Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks

International Journal of Computer Vision - Visual tracking of generic objects is one of the fundamental but challenging problems in computer vision. Here, we propose a novel fully convolutional...     

Infrared target tracking based on proximal robust principal component analysis method

Applied Intelligence - Infrared target tracking plays an important role in both civil and military fields. The main challenges in designing a robust and high-precision tracker for infrared...     

Data-driven physical law learning model for chaotic robot dynamics prediction

Applied Intelligence - A robot control system is a multivariable, nonlinear automatic control system, as well as a dynamic coupling system. To address the difficult problem of data prediction under...     

The Effect of the Rotary Steerable Spindle Structure Parameters on the Characteristics of Cantilever Bearing

Journal of Failure Analysis and Prevention - In point-the-bit rotary steerable drilling system, the internal and outer diameter of the spindles and the fillet radius of the shaft shoulder have a...     

Effect of Sintering Temperature on Magnetic and Electrical Properties of GdBaCo<Subscript>2</Subscript><Emphasis Type="Italic">O</Emphasis><Subscript>5 + <Emphasis Type="Italic">δ</Emphasis></Subscript>

In this study, we report the results of an investigation into the sintering temperature dependence of magnetic and transport properties for GdBaCo₂ O _{5 + δ} synthesized through a sol-gel method. The lowering of sintering temperature leads to the increase of oxygen content and the reduction of grain size. The increase of oxygen content results in the enhancement of magnetic interactions and the weakening of Coulomb repulsion effect, while the reduction of grain size improves the magnetoresistance effect. Metal-insulator transition accompanied with spin-state transition is observed in all samples.     

Selective toxicity of hydroxyl-rich carbon nanodots for cancer research

Nano Research - The toxicity of nanoparticles in a biological system is an integration of effects arising from surface functionality, particle size, ionic dissolution, etc. This complexity suggests...     

Aggregation-induced emission luminogen-assisted stimulated emission depletion nanoscopy for super-resolution mitochondrial visualization in live cells

Nano Research - Aggregation-induced emission luminogens (AIEgens) are fluorescent agents that are ideal for bioimaging and have been widely used for organelle targeting, cellular mapping, and...     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Container-Based Internet of Vehicles Edge Application Migration Mechanism

Internet of Vehicles (IoV) applications integrating with edge computing will significantly drive the growth of IoV. However, the contradiction between the high-speed mobility of vehicles, the delay sensitivity of corresponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV applications. IoV application migration is a promising solution that can be supported by application containerization, a technology forseamless cross-edge-server application migration without user perception. Therefore, this paper proposes the container-based IoV edge application migration mechanism, consisting of three parts. The first is the migration trigger determination algorithm for cross-border migration and service degradation migration, respectively, based on trajectory prediction and traffic awareness to improve the determination accuracy. The second is the migration target decision calculation model for minimizing the average migration time and maximizing the average service time to reduce migration times and improve the stability and adaptability of migration decisions. The third is the migration decision algorithm based on the improved artificial bee colony algorithm to avoid local optimal migration decisions. Simulation results show that the proposed migration mechanism can reduce migration times, reduce average migration time, improve average service time and enhance the stability and adaptability of IoV application services.