Motion capture technology has advanced significantly, capturing real-time motion imagery in 2D and 3D. While marker-based systems have achieved sub-millimeter accuracy, their setup complexity and interference with nat...
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Battery health monitoring methods including machine learning (ML) models rely on trustworthiness of battery sensor data and features. As more battery systems require network connectivity for intelligent health monitor...
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With the rapid development of urban rail transit across the country, the industry has put forward higher requirements for quickly cultivating high-quality train drivers, maintenance personnel, and drivers. Therefore, ...
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This work proposed a vacancy-modulated analog resistive random-access memory (ReRAM) for neuromorphic computing, utilizing a structure composed of Ag/Zn@ZnO/ZnO/FTO. The resistive switching behavior can be modulated b...
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Background:The association between cancer and venous thromboembolism(VTE)is well-established with cancer patients accounting for approximately 20%of all VTE *** this paper,we have performed a comparison of machine lea...
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Background:The association between cancer and venous thromboembolism(VTE)is well-established with cancer patients accounting for approximately 20%of all VTE *** this paper,we have performed a comparison of machine learning(ML)methods to traditional clinical scoring models for predicting the occurrence of VTE in a cancer patient population,identified important features(clinical biomarkers)for ML model predictions,and examined how different approaches to reducing the number of features used in the model impact model ***:We have developed an ML pipeline including three separate feature selection processes and applied it to routine patient care data from the electronic health records of 1910 cancer patients at the University of California Davis Medical ***:Our ML-based prediction model achieved an area under the receiver operating characteristic curve of 0.778±0.006(mean±SD)when trained on a set of 15 *** result is comparable with the model performance when trained on all features in our feature pool[0.779±0.006(mean±SD)with 29 features].Our result surpasses the most validated clinical scoring system for VTE risk assessment in cancer patients by 16.1%.We additionally found cancer stage information to be a useful predictor after all performed feature selection processes despite not being used in existing score-based ***:From these findings,we observe that ML can offer new insights and a significant improvement over the most validated clinical VTE risk scoring systems in cancer *** results of this study also allowed us to draw insight into our feature pool and identify the features that could have the most utility in the context of developing an efficient ML *** a model trained on our entire feature pool of 29 features significantly outperformed the traditionally used clinical scoring system,we were able to achieve an equivalent performance using a subset of only 15 features through stra
In this paper, we introduce Heteroflow, a new C++ library to help developers quickly write parallel CPU-GPU programs using task dependency graphs. Heteroflow leverages the power of modern C++ and task-based approaches...
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A large-scale MIMO (multiple-input multiple-output) system offers significant advantages in wireless communication, including potential spatial multiplexing and beamforming capabilities. However, channel estimation be...
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We propose two Match-Zehnder interferometers coupled to create a structured illumination digital holographic microscope with tunable modulation frequency capability, expanding the system's numerical aperture regar...
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The trend in renewable energy calls for safe peer-to-peer(P2P)energy trading in a microgrid. Blockchain technology (BCT) addresses this by providing a secure, tamper-proof ledger that enables transparent and sustainab...
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The economic dispatch problem (EDP) is crucial in optimizing and controlling power systems. As modern power system become more complex, traditional centralized communication methods are becoming less reliable. Therefo...
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