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Opportunity Recognition, Career Decision-Making, Self-Efficacy and Social Entrepreneurial Intention among Higher Education Students
Building on the entrepreneurship cognition literature, the present research aims to develop a model to examine the direct and indirect effects of opportunity recognition, career decisionmaking and self-efficacy on social entrepreneurial intention. The research adopted a crosssectional design. The research was divided into three distinct studies, each conducted with a specific objective. The data collected for three studies included higher education students newlineacross India. Studies 1 and 2 aimed to develop and validate two scales, namely social entrepreneurial opportunity recognition and social entrepreneurial career decision-making following steps in tool construction. The sample size was 600 for study 1 and 845 for study 2. The social entrepreneurial opportunity recognition scale had 24-items that measures opportunity recognition with six motivating factors as the lower order constructs which are life experiences, social awareness, social inclination, community development, institutional voids, and natural option for a meaningful career. The social entrepreneurial career decision scale had 20 items focusing on the appraisal components in pre-entry social entrepreneurial career decision-making and has four factors, which are relevance, coping potential, knowledge and resources, and normative significance. Study 3 examined the direct and indirect effects of opportunity recognition, career decision-making and self-efficacy on social newlineentrepreneurial intention using a sample of 605 students. The findings show that opportunity recognition influences social entrepreneurial intention and is partially mediated by career decision-making. Furthermore, self-efficacy moderates the mediating role of career decisionmaking between opportunity recognition and intention. This research facilitates a profound understanding of social entrepreneurial cognition and pre-entry decision-making. -
Large Scale Transportation Data Analysis and Distributed Computational Pipeline for Optimal Metro Passenger Flow Prediction
Transportation has a signifcant impact on controlling traffc around a busy city. Among the transport system, metro rails became the backbone by operating above the traffc. For this reason, we have to take special consideration of the passenger and#64258;ow in the transport system and, by understanding the needs, take timely actions for smooth running. Every metro system stores information about the and#64258;ow of passengers in the form of transactions known as Automatic Fare Collection (AFC) data. For this research, AFC data is taken as the primary newlinesource of information to identify the passenger and#64258;ow within the metro rail platform. Each metro system generates massive data throughout its running period and stores data within the system and considering the size of data generated, the analytic platform has to process them in a distributed paradigm to handle quotBig Dataquot. Artifcial Intelligence (AI) algorithms can derives information, insights, and patterns from this data. The patterns in time series can be identifed from the passenger and#64258;ow data using exploratory analysis. The step is an essential step in data science for understanding the underlying properties of the raw data. The research uses a data platform with a distributed computing and storage mechanism called the JP-DAP. The research leverages the above mentioned platform to extract passenger and#64258;ow data from AFC Ticketing data. After the data engineering, the results of passenger and#64258;ow information underwent further visualization and trend analysis. Based on the facts or patterns identifed from the passenger and#64258;ow information, a decision is taken for forecasting. The initial study will reveal the characteristics of metro usage and practices within the system and fnally derive a solution with machine learning-based forecasting method. The passenger and#64258;ow newlineforecasts based on the above patterns depend on factors like seasonality, trends, cyclicity, location, events, and random effects. -
Friction Stir Welding Process Parameters Optimization By Taguchi Analysis and Validating The Mathematical Model Using RSM For AA6101-C11000 Alloy Joints
