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Sample records for hierarchical feature maps

  1. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  2. Hierarchical Reverberation Mapping

    CERN Document Server

    Brewer, Brendon J

    2013-01-01

    Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag $\\tau$ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of $\\tau$ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass $M_{\\rm BH}$. A major difficulty with RM campaigns is the large amount of data needed to measure $\\tau$. Recently, Fine et al (2012) introduced a new approach to RM where the BLR light curve is sparsely sampled, but this is counteracted by observing a large sample of AGN, rather than a single system. The results are combined to infer properties of the sample of AGN. In this letter we implement this method using a hierarchical Bayesian model and contrast this with the results from the previous stacked cross-correlation technique. We find that our inferences are more precise and allow fo...

  3. Hierarchical Reverberation Mapping

    OpenAIRE

    Brendon J. Brewer; Elliott, Tom M.

    2013-01-01

    Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag $\\tau$ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of $\\tau$ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass $M_{\\rm BH}$. A major difficulty with RM campaigns is the large a...

  4. Hierarchical Gompertzian growth maps with application in astrophysics

    CERN Document Server

    De Martino, S

    2010-01-01

    The Gompertz model describes the growth in time of the size of significant quantities associated to a large number of systems, taking into account nonlinearity features by a linear equation satisfied by a nonlinear function of the size. Following this scheme, we introduce a class of hierarchical maps which describe discrete sequences of intermediate characteristic scales. We find the general solutions of the maps, which account for a rich set of possible phenomena. Eventually, we provide an important application, by showing that a map belonging to the class so introduced generates all the observed astrophysical length and mass scales.

  5. Mobile Robot Hierarchical Simultaneous Localization and Mapping Using Monocular Vision

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A hierarchical mobile robot simultaneous localization and mapping (SLAM) method that allows us to obtain accurate maps was presented. The local map level is composed of a set of local metric feature maps that are guaranteed to be statistically independent. The global level is a topological graph whose arcs are labeled with the relative location between local maps. An estimation of these relative locations is maintained with local map alignment algorithm, and more accurate estimation is calculated through a global minimization procedure using the loop closure constraint. The local map is built with Rao-Blackwellised particle filter (RBPF), where the particle filter is used to extending the path posterior by sampling new poses. The landmark position estimation and update is implemented through extended Kalman filter (EKF). Monocular vision mounted on the robot tracks the 3D natural point landmarks, which are structured with matching scale invariant feature transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-tree in the time cost of O(lbN). Experiment results on Pioneer mobile robot in a real indoor environment show the superior performance of our proposed method.

  6. Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

    Directory of Open Access Journals (Sweden)

    A. Kushki

    2009-02-01

    Full Text Available This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.

  7. Two-level hierarchical feature learning for image classification

    Institute of Scientific and Technical Information of China (English)

    Guang-hui SONG; Xiao-gang JIN; Gen-lang CHEN; Yan NIE

    2016-01-01

    In some image classifi cation tasks, similarities among different categories are different and the samples are usually misclassifi ed as highly similar categories. To distinguish highly similar categories, more specifi c features are required so that the classifi er can improve the classifi cation performance. In this paper, we propose a novel two-level hierarchical feature learning framework based on the deep convolutional neural network (CNN), which is simple and effective. First, the deep feature extractors of different levels are trained using the transfer learning method that fi ne-tunes the pre-trained deep CNN model toward the new target dataset. Second, the general feature extracted from all the categories and the specifi c feature extracted from highly similar categories are fused into a feature vector. Then the fi nal feature representation is fed into a linear classifi er. Finally, experiments using the Caltech-256, Oxford Flower-102, and Tasmania Coral Point Count (CPC) datasets demonstrate that the expression ability of the deep features resulting from two-level hierarchical feature learning is powerful. Our proposed method effectively increases the classifi cation accuracy in comparison with fl at multiple classifi cation methods.

  8. Using PSO-Based Hierarchical Feature Selection Algorithm

    Directory of Open Access Journals (Sweden)

    Zhiwei Ji

    2014-01-01

    Full Text Available Hepatocellular carcinoma (HCC is one of the most common malignant tumors. Clinical symptoms attributable to HCC are usually absent, thus often miss the best therapeutic opportunities. Traditional Chinese Medicine (TCM plays an active role in diagnosis and treatment of HCC. In this paper, we proposed a particle swarm optimization-based hierarchical feature selection (PSOHFS model to infer potential syndromes for diagnosis of HCC. Firstly, the hierarchical feature representation is developed by a three-layer tree. The clinical symptoms and positive score of patient are leaf nodes and root in the tree, respectively, while each syndrome feature on the middle layer is extracted from a group of symptoms. Secondly, an improved PSO-based algorithm is applied in a new reduced feature space to search an optimal syndrome subset. Based on the result of feature selection, the causal relationships of symptoms and syndromes are inferred via Bayesian networks. In our experiment, 147 symptoms were aggregated into 27 groups and 27 syndrome features were extracted. The proposed approach discovered 24 syndromes which obviously improved the diagnosis accuracy. Finally, the Bayesian approach was applied to represent the causal relationships both at symptom and syndrome levels. The results show that our computational model can facilitate the clinical diagnosis of HCC.

  9. Hierarchical Geometric Constraint Model for Parametric Feature Based Modeling

    Institute of Scientific and Technical Information of China (English)

    高曙明; 彭群生

    1997-01-01

    A new geometric constraint model is described,which is hierarchical and suitable for parametric feature based modeling.In this model,different levels of geometric information are repesented to support various stages of a design process.An efficient approach to parametric feature based modeling is also presented,adopting the high level geometric constraint model.The low level geometric model such as B-reps can be derived automatically from the hig level geometric constraint model,enabling designers to perform their task of detailed design.

  10. Modeling place field activity with hierarchical slow feature analysis

    Directory of Open Access Journals (Sweden)

    Fabian eSchoenfeld

    2015-05-01

    Full Text Available In this paper we present six experimental studies from the literature on hippocampal place cells and replicate their main results in a computational framework based on the principle of slowness. Each of the chosen studies first allows rodents to develop stable place field activity and then examines a distinct property of the established spatial encoding, namely adaptation to cue relocation and removal; directional firing activity in the linear track and open field; and results of morphing and stretching the overall environment. To replicate these studies we employ a hierarchical Slow Feature Analysis (SFA network. SFA is an unsupervised learning algorithm extracting slowly varying information from a given stream of data, and hierarchical application of SFA allows for high dimensional input such as visual images to be processed efficiently and in a biologically plausible fashion. Training data for the network is produced in ratlab, a free basic graphics engine designed to quickly set up a wide range of 3D environments mimicking real life experimental studies, simulate a foraging rodent while recording its visual input, and training & sampling a hierarchical SFA network.

  11. Occupancy Grid Map Merging Using Feature Maps

    Science.gov (United States)

    2010-11-01

    Gonzalez, “Toward a unified bayesian approach to hybrid metric-topological SLAM,” IEEE Transactions on Robotics , 24(2), April 2008, 259-270. [14] G...Risetti, C. Stachniss, and W. Burgard, “Improved Techniques for grid mapping with Rao-Blackwellized Particle Filter,” IEEE Transactions on Robotics , 23

  12. Hierarchical Multi-modal Image Registration by Learning Common Feature Representations.

    Science.gov (United States)

    Ge, Hongkun; Wu, Guorong; Wang, Li; Gao, Yaozong; Shen, Dinggang

    2015-10-05

    Mutual information (MI) has been widely used for registering images with different modalities. Since most inter-modality registration methods simply estimate deformations in a local scale, but optimizing MI from the entire image, the estimated deformations for certain structures could be dominated by the surrounding unrelated structures. Also, since there often exist multiple structures in each image, the intensity correlation between two images could be complex and highly nonlinear, which makes global MI unable to precisely guide local image deformation. To solve these issues, we propose a hierarchical inter-modality registration method by robust feature matching. Specifically, we first select a small set of key points at salient image locations to drive the entire image registration. Since the original image features computed from different modalities are often difficult for direct comparison, we propose to learn their common feature representations by projecting them from their native feature spaces to a common space, where the correlations between corresponding features are maximized. Due to the large heterogeneity between two high-dimension feature distributions, we employ Kernel CCA (Canonical Correlation Analysis) to reveal such non-linear feature mappings. Then, our registration method can take advantage of the learned common features to reliably establish correspondences for key points from different modality images by robust feature matching. As more and more key points take part in the registration, our hierarchical feature-based image registration method can efficiently estimate the deformation pathway between two inter-modality images in a global to local manner. We have applied our proposed registration method to prostate CT and MR images, as well as the infant MR brain images in the first year of life. Experimental results show that our method can achieve more accurate registration results, compared to other state-of-the-art image registration

  13. Harvesting geographic features from heterogeneous raster maps

    Science.gov (United States)

    Chiang, Yao-Yi

    2010-11-01

    Raster maps offer a great deal of geospatial information and are easily accessible compared to other geospatial data. However, harvesting geographic features locked in heterogeneous raster maps to obtain the geospatial information is challenging. This is because of the varying image quality of raster maps (e.g., scanned maps with poor image quality and computer-generated maps with good image quality), the overlapping geographic features in maps, and the typical lack of metadata (e.g., map geocoordinates, map source, and original vector data). Previous work on map processing is typically limited to a specific type of map and often relies on intensive manual work. In contrast, this thesis investigates a general approach that does not rely on any prior knowledge and requires minimal user effort to process heterogeneous raster maps. This approach includes automatic and supervised techniques to process raster maps for separating individual layers of geographic features from the maps and recognizing geographic features in the separated layers (i.e., detecting road intersections, generating and vectorizing road geometry, and recognizing text labels). The automatic technique eliminates user intervention by exploiting common map properties of how road lines and text labels are drawn in raster maps. For example, the road lines are elongated linear objects and the characters are small connected-objects. The supervised technique utilizes labels of road and text areas to handle complex raster maps, or maps with poor image quality, and can process a variety of raster maps with minimal user input. The results show that the general approach can handle raster maps with varying map complexity, color usage, and image quality. By matching extracted road intersections to another geospatial dataset, we can identify the geocoordinates of a raster map and further align the raster map, separated feature layers from the map, and recognized features from the layers with the geospatial

  14. Random Feature Maps for Dot Product Kernels

    OpenAIRE

    Kar, Purushottam; Karnick, Harish

    2012-01-01

    Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and other kernel based learning algorithms. We extend this line of work and present low distortion embeddings for dot product kernels into linear Euclidean spaces. We base our results on a classical result in harmonic analysis characterizing all dot product kernels and use it to define randomized feature maps into explic...

  15. Random Feature Maps for Dot Product Kernels

    CERN Document Server

    Kar, Purushottam

    2012-01-01

    Approximating non-linear kernels using feature maps has gained a lot of interest in recent years due to applications in reducing training and testing times of SVM classifiers and other kernel based learning algorithms. We extend this line of work and present low distortion embeddings for dot product kernels into linear Euclidean spaces. We base our results on a classical result in harmonic analysis characterizing all dot product kernels and use it to define randomized feature maps into explicit low dimensional Euclidean spaces in which the native dot product provides an approximation to the dot product kernel with high confidence.

  16. Adaptive object recognition model using incremental feature representation and hierarchical classification.

    Science.gov (United States)

    Jeong, Sungmoon; Lee, Minho

    2012-01-01

    This paper presents an adaptive object recognition model based on incremental feature representation and a hierarchical feature classifier that offers plasticity to accommodate additional input data and reduces the problem of forgetting previously learned information. The incremental feature representation method applies adaptive prototype generation with a cortex-like mechanism to conventional feature representation to enable an incremental reflection of various object characteristics, such as feature dimensions in the learning process. A feature classifier based on using a hierarchical generative model recognizes various objects with variant feature dimensions during the learning process. Experimental results show that the adaptive object recognition model successfully recognizes single and multiple-object classes with enhanced stability and flexibility.

  17. Visualizing Meta-Features in Proteomic Maps

    Directory of Open Access Journals (Sweden)

    Lepouras George

    2011-07-01

    Full Text Available Abstract Background The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the identified proteins through their association with interaction networks, biological pathways, analysis of the effect of post-translational modifications, and other protein-related information. Results In this paper, we present an integrative visualization methodology that allows combining experimentally produced proteomic features with protein meta-features, typically coming from meta-analysis tools and databases, in synthetic Proteomic Feature Maps. Using three proteomics analysis scenarios, we show that the proposed visualization approach is effective in filtering, navigating and interacting with the proteomics data in order to address visually challenging biological questions. The novelty of our approach lies in the ease of integration of any user-defined proteomic features in easy-to-comprehend visual representations that resemble the familiar 2D-gel images, and can be adapted to the user's needs. The main capabilities of the developed VIP software, which implements the presented visualization methodology, are also highlighted and discussed. Conclusions By using this visualization and the associated VIP software, researchers can explore a complex heterogeneous proteomics dataset from different perspectives in order to address visually important biological queries and formulate new hypotheses for further investigation. VIP is freely available at http://pelopas.uop.gr/~egian/VIP/index.html.

  18. Featured Image: Mapping Jupiter with Hubble

    Science.gov (United States)

    Kohler, Susanna

    2016-07-01

    Zonal wind profile for Jupiter, describing the speed and direction of its winds at each latitude. [Simon et al. 2015]This global map of Jupiters surface (click for the full view!) was generated by the Hubble Outer Planet Atmospheres Legacy (OPAL) program, which aims to createnew yearly global maps for each of the outer planets. Presented in a study led by Amy Simon (NASA Goddard Space Flight Center), the map above is the first generated for Jupiter in the first year of the OPAL campaign. It provides a detailed look at Jupiters atmospheric structure including the Great Red Spot and allowed the authors to measure the speed and direction of the wind across Jupiters latitudes, constructing an updated zonal wind profile for Jupiter.In contrast to this study, the Juno mission (which will be captured into Jupiters orbit today after a 5-year journey to Jupiter!) will be focusing more on the features below Jupiters surface, studying its deep atmosphere and winds. Some of Junos primary goals are to learn about Jupiters composition, gravitational field, magnetic field, and polar magnetosphere. You can follow along with the NASATV livestream as Juno arrives at Jupiter tonight; orbit insertion coverage starts at 10:30 EDT.CitationAmy A. Simon et al 2015 ApJ 812 55. doi:10.1088/0004-637X/812/1/55

  19. A Privacy Data-Oriented Hierarchical MapReduce Programming Model

    Directory of Open Access Journals (Sweden)

    Haiwen Han

    2013-08-01

    Full Text Available To realize privacy data protection efficiently in hybrid cloud service, a hierarchical control architecture based multi-cluster MapReduce programming model (the Hierarchical MapReduce Model,HMR is presented. Under this hierarchical control architecture,  data isolation and placement among private cloud and public clouds according to the data privacy characteristic is implemented by the control center in private cloud.  And then, to perform the corresponding distributed parallel computation correctly under the multi-clusters mode that is different to the conventional single-cluster mode, the Map-Reduce-GlobalReduce three stage scheduling process is designed. Limiting the computation about privacy data in private cloud while outsourcing the computation about non-privacy data to public clouds as much as possible, HMR reaches the performance of both security and low cost.  

  20. A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids using Genetic Algorithms

    Science.gov (United States)

    Sanyal, Soumya; Jain, Amit; Das, Sajal K.; Biswas, Rupak

    2003-01-01

    In this paper, we propose a distributed approach for mapping a single large application to a heterogeneous grid environment. To minimize the execution time of the parallel application, we distribute the mapping overhead to the available nodes of the grid. This approach not only provides a fast mapping of tasks to resources but is also scalable. We adopt a hierarchical grid model and accomplish the job of mapping tasks to this topology using a scheduler tree. Results show that our three-phase algorithm provides high quality mappings, and is fast and scalable.

  1. Spatio-temporal map generalizations with the hierarchical Voronoi data structure

    DEFF Research Database (Denmark)

    Mioc, Darka; Anton, François; Gold, Christopher M.

    of map objects, together with their temporal and spatial adjacency relationships. In this paper, we present new solutions to the problems of spatio-temporal generalizations using the hierarchical Voronoi spatio-temporal data structure. The application of the hierarchical Voronoi data structure presented...... in this research is in spatio-temporal map generalization, which is needed for reasoning about dynamic aspects of the world, primarily about actions, events and processes. This provides an advance in the domain of map generalization as we are able to deal not only with the cartographic objects, but also...... implemented in commercial GIS systems. In this research, we used the Voronoi spatial data model for map generalizations. We were able to demonstrate that the map generalization does not affect only spatial objects (points, lines or polygons), but also the events corresponding to the creation and modification...

  2. FeatureMap3D - a tool to map protein features and sequence conservation onto homologous structures in the PDB

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik

    2006-01-01

    FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB...... without sequence annotation, to evaluate the quality of the alignment of the input sequences to the most homologous structures in the PDB, through the sequence conservation colored 3D structure visualization tool. FeatureMap3D is available at: http://www.cbs.dtu.dk/services/FeatureMap3D/....

  3. Hierarchical Structure of the Eysenck Personality Inventory in a Large Population Sample: Goldberg's Trait-Tier Mapping Procedure.

    Science.gov (United States)

    Chapman, Benjamin P; Weiss, Alexander; Barrett, Paul; Duberstein, Paul

    2013-03-01

    The structure of the Eysenck Personality Inventory (EPI) is poorly understood, and applications have mostly been confined to the broad Neuroticism, Extraversion, and Lie scales. Using a hierarchical factoring procedure, we mapped the sequential differentiation of EPI scales from broad, molar factors to more specific, molecular factors, in a UK population sample of over 6500 persons. Replicable facets at the lowest tier of Neuroticism included emotional fragility, mood lability, nervous tension, and rumination. The lowest order set of replicable Extraversion facets consisted of social dynamism, sociotropy, decisiveness, jocularity, social information seeking, and impulsivity. The Lie scale consisted of an interpersonal virtue and a behavioral diligence facet. Users of the EPI may be well served in some circumstances by considering its broad Neuroticism, Extraversion, and Lie scales as multifactorial, a feature that was explicitly incorporated into subsequent Eysenck inventories and is consistent with other hierarchical trait structures.

  4. Mapping local microstructure and mechanical performance around carbon nanotube grafted silica fibres: Methodologies for hierarchical composites

    Science.gov (United States)

    Qian, Hui; Kalinka, Gerhard; Chan, K. L. Andrew; Kazarian, Sergei G.; Greenhalgh, Emile S.; Bismarck, Alexander; Shaffer, Milo S. P.

    2011-11-01

    The introduction of carbon nanotubes (CNTs) modifies bulk polymer properties, depending on intrinsic quality, dispersion, alignment, interfacial chemistry and mechanical properties of the nanofiller. These effects can be exploited to enhance the matrices of conventional microscale fibre-reinforced polymer composites, by using primary reinforcing fibres grafted with CNTs. This paper presents a methodology that combines atomic force microscopy, polarised Raman spectroscopy, and nanoindentation techniques, to study the distribution, alignment and orientation of CNTs in the vicinity of epoxy-embedded micrometre-scale silica fibres, as well as, the resulting local mechanical properties of the matrix. Raman maps of key features in the CNT spectra clearly show the CNT distribution and orientation, including a `parted' morphology associated with long grafted CNTs. The hardness and indentation modulus of the epoxy matrix were improved locally by 28% and 24%, respectively, due to the reinforcing effects of CNTs. Moreover, a slower stress relaxation was observed in the epoxy region containing CNTs, which may be due to restricted molecular mobility of the matrix. The proposed methodology is likely to be relevant to further studies of nanocomposites and hierarchical composites.The introduction of carbon nanotubes (CNTs) modifies bulk polymer properties, depending on intrinsic quality, dispersion, alignment, interfacial chemistry and mechanical properties of the nanofiller. These effects can be exploited to enhance the matrices of conventional microscale fibre-reinforced polymer composites, by using primary reinforcing fibres grafted with CNTs. This paper presents a methodology that combines atomic force microscopy, polarised Raman spectroscopy, and nanoindentation techniques, to study the distribution, alignment and orientation of CNTs in the vicinity of epoxy-embedded micrometre-scale silica fibres, as well as, the resulting local mechanical properties of the matrix. Raman

  5. Mapping informative clusters in a hierarchical [corrected] framework of FMRI multivariate analysis.

    Directory of Open Access Journals (Sweden)

    Rui Xu

    Full Text Available Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies.

  6. Mapping local microstructure and mechanical performance around carbon nanotube grafted silica fibres: methodologies for hierarchical composites.

    Science.gov (United States)

    Qian, Hui; Kalinka, Gerhard; Chan, K L Andrew; Kazarian, Sergei G; Greenhalgh, Emile S; Bismarck, Alexander; Shaffer, Milo S P

    2011-11-01

    The introduction of carbon nanotubes (CNTs) modifies bulk polymer properties, depending on intrinsic quality, dispersion, alignment, interfacial chemistry and mechanical properties of the nanofiller. These effects can be exploited to enhance the matrices of conventional microscale fibre-reinforced polymer composites, by using primary reinforcing fibres grafted with CNTs. This paper presents a methodology that combines atomic force microscopy, polarised Raman spectroscopy, and nanoindentation techniques, to study the distribution, alignment and orientation of CNTs in the vicinity of epoxy-embedded micrometre-scale silica fibres, as well as, the resulting local mechanical properties of the matrix. Raman maps of key features in the CNT spectra clearly show the CNT distribution and orientation, including a 'parted' morphology associated with long grafted CNTs. The hardness and indentation modulus of the epoxy matrix were improved locally by 28% and 24%, respectively, due to the reinforcing effects of CNTs. Moreover, a slower stress relaxation was observed in the epoxy region containing CNTs, which may be due to restricted molecular mobility of the matrix. The proposed methodology is likely to be relevant to further studies of nanocomposites and hierarchical composites.

  7. Disparity map generation from illumination variant stereo images using efficient hierarchical dynamic programming.

    Science.gov (United States)

    Borisagar, Viral H; Zaveri, Mukesh A

    2014-01-01

    A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.

  8. Disparity Map Generation from Illumination Variant Stereo Images Using Efficient Hierarchical Dynamic Programming

    Directory of Open Access Journals (Sweden)

    Viral H. Borisagar

    2014-01-01

    Full Text Available A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.

  9. The Role of Feature Sharedness in the Hierarchical Organization of Semantic Knowledge

    Directory of Open Access Journals (Sweden)

    J. Frederico Marques

    2013-01-01

    Full Text Available Data from neuropsychological research suggest that categorizing objects at different levels of specificity requires different cognitive and neural processes. This short paper presents and discusses a theoretical hypothesis for this organization in terms of feature sharedness. It is proposed that superordinate concepts involve a larger absolute number of exemplars that share a particular feature, thus making them more resistant to damage than basic level concepts (i.e. superordinate advantage. Simultaneously, in relative terms, features are less shared overall by superordinate members than by basic level members, which imply higher executive requirements and can conversely lead to superordinate deficits. This hypothesis is discussed in relation to behavioral data from semantic dementia and stroke aphasia patients and fMRI data from healthy subjects that support the role of feature sharedness in the hierarchical organization of semantic knowledge.

  10. A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis

    Science.gov (United States)

    An, Le; Adeli, Ehsan; Liu, Mingxia; Zhang, Jun; Lee, Seong-Whan; Shen, Dinggang

    2017-01-01

    Classification is one of the most important tasks in machine learning. Due to feature redundancy or outliers in samples, using all available data for training a classifier may be suboptimal. For example, the Alzheimer’s disease (AD) is correlated with certain brain regions or single nucleotide polymorphisms (SNPs), and identification of relevant features is critical for computer-aided diagnosis. Many existing methods first select features from structural magnetic resonance imaging (MRI) or SNPs and then use those features to build the classifier. However, with the presence of many redundant features, the most discriminative features are difficult to be identified in a single step. Thus, we formulate a hierarchical feature and sample selection framework to gradually select informative features and discard ambiguous samples in multiple steps for improved classifier learning. To positively guide the data manifold preservation process, we utilize both labeled and unlabeled data during training, making our method semi-supervised. For validation, we conduct experiments on AD diagnosis by selecting mutually informative features from both MRI and SNP, and using the most discriminative samples for training. The superior classification results demonstrate the effectiveness of our approach, as compared with the rivals. PMID:28358032

  11. A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis

    Science.gov (United States)

    An, Le; Adeli, Ehsan; Liu, Mingxia; Zhang, Jun; Lee, Seong-Whan; Shen, Dinggang

    2017-03-01

    Classification is one of the most important tasks in machine learning. Due to feature redundancy or outliers in samples, using all available data for training a classifier may be suboptimal. For example, the Alzheimer’s disease (AD) is correlated with certain brain regions or single nucleotide polymorphisms (SNPs), and identification of relevant features is critical for computer-aided diagnosis. Many existing methods first select features from structural magnetic resonance imaging (MRI) or SNPs and then use those features to build the classifier. However, with the presence of many redundant features, the most discriminative features are difficult to be identified in a single step. Thus, we formulate a hierarchical feature and sample selection framework to gradually select informative features and discard ambiguous samples in multiple steps for improved classifier learning. To positively guide the data manifold preservation process, we utilize both labeled and unlabeled data during training, making our method semi-supervised. For validation, we conduct experiments on AD diagnosis by selecting mutually informative features from both MRI and SNP, and using the most discriminative samples for training. The superior classification results demonstrate the effectiveness of our approach, as compared with the rivals.

  12. Intrusion Detection Method Based on Improved Growing Hierarchical Self-Organizing Map

    Institute of Scientific and Technical Information of China (English)

    张亚平; 布文秀; 苏畅; 王璐瑶; 许涵

    2016-01-01

    Considering that growing hierarchical self-organizing map(GHSOM) ignores the influence of individ-ual component in sample vector analysis, and its accurate rate in detecting unknown network attacks is relatively lower, an improved GHSOM method combined with mutual information is proposed. After theoretical analysis, experiments are conducted to illustrate the effectiveness of the proposed method by accurately clustering the input data. Based on different clusters, the complex relationship within the data can be revealed effectively.

  13. Periorbital melasma: Hierarchical cluster analysis of clinical features in Asian patients.

    Science.gov (United States)

    Jung, Y S; Bae, J M; Kim, B J; Kang, J-S; Cho, S B

    2017-03-19

    Studies have shown melasma lesions to be distributed across the face in centrofacial, malar, and mandibular patterns. Meanwhile, however, melasma lesions of the periorbital area have yet to be thoroughly described. We analyzed normal and ultraviolet light-exposed photographs of patients with melasma. The periorbital melasma lesions were measured according to anatomical reference points and a hierarchical cluster analysis was performed. The periorbital melasma lesions showed clinical features of fine and homogenous melasma pigmentation, involving both the upper and lower eyelids that extended to other anatomical sites with a darker and coarser appearance. The hierarchical cluster analysis indicated that patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. Significant differences between cluster 1 and cluster 2 were found in lateral distance and inferolateral distance, but not in medial distance and superior distance. Comparing the two clusters, patients in cluster 2 were found to be significantly older and more commonly accompanied by melasma lesions of the temple and medial cheek. Our hierarchical cluster analysis of periorbital melasma lesions demonstrated that Asian patients with periorbital melasma can be categorized into two clusters according to the surface anatomy of the face. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

    Science.gov (United States)

    Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

    2015-12-01

    Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions.

  15. A hierarchical Bayesian-MAP approach to inverse problems in imaging

    Science.gov (United States)

    Raj, Raghu G.

    2016-07-01

    We present a novel approach to inverse problems in imaging based on a hierarchical Bayesian-MAP (HB-MAP) formulation. In this paper we specifically focus on the difficult and basic inverse problem of multi-sensor (tomographic) imaging wherein the source object of interest is viewed from multiple directions by independent sensors. Given the measurements recorded by these sensors, the problem is to reconstruct the image (of the object) with a high degree of fidelity. We employ a probabilistic graphical modeling extension of the compound Gaussian distribution as a global image prior into a hierarchical Bayesian inference procedure. Since the prior employed by our HB-MAP algorithm is general enough to subsume a wide class of priors including those typically employed in compressive sensing (CS) algorithms, HB-MAP algorithm offers a vehicle to extend the capabilities of current CS algorithms to include truly global priors. After rigorously deriving the regression algorithm for solving our inverse problem from first principles, we demonstrate the performance of the HB-MAP algorithm on Monte Carlo trials and on real empirical data (natural scenes). In all cases we find that our algorithm outperforms previous approaches in the literature including filtered back-projection and a variety of state-of-the-art CS algorithms. We conclude with directions of future research emanating from this work.

  16. A Sparse Hierarchical Map Representation for Mars Science Laboratory Science Operations

    Science.gov (United States)

    Nefian, A. V.; Edwards, L. J.; Keely, L.; Lees, D. S.; Fluckinger, L.; Malin, M. C.; Parker, T. J.

    2015-12-01

    We describe a solution for multi-scale Mars terrain modeling and mapping with Digital Elevation Models (DEMs) and co-registered orthogonally projected imagery (ortho-images). High resolution DEMs and ortho-images derived from Mars Science Laboratory (MSL) rover science and navigation cameras are represented in context with lower resolution, wide coverage DEMs and ortho-images derived from Mars Reconnaissance Orbiter (MRO) HiRISE and CTX camera images and Mars Express (MEX) mission HRSC images. Merging MSL rover image derived terrain models with those from orbital images at a uniform high resolution would require super-sampling of the orbital data across a large area to maintain significant context. This solution is not practical, and would result in a mapping product of enormous size. Instead, we choose a sparse hierarchical map representation. Each level in this hierarchical representation is a map described by a set of tiles with fixed number of samples and fixed resolution. The number of samples in a tile is fixed for all levels and each level is associated with a specific resolution. In this work, the resolution ratio between two adjacent levels is set to two. The map at each level is sparse and it contains only the tiles for which data is available at the resolution of the given level. For example, at the highest resolution level only MSL science camera models are available and only a small set of tiles are generated in a sparse map. At the lowest resolution, the map contains the complete set of tiles. The reference level of the representation is chosen to be the HiRISE terrain model and CTX, HRSC and MSL data are projected onto this model before being mapped. While our terrain representation was developed for use in "Antares", a visual planning and sequencing tool for MSL science cameras developed at NASA Ames Research Center, it is general purpose and has a number of potential geo-science visualization applications.

  17. Efficient $\\chi ^{2}$ Kernel Linearization via Random Feature Maps.

    Science.gov (United States)

    Yuan, Xiao-Tong; Wang, Zhenzhen; Deng, Jiankang; Liu, Qingshan

    2016-11-01

    Explicit feature mapping is an appealing way to linearize additive kernels, such as χ(2) kernel for training large-scale support vector machines (SVMs). Although accurate in approximation, feature mapping could pose computational challenges in high-dimensional settings as it expands the original features to a higher dimensional space. To handle this issue in the context of χ(2) kernel SVMs learning, we introduce a simple yet efficient method to approximately linearize χ(2) kernel through random feature maps. The main idea is to use sparse random projection to reduce the dimensionality of feature maps while preserving their approximation capability to the original kernel. We provide approximation error bound for the proposed method. Furthermore, we extend our method to χ(2) multiple kernel SVMs learning. Extensive experiments on large-scale image classification tasks confirm that the proposed approach is able to significantly speed up the training process of the χ(2) kernel SVMs at almost no cost of testing accuracy.

  18. A Hierarchical Framework Combining Motion and Feature Information for Infrared-Visible Video Registration

    Science.gov (United States)

    Sun, Xinglong; Xu, Tingfa; Zhang, Jizhou; Li, Xiangmin

    2017-01-01

    In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotation prior to matching. In precise registration based on keypoint matching, the scale and rotation are used in re-location to eliminate their impact on targets and keypoints. To strictly match the keypoints, first, we improve the quality of keypoint matching by using normalized location descriptors and descriptors generated by the histogram of edge orientation. Second, we remove most mismatches by counting the matching directions of correspondences. We tested our framework on a public dataset, where our proposed framework outperformed two recently-proposed state-of-the-art global registration methods in almost all tested videos. PMID:28212350

  19. Full hierarchic versus non-hierarchic classification approaches for mapping sealed surfaces at the rural-urban fringe using high-resolution satellite data.

    Science.gov (United States)

    De Roeck, Tim; Van de Voorde, Tim; Canters, Frank

    2009-01-01

    Since 2008 more than half of the world population is living in cities and urban sprawl is continuing. Because of these developments, the mapping and monitoring of urban environments and their surroundings is becoming increasingly important. In this study two object-oriented approaches for high-resolution mapping of sealed surfaces are compared: a standard non-hierarchic approach and a full hierarchic approach using both multi-layer perceptrons and decision trees as learning algorithms. Both methods outperform the standard nearest neighbour classifier, which is used as a benchmark scenario. For the multi-layer perceptron approach, applying a hierarchic classification strategy substantially increases the accuracy of the classification. For the decision tree approach a one-against-all hierarchic classification strategy does not lead to an improvement of classification accuracy compared to the standard all-against-all approach. Best results are obtained with the hierarchic multi-layer perceptron classification strategy, producing a kappa value of 0.77. A simple shadow reclassification procedure based on characteristics of neighbouring objects further increases the kappa value to 0.84.

  20. Acoustic seafloor sediment classification using self-organizing feature maps

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Kaustubha, R.; Hegde, A.; Pereira, A.

    A self-organizing feature map (SOFM), a kind of artificial neural network (ANN) architecture, is used in this work for continental shelf seafloor sediment classification. Echo data are acquired using an echosounding system from three types...

  1. Multi-scale hierarchical approach for parametric mapping: assessment on multi-compartmental models.

    Science.gov (United States)

    Rizzo, G; Turkheimer, F E; Bertoldo, A

    2013-02-15

    This paper investigates a new hierarchical method to apply basis function to mono- and multi-compartmental models (Hierarchical-Basis Function Method, H-BFM) at a voxel level. This method identifies the parameters of the compartmental model in its nonlinearized version, integrating information derived at the region of interest (ROI) level by segmenting the cerebral volume based on anatomical definition or functional clustering. We present the results obtained by using a two tissue-four rate constant model with two different tracers ([(11)C]FLB457 and [carbonyl-(11)C]WAY100635), one of the most complex models used in receptor studies, especially at the voxel level. H-BFM is robust and its application on both [(11)C]FLB457 and [carbonyl-(11)C]WAY100635 allows accurate and precise parameter estimates, good quality parametric maps and a low percentage of voxels out of physiological bound (approach for PET quantification by using compartmental modeling at the voxel level. In particular, different from other proposed approaches, this method can also be used when the linearization of the model is not appropriate. We expect that applying it to clinical data will generate reliable parametric maps. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. CAFÉ-Map: Context Aware Feature Mapping for mining high dimensional biomedical data.

    Science.gov (United States)

    Minhas, Fayyaz Ul Amir Afsar; Asif, Amina; Arif, Muhammad

    2016-12-01

    Feature selection and ranking is of great importance in the analysis of biomedical data. In addition to reducing the number of features used in classification or other machine learning tasks, it allows us to extract meaningful biological and medical information from a machine learning model. Most existing approaches in this domain do not directly model the fact that the relative importance of features can be different in different regions of the feature space. In this work, we present a context aware feature ranking algorithm called CAFÉ-Map. CAFÉ-Map is a locally linear feature ranking framework that allows recognition of important features in any given region of the feature space or for any individual example. This allows for simultaneous classification and feature ranking in an interpretable manner. We have benchmarked CAFÉ-Map on a number of toy and real world biomedical data sets. Our comparative study with a number of published methods shows that CAFÉ-Map achieves better accuracies on these data sets. The top ranking features obtained through CAFÉ-Map in a gene profiling study correlate very well with the importance of different genes reported in the literature. Furthermore, CAFÉ-Map provides a more in-depth analysis of feature ranking at the level of individual examples. CAFÉ-Map Python code is available at: http://faculty.pieas.edu.pk/fayyaz/software.html#cafemap . The CAFÉ-Map package supports parallelization and sparse data and provides example scripts for classification. This code can be used to reconstruct the results given in this paper. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Online Learning of Hierarchical Pitman-Yor Process Mixture of Generalized Dirichlet Distributions With Feature Selection.

    Science.gov (United States)

    Fan, Wentao; Sallay, Hassen; Bouguila, Nizar

    2016-06-09

    In this paper, a novel statistical generative model based on hierarchical Pitman-Yor process and generalized Dirichlet distributions (GDs) is presented. The proposed model allows us to perform joint clustering and feature selection thanks to the interesting properties of the GD distribution. We develop an online variational inference algorithm, formulated in terms of the minimization of a Kullback-Leibler divergence, of our resulting model that tackles the problem of learning from high-dimensional examples. This variational Bayes formulation allows simultaneously estimating the parameters, determining the model's complexity, and selecting the appropriate relevant features for the clustering structure. Moreover, the proposed online learning algorithm allows data instances to be processed in a sequential manner, which is critical for large-scale and real-time applications. Experiments conducted using challenging applications, namely, scene recognition and video segmentation, where our approach is viewed as an unsupervised technique for visual learning in high-dimensional spaces, showed that the proposed approach is suitable and promising.

  4. Facial Feature Extraction Using Frequency Map Series in PCNN

    Directory of Open Access Journals (Sweden)

    Rencan Nie

    2016-01-01

    Full Text Available Pulse coupled neural network (PCNN has been widely used in image processing. The 3D binary map series (BMS generated by PCNN effectively describes image feature information such as edges and regional distribution, so BMS can be treated as the basis of extracting 1D oscillation time series (OTS for an image. However, the traditional methods using BMS did not consider the correlation of the binary sequence in BMS and the space structure for every map. By further processing for BMS, a novel facial feature extraction method is proposed. Firstly, consider the correlation among maps in BMS; a method is put forward to transform BMS into frequency map series (FMS, and the method lessens the influence of noncontinuous feature regions in binary images on OTS-BMS. Then, by computing the 2D entropy for every map in FMS, the 3D FMS is transformed into 1D OTS (OTS-FMS, which has good geometry invariance for the facial image, and contains the space structure information of the image. Finally, by analyzing the OTS-FMS, the standard Euclidean distance is used to measure the distances for OTS-FMS. Experimental results verify the effectiveness of OTS-FMS in facial recognition, and it shows better recognition performance than other feature extraction methods.

  5. Java Parallel Implementations of Kohonen Self-Organizing Feature Maps

    Institute of Scientific and Technical Information of China (English)

    YANG Shang-ming; HU Jie

    2004-01-01

    The Kohonen self-organizing map (SOM) is an important tool to find a mapping from high-dimensional space to low dimensional space. The time a SOM requires increases with the number of neurons. A parallel implementation of the algorithm can make it faster. This paper investigates the most recent parallel algorithms on SOMs. Using Java network programming utilities, improved parallel and distributed system are set up to simulate these algorithms. From the simulations, we conclude that those algorithms form good feature maps.

  6. Probing the Feature Map for Faces in Visual Search

    Directory of Open Access Journals (Sweden)

    Hua Yang

    2011-05-01

    Full Text Available Controversy surrounds the mechanisms underlying the pop-out effect for faces in visual search. Is there a feature map for faces? If so, does it rely on the categorical distinction between faces and nonfaces, or on image-level face semblance? To probe the feature map, we compared search efficiency for faces, and nonface stimuli with high, low, and no face semblance. First, subjects performed a visual search task with objects as distractors. Only faces popped-out. Moreover, search efficiency for nonfaces correlated with image-level face semblance of the target. In a second experiment, faces were used as distractors but nonfaces did not pop-out. Interestingly, search efficiency for nonfaces was not modulated by face semblance, although searching for a face among faces was particularly difficult, reflecting a categorical boundary between nonfaces and faces. Finally, inversion and contrast negation significantly interacted with the effect of face semblance, ruling out the possibility that search efficiency solely depends on low-level features. Our study supports a parallel search for faces that is perhaps preattentive. Like other features (color, orientation etc., there appears to be a continuous face feature map for visual search. Our results also suggest that this map may include both image-level face semblance and face categoricity.

