Browse Items (472 total)

• PhD

  Development and Efficacy of Parenting Skill Training for Mothers of Adolescents in Kerala

  The primary objective of this research is to develop and assess the effectiveness of an intervention program tailored for mothers of adolescents in Kerala to strengthen their parenting skills. The digital age and unique socio-cultural context present new challenges in child-rearing, and existing parenting programs fall short of addressing these evolving issues. The study employed a mixed-method framework with specific objectives to fill this research gap. The research unfolded in three phases. The initial stage encompassed comprehensive interviews with ten mothers and their adolescents, utilizing a constructionist model for thematic analysis. It unveiled five main and 22 sub-themes, shedding light on mothers' and adolescents' needs and challenges in Kerala. The second phase focused on designing an intervention module specifically suited to address the needs and challenges identified in the qualitative phase. The study used a pre-test, post-test, and experimental design with a control group for the third phase. The researcher used the Alabama Parenting Questionnaire, the Family Environmental Scale, and the Parental Satisfaction Scale to measure the efficacy of the training. The results presented significant improvements in parenting practices in the experimental group, particularly in positive parenting and mothers' involvement with their children. Corporal punishment and inconsistent discipline decreased, while family environment and parenting satisfaction increased. This study contributes substantially to the mental health field by offering an evidence-based program to assist mothers in navigating parenting challenges during adolescence. This intervention aims to improve family dynamics and adolescent well-being. It is a valuable resource for trainers seeking to facilitate behavioral changes within the target groups.
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  Experience and Agency of Children with Intellectual Disabilities in Schools : An Ethnographic Study in Haryana, India

  India currently has more than 24 million children within the age group of 0-18 years experiencing some form of disability. Among them, India has the highest population of children at risk of developmental disabilities (UNICEF, 2011). However, there is a significant dearth of knowledge regarding their lived experiences. Surprisingly, qualitative understandings of the lives of children with intellectual disabilities within their school environments are lacking in India. Thus, this research aims to fill this gap by focusing on comprehending the lived experiences and agency of these children within their schools, families, and neighborhoods. Recognizing them as social agents has the potential to challenge the marginalized status often attributed to them. The objective of this research was to understand the lived experiences of children with intellectual disabilities across various school setups, including government schools, private schools, and mainstream schools. Furthermore, it seeks to understand the values and perspectives of the schools, school authorities and teachers, and the manner in which children with intellectual disabilities employ their agency in their day- to-day lives within different educational structures. Ethnographic research was, therefore, conducted in four government schools, two private schools and two special schools in Karnal district, Haryana, India. Haryana was chosen due to the existence of previous research on the cultural understanding of disability in the state. A total of 25 children with intellectual disabilities and 44 school teachers were interviewed and observed. Classroom observations and shadowing also served as important methods of data collection. The findings reveal that policies, school structures and processes, as well as teachers' practices and attitudes, continue to perpetuate exclusionary practices for children with intellectual disabilities. The notion of "inclusive schooling" remains superficial within the Indian context. However, within these exclusionary systems and processes, a diverse range of differences were noted in terms of the experiences, beliefs, and preferences of children. These differences are influenced by a complex interplay of their social environment (school and home), cultural norms and personal attributes. Academic aspirations and experiences of personal friendship emerged as dynamic and intricate aspects of their lives. Evaluating these elements presents challenges as children's academic achievements and friendships are continually evolving, forming, and dissolving. Data analysis also demonstrates that children with intellectual disabilities not only actively construct meanings but also possess an awareness of the cultural context in which they exist. Their interactions with others, including the researcher, were heavily influenced by these cultural contexts. Their actions contribute differently to social and relational networks, depending on the barriers they encounter within each institution. The performativity of their agency was explored through an understanding of their "silences," which proved to be an essential element in analyzing their agency.Additionally, their agency was examined through their utilization of digital technologies which was actively used by children to maintain friendships with old friends, to develop new friendships and for entertainment purposes. This research, therefore, aims to integrate the notions of agency, culture, and structure in order to gain a comprehensive understanding of the experiences of children with intellectual disabilities in various educational environments in an Indian state.
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  A Model for Churn Prediction Based on Qualitative Support Interaction Features for Hotel Technology Provider

