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Formation mechanism of A-site complex perovskite (Ba, Sr)TiO3 microplatelets EI Scopus SCIE
期刊论文 | 2019 , 45 (2) , 2667-2669 | Ceramics International
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Abstract :

A-site complex perovskite (Ba, Sr)TiO3 microplatelets with high aspect ratio were synthesized successfully by molten salt synthesis (MSS) and topochemical microcrystal conversion(TMC) technique. In the process of synthesis, Bi4Ti3O12 (BiT) platelets firstly prepared by MSS method were used as precursor and powdered SrCO3-BaCO3 mixture were employed as reactants in NaCl flux at 1000 °C. The effects of BiT-to-SrCO3-to-BaCO3 molar ratios on phase and microstructure of the resultant products were investigated. The synthetic (Ba0.5Sr0.5)TiO3 platelets would be effective templates for producing highly textured ceramics using the templated grain growth(TGG) method. © 2018 Elsevier Ltd and Techna Group S.r.l.

Keyword :

Complex perovskites Formation mechanism High aspect ratio Molten salt synthesis Phase and microstructures Powder Technology Templated grain growth Textured ceramics

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GB/T 7714 Wei, Dandan , Li, Wenxuan . Formation mechanism of A-site complex perovskite (Ba, Sr)TiO3 microplatelets [J]. | Ceramics International , 2019 , 45 (2) : 2667-2669 .
MLA Wei, Dandan 等. "Formation mechanism of A-site complex perovskite (Ba, Sr)TiO3 microplatelets" . | Ceramics International 45 . 2 (2019) : 2667-2669 .
APA Wei, Dandan , Li, Wenxuan . Formation mechanism of A-site complex perovskite (Ba, Sr)TiO3 microplatelets . | Ceramics International , 2019 , 45 (2) , 2667-2669 .
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A new unsupervised feature selection algorithm using similarity-based feature clustering EI Scopus SCIE
期刊论文 | 2019 , 35 (1) , 2-22 | Computational Intelligence
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Abstract :

Unsupervised feature selection is an important problem, especially for high-dimensional data. However, until now, it has been scarcely studied and the existing algorithms cannot provide satisfying performance. Thus, in this paper, we propose a new unsupervised feature selection algorithm using similarity-based feature clustering, Feature Selection-based Feature Clustering (FSFC). FSFC removes redundant features according to the results of feature clustering based on feature similarity. First, it clusters the features according to their similarity. A new feature clustering algorithm is proposed, which overcomes the shortcomings of K-means. Second, it selects a representative feature from each cluster, which contains most interesting information of features in the cluster. The efficiency and effectiveness of FSFC are tested upon real-world data sets and compared with two representative unsupervised feature selection algorithms, Feature Selection Using Similarity (FSUS) and Multi-Cluster-based Feature Selection (MCFS) in terms of runtime, feature compression ratio, and the clustering results of K-means. The results show that FSFC can not only reduce the feature space in less time, but also significantly improve the clustering performance of K-means. © 2018 Wiley Periodicals, Inc.

Keyword :

clustering Feature clustering Feature compression Feature similarities High dimensional data Interesting information Redundant features Unsupervised feature selection

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GB/T 7714 Zhu, Xiaoyan , Wang, Yu , Li, Yingbin et al. A new unsupervised feature selection algorithm using similarity-based feature clustering [J]. | Computational Intelligence , 2019 , 35 (1) : 2-22 .
MLA Zhu, Xiaoyan et al. "A new unsupervised feature selection algorithm using similarity-based feature clustering" . | Computational Intelligence 35 . 1 (2019) : 2-22 .
APA Zhu, Xiaoyan , Wang, Yu , Li, Yingbin , Tan, Yonghui , Wang, Guangtao , Song, Qinbao . A new unsupervised feature selection algorithm using similarity-based feature clustering . | Computational Intelligence , 2019 , 35 (1) , 2-22 .
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Architectural Exploration to Address the Reliability Challenges for ReRAM-Based Buffer in SSD EI Scopus SCIE
期刊论文 | 2019 , 66 (1) , 226-238 | IEEE Transactions on Circuits and Systems I: Regular Papers
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Abstract :

