This work aims at building a flexible data communication structure for a polymer processing machine by employing a publisher-subscriber based protocol called Message Queuing Telemetry Transport (MQTT), which is operated over TCP/IP. Even when using conventional equipment, processing data can be measured and recorded by various devices anywhere through an Internet communication. A message-based protocol allows flexible communication that overcomes the shortcomings of the existing server-client protocol. Multiple devices can subscribe to the processing data published by source devices. The proposed method facilitates data communication between multiple publishers and subscribers. This work has implemented a system that publishes data from the equipment and additional sensors to a message broker. The subscribers can monitor and store the process data relayed by the broker. The system has been deployed and run for a film extrusion line to demonstrate the effectiveness.
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http://dx.doi.org/10.3791/63717 | DOI Listing |
J Imaging Inform Med
January 2025
Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St., Philadelphia, PA, 19104, USA.
Integration of artificial intelligence (AI) into radiology practice can create opportunities to improve diagnostic accuracy, workflow efficiency, and patient outcomes. Integration demands the ability to seamlessly incorporate AI-derived measurements into radiology reports. Common data elements (CDEs) define standardized, interoperable units of information.
View Article and Find Full Text PDFJ Gen Intern Med
January 2025
Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
Background: Active surveillance (AS) is the guideline-recommended treatment for low-risk prostate cancer and involves routine provider visits, lab tests, imaging, and prostate biopsies. Despite good uptake, adherence to AS, in terms of receiving recommended follow-up testing and remaining on AS in the absence of evidence of cancer progression, remains challenging.
Objective: We sought to better understand urologist, primary care providers (PCPs), and patient experiences with AS care delivery to identify opportunities to improve adherence.
Sci Rep
January 2025
Department of Computer Science, College of Computer and Information Sciences, King Saud University, 11543, Riyadh, Saudi Arabia.
Understanding the nuanced emotions and points of view included in user-generated content remains challenging, even though text data analysis for mental health is a crucial instrument for assessing emotional well-being. Most current models neglect the significance of integrating viewpoints in comprehending mental health in favor of single-task learning. To offer a more thorough knowledge of mental health, in this study, we present an Opinion-Enhanced Hybrid BERT Model (Opinion-BERT), built to handle multi-task learning for simultaneous sentiment and status categorization.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Global Health Research, Graduate School of Medicine, Juntendo University, Tokyo, Japan.
Background: Maintaining the physical and psychological well-being of healthcare workers (HCWs) is crucial for health system resilience. In sub-Saharan Africa, particularly Uganda, HCWs faced significant challenges during the coronavirus disease 2019 (COVID-19) pandemic, compounded by pre-existing resource constraints. This study investigated challenges faced by HCWs at a designated COVID-19 hospital ('the Hospital') and explored determinants of maintaining healthcare personnel's motivation during the COVID-19 pandemic in Uganda.
View Article and Find Full Text PDFSci Rep
January 2025
Computational Learning Theory Team, RIKEN-Advanced Intelligence Project, Fukuoka, 819-0395, Japan.
Providing continuous wireless connectivity for high-speed trains (HSTs) is challenging due to their high speeds, making installing numerous ground base stations (BSs) along the HST route an expensive solution, particularly in rural and wilderness areas. This paper proposes using multiple unmanned aerial vehicles (UAVs) to deliver high data rate wireless connectivity for HSTs, taking advantage of their ability to fly, hover, and maneuver at low altitudes. However, autonomously selecting the optimal UAV by the HST is challenging.
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