  7. Hierarchical image feature extraction by an irregular pyramid of polygonal partitions

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2008-01-01

    We present an algorithmic framework for hierarchical image segmentation and feature extraction. We build a successive fine-to-coarse hierarchy of irregular polygonal partitions of the original image. This multiscale hierarchy forms the basis for object-oriented image analysis. The framework incorporates the Gestalt principles of visual perception, such as proximity and closure, and exploits spectral and textural similarities of polygonal partitions, while iteratively grouping them until dissimilarity criteria are exceeded. Seed polygons are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on the top of detected spectral discontinuities (such as edges), which form a network of constraints for the Delaunay triangulation. The image is then represented as a spatial network in the form of a graph with vertices corresponding to the polygonal partitions and edges reflecting their relations. The iterative agglomeration of partitions into object-oriented segments is formulated as Minimum Spanning Tree (MST) construction. An important characteristic of the approach is that the agglomeration of polygonal partitions is constrained by the detected edges; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects. The constructed partitions and their spatial relations are characterized using spectral, textural and structural features based on proximity graphs. The framework allows searching for object-oriented features of interest across multiple levels of details of the built hierarchy and can be generalized to the multi-criteria MST to account for multiple criteria important for an application.

  8. Orthographic Perspective Mappings for Consistent Wide-Area Motion Feature Maps from Multiple Cameras.

    Science.gov (United States)

    O'Gorman, Lawrence; Yang, Guang

    2016-04-15

    Spatiotemporal activity maps have been used to visualize where activity occurs over time, and are often displayed as pseudo-color heat maps. Our multi-dimensional activity map includes the following motion features: density, direction, bi-direction, velocity, and dwell. The primary contribution of this paper is to describe a set of mappings that will transform activity maps captured from cameras of different perspectives to ones from a single orthographic perspective. The purpose of this is to be able to view and compare multiple activity maps from different cameras views over a wide area with consistently comparable data. A second contribution is that most mappings are based upon statistically learned camera perspectives, to minimize manual camera calibration. We demonstrate mapping results with multiple video datasets and describe applications for visualization and wide-area spatial probability estimation.

  9. Extract relevant features from DEM for groundwater potential mapping

    Science.gov (United States)

    Liu, T.; Yan, H.; Zhai, L.

    2015-06-01

    Multi-criteria evaluation (MCE) method has been applied much in groundwater potential mapping researches. But when to data scarce areas, it will encounter lots of problems due to limited data. Digital Elevation Model (DEM) is the digital representations of the topography, and has many applications in various fields. Former researches had been approved that much information concerned to groundwater potential mapping (such as geological features, terrain features, hydrology features, etc.) can be extracted from DEM data. This made using DEM data for groundwater potential mapping is feasible. In this research, one of the most widely used and also easy to access data in GIS, DEM data was used to extract information for groundwater potential mapping in batter river basin in Alberta, Canada. First five determining factors for potential ground water mapping were put forward based on previous studies (lineaments and lineament density, drainage networks and its density, topographic wetness index (TWI), relief and convergence Index (CI)). Extraction methods of the five determining factors from DEM were put forward and thematic maps were produced accordingly. Cumulative effects matrix was used for weight assignment, a multi-criteria evaluation process was carried out by ArcGIS software to delineate the potential groundwater map. The final groundwater potential map was divided into five categories, viz., non-potential, poor, moderate, good, and excellent zones. Eventually, the success rate curve was drawn and the area under curve (AUC) was figured out for validation. Validation result showed that the success rate of the model was 79% and approved the method's feasibility. The method afforded a new way for researches on groundwater management in areas suffers from data scarcity, and also broaden the application area of DEM data.

  10. Cosmological parameters, shear maps and power spectra from CFHTLenS using Bayesian hierarchical inference

    CERN Document Server

    Alsing, Justin; Jaffe, Andrew H

    2016-01-01

    We apply two Bayesian hierarchical inference schemes to infer shear power spectra, shear maps and cosmological parameters from the CFHTLenS weak lensing survey - the first application of this method to data. In the first approach, we sample the joint posterior distribution of the shear maps and power spectra by Gibbs sampling, with minimal model assumptions. In the second approach, we sample the joint posterior of the shear maps and cosmological parameters, providing a new, accurate and principled approach to cosmological parameter inference from cosmic shear data. As a first demonstration on data we perform a 2-bin tomographic analysis to constrain cosmological parameters and investigate the possibility of photometric redshift bias in the CFHTLenS data. Under the baseline $\\Lambda$CDM model we constrain $S_8 = \\sigma_8(\\Omega_\\mathrm{m}/0.3)^{0.5} = 0.67 ^{\\scriptscriptstyle+ 0.03 }_{\\scriptscriptstyle- 0.03 }$ $(68\\%)$, consistent with previous CFHTLenS analysis but in tension with Planck. Adding neutrino m...

  11. Marginality: a numerical mapping for enhanced treatment of nominal and hierarchical attributes

    CERN Document Server

    Domingo-Ferrer, Josep

    2012-01-01

    The purpose of statistical disclosure control (SDC) of microdata, a.k.a. data anonymization or privacy-preserving data mining, is to publish data sets containing the answers of individual respondents in such a way that the respondents corresponding to the released records cannot be re-identified and the released data are analytically useful. SDC methods are either based on masking the original data, generating synthetic versions of them or creating hybrid versions by combining original and synthetic data. The choice of SDC methods for categorical data, especially nominal data, is much smaller than the choice of methods for numerical data. We mitigate this problem by introducing a numerical mapping for hierarchical nominal data which allows computing means, variances and covariances on them.

  12. Robust feature estimation by non-rigid hierarchical image registration and its application in disparity measurement

    Science.gov (United States)

    Badshah, Amir; Choudhry, Aadil Jaleel; Ullah, Shan

    2017-03-01

    Industries are moving towards automation in order to increase productivity and ensure quality. Variety of electronic and electromagnetic systems are being employed to assist human operator in fast and accurate quality inspection of products. Majority of these systems are equipped with cameras and rely on diverse image processing algorithms. Information is lost in 2D image, therefore acquiring accurate 3D data from 2D images is an open issue. FAST, SURF and SIFT are well-known spatial domain techniques for features extraction and henceforth image registration to find correspondence between images. The efficiency of these methods is measured in terms of the number of perfect matches found. A novel fast and robust technique for stereo-image processing is proposed. It is based on non-rigid registration using modified normalized phase correlation. The proposed method registers two images in hierarchical fashion using quad-tree structure. The registration process works through global to local level resulting in robust matches even in presence of blur and noise. The computed matches can further be utilized to determine disparity and depth for industrial product inspection. The same can be used in driver assistance systems. The preliminary tests on Middlebury dataset produced satisfactory results. The execution time for a 413 x 370 stereo-pair is 500ms approximately on a low cost DSP.

  13. Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra

    Science.gov (United States)

    Unglert, K.; Radić, V.; Jellinek, A. M.

    2016-06-01

    Variations in the spectral content of volcano seismicity related to changes in volcanic activity are commonly identified manually in spectrograms. However, long time series of monitoring data at volcano observatories require tools to facilitate automated and rapid processing. Techniques such as self-organizing maps (SOM) and principal component analysis (PCA) can help to quickly and automatically identify important patterns related to impending eruptions. For the first time, we evaluate the performance of SOM and PCA on synthetic volcano seismic spectra constructed from observations during two well-studied eruptions at Klauea Volcano, Hawai'i, that include features observed in many volcanic settings. In particular, our objective is to test which of the techniques can best retrieve a set of three spectral patterns that we used to compose a synthetic spectrogram. We find that, without a priori knowledge of the given set of patterns, neither SOM nor PCA can directly recover the spectra. We thus test hierarchical clustering, a commonly used method, to investigate whether clustering in the space of the principal components and on the SOM, respectively, can retrieve the known patterns. Our clustering method applied to the SOM fails to detect the correct number and shape of the known input spectra. In contrast, clustering of the data reconstructed by the first three PCA modes reproduces these patterns and their occurrence in time more consistently. This result suggests that PCA in combination with hierarchical clustering is a powerful practical tool for automated identification of characteristic patterns in volcano seismic spectra. Our results indicate that, in contrast to PCA, common clustering algorithms may not be ideal to group patterns on the SOM and that it is crucial to evaluate the performance of these tools on a control dataset prior to their application to real data.

  14. MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization

    Directory of Open Access Journals (Sweden)

    Kellermann Walter

    2007-01-01

    Full Text Available We address the problem of underdetermined BSS. While most previous approaches are designed for instantaneous mixtures, we propose a time-frequency-domain algorithm for convolutive mixtures. We adopt a two-step method based on a general maximum a posteriori (MAP approach. In the first step, we estimate the mixing matrix based on hierarchical clustering, assuming that the source signals are sufficiently sparse. The algorithm works directly on the complex-valued data in the time-frequency domain and shows better convergence than algorithms based on self-organizing maps. The assumption of Laplacian priors for the source signals in the second step leads to an algorithm for estimating the source signals. It involves the -norm minimization of complex numbers because of the use of the time-frequency-domain approach. We compare a combinatorial approach initially designed for real numbers with a second-order cone programming (SOCP approach designed for complex numbers. We found that although the former approach is not theoretically justified for complex numbers, its results are comparable to, or even better than, the SOCP solution. The advantage is a lower computational cost for problems with low input/output dimensions.

  15. Large Scale Hierarchical K-Means Based Image Retrieval With MapReduce

    Science.gov (United States)

    2014-03-27

    version of Hadoop at the time of this research. Hadoop is the open-source implementation of MapReduce and HDFS. • OpenCV [10]: C++ library for Computer...Boost.Python[1]: Allows for wrapping C++ code to create Python modules. Exposes full C++ OpenCV libraries, as well as native speeds for computation intensive...Yield (′0′, (ImageName, f eature)) end for end function Figure 3.3: MapReduce Feature Extraction Algorithm C++ using the OpenCV libraby. The C

  16. Hierarchical Bayesian approach for estimating physical properties in spiral galaxies: Age Maps for M74

    Science.gov (United States)

    Sánchez Gil, M. Carmen; Berihuete, Angel; Alfaro, Emilio J.; Pérez, Enrique; Sarro, Luis M.

    2015-09-01

    One of the fundamental goals of modern Astronomy is to estimate the physical parameters of galaxies from images in different spectral bands. We present a hierarchical Bayesian model for obtaining age maps from images in the Ha line (taken with Taurus Tunable Filter (TTF)), ultraviolet band (far UV or FUV, from GALEX) and infrared bands (24, 70 and 160 microns (μm), from Spitzer). As shown in [1], we present the burst ages for young stellar populations in the nearby and nearly face on galaxy M74. As it is shown in the previous work, the Hα to FUV flux ratio gives a good relative indicator of very recent star formation history (SFH). As a nascent star-forming region evolves, the Ha line emission declines earlier than the UV continuum, leading to a decrease in the HαFUV ratio. Through a specific star-forming galaxy model (Starburst 99, SB99), we can obtain the corresponding theoretical ratio Hα / FUV to compare with our observed flux ratios, and thus to estimate the ages of the observed regions. Due to the nature of the problem, it is necessary to propose a model of high complexity to take into account the mean uncertainties, and the interrelationship between parameters when the Hα / FUV flux ratio mentioned above is obtained. To address the complexity of the model, we propose a Bayesian hierarchical model, where a joint probability distribution is defined to determine the parameters (age, metallicity, IMF), from the observed data, in this case the observed flux ratios Hα / FUV. The joint distribution of the parameters is described through an i.i.d. (independent and identically distributed random variables), generated through MCMC (Markov Chain Monte Carlo) techniques.

  17. Cosmological parameters, shear maps and power spectra from CFHTLenS using Bayesian hierarchical inference

    Science.gov (United States)

    Alsing, Justin; Heavens, Alan; Jaffe, Andrew H.

    2017-04-01

    We apply two Bayesian hierarchical inference schemes to infer shear power spectra, shear maps and cosmological parameters from the Canada-France-Hawaii Telescope (CFHTLenS) weak lensing survey - the first application of this method to data. In the first approach, we sample the joint posterior distribution of the shear maps and power spectra by Gibbs sampling, with minimal model assumptions. In the second approach, we sample the joint posterior of the shear maps and cosmological parameters, providing a new, accurate and principled approach to cosmological parameter inference from cosmic shear data. As a first demonstration on data, we perform a two-bin tomographic analysis to constrain cosmological parameters and investigate the possibility of photometric redshift bias in the CFHTLenS data. Under the baseline ΛCDM (Λ cold dark matter) model, we constrain S_8 = σ _8(Ω _m/0.3)^{0.5} = 0.67+0.03-0.03 (68 per cent), consistent with previous CFHTLenS analyses but in tension with Planck. Adding neutrino mass as a free parameter, we are able to constrain ∑mν linear redshift-dependent photo-z bias Δz = p2(z - p1), we find p_1=-0.25+0.53-0.60 and p_2 = -0.15+0.17-0.15, and tension with Planck is only alleviated under very conservative prior assumptions. Neither the non-minimal neutrino mass nor photo-z bias models are significantly preferred by the CFHTLenS (two-bin tomography) data.

  18. Combining Self-organizing Feature Map with Support Vector Regression Based on Expert System

    Institute of Scientific and Technical Information of China (English)

    WANGLing; MUZhi-Chun; GUOHui

    2005-01-01

    A new approach is proposed to model nonlinear dynamic systems by combining SOM(self-organizing feature map) with support vector regression (SVR) based on expert system. The whole system has a two-stage neural network architecture. In the first stage SOM is used as a clustering algorithm to partition the whole input space into several disjointed regions. A hierarchical architecture is adopted in the partition to avoid the problem of predetermining the number of partitioned regions. Then, in the second stage, multiple SVR, also called SVR experts, that best fit each partitioned region by the combination of different kernel function of SVR and promote the configuration and tuning of SVR. Finally, to apply this new approach to time-series prediction problems based on the Mackey-Glass differential equation and Santa Fe data, the results show that SVR experts has effective improvement in the generalization performance in comparison with the single SVR model.

  19. Multi-modal, Multi-measure, and Multi-class Discrimination of ADHD with Hierarchical Feature Extraction and Extreme Learning Machine Using Structural and Functional Brain MRI.

    Science.gov (United States)

    Qureshi, Muhammad Naveed Iqbal; Oh, Jooyoung; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

    2017-01-01

    Structural and functional MRI unveil many hidden properties of the human brain. We performed this multi-class classification study on selected subjects from the publically available attention deficit hyperactivity disorder ADHD-200 dataset of patients and healthy children. The dataset has three groups, namely, ADHD inattentive, ADHD combined, and typically developing. We calculated the global averaged functional connectivity maps across the whole cortex to extract anatomical atlas parcellation based features from the resting-state fMRI (rs-fMRI) data and cortical parcellation based features from the structural MRI (sMRI) data. In addition, the preprocessed image volumes from both of these modalities followed an ANOVA analysis separately using all the voxels. This study utilized the average measure from the most significant regions acquired from ANOVA as features for classification in addition to the multi-modal and multi-measure features of structural and functional MRI data. We extracted most discriminative features by hierarchical sparse feature elimination and selection algorithm. These features include cortical thickness, image intensity, volume, cortical thickness standard deviation, surface area, and ANOVA based features respectively. An extreme learning machine performed both the binary and multi-class classifications in comparison with support vector machines. This article reports prediction accuracy of both unimodal and multi-modal features from test data. We achieved 76.190% (p multi-class settings as well as 92.857% (p multi-modal group analysis approach with multi-measure features may improve the accuracy of the ADHD differential diagnosis.

  20. Hierarchical Bayesian approach for estimating physical properties in spiral galaxies: Age Maps for M74

    CERN Document Server

    Gil, M Carmen Sánchez; Alfaro, Emilio J; Pérez, Enrique; Sarro, Luis M

    2015-01-01

    One of the fundamental goals of modern Astronomy is to estimate the physical parameters of galaxies from images in different spectral bands. We present a hierarchical Bayesian model for obtaining age maps from images in the \\Ha\\ line (taken with Taurus Tunable Filter (TTF)), ultraviolet band (far UV or FUV, from GALEX) and infrared bands (24, 70 and 160 microns ($\\mu$m), from Spitzer). As shown in S\\'anchez-Gil et al. (2011), we present the burst ages for young stellar populations in the nearby and nearly face on galaxy M74. As it is shown in the previous work, the \\Ha\\ to FUV flux ratio gives a good relative indicator of very recent star formation history (SFH). As a nascent star-forming region evolves, the \\Ha\\ line emission declines earlier than the UV continuum, leading to a decrease in the \\Ha\\/FUV ratio. Through a specific star-forming galaxy model (Starburst 99, SB99), we can obtain the corresponding theoretical ratio \\Ha\\ / FUV to compare with our observed flux ratios, and thus to estimate the ages of...

  1. CosmoQuest: A software platform for surface feature mapping

    Science.gov (United States)

    Gay, Pamela

    2016-07-01

    While many tools exist for allowing individuals to mark features in images, it has previously been unwieldy to get entire teams collaboratively mapping out surface features, and to statistically compare each team members contributions. Our CSB software was initially developed to facilitate crowd-sourcing projects, including CosmoQuest's "Moon Mappers" project. Statistically study of its results (Robbins et al 2014) has shown that professionals using this software get results that are as good as those they get using other commonly used software packages. This has lead to an expansion of the software to facilitate professional science use of the software. In order to allow the greatest use of CSB, and to facilitate better science collaboration, CosmoQuest now allows teams to create private projects. Basic features include: using their own data sets, allowing multiple team members to annotate the images, performing basic statistics on the resulting data, downloading all results in either .sql or .csv formats. In this presentation, we will overview how best to use CSB to improve your own science collaboration. Current applications include surface science and transient object identification, and published results include both crater maps and the discovery of KBOs.

  2. Coordinated Mapping of Sea Ice Deformation Features with Autonomous Vehicles

    Science.gov (United States)

    Maksym, T.; Williams, G. D.; Singh, H.; Weissling, B.; Anderson, J.; Maki, T.; Ackley, S. F.

    2016-12-01

    Decreases in summer sea ice extent in the Beaufort and Chukchi Seas has lead to a transition from a largely perennial ice cover, to a seasonal ice cover. This drives shifts in sea ice production, dynamics, ice types, and thickness distribution. To examine how the processes driving ice advance might also impact the morphology of the ice cover, a coordinated ice mapping effort was undertaken during a field campaign in the Beaufort Sea in October, 2015. Here, we present observations of sea ice draft topography from six missions of an Autonomous Underwater Vehicle run under different ice types and deformation features observed during autumn freeze-up. Ice surface features were also mapped during coordinated drone photogrammetric missions over each site. We present preliminary results of a comparison between sea ice surface topography and ice underside morphology for a range of sample ice types, including hummocked multiyear ice, rubble fields, young ice ridges and rafts, and consolidated pancake ice. These data are compared to prior observations of ice morphological features from deformed Antarctic sea ice. Such data will be useful for improving parameterizations of sea ice redistribution during deformation, and for better constraining estimates of airborne or satellite sea ice thickness.

  3. Tiled vector data model for the geographical features of symbolized maps

    Science.gov (United States)

    Zhu, Haihong; Li, You; Zhang, Hang

    2017-01-01

    Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and ‘addition’ (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity. PMID:28475578

  4. Highlighting landslides and other geomorphological features using sediment connectivity maps

    Science.gov (United States)

    Bossi, Giulia; Crema, Stefano; Cavalli, Marco; Marcato, Gianluca; Pasuto, Alessandro

    2016-04-01

    Landslide identification is usually made through interpreting geomorphological features in the field or with remote sensing imagery. In recent years, airborne laser scanning (LiDAR) has enhanced the potentiality of geomorphological investigations by providing a detailed and diffuse representation of the land surface. The development of algorithms for geomorphological analysis based on LiDAR derived high-resolution Digital Terrain Models (DTMs) is increasing. Among them, the sediment connectivity index (IC) has been used to quantify sediment dynamics in alpine catchments. In this work, maps of the sediment connectivity index are used for detecting geomorphological features and processes not exclusively related to water-laden processes or debris flows. The test area is located in the upper Passer Valley in South Tyrol (Italy). Here a 4 km2 Deep-seated Gravitational Slope Deformation (DGSD) with several secondary phenomena has been studied for years. The connectivity index was applied to a well-known study area in order to evaluate its effectiveness as an interpretative layer to assist geomorphological analysis. Results were cross checked with evidence previously identified by means of in situ investigations, photointerpretation and monitoring data. IC was applied to a 2.5 m LiDAR derived DTM using two different scenarios in order to test their effectiveness: i) IC derived on the hydrologically correct DTM; ii) IC derived on the original DTM. In the resulting maps a cluster of low-connectivity areas appears as the deformation of the DGSD induce a convexity in the central part of the phenomenon. The double crests, product of the sagging of the landslide, are extremely evident since in those areas the flow directions diverge from the general drainage pattern, which is directed towards the valley river. In the crown area a rock-slab that shows clear evidence of incumbent detachment is clearly highlighted since the maps emphasize the presence of traction trenches and

  5. Sentinel-2 for Mapping Iron Absorption Feature Parameters

    Directory of Open Access Journals (Sweden)

    Harald van der Werff

    2015-09-01

    Full Text Available Iron is an indicator for soil fertility and the usability of an area for cultivating crops. Remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval, yet a relative high spectral resolution is needed for mapping iron contents with reflectance data. Sentinel-2 has several bands that cover the 0.9 μm iron absorption feature, while space-borne sensors traditionally used for geologic remote sensing, like ASTER and Landsat, had only one band in this feature. In this paper, we introduce a curve-fitting technique for Sentinel-2 that approximates the iron absorption feature at a hyperspectral resolution. We test our technique on library spectra of different iron bearing minerals and we apply it to a Sentinel-2 image synthesized from an airborne hyperspectral dataset. Our method finds the wavelength position of maximum absorption and absolute absorption depth for minerals Beryl, Bronzite, Goethite, Jarosite and Hematite. Sentinel-2 offers information on the 0.9 μm absorption feature that until now was reserved for hyperspectral instruments. Being a satellite mission, this information comes at a lower spatial resolution than airborne hyperspectral data, but with a large spatial coverage and frequent revisit time.

  6. Discovering enhancers by mapping chromatin features in primary tissue.

    Science.gov (United States)

    Bowman, Sarah K

    2015-09-01

    Enhancers work with promoters to refine the timing, location, and level of gene expression. As they perform these functions, active enhancers generate a chromatin environment that is distinct from other areas of the genome. Therefore, profiling enhancer-associated chromatin features can produce genome-wide maps of potential regulatory elements. This review focuses on current technologies used to produce maps of potential tissue-specific enhancers by profiling chromatin from primary tissue. First, cells are separated from whole organisms either by affinity purification, automated cell sorting, or microdissection. Isolating the tissue prior to analysis ensures that the molecular signature of active enhancers will not become lost in an averaged signal from unrelated cell types. After cell isolation, the molecular feature that is profiled will depend on the abundance and quality of the harvested material. The combination of tissue isolation plus genome-wide chromatin profiling has successfully identified enhancers in several pioneering studies. In the future, the regulatory apparatus of healthy and diseased tissues will be explored in this manner, as researchers use the combined techniques to gain insight into how active enhancers may influence disease progression.

  7. Representation of Molecular Electrostatic Potentials of Biopolymer by Self-organizing Feature Map

    Institute of Scientific and Technical Information of China (English)

    QIAO,Xue-Bin(乔学斌); JIANG,Bo(姜波); HOU,Ting-Jun(侯廷军); XU,Xiao-Jie(徐筱杰)

    2001-01-01

    The Kohonen serf-organizing map was introduced to map theprotein molecular surface features.The protein or polypeptideproperties,such as shape and molecular electrostatic poten-rial,can be visualized by seff-organizing map,which wastrained by the 3D surface coordinates.Such maps allow thevisual comparison of molecular properties between proteinshaving common topological or chemical features.``

  8. On Simplifying Features in OpenStreetMap database

    Science.gov (United States)

    Qian, Xinlin; Tao, Kunwang; Wang, Liang

    2015-04-01

    Currently the visualization of OpenStreetMap data is using a tile server which stores map tiles that have been rendered from vector data in advance. However, tiled map are short of functionalities such as data editing and customized styling. To enable these advanced functionality, Client-side processing and rendering of geospatial data is needed. Considering the voluminous size of the OpenStreetMap data, simply sending region queries results of OSM database to client is prohibitive. To make the OSM data retrieved from database adapted for client receiving and rendering, It must be filtered and simplified at server-side to limit its volume. We propose a database extension for OSM database to make it possible to simplifying geospatial objects such as ways and relations during data queries. Several auxiliary tables and PL/pgSQL functions are presented to make the geospatial features can be simplified by omitting unimportant vertices. There are five components in the database extension: Vertices weight computation by polyline and polygon simplification algorithm, Vertices weight storage in auxiliary tables. filtering and selecting of vertices using specific threshold value during spatial queries, assembling of simplified geospatial objects using filtered vertices, vertices weight updating after geospatial objects editing. The database extension is implemented on an OSM APIDB using PL/pgSQL. The database contains a subset of OSM database. The experimental database contains geographic data of United Kingdom which is about 100 million vertices and roughly occupy 100GB disk. JOSM are used to retrieve the data from the database using a revised data accessing API and render the geospatial objects in real-time. When serving simplified data to client, The database allows user to set the bound of the error of simplification or the bound of responding time in each data query. Experimental results show the effectiveness and efficiency of the proposed methods in building a

  9. Cross-Modality Feature Learning Through Generic Hierarchical Hyperlingual-Words.

    Science.gov (United States)

    Shao, Ming; Fu, Yun

    2017-02-01

    Recognizing facial images captured under visible light has long been discussed in the past decades. However, there are many impact factors that hinder its successful application in real-world, e.g., illumination, pose variations. Recent work has concentrated on different spectrals, i.e., near infrared, that can only be perceived by specifically designed device to avoid the illumination problem. However, this inevitably introduces a new problem, namely, cross-modality classification. In brief, images registered in the system are in one modality, while images that captured momentarily used as the tests are in another modality. In addition, there could be many within-modality variations-pose and expression-leading to a more complicated problem for the researchers. To address this problem, we propose a novel framework called hierarchical hyperlingual-words (Hwords) in this paper. First, we design a novel structure, called generic Hwords, to capture the high-level semantics across different modalities and within each modality in weakly supervised fashion, meaning only modality pair and variations information are needed in the training. Second, to improve the discriminative power of Hwords, we propose a novel distance metric through the hierarchical structure of Hwords. Extensive experiments on multimodality face databases demonstrate the superiority of our method compared with the state-of-the-art works on face recognition tasks subject to pose and expression variations.

  10. Theory for the alignment of cortical feature maps during development

    KAUST Repository

    Bressloff, Paul C.

    2010-08-23

    We present a developmental model of ocular dominance column formation that takes into account the existence of an array of intrinsically specified cytochrome oxidase blobs. We assume that there is some molecular substrate for the blobs early in development, which generates a spatially periodic modulation of experience-dependent plasticity. We determine the effects of such a modulation on a competitive Hebbian mechanism for the modification of the feedforward afferents from the left and right eyes. We show how alternating left and right eye dominated columns can develop, in which the blobs are aligned with the centers of the ocular dominance columns and receive a greater density of feedforward connections, thus becoming defined extrinsically. More generally, our results suggest that the presence of periodically distributed anatomical markers early in development could provide a mechanism for the alignment of cortical feature maps. © 2010 The American Physical Society.

  11. Design Method of the Semantic-driven Hierarchical Map Symbols%语义驱动的层次化地图符号设计方法

    Institute of Scientific and Technical Information of China (English)

    田江鹏; 贾奋励; 夏青; 吴金兵

    2012-01-01

    Research of map symbols is an important part of cartography. Currently, the main research of map symbols was focused on the visual graphics but paying little attention to the semantic. This paper puts forward a method of semantic-driven hierarchical map symbols design. In this method the semantic relation of map symbols is as a benchmark to the construction of symbol graphics, and the symbol graphics is controlled by semantic model. So we can fully exploit the intrinsic value of the semantic components of the map symbols in its design activities. We mainly focused on such four key steps of the method. The first one is semantic feature extraction. We systematically summarized the semantic feature of the map symbols by using ontological level concept. Second step is about morphemes design. The concept, design principles of morphemes and its important role in map symbols design was discussed. The third is about modeling of the associative semantic relation. In this step the modeling methods was discussed and a practice that show how to construct an associative semantic model based on common map symbols for the public geographical information was conducted. The fourth is semantics-driven generation of map symbols. The processes and characteristics of a symbol's generation was analyzed. An existing map symbol standard was improved by using our symbol design method. And a group of cognitive experiments have been done which show that the propound method has a superior performance in cognitive efficiency and relatively stable and high transmission efficiency in the analog process of information transmission. In conclusion, the semantic relation of the geospatial objects is the core of the method of semantic-driven hierarchical map symbols design, which is aimed to improve the graphic design and understanding of map symbols. Characterized by the symbol design oriented ontology domain, this method makes the map symbols more semantic-evident for better recognition

  12. Mapping Phonetic Features for Voice-Driven Sound Synthesis

    Science.gov (United States)

    Janer, Jordi; Maestre, Esteban

    In applications where the human voice controls the synthesis of musical instruments sounds, phonetics convey musical information that might be related to the sound of the imitated musical instrument. Our initial hypothesis is that phonetics are user- and instrument-dependent, but they remain constant for a single subject and instrument. We propose a user-adapted system, where mappings from voice features to synthesis parameters depend on how subjects sing musical articulations, i.e. note to note transitions. The system consists of two components. First, a voice signal segmentation module that automatically determines note-to-note transitions. Second, a classifier that determines the type of musical articulation for each transition based on a set of phonetic features. For validating our hypothesis, we run an experiment where subjects imitated real instrument recordings with their voice. Performance recordings consisted of short phrases of saxophone and violin performed in three grades of musical articulation labeled as: staccato, normal, legato. The results of a supervised training classifier (user-dependent) are compared to a classifier based on heuristic rules (user-independent). Finally, from the previous results we show how to control the articulation in a sample-concatenation synthesizer by selecting the most appropriate samples.

  13. Mapping the hierarchical layout of the structural network of the macaque prefrontal cortex.

    Science.gov (United States)

    Goulas, Alexandros; Uylings, Harry B M; Stiers, Peter

    2014-05-01

    A consensus on the prefrontal cortex (PFC) holds that it is pivotal for flexible behavior and the integration of the cognitive, affective, and motivational domains. Certain models have been put forth and a dominant model postulates a hierarchical anterior-posterior gradient. The structural connectivity principles of this model dictate that increasingly anterior PFC regions exhibit more efferent connections toward posterior ones than vice versa. Such hierarchical asymmetry principles are thought to pertain to the macaque PFC. Additionally, the laminar patterns of the connectivity of PFC regions can be used for defining hierarchies. In the current study, we formally tested the asymmetry-based hierarchical principles of the anterior-posterior model by employing an exhaustive dataset on macaque PFC connectivity and tools from network science. On the one hand, the asymmetry-based principles and predictions of the hierarchical anterior-posterior model were not confirmed. The wiring of the macaque PFC does not fully correspond to the principles of the model, and its asymmetry-based hierarchical layout does not follow a strict anterior-posterior gradient. On the other hand, our results suggest that the laminar-based hierarchy seems a more tenable working hypothesis for models advocating an anterior-posterior gradient. Our results can inform models of the human PFC.

  14. Classifying airborne radiometry data with Agglomerative Hierarchical Clustering: A tool for geological mapping in context of rainforest (French Guiana)

    Science.gov (United States)

    Martelet, G.; Truffert, C.; Tourlière, B.; Ledru, P.; Perrin, J.

    2006-09-01

    In highly weathered environments, it is crucial that geological maps provide information concerning both the regolith and the bedrock, for societal needs, such as land-use, mineral or water resources management. Often, geologists are facing the challenge of upgrading existing maps, as relevant information concerning weathering processes and pedogenesis is currently missing. In rugged areas in particular, where access to the field is difficult, ground observations are sparsely available, and need therefore to be complemented using methods based on remotely sensed data. For this purpose, we discuss the use of Agglomerative Hierarchical Clustering (AHC) on eU, K and eTh airborne gamma-ray spectrometry grids. The AHC process allows primarily to segment the geophysical maps into zones having coherent U, K and Th contents. The analysis of these contents are discussed in terms of geochemical signature for lithological attribution of classes, as well as the use of a dendrogram, which gives indications on the hierarchical relations between classes. Unsupervised classification maps resulting from AHC can be considered as spatial models of the distribution of the radioelement content in surface and sub-surface formations. The source of gamma rays emanating from the ground is primarily related to the geochemistry of the bedrock and secondarily to modifications of the radioelement distribution by weathering and other secondary mechanisms, such as mobilisation by wind or water. The interpretation of the obtained predictive classified maps, their U, K, Th contents, and the dendrogram, in light of available geological knowledge, allows to separate signatures related to regolith and solid geology. Consequently, classification maps can be integrated within a GIS environment and used by the geologist as a support for mapping bedrock lithologies and their alteration. We illustrate the AHC classification method in the region of Cayenne using high-resolution airborne radiometric data

  15. Feature Space Mapping as a universal adaptive system

    Science.gov (United States)

    Duch, Włodzisław; Diercksen, Geerd H. F.

    1995-06-01

    The most popular realizations of adaptive systems are based on the neural network type of algorithms, in particular feedforward multilayered perceptrons trained by backpropagation of error procedures. In this paper an alternative approach based on multidimensional separable localized functions centered at the data clusters is proposed. In comparison with the neural networks that use delocalized transfer functions this approach allows for full control of the basins of attractors of all stationary points. Slow learning procedures are replaced by the explicit construction of the landscape function followed by the optimization of adjustable parameters using gradient techniques or genetic algorithms. Retrieving information does not require searches in multidimensional subspaces but it is factorized into a series of one-dimensional searches. Feature Space Mapping is applicable to learning not only from facts but also from general laws and may be treated as a fuzzy expert system (neurofuzzy system). The number of nodes (fuzzy rules) is growing as the network creates new nodes for novel data but the search time is sublinear in the number of rules or data clusters stored. Such a system may work as a universal classificator, approximator and reasoning system. Examples of applications for the identification of spectra (classification), intelligent databases (association) and for the analysis of simple electrical circuits (expert system type) are given.

  16. Fukunaga-Koontz feature transformation for statistical structural damage detection and hierarchical neuro-fuzzy damage localisation

    Science.gov (United States)

    Hoell, Simon; Omenzetter, Piotr

    2017-07-01

    Considering jointly damage sensitive features (DSFs) of signals recorded by multiple sensors, applying advanced transformations to these DSFs and assessing systematically their contribution to damage detectability and localisation can significantly enhance the performance of structural health monitoring systems. This philosophy is explored here for partial autocorrelation coefficients (PACCs) of acceleration responses. They are interrogated with the help of the linear discriminant analysis based on the Fukunaga-Koontz transformation using datasets of the healthy and selected reference damage states. Then, a simple but efficient fast forward selection procedure is applied to rank the DSF components with respect to statistical distance measures specialised for either damage detection or localisation. For the damage detection task, the optimal feature subsets are identified based on the statistical hypothesis testing. For damage localisation, a hierarchical neuro-fuzzy tool is developed that uses the DSF ranking to establish its own optimal architecture. The proposed approaches are evaluated experimentally on data from non-destructively simulated damage in a laboratory scale wind turbine blade. The results support our claim of being able to enhance damage detectability and localisation performance by transforming and optimally selecting DSFs. It is demonstrated that the optimally selected PACCs from multiple sensors or their Fukunaga-Koontz transformed versions can not only improve the detectability of damage via statistical hypothesis testing but also increase the accuracy of damage localisation when used as inputs into a hierarchical neuro-fuzzy network. Furthermore, the computational effort of employing these advanced soft computing models for damage localisation can be significantly reduced by using transformed DSFs.

  17. Optimizing map labeling of point features based on an onion peeling approach

    OpenAIRE

    Bae, Wan D.; Shayma Alkobaisi; Sada Narayanappa; Petr Vojtechovsky; Kye Y. Bae

    2011-01-01

    Map labeling of point features is the problem of placing text labels to corresponding point features on a map in a way that minimizes overlaps while satisfying basic rules for the quality. This is a critical problem in the application of cartography and geographical information systems (GIS). In this paper we study the fundamental issues related to map labeling of point features and develop a new genetic algorithm to solve this problem. We adopt a method called convex onion peeling and utiliz...

  18. Object Recognition using Channel-Coded Feature Maps: C++ Implementation Documentation

    OpenAIRE

    Jonsson, Erik

    2008-01-01

    This report gives an overview and motivates the design of a C++ framework for object recognition using channel-coded feature maps. The code was produced in connection to the work on my PhD thesis Channel-Coded Feature Maps for Object Recognition and Machine Learning. The package contains algorithms ranging from basic image processing routines to specific complex algorithms for creating channel-coded feature maps through piecewise polynomials. Much emphasis has been put in creating a flexible ...

  19. Multiscale vascular surface model generation from medical imaging data using hierarchical features.

    Science.gov (United States)

    Bekkers, Eric J; Taylor, Charles A

    2008-03-01

    Computational fluid dynamics (CFD) modeling of blood flow from image-based patient specific models can provide useful physiologic information for guiding clinical decision making. A novel method for the generation of image-based, 3-D, multiscale vascular surface models for CFD is presented. The method generates multiscale surfaces based on either a linear triangulated or a globally smooth nonuniform rational B-spline (NURB) representation. A robust local curvature analysis is combined with a novel global feature analysis to set mesh element size. The method is particularly useful for CFD modeling of complex vascular geometries that have a wide range of vasculature size scales, in conditions where 1) initial surface mesh density is an important consideration for balancing surface accuracy with manageable size volumetric meshes, 2) adaptive mesh refinement based on flow features makes an underlying explicit smooth surface representation desirable, and 3) semi-automated detection and trimming of a large number of inlet and outlet vessels expedites model construction.

  20. Blank Panel Design of Integral Wing Skin Panels Based on Feature Mapping Methods

    Institute of Scientific and Technical Information of China (English)

    Wang; Junbiao; Zhang; Xianjie

    2007-01-01

    A blank panel design algorithm based on feature mapping methods for integral wing skin panels with supercritical airfoil surface is presented.The model of a wing panel is decomposed into features,and features of the panel are decomposed into information of location,direction,dimension and Boolean types.Features are mapped into the plane through optimal surface development algorithm.The plane panel is modeled by rebuilding the mapped features.Blanks of shot-peen forming panels are designed to identify the effectiveness of the methods.

  1. Classification of cancer cell lines using an automated two-dimensional liquid mapping method with hierarchical clustering techniques.

    Science.gov (United States)

    Wang, Yanfei; Wu, Rong; Cho, Kathleen R; Shedden, Kerby A; Barder, Timothy J; Lubman, David M

    2006-01-01

    A two-dimensional liquid mapping method was used to map the protein expression of eight ovarian serous carcinoma cell lines and three immortalized ovarian surface epithelial cell lines. Maps were produced using pI as the separation parameter in the first dimension and hydrophobicity based upon reversed-phase HPLC separation in the second dimension. The method can be reproducibly used to produce protein expression maps over a pH range from 4.0 to 8.5. A dynamic programming method was used to correct for minor shifts in peaks during the HPLC gradient between sample runs. The resulting corrected maps can then be compared using hierarchical clustering to produce dendrograms indicating the relationship between different cell lines. It was found that several of the ovarian surface epithelial cell lines clustered together, whereas specific groups of serous carcinoma cell lines clustered with each other. Although there is limited information on the current biology of these cell lines, it was shown that the protein expression of certain cell lines is closely related to each other. Other cell lines, including one ovarian clear cell carcinoma cell line, two endometrioid carcinoma cell lines, and three breast epithelial cell lines, were also mapped for comparison to show that their protein profiles cluster differently than the serous samples and to study how they cluster relative to each other. In addition, comparisons can be made between proteins differentially expressed between cell lines that may serve as markers of ovarian serous carcinomas. The automation of the method allows reproducible comparison of many samples, and the use of differential analysis limits the number of proteins that might require further analysis by mass spectrometry techniques.

  2. On the use of topological features and hierarchical characterization for disambiguating names in collaborative networks

    CERN Document Server

    Amancio, Diego R; Costa, Luciano da F; 10.1209/0295-5075/99/48002

    2013-01-01

    Many features of complex systems can now be unveiled by applying statistical physics methods to treat them as social networks. The power of the analysis may be limited, however, by the presence of ambiguity in names, e.g., caused by homonymy in collaborative networks. In this paper we show that the ability to distinguish between homonymous authors is enhanced when longer-distance connections are considered, rather than looking at only the immediate neighbors of a node in the collaborative network. Optimized results were obtained upon using the 3rd hierarchy in connections. Furthermore, reasonable distinction among authors could also be achieved upon using pattern recognition strategies for the data generated from the topology of the collaborative network. These results were obtained with a network from papers in the arXiv repository, into which homonymy was deliberately introduced to test the methods with a controlled, reliable dataset. In all cases, several methods of supervised and unsupervised machine lear...

