Volume 12 | Issue 4 |

 Abstract

This research draws from an ecofeminist perspective, and this narrative provides an understanding of how female characters navigate their relationships with nature and resist morality, justice, and harm to the environment. Anita Desai's "Fire on the Mountain" and "Where Are We Going This Summer?" Illustrations of women seeking comfort, function and tone exploration in physical space are presented. Desai's heroes travel the rugged terrain of the Himalayas and the serene coasts of India, escaping the constraints of patriarchy in the splendor of the natural world. Through these narratives, Desai demonstrates that women engage with their environment and challenge notions of women and culture by questioning genderless forces of power and respect. In Coffer Dams, Kamala Markandaya explores the dangers of intervening in the world, particularly through head design. The intersection of gender, class, and environmental injustice is exacerbated by Markandaya's female characters who face the loss of ancestral lands and ecosystems. Markandaya turned away from the advocates of patriarchal music and feminist ecological practice, whose struggles included the voices of marginalized groups. Examine how female characters are images of women that differ slightly from natural interaction. By analyzing these narratives, we can reveal the flexibility of ecofeminism in literature and its protective value for environmental promotion and justice.

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 Keywords

Ecofeminism , Women, Nature, Environmental

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The deaf population uses sign language, a visual form of communication that uses hand gestures and movements instead of spoken words, to communicate. For efficient communication, deaf people frequently need sign language interpreters, which can be difficult and expensive. As such, there is a pressing need to create a system that enables communication using sign language. This kind of communication uses gestures, hand forms, and facial expressions to transmit information. Sign languages exhibit both national and regional diversity; examples include Arabic, American, Chinese, and Indian sign languages. Everyone needs effective communication, but those who are hard of hearing or deaf really need it. Closing the communication gap between hearing and non-hearing people is critical given the increasing incidence of hearing impairments. Therefore, we are presenting a novel system that uses machine learning and computer vision techniques to translate Sign Language into text.

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Machine Learning, Computer vision, CNN, Hand Gesture.

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The community of northeast India is a minority and as students, receiving the adequate resources for their capabilities is necessary, thus that is usually the reason why the students from different northeast states decide on pursuing their higher education in more developed cities that have better facilities. The purpose of the present study is to examine Academic Procrastination behavior among northeast students studying in Delhi NCR, by investigating its prevalence and possible reasons, as well as differences in gender. The cross-sectional study was conducted on a sample of 120 northeast university students (69 female, 51 male), using a purposive sampling method. Data was collected by administering the Procrastination Assessment Scale-Student (PASS) by Solomon & Rothblum (1984) to measure the prevalence and reasons of academic procrastination. Results showed that overall 44.1% of the students were "nearly always/always" procrastinators. 39.1%, 51.6%, 483%, 30.8%, 22.4%, and 24.9% of the participants procrastinated almost always/always in the first to sixth areas of the PASS respectively. Additionally, the results revealed that procrastination was an issue quite often and most of the students indicated an eagerness to lessen this behavior. The main reasons for academic procrastination were found to be decision-making difficulty, time management, task aversivesness, and laziness. Independent sample t-test revealed no significant differences in gender with respect to the level of academic procrastination.

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 Keywords

academic procrastination, prevalence, reasons, gender, northeast students.

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One of the most common and recurrent natural disasters in the world is flood. The economic damage and casualties brought on by the flood have burdened the economy more than any other natural disaster because of its recurrent prevalence. India has consistently experienced numerous floods, which have resulted in significant financial, human and aquatic habitat losses. India suffered a whopping USD 79.5 billion (UN) economic loss due to climate-related disasters in the last 20 years, according to a UN report which highlights the impact of extreme weather events on the global economy. It has been discovered that flood incidents are rising quite quickly. Climate change, cloud bursts, tsunamis, inadequate river management, silting, etc. are many potential causes, but the destruction is getting worse for both lives and economies. India's disaster management policies and programs are very structured and well-organized, but more efficiency is needed in their administration and execution. Floods caused greater economic and human losses during the past ten years than any other calamity.

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: Floods, UN, Natural calamities, Economic losses

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1. ABSTRACT Mr. Rangaraja.R.V, Student Department of Information Technology, SRM Valliammai Engineering College, Chennai, Tamil Nadu, India rangaraja568@gmail.com Mr.Pradeep.S, Student Department of Information Technology, SRM Valliammai Engineering college, Chennai, Tamil Nadu, India pradeep07@gmail.com An online program for hyper-local e-commerce connects clients in the vicinity with local businesses. With the app, consumers can browse products and services offered by local businesses, place orders, and quickly have their purchases delivered or picked up. Clientele may Thanks to the application's simple and user-friendly design, users can easily determine what they need and place orders. Selling products and services online is made easier for merchants by a number of advantages provided by the hyper-local e-commerce web application. Retailers may upload their products and maintain their online store with ease thanks to an intuitive interface. Customers are able to shop whenever they choose because they have the option to choose their working hours and delivery or pickup options. A significant advantage of a hyper-local e- commerce web application is its support for local businesses and the promotion of local shopping. This platform aids in community growth and strengthens the local economy by simplifying the process for customers to find and buy products from nearby shops. In summary, a hyper-local e- commerce web application serves as an effective conduit for enhancing communication between local customers and small enterprises.