Hybrid solid state drive based on ReRAM and NAND flash technologies has shown promising performance and energy efficiency. In this application, ReRAM is mainly used as a non-volatile buffer to hold recently accessed data pages or address mapping information. The previous studies on the ReRAM-based buffer mainly focus on performance and efficiency improvement, while reliability issues are not taken into consideration. Nevertheless, according to our quantitative evaluation, the limited endurance and random bit errors pose challenges to ReRAM-based buffer design. For example, without wear leveling, the raw lifetime of ReRAM-based SSD buffer may be as low as 0.02 year for some specific I/O traces. Therefore, we propose two efficient architecture techniques, i.e., multi-bloom-filter-based wear leveling and hybrid error protection, to improve the lifetime and reduce the error protection cost of ReRAM-based buffer, respectively. Simulation results demonstrate that the proposed wear leveling technique can extend the lifetime of ReRAM-based buffer by $34.7x$ on average. The proposed hybrid error protection scheme can improve the response time by at least 4.2&#x0025; compared with other error protection schemes. IEEE

Keyword :

Address mappings Efficiency improvement Efficient architecture Non-volatile memory Prototypes Quantitative evaluation Random bit errors Solid state drives

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GB/T 7714 Zhao, Xiaoqing , Sun, Hongbin , Liu, Longjun et al. Architectural Exploration to Address the Reliability Challenges for ReRAM-Based Buffer in SSD [J]. | IEEE Transactions on Circuits and Systems I: Regular Papers , 2019 , 66 (1) : 226-238 .
MLA Zhao, Xiaoqing et al. "Architectural Exploration to Address the Reliability Challenges for ReRAM-Based Buffer in SSD" . | IEEE Transactions on Circuits and Systems I: Regular Papers 66 . 1 (2019) : 226-238 .
APA Zhao, Xiaoqing , Sun, Hongbin , Liu, Longjun , Yang, Yang , Dai, Liangliang , Wu, Xiulong et al. Architectural Exploration to Address the Reliability Challenges for ReRAM-Based Buffer in SSD . | IEEE Transactions on Circuits and Systems I: Regular Papers , 2019 , 66 (1) , 226-238 .
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Decade progress of palmprint recognition: A brief survey EI Scopus CPCI-S SCIE
期刊论文 | 2019 , 328 , 16-28 | Neurocomputing
SCOPUS Cited Count: 1
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Abstract :

As an advanced research topic in biometrics techniques, palmprint recognition has been fully studied for more than 20 years. Due to its superiority to other biological features, i.e. high recognition accuracy and convenience for practical application, many research achievements on palmprint have emerged recently, especially in the past decade. This paper presents a comprehensive overview of recent research progress of palmprint recognition as well as the basic background knowledge for it. In addition, it mainly focuses on data acquisition, database, preprocessing, feature extraction, matching and fusion. Ultimately, we discuss the challenges and future perspectives in palmprint recognition for further works. © 2018

Keyword :

Advanced researches Back-ground knowledge Biological features Future perspectives Matching Recognition accuracy Region of interest Research achievements

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GB/T 7714 Zhong, Dexing , Du, Xuefeng , Zhong, Kuncai . Decade progress of palmprint recognition: A brief survey [J]. | Neurocomputing , 2019 , 328 : 16-28 .
MLA Zhong, Dexing et al. "Decade progress of palmprint recognition: A brief survey" . | Neurocomputing 328 (2019) : 16-28 .
APA Zhong, Dexing , Du, Xuefeng , Zhong, Kuncai . Decade progress of palmprint recognition: A brief survey . | Neurocomputing , 2019 , 328 , 16-28 .
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Robust Seismic Volumetric Dip Estimation Combining Structure Tensor and Multiwindow Technology EI Scopus SCIE
期刊论文 | 2019 , 57 (1) , 395-405 | IEEE Transactions on Geoscience and Remote Sensing
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Abstract :