  3. Iterative Maps with Hierarchical Clustering for the Observed Scales of Astrophysical and Cosmological Structures

    CERN Document Server

    Capozziello, S; De Siena, S; Guerra, F; Illuminati, F

    2000-01-01

    We derive, in order of magnitude, the observed astrophysical and cosmologicalscales in the Universe, from neutron stars to superclusters of galaxies, up to,asymptotically, the observed radius of the Universe. This result is obtained byintroducing a recursive scheme of alternating hierachical mechanisms ofthree-dimensional and two-dimensional close packings of gravitationallyinteracting objects. The iterative scheme yields a rapidly converging geometricsequence, which can be described as a hierarchical clustering of aggregates,having the observed radius of the Universe as its fixed point.

  4. Sea-Ice Feature Mapping using JERS-1 Imagery

    Science.gov (United States)

    Maslanik, James; Heinrichs, John

    1994-01-01

    JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

  5. A topographic feature taxonomy for a U.S. national topographic mapping ontology

    Science.gov (United States)

    Varanka, Dalia E.

    2013-01-01

    Using legacy feature lists from the U.S. National Topographic Mapping Program of the twentieth century, a taxonomy of features is presented for purposes of developing a national topographic feature ontology for geographic mapping and analysis. After reviewing published taxonomic classifications, six basic classes are suggested; terrain, surface water, ecological regimes, built-up areas, divisions, and events. Aspects of ontology development are suggested as the taxonomy is described.

  6. Map Building Method Based on Hierarchical Temporal Memory%基于层级实时记忆的地图创建方法∗

    Institute of Scientific and Technical Information of China (English)

    张新征; 麦晓春; 张建芬

    2015-01-01

    提出基于层级实现记忆( HTM)网络的地图创建方法。该方法利用层级实时记忆将制图问题等效为场景识别问题,环境地图由一系列HTM模型输出的场景构成。首先从获取图像中提取位置不变鲁棒特征( PIRF)。并利用PIRF构建视觉词汇表,根据词汇表将图像的PIRF描述符映射为视觉单词频率矢量。多个视觉单词频率矢量构成的序列输入HTM网络,用于实现环境地图的学习与创建及环路场景的推断识别。采用两组实验数据验证文中方法,结果表明基于HTM的制图策略能成功建立环境地图,并能高效处理环路检测问题。%A map building method based on hierarchical temporal memory ( HTM) is proposed. The mapping problem is treated as scene recognition. The map is composed of a series of scenes being the outputs of HTM network. Firstly, the position invariant robust feature ( PIRF) is extracted from the obtained images and then the PIRFs are applied to build the visual vocabulary. Secondly, according to the visual vocabulary PIRF descriptors of an image are projected to the vector of visual word occurrences. Multiple visual word occurrences vectors are formed as a sequence of visual word occurrences. This sequence is inputted to HTM to implement the environment map learning and building and closed loop scenes recognition. The performance of the proposed mapping method is evaluated by two experiments. The results show that the proposed strategy based on HTM is effective for map building and closed loop detection.

  7. Mapping Plant Functional Types over Broad Mountainous Regions: A Hierarchical Soft Time-Space Classification Applied to the Tibetan Plateau

    Directory of Open Access Journals (Sweden)

    Danlu Cai

    2014-04-01

    Full Text Available Research on global climate change requires plant functional type (PFT products. Although several PFT mapping procedures for remote sensing imagery are being used, none of them appears to be specifically designed to map and evaluate PFTs over broad mountainous areas which are highly relevant regions to identify and analyze the response of natural ecosystems. We present a methodology for generating soft classifications of PFTs from remotely sensed time series that are based on a hierarchical strategy by integrating time varying integrated NDVI and phenological information with topography: (i Temporal variability: a Fourier transform of a vegetation index (MODIS NDVI, 2006 to 2010. (ii Spatial partitioning: a primary image segmentation based on a small number of thresholds applied to the Fourier amplitude. (iii Classification by a supervised soft classification step is based on a normalized distance metric constructed from a subset of Fourier coefficients and complimentary altitude data from a digital elevation model. Applicability and effectiveness is tested for the eastern Tibetan Plateau. A classification nomenclature is determined from temporally stable pixels in the MCD12Q1 time series. Overall accuracy statistics of the resulting classification reveal a gain of about 7% from 64.4% compared to 57.7% by the MODIS PFT products.

  8. Mapping brucellosis increases relative to elk density using hierarchical Bayesian models

    Science.gov (United States)

    Cross, Paul C.; Heisey, Dennis M.; Scurlock, Brandon M.; Edwards, William H.; Brennan, Angela; Ebinger, Michael R.

    2010-01-01

    The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus) in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km2; range = [95–10237]). The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.

  9. Mapping brucellosis increases relative to elk density using hierarchical Bayesian models.

    Directory of Open Access Journals (Sweden)

    Paul C Cross

    Full Text Available The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km(2; range = [95-10237]. The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.

  10. Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagram and a hierarchical task analysis diagram

    Directory of Open Access Journals (Sweden)

    Potts Henry WW

    2010-01-01

    Full Text Available Abstract Background Many quality and safety improvement methods in healthcare rely on a complete and accurate map of the process. Process mapping in healthcare is often achieved using a sequential flow diagram, but there is little guidance available in the literature about the most effective type of process map to use. Moreover there is evidence that the organisation of information in an external representation affects reasoning and decision making. This exploratory study examined whether the type of process map - sequential or hierarchical - affects healthcare practitioners' judgments. Methods A sequential and a hierarchical process map of a community-based anti coagulation clinic were produced based on data obtained from interviews, talk-throughs, attendance at a training session and examination of protocols and policies. Clinic practitioners were asked to specify the parts of the process that they judged to contain quality and safety concerns. The process maps were then shown to them in counter-balanced order and they were asked to circle on the diagrams the parts of the process where they had the greatest quality and safety concerns. A structured interview was then conducted, in which they were asked about various aspects of the diagrams. Results Quality and safety concerns cited by practitioners differed depending on whether they were or were not looking at a process map, and whether they were looking at a sequential diagram or a hierarchical diagram. More concerns were identified using the hierarchical diagram compared with the sequential diagram and more concerns were identified in relation to clinical work than administrative work. Participants' preference for the sequential or hierarchical diagram depended on the context in which they would be using it. The difficulties of determining the boundaries for the analysis and the granularity required were highlighted. Conclusions The results indicated that the layout of a process map does

  11. Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagram and a hierarchical task analysis diagram.

    Science.gov (United States)

    Colligan, Lacey; Anderson, Janet E; Potts, Henry W W; Berman, Jonathan

    2010-01-07

    Many quality and safety improvement methods in healthcare rely on a complete and accurate map of the process. Process mapping in healthcare is often achieved using a sequential flow diagram, but there is little guidance available in the literature about the most effective type of process map to use. Moreover there is evidence that the organisation of information in an external representation affects reasoning and decision making. This exploratory study examined whether the type of process map - sequential or hierarchical - affects healthcare practitioners' judgments. A sequential and a hierarchical process map of a community-based anti coagulation clinic were produced based on data obtained from interviews, talk-throughs, attendance at a training session and examination of protocols and policies. Clinic practitioners were asked to specify the parts of the process that they judged to contain quality and safety concerns. The process maps were then shown to them in counter-balanced order and they were asked to circle on the diagrams the parts of the process where they had the greatest quality and safety concerns. A structured interview was then conducted, in which they were asked about various aspects of the diagrams. Quality and safety concerns cited by practitioners differed depending on whether they were or were not looking at a process map, and whether they were looking at a sequential diagram or a hierarchical diagram. More concerns were identified using the hierarchical diagram compared with the sequential diagram and more concerns were identified in relation to clinical work than administrative work. Participants' preference for the sequential or hierarchical diagram depended on the context in which they would be using it. The difficulties of determining the boundaries for the analysis and the granularity required were highlighted. The results indicated that the layout of a process map does influence perceptions of quality and safety problems in a process. In

  12. Morphological self-organizing feature map neural network with applications to automatic target recognition

    Institute of Scientific and Technical Information of China (English)

    Shijun Zhang; Zhongliang Jing; Jianxun Li

    2005-01-01

    @@ The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and realworld infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

  13. Mapped Wetland Features for Miller Pond in the Lower Brule Indian Reservation, 2012-13

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Real-time kinematic global navigation satellite systems equipment was used to map features of wetlands at six locations of interest to the Lower Brule Sioux Tribe....

  14. Mapped Wetland Features for an Unnamed Wetland in the Lower Brule Indian Reservation

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Real-time kinematic global navigation satellite systems equipment was used to map features of wetlands at six locations of interest to the Lower Brule Sioux Tribe....

  15. Stability of radiomic features in CT perfusion maps

    Science.gov (United States)

    Bogowicz, M.; Riesterer, O.; Bundschuh, R. A.; Veit-Haibach, P.; Hüllner, M.; Studer, G.; Stieb, S.; Glatz, S.; Pruschy, M.; Guckenberger, M.; Tanadini-Lang, S.

    2016-12-01

    This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate  >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size

  16. Hierarchical multivariate mixture generalized linear models for the analysis of spatial data: An application to disease mapping.

    Science.gov (United States)

    Torabi, Mahmoud

    2016-09-01

    Disease mapping of a single disease has been widely studied in the public health setup. Simultaneous modeling of related diseases can also be a valuable tool both from the epidemiological and from the statistical point of view. In particular, when we have several measurements recorded at each spatial location, we need to consider multivariate models in order to handle the dependence among the multivariate components as well as the spatial dependence between locations. It is then customary to use multivariate spatial models assuming the same distribution through the entire population density. However, in many circumstances, it is a very strong assumption to have the same distribution for all the areas of population density. To overcome this issue, we propose a hierarchical multivariate mixture generalized linear model to simultaneously analyze spatial Normal and non-Normal outcomes. As an application of our proposed approach, esophageal and lung cancer deaths in Minnesota are used to show the outperformance of assuming different distributions for different counties of Minnesota rather than assuming a single distribution for the population density. Performance of the proposed approach is also evaluated through a simulation study. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

    Directory of Open Access Journals (Sweden)

    Hyungjin Kim

    2015-08-01

    Full Text Available Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments

  18. Methodologies of preparing erosion features map by using RS and GIS

    Institute of Scientific and Technical Information of China (English)

    Mohammadi Torkashvand Ali; Nikkami,Davood

    2008-01-01

    The erosion features map is one of the basic maps in erosion and sediment studies and watershed management programs.Some methodologies of preparing erosion features map by using RS and GIS were compared in research which took place in the Jajrood sub-basin in north-east Tehran,Iran.In the first phase,four working units' maps were prepared by integration a) plant cover,geology and slope b)land use,geology and slope c) land use,rocks sensitivity to erosion and slope and d) land use,rocks sensitivity to erosion and land units' layers.In addition to these four working units' maps,three more maps were also evaluated in separating erosion features including e) land units f) sensitivity of rocks to erosion and g) image photomorphic units.The efficiency of these seven working units' maps was evaluated by 314 control points.For this purpose,by using erosion features of control points regarding field views,surface,rill,gully and channel erosion maps were prepared and compared by crossing them with working units' maps.Results showed that method "d" was better than "a","b" and "c" in providing soil erosion features regarding economic and executive considerations.The accuracy of methods "e"and "f" was 53.0 and 42.9% and their Root Mean Squared Error was more than method "g" and methods "a" to "d".The coefficient of variation was highest for methods "e" and "f" and the least for method "e" and the greatest precision was related to image interpretation.

  19. Landscape features, standards, and semantics in U.S. national topographic mapping databases

    Science.gov (United States)

    Varanka, Dalia

    2009-01-01

    The objective of this paper is to examine the contrast between local, field-surveyed topographical representation and feature representation in digital, centralized databases and to clarify their ontological implications. The semantics of these two approaches are contrasted by examining the categorization of features by subject domains inherent to national topographic mapping. When comparing five USGS topographic mapping domain and feature lists, results indicate that multiple semantic meanings and ontology rules were applied to the initial digital database, but were lost as databases became more centralized at national scales, and common semantics were replaced by technological terms.

  20. Mapping the structural and dynamical features of kinesin motor domains.

    Directory of Open Access Journals (Sweden)

    Guido Scarabelli

    Full Text Available Kinesin motor proteins drive intracellular transport by coupling ATP hydrolysis to conformational changes that mediate directed movement along microtubules. Characterizing these distinct conformations and their interconversion mechanism is essential to determining an atomic-level model of kinesin action. Here we report a comprehensive principal component analysis of 114 experimental structures along with the results of conventional and accelerated molecular dynamics simulations that together map the structural dynamics of the kinesin motor domain. All experimental structures were found to reside in one of three distinct conformational clusters (ATP-like, ADP-like and Eg5 inhibitor-bound. These groups differ in the orientation of key functional elements, most notably the microtubule binding α4-α5, loop8 subdomain and α2b-β4-β6-β7 motor domain tip. Group membership was found not to correlate with the nature of the bound nucleotide in a given structure. However, groupings were coincident with distinct neck-linker orientations. Accelerated molecular dynamics simulations of ATP, ADP and nucleotide free Eg5 indicate that all three nucleotide states could sample the major crystallographically observed conformations. Differences in the dynamic coupling of distal sites were also evident. In multiple ATP bound simulations, the neck-linker, loop8 and the α4-α5 subdomain display correlated motions that are absent in ADP bound simulations. Further dissection of these couplings provides evidence for a network of dynamic communication between the active site, microtubule-binding interface and neck-linker via loop7 and loop13. Additional simulations indicate that the mutations G325A and G326A in loop13 reduce the flexibility of these regions and disrupt their couplings. Our combined results indicate that the reported ATP and ADP-like conformations of kinesin are intrinsically accessible regardless of nucleotide state and support a model where neck

  1. Ensemble based system for whole-slide prostate cancer probability mapping using color texture features.

    LENUS (Irish Health Repository)

    DiFranco, Matthew D

    2011-01-01

    We present a tile-based approach for producing clinically relevant probability maps of prostatic carcinoma in histological sections from radical prostatectomy. Our methodology incorporates ensemble learning for feature selection and classification on expert-annotated images. Random forest feature selection performed over varying training sets provides a subset of generalized CIEL*a*b* co-occurrence texture features, while sample selection strategies with minimal constraints reduce training data requirements to achieve reliable results. Ensembles of classifiers are built using expert-annotated tiles from training images, and scores for the probability of cancer presence are calculated from the responses of each classifier in the ensemble. Spatial filtering of tile-based texture features prior to classification results in increased heat-map coherence as well as AUC values of 95% using ensembles of either random forests or support vector machines. Our approach is designed for adaptation to different imaging modalities, image features, and histological decision domains.

  2. Prioritizing the risk of plant pests by clustering methods; self-organising maps, k-means and hierarchical clustering

    Directory of Open Access Journals (Sweden)

    Susan Worner

    2013-09-01

    Full Text Available For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased, relying mostly on expert and stakeholder consultation. In recent years, cluster based analyses have been used to investigate regional pest species assemblages or pest profiles to indicate the risk of new organism establishment. Such an approach is based on the premise that the co-occurrence of well-known global invasive pest species in a region is not random, and that the pest species profile or assemblage integrates complex functional relationships that are difficult to tease apart. In other words, the assemblage can help identify and prioritise species that pose a threat in a target region. A computational intelligence method called a Kohonen self-organizing map (SOM, a type of artificial neural network, was the first clustering method applied to analyse assemblages of invasive pests. The SOM is a well known dimension reduction and visualization method especially useful for high dimensional data that more conventional clustering methods may not analyse suitably. Like all clustering algorithms, the SOM can give details of clusters that identify regions with similar pest assemblages, possible donor and recipient regions. More important, however SOM connection weights that result from the analysis can be used to rank the strength of association of each species within each regional assemblage. Species with high weights that are not already established in the target region are identified as high risk. However, the SOM analysis is only the first step in a process to assess risk to be used alongside or incorporated within other measures. Here we illustrate the application of SOM analyses in a range of contexts in invasive species risk assessment, and discuss other clustering methods such as k

  3. Evolutionary Feature Selection for Big Data Classification: A MapReduce Approach

    Directory of Open Access Journals (Sweden)

    Daniel Peralta

    2015-01-01

    Full Text Available Nowadays, many disciplines have to deal with big datasets that additionally involve a high number of features. Feature selection methods aim at eliminating noisy, redundant, or irrelevant features that may deteriorate the classification performance. However, traditional methods lack enough scalability to cope with datasets of millions of instances and extract successful results in a delimited time. This paper presents a feature selection algorithm based on evolutionary computation that uses the MapReduce paradigm to obtain subsets of features from big datasets. The algorithm decomposes the original dataset in blocks of instances to learn from them in the map phase; then, the reduce phase merges the obtained partial results into a final vector of feature weights, which allows a flexible application of the feature selection procedure using a threshold to determine the selected subset of features. The feature selection method is evaluated by using three well-known classifiers (SVM, Logistic Regression, and Naive Bayes implemented within the Spark framework to address big data problems. In the experiments, datasets up to 67 millions of instances and up to 2000 attributes have been managed, showing that this is a suitable framework to perform evolutionary feature selection, improving both the classification accuracy and its runtime when dealing with big data problems.

  4. Implementation of extended Kalman filter-based simultaneous localization and mapping: a point feature approach

    Indian Academy of Sciences (India)

    MANIGANDAN NAGARAJAN SANTHANAKRISHNAN; JOHN BOSCO BALAGURU RAYAPPAN; RAMKUMAR KANNAN

    2017-09-01

    The implementation of extended Kalman filter-based simultaneous localization and mapping is challenging as the associated system state and covariance matrices along with the memory requirements become significantly large as the information space increases. Unique and consistent point features representing a segment of the map would be an optimal choice to control the size of covariance matrix and maximize the operating speed in a real-time scenario. A two-wheel differential drive mobile robot equipped with a Laser Range Finder with 0.02 m resolution was used for the implementation. Unique point features from the environment were extracted through an elegant line fitting algorithm, namely split only technique. Finally, the implementation showed remarkably good results with a success rate of 98% in feature identification and ±0.08 to ±0.11 m deviation in the generated map

  5. Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping

    Directory of Open Access Journals (Sweden)

    Veronika Kopačková

    2017-09-01

    Full Text Available Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS, near-infrared (NIR, shortwave infrared (SWIR and longwave infrared (LWIR spectral ranges, these different spectral ranges were analysed and interpreted separately. This limits the complexity of the final interpretation. In this study a presentation is made of how multiple absorption features, which are directly linked to the mineral composition and are present throughout the VIS, NIR, SWIR and LWIR ranges, can be automatically derived and, moreover, how these new datasets can be successfully used for mineral/lithology mapping. The biggest advantage of this approach is that it overcomes the issue of prior definition of endmembers, which is a requested routine employed in all widely used spectral mapping techniques. In this study, two different airborne image datasets were analysed, HyMap (VIS/NIR/SWIR image data and Airborne Hyperspectral Scanner (AHS, LWIR image data. Both datasets were acquired over the Sokolov lignite open-cast mines in the Czech Republic. It is further demonstrated that even in this case, when the absorption feature information derived from multispectral LWIR data is integrated with the absorption feature information derived from hyperspectral VIS/NIR/SWIR data, an important improvement in terms of more complex mineral mapping is achieved.

  6. Probability mapping of scarred myocardium using texture and intensity features in CMR images

    Science.gov (United States)

    2013-01-01

    Background The myocardium exhibits heterogeneous nature due to scarring after Myocardial Infarction (MI). In Cardiac Magnetic Resonance (CMR) imaging, Late Gadolinium (LG) contrast agent enhances the intensity of scarred area in the myocardium. Methods In this paper, we propose a probability mapping technique using Texture and Intensity features to describe heterogeneous nature of the scarred myocardium in Cardiac Magnetic Resonance (CMR) images after Myocardial Infarction (MI). Scarred tissue and non-scarred tissue are represented with high and low probabilities, respectively. Intermediate values possibly indicate areas where the scarred and healthy tissues are interwoven. The probability map of scarred myocardium is calculated by using a probability function based on Bayes rule. Any set of features can be used in the probability function. Results In the present study, we demonstrate the use of two different types of features. One is based on the mean intensity of pixel and the other on underlying texture information of the scarred and non-scarred myocardium. Examples of probability maps computed using the mean intensity of pixel and the underlying texture information are presented. We hypothesize that the probability mapping of myocardium offers alternate visualization, possibly showing the details with physiological significance difficult to detect visually in the original CMR image. Conclusion The probability mapping obtained from the two features provides a way to define different cardiac segments which offer a way to identify areas in the myocardium of diagnostic importance (like core and border areas in scarred myocardium). PMID:24053280

  7. Towards High-Definition 3D Urban Mapping: Road Feature-Based Registration of Mobile Mapping Systems and Aerial Imagery

    Directory of Open Access Journals (Sweden)

    Mahdi Javanmardi

    2017-09-01

    Full Text Available Various applications have utilized a mobile mapping system (MMS as the main 3D urban remote sensing platform. However, the accuracy and precision of the three-dimensional data acquired by an MMS is highly dependent on the performance of the vehicle’s self-localization, which is generally performed by high-end global navigation satellite system (GNSS/inertial measurement unit (IMU integration. However, GNSS/IMU positioning quality degrades significantly in dense urban areas with high-rise buildings, which block and reflect the satellite signals. Traditional landmark updating methods, which improve MMS accuracy by measuring ground control points (GCPs and manually identifying those points in the data, are both labor-intensive and time-consuming. In this paper, we propose a novel and comprehensive framework for automatically georeferencing MMS data by capitalizing on road features extracted from high-resolution aerial surveillance data. The proposed framework has three key steps: (1 extracting road features from the MMS and aerial data; (2 obtaining Gaussian mixture models from the extracted aerial road features; and (3 performing registration of the MMS data to the aerial map using a dynamic sliding window and the normal distribution transform (NDT. The accuracy of the proposed framework is verified using field data, demonstrating that it is a reliable solution for high-precision urban mapping.

  8. Mapping the Indonesian territory, based on pollution, social demography and geographical data, using self organizing feature map

    Science.gov (United States)

    Hernawati, Kuswari; Insani, Nur; Bambang S. H., M.; Nur Hadi, W.; Sahid

    2017-08-01

    This research aims to mapping the 33 (thirty-three) provinces in Indonesia, based on the data on air, water and soil pollution, as well as social demography and geography data, into a clustered model. The method used in this study was unsupervised method that combines the basic concept of Kohonen or Self-Organizing Feature Maps (SOFM). The method is done by providing the design parameters for the model based on data related directly/ indirectly to pollution, which are the demographic and social data, pollution levels of air, water and soil, as well as the geographical situation of each province. The parameters used consists of 19 features/characteristics, including the human development index, the number of vehicles, the availability of the plant's water absorption and flood prevention, as well as geographic and demographic situation. The data used were secondary data from the Central Statistics Agency (BPS), Indonesia. The data are mapped into SOFM from a high-dimensional vector space into two-dimensional vector space according to the closeness of location in term of Euclidean distance. The resulting outputs are represented in clustered grouping. Thirty-three provinces are grouped into five clusters, where each cluster has different features/characteristics and level of pollution. The result can used to help the efforts on prevention and resolution of pollution problems on each cluster in an effective and efficient way.

  9. Adaptive training of cortical feature maps for a robot sensorimotor controller.

    Science.gov (United States)

    Adams, Samantha V; Wennekers, Thomas; Denham, Sue; Culverhouse, Phil F

    2013-08-01

    This work investigates self-organising cortical feature maps (SOFMs) based upon the Kohonen Self-Organising Map (SOM) but implemented with spiking neural networks. In future work, the feature maps are intended as the basis for a sensorimotor controller for an autonomous humanoid robot. Traditional SOM methods require some modifications to be useful for autonomous robotic applications. Ideally the map training process should be self-regulating and not require predefined training files or the usual SOM parameter reduction schedules. It would also be desirable if the organised map had some flexibility to accommodate new information whilst preserving previous learnt patterns. Here methods are described which have been used to develop a cortical motor map training system which goes some way towards addressing these issues. The work is presented under the general term 'Adaptive Plasticity' and the main contribution is the development of a 'plasticity resource' (PR) which is modelled as a global parameter which expresses the rate of map development and is related directly to learning on the afferent (input) connections. The PR is used to control map training in place of a traditional learning rate parameter. In conjunction with the PR, random generation of inputs from a set of exemplar patterns is used rather than predefined datasets and enables maps to be trained without deciding in advance how much data is required. An added benefit of the PR is that, unlike a traditional learning rate, it can increase as well as decrease in response to the demands of the input and so allows the map to accommodate new information when the inputs are changed during training.

  10. Efficient feature extraction from wide-area motion imagery by MapReduce in Hadoop

    Science.gov (United States)

    Cheng, Erkang; Ma, Liya; Blaisse, Adam; Blasch, Erik; Sheaff, Carolyn; Chen, Genshe; Wu, Jie; Ling, Haibin

    2014-06-01

    Wide-Area Motion Imagery (WAMI) feature extraction is important for applications such as target tracking, traffic management and accident discovery. With the increasing amount of WAMI collections and feature extraction from the data, a scalable framework is needed to handle the large amount of information. Cloud computing is one of the approaches recently applied in large scale or big data. In this paper, MapReduce in Hadoop is investigated for large scale feature extraction tasks for WAMI. Specifically, a large dataset of WAMI images is divided into several splits. Each split has a small subset of WAMI images. The feature extractions of WAMI images in each split are distributed to slave nodes in the Hadoop system. Feature extraction of each image is performed individually in the assigned slave node. Finally, the feature extraction results are sent to the Hadoop File System (HDFS) to aggregate the feature information over the collected imagery. Experiments of feature extraction with and without MapReduce are conducted to illustrate the effectiveness of our proposed Cloud-Enabled WAMI Exploitation (CAWE) approach.

  11. Feature Specific Criminal Mapping using Data Mining Techniques and Generalized Gaussian Mixture Model

    Directory of Open Access Journals (Sweden)

    Uttam Mande

    2012-06-01

    Full Text Available Lot of research is projected to map the criminal with that of crime and it is observed that there is still a huge increase in the crime rate due to the gap between the optimal usage of technologies and investigation. This has given scope for the development of new methodologies in the area of crime investigation using the techniques based on data mining, image processing, forensic, and social mining. In this paper, presents a model using new methodology for mapping the criminal with the crime. This model clusters the criminal data basing on the type crime. When a crime occurs, based on the eye witness specified features, the criminal is mapped. Here we propose a novel methodology that uses Generalized Gaussian Mixture Model to map the features specified by the eyewitness with that of the features of the criminal who have committed the same type of the crime, if the criminal is not mapped, the suspect table is checked and the reports are generated

  12. Vision-based topological map building and localisation using persistent features

    CSIR Research Space (South Africa)

    Sabatta, DG

    2008-11-01

    Full Text Available of the image onto the right and vice versa. We copy a segment equal to the height of the panoramic image from each side resulting in a 1200 x 200 pixel image. The SIFT algorithm that we use has been modified to incorpo- rate colour information. The colour... of a feature “snake”. A snake of features is a list of feature IDs related to successive frames from the dataset for which a positive match was obtained using the method of Section III-A. The heart of the map building algorithm is centred around a...

  13. Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays

    Directory of Open Access Journals (Sweden)

    Hu Shengwa

    2009-05-01

    Full Text Available Abstract Background Wheat (Triticum aestivum L. is a staple food crop worldwide. The wheat genome has not yet been sequenced due to its huge genome size (~17,000 Mb and high levels of repetitive sequences; the whole genome sequence may not be expected in the near future. Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps. A high-resolution map is a critical tool for gene isolation, molecular breeding and genomic research. Single feature polymorphism (SFP is a new microarray-based type of marker that is detected by hybridization of DNA or cRNA to oligonucleotide probes. This study was conducted to explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome. Results Six wheat varieties of diverse origins (Ning 7840, Clark, Jagger, Encruzilhada, Chinese Spring, and Opata 85 were analyzed for significant probe by variety interactions and 396 probe sets with SFPs were identified. A subset of 164 unigenes was sequenced and 54% showed polymorphism within probes. Microarray analysis of 71 recombinant inbred lines from the cross Ning 7840/Clark identified 955 SFPs and 877 of them were mapped together with 269 simple sequence repeat markers. The SFPs were randomly distributed within a chromosome but were unevenly distributed among different genomes. The B genome had the most SFPs, and the D genome had the least. Map positions of a selected set of SFPs were validated by mapping single nucleotide polymorphism using SNaPshot and comparing with expressed sequence tags mapping data. Conclusion The Affymetrix array is a cost-effective platform for SFP discovery and SFP mapping in wheat. The new high-density map constructed in this study will be a useful tool for genetic and genomic research in wheat.

  14. a Performance Comparison of Feature Detectors for Planetary Rover Mapping and Localization

    Science.gov (United States)

    Wan, W.; Peng, M.; Xing, Y.; Wang, Y.; Liu, Z.; Di, K.; Teng, B.; Mao, X.; Zhao, Q.; Xin, X.; Jia, M.

    2017-07-01

    Feature detection and matching are key techniques in computer vision and robotics, and have been successfully implemented in many fields. So far there is no performance comparison of feature detectors and matching methods for planetary mapping and rover localization using rover stereo images. In this research, we present a comprehensive evaluation and comparison of six feature detectors, including Moravec, Förstner, Harris, FAST, SIFT and SURF, aiming for optimal implementation of feature-based matching in planetary surface environment. To facilitate quantitative analysis, a series of evaluation criteria, including distribution evenness of matched points, coverage of detected points, and feature matching accuracy, are developed in the research. In order to perform exhaustive evaluation, stereo images, simulated under different baseline, pitch angle, and interval of adjacent rover locations, are taken as experimental data source. The comparison results show that SIFT offers the best overall performance, especially it is less sensitive to changes of image taken at adjacent locations.

  15. Hierarchical Object-Based Mapping of Riverscape Units and in-Stream Mesohabitats Using LiDAR and VHR Imagery

    Directory of Open Access Journals (Sweden)

    Luca Demarchi

    2016-01-01

    Full Text Available In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS data. This novel approach is based on the integration of spectral and topographic information within a multilevel, geographic, object-based image analysis (GEOBIA. Different segmentation levels were generated based on the two sources of Remote Sensing (RS data, namely very-high spatial resolution, near-infrared imagery (VHR and high-resolution LiDAR topography. At each level, different input object features were tested with Machine Learning classifiers for mapping riverscape units and in-stream mesohabitats. The GEOBIA approach proved to be a powerful tool for analyzing the river system at different levels of detail and for coupling spectral and topographic datasets, allowing for the delineation of the natural fluvial corridor with its primary riverscape units (e.g., water channel, unvegetated sediment bars, riparian densely-vegetated units, etc. and in-stream mesohabitats with a high level of accuracy, respectively of K = 0.91 and K = 0.83. This method is flexible and can be adapted to different sources of data, with the potential to be implemented at regional scales in the future. The analyzed dataset, composed of VHR imagery and LiDAR data, is nowadays increasingly available at larger scales, notably through European Member States. At the same time, this methodology provides a tool for monitoring and characterizing the hydromorphological status of river systems continuously along the entire channel network and coherently through time, opening novel and significant perspectives to river science and management, notably for planning and targeting actions.

  16. Design of vector quantizer for image compression using self-organizing feature map and surface fitting.

    Science.gov (United States)

    Laha, Arijit; Pal, Nikhil R; Chanda, Bhabatosh

    2004-10-01

    We propose a new scheme of designing a vector quantizer for image compression. First, a set of codevectors is generated using the self-organizing feature map algorithm. Then, the set of blocks associated with each code vector is modeled by a cubic surface for better perceptual fidelity of the reconstructed images. Mean-removed vectors from a set of training images is used for the construction of a generic codebook. Further, Huffman coding of the indices generated by the encoder and the difference-coded mean values of the blocks are used to achieve better compression ratio. We proposed two indices for quantitative assessment of the psychovisual quality (blocking effect) of the reconstructed image. Our experiments on several training and test images demonstrate that the proposed scheme can produce reconstructed images of good quality while achieving compression at low bit rates. Index Terms-Cubic surface fitting, generic codebook, image compression, self-organizing feature map, vector quantization.

  17. Hierarchical image segmentation for learning object priors

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

  18. Effective palette indexing for image compression using self-organization of Kohonen feature map.

    Science.gov (United States)

    Pei, Soo-Chang; Chuang, Yu-Ting; Chuang, Wei-Hong

    2006-09-01

    The process of limited-color image compression usually involves color quantization followed by palette re-indexing. Palette re-indexing could improve the compression of color-indexed images, but it is still complicated and consumes extra time. Making use of the topology-preserving property of self-organizing Kohonen feature map, we can generate a fairly good color index table to achieve both high image quality and high compression, without re-indexing. Promising experiment results will be presented.

  19. Hierarchical Design Method for Micro Device

    Directory of Open Access Journals (Sweden)

    Zheng Liu

    2013-05-01

    Full Text Available Traditional mask-beginning design flow of micro device is unintuitive and fussy for designers. A hierarchical design method and involved key technologies for features mapping procedure are presented. With the feature-based design framework, the model of micro device is organized by various features in different designing stages, which can be converted into each other based on the mapping rules. The feature technology is the foundation of the three-level design flow that provides a more efficient design way. In system level, functional features provide the top level of schematic and functional description. After the functional mapping procedure, on the other hand, parametric design features construct the 3D model of micro device in device level, which is based on Hybird Model representation. By means of constraint features, the corresponding revision rules are applied to the rough model to optimize the original structure. As a result, the model reconstruction algorithm makes benefit for the model revision and constraint features mapping process. Moreover, the formulating description of manufacturing features derivation provides the automatic way for model conversion.

  20. Manifold Learning with Self-Organizing Mapping for Feature Extraction of Nonlinear Faults in Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Lin Liang

    2015-01-01

    Full Text Available A new method for extracting the low-dimensional feature automatically with self-organization mapping manifold is proposed for the detection of rotating mechanical nonlinear faults (such as rubbing, pedestal looseness. Under the phase space reconstructed by single vibration signal, the self-organization mapping (SOM with expectation maximization iteration algorithm is used to divide the local neighborhoods adaptively without manual intervention. After that, the local tangent space alignment algorithm is adopted to compress the high-dimensional phase space into low-dimensional feature space. The proposed method takes advantages of the manifold learning in low-dimensional feature extraction and adaptive neighborhood construction of SOM and can extract intrinsic fault features of interest in two dimensional projection space. To evaluate the performance of the proposed method, the Lorenz system was simulated and rotation machinery with nonlinear faults was obtained for test purposes. Compared with the holospectrum approaches, the results reveal that the proposed method is superior in identifying faults and effective for rotating machinery condition monitoring.

  1. Acquiring concepts and features of novel words by two types of learning: direct mapping and inference.

    Science.gov (United States)

    Chen, Shuang; Wang, Lin; Yang, Yufang

    2014-04-01

    This study examined the semantic representation of novel words learnt in two conditions: directly mapping a novel word to a concept (Direct mapping: DM) and inferring the concept from provided features (Inferred learning: IF). A condition where no definite concept could be inferred (No basic-level meaning: NM) served as a baseline. The semantic representation of the novel word was assessed via a semantic-relatedness judgment task. In this task, the learned novel word served as a prime, while the corresponding concept, an unlearned feature of the concept, and an unrelated word served as targets. ERP responses to the targets, primed by the novel words in the three learning conditions, were compared. For the corresponding concept, smaller N400s were elicited in the DM and IF conditions than in the NM condition, indicating that the concept could be obtained in both learning conditions. However, for the unlearned feature, the targets in the IF condition produced an N400 effect while in the DM condition elicited an LPC effect relative to the NM learning condition. No ERP difference was observed among the three learning conditions for the unrelated words. The results indicate that conditions of learning affect the semantic representation of novel word, and that the unlearned feature was only activated by the novel word in the IF learning condition.

  2. CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping

    Directory of Open Access Journals (Sweden)

    Shi Weisong

    2011-06-01

    Full Text Available Abstract Background Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS. However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. Results To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80% mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http

  3. CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping.

    Science.gov (United States)

    Nguyen, Tung; Shi, Weisong; Ruden, Douglas

    2011-06-06

    Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS). However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80%) mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http://cloudaligner.sourceforge.net/ and its web version is at http

  4. Using Mobile Laser Scanning Data for Features Extraction of High Accuracy Driving Maps

    Science.gov (United States)

    Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Dong, Zhen

    2016-06-01

    High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

  5. Feature-Based Laser Scan Matching and Its Application for Indoor Mapping

    Directory of Open Access Journals (Sweden)

    Jiayuan Li

    2016-08-01

    Full Text Available Scan matching, an approach to recover the relative position and orientation of two laser scans, is a very important technique for indoor positioning and indoor modeling. The iterative closest point (ICP algorithm and its variants are the most well-known techniques for such a problem. However, ICP algorithms rely highly on the initial guess of the relative transformation, which will reduce its power for practical applications. In this paper, an initial-free 2D laser scan matching method based on point and line features is proposed. We carefully design a framework for the detection of point and line feature correspondences. First, distinct feature points are detected based on an extended 1D SIFT, and line features are extracted via a modified Split-and-Merge algorithm. In this stage, we also give an effective strategy for discarding unreliable features. The point and line features are then described by a distance histogram; the pairs achieving best matching scores are accepted as potential correct correspondences. The histogram cluster technique is adapted to filter outliers and provide an accurate initial value of the rigid transformation. We also proposed a new relative pose estimation method that is robust to outliers. We use the lq-norm (0 < q < 1 metric in this approach, in contrast to classic optimization methods whose cost function is based on the l2-norm of residuals. Extensive experiments on real data demonstrate that the proposed method is almost as accurate as ICPs and is initial free. We also show that our scan matching method can be integrated into a simultaneous localization and mapping (SLAM system for indoor mapping.

  6. Digital field mapping for stimulating Secondary School students in the recognition of geological features and landforms

    Science.gov (United States)

    Giardino, Marco; Magagna, Alessandra; Ferrero, Elena; Perrone, Gianluigi

    2015-04-01

    Piedmont region, and in the Sesia Val Grande Geopark, for testing the utility of digital field mapping in Geoscience education. Feedback from students are positive: they are stimulated and involved by the use of ICT for learning Geoscience, and they voluntary choose to work with their personal mobile device (more than 90% of them own a smartphone); they are interested in knowing the features of GPS, and of software for the visualization of satellite and aerial images, but they recognize the importance of integrating and comparing traditional and innovative methods in the field.

  7. Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Feature Map

    Science.gov (United States)

    Motter, Mark A.

    1998-01-01

    A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are

  8. Intelligent Control of the Complex Technology Process Based on Adaptive Pattern Clustering and Feature Map

    Directory of Open Access Journals (Sweden)

    Wushan Cheng

    2008-01-01

    Full Text Available A kind of fuzzy neural networks (FNNs based on adaptive pattern clustering and feature map (APCFM is proposed to improve the property of the large delay and time varying of the sintering process. By using the density clustering and learning vector quantization (LVQ, the sintering process is divided automatically into subclasses which have similar clustering center and labeled fitting number. Then these labeled subclass samples are taken into fuzzy neural network (FNN to be trained; this network is used to solve the prediction problem of the burning through point (BTP. Using the 707 groups of actual training process data and the FNN to train APCFM algorithm, experiments prove that the system has stronger robustness and wide generality in clustering analysis and feature extraction.

  9. Development of an ultra-dense genetic map of the sunflower genome based on single-feature polymorphisms.

    Directory of Open Access Journals (Sweden)

    John E Bowers

    Full Text Available The development of ultra-dense genetic maps has the potential to facilitate detailed comparative genomic analyses and whole genome sequence assemblies. Here we describe the use of a custom Affymetrix GeneChip containing nearly 2.4 million features (25 bp sequences targeting 86,023 unigenes from sunflower (Helianthus annuus L. and related species to test for single-feature polymorphisms (SFPs in a recombinant inbred line (RIL mapping population derived from a cross between confectionery and oilseed sunflower lines (RHA280×RHA801. We then employed an existing genetic map derived from this same population to rigorously filter out low quality data and place 67,486 features corresponding to 22,481 unigenes on the sunflower genetic map. The resulting map contains a substantial fraction of all sunflower genes and will thus facilitate a number of downstream applications, including genome assembly and the identification of candidate genes underlying QTL or traits of interest.

