Volume 13 | Issue 4 |

 Abstract

ABSTRACT: This paper attempts to study the implementation of Artificial intelligence in Hotel management & Hospitality sector. The purpose of this study is to know about the need and the impact of Artificial Intelligence in Hotel management sector in India.To know about customer satisfaction towards the service & its quality in hotels, to knowhow it is served & in what time and accordingly implementation of AI in the hotel management sector in India. Only 1% hotelsare using AI in India. The paper focuses on the future use of AI in Indian hotels. The use of AI in hotel management sector, proves to be a game changer.The main aim of the study is to find out the ways of implementation of AI in hotel industry in India. For that the researcher proposed a

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KEYWORDS: Artificial Intelligence, Hospitality, Hotel Management, Human Computer Interaction (HCI), Virtual Assis

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Creative Commons Attribution 4.0 and The Open Definition

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This paper focuses on the impact and the complexities arising out of the intersection between social media and the right of free speech and expression in India. It examines and explores the challenges posed to the constitutional provisions by the rise of social media, legal limitations and the role of judiciary in protecting the freedom of expression in today's era of digital advancements. Secondary method of research has been implemented to collect data from books, case laws, scholarly works, statutes to analyse the harmony between the freedom of speech and the legislative and regulatory framework in place. This paper also delves into the need of judicial oversight in today's digital era and its role in safeguarding the freedom of speech.

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Free speech, social media, digital era

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Creative Commons Attribution 4.0 and The Open Definition

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The system is a research project on developing a Visual Inquiry (VI) system utilizing deep learning for visual comprehension and Natural Language Processing (NLP) for making context-based replies. VI systems are intended to understand and respond to visual content questions to deliver natural-style cognition and interaction. The system leverages Convolutional Neural Networks (CNNs) to obtain the visual features of the images to obtain salient facts like objects, scenes, and spatial relationships. They are then merged with NLP models that detect the input question in an attempt to display a compound presentation of text and image knowledge.Worthy of mention here are the use of state-of-the-art models such as attention mechanisms and Transformer models to project the image features onto the semantic features of the question. Attention layers enable the model to attend to the correct location in the image and enhance the accuracy of response generation. VI system is trained on vast amounts of data, for example, the VI v2 or Visual Genome dataset, with labeled images, questions, and answers.With the addition of vision and language processing, this VI system is able to answer appropriately to various types of questions, ranging from object recognition to more abstract reasoning questions.

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 Keywords

Convolution Neural Networks(CNN), Vision Transaction, Image segmentation, Large Language Models(LLms), Transformer Architecture (BERT,GPT,T5), Question Answering Systems, Named Entity Recognition

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Underwater imaging often faces challenges such as reduced visibility, poor contrast, and color distortions due to light absorption and scattering in water. This project presents a novel approach to underwater image enhancement using a UNet convolutional neural network. The model was trained on a publicly available dataset of underwater images and their enhanced versions. Through its encoder-decoder structure, the U-Net model effectively improves clarity, contrast, and color fidelity. The solution includes preprocessing data, building and training the model, and developing a web application for user interaction. The application, with a Flask backend and a user-friendly frontend, allows users to upload underwater images and view enhanced outputs. By combining deep learning with accessibility, this project offers a practical tool for improving underwater image quality, catering to diverse audiences and applications.

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Image Enhancement, Convolutional Neural Networks, Underwater image processing, Deep Neural Network, Machine Learning.

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As libraries embrace advanced technologies to enhance efficiency and user experience, this project presents a Library Management System integrating Radio-Frequency Identification (RFID) and Internet of Things (IoT). This system modernizes library operations by enabling seamless book borrowing and returning through RFID-enabled student identity cards and book tags. When a student places their card near an RFID reader, the system instantly verifies their identity, ensuring fast, secure, and error-free transactions. Beyond automation, the system incorporates real-time tracking of books within library racks, minimizing misplaced or lost items. Additionally, automated notifications remind students of due dates and alert them about overdue books, promoting timely returns. Designed for efficiency at minimal cost, this system optimizes library management, enhances security, and offers a more organized and user-friendly experience.

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Library Management System, RFID, IoT, Real-Time Tracking, Automated Notifications, Book Borrowing and Returning, Student Identity Verification, Misplaced Book Detection, Smart Library, Low-Cost Automation.

