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Empowering Adolescent Emergent Readers in Government Schools: An Exploration of Multimodal Texts as Pathways to Comprehension
This exploratory study, which was part of a larger investigation into multimodality, looked at the comprehension levels of 62 Grade 8 students from two government schools who were identified as emerging readers out of a group of 118 students. Through observations and interactions with teachers and students, the potential for multimodal texts to enhance comprehension was highlighted. The study specifically compared the effectiveness of a digital comic (Text A) and an audio-visual text (Text B) in enabling comprehension among these emergent readers. Participants were instructed to narrate the content and share their interpretations of these texts, with their responses recorded and analyzed. Feedback revealed a marked preference for Text B among 45 of the 62 emergent readers assessed. Employing theoretical frameworks related to comprehension, language production, multimodality, and task structure, this research concentrated on the subset of 45 students who favored Text B. The findings underscore the importance of aligning instructional materials with students preferred learning modalities, suggesting that such alignment enhances comprehension. The study proposes a refined approach to literacy education policy, advocating for the inclusion of diverse modalities to better meet the varied learning needs of students. 2024 Association of Literacy Educators and Researchers. -
Lexical Richness of Adolescents Across Multimodalities: Measures, Issues and Future Directions
Lexical Richness (LR) is a scarcely researched subject in India. The objective of this paper is twofold: (i) To statistically inquire whether LR varies across three multimodalities: visual-only, audio-only, and audio-visual; and (ii) To see which of the two measures of LR (MATTR and Guiraud) is independent of text length and is best suited for short oral productions. 270 students across three types of schools were examined, out of whom 100 willingly completed all three oral tasks. The students were asked to retell the stories transacted in each modality in their own words. Randomization of sampling is done to mitigate the confounding modality bias. Additionally, the genre and parts of the storyline in each modality are similar. The students oral speech samples were recorded, transcribed and analyzed on WordCruncher and TextElixir software. The results revealed that there is statistically significant variance among the modalities. Furthermore, the Moving Average Type Token Ratio (MATTR) is seen to be independent of text length compared to Index of Guiraud. This study also throws light on the observations made during the study, pertinent issues in the field of education, and future directions for research on LR. 2023 IUP. All Rights Reserved. -
Exploring Socio-Variational Patterns in Indian Adolescents Lexical Diversity: Insights for Education
Following the COVID-19 pandemic, vast data emerged regarding the plummeting literacy and readability levels among Indian adolescents, posing a challenge to address in its present condition of a vastly heterogeneous socio-demographic environment. This study is grounded in Bourdieu and Passeron's (1977) theory, which acknowledges schools as places with societal relevance that perpetuate social inequality. This implies the need to formulate robust policies to address educational inequalities. To this extent, the researchers used an exploratory design to evaluate lexical diversity by purposively sampling 100 volunteer teenagers across three schools. In addition to the data received from school officials, survey questionnaires collected socio-economic information (age, gender, area of stay, socio-economic scale [SES], and school type). The authors used the Kuppuswamy SES scale (2022) to determine socio-economic scale measures, as well as the calculation of Lexical Diversity scores through the computational open-source software TextElixir. The findings reveal that age and gender do not affect lexical diversity. However, school type, SES, and area of stay significantly affect adolescents from the lower social class, who need targeted interventions to bridge gaps of educational inequity. This study addresses the limitations of previous correlational studies by offering educational insights to ensure educational equity amidst prevalent social class inequalities. Authors. -
Investigating stock market efficiency in India
International Journal of Computer Application & Management, Vol. 3, Issue 3,pp.45-48 ISSN No. 2231-109 -
Application of smart manufacturing in business
The application of machine learning to production is becoming a chief objective for businesses all around the world. Smart product-service systems enable digital business model innovation by merging digitized product and service components. The life cycle that comes with the realization of customer value is a critical component of these industrial solutions and manufacturing industry is undergoing significant changes as a result of digitalization and automation. As a result, smart services, or digital services that generate value from product data, are gaining popularity. Customers may now contribute in greater numbers in product design during the design process. Giving more people access, on the other hand, increases the security vulnerabilities associated with cloud manufacturing. Smart Manufacturing is one of the technology-driven approach to manufacturing that uses network-connected machines to monitor the process. Smart manufacturing has the ability to be used in a variety of ways, including putting sensors in manufacturing machines and collecting data on their operating state and performance. Thus, the main purpose here is to find ways to improve and automate production performance. This conceptual paper attempts to give a view of how a smart intelligence system may be used in business and how individuals and organizations can produce value. 2023 Author(s). -