Friction Stir Welding (FSW) is a well-established joining method that offers newlinesignificant advantages over traditional methods, including improved mechanical newlinecharacteristics, less distortion, and environmental friendliness. Due to its solid-state nature, the heat produced through the welding mainly influences the features of joints in FSW. In this investigation, 2D and 3D models of the base metals and welding tool newlinewith different pin profiles were designed using SOLIDWORKS. Fixture was designed and manufactured in accordance with the specifications of the welding machine. ANSYS software was used to investigate the temperature distributions near the weld newlinezones. The base metals AA6101 and C11000 of each 5 mm thickness with butt weld newlinepositioned, were joined by FSW mechanism with the help of OHNS steel tool with circular pin profile. Taguchi analysis was employed to optimize the FSW welding input process parameters, including tool rotational speed (rpm), feed rate (mm/min), and tool offset (mm), to determine their respective contribution (%) to the output response, namely ultimate tensile strength (UTS), hardness, impact load, and electrical newlineconductivity to achieve the high joint strength. During experimental work using the newlineTaguchi s design matrix, the maximum output response values were obtained when the input parameters were set to 1000 rpm, 50 mm/min and -1 mm. Taguchi analysis revealed that the tool rotational speed encounters high significance effects, followed by feed rate and least tool offset upon output response. The X-ray diffractometer (XRD) test was employed to specifically determine the existence of Al-Cu intermetallic compounds (IMCs) generated within the FSW of Al (AA6101) and Cu (C11000) joints. At medium 40 mm/min, 1000 rpm, and -1.68 mm, the IMCs newlinedeveloped were Al4Cu9 and Al1Cu3 giving a high UTS value of about 142.69 MPa. newlineMathematical model was developed utilizing the Response Surface Method (RSM) to newlinepredict the output response. -
Study of Low-Mass Stars and Brown Dwarfs In Star Forming Regions of Diverse Environments
The formation and evolution of low-mass stars and brown dwarfs is an intricate process orchestrated by the environmental conditions in which they form. As a natural byproduct of this process, circumstellar disks are formed, whose dynamic relationship with the environment plays a pivotal role in determining the fate of the star and the timescale for planet formation. While low-mass stars are a dominant product of the star formation process, brown dwarfs occupy a unique position, bridging the gap between newlinelow-mass stars and planets. In this thesis, we have examined the low-mass stars and brown dwarfs in young clusters located at different distances with diverse UV radiation felds and stellar densities to decode the role of environment in shaping the IMF, its inand#64258;uence on disk evolution and to understand the formation of brown dwarfs. We have targeted three young star forming regions for the newlinestudy namely and#963; Orionis, twin clusters IC 1848-East and West, and IC 1396 using deep multi-wavelength photometry as well as near-IR spectroscopy with 4m and 10m class facilities. For the and#963; Orionis cluster we used deep CFHT-WIRCAM near-IR data and the novel water-band photometry technique along with Gaia DR3 to identify the candidate low-mass members. Spectroscopic follow-up observations conducted with IRTF-SpeX validated the selection of the candidates by this technique with a 100% effcacy. We then compiled a comprehensive membership catalog for a mass range and#8764;19-0.004 Mand#8857;. The form of the stellar-substellar IMF was found to be consistent with other nearby star forming regions suggesting a lack of signifcant environmental inand#64258;uence. Further, we analysed the evolutionary class of the members based on the mid-IR slope of the SED to study their disk properties. We estimated the disk fraction of the low-mass sources to be consistent with other star form ing regions considering the age of the cluster. This showed that in this region, external photoevaporation does not play a major role in the inner disk evolution. -
Effect Of Cooperative Learning Strategies on Self-Directed Learning and Reflective Thinking of Pre-Service Teachers
Cooperative learning (CL) research demonstrates its robustness. While acknowledging the empirical benefits, there is room for improvement in implementing CL in teacher education classrooms. Teacher educators often resist adopting CL, favouring the frontal teaching method. The cultivation of self-directed learning and reflective newlinethinking is crucial for pre-service teachers (PSTs) to evolve into lifelong learners, newlinemeeting the demands of 21st-century classrooms. Online cooperative learning (OCL) newlineplays a vital role in enhancing essential skill sets such as collaboration, digital newlineproficiency, communication, and interaction among pre-service teachers. This study newlineunfolded in two phases. The initial pilot study, utilizing a concurrent triangulation newlinemixed-method research design, delved into perceived challenges faced by teacher newlineeducators in India regarding cooperative learning implementation. The subsequent newlineexperimental stage employed a quasi-experimental non-equivalent control group newlinedesign to investigate the impact of OCL strategies on self-directed learning (SDL) and reflective thinking (RT) among Indian pre-service teachers. Following the newlineintervention with OCL modules, the researcher also assessed pre-service teachers newlinesatisfaction and perceptions towards OCL, utilizing a mixed-method research approach with concurrent triangulation. The sample for experimental stage encompassed 130 pre-service teachers from two teacher education colleges affiliated with Mangalore University, Karnataka, India. The researcher constructed OCL intervention modules for the study and experts validated it. The researcher adopted standardized instrument for measuring SDL by Acar et al. (2016), and standardised instrument for measuring RT by Kember et al. (2000). The pilot study revealed that teacher educators perceived challenges at an average rate of 63% due to teacher challenges, learner challenges, curriculum syllabus, and administrative challenges. -
