Volume 12 | Issue 3

 Abstract

This comprehensive review explores various dimensions of dyslexia, focusing on its neurological underpinnings and the intricate challenges it poses to education. Emphasizing the multifaceted nature of dyslexia,the paper scrutinizes educational approaches, highlighting the pivotal role of inclusive education and assistive technology. Theimpact of dyslexia on online learning is examined, revealing a gap in research on the challenges faced by dyslexic individuals in digital education. Amid the global shift to online education during the COVID-19 pandemic, the study suggests solutions such as voice recognition technology to address educational inequality. The paper further reviews the evolving landscape of technicalsolutions, advocating for standardized assessmentsand usability testing. Special attention is given to voice navigation technologies and their potential to enhance the learning experience for dyslexic children. Additionally, the integration of smart technologies, including voice assistants, is explored to create inclusive and interactive learning environments, particularly in early childhood education.

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 Keywords

Dyslexia, Inclusive Education, Assistive Technology, Online Learning, Voice Recognition Technology, Voice Navigation, Smart Technologies, Inclusive Learning, Language Evolution, Human-Machine Interaction, Internet of Things, Convolutional Neural Networks.

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privacy preserving data mining, anonymization based approaches have been utilized to safeguard the privacy of a person. Existing writing tends to different anonymization based approaches for preserving the delicate private data of a person. The k-namelessness model is one of the broadly utilized anonymization based approach. Be that as it may, the anonymization based approaches experience the ill effects of the issue of data misfortune. To limit the data misfortune different best in class anonymization based clustering approaches viz. Ravenous k-part calculation and Systematic clustering calculation have been proposed. Among them, the Systematic clustering calculation gives lesser data misfortune. Furthermore, these approaches utilize all characteristics during the making of an anonym zed database. Along these lines, the danger of exposure of delicate private data is higher through distribution of the considerable number of traits. In this paper, we propose two approaches for limiting the revelation hazard and preserving the privacy by utilizing deliberate clustering calculation. First approach makes an inconsistent mix of semi identifier and touchy property. Second approach makes an equivalent mix of semi identifier and touchy property. We likewise assess our approach exactly concentrating on the data misfortune and execution time as essential measurements.

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privacy, k-anonymity, clustering, data mining, information loss, data utility Big Data, Privacy Preserving

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During the past few years, the fields of computer vision and natural language processing has drawn more attention in the issue of automatically generating descriptive sentences for images, which is known as image captions.An image caption is a written description of an image that is widely used in programs that require information from images in a text format.Understanding the image's semantics and being able to construct descriptive sentences with the right structures are necessary to generate image captions. Rapid progress in AI (Artificial Intelligence) has led numerous researchers to focus on the area of image captioning. By utilising advanced deep- learning techniques, large datasets, and computer power, a model can be built to efficiently generate captions. The model is trained to generate captions that describe the input image. To achieve this objective, the Encoder - Decoder model utilises two advanced deep learning algorithms: CNN (Convolutional Neural Network) and Transformers. Initially, feature extraction is performed, followed by generation of captions. For this task, a pre-trained CNN model, EfficientNetB0 is employed.The Flickr_8k dataset, which contains 8000 images and five different captions for each image, is used to train the model.

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 Keywords

Caption generator, Transformers, CNN (Convolutional Neural Network), EfficientNetB0, Encoder - Decoder.

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Employee retention has emerged as a critical concern in the Business Process Outsourcing (BPO) industry due to its direct impact on organizational stability, productivity, and profitability. This paper provides a comprehensive review of employee retention strategies within the BPO sector, aiming to identify key factors influencing retention and effective strategies for mitigating turnover. The study also focuses on employees' preferences about different variables of the work environment. The study was conducted through descriptive analysis at PharmDart Consulting (OPC) Pvt. Ltd. in Raipur with a sample size of 30 employees which includes administered to managers, executives, and various other employees belonging to various departments. The review highlights several factors contributing to high turnover rates in the BPO industry, including work stress, job satisfaction, organizational culture, career development opportunities, and compensation packages. Furthermore, it examines the unique challenges faced by BPO firms, such as intense competition, demanding client expectations, and the nature of repetitive tasks. Moreover, this paper identifies and evaluates various retention strategies BPO companies adopt to address these challenges. These strategies encompass a range of approaches, including the enhancement of workplace culture, implementation of flexible work arrangements, provision of skill development programs, improvement of compensation and benefits packages, and fostering a supportive work environment.