Computational techniques for sustainable green procurement and production
Computational techniques are used to generate, solve, analyze, explain, or manage any simple or complex task. The use of environmentally responsible techniques to meet demand for resources, commodities, utilities, and services is known as green procurement. Computational technique in green procurement and production is one of the components of sustainable procurement, along with a commitment to social responsibility and good corporate behavior. Some solutions for this kind of issue are low-maintenance, energy-efficient, and long-lasting. Several experts and researchers provided their findings on the environmental impact of ICT with the use of computational techniques. Also, the importance of energy-efficient information technology for environmentally conscious and feasible information technology is a hot topic because a computer faces environmental challenges at every stage of its life, from development to use to disposal. Due to changing environmental conditions, corporations have prioritized carbon emissions in procurement and transportation, which have the highest carbon impact. To encourage potential suppliers to adopt environmentally friendly practices, green criteria should be introduced into public procurement. Environmentally friendly corporate practices and environmental conservation are considered significant tools through public procurement. Techniques for green procurement and production procedures have recently been correlated with the concept of computational techniques of green procurement and production, owing to the increased emphasis on the concept of computational approaches. For eco-friendly procurement and production operations, computational approaches are inculcated and presented in the same way that they are for green procurement and manufacturing. From this perspective, this chapter presents a methodology for merging computational techniques into green procurement and production in public procurement in the form of green computing. 2024 by Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies. -
An Impact of technology based constructivist teaching on acdemic achivement of IX standrad students of Bengaluru city
Modern education emphasizes on learner centered and joyful learning which is the newlineneed of the hour as well initiated by educationists and education commission. They opine that, children need to keep active throughout the teaching and learning process and encourage self-learning and independent learning. One such emerging practice is constructivist teaching. It has changed the educational practice and converted Passive Learner Centered Environment into Active Learner Centered Environment.Constructivism newlinebelieves that learning is not encouraged in zero ground but on previous experience and newlineprior knowledge. It is the beginning for construction of new knowledge. In the context of Indian school education, it is rightly accepted as one of the pedagogical practice in National Curriculum Framework 2005 and National Curriculum Framework for Teacher newlineEducation 2009. It is also duly adopted in school education and teacher education newlineprogramme of Karnataka. Apart from constructivist approach, technology and technology integration highly influence on present education system. Technology not used only for drill,practice, tutorial etc. but also for construction of knowledge. newlineIn this context, there is a need for technology integration in constructivist practice and to give new framework for learning, teaching as well as for learner centered education. newlineHence, this research is conducted to study An Impact of Technology Based Constructivist Teaching on Academic Achievement of IX Standard Students of Bengaluru City .The main objective of the study is to compare the effectiveness of Constructivist Teaching and Technology Based Constructivist Teaching on academic achievement of IX standard students in Social Science subject. newlineThe present study is experimental in nature newlinewith two equivalent group design. In this study purposive sampling technique is used. The sample comprised of 156 students studying in IX standard of two schools (Government newlineand Private School) of Bengaluru city affiliated to state board. -
Neuro-technology and counselling
[No abstract available] -
Occupancy Monitoring to Prevent Spread of COVID-19 in Public Places Using AI