As one type of important seismic geometric attributes, the seismic volumetric dip is extensively used to assist interpretation of horizons, faults, and other geologic structures in 3-D seismic data. In this paper, we mainly focus on estimating seismic volumetric dip robustly and try to reduce the influences of amplitude's lateral changes, faults, and other discontinuous structures. We first use the instantaneous phase (IP) as one fundamental data set to reduce the influence of amplitude's lateral variation. Second, we construct structure tensor (ST) on IP and apply eigendecomposition on corresponding ST covariance matrix to obtain three eigenvalues and corresponding eigenvectors. Then, the seismic volumetric dip can be calculated from the dominant eigenvector, and a similarity measure can be constructed based on these three eigenvalues. Third, based on the similarity measure, we reduce the influence of fault on dip estimation by using multiwindow technology if the analyzing window spans a fault. Finally, we applied our method to three synthetic data examples and two field data examples. The results of seismic volumetric dip and curvature estimation verify that the proposed method has better antinoise and antifault performance comparing with the corresponding sophisticated method in commercial software and the conventional ST-based method. IEEE

Keyword :

Gradient structure tensors Instantaneous phase Multi-window Seismic curvature seismic volumetric dip

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GB/T 7714 Wang, Xiaokai , Chen, Wenchao , Zhu, Zhenyu . Robust Seismic Volumetric Dip Estimation Combining Structure Tensor and Multiwindow Technology [J]. | IEEE Transactions on Geoscience and Remote Sensing , 2019 , 57 (1) : 395-405 .
MLA Wang, Xiaokai et al. "Robust Seismic Volumetric Dip Estimation Combining Structure Tensor and Multiwindow Technology" . | IEEE Transactions on Geoscience and Remote Sensing 57 . 1 (2019) : 395-405 .
APA Wang, Xiaokai , Chen, Wenchao , Zhu, Zhenyu . Robust Seismic Volumetric Dip Estimation Combining Structure Tensor and Multiwindow Technology . | IEEE Transactions on Geoscience and Remote Sensing , 2019 , 57 (1) , 395-405 .
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Research and application of digital oilfield cloud computing EI Scopus CPCI-S
会议论文 | 2019 , 595-599 | 7th International Field Exploration and Development Conference, IFEDC 2017
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Abstract :

As core of back-end system of digital oilfield framework, Reservoir Decision-Making Supporting System (RDMS) of Changqing Oilfield Company contains variety of databases, softwares, and large amount of users. The management of hardware, software resources, and IT operations faces new challenges. Due to difficulties above, a working mentality of RDMS cloud service center is proposed according to the advantage of could computing in system infrastructure, user desktop, and data storage. Based on recent RDMS resource situation, the center mainly focuses on establishment of cloud computing resource pool, virtual desktop access, and cloud storage. Besides, application in the field conveys that utilization ratio of hardware increases from 10 to 70%, bearing capacity improves three times, as well as it greatly improves the implementation efficiency of RDMS software. Problems such as low utilization ratio of hardware resources, fussy initialization of RDMS plug-ins, and security of intermediate outcomes storage are solved. In the meanwhile, cloud service center realizes centralized management of hardware resource, dynamic allocation of users’ need, unity of program development, integrated application of professional softwares. Finally, technical support of cloud computing facilitation in other oilfield business area is provided. © Springer Nature Singapore Pte Ltd. 2019.

Keyword :

Centralized management Changqing oilfield companies Cloud storages Integrated applications Professional software Research and application Server resources System infrastructure

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GB/T 7714 Jiao, Yang , Shi, Yujiang , Wang, Juan et al. Research and application of digital oilfield cloud computing [C] . 2019 : 595-599 .
MLA Jiao, Yang et al. "Research and application of digital oilfield cloud computing" . (2019) : 595-599 .
APA Jiao, Yang , Shi, Yujiang , Wang, Juan , Xie, Shan , Liang, Lixing . Research and application of digital oilfield cloud computing . (2019) : 595-599 .
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Compressive sensing image recovery using dictionary learning and shape-adaptive DCT thresholding. PubMed Scopus SCIE
期刊论文 | 2019 , 55 , 60-71 | Magnetic resonance imaging
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Abstract :