Biomarkers of Autistic Study : Biochemical, Genomics, Epigenetics and Cytogenetic Signatures
Autism is a complex disorder characterized by social issues, impaired communication, newlineand repetitive behavior. The prevalence of autism has increased significantly over the past two decades, with an estimated incidence of 1 in 150 children in 2000. Cytogenetic investigations are essential for confirming clinical diagnoses, as the disorder has high phenotypic variability and genetic heterogeneity. A study aims to confirm behavioral phenotypes of autistic subjects newlinein South India using DSM IV and ATEC open questionnaires. The study found that metabolic factors, including hormones, neurotransmitters, and oxidative ions, play crucial roles in the progression of symptoms. The study also revealed the roles of two major causative genes (NRXN1 and CNTNAP2) in a spectrum of genotypes imparting severity and heterogeneity. -
Impact of Heavy Metals on Growth and Biosynthesis of Important Secondary Metabolites from Mucuna Pruiens (L.) DC and Withania Somnifera (L). DUNAL
Herbal medicine has a long history of utilizing medicinal plants to treat various newlineailments for a long time. However, heavy metal toxicity in herbal medicines has been newlinedocumented. The occurrence of heavy metals in medicinal plants is a consequence of exposure to tainted agricultural sources. The consumption of medicinal plants newlinecontaminated with heavy metals has caused detrimental health implications. On the newlineother hand, plants when subjected to heavy metal stress exhibit changes in secondary newlinemetabolite production. Thus, the assessment of heavy metal stress on plant growth, newlinesecondary metabolite production, and its bioaccumulation must be worked on. The newlinepresent study investigates the effect of heavy metals such as lead, cadmium and newlinemercury on germination, growth, biochemical variations, heavy metal accumulation, newlineand biosynthesis of secondary metabolites in two of the most valuables ayurvedic newlinemedicinal plants Mucuna pruriens (L.) DC and Withania somnifera (L). Dunal. The M. pruriens seeds were exposed to 25 -250 ppm Cd and Hg and 200-2000 ppm Pb and the seeds of W. somnifera were exposed to 20-200 ppm Cd, 10-100 ppm Hg and 100-1000 ppm Pb for 21 days to evaluate the LD50 value. M. pruriens showed 50% germination at 150 ppm Cd, 175 ppm Hg, and 1200 ppm Pb. W. somnifera showed newline50% germination at 70 ppm of Hg, 140 ppm Cd and 400 ppm Pb. The LD50 value obtained was used to select the appropriate Cd concentrations for further studies to newlinebe carried out in the polyhouse. The seeds of M. pruriens were sown in soil pretreated newlinewith metals ranging from 50-200 ppm Cd, 25-225 ppm Hg and 400- 1600 ppm Pb, newlinewhereas the two months old W. somnifera were exposed to 40-200 ppm Cd, 20-100 ppm Hg and 200-1000 ppm Pb. The heavy metals impacted the growth of plants and significantly varied biochemical parameters, such as carbohydrate, chlorophyll, flavonoid, protein, proline, phenol, MDA content, metabolite content, and newlineantioxidant activity. -
Vanet Framework for Optimal Target Selection in Handoff using machine Learning
The impact of mobile networking has been far-reaching and has transformed many technologies for the better. Among the more pioneering technologies of recent times, autonomous vehicles (AV) are being touted as the future of transportation. AVs are featured prominently due to their ability to provide services across the implementations concerning smart-city applications. Since the newlinenodes (AV) involved are highly mobile, it is important to keep the device connected and adapt the dynamic topology change. The network should be capable of switching AV between access points (AP s) dynamic and must take place without much delay. Handoff is the process where a node switches between APs depending on the changes in the network topology. Various studies have claims that the use of Machine Learning or Deep Learning improves the efficiency of decision making in mobile networks. In this research work a dynamic handoff framework, inspired by the traditional Indian game of Kho-Kho is proposed. It selects the most optimal AP for newlinecommunication in a mobile environment. Initially the nodes within an AP are newlinecategorized as sticking and steering nodes. Identifying the nodes list for executing newlinethe Kho-Kho based handoff for the steering nodes. The framework makes use of Artificial Neural Networks (ANN) to perform the operation of handoff and selects the most optimal AP once the handoff trigger occurs. ANN is designed for multiple parameters, including signal strength, noise, and direction to make its decisions regarding handoff. The proposed Kho-Kho model has been newlineimplemented and analyzed using the NS3 simulator. Simulation results have indicated a higher performance of the proposed Kho-Kho approach when compared to the existing standard implemented for vehicular ad hoc newlinecommunications in IEEE -