  Customer retention is a significant driver of a company s growth. Machine learning has gained immense popularity as a means to predict customers at risk of churn. Churn prediction models are capable of highlighting customers who are at high risk of churn well in advance. A popular approach to improve the performance of churn prediction models is by using input variables that are mainly quantitative and structured in nature. There are limited works in literature that newlineinvestigate smart means to effectively utilize and integrate unstructured data into churn prediction models, and study the impact on model efficacy. One of the roadblocks to effectively utilize unstructured data is the associated cost of annotation which is both time consuming and requires intensive manual effort. To overcome this obstacle, researchers often adopt a semi-supervised newlineapproach called active learning that aims to achieve state-of-the-art performance using minimal number of samples. Although active learning boosts classifier performance, the underlying query strategies are unable to eliminate redundancy in selected samples for manual annotation. Redundant samples lead to increased cost and sub-optimal performance of learner. Inspired by this challenge, the study proposes a new representation-based query strategy that selects highly newlineinformative and representative subsets of samples for manual annotation. Data comprises newlinemessages of a set of customers sent to a service provider. Series of experiments are conducted to analyse the effectiveness of the proposed query strategy, called Entropy-based Min Max Similarity (E-MMSIM), in the context of topic classification for churn prediction. The foundation of E-MMSIM is an algorithm that is popularly used to sequence proteins in protein databases. The algorithm is modified and utilized to select the most representative and informative samples. The performance is evaluated using F1-score, AUC and accuracy.
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  Molecularly Imprinted Nanomaterials for the Electrochemical Sensing of Environmental Pollutants

  ntegrating molecularly imprinted nanoparticles, environmental contaminants are detected electrochemically on a glassy carbon electrode that caters as the transducer host. The modification of electrodes using different noble nanoparticles resulted in enhanced electrooxidation of analytes. The allocation of chitosan as a reducing and stabilizing agent in the green synthesis of noble metal nanoparticles enhances the sensor's efficiency. Different characterizations like UV-Visible Spectroscopy, Fourier Transform Infra Red Spectroscopy, Transmission Electron Microscopy, and Dynamic Light Scattering analysis further confirm the synthesized nanoparticles' morphology, stability, and size. The different experimental conditions needed for effective detection, like electrolytes, potential window, scan rate, and pH, were optimized with utmost careful examination. The morphological characterization of the electrodes were executed utilizing Scanning Electron Microscopy and Optical profilometry, whereas the electrochemical characterization was performed using Electrochemical Impedance Spectroscopy. The Nyquist plot showcased the low resistance and high charge transfer of modified imprinted electrodes with enhanced surface area. Using Differential Pulse Voltammetry, the sensor was validated with nano to femto-level detection limits and a wide linear range with good sensitivity. The imprinting factor displays the superior electroactivity of imprinted sensors compared to non-imprinted sensors. The molecularly imprinted electrode effectively detected environmental pollutants in different water samples. Hence, all the works point to the exceptional approach of imprinted nanomaterials in electrochemical detection with its simplicity and facile preparation. It may be used to develop a susceptible voltammetric sensor for researching environmental pollutants.
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  Effect of Museum Visit Intervention on Learning and Attitude Towards History

  Place-Based Education is an education where learning happens in a place. The place could be museum, garden, palace, library etc. Place-based education is useful for the discipline of History as places are the existing evidence of past historical events. Therefore, students in History discipline can use place-based education for effective learning of history. The study attempts to find out the effect of museum visit intervention on learning and attitude towards newlinehistory. The study brings out how Museums act as an active agency to learn history. The study employed Quasi-experimental model with pre-test, post-test and follow-up post-test. Through purposive random sampling method, the participants were selected from 6th grade students of secondary schools of ICSE board located in the urban area of Kolkata in India. 120 students are included in the study group of the research (control group=60, experimental group=60). For the purpose of measuring museum visit intervention on learning and attitude towards history, researcher made achievement test and attitude scale with 5 point Likert scale was used. newlineThe instruction was provided in accordance with the History Course Curriculum of ICSE newlineboard. Experimental group visited the museum whilst the control group did not visit the newlinemuseum. Data analysis was conducted through SPSS program version 29. The result of the newlinestudy revealed that students of the experimental groups have performed better in comparison to the students of the control groups in learning and attitude towards history. Therefore, there is a recommendation to include museum visits pedagogies in the scope of social studies in History discipline.
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  Indian Approach to International Commercial and Investment Arbitration Vis-A-Vis Global Arbitral Institutes : A Critical Analysis