The chapter aims to automate the counting of people for occupancy monitoring and send an alert email if the occupancy exceeds the defined threshold in case of restricted occupancy guidelines. The study aims to reduce the manual error, effort, and time for people counting and provide a tool for footfall analysis. We propose and implement an occupancy monitoring system by counting the number of people entering and exiting a building/room using cameras and machine learning (ML) algorithms. The Single Shot Detector (SSD) algorithm, which is based on the MobileNet architecture, is used. This project provides an effective process for execution using either a recorded video file or a live stream from a camera. As the system automates counting people, it reduces human effort and error. It provides accurate results on time. The project can be implemented anywhere using a laptop and a camera for capturing the video. Thus, it provides high portability of the project. The system can leverage pre-installed CCTV cameras and systems in colleges, malls, offices, etc. Thus, it requires less additional expenses and is economically friendly for the organization/decision-making authority. This chapter includes implications for various use cases such as ensuring adherence to COVID-19 guidelines by organizations, streamlining janitorial services, prevention of stampedes, improving indoor air quality, improving electricity efficiency, etc. This project fulfills an identified need to automate the people counting process and generate alerts accordingly. 2025 by Apple Academic Press, Inc. -
Global and Indian Perspectives on Russia-Ukraine War using Sentiment Analysis
In today's world, social media has become a platform through which people express their opinions and thoughts regarding various topics. Twitter is one such platform wherein people resort to expressing their opinions or portraying sentiments to the world. Today it has become easier to analyze mass opinion by using sentiment analysis. This paper investigates the ongoing Russia-Ukraine war by analyzing opinionated tweets, and it seeks to understand the sentiments from a global and Indian perspective. Operation Ganga was carried out to evacuate Indian citizens from the war-hit region. Multinomial Naive Bayes classifier classified the tweets into positive, neutral, and negative categories. The paper employed NRCLex for emotion classification and aspect-based sentiment analysis to divide opinions into aspects and determine the sentiment associated with each element. For the study, 4,31,857 tweets were extracted, and the results of sentiment analysis depict that 44.09% users had negative sentiments followed by 33.378% users expressing positive sentiment and remaining 22.53% people were neutral in their tweets. Fear, anger and sadness were amongst the top emotions expressed in the negative tweets whereas the positive tweets expressed trust and anticipation that the war would end soon. Operation Ganga was carried out to evacuate Indian citizens from the war-hit region. An analysis was performed on 1542 tweets that were obtained for Operation Ganga. 74.5% of the users had positive sentiments about Operation Ganga, whereas 16.67% and 8.5% had negative and neutral sentiments respectively. The people trusted this evacuation process resulting in more positive sentiments. Fear of losing near and dear ones and fear of safety was the topmost concern for Indians and leadership was one of the topmost aspects tweeted in the positive sentiments. Thus, the overall results depict that the common man does not prefer war and is fearful of the outcomes. The government should hear the voice of the common man and plan strategies and decisions considering the common man's sentiments. 2022 ACM. -
Celebration of christmas as a symphony of interfaith in ?tm?nut?pam of St Chavara
This article is an attempt to reflect on the interfaith consciousness of St Kuriakose Elias Chavara, by making an Indian reading of his classical work ?tm?nut?pam, specifically focusing on how the incarnation of Christ is presented and celebrated with an open and inclusive approach. In ?tm?nut?pam, while explaining the episode of the Infancy Narrative, St Chavara addresses Child Jesus with the significant Indian name, Brahman?than, and Jesus is being worshipped by Brahmac?rinis with unique Indian offerings. The addition of an Indian character called S?nti as an aged shepherdess making conversation with Mother Mary makes the narrative Indian. Because of his deep and affective knowledge of Indian culture and religion, and having a moving openness and a dialogical approach to them, St. Chavara could develop a relevant cultural modification of his faith, which will have its unique stamp in the Indian Christian Theology. 2017 Journal of Dharma: Dharmaram Journal of Religions and Philosophies. -
A Review on Rural Womens Entrepreneurship Using Machine Learning Models
Rural womens entrepreneurship has contributed significantly to the countrys economy. Entrepreneurship rates have fluctuated in recent years, according to a variety of reasons including economic, social, and cultural influences. Therefore, machine learning models are used to assess the features to make better business decisions. In this research paper, papers from 2009 to 2022 were studied and found that machine learning models are being used to improve womens entrepreneurship. In this paper, nine machine learning models have been described in detail which include multiple regression, lasso regression, logistic regression, decision tree, Naive Bayes, clustering, classification, deep learning, artificial neural network, etc. In the study of all these models, it was found how accurately this model has been used in womens entrepreneurship work. It has been observed that by using different machine learning models with the data acquired from rural entrepreneurship, women entrepreneurs may use a new way of understanding the dynamics of rural entrepreneurship. Various machine learning models have been studied to improve rural development for women working in rural areas. Thus, we have proposed a comparative study of various machine learning models to predict entrepreneurship-based data. The findings of this study may be used to assess how rural women entrepreneurs may change the decisions made in several domains, such as making use of different economic policies and promoting the long-term viability of women entrepreneurs for the countrys economic growth. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Constraints on the Labour Market Trajectory of Youth and Growth of NEET in India
