检索结果-南通市图书馆

Rare Metals 2018年第12期37卷 1070-1075页

作者： Yu-Lin Liu Lei Luo Ming-Ze Shun Li Zhang Yu-Hua Zhao Bao-Lin Wu Liaoning provincial key laboratory of Light Alloys and processing Technology School of Materials Science and Engineering Shenyang Aerospace University

Al-Fe-V-Si alloys were developed for use at elevated temperature and usually produced through a rapid solidification-powder metallurgy route. In this work, effort was made to produce the material via casting route. The studied alloys were cast under the condition of near-rapid cooling. The influence of Ce addition on microstructure and mechanical properties of near-rapid solidified alloys were investigated. The results indicate that the as-cast microstructure of Al-5.5 Fe-1.1 V-0.6 Si alloy is significantly refined when the alloy was solidified under nearrapid cooling. Adding Ce results in the further refinement of intermetallic compound and the formation of an Al-V-Ce phase which replaces the primary phase Al(Fe,V)Si. The mechanical properties of the alloy are significantly improved by Ce addition: More than 70% increase in tensile strength and elongation is achieved by adding 1.00 wt% Ce to the alloy. It is concluded that near-rapid cooling and Ce addition are effective in improving mechanical properties of cast Al-5.5 Fe-1.1 V-0.6 Si alloy.

关键词： Aluminum alloys Al-Fe-V-Si alloy Rapid solidification Solidification microstructures Mechanical properties

Grain boundary restructuring and La/Ce/Y application in Nd–Fe–B magnets

在线全文

学校读者我要写书评

暂无评论

Chinese Physics B 2019年第7期28卷 25-53页

作者： Mi Yan Jiaying Jin Tianyu Ma School of Materials Science and Engineering State Key Laboratory of Silicon MaterialsKey Laboratory of Novel Materials for Information Technology of Zhejiang Province Zhejiang University

Since the 1980 s, Nd–Fe–B with largest energy product(BH)max approaching the theoretical limit has become the landmark of permanent magnetic *** application spectrum for Nd–Fe–B continues to expand over time both in the industrial and commercial sectors, which leads to growing research interests for solving the long-standing drawbacks of Nd–Fe–B, i.e., poor corrosion resistance, low coercivity, high Dy/Tb and low La/Ce/Y *** the above obstacles, we aim to present the novel grain boundary restructuring(GBR) approach, from GB design, processing, to structure evolution and property evaluation with a focus on the corrosion and coercivity mechanism of the restructured 2:14:1-typed *** with an introduction to the fundamental of GBR, two representative examples,high-electrode-potential(Pr, Nd)32.5Fe62.0Cu5.5 and low-melting-point Dy71.5Fe28.5, are given with detailed descriptions of the advantages of GBR to enhance the intrinsic anti-corrosion stability and to strengthen the coercivity at low Dy ***–property correlations are established to understand the critical importance of regulating the restructured GB phase to maximize the all-round performance of the 2:14:1-typed permanent *** at sustainable and balanced development of rare earth(RE) industry, the proceeding section proposes new prototypes of La–Ce and Y–Ce co-substitutions with dual benefits of stabilizing the 2:14:1 tetragonal phase and strengthening the intrinsic hard *** findings of additional REFe2 intergranular phase delight that the GBR approach also opens up a new horizon of research and application to develop high-performance La/Ce/Y-rich permanent magnets with deliberately tailored GB phase.

关键词： grain boundary restructuring coercivity corrosion resistance Dy/Tb La/Ce/Y

Content based error resilience coding using redundant coding, reference frame modification, and mode decision

在线全文

学校读者我要写书评

暂无评论

Journal of Central South University 2014年第11期21卷 4199-4209页

作者：徐巍炜蒋荣欣田翔陈耀武 Institute of Advanced Digital Technology and Instrument zhejiang University zhejiang provincial key laboratory for Network Multimedia Technologies (zhejiang University)

Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.

关键词： error resilience coding redundant picture macro-block(MB) refresh reference frame selection error propagation distortion

DeepHGNN: A Novel Deep Hypergraph Neural Network

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2022年第5期31卷 958-968页

作者： LIN Jingjing YE Zhonglin ZHAO Haixing FANG Lusheng Tibetan information processing and Machine Translation key laboratory of Qinghai Province College of Computer Qinghai Normal University Xining Urban Vocational & Technical College The State key laboratory of Tibetan Intelligent information processing and Application

With the development of deep learning,graph neural networks(GNNs) have yielded substantial results in various application fields. GNNs mainly consider the pair-wise connections and deal with graph-structured data. In many real-world networks, the relations between objects are complex and go beyond *** is a flexible modeling tool to describe intricate and higher-order correlations. The researchers have been concerned how to develop hypergraph-based neural network model. The existing hypergraph neural networks show better performance in node classification tasks and so on, while they are shallow network because of oversmoothing, over-fitting and gradient vanishment. To tackle these issues, we present a novel deep hypergraph neural network(Deep HGNN). We design Deep HGNN by using the technologies of sampling hyperedge, residual connection and identity mapping, residual connection and identity mapping bring from graph convolutional neural networks. We evaluate Deep HGNN on two visual object datasets. The experiments show the positive effects of Deep HGNN, and it works better in visual object classification tasks.