  The rise of international trade and investments by the foreign states has led to increased number of contractual relationships between the parties. The world is now moving towards a new regime of dispute settlement via alternative dispute redressal mechanisms like arbitration, mediation, conciliation, and negotiation. Arbitration and Conciliation Act, 1996 and amendments in 2015, 2019 and 2021 have promoted international commercial newlineand institutional arbitration in India. The amendments provide a slight sigh of relief but do not completely cater to the global needs of making India a preferred seat for international arbitration. The title of the thesis is INDIAN APPROACH TO INTERNATIONAL newlineCOMMERCIAL AND INVESTMENT ARBITRATION VIS- A- VIS GLOBAL ARBITRAL INSTITUTES: A CRITICAL ANALYSIS . It is covering the conceptual and theoretical framework of International commercial and International Investment arbitration, evolution of arbitration laws in India, comparative study of Indian arbitral institutes with respect to Singapore, UK and USA and judicial approach in international arbitration. It also analyses the judicial approach towards arbitration regime pertaining to enforcement of awards, newlineappointment of arbitrators or interim reliefs. The judicial intervention must be minimized and there is requirement of trained arbitration personals including foreign lawyers or academicians. Provisions must be made for third party funding and consolidation of arbitration proceedings providing data privacy. This study applies doctrinal methodology and through legislations, cases study, books, articles and research papers, relevant material newlinehas been collected. Along with doctrinal methodology, the empirical methodology newline(qualitative) has been adopted whereby hypothesis has been tested to reach out the findings and to find the answers of research questions.
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  In Service Teachers' Diffrentiated Instructional Strategy and Students' Reflective Thinking and Empowered Learning

  Every educational program aims at the comprehensive growth and development of learners. Education policymakers and teachers who are part of any education system have a pivotal role in providing an environment that empowers learners. Thinking pervades all spheres of human action and the ability to think reflectively differentiates man from other animals. Psychological theories have proved that, in a classroom, each learner is unique and has different learning profiles, i.e., learning style, intelligence preference, culture and gender. Therefore, one- sized curriculum doesn't fit all. This research was conducted to measure the influence of differentiated instructional strategy of in-service- teachers as a pedagogy on students' reflective thinking and empowered learning. The researcher developed and standardized a module of 16 lesson plans on English grammar and poetry integrating essential components of reflective thinking and empowered learning into differentiated instruction. Randomly selected samples of this research consisted of 100 students of standard 9, boys and girls, from an English medium ICSE school in the urban district of Bangalore. After a try-out of a few lessons on 25 samples, the researcher taught the lessons through differentiated instruction within 3 months. Through control and experimental groups, pre-test and post-test design, data were collected through 2 measuring tools (1) a questionnaire to measure the level of reflective thinking and (2) Learner empowerment measure. Data analysis of the pre and post-test scores of the experiment group shows a significant impact of differentiated instruction on all four components of reflective thinking of students, i.e., Habitual Action, Understanding, Reflection and Critical Reflection; and on the components of empowered learning of students, i.e., Meaningfulness, Competence, Impact and Choice irrespective of the difference in the gender. The results indicate that differentiated instruction could be implemented in schools as an instructional method to include all types of students and respect their diversity.
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  A Comprehensive Model for Forecasting the Nifty50 Index Using MAchine and Deep Learning Methodologgy with Reference to National Stock Exchange

  The volatility and uncertainty make stock and stock price index predictions challenging. Many financial professionals and academics are interested in stock price/index prediction studies. This study presents computational ML and DL intelligence techniques for estimating the NIFTY50 index closing value on the Indian NSE using Fundamental Analysis and Technical Analysis. To forecast the NIFTY50 index, we first employed Fundamental Analysis and max voting, bagging, boosting, and stacking ensemble learning techniques. An embedded feature selection algorithm is utilized to determine the model's best fundamental indicators, and a grid search is performed to tweak hyperparameters for each base regressor. Our results demonstrate that the bagging and stacking regressor model 2 beat all other models, with the lowest RMSE of 0.0084 and 0.0085, respectively, indicating an improved fit of ensemble regressors. Subsequently, TA research was done to exhibit the influence of deep learning on the NIFTY50. This method employs a data augmentation mechanism and three GRU model variations. It is examined using two datasets, TA1 and TA2, which include technical indicators from the NIFTY50 index. The GRU model enhanced the NIFTY50 index prediction using the TA1 technical indicator dataset. Finally, the study examines a hybrid model to estimate equity market trends, combining PCA with ML methods such as ANN, SVM, NB, and RF. The proposed approach uses the trend deterministic data preparation layer to convert the continuous data to a discrete form denoted by +1 or -1. The empirical findings of this hybrid model demonstrate that the RF model with the first three principal components obtains precision of 0.9969, F1-score 0.9968 and AUC score of 1. Overall, the suggested research design outperforms baseline models in our experiments and shows promising results using fundamental and technical analysis indicators. Thus, this study provides an ideal tool for stock market prediction and financial decision-makers.
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  A Study on Nutritional, Biochemical and Pharmacological Property of Punica grantum L.

