cancer Potential of Rhododendron arboreum Sm. in Gastric Cancer using in vitro and in vivo models. Abstract : The antioxidant potential of the leaf extracts possessed stronger radical scavenging capabilities when compared to the flower extracts. For instance, the DPPH and ABTS test showed IC50 values of 56.8±1.91 μg/mL and 60.7±2.13 μg/mL for leaves and 67.3±2.95 μg/mL and 65.9±1.97 μg/mL for flowers respectively. Similarly, In H2O2 and LPO assay, the leaf extracts exhibited higher inhibition rates when compared to the flower extracts. Whereas, the FRAP assay indicated that the flower extracts had superior reducing power, with activity increasing at higher concentrations than the leaf extracts. In the cytotoxicity assay, the methanol extracts inflicted substantial damage to the AGS gastric cancer cell line. Whereas the anti-cancer potential of R. arboreum was evidenced by significant suppression of tumour growth in C57BL/6 mice model. In GC-MS spectrum revealed the presence of several bioactive compounds and cross-referencing with IMPPAT database identified ten compounds, which binds to 113 proteins, with 22 linked to gastric cancer via GeneCards. Cytoscape revealed a binary network with 10 nodes and 35 edges. ShinyGO identified 20 cancer-related enriched functions, including EGFR Tyrosine Kinase Inhibitor Resistance Among the identified compounds, quercetin showed the highest binding constant, with molecular dynamics confirming stable protein-ligand interactions over 100 ns. Conclusion This research highlights the significant phytochemical, antioxidant and anticancer properties of Rhododendron arboreum leaf and flower extracts. The in vivo results showing significant tumour suppression, alongside the identification of quercetin as a key bioactive compound providing a strong foundation for further investigation of R. arboreum as a source of novel anticancer agents for gastric cancer. These findings pave the way for exploring the molecular mechanisms and potential as a plant -based therapeutic for gastric cancer. Future research will aim to strengthen the correlation between in vitro and in vivo results through detailed pharmacokinetic studies and exploring its efficacy against other cancer types to expand its translational applications.Item Physicochemical Characteristics Safety of Under Utilized Selected Natural Food Colourants and Development of Food Colour Sensor(Avinashilingam, 2024-12) Yoshia Leela J; Guide - Dr. PL.Sridevi SivakamiA global looming situation over food safety and quality is that the synthetic food colourants more than the permissible level are being added in foods, causing concern over human health. This study has focused on the impacts of synthetic food colourants stratified through a survey conducted among the selected random samples of food vendors (N=100) and home makers (N=100) in Northern region of Coimbatore city, Tamilnadu, along with which, supermarkets and shops (N=150) were surveyed for popular brands of synthetic food colourants. Equivalent natural food colouring sources were studied, where annatto seeds (Bixa Orellana), eucalyptus bark (Eucalyptus grandis), madder roots (Rubia cordifolia), roselle petals (Hibiscus sabdariffa) and tamarind seeds (Tamarindus indica) were selected. The natural sources were subjected to the processes of aqueous extraction and powdering of the natural substance. Tamarind seeds did not leach out any colour and was ruled out. The shelf life of the natural colourants were monitored in room temperature of 27ºC till tenth day and refrigeration of 5ºC till fifteenth day, where a slimy layer was found at the bottom of the glass bottles in the aqueous extracts which were confirmed to be microbial growth. Microbial assay for fungal and bacteria identification of species were done through Rose Bengal Chloramphenicol Agar Medium and Nutrient Agar Medium, respectively. Then, primary toxicity study was done with brine shrimp assay for all the selected natural food colourants, in which roselle petals showed higher toxicity and was omitted from further analysis. Chemical analysis for antioxidants and phytonutrients were analysed in the samples of annatto seeds, eucalyptus bark and madder roots from which all the substances showed less antioxidant properties and presence of maximum of six to nine metabolites out of 17 metabolites of phytonutrients were present. The aqueous extracts were unstable and started to degenerate the colours, thus further processing was done with powdered substances. Inductive Coupled Mass Spectrometer (ICPMS) analysis was done to detect the heavy metals toxic to human health. In ICPMS, madder root powder had high amount of lead (3.28560 μg), cadmium (0.05162 μg) and chromium (5.48116 μg). Thus, it was not further analysed. During characterization, annatto seeds powder was amorphous in nature with less loss of mass in it, whereas eucalyptus bark powder was crystalline in nature and had a heavy loss of mass whenever there was increase in temperature, while the colours of both the substances were stable. The characterised powders were optimized to determine the level of consumption through an eight weeks (56 days) in vivo study, which revealed that annatto seeds powder can be consumed 3 mg/kg of body weight and eucalyptus bark powder of 6 mg/kg of body weight. The animals were sacrificed, the vital organs were harvested and no significant changes were found in histology and hematological parameters, when compared with the reference ranges. Then to analyse their safety in foods, the selected natural food colourants were incorporated into selected recipes of sweets, snacks and fruit preservatives in accord with the optimized level. Then the natural colour incorporated recipes were checked for discolouring and were evaluated organoleptically which showed an overall of good acceptability ranging between three to four points in five points hedonic scale rating, rated by the selected panel members. Keeping the rating in mind, the researcher has developed a sensor that detects the toxicity in the food colours which hinders the safety of the foods, with the RGB values in the Colour sensor was operated to detect the level of permissible limit prescribed by the FSSAI for each colourant to reveal the level of toxicity present in the solid foods added with commercial food colourants.Item Effectiveness of Developmentally Appropriate Practice-Based Curriculum Framework on Emergent Literacy and Numeracy Skills of Preschoolers(Avinashilingam, 2025-05) Kongkona Sonowal; Guide - Dr. K. Arockia MaraichelviThe early years of a child’s life are crucial for holistic development, laying the foundation for physical, cognitive, emotional, and social growth. Between ages 3 and 8, children acquire essential skills that influence their academic success and lifelong learning. Recognising this, Early Childhood Care and Education (ECCE) has gained global and national focus. In India, the National Education Policy (NEP) 2020 prioritises universal access