A Metaverse: Significance and Dimensions in Various Sectors

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Год журнала: 2024, Номер unknown, С. 1781 - 1786

Опубликована: Фев. 28, 2024

The term "metaverse" is being spoken around often in the IT sector. Investments, startups constructing components, new platform announcements, and major corporations joining this realm of digital interaction are constantly news. There a great deal momentum towards nearly natural 3D virtual environment, clarion cry may have led to Facebook renaming as Meta, which be recognized watershed point development Metaverse. One can work, play, socialize Metaverse at any time, from location, using whatever device you want. Users engage real-time interactions by merging physical, augmented, realities. It game-changer connection, with boundless, unrealized potential enormous commercial prospects. In chapter, researchers explore meaning metaverse, its use different fields, advantages. This chapter assist people organizations better preparing themselves for possibilities difficulties that today's state-of-the-art technology brings.

Язык: Английский

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Bidirectional attentional mechanism for Arabic chatbot

International Journal of Information Technology, Год журнала: 2024, Номер 16(5), С. 3109 - 3120

Опубликована: Март 29, 2024

Язык: Английский

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A comprehensive framework for secure keyword search in cloud databases through hybrid attribute-based encryption (HABE)

International Journal of Information Technology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 8, 2025

Язык: Английский

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CMedRAGBot: A Chinese Medical Chatbot Based on Graph RAG and Large Language Models

Interdisciplinary Sciences Computational Life Sciences, Год журнала: 2025, Номер unknown

Опубликована: Июнь 5, 2025

Язык: Английский

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Exploring Video Event Classification: Leveraging Two-Stage Neural Networks and Customized CNN Models with UCF-101 and CCV Datasets

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Год журнала: 2024, Номер unknown, С. 100 - 105

Опубликована: Фев. 28, 2024

Rapid technological advances have significantly improved our ability to analyse video data. This comprehensive review examines machine learning (ML) models applied event detection and classification, including CNNs, deep neural networks (DNNs), RNNs. When evaluated on benchmark datasets for accuracy, these approaches demonstrate their relative strengths weaknesses. Researchers encountered numerous challenges in detection, which are addressed throughout the review. However, achieving high precision remains challenging due diverse types, quality issues, model over fitting risks, lack of large labeled training datasets. Background scenes, lighting, object occlusion further complicate accurate identification. As computational power grow, stands gain significantly. assessed action recognition trained UCF-101 CCV databases. On CCV, a 2-stage network achieved 75% accuracy; while multi-stream (DL) system obtained 77.5%. For larger UCF101, 2-stream RNN architectures realized 92% 89% accuracy using video-level prediction.

Язык: Английский

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Intent Recognition Leveraging XLM-RoBERTa for Effective NLU

Опубликована: Июнь 5, 2024

Язык: Английский

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Improve Accuracy in Healthcare Data Analysis using Competitive Ensemble Deep Learning Model

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Год журнала: 2024, Номер unknown, С. 1792 - 1797

Опубликована: Фев. 28, 2024

This paper discusses the significance of Machine Learning (ML) and Deep (DL) techniques for structured unstructured healthcare data. As data is increasing tremendously, it difficult to identify hidden patterns in huge amounts DL handles a massive amount clinical provides better outcomes. A novel competitive ensemble deep learning model has been proposed improve classification performance However, dealing with data, work highlights Twitter sentiment analysis. In addition, this Competitive Ensemble (CEPL) algorithm text The compared traditional evaluate model's range 0.2%-0.5%.

Язык: Английский

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Digital Twins: A Comprehensive Study on Models, Platforms, Applications and Challenges

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Год журнала: 2024, Номер unknown, С. 1072 - 1077

Опубликована: Фев. 28, 2024

Technological innovation has created "digital twins," which can replicate and synchronize digital physical things in (almost) real-time, assess situations from multiple perspectives, optimize objects by predicting how they will behave the future based on these analyses. This study delves deeply into Digital Twin technology, covering its origins as a game-changing link between real virtual. It explores diverse models, dissecting their functionalities predictive capacities. Through comparative lens, it evaluates prominent platforms Oracle Twin, ANSYS Builder, Siemens - examining features adaptability across industries. Extensive applications Manufacturing, Energy, Automotive, Logistics underscore technology's optimization potential operational enhancements. Lastly, discusses challenges perspectives for twin offering insight breakthroughs areas of exploration this rapidly evolving sector.

Язык: Английский

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Decrypting Secrets: Deep Learning for Unmasking Malicious Traffic

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Год журнала: 2024, Номер unknown

Опубликована: Фев. 28, 2024

Язык: Английский

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Predictive Modeling of Concrete Compressive Strength using Machine Learning Algorithms

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Год журнала: 2024, Номер unknown, С. 1225 - 1229

Опубликована: Фев. 28, 2024

The culture and modern-day society reflect their attributes with style of architecture. A particular holds value certain characteristics. In today's world, concrete is a common factor across nations cultures. It has proven to be fundamental component construction. so far become the most used man-made material. Concrete made by mixing aggregates like cement, water, sand, gravel, other strength-boosting materials, later hydration process that converts moldable mixture into solid. Statistical metrics such as mean absolute error, squared root square coefficient determination are test learning models. To create ensemble models, several techniques were examined used, including support vector regression, random forest, k-nearest neighbors. using 0.98, stacking-based regression neighbor final estimator beat models in study, bagging forest. Furthermore, web application was created trained machine for user-friendliness.

Язык: Английский

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