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Employee retention, BPO Industry, organizational stability, productivity, and profitability.

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A Quasi experimental one group pre-test post-test study was conducted to assess the effectiveness of video assisted teaching regarding Good touch and Bad touch among pre puberty age students in a selected school of Guwahati, Assam. The objectives of the study were to assess the pre - test knowledge score regarding "Good touch and Bad touch" among pre pubertal age students in a selected school of Guwahati Assam, to assess the post test knowledge score regarding "Good touch and Bad touch" among pre pubertal age students in a selected school of Guwahati Assam, to evaluate the effectiveness of video assisted teaching regarding "Good touch and Bad touch" among pre pubertal age students in a selected school of Guwahati Assam, to find out the association of the knowledge of Good touch and Bad touch among the pre pubertal age students with the selected demographic variables such as age, gender, religion, class, type of family. The children who were studying in class 3, and 4 who were selected by proportionate random sampling technique. Total 68 samples were selected. Self structured questionnaire were used to collect the data and analyzed according to the objectives of the study. Using both descriptive and inferential statistics the findings shows that out of 68 majority of the students, 37(63.79%) students fall under the age group of <7years,36 (52.94%) students are female,48 (70.58%) students are Hindu,25 (36.76%) students have nuclear family, and 40 (58.82 %) are from class 3. The study reveals that the Pre test knowledge score is found that out 68 students majority i.e 44 (64.70%) students had inadequate knowledge, 14 (17.41%) students had adequate knowledge and 10 (14.70%) students had moderately adequate knowledge regarding Good Touch and Bad Touch with overall M = 11.63 and SD = 1.5 and the Post test knowledge score shows that out of 68 students 32 (47.05%) students had adequate knowledge and 22 (32.35%) students had moderately adequate knowledge and 14 (20.58%) students had inadequate knowledge regarding Good touch and Bad touch after video assisted teaching with overall M=13.62 and SD = 1.89. The comparison between pre test score and post test score shows that there was significant difference between pre test (M = 11.63, SD = 1.5) score and post test (M = 12.62, SD = 1.89) score with a mean difference of 1.99 and Paired t test score is 6.55 and df = 67.Hence the Video assisted teaching programme has improved the knowledge regarding Good touch and Bad touch among pre puberty age students. In association we found that there is significant association between the pre test knowledge with religion, and there is no significant difference between pre test knowledge with age, gender, types of family and class.

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 Keywords

effectiveness, video assisted teaching , good touch, bad touch, pre pubertal age

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Idiopathic pulmonary fibrosis (IPF) is a common and deadly fibrotic lung disease with a median survival time of 2 to 3 years. It is characterized by chronic, progressive fibrosis that worsens over time and is linked to high mortality, progressive respiratory failure, and loss of lung function. Diagnosing IPF requires clinicians to integrate clinical, laboratory, radiologic, and pathologic data. Epidemiologically, IPF primarily affects older adults, with prevalence increasing with age, especially in those over 60. Gender and race differences exist, and risk factors include smoking, environmental exposures, and genetics. IPF is often associated with comorbidities, and its prognosis varies, with a median survival of 3 to 5 years. Early detection of pulmonary fibrosis is crucial for better outcomes, relying on clinical history, physical examination, pulmonary function tests, imaging, biomarkers, and, in some cases, genetic testing. Early intervention may slow disease progression. Currently, no established therapy exists for IPF, but new approaches aim to minimize acute lung injury consequences. Medications such as azathioprine and cyclophosphamide, and interventions like lung transplantation, have been explored with varying success. IPF poses a significant threat to society, necessitating ongoing research efforts for effective therapeutic targets. Understanding the molecular mechanisms underlying IPF development is crucial for future investigations and the development of successful treatments.

