Volume 13 | Issue 4

 Abstract

The impact of coalition governments on the Indian political system, focusing on their evolution since the 1990s. The rise of coalition politics marked a significant shift from single-party dominance to a more fragmented and pluralistic governance model. The study examines how coalitions have influenced policy-making, political stability, federal relations, and democratic representation. While coalition governments have enhanced inclusivity and regional representation, they have also led to compromises in governance and frequent political realignments. Overall, the analysis highlights the complex role coalition politics play in shaping India's democratic and administrative landscape.

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 Keywords

Coalition Government, India, 1990s, political stability, policy-making, federalism, regional representation, inclusivity, governance challenges, party alliances, democratic evolution.

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Attention Deficit Hyperactivity Disorder (ADHD) is the most common neurological disorder of childhood. In this growing era of competition children suffering with ADHD find it difficult to cope up and even for parents and teachers to exactly determine the distinguishing factor for the children. Ayurveda is found to be the world's oldest and most complete holistic healing modality. So, this article deals with the general knowledge about ADHD and an Ayurveda approach towards its causes, pathophysiology and treatment which include the basic treatment of Manas Roga Chikitsa i.e Daiva-Vyapashraya Chikitsa, Satvajay Chiktisa and Aushada Chikitsa

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Manas Roga Chikitsa, Daiva-Vyapashraya Chikitsa, Satvajay Chiktisa. behavioral, neurological hyperactive disorders

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Credit card fraud has become a significant threat in the financial sector, with substantial economic implications. The increasing reliance on digital payment systems necessitates the development of advanced techniques for detecting fraudulent activities. Machine learning (ML) has emerged as a powerful tool for identifying and preventing fraudulent transactions by learning from historical data and recognizing suspicious patterns. This paper explores the application of various ML algorithms for credit card fraud detection. We evaluate techniques such as Logistic Regression, Decision Trees, Random Forest, Support Vector Machines, and Neural Networks using a public dataset. Our study emphasizes the importance of data preprocessing, handling imbalanced datasets, and selecting appropriate evaluation metrics. The results demonstrate that ensemble methods, particularly Random Forest, provide high accuracy and robustness in detecting fraud. Future research directions are also suggested, focusing on real-time fraud detection and adaptive learning systems.

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 Keywords

Credit Card Fraud, Machine Learning, Classification, Imbalanced Data, Random Forest

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The 2019-2020 Hong Kong protests marked a pivotal moment in the city's political landscape, originating from opposition to a proposed extradition bill and evolving into a broader pro-democracy movement. This essay critically examines the role of media in shaping narratives around the protests, focusing particularly on how coverage influenced public perception and international discourse. Through a metaphor analysis of selected media reports, the paper explores the rhetorical strategies and linguistic choices employed by various outlets across different regions. By drawing on media theory and political communication frameworks, the study highlights the media's capacity to both amplify and polarize social movements. It also considers how the portrayal of protestors and law enforcement impacted the dynamics of the conflict. Ultimately, the essay aims to unpack the intersection between media, language, and power during one of Hong Kong's most turbulent periods in recent history.

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Hong Kong Protests, Media Representation, Metaphor Analysis, Political Communication, Police Brutality

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Introduction: Hypothyroidism is a prevalent condition affecting individuals of both sexes mostly females , Significantly impacting quality of life. Homoeopathy based on the principle of individualization, offers a unique therapeutic approach to managing this condition. Objectives: This study aims to evaluate the effect of homoeopathic medicine in management of hypothyroidism . Methods: A total 30 patients diagnosed with hypothyroidism to evaluate the effect of homoeopathic medicine in management of hypothyroidism as an add therapy in adult population a randomised control trial are treated with individualized homoeopathic remedies based on their presenting symptoms, mental general, and physical generals. The selection of remedies given according to detailed case - taking, repertorization, and systemic examination. The outcome were assessed based on symptomatic relief and overall improvement in well- being. Result: Out of 30 patients, Out of 30 patients, 23 showed significant improvement in their hypothyroid complaints. . The positive response in the majority of cases highlights the potential effectiveness of individualized homoeopathic treatment in Hypothyroidism management. Conclusion: This study suggest that individualized homoeopathic treatment plays a beneficial role in managing Hypothyroidism. However, further large - scale studies with randomized control trail are recommended to establish the efficacy and reproducibility of these findings.

