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< Page ,Total 221 >
A two-level finite element method for the Allen–Cahn equation EI Scopus SCIE
期刊论文 | 2019 , 96 (1) , 158-169 | International Journal of Computer Mathematics
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Abstract :

We consider the fully implicit treatment for the nonlinear term of the Allen–Cahn equation. To solve the nonlinear problem efficiently, the two-level scheme is employed. We obtain the discrete energy law of the fully implicit scheme and two-level scheme with finite element method. Also, the convergence of the two-level method is presented. Finally, some numerical experiments are provided to confirm the theoretical analysis. © 2018 Informa UK Limited, trading as Taylor & Francis Group

Keyword :

Discrete energies Fully implicit scheme Implicit treatment Nonlinear problems Numerical experiments Numerical tests Stability and convergence Two level methods

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GB/T 7714 Liu, Qingfang , Zhang, Ke , Wang, Zhiheng et al. A two-level finite element method for the Allen–Cahn equation [J]. | International Journal of Computer Mathematics , 2019 , 96 (1) : 158-169 .
MLA Liu, Qingfang et al. "A two-level finite element method for the Allen–Cahn equation" . | International Journal of Computer Mathematics 96 . 1 (2019) : 158-169 .
APA Liu, Qingfang , Zhang, Ke , Wang, Zhiheng , Zhao, Jiakun . A two-level finite element method for the Allen–Cahn equation . | International Journal of Computer Mathematics , 2019 , 96 (1) , 158-169 .
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A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving EI Scopus SCIE
期刊论文 | 2019 , 100 (5-8) , 1635-1645 | International Journal of Advanced Manufacturing Technology
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Abstract :

As a particular two degree of freedom generating method, skiving is effective to manufacture the periodically distributed internal and external profiles, and its cutting edge design is a foundational problem. In order to avoid the singularity in analytical methods, this paper studied a discrete surface assisted universal method to identify the cutting edge of skiving cutter and simulate the machining process by discrete cutting points. Firstly, the kinematic model of skiving was constructed in aspects of the parametrical modeling of the cutter and workpiece as well as the machining configuration. The principle of cutting edge identification was investigated based on the conjugation process of skiving in the following. Then, the entire procedure for cutting edge calculation was presented in detail. Therefrom, according to the profile generation during cutting action, the skiving spatial contacts were analyzed through reasonable coordinate frame transformation. At last, an external skiving for involute gear was taken, the cutting edges for two kinds of rake flank were calculated, and the machining error between the machined profile and desired profile was compared to proof the correctness of calculated cutting edges. Besides, the analysis of the spatial contact motions for these cases validated the effectiveness and the practicality of the proposed method. © 2018, Springer-Verlag London Ltd., part of Springer Nature.

Keyword :

Contact curves Cutting edges Kinematic model Machining process simulation Skiving

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GB/T 7714 Jia, Kang , Zheng, Shuai , Guo, Junkang et al. A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving [J]. | International Journal of Advanced Manufacturing Technology , 2019 , 100 (5-8) : 1635-1645 .
MLA Jia, Kang et al. "A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving" . | International Journal of Advanced Manufacturing Technology 100 . 5-8 (2019) : 1635-1645 .
APA Jia, Kang , Zheng, Shuai , Guo, Junkang , Hong, Jun . A surface enveloping-assisted approach on cutting edge calculation and machining process simulation for skiving . | International Journal of Advanced Manufacturing Technology , 2019 , 100 (5-8) , 1635-1645 .
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Robust point cloud registration based on both hard and soft assignments EI Scopus SCIE
期刊论文 | 2019 , 110 , 202-208 | Optics and Laser Technology
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Abstract :

For the registration of partially overlapping point clouds, this paper proposes an effective approach based on both the hard and soft assignments. Given two initially posed clouds, it firstly establishes the forward correspondence for each point in the data shape and calculates the value of a binary variable, which indicates whether this point correspondence is located in the overlapping areas or not. Then, it establishes the bilateral correspondence and computes bidirectional distances for each point in the overlapping areas. Based on the ratio of bidirectional distances, the exponential function is selected and utilized to calculate the probability value, which indicates the reliability of the point correspondence. Subsequently, both the values of hard and soft assignments are embedded into the proposed objective function for registration of partially overlapping point clouds, which then be solved by the proposed variant of ICP algorithm to obtain the optimal rigid transformation. The proposed approach can achieve good registration of point clouds, even when their overlap percentage is low. Experimental results tested on public datasets illustrate its superiority over previous approaches on accuracy and robustness. © 2018 Elsevier Ltd