  Biologically active components present in different medicinal plants which protects the human from diseases and allow health benefits. In the present study, the nutritional, biochemical and newlinepharmacological analysis of the different parts of Punica granatum var Bhagwa was done. In the nutritional profiling, dry moisture content was found high in the flower (9.63%) followed by leaf, peel, root, stem and fruit. Ash content was recorded higher in the stem (30%/gm) followed by root, leaf, flower, fruit and peel. Also, the macro and microelements present in different parts of newlineP. granatum var Bhagwa were analyzed. The fruit recorded the highest amount of nitrogen and phosphorus whereas the peel was recorded with more potassium. The phytochemical newlinequantification showed the major content of carbohydrates in the flower (317.96 mg/g) and leaf (315.62 mg/g). The protein in fruit (69 mg/g) and proline in root (19.54 mg/g) were recorded. P. granatum peel was recorded with maximum phenolic and flavonoid content. It showed a high antioxidative response in comparison to other plant parts. This study also aims to explore the use of P. granatum seed oil as a reducing agent for the synthesis of cobalt nanoparticles. These cobalt particles showed a and#955;max at 279.88 nm for UV-visible spectrometry analysis. Furthermore, X-ray Diffraction, Fourier Transform Infrared Spectroscopy, Field Emission Scanning Electron Microscope and Dynamic Light Scattering were performed to confirm the nature of these nanoparticles. The pharmacological potential of these cobalt oxide nanoparticles was tested against microbial pathogens. The results suggest that these nanoparticles exhibited significant newlineactivity against various human bacterial and fungal pathogens. Additionally, in vitro cytotoxicity analysis of CoONPs had targeted MCF-7 cancer cells with a significant IC50 value compared to non-cancerous cells (L929). This study concluded that Bhagwa variety of P.
• PhD

  A Study on The Utilization of Lactic Acid Bacteria Fermented Sea Weed As Aqua Feed For Growth and Disease Resistance in Oreochromis Niloticus

  Consumption of fermented foods are known to provide various health benefits. Fermentative microbes present in traditional foods are reported to confer health benefits. The present study was aimed to isolate a novel potent probiotic strain from the homemade fermented Indian recipe Moor Kuzhambu and Pickle, and its characterization to elucidate the efficacy of isolate in cholesterol and heavy metal reduction. Cultures isolated from Pickle (CK2) and Moor Kuzhambu (CK3) were newlineidentified as different strains of Pediococcus pentosaceus using 16S rDNA newlinesequence based bacterial identification method. The isolated strains exhibited newlinetolerance to gastric juice and was able to exhibit a broad range of tolerance to newlinevarying temperatures, pH, NaCl, solvent, phenol, trypsin, and artificial gastric newlinejuice. Cell surface studies such as auto aggregation, co-aggregations, and cell newlinesurface hydrophobicity determined the ability of the strains to aggregate on to intestinal cell surface and manifest competitive pathogen displacement. Remarkable biofilm reduction of 48% to 80% was observed in the probioticsupplemented samples. Similarly, a reduction of 80% to 85% free cholesterol was newlinenoted in cholesterol assimilation assays, and heavy metal (Cu+, Pb+, Zn+ and Fe+) newlineassimilation ability was observed. Pediococcus pentosaceus MK459541 strain newlineCK2 and (MK459539) CK3 were assessed for EPS synthesis, structural characteristics, antioxidant properties and heavy metal assimilation abilities. Maximum yield of EPS was observed in carbon source Xylose for CK3 and fructose for CK2. Similarly, EPS production was found to maximum when bacteria newlinewere supplemented with meat extract (CK2) and yeast extract (CK3). FTIR results exhibited the presence of functional groups such as Imine/Oxime group, carboxylic group, Halo groups, Nitro compounds, etc. Further studies on EPS CK2 and EPS CK3 revealed a strong antioxidant capacity of 73.92% to 97.75%. Heavy metal assimilation ability of the EPS was found to be strong and in decreasing order as follows Cu+, Fe+ and Zn+.
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  A Study on the Emergence of Subaltern Counterpublics in Select Malayalam Dalit Christian Narratives