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Pulmonary Fibrosis, Diagnosis, Treatment, Idiopathic, Pathogenesis

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 Abstract

JANPAD PILIBHIT KE KASHTURBA GANDHI AVASHIY VIDHYALAY AVM PARISHADIY UCCH PRATHMIK VIDHYALYO ME UDHYAPANRAT BALIKAO KI SAIKSHIK UPLABDHI KA ADHYAYAN

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JANPAD PILIBHIT KE KASHTURBA GANDHI AVASHIY VIDHYALAY AVM PARISHADIY UCCH PRATHMIK VIDHYALYO ME UDHYAPANRAT BALIKAO KI SAIKSHIK UPLABDHI KA ADHYAYAN

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Ensuring the integrity and security of electoral processes is paramount in democratic societies. Current Electronic Voting Machines (EVMs) have become prevalent in modern elections due to their efficiency and reliability. However, they still face challenges such as identity verification and security threats. This project proposes the development of an Electronic Voting System (EVS) integrated with facial recognition technology to address these issues. The EVS aims to enhance the existing EVM by providing a more secure, efficient, and accessible platform for voters. Leveraging facial recognition and iris detection technology, voters can authenticate their identity seamlessly and securely, mitigating impersonation and unauthorized access concerns. Furthermore, the EVS offers convenience to voters by eliminating the need for EVMs and reducing waiting times at polling stations.

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Electronic Voting Machines, Facial Recognition, Electronic Voting System with Face Recognition.

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Wheelchair and stretchers are commonly used in hospitals. And this medical equipment is used for transferring patients from one place to another. During transferring patients, it creates problems to patients and also creates problems for attendant and nurse. Sometimes it creates problems to patient while transferring patient from wheelchair to stretcher, stretcher to bed and bed to wheelchair is always issue for both hospital staff and family members of patient. This system causes stress, body pain to patients and sometimes chances to sleep down the patient. Understanding the various issues regarding the mobility equipment a better design will be an asset for medical field and helpful for disabled person. This paper presents the various design and fabrication of wheelchair cum stretcher and aims to explore design for patient to transfer patient from bed to wheelchair and wheelchair to stretcher. This innovation helps medical staff to transfer patient from chair to bed very easily because chair become a stretcher and it is adjustable to height of bed. Conversion of wheelchair to stretcher and vice versa is achieved by simple linkage mechanism which can be manually or automatically operated mechanism.

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 Keywords

propulsion, CAD, strecher

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Artificial intelligence (AI) has come a long way from philosophical musings to a reality transforming our world. Its emergence can be traced through history, with advancements in computing power and algorithms fueling its growth. This abstract explores various aspects of AI: o History and Evolution: We'll delve into the early ideas of AI and its development over time, highlighting key breakthroughs in machine learning and neural networks. o Impact on Society: The focus then shifts to how AI is influencing our lives, from revolutionizing industries to prompting ethical questions about data privacy and automation. o The Future of AI: We'll explore what the future holds for AI, considering its potential to address global challenges and the need for responsible development. Artificial intelligence (AI) has come a long way since its theoretical beginnings in the mid20th century. From the pursuit of replicating human thought processes to the current focus on machine learning and deep learning algorithms, AI is rapidly transforming our world. This emergence of AI presents a multifaceted picture, brimming with both opportunities and challenges. On the positive side, AI holds immense potential for progress across various sectors. It can revolutionize industries through automation, enhance scientific discovery with its analytical prowess, and improve our quality of life through personalized services and intelligent machines. This abstract provides a glimpse into the multifaceted world of AI, highlighting its historical roots, societal influence, and its exciting, yet thought-provoking, future

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#AI #ArtificialIntelligence #EmergenceofAI

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 Abstract

Marathi Abhilekhon Me Rampura

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Marathi Abhilekhon Me Rampura

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'Lakshmi' is much sought after in Hindu mythology. Devas, Asuras. Rakshash, Yakshas all need and vie for them. Rakshashas usurp wealth. Yakshas too forcefully seize and hoard wealth. Asuras who live in 'patal' believe that Lakshmi rightfully belongs to them and is therefore in perpetual war with the Devas who enjoy prosperity in 'Swarg'. The monastic order on the other hand shuns wealth and is therefore conspicuous by the absence of the role of women. Wisdom however is all about appreciating and not denying wealth. In the Puranas, it is said Vishnu always attracts wealth. That is why his abode, Vaikuntha, is the land of happiness. It's a playground or 'ranga-bhoomi'. Pattanaik contrasts this with Swarga, the paradise of Indra, king of the devas, who is constantly fighting Asuras. His abode is 'rana-bhoomi' or battleground as he chases Lakshmi and tries to prevent the Asuras from taking her away. Rich companies phenomenally successful are all under siege constantly battling workers, courts, regulators, struggling to get land from villagers and licenses from the government. They don't attract investments, the absence of Vaikuntha. But they are constantly fighting starvation despite bumper harvests; we are 'Swarga'. Menaka and Mohini are same in appearance. But while Menaka seeks to entrap the sage, Mohini seeks to enlighten the sage. In a society that wanted all men to have wives, women's freedom had to be curtailed. Laws had to be created so that she did not leave her husband for a better or more desirable man. Chastity of women served to allay male anxiety over their incompetence and inadequacy. This paper looks at the myth making of women that justifies the troubled relationship between the entrepreneur and the enterprise thus paving the way for social inequality in India.

