Volume 7 | Issue 1 |

 Abstract

It is essential for any country to develop the various sectors for the sustainable development of country's economy and to get the competitive advantage in the current global scenario. After introducing economic reforms and globalization in 1991, it is a challenging to the developing countries to participate in the global markets to prove themselves and to get possible competitive advantage. In spite of these obstacles, the government has introduced the concept of SEZs in the year 2001 in India in the name of the enhancing the industrial production as well as development. For the establishment of SEZs in India agriculture farmers are losing their land and migrating to other places along with their families. Of course, SEZs are supporting the GDP and economic development in India. In this backdrop this paper made an attempt to identify the performance in terms of investment, employment and exports. For this study the secondary data has been collected from various secondary sources like journals, magazines, newspapers and other literature review and the collected data analyzed and presented in tables.

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 Keywords

Special Economic Zones, Investment, Employment, Exports, India

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Indira Goswami, widely recognized by her pen name Mamoni Raisom Goswami and affectionately known as Mamoni Baideo, stands as one of the most illustrious figures in modern Assamese literature. As Prof. Hiren Gohain remarked, "Mamoni Raisom Goswami is the most extraordinary thing to have happened to Assamese literature in recent years," highlighting the profound impact she has made on the literary landscape of Assam. Her contributions as a writer, poet, professor, scholar, and editor have earned her numerous accolades, including the prestigious Sahitya Akademi Award in 1982 for her novel Mamare Dhara Tarowal (The Rusted Sword). She is the only female writer from Assam to have received the Jnanpith Award in 2000 for her significant contributions to Assamese literature. In addition to these honors, she was awarded the international Tulsi Award from Florida International University for her book Ramayana From Ganga to Brahmaputra and was recognized with the Asom Ratna, Assam's highest civilian award, for her immense contributions to the state.

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Revolt and Resilience: The Role of Women in Mamoni Raisom Goswami's Moth Eaten Howdah of the Tuskar

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In recent years, the process of identifying criminals has become more complex due to the evolving tactics used to evade capture. Traditional identification methods, such as fingerprinting and DNA analysis, are often slow and inefficient, especially when modern criminals consciously avoid leaving behind biological traces. To address this challenge, law enforcement agencies are increasingly adopting advanced technological tools like face recognition systems, which offer faster and more reliable methods for identifying suspects. This paper presents the development of a criminal identification system using face recognition technology, implemented in Python. The system harnesses existing surveillance infrastructure, such as CCTV cameras, and employs machine learning algorithms to detect and recognize faces in real-time. By integrating computer vision techniques with deep learning-based facial recognition models, the system automates the identification process, reducing the dependency on traditional methods. The proposed system is designed to work in diverse environmental conditions and can handle variations in lighting, facial expressions, and occlusions. Through extensive testing, the system has demonstrated a high level of accuracy and efficiency, making it a valuable tool for law enforcement agencies. This project aims to streamline criminal identification, ensuring faster suspect tracking, enhancing public safety, and improving response times. The paper further explores the potential challenges, including data privacy concerns, ethical implications, and system limitations, providing insights into how such technologies can be effectively integrated into modern law enforcement practices.

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 Keywords

Criminal, Face detection, Face Recognition, Criminal Identification, python

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This research article examines gender parity in politics by assessing the progress made, obstacles encountered, and future prospects for women in political leadership roles. It traces the historical evolution of women's political participation and highlights the increasing number of women in leadership positions globally. Despite these advancements, persistent structural, social, and cultural barriers continue to hinder women's equal representation in political systems. The article discusses key challenges such as gender bias, unequal access to resources, and political violence. It also reviews successful strategies like gender quotas and grassroots advocacy that have empowered women in politics. Through case studies and trend analysis, the article provides a comprehensive overview of the current state of gender parity in politics and offers recommendations for overcoming obstacles and accelerating progress.

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 Keywords

Gender Parity, Political Representation, Gender Quotas, Women in Politics, Political Leadership, Gender Bias, Political Empowerment, Structural Barriers, Political Violence.

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In the year 2007, the Government of Karnataka implemented the English as a second language from the first standard in Non-English Medium schools. Here, I try to analyze the opinions of the stakeholders such as teachers, parents, learners, inspecting authorities and administrators in this article. The opinions of the stake holders that I sketch here are based on the data that I have collected through the questionnaires and ethnographic interviews. My intention here is to test whether the opinions of the stakeholders meet the objectives set by the Government and policy makers or not. The Government has already declared that it had passed the order after the serious discussions relating to the implementation of the policy of teaching English from the first standard on the public demand, and it has quoted the findings of surveys in the field of English language teaching. But some of the intellectuals blamed the Government's action and complained that it was an act to secure vote bank and it did it to please capitalists. So, here I want to know the mindset of public/stakeholders towards English language and correlate it with the official objectives.

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 Keywords

ELT, Occupation, Profession, Tuition, profile

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Food security refers to the reliable availability, affordability, and access to food for everyone. Achieving food security and ending hunger are central objectives of the Sustainable Development Goals (SDGs). For India, food security remains a top development priority because high economic growth rates have not translated into reduced hunger and malnutrition. While large segments of the Indian population suffer from acute undernutrition, rising incomes and urbanization are quickly changing food consumption patterns away from cereals towards high-value foods like fish and meat. As a result, total demand for foodgrains is projected to increase due to population growth and indirect demand from animal feed. Eradicating hunger and malnutrition is critical for improving overall development, since healthy people contribute more to the economy through higher productivity and efficiency. The UN's post-2015 sustainable development agenda aims to end all forms of hunger and malnutrition by 2030. To do so, the interconnected issues of water, food and livelihoods must be addressed together. Food security involves not just food distribution but also production, people's livelihoods, and overall food system management. India's National Food Security Act (NFSA) 2013 aims to provide 75% of rural and 50% of urban populations with subsidized foodgrains under the targeted public distribution system.

