Big Data refers to extremely large datasets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It's characterized by its high volume, velocity, and variety (the "3 Vs"), and requires specific tools and methods for storage, processing, and analysis.
This article introduces cutting-edge deep learning techniques as a solution to combat evolving web-based attacks in the context of Industry 5.0. By merging human expertise and advanced models, the study proposes a comprehensive approach to fortify cybersecurity, ensuring a safer and more resilient future for transformative technologies.
Researchers demonstrated the use of heterogeneous machine learning (ML) classifiers and explainable artificial intelligence (XAI) techniques to predict strokes with high accuracy and transparency. The proposed model, utilizing a novel ensemble-stacking architecture, achieved exceptional performance in stroke prediction, with 96% precision, accuracy, and recall. The XAI techniques used in the study allowed for better understanding and interpretation of the model, paving the way for more efficient and personalized patient care in the future.
Researchers explore the game-changing capabilities of Google Earth Engine (GEE) in revolutionizing archaeological research. By bridging the gap between remotely sensed big data (RSBD) and archaeological analysis, GEE overcomes challenges related to data access, computational resources, and methodological awareness.
The integration of AIoT and digital twin technology in aquaculture holds the key to revolutionizing fish farming. By combining real-time data collection, cloud computing, and AI functionalities, intelligent fish farming systems enable remote monitoring, precise fish health assessment, optimized feeding strategies, and enhanced productivity. This integration presents significant implications for the industry, paving the way for sustainable practices and improved food security.
This article reviews the transformative impact of artificial intelligence (AI) techniques such as deep learning and machine learning in the field of superconductivity. From condition monitoring and design optimization to intelligent modeling and estimation, AI offers innovative solutions to overcome challenges, accelerate commercialization, and unlock new opportunities in the realm of superconducting technologies and materials.
This groundbreaking study explores the transformative potential of artificial intelligence, machine learning, deep learning, and big data in revolutionizing the field of superconductivity. The integration of these cutting-edge technologies promises to enhance the development, production, operation, fault identification, and condition monitoring of superconducting devices and systems.
Researchers delve into the intersection of artificial intelligence (AI) and music education, showcasing how AI-driven technologies such as intelligent instruments, music software, and online teaching platforms have revolutionized the learning experience. With the ability to personalize instruction, enhance collaboration, and support students with disabilities, AI in music education holds immense promise for the future of music learning and teaching.
The study demonstrates the use of text mining to identify emerging ML/AI technologies in the Korean semiconductor industry, enabling SMEs to establish an R&D roadmap and enhance competitiveness. Deep neural networks and AI technology applications in semiconductor R&D and manufacturing processes were found to be crucial, with potential for improved reasoning, learning abilities, and process optimization.
Study examines the implementation of ChatGPT, an AI chatbot, in sport management education. The findings suggest that ChatGPT can generate comprehensive and accurate responses to sport management inquiries, highlighting its potential to enhance teaching and learning in the field.
Manufacturing companies are embracing AI and IoT technologies to revolutionize their operations, achieve sustainability goals, and remain competitive. The implementation of smart configurations, such as digital twins, sensors, 5G networks, and advanced ML models, enables real-time monitoring, analysis, and optimization of production processes.
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