Multi-Objective Optimization Approaches for Solar Photovoltaic Inverter Control and Energy Balance in A Smart Grid Environment
Placement of distributed generation in electrical distribution system is a critical newlineaspect of optimizing grid performance and ensuring effcient integration of renewable energy sources. Renewable based sources must be properly positioned and sized to avoid bidirectional power and#64258;ows, voltage/frequency and#64258;uctuations and performance degradation. Solar Photovoltaic Systems and Wind Turbines are potentially becoming the preferred renewable energy based, distribution generation sources. Precise control mechanisms like advanced inverter strategies and direct load control are crucial for regulating voltage, frequency and reactive power output, thereby optimizing grid operation and maximizing integration benefts from these sources. However, optimizing the allocation and operation of these systems in grid connected and islanded modes, particularly in radially confgured systems, requires addressing algorithmic challenges, problems related to nonlinear optimization, newlinevariable generations and load variations. To effectively allocate these systems in the newlineelectrical distribution system, advanced optimization techniques capable of newlinehandling multi-objective, nonlinear problems are needed. Similarly, optimizing the power factor of the distributed generation sources and optimizing the load factor in these systems demand adaptive algorithms that can manage nonlinear objectives and dynamic system conditions. In response to the above research questions, this study focuses on determining the optimal placement and sizing of the distributed generation sources in the electrical distribution system with the objective to minimize real power loss and improve voltage stability. Learning enthusiasm based teaching learning based optimization algorithm has been employed for location selection and sizing optimization. The effectiveness of the proposed approach is validated on standard IEEE 33-bus and newline69-bus test systems, demonstrating decreased distribution losses and improved voltage stability. -
Photocatalytic Degradation of Textile Dyes Using Strobilanthes Species Mediated Nanoparticles
Discharge of dye pollutants from textile industries jeopardizes ecosystem by leading to grave threats like contamination of water resources and hazardous health effects. The current study points and focuses at the synthesis, characterization, dye degradation and toxicity analysis of zinc oxide nanoparticles (ZnO NPs) and silver nanoparticles (Ag NPs) derived from Strobilanthes barbatus and Strobilanthes hamiltoniana leaf extracts. UV-visible spectrum analysis validated the biogenesis of ZnO and Ag NPs, revealing unique peaks at 359 nm for ZnOSB NPs, 360 nm for ZnOSH NPs, 428 nm for AgSB NPs, and 432 nm for AgSH NPs. Fourier transform infrared spectroscopy (FTIR) investigation identified phytochemicals involved in nanoparticle synthesis, manifesting the presence of flavonoids, saponins and alkaloids. The X-ray diffraction (XRD) examination disclosed the crystalline structures of ZnOSB NPs, ZnOSH NPs, AgSB NPs and AgSH NPs displayed an average crystalline size of 22.29 nm, 26.9 nm, 23.5 nm and 20.6 nm. Dynamic Light Scattering (DLS) study revealed information on the hydrodynamic diameter and colloidal stability of the NPs, which showed average particle size for ZnOSB NPs, ZnOSH NPs, AgSB NPs and AgSH NPs as 91.6 nm, 165.4 nm, 142.3 nm and 255.3 nm. Field Emission Scanning Electron Microscopy (FESEM) and Energy-dispersive X-ray spectroscopy (EDS) were used to investigate the morphology and elemental composition of ZnO NPs and Ag NPs, revealing particle shape and size variations. The morphological shapes of ZnOSB NPs were spherically shaped NPs, ZnOSH NPs showed rod-shaped NPs, AgSB NPs and AgSH NPs both showed spherical-shaped NPs. The High-resolution Transmission Electron Microscopy (HRTEM) validated the nanoparticles' size and crystalline characteristics, similar to FESEM. The photocatalytic degradation of textile dyes using ZnO NPs and Ag NPs were researched, and the results revealed that diverse dyes degraded efficiently under UV light exposure. The ZnO NPs and Ag NPs showed excellent catalytic degradation at dye (Reactive Blue 220, Reactive Blue 222A, Reactive Yellow 145, and Reactive Yellow 86) concentrations of 1 ppm, 5 ppm, and 10 ppm with NP concentrations of 1 mg/ml. Chemical kinetics research unveiled that the degrading processes had pseudo-first-order kinetics. It has been observed that nanoparticles such as ZnO NPs and Ag NPs can maintain their photocatalytic activity across multiple cycles of dye degradation. Phytotoxicity tests conveyed that ZnO and Ag NPs were beneficial in lowering seed germination inhibition and toxicity in Vigna radiata. The brine shrimp lethality experiment indicated that the synthesized nanoparticles were not hazardous. This comprehensive work gives insight and sheds light on the synthesis, characterization, and use of ZnO and Ag NPs utilizing plant extracts, highlighting their promise for environmental remediation and sustainable nanoparticle synthesis. -