关键词： Deep neural networks Graph neural network Hypergraph neural network Deep hypergraph neural network

Unsupervised feature selection via joint local learning and group sparse regression

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Frontiers of information Technology & Electronic Engineering 2019年第4期20卷 538-553页

作者： Yue WU Can WANG Yue-qing ZHANG Jia-jun BU zhejiang provincial key laboratory of Service Robot College of Computer Science and Technology Zhejiang University Alibaba-zhejiang University Joint Institute of Frontier Technologies

Feature selection has attracted a great deal of interest over the past decades. By selecting meaningful feature subsets, the performance of learning algorithms can be effectively improved. Because label information is expensive to obtain, unsupervised feature selection methods are more widely used than the supervised ones. The key to unsupervised feature selection is to find features that effectively reflect the underlying data distribution. However,due to the inevitable redundancies and noise in a dataset, the intrinsic data distribution is not best revealed when using all features. To address this issue, we propose a novel unsupervised feature selection algorithm via joint local learning and group sparse regression(JLLGSR). JLLGSR incorporates local learning based clustering with group sparsity regularized regression in a single formulation, and seeks features that respect both the manifold structure and group sparse structure in the data space. An iterative optimization method is developed in which the weights finally converge on the important features and the selected features are able to improve the clustering results. Experiments on multiple real-world datasets(images, voices, and web pages) demonstrate the effectiveness of JLLGSR.

关键词： Unsupervised Local learning Group sparse regression Feature selection

Effect of Fe, Si and Cooling Rate on the Formation of Fe-and Mn-rich Intermetallics in Al–5Mg–0.8Mn Alloy

在线全文

学校读者我要写书评

暂无评论

Journal of Materials Science & Technology 2016年第4期32卷 305-312页

作者： Yulin Liu Lei Luo Chaofei Han Liangyun Ou Jijie Wang Chunzhong Liu Liaoning provincial key laboratory of Light Alloys and processing Technology School of Materials Science and Engineering Shenyang Aerospace University

The Fe- and Mn-rich intermetallics are of great effect on the mechanical properties of the AA5083 type alloy （Al-5Mg-0.8Mn）. The effect of Fe, Si and cooling rate on the formation of the intermetallics were investigated by analyzing the microstructures of the alloys with different Fe and Si contents. The results indicated that increasing the Fe content resulted in the increase of the Al6（Fe,Mn） phase in both amount and size. In the alloys with high Fe content, the platelet-like Al6（Fe,Mn） compounds lined up and formed a band. Increasing the content of Si resulted in the increase of the Mg2Si phase which formed a network structure. Increasing the cooling rate significantly refined the intermetallics. However, increasing the cooling rate did not change the characteristic of the intermetallic compounds in the alloys with low or medium Si contents. For the alloys with high contents of Fe and Si under the condition of near-rapid cooling, the Fe- and Mn-rich intermetallic compound changed to the quaternary Al15（Fe,Mn）3Si phase and displayed a fine fish bone or Chinese script structure. The refinement of the intermetallics would allow higher tol- erance of Fe and Si contents in the AA5083 alloy produced, for instance, via the continuous strip casting process.

关键词： Aluminum alloyIntermetallicsPhase transformationCastingRapid solidification

Randomly coupled trench-assisted multicore fibers with different arrangements for high tolerance of manufacturing errors

在线全文

学校读者我要写书评

暂无评论

Science China(information Sciences) 2023年第11期66卷 260-272页

作者： Yongneng JIANG Jiajing TU Shecheng GAO Weiping LIU Zhaohui LI Department of Electronic Engineering College of Information Science and Technology Jinan University School of Electronics and information Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University Southern Marine Science and Engineering Guangdong laboratory(Zhuhai)

Randomly coupled multicore fibers(RC-MCFs) are promising candidates for long-haul transmission. However, the degree of coupling between the homogeneous cores of an RC-MCF is weakened if manufacturing errors appear. Therefore, a low-index trench layer is introduced into the coupled cores to investigate the effects of its position and thickness on the group index to enhance the tolerance of manufacturing errors. A depressed region is designed in the center of the core to solve the problem of the effective area decreasing because of the confinement of the low-index trench. Additionally, it is important to study the effective arrangement of the coupled cores to obtain a smaller group delay spread(GDS) within the limited 125-μm cladding; we discuss the single-layer and double-layer arrangements. A moderate range is found for both the bending radius and core pitch to minimize the GDS. For the single-layer arrangement, the degree of mixing is weak, and the degeneracy state does not easily change the bending conditions; thus, it may be a good candidate for designing systemically coupled multicore fibers. For the double-layer arrangement, the bending and twisting factors can induce sufficient mixing among the different modes to reduce GDS; thus,this arrangement is more suitable for the design of RC-MCFs.