to quality ECCE and foundational literacy and numeracy. Despite this, significant gaps remain in ECCE delivery, with issues of quality, access, and equity hindering children’s development. The major challenge is the lack of developmentally appropriate, culturally responsive pedagogical framework to support Emergent Literacy and Numeracy, essential skills of school readiness. These gaps underscore the urgent need for context-specific, evidence-based interventions to translate policy into effective classroom practice. Furthermore, the systematic review conducted in the initial stage using the PRISMA model substantiates the critical and persistent challenges in India’s ECCE system, underscoring a significant disconnect between ECCE policy intentions and on-ground implementation. The findings of the systematic review not only identified the systemic barriers but also pointed towards actionable reforms in terms of DAP’s five key dimensions as outlined by the National Association for the Education of Young Children (NAEYC). Henceforth, with a realisation that adopting DAP is not just a pedagogical choice, but a strategic imperative to achieve equitable, inclusive, and high-quality early education in India. In response to this need, the present study was undertaken with the primary objective of developing a DAP-based curriculum framework focused on Emergent Literacy and Numeracy Skills of preschoolers. Secondary objectives included assessing skill acquisition under the existing pedagogical framework, examining the impact of socio-demographic factors on these skills, and implementing and evaluating the effectiveness of the DAP-based curriculum in enhancing these foundational skills. The study was conducted in two sequential phases. Phase I employed a cross- sectional research design to establish a baseline understanding of the Emergent Literacy and Numeracy Skills of preschool children. A sample of 281 children, aged 3 to 6 years,was drawn from five private ECCE centres in Coimbatore District, of Tamil Nadu. An “Emergent Literacy and Numeracy Assessment Pack”, a modified version of the North Carolina Kindergarten Common Core Standards (2017), was used as the assessment tool, which was tailored to suit the Indian context. The assessment tool included 22 items divided between Emergent Literacy and Numeracy Skills. The Emergent Literacy comprised 13 items, with a focus on Reading Skills such as Phonological awareness, Print awareness, and Listening comprehension. Writing Skills involving Alphabet and Number writing. Emergent Numeracy Skills contained 9 items, covering key areas such as Number and operation, Data analysis, measurement, Algebra and pattern making, Geometry and spatial awareness. Moreover, socio-demographic markers - such as age, gender, birth order, parental educational and occupational status - were collected to identify patterns or disparities in skill acquisition across different backgrounds. Percentage analysis and ANOVA were carried out in the subsequent phase. Phase II of the study adopted a "Before and After with Waitlist Control Group" design. A total of 62 children, aged 4–5 years, from four of the preschools of phase I were selected and equally divided into an experimental group and a control group. A Developmentally Appropriate Practice (DAP)-based curriculum framework focused on Emergent Literacy and Numeracy Skills was developed, drawing on the HighScope and Head Start curricula, with significant adaptations to suit the specific needs and contextual realities of Indian preschools. The curriculum was implemented over a period of 70 working days by the educators who were trained for 7 days. A pre and post-assessment test was conducted using the same adapted tool from Phase I, and results were analysed using ANCOVA statistics.Key findings of Phase I revealing the existing levels of Emergent Literacy and Numeracy Skills demonstrated that the educators' practices were particularly effective in fostering Listening comprehension and Number writing skills. While some children aged 3 to 4 and 4 to 5 were in the gaining stage in Print awareness, mastery level in Phonological awareness, and Alphabet writing, and just approaching level in all indicators of Numeracy Skills. Over a quarter of 5–6-year-olds remained at lower performance levels across these areas. These findings further confirm the need for a suitable pedagogical framework grounded in DAP. Further, significant associations were identified between various socio- demographic factors and these foundational skills. Birth order influenced Listening comprehension and Number operation skills of the preschoolers, with first-borns performing better. Writing skills and Number and operation were linked to the type of ECCE centres. Fathers’ education was significantly related to Number writing, Geometry and spatial awareness, and Algebra and pattern-making, while mothers’ education influenced Listening comprehension, Phonological awareness, and Algebra and pattern- making. Fathers’ occupation was associated with Print awareness, and mothers’ occupation impacted Listening comprehension, Geometry and spatial awareness, and Algebra and pattern-making Skills. The key findings of Phase II revealed that except for Listening comprehension, all other indicators of Emergent Literacy and Numeracy showed significant positive effects following the DAP-based intervention, with moderate to high effect sizes demonstrating the curriculum’s effectiveness. Phonological awareness had a large effect size of 78%, reflecting the success of rhyming and phoneme manipulation activities. Print awareness improved moderately by 25%, showing increased engagement with print. Writing skills saw notable gains, with Alphabet writing improving by 27% and Number writing by 54%, highlighting the impact of structured, age-appropriate, play-based activities. Numeracy skills also improved significantly across domains: Number and operations (43%), Data analysis and measurement (64%), Algebra and pattern-making (41%), and Geometry and spatial awareness (54%). Thus, the developed DAP-based curriculum framework holds strong potential to bridge existing gaps and significantly enhance preschoolers’ Emergent Literacy and Numeracy Skills. Additionally, aligning ECCE efforts with the Sustainable Development Goals (SDGs) - particularly SDG 4 (Quality Education) - ensures that such initiatives contribute to inclusive and equitable quality education for all children, promoting lifelong learning opportunities and supporting broader social and economic development. Key words : ECCE, NEP, Preschoolers, DAP, NAEYC, Emergent Literacy and Numeracy Skills,Emergent Literacy and Numeracy Assessment Pack, Preschoolers, ANCOVAItem Energy Efficient Congestion Control Techniques in Wireless Sensor Networks(Avinashilingam, 2024-06) Vanitha G; Guide - Dr. P.AmudhaIn Wireless Sensor Network (WSN), the congestion is controlled by many strategies like congestion detection and avoidance. The rate