  10. Mapped Wetland Features for a part of Dorman Slough near the Lower Brule Indian Reservation, 2012-13

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Real-time kinematic global navigation satellite systems equipment was used to map features of wetlands at six locations of interest to the Lower Brule Sioux Tribe....

  11. Mapped Wetland Features for Wetlands near the Community of West Brule in the Lower Brule Indian Reservation, 2012-13

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Real-time kinematic global navigation satellite systems equipment was used to map features of wetlands at six locations of interest to the Lower Brule Sioux Tribe....

  12. Mapped Wetland Features for part of Potter Slough near the Lower Brule Indian Reservation, 2012-13

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Real-time kinematic global navigation satellite systems equipment was used to map features of wetlands at six locations of interest to the Lower Brule Sioux Tribe....

  13. Mapped Wetland Features for the Little Bend Wetlands in the Lower Brule Indian Reservation, 2012-13

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Real-time kinematic global navigation satellite systems equipment was used to map features of wetlands at six locations of interest to the Lower Brule Sioux Tribe....

  14. Boolean map saliency combined with motion feature used for dim and small target detection in infrared video sequences

    Science.gov (United States)

    Wang, Xiaoyang; Peng, Zhenming; Zhang, Ping

    2016-10-01

    Infrared dim and small target detection plays an important role in infrared search and tracking systems. In this paper, a novel infrared dim and small target detection method based on Boolean map saliency and motion feature is proposed. Infrared targets are the most salient parts in images, with high gray level and continuous moving trajectory. Utilizing this property, we build a feature space containing gray level feature and motion feature. The gray level feature is the intensity of input images, while the motion feature is obtained by motion charge in consecutive frames. In the second step, the Boolean map saliency approach is implemented on the gray level feature and motion feature to obtain the gray saliency map and motion saliency map. In the third step, two saliency maps are combined together to get the final result. Numerical experiments have verified the effectiveness of the proposed method. The final detection result can not only get an accurate detection result, but also with fewer false alarms, which is suitable for practical use.

  15. Feature Point Extraction from the Local Frequency Map of an Image

    Directory of Open Access Journals (Sweden)

    Jesmin Khan

    2012-01-01

    Full Text Available We propose a novel technique for detecting rotation- and scale-invariant interest points from the local frequency representation of an image. Local or instantaneous frequency is the spatial derivative of the local phase, where the local phase of any signal can be found from its Hilbert transform. Local frequency estimation can detect edge, ridge, corner, and texture information at the same time, and it shows high values at those dominant features of an image. For each pixel, we select an appropriate width of the window for computing the derivative of the phase. In order to select the width of the window for any given pixel, we make use of the measure of the extent to which the phases, in the neighborhood of that pixel, are in the same direction. The local frequency map, thus obtained, is then thresholded by employing a global thresholding approach to detect the interest or feature points. Repeatability rate, a performance evaluation criterion for an interest point detector, is used to check the geometric stability of the proposed method under different transformations. We present simulation results of the detection of feature points from image utilizing the suggested technique and compare the proposed method with five existing approaches that yield good results. The results prove the efficacy of the proposed feature point detection algorithm. Moreover, in terms of repeatability rate; the results show that the performance of the proposed method with respect to different aspect is compatible with the existing methods.

  16. Classifying content-based Images using Self Organizing Map Neural Networks Based on Nonlinear Features

    Directory of Open Access Journals (Sweden)

    Ebrahim Parcham

    2014-07-01

    Full Text Available Classifying similar images is one of the most interesting and essential image processing operations. Presented methods have some disadvantages like: low accuracy in analysis step and low speed in feature extraction process. In this paper, a new method for image classification is proposed in which similarity weight is revised by means of information in related and unrelated images. Based on researchers’ idea, most of real world similarity measurement systems are nonlinear. Thus, traditional linear methods are not capable of recognizing nonlinear relationship and correlation in such systems. Undoubtedly, Self Organizing Map neural networks are strongest networks for data mining and nonlinear analysis of sophisticated spaces purposes. In our proposed method, we obtain images with the most similarity measure by extracting features of our target image and comparing them with the features of other images. We took advantage of NLPCA algorithm for feature extraction which is a nonlinear algorithm that has the ability to recognize the smallest variations even in noisy images. Finally, we compare the run time and efficiency of our proposed method with previous proposed methods.

  17. The Use of Self Organizing Map Method and Feature Selection in Image Database Classification System

    CERN Document Server

    Pratiwi, Dian

    2012-01-01

    This paper presents a technique in classifying the images into a number of classes or clusters desired by means of Self Organizing Map (SOM) Artificial Neural Network method. A number of 250 color images to be classified as previously done some processing, such as RGB to grayscale color conversion, color histogram, feature vector selection, and then classifying by the SOM Feature vector selection in this paper will use two methods, namely by PCA (Principal Component Analysis) and LSA (Latent Semantic Analysis) in which each of these methods would have taken the characteristic vector of 50, 100, and 150 from 256 initial feature vector into the process of color histogram. Then the selection will be processed into the SOM network to be classified into five classes using a learning rate of 0.5 and calculated accuracy. Classification of some of the test results showed that the highest percentage of accuracy obtained when using PCA and the selection of 100 feature vector that is equal to 88%, compared to when using...

  18. booc.io: An Education System with Hierarchical Concept Maps and Dynamic Non-linear Learning Plans.

    Science.gov (United States)

    Schwab, Michail; Strobelt, Hendrik; Tompkin, James; Fredericks, Colin; Huff, Connor; Higgins, Dana; Strezhnev, Anton; Komisarchik, Mayya; King, Gary; Pfister, Hanspeter

    2017-01-01

    Information hierarchies are difficult to express when real-world space or time constraints force traversing the hierarchy in linear presentations, such as in educational books and classroom courses. We present booc.io, which allows linear and non-linear presentation and navigation of educational concepts and material. To support a breadth of material for each concept, booc.io is Web based, which allows adding material such as lecture slides, book chapters, videos, and LTIs. A visual interface assists the creation of the needed hierarchical structures. The goals of our system were formed in expert interviews, and we explain how our design meets these goals. We adapt a real-world course into booc.io, and perform introductory qualitative evaluation with students.

  19. Segmentation of color images by chromaticity features using self-organizing maps

    Directory of Open Access Journals (Sweden)

    Farid García-Lamont

    2016-08-01

    Full Text Available Usually, the segmentation of color images is performed using cluster-based methods and the RGB space to represent the colors. The drawback with these methods is the a priori knowledge of the number of groups, or colors, in the image; besides, the RGB space issensitive to the intensity of the colors. Humans can identify different sections within a scene by the chromaticity of its colors of, as this is the feature humans employ to tell them apart. In this paper, we propose to emulate the human perception of color by training a self-organizing map (SOM with samples of chromaticity of different colors. The image to process is mapped to the HSV space because in this space the chromaticity is decoupled from the intensity, while in the RGB space this is not possible. Our proposal does not require knowing a priori the number of colors within a scene, and non-uniform illumination does not significantly affect the image segmentation. We present experimental results using some images from the Berkeley segmentation database by employing SOMs with different sizes, which are segmented successfully using only chromaticity features.

  20. Interpretation of fingerprint image quality features extracted by self-organizing maps

    Science.gov (United States)

    Danov, Ivan; Olsen, Martin A.; Busch, Christoph

    2014-05-01

    Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

  1. Application of Geologic Mapping Techniques and Autonomous Feature Detection to Future Exploration of Europa

    Science.gov (United States)

    Bunte, M. K.; Tanaka, K. L.; Doggett, T.; Figueredo, P. H.; Lin, Y.; Greeley, R.; Saripalli, S.; Bell, J. F.

    2013-12-01

    Europa's extremely young surface age, evidence for extensive resurfacing, and indications of a sub-surface ocean elevate its astrobiological potential for habitable environments and make it a compelling focus for study. Knowledge of the global distribution and timing of Europan geologic units is a key step in understanding the history of the satellite and for identifying areas relevant for exploration. I have produced a 1:15M scale global geologic map of Europa which represents a proportionate distribution of four unit types and associated features: plains, linea, chaos, and crater materials. Mapping techniques differ somewhat from other planetary maps but do provide a method to establish stratigraphic markers and to illustrate the surface history through four periods of formation as a function of framework lineament cross-cutting relationships. Correlations of observed features on Europa with Earth analogs enforce a multi-process theory for formation rather than the typical reliance on the principle of parsimony. Lenticulae and microchaos are genetically similar and most likely form by diapirism. Platy and blocky chaos units, endmembers of archetypical chaos, are best explained by brine mobilization. Ridges account for the majority of lineaments and may form by a number of methods indicative of local conditions; most form by either tidal pumping or shear heating. The variety of morphologies exhibited by bands indicates that multiple formation mechanisms apply once fracturing of the brittle surface over a ductile subsurface is initiated. Mapping results support the interpretation that Europa's shell has thickened over time resulting in changes in the style and intensity of deformation. Mapping serves as an index for change detection and classification, aids in pre-encounter targeting, and supports the selection of potential landing sites. Highest priority target areas are those which indicate geophysical activity by the presence of volcanic plumes, outgassing, or

  2. Extraction of Subject-Specific Facial Expression Categories and Generation of Facial Expression Feature Space using Self-Mapping

    Directory of Open Access Journals (Sweden)

    Masaki Ishii

    2008-06-01

    Full Text Available This paper proposes a generation method of a subject-specific Facial Expression Map (FEMap using the Self-Organizing Maps (SOM of unsupervised learning and Counter Propagation Networks (CPN of supervised learning together. The proposed method consists of two steps. In the first step, the topological change of a face pattern in the expressional process of facial expression is learned hierarchically using the SOM of a narrow mapping space, and the number of subject-specific facial expression categories and the representative images of each category are extracted. Psychological significance based on the neutral and six basic emotions (anger, sadness, disgust, happiness, surprise, and fear is assigned to each extracted category. In the latter step, the categories and the representative images described above are learned using the CPN of a large mapping space, and a category map that expresses the topological characteristics of facial expression is generated. This paper defines this category map as an FEMap. Experimental results for six subjects show that the proposed method can generate a subject-specific FEMap based on the topological characteristics of facial expression appearing on face images.

  3. Hierarchical classification approach for mapping rubber tree growth using per-pixel and object-oriented classifiers with SPOT-5 imagery

    Directory of Open Access Journals (Sweden)

    Hayder Dibs

    2017-06-01

    Full Text Available There has been growing interest in Malaysia to increase the productivity of latex. This made accurate knowledge of rubber tree growth and age distribution a helpful decision making tool for the government, rubber plantation managers, and harvesters. Gathering this information using conventional methods is difficult, time consuming, and limited in spatial coverage. This paper presents hierarchical classification approach to obtain accurate map of rubber tree growth age distribution using SPOT-5 satellite imagery. The objective of the study is to evaluate the performance of pixel-based and object-oriented classifiers for rubber growth classification. At the first level, the general land cover was classified into eight land cover classes (soil, water body, rubber, mature oil palm, young oil palm, forest, urban area, and other vegetation using Mahalanobis distance (MD, k-nearest neighbor (k-NN, and Support Vector Machine (SVM classifiers. Thereafter, the best classification map, k-NN output, was used to select only pixels that belong to the rubber class from the SPOT-5 image. The extracted pixels served as input into the next classification hierarchy where four classifiers, MD, k-NN, SVM, and decision tree (DT, were implemented to map rubber trees into three intra-classes (mature, middle-aged, and young rubbers. The result produced overall accuracy of 97.48%, 96.90%, 96.25%, and 80.80% for k-NN, SVM, MD, and DT respectively. The result indicates that object-oriented classifiers are better than pixel-based methods mapping rubber tree growth.

  4. A Near-Infrared and Thermal Imager for Mapping Titan's Surface Features

    Science.gov (United States)

    Aslam, S.; Hewagma, T.; Jennings, D. E.; Nixon, C.

    2012-01-01

    Approximately 10% of the solar insolation reaches the surface of Titan through atmospheric spectral windows. We will discuss a filter based imaging system for a future Titan orbiter that will exploit these windows mapping surface features, cloud regions, polar storms. In the near-infrared (NIR), two filters (1.28 micrometer and 1.6 micrometer), strategically positioned between CH1 absorption bands, and InSb linear array pixels will explore the solar reflected radiation. We propose to map the mid, infrared (MIR) region with two filters: 9.76 micrometer and 5.88-to-6.06 micrometers with MCT linear arrays. The first will map MIR thermal emission variations due to surface albedo differences in the atmospheric window between gas phase CH3D and C2H4 opacity sources. The latter spans the crossover spectral region where observed radiation transitions from being dominated by thermal emission to solar reflected light component. The passively cooled linear arrays will be incorporated into the focal plane of a light-weight thin film stretched membrane 10 cm telescope. A rad-hard ASIC together with an FPGA will be used for detector pixel readout and detector linear array selection depending on if the field-of-view (FOV) is looking at the day- or night-side of Titan. The instantaneous FOV corresponds to 3.1, 15.6, and 31.2 mrad for the 1, 5, and 10 micrometer channels, respectively. For a 1500 km orbit, a 5 micrometer channel pixel represents a spatial resolution of 91 m, with a FOV that spans 23 kilometers, and Titan is mapped in a push-broom manner as determined by the orbital path. The system mass and power requirements are estimated to be 6 kg and 5 W, respectively. The package is proposed for a polar orbiter with a lifetime matching two Saturn seasons.

  5. Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

    Science.gov (United States)

    Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

    2016-06-01

    Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

  6. 基于特征的二值商标分层检索方法%A Hierarchical Binary Trademark Retrieval Method Based on Feature

    Institute of Scientific and Technical Information of China (English)

    褚菁菁; 张吉楠

    2011-01-01

    针对以往商标图像搜索方法单一,并且缺少用户反馈的缺点,文中提出一种基于形状特征和纹理特征的二值商标图像分层搜索方法.该方法首先利用HU不变矩提取图像的形状特征;然后利用欧氏距离来测量图像的相似度,进行第一次筛选得到一个数目不定的候选集;接着利用灰度直方图的方法提取候选集中的图像的纹理信息,进行第二次筛选;最后通过用户的反馈进行不断的优化.从而使检索出来的图像更加迅速和准确,更加符合人的视觉感受.%The previous binary trademark image retrieval method is not perfect for lack of comprehensive approach and user feedback.This paper presents a hierarchical binary trademark image retrieval method based on shape and texture features. Firstly, this method uses Hu invariant moments shape feature to extract the images and then uses Euclidean distance to measure the image similarity, and filter a number of uncertainties in the candidate set; then extracts gray level histogram of the image the candidate focused on texture information,and get a second filter; Finally, it is optimized by continuous user feedback. This binary trademark images retrieval mothed is more quickly, accurately, and more in line with human perception.

  7. Features of annual and semiannual variations derived from the global ionospheric maps of total electron content

    Directory of Open Access Journals (Sweden)

    B. Zhao

    2008-01-01

    Full Text Available In the present work we use the NASA-JPL global ionospheric maps of total electron content (TEC, firstly to construct TEC maps (TEC vs. magnetic local time MLT, and magnetic latitude MLAT in the interval from 1999 to 2005. These TEC maps were, in turn, used to estimate the annual-to-mean amplitude ratio, A1, and the semiannual-to-mean amplitude ratio, A2, as well as the latitudinal symmetrical and asymmetrical parts, A' and A" of A1. Thus, we investigated in detail the TEC climatology from maps of these indices, with an emphasis on the quantitative presentation for local time and latitudinal changes in the seasonal, annual and semiannual anomalies of the ionospheric TEC. Then we took the TEC value at 14:00 LT to examine various anomalies at a global scale following the same procedure. Results reveal similar features appearing in NmF2, such as that the seasonal anomaly is more significant in the near-pole regions than in the far-pole regions and the reverse is true for the semiannual anomaly; the winter anomaly has least a chance to be observed at the South America and South Pacific areas. The most impressive feature is that the equinoctial asymmetry is most prominent at the East Asian and South Australian areas. Through the analysis of the TIMED GUVI columnar [O/N2] data, we have investigated to what extent the seasonal, annual and semiannual variations can be explained by their counterparts in [O/N2]. Results revealed that the [O/N2] variation is a major contributor to the daytime winter anomaly of TEC, and it also contributes to some of the semiannual and annual anomalies. The contribution to the anomalies unexplained by the [O/N2] data could possibly be due to the dynamics associated with thermospheric winds and electric fields.

  8. GEOLOGICAL FEATURES MAPPING USING PALSAR-2 DATA IN KELANTAN RIVER BASIN, PENINSULAR MALAYSIA

    Directory of Open Access Journals (Sweden)

    A. B. Pour

    2016-09-01

    Full Text Available In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2 onboard the Advanced Land Observing Satellite-2 (ALOS-2, remote sensing data were used to map geologic structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides and flooding areas. A ScanSAR and two fine mode dual polarization level 3.1 images cover Kelantan state were processed for comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. Red-Green-Blue (RGB colour-composite was applied to different polarization channels of PALSAR-2 data to extract variety of geological information. Directional convolution filters were applied to the data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results derived from ScanSAR image indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ in the west and Lebir Fault Zone in the east of the Kelantan state. Combination of different polarization channels produced image maps contain important information related to water bodies, wetlands and lithological units for the Kelantan state using fine mode observation data. The N-S, NE-SW and NNE-SSW lineament trends were identified in the study area using directional filtering. Dendritic, sub-dendritic and rectangular drainage patterns were detected in the Kelantan river basin. The analysis of field investigations data indicate that many of flooded areas were associated with high potential risk zones for hydro-geological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topograghy regions. Numerous landslide points were located in rectangular drainage system

  9. Geological Features Mapping Using PALSAR-2 Data in Kelantan River Basin, Peninsular Malaysia

    Science.gov (United States)

    Pour, A. B.; Hashim, M.

    2016-09-01

    In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), remote sensing data were used to map geologic structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides and flooding areas. A ScanSAR and two fine mode dual polarization level 3.1 images cover Kelantan state were processed for comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. Red-Green-Blue (RGB) colour-composite was applied to different polarization channels of PALSAR-2 data to extract variety of geological information. Directional convolution filters were applied to the data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results derived from ScanSAR image indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ) in the west and Lebir Fault Zone in the east of the Kelantan state. Combination of different polarization channels produced image maps contain important information related to water bodies, wetlands and lithological units for the Kelantan state using fine mode observation data. The N-S, NE-SW and NNE-SSW lineament trends were identified in the study area using directional filtering. Dendritic, sub-dendritic and rectangular drainage patterns were detected in the Kelantan river basin. The analysis of field investigations data indicate that many of flooded areas were associated with high potential risk zones for hydro-geological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topograghy regions. Numerous landslide points were located in rectangular drainage system that associated

  10. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, M.

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  11. Non-Trivial Feature Derivation for Intensifying Feature Detection Using LIDAR Datasets Through Allometric Aggregation Data Analysis Applying Diffused Hierarchical Clustering for Discriminating Agricultural Land Cover in Portions of Northern Mindanao, Philippines

    Science.gov (United States)

    Villar, Ricardo G.; Pelayo, Jigg L.; Mozo, Ray Mari N.; Salig, James B., Jr.; Bantugan, Jojemar

    2016-06-01

    Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging (LiDAR) derived products in arriving quality Landcover classification considering the theoretical approach of data analysis principles to minimize the common problems in image classification. These are misclassification of objects and the non-distinguishable interpretation of pixelated features that results to confusion of class objects due to their closely-related spectral resemblance, unbalance saturation of RGB information is a challenged at the same time. Only low density LiDAR point cloud data is exploited in the research denotes as 2 pts/m2 of accuracy which bring forth essential derived information such as textures and matrices (number of returns, intensity textures, nDSM, etc.) in the intention of pursuing the conditions for selection characteristic. A novel approach that takes gain of the idea of object-based image analysis and the principle of allometric relation of two or more observables which are aggregated for each acquisition of datasets for establishing a proportionality function for data-partioning. In separating two or more data sets in distinct regions in a feature space of distributions, non-trivial computations for fitting distribution were employed to formulate the ideal hyperplane. Achieving the distribution computations, allometric relations were evaluated and match with the necessary rotation, scaling and transformation techniques to find applicable border conditions. Thus, a customized hybrid feature was developed and embedded in every object class feature to be used as classifier with employed hierarchical clustering strategy for cross-examining and filtering features. This features are boost using machine learning algorithms as trainable sets of information for a more competent feature detection. The product classification in this

  12. Hierarchical object-based mapping of riverscape units and in-stream mesohabitats using LiDAR and VHR imagery

    OpenAIRE

    Luca Demarchi; Simone Bizzi; Hervé Piégay

    2015-01-01

    In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS) data. This novel approach is based on the integration of spectral and topographic information within a multilevel, geographic, object-based image analysis (GEOBIA). Different segmentation levels were generated based on the two sources of Remote Sensing (RS) data, namely very-high spatial resolution, near-infrared imagery (VHR...

  13. Low-Level Tie Feature Extraction of Mobile Mapping Data (mls/images) and Aerial Imagery

    Science.gov (United States)

    Jende, P.; Hussnain, Z.; Peter, M.; Oude Elberink, S.; Gerke, M.; Vosselman, G.

    2016-03-01

    Mobile Mapping (MM) is a technique to obtain geo-information using sensors mounted on a mobile platform or vehicle. The mobile platform's position is provided by the integration of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, especially in urban areas, building structures can obstruct a direct line-of-sight between the GNSS receiver and navigation satellites resulting in an erroneous position estimation. Therefore, derived MM data products, such as laser point clouds or images, lack the expected positioning reliability and accuracy. This issue has been addressed by many researchers, whose aim to mitigate these effects mainly concentrates on utilising tertiary reference data. However, current approaches do not consider errors in height, cannot achieve sub-decimetre accuracy and are often not designed to work in a fully automatic fashion. We propose an automatic pipeline to rectify MM data products by employing high resolution aerial nadir and oblique imagery as horizontal and vertical reference, respectively. By exploiting the MM platform's defective, and therefore imprecise but approximate orientation parameters, accurate feature matching techniques can be realised as a pre-processing step to minimise the MM platform's three-dimensional positioning error. Subsequently, identified correspondences serve as constraints for an orientation update, which is conducted by an estimation or adjustment technique. Since not all MM systems employ laser scanners and imaging sensors simultaneously, and each system and data demands different approaches, two independent workflows are developed in parallel. Still under development, both workflows will be presented and preliminary results will be shown. The workflows comprise of three steps; feature extraction, feature matching and the orientation update. In this paper, initial results of low-level image and point cloud feature extraction methods will be discussed as well as an outline of

  14. LOW-LEVEL TIE FEATURE EXTRACTION OF MOBILE MAPPING DATA (MLS/IMAGES AND AERIAL IMAGERY

    Directory of Open Access Journals (Sweden)

    P. Jende

    2016-03-01

    Full Text Available Mobile Mapping (MM is a technique to obtain geo-information using sensors mounted on a mobile platform or vehicle. The mobile platform’s position is provided by the integration of Global Navigation Satellite Systems (GNSS and Inertial Navigation Systems (INS. However, especially in urban areas, building structures can obstruct a direct line-of-sight between the GNSS receiver and navigation satellites resulting in an erroneous position estimation. Therefore, derived MM data products, such as laser point clouds or images, lack the expected positioning reliability and accuracy. This issue has been addressed by many researchers, whose aim to mitigate these effects mainly concentrates on utilising tertiary reference data. However, current approaches do not consider errors in height, cannot achieve sub-decimetre accuracy and are often not designed to work in a fully automatic fashion. We propose an automatic pipeline to rectify MM data products by employing high resolution aerial nadir and oblique imagery as horizontal and vertical reference, respectively. By exploiting the MM platform’s defective, and therefore imprecise but approximate orientation parameters, accurate feature matching techniques can be realised as a pre-processing step to minimise the MM platform’s three-dimensional positioning error. Subsequently, identified correspondences serve as constraints for an orientation update, which is conducted by an estimation or adjustment technique. Since not all MM systems employ laser scanners and imaging sensors simultaneously, and each system and data demands different approaches, two independent workflows are developed in parallel. Still under development, both workflows will be presented and preliminary results will be shown. The workflows comprise of three steps; feature extraction, feature matching and the orientation update. In this paper, initial results of low-level image and point cloud feature extraction methods will be discussed

  15. Acoustic Longitudinal Field NIF Optic Feature Detection Map Using Time-Reversal & MUSIC

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S K

    2006-02-09

    We developed an ultrasonic longitudinal field time-reversal and MUltiple SIgnal Classification (MUSIC) based detection algorithm for identifying and mapping flaws in fused silica NIF optics. The algorithm requires a fully multistatic data set, that is one with multiple, independently operated, spatially diverse transducers, each transmitter of which, in succession, launches a pulse into the optic and the scattered signal measured and recorded at every receiver. We have successfully localized engineered ''defects'' larger than 1 mm in an optic. We confirmed detection and localization of 3 mm and 5 mm features in experimental data, and a 0.5 mm in simulated data with sufficiently high signal-to-noise ratio. We present the theory, experimental results, and simulated results.

  16. Incorporating Endmember Variability into Linear Unmixing of Coarse Resolution Imagery: Mapping Large-Scale Impervious Surface Abundance Using a Hierarchically Object-Based Spectral Mixture Analysis

    Directory of Open Access Journals (Sweden)

    Chengbin Deng

    2015-07-01

    Full Text Available As an important indicator of anthropogenic impacts on the Earth’s surface, it is of great necessity to accurately map large-scale urbanized areas for various science and policy applications. Although spectral mixture analysis (SMA can provide spatial distribution and quantitative fractions for better representations of urban areas, this technique is rarely explored with 1-km resolution imagery. This is due mainly to the absence of image endmembers associated with the mixed pixel problem. Consequently, as the most profound source of error in SMA, endmember variability has rarely been considered with coarse resolution imagery. These issues can be acute for fractional land cover mapping due to the significant spectral variations of numerous land covers across a large study area. To solve these two problems, a hierarchically object-based SMA (HOBSMA was developed (1 to extrapolate local endmembers for regional spectral library construction; and (2 to incorporate endmember variability into linear spectral unmixing of MODIS 1-km imagery for large-scale impervious surface abundance mapping. Results show that by integrating spatial constraints from object-based image segments and endmember extrapolation techniques into multiple endmember SMA (MESMA of coarse resolution imagery, HOBSMA improves the discriminations between urban impervious surfaces and other land covers with well-known spectral confusions (e.g., bare soil and water, and particularly provides satisfactory representations of urban fringe areas and small settlements. HOBSMA yields promising abundance results at the km-level scale with relatively high precision and small bias, which considerably outperforms the traditional simple mixing model and the aggregated MODIS land cover classification product.

  17. Using multiple spectral feature analysis for quantitative pH mapping in a mining environment

    Science.gov (United States)

    Kopačková, Veronika

    2014-05-01

    The pH is one of the major chemical parameters affecting the results of remediation programs carried out at abandoned mines and dumps and one of the major parameters controlling heavy metal mobilization and speciation. This study is concerned with testing the feasibility of estimating surface pH on the basis of airborne hyperspectral (HS) data (HyMap). The work was carried on the Sokolov lignite mine, as it represents a site with extreme material heterogeneity and high pH gradients. First, a geochemical conceptual model of the site was defined. Pyrite, jarosite or lignite were the diagnostic minerals of very low pH (6.5). It was found that these minerals have absorption feature parameters which are common for both forms, individual minerals as well as parts of the mixtures, while the shift to longer wavelengths of the absorption maximum centered between 0.90 and 1.00 μm is the main parameter that allows differentiation among the ferric minerals. The multi range spectral feature fitting (MRSFF) technique was employed to map the defined end-members indicating certain pH ranges in the HS image datasets. This technique was found to be sensitive enough to assess differences in the desired spectral parameters (e.g., absorption shape, depth and indirectly maximum absorption wavelength position). Furthermore, the regression model using the fit images, the results of MRSFF, as inputs was constructed (R2 = 0.61, Rv2 = 0.76) to estimate the surface pH. This study represents one of the few approaches employing image spectroscopy for quantitative pH modeling in a mining environment and the achieved results demonstrate the potential application of hyperspectral remote sensing as an efficient method for environmental monitoring.

  18. Mining for diagnostic information in body surface potential maps: A comparison of feature selection techniques

    Directory of Open Access Journals (Sweden)

    McCullagh Paul J

    2005-09-01

    Full Text Available Abstract Background In body surface potential mapping, increased spatial sampling is used to allow more accurate detection of a cardiac abnormality. Although diagnostically superior to more conventional electrocardiographic techniques, the perceived complexity of the Body Surface Potential Map (BSPM acquisition process has prohibited its acceptance in clinical practice. For this reason there is an interest in striking a compromise between the minimum number of electrocardiographic recording sites required to sample the maximum electrocardiographic information. Methods In the current study, several techniques widely used in the domains of data mining and knowledge discovery have been employed to mine for diagnostic information in 192 lead BSPMs. In particular, the Single Variable Classifier (SVC based filter and Sequential Forward Selection (SFS based wrapper approaches to feature selection have been implemented and evaluated. Using a set of recordings from 116 subjects, the diagnostic ability of subsets of 3, 6, 9, 12, 24 and 32 electrocardiographic recording sites have been evaluated based on their ability to correctly asses the presence or absence of Myocardial Infarction (MI. Results It was observed that the wrapper approach, using sequential forward selection and a 5 nearest neighbour classifier, was capable of choosing a set of 24 recording sites that could correctly classify 82.8% of BSPMs. Although the filter method performed slightly less favourably, the performance was comparable with a classification accuracy of 79.3%. In addition, experiments were conducted to show how (a features chosen using the wrapper approach were specific to the classifier used in the selection model, and (b lead subsets chosen were not necessarily unique. Conclusion It was concluded that both the filter and wrapper approaches adopted were suitable for guiding the choice of recording sites useful for determining the presence of MI. It should be noted however

  19. Chemical map of Schizosaccharomyces pombe reveals species-specific features in nucleosome positioning.

    Science.gov (United States)

    Moyle-Heyrman, Georgette; Zaichuk, Tetiana; Xi, Liqun; Zhang, Quanwei; Uhlenbeck, Olke C; Holmgren, Robert; Widom, Jonathan; Wang, Ji-Ping

    2013-12-10

    Using a recently developed chemical approach, we have generated a genome-wide map of nucleosomes in vivo in Schizosaccharomyces pombe (S. pombe) at base pair resolution. The shorter linker length previously identified in S. pombe is due to a preponderance of nucleosomes separated by ∼4/5 bp, placing nucleosomes on opposite faces of the DNA. The periodic dinucleotide feature thought to position nucleosomes is equally strong in exons as in introns, demonstrating that nucleosome positioning information can be superimposed on coding information. Unlike the case in Saccharomyces cerevisiae, A/T-rich sequences are enriched in S. pombe nucleosomes, particularly at ±20 bp around the dyad. This difference in nucleosome binding preference gives rise to a major distinction downstream of the transcription start site, where nucleosome phasing is highly predictable by A/T frequency in S. pombe but not in S. cerevisiae, suggesting that the genomes and DNA binding preferences of nucleosomes have coevolved in different species. The poly (dA-dT) tracts affect but do not deplete nucleosomes in S. pombe, and they prefer special rotational positions within the nucleosome, with longer tracts enriched in the 10- to 30-bp region from the dyad. S. pombe does not have a well-defined nucleosome-depleted region immediately upstream of most transcription start sites; instead, the -1 nucleosome is positioned with the expected spacing relative to the +1 nucleosome, and its occupancy is negatively correlated with gene expression. Although there is generally very good agreement between nucleosome maps generated by chemical cleavage and micrococcal nuclease digestion, the chemical map shows consistently higher nucleosome occupancy on DNA with high A/T content.

  20. Prioritizing spatial accuracy in high-resolution fMRI data using multivariate feature weight mapping

    Directory of Open Access Journals (Sweden)

    Johannes eStelzer

    2014-04-01

    Full Text Available Although ultra-high-field fMRI at field strengths of 7T or above provides substantial gains in BOLD contrast-to-noise ratio, when very high-resolution fMRI is required such gains are inevitably reduced. The improvement in sensitivity provided by multivariate analysis techniques, as compared with univariate methods, then becomes especially welcome. Information mapping approaches are commonly used, such as the searchlight technique, which take into account the spatially distributed patterns of activation in order to predict stimulus conditions. However, the popular searchlight decoding technique, in particular, has been found to be prone to spatial inaccuracies. For instance, the spatial extent of informative areas is generally exaggerated, and their spatial configuration is distorted. We propose the combination of a nonparametric and permutation-based statistical framework with linear classifiers. We term this new combined method Feature Weight Mapping (FWM. The main goal of the proposed method is to map the specific contribution of each voxel to the classification decision while including a correction for the multiple comparisons problem. Next, we compare this new method to the searchlight approach using a simulation and ultra-high-field 7T experimental data. We found that the searchlight method led to spatial inaccuracies that are especially noticeable in high-resolution fMRI data. In contrast, FWM was more spatially precise, revealing both informative anatomical structures as well as the direction by which voxels contribute to the classification. By maximizing the spatial accuracy of ultra-high-field fMRI results, global multivariate methods provide a substantial improvement for characterizing structure-function relationships.

  1. Cytogenetic Mapping of Disease Resistance Genes and Analysis of Their Distribution Features on Chromosomes in Maize

    Institute of Scientific and Technical Information of China (English)

    LiLi-jia; SongYun-chun

    2003-01-01

    Cytogenetic maps of four clusters of disease resistance genes were generated by ISH of the two RFLP markers tightly linked to and flanking each of maize resistance genes and the cloned resistance genes from other plant species onto maize chromosomes, combining with data published before. These genes include Helminthosporium turcium Pass resistance genes Htl, Htnl and Ht2, Helminthosporium maydis Nisik resistance genes Rhml and Rhm2,maize dwarf mosaic virus resistance gene Mdml, wheat streak mosaic virus resistance gene Wsml, Helminthosporium carbonum ULLstrup resistance gene Hml and the cloned Xanthomonas oryzae pv. Oryzae resistance gene Xa21 of rice, Cladosporium fulvum resistance genes Cf-9 and Cf-2. 1 of tomato, and Pseudomonas syringae resistance gene RPS2 of Arabidopsis. Most of the tested disease resistance genes located on the four chromosomes, i. e. , chromosomesl, 3, 6 and 8, and they closely distributed at the interstitial regions of these chromosomal long arms with percentage distances ranging 31.44(±3.72)-72.40(±3. 25) except for genes Rhml, Rhm2, Mdml and Wsml which mapped on the satellites of the short arms of chromosome6. It showed that the tested RFLP markers and genes were duplicated or triplicated in maize genome. Homology and conservation of disease resistance genes among species, and relationship between distribution features and functions of the genes were discussed. The results provide important scientific basis for deeply understanding structure and function of disease resistance genes and breeding in maize.

  2. High-density three-dimensional mapping of internal strain by tracking microstructural features

    Energy Technology Data Exchange (ETDEWEB)

    Kobayashi, Masakazu [Department of Production Systems Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580 (Japan)], E-mail: m-kobayashi@pse.tut.ac.jp; Toda, Hiroyuki; Kawai, Yuji; Ohgaki, Tomomi [Department of Production Systems Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580 (Japan); Uesugi, Kentaro [Japan Synchrotron Radiation Research Institute, Sayo-gun, Hyogo 679-5198 (Japan); Wilkinson, David S. [Department of Materials Science and Engineering, McMaster University, Hamilton, Ontario, Canada L8S 4L7 (Canada); Kobayashi, Toshiro [Department of Production Systems Engineering, Toyohashi University of Technology, Toyohashi, Aichi 441-8580 (Japan); Aoki, Yoshimitsu; Nakazawa, Mitsuru [Department of Information Engineering, Shibaura Institute of Technology, Koto-Ku, Tokyo 135-8548 (Japan)

    2008-06-15

    The three-dimensional (3-D) strain map is useful to elucidate the relationships between microstructures and locally caused deformation and fracture. However, a robust tracking method, which enables error-free tracking in synchrotron radiation computed tomography (SR-CT) images with >10 000 microstructural features, is not currently available. In this study, a model sample was subjected to a tensile test and scanned by the SR-CT technique in order to develop a new tracking method. The developed tracking methods indicated a high tracking ratio and tracking success ratio of nearly 100% in a wide strain range, which included the assumed strain in a practical experiment. It was confirmed that tracking errors produce an incorrect strain distribution in 3-D strain mapping. This study verified the validity of the developed tracking method. The application of this method to high-resolution SR-CT images will make measurement and visualization of the strain distribution possible in three dimensions in bulk materials.

  3. High-resolution Mapping of Offshore and Onshore Glaciogenic Features in Melville Bay, Northwestern Greenland

    Science.gov (United States)

    Freire, F.; Gyllencreutz, R.; Greenwood, S.; Mayer, L. A.; Jakobsson, M.

    2014-12-01

    This study presents results from high resolution mapping in the northwestern part of Greenland's continental shelf, offshore from the Greenland Ice Sheet. The study area is located at about 74o30'N and 58 o40'W where high-resolution seafloor imagery were collected from ~200-500 m water depth. These data were analyzed and compared to existing high-resolution satellite imagery of exposed glacial landforms from the nearby coastal areas. Offshore geophysical mapping equipment consisted of a Kongsberg EM2040 multibeam that was bow-mounted on the sailing vessel Explorer of Sweden together with a Seatex MRU5+ motion sensor and GPS antennas. In addition, a GAVIA autonomous underwater vehicle (AUV) from University of Iceland with installed Geoswath interfometric sonar and Marine Sonic side-scan was used. The data from these systems permitted the production of both 5-m (for the EM2040) and 2-m (for the Geoswath) resolution bathymetric grids for landform analyzes. Sediment characterization analysis was also undertaken using the co-registered backscatter data. The exposed onshore landforms were studied using data from the high-res QuickBird satellite images with a 2-m pixel resolution. Geomorphic analysis of the data shows that past tectonic and glacial scouring processes have shaped the present-day landscape in both the offshore and onshore study areas. The terrain consists of glacially eroded bedrock covered with very thin surficial sediments resembling a 'cnoc-and-lochan' terrain, although the degree of erosion varies spatially, probably as a result of local variations in the rock properties. Different glacially influenced features are identified and described in the study. These features have been used to understand and infer past ice-sheet processes, particularly ice-flow direction and the extent of ice-cover on the continental shelves from previous extreme glaciation events. The backscatter information from the high-resolution interferometric sonar show fine

  4. Interference features in scanning gate conductance maps of quantum point contacts with disorder

    Science.gov (United States)

    Kolasiński, K.; Szafran, B.; Brun, B.; Sellier, H.

    2016-08-01

    We consider quantum point contact (QPC) defined within a disordered two-dimensional electron gas as studied by scanning gate microscopy. We evaluate the conductance maps in the Landauer approach with a wave-function picture of electron transport for samples with both low and high electron mobility at finite temperatures. We discuss the spatial distribution of the impurities in the context of the branched electron flow. We reproduce the surprising temperature stability of the experimental interference fringes far from the QPC. Next, we discuss funnel-shaped features that accompany splitting of the branches visible in previous experiments. Finally, we study elliptical interference fringes formed by an interplay of scattering by the pointlike impurities and by the scanning probe. We discuss the details of the elliptical features as functions of the tip voltage and the temperature, showing that the first interference fringe is very robust against the thermal widening of the Fermi level. We present a simple analytical model that allows for extraction of the impurity positions and the electron-gas depletion radius induced by the negatively charged tip of the atomic force microscope, and apply this model on experimental scanning gate images showing such elliptical fringes.

  5. Mapping disability-adjusted life years: a Bayesian hierarchical model framework for burden of disease and injury assessment.