Compressed sensing (CS) has shown to be a successful technique for image recovery. Designing an effective regularization term reflecting the image sparse prior information plays a critical role in this field. Dictionary learning (DL) strategy alleviates the drawback of fixed bases. But the structure information of the image is easy to be blurred in complex regions due to the absence of sparsity in dictionary learning. This paper proposes a novel joint dictionary learning and Shape-Adaptive DCT (SADCT) thresholding method. We first propose to exploit sparsity of image in shape-adaptive regions, which is beneficial to medical images of complex textures. In this framework, the local sparsity depicts the smoothness redundancies exploited by dictionary learning. Moreover, the sparsity is enhanced especially in detail areas by the newly introduced SADCT thresholding. The attenuated SADCT coefficients are used to reconstruct a local estimation of the signal within the adaptive-shape support. Image is represented sparser in SADCT transform domain and the details of the image information can be kept with a much larger probability. Based on split Bregman iterations, an efficient alternating minimization algorithm is developed to solve the proposed CS medical image recovery problem. The results of various experiments on MR images consistently demonstrate that the proposed algorithm efficiently recovers MR images and shows advantages over the current leading CS reconstruction approaches.

Keyword :

Image reconstruction Dictionary learning Splitting Bregman iteration Shape-adaptive DCT Compressed sensing Sparse representation

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GB/T 7714 Du Dong , Pan Zhibin , Zhang Penghui et al. Compressive sensing image recovery using dictionary learning and shape-adaptive DCT thresholding. [J]. | Magnetic resonance imaging , 2019 , 55 : 60-71 .
MLA Du Dong et al. "Compressive sensing image recovery using dictionary learning and shape-adaptive DCT thresholding." . | Magnetic resonance imaging 55 (2019) : 60-71 .
APA Du Dong , Pan Zhibin , Zhang Penghui , Li Yuxin , Ku Weiping . Compressive sensing image recovery using dictionary learning and shape-adaptive DCT thresholding. . | Magnetic resonance imaging , 2019 , 55 , 60-71 .
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Differential Dual-Band Superconducting Bandpass Filter Using Multimode Square Ring Loaded Resonators With Controllable Bandwidths EI SCIE
期刊论文 | 2019 , 67 (2) , 726-737 | IEEE Transactions on Microwave Theory and Techniques
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Abstract :

In this paper, a fourth-order dual-band high-temperature superconducting (HTS) differential bandpass filter (BPF) with controllable midband frequencies and bandwidths is developed by using modified multimode square ring loaded resonators (SRLRs). The differential-mode (DM) bisection and common-mode (CM) bisection of the modified SRLR are analyzed by using the even- and odd-mode method twice, and the corresponding resonant properties are obtained. With a proper design of the modified SRLR, two lowest DM resonances are chosen to construct two DM passbands with high in-band CM suppression. The DM resonances can be adjusted flexibly after adding tunable patches to the square ring. Meanwhile, the internal coupling between two modified SRLRs can be controlled separately by using two geometrical parameters. Consequently, the proposed dual-band BPF can achieve independent control of both the midband frequencies and the bandwidths of its two passbands. Moreover, a wideband CM suppression is realized by a combined use of an appropriately selected feeding structure and a frequency discrepancy technique. A fourth-order dual-band differential BPF is designed with two passbands operating at 2.325 and 4.900 GHz, respectively. The filter is fabricated using HTS YBCO thin films on a MgO substrate. Good agreement between the simulated and measured frequency responses are observed, verifying well the proposed structure and design method. IEEE

Keyword :

Band-pass filter (BPF) differential Dual Band High temperature superconducting Loaded resonators

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GB/T 7714 Ren, Baoping , Ma, Zhewang , Liu, Haiwen et al. Differential Dual-Band Superconducting Bandpass Filter Using Multimode Square Ring Loaded Resonators With Controllable Bandwidths [J]. | IEEE Transactions on Microwave Theory and Techniques , 2019 , 67 (2) : 726-737 .
MLA Ren, Baoping et al. "Differential Dual-Band Superconducting Bandpass Filter Using Multimode Square Ring Loaded Resonators With Controllable Bandwidths" . | IEEE Transactions on Microwave Theory and Techniques 67 . 2 (2019) : 726-737 .
APA Ren, Baoping , Ma, Zhewang , Liu, Haiwen , Guan, Xuehui , Wang, Xiaolong , Wen, Pin et al. Differential Dual-Band Superconducting Bandpass Filter Using Multimode Square Ring Loaded Resonators With Controllable Bandwidths . | IEEE Transactions on Microwave Theory and Techniques , 2019 , 67 (2) , 726-737 .
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mrMoulder: A recommendation-based adaptive parameter tuning approach for big data processing platform EI SCIE
期刊论文 | 2019 , 93 , 570-582 | Future Generation Computer Systems
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Abstract :