Managing Sustainability in Perishable Food Supply Chains : A Case of Mango From Farm-to-Table
This research explores the significant role of India in the global food production sector, with a specific focus on perishable goods. It examines how this sector contributes to rural income and overall economic growth, while also addressing issues like post-harvest losses and inefficiencies in the perishable sector. The study highlights the necessity of a sustainable and efficient perishable sector for the progression of the Indian economy. By utilizing insights from resource-based view theory, stakeholders theory and systems theory, the research delves into the challenges and opportunities present in India's perishable food supply chain, emphasizing the crucial role of farmers in ensuring quality and effectiveness in India. Additionally, the study explores the broader context of Indian agriculture, with a specific focus on the perishable and horticulture sectors, their economic importance, and challenges such as post-harvest losses and the impacts of climate change. The research advocates for a strategic collaborative approach involving governments, businesses and communities to secure the sustainability and resilience of the perishable food supply chain in light of current and future challenges. The existing literature on the perishable food supply chain is evaluated to find the research gaps. This evaluation is conducted through a bibliometric analysis, shedding light on areas that have been neglected or inadequately explored in prior research. The identified gaps serve as the foundation for the research objectives of the study, aiming to fill these voids with fresh insights and discoveries. To establish the groundwork for the investigation, this research also initiates an in-depth discourse on each hypothesis, ensuring that the research design presented is both transparent and logical. The ultimate objective is to enhance comprehension of the perishable foodsupply chain, paving the way for future studies to build upon this foundational work. Then the research seeks to elucidate the research methods utilized to meticulously validate the researchmodel, employing stringent techniques and measures to guarantee the integrity and dependability of the findings. This framework aims to encapsulate the entire research process succinctly, from its fundamental objectives to the eventual implications of its findings, guiding readers through the investigative journey undertaken in the study. To achieve these objectives, a research model is presented that examines the interrelationships between quality, efficiency, sustainability and technological capabilities within the perishable food supply chain. The research methodology employed in this study combines both quantitative and qualitative techniques. It encompasses a detailed description of the sampling procedure and data collection methods, including the utilization of probability sampling techniques and surveys. Furthermore, the statistical tools and techniques employed in the study is Partial Least Square Structural Equation Modelling (PLS-SEM). The study formulates a comprehensive model that takes into account quality, efficiency and sustainability within the perishable food supply chain, with a specific focus on the moderating impact of technological capabilities. It identifiespositive connections between quality and sustainability, efficiency and sustainability, as well as the combined influence of quality and efficiency on sustainability. Technological capabilities are revealed to bolster these connections, underscoring the significance of circularity in the supply chain to minimize waste and align with sustainability objectives. The research concludes by providing insights on the challenges and prospective pathways towards more sustainable, efficient, and quality-driven practices in the perishable sector, particularly in light of technological advancements and the global trend towards circularity. -
Understanding The Pastoral Ethnobotany in Koppal and Vijayanagar Districts of Karnataka for Sustainability