control is one of the most significant strategies for mitigating the congestion. The priority based rate control algorithms have been proposed in the literature to overcome the congestion due to transmission of the Real Time (RT) data together with the Non-Real Time (NRT) data,but congestion in a network still remains a challenge. The RT data traffic may often be bursty in nature, combined with the high priority NRT data makes the problem more compounded. Neither the fair allocation of bandwidth on different nodes nor prioritizing the traffic class suffices to overcome congestion in a network. As a long queue might sometimes use more than half of the buffer, leading to significant packet loss and delay, a Proficient Rate Control (PRC) algorithm is proposed in the first phase of research by considering Weighted Priority Difference of Differential Rate Control (WPDDRC) with an adaptive priority based system to address the buffer occupancy and queue size. Each child node's input packets are accumulated in one of two virtual queues on a single physical queue, one for low priority traffic and another for high-priority traffic, both are made possible by the PRC algorithm. When a packet is successfully received, the PRC determines whether there is congestion in the virtual queue and then adjusts the transmission rate of child node accordingly. The PRC technique may control the consequent buffer overflow and congestion in WSN by considering the priority of each traffic type and the current queue status. The Proficient Rate Control with Fair Bandwidth Allocation (PRC-FBA) method is proposed in the second phase of research, with the principles of traffic type priority and equitable assignment of bandwidth. The Signal to Noise Interference Ratio (SINR) model is used for bandwidth distribution in WSN which is used to balance between fairness and performance. Next, a novel utility factor for bandwidth is given in terms of productiveness and fairness. The approximate solution is derived from the sum of the node-to-node computation and the allocation of time slots. Then, the problem has been framed as a non-linear programming problem, partitioned into two halves and the 2-phase approach has been adopted. During the first stage, the connections between nodes are calculated, and in the second stage, time slots are allotted with the goal of optimizing the utility factor. As a consequence, WSNs are able to increase their efficiency and achieve more equitable bandwidth distribution. Proficient Rate Control Data Aggregation Fair Bandwidth Allocation (PRCDA-FBA) is proposed in the third phase of research that makes use of a powerful data aggregation mechanism to maximize the equitable consumption of battery life across all involved nodes. On the other hand, Random Linear Network Coding (RLNC) is used to reduce transmission frequency, increased network channel capacity, which enhanced overall network throughput. The network coding path combines data for transmission to the next hop, increasing channel usage and reducing packet redundancy in the network. When congestion occurs, an adaptive methodology is triggered in which node transmits data using network coding to decrease packet dropping rate. In addition, Long Short-Term Memory (LSTM) recurrent neural networks, which can learn long-term dependencies, enhance the bandwidth allocation of PRCDA-FBA. They have a temporal dimension that allows them to determine patterns in data sequences. The bandwidth utilized in the past events with parameters like packet drop rate, energy, priority of packets and delay of packets are used to predict the future bandwidth requirements of path. In the fourth phase of research work, Enhanced Priority Rate Control Data Aggregation Fair Bandwidth Allocation (EPRCDA-FBA) is proposed to further save energy utilization and improve network life time. The major purpose of this work to ensure that Quality of Service (QoS) standards are met in terms of delayed data delivery,reduced energy consumption of energy-intensive nodes and increased network lifespan. This protocol's priority-based technique of regulating data transfer rates considers the node's spare processing capacity of node. Then, a prediction model is utilized to work out how much of a dip in node transmit power can be tolerated without significantly impacting the packet delivery ratio. Then, to avoid overhearing energy-critical nodes, a priority of nodes for delivering traffic classes of packets is determined using a combination of energy.Item Securing the VANET through a Hybrid Approach by Mitigating DoS Attacks and its types with Self-healing and Immunization(Avinashilingam, 2025-01) Rama Mercy S; Guide - Dr. G. PadmavathiVehicular Ad Hoc Networks (VANETs), crucial for Intelligent Transportation Systems (ITS), face significant security threats, especially Denial of Service (DoS) and Distributed DoS (DDoS) attacks. These attacks disrupt communication, leading to packet loss, increased latency, and reduced reliability. While existing solutions like trust-based models, cryptographic techniques, and machine learning approaches exist, they often fall short in detection accuracy, energy efficiency, adaptability to mobile environments, and managing system overhead. This research, titled "Securing VANETs through a Hybrid Approach: Mitigating Denial of Service (DoS) Attacks and its types with Self-healing and Immunization," proposes a three-phase methodology to enhance the security of VANETs. It leverages a hybrid approach having six key contributions with the major objective to secure VANETs—a key part of Intelligent Transportation Systems—from DoS attacks by detecting and preventing these attacks including self-healing and immunization features. The scope of the research tends to focus on DoS attacks and its types with multi-layered defense incorporating security and robustness. In Phase 1, the objective is to detect and isolate vehicles under malicious DoS attacks with optimized feature selection using GLW-SLFN (Glow-worm Single Layer Feed Forward Neural Network). MCOD-LR (Micro Cluster Outlier Detection and Linear Regression) is applied to detect malicious behavior for multi-class DoS attacks. Furthermore, Kernel Density Estimation and Entropy-based SVM (Support Vector Machine), incorporating trust factors, are leveraged to detect, predict, and classify DoS attacks. A Bayesian aggregate model, in conjunction with Self-healing AIS (Artificial Immune Systems), ensures the continuous monitoring, detection, and isolation of these attacks.The changing topology in VANET remains a challenge in securing VANET operations. This challenge is addressed in phase 2, as the traffic signals are encrypted using Triple Random Hyperbolic Encryption (TRHE) integrated with Hex-Tuple Matched Mapping, which classifies twelve types of DoS attacks. The classification relies on mapping reports and a Deep Trust Factorization Neural Network (DT - NN).Furthermore, to achieve stable data transmission and routing