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 review explores the applications of artificial intelligence (AI) in studying fishing fleet (FV) behavior, emphasizing the role of AI in monitoring and managing fisheries. The paper discusses data sources for FV behavior research, AI techniques used in monitoring FV behavior, and the uses of AI in identifying vessel types, forecasting fishery resources, and analyzing fishing density.
Researchers have harnessed the power of Vision Transformers (ViT) to revolutionize fashion image classification and recommendation systems. Their ViT-based models outperformed CNN and pre-trained models, achieving impressive accuracy in classifying fashion images and providing efficient and accurate recommendations, showcasing the potential of ViTs in the fashion industry.
In a groundbreaking study, AI-driven data analysis accurately predicts Greco-Roman wrestlers' competitive success, with just an 11% error rate. This research has the potential to revolutionize athlete selection and training in various sports, offering valuable insights for coaches and athletes alike.
Researchers conducted a comprehensive bibliometric exploration of non-destructive testing techniques for assessing fruit quality. Leveraging Web of Science data, they unveiled evolving research trends, hotspots, and the promising integration of advanced technologies like machine vision and deep learning, offering valuable insights for the fruit industry's competitiveness and quality assurance.
Researchers introduce the "general theory of data, artificial intelligence, and governance," offering fresh insights into the complexities of the data economy and its implications for digital governance. Their model, which incorporates data flows, knowledge concentration, and data sharing, provides a foundation for addressing the challenges of data capitalism and shaping equitable and innovative data policies in the digital age.
Researchers have successfully employed the MegaDetector open-source object detection model to automate cross-regional wildlife and visitor monitoring using camera traps. This innovation not only accelerates data processing but also ensures accurate and privacy-compliant monitoring of wildlife-human interactions.
Researchers use artificial neural networks (ANN) to classify UNESCO World Heritage Sites (WHS) and evaluate the impact of input variables on classification outcomes. The study compares multilayer perceptron (MLP) and radial basis function (RBF) neural networks, highlighting the significance of feature selection and the trade-off between evaluation time and accuracy.
This paper explores how the fusion of big data and artificial intelligence (AI) is reshaping product design in response to heightened consumer preferences for customized experiences. The study highlights how these innovative methods are breaking traditional design constraints, providing insights into user preferences, and fostering automation and intelligence in the design process, ultimately driving more competitive and intelligent product innovations.
Researchers delve into AI's role in carbon reduction in buildings, discussing energy prediction, ML-driven emission mitigation, and carbon accounting. The paper underscores urgent emission reduction in construction, highlighting ML's potential to drive sustainable practices, with a focus on AI's positive impact on the low-carbon building sector.
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.
Terms
While we only use edited and approved content for Azthena
answers, it may on occasions provide incorrect responses.
Please confirm any data provided with the related suppliers or
authors. We do not provide medical advice, if you search for
medical information you must always consult a medical
professional before acting on any information provided.
Your questions, but not your email details will be shared with
OpenAI and retained for 30 days in accordance with their
privacy principles.
Please do not ask questions that use sensitive or confidential
information.
Read the full Terms & Conditions.