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KEYWORDS- Hyper local, E-commerce, Application, Online shopping, Local delivery, neighborhood, Marketplace, Customer experience, Mobile optimization, Local vendors, User interface, Shopping cart, Checkout process.

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Deep learning and neural networks have had a dramatic impact on many fields, notably with the widespread use of Convolutional Neural Network (CNN) models. These models have proved indispensable in a wide range of applications, including image recognition and segmentation. The introduction of CNNs has ushered in an era of extraordinary accuracy and efficiency in activities that were previously considered difficult for standard algorithms. One of the most recent developments in this field is the release of "CogniCapture: Visual Insight Engine," a cutting-edge application that uses CNN models. This utility uses numerous critical components to improve its performance. To efficiently handle visual data, it uses the Max pooling function in conjunction with two crucial activation functions, ReLU and Simoid. Furthermore, to successfully fine-tune the model parameters, the Adam optimizer is used, with categorical_crossentropy as the loss function. Furthermore, the model's cornerstone is its pretraining with the widely regarded EfficientNetB1 architecture, which ensures resilience and adaptability acrossa wide range of datasets. The integration of these components within CogniCapture demonstrates a comprehensive approach to visual data analysis and insight development. CogniCapture improves accuracy and speed in picture classification and segmentation by leveraging the power of CNNs and optimising their design and training procedures. This technology offers a big step forward in using deep learning for practical applications, with transformational capabilities in domains ranging from healthcare and autonomous systems to marketing and security.

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Convolutional Neural Network (CNN), EfficientNet Activation Function, MaxPooling2D, Adam Optimizer, Categorical Crossentropy

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This paper proposes a method to reduce the cogging torque of PMBLDC motor. This paper presents some effective methods of minimizing cogging torque, which have minimum effects on the performance of the motor. In this paper we are applied two techniques 5- Parts Alternate PM and Stator Slot design. In this paper using Magnet Software a cogging torque reduction can be achieved.

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Cogging Torque, Permanent Magnet Brushless DC Motor (PMBLDC), Torque Ripple, Finite Element Analysis (FEA).

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Asthma is the most common inflammatory disease of the lungs. The prevalence of asthma is increasing in many parts of the world that have adopted aspects of t Western lifestyle, and the disease poses a substantial global health and economic burden. Asthma involves both the large-conducting and the small- conducting air ways, and is characterized by a combination of inflammation and structural remodeling that might begin in utero. Disease progression occurs in the context of a developmental background in which the postnatal acquisition of asthma is strongly linked with allergic sensitization. Most asthma cases follow a variable course, involving viral- induced wheezing and allergen sensitization, that is associated with various underlying mechanisms (or endotypes) that can differ between individuals. Each set of endotypes, in turn, produces specific asthma characteristics that evolve across the life course of the patient. Strong genetic and environmental drivers of asthma interconnect through novel epigenetic mechanisms that operate prenatally and throughout childhood. Asthma can spontaneously remit or begin de novo in adulthood, and the factors that lead to the emergence and regression of asthma, irrespective of age, are poorly understood. None the less, there is mounting evidence that supports a primary role for structural changes in the airways with asthma acquisition, on which altered innate immune mechanisms and microbiota interactions are superimposed. On the basis of the identification of new causative pathways, the sub phenotyping of asthma across the life course of patients is paving the way for more-personalized and precise pathway- specific approaches for the prevention and treatment of asthma, creating the real possibility of total prevention and cure for this chronic inflammatory disease.

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Asthma , Chronic etc.

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It is a species of double stranded DNA contagion that causes in humans and other mammals.

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Monkey Pox, mammals

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The "Leaf Disease Detection using Image Processing " project aims to tackle the critical challenge of timely and accurate detection of plant diseases through the integration of advanced image processing techniques and Convolutional Neural Networks (CNNs). Plant diseases can significantly impact agricultural productivity, making early detection a crucial aspect of modern farming practices. This project seeks to develop an efficient and automated system for identifying leaf diseases using the MATLAB environment. The project begins by assembling a comprehensive dataset of leaf images, encompassing both healthy and diseased samples. These images undergo preprocessing to enhance their quality, including noise reduction, resizing, and normalization .

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Convolutional Neural Networks , MATLAB ,Noise Reduction, Resizing and Normalization

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