  The research A Study on the Emergence of Subaltern Counterpublics in Select Malayalam Dalit Christian Narratives attempts to put Kerala's vernacular Dalit Christian narratives into the scholarly canvas. As statistics do not provide solid data on the quotidian resistance, the narratives reveal the overt and covert struggles of the Dalit Christians. The study problematises the dominant narrative of the State and the Church and provides a way to articulate their voices and the transition from one religion to another. The primary texts for the study include Paul Chirakkarodes Pulayathara, Nostalgia and Eli Eli, Lama Sabach Thani, T.K.C. Vaduthalas Achante Venthinga Inna! and C Ayyapans Ghost Speech. The current study uses the combined frameworks of narratology, Lacanian psychoanalysis and subaltern counterpublics through the method of narrative analysis. Narrative analysis involves analysing stories or narratives to understand their meanings, experiences and values. The research argues that the Dalit Christian narratives become a testimony of subaltern counterpublics, narratology, and resistance tactics, suggesting a counter- narrative effect. They become treasure houses that carry group memory of community life and history. They are enclaved spaces where unfiltered articulations of marginalisation, abandonment, exploitation, rejection, resistance and empowerment occur. They function as proactive spaces that challenge dominant stereotypes and create an ideologically sound public sphere. Alternative discourse arenas become places of empowerment where subaltern counterpublics emerge, thus transforming the narratives into counter-narratives. The study acknowledges the agency of the Dalit Christian narratives to reform, rethink and reinterpret the form and content of Dalit Christian literature from a subaltern perspective. From an epistemological perspective, the Dalit Christian narratives produce knowledge garnered through analysing and interpreting the primary texts as representative of fusing personal and political resources to create a narrative of resistance and survival.
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  Efficacy of Canine - Assisted Therapy on Social Competence among INdividuals with Autism Spectrum Disorder

  Adults with Autism Spectrum Disorder (ASD), because of their deficits in social newlinecompetence, often suffer a great deal in the community. Canine-assisted therapy (CAT) seems to be a useful approach to improve social functioning. This study aimed to investigate whether CAT can assist in improving the social competence of adults newlinewith ASD. The study employed an ABAB single case experimental design with four newlineparticipants. The social performance and social interactions with the therapy dog and newlinetherapist were the target measures of the study, and they were assessed using the newlineVellore Assessment of Social Performance and Animal-assisted Therapy Flowsheet. The baseline measures for the study were taken four times for 4 weeks for two newlinebaseline/reversal phases of the study. CAT was delivered by a trained dog along with newlinea certified animal-assisted practitioner twice a week for 4 weeks for 45-60 minutes newlineduring two intervention phases. The results were interpreted using descriptive, newlinegraphical, and numerical analysis. The mean scores indicated improvement in social newlineperformance and social interaction scores in the intervention phases. The visual newlineinspection showed similar results as indicated by the increasing trend line in newlineintervention phases. The results of the non-overlap of all pairs showed a medium to newlinestrong effect of CAT on improving social performance. The results validated the use newlineof CAT in the enhancement of social competence among adults with ASD. The study newlinesignificantly contributed to the field of CAT as well as has implications for aiding the newlineintegration of adults with ASD into mainstream society by enhancing their social newlinefunctioning.
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  Aspect Based Multi Classification for Text Mining Using Neural Attention Model

