Maintenance management is a vital part of the business of a production company. It contributes to determining the long-term success of the company because poorly maintained resources can stop production activities, ca...
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Maintenance management is a vital part of the business of a production company. It contributes to determining the long-term success of the company because poorly maintained resources can stop production activities, causing delays, loss of profit and even personal injuries. While the predictive maintenance approach is nowadays a mainstay of modern factory management, usually only big companies with dedicated research department can deploy it, since its application involves scientific knowledge that is not available in smaller production environments. This paper describes how the EU project PROGRAMS answers the needs of small and medium companies that wish to apply an Industrial Internet of Things (IIoT) approach to maintenance management.
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not ref...
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It was reported that cancer cells could biologically respond and adapt to the confined environment during migration in extracellular matrix (ECM). But it is not clearly studied that how cancer cells respond and adapt ...
ISBN:
(数字)9781728150734
ISBN:
(纸本)9781728150741
It was reported that cancer cells could biologically respond and adapt to the confined environment during migration in extracellular matrix (ECM). But it is not clearly studied that how cancer cells respond and adapt to confined environment in mechanical way. Thus, in this study, we designed and fabricated a kind of one-layer micro channel to mimic confined environment for analyzing mechanical adaption of cell. This micro channel could apply sequential mechanical stresses on a number of cells with high throughput, and the time of cells passing through five rows of micro channels were used to evaluate their adaptability to the sequential and confined space. In experiments, each cell suffered 20 times of mechanical stresses after passing through 20 squeezing channels arranged in 5 rows. We observed the sequential squeezing processes under microscope and investigated the passing time using a high-speed camera. The preliminary results indicated that cancer cells could pass through and adapt to the confined environment faster than normal cells.
Population structure strongly affects the dynamic behavior and performance of the particle swarm optimization (PSO) algorithm. Most of PSOs use one of two simple sociometric principles for defining the structure. One ...
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Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We ...
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Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, mes...
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In the above article [1] , the affiliations of authors Lihong Dai and Yang Gao need to be corrected. Moreover, the biography of Yang Gao needs to be corrected. The specific corrections are as follows.
In the above article [1] , the affiliations of authors Lihong Dai and Yang Gao need to be corrected. Moreover, the biography of Yang Gao needs to be corrected. The specific corrections are as follows.
Dual-drive H-gantry is widely used in many industrial processes that require high-speed and high-precision Cartesian motion. Unlike the rigid-linked gantry design, the flexure-linked design is able to prevent the dama...
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