The research aimed to comprehensively explore the ethnobotanical significance and nutritional value of wild plants utilized by pastoralists in Koppal and Vijayanagar districts. The study area selection involved meticulous consideration of the geographical and ecological relevance. Determining an appropriate sample size was crucial to ensure representative data collection, achieved through systematic methodologies. Informants were thoughtfully selected to gather newlineindigenous knowledge about the diverse uses of wild plants, emphasizing their fodder, newlineveterinary, edible, and medicinal applications. Employing ethnobotanical research methods, interviews were conducted to document plant usage, elucidate their taxonomical identities, and create an extensive inventory. The collection of plants referenced by pastoralists during interviews was a pivotal step. Detailed assessments of plant categories, habits, habitats, and newlinespecific plant parts used were documented. Herbarium preparation and authentication were newlineconducted meticulously to preserve and validate the collected plant specimens. newlineComparison with ethnobotanical studies from other subtropical regions worldwide was newlineconducted using the Jacquard index, revealing similarities and differences. The evaluation of sustainable utility focused on wild edible plants, analysing their viability for long-term utilization. Furthermore, investigating the forage quality of selected wild fodder and hay supplement plants was carried out. Analysing their proximate provided insights into their nutritional value. In summary, this comprehensive research delved into ethnobotanical practices, taxonomic identification, nutritional evaluation, and sustainable utilization of wild plants among pastoral communities. The findings not only contributed to ethnobotanical knowledge but also provided valuable insights into the potential economic and ecological significance of these plants for the communities involved. -
Evaluation of Bending Stiffness of Transmission Line Conductors
Cables are made of helically wound wires and have a wide range of engineering applications. This thesis considers the use of such cables in overhead electrical power transmission lines. The loading on such cables is generally axial pull or tension and torsion. The oscillation of the overhead power transmission lines due to the wind or static bending in any applications, newlineintroduce an additional bending load on such cable assemblies and are subjected to varying newlinebending curvatures and results in reduction in bending stiffness. The effective stiffness of the cable assembly in its bent state varies widely between two extreme newlinebehaviours a monolithic infinite friction state offering the maximum stiffness and a newlinecompletely loose wire zero friction state offering the minimum thickness. Due to the wide variation of this extreme values, the estimation of the cable stiffness at any intermittent stage of bending has been quite challenging and is under continuous refinement. Though many mathematical models are stipulated in the last seven decades in cables, seldom they consider the influence of wire forces and moments about its normal, bi-normal, and axial directions together, in any analysis and evaluated the cable response. newlineThe dominant wire force and moments about the axial directions were never missed by many newlineauthors. Though the global behavior of the cable apparently seems to be all right even with the omission of some forces/moments, the mechanism of its constituent wires needs a fully proven scientific explanation that predicts the local behavior also correctly. The ultimate response of the cable will be complete when accurate theories are attributed for the global and local newlinebehaviours. Hence, this research work addresses the complete mechanics of the helically wound cables and considers the influence of wire forces and moments, in all the three directions, together in the newlineanalysis and evaluates the cable response. -
Effect of Phonological and Phonetic Intervention on Proficiency in English Pronunciation and Oral Reading Among Bengaluru Teacher Trainees
The current research aimed to determine the effect of phonological and phonetic intervention in enhancing proficiency in English pronunciation and oral reading among teacher trainees. The study adopted a single-group pre and post-test intervention design. The researcher developed intervention modules on phonology and phonetics, and a segmental approach was adopted to teach individual sounds. The research design was executed in five stages: experts' opinions on the need for such a study, a preliminary study to find the need for the study, the development of intervention modules and validation of the modules, the pilot study to check the reliability of the tools, and the main study. The researcher applied Oscillo-graphic and observation methods to analyse and test the participants' pronunciation and oral reading progress during the experiment. Communicative Language Learning (CLL) and Audiolingual approaches were adopted to teach individual sounds to participants. The National Assessment of Educational Progress Scale for Reading and Pronunciation (NAEP 2012) was adopted to measure the scores. The other