Nowadays the world has entered the big data era. Big data processing platforms, such as Hadoop and Spark, are increasingly adopted by many applications, in which there are numerous parameters that can be tuned to improve processing performance for big data platform operators. However, due to the large number of these parameters and the complex relationship among them, it is very time-consuming to manually tune parameters. Therefore, it is a challenge to automatically configure parameters as quickly as possible to optimize the performance of the current job. Existing auto-tuning methods often take a certain time before job runs to get the optimal configuration, which would increase the job's total processing time and reduce the overall efficiency of cluster. In this paper, we propose an adaptive tuning framework, mrMoulder, to recommend a near-optimal configuration for the new job in a short time. mrMoulder sets a self-extending configuration repository and a collaborative filtering based recommendation engine, to speed up the process of optimizing parameter configuration. We have deployed mrMoulder in a Hadoop cluster, and the experiment results have demonstrated that, for a new big data application, the recommend time of mrMoulder is only 20% to 30% of that for the existing auto-tuning methods, while the recommendation quality remains almost unchanged. © 2018 Elsevier B.V.

Keyword :

Big data applications Complex relationships Online-Configurations Optimizing parameters Parameter-tuning Performance optimizations Processing performance Total processing time

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GB/T 7714 Cai, Lin , Qi, Yong , Wei, Wei et al. mrMoulder: A recommendation-based adaptive parameter tuning approach for big data processing platform [J]. | Future Generation Computer Systems , 2019 , 93 : 570-582 .
MLA Cai, Lin et al. "mrMoulder: A recommendation-based adaptive parameter tuning approach for big data processing platform" . | Future Generation Computer Systems 93 (2019) : 570-582 .
APA Cai, Lin , Qi, Yong , Wei, Wei , Wu, Jinsong , Li, Jingwei . mrMoulder: A recommendation-based adaptive parameter tuning approach for big data processing platform . | Future Generation Computer Systems , 2019 , 93 , 570-582 .
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Central pixel selection strategy based on local gray-value distribution by using gradient information to enhance LBP for texture classification EI SCIE
期刊论文 | 2019 , 120 , 319-334 | Expert Systems with Applications
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Abstract :

Local binary pattern (LBP) has been successfully used in computer vision and pattern recognition applications, such as biomedical image analysis, remote sensing and image retrieval. However, the current LBP-based features, which assign a fixed sampling radius for all pixels in a single scale, completely ignore the fact that different central pixels actually have different local gray-value distributions and the proper sampling radius should be different for pixels. In this paper, we propose a novel and effective central pixel selection (CPS) strategy by using gradient information to classify central pixels of a texture image into different classes based on their local gray-value distributions. Then, we introduce this CPS strategy into the LBP framework and assign an adaptive sampling radius for each central pixel according to the class it belongs to. As a preprocessing step of LBP framework, this CPS strategy can also be integrated into any other LBP variants so as to extract more effective local texture features. Extensive experiments on five representative texture databases of Outex, UIUC, CUReT, UMD and ALOT validate the efficiency of the proposed central pixel selection (CPS) strategy, which can achieve almost 16% improvement over the original LBP and 1%–10% improvement compared with the best classification accuracy among other benchmarked state-of-the-art LBP variants. © 2018 Elsevier Ltd

Keyword :

Central pixel class Gray value Local binary pattern (LBP) Pixel selection Texture classification

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GB/T 7714 Pan, Zhibin , Wu, Xiuquan , Li, Zhengyi . Central pixel selection strategy based on local gray-value distribution by using gradient information to enhance LBP for texture classification [J]. | Expert Systems with Applications , 2019 , 120 : 319-334 .
MLA Pan, Zhibin et al. "Central pixel selection strategy based on local gray-value distribution by using gradient information to enhance LBP for texture classification" . | Expert Systems with Applications 120 (2019) : 319-334 .
APA Pan, Zhibin , Wu, Xiuquan , Li, Zhengyi . Central pixel selection strategy based on local gray-value distribution by using gradient information to enhance LBP for texture classification . | Expert Systems with Applications , 2019 , 120 , 319-334 .
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