    Science.gov (United States)

    MacNab, Ying C

    2007-11-20

    This paper presents a Bayesian disability-adjusted life year (DALY) methodology for spatial and spatiotemporal analyses of disease and/or injury burden. A Bayesian disease mapping model framework, which blends together spatial modelling, shared-component modelling (SCM), temporal modelling, ecological modelling, and non-linear modelling, is developed for small-area DALY estimation and inference. In particular, we develop a model framework that enables SCM as well as multivariate CAR modelling of non-fatal and fatal disease or injury rates and facilitates spline smoothing for non-linear modelling of temporal rate and risk trends. Using British Columbia (Canada) hospital admission-separation data and vital statistics mortality data on non-fatal and fatal road traffic injuries to male population age 20-39 for year 1991-2000 and for 84 local health areas and 16 health service delivery areas, spatial and spatiotemporal estimation and inference on years of life lost due to premature death, years lived with disability, and DALYs are presented. Fully Bayesian estimation and inference, with Markov chain Monte Carlo implementation, are illustrated. We present a methodological framework within which the DALY and the Bayesian disease mapping methodologies interface and intersect. Its development brings the relative importance of premature mortality and disability into the assessment of community health and health needs in order to provide reliable information and evidence for community-based public health surveillance and evaluation, disease and injury prevention, and resource provision.

  6. Advanced Tie Feature Matching for the Registration of Mobile Mapping Imaging Data and Aerial Imagery

    Science.gov (United States)

    Jende, P.; Peter, M.; Gerke, M.; Vosselman, G.

    2016-06-01

    Mobile Mapping's ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform's position. Consequently, acquired data products' positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images' geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability

  7. Simple mineral mapping algorithm based on multitype spectral diagnostic absorption features: a case study at Cuprite, Nevada

    Science.gov (United States)

    Wei, Jing; Ming, Yanfang; Jia, Qiang; Yang, Dongxu

    2017-04-01

    Hyperspectral remote sensing has been widely used in mineral identification using the particularly useful short-wave infrared (SWIR) wavelengths (1.0 to 2.5 μm). Current mineral mapping methods are easily limited by the sensor's radiometric sensitivity and atmospheric effects. Therefore, a simple mineral mapping algorithm (SMMA) based on the combined application with multitype diagnostic SWIR absorption features for hyperspectral data is proposed. A total of nine absorption features are calculated, respectively, from the airborne visible/infrared imaging spectrometer data, the Hyperion hyperspectral data, and the ground reference spectra data collected from the United States Geological Survey (USGS) spectral library. Based on spectral analysis and statistics, a mineral mapping decision-tree model for the Cuprite mining district in Nevada, USA, is constructed. Then, the SMMA algorithm is used to perform mineral mapping experiments. The mineral map from the USGS (USGS map) in the Cuprite area is selected for validation purposes. Results showed that the SMMA algorithm is able to identify most minerals with high coincidence with USGS map results. Compared with Hyperion data (overall accuracy=74.54%), AVIRIS data showed overall better mineral mapping results (overall accuracy=94.82%) due to low signal-to-noise ratio and high spatial resolution.

  8. Hierarchical state space partitioning with a network self-organising map for the recognition of ST-T segment changes.

    Science.gov (United States)

    Bezerianos, A; Vladutu, L; Papadimitriou, S

    2000-07-01

    The problem of maximising the performance of ST-T segment automatic recognition for ischaemia detection is a difficult pattern classification problem. The paper proposes the network self-organising map (NetSOM) model as an enhancement to the Kohonen self-organised map (SOM) model. This model is capable of effectively decomposing complex large-scale pattern classification problems into a number of partitions, each of which is more manageable with a local classification device. The NetSOM attempts to generalize the regularization and ordering potential of the basic SOM from the space of vectors to the space of approximating functions. It becomes a device for the ordering of local experts (i.e. independent neural networks) over its lattice of neurons and for their selection and co-ordination. Each local expert is an independent neural network that is trained and activated under the control of the NetSOM. This method is evaluated with examples from the European ST-T database. The first results obtained after the application of NetSOM to ST-T segment change recognition show a significant improvement in the performance compared with that obtained with monolithic approaches, i.e. with single network types. The basic SOM model has attained an average ischaemic beat sensitivity of 73.6% and an average ischaemic beat predictivity of 68.3%. The work reports and discusses the improvements that have been obtained from the implementation of a NetSOM classification system with both multilayer perceptrons and radial basis function (RBF) networks as local experts for the ST-T segment change problem. Specifically, the NetSOM with multilayer perceptrons (radial basis functions) as local experts has improved the results over the basic SOM to an average ischaemic beat sensitivity of 75.9% (77.7%) and an average ischaemic beat predictivity of 72.5% (74.1%).

  9. Cytogenetic Mapping of Disease Resistance Genes and Analysis of Their Distribution Features on Chromosomes in Maize

    Institute of Scientific and Technical Information of China (English)

    Li Li-jia; Song Yun-chun

    2003-01-01

    Cytogenetic maps of four clusters of disease resistance genes were generated by ISH of the two RFLP markers tightly linked to and flanking each of maize resistance genes and the cloned resistance genes from other plant species onto maize chromosomes, combining with data published before. These genes include Helminthosporium turcium Pass resistance genes Ht1, Htn1 and Ht2, Helminthosporium maydis Nisik resistance genes Rhm1 and Rhm2, maize dwarf mosaic virus resistance gene Mdm1, wheat streak mosaic virus resistance gene Wsm1, Helminthosporium carbonum ULLstrup resistance gene Hml and the cloned Xanthomonas oryzae pv. Oryzae resistance gene Xa21 of rice, Cladosporium fulvum resistance genes Cf-9 and Cf-2.1 of tomato,and Pseudomonas syringae resistance gene RPS2 of Arabidopsis. Most of the tested disease resistance genes located on the four chromosomes, i.e., chromosomes1, 3, 6 and 8, and they closely distributed at the interstitial regions of these chromosomal long arms with percentage distances ranging 31.44(±3.72)-72.40(±3.25) except for genes Rhm1, Rhm2, Mdm1 and Wsm1 which mapped on the satellites of the short arms of chromosome6. It showed that the tested RFLP markers and genes were duplicated or triplicated in maize genome. Homology and conservation of disease resistance genes among species, and relationship between distribution features and functions of the genes were discussed. The results provide important scientific basis for deeply understanding structure and function of disease resistance genes and breeding in maize.

  10. Genome-Wide Mapping of Collier In Vivo Binding Sites Highlights Its Hierarchical Position in Different Transcription Regulatory Networks.

    Directory of Open Access Journals (Sweden)

    Mathilde de Taffin

    Full Text Available Collier, the single Drosophila COE (Collier/EBF/Olf-1 transcription factor, is required in several developmental processes, including head patterning and specification of muscle and neuron identity during embryogenesis. To identify direct Collier (Col targets in different cell types, we used ChIP-seq to map Col binding sites throughout the genome, at mid-embryogenesis. In vivo Col binding peaks were associated to 415 potential direct target genes. Gene Ontology analysis revealed a strong enrichment in proteins with DNA binding and/or transcription-regulatory properties. Characterization of a selection of candidates, using transgenic CRM-reporter assays, identified direct Col targets in dorso-lateral somatic muscles and specific neuron types in the central nervous system. These data brought new evidence that Col direct control of the expression of the transcription regulators apterous and eyes-absent (eya is critical to specifying neuronal identities. They also showed that cross-regulation between col and eya in muscle progenitor cells is required for specification of muscle identity, revealing a new parallel between the myogenic regulatory networks operating in Drosophila and vertebrates. Col regulation of eya, both in specific muscle and neuronal lineages, may illustrate one mechanism behind the evolutionary diversification of Col biological roles.

  11. Multibeam Mapping of Active Slope Instability Features: Examples from the Fraser River and Squamish River Deltas, British Columbia, Canada

    Science.gov (United States)

    Hill, P. R.

    2004-12-01

    Multibeam mapping of the coastal waters of British Columbia has immensly improved our ability to identify and assess submarine landslide and tsunami hazard. This paper will present analysis of high-resolution images of slope instability features from two delta slopes where recent slope failure can be documented through repetitive multibeam mapping and/or comparison with previous single-beam hydrographic soundings. Numerous mass movement features characterize the slope of the Fraser River delta, all the recent features being located at the mouths of distributary channels. Engineering works have maintained the main channel in a fixed position since the 1930's, contributing to over-steepening of the slope and development of a network of submarine channels. Repetitive multibeam mapping shows that recent slope failures have occurred in numerous locations around the main channel lobe, some at the head of a large submarine channel system and others as isolated small failures that form the headwalls of small submarine channels. The scalloped morphology and association with channels, together with volume estimates derived from repetitive multibeam mapping, indicate that these features result from shallow, small volume liquefaction failures. Smaller scale, shallow slides are present on the very shallow water slope area adjacent to the channels, raising the possibility of groundwater seepage as an influence on slope stability. The slide masses from these failures are rapidly transformed into gravity flows that carve the submarine channels. Slides and channels of a similar scale are found at the mouth of a secondary distributary channel and an abandoned distributary channel. The multibeam imagery allows discrimination between recent slide features and relict features, the latter showing infilling or reworking by bottom currents. An area of undulatory seafloor, located on the flank of the main distributary channel lobe, has been cited as a possible creep displacement feature

  12. Analysis of Vehicle-Following Heterogeneity Using Self-Organizing Feature Maps

    Directory of Open Access Journals (Sweden)

    Jie Yang

    2014-01-01

    Full Text Available A self-organizing feature map (SOM was used to represent vehicle-following and to analyze the heterogeneities in vehicle-following behavior. The SOM was constructed in such a way that the prototype vectors represented vehicle-following stimuli (the follower’s velocity, relative velocity, and gap while the output signals represented the response (the follower’s acceleration. Vehicle trajectories collected at a northbound segment of Interstate 80 Freeway at Emeryville, CA, were used to train the SOM. The trajectory information of two selected pairs of passenger cars was then fed into the trained SOM to identify similar stimuli experienced by the followers. The observed responses, when the stimuli were classified by the SOM into the same category, were compared to discover the interdriver heterogeneity. The acceleration profile of another passenger car was analyzed in the same fashion to observe the interdriver heterogeneity. The distribution of responses derived from data sets of car-following-car and car-following-truck, respectively, was compared to ascertain inter-vehicle-type heterogeneity.

  13. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

    As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.

  14. Sensors Fusion based Online Mapping and Features Extraction of Mobile Robot in the Road Following and Roundabout

    Science.gov (United States)

    Ali, Mohammed A. H.; Mailah, Musa; Yussof, Wan Azhar B.; Hamedon, Zamzuri B.; Yussof, Zulkifli B.; Majeed, Anwar P. P.

    2016-02-01

    A road feature extraction based mapping system using a sensor fusion technique for mobile robot navigation in road environments is presented in this paper. The online mapping of mobile robot is performed continuously in the road environments to find the road properties that enable the robot to move from a certain start position to pre-determined goal while discovering and detecting the roundabout. The sensors fusion involving laser range finder, camera and odometry which are installed in a new platform, are used to find the path of the robot and localize it within its environments. The local maps are developed using camera and laser range finder to recognize the roads borders parameters such as road width, curbs and roundabout. Results show the capability of the robot with the proposed algorithms to effectively identify the road environments and build a local mapping for road following and roundabout.

  15. Facial/License Plate Detection Using a Two-Level Cascade Classifier and a Single Convolutional Feature Map

    Directory of Open Access Journals (Sweden)

    Ying-Nong Chen

    2015-12-01

    Full Text Available In this paper, an object detector is proposed based on a convolution/subsampling feature map and a two-level cascade classifier. First, a convolution/subsampling operation alleviates illumination, rotation and noise variances. Then, two classifiers are concatenated to check a large number of windows using a coarse-to-fine strategy. Since the sub-sampled feature map with enhanced pixels was fed into the coarse-level classifier, the checked windows were drastically reduced to a quarter of the original image. A few remaining windows showing detailed data were further checked using a fine-level classifier. In addition to improving the detection process, the proposed mechanism also sped up the training process. Some features generated from the prototypes within the small window were selected and trained to obtain the coarse-level classifier. Moreover, a feature ranking algorithm reduced the large feature pool to a small set, thus speeding up the training process without losing detection performance. The contribution of this paper is twofold: first, the coarse-to-fine scheme shortens both the training and detection processes. Second, the feature ranking algorithm reduces training time. Finally, some experimental results were achieved for evaluation. From the results, the proposed method was shown to outperform the rapidly performing Adaboost, as well as forward feature selection methods.

  16. Functional maps of human auditory cortex: effects of acoustic features and attention.

    Directory of Open Access Journals (Sweden)

    David L Woods

    , ARMs increased in amplitude throughout stimulus blocks. CONCLUSIONS/SIGNIFICANCE: The results are consistent with the view that medial regions of human auditory cortex contain tonotopically organized core and belt fields that map the basic acoustic features of sounds while surrounding higher-order parabelt regions are tuned to more abstract stimulus attributes. Intermodal selective attention enhances processing in neuronal populations that are partially distinct from those activated by unattended stimuli.

  17. Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas

    Science.gov (United States)

    Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas

    2017-06-01

    The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping

  18. Feature-based alert correlation in security systems using self organizing maps

    Science.gov (United States)

    Kumar, Munesh; Siddique, Shoaib; Noor, Humera

    2009-04-01

    The security of the networks has been an important concern for any organization. This is especially important for the defense sector as to get unauthorized access to the sensitive information of an organization has been the prime desire for cyber criminals. Many network security techniques like Firewall, VPN Concentrator etc. are deployed at the perimeter of network to deal with attack(s) that occur(s) from exterior of network. But any vulnerability that causes to penetrate the network's perimeter of defense, can exploit the entire network. To deal with such vulnerabilities a system has been evolved with the purpose of generating an alert for any malicious activity triggered against the network and its resources, termed as Intrusion Detection System (IDS). The traditional IDS have still some deficiencies like generating large number of alerts, containing both true and false one etc. By automatically classifying (correlating) various alerts, the high-level analysis of the security status of network can be identified and the job of network security administrator becomes much easier. In this paper we propose to utilize Self Organizing Maps (SOM); an Artificial Neural Network for correlating large amount of logged intrusion alerts based on generic features such as Source/Destination IP Addresses, Port No, Signature ID etc. The different ways in which alerts can be correlated by Artificial Intelligence techniques are also discussed. . We've shown that the strategy described in the paper improves the efficiency of IDS by better correlating the alerts, leading to reduced false positives and increased competence of network administrator.

  19. Self-organizing feature map neural network classification of the ASTER data based on wavelet fusion

    Institute of Scientific and Technical Information of China (English)

    HASI Bagan; MA Jianwen; LI Qiqing; HAN Xiuzhen; LIU Zhili

    2004-01-01

    Most methods for classification of remote sensing data are based on the statistical parameter evaluation with the assumption that the samples obey the normal distribution. However, more accurate classification results can be obtained with the neural network method through getting knowledge from environments and adjusting the parameter (or weight) step by step by a specific measurement. This paper focuses on the double-layer structured Kohonen self-organizing feature map (SOFM), for which all neurons within the two layers are linked one another and those of the competition layers are linked as well along the sides. Therefore, the self-adapting learning ability is improved due to the effective competition and suppression in this method. The SOFM has become a hot topic in the research area of remote sensing data classification. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a new satellite-borne remote sensing instrument with three 15-m resolution bands and three 30-m resolution bands at the near infrared. The ASTER data of Dagang district, Tianjin Municipality is used as the test data in this study. At first, the wavelet fusion is carried out to make the spatial resolutions of the ASTER data identical; then, the SOFM method is applied to classifying the land cover types. The classification results are compared with those of the maximum likelihood method (MLH). As a consequence, the classification accuracy of SOFM increases about by 7% in general and, in particular, it is almost as twice as that of the MLH method in the town.

  20. Assessment of seasonal features based on Landsat time series for tree crown cover mapping in Burkina Faso

    Science.gov (United States)

    Liu, Jinxiu; Heiskanen, Janne; Aynekuly, Ermias; Pellikka, Petri

    2016-04-01

    Tree crown cover (CC) is an important vegetation attribute for land cover characterization, and for mapping and monitoring forest cover. Free data from Landsat and Sentinel-2 allow construction of fine resolution satellite image time series and extraction of seasonal features for predicting vegetation attributes. In the savannas, surface reflectance vary distinctively according to the rainy and dry seasons, and seasonal features are useful information for CC mapping. However, it is unclear if it is better to use spectral bands or vegetation indices (VI) for computation of seasonal features, and how feasible different VI are for CC prediction in the savanna woodlands and agroforestry parklands of West Africa. In this study, the objective was to compare seasonal features based on spectral bands and VI for CC mapping in southern Burkina Faso. A total of 35 Landsat images from November 2013 to October 2014 were processed. Seasonal features were computed using a harmonic model with three parameters (mean, amplitude and phase), and spectral bands, normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), normalized difference water index (NDWI), tasseled cap (TC) indices (brightness, greenness, wetness) as input data. The seasonal features were employed to predict field estimated CC (n = 160) using Random Forest algorithm. The most accurate results were achieved when using seasonal features based on TC indices (R2: 0.65; RMSE: 10.7%) and spectral bands (R2: 0.64; RMSE: 10.8%). GNDVI performed better than NDVI or NDWI, and NDWI resulted in the poorest results (R2: 0.56; RMSE: 11.9%). The results indicate that spectral features should be carefully selected for CC prediction as shown by relatively poor performance of commonly used NDVI. The seasonal features based on three TC indices and all the spectral bands provided superior accuracy in comparison to single VI. The method presented in this study provides a feasible method to map

  1. Collaborative Hierarchical Sparse Modeling

    CERN Document Server

    Sprechmann, Pablo; Sapiro, Guillermo; Eldar, Yonina C

    2010-01-01

    Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global opt...

  2. Feature Mapping and Recuperation by Using Elliptical Basis Function Networks for Robust Speaker Verification

    Institute of Scientific and Technical Information of China (English)

    李昕; 郑宇; 等

    2002-01-01

    The performance of speaker verification systems is often compromised under real-world environments.For example,variations in handset characteristics could cause severe performance degradation.This paper presents a novel method to overcome this problem by using a non-linear handset mapper.Under this method,a mapper is constructed by training an elliptical basis function network using distorted speech features as inputs and the corresponding clean features as the desired outputs.During feature recuperation,clean features are recovered by feeding the distorted features to the feature mapper.The recovered features are then presented to a speaker model as if they were derived from clean speech.Experimental evaluation based on 258 speakers of the TIMIT and NTIMIT corpuses suggest that the feature mappers improve the verification performance remarkably.

  3. 一种基于特征地图的移动机器人SLAM方案%Mobile Robot Simultaneous Localization and Mapping Based on Feature Map

    Institute of Scientific and Technical Information of China (English)

    严文; 潘炼; 陶辉; 严共灿

    2011-01-01

    设计了一种结构化环境中基于特征地图的地图创建方案;采用激光测距仪进行特征地图创建,利用"聚合-分害虫-聚合"的方法来提取线段表示环境信息实现局部地图创建;为了实现移动机器人的同时定位与地图创建,采用扩展卡尔曼滤波方法对机器人的位姿与地图信息进行预测及更新,结合状态估计和数据关联理论,实验显示x的校正量保持在±0.9cm之内;y的校正量保持在±2.5cm之内;θ的校正量在±1.2之内,实现了基于扩展卡尔曼滤波器的SLAM.%A Map building algorithm basedon feature map in structured indoor environment is presented in this paper, this thesis introduces a method of feature-based map building based on laser range finder. In the process of local map building, an improved“ merge-divided-merge” method is adopted, using line segments to denote the environment information. To realize simultaneous localization and mapping, an extended Kalman filter (EKF) is used to update the robot position and the environment character. Combining state estimates and data association theory, SLAM based on the extend Kalman filter is obtained. This method has been implemented on the mobile robot platform;its validity has been demonstrated.

  4. SOFM Neural Network Based Hierarchical Topology Control for Wireless Sensor Networks

    OpenAIRE

    2014-01-01

    Well-designed network topology provides vital support for routing, data fusion, and target tracking in wireless sensor networks (WSNs). Self-organization feature map (SOFM) neural network is a major branch of artificial neural networks, which has self-organizing and self-learning features. In this paper, we propose a cluster-based topology control algorithm for WSNs, named SOFMHTC, which uses SOFM neural network to form a hierarchical network structure, completes cluster head selection by the...

  5. Combining Self-organizing Feature Map with Support Vector Regression Based on Expert System%自组织映射算法与基于专家系统的支持向量回归的结合

    Institute of Scientific and Technical Information of China (English)

    王玲; 穆志纯; 郭辉

    2005-01-01

    A new approach is proposed to model nonlinear dynamic systems by combining SOM (self-organizing feature map) with support vector regression (SVR) based on expert system. The whole system has a two-stage neural network architecture. In the first stage SOM is used as a clustering algorithm to partition the whole input space into several disjointed regions. A hierarchical architecture is adopted in the partition to avoid the problem of predetermining the number of partitioned regions. Then, in the second stage, multiple SVR, also called SVR experts, that best fit each partitioned region by the combination of different kernel function of SVR and promote the configuration and tuning of SVR. Finally, to apply this new approach to time-series prediction problems based on the Mackey-Glass differential equation and Santa Fe data, the results show that SVR experts has effective improvement in the generalist performance in comparison with the single SVR model.

  6. TEMPO: Feature-Endowed Teichm\\"uller Extremal Mappings of Point Clouds

    OpenAIRE

    Meng, Ting Wei; Choi, Gary Pui-Tung; Lui, Lok Ming

    2015-01-01

    In recent decades, the use of 3D point clouds has been widespread in computer industry. The development of techniques in analyzing point clouds is increasingly important. In particular, mapping of point clouds has been a challenging problem. In this paper, we develop a discrete analogue of the Teichm\\"{u}ller extremal mappings, which guarantee uniform conformality distortions, on point cloud surfaces. Based on the discrete analogue, we propose a novel method called TEMPO for computing Teichm\\...

  7. A MapReduce scheme for image feature extraction and its application to man-made object detection

    Science.gov (United States)

    Cai, Fei; Chen, Honghui

    2013-07-01

    A fundamental challenge in image engineering is how to locate interested objects from high-resolution images with efficient detection performance. Several man-made objects detection approaches have been proposed while the majority of these methods are not truly timesaving and suffer low degree of detection precision. To address this issue, we propose a novel approach for man-made object detection in aerial image involving MapReduce scheme for large scale image analysis to support image feature extraction, which can be widely used to compute-intensive tasks in a highly parallel way, and texture feature extraction and clustering. Comprehensive experiments show that the parallel framework saves voluminous time for feature extraction with satisfied objects detection performance.

  8. Feature Specific Criminal Mapping using Data Mining Techniques and Generalized Gaussian Mixture Model

    OpenAIRE

    Uttam Mande; Y. Srinivas; Murthy, J. V. R.

    2012-01-01

    Lot of research is projected to map the criminal with that of crime and it is observed that there is still a huge increase in the crime rate due to the gap between the optimal usage of technologies and investigation. This has given scope for the development of new methodologies in the area of crime investigation using the techniques based on data mining, image processing, forensic, and social mining. In this paper, presents a model using new methodology for mapping the criminal with the crime...

  9. Visualizing the Quality of Vectur Features - a Proposal for Cadastral Maps

    Science.gov (United States)

    Navratil, G.; Leopoldseder, V.

    2017-09-01

    A well-known problem of geographical information is the communication of the quality level. It can be either done verbally / numerically or it can be done graphically. The graphical form is especially useful if the quality has a spatial variation because the spatial distribution is visualized as well. The problem of spatial variation of quality is an issue for cadastral maps. Non-experts cannot determine the quality at a specific location. Therefore a visual representation was tested for the Austrian cadastre. A map sheet was redesigned to give some indication of cadastral quality and presented to both experts and non-experts. The paper presents the result of the interviews.

  10. C-band RISAT-1 imagery for geospatial mapping of cryospheric surface features in the Antarctic environment

    Science.gov (United States)

    Jawak, Shridhar D.; Panditrao, Satej N.; Luis, Alvarinho J.

    2016-05-01

    Cryospheric surface feature classification is one of the widely used applications in the field of polar remote sensing. Precise surface feature maps derived from remotely sensed imageries are the major requirement for many geoscientific applications in polar regions. The present study explores the capabilities of C-band dual polarimetric (HH & HV) SAR imagery from Indian Radar Imaging Satellite (RISAT-1) for land cryospheric surface feature mapping. The study areas selected for the present task were Larsemann Hills and Schirmacher Oasis, East Antarctica. RISAT-1 Fine Resolution STRIPMAP (FRS-1) mode data with 3-m spatial resolution was used in the present research attempt. In order to provide additional context to the amount of information in dual polarized RISAT-1 SAR data, a band HH+HV was introduced to make use of the original two polarizations. In addition to the data calibration, transformed divergence (TD) procedure was performed for class separability analysis to evaluate the quality of the statistics before image classification. For most of the class pairs the TD values were comparable, which indicated that the classes have good separability. Fuzzy and Artificial Neural Network classifiers were implemented and accuracy was checked. Nonparametric classifier Support Vector Machine (SVM) was also used to classify RISAT-1 data with an optimized polarization combination into three land-cover classes consisting of sea ice/snow/ice, rocks/landmass, and lakes/waterbodies. This study demonstrates that C-band FRS1 image mode data from the RISAT-1 mission can be exploited to identify, map and monitor land cover features in the polar regions, even during dark winter period. For better landcover classification and analysis, hybrid polarimetric data (cFRS-1 mode) from RISAT-1, which incorporates phase information, unlike the dual-pol linear (HH, HV) can be used for obtaining better polarization signatures.

  11. EPA Region 1 - Map Layers for Valley ID Tool (Hosted Feature Service)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Valley Service Feature Layer hosts spatial data for EPA Region 1's Valley Identification Tool. These layers contain attribute information added by EPA R1 GIS...

  12. Features of collisionless turbulence in the intracluster medium from simulated Faraday rotation maps - II. The effects of instabilities feedback

    Science.gov (United States)

    Santos-Lima, R.; de Gouveia Dal Pino, E. M.; Falceta-Gonçalves, D. A.; Nakwacki, M. S.; Kowal, G.

    2017-03-01

    Statistical analysis of Faraday rotation measure (RM) maps of the intracluster medium (ICM) of galaxy clusters provides a unique tool to evaluate some spatial features of the magnetic fields there. Its combination with numerical simulations of magnetohydrodynamic (MHD) turbulence allows the diagnosis of the ICM turbulence. Being the ICM plasma weakly collisional, the thermal velocity distribution of the particles naturally develops anisotropies as a consequence of the large-scale motions and the conservation of the magnetic moment of the charged particles. A previous study (Paper I) analysed the impact of large-scale thermal anisotropy on the statistics of RM maps synthesized from simulations of turbulence; these simulations employed a collisionless MHD model that considered a tensor pressure with uniform anisotropy. In this work, we extend that analysis to a collisionless MHD model in which the thermal anisotropy develops according to the conservation of the magnetic moment of the thermal particles. We also consider the effect of anisotropy relaxation caused by the microscale mirror and firehose instabilities. We show that if the relaxation rate is fast enough to keep the anisotropy limited by the threshold values of the instabilities, the dispersion and power spectrum of the RM maps are indistinguishable from those obtained from collisional MHD. Otherwise, there is a reduction in the dispersion and steepening of the power spectrum of the RM maps (compared to the collisional case). Considering the first scenario, the use of collisional MHD simulations for modelling the RM statistics in the ICM becomes better justified.

  13. Adaptive mobility management scheme in hierarchical mobile IPv6

    Science.gov (United States)

    Fang, Bo; Song, Junde

    2004-04-01

    Hierarchical mobile IPv6 makes the mobility management localized. Registration with HA is only needed while MN moving between MAP domains. This paper proposed an adaptive mobility management scheme based on the hierarchical mobile IPv6. The scheme focuses on the MN operation as well as MAP operation during the handoff. Adaptive MAP selection algorithm can be used to select a suitable MAP to register with once MN moves into a new subnet while MAP can thus adaptively changing his management domain. Furthermore, MAP can also adaptively changes its level in the hierarchical referring on the service load or other related information. Detailed handoff algorithm is also discussed in this paper.

  14. A Modified T-test Feature Selection Method and Its Application on the HapMap Genotype Data

    Institute of Scientific and Technical Information of China (English)

    Nina Zhou; Lipo Wang

    2007-01-01

    Single nucleotide polymorphisms (SNPs) are genetic variations that determine the differences between any two unrelated individuals. Various population groups can be distinguished from each other using SNPs. For instance, the HapMap dataset has four population groups with about ten million SNPs. For more insights on human evolution, ethnic variation, and population assignment, we propose to find out which SNPs are significant in determining the population groups and then to classify different populations using these relevant SNPs as input features. In this study, we developed a modified t-test ranking measure and applied it to the HapMap genotype data. Firstly, we rank all SNPs in comparison with other feature importance measures including F-statistics and the informativeness for assignment. Secondly, we select different numbers of the most highly ranked SNPs as the input to a classifier, such as the support vector machine, so as to find the best feature subset corresponding to the best classification accuracy. Experimental results showed that the proposed method is very effective in finding SNPs that are significant in determining the population groups, with reduced computational burden and better classification accuracy.

  15. Features of collisionless turbulence in the intracluster medium from simulated Faraday rotation maps II: the effects of instabilities feedback

    CERN Document Server

    Santos-Lima, R; Falceta-Gonçalves, D A; Nakwacki, M S; Kowal, G

    2016-01-01

    Statistical analysis of Faraday Rotation Measure (RM) maps of the intracluster medium (ICM) of galaxy clusters provides a unique tool to evaluate some spatial features of the magnetic fields there. Its combination with numerical simulations of magnetohydrodynamic (MHD) turbulence allows the diagnosis of the ICM turbulence. Being the ICM plasma weakly collisional, the thermal velocity distribution of the particles naturally develops anisotropies as a consequence of the large scale motions and the conservation of the magnetic moment of the charged particles. A previous study (Paper I) analyzed the impact of large scale thermal anisotropy on the statistics of RM maps synthesized from simulations of turbulence; these simulations employed a collisionless MHD model which considered a tensor pressure with uniform anisotropy. In the present work, we extend that analysis to a collisionless MHD model in which the thermal anisotropy develops according to the conservation of the magnetic moment of the thermal particles. ...

  16. Weather regimes over Senegal during the summer monsoon season using self-organizing maps and hierarchical ascendant classification. Part II: interannual time scale

    Energy Technology Data Exchange (ETDEWEB)

    Gueye, A.K. [ESP, UCAD, Dakar (Senegal); Janicot, Serge; Sultan, Benjamin [LOCEAN/IPSL, IRD, Universite Pierre et Marie Curie, Paris cedex 05 (France); Niang, A. [LTI, ESP/UCAD, Dakar (Senegal); Sawadogo, S. [LTI, EPT, Thies (Senegal); Diongue-Niang, A. [ANACIM, Dakar (Senegal); Thiria, S. [LOCEAN/IPSL, UPMC, Paris (France)

    2012-11-15

    The aim of this work is to define over the period 1979-2002 the main synoptic weather regimes relevant for understanding the daily variability of rainfall during the summer monsoon season over Senegal. ''Interannual'' synoptic weather regimes are defined by removing the influence of the mean 1979-2002 seasonal cycle. This is different from Part I where the seasonal evolution of each year was removed, then removing also the contribution of interannual variability. As in Part I, the self-organizing maps approach, a clustering methodology based on non-linear artificial neural network, is combined with a hierarchical ascendant classification to compute these regimes. Nine weather regimes are identified using the mean sea level pressure and 850 hPa wind field as variables. The composite circulation patterns of all these nine weather regimes are very consistent with the associated anomaly patterns of precipitable water, mid-troposphere vertical velocity and rainfall. They are also consistent with the distribution of rainfall extremes. These regimes have been then gathered into different groups. A first group of four regimes is included in an inner circuit and is characterized by a modulation of the semi-permanent trough located along the western coast of West Africa and an opposite modulation on the east. This circuit is important because it associates the two wettest and highly persistent weather regimes over Senegal with the driest and the most persistent one. One derivation of this circuit is highlighted, including the two driest regimes and the most persistent one, what can provide important dry sequences occurrence. An exit of this circuit is characterised by a filling of the Saharan heat low. An entry into the main circuit includes a southward location of the Saharan heat low followed by its deepening. The last weather regime is isolated from the other ones and it has no significant impact on Senegal. It is present in June and September, and

  17. Importance of landscape features and Earth observation derived habitat maps for modelling amphibian distribution in the Alta Murgia National Park

    Science.gov (United States)

    Ficetola, Gentile Francesco; Adamo, Maria; Bonardi, Anna; De Pasquale, Vito; Liuzzi, Cristiano; Lovergine, Francesco; Marcone, Francesco; Mastropasqua, Fabio; Tarantino, Cristina; Blonda, Palma; Padoa-Schioppa, Emilio

    2015-05-01

    Traditionally, analyses of relationships between amphibians and habitat focused on breeding environments (i.e., pond features) more than on the features of the surrounding environment. Nevertheless, for most amphibians the terrestrial phase is longer than the aquatic phase, and consequently landscape features (i.e., habitat mosaics) may have an important role for modelling amphibian distribution. There were different aims in this analysis. Firstly, we compared the effectiveness of the information provided by land cover/use (LC/LU) classes and habitat classes defined according to a new habitat taxonomy named General Habitat Category (GHC), which is based on the concept of biological forms of dominant vegetation and class naturalness. The GHC map used was obtained from a pre-existing validated LC/LU map, by integrating spectral and spatial measurements from very high resolution Earth observation data according to ecological expert rules involving concepts related to spatial and temporal relationships among LC/LU and habitat classes. Then, we investigated the importance for amphibians of the landscape surrounding ponds within the Italian Alta Murgia National Park. The work assessed whether LC/LU classes in pond surrounds are important for the presence/absence of amphibians in this area, and identified which classes are more important for amphibians. The results obtained can provide useful indications to management strategies aiming at the conservation of amphibians within the study area. An information-theoretic approach was adopted to assess whether GHC maps allow to improve the performance of species distribution models. We used the Akaike's Information Criterion (AICc) to compare the effectiveness of GHC categories versus LC/LU categories in explaining the presence/absence of pool frogs. AICc weights suggest that GHC categories can better explain the distribution of frogs, compared to LC/LU classes.

  18. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  19. Mapping Drug Physico-Chemical Features to Pathway Activity Reveals Molecular Networks Linked to Toxicity Outcome

    OpenAIRE

    Philipp Antczak; Fernando Ortega; J Kevin Chipman; Francesco Falciani

    2010-01-01

    The identification of predictive biomarkers is at the core of modern toxicology. So far, a number of approaches have been proposed. These rely on statistical inference of toxicity response from either compound features (i.e., QSAR), in vitro cell based assays or molecular profiling of target tissues (i.e., expression profiling). Although these approaches have already shown the potential of predictive toxicology, we still do not have a systematic approach to model the interaction between chemi...

  20. The Precedence of Global Features in the Perception of Map Symbols

    Science.gov (United States)

    1988-06-01

    emphasis in the experimental literature ( Atkinson & Shiffrin , 1968; Neisser, 1967) has had an impact on perceptual theorizing. The position did not... Shiffrin , R. M. Human Memory : A proposed system and its control processes. In The Psychology of Learning and Motivation. Vol. 2, G. H. Bowen & J. T...discrimination of new symbol features can be obtained on any symbol population to validly predict performance. 81 REFERENCES Atkinson , R. C., and

  1. Mapping drug physico-chemical features to pathway activity reveals molecular networks linked to toxicity outcome.

    Directory of Open Access Journals (Sweden)

    Philipp Antczak

    Full Text Available The identification of predictive biomarkers is at the core of modern toxicology. So far, a number of approaches have been proposed. These rely on statistical inference of toxicity response from either compound features (i.e., QSAR, in vitro cell based assays or molecular profiling of target tissues (i.e., expression profiling. Although these approaches have already shown the potential of predictive toxicology, we still do not have a systematic approach to model the interaction between chemical features, molecular networks and toxicity outcome. Here, we describe a computational strategy designed to address this important need. Its application to a model of renal tubular degeneration has revealed a link between physico-chemical features and signalling components controlling cell communication pathways, which in turn are differentially modulated in response to toxic chemicals. Overall, our findings are consistent with the existence of a general toxicity mechanism operating in synergy with more specific single-target based mode of actions (MOAs and provide a general framework for the development of an integrative approach to predictive toxicology.

  2. Image Fusion Based on the Self-Organizing Feature Map Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhaoli; SUN Shenghe

    2001-01-01

    This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).

  3. New non-Gaussian feature in COBE-DMR Four Year Maps

    CERN Document Server

    Magueijo, J

    2000-01-01

    We extend a previous bispectrum analysis of the Cosmic Microwave Background temperature anisotropy, allowing for the presence of correlations between different angular scales. We find a strong non-Gaussian signal in the ``inter-scale'' components of the bispectrum: their observed values concentrate close to zero instead of displaying the scatter expected from Gaussian maps. This signal is present over the range of multipoles $\\ell=6 -18$, in contrast with previous detections. We attempt to attribute this effect to galactic foreground contamination, pixelization effects, possible anomalies in the noise, documented systematic errors studied by the COBE team, and the effect of assumptions used in our Monte Carlo simulations. Within this class of systematic errors the confidence level for rejecting Gaussianity varies between 97% and 99.8%.

  4. Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagram and a hierarchical task analysis diagram

    OpenAIRE

    Potts Henry WW; Anderson Janet E; Colligan Lacey; Berman Jonathan

    2010-01-01

    Abstract Background Many quality and safety improvement methods in healthcare rely on a complete and accurate map of the process. Process mapping in healthcare is often achieved using a sequential flow diagram, but there is little guidance available in the literature about the most effective type of process map to use. Moreover there is evidence that the organisation of information in an external representation affects reasoning and decision making. This exploratory study examined whether the...

  5. 基于层次MAP的虚拟试验系统互操作协议研究%Interoperability Protocol Study of Virtual Test System Based on Hierarchical MAP

    Institute of Scientific and Technical Information of China (English)

    李雨江; 杜承烈; 尤涛

    2011-01-01

    Aiming at the problem that Ethernet and VMIC rellective memory network cannot communicate directly in virtual test system, an interoperability protocol scheme based on hierarchical MAP is proposed .BAsed on the introduction of gateway node which connects Ethernet and VWIC reflective memory network, we propose three-tier memory division scheme of VMIC refective memory, achieve the distribution and release algorithms of reflective memory by hierarchical MAP, complete the mutual mapping between Ethernet data and reflective memory data, thus achieving interoperability protocol of virtual test system. Tests show the the interoperability protocol can effectively exchanges and shares data between Ethernet and VMIC real-time metwor,and satisfies the real-time request of virtual test system.%在虚拟试验系统中,针对以太网和VMIC反射内存网不能直接通信的问题,提出了一种基于层次MAP的互操作协议方案;在引入网关节点连接以太网和VMIC反射内存网的基础上,提出了VMIC反射内存的三层内存划分方案,利用层次MAP实现了反射内存的分配和释放算法,完成了以太网数据和反射内存网数据的相互映射,从而实现了虚拟试验系统的互操作;试验表明,该互操作协议方案能够有效实现以太网和VMIC实时网之间的数据交换和共享,较好地满足了虚拟试验系统的实时性要求.

  6. Mapping mantle flow during retreating subduction: Laboratory models analyzed by feature tracking

    Science.gov (United States)

    Funiciello, F.; Moroni, M.; Piromallo, C.; Faccenna, C.; Cenedese, A.; Bui, H. A.

    2006-03-01

    Three-dimensional dynamically consistent laboratory models are carried out to model the large-scale mantle circulation induced by subduction of a laterally migrating slab. A laboratory analogue of a slab-upper mantle system is set up with two linearly viscous layers of silicone putty and glucose syrup in a tank. The circulation pattern is continuously monitored and quantitatively estimated using a feature tracking image analysis technique. The effects of plate width and mantle viscosity/density on mantle circulation are systematically considered. The experiments show that rollback subduction generates a complex three-dimensional time-dependent mantle circulation pattern characterized by the presence of two distinct components: the poloidal and the toroidal circulation. The poloidal component is the answer to the viscous coupling between the slab motion and the mantle, while the toroidal one is produced by lateral slab migration. Spatial and temporal features of mantle circulation are carefully analyzed. These models show that (1) poloidal and toroidal mantle circulation are both active since the beginning of the subduction process, (2) mantle circulation is intermittent, (3) plate width affects the velocity and the dimension of subduction induced mantle circulation area, and (4) mantle flow in subduction zones cannot be correctly described by models assuming a two-dimensional steady state process. We show that the intermittent toroidal component of mantle circulation, missed in those models, plays a crucial role in modifying the geometry and the efficiency of the poloidal component.