instruments, i.e., audio-to-test phonetic transcription software and Audacity recording software, were used in the experiment to record and analyse the audio clips. The experiment was conducted on n=104 teacher trainees of Bengaluru, India. The current study targeted teacher trainees/ B Ed college students of English method as a population. The population of teacher trainees was 1470 English methods from Bangalore north, south, and central. Further, the sample size for the main study was 104, and it was selected through a stratified random sampling technique. The assessment tools overall reliability (Cronbach Alpha value) (NAEP) on Pronunciation and Oral reading is 0.873. The data normality was tested with the Kolmogorov-Smirnov test. The data EFFECT OF PHONOLOGICAL AND PHONETIC INTERVENTION was normally distributed. Hence, the data was not normally distributed; the non- parametric tests were used to test the hypotheses. The hypotheses testing on phonological and phonetic awareness revealed the difference between pre- intervention and post-intervention scores in phonological and phonemic awareness and oral reading among teacher trainees, the sig. Value is less than 0.05 across all the attributes. The Wilcoxon signed rank test revealed the scores after the intervention, a post-test with a statistically significant value of 0.001. The post-test score, which was after the intervention, is significantly higher. The values across all the attributes related to oral reading and pronunciation with a statistically significant value of 0.001. The other hypotheses testing on gender, age, and qualification, the Mann-Whitney test, and Kruskal Wallis were used, and the results were not statistically significant. The statistical test was used to test the progressive improvement of teacher trainees during the intervention, and it was statistically significant with 0.001 across all the attributes. The data analysis revealed a positive impact of intervention at the post-test on teacher trainees. The study has navigated the need for language proficiency among teacher trainees, especially in English pronunciation and oral reading. The study substantiates the evidence that effective intervention and teachers' knowledge of pronunciation would enhance proficiency levels in pronunciation and oral reading among teacher trainees. The study also hopes that Policy Makers, Universities, B.Ed. Colleges and teacher educators will be beckoned to use technology-integrated intervention to teach phonology and phonetics. -
Economic Burden and Productivity Loss of Employees with Lifestyle Diseases in Sedentary Occupations During Pandemic
Over the past few decades, the prevalence of Lifestyle Diseases or Non-Communicable Diseases (NCDs) have increased. There has been an increasing concern about these lifestyle diseases, with hypertension acting as the most prevalent lifestyle disease in the populace. It further exaggerates the issue as its prevalence increases exposure to other lifestyle diseases such as Diabetes and Cardiovascular Diseases (CVD). With health being an important component of human capital, the presence of lifestyle diseases has an economic impact on the individual and the organisation. The presence of an illness reduces the productivity level delivered by the individual to work, resulting in productivity loss. Apart from impacting an employee's productivity, the prevalence of lifestyle diseases incurs a significant monetary expense in the form of healthcare required to manage them. This monetary expense is called an economic burden or out-of-pocket expenditure. On these grounds, the current study examines the economic burden and impact on the productivity of employees suffering from lifestyle diseases (Hypertension, Diabetes and CVD) working in sedentary occupations. With lifestyle diseases majorly influenced by the lifestyle patterns of an individual, employees working in a sedentary occupation are at greater exposure to lifestyle diseases and hence were selected as the target population. A cross-sectional study was conducted among 426 employees of sedentary occupations in the Delhi-NCR region. The economic burden has been measured as a sum of the direct and indirect costs of the diseases incurred in a year. Using the estimates of economic burden, Catastrophic Healthcare Expenditure (CHE) was measured at different threshold levels. The study has also evaluated productivity loss through presenteeism and absenteeism approaches. An attempt was made to examine the relationship between the economic burden 7 and productivity loss through presenteeism and absenteeism approaches. The result of the study shows a significant share of the economic burden for lifestyle diseases and their comorbidities. CHE was highest at the 40% threshold level. The level of disparity in catastrophe among lower and high-income individuals was also highest at the 40% threshold level. Further statistical results show a high cost of absenteeism due to lifestyle diseases compared to presenteeism and found that economic burden has a strong positive relationship with absenteeism and presenteeism. Overall, the study concludes that lifestyle disease incurs a substantial economic burden and CHE for employees working in sedentary occupations. The estimate for the same increases if multiple lifestyle diseases are present. Further, the impact of catastrophe is more for low-income than high-income individuals due to the limited availability of resources to manage the health issue. Apart from causing monetary expense, the presence of lifestyle diseases also causes a high cost of absenteeism and presenteeism, increasing the economic cost of managing lifestyle diseases. -
