New technologies have always provided new opportunities for crime. In the past, the invention of cars led to a surge in criminal activities like bank robberies and theft. Today, computers and e-commerce have opened up a global, automated, and anonymous platform for criminals to operate, creating new

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Highly segmented detectors with millions to billions of readout channels require a practical approach for simulation and reconstruction. Implementing each channel separately is impractical, necessitating the use of virtual segmentation to define readouts for different detector components. Dependenci

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KGC Solutions, Inc., in partnership with CONSOL Energy, is digitally transforming the manual process of completing Pennsylvania State Inspection forms used in mining locations. This conversion aims to streamline data entry, ensure accuracy, and enhance compliance with state regulations. The selected

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Alessandro Ruggeri presents the collaboration between DUNE-Italia and Nu@FNAL Bologna group on event classification in sand using deep learning. The project involves applying machine learning to digitized STT data for event classification, with a focus on CNNs and processing workflows to extract pri

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This study focuses on utilizing deep learning techniques for time estimation in monolithic PET detectors using digitized readouts. The proposed detector design includes a polished LYSO reflector, 6 virtual DOI layers, and an 8x8 SiPM array. Simulation studies and dataset generation for training the

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The Caribbean Plants Digitization Project at New York Botanical Garden aims to image and catalog over 150,000 specimens from the Caribbean region. Through OCR and data parsing, the project focuses on curation, barcoding, cataloging, and imaging of specimens. Expeditions since 1895 have contributed t

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Andy White from the University of Texas at Arlington presented on the application of Large-Scale Gas Electron Multiplier (GEM) technology to digital hadron calorimetry at the SiD Workshop in SLAC 2012. The study focuses on developing precision calorimetry for future accelerators using Double GEM lay

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In this study by Jennifer Stevenson, a supervised machine learning approach is proposed for arrangement and description in archives, specifically focusing on the DTRIAC collection which contains a vast amount of historical documents related to nuclear technology. The aim is to expedite the catalogin

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Explore how the U.S. Census Bureau utilized custom Optical Character Recognition algorithms to automate name capture from digitized images of decennial census forms. The project aimed to enhance longitudinal research by efficiently collecting and processing high-quality data, showcasing the benefits

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