  Aspect-based text classification is crucial for multi-classification in e- commerce, including diverse sectors like food, online shopping, and restaurants. Traditional research often focuses on a few classes and domains, such as restaurants or electronics, and overlooks the need to categorize sentences based on domain- specific contexts. However, e-commerce involves numerous domains that require more sophisticated classification methods. E-commerce platforms generate vast amounts of textual data, including comments, product descriptions, and customer reviews, which contain valuable information about various aspects of products or services. Since customers often research product reviews from multiple sources before purchasing, these reviews become essential user-generated content for e-commerce businesses. To address this gap, the Aspect-Based Neural Attention Model (ABNAM) was developed. ABNAM enhances classification's accuracy and comprehensiveness by considering each domain's unique characteristics. This leads to better categorization and provides more relevant insights for businesses operating across various e- commerce sectors. Experimental real-world data results demonstrate that ABNAM identifies more meaningful and coherent features. It significantly outperforms other methods by achieving higher accuracy, better recall and precision, and more robust performance across different datasets. The current research introduces an efficient and innovative sentence classification model using ABNAM. Unlike traditional automated text classification models, which struggle to categorize data into sixteen classes, ABNAM excels by leveraging technologies such as TF-IDF, N-Gram, Convolutional Neural Networks (CNN), Linear Support Vector Machines (SVM), Random Forest, and Nae Bayes. Among these methods, ABNAM achieved the highest accuracy at 97%, successfully classifying sentences into one of the sixteen categories. The research positions ABNAM as a novel and highly effective classification model, particularly in achieving high-class categorizations.
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  A Self-Reflective and Empathy Based Environmental Education Intervention to Enhance Environmental Values and Knowledge of Preadolescents

  Environmental degradation and climate change have become common phenomena and they are attributable to human actions focusing solely on economic growth. Therefore, it is necessary to fetch drastic changes in the lifestyles of majority of the public and to acquire the collective capacity of ecological intelligence. The accumulation of ecological intelligence results in environmental knowledge, values, and skills to deal effectively with the environment. The present study is an attempt to develop and apply a self-reflection and empathy-based Environmental Education module for 11-12 years old children to enhance their environmental values and knowledge. The study utilized a pre-test post-test quasi experimental design for which two existing sixth grade classes (intervention group and control group) from different schools, selected through purposive sampling formed the sample. A pre-test and a post-test were conducted on the participants environmental values, attitude, knowledge for the intervention and control groups. Additionally, environmental behaviour, self-reflection and insight were assessed before and after the intervention and the student workbooks were undergone content analysis for the intervention group. The self- reflective and empathy-based Environmental Education intervention was administered for the class selected as the intervention group in between the pre and post-tests. The researcher observed the interventions effectiveness on environmental values with the help of the attitude scale of the Children's Environmental Attitude and Knowledge Scale (CHEAKS), through the content analysis of student workbooks, and through session feedback form. The positive impact of the intervention on environmental knowledge was understood from the analysis of the knowledge scale of the Children's Environmental Attitude and Knowledge Scale (CHEAKS) and from the session feedback form. Additionally, there is an improvement in the intervention groups reflective thinking ability and environmental behaviour when assessed through Self-Reflection and Insight Scale for Youth and parent observation checklist. The study has implications concerning the implementation of Environmental Education.
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  Designing A New Encryption - Then - Compression System for Grayscale Images Utilizing Entropy Encryption

  In the digital era, images and video sequences have dramatically increased newlinebecause of the rapid growth of the Internet and the widespread utilization of multimedia systems. The advancement in technology facilitates a faster way of transmitting data; however, the channel used for communication is an untrusted medium. The proposed research focus on the secure newlinetransmission of grayscale images over a social networking site (SNS) provider called the untrusted channel. Rigorous research has been conducted on the secure transmission of images and proposed different models, namely Compression-then-Encryption (CtE) Systems and newlineEncryption-then-Compression (EtC) Systems. In EtC, the encrypted information is transmitted over the channel. However, the channel is newlinecompressing the information to reduce the overall traffic. Due to the compression performed by the channel, the decryption process may fail on the receiver side. Constructing an efficient EtC model, as good as the standard compression algorithms, will address the gap in research. Four objectives were formulated, and schemes were proposed for each objective to address the problem. Two schemes were developed to address the first objective, eliminating noise incurred during transmission through the channel. The first scheme eliminates the noise using a two-pass hybrid mean and median filter. In the second scheme, a supervised curve fitting a linear regression model with a mean filter is applied. To secure the transmission of images over the untrusted channel, the objectives two and three address the scrambling and encryption of images. A hybrid of improved Arnold transforms and ElGamal encryption is experimented with in the first scheme to address scrambling and encryption. In this initially, a Block-wise scrambling is applied to the image, followed by pixels-wise newlinescrambling within the block followed by Arnolds transform. The outcome is given to ElGamal encryption.
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  The Development and Feasibility of A Self-Efficacy and Self-Esteem Based Intervention on Music Performance Anxiety Among Majors