This paper explores the trends, composition, and determinants of the rising Not in Employment, Education and Training (NEET) population in India. Based on the national level employment-unemployment surveys and macro level panel data, and using instrumental variable (IV) Probit and system generalized method of moments (GMM) regression models, it is explored that a set of supply and demand side factors determining the growth of NEET population in India. At the micro level, the individuals level of general education, technical and vocational training, gender, occupation and gender of head of the family, religion, standard of living of the family, earnings of the spouse, and a set of complex socio-cultural factors determine the NEET status of educated and trained youth. On the other hand, the macro level factors, including the growth of mechanization in agriculture, stagnant real wages, sluggish non-farm sector output growth, infrastructural backwardness, and the existing social-cultural setup in which educated youth live together create a negative macro level environment that compels them to remain out of the workforce for a longer period even after completion of their education/training. Based on these results, it is argued that policies aiming at the development of infrastructure along with the promotion of industry and modern service sectors should be given the top priority for checking the upsurge in the NEET population in India. 2023 XLRI Jamshedpur, School of Business Management & Human Resources. -
Why is the size of discouraged labour force increasing in India?
The Indian economy is currently passing through a critical phase of economic development as its structural transformation in employment has stalled, whilst both the youth unemployment rate and the number of youths Not in Employment, Education, and Training (NEET) have increased to an unprecedentedly high level. In the context in which the share of the youth population is continuing to rise despite the declining fertility rate to below the replacement rate, increased educated youth unemployment has caused an upsurge in the Discouraged Labour Force (DLF). This paper explores the trends, composition, and determinants of rising DLF in India using national level employment-unemployment surveys and macro-level panel data. Based on Multinomial logit and System GMM regression results, it is argued that policies aiming to enhance human capabilities through an improved base of technical education and the promotion of industry are necessary to enhance the growth of quality jobs in order to combat the problem of rising educated youth unemployment and DLF. Moreover, these measures could help in the process of harnessing the demographic dividend in India through an increased level of labour productivity in the long run. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Production of biodiesel from waste fish fat through ultrasound-assisted transesterification using petro-diesel as cosolvent and optimization of process parameters using response surface methodology
Biodiesel is a highly promising and viable alternative to fossil-based diesel that also addresses the urgent need for effective waste management. It can be synthesized by the chemical modification of triglycerides sourced from vegetable origin, animal fat, or algal oil. The transesterification reaction is the preferred method of producing biodiesel. However, the non-miscibility of alcohol and oil layer causes excessive utilization of alcohol, catalyst, and a substantial reacting time and temperature. In the current investigation, transesterification of waste fish oil was performed with petro-diesel as cosolvent, under the influence of ultrasound energy. The combination of both techniques is a unique and efficient way to minimize the mass transfer limitations considerably and hence reduces the parameters of the reaction. It is also a sincere effort to comply with the principles of green chemistry. The optimum reaction conditions were obtained using response surface methodology (RSM) that were as follows: molar ratio of methanol to oil 9.09:1, catalyst concentration of 0.97 wt%, cosolvent concentration of 29.1 wt%, temperature 60.1?, and a reacting time 30min. Under these listed conditions, 98.1% biodiesel was achievable, which was in close agreement with the expected result. In addition, the cosolvent removal step from the crude biodiesel was also eliminated as it could be employed as a blended fuel in CI engines. The Author(s) 2024. -
Efficient Power Conversion in Single-Phase Grid-Connected PV Systems through a Nine-Level Inverter
In this paper, a novel nine-level inverter-based method for achieving efficient power conversion in single-phase grid-connected photovoltaic (PV) systems is proposed. The traditional two-level inverter has poor power quality and a high harmonic content. By using fewer power switches and adding more voltage levels, the proposed nine-level inverter gets around these restrictions, improving power conversion efficiency and lowering total harmonic distortion (THD). The effectiveness of the indicated technique for accomplishing better power quality and greater overall system efficiency is demonstrated by the simulation findings. A promising approach to improving the efficiency of single-phase grid-connected PV systems is the suggested nine-level inverter. 2023 IEEE. -