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wealth, alakshmi, vaikuntha, rangabhoomi,ranabhoomi,appropriation, appreciation

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Abstract: Graph pattern mining is a vital research field. It includes the identification of interaction flows between compounds found in chemicals or genes. This is attained by representing these compounds as graph interactions, allowing researchers to evaluate and recognize complex relationships and patterns. Graph-based representations provide researchers with a powerful tool to uncover valuable insights and make informed decisions in various fields. Extracting the interaction flow from these graphs is a very challenging task. Data mining technique such as Clustering is used to groups graph nodes with significant communication to discover the graphical interaction flow. To address this, we propose the Irrelevant Feature-aware NMF Clustering Method (IF-NMFCM) for clustering graph nodes. This technique focuses on eliminating irrelevant features to improve clustering accuracy while reducing associated dataset complexities. It incorporates principal component analysis for data pre-processing and utilizes the Particle Swarm Optimization (PSO) method for feature selection, ensuring the exclusion of irrelevant features. By adopting this technique, we obtain an optimal feature set that enhances clustering accuracy. Finally, pre-processed data is represented as a graph and then clustered using the hierarchical NMF clustering method. Our proposed research work establishes superior results in terms of improved accuracy rate than the existing approaches. The research work is implemented in MATLAB simulation environment for comprehensive analysis.

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Graph Mining, Clustering, Preprocessing, Classification, IF-NMFCM, NMF

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 Abstract

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This research delves into the intricate interplay of geography, politics, and society in the Hindoli Assembly Constituency during the November 2023 elections in Rajasthan, India. As a microcosm of India's democratic ethos, Hindoli witnessed the convergence of 210 polling villages, each with unique socio-economic dynamics, contributing to the mosaic of regional identities and cultural nuances. Through a multidisciplinary approach, the study aims to unravel spatial variations in voter turnout, political affiliations, and electoral participation, shedding light on the impact of local issues on electoral dynamics. The research bridges the gap between political science and geography, contributing valuable insights to the broader discourse on election geography and democratic processes.

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Elections, Electoral geography, Voter behaviour and Spatial dynamics

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Digital-financial education is a very important part of the modern finance and economy. It is a very essential part for success of digital financial inclusion via extensive use of e payment platforms. In the times of e-commerce, it is difficult to imagine the economy without e payment platforms. They are used in online shopping, money transfer, vendor payment as well as for investments. Purpose: The paper deals with the impact of digital-financial literacy on the factors that are responsible for adoption and usage of e payment platforms(derived from TAM and its extension). Methodology: The research was done on a sample size of 125 students in order to understand how digital financial literacy impacts Perceived Risk, Perceived usefulness, Perceived ease of use, Trust, Attitude and Behavioral intention towards usage of e payment platforms. Correlation and Regression was used to understand the relationship between the variable. Findings: The impact of Digital financial literacy on Trust on e-payment platforms was found to be positively significant.It also has a significant impact on Behavioral intention to use e-payment platforms and Attitude towards e payment platforms ( R2 values of .416,.650 and .606 respectively) while its impact on Perceived Risk was not found significant.Perceived usefulness and perceived ease to use the e payment platform also had positive correlations with Digital financial literacy. Originality:The use of digital tools for financial services has achieved popularity in the recent times.It becomes important to understand how the digital financial literacy is impacting the usage of digital financial tools. The paper helps to understand how digital-financial literacy impacts the factors that are responsible for adoption and usage of e payment platforms.This paper will help not only help to understand these relations but also open ways for open ended studies of such relations.