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Hypothyroidism, Homoeopathic Individualized remedies, Standardized medicines, Randomized Control Trial

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In India, cultural norms often place a significant financial burden on families with daughters, particularly those living in poverty, where marriage expenses become a major obstacle. This economic pressure can unfortunately lead to child marriages. To address this issue, the Telangana government has initiated the Kalyana Laxmi scheme. The core objective of this scheme is to relieve poor families from the overwhelming financial strain of marrying off their daughters, thereby providing a safety net and reducing the incidence of child marriages. This research examines the Kalyana Lakshmi scheme, a Telangana government initiative providing financial assistance to brides from marginalized communities, focusing on its implementation and impact within Kamareddy district. The study aims to know the extent of awareness, evaluate the scheme's effectiveness in curbing child marriage, and addressing associated challenges. Findings indicate a high level of awareness regarding the scheme's eligibility criteria, with a significant impact on the postponement of marriages until legal age. The financial assistance primarily supports wedding expenses, demonstrating its immediate utility. However, the study identifies certain implementation challenges, related to documentation, which affected a substantial majority of respondents.

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Key words: Child marriage, Gender inequality, Legal age of marriage, financial assistance.

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This study examines the employee welfare measures and their impact on employee satisfaction and productivity at Ident Automation and Info Technologies .Employee welfare entails everything from services , facilities and benefits that are provided or done by the employer for the advantage or comfort of an employee. The Study aims to identify the existing welfare schemes, assess employee perceptions, and analyze the relationship between welfare measures and employee outcomes . We collected data from 120 respondents through structured questionnaires, utilizing a descriptive research methodology. The analysis employs tools such as chi-square, and one way anova to interpret employee welfare and the challenges they face. The Findings provide valuable recommendations for enhancing employee welfare and improving organizational performance.

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Employee welfare ,Employee Satisfaction, Productivity.

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Accurate and robust lane detection is a critical component of safe, stable autonomous driving systems that navigate vehicles efficiently. This work proposes an improved lane detection method by advanced image preprocessing and hybrid machine learning pipeline. The frame combines traditional computer vision approaches with deep literacy models to overcome issues related lighting conditions, occlusions, and road Inconsistencies. A large dataset has been used for training and testing the model to achieve better precision in accuracy and near- real-time performance. The experiments carried out demonstrate that our technique supersedes the baseline techniques in terms of accuracy, recall, and robustness. Some takeaways have been shared toward building scalable, adaptive lane detection systems in real-world driving scenarios.

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Autonomous Driving, Lane Detection, Prepro- cessing, Machine Learning, Deep Learning, Computer Vision, Real-time Systems

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Emojis have become an essential part of digital communication, influencing how sentiment is conveyed in online interactions. However, traditional sentiment analysis models often struggle to interpret emojis accurately due to their context dependent nature and cultural variations. This study explores the application of machine learning techniques to classify emoji sentiment, integrating deep learning models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and transformer-based architectures. Additionally, a multimodal approach is proposed, combining textual and visual features to enhance sentiment classification accuracy. The research evaluates model performance using precision, recall, F1-score, and accuracy metrics. Results indicate that transformer-based models and multimodal learning outperform conventional methods, offering a more nuanced understanding of emoji sentiment. By addressing contextual dependencies and cultural influences, this study contributes to the development of more advanced sentiment analysis systems, improving their effectiveness in social media monitoring, customer feedback analysis, and human-computer interaction.

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Emoji Sentiment Analysis, Machine Learning, Deep Learning, Sentiment Classification, Multimodal Learning, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Sentiment Classification.

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In today's digital world, the Internet plays a vital role in transforming shopping habits.Zepto is one of the leading Q-commerce platforms in India and it is also known for 10-minute delivery service in big cities. With the rise of online services, people now prefer purchasing groceries through digital platforms.The objective of this study is to identify the customer awareness and satisfaction levels of Zepto (Q-Commerce) in Coimbatore city. It highlights customer preferences, factors influencing usage, and suggests improvements to enhance service quality in emerging markets.

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 Keywords

Zepto, Online Shopping, Q-Commerce, Fast Delivery.

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This study examines the employee perception towards human resource pratices and work satisfaction in Spectra. As organizations recognize the strategic role of human resources initiatives becomes vital. This study aims to identity the existing human resource practices and work satisfaction of the employees. We collected data from 90 respondents through structured questionnaries, utilizing a descriptive research methodology. The analysis employs tools such as chi-square. and t-test to elucidate existing human resource practices and work satisfaction. The study concludes with recommendations to enhance human resources practices and work satisfaction and overall improving organizational performance.