even with dynamic network topology, phase 3 is proposed to immunize the behavior of its clusters by the Deep Trust Factorization Neural Network (which provided trust scores), the Moth Flame Optimization (MFO) Algorithm, and Cache Parallelized Circulation Link Routing (CCL). The system achieved stable data transmission and routing, even with dynamic network topology, due to the immunized behavior of its clusters. The Moth Flame Optimization (MFO) algorithm optimizes the Packet Delivery Rate (PDR) essential for ensuring data is delivered efficiently. This system efficiently creates stable clusters and identifies reliable relay nodes within a VANET. This feature enables the isolation of malicious nodes, directly leading to a significant increase in the Packet Delivery Rate (PDR). The performance of Phase 1 demonstrated significant improvements: a 37% increased detection rate over AODV, 32% over Trust-based methods, and 20% over Firecol. The approach also reduced energy consumption by 38% compared to AODV, Trust-based, and Firecol. Furthermore, it achieved a 25% lower latency, markedly outperforming AODV (95%), Firecol (58%), and the Trust-Based Framework (27%). Building on this, Phases 2 and 3 collectively enhanced overall performance, resulting in a minimized packet loss of 0.5 bits for 200 nodes, a maximized attack detection accuracy of 97%, and a Packet Delivery Ratio (PDR) of 98%. These figures represent a substantial improvement over existing techniques: Trilateral Trust (42% accuracy, 60% PDR), Host- based Intrusion Detection System (H-IDS) (60% accuracy, 70% PDR), Multi-filter (80% accuracy and PDR), and Stream Position Performance Analysis (SPPA) (90% accuracy and PDR). This approach demonstrates remarkable scalability and adaptability, particularly in challenging environments with high node mobility and dense vehicular traffic. The methods ensure resilient network operations in intelligent transportation systems, delivering reduced energy usage, lower communication delays, and high detection accuracy for secure, reliable, and scalable communication. This research provides highly relevant solutions for real-time VANET applications, effectively incorporating self-healing, immune-inspired mechanisms.Item Computation of Nutritional Footprint of Food Consumed by Selected Subjects and Creating Awareness on Planetary Health Diet using the Developed e-Application(Avinashilingam, 2024-11) N. Komathy; Guide - Dr. R.RadhaThe Planetary Health Diet has been developed by the EAT-Lancet Commission; the diet aims to promote both individual well-being and the health of the planet by offering a set of guidelines for sustainable and nutritious food consumption. The study was carried out with the primary objective of promoting a sustainable food ecosystem by following a planetary health diet. The secondary objectives were to analyze the knowledge, attitude, and practice of the planetary health diet among selected subjects, to calculate the carbon and nutritional footprint of the food consumed by selected subjects, to develop and evaluate an e-application for promoting the planetary health diet, and to create awareness about the importance of the planetary health diet and analyze the pre- and post-knowledge levels on the planetary health diet among selected subjects. Nearly 400 women subjects within the age group of 30–50 years were selected using the purposive random sampling method. A survey was also conducted to analyze the pre- and post-knowledge, attitude, and practice of the planetary health diet, and the carbon and nutritional footprint of food consumed by selected subjects after awareness was calculated. Further, an e-application for promoting the planetary health diet was developed. The results highlight that there was a statistically significant negative relationship between the knowledge of the subjects and their adherence to the planetary health diet. This suggests that enhanced knowledge alone may not be sufficient to drive behavior change, and other barriers such as accessibility, cultural preferences, or personal habits may inhibit adherence. The carbon footprint of the study subjects in the 30–35 age groups was higher than all other age groups. Additionally, the 46–50 age groups had the lowest carbon footprint, followed by the 41–45 age groups. Further, there was no significant difference between the implementation of a planetary health diet before and after the awareness program. This implies that while the subjects are cognizant of the significance of a planetary health diet, they fail to put it into practice even after receiving the necessary information and guidance. The planetary health diet is a holistic approach to nutrition that not only promotes human health but also aims to safeguard the well-being of the planet.Item Exploring the Factors Influencing Disaster Preparedness Behaviour of Local Residents in Disaster Affected Tourism Destinations in Kerala(Avinashilingam, 2025-04) Sharon Treesa Abraham; Guide - Dr.V. T. BinduDisaster preparedness possesses the capacity to alleviate the detrimental consequences in destinations. Wayanad and Kozhikode districts are well known tourism destinations in Kerala and highly susceptible areas to disasters. The disasters have been continuously affected by disasters in recent years and drastically caused impact on the tourism industry in which the districts rely upon. The local community, tourists, tourism destinations are severely affected by the disasters. Due to the vulnerable situations of the districts, the significance of disaster preparedness cannot be overstated; but preparedness is an ongoing, adaptive process. The study not only addresses residents’ preparedness but how they evolve their behaviours for improving future preparedness efforts. The behaviour centric model developed emphasizes an integrated approach of residents for community-based crisis management. The study was supported by the Theory of Planned Behaviour and Place Attachment Theory to elucidate the preparedness behavior of vulnerable residents in Wayanad and Kozhikode districts. The study addressed the gap on dentification of residents’ behavioural factors and evaluated the causal relationship of influencing factors on Disaster Preparedness Behaviour (DPB); also identified the mediating roles of Self Efficacy (SE), Community Participation Attitude (CPA) and Community Participation Intention (CPI) between Place Attachment (PA), Risk Perception (RP) and DPB. To investigate the context, questionnaires were distributed to the residents of disaster affected tourism destinations of the districts through stratified sampling. Behavioural Dynamics of Disaster Preparedness framework was developed to explain the behavioural factors and the SEM model analysis shows overall good fit. The findings of the relationship between the influencing factors and DPB show that significant relationship exists between PA, SE, CPI to DPB. And insignificant relationship exists between risk perception