关键词： manufacturing errors randomly coupled multicore fibers trench-assisted core single-layer arrangement double-layer arrangement

Pore plugging effects on the performance of ZSM-5 catalyst in MTP reaction using a discrete model

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Chemical Engineering 2021年第4期34卷 253-263页

作者： Yudong Shen Hao Liang Zuwei Liao Binbo Jiang Jingdai Wang Yongrong Yang Minggang Li Yibin Luo Xingtian Shu zhejiang provincial key laboratory of Advanced Chemical Engineering Manufacture Technology College of Chemical and Biological EngineeringZhejiang UniversityHangzhou 310027China State key laboratory of Chemical Engineering College of Chemical and Biological EngineeringZhejiang UniversityHangzhou 310027China SINOPEC Research Institute of Petroleum processing Beijing 100083China

Coke is an important medium for connecting reaction and regeneration of the methanol to propylene process on the ZSM5 *** grows in the meso and macro pores,it gradually worsens the diffusion inside the catalyst ***,pore plugging is inevitable which causes the deactivation of ZSM5 ***,current continuum model cannot reflect the changes in pore structure with clear physical concepts.A discrete model that is verified by the carbon deposition experiments is introduced to indicate the behavior of pore plugging *** show that the pore plugging has a significant effect on the performance of the *** time varying profile of effectiveness factor is obtained,indicating a regular reduction with the increase of the pore plugging *** distributions of pore size that would significantly enhance the plugging effect are also identified.

关键词： Discrete model Pore plugging effects MTP reaction Pore network

Action Status Based Novel Relative Feature Representations for Interaction Recognition

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2022年第1期31卷 168-180页

作者： LI Yanshan GUO Tianyu LIU Xing LUO Wenhan XIE Weixin ATR National key laboratory of Defense Technology Shenzhen University Guangdong key laboratory of Intelligent information processing Shenzhen University Tencent

Skeleton-based action recognition has always been an important research topic in computer vision. Most of the researchers in this field currently pay more attention to actions performed by a single person while there is very little work dedicated to the identification of interactions between two people. However, the practical application of interaction recognition is actually more critical in our society considering that actions are often performed by multiple people. How to design an effective scheme to learn discriminative spatial and temporal representations for skeleton-based interaction recognition is still a challenging problem. Focusing on the characteristics of skeleton data for interactions, we first define the moving distance to distinguish the action status of the participants. Then some view-invariant relative features are proposed to fully represent the spatial and temporal relationship of the skeleton sequence. Further, a new coding method is proposed to obtain the novel relative feature representations. Finally, we design a three-stream CNN model to learn deep features for interaction recognition. We evaluate our method on SBU dataset, NTU RGB+D 60 dataset and NTU RGB+D 120 dataset. The experimental results also verify that our method is effective and exhibits great robustness compared with current state-of-the-art methods.

关键词： image representation relative feature representations skeleton-based interaction recognition skeleton sequence skeleton data image coding deep learning (artificial intelligence) image recognition temporal representations temporal relationship view-invariant relative features spatial relationship skeleton-based action recognition action status computer vision convolutional neural nets discriminative spatial representations image motion analysis

Active constraints selection based semi-supervised dimensionality in ensemble subspaces

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2015年第5期26卷 1088-1099页

作者： Jie Zeng Wei Nie Yong Zhang College of information Engineering Shenzhen University Modern Communication and information processing key laboratory Shenzhen University ATR key laboratory of National Defense Technology Shenzhen University

Semi-supervised dimensionality reduction(SSDR) has attracted an increasing amount of attention in this big-data *** algorithms have been developed with a small number of pairwise constraints to achieve performances comparable to those of fully supervised methods. However, one challenging problem with semi-supervised approaches is the appropriate choice of the constraint set, including the cardinality and the composition of the constraint set, which to a large extent, affects the performance of the resulting algorithm. In this work, we address the problem by incorporating ensemble subspace and active learning into dimensionality reduction and propose a new algorithm, termed as global and local scatter based SSDR with active pairwise constraints selection in ensemble subspaces(SSGL-ESA). Unlike traditional methods that select the supervised information in one subspace,we pick up pairwise constraints in ensemble subspace, where a novel active learning algorithm is designed with both exploration and filtering to generate informative pairwise constraints. The automatic constraint selection approach proposed in this paper can be generalized to be used with all constraint-based semi-supervised learning algorithms. Comparative experiments are conducted on two face database and the results validate the effectiveness of the proposed method.

关键词： semi-supervised dimensionality reduction(SSDR) ensemble subspace active learning machine learning