Efficient Integration of Photovoltaic Cells with Multiport Converter for Enhanced Energy Harvesting
This research work presents a novel approach for the efficient integration of photovoltaic (PV) cells with a multiport converter to enhance energy harvesting in renewable energy systems. The proposed system combines the advantages of PV technology with the flexibility and scalability of multiport converters, enabling improved power extraction and utilization from solar energy sources. The integration is achieved by employing a multi-input multi-output (MIMO) control strategy, which optimally distributes power among multiple energy storage systems and loads. A comprehensive modeling and analysis of the PV cell characteristics and the multiport converter are conducted to identify the optimal operating conditions. Furthermore, a power management algorithm is developed to dynamically regulate the power flow and maximize the energy harvesting efficiency. The proposed approach demonstrates superior performance compared to traditional single-input single-output converters, achieving higher energy yields and enabling effective integration of PV cells in diverse applications. Simulation results validate the effectiveness of the proposed approach, showcasing its potential to significantly enhance energy harvesting from photovoltaic sources and contribute to the development of sustainable and reliable renewable energy systems. 2023 IEEE. -
Enhanced Design and Performance Analysis of a Seven-Level Multilevel Inverter for High-Power Applications
The structure and performance analysis of a seven-level multilevel inverter is discussed in this study. Due to their capacity to get around the drawbacks of traditional two-level inverters, like high voltage stress on power devices and harmonic distortion, multilevel inverters have attracted a lot of attention lately. Multiple voltage levels can be produced by the seven-level multilevel inverter which is being proposed because it uses a sequential arrangement of power sources and capacitors. The design methodology involves selecting appropriate power devices and capacitance values to achieve the desired voltage levels while minimizing losses and ensuring reliable operation. Total harmonic distortion (THD), inverter efficiency, and voltage stress on power devices are all considered as part of the performance analysis. In comparison to conventional two-level inverters, simulation results indicate that the proposed seven-level multilevel inverter offers lower THD, increased efficiency, and reduced voltage stress. This research contributes to the advancement of multilevel inverter technology and its potential applications in various power conversion systems. 2023 IEEE. -
Strategic Power Factor Management for Elevated Lift and Hoist Performance
The paper outlines the design and simulation of active power factor correction for a 100 hp induction motor using MATLAB/Simulink. In this system, the induction motor functions as the primary load, operating with a low power factor. Different load scenarios are simulated to examine the motor's performance. The current drawn from the supply is verified under varying conditions, both with and without the implementation of a variable capacitance bank. The power system network comprises apparatus such as Induction Motors, Power Transformers, and Induction Furnaces, contributing to a low power factor. The resultant low power factor leads to elevated energy consumption. To mitigate this, power factor correction is imperative. Utilizing a variable capacitance proves instrumental in enhancing the power factor. The capacitor compensates for a portion of the reactive power, consequently reducing the total reactive power drawn from the source. This reduction in reactive power contributes to an overall decrease in power consumption. The research focus is on the effective correction of the power factor for a 100 hp induction motor through comprehensive design and simulation using MATLAB/Simulink, providing valuable insights into the impact of variable capacitance on current draw under diverse load conditions. 2024 IEEE. -
Analysis of Nine Level Single-Phase Cascaded H-Bridge Inverters for EVs
This paper explores the design and operation of a Modular Nine-Level Inverter (MLI)-Electric Vehicle (EV) charging system, incorporating solar energy to power domestic loads and charge EVs. The system comprises a solar panel, DC-DC regulator, and MLI for efficient energy conversion. The MLI's modular design reduces complexity and enhances efficiency. Equivalent circuits illustrate voltage level generation, while PWM control regulates power device switching for precise output control. Performance metrics, including regulated DC supply voltage and staircase nine-level output voltage, demonstrate the system's capability for diverse applications. A nearly sinusoidal current waveform and harmonic analysis underscore the system's effectiveness in delivering stable power with reduced harmonic distortion. Comparisons between filtered and unfiltered output highlight the importance of filtering techniques in improving power quality. Overall, the MLI-EV charging system showcases advancements in renewable energy integration, offering a versatile solution for sustainable electricity generation and EV charging. 2024 IEEE.