  Music Performance Anxiety (MPA) has been seen to adversely affect a student s goal-setting with respect to careers in music. Two variables that are closely related to the development and maintenance of MPA are self-efficacy and self-esteem of the student. The aim of this research is to present the experiences of students with MPA and the feasibility of an intervention to help reduce MPA among music majors while focusing on building their self-esteem and self-efficacy. The study followed a mixed method, exploratory sequential design. Ten participants were recruited for the newlinequalitative phase and were interviewed using a phenomenological approach. Data from these interviews were analysed using Interpretive Phenomenological Analysis. Themes that were found in the qualitative phase such as blocks growth of performer , Fear of judgment , lacking confidence in skills , comparison with peers , need for appreciation , pointed toward the need to build self-efficacy and self-esteem among the performers. The themes from this analysis were then used, along with previous research evidence to develop a self-esteem and self-efficacy based intervention. A quasi-experimental design was used to carry out and assess the feasibility of this intervention. The intervention lasted for eight sessions, where the experimental group took part in these sessions that consisted of both theoretical and practical components, which lasted for one hour each. The control group on the other hand did not receive any treatment and were not a part of any of these sessions either. The experimental group that consisted of 13 participants and the control group that consisted of 12 participants were assessed on their MPA, Musical Self-Efficacy and Musical Self-Esteem levels at the start of eight weeks and then at the end of eight newlineweeks. The scale used to assess these variable were the K-MPAI (Kenny, 2009), the newlineMusical Self-efficacy scale (Ritchie and Williamon, 2010), and the Self-esteem of newlinemusic ability scale (Schmitt, 1979) respectively.
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  Adoption and Usage of Artificial Intelligence in Food Processing Industries

  In recent years, technological changes and advancements have forced Fast Moving Consumer Goods (FMCG) industries, especially food processing, to redesign their functionality. This includes the integration of technologies like Artificial Intelligence (AI) to enhance performance. Future trends in the food processing industry will be shaped by sustainability, efficiency, traceability, wellness, safety, hygiene, health, and newlinetransparency. Food processing industries are compelled to embrace digitalization in the newlinecurrent era of globalization and digital transformation. AI encompasses programs, newlinealgorithms, robotics, drones, data mining, cloud computing, sensors, driver-less newlinevehicles, the internet of things, digital platforms, and machines, representing a new newlinelevel of intelligence. AI aims to replicate human reasoning and problem-solving newlinecapabilities, leading to task automation, increased efficiency, and reduced human newlineeffort. The growth of AI is reshaping the food processing industry, with potential newlineapplications spanning from cultivation, supply chain management, storage and safety, newlineHuman Resource Management (HRM), and Customer Relationship Management (CRM). Integrating and adopting AI in food processing can address unique challenges and offer substantial benefits across these functions. While large-scale food processing newlineindustries have made significant progress in adopting AI systems, small and mediumscale food industries are also integrating AI technology. The current research study employs a quantitative research methodology and obtained data from 320 small and medium-scale food processing industries employees in the city of Bengaluru. The primary surveyed data were analyzed using the Structural Equation Modeling (SEM) approach through AMOS 26. The research used the UTAUT 2 model to measure the usage and adoption of Artificial Intelligence (AI) among the employees of small and medium-scale food processing industries.
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  Green Synthesis of Nano Carbon-Infused Polymer for The Detection of Toxic Heavy Metals

