The goal of this study is to use the proactive procedure to categorize the failure, which likely to occur in hovercraft assembly. First, the hovercraft model is developed for standard sizes to identify the critical co...
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Unmanned aerial vehicles and drones are flying objects carrying small payloads for various applications, including agriculture, photography for weddings & religious ceremonies, e-commerce deliveries, remote sensin...
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The main objective of this paper is to develop and characterize silver-doped hydroxyapatite (Ag-HA) coating on Polyether ether ketone (PEEK). The physicochemical characteristic of Ag-HA coated on PEEK was evaluated by...
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Self-driving cars have gained significant attention in recent years. Real-time object detection is a critical component of their perception system. One of the main challenges in developing safe and efficient self-driv...
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With the development of microfluidics, fluid manipulation is becoming an increasingly critical process. In the macroscale environment, numerous robotic systems are commercially available, however development of these ...
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Dye Sensitize Solar Cell (DSSC) gained attention as a replacement for silicon solar cells owing to operational and economic benefits. This study aims to synthesize the Fe2O3/ZnO composites using two different methods;...
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Traditional motor function assessment for stroke patients involves subjective scoring by rehabilitation physicians, a process that is time-consuming, expensive, and subject to variability. By utilizing sensors (marker...
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Compliant grippers hold great promise in improving precision and safety in Minimally Invasive Surgery (MIS), offering versatile solutions for tissue manipulation while minimizing trauma. A novel focus on a capsule-sha...
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Visible/near-infrared(Vis/NIR)spectroscopy technology has been extensively utilized for the determination of soluble solids content(SSC)in ***,the spectral distortion resulting from temperature variations in the sampl...
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Visible/near-infrared(Vis/NIR)spectroscopy technology has been extensively utilized for the determination of soluble solids content(SSC)in ***,the spectral distortion resulting from temperature variations in the sample leads to a decrease in detection *** mitigate the influence of temperature fluctuations on the accuracy of SSC detection in fruits,using watermelon as an example,this study presents a knowledge-guided temperature correction method utilizing one-dimensional convolutional neural networks(1D-CNN).This method consists of two stages:the first stage involves utilizing 1D-CNN models and gradient-weighted class activation mapping(Grad-CAM)method to acquire gradient-weighted features correlating with *** second stage involves mapping these features and integrating them with the original Vis/NIR spectrum,and then train and test the partial least squares(PLS)*** knowledge-guided method can identify wavelength bands with high temperature correlation in the Vis/NIR spectra,offering valuable guidance for spectral data *** performance of the PLS model constructed using the 15℃ spectrum guided by this method is superior to that of the global model,and can reduce the root mean square error of the prediction set(RMSEP)to 0.324°Brix,which is 32.5%lower than the RMSEP of the global model(0.480°Brix).The method proposed in this study has superior temperature correction effects than slope and bias correction,piecewise direct standardization,and external parameter orthogonalization correction *** results indicate that the knowledge-guided temperature correction method based on deep learning can significantly enhance the detection accuracy of SSC in watermelon,providing valuable reference for the development of PLS calibration methods.
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