and DPB. The insignificant relationship shows the compelling necessity for the sensitive destinations through alternative disaster preparedness approach to enhance risk reduction. SE has partial mediation between PA and DPB. CPA and CPI have mediating roles between RP (Full), PA (Partial) and DPB. The study provides insights to tourism stakeholders in building a framework for disaster preparedness practices to cope with future disasters through psychological and behavioural factors to shape decision- making for related actions. Also contribute to the existing body of literature of behavioural theory of disaster preparedness for sustainable development. Keywords: Disaster Preparedness Behaviour, Place Attachment, Community Participation Intention, Self Efficacy, Risk PerceptionItem Responsible Tourism Practices and Support for Sustainable Tourism Development: The Perspectives of Local Community in Wayanad(Avinashilingam, 2025-01) Nimi Markose; Guide - Dr.V .T .BinduSustainable tourism gained significant attention in the 1990s. Responsible Tourism Practices (RTP) emerged as a key framework to ensure tourism development that aims to attain sustainability goals, community benefits, increased environmental protection, and social justice. RTP emphasizes the involvement of local communities, as their engagement and attitudes directly influence tourism's outcomes. Wayanad was selected as a pilot region for RTP implementation in Kerala due to its socio-cultural and environmental significance. However, there needs to be more research on how responsible tourism practices have been applied in Wayanad and their effects on local communities. This study aims to bridge this gap by evaluating the implementation of RTP in Wayanad, focusing on how it affects local communities' perceptions of tourism impacts, their Quality of Life Satisfaction (QOLS), and their support for sustainable tourism development (SSTD). It integrates the Triple Bottom-Line Theory, exploring the interaction between tourism impacts (economic, social, environmental, and cultural), community well-being, RTP, and OQLS. The research adopts a quantitative methodology, using statistical tools such as Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Structural Equation Modelling (SEM), and Moderation Analysis to test the relationships. The findings reveal a positive relationship between tourism impacts and residents' well-being across various life domains, influencing their overall quality of life satisfaction and support for sustainable tourism. RTP significantly moderates the effects on economic, social and environmental dimensions of quality of life satisfaction, although it does not significantly moderate the cultural impacts on emotional well-being. These results suggest responsible tourism practices can improve community’s well-being amidst tourism development. Still, there is a need to mitigate the negative effects to enhance emotional well-being. This study contributes to tourism theory by introducing a Responsible Tourism Model that links tourism impacts, Sense of well-being in all life domains, and OQLS to SSTD. The model offers valuable insights for tourism planners and stakeholders, advocating for a more nuanced approach to RTP implementation that addresses both positive and negative tourism impacts. Further research is needed to explore the cultural dimensions of RTP and emotional well-being in depth. Keywords: Tourism Impacts, Sense of well-being in various Life Domains, Overall Quality of Life Satisfaction, Responsible Tourism Practices, Support for Sustainable Tourism Development.Item Finger Vein Biometric Authentication using Deep Learning Techniques with Hybrid Labelling and Data Augmentation(Avinashilingam, 2025-05) Amitha Mathew; Guide - Dr. P. AmudhaBiometric systems, designed to identify individuals through unique biological or behavioural characteristics, have become critical in modern security and identity verification applications. Finger vein authentication, which utilizes the unique vascular patterns within a person’s finger, offers intrinsic security due to the internal and difficult-to-replicate nature of vein patterns. However, the accuracy and reliability of finger vein recognition systems are heavily influenced by the quality of feature extraction techniques and environmental factors, such as motion artifacts, lighting, and finger positioning. This study focuses on developing a motion-tolerant deep learning model for finger vein recognition by employing advanced image labelling and dataset augmentation techniques. Traditional finger vein recognition systems rely on handcrafted features and classical machine learning algorithms, which face limitations in adaptability and accuracy under variable conditions. Recent advancements in deep learning have demonstrated the potential to automatically extract complex patterns from raw image data, addressing these challenges. In the first phase, a modified UNET and VGG16 model are used for recognition and the performance have been compared on the benchmark datasets, SDUMLA-HMT and THUFV. The U-Net, originally developed for biomedical image segmentation, has been modified by incorporating a fully connected layer, extending its capabilities to include classification tasks. VGG16 outperformed UNET across multiple metrics, with its deep feature extraction capabilities enabling it to capture intricate vein patterns and achieve higher classification accuracy. VGG16 also demonstrated superior precision and recall, minimizing false negatives and improving robustness in practical applications. The second phase explores the impact of using a hybrid labelling algorithm on the VGG16 model’s performance. By accurately labelling finger vein images, the model is able to learn detailed vein patterns more effectively, leading to improved recognition accuracy and reduced over fitting. This phase emphasized the importance of creating diverse and representative datasets to enhance the model’s generalization ability. In the third phase, various dataset augmentation techniques are investigated, including conventional transformations (rotation, scaling, and flipping) and an advanced approach using Generative Adversarial Networks (GANs). The experimental results revealed that the augmentation techniques significantly enhanced the diversity and quality of the training dataset, further improving the VGG16 model’s recognition performance. In the final phase, an adaptive finger vein recognition system that integrates VGG16 for feature extraction with Long Short-Term Memory (LSTM) for sequence learning has been developed. This motion-tolerant model is designed to handle real-world conditions, including motion artifacts and environmental variations, ensuring accurate recognition even when the finger is not perfectly still. The architecture was tested on the THUFV and SDUMLA-HMT datasets, demonstrated improvements in accuracy and robustness. This research demonstrates the effectiveness of combining