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With the rapid pace of urbanization and industrial growth, noise pollution has become an inevitable by-product of modern development. This escalating issue is now a major concern for industrial corporations, businesses, and urban planners, affecting both productivity and quality of life. Noise mapping involves analysing and categorizing urban areas based on noise levels to assess and manage noise pollution. In this study, noise levels were surveyed at seven key locations in Nashik city using a noise level meter. The collected data was utilized to develop GIS-based noise maps, which were subsequently compared with the permissible noise levels outlined by the Central Pollution Control Board (CPCB), New Delhi. The findings revealed significant exceedances of permissible noise limits in several zones, underscoring the urgent need for targeted noise mitigation measures. These insights provide a critical foundation for local authorities to implement effective noise reduction strategies and inform urban planning initiatives aimed at minimizing the adverse impacts of noise pollution on public health and quality of life.

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Road traffic noise, urban intersection, noise map, GIS

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Neuromarketing refers to the confluence of neuroscience and marketing. It is concerned with understanding how marketing strategies are designed to elicit consumer purchases. It has now extended to the financial domain, where it is crucial in determining how investment decisions are made. investors are swayed by emotions, branding, and psychological aspects more than reasoning. Interdisciplinary research demonstrates that emotions such as fear, enthusiasm, and trust have a significant influence on investment decisions in stocks, mutual funds, and other financial instruments. Financial marketers employ neuromarketing through enticing promotional and branding campaigns. Investors are unknowingly influenced by subconscious stimuli which causes them to engage in irrational, emotional, or overly cautious investing. This paper builds on past research and behavioural finance studies to discuss the role of neuromarketing in changing investor behaviour. Grasping these matters allows financial firms to better structure their marketing and enables investors to use reasoning while making investment decisions.

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Neuromarketing, Investment Decisions, Investor Behaviour, Emotional Biases, Behavioural Finance, Financial Neuroscience.

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Career decision-making plays a crucial role in shaping students' futures, yet many struggle due to lack of structured guidance and awareness of their strengths. This paper presents an AI-powered Career Assistance Platform, a web-based system designed to recommend personalized job roles based on students' academic performance and personality traits. The platform employs Support Vector Machine (SVM) algorithms to classify inputs and suggest relevant career paths. It is developed using PHP and Flask, with a secure backend for data management. The system was tested using real and sample input data and achieved a prediction accuracy of over 95%, validating its effectiveness in career role classification. The platform aims to bridge the gap between education and employment by offering reliable, accessible, and intelligent career guidance.

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Career Prediction, Machine Learning, SVM, Web Development, Career Guidance, PHP, Flask

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The importance of Indian libraries to the country's knowledge system and their important role in its preservation shall be the main topics of this essay. With the goal of encouraging multidisciplinary research via preservation and dissemination, the 2020 education strategy has placed a strong emphasis on the Indian knowledge system. The Indian Knowledge System (IKS) is a priceless cultural legacy that offers insightful information and environmentally friendly methods. However, traditional knowledge is seriously threatened at a time of fast technological development, cultural uniformity, and globalization. With a rich history spanning thousands of years, the Indian knowledge system covers a broad range of topics, such as mathematics, astronomy, philosophy, medicine, and more. Libraries are essential for maintaining, sharing, and expanding this information. Ancient Indian libraries housed literary works, scientific papers, philosophical treatises, and holy writings. Libraries were centers for talks, debates, and intellectual interaction in addition to being locations to store books. The preservation of information, manuscripts, artifacts, and historical items is the duty of libraries that function as administrators. An extensive review of the state of the art in traditional knowledge preservation is given in this study.

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Indian Knowledge System (IKS), Knowledge Preservation, National Mission for Manuscript (NMM), National Digital Library of India (NDLI), and Traditional Knowledge Digital Library (TKDL), Libraries; New Education Policy etc.

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Tablets and capsules are prone to dysphagia, leading to non-compliance and inefficient therapy. To avoid difficulties associated with conventional Mouth dissolving tablets are the preferred dosage form for paediatrics, geriatrics, and traveling patients due to its hardness, consistent dose, and ease of administration. The MDTs were designed to have high hardness, integrity, and rapid disintegration without water. Fast dissolving Tablets dissolve easily in saliva, eliminating the need for water. Fast-dissolving pills dissolve quickly in saliva, taking only a few seconds. Fast-disintegrating tablets contain chemicals that speed up tablet disintegration in the oral cavity, taking up to a minute to fully dissolve. This tablet type allows for oral delivery of a substantial dose without the need for water. Tablets dissolve quickly in saliva, typically within 60 seconds.

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Mouth dissolving tablet, Disintegration, Patented technologies, Marketed MDTs

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Creative Commons Attribution 4.0 and The Open Definition