Keyword :

Bidirectional distances Hard assignment Overlap percentage Point cloud registration Soft assignments

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GB/T 7714 Zhu, Jihua , Jin, Congcong , Jiang, Zutao et al. Robust point cloud registration based on both hard and soft assignments [J]. | Optics and Laser Technology , 2019 , 110 : 202-208 .
MLA Zhu, Jihua et al. "Robust point cloud registration based on both hard and soft assignments" . | Optics and Laser Technology 110 (2019) : 202-208 .
APA Zhu, Jihua , Jin, Congcong , Jiang, Zutao , Xu, Siyu , Xu, Minmin , Pang, Shanmin . Robust point cloud registration based on both hard and soft assignments . | Optics and Laser Technology , 2019 , 110 , 202-208 .
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Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation EI Scopus SCIE
期刊论文 | 2019 , 28 (2) , 841-852 | IEEE Transactions on Image Processing
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Abstract :

© 1992-2012 IEEE. Embedding and aggregating a set of local descriptors (e.g., SIFT) into a single vector is normally used to represent images in image search. Standard aggregation operations include sum and weighted aggregations. While showing high efficiency, sum aggregation lacks discriminative power. In contrast, weighted aggregation shows promising retrieval performance but suffers extremely high time cost. In this paper, we present a general mixed aggregation method that unifies sum and weighted aggregation methods. Owing to its general formulation, our method is able to balance the trade-off between retrieval quality and image representation efficiency. Additionally, to improve query performance, we propose computing multiple weighting coefficients rather than one for each to be aggregated vector by partitioning them into several components with negligible computational cost. Extensive experimental results on standard public image retrieval benchmarks demonstrate that our aggregation method achieves state-of-the-art performance while showing over ten times speedup over baselines.

Keyword :

Aggregation image representation image search multiple weights

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GB/T 7714 Pang, Shanmin , Xue, Jianru , Zhu, Jihua et al. Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation [J]. | IEEE Transactions on Image Processing , 2019 , 28 (2) : 841-852 .
MLA Pang, Shanmin et al. "Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation" . | IEEE Transactions on Image Processing 28 . 2 (2019) : 841-852 .
APA Pang, Shanmin , Xue, Jianru , Zhu, Jihua , Zhu, Li , Tian, Qi . Unifying Sum and Weighted Aggregations for Efficient Yet Effective Image Representation Computation . | IEEE Transactions on Image Processing , 2019 , 28 (2) , 841-852 .
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Bibliographic Network Representation Based Personalized Citation Recommendation SCIE
期刊论文 | 2019 , 7 , 457-467 | IEEE ACCESS
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Abstract :

With the increasing number of scientific papers, researchers find it more and more difficult to obtain relevant and appropriate papers to cite. Citation recommendation aims to overcome this problem by providing a reference paper list for a given manuscript. In this paper, we propose a bibliographic network representation (BNR) model, which simultaneously incorporates bibliographic network structure and content of different kinds of objects (authors, papers, and venues) for efficient recommendation. The proposed model also makes personalized citation recommendation possible, which is a new issue that a few papers addressed in the past. When conducting experiments on the ACL Anthology Network and DBLP datasets, the results demonstrate that the proposed BNR-based citation recommendation approach is able to achieve considerable improvement over other network representation-based citation recommendation approaches. The performance of the personalized recommendation approach is also competitive with the non-personalized recommendation approach.

Keyword :

personalized citation recommendation network representation Bibliographic network

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GB/T 7714 Cai, Xiaoyan , Zheng, Yu , Yang, Libin et al. Bibliographic Network Representation Based Personalized Citation Recommendation [J]. | IEEE ACCESS , 2019 , 7 : 457-467 .
MLA Cai, Xiaoyan et al. "Bibliographic Network Representation Based Personalized Citation Recommendation" . | IEEE ACCESS 7 (2019) : 457-467 .
APA Cai, Xiaoyan , Zheng, Yu , Yang, Libin , Dai, Tao , Guo, Lantian . Bibliographic Network Representation Based Personalized Citation Recommendation . | IEEE ACCESS , 2019 , 7 , 457-467 .
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Joint Model Feature Regression and Topic Learning for Global Citation Recommendation SCIE
期刊论文 | 2019 , 7 , 1706-1720 | IEEE ACCESS
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Citation recommendation has gained increasing attention in recent years. In practice, researchers usually prefer to cite the most topic-relevant articles. Nevertheless, how to model the implicit correlations between topics and citations is still a challenging task. In this paper, we propose a novel citation recommendation model, called TopicCite, which mines such fine-grained correlations. We extract various citation features from citation network, and integrate the learning process of feature regression with topic modeling. At the recommendation stage, we expand the folding-in process by adding the topic influence of papers that correlated with user-provided information. TopicCite can also be considered a technique for extracting topic-related citation features from manually defined citation features, which can essentially improve the granularity of pre-extracted features. In addition, the unsupervised topic model is supervised and mutually reinforced by abundant citation features in TopicCite; thus, the proposed model can also extract more reliable topic distributions from citation data, which brings a new perspective to topic discovery on linked data. The experimental results on the AAN and DBLP datasets demonstrate that our model is competitive with the state-of-the-art methods.

