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Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. Differences between the two domains, such as significant variations in the scale of visual things and the higher granularity of pixels in images compared to words in the text, make it difficult to transfer Transformer from language to vision.

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Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.

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This paper deals with a "digital twin" (DT) approach for processing, reprocessing, and scrapping (P/R/S) technology running on a modular production system (MPS) assisted by a mobile cyber-physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC.

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Receiving a diagnosis, such as cerebral palsy (CP), can have lasting impacts on caregivers and families. Previous literature has described that caregivers wish to receive a diagnosis together, without delay, in a private, direct, honest, and sympathetic way. This study aimed to understand the experience of caregivers of children with cerebral palsy (CP) or similar conditions when receiving a diagnosis for their child.

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Current work environments, driven by globalization, demographic changes, and digitalization, demand substantial adaptation, which leads to decreased employee well-being. While occupational psychology research has identified supportive mechanisms, it often lacks a deepened understanding of how interventions function. This study aims to analyze the impacts of VUCA contexts and leadership behavior on job crafting, focusing on white-collar workers.

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