Volume 13 | Issue 4 |

 Abstract

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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Employees Perception, Human Resource Practices, Work Satisfaction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

automatic, detection, window.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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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Creative Commons Attribution 4.0 and The Open Definition