VGG16 and LSTM architectures along with labelled and augmented dataset, to develop a reliable and scalable motion-tolerant finger vein recognition system. The findings contribute to the advancement of biometric authentication technologies, offering a robust solution for real-world applications.Item Prediction of Heart Diseases Risk Using Novel Machine Learning Techniques(Avinashilingam, 2024-11) Anuradha P; Guide - Dr. Vasantha Kalyani DavidHeart diseases are a major health concern globally and early detection of the disease plays a crucial role in reducing mortality rates and improving patient outcomes. With the advancements in machine learning, there is an increasing focus on utilizing these techniques to enhance the prediction and diagnosis of heart diseases, even before symptoms manifest. Machine learning (ML) research in this field aims to develop accurate and efficient models that can assist in early detection, risk assessment, and clinical decision-making. There are a variety of ML methods making use of stand-alone classifiers and hybrids. However, the results from these models vary considerably between various cardiac datasets and/or they are not modeled using both low and high dimensional data. With increased dimensionality of data, it becomes imperative to address shortcomings of existing feature selection and prediction approaches in handling such datasets with complicated feature relationships and significant degrees of redundancy. This research identifies and addresses issues with existing feature selection and classification methods and proposes novel and improved feature selection and classification techniques towards enhancing and improving heart disease prediction performance. In the first stage of work, feature selection using Feature Importance (FI) ranking of Gradient Boosting algorithms is done and a significant reduction in the search space of feature subsets is identified. Next, this research work proposes a novel feature selection algorithm called ModifiedBoostARoota (MBAR), which identifies the risk parameters that strongly contributes to the prediction of heart disease. This algorithm incorporates CatBoost as the base model and utilizes a novel feature elimination process. In the second phase of the work, a novel Super Learner Ensemble Model (SLEM) is proposed to perform on features selected by MBAR. The SLEM model is an integration of diverse ML base models selected by repeated stratified k-fold cross validation. A meta learner logistic regression is employed to learn from the predictions of the base classifiers. By backward elimination method, an optimal combination of classifiers in SLEM was identified as Catboost and Decision Tree, in order to improve the classification time complexity and performance. The performance of the SLEM model improved when used on features selected by MBAR compared to its performance on datasets with no feature selection. In the third phase of the work, to further improve the classification by selecting an optimal combination of base classifiers in the Super Learner Ensemble Model (SLEM) model, a new Optimized Super Learner Ensemble Model (OSLEM) is proposed. OSLEM utilizes the Whale Optimization Algorithm and pairwise divergence measure to select an optimal base classifier combination. The performance of the final proposed model where ModifiedBoostARoota algorithm is used for feature selection and Optimized Super Learner Ensemble Model (OSLEM) is used for classification was analyzed on both low and high dimensional heart datasets. The proposed model presented high performance in terms of recision, recall, f1-score, specificity and accuracy, when compared with existing models across the heart datasets. The proposed model improved prediction accuracy while being robust against overfitting. Overall, the contributions from this research work would improve the accuracy, efficiency, and decision-making support of heart disease prediction systems, ultimately benefiting clinical practice.Item Chitosan nanoencapsulation of garlic and turmeric essential oils for its insecticidal and antifungal activities against stored groundnut(Avinashilingam, 2024-08) Sindhu M; Guide - Dr. C. A. AnnapooraniAgriculture and food processing are crucial industries in any country, especially in emerging economies. Stored grain insect pests and microbes control mainly depend on synthetic pesticides, recent scientific research is vital in developing new sustainable and eco-friendly approaches. In this study, garlic essential oil (GEO) and turmeric essential oil (TEO) were nanoencapsulated within chitosan nanoparticles (CSNPs) to create an innovative preservative aimed to protect stored food from insect pests and fungal infection. The GC-MS analysis of GEO identified allyl methyl trisulfide-23.10% and diallyl sulfide-19.47% as the predominant components, while TEO primarily contained α- turmerone-42.0% and β-turmerone-14.0%. The encapsulated of GEO and TEO into chitosan nanoparticles (GEO-CSNPs and TEO-CSNPs) was achieved using the ionic-gelation method and confirmed through TEM micrograph, DLS, XRD, and FT-IR analyses. The in vitro DPPH free radical activity of GEO-CSNPs and TEO-CSNPs showed a significant increase compared to non-encapsulated GEO and TEO. Additionally, GEO-CSNPs and TEO-CSNPs exhibited stronger insecticidal, repellent, and antifeedant activities against adults C. serratus, and T. castaneum, compared to GEO/TEO. Growth regulated gene expression levels of InR and Cyclin E were found to be reduced in the LC20 and LC50 treatment in comparsion to the control group, conversely, LC20 and LC50 treatments exhibited high expression levels of 4EBP and FOXO in T. castaneum. In vitro experiments demonstrated that GEO-CSNPs (1.0 μL/mL) and TEO-CSNPs (0.75μL/mL) effectively inhibited the growth of A. flavus at low doses, while also preventing AFB1 synthesis at concentrations of 0.75 μL/mL and 0.50 μL/mL, compared to the pure GEO and TEO. The biochemical analysis revealed that exposure to GEO-CSNPs and TEO- CSNPs significantly altered the ergosterol level, ions leakage, mitochondrial membrane potential (MMP), and antioxidant system of A. flavus. Similarly, in-situ tests on A .hypogea showed that GEO-CSNPs and TEO-CSNPs at MIC and 2 MIC concentration inhibited fungal growth, AFB1 production, and lipid peroxidation without affecting the seeds. Overall, these experiments suggest that EO-based nanoformulations could enhance insecticidal efficacy against pests, improve antimicrobial activity against stored foodborne pathogens, and serve as innovative preservation agents to extend the shelf life of deposited food products.Item Impact of Creating Awareness on Environmental Hygienic Practices Among Selected Urban Slum Households(Avinashilingam, 2024-11) Vidhya J; Guide - Dr.K.ManimozhiIndia's urban slums have serious environmental hygiene issues, such as poor waste management, poor sanitation, and a lack of awareness, which pose serious health concerns. The purpose of the study, "Impact of Creating Awareness on Environmental Hygienic Practices Among Selected Urban Slum Households," was to determine the current state of hygiene, gauge the level of awareness among a subset of urban slum women, develop training materials, implement an environmental hygiene awareness campaign, and analyze its results. This study examines the impact of an environmental hygiene awareness program in an urban slum, with a specific focus on how women's knowledge, attitudes, and practices have evolved. 