Keyword :

Citation recommendation feature regression topic model

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GB/T 7714 Dai, Tao , Zhu, Li , Wang, Yifan et al. Joint Model Feature Regression and Topic Learning for Global Citation Recommendation [J]. | IEEE ACCESS , 2019 , 7 : 1706-1720 .
MLA Dai, Tao et al. "Joint Model Feature Regression and Topic Learning for Global Citation Recommendation" . | IEEE ACCESS 7 (2019) : 1706-1720 .
APA Dai, Tao , Zhu, Li , Wang, Yifan , Zhang, Hongfei , Cai, Xiaoyan , Zheng, Yu . Joint Model Feature Regression and Topic Learning for Global Citation Recommendation . | IEEE ACCESS , 2019 , 7 , 1706-1720 .
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Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision Scopus SSCI SCIE
期刊论文 | 2019 , 83 , 1-13 | Omega (United Kingdom)
WoS CC Cited Count: 2 SCOPUS Cited Count: 1
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© 2018 Elsevier Ltd. We propose a new multiple criteria decision aiding approach for market segmentation that integrates preference analysis and segmentation decision within a unified framework. The approach employs an additive value function as the preference model and requires consumers to provide pairwise comparisons of some products as the preference information. To analyze each consumer's preferences, the approach applies the disaggregation paradigm and the stochastic multicriteria acceptability analysis to derive a set of value functions according to the preference information provided by each consumer. Then, each consumer's preferences can be represented by the distribution of possible rankings of products and associated support degrees by applying the derived value functions. On the basis of preference analysis, a new metric is proposed to measure the similarity between preferences of different consumers, and a hierarchical clustering algorithm is developed to perform market segmentation. To help firms serve consumers from different segments with targeted marketing policies and appropriate products, the approach proposes to work out a representative value function and the univocal ranking of products for each consumer so that products that rank in the front of the list can be presented to her/him. Finally, an illustrative example of a market segmentation problem details the application of the proposed approach.

Keyword :

Clustering analysis Market segmentation Multiple criteria decision aiding Preference modeling

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GB/T 7714 Liu, Jiapeng , Liao, Xiuwu , Huang, Wei et al. Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision [J]. | Omega (United Kingdom) , 2019 , 83 : 1-13 .
MLA Liu, Jiapeng et al. "Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision" . | Omega (United Kingdom) 83 (2019) : 1-13 .
APA Liu, Jiapeng , Liao, Xiuwu , Huang, Wei , Liao, Xianzhao . Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision . | Omega (United Kingdom) , 2019 , 83 , 1-13 .
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Red Blood Cell Detection by the Improved Two-Layer Watershed Segmentation Method with a Full Convolutional Neural Network SCIE
期刊论文 | 2018 , 8 (1) , 50-54 | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
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Abstract :

Identifying cells in an image (cell segmentation) is essential for quantitative single-cell biology. The development of automatic medical image analysis of erythrocyte morphology has simplified the diagnosis of many diseases and combined a good reliability with high performance. However, in computational molecular biology, the elaboration of reliable and fully automated image analysis techniques for red blood cells imaging is still quite problematic. In this respect, quite lucrative is the watershed transformation concept, which can be utilized in image segmentation to generate partitions of the image corresponding to objects of interest. This approach is used in the current study, which presents a two-layer red blood cells detection framework, including a full convolutional neural network to extract the candidate cell regions with about 97% accuracy rate, and a novel labeled watershed method based on the morphology label and conditional skeleton extraction for improving the overlapped cells' segmentation. It is shown that the proposed method successfully extracts the red blood candidate regions, including single and overlapped ones. A comparative analysis of the proposed detection method and several other general methods was performed. The experimental results obtained indicate that the proposed framework is robust and accurate, with the cell extracting ratio over 87.76% accuracy.

