Goaling recognition based on intelligent analysis of real-time basketball image of Internet of Things

The Journal of Supercomputing - This research aims to study the goaling recognition methods based on the intelligent analysis of real-time basketball images of the Internet of Things, so as to...     

Confidence regions of two-stage stochastic linear complementarity problems

Two-stage stochastic linear complementarity problems (TSLCP) model a large class of equilibrium problems subject to data uncertainty, and are closely related to two-stage stochastic optimization problems. The sample average approximation (SAA) method is one of the basic approaches for solving TSLCP and the consistency of the SAA solutions has been well studied. This paper focuses on building confidence regions of the solution to TSLCP when SAA is implemented. We first establish the error-bound condition of TSLCP and then build the asymptotic and nonasymptotic confidence regions of the solutions to TSLCP by error-bound approach, which is to combine the error-bound condition with central limit theory, empirical likelihood theory, and large deviation theory.     

Exploring the Semi-Supervised Video Object Segmentation Problem from a Cyclic Perspective

International Journal of Computer Vision - Modern video object segmentation (VOS) algorithms have achieved remarkably high performance in a sequential processing order, while most of currently...     

A novel approach of data race detection based on CNN-BiLSTM hybrid neural network

Neural Computing and Applications - Existing data race detection approaches based on deep learning are suffering from the problems of unique feature extraction and low accuracy. To this end, this...     

Heterogeneous feature ensemble modeling with stochastic configuration networks for predicting furnace temperature of a municipal solid waste incineration process

Neural Computing and Applications - Considering the accuracy, generalization ability, stability, and training efficiency of a furnace temperature model in the process of municipal solid waste...     

机械结构相似度评价及可靠性预计研究

在用传统的相似产品法进行可靠性预计时,所选取的相似产品与评价对象之间差异较大,会造成预计结果的偏差较大。为解决这一问题,提出了一种基于"功能—运动—动作"结构化分解的可靠性预计新方法。通过明确产品的各大运动功能建立功能层,分析完成各功能的机械部件运动建立运动层,确定实现各机械部件运动的元动作运动单元建立元动作层,建立了可靠性预计的"功能—运动—元动作运动单元"层次模型。引入区间层次分析法,确定了"功能—运动—元动作运动单元"层次模型中各子代运动单元对父代运动单元的可靠性影响权重,并构建了由子代运动单元预计父代运动单元可靠性的数学模型。确定影响评价机械结构相似度的因素,构建了区间数综合评判云模型并选取与元动作运动单元相似的参考结构,以区间数综合评价云模型得出的相似度值修正参考结构的可靠性数据来预计元动作运动单元的可靠性。将元动作运动单元的可靠性预计值代入数学模型,层层预计父代运动单元的可靠性,从而得出整个产品的可靠性水平。最后以数控转台为例进行了分析,得出了可靠性预计值,并将该方法与传统方法进行了比较。结果表明,新的可靠性预计方法具有较好的可行性和较高的准确性。     

Hollow Pd/MOF Nanosphere with Double Shells as Multifunctional Catalyst for Hydrogenation Reaction

A new type of hollow nanostructure featured double metal‐organic frameworks shells with metal nanoparticles (MNPs) is designed and fabricated by the methods of ship in a bottle and bottle around the ship. The nanostructure material, hereinafter denoted as Void@HKUST‐1/Pd@ZIF‐8, is confirmed by the analyses of photograph, transmission electron microscopy, scanning electron microscopy, powder X‐ray diffraction, inductively coupled plasma, and N₂ sorption. It possesses various multifunctionally structural characteristics such as hollow cavity which can improve mass transfer, the adjacent of the inner HKUST‐1 shell to the void which enables the matrix of the shell to host and well disperse MNPs, and an outer ZIF‐8 shell which acts as protective layer against the leaching of MNPs and a sieve to guarantee molecular‐size selectivity. This makes the material eligible candidates for the heterogeneous catalyst. As a proof of concept, the liquid‐phase hydrogenation of olefins with different molecular sizes as a model reaction is employed. It demonstrates the efficient catalytic activity and size‐selectivity of Void@HKUST‐1/Pd@ZIF‐8.     

Proline-derived in situ synthesis of nitrogen-doped porous carbon nanosheets with encaged Fe2O3@Fe3C nanoparticles for lithium-ion battery anodes

The homogeneous incorporation of heteroatoms into two-dimensional C nanostructures, which leads to an increased chemical reactivity and electrical conductivity as well as enhanced synergistic catalysis as a conductive matrix to disperse and encapsulate active nanocatalysts, is highly attractive and quite challenging. In this study, by using the natural and cheap hydrotropic amino acid proline—which has remarkably high solubility in water and a desirable N content of ~12.2 wt.%—as a C precursor pyrolyzed in the presence of a cubic KCl template, we developed a facile protocol for the large-scale production of N-doped C nanosheets with a hierarchically porous structure in a homogeneous dispersion. With concomitantly encapsulated and evenly spread Fe₂O₃ nanoparticles surrounded by two protective ultrathin layers of inner Fe₃C and outer onion-like C, the resulting N-doped graphitic C nanosheet hybrids (Fe₂O₃@Fe₃C-NGCNs) exhibited a very high Li-storage capacity and excellent rate capability with a reliable and prolonged cycle life. A reversible capacity as high as 857 mAh•g^–1 at a current density of 100 mA•g^–1 was observed even after 100 cycles. The capacity retention at a current density 10 times higher—1,000 mA•g^–1—reached 680 mAh•g^–1, which is 79% of that at 100 mA•g^–1, indicating that the hybrids are promising as anodes for advanced Li-ion batteries. The results highlight the importance of the heteroatomic dopant modification of the NGCNs host with tailored electronic and crystalline structures for competitive Li-storage features.