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Employees Perception, Human Resource Practices, Work Satisfaction

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Penetration testing is essential for identifying system vulnerabilities, but it often requires multiple specialized tools, which can complicate the process. This paper proposes an integrated toolkit that combines key penetration testing functions--such as vulnerability scanning, exploitation, and network analysis--into a single platform. This integration streamlines the workflow, reduces errors, and enhances efficiency by eliminating the need to switch between different tools. We discuss the design, features, and potential challenges of this unified toolkit, aiming to simplify and accelerate the penetration testing process for cybersecurity professionals

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Security testing, Penetration testing, Cyber Security, Vulnerability Assessment, Penetration testing tool

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This research presents a new way to enhance smart home security by combining automated circuit control and NFC technology. A PN532 Reader Writer and a Raspberry Pi are used in the system's construction to control a servo motor for door access. Authentication uses symmetric encryption techniques to protect sensitive data by matching encrypted passwords saved on NFC tags with secure credentials controlled on a Flask server. In-depth evaluation confirmed the correctness and dependability of the system by showing a 100% success rate in correctly detecting and authorizing NFC cards. Rapid credential resets are facilitated by the system to mitigate any security threats such as theft or unauthorized access, guaranteeing ongoing protection. The system is further improved by an associated Android application that lets users keep an eye on access logs, add new users, and get real-time alerts when an unlock event occurs. This mobile interface improves user experience by facilitating smooth control over access management. The method provides a simple, effective way to regulate access while also strengthening the physical security of smart homes by combining NFC technology with cutting-edge encryption methods. By addressing major issues with automated, secure access systems, this study offers a workable and expandable solution for contemporary smart homes that advances IoT-based security while safeguarding data security, accessibility, and dependability.

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Smart Home Security, NFC Technology, Authentication, Encryption, IoT-based Security.

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Digital investment applications have revolutionized the way retail investors participate in financial markets. This study examines investor perception of the Groww app in Coimbatore, focusing on factors such as security, usability, awareness, and satisfaction. A descriptive research design was employed, collecting data from 141 respondents through structured questionnaires. Results reveal that while the app is widely appreciated for its ease of use and low-cost investments, concerns about fraud, lack of human guidance, and customer support persist. Suggestions include enhancing security features and providing personalized financial services to improve long-term engagement.

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Groww App, Digital Investment, Investor Perception, FinTech, Mobile Investment Apps

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 Abstract

By arguing that people are systematically conditioned into inflexible political, economic, and cultural frameworks but are inherently free from systemic dogma, freemism offers a radical rethinking of human ideological engagement. According to this thesis, traditional ideologies--from capitalism to communism--inevitably fall short because they stifle individual thought and are unable to change to meet the demands of a changing society. The work creates a "conditioning matrix" whereby media, education, and cultural norms enforce ideological compliance by analyzing historical instances of 20th-century ideological collapses (such as the Soviet purges, the 2008 financial crisis, and the fascist genocides) and philosophically criticizing conformity mechanisms. Freemism manifests as a dynamic approach to the construction of one's own belief system as well as a rejection of dogma. Its fundamental principles--complete ideological autonomy, ethical ephemeralism, and responsible anarchy--are presented as intentional paradoxes that avoid dogmatic recidivism rather than as contradictions. Three innovations are introduced in the study: 1) Fluid consensus protocols for collective action without permanent systems, 2) Metrics such as the Ideological Autonomy Index to measure societal freedom from dogma, and 3) A developmental model for ideological deconditioning employing Socratic self-inquiry and cognitive bias inoculation. A Freemist (one who follow freemism) is an individual who is free from all ideological boundaries and does not subscribe to any existing political, economic, or philosophical system such as Communism, Capitalism, Socialism, Anarchism, Fascism, or Centrism. Instead, a Freemist believes in and follows their own self-defined ideology, shaped by personal reasoning, experience, free will and independent thought. This work adds to political philosophy a self-correcting framework for post-ideological societies--one in which people transform from passive ideology consumers to active worldview architects--by redefining freedom as the ability to continuously rebuild belief systems rather than reject all structure.

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 Keywords

Political Science, Psychology, New Mindset, Free Will, Human Behavior and Nature, Ideology

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In urban and rural areas, unexpected rain can cause inconvenience, especially when windows are left open. This can lead to damage to interior furnishings, electronics, and other items. Conventional manual systems require human intervention to operate windows, which is not always feasible, especially when residents are away. An automatic rain detection window system provides a practical solution by sensing rain and actuating the windows to open or close as needed.

