Volume 13 | Issue 4 |

 Abstract

The agricultural sector is the backbone of our economy, providing food, clothing, shelter, and employment opportunities to the people, as well as a significant source of income to the state. Karnataka state is a predominantly agriculture-oriented economy where nearly 65% of the population follows agriculture and allied activities as their major occupation. In this context, agricultural sector development always depends on governmental effort to extend supportive policies and programs; simultaneously, farmers' active participation assists in achieving targeted goals for development is an essential precondition required.But while delivering governmental services through electronic means, we face many issues and challenges from different perspectives, which hinder the effective implementation of E-governance in the farming sector. In this context, this paper focuses on the E-governance initiatives of the Karnataka government for agricultural sector development and also issues and challenges faced while delivering E-governance in the agrarian sector. The paper also analyses remedial measures to be undertaken for the successful E-projects to be effectively implemented and sustained for a longer time.

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 Keywords

E-governance initiatives, Agricultural development, issues and challenges

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The study mostly focuses on the use of machine learning techniques to find fraudulent behavior in financial facts. This is the main challenge in the financial sector, where it is important to recognize and prevent fraud. Images are hyperparameters of tuning class as a method for increasing fraud detection. These settings improve fraud detection system by helping the version of the extra precisely distinguish between real and fraudulent transactions. The work deliberately uses three machine learning techniques: XGBoost, LightGBM, and CatBoost. Every method has sure advantages; their combined use seeks to improve the general fraud detection method performance. The research includes deep learning algorithms to adapt to hyperparameters. This connection improves the effectiveness and adaptability of fraud detection systems, and increases the efficiency of identifying modified fraud strategies. The effort employs actual data to conduct comprehensive analyses. The findings indicate that Lightgbm and XGBOOST outperformed the contemporary method when assessing numerous factors. This suggests that, among other strategies, the suggested one is more a success in spotting fraudulent behaviour. It incorporates a Stacking Classifier, which combines with precise parameters Random forest and LightGBM classifier predictions. Through using the strengths of numerous models, this ensemble technique improves prediction accuracy by means of a GradientBoostingClassifier as the final estimator.

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 Keywords

Bayesian optimization, data mining, deep learning, ensemble learning, hyper parameter, unbalanced data, machine learning".

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Creative Commons Attribution 4.0 and The Open Definition

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Data Science plays a crucial role in Business Analytics by enabling data-driven decision-making through statistical analysis, machine learning, and predictive modeling. Businesses leverage data science techniques to identify trends, optimize operations, enhance customer experiences, and gain competitive advantages. This paper explores the integration of data science in business analytics, covering key concepts such as data collection, preprocessing, exploratory data analysis, and advanced predictive modeling. Real-world applications in marketing, finance, supply chain, and customer insights demonstrate how businesses harness data science to drive strategic growth and efficiency. The study also highlights challenges such as data quality, security, and ethical considerations in business analytics.

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 Keywords

- Data Science, Business Analytics, Data-Driven Decision-Making, Statistical Analysis, Machine Learning, Predictive Modeling, Data Collection.

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Women have an important place in social and family life, without them a family or society cannot be imagined. Their contribution to family and society is incomparable. Women are the guides of society and family, the audience of the success of the young generation, the guide of the family. Women have always had an inventive mind. But with time the mind stopped thinking like this, now they have to start this inventive thought again and show the path to the society created by them. Only then will equality come in society. Nari Shakti Bandhan Act is an important legal step for the empowerment of Indian women. Through this, women get assurance of protection of their rights and freedom. However, for this Act to be completely successful, there is a need to change the thinking towards women in the society. Women can be empowered through awareness, education, and legal protection, so that they can live freely and with respect in the society

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Bharteey samaj me mahila sashktikaran yew sarkari prayash

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This paper explores the lived experiences of a transgender individual in kerala, India within the broader context of the LGBTQ movement. This paper delves into the life of Deepu, a transman from kerala, to shed light on the personal and social challenges faced by transgender individuals. Based on an in-depth interview , Deepu's story is presented as a reflective narrative that highlights his journey through gender identity, social stigma, family dynamics and personal resilience. The paper also focuses on the transgender rights and the initiatives undertaken by the government of kerala such as the 2015 Transgender policy to promote transgender welfare and inclusion.

