Grammatical Error Correction is an important research direction in NLP field. Although many models of different architectures and datasets across different languages have been developed to support the research, there ...
详细信息
Generalized Lyapunov matrix equations appear in the fields of controllability analysis and model reduction of bilinear systems, stability analysis and optimal stabilization of linear stochastic systems, etc. The autho...
详细信息
Information designer Alberto Cairo talks to Brian Tarran about his new book and why bravery, reason and anarchy are intrinsic to all the best data visualisation
Information designer Alberto Cairo talks to Brian Tarran about his new book and why bravery, reason and anarchy are intrinsic to all the best data visualisation
As a main approach towards touch-free human-computer interaction, hand gesture recognition (HGR) has long been a research focus for both academia and industry. Meanwhile, visible light communication (VLC) has become i...
详细信息
1 Introduction Encouraged by the success of Convolutional Neural Networks(CNNs),many studies[1],known as Graph Convolutional Networks(GCNs),borrowed the idea of convolution and redefined it for graph *** graph-level c...
详细信息
1 Introduction Encouraged by the success of Convolutional Neural Networks(CNNs),many studies[1],known as Graph Convolutional Networks(GCNs),borrowed the idea of convolution and redefined it for graph *** graph-level classification tasks,Classic GCN methods[2,3]generate graph embeddings based on the learned node embeddings which consider each node’s representation as multiple independent scalar ***,they neglect the detailed mutual relations among different node features such as position,direction,and *** by CapsNet[4]which encodes each feature of an image as a vector(a capsule),CapsGNN[5]extracts multi-scale node features from different convolutional layers in the form of ***,CapsGNN uses a static model structure to conduct training,which inherently restricts its representation ability on different datasets.
Machine learning has been massively utilized to construct data-driven solutions for predicting the lifetime of rechargeable batteries in recent years, which project the physical measurements obtained during the early ...
详细信息
Machine learning has been massively utilized to construct data-driven solutions for predicting the lifetime of rechargeable batteries in recent years, which project the physical measurements obtained during the early charging/discharging cycles to the remaining useful lifetime. While most existing techniques train the prediction model through minimizing the prediction error only, the errors associated with the physical measurements can also induce negative impact to the prediction accuracy. Although total-least-squares(TLS) regression has been applied to address this issue, it relies on the unrealistic assumption that the distributions of measurement errors on all input variables are equivalent, and cannot appropriately capture the practical characteristics of battery degradation. In order to tackle this challenge, this work intends to model the variations along different input dimensions, thereby improving the accuracy and robustness of battery lifetime prediction. In specific, we propose an innovative EM-TLS framework that enhances the TLS-based prediction to accommodate dimension-variate errors, while simultaneously investigating the distributions of them using expectation-maximization(EM). Experiments have been conducted to validate the proposed method based on the data of commercial Lithium-Ion batteries, where it reduces the prediction error by up to 29.9 % compared with conventional TLS. This demonstrates the immense potential of the proposed method for advancing the R&D of rechargeable batteries.
Steganography is a technique for obfuscating secret information by enclosing it in a regular, non-secret file or communication;the information is subsequently extracted at the intended location. Steganography can be u...
详细信息
The adsorption of Pb(II)on silica gel synthesized from chemical glass bottle waste has been *** effect of independent variables(adsorbent dose,initial concentration of Pb(II),contact time,and pH)on the Pb(II)removal f...
详细信息
The adsorption of Pb(II)on silica gel synthesized from chemical glass bottle waste has been *** effect of independent variables(adsorbent dose,initial concentration of Pb(II),contact time,and pH)on the Pb(II)removal from water was evaluated and optimized using the Response Surface Methodology(RSM).Under optimized conditions(adsorbent dose:20 mg;contact time:30 min;initial Pb(II)concentration:120 mg.L^(−1);and pH:8),the removal of Pb(II)was 99.77%.The adsorption equilibrium data obtained from the batch experiment were investigated using different isotherm *** Langmuir isotherm model fits the experimental *** shows that the surface of the silica gel synthesized from chemical bottles waste was covered by a Pb(II)*** analysis showed that the synthesized silica gel had a SiO_(2) content of 75.63%.Amorphous silica was observed from XRD ***-EDX characterization showed that Pb was adsorbed on the silica gel *** analysis showed that silica gel has irregular particles with a surface area of 297.08 m2.g^(−1) with a pore radius of 15.74 nm calculated from BET analysis.
The development of the Space-Air-Ground Integrated Network (SAGIN) represents a significant advancement in satellite Internet technology, primarily because it facilitates the provision of pervasive networking solution...
详细信息
In the recent past, there were several works on the prediction of stock prices using different methods. Sentiment analysis of news and tweets and relating them to the movement of stock prices have already been explore...
详细信息
暂无评论