  The global population is marching towards greener ways of life. Green nanotechnology, newlinewhich uses carbon nanomaterials for environmental remediation, is the pioneer among the existing strategies for the production, characterization, and applications of carbon nanomaterials derived from sustainable and renewable energy resources. Additionally, easily available natural ingredients are effective carbon precursors for producing carbon dots with newlineenthralling physical and chemical properties. Compared to other approaches, plant-based newlinesynthesis of nanomaterials is more dependable because it is simple, fast, ecologically newlinefriendly, and does not require particular conditions. We report for the first time, the use of a fluorescent nanocarbon material synthesised from plant, Indigofera Tinctora (L.) (IBLH), for the detection of metal ions. This nanomaterial developed using a green synthesis method that aided hydrothermal processing from the leaf extract of IBLH. The IBLH sensor used to detect hazardous metal ions (Pb2+) was very sensitive and selective. Considering the concentration from 1 nM to 100 mM and 100 mM to 1M, developed sensor displayed broad, dual linearity. The limit of detection (LOD) for the sensor appreciable low with 14.74 nM as the detection limit, with a wide and linear response spanning from 1 nM to 1M Cd2+ concentration range. Utilising Ruta Graveolens as the carbon source, we developed ARH-CDs from agricultural waste using chemical-free, one-step hydrothermal procedures that are safe for the environment. The synthesized ARH-CDs showed nano particle size, outstanding water newlinesolubility, great biocompatibility, and appreciable optical characteristics. The FTIR and XPS findings validated the existence of functional groups. such as C-O, C-C, and O-H with various oxygen functional groups, with predominating hydroxyl group, supporting the newlineexistence of CDs. For the selective detection of Hg2+, the synthesized ARH-CDs are employed as a biocompatible fluorescence sensor.
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  Spectral and Timing Properties of Selected Black Hole Binaries

  X-ray binaries hosting a black hole (accretor) and a main sequence or a post-main sequence star (companion star) are called black hole X-ray binaries (BHXBs). BHXBs are gravitationally bound systems where the matter from the companion star is accreted onto the accretor either via a Roche lobe overand#64258;ow (low-mass companion star) or stellar wind (high-mass companion star). The accreted matter spirals towards the accretor, losing its angular momentum in the process. The gravitational potential energy of the in-falling matter is converted to kinetic energy which is eventually released as X-rays. X-ray spectrum of BHXB is quite complex by nature, which is contributed by various X-ray production processes. Systematic and comprehensive investigations of the X-ray production mechanisms are essential for understanding the fundamentals of accretion physics and exploring the general relativistic effects in extreme gravity environments. Launch of several dedicated X-ray missions like Uhuru, Ginga, RXTE, Chandra, XMM-Newton, NuSTAR, Swift, etc. for over half a century have led to the discovery, classifcation and fair understanding of spectro-temporal properties of BHXBs. Despite the continuous and ongoing newlineefforts, the physics of the accretion mechanism in BHXBs, accretion disk geometry, the origin of quasi periodic oscillations (QPOs), energy-dependent time lags and coherence of X-ray photons in different energies, etc., are yet to be completely understood. Hence, there is a need for newlinerevisiting these problems using the data from more sensitive instruments, that have broadband energy coverage and have better spectral and timing resolutions than RXTE. Thus, data from the latest missions like AstroSat, Swift, NuSTAR with their broadband energy coverage, especially in the lower energy regime (and#8804; 3.0 keV), and larger effective area can help fll in the gap in the newlineexisting body of knowledge and provide a holistic understanding of these sources.
• PhD

  The Transnational Influence of Energy on Cultural Practices : A Study on Kuttanad Wetland Systems

  The phenomenon of the extensive Kerala-Gulf migrations has exerted a significant influence on the socio-economic development and local cultures of the state. This study newlineinvestigates the evolving cultural perceptions and practices in the region with the rapid migrations, employing the conceptual framework of energy as a guiding lens. Energy is viewed as the fundamental and material fuel communities engage with to shape and organise their cultures. By situating the research in the field of Energy Humanities, it interrogates the role of shifting energy regimes and transnational energy systems in specifically shaping the local community s relation with the land and environment. The study focuses on Kuttanad, a wetland-based region in Kerala, historically known for its intense paddy cultivation and rice production. Wetland environments play a significant role in environmental sustainability by sustaining the carbon cycle and exist as complex biodiverse ecosystems. The study employs a mixed-method qualitative approach by combining ethnography and textual analysis that form the primary data for analysis. The selected novel Moustache (2020) by S. Hareesh translated by Jayashree Kalathil serves as the primary text. In ethnography, methods like semi-structured interviews, participant observation, and focus-group discussions were utilised to directly obtain insights from the newlineparticipants perspective. The collected data was systematically coded and analysed to newlineexplore an underlying energy unconscious within the culture. The findings present early agrarian Kuttanad as an organic-based energy regime with flow and animate forms as newlineprimary sources of energy that act as agency and effect in shaping local cultures. It newlinehighlights the overlooked aspect of energy s influence on the social dynamics, power newlinestructures, and everyday values and practices of local cultures.