  7. Comparative Chromosome Map and Heterochromatin Features of the Gray Whale Karyotype (Cetacea).

    Science.gov (United States)

    Kulemzina, Anastasia I; Proskuryakova, Anastasia A; Beklemisheva, Violetta R; Lemskaya, Natalia A; Perelman, Polina L; Graphodatsky, Alexander S

    2016-01-01

    Cetacean karyotypes possess exceptionally stable diploid numbers and highly conserved chromosomes. To date, only toothed whales (Odontoceti) have been analyzed by comparative chromosome painting. Here, we studied the karyotype of a representative of baleen whales, the gray whale (Eschrichtius robustus, Mysticeti), by Zoo-FISH with dromedary camel and human chromosome-specific probes. We confirmed a high degree of karyotype conservation and found an identical order of syntenic segments in both branches of cetaceans. Yet, whale chromosomes harbor variable heterochromatic regions constituting up to a third of the genome due to the presence of several types of repeats. To investigate the cause of this variability, several classes of repeated DNA sequences were mapped onto chromosomes of whale species from both Mysticeti and Odontoceti. We uncovered extensive intrapopulation variability in the size of heterochromatic blocks present in homologous chromosomes among 3 individuals of the gray whale by 2-step differential chromosome staining. We show that some of the heteromorphisms observed in the gray whale karyotype are due to distinct amplification of a complex of common cetacean repeat and heavy satellite repeat on homologous autosomes. Furthermore, we demonstrate localization of the telomeric repeat in the heterochromatin of both gray and pilot whale (Globicephala melas, Odontoceti). Heterochromatic blocks in the pilot whale represent a composite of telomeric and common repeats, while heavy satellite repeat is lacking in the toothed whale consistent with previous studies.

  8. Persistent small-scale features in maps of the anisotropy of ocean surface velocities

    Science.gov (United States)

    Sen, A.; Arbic, B. K.; Scott, R. B.; Holland, C. L.; Logan, E.; Qiu, B.

    2006-12-01

    Much of the stirring and mixing in the upper ocean is due to geostrophically balanced mesoscale eddies. Ocean general circulation models commonly parameterize eddy effects and can aid in predicting dispersal of materials throughout the ocean or in predicting long-term climate change. Parameterizations of eddy mixing depend on the isotropy of the eddies. Motivated by this, we investigate the isotropy of oceanic mesoscale eddies with seven years of sea surface height data recorded by satellite altimeters. From these data, we determined a sea surface height anomaly, and surface geostrophic velocities u and v in the zonal (east-west) and meridional (north-south) directions, respectively. From the latter two quantities we can calculate zonal and meridional kinetic energies u2 and v2. Integrals of u2 and v2 around latitude bands 10 degrees wide are nearly equal, in contrast with the results of simple beta-plane geostrophic turbulence models, which suggest that zonal motions should predominate. Maps of the quantity u2-v2 (normalized by standard error) show fine-scale structures that persist over times longer than the lifespan of turbulent eddies. Thus the mesoscale eddy field is locally anisotropic almost everywhere. Further investigation into the causes of these small-scale structures is needed and may take advantage of animations of sea surface height, in which quasi- circular, westward-propagating eddies can easily be seen.

  9. Point Cloud Mapping Methods for Documenting Cultural Landscape Features at the Wormsloe State Historic Site, Savannah, Georgia, USA

    Science.gov (United States)

    Jordana, T. R.; Goetcheus, C. L.; Madden, M.

    2016-06-01

    Documentation of the three-dimensional (3D) cultural landscape has traditionally been conducted during site visits using conventional photographs, standard ground surveys and manual measurements. In recent years, there have been rapid developments in technologies that produce highly accurate 3D point clouds, including aerial LiDAR, terrestrial laser scanning, and photogrammetric data reduction from unmanned aerial systems (UAS) images and hand held photographs using Structure from Motion (SfM) methods. These 3D point clouds can be precisely scaled and used to conduct measurements of features even after the site visit has ended. As a consequence, it is becoming increasingly possible to collect non-destructive data for a wide variety of cultural site features, including landscapes, buildings, vegetation, artefacts and gardens. As part of a project for the U.S. National Park Service, a variety of data sets have been collected for the Wormsloe State Historic Site, near Savannah, Georgia, USA. In an effort to demonstrate the utility and versatility of these methods at a range of scales, comparisons of the features mapped with different techniques will be discussed with regards to accuracy, data set completeness, cost and ease-of-use.

  10. POINT CLOUD MAPPING METHODS FOR DOCUMENTING CULTURAL LANDSCAPE FEATURES AT THE WORMSLOE STATE HISTORIC SITE, SAVANNAH, GEORGIA, USA

    Directory of Open Access Journals (Sweden)

    T. R. Jordana

    2016-06-01

    Full Text Available Documentation of the three-dimensional (3D cultural landscape has traditionally been conducted during site visits using conventional photographs, standard ground surveys and manual measurements. In recent years, there have been rapid developments in technologies that produce highly accurate 3D point clouds, including aerial LiDAR, terrestrial laser scanning, and photogrammetric data reduction from unmanned aerial systems (UAS images and hand held photographs using Structure from Motion (SfM methods. These 3D point clouds can be precisely scaled and used to conduct measurements of features even after the site visit has ended. As a consequence, it is becoming increasingly possible to collect non-destructive data for a wide variety of cultural site features, including landscapes, buildings, vegetation, artefacts and gardens. As part of a project for the U.S. National Park Service, a variety of data sets have been collected for the Wormsloe State Historic Site, near Savannah, Georgia, USA. In an effort to demonstrate the utility and versatility of these methods at a range of scales, comparisons of the features mapped with different techniques will be discussed with regards to accuracy, data set completeness, cost and ease-of-use.

  11. Mapping Soil hydrologic features in a semi-arid irrigated area in Spain

    Science.gov (United States)

    Jiménez-Aguirre, M.° Teresa; Isidoro, Daniel; Usón, Asunción

    2016-04-01

    The lack of soil information is a managerial problem in irrigated areas in Spain. The Violada Irrigation District (VID; 5234 ha) is a gypsic, semi-arid region in the Middle Ebro River Basin, northeast Spain. VID is under irrigation since the 1940's. The implementation of the flood irrigation system gave rise to waterlogging problems, solved along the years with the installation of an artificial drainage network. Aggregated water balances have been performed in VID since the early 1980's considering average soil properties and aggregated irrigation data for the calculations (crop evapotranspiration, canal seepage, and soil drainage). In 2008-2009, 91% of the VID was modernized to sprinkler irrigation. This new system provides detailed irrigation management information that together with detailed soil information would allow for disaggregated water balances for a better understanding of the system. Our goal was to draw a semi-detailed soil map of VID presenting the main soil characteristics related to irrigation management. A second step of the work was to set up pedotransfer functions (PTF) to estimate the water content and saturated hydraulic conductivity (Ks) from easily measurable parameters. Thirty four pits were opened, described and sampled for chemical and physical properties. Thirty three additional auger holes were sampled for water holding capacity (WHC; down to 60 cm), helping to draw the soil units boundaries. And 15 Ks tests (inverse auger hole method) were made. The WHC was determined as the difference between the field capacity (FC) and wilting point (WP) measured in samples dried at 40°C during 5 days. The comparison with old values dried at 105°C for 2 days highlighted the importance of the method when gypsum is present in order to avoid water removal from gypsum molecules. The soil map was drawn down to family level. Thirteen soil units were defined by the combination of five subgroups [Typic Calcixerept (A), Petrocalcic Calcixerept (B), Gypsic

  12. Near-surface gas mapping studies of salt geologic features at Weeks Island and other sites

    Energy Technology Data Exchange (ETDEWEB)

    Molecke, M.A. [Sandia National Lab., Albuquerque, NM (United States); Carney, K.R.; Autin, W.J.; Overton, E.B. [Louisiana State Univ., Baton Rouge, LA (United States)

    1996-10-01

    Field sampling and rapid gas analysis techniques were used to survey near-surface soil gases for geotechnical diagnostic purposes at the Weeks Island Strategic Petroleum Reserve (SPR) site and other salt dome locations in southern Louisiana. This report presents the complete data, results and interpretations obtained during 1995. Weeks Island 1994 gas survey results are also briefly summarized; this earlier study did not find a definitive correlation between sinkhole No. 1 and soil gases. During 1995, several hundred soil gas samples were obtained and analyzed in the field by gas chromatography, for profiling low concentrations and gas anomalies at ppm to percent levels. The target gases included hydrogen, methane, ethane and ethylene. To supplement the field data, additional gas samples were collected at various site locations for laboratory analysis of target gases at ppb levels. Gases in the near-surface soil originate predominantly from the oil, from petrogenic sources within the salt, or from surface microbial activity. Surveys were conducted across two Weeks Island sinkholes, several mapped anomalous zones in the salt, and over the SPR repository site and its perimeter. Samples were also taken at other south Louisiana salt dome locations for comparative purposes. Notable results from these studies are that elevated levels of hydrogen and methane (1) were positively associated with anomalous gassy or shear zones in the salt dome(s) and (2) are also associated with suspected salt fracture (dilatant) zones over the edges of the SPR repository. Significantly elevated areas of hydrogen, methane, plus some ethane, were found over anomalous shear zones in the salt, particularly in a location over high pressure gas pockets in the salt, identified in the mine prior to SPR operations. Limited stable isotope ratio analyses, SIRA, were also conducted and determined that methane samples were of petrogenic origin, not biogenic.

  13. Structural integrity of hierarchical composites

    Directory of Open Access Journals (Sweden)

    Marco Paggi

    2012-01-01

    Full Text Available Interface mechanical problems are of paramount importance in engineering and materials science. Traditionally, due to the complexity of modelling their mechanical behaviour, interfaces are often treated as defects and their features are not explored. In this study, a different approach is illustrated, where the interfaces play an active role in the design of innovative hierarchical composites and are fundamental for their structural integrity. Numerical examples regarding cutting tools made of hierarchical cellular polycrystalline materials are proposed, showing that tailoring of interface properties at the different scales is the way to achieve superior mechanical responses that cannot be obtained using standard materials

  14. Assessment of habitat conditions using Self-Organizing Feature Maps for reintroduction/introduction of Aldrovanda vesiculosa L. in Poland

    Directory of Open Access Journals (Sweden)

    Piotr Kosiba

    2011-07-01

    Full Text Available The study objects were Aldrovanda vesiculosa L., an endangered species and fifty five water sites in Poland. The aim of the present work was to test the Self-Organizing Feature Map in order to examine and predict water properties and type of trophicity for restoration of the rare plant. Descriptive statistical parameters have been calculated, analysis of variance and cluster analysis were carried out and SOFM model has been constructed for analysed sites. The results of SOFM model and cluster analysis were compared. The study revealed that the ordination of individuals and groups of neurons in topological map of sites are similar in relation to dendrogram of cluster analysis, but not identical. The constructed SOFM model is related with significantly different contents of chemical water properties and type of trophicity. It appeared that sites with A. vesiculosa are predominantly distrophic and eutrophic waters shifted to distrophicity. The elevated model showed the sites with chemical properties favourable for restoration the species. Determined was the range of ecological tolerance of the species in relation to habitat conditions as stenotopic or relatively stenotopic in respect of the earlier accepted eutrophic status. The SOFM appeared to be a useful technique for ordination of ecological data and provides a novel framework for the discovery and forecasting of ecosystem properties constituting a validation of the SOFM method in this type of studies.

  15. Building a Secure and Feature-rich Mobile Mapping Service App Using HTML5: Challenges and Best Practices

    Energy Technology Data Exchange (ETDEWEB)

    Karthik, Rajasekar [ORNL; Patlolla, Dilip Reddy [ORNL; Sorokine, Alexandre [ORNL; Myers, Aaron T [ORNL

    2014-01-01

    Managing a wide variety of mobile devices across multiple mobile operating systems is a security challenge for any organization [1, 2]. With the wide adoption of mobile devices to access work-related apps, there is an increase in third-party apps that might either misuse or improperly handle user s personal or sensitive data [3]. HTML5 has been receiving wide attention for developing cross-platform mobile apps. According to International Data Corporation (IDC), by 2015, 80% of all mobile apps will be based in part or wholly upon HTML5 [4]. Though HTML5 provides a rich set of features for building an app, it is a challenge for organizations to deploy and manage HTML5 apps on wide variety of devices while keeping security policies intact. In this paper, we will describe an upcoming secure mobile environment for HTML5 apps, called Sencha Space that addresses these issues and discuss how it will be used to design and build a secure and cross-platform mobile mapping service app. We will also describe how HTML5 and a new set of related technologies such as Geolocation API, WebGL, Open Layers 3, and Local Storage, can be used to provide a high end and high performance experience for users of the mapping service app.

  16. Multi-channel EEG Feature Extraction Using Hierarchical Vector Autoregression%分层向量自回归的多通道脑电信号的特征提取研究

    Institute of Scientific and Technical Information of China (English)

    王金甲; 陈春

    2016-01-01

    Feature extraction and classification of electroencephalogram (EEG) signals is a core part of brain-computer interface (BCI). For multi-channel EEG signal and high dimension of feature vector of BCI system, a novel EEG signal recognition method called hierarchical vector autoregression (HVAR) is presented, which extracts EEG feature using regression coefficient of HVAR model and linear support vector machine (SVM). It overcomes the limitations of the autoregression (AR) model that can be used to extract the single channel EEG only, and effectively avoids the vector autoregression (VAR) model sharing a same delay for all channels. Our contribution is that regularization is added on the traditional VAR model and a reasonable hierarchical structure is adopted. It effectively compresses parameter space of VAR model. In this paper, HVAR model is used for EEG data classification for the first time. Experimental results show that the recognition accuracy of extracted feature of HVAR model using a 2 lag order multi-channel is higher than that of AR model of 6 lag order. So low-level HVAR model can describe the portrayed temporal relationship of EEG well. This shows HVAR may be a novel method to portray EEG signal, which has reference significance to other multi-channel time-series.%有效的特征提取方法能提高脑机接口(Brain-computer interface, BCI)系统对脑电(Electroencephalogram, EEG)信号的识别率。因脑电信号都是多通道的,本文将分层向量自回归(Hierarchical vector autoregression, HVAR)模型用于脑电信号的特征提取,并结合传统的线性支持向量机(Support vector machine, SVM)用于脑电信号识别。该模型不仅克服了自回归(Autoregression, AR)模型只能用来提取单通道特征的局限性,而且不再采用传统VAR (Vector autoregression)模型所有通道共用一个时滞的处理方法。创新之处在于在传统的VAR 模型基础上添加正则化思想,有效地压缩参数空间,实现合

  17. Application of growing hierarchical SOM for visualisation of network forensics traffic data.

    Science.gov (United States)

    Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T

    2012-08-01

    Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  19. Improved Discrimination of Volcanic Complexes, Tectonic Features, and Regolith Properties in Mare Serenitatis from Earth-Based Radar Mapping

    Science.gov (United States)

    Campbell, Bruce A.; Hawke, B. Ray; Morgan, Gareth A.; Carter, Lynn M.; Campbell, Donald B.; Nolan, Michael

    2014-01-01

    Radar images at 70 cm wavelength show 4-5 dB variations in backscatter strength within regions of relatively uniform spectral reflectance properties in central and northern Mare Serenitatis, delineating features suggesting lava flow margins, channels, and superposition relationships. These backscatter differences are much less pronounced at 12.6 cm wavelength, consistent with a large component of the 70 cm echo arising from the rough or blocky transition zone between the mare regolith and the intact bedrock. Such deep probing is possible because the ilmenite content, which modulates microwave losses, of central Mare Serenitatis is generally low (2-3% by weight). Modeling of the radar returns from a buried interface shows that an average regolith thickness of 10m could lead to the observed shifts in 70 cm echo power with a change in TiO2 content from 2% to 3%. This thickness is consistent with estimates of regolith depth (10-15m) based on the smallest diameter for which fresh craters have obvious blocky ejecta. The 70 cm backscatter differences provide a view of mare flow-unit boundaries, channels, and lobes unseen by other remote sensing methods. A localized pyroclastic deposit associated with Rima Calippus is identified based on its low radar echo strength. Radar mapping also improves delineation of units for crater age dating and highlights a 250 km long, east-west trending feature in northern Mare Serenitatis that we suggest is a large graben flooded by late-stage mare flows.

  20. Hierarchical Feature Extraction and Selection Method and the Applications in Automatic Target Recognition System%分级特征提取与选择及在自动目标识别系统中的应用

    Institute of Scientific and Technical Information of China (English)

    梅雪; 张继法; 许松松; 巩建鸣

    2012-01-01

    应用于遥感图像、武器制导等的自动目标识别系统中,经常遇到形状相似目标的鉴别问题。为提高其识别的快速性和识别率,提出一种分级的基于形状的目标识别方法。借鉴人类视觉感知方式提取多尺度特征,大尺度下采用全局特征快速粗分类,小尺度下采用局部特征鉴别形状相似目标。然后运用模糊规则对提取的特征进行选择,降低特征维数,加快目标匹配过程。实验结果表明:该方法能快速有效地识别形状相似的目标,特征选择后平均识别率较选择之前提高了6.99/6。%Similar shape object recognition is widely used in automatic target recognition system of remote sensing and weapon guidance. A hierarchical method of shape feature extraction and selection is proposed to increase the recognition efficiency and rate. I.earning from human visual perception, multi-scale features are extracted. C-lobal features are used to make a quick classification,and local features are used to distinguish targets with similar shape. To achieve the feature selection, fuzzy criterion is introduced which improves the matching processing and increases the recognition rate. Experimental results show this method is an effective and general way in recognizing targets with similar shape,and the feature selection improves the recognition rate by 6.9%than before.

  1. A Hierarchical Clustering Method Based on the Threshold of Semantic Feature in Big Data%大数据中一种基于语义特征阈值的层次聚类方法

    Institute of Scientific and Technical Information of China (English)

    罗恩韬; 王国军

    2015-01-01

    云计算、健康医疗、街景地图服务、推荐系统等新兴服务促使数据的种类和规模以前所未有的速度增长,数据量的激增会导致很多共性问题.例如数据的可表示,可处理和可靠性问题.如何有效处理和分析数据之间的关系,提高数据的划分效率,建立数据的聚类分析模型,已经成为学术界和企业界共同亟待解决的问题.该文提出一种基于语义特征的层次聚类方法,首先根据数据的语义特征进行训练,然后在每个子集上利用训练结果进行层次聚类,最终产生整体数据的密度中心点,提高了数据聚类效率和准确性.此方法采样复杂度低,数据分析准确,易于实现,具有良好的判定性.%The type and scale of data has been promoted with a hitherto unknown speed by the emerging services including cloud computing, health care, street view services recommendation system and so on. However, the surge in the volume of data may lead to many common problems, such as the representability, reliability and handlability of data. Therefore, how to effectively handle the relationship between the data and the analysis to improve the efficiency of classification of the data and establish the data clustering analysis model has become an academic and business problem, which needs to be solved urgently. A hierarchical clustering method based on semantic feature is proposed. Firstly, the data should be trained according to the semantic features of data, and then is used the training result to process hierarchical clustering in each subset; finally, the density center point is produced. This method can improve the efficiency and accuracy of data clustering. This algorithm is of low complexity about sampling, high accuracy of data analysis and good judgment. Furthermore, the algorithm is easy to realize.

  2. Intrahepatic Cholestasis of Pregnancy (ICP) in U.S. Latinas and Chileans: Clinical features, Ancestry Analysis, and Admixture Mapping.

    Science.gov (United States)

    Bull, Laura N; Hu, Donglei; Shah, Sohela; Temple, Luisa; Silva, Karla; Huntsman, Scott; Melgar, Jennifer; Geiser, Mary T; Sanford, Ukina; Ortiz, Juan A; Lee, Richard H; Kusanovic, Juan P; Ziv, Elad; Vargas, Juan E

    2015-01-01

    In the Americas, women with Indigenous American ancestry are at increased risk of intrahepatic cholestasis of pregnancy (ICP), relative to women of other ethnicities. We hypothesized that ancestry-related genetic factors contribute to this increased risk. We collected clinical and laboratory data, and performed biochemical assays on samples from U.S. Latinas and Chilean women, with and without ICP. The study sample included 198 women with ICP (90 from California, U.S., and 108 from Chile) and 174 pregnant control women (69 from California, U.S., and 105 from Chile). SNP genotyping was performed using Affymetrix arrays. We compared overall genetic ancestry between cases and controls, and used a genome-wide admixture mapping approach to screen for ICP susceptibility loci. We identified commonalities and differences in features of ICP between the 2 countries and determined that cases had a greater proportion of Indigenous American ancestry than did controls (p = 0.034). We performed admixture mapping, taking country of origin into account, and identified one locus for which Native American ancestry was associated with increased risk of ICP at a genome-wide level of significance (P = 3.1 x 10(-5), Pcorrected = 0.035). This locus has an odds ratio of 4.48 (95% CI: 2.21-9.06) for 2 versus zero Indigenous American chromosomes. This locus lies on chromosome 2, with a 10 Mb 95% confidence interval which does not contain any previously identified hereditary 'cholestasis genes.' Our results indicate that genetic factors contribute to the risk of developing ICP in the Americas, and support the utility of clinical and genetic studies of ethnically mixed populations for increasing our understanding of ICP.

  3. Intrahepatic Cholestasis of Pregnancy (ICP in U.S. Latinas and Chileans: Clinical features, Ancestry Analysis, and Admixture Mapping.

    Directory of Open Access Journals (Sweden)

    Laura N Bull

    Full Text Available In the Americas, women with Indigenous American ancestry are at increased risk of intrahepatic cholestasis of pregnancy (ICP, relative to women of other ethnicities. We hypothesized that ancestry-related genetic factors contribute to this increased risk. We collected clinical and laboratory data, and performed biochemical assays on samples from U.S. Latinas and Chilean women, with and without ICP. The study sample included 198 women with ICP (90 from California, U.S., and 108 from Chile and 174 pregnant control women (69 from California, U.S., and 105 from Chile. SNP genotyping was performed using Affymetrix arrays. We compared overall genetic ancestry between cases and controls, and used a genome-wide admixture mapping approach to screen for ICP susceptibility loci. We identified commonalities and differences in features of ICP between the 2 countries and determined that cases had a greater proportion of Indigenous American ancestry than did controls (p = 0.034. We performed admixture mapping, taking country of origin into account, and identified one locus for which Native American ancestry was associated with increased risk of ICP at a genome-wide level of significance (P = 3.1 x 10(-5, Pcorrected = 0.035. This locus has an odds ratio of 4.48 (95% CI: 2.21-9.06 for 2 versus zero Indigenous American chromosomes. This locus lies on chromosome 2, with a 10 Mb 95% confidence interval which does not contain any previously identified hereditary 'cholestasis genes.' Our results indicate that genetic factors contribute to the risk of developing ICP in the Americas, and support the utility of clinical and genetic studies of ethnically mixed populations for increasing our understanding of ICP.

  4. Preliminary Assessment of JERS-1 SAR to Discriminating Boreal Landscape Features for the Boreal Forest Mapping Project

    Science.gov (United States)

    McDonald, Kyle; Williams, Cynthia; Podest, Erika; Chapman, Bruce

    1999-01-01

    This paper presents an overview of the JERS-1 North American Boreal Forest Mapping Project and a preliminary assessment of JERS-1 SAR imagery for application to discriminating features applicable to boreal landscape processes. The present focus of the JERS-1 North American Boreal Forest Mapping Project is the production of continental scale wintertime and summertime SAR mosaics of the North American boreal forest for distribution to the science community. As part of this effort, JERS-1 imagery has been collected over much of Alaska and Canada during the 1997-98 winter and 1998 summer seasons. To complete the mosaics, these data will be augmented with data collected during previous years. These data will be made available to the scientific community via CD ROM containing these and similar data sets compiled from companion studies of Asia and Europe. Regional landscape classification with SAR is important for the baseline information it will provide about distribution of woodlands, positions of treeline, current forest biomass, distribution of wetlands, and extent of major rivercourses. As well as setting the stage for longer term change detection, comparisons across several years provides additional baseline information about short-term landscape change. Rapid changes, including those driven by fire, permafrost heat balance, flooding, and insect outbreaks can dominate boreal systems. We examine JERS-1 imagery covering selected sites in Alaska and Canada to assess quality and applicability to such relevant ecological and hydrological issues. The data are generally of high quality and illustrate many potential applications. A texture-based classification scheme is applied to selected regions to assess the applicability of these data for distinguishing distribution of such landcover types as wetland, tundra, woodland and forested landscapes.

  5. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  6. Collaborative Research: Multisensor Approach Mapping of 2D and 3D Geologic Features from Remotely Sensed Imagery

    Science.gov (United States)

    2005-09-23

    Lecture Notes in Computer Science , #2364...hierarchical multiclassifier system for hyperspectral data analysis,” Lecture Notes in Computer Science , Ed. F. Roli and J. Kittler, 1857:270-279. 19. S...Roli and J. Kittler, Eds. Germany: Springer-Verlag Lecture Notes in Computer Science , #2364: 189-200. J. Ham, Y. Chen, M. Crawford, and J.

  7. 应用生长、分级的自组织映射模型进行意识任务分类%GROWING HIERARCHICAL SELF-ORGANIZING MAP MODELS FOR MENTAL TASK CLASSIFICATION

    Institute of Scientific and Technical Information of China (English)

    刘海龙; 王珏; 郑崇勋

    2005-01-01

    提出一种使用生长、分级的自组织映射(growing hierarchical self-organizing map,GHSOM)模型进行基于EEG信号的意识任务分类来实现脑机接口技术的方法.GHSOM模型是自组织映射(self-organizing map,SOM)的一种变体,由多层的SOM组成,具有一定的分级结构,能够表达数据中不同层次的信息.同时研究了使用平均量化误差(mean quantization error,mqe)和量化误差(quantization error,qe)两种方法实现的GHSOM模型对意识任务分类的作用.结果表明,GHSOM模型对于意识任务的可分性能够提供可视化的信息,并且发现使用量化误差方法实现的GHSOM模型提供较多的数据信息和较高的分类精度.使用GHSOM模型进行了5类意识任务的分类,平均分类精度可达80%.

  8. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

    In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

  9. Incorporating Endmember Variability into Linear Unmixing of Coarse Resolution Imagery: Mapping Large-Scale Impervious Surface Abundance Using a Hierarchically Object-Based Spectral Mixture Analysis

    OpenAIRE

    Chengbin Deng

    2015-01-01

    As an important indicator of anthropogenic impacts on the Earth’s surface, it is of great necessity to accurately map large-scale urbanized areas for various science and policy applications. Although spectral mixture analysis (SMA) can provide spatial distribution and quantitative fractions for better representations of urban areas, this technique is rarely explored with 1-km resolution imagery. This is due mainly to the absence of image endmembers associated with the mixed pixel problem. Con...

  10. Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells.

    Directory of Open Access Journals (Sweden)

    Praveen K Pilly

    Full Text Available Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous

  11. Object-oriented feature extraction approach for mapping supraglacial debris in Schirmacher Oasis using very high-resolution satellite data

    Science.gov (United States)

    Jawak, Shridhar D.; Jadhav, Ajay; Luis, Alvarinho J.

    2016-05-01

    Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80-85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

  12. Mapping the structural and dynamical features of multiple p53 DNA binding domains: insights into loop 1 intrinsic dynamics.

    Directory of Open Access Journals (Sweden)

    Suryani Lukman

    Full Text Available The transcription factor p53 regulates cellular integrity in response to stress. p53 is mutated in more than half of cancerous cells, with a majority of the mutations localized to the DNA binding domain (DBD. In order to map the structural and dynamical features of the DBD, we carried out multiple copy molecular dynamics simulations (totaling 0.8 μs. Simulations show the loop 1 to be the most dynamic element among the DNA-contacting loops (loops 1-3. Loop 1 occupies two major conformational states: extended and recessed; the former but not the latter displays correlations in atomic fluctuations with those of loop 2 (~24 Å apart. Since loop 1 binds to the major groove whereas loop 2 binds to the minor groove of DNA, our results begin to provide some insight into the possible mechanism underpinning the cooperative nature of DBD binding to DNA. We propose (1 a novel mechanism underlying the dynamics of loop 1 and the possible tread-milling of p53 on DNA and (2 possible mutations on loop 1 residues to restore the transcriptional activity of an oncogenic mutation at a distant site.

  13. Visualization of amino acid composition differences between processed protein from different animal species by self-organizing feature maps

    Directory of Open Access Journals (Sweden)

    Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN

    2016-06-01

    Full Text Available Amino acids are the dominant organic components of processed animal proteins, however there has been limited investigation of differences in their composition between various protein sources. Information on these differences will not only be helpful for their further utilization but also provide fundamental information for developing species-specific identification methods. In this study, self-organizing feature maps (SOFM were used to visualize amino acid composition of fish meal, and meat and bone meal (MBM produced from poultry, ruminants and swine. SOFM display the similarities and differences in amino acid composition between protein sources and effectively improve data transparency. Amino acid composition was shown to be useful for distinguishing fish meal from MBM due to their large concentration differences between glycine, lysine and proline. However, the amino acid composition of the three MBMs was quite similar. The SOFM results were consistent with those obtained by analysis of variance and principal component analysis but more straightforward. SOFM was shown to have a robust sample linkage capacity and to be able to act as a powerful means to link different sample for further data mining.

  14. Associative Hierarchical Random Fields.

    Science.gov (United States)

    Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2014-06-01

    This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

  15. An Image Local Feature Representation Method Using Hierarchical Vision Network Model%利用多层视觉网络模型进行图像局部特征表征的方法

    Institute of Scientific and Technical Information of China (English)

    郎波; 黄静; 危辉

    2015-01-01

    为了寻求代价更小、效率更高、适应性更强的图像局部特征表征方法,提出一种基于视觉机制的多层网络计算模型。首先对初级视皮层中的简单细胞和复杂细胞等神经元进行建模;然后对腹侧视通路上的V4区神经元和下颞叶皮层区神经元的响应模式进行研究,并利用该计算模型对输入图像进行局部特征的表征。实验结果表明,与传统的图像特征描述方法相比,该模型所提取的图像局部特征具有足够的区分度;此外,利用生物视觉模型提取出的图像局部特征在具有复杂背景的场景中显示出了更加优秀的泛化能力。%For representing local image features, minor price, more efficient and more flexible, a hierarchical network model based on human vision physiological mechanism was put forward. Firstly, simple cell and com-plex cell in primary visual cortex are modeled, then studied the response pattern of V4 area and inferior temporal cortex on ventral side channel and representing the local features of input image utilized the computational model. The experiment results show that local image features extracted by computational model have sufficient dis-crimination; furthermore, the local image features extracted using biological visual model demonstrated much more excellent generalization ability in natural scene with complicated background.

  16. A high-density SNP-based linkage map of the chicken genome reveals sequence features correlated with recombination rate

    NARCIS (Netherlands)

    Groenen, M.A.M.; Wahlberg, O.; Foglio, M.; Cheng, H.H.; Megens, H.J.W.C.; Crooijmans, R.P.M.A.; Besnier, F.; Lathrop, A.; Muir, W.M.; Wong, G.K.; Gut, I.; Andersson, L.

    2009-01-01

    The resolution of the chicken consensus linkage map has been dramatically improved in this study by genotyping 12,945 single nucleotide polymorphisms (SNPs) on three existing mapping populations in chicken: the Wageningen (WU), East Lansing (EL), and Uppsala (UPP) mapping populations. As many as 859

  17. A Model for Slicing JAVA Programs Hierarchically

    Institute of Scientific and Technical Information of China (English)

    Bi-Xin Li; Xiao-Cong Fan; Jun Pang; Jian-Jun Zhao

    2004-01-01

    Program slicing can be effectively used to debug, test, analyze, understand and maintain objectoriented software. In this paper, a new slicing model is proposed to slice Java programs based on their inherent hierarchical feature. The main idea of hierarchical slicing is to slice programs in a stepwise way, from package level, to class level, method level, and finally up to statement level. The stepwise slicing algorithm and the related graph reachability algorithms are presented, the architecture of the Java program Analyzing Tool (JATO) based on hierarchical slicing model is provided, the applications and a small case study are also discussed.

  18. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  19. Towards an Efficient Hierarchical Codebooks for Content-Based Images Retrieval

    Institute of Scientific and Technical Information of China (English)

    Z.Elleuch; K.Marzouki

    2014-01-01

    In space feature quantization, the most important problem is designing an efficient and compact codebook. The hierarchical clustering approach successfully solves the problem of quantifying the feature space in a large vocabulary size. In this paper we propose to use a tree structure of hierarchical self-organizing-map (H-SOM) with the depth length equal to two and a high size of branch factors (50, 100, 200, 400, and 500). Moreover, an incremental learning process of H-SOM is used to overcome the problem of the curse of the dimensionality of space. The method is evaluated on three public datasets. Results exceed the current state-of-art retrieval performance on Kentucky and Oxford5k dataset. However, it is with less performance on the Holidays dataset. The experiment results indicate that the proposed tree structure shows significant improvement with a large number of branch factors.

  20. Techniques for Revealing 3d Hidden Archeological Features: Morphological Residual Models as Virtual-Polynomial Texture Maps

    Science.gov (United States)

    Pires, H.; Martínez Rubio, J.; Elorza Arana, A.

    2015-02-01

    The recent developments in 3D scanning technologies are not been accompanied by visualization interfaces. We are still using the same types of visual codes as when maps and drawings were made by hand. The available information in 3D scanning data sets is not being fully exploited by current visualization techniques. In this paper we present recent developments regarding the use of 3D scanning data sets for revealing invisible information from archaeological sites. These sites are affected by a common problem, decay processes, such as erosion, that never ceases its action and endangers the persistence of last vestiges of some peoples and cultures. Rock art engravings, or epigraphical inscriptions, are among the most affected by these processes because they are, due to their one nature, carved at the surface of rocks often exposed to climatic agents. The study and interpretation of these motifs and texts is strongly conditioned by the degree of conservation of the imprints left by our ancestors. Every single detail in the remaining carvings can make a huge difference in the conclusions taken by specialists. We have selected two case-studies severely affected by erosion to present the results of the on-going work dedicated to explore in new ways the information contained in 3D scanning data sets. A new method for depicting subtle morphological features in the surface of objects or sites has been developed. It allows to contrast human patterns still present at the surface but invisible to naked eye or by any other archaeological inspection technique. It was called Morphological Residual Model (MRM) because of its ability to contrast the shallowest morphological details, to which we refer as residuals, contained in the wider forms of the backdrop. Afterwards, we have simulated the process of building Polynomial Texture Maps - a widespread technique that as been contributing to archaeological studies for some years - in a 3D virtual environment using the results of MRM

  1. Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters

    Directory of Open Access Journals (Sweden)

    Muhammad Shahzad Sarfraz

    2014-12-01

    Full Text Available The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.

  2. Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters.

    Science.gov (United States)

    Sarfraz, Muhammad Shahzad; Tripathi, Nagesh K; Faruque, Fazlay S; Bajwa, Usama Ijaz; Kitamoto, Asanobu; Souris, Marc

    2014-12-01

    The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.

  3. DeepMap+: Recognizing High-Level Indoor Semantics Using Virtual Features and Samples Based on a Multi-Length Window Framework.

    Science.gov (United States)

    Zhang, Wei; Zhou, Siwang

    2017-05-26

    Existing indoor semantic recognition schemes are mostly capable of discovering patterns through smartphone sensing, but it is hard to recognize rich enough high-level indoor semantics for map enhancement. In this work we present DeepMap+, an automatical inference system for recognizing high-level indoor semantics using complex human activities with wrist-worn sensing. DeepMap+ is the first deep computation system using deep learning (DL) based on a multi-length window framework to enrich the data source. Furthermore, we propose novel methods of increasing virtual features and virtual samples for DeepMap+ to better discover hidden patterns of complex hand gestures. We have performed 23 high-level indoor semantics (including public facilities and functional zones) and collected wrist-worn data at a Wal-Mart supermarket. The experimental results show that our proposed methods can effectively improve the classification accuracy.

  4. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  5. Spatial features of dose-surface maps from deformably-registered plans correlate with late gastrointestinal complications

    Science.gov (United States)

    Moulton, Calyn R.; House, Michael J.; Lye, Victoria; Tang, Colin I.; Krawiec, Michele; Joseph, David J.; Denham, James W.; Ebert, Martin A.

    2017-05-01

    This study investigates the associations between spatial distribution of dose to the rectal surface and observed gastrointestinal toxicities after deformably registering each phase of a combined external beam radiotherapy (EBRT)/high-dose-rate brachytherapy (HDRBT) prostate cancer treatment. The study contains data for 118 patients where the HDRBT CT was deformably-registered to the EBRT CT. The EBRT and registered HDRBT TG43 dose distributions in a reference 2 Gy/fraction were 3D-summed. Rectum dose-surface maps (DSMs) were obtained by virtually unfolding the rectum surface slice-by-slice. Associations with late peak gastrointestinal toxicities were investigated using voxel-wise DSM analysis as well as parameterised spatial patterns. The latter were obtained by thresholding DSMs from 1-80 Gy (increment  =  1) and extracting inferior-superior extent, left-right extent, area, perimeter, compactness, circularity and ellipse fit parameters. Logistic regressions and Mann-Whitney U-tests were used to correlate features with toxicities. Rectal bleeding, stool frequency, diarrhoea and urgency/tenesmus were associated with greater lateral and/or longitudinal spread of the high doses near the anterior rectal surface. Rectal bleeding and stool frequency were also influenced by greater low-intermediate doses to the most inferior 20% of the rectum and greater low-intermediate-high doses to 40-80% of the rectum length respectively. Greater low-intermediate doses to the superior 20% and inferior 20% of the rectum length were associated with anorectal pain and urgency/tenesmus respectively. Diarrhoea, completeness of evacuation and proctitis were also related to greater low doses to the posterior side of the rectum. Spatial features for the intermediate-high dose regions such as area, perimeter, compactness, circularity, ellipse eccentricity and confinement to ellipse fits were strongly associated with toxicities other than anorectal pain. Consequently, toxicity is

  6. System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

    Science.gov (United States)

    Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

    2014-06-17

    A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

  7. A hierarchical framework of aquatic ecological units in North America (Nearctic Zone).

    Science.gov (United States)

    James R. Maxwell; Clayton J. Edwards; Mark E. Jensen; Steven J. Paustian; Harry Parrott; Donley M. Hill

    1995-01-01

    Proposes a framework for classifying and mapping aquatic systems at various scales using ecologically significant physical and biological criteria. Classification and mapping concepts follow tenets of hierarchical theory, pattern recognition, and driving variables. Criteria are provided for the hierarchical classification and mapping of aquatic ecological units of...

  8. Hierarchical Linear Models for Energy Prediction using Inertial Sensors: A Comparative Study for Treadmill Walking.

    Science.gov (United States)

    Vathsangam, Harshvardhan; Emken, B Adar; Schroeder, E Todd; Spruijt-Metz, Donna; Sukhatme, Gaurav S

    2013-12-01

    Walking is a commonly available activity to maintain a healthy lifestyle. Accurately tracking and measuring calories expended during walking can improve user feedback and intervention measures. Inertial sensors are a promising measurement tool to achieve this purpose. An important aspect in mapping inertial sensor data to energy expenditure is the question of normalizing across physiological parameters. Common approaches such as weight scaling require validation for each new population. An alternative is to use a hierarchical approach to model subject-specific parameters at one level and cross-subject parameters connected by physiological variables at a higher level. In this paper, we evaluate an inertial sensor-based hierarchical model to measure energy expenditure across a target population. We first determine the optimal movement and physiological features set to represent data. Periodicity based features are more accurate (phierarchical model with a subject-specific regression model and weight exponent scaled models. Subject-specific models perform significantly better (pmodels at all exponent scales whereas the hierarchical model performed worse than both. However, using an informed prior from the hierarchical model produces similar errors to using a subject-specific model with large amounts of training data (phierarchical modeling is a promising technique for generalized prediction energy expenditure prediction across a target population in a clinical setting.

