Graph neural networks (GNNs), designed specifically for handling graph-structured data, have been widely applied in many domains involving such data. As public awareness of privacy grows, data privacy protection is in...
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Graph layout can help users explore graph data intuitively. However, when handling large graph data volumes, the high time complexity of the layout algorithm and the overlap of visual elements usually lead to a signif...
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Silicon(Si)holds promise as an anode material for lithium-ion batteries(LIBs)as it is widely avail-able and characterized by high specific capacity and suitable working ***,the relatively low electrical conductivity o...
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Silicon(Si)holds promise as an anode material for lithium-ion batteries(LIBs)as it is widely avail-able and characterized by high specific capacity and suitable working ***,the relatively low electrical conductivity of Si and the significantly high extent of volume expansion realized dur-ing lithiation hinder its practical *** prepared N-doped carbon polyhedral micro cage en-capsulated Si nanoparticles derived from Co-Mo bimetal metal-organic framework(MOFs)(denoted as Si/CoMo@NCP)and explored their lithium storage performance as anode materials to address these *** Si/CoMo@NCP anode exhibited a high reversible lithium storage capacity(1013 mAh g^(−1)at 0.5 A g^(−1)after 100 cycles),stable cycle performance(745 mAh g^(−1)at 1 A g^(−1)after 400 cycles),and excellent rate performance(723 mAh g^(−1)at 2 A g^(−1)).Also,the constructed the full-cell NCM 811//Si/CoMo@NCP exhibited well reversible *** excellent electrochemical performances of Si/CoMo@NCP were at-tributed to two unique *** encapsulation of NCP with doped nitrogen and porous structural carbon improves the electrical conductivity and cycling stability of the *** introductions of metallic cobalt and its oxides help to improve the rate capability and lithiation capacity of the materials following multi-electron reaction mechanisms.
Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for st...
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Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a *** stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data *** information on the corrosion process was recorded using the galvanic corrosion current monitoring *** gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was *** exposure tests were conducted to verify the calculated results using the GBDT *** indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni ***-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of *** the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this *** the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion *** corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.
Crystallization speed of phase change material is one of the main obstaclesfor the application of phase change memory(PCM)as storage classmemory in computing systems,which requires the combination ofnonvolatility with...
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Crystallization speed of phase change material is one of the main obstaclesfor the application of phase change memory(PCM)as storage classmemory in computing systems,which requires the combination ofnonvolatility with ultra-fast operation speed in ***,wepropose a novel approach to speed up crystallization process of the onlycommercial phase change chalcogenide Ge_(2)Sb_(2)Te_(5)(GST).By employingTiO_(2) as the dielectric layer in phase change device,operation speed of650 ps has been achieved,which is the fastest among existing representativePCM,and is comparable to the programing speed of commercialdynamic random access memory(DRAM).Because of its octahedralatomic configuration,TiO_(2) can provide nucleation interfaces for GST,thus facilitating the crystal growth at the determinate interface ***–O–Ti–O four-fold rings on the(110)plane of tetragonal TiO_(2) is critical forthe fast-atomic rearrangement in the amorphous matrix of GST thatenables ultra-fast operation *** significant improvement of operationspeed in PCM through incorporating standard dielectric materialTiO_(2) in DRAM paves the way for the application of phase change memoryin high performance cache-type data storage.
Green sand is a mixture of silica sand,bentonite,water and coal powder,and other *** content is an important index to characterize the properties of green *** on the dielectric characteristics of green sand and transm...
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Green sand is a mixture of silica sand,bentonite,water and coal powder,and other *** content is an important index to characterize the properties of green *** on the dielectric characteristics of green sand and transmission line theory,a method for rapidly measuring the moisture content of green sand by means of a low frequency multiprobe detector was proposed.A system was constructed,where six detectors with different arrangements and probes were *** experimental results showed that the voltage difference of transmission line increases with the increasing frequency before 29 MHz while decreases after 35 MHz.A voltage difference platform occurs in the range of 29-35 MHz,which is suitable for measuring the moisture content due to its insensitivity to *** electric field intensity gradually decreases with the increase of the probe depth,and the intensity of central probe is always greater than that of the edge *** the distance of the probe away from the sand sample surface is 80 mm,the electric field intensity of the edge probe is found to be very *** optimal excitation frequency for measuring the moisture content of green sand is 29-33 *** optimal detector is the one with one center probe and three edge probes,and their lengths are 80 mm and 60 mm,*** distance between the center and edge probes is 25 mm,and the diameter of probes is 5 *** the voltage difference of transmission line,bentonite content,coal powder content and compactability as parameters of the input layer,and the moisture content as a parameter of the output layer,a three-layer BP artificial neural network model for predicting the moisture content of green sand was constructed according to the experimental results at 33 *** prediction error of the model is not higher than 3.3% when the moisture content of green sand is within the range of 3wt.%-7wt.%.
With the remarkable success of change detection(CD)in remote sensing images in the context of deep learning,many convolutional neural network(CNN)based methods have been *** the current research,to obtain a better con...
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With the remarkable success of change detection(CD)in remote sensing images in the context of deep learning,many convolutional neural network(CNN)based methods have been *** the current research,to obtain a better context modeling method for remote sensing images and to capture more spatiotemporal characteristics,several attention-based methods and transformer(TR)-based methods have been *** research has also continued to innovate on TR-based methods,and many new methods have been *** of them require a huge number of calculation to achieve good ***,using the TR-based mehtod while maintaining the overhead low is a problem to be ***,we propose a GNN-based multi-scale transformer siamese network for remote sensing image change detection(GMTS)that maintains a low network overhead while effectively modeling context in the spatiotemporal *** also design a novel hybrid backbone to extract *** with the current CNN backbone,our backbone network has a lower overhead and achieves better ***,we use high/low frequency(HiLo)attention to extract more detailed local features and the multi-scale pooling pyramid transformer(MPPT)module to focus on more global features ***,we leverage the context modeling capabilities of TR in the spatiotemporal domain to optimize the extracted *** have a relatively low number of parameters compared to that required by current TR-based methods and achieve a good effect improvement,which provides a good balance between efficiency and performance.
With the deepening of neural network research,object detection has been developed rapidly in recent years,and video object detection methods have gradually attracted the attention of scholars,especially frameworks inc...
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With the deepening of neural network research,object detection has been developed rapidly in recent years,and video object detection methods have gradually attracted the attention of scholars,especially frameworks including multiple object tracking and *** current works prefer to build the paradigm for multiple object tracking and detection by multi-task *** with others,a multi-level temporal feature fusion structure is proposed in this paper to improve the performance of framework by utilizing the constraint of video temporal *** training the temporal network end-to-end,a feature exchange training strategy is put forward for training the temporal feature fusion structure *** proposed method is tested on several acknowledged benchmarks,and encouraging results are obtained compared with the famous joint detection and tracking *** ablation experiment answers the problem of a good position for temporal feature fusion.
For dual active bridge (DAB) DC/DC converters, DC bias of the inductor current caused by the system parameters variation increases system losses, leads to core saturation, and even jeopardizes the safe and reliable op...
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The task of Fine-Grained Visual Classification (FGVC) aims to distinguish between closely related subclasses within a broader category. Challenges include high intra-class variation, minimal inter-class differences, a...
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