Design and Implementation of Low Complexity Multiplier-Less Reconfigurable Band Tuning Filter Structure with Sharp Sub-Bands
Digital flter banks are extensively used for communication purposes for channelization. Reconfgurable non-uniform multi-channels with sharp transition widths are necessary for channelization in digital channelizer and spectrum sensing in wireless communication networks. The aim of this research work is to design reconfgurable flter structures featuring non-uniform and sharp transition newlinewidth channels with reduced number of flter coeffcients. The four different flter structures are proposed in this research for achieving low complexity reconfgurable structure for the design of multiple non-uniform sharp transition width arbitrary bandwidth channels. The foundational newlineelement of this research is centered around the design of a prototype flter. This prototype flter serves as a basis for developing various reconfgurable flter structures. Leveraging the prototype newlineflter s bandwidth characteristics, these structures are categorized into two main groups: narrow band prototype flters and wide band prototype flters. The narrow band prototype flter category comprises structures capable of designing a single fnite impulse response flter with a narrow passband characterized by sharp transition widths. In contrast, the wide band prototype flter category includes structures capable of designing a single FIR flter with a wide passband also characterized by sharp transition widths. A novel flter structures are designed with the help of interpolated newlinefnite impulse response, cosine modulation technique, complex exponential modulation technique and frequency response masking techniques. The proposed method is evaluated using MATLAB R2019b, where the linear phase FIR flter coeffcients are computed based on the Parks-McClellan algorithm. The examples are employed to illustrate the effcient operation of the proposed designs. The results point to the fact that the proposed designs have less multiplier complexity than existing cuttingedge techniques. -
Design, Analysis and Validation of Electric Vehicle Control and Safety for Different Path Profiles and Braking Conditions
Energy conservation and Environmental pollution are two major challenges today for our society. Currently, utilization of the latest technology, to reduce energy consumption and harmful emissions from vehicles, is gaining significance in the contexts related to automobile, energy and power industries. Considerations of these contexts enable us to form a more realistic newlineperspective and a need for developing fuel efficient, comfortable and affordable electric vehicles. The importance of design and development of electric vehicle (EV) is better perceived when, there is a major impact on our future society due to (i) the energy saving aspect from newlineboth the customer side on individual expenditure as well as from the national economy viewpoint and (ii) the huge benefit due to reduction of emissions from internal combustion engines using fossil fuels. EV offers the best solution which not only avoids emissions but overcome the dependency on petroleum resources as well. Due to fewer moving parts, monitoring and controlling of EV are also smooth and relatively much easier. The embedded control techniques used in EV also contribute for a better controllable, observable, predictable newlineand efficient vehicle drive. This current research work focuses mainly on Electric Vehicle Mobility and Control aspects for a deeper study. This research work addresses topics related to mathematical modelling and simulation studies for design and analysis of EV control and safety. Validations of the several case studies done during this research are supported by software tools namely MATLAB/Simulink and IPG Carmaker Virtual Driving Simulation Platform. Starting from modelling, throughout the various stages of this work, realistic vehicle parameters and specifications are considered. The newlinedifferent levels of testing, validation and trial runs of the model-based designs are also validated by software in loop and hardware in loop approaches. Automotive Safety Integrity Level B/C hardware was used for the implementation purpose. -
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. -
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. -
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.