  9. Topology-based hierarchical scheduling using deficit round robin

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    This paper proposes a topology-based hierarchical scheduling scheme using Deficit Round Robin (DRR). The main idea of the topology-based hierarchical scheduling is to map the topology of the connected network into the logical structure of the scheduler, and combine several token schedulers...

  10. Texture mapping for feature based on points constraint%基于特征点约束的人脸纹理映射

    Institute of Scientific and Technical Information of China (English)

    王法强; 耿国华; 李康; 贺毅岳

    2012-01-01

    Texture mapping for feature is a very special technology of realistic processing in computer-aided craniofacial rehabilitation. To realize the texture mapping for local organs of 3D human face accurately, this paper introduced a texture mapping method for feature based on points constraint. It used least squares conformal maps to realize this constraint. Using front photos for actual texture mapping proved that the method was effective. The experiment results show that this method is robust and efficient, and reduced the complexity of the algorithm.%人脸纹理映射技术是计算机辅助颅骨面貌复原中一种特殊的真实感处理技术.针对人脸面部器官纹理映射难以准确实现的问题,提出一种基于特征点约束的人脸纹理映射方法.利用最小二乘保角映射参数化时需固定顶点来完成特征点约束.通过对大量单张、正面照片作为纹理进行映射,证实了该方法能够取得良好的映射效果.实验结果表明本方法鲁棒且效率高,降低了算法的复杂性.

  11. Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

    Science.gov (United States)

    Singha, Mrinal; Wu, Bingfang; Zhang, Miao

    2016-12-22

    Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

  12. SIFT Feature Detection and Matching Based on Salient Map%基于显著图的SIFT特征检测与匹配

    Institute of Scientific and Technical Information of China (English)

    尹春霞; 徐德; 李成荣; 罗杨宇

    2012-01-01

    基于尺度不变特征变换(SIFT)特征的图像匹配存在特征点数量大、运算时间长等问题.为此,引入视觉注意机制,提出一种基于显著图的SIFT特征检测与匹配方法.比较常用的显著图计算模型,选择谱残差方法提取图片的显著图.对显著图进行二值化和形态学等处理,得到规则合理的显著区域.在显著区域内提取SIFT特征,生成特征向量,进行图像匹配.实验结果表明,该方法能提高运算效率,并且得到的SIFT特征更加稳定.%Image matching based on Scale Invariant Feature Transform(SIFT) feature is time-consuming, and there are always a large number of feature points. By introducing salient map into feature extraction and image matching, a new SIFT feature detection and matching method is put forward. Salient computing models are compared, and an efficient spectral residual method is selected to compute the salient map. Then the salient map is processed with binarization and morphology to get regular salient area. SIFT features are detected and matched just in the salient area instead of in the whole image. Experimental results show that the proposed method is much faster and the features in salient area are more stable.

  13. Deep subspace mapping in hyperspectral imaging

    Science.gov (United States)

    Wadströmer, Niclas; Gustafsson, David; Perersson, Henrik; Bergström, David

    2016-10-01

    We propose a novel Deep learning approach using autoencoders to map spectral bands to a space of lower dimensionality while preserving the information that makes it possible to discriminate different materials. Deep learning is a relatively new pattern recognition approach which has given promising result in many applications. In Deep learning a hierarchical representation of increasing level of abstraction of the features is learned. Autoencoder is an important unsupervised technique frequently used in Deep learning for extracting important properties of the data. The learned latent representation is a non-linear mapping of the original data which potentially preserve the discrimination capacity.

  14. Unsupervised feature selection and general pattern discovery using Self-Organizing Maps for gaining insights into the nature of seismic wavefields

    Science.gov (United States)

    Köhler, Andreas; Ohrnberger, Matthias; Scherbaum, Frank

    2009-09-01

    This study presents an unsupervised feature selection and learning approach for the discovery and intuitive imaging of significant temporal patterns in seismic single-station or network recordings. For this purpose, the data are parametrized by real-valued feature vectors for short time windows using standard analysis tools for seismic data, such as frequency-wavenumber, polarization, and spectral analysis. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure, which is in particular suitable for high-dimensional data sets. Our feature selection method is based on significance testing using the Wald-Wolfowitz runs test for individual features and on correlation hunting with SOMs in feature subsets. Using synthetics composed of Rayleigh and Love waves and real-world data, we show the robustness and the improved discriminative power of that approach compared to feature subsets manually selected from individual wavefield parametrization methods. Furthermore, the capability of the clustering and visualization techniques to investigate the discrimination of wave phases is shown by means of synthetic waveforms and regional earthquake recordings.

  15. Integration of remote sensing and aeromagnetic data for mapping structural features and hydrothermal alteration zones in Wadi Allaqi area, South Eastern Desert of Egypt

    Science.gov (United States)

    Eldosouky, Ahmed M.; Abdelkareem, Mohamed; Elkhateeb, Sayed O.

    2017-06-01

    Remote sensing and aeromagnetic data provided significant information for detecting potential areas of mineralization in Wadi Allaqi in the South Eastern Desert of Egypt. Application of band ratios and Crosta technique of Principal Component Analysis (PCA) using Landsat-8 successfully highlighted the hydrothermal alteration zones and the structural elements represented by lithologic contacts and faults/fracture zones. Structural lineaments were also successfully extracted using remote sensing and aeromagnetic data. Center for Exploration Targeting (CET) Grid analysis and CET Porphyry Analysis techniques were applied for constructing the structural complexity heat map and probable near circular features of porphyry intrusions respectively. Combining data of lineaments, alteration zones and porphyry intrusions after obtaining a consequence of each map allowed predicting and mapping areas of probable high mineral resources. Overlaying the present sites of mineralization on the final map validated the prepared mineral predictive map. Overall results clearly revealed that areas of high structural complexity, fractures/faults density are in agreement with the detected areas of hydrothermal alterations which also matched with the known mineralization mines in the study area.

  16. Study of Noise Map and its Features in an Indoor Work Environment through GIS-Based Software

    Directory of Open Access Journals (Sweden)

    Faramarz Majidi

    2016-06-01

    Full Text Available Background: Noise mapping in industry can be useful to assess the risks of harmful noise, or to monitor noise in machine rooms. Using GIS -based software for plotting noise maps in an indoor noisy work environment can be helpful for occupational hygienists to monitor noise pollution. Methods: This study was carried out in a noisy packaging unit of a food industry in Ghazvin industrial zone, to evaluate noise levels by GIS technique. For this reason the floor of packaging unit was divided into squares of 2×2 meters and the center of each square was marked as a measurement station based on NIOSH method. The sound pressure level in each station was measured and then the measurement values were imported into Arc GIS software to plot noise map. Results: Unlike the current method, the noise maps generated by GIS technique are consistent with the nature of sound propagation. Conclusion: This study showed that for an indoor work environment, the application of GIS technology rendering the assessment of noise levels in the form of noise maps, is more realistic and more accurate than the routine method which is now being used by the occupational hygienists.

  17. Useful clinical features for the selection of ideal patients with strial fibrillation for mapping and catheter ablation

    Directory of Open Access Journals (Sweden)

    Mehta Niraj

    2002-01-01

    Full Text Available OBJECTIVE: To identify useful clinical characteristics for selecting patients eligible for mapping and ablation of atrial fibrillation. METHODS: We studied 9 patients with atrial fibrillation, without structural heart disease, associated with: 1 antiarrhythmic drugs, 2 symptoms of low cardiac output, and 3 intention to treat. Seven patients had paroxysmal atrial fibrillation and 2 had recurrent atrial fibrillation. RESULTS: In the 6 patients who underwent mapping (all had paroxysmal atrial fibrillation, catheter ablation was successfully carried out in superior pulmonary veins in 5 patients (the first 3 in the left superior pulmonary vein and the last 2 in the right superior pulmonary vein. One patient experienced a recurrence of atrial fibrillation after 10 days. We observed that patients who had short episodes of atrial fibrillation on 24-hour Holter monitoring before the procedure were those in whom mapping the focus of tachycardia was possible. Tachycardia was successfully suppressed in 4 of 6 patients. The cause of failure was due to the impossibility of maintaining sinus rhythm long enough for efficient mapping. CONCLUSION: Patients experiencing short episodes of atrial fibrillation during 24-hour Holter monitoring were the most eligible for mapping and ablation, with a final success rate of 66%, versus the global success rate of 44%. Patients with persistent atrial fibrillation were not good candidates for focal ablation.

  18. Using side-scan sonar to characterize and map physical habitat and anthropogenic underwater features in the St. Louis River.

    Science.gov (United States)

    Characterizing underwater habitat and other features is difficult and costly, especially in the large St. Louis River Estuary. We are using side-scan sonar (SSS), first developed in the 1960s to remotely sense underwater habitat features from reflected acoustic signals (backscatt...

  19. Universal hierarchical behavior of citation networks

    CERN Document Server

    Mones, Enys; Vicsek, Tamás

    2014-01-01

    Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or in other words, edges describe the impact of papers on other publications. This inherent meaning of the edges infers that citation networks can exhibit hierarchical features, that is typical of networks based on decision-making. In this paper, we investigate the hierarchical structure of citation networks consisting of papers in the same field. We find that the majority of the networks follow a universal trend towards a highly hierarchical state, and i) the various fields display differences only concerning their phase in life (distance from the "birth" of a field) or ii) the characteristic time according to which they are approaching the stationary state. We also show by a simple argument that the alterations in the behavior are related to and can be understood by the degree of specializatio...

  20. [A medical image semantic modeling based on hierarchical Bayesian networks].

    Science.gov (United States)

    Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu

    2009-04-01

    A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.

  1. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  2. Evaluating Hierarchical Structure in Music Annotations

    Directory of Open Access Journals (Sweden)

    Brian McFee

    2017-08-01

    Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  3. Feature-expression heat maps - A new visual method to explore complex associations between two variable sets

    NARCIS (Netherlands)

    Haarman, Bartholomeus C. M. (Benno); Riemersma-Van der Lek, Rixt F.; Nolen, Willem A.; Mendes, R.; Drexhage, Hemmo A.; Burger, Huibert

    2015-01-01

    Introduction: Existing methods such as correlation plots and cluster heat maps are insufficient in the visual exploration of multiple associations between genetics and phenotype, which is of importance to achieve a better understanding of the pathophysiology of psychiatric and other illnesses. The i

  4. Central auditory processing during chronic tinnitus as indexed by topographical maps of the mismatch negativity obtained with the multi-feature paradigm.

    Science.gov (United States)

    Mahmoudian, Saeid; Farhadi, Mohammad; Najafi-Koopaie, Mojtaba; Darestani-Farahani, Ehsan; Mohebbi, Mehrnaz; Dengler, Reinhard; Esser, Karl-Heinz; Sadjedi, Hamed; Salamat, Behrouz; Danesh, Ali A; Lenarz, Thomas

    2013-08-21

    This study aimed to compare the neural correlates of acoustic stimulus representation in the auditory sensory memory on an automatic basis between tinnitus subjects and normal hearing (NH) controls, using topographical maps of the MMNs obtained with the multi-feature paradigm. A new and faster paradigm was adopted to look for differences between 2 groups of subjects. Twenty-eight subjects with chronic subjective idiopathic tinnitus and 33 matched healthy controls were included in the study. Brain electrical activity mapping of multi-feature MMN paradigm was recorded from 32 surface scalp electrodes. Three MMN parameters for five deviants consisting frequency, intensity, duration, location and silent gap were compared between the two groups. The MMN amplitude, latency and area under the curve over a region of interest comprising: F3, F4, Fz, FC3, FC4, FCz, and Cz were computed to provide better signal to noise ratio. These three measures could differentiate the cognitive processing disturbances in tinnitus sufferers. The MMN topographic maps revealed significant differences in amplitude and area under the curve for frequency, duration and silent gap deviants in tinnitus subjects compared to NH controls. The current study provides electrophysiological evidence supporting the theory that the pre-attentive and automatic central auditory processing is impaired in individuals with chronic tinnitus. Considering the advantages offered by the MMN paradigm used here, these data might be a useful reference point for the assessment of sensory memory in tinnitus patients and it can be applied with reliability and success in treatment monitoring.

  5. Equivalence Checking of Hierarchical Combinational Circuits

    DEFF Research Database (Denmark)

    Williams, Poul Frederick; Hulgaard, Henrik; Andersen, Henrik Reif

    1999-01-01

    This paper presents a method for verifying that two hierarchical combinational circuits implement the same Boolean functions. The key new feature of the method is its ability to exploit the modularity of circuits to reuse results obtained from one part of the circuits in other parts. We demonstrate...... our method on large adder and multiplier circuits....

  6. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  7. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

    2015-02-11

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  8. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  9. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

    2015-02-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  10. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  11. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  12. Optimization of mathematical models for thematic maps

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The thematic map is a major class of maps designed to demonstrate particular features or concepts,functioning as an indispensable tool in geographical research.The process of thematic mapping is one into which geographical research goes deeply and broadly.The key activity and course of thematic map production is the use of mathematical models to create thematic data layers.Therefore,the selection and optimization of mathematical models is in the forefront of thematic map research.The theoretical foundations,mechanisms and methods of mathematical model optimization are expounded in this paper,including two approaches,the phase by phase mode and the multi-aim scheme balance mode.Case studies in eco-environment mapping and emergency mapping are described and analyzed,with a hierarchical analysis method being used in the model optimization for eco-environment fragility and sensitivity assessment mapping in Beibuwan (Guangxi) District,the dynamic system (DS) method being used in the model optimization for ecological security adjustment mapping in Xishuang Banna,Yunnan province,and the multi-phase mode being used in the models for forest fire and infectious diseases mapping.

  13. Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

    Science.gov (United States)

    Naghibi, Seyed Amir; Moradi Dashtpagerdi, Mostafa

    2016-09-01

    One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.

  14. Clavulanic acid production estimation based on color and structural features of Streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm.

    Science.gov (United States)

    Nurmohamadi, Maryam; Pourghassem, Hossein

    2014-05-01

    The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorithm based on visual and structural features of SC bacteria instead of statistical methods and experimental evaluation by microbiologist is proposed. In this algorithm, structural features such as the number of newborn branches, thickness of hyphal and bacterial density and also color features such as acceptance color levels are extracted from the SC bacteria. Moreover, PH and biomass of the medium provided by microbiologists are considered as specified features. The level of CA production is estimated by using a new application of Self-Organizing Map (SOM), and a hybrid model of genetic algorithm with back propagation network (GA-BPN). The proposed algorithm is evaluated on four carbonic resources including malt, starch, wheat flour and glycerol that had used as different mediums of bacterial growth. Then, the obtained results are compared and evaluated with observation of specialist. Finally, the Relative Error (RE) for the SOM and GA-BPN are achieved 14.97% and 16.63%, respectively.

  15. A hierarchical model of the evolution of human brain specializations.

    Science.gov (United States)

    Barrett, H Clark

    2012-06-26

    The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domain-specific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised.

  16. Large-scale mapping of submarine geohazard-related features: example from the Italian Project MAGIC (Marine Geohazards along the Italian Coasts)

    Science.gov (United States)

    Ridente, Domenico; Bosman, Alessandro; Casalbore, Daniele; Sposato, Andrea; Chiocci, Francesco L.

    2010-05-01

    In very recent times, the impact of catastrophic tsunami at global (Indonesia, 2004) and local scale (Stromboli, 2002) has made evident the necessity of knowing the worldwide distribution of submarine geological structures responsible for their generation, with particular reference to seismogenic faults, volcanic activity, submarine and coastal landslides. More in general, marine geohazard derives from a vast variety of geological processes owing to the recent/modern seafloor morpho-dynamics, in the framework of the long-term tectono-sedimentary evolution of continental margins. The capability to identify and characterize marine geohazards significantly improved because of the recent developments in seafloor imaging and mapping techniques. As a consequence, many research projects specifically designed for defining marine geohazard relative to human activity and infrastructures can be conceived based on extensive (regional-scale) seafloor mapping. In this view, the Italian Civil Protection Department promoted the national project MAGIC (Marine Geohazards along the Italian Coasts), aimed at acquiring multibeam morpho-bathymetry along the most geologically active margins of Italy; the acquired dataset will then be the basis for interpreting geomorphic features and identifying potential geohazard. Marine geohazards, and their related potential risk have to be defined at different scales and level of detail and accuracy. As a starting point, geohazard mapping relies on the reconnaissance of the geohazard-related geological features, and is essentially regarded as the detection of their presence/absence and state of activity/non-activity; this reconnaissance issues is achieved through the interpretation of the morpho-tectonic and sedimentary dynamics shaping continental margins at diverse temporal and spatial scales. We discuss some general aspects of geohazard reconnaissance and cartographic criteria relative to regional scale multibeam mapping, based on the experience

  17. Onboard hierarchical network

    Science.gov (United States)

    Tunesi, Luca; Armbruster, Philippe

    2004-02-01

    The objective of this paper is to demonstrate a suitable hierarchical networking solution to improve capabilities and performances of space systems, with significant recurrent costs saving and more efficient design & manufacturing flows. Classically, a satellite can be split in two functional sub-systems: the platform and the payload complement. The platform is in charge of providing power, attitude & orbit control and up/down-link services, whereas the payload represents the scientific and/or operational instruments/transponders and embodies the objectives of the mission. One major possibility to improve the performance of payloads, by limiting the data return to pertinent information, is to process data on board thanks to a proper implementation of the payload data system. In this way, it is possible to share non-recurring development costs by exploiting a system that can be adopted by the majority of space missions. It is believed that the Modular and Scalable Payload Data System, under development by ESA, provides a suitable solution to fulfil a large range of future mission requirements. The backbone of the system is the standardised high data rate SpaceWire network http://www.ecss.nl/. As complement, a lower speed command and control bus connecting peripherals is required. For instance, at instrument level, there is a need for a "local" low complexity bus, which gives the possibility to command and control sensors and actuators. Moreover, most of the connections at sub-system level are related to discrete signals management or simple telemetry acquisitions, which can easily and efficiently be handled by a local bus. An on-board hierarchical network can therefore be defined by interconnecting high-speed links and local buses. Additionally, it is worth stressing another important aspect of the design process: Agencies and ESA in particular are frequently confronted with a big consortium of geographically spread companies located in different countries, each one

  18. Music Emotion Detection Using Hierarchical Sparse Kernel Machines

    OpenAIRE

    Yu-Hao Chin; Chang-Hong Lin; Ernestasia Siahaan; Jia-Ching Wang

    2014-01-01

    For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-l...

  19. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

    Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

  20. High temperature conductance mapping for correlation of electrical properties with micron-sized chemical and microstructural features

    DEFF Research Database (Denmark)

    Hansen, Karin Vels; Norrman, Kion; Jacobsen, Torben

    2016-01-01

    High temperature AC conductance mapping is a scanning probe technique for resolving local electrical properties in microscopic areas. It is especially suited for detecting poorly conducting phases and for ionically conducting materials such as those used in solid oxide electrochemical cells....... Secondary silicate phases formed at the edge of lanthanum strontium manganite microelectrodes are used as an example for correlation of chemical, microstructural and electrical properties with a spatial resolution of 1–2 µm to demonstrate the technique. The measurements are performed in situ in a controlled...

  1. Improving broadcast channel rate using hierarchical modulation

    CERN Document Server

    Meric, Hugo; Arnal, Fabrice; Lesthievent, Guy; Boucheret, Marie-Laure

    2011-01-01

    We investigate the design of a broadcast system where the aim is to maximise the throughput. This task is usually challenging due to the channel variability. Forty years ago, Cover introduced and compared two schemes: time sharing and superposition coding. The second scheme was proved to be optimal for some channels. Modern satellite communications systems such as DVB-SH and DVB-S2 mainly rely on time sharing strategy to optimize throughput. They consider hierarchical modulation, a practical implementation of superposition coding, but only for unequal error protection or backward compatibility purposes. We propose in this article to combine time sharing and hierarchical modulation together and show how this scheme can improve the performance in terms of available rate. We present the gain on a simple channel modeling the broadcasting area of a satellite. Our work is applied to the DVB-SH standard, which considers hierarchical modulation as an optional feature.

  2. Self-organizing maps: A tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence

    Indian Academy of Sciences (India)

    D V Raje; H J Purohit; Y P Badhe; S S Tambe; B D Kulkarni

    2010-12-01

    Exploitation of microbial wealth, of which almost 95% or more is still unexplored, is a growing need. The taxonomic placements of a new isolate based on phenotypic characteristics are now being supported by information preserved in the 16S rRNA gene. However, the analysis of 16S rDNA sequences retrieved from metagenome, by the available bioinformatics tools, is subject to limitations. In this study, the occurrences of nucleotide features in 16S rDNA sequences have been used to ascertain the taxonomic placement of organisms. The tetra- and penta-nucleotide features were extracted from the training data set of the 16S rDNA sequence, and was subjected to an artificial neural network (ANN) based tool known as self-organizing map (SOM), which helped in visualization of unsupervised classification. For selection of significant features, principal component analysis (PCA) or curvilinear component analysis (CCA) was applied. The SOM along with these techniques could discriminate the sample sequences with more than 90% accuracy, highlighting the relevance of features. To ascertain the confidence level in the developed classification approach, the test data set was specifically evaluated for Thiobacillus, with Acidiphilium, Paracocus and Starkeya, which are taxonomically reassigned. The evaluation proved the excellent generalization capability of the developed tool. The topology of genera in SOM supported the conventional chemo-biochemical classification reported in the Bergey manual.

  3. Self-organizing maps: a tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence.

    Science.gov (United States)

    Raje, D V; Purohit, H J; Badhe, Y P; Tambe, S S; Kulkarni, B D

    2010-12-01

    Exploitation of microbial wealth, of which almost 95% or more is still unexplored, is a growing need. The taxonomic placements of a new isolate based on phenotypic characteristics are now being supported by information preserved in the 16S rRNA gene. However, the analysis of 16S rDNA sequences retrieved from metagenome, by the available bioinformatics tools, is subject to limitations. In this study, the occurrences of nucleotide features in 16S rDNA sequences have been used to ascertain the taxonomic placement of organisms. The tetra- and penta-nucleotide features were extracted from the training data set of the 16S rDNA sequence, and was subjected to an artificial neural network (ANN) based tool known as self-organizing map (SOM), which helped in visualization of unsupervised classification. For selection of significant features, principal component analysis (PCA) or curvilinear component analysis (CCA) was applied. The SOM along with these techniques could discriminate the sample sequences with more than 90% accuracy, highlighting the relevance of features. To ascertain the confidence level in the developed classification approach, the test data set was specifically evaluated for Thiobacillus, with Acidiphilium, Paracocus and Starkeya, which are taxonomically reassigned. The evaluation proved the excellent generalization capability of the developed tool. The topology of genera in SOM supported the conventional chemo-biochemical classification reported in the Bergey manual.

  4. Hierarchical linear regression models for conditional quantiles

    Institute of Scientific and Technical Information of China (English)

    TIAN Maozai; CHEN Gemai

    2006-01-01

    The quantile regression has several useful features and therefore is gradually developing into a comprehensive approach to the statistical analysis of linear and nonlinear response models,but it cannot deal effectively with the data with a hierarchical structure.In practice,the existence of such data hierarchies is neither accidental nor ignorable,it is a common phenomenon.To ignore this hierarchical data structure risks overlooking the importance of group effects,and may also render many of the traditional statistical analysis techniques used for studying data relationships invalid.On the other hand,the hierarchical models take a hierarchical data structure into account and have also many applications in statistics,ranging from overdispersion to constructing min-max estimators.However,the hierarchical models are virtually the mean regression,therefore,they cannot be used to characterize the entire conditional distribution of a dependent variable given high-dimensional covariates.Furthermore,the estimated coefficient vector (marginal effects)is sensitive to an outlier observation on the dependent variable.In this article,a new approach,which is based on the Gauss-Seidel iteration and taking a full advantage of the quantile regression and hierarchical models,is developed.On the theoretical front,we also consider the asymptotic properties of the new method,obtaining the simple conditions for an n1/2-convergence and an asymptotic normality.We also illustrate the use of the technique with the real educational data which is hierarchical and how the results can be explained.

  5. Retention of features on a mapped Drosophila brain surface using a Bézier-tube-based surface model averaging technique.

    Science.gov (United States)

    Chen, Guan-Yu; Wu, Cheng-Chi; Shao, Hao-Chiang; Chang, Hsiu-Ming; Chiang, Ann-Shyn; Chen, Yung-Chang

    2012-12-01

    Model averaging is a widely used technique in biomedical applications. Two established model averaging methods, iterative shape averaging (ISA) method and virtual insect brain (VIB) method, have been applied to several organisms to generate average representations of their brain surfaces. However, without sufficient samples, some features of the average Drosophila brain surface obtained using the above methods may disappear or become distorted. To overcome this problem, we propose a Bézier-tube-based surface model averaging strategy. The proposed method first compensates for disparities in position, orientation, and dimension of input surfaces, and then evaluates the average surface by performing shape-based interpolation. Structural features with larger individual disparities are simplified with half-ellipse-shaped Bézier tubes, and are unified according to these tubes to avoid distortion during the averaging process. Experimental results show that the average model yielded by our method could preserve fine features and avoid structural distortions even if only a limit amount of input samples are used. Finally, we qualitatively compare our results with those obtained by ISA and VIB methods by measuring the surface-to-surface distances between input surfaces and the averaged ones. The comparisons show that the proposed method could generate a more representative average surface than both ISA and VIB methods.

  6. Typha latifolia (broadleaf cattail) as bioindicator of different types of pollution in aquatic ecosystems-application of self-organizing feature map (neural network).

    Science.gov (United States)

    Klink, Agnieszka; Polechońska, Ludmiła; Cegłowska, Aurelia; Stankiewicz, Andrzej

    2016-07-01

    The contents of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in leaves of Typha latifolia (broadleaf cattail), water and bottom sediment from 72 study sites designated in different regions of Poland were determined using atomic absorption spectrometry. The aim of the study was to evaluate potential use of T. latifolia in biomonitoring of trace metal pollution. The self-organizing feature map (SOFM) identifying groups of sampling sites with similar concentrations of metals in cattail leaves was able to classify study sites according to similar use and potential sources of pollution. Maps prepared for water and bottom sediment showed corresponding groups of sampling sites which suggested similarity of samples features. High concentrations of Fe, Cd, Cu, and Ni were characteristic for industrial areas. Elevated Pb concentrations were noted in regions with intensive vehicle traffic, while high Mn and Zn contents were reported in leaves from the agricultural area. Manganese content in leaves of T. latifolia was high irrespectively of the concentrations in bottom sediments and water so cattail can be considered the leaf accumulator of Mn. Once trained, SOFMs can be applied in ecological investigations and could form a future basis for recognizing the type of pollution in aquatic environments by analyzing the concentrations of elements in T. latifolia.

  7. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  8. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  9. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  10. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  11. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations.

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C; Zhou, Changsong

    2011-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  12. Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

    Science.gov (United States)

    Higuera, Clara; Gardiner, Katheleen J.; Cios, Krzysztof J.

    2015-01-01

    Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets. PMID:26111164

  13. Persistent small-scale features in maps of the anisotropy of ocean surface velocities--implications for mixing?

    Science.gov (United States)

    Sen, A.; Arbic, B. K.; Scott, R. B.; Holland, C. L.; Logan, E.; Qiu, B.

    2006-12-01

    Much of the stirring and mixing in the upper ocean is due to geostrophically balanced mesoscale eddies. Ocean general circulation models commonly parameterize eddy effects. Geostrophic turbulence models show that parameterizations of eddy mixing depend on the isotropy of the eddies. Motivated by this, we investigate the isotropy of oceanic mesoscale eddies with seven years of sea surface height data recorded by satellite altimeters. From these data, we determined a sea surface height anomaly, and surface geostrophic velocities u and v in the zonal (east-west) and meridional (north-south) directions, respectively. From the latter two quantities we can calculate zonal and meridional kinetic energies u2 and v2. Integrals of u2 and v2 around latitude bands 10 degrees wide are nearly equal, in contrast with the results of simple beta-plane geostrophic turbulence models, which suggest that zonal motions should predominate. Maps of the quantity u2-v2 (normalized by standard error) show fine-scale structures that persist over times longer than the lifespan of a turbulent eddy. Thus the mesoscale eddy field is locally anisotropic almost everywhere. Further investigation into the causes of these small-scale structures is needed and is currently underway.

  14. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  15. Salient Region Detection via Feature Combination and Discriminative Classifier

    Directory of Open Access Journals (Sweden)

    Deming Kong

    2015-01-01

    Full Text Available We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.

  16. Object tracking with hierarchical multiview learning

    Science.gov (United States)

    Yang, Jun; Zhang, Shunli; Zhang, Li

    2016-09-01

    Building a robust appearance model is useful to improve tracking performance. We propose a hierarchical multiview learning framework to construct the appearance model, which has two layers for tracking. On the top layer, two different views of features, grayscale value and histogram of oriented gradients, are adopted for representation under the cotraining framework. On the bottom layer, for each view of each feature, three different random subspaces are generated to represent the appearance from multiple views. For each random view submodel, the least squares support vector machine is employed to improve the discriminability for concrete and efficient realization. These two layers are combined to construct the final appearance model for tracking. The proposed hierarchical model assembles two types of multiview learning strategies, in which the appearance can be described more accurately and robustly. Experimental results in the benchmark dataset demonstrate that the proposed method can achieve better performance than many existing state-of-the-art algorithms.

  17. Comparison of Different Machine Learning Algorithms for Lithological Mapping Using Remote Sensing Data and Morphological Features: A Case Study in Kurdistan Region, NE Iraq

    Science.gov (United States)

    Othman, Arsalan; Gloaguen, Richard

    2015-04-01

    Topographic effects and complex vegetation cover hinder lithology classification in mountain regions based not only in field, but also in reflectance remote sensing data. The area of interest "Bardi-Zard" is located in the NE of Iraq. It is part of the Zagros orogenic belt, where seven lithological units outcrop and is known for its chromite deposit. The aim of this study is to compare three machine learning algorithms (MLAs): Maximum Likelihood (ML), Support Vector Machines (SVM), and Random Forest (RF) in the context of a supervised lithology classification task using Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite, its derived, spatial information (spatial coordinates) and geomorphic data. We emphasize the enhancement in remote sensing lithological mapping accuracy that arises from the integration of geomorphic features and spatial information (spatial coordinates) in classifications. This study identifies that RF is better than ML and SVM algorithms in almost the sixteen combination datasets, which were tested. The overall accuracy of the best dataset combination with the RF map for the all seven classes reach ~80% and the producer and user's accuracies are ~73.91% and 76.09% respectively while the kappa coefficient is ~0.76. TPI is more effective with SVM algorithm than an RF algorithm. This paper demonstrates that adding geomorphic indices such as TPI and spatial information in the dataset increases the lithological classification accuracy.

  18. Self-organizing feature map (neural networks) as a tool to select the best indicator of road traffic pollution (soil, leaves or bark of Robinia pseudoacacia L.)

    Energy Technology Data Exchange (ETDEWEB)

    Samecka-Cymerman, A., E-mail: sameckaa@biol.uni.wroc.p [Department of Ecology, Biogeochemistry and Environmental Protection, Wroclaw University, ul. Kanonia 6/8, 50-328 Wroclaw (Poland); Stankiewicz, A.; Kolon, K. [Department of Ecology, Biogeochemistry and Environmental Protection, Wroclaw University, ul. Kanonia 6/8, 50-328 Wroclaw (Poland); Kempers, A.J. [Department of Environmental Sciences, Radboud University of Nijmegen, Toernooiveld, 6525 ED Nijmegen (Netherlands)

    2009-07-15

    Concentrations of the elements Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were measured in the leaves and bark of Robinia pseudoacacia and the soil in which it grew, in the town of Olesnica (SW Poland) and at a control site. We selected this town because emission from motor vehicles is practically the only source of air pollution, and it seemed interesting to evaluate its influence on soil and plants. The self-organizing feature map (SOFM) yielded distinct groups of soils and R. pseudoacacia leaves and bark, depending on traffic intensity. Only the map classifying bark samples identified an additional group of highly polluted sites along the main highway from Wroclaw to Warszawa. The bark of R. pseudoacacia seems to be a better bioindicator of long-term cumulative traffic pollution in the investigated area, while leaves are good indicators of short-term seasonal accumulation trends. - Once trained, SOFM could be used in the future to recognize types of pollution.

  19. NOAA's Shoreline Survey Maps - Raster NOAA-NOS Shoreline Survey Manuscripts that define the shoreline and alongshore natural and man-made features

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOS coastal survey maps (often called t-sheet or tp-sheet maps) are special use planimetric or topographic maps that precisely define the shoreline and alongshore...

  20. TRANSIMS and the hierarchical data format

    Energy Technology Data Exchange (ETDEWEB)

    Bush, B.W.

    1997-06-12

    The Hierarchical Data Format (HDF) is a general-purposed scientific data format developed at the National Center for Supercomputing Applications. It supports metadata, compression, and a variety of data structures (multidimensional arrays, raster images, tables). FORTRAN 77 and ANSI C programming interfaces are available for it and a wide variety of visualization tools read HDF files. The author discusses the features of this file format and its possible uses in TRANSIMS.

  1. Modular, Hierarchical Learning By Artificial Neural Networks

    Science.gov (United States)

    Baldi, Pierre F.; Toomarian, Nikzad

    1996-01-01

    Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

  2. Hierarchical mixture models for assessing fingerprint individuality

    OpenAIRE

    Dass, Sarat C.; Li, Mingfei

    2009-01-01

    The study of fingerprint individuality aims to determine to what extent a fingerprint uniquely identifies an individual. Recent court cases have highlighted the need for measures of fingerprint individuality when a person is identified based on fingerprint evidence. The main challenge in studies of fingerprint individuality is to adequately capture the variability of fingerprint features in a population. In this paper hierarchical mixture models are introduced to infer the extent of individua...

  3. Hierarchical manifold learning.

    Science.gov (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel

    2012-01-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

  4. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  5. HDS: Hierarchical Data System

    Science.gov (United States)

    Pearce, Dave; Walter, Anton; Lupton, W. F.; Warren-Smith, Rodney F.; Lawden, Mike; McIlwrath, Brian; Peden, J. C. M.; Jenness, Tim; Draper, Peter W.

    2015-02-01

    The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023). HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

  6. Comprehensive definition of genome features in Spirodela polyrhiza by high-depth physical mapping and short-read DNA sequencing strategies.

    Science.gov (United States)

    Michael, Todd P; Bryant, Douglas; Gutierrez, Ryan; Borisjuk, Nikolai; Chu, Philomena; Zhang, Hanzhong; Xia, Jing; Zhou, Junfei; Peng, Hai; El Baidouri, Moaine; Ten Hallers, Boudewijn; Hastie, Alex R; Liang, Tiffany; Acosta, Kenneth; Gilbert, Sarah; McEntee, Connor; Jackson, Scott A; Mockler, Todd C; Zhang, Weixiong; Lam, Eric

    2017-02-01

    Spirodela polyrhiza is a fast-growing aquatic monocot with highly reduced morphology, genome size and number of protein-coding genes. Considering these biological features of Spirodela and its basal position in the monocot lineage, understanding its genome architecture could shed light on plant adaptation and genome evolution. Like many draft genomes, however, the 158-Mb Spirodela genome sequence has not been resolved to chromosomes, and important genome characteristics have not been defined. Here we deployed rapid genome-wide physical maps combined with high-coverage short-read sequencing to resolve the 20 chromosomes of Spirodela and to empirically delineate its genome features. Our data revealed a dramatic reduction in the number of the rDNA repeat units in Spirodela to fewer than 100, which is even fewer than that reported for yeast. Consistent with its unique phylogenetic position, small RNA sequencing revealed 29 Spirodela-specific microRNA, with only two being shared with Elaeis guineensis (oil palm) and Musa balbisiana (banana). Combining DNA methylation data and small RNA sequencing enabled the accurate prediction of 20.5% long terminal repeats (LTRs) that doubled the previous estimate, and revealed a high Solo:Intact LTR ratio of 8.2. Interestingly, we found that Spirodela has the lowest global DNA methylation levels (9%) of any plant species tested. Taken together our results reveal a genome that has undergone reduction, likely through eliminating non-essential protein coding genes, rDNA and LTRs. In addition to delineating the genome features of this unique plant, the methodologies described and large-scale genome resources from this work will enable future evolutionary and functional studies of this basal monocot family. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

  7. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

    Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

    2005-07-01

    There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

  8. An Analysis of Prospective Teachers' Knowledge for Constructing Concept Maps

    Science.gov (United States)

    Subramaniam, Karthigeyan; Esprívalo Harrell, Pamela

    2015-01-01

    Background: Literature contends that a teacher's knowledge of concept map-based tasks influence how their students perceive the task and execute the creation of acceptable concept maps. Teachers who are skilled concept mappers are able to (1) understand and apply the operational terms to construct a hierarchical/non-hierarchical concept map; (2)…

  9. Multi-component mapping of karst features with remote sensing, digital elevation data and GIS: a case study from Central Crete

    Science.gov (United States)

    Siart, C.; Bubenzer, O.; Eitel, B.

    2009-04-01

    The application of remote sensing (RS) and GIS techniques based on high resolution satellite imagery in combination with digital elevation models (DEMs) can provide detailed information for geomorphologic purposes such as karst feature mapping. Moreover, area wide surveying is significantly improved and supported, as computer applications allow a very cost and time effective proceeding. The exemplary focus of the project at hand is on the Ida-Ori in Central Crete, a high mountain range predominantly consisting of Palaeozoic to Mesozoic limestones and dolomites. Subdivided into several vast high plateaus, its main geomorphologic characteristics are dry valleys of Miocene age and an intense karstification reaching from the base up to the highest peak at 2456 m a.s.l. Nearly all types of karst forms appear in immediate adjacency, while dolines, uvalas and poljes are the most frequent objects. Such depressions provide sediment traps for eroded soils or aeolian deposits and, thus, can be significantly filled with colluvial materials. Since the area wide karstification of Mount Ida has not been fully explored so far, the prime objective is to evaluate the potential and suitability of satellite data and DEMs (SRTM 90m, ASTER 15m) for the precise mapping of those structures. Furthermore, the dominant influencing variables of karst processes are investigated. To acquire spatially comprehensive information, Quickbird MS tiles (0.6 m resolution) were used for land surface classifications with RS-techniques. Subsequent to image correction and enhancement, a hybrid parallelepiped maximum likelihood classification approach was carried out. Postprocessing and conversion of raster data into vector format finally allowed spatial analyses in a GIS environment. Derivatives of DEMs (slope, aspect, contours, curvature, hydrologic drainage pattern) were generated in order to assess their suitability for karst mapping and to specify the remote sensing outcomes, particularly by conducting

  10. 基于Eye Map和SIFT特征的人眼定位%Eye Location Based on Eye Map and SIFT Features

    Institute of Scientific and Technical Information of China (English)

    谢春芝

    2012-01-01

    人脸对齐是人脸识别的前提,精确的人眼定位是人脸对齐的主要手段,为此提出了一种基于eye map和SIFT特征的人眼定位方法.首先根据人眼眼球部分的像素灰度比周围像素灰度更黑的特点,在人脸图像中选出满足该特征的像素点,接着通过排序滤波器得到这些像素点的连续区域及它们的几何中心,然后根据人眼特征点的几何限制粗选出候选的眼球像素点,最后在候选点的特定区域内提取SIFT特征,并采用支持向量机回归的方法得到响应值最大的像素点,该点即为人眼的精确定位点.实验结果分析表明该方法既具有较高的定位精度又具有较快的计算速度.%Eye alignment is the precondition for face registration, and the accurate eye localization is the main method for eye a-lignment. In this paper, a novel eye localization method based on eye map and SIFT feature is presented. First, based on the fact that eyeball is dark and round; those pixels darker than their surroundings are those from a face image. Then, connected regions in the eye map and their geometric centers are obtained by a rank order filter. Once more, candidate suitable eyeball pairs are selected based on a set of geometric constraints. And finally, SIFT features are extracted from the area of candidate eyeball pairs, with which the corresponding values are obtained by the support vector machine regressor. The pixel corresponding to the maximal value is just the accurate eye localization expected. Experiments show that the method not only has higher location accuracy but also has faster computation speed.