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Digital financial literacy, Digital financial inclusion, e payment platforms, Perceived Risk, Perceived usefulness, Perceived ease of use, Trust,Attitude, Behavioral intention

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Cosmology is a discipline to understand the nature of origin, evolution, large Scale Structure, and ultimate fate of the universe. It is perhaps the oldest discipline of the world. Cosmological models which are spatially homogeneous but anisotropic have significant role in the description of the universe at its early stages of evolution. The cosmological and astronomical data obtained from the supernovae Ia (SNeIa), the CMB radiation anisotropies, The Large Scale Structure (LSS) and X-ray experiments support the discovery of accelerated expansion of the present day universe [1-8].

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Anisotropic; Bianchi Type-vi; Cosmological; Model; Dark Energy; Electromagnetic; Field

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Creative Commons Attribution 4.0 and The Open Definition

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Service quality is the ability of the organization to meet or exceed customer expectations. The SERVQUAL scale developed by Parasuraman, Zeithaml and Berry has been widely accepted throughout the world to measure the gaps in service quality. Globalization, liberalization and privatization of Indian economy has given rise the scope for the service industry to grow at a rapid pace. Indian consumers become more conscious in terms of quality. Higher education in India has become more competitive after private players' entry in to the market and competition from global players. Existing players, especially private institutions, need to concentrate more on quality aspects to satisfy the present customer requirements. The present study has been conducted to find the gap between student expectations from a higher education institution, their perception of the present institution and their satisfaction levels. The study has been conducted at one of the top engineering colleges in Chittor district. SERVQUAL Questionnaire was used as a data collection tool. The sample size used for the study is 100. The study supports Hasan et al. (2008) work that empathy and assurance are the more critical factors that determine the student satisfaction, and there is a relationship between service quality and student satisfaction.

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SERVQUAL higher education

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Creative Commons Attribution 4.0 and The Open Definition

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Historically, writers like Christopher Marlowe, William Blake, and PB Shelley, were seen as mad or a threat to society because they challenged societal norms and explored taboo subjects, often at great personal cost. Old English Law defines lunacy as, a person who had understanding but by disease, grief or other incidences had lost the use of his reason while still retaining some lucid intervals. Victor Frankenstein, in Frankenstein by Mary Shelley (1818) experiences grief due to the dismissal of his beloved mother. He was continuously denied opportunities to process his grief. His repressed grief and isolation turned him into an ambitious man, perhaps a madman in the eyes of society. Although Victor wasn't a good person or even a human being with humanity towards his creation, Victor was ahead of his time in understanding and creating a human life, and so was Mary Shelley for challenging the "Victorian values" and exploring themes like sexuality, grief, ambition, God and creation. Mary Shelley's Frankenstein was ahead of its time. Be it for its scientific approach and being the pioneer of the sci-fi genre but also for commenting on nature vs nurture and forcing the reader to question whether a monster or a madman is born or created by society.

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taboo subjects, madness, grief, ambition, Victorian values,nature vs nurture.

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Creative Commons Attribution 4.0 and The Open Definition

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Complex mobile applications have increased as a result of Wireless Sensor Networks (WSN) being more prevalent and having improved communication and sensing capabilities. But with less resources, WSNs now have even stricter capacity constraints to contend with. A novel network architecture that expands cloud computing provides a potential remedy for this. However, because of its dynamic edge computing environments and high implementation costs, cloud computing presents certain unique issues, such as server strain. The challenge is to allocate compute and network resources as cheaply as possible while satisfying WSN demands under dynamic circumstances. We provide a clever Machine Learning (ML) strategy to address this. In changing cloud settings, it balances resource utilization, shortens service times, and assigns resources dynamically. In our project we have used algorithms like Particle Swarm Optimization (PSO) and Bee Colony Optimization (BCO) as existing and Atomic Orbital Search Optimization (AOSO) as proposed. All are measured in terms of Delay, Packet Delivery Ratio, Energy Efficiency and Throughput. From the results the proposed Atomic Orbital Search Optimization (AOSO) performs well compared to other algorithms.

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Wireless sensor network, Optimization, Clustering, Machine Learning, Atomic Orbital Search

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Creative Commons Attribution 4.0 and The Open Definition