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 Keywords

Food security, Malnutrition, Public Distribution System (PDS).

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The ongoing paper tries to find the story techniques used by M. K. Gandhi in his self-depicting account named "An Assortment of diaries or The Story of My Assessments with Truth". Gandhi's life story was first formed without assistance from any other person in a surprisingly long time essential language viz. Gujarati and appropriated in the serialized structure in Navajivan and Young India from the completion of 1925 to February 1929. The series appeared in book structure in English in two volumes, the first in 1927 and the second in 1929. Since its dissemination, Gandhi's own set of experiences has been potentially of the most well known book across the world. It has been changed over into more than fifty tongues. Even more inquisitively, different translations of this book have appeared in a comparative language. Taking into account this, the ongoing paper endeavors to address the extraordinary commonness of this book as well as the colossal effect it has on the peruser. The ongoing expert is of the view that self-depiction was one of the critical academic designs that was used in the early phase of the improvement of Indian English Composition and as an imaginative story Gandhi's own set of experiences has contributed uncommonly to the Indian English composition. Also, even in the time of media narratives and self-depictions, Gandhi's story stands separated in view of its original record strategies.

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 Keywords

Life account, Imaginative Story, Record Procedures,

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Abstract Deep learning-based weed crop for farmers represent an innovative application of artificial intelligence in agriculture. These drones are designed to identify and pluck weed from plants with precision and efficiency, reducing labor costs and improving productivity. Automation in the agricultural industry moderates the usage of resources and can increase the quality of food in the post-pandemic world. Agricultural robots have been developed for crop seeding, monitoring, weed control, pest management and harvesting. Physical counting of fruitless, flowers or fruits at various phases of growth is labor intensive as well as an expensive procedure for crop yield estimation. Remote sensing technologies offer accuracy and reliability in crop yield prediction and estimation. The automation in image analysis with computer vision and deep learning models provides precise field and yield maps. In this review, it has been observed that the application of deep learning techniques has provided a better accuracy for smart farming. As the demand for pollution-free and organic agricultural products rises, there is a pressing need for innovative solutions. The emergence of smart agricultural equipment, including intelligent robots, unmanned aerial vehicles and satellite technology, proves to be pivotal in addressing weed-related challenges. The effectiveness of smart agricultural equipment, however, things on accurate detection, a task influenced by various factors, like growth stages, environmental conditions and shading. To achieve precise crop identification, it is essential to employ suitable sensors and optimized algorithms. Deep learning plays a crucial role in enhancing weed recognition accuracy. This advancement enables targeted actions such as minimal pesticide spraying or precise laser excision of weeds, effectively reducing the overall cost of agricultural production. Keyword Deep Learning, Data Collection: Model Training: Semantic Segmentation Robotics and Drones: Spraying Mechanism, Edge Computing.

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Keywords: Deep Learning, Weed Detection, Crop Classification, Smart Agriculture, Convolution Neural Networks (CNN), Image Processing, Precision Farming

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Communication involves conveying thoughts and ideas to others through speech and facial expressions. It is a vital aspect of human life, facilitating interaction with the world. However, for individuals with hearing impairments, communication can be challenging without the aid of devices like battery-operated hearing aids, hand signals, and facial expressions. In this project, an Audio-Visual Speech Recognition (AVSR) system is introduced, leveraging image-processing capabilities in lip-reading to support speech recognition systems. This approach integrates both audio and visual processing, meaning that separate video and audio recognition processes are combined. Our project utilizes a Kannada audio database--a Dravidian language spoken by over 60 million people in Karnataka--to assist those with hearing impairments. The proposed AVSR model comprises three main components: (a) an audio feature extraction mechanism, (b) a visual feature extraction mechanism, and (c) an audio and visual feature integration mechanism. The integration mechanism merges the outputs from both the audio and visual extraction processes to produce final classification results. In this work, the audio feature mechanism is designed using Mel-frequency Cepstral Coefficients (MFCC) and a Random Forest system, while the visual feature mechanism is developed using Haar-Cascade Detection with MATLAB and a Feedforward Neural Network system. These extracted features are then integrated using a hybrid model that includes both Random Forest and Artificial Neural Network (ANN) techniques. The system's performance, in terms of speech recognition accuracy and robustness, was tested using speech data in a clean environment. On average, the final audio recognition rate is 88%, the visual recognition rate is 57%, and the integrated system achieves an overall recognition rate of 86%.

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 Keywords

Hybrid Model, Random Forest, AVSR, Feature Extraction, Lip Localization, Word Recognition.

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Sharan Kumar Limbale's novel Outcaste vividly portrays the psychological, social, and economic facets of caste-based prejudice in India by exposing the exploitation of Dalits. The Dalit community is impacted by the book's portrayal of systemic oppression. The article examines the protagonist's experiences using caste exploitation as a lens, and it also looks at broader implications for understanding the challenges faced by oppressed groups and the role literature plays in fostering social change.

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 Keywords

Dalit Exploitation in Sharan Kumar Limbale's Outcaste

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