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Search Results: 1 - 10 of 104641 matches for " Chunhua Zhang "
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Exploration and Practice of the Practical Teaching Curriculum System for Cultivating Applied and Innovative Undergraduate Talents  [PDF]
Chunhua He, Haiyan Zhang, Aixiang Wei
Creative Education (CE) , 2012, DOI: 10.4236/ce.2012.37B047
Abstract: Aiming at shortcomings in the current system of practice teaching in high schools especially in regional high schools, a system of practice teaching that fit current cultivation of practical and innovative talents is explored in education. In accordance with the progressive regularity of ability cultivation, the system of practice teaching is divided into four levels: basic practice, basic experiment, advanced practice and comprehensive innovation. And this characteristic system of practice teaching is built up to cultivate practical and innovative talents in grassroots who can meet the requirements of current socio-economic development.
Planar Symmetric Concave Central Configurations in Four-body Problem
Chunhua Deng,Shiqing Zhang
Physics , 2012,
Abstract: In this paper, we consider the problem: given a symmetric concave configuration of four bodies, under what conditions is it possible to choose positive masses which make it central. We show that there are some regions in which no central configuration is possible for positive masses. Conversely, for any configuration in the complement of the union of these regions, it is always possible to choose positive masses to make the configuration central.
Plant Vacuole Morphology and Vacuolar Trafficking
Chunhua Zhang,Glenn R. Hicks
Frontiers in Plant Science , 2014, DOI: 10.3389/fpls.2014.00476
Abstract: Plant vacuoles are essential organelles for plant growth and development, and have multiple functions. Vacuoles are highly dynamic and pleiomorphic, and their size varies depending on the cell type and growth conditions. Vacuoles compartmentalize different cellular components such as proteins, sugars, ions and other secondary metabolites and play critical roles in plants response to different biotic/abiotic signaling pathways. In this review, we will summarize the patterns of changes in vacuole morphology in certain cell types, our understanding of the mechanisms of plant vacuole biogenesis, and the role of SNAREs and Rab GTPases in vacuolar trafficking.
Minimum Amount of Extracting Solvent of a Separation of Two Rare Earth Components  [PDF]
Fuxiang Cheng, Sheng Wu, Yan Liu, Songling Wang, Bo Zhang, Chunsheng Liao, Chunhua Yan
Advances in Materials Physics and Chemistry (AMPC) , 2014, DOI: 10.4236/ampc.2014.412030
Abstract: A significant development in the theory of countercurrent extraction will be presented in this article. New expressions of the term in countercurrent extraction process analysis, “Adjacent Stage Impurity Ratio” (ASIR), are deduced. Furthermore, based on the term together with mass balance and extraction equilibrium, the conditions where a given countercurrent extraction separation operation can have minimum amounts of both extracting solvent and scrubbing agent solution can be estimated, and the equations of the two minimum amounts can be deduced. It was found that the equations for a two-component separation using a single aqueous or organic feed are exactly the same as they appeared in the theory initially established in 1970s. Unlike its earlier version, the present derivation does not involve feed-stage-composition hypothesis, and also has the advantage of dealing with a double-feed system where both aqueous and organic feeds are simultaneously employed whereas the earlier theory can only analyze a separation using a single aqueous or organic feed.
Poincaré series and rational cohomology rings of Kac-Moody groups and their flag manifolds
Zhao Xu-an,Jin Chunhua,Zhang Jimin
Mathematics , 2013,
Abstract: In this paper, we study the rational cohomology rings of indefinite Kac-Moody groups and their flag manifolds. By extracting the information of cohomology from the Poincar\'{e} series, we are able to determine the rational cohomology rings of Kac-Moody groups and their flag manifolds. Since Kac-Moody groups and their flag manifolds are rational formal, we also determine their rational homotopy groups and rational homotopy types.
Face Detection with Effective Feature Extraction
Sakrapee Paisitkriangkrai,Chunhua Shen,Jian Zhang
Computer Science , 2010,
Abstract: There is an abundant literature on face detection due to its important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detector, Haar-like features have been adopted as the method of choice for frontal face detection. In this work, we show that simple features other than Haar-like features can also be applied for training an effective face detector. Since, single feature is not discriminative enough to separate faces from difficult non-faces, we further improve the generalization performance of our simple features by introducing feature co-occurrences. We demonstrate that our proposed features yield a performance improvement compared to Haar-like features. In addition, our findings indicate that features play a crucial role in the ability of the system to generalize.