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 Keywords

Transgender- transman- social stigma- queer- LGBTQ

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Creative Commons Attribution 4.0 and The Open Definition

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Wireless Sensor Networks (WSNs) are utilized in a variety of applications, including environmental monitoring, disaster management, and smart cities. In these networks, a collection of sensor nodes gathers and transmits data to a central unit for analysis. However, one of the main challenges in WSNs is achieving energy efficiency. Since sensor nodes are usually battery-powered, energy depletion directly impacts the network's lifespan and performance. Traditional data collection methods often lead to premature energy exhaustion of nodes located near the base station due to the heavy communication load. This creates a bottleneck that limits the scalability of the network. To tackle this problem, this project proposes an optimized energy-efficient path-planning strategy that employs multiple mobile sinks to distribute the data collection load more evenly across the network. In this strategy, mobile sinks move throughout the network to collect data from sensor nodes, which reduces the distance that the nodes need to transmit data. This effectively minimizes energy consumption. The project focuses on developing an optimal path-planning algorithm that ensures each mobile sink follows an efficient route to maximize data collection while minimizing redundant movements and energy usage. Simulation results indicate that the proposed approach significantly reduces energy consumption, enhances network longevity, and balances the load across the network when compared to traditional stationary sink methods.

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 Keywords

Wireless Sensor Network, Network Simulation 2, Internet of Things, Mobile Ad Hoc Networks

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Creative Commons Attribution 4.0 and The Open Definition

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Bhartiya Dak Pranali ki Etihashik Vivechana

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Bhartiya Dak Pranali ki Etihashik Vivechana

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Sewage treatment plants are vital infrastructures that safeguard public health and protect the environment by treating and purifying wastewater. The design of these plants plays a crucial role in ensuring efficient and effective treatment processes. This research paper focuses on the design principles and considerations for sewage treatment plants and explores various methods for improving existing facilities. By implementing innovative design strategies and adopting optimization techniques, wastewater treatment plants can enhance their performance, increase treatment capacity, and achieve higher levels of environmental sustainability.

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Sewage treatment plant, wastewater, design principles, optimization, environmental sustainability.

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Mental health disorders, particularly depression, are on the rise due to factors like excessive social media use, stress, and unhealthy lifestyle habits. To tackle this issue, we've developed a groundbreaking system that combines artificial intelligence, natural language processing, and personalized insights to provide real-time mental wellness support. Our Deep Learning-Powered Holistic Mental Health and Wellness Analyzer is designed to assess user mood, detect depression symptoms, and offer tailored recommendations. Using advanced sentiment analysis and emotional intelligence, our system achieves an impressive 98.9% accuracy in depression detection. But that's not all. Our platform also includes a personalized nutrition module that explores the link between diet and mental well-being, as well as Fit-Harmony music therapy, which creates customized playlists to promote relaxation and balance. With accuracy rates of 78.5% in mood-based music recommendations and 82.3% in dietary suggestions, our system provides users with a comprehensive and supportive mental health journey. By harnessing the power of machine learning, predictive analytics, and real-time monitoring, our platform offers an interactive and user-friendly mental health tracking experience.

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 Keywords

Deep Learning, Mental Health Analysis, Depression Detection, Sentiment Analysis, Natural Language Processing (NLP), Recurrent Neural Network (RNN), Two-State LSTM (TS-LSTM), Support Vector Machine (SVM), Emotion Classification, Personalized Mental Health Recommendations, Fit-Harmony Music Therapy, Personalized Nutrition Insights, Machine Learning in Healthcare, Mental Wellness Companion, Healthcare Data Analysis.

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Low back pain is a significant and common public health issue. Low back pain (LBP) is a public health issue that has reached epidemic proportion. Most of patients suffering from back pain practice yoga. Astang yoga comprised of eight limbs Yama (rule of moral conduct),Niyama(rule of personal conduct),Asana(postures),Breath control(pranayama),Pratyahara(sense withdrawal),Dharma(concentration),Dhyana(meditation)and Samadhi(self-realization).out of many style of yoga, Iyenger Yoga has applied yoga pose emphasis on precise structural alignment and has a good result in low back pain.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Back pain; Yoga; Stiffness and Pain

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Creative Commons Attribution 4.0 and The Open Definition