  11. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard;

    2012-01-01

    a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure......Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  12. 基于层次结构的农民工就业特征模型研究%Study on the Employment Feature Model of Migrant Workers Based on the Hierarchical Structure

    Institute of Scientific and Technical Information of China (English)

    陈玉峰; 张红燕; 敬松; 谢元瑰; 隆珂

    2013-01-01

    为了更有效地为农民工提供个性化就业推荐信息,促进农村剩余劳动力转移.通过采用层次结构表示方法融合决策树模型和向量空间模型,分析了农民工就业个性化推送服务的特点,并将农民工的基本信息特征与其网络上求职的操作特征有机结合,建立农民工就业特征模型.实证结果表明,该模型能够更好地对农民工的就业特征进行表示,提高就业推荐准确率.%To provide employment recommendation information for migrant workers more specific and promote the transfer of rural surplus labor, we integrate the decision tree model and vector space model into hierarchical structure representation method, analyze the characteristics of personalized employment recommendation service for migrant workers, combine the basic characteristics of the migrant workers with their concrete operation for job wanted on the network, then establish an employment characteristics model for migrant workers. The results showed that, the model could represent the employment characteristics of the migrant workers more effectively than existing models, so as to improve the recommendation accuracy for the employment of the migrant workers.

  13. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

    Full Text Available This squib studies the order in which elements are added to the shared context of interlocutors in a conversation. It focuses on context updates within one hierarchical structure and argues that structurally higher elements are entered into the context before lower elements, even if the structurally higher elements are pronounced after the lower elements. The crucial data are drawn from a comparison of relative clauses in two head-initial languages, English and Icelandic, and two head-final languages, Korean and Japanese. The findings have consequences for any theory of a dynamic semantics.

  14. Hierarchical Fixed Point Problems in Uniformly Smooth Banach Spaces

    Directory of Open Access Journals (Sweden)

    Lu-Chuan Ceng

    2014-01-01

    Full Text Available We propose some relaxed implicit and explicit viscosity approximation methods for hierarchical fixed point problems for a countable family of nonexpansive mappings in uniformly smooth Banach spaces. These relaxed viscosity approximation methods are based on the well-known viscosity approximation method and hybrid steepest-descent method. We obtain some strong convergence theorems under mild conditions.

  15. HYDROTHEMAL ALTERATION MAPPING USING FEATURE-ORIENTED PRINCIPAL COMPONENT SELECTION (FPCS METHOD TO ASTER DATA:WIKKI AND MAWULGO THERMAL SPRINGS, YANKARI PARK, NIGERIA

    Directory of Open Access Journals (Sweden)

    A. J. Abubakar

    2017-10-01

    Full Text Available Geothermal systems are essentially associated with hydrothermal alteration mineral assemblages such as iron oxide/hydroxide, clay, sulfate, carbonate and silicate groups. Blind and fossilized geothermal systems are not characterized by obvious surface manifestations like hot springs, geysers and fumaroles, therefore, they could not be easily identifiable using conventional techniques. In this investigation, the applicability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER were evaluated in discriminating hydrothermal alteration minerals associated with geothermal systems as a proxy in identifying subtle Geothermal systems at Yankari Park in northeastern Nigeria. The area is characterized by a number of thermal springs such as Wikki and Mawulgo. Feature-oriented Principal Component selection (FPCS was applied to ASTER data based on spectral characteristics of hydrothermal alteration minerals for a systematic and selective extraction of the information of interest. Application of FPCS analysis to bands 5, 6 and 8 and bands 1, 2, 3 and 4 datasets of ASTER was used for mapping clay and iron oxide/hydroxide minerals in the zones of Wikki and Mawulgo thermal springs in Yankari Park area. Field survey using GPS and laboratory analysis, including X-ray Diffractometer (XRD and Analytical Spectral Devices (ASD were carried out to verify the image processing results. The results indicate that ASTER dataset reliably and complementarily be used for reconnaissance stage of targeting subtle alteration mineral assemblages associated with geothermal systems.

  16. Two-dimensional finite element neutron diffusion analysis using hierarchic shape functions

    Energy Technology Data Exchange (ETDEWEB)

    Carpenter, D.C.

    1997-04-01

    Recent advances have been made in the use of p-type finite element method (FEM) for structural and fluid dynamics problems that hold promise for reactor physics problems. These advances include using hierarchic shape functions, element-by-element iterative solvers and more powerful mapping techniques. Use of the hierarchic shape functions allows greater flexibility and efficiency in implementing energy-dependent flux expansions and incorporating localized refinement of the solution space. The irregular matrices generated by the p-type FEM can be solved efficiently using element-by-element conjugate gradient iterative solvers. These solvers do not require storage of either the global or local stiffness matrices and can be highly vectorized. Mapping techniques based on blending function interpolation allow exact representation of curved boundaries using coarse element grids. These features were implemented in a developmental two-dimensional neutron diffusion program based on the use of hierarchic shape functions (FEM2DH). Several aspects in the effective use of p-type analysis were explored. Two choices of elemental preconditioning were examined--the proper selection of the polynomial shape functions and the proper number of functions to use. Of the five shape function polynomials tested, the integral Legendre functions were the most effective. The serendipity set of functions is preferable over the full tensor product set. Two global preconditioners were also examined--simple diagonal and incomplete Cholesky. The full effectiveness of the finite element methodology was demonstrated on a two-region, two-group cylindrical problem but solved in the x-y coordinate space, using a non-structured element grid. The exact, analytic eigenvalue solution was achieved with FEM2DH using various combinations of element grids and flux expansions.

  17. Levels and properties of map perception

    Directory of Open Access Journals (Sweden)

    Żyszkowska Wiesława

    2017-03-01

    Full Text Available Map perception consists of numerous processes of information processing, taking place almost simultaneously at different levels and stages which makes it conditioned by many factors. In the article, a review of processes related to the perception of a map as well as levels and properties of perception which impact its course and the nature of information obtained from a map is presented. The most important process constituting the basis of a map perception is a visual search (eye movement. However, as stated based on the studies, the process is individual depending on the purpose of map perception and it may be guided by its image (visual search guidance or by the knowledge of users (cognitive search guidance. Perception can take place according to various schemes – “local-to-global” or “global-to-local”, or in accordance with the guided search theory. Perception is divided into three processes: perceiving, distinguishing and identifying, which constitute the basis to interpret and understand a map. They are related to various degrees of intellectual involvement of the user and to various levels of questions concerning the relations between signs and their content. Identification involves referring a sign to its explanation in the legend. Interpretation means transformation of the initial information collected from the map into derivative information in which two basic types of understanding take place: deductive and inductive. Identification of geographical space objects on the map and the interpretation of its content constitute the basis to introduce information into memory structures. In the brain a resource of information is generated called geographic knowledge or spatial representation (mental map which may have a double nature – verbal or pictorial. An important feature of mental maps is organization of spatial information into hierarchical structures, e.g. grouping towns into regions as well as deformation of spatial

  18. Hierarchical Neural Regression Models for Customer Churn Prediction

    Directory of Open Access Journals (Sweden)

    Golshan Mohammadi

    2013-01-01

    Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

  19. Robust method for infrared small-target detection based on Boolean map visual theory.

    Science.gov (United States)

    Qi, Shengxiang; Ming, Delie; Ma, Jie; Sun, Xiao; Tian, Jinwen

    2014-06-20

    In this paper, we present an infrared small target detection method based on Boolean map visual theory. The scheme is inspired by the phenomenon that small targets can often attract human attention due to two characteristics: brightness and Gaussian-like shape in the local context area. Motivated by this observation, we perform the task under a visual attention framework with Boolean map theory, which reveals that an observer's visual awareness corresponds to one Boolean map via a selected feature at any given instant. Formally, the infrared image is separated into two feature channels, including a color channel with the original gray intensity map and an orientation channel with the orientation texture maps produced by a designed second order directional derivative filter. For each feature map, Boolean maps delineating targets are computed from hierarchical segmentations. Small targets are then extracted from the target enhanced map, which is obtained by fusing the weighted Boolean maps of the two channels. In experiments, a set of real infrared images covering typical backgrounds with sky, sea, and ground clutters are tested to verify the effectiveness of our method. The results demonstrate that it outperforms the state-of-the-art methods with good performance.

  20. Hierarchical partial order ranking.

    Science.gov (United States)

    Carlsen, Lars

    2008-09-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritization of polluted sites is given.

  1. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

    The "raison d'etre" of hierarchical dustering theory stems from one basic phe­ nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das­ sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.

  2. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  3. Optimisation by hierarchical search

    Science.gov (United States)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

    Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

  4. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  5. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L; Bod, Rens; Christiansen, Morten H

    2012-11-22

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

  6. A New Metrics for Hierarchical Clustering

    Institute of Scientific and Technical Information of China (English)

    YANGGuangwen; SHIShuming; WANGDingxing

    2003-01-01

    Hierarchical clustering is a popular method of performing unsupervised learning. Some metric must be used to determine the similarity between pairs of clusters in hierarchical clustering. Traditional similarity metrics either can deal with simple shapes (i.e. spherical shapes) only or are very sensitive to outliers (the chaining effect). The main contribution of this paper is to propose some potential-based similarity metrics (APES and AMAPES) between clusters in hierarchical clustering, inspired by the concepts of the electric potential and the gravitational potential in electromagnetics and astronomy. The main features of these metrics are: the first, they have strong antijamming capability; the second, they are capable of finding clusters of different shapes such as spherical, spiral, chain, circle, sigmoid, U shape or other complex irregular shapes; the third, existing algorithms and research fruits for classical metrics can be adopted to deal with these new potential-based metrics with no or little modification. Experiments showed that the new metrics are more superior to traditional ones. Different potential functions are compared, and the sensitivity to parameters is also analyzed in this paper.

  7. Anisotropic and Hierarchical Porosity in Multifunctional Ceramics

    Science.gov (United States)

    Lichtner, Aaron Zev

    The performance of multifunctional porous ceramics is often hindered by the seemingly contradictory effects of porosity on both mechanical and non-structural properties and yet a sufficient body of knowledge linking microstructure to these properties does not exist. Using a combination of tailored anisotropic and hierarchical materials, these disparate effects may be reconciled. In this project, a systematic investigation of the processing, characterization and properties of anisotropic and isotropic hierarchically porous ceramics was conducted. The system chosen was a composite ceramic intended as the cathode for a solid oxide fuel cell (SOFC). Comprehensive processing investigations led to the development of approaches to make hierarchical, anisotropic porous microstructures using directional freeze-casting of well dispersed slurries. The effect of all the important processing parameters was investigated. This resulted in an ability to tailor and control the important microstructural features including the scale of the microstructure, the macropore size and total porosity. Comparable isotropic porous ceramics were also processed using fugitive pore formers. A suite of characterization techniques including x-ray tomography and 3-D sectional scanning electron micrographs (FIB-SEM) was used to characterize and quantify the green and partially sintered microstructures. The effect of sintering temperature on the microstructure was quantified and discrete element simulations (DEM) were used to explain the experimental observations. Finally, the comprehensive mechanical properties, at room temperature, were investigated, experimentally and using DEM, for the different microstructures.

  8. Resilient 3D hierarchical architected metamaterials.

    Science.gov (United States)

    Meza, Lucas R; Zelhofer, Alex J; Clarke, Nigel; Mateos, Arturo J; Kochmann, Dennis M; Greer, Julia R

    2015-09-15

    Hierarchically designed structures with architectural features that span across multiple length scales are found in numerous hard biomaterials, like bone, wood, and glass sponge skeletons, as well as manmade structures, like the Eiffel Tower. It has been hypothesized that their mechanical robustness and damage tolerance stem from sophisticated ordering within the constituents, but the specific role of hierarchy remains to be fully described and understood. We apply the principles of hierarchical design to create structural metamaterials from three material systems: (i) polymer, (ii) hollow ceramic, and (iii) ceramic-polymer composites that are patterned into self-similar unit cells in a fractal-like geometry. In situ nanomechanical experiments revealed (i) a nearly theoretical scaling of structural strength and stiffness with relative density, which outperforms existing nonhierarchical nanolattices; (ii) recoverability, with hollow alumina samples recovering up to 98% of their original height after compression to ≥ 50% strain; (iii) suppression of brittle failure and structural instabilities in hollow ceramic hierarchical nanolattices; and (iv) a range of deformation mechanisms that can be tuned by changing the slenderness ratios of the beams. Additional levels of hierarchy beyond a second order did not increase the strength or stiffness, which suggests the existence of an optimal degree of hierarchy to amplify resilience. We developed a computational model that captures local stress distributions within the nanolattices under compression and explains some of the underlying deformation mechanisms as well as validates the measured effective stiffness to be interpreted as a metamaterial property.

  9. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    CERN Document Server

    Jelonek, M

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.

  10. Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features.

    Science.gov (United States)

    Gevaert, Olivier; Mitchell, Lex A; Achrol, Achal S; Xu, Jiajing; Echegaray, Sebastian; Steinberg, Gary K; Cheshier, Samuel H; Napel, Sandy; Zaharchuk, Greg; Plevritis, Sylvia K

    2014-10-01

    To derive quantitative image features from magnetic resonance (MR) images that characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to create radiogenomic maps associating these features with various molecular data. Clinical, molecular, and MR imaging data for GBMs in 55 patients were obtained from the Cancer Genome Atlas and the Cancer Imaging Archive after local ethics committee and institutional review board approval. Regions of interest (ROIs) corresponding to enhancing necrotic portions of tumor and peritumoral edema were drawn, and quantitative image features were derived from these ROIs. Robust quantitative image features were defined on the basis of an intraclass correlation coefficient of 0.6 for a digital algorithmic modification and a test-retest analysis. The robust features were visualized by using hierarchic clustering and were correlated with survival by using Cox proportional hazards modeling. Next, these robust image features were correlated with manual radiologist annotations from the Visually Accessible Rembrandt Images (VASARI) feature set and GBM molecular subgroups by using nonparametric statistical tests. A bioinformatic algorithm was used to create gene expression modules, defined as a set of coexpressed genes together with a multivariate model of cancer driver genes predictive of the module's expression pattern. Modules were correlated with robust image features by using the Spearman correlation test to create radiogenomic maps and to link robust image features with molecular pathways. Eighteen image features passed the robustness analysis and were further analyzed for the three types of ROIs, for a total of 54 image features. Three enhancement features were significantly correlated with survival, 77 significant correlations were found between robust quantitative features and the VASARI feature set, and seven image features were correlated with molecular subgroups (P < .05 for all). A radiogenomics map was

  11. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    OpenAIRE

    Jelonek, Magdalena

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of m...

  12. Hierarchical fringe tracking

    CERN Document Server

    Petrov, Romain G; Boskri, Abdelkarim; Folcher, Jean-Pierre; Lagarde, Stephane; Bresson, Yves; Benkhaldoum, Zouhair; Lazrek, Mohamed; Rakshit, Suvendu

    2014-01-01

    The limiting magnitude is a key issue for optical interferometry. Pairwise fringe trackers based on the integrated optics concepts used for example in GRAVITY seem limited to about K=10.5 with the 8m Unit Telescopes of the VLTI, and there is a general "common sense" statement that the efficiency of fringe tracking, and hence the sensitivity of optical interferometry, must decrease as the number of apertures increases, at least in the near infrared where we are still limited by detector readout noise. Here we present a Hierarchical Fringe Tracking (HFT) concept with sensitivity at least equal to this of a two apertures fringe trackers. HFT is based of the combination of the apertures in pairs, then in pairs of pairs then in pairs of groups. The key HFT module is a device that behaves like a spatial filter for two telescopes (2TSF) and transmits all or most of the flux of a cophased pair in a single mode beam. We give an example of such an achromatic 2TSF, based on very broadband dispersed fringes analyzed by g...

  13. Effective thermal conductivity of complicated hierarchic multilayer fabric

    Directory of Open Access Journals (Sweden)

    Fan Jie

    2014-01-01

    Full Text Available Warm retention property of fabric is one of the most important factors for clothing comfortability. The worm retention efficiency of a multilayer fabric with hierarchic inner structure was investigated based on its geometric feature. The thermal resistance of the multilayer fabric increases as the layer of the fabric increases.

  14. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  15. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  16. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  17. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  18. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm.

  19. Quark flavor mixings from hierarchical mass matrices

    Energy Technology Data Exchange (ETDEWEB)

    Verma, Rohit [Chinese Academy of Sciences, Institute of High Energy Physics, Beijing (China); Rayat Institute of Engineering and Information Technology, Ropar (India); Zhou, Shun [Chinese Academy of Sciences, Institute of High Energy Physics, Beijing (China); Peking University, Center for High Energy Physics, Beijing (China)

    2016-05-15

    In this paper, we extend the Fritzsch ansatz of quark mass matrices while retaining their hierarchical structures and show that the main features of the Cabibbo-Kobayashi-Maskawa (CKM) matrix V, including vertical stroke V{sub us} vertical stroke ≅ vertical stroke V{sub cd} vertical stroke, vertical stroke V{sub cb} vertical stroke ≅ vertical stroke V{sub ts} vertical stroke and vertical stroke V{sub ub} vertical stroke / vertical stroke V{sub cb} vertical stroke < vertical stroke V{sub td} vertical stroke / vertical stroke V{sub ts} vertical stroke can be well understood. This agreement is observed especially when the mass matrices have non-vanishing (1, 3) and (3, 1) off-diagonal elements. The phenomenological consequences of these for the allowed texture content and gross structural features of 'hierarchical' quark mass matrices are addressed from a model-independent prospective under the assumption of factorizable phases in these. The approximate and analytical expressions of the CKM matrix elements are derived and a detailed analysis reveals that such structures are in good agreement with the observed quark flavor mixing angles and the CP-violating phase at the 1σ level and call upon a further investigation of the realization of these structures from a top-down prospective. (orig.)

  20. Hierarchical self-organization of non-cooperating individuals

    OpenAIRE

    Tamás Nepusz; Tamás Vicsek

    2013-01-01

    Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introdu...

  1. Contextual Hierarchical Part-Driven Conditional Random Field Model for Object Category Detection

    Directory of Open Access Journals (Sweden)

    Lizhen Wu

    2012-01-01

    Full Text Available Even though several promising approaches have been proposed in the literature, generic category-level object detection is still challenging due to high intraclass variability and ambiguity in the appearance among different object instances. From the view of constructing object models, the balance between flexibility and discrimination must be taken into consideration. Motivated by these demands, we propose a novel contextual hierarchical part-driven conditional random field (CRF model, which is based on not only individual object part appearance but also model contextual interactions of the parts simultaneously. By using a latent two-layer hierarchical formulation of labels and a weighted neighborhood structure, the model can effectively encode the dependencies among object parts. Meanwhile, beta-stable local features are introduced as observed data to ensure the discriminative and robustness of part description. The object category detection problem can be solved in a probabilistic framework using a supervised learning method based on maximum a posteriori (MAP estimation. The benefits of the proposed model are demonstrated on the standard dataset and satellite images.

  2. Hierarchical Place Trees: A Portable Abstraction for Task Parallelism and Data Movement

    Science.gov (United States)

    Yan, Yonghong; Zhao, Jisheng; Guo, Yi; Sarkar, Vivek

    Modern computer systems feature multiple homogeneous or heterogeneous computing units with deep memory hierarchies, and expect a high degree of thread-level parallelism from the software. Exploitation of data locality is critical to achieving scalable parallelism, but adds a significant dimension of complexity to performance optimization of parallel programs. This is especially true for programming models where locality is implicit and opaque to programmers. In this paper, we introduce the hierarchical place tree (HPT) model as a portable abstraction for task parallelism and data movement. The HPT model supports co-allocation of data and computation at multiple levels of a memory hierarchy. It can be viewed as a generalization of concepts from the Sequoia and X10 programming models, resulting in capabilities that are not supported by either. Compared to Sequoia, HPT supports three kinds of data movement in a memory hierarchy rather than just explicit data transfer between adjacent levels, as well as dynamic task scheduling rather than static task assignment. Compared to X10, HPT provides a hierarchical notion of places for both computation and data mapping. We describe our work-in-progress on implementing the HPT model in the Habanero-Java (HJ) compiler and runtime system. Preliminary results on general-purpose multicore processors and GPU accelerators indicate that the HPT model can be a promising portable abstraction for future multicore processors.

  3. Advanced hierarchical distance sampling

    Science.gov (United States)

    Royle, Andy

    2016-01-01

    In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

  4. A Hierarchical Bayesian Model for Crowd Emotions

    Science.gov (United States)

    Urizar, Oscar J.; Baig, Mirza S.; Barakova, Emilia I.; Regazzoni, Carlo S.; Marcenaro, Lucio; Rauterberg, Matthias

    2016-01-01

    Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the behavior of individuals and of the crowd as a single entity, and explore the relation between behavior and emotions to infer emotional states. Information about the motion patterns of individuals are described using a self-organizing map, and a hierarchical Bayesian network builds probabilistic models to identify behaviors and infer the emotional state of individuals and the crowd. This model is trained and tested using data produced from simulated scenarios that resemble real-life environments. The conducted experiments tested the efficiency of our method to learn, detect and associate behaviors with emotional states yielding accuracy levels of 74% for individuals and 81% for the crowd, similar in performance with existing methods for pedestrian behavior detection but with novel concepts regarding the analysis of crowds. PMID:27458366

  5. Bioindication of trace metals in Brachythecium rutabulum around a copper smelter in Legnica (Southwest Poland): Use of a new form of data presentation in the form of a self-organizing feature map.

    Science.gov (United States)

    Samecka-Cymerman, A; Stankiewicz, A; Kolon, K; Kempers, A J

    2009-05-01

    Concentrations of the elements Al, Be, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn were measured in the terrestrial moss Brachythecium rutabulum and the soil on which it grew. Soil and moss plants were sampled at sites situated 1.5, 3, 6, 9 and 15 km to the north, south, east and west of the Legnica copper smelter (SW Poland). The self-organizing feature map (SOFM) or Kohonen network was used to classify the soil and moss samples according to the concentrations of the elements. The self-organizing map yielded distinct groups of B. rutabulum and soil samples, depending on the distance from and direction to the source of pollution. When the map-identified groups of sites with similar soil metal concentrations were combined with the map-identified groups of sites with similar metal concentrations in B. rutabulum, these maps were found to correspond closely. The SOFMs accurately represented the least polluted, moderately polluted and severely polluted sites, reflecting the distribution of metals that is typical of the smelter area, caused by the prevailing westerly and northerly winds.

  6. Hierarchical topic modeling with nested hierarchical Dirichlet process

    Institute of Scientific and Technical Information of China (English)

    Yi-qun DING; Shan-ping LI; Zhen ZHANG; Bin SHEN

    2009-01-01

    This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as welt as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more free-grained topic relationships compared to the hierarchical latent Dirichlet allocation model.

  7. Hierarchical organization of segmentation in non-functional action sequences

    DEFF Research Database (Denmark)

    Nielbo, Kristoffer Laigaard; Schjødt, Uffe; Sørensen, Jesper

    2013-01-01

    Both folk and scientific taxonomies of behavior distinguish between instrumental and ritual behavior. Recent studies indicate that behaviors dominated by ritual features tend to increase cognitive load by focusing attentional and working memory resources on low-level perceptual details and psycho......-physics. In contrast to the general consensus in anthropology and the study of religion, one study did not find any modulation effect of expectations (e.g., cultural information or priors) on cognitive load. It has, therefore, been suggested that the increase reflects a perceptual mechanism that drives categorization...... of ritual behavior. The present study investigated how an increase in cognitive load elicited by ritual behavior can influence hierarchically-related representations of actions and if expectation can modulate such hierarchical action representations. The study found that hierarchical alignment during...

  8. Hierarchical Planning Methodology for a Supply Chain Management

    Directory of Open Access Journals (Sweden)

    Virna ORTIZ-ARAYA

    2012-01-01

    Full Text Available Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.

  9. Synthesis strategies in the search for hierarchical zeolites.

    Science.gov (United States)

    Serrano, D P; Escola, J M; Pizarro, P

    2013-05-07

    Great interest has arisen in the past years in the development of hierarchical zeolites, having at least two levels of porosities. Hierarchical zeolites show an enhanced accessibility, leading to improved catalytic activity in reactions suffering from steric and/or diffusional limitations. Moreover, the secondary porosity offers an ideal space for the deposition of additional active phases and for functionalization with organic moieties. However, the secondary surface represents a discontinuity of the crystalline framework, with a low connectivity and a high concentration of silanols. Consequently, hierarchical zeolites exhibit a less "zeolitic behaviour" than conventional ones in terms of acidity, hydrophobic/hydrophilic character, confinement effects, shape-selectivity and hydrothermal stability. Nevertheless, this secondary surface is far from being amorphous, which provides hierarchical zeolites with a set of novel features. A wide variety of innovative strategies have been developed for generating a secondary porosity in zeolites. In the present review, the different synthetic routes leading to hierarchical zeolites have been classified into five categories: removal of framework atoms, surfactant-assisted procedures, hard-templating, zeolitization of preformed solids and organosilane-based methods. Significant advances have been achieved recently in several of these alternatives. These include desilication, due to its versatility, dual templating with polyquaternary ammonium surfactants and framework reorganization by treatment with surfactant-containing basic solutions. In the last two cases, the materials so prepared show both mesoscopic ordering and zeolitic lattice planes. Likewise, interesting results have been obtained with the incorporation of different types of organosilanes into the zeolite crystallization gels, taking advantage of their high affinity for silicate and aluminosilicate species. Crystallization of organofunctionalized species favours the

  10. Hierarchical self-organization of non-cooperating individuals

    CERN Document Server

    Nepusz, Tamás

    2013-01-01

    Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network) can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchic...

  11. Concept Association and Hierarchical Hamming Clustering Model in Text Classification

    Institute of Scientific and Technical Information of China (English)

    Su Gui-yang; Li Jian-hua; Ma Ying-hua; Li Sheng-hong; Yin Zhong-hang

    2004-01-01

    We propose two models in this paper. The concept of association model is put forward to obtain the co-occurrence relationships among keywords in the documents and the hierarchical Hamming clustering model is used to reduce the dimensionality of the category feature vector space which can solve the problem of the extremely high dimensionality of the documents' feature space. The results of experiment indicate that it can obtain the co-occurrence relations among keywords in the documents which promote the recall of classification system effectively. The hierarchical Hamming clustering model can reduce the dimensionality of the category feature vector efficiently, the size of the vector space is only about 10% of the primary dimensionality.

  12. Music emotion detection using hierarchical sparse kernel machines.

    Science.gov (United States)

    Chin, Yu-Hao; Lin, Chang-Hong; Siahaan, Ernestasia; Wang, Jia-Ching

    2014-01-01

    For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA) is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target) side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM) with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET) curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.

  13. Organizing Search Results with a Reference Map.

    Science.gov (United States)

    Nocaj, A; Brandes, U

    2012-12-01

    We propose a method to highlight query hits in hierarchically clustered collections of interrelated items such as digital libraries or knowledge bases. The method is based on the idea that organizing search results similarly to their arrangement on a fixed reference map facilitates orientation and assessment by preserving a user's mental map. Here, the reference map is built from an MDS layout of the items in a Voronoi treemap representing their hierarchical clustering, and we use techniques from dynamic graph layout to align query results with the map. The approach is illustrated on an archive of newspaper articles.

  14. Hierarchical model of matching

    Science.gov (United States)

    Pedrycz, Witold; Roventa, Eugene

    1992-01-01

    The issue of matching two fuzzy sets becomes an essential design aspect of many algorithms including fuzzy controllers, pattern classifiers, knowledge-based systems, etc. This paper introduces a new model of matching. Its principal features involve the following: (1) matching carried out with respect to the grades of membership of fuzzy sets as well as some functionals defined on them (like energy, entropy,transom); (2) concepts of hierarchies in the matching model leading to a straightforward distinction between 'local' and 'global' levels of matching; and (3) a distributed character of the model realized as a logic-based neural network.

  15. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

    Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

    2017-01-01

    Purpose This paper aims to present that deliberate change is strongly associated with formal structures and top-down influence. Hierarchical configurations have been used to structure processes, overcome resistance and get things done. But is deliberate change also possible without formal...... reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  16. Static Correctness of Hierarchical Procedures

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1990-01-01

    A system of hierarchical, fully recursive types in a truly imperative language allows program fragments written for small types to be reused for all larger types. To exploit this property to enable type-safe hierarchical procedures, it is necessary to impose a static requirement on procedure calls....... We introduce an example language and prove the existence of a sound requirement which preserves static correctness while allowing hierarchical procedures. This requirement is further shown to be optimal, in the sense that it imposes as few restrictions as possible. This establishes the theoretical...... basis for a general type hierarchy with static type checking, which enables first-order polymorphism combined with multiple inheritance and specialization in a language with assignments. We extend the results to include opaque types. An opaque version of a type is different from the original but has...

  17. Fully automatic feature-based registration of mobile mapping and aerial nadir images for enabling the adjustment of mobile platform locations in gnss-denied urban environments

    NARCIS (Netherlands)

    Jende, P.; Nex, F.; Gerke, M.; Vosselman, G.; Heipke, C.

    2017-01-01

    Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM?s georeferencing relies on a conjunction of Global Navigation

  18. Hierarchical fractal Weyl laws for chaotic resonance states in open mixed systems.

    Science.gov (United States)

    Körber, M J; Michler, M; Bäcker, A; Ketzmerick, R

    2013-09-13

    In open chaotic systems the number of long-lived resonance states obeys a fractal Weyl law, which depends on the fractal dimension of the chaotic saddle. We study the generic case of a mixed phase space with regular and chaotic dynamics. We find a hierarchy of fractal Weyl laws, one for each region of the hierarchical decomposition of the chaotic phase-space component. This is based on our observation of hierarchical resonance states localizing on these regions. Numerically this is verified for the standard map and a hierarchical model system.

  19. Hierarchical video summarization for medical data

    Science.gov (United States)

    Zhu, Xingquan; Fan, Jianping; Elmagarmid, Ahmed K.; Aref, Walid G.

    2001-12-01

    To provide users with an overview of medical video content at various levels of abstraction which can be used for more efficient database browsing and access, a hierarchical video summarization strategy has been developed and is presented in this paper. To generate an overview, the key frames of a video are preprocessed to extract special frames (black frames, slides, clip art, sketch drawings) and special regions (faces, skin or blood-red areas). A shot grouping method is then applied to merge the spatially or temporally related shots into groups. The visual features and knowledge from the video shots are integrated to assign the groups into predefined semantic categories. Based on the video groups and their semantic categories, video summaries for different levels are constructed by group merging, hierarchical group clustering and semantic category selection. Based on this strategy, a user can select the layer of the summary to access. The higher the layer, the more concise the video summary; the lower the layer, the greater the detail contained in the summary.

  20. A network of topographic numerosity maps in human association cortex.

    NARCIS (Netherlands)

    Harvey, Ben M.; Dumoulin, Serge O.

    2017-01-01

    Sensory and motor cortices each contain multiple topographic maps with the structure of sensory organs (such as the retina or cochlea) mapped onto the cortical surface. These sensory maps are hierarchically organized. For example, visual field maps contain neurons that represent increasingly large

  1. A network of topographic numerosity maps in human association cortex.

    NARCIS (Netherlands)

    Harvey, Ben M.; Dumoulin, Serge O.

    2017-01-01

    Sensory and motor cortices each contain multiple topographic maps with the structure of sensory organs (such as the retina or cochlea) mapped onto the cortical surface. These sensory maps are hierarchically organized. For example, visual field maps contain neurons that represent increasingly large p

  2. Hierarchical resource analysis for land use planning through remote sensing

    Science.gov (United States)

    Byrnes, B. H.; Frazee, C. J.; Cox, T. L.

    1976-01-01

    A hierarchical resource analysis was applied to remote sensing data to provide maps at Planning Levels I and III (Anderson et al., U.S. Geological Survey Circular 671) for Meade County, S. Dak. Level I land use and general soil maps were prepared by visual interpretation of imagery from a false color composite of Landsat MSS bands 4, 5, and 7 and single bands (5 and 7). A modified Level III land use map was prepared for the Black Hills area from RB-57 photography enlarged to a scale of 1:24,000. Level III land use data were used together with computer-generated interpretive soil maps to analyze relationships between developed and developing areas and soil criteria.

  3. Fish assemblage composition and mapped mesohabitat features over a range of streamflows in the Middle Rio Grande, New Mexico, winter 2011-12, summer 2012

    Science.gov (United States)

    Pearson, Daniel K.; Braun, Christopher L.; Moring, J. Bruce

    2016-01-21

    This report documents differences in the mapped spatial extents and physical characteristics of in-channel fish habitat evaluated at the mesohabitat scale during winter 2011–12 (moderate streamflow) and summer 2012 (low streamflow) at 15 sites on the Middle Rio Grande in New Mexico starting about 3 kilometers downstream from Cochiti Dam and ending about 40 kilometers upstream from Elephant Butte Reservoir. The results of mesohabitat mapping, physical characterization, and fish assemblage surveys are summarized from the data that were collected. The report also presents general comparisons of physical mesohabitat data, such as wetted area and substrate type, and biological mesohabitat data, which included fish assemblage composition, species richness, Rio Grande silvery minnow relative abundance, and Rio Grande silvery minnow catch per unit effort.

  4. Survey of linear structural features from remote sensing – a contribution to the geotechnical mapping in Baturité Mountain, Ceará

    Directory of Open Access Journals (Sweden)

    Clístenes Teixeira Batista

    2014-06-01

    Full Text Available The use of techniques of digital image processing remote sensing allows applications of great importance for the geosciences. One of the possible fields of application of these resources is the geotechnical mapping. Filtering techniques for radar and optical images emphasize natural linear structures that can be interpreted as fractures, drainages, ridges, valley bottoms and foliation. With the lifting of these data, combined with field work, the geotechnical mapping gains in precision and agility. The high incidence of slope instability events recently occurred in some parts of Brazil, especially in the Southeast, has attracted the interest of researchers in engineering and geoscience areas in the preparation of monographs, dissertations, theses and academic articles that address this issue. For subsequent generation of a diagram rosettes and visualization of regional trend of the structures and preparation of lineament density map, the vectors corresponding to the guidelines direction were measured in azimuth, and the length was measured in meters. The importance of applying frequency spectrum filters is therefore to quantify and qualify these geological and geomorphological structures, which are among the main components of conditions of mass movements and erosion.

  5. Sensory Hierarchical Organization and Reading.

    Science.gov (United States)

    Skapof, Jerome

    The purpose of this study was to judge the viability of an operational approach aimed at assessing response styles in reading using the hypothesis of sensory hierarchical organization. A sample of 103 middle-class children from a New York City public school, between the ages of five and seven, took part in a three phase experiment. Phase one…

  6. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  7. 基于特征映射的义齿表面三维变形设计方法%3D Deformation Design Method for Prosthetic Dental Surface Based on Feature Mapping

    Institute of Scientific and Technical Information of China (English)

    郑淑贤; 李佳; 孙庆丰

    2011-01-01

    The prosthetic tooth surface design is an important issue in dental computer aided design systems(CAD). The designed tooth shape should fit to the patient's tooth articulation environment and keep the topological features of the generic teeth. Aiming at the problem, a 3D deformation approach for prosthetic dental surface design based on feature mapping is presented. The main idea is by identifying the corresponding feature points between the preparation tooth and the standard tooth firstly, using a suitable radial basis function to define the feature mapping relations in both teeth, then through the corresponding features alignment and the surface interpolation deformation, the prosthetic tooth surface deformation is realized. The result of case study of the first molar in lower jaw shows that the design process is simple, the standard tooth surface deformation is reasonable, the surface distortion can be avoided and the final inlay surface matches well with the preparation tooth. The feature mapping design method provides a new way for clinic application in dental CAD.%义齿表面设计是牙科计算机辅助设计和制造系统的一个重要环节,设计的义齿形状必须符合患者的口腔咬合环境并能保持牙齿的拓扑结构特征.针对这一问题,在此提出一种基于特征映射的义齿表面三维变形设计方法.该方法主要思想是首先识别预备体与同名标准牙的重要特征点,采用径向基函数建立两者的特征映射关系,再通过对应特征点的位置对齐和表面的插值变形,实现义齿表面的变形设计.下颌第一磨牙嵌体的设计案例结果表明,该方法设计程序简单,标准牙曲面变形合理,能有效地避免曲面失真,最终生成的嵌体与预备体匹配良好,为牙科计算机辅助设计和制造系统的临床应用提供一种新的方法.

  8. Variability of surfer circulation and Kuroshio intrusion in northern South China Sea using growing hierarchical self-organizing maps%应用GHSOM网络分析南海北部表层环流模态与黑潮入侵

    Institute of Scientific and Technical Information of China (English)

    徐晓华; 廖光洪; 杨成浩; 袁耀初; 黄韦艮

    2013-01-01

    基于1992年10月至2009年11月卫星观测的海表高度(SSH)时间序列数据,应用增长型分级自组织映射(GHSOM)人工神经网络方法研究南海北部和西太平洋 SSH和中尺度涡旋的变化,识别出该海域 SSH的季节和年际变化信号。分析表明,流经吕宋海峡的黑潮分支在冷季入侵南海北部,同时在吕宋岛西北海域出现一个强烈的气旋式涡旋,表层黑潮的入侵与跨过吕宋海峡南北的经向压力梯度密切相关。黑潮的非入侵事件主要出现在暖季。春秋季节作为两个事件的过渡期,环流结构复杂,由 GHSOM的第2层特征图进一步进行分类识别。黑潮入侵事件和非入侵事件发生的百分比分别为24.57%和27.53%,过渡模态的百分比为47.87%。当入侵南海事件发生时,南海北部表层环流流态相对简单,主要为气旋环流控制南海北部,吕宋海峡表层海流是否入侵南海,与南海北部中尺度涡旋特别是吕宋岛西北的气旋式涡的变化关系密切;反之,在非入侵事件发生时,南海北部出现多涡结构,环流流态复杂,表明吕宋海峡海流入侵南海对南海北部环流也有重要调整作用。除季节尺度变化外,年际时间尺度变化信号也十分显著。在1994-1995、1997-1998和2002-2003年期间,表层黑潮入侵南海北部的事件要显著多于其他年份,然而入侵事件在1998-2001年和2006-2009年时间段明显减少,非入侵事件增加。应用欧氏距离定义的模态2的时间发展序列与Niño3.4指数序列延迟相关。%Sea surface height (SSH) variations and eddies on both sides of the Luzon Strait are examined from the merged satellite altimeter data from October 1992 to November 2009. The neural network analyses based on the growing hierarchical self-organizing map (GHSOM) are used to extract feature patterns of the circulation variability. The evolution of the characteristic circulation patterns

  9. Antiferromagnetic Ising Model in Hierarchical Networks

    Science.gov (United States)

    Cheng, Xiang; Boettcher, Stefan

    2015-03-01

    The Ising antiferromagnet is a convenient model of glassy dynamics. It can introduce geometric frustrations and may give rise to a spin glass phase and glassy relaxation at low temperatures [ 1 ] . We apply the antiferromagnetic Ising model to 3 hierarchical networks which share features of both small world networks and regular lattices. Their recursive and fixed structures make them suitable for exact renormalization group analysis as well as numerical simulations. We first explore the dynamical behaviors using simulated annealing and discover an extremely slow relaxation at low temperatures. Then we employ the Wang-Landau algorithm to investigate the energy landscape and the corresponding equilibrium behaviors for different system sizes. Besides the Monte Carlo methods, renormalization group [ 2 ] is used to study the equilibrium properties in the thermodynamic limit and to compare with the results from simulated annealing and Wang-Landau sampling. Supported through NSF Grant DMR-1207431.

  10. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Olsen, Ole Fogh; Sporring, Jon

    2006-01-01

    . To address this problem we introduce a novel photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way we preserve the important illumination features......, while eliminating noise. We call our method diffusion based photon mapping....

  11. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Fogh Olsen, Ole; Sporring, Jon

    2007-01-01

    . To address this problem we introduce a novel photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way we preserve the important illumination features......, while eliminating noise. We call our method diffusion based photon mapping....

  12. Breast image feature learning with adaptive deconvolutional networks

    Science.gov (United States)

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  13. Mobile Node Speed Detection Mechanism in Hierarchical Mobile Internet Protocol (IPv6

    Directory of Open Access Journals (Sweden)

    Zulkeflee Kusin

    2011-01-01

    Full Text Available Problem statement: IETF has introduced Hierarchical Mobile IPv6 (HMIPv6 to support mobility problem in the next generation Internet Protocol (IPv6. The key concept behind this protocol is the usage of Mobility Anchor Point (MAP located at any level