500 households participated in the study, and the results showed that 38 per cent of family heads lacked literacy and 86 per cent of family heads and 67 per cent of homemakers were older than 31. Eighty percent of houses disposed of sewage water incorrectly before the intervention, resulting in poor sanitation and mosquito breeding. Additionally, 87per cent of homes had trash and standing water surrounding them, while only 34per cent of interiors were tidy and clean. Notable gains were noted after the awareness program. The knowledge-practice correlation, which rose from an insignificant level to 0.671, indicated significant behavioral change. Before the intervention, only 20per cent of respondents had strong hygiene awareness, 55 per cent had fair knowledge, and 25per cent had poor understanding. 71 per cent achieved good knowledge after the training, indicating a notable improvement. Similarly, 54 percent of people exhibited good hygiene behaviors, up from 26 percent who practiced poor hygiene and 56 percent who practiced fair hygiene. The frequency study also revealed that 85 per cent of people were aware of the health risks associated with open defecation, and 97 per cent were aware of the need to separate waste into wet and dry categories. Compared to lower levels before the intervention, hand-washing awareness increased, with 31per cent recognizing its significance. Additionally, with the help of NGOs and government organizations, structural improvements, including better drainage and waste management facilities, were implemented. Following awareness training, environmental cleanliness habits showed significant improvement (p < 0.05), as indicated by statistical analysis. The results demonstrate the value of organized awareness and training campaigns in changing personal hygiene practices, thereby improving public health in urban slum areas. To ensure long-term behavioral changes and improvements in environmental cleanliness, this study emphasizes the importance of sustainable intervention strategies and government support. Community involvement, government action, and ongoing education are essential for achieving and maintaining long-lasting hygienic improvements. These findings underscore the importance of continuing support in promoting long-term behavioral change, ultimately leading to a healthier and cleaner environment for residents of urban slums. Key Words: Environmental Hygiene, Households, Hygiene Education, Public Health, Urban Slum, Waste Management.Item Exploring the Essence of Suruti Raga through Musical Forms with Special Reference to the Kritis of Tyagaraja and Muthuswamy Dikshitar(Avinashilingam, 2025-01) Praseeda Bal; Guide - Dr.V.Janaka Maya DeviIn Carnatic music, ragas are having vital role. The concept of raga said to be developed from Matanga’s period (6th- 9th century).It has undergone many changes through the ages but its fundamental characteristics have never been disputed. It is not merely a musical scale, but it is a systematic arrangement of notes. Carnatic music is generally based on two classifications of ragas-Janaka and Janya. There are 72 Janaka ragas (Melakarta ragas) in Carnatic music. Many ragas are derived from these Melakartha ragas are termed as Janya ragas. In Carnatic music Janya ragas are mainly classified into Upanga, Bhashanga,Vakra and Varja. According to the scale of notes these Janya ragas again classified into many groups like Svarantara, Audava, Shadava, Sampurna and many other combinations. The raga Suruti is a gem among the Janya ragas. It is a Janya raga of the 28thMelakartha, Harikambhoji. Suruti is an Upanga Audava Vakra Sampurna Janya raga. Currently it is also considered as an Ubhaya Vakra Shadava Sampurna raga. Raga is the foundation within which all the compositions are being created. Raga is the most significant concept in music composition, and raga classification is pivotal in Indian music theory.Musical forms or compositions have many musical structures, resulting in all shades of a raga. In Carnatic music Suruti raga has utilized almost in all musical forms. This thesis is entitled ‘Exploring the Essence of Suruti Raga through Musical Forms with Special Reference to the Kritis of Tyagaraja and Muthuswamy Dikshitar’ is divided into four chapters excluding introduction and conclusion. The first chapter is tracing out the name of the Parent raga of Suruti: Harikambhoji from selected Lakshanagrandhas. The second chapter is exploring the significance of Suruti raga in various aspects.The third chapter is the execution of svaras of Suruti through various musical compositions of different composers.The fourth chapter,is having the detailed analysis of the Suruti raga compositions of Tyagaraja and Dikshitar. This study is based on the richness of the raga Suruti and tracing out the bhava through different musical compositions of various composers.Item Photodegradation, Anti-bacterial and Self-cleaning Analysis of Surface Modified Zinc Oxide and its Composites for Environmental Remediation(Avinashilingam, 2025-01) Cathelene Antonette L; Guide - Dr. J. ShanthiGlobalization and industrial expansion have increased environmental pollution. Discharge of untreated dye effluents into the waterways disrupts marine ecosystem and also poses considerable risks to human health. Developing nanomaterials as absorbents is an effective alternative for removing the organic and inorganic contaminants, and also an alternative treatment for microbial disinfection. Increased surface area of the nanoparticle facilitates generation of more hydroxyl radicals which participate actively in dye degradation, but they often lead to particle aggregation, which is a significant challenge. Hence, can be reduced using suitable surface modifiers for the photocatalytic nanomaterials. In this work environmentally stable, reusable photocatalytic material was synthesized for reducing environmental degradation. Nanomaterials of ZnO, ZnO/PEG and various combinations of silane (MTMS, MTES, VTMS and VTES) were synthesized by sol-gel technique. The semiconducting metal oxide and its surface modified nanocomposites were tested for their structural, morphological, optical, antibacterial activity, and photocatalytic degradation efficiency with UV and visible light exposure. Photodegradation analysis was done for Methylene blue, Malachite green and textile dye wastewater. ZnO/PEG/VTMS exhibited better degradation efficiency than all other composites due to its reduced