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automatic, detection, window.

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Semi-Automated Solar Grass Cutter is an innovative and eco-friendly solution for lawn maintenance, designed to operate semi-autonomously using solar energy. This project combines advanced technologies to develop a sustainable lawn mower, addressing challenges associated with traditional mowing methods, such as reliance on fossil fuels, high maintenance requirements, and labor-intensive operations. The system's main components include an Arduino Uno microcontroller, a motor driver, a BLDC motor for cutting, and a Bluetooth module for wireless control. Energy efficiency is achieved through solar panels that charge lithium-ion batteries, ensuring continuous operation without external power. Additionally, a Type-C charging setup, incorporating a charging module and step- down module, provides an emergency power source. Durable tires and a robust solar panel mounting system enhance its functionality as a compact, mobile unit. Historically, conventional lawn mowers have faced issues like greenhouse gas emissions and noise pollution due to internal combustion engines. This solar-powered alternative addresses these concerns by utilizing renewable energy. Its semi-automated control system, enabled by the Bluetooth module, allows users to steer and control the vehicle remotely via a mobile phone. This enhances flexibility, operational ease, and safety by allowing real-time maneuvering across various terrains without physical interaction.

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Solar energy, Solar panel, Lawn mower, Eco-friendly, Bluetooth module, Microcontroller

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Underwater species exploration using deep learning technology is designed to classify underwater species from images and retrieve key details such as their biological name, extinction status, and geographic origin. The system employs advanced convolutional neural networks (CNN) for accurate image classification. A well-organized dataset of underwater species is used to train, validate, and test the model, ensuring robustness. The project integrates a backend system with a REST API to connect the model and a database storing species information. A user-friendly frontend allows seamless image upload from system or image link and instant results display. Deployed on cloud platforms, the system ensures scalability and real-time accessibility. This project has significant applications in marine biology, conservation, and environmental monitoring. By automating species identification, it aids in studying biodiversity, tracking invasive species, and supporting ecosystem preservation efforts. The innovative approach minimizes manual effort, provides accurate results, and contributes to sustainable marine research.

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deep learning, image classification, Convolutional Neural Networks (CNN) dataset, training, validation, testing, REST API, backend, database, frontend, image upload, cloud deployment

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This study explores the awareness, preferences, and purchasing behavior of women in Coimbatore City toward the luxury fashion brand Prada, with a focus on sustainable fashion. The Indian luxury apparel sector is witnessing significant transformation due to evolving consumer tastes and growing affluence. This research, conducted through descriptive methodology and convenience sampling of 120 women, investigates the level of brand familiarity, perception of pricing, key influencing factors in luxury purchases, and the likelihood of product recommendation. Findings reveal that a majority of respondents are unfamiliar with the Prada brand, perceive its pricing as unrealistic, and are hesitant to purchase or recommend its products. However, brand reputation remains a major influencing factor in luxury product consideration. The study underscores the need for increased brand visibility, strategic pricing, and localized marketing efforts to enhance consumer engagement and market penetration in emerging urban regions like Coimbatore. The insights can aid Prada and similar luxury brands in tailoring their strategies to better resonate with the Indian middle-class and working professionals.

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Consumer Preference, Prada, Coimbatore, Luxury Fashion, Brand Awareness, Working women, House wife.

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This paper presents a mobile-based interior design solution using Augmented Reality (AR) to help users visualize furniture in their own space before making a purchase. The system is designed using Java, the Android SDK, Google's ARCore framework, and Firebase for backend support. It enables furniture owners to upload their furniture, which can then be viewed in real-time by customers through AR. Initially developed using Unity and ARCore for rapid prototyping, the system was later rebuilt with native Java for better Android integration and flexibility. This paper outlines the challenges in traditional interior design methods, the motivation for using AR, and the step-by-step development of an AR-based shopping interface for interior design. Our goal is to bridge the gap between imagination and reality by allowing users to digitally place and preview furniture in their real environment, improving decision-making and reducing product return rates.

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Augmented Reality (AR), Interior Designing, Unity Engine, ARCore, Java, Android SDK, Firebase, Real-Time Visualization, 3D Furniture Placement, Mobile AR Experience

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Creative Commons Attribution 4.0 and The Open Definition