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(anterovium/Shutterstock) The ability to harness, process, and leverage vast amounts of data sets leading organizations apart in today’s data-driven landscape. To stay ahead, enterprises must master the complexities of artificial intelligence (AI) data pipelines. The use of data analytics, BI applications, and data warehouses for structured data is a mature industry, and the strategies to extract value from structured data are well known. However, the emerging explosion of generative AI now holds the promise of extracting hidden value from unstructured data as well. Enterprise data often resides in disparate silos, each with its own structure, format, and access protocols. Integrating…

arXiv:2407.14631v1 Announce Type: new Abstract: Breast cancer is not preventable because of its unknown causes. However, its early diagnosis increases patients' recovery chances. Machine learning (ML) can be utilized to improve treatment outcomes in healthcare operations while diminishing costs and time. In this research, we suggest two novel feature selection (FS) methods based upon an imperialist competitive algorithm (ICA) and a bat algorithm (BA) and their combination with ML algorithms. This study aims to enhance diagnostic models' efficiency and present a comprehensive analysis to help clinical physicians make much more precise and reliable decisions than before. K-nearest neighbors, support vector…

arXiv:2407.14649v1 Announce Type: new Abstract: Industry 4.0 introduced AI as a transformative solution for modernizing manufacturing processes. Its successor, Industry 5.0, envisions humans as collaborators and experts guiding these AI-driven manufacturing solutions. Developing these techniques necessitates algorithms capable of safe, real-time identification of human positions in a scene, particularly their hands, during collaborative assembly. Although substantial efforts have curated datasets for hand segmentation, most focus on residential or commercial domains. Existing datasets targeting industrial settings predominantly rely on synthetic data, which we demonstrate does not effectively transfer to real-world operations. Moreover, these datasets lack uncertainty estimations critical for safe collaboration.…