Keyword :

Full Convolutional Neural Network Red Blood Cells Cell Segmentation Conditional Skeleton Watershed Algorithm

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GB/T 7714 Jiang, Peilin , Zhang, Xuetao , Wang, Fei . Red Blood Cell Detection by the Improved Two-Layer Watershed Segmentation Method with a Full Convolutional Neural Network [J]. | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS , 2018 , 8 (1) : 50-54 .
MLA Jiang, Peilin et al. "Red Blood Cell Detection by the Improved Two-Layer Watershed Segmentation Method with a Full Convolutional Neural Network" . | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 8 . 1 (2018) : 50-54 .
APA Jiang, Peilin , Zhang, Xuetao , Wang, Fei . Red Blood Cell Detection by the Improved Two-Layer Watershed Segmentation Method with a Full Convolutional Neural Network . | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS , 2018 , 8 (1) , 50-54 .
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A Novel Prediction of High-Risk Schizophrenia in Neonates Using Reconstructed Surface and Local Structure in MR Image SCIE
期刊论文 | 2018 , 8 (1) , 9-15 | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
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Schizophrenia is a severe mental disorder associated with delicate aberrant cortical. Currently, many methods which have been proposed for identifying possible abnormalities of surface area or cortical thickness in the high-risk neonates, have made initial progress driven by the techniques for neonates brain Magnetic Resonance (MR) image processing. However, it is in the initial study of neonates high-risk schizophrenia prediction that their methods have few achieve satisfactory accuracy because they only focus on the cortical reconstructed surface characteristic. The local structural texture can contribute the classification mode for prediction, but little attention to cortical structured MR image based feature was paid. To this end, we present a novel framework that jointed surface feature from reconstructed surface with 3D Haar-like features from structured MR image by SCAD SVM. We used this hybrid feature to train the SVM mode for neonates high-risk schizophrenia prediction. In the experiment, our method shows significant performance advance with an improvement of 8.5% in the accuracy rate on a challenging neonates high-risk schizophrenia prediction application.

Keyword :

Hybrid Features Schizophrenia Neonates Prediction SCAD SVM

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GB/T 7714 Fan, Caili , Jiang, Peilin , Chen, Lei et al. A Novel Prediction of High-Risk Schizophrenia in Neonates Using Reconstructed Surface and Local Structure in MR Image [J]. | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS , 2018 , 8 (1) : 9-15 .
MLA Fan, Caili et al. "A Novel Prediction of High-Risk Schizophrenia in Neonates Using Reconstructed Surface and Local Structure in MR Image" . | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 8 . 1 (2018) : 9-15 .
APA Fan, Caili , Jiang, Peilin , Chen, Lei , Wang, Fei , Yang, Haiwei . A Novel Prediction of High-Risk Schizophrenia in Neonates Using Reconstructed Surface and Local Structure in MR Image . | JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS , 2018 , 8 (1) , 9-15 .
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Capturing Car-Following Behaviors by Deep Learning EI SCIE Scopus
期刊论文 | 2018 , 19 (3) , 910-920 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
WoS CC Cited Count: 3 SCOPUS Cited Count: 6
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Abstract :

In this paper, we propose a deep neural network-based car-following model that has two distinctive properties. First, unlike most existing car-following models that take only the instantaneous velocity, velocity difference, and position difference as inputs, this new model takes the velocities, velocity differences, and position differences that were observed in the last few time intervals as inputs. That is, we assume that drivers' actions are temporally dependent in this model and try to embed prediction capability or memory effect of human drivers in a natural and efficient way. Second, this car-following model is built in a data-driven way, in which we reduce human interference to the minimum degree. Specially, we use recently developing deep neural networks rather than conventional neural networks to establish the model, since deep learning technique provides us more flexibility and accuracy to describe complicated human actions. Tests on empirical trajectory records show that this deep neural network-based car-following model yield significantly higher simulation accuracy than existing car-following models. All these findings provide a novel way to study traffic flow theory and traffic simulations.

Keyword :

recurrent neural network (RNN) deep learning Microscopic car-following model gated recurrent unit (GRU) neural networks

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GB/T 7714 Wang, Xiao , Jiang, Rui , Li, Li et al. Capturing Car-Following Behaviors by Deep Learning [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2018 , 19 (3) : 910-920 .
MLA Wang, Xiao et al. "Capturing Car-Following Behaviors by Deep Learning" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 19 . 3 (2018) : 910-920 .
APA Wang, Xiao , Jiang, Rui , Li, Li , Lin, Yilun , Zheng, Xinhu , Wang, Fei-Yue . Capturing Car-Following Behaviors by Deep Learning . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2018 , 19 (3) , 910-920 .
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