crystallite size and PL intensity. The composite exhibited high stability and was found to be reusable even after five cyclic degradation of textile dye wastewater. Hence, this particular sample works as an efficient photocatalyst for dye effluent treatment. All the composites exhibited better antibacterial activity against the bacterial pathogens (Staphylococcus aureus, Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa) than the control (Teicoplanin) used. Enhanced bacterial inhibition to gram positive bacteria than gram negative bacteria were noted. Optically transparent hydrophobic thin films were fabricated using sol-gel based spin coating technique for different silane-PEG combinations. The hydrophobic films with water repellent behavior demonstrated better self-cleaning activity. Stearic acid was deposited on ZnO/PEG/Silane film and its degradation upon UV irradiation was analyzed using FTIR and water contact angle analysis. Upon exposure to UV light, reduction in the hydrophobic behavior of the surface was observed due to photo-induced catalysis, confirming degradation of stearic acid. Among all composite films, ZnO/PEG/VTMS exhibited better degradation of stearic acid. Therefore, the composites aids in reducing environmental degradation.Item Hybrid Transfer Learning Models for Video Anomaly Detection in Surveillance Systems(Avinashilingam, 2025-03) Sreedevi R Krishnan; Guide - Dr. P. AmudhaIn a modern civilized community, public safety is of prime importance, and the detection of anomalous events has become a vital factor for a successful security system. Conventional Video Surveillance (VS) methods are inadequate for identifying anomalous events by themselves. It is due to their inability to analysis large sequential data in dynamic environments. Video Anomaly Detection (VAD) has undergone swift development with the emerging Artificial Intelligence (AI) technologies. The research addresses the challenges of conventional VAD and proposes hybrid Deep learning (DL) models using transfer learning techniques for an efficient VAD system in dynamic environments. The application range of VAD is not limited to but includes social, commercial and industrial surveillance systems. Traffic management in urban areas, crowd management, emergency response and resource optimization are VAD's key application fields. The wide requirement for intelligent VAD inspires the design and development of reliable and efficient video surveillance systems capable of automating Anomaly Detection (AD) with minimal human intervention. The study develops and evaluates four hybrid models for VAD using Deep Learning techniques based on transfer learning to obtain improved performance. The first research phase proposed a CNN-YOLO hybrid model capable of anomaly detection. This model uses CNN for model training and modified YOLOv4 for object detection, ensuring accurate and high-speed anomaly detection. This model processes a single random frame out of 100 input frames and yields a faster response. The CNN-YOLO have high accuracy and faster response but being a small model, it samples a random frame input only. To overcome this limitation and the inability of sequential video processing of the CNN-YOLO model, a hybrid model comprised of Residual Network (ResNet) and Long Short-Term Memory (LSTM) was executed in the second phase. This model can execute feature extraction and sequential information processing in more than thousands of video frames. ResNet-50 is employed for spatial feature extraction and LSTM to capture temporal relationships of the input video data even though this hybrid model enhances detection capability but has low accuracy, efficiency and generalization skill due to overfitting. In the third research phase, a segmentation-based anomaly detection technique is implemented, reducing overfitting. This model is constituted by hybridizing Improved UNet (IUNet) with the Cascade Sliding Window Technique (CSWT). In the IUNet-CSWT hybrid model, standard convolutional layers of IUNet are replaced with a ConvLSTM for spatiotemporal feature extraction. CSWT estimates the anomaly score of the input video and thus classifies it to normal and anomalous events. This model is equipped for processing complex patterns since it has an effective equilibrium between generalization skill and precision. A low false positive rate and high detection accuracy make the model work effectively in crowded environments. The fourth phase implemented a Hierarchical Multiscale-CNN with LSTM model, enhancing multi-scale feature identification and temporal data analysis. This model can work efficiently even in low-resolution video utilizing a Bilateral-Wave Denoise Technique. Multi-scale CNN is augmented by a Spatial Pyramid Pooling (SPP), which enhances the feature extraction. The performance of this model outperforms all the other models.Item Efficacy of Expressive Arts Therapy to enhance Academic Achievement among Learning Disabled Adolescents(Avinashilingam, 2024-10) Vatsala Mirnaalini; Guide - Dr. S. GayatrideviThe current study aimed to enhance academic achievement among Learning Disabled Adolescents using Expressive Arts Therapy and Brain Gym technique. The Research Design used was before, after and follow-up with waitlist control group. Raven’s Standard Progressive Matrices, Schonell: Graded Reading Test, Schonell: Graded Spelling Test, The Schutte Self Report Emotional Intelligence Test, Social Competence Scale, Moss Attention Rating Scale, Youth Disability Screener, Digit Span Test were administered to the participants. Initially 80 participants underwent IQ test and filtered to 70 participants. Out of 70 participants, 66 became part of the study with 35 participants in experimental group and 31 in waitlist control group. The participants in the experimental group took part in the Expressive Arts Therapy and Brain Gym intervention for 8 weeks. Participants in the waitlist control group were administered to the same intervention after follow-up phase. The results revealed that most of the participants had scored moderate Emotional Intelligence, Social Competence, Attention, Working Memory, Academic Achievement and Quality of Life. There was significant difference between Learning Disabled Boy and Girl Adolescent students in Emotional Intelligence. There is a significant difference in Experimental group and Waitlist control group in Emotional Intelligence, Attention and Quality of Life. Expressive Arts Therapy and Brain Gym technique had been effective in enhancing the Emotional Intelligence, Social Competence, Working Memory, Academic Achievement of the Learning Disabled Adolescents in the Experimental Group. From the study, it is imperative that Expressive Arts Therapy can be included in the curriculum to enhance the Academic Achievement of the Learning Disabled students and recommends inclusive education. Key Words: Learning Disability, Expressive Arts Therapy, Emotional Intelligence, Social Competence, Academic Achievement