Efficiently Learning a Detection Cascade with Sparse Eigenvectors
Chunhua Shen,Sakrapee Paisitkriangkrai,Jian Zhang
Computer Science , 2009,
Abstract: In this work, we first show that feature selection methods other than boosting can also be used for training an efficient object detector. In particular, we introduce Greedy Sparse Linear Discriminant Analysis (GSLDA) \cite{Moghaddam2007Fast} for its conceptual simplicity and computational efficiency; and slightly better detection performance is achieved compared with \cite{Viola2004Robust}. Moreover, we propose a new technique, termed Boosted Greedy Sparse Linear Discriminant Analysis (BGSLDA), to efficiently train a detection cascade. BGSLDA exploits the sample re-weighting property of boosting and the class-separability criterion of GSLDA.
Incremental Training of a Detector Using Online Sparse Eigen-decomposition
Sakrapee Paisitkriangkrai,Chunhua Shen,Jian Zhang
Computer Science , 2010, DOI: 10.1109/TIP.2010.2053548
Abstract: The ability to efficiently and accurately detect objects plays a very crucial role for many computer vision tasks. Recently, offline object detectors have shown a tremendous success. However, one major drawback of offline techniques is that a complete set of training data has to be collected beforehand. In addition, once learned, an offline detector can not make use of newly arriving data. To alleviate these drawbacks, online learning has been adopted with the following objectives: (1) the technique should be computationally and storage efficient; (2) the updated classifier must maintain its high classification accuracy. In this paper, we propose an effective and efficient framework for learning an adaptive online greedy sparse linear discriminant analysis (GSLDA) model. Unlike many existing online boosting detectors, which usually apply exponential or logistic loss, our online algorithm makes use of LDA's learning criterion that not only aims to maximize the class-separation criterion but also incorporates the asymmetrical property of training data distributions. We provide a better alternative for online boosting algorithms in the context of training a visual object detector. We demonstrate the robustness and efficiency of our methods on handwriting digit and face data sets. Our results confirm that object detection tasks benefit significantly when trained in an online manner.
Unsupervised Feature Learning for Dense Correspondences across Scenes
Chao Zhang,Chunhua Shen,Tingzhi Shen
Computer Science , 2015,
Abstract: We propose a fast, accurate matching method for estimating dense pixel correspondences across scenes. It is a challenging problem to estimate dense pixel correspondences between images depicting different scenes or instances of the same object category. While most such matching methods rely on hand-crafted features such as SIFT, we learn features from a large amount of unlabeled image patches using unsupervised learning. Pixel-layer features are obtained by encoding over the dictionary, followed by spatial pooling to obtain patch-layer features. The learned features are then seamlessly embedded into a multi-layer match- ing framework. We experimentally demonstrate that the learned features, together with our matching model, outperforms state-of-the-art methods such as the SIFT flow, coherency sensitive hashing and the recent deformable spatial pyramid matching methods both in terms of accuracy and computation efficiency. Furthermore, we evaluate the performance of a few different dictionary learning and feature encoding methods in the proposed pixel correspondences estimation framework, and analyse the impact of dictionary learning and feature encoding with respect to the final matching performance.
3-(Dihydroxyboryl)anilinium 6-carboxypyridine-2-carboxylate
Chunhua Ge,Xiangdong Zhang,Rui Zhang,Chenglong Zhang
Acta Crystallographica Section E , 2012, DOI: 10.1107/s1600536812031790
Abstract: In the anion of the title molecular salt, C6H9BNO2+·C7H4NO4 , the dihedral angles between the –COO2 and –CO2H groups and their attached ring are 4.02 (13) and 21.41 (10)°, respectively. The B atom in the cation adopts a syn–syn geometry and the dihedral angle between the –B(OH)2 group and its attached ring is 11.06 (5)°. In the crystal, O—H...O, N—H...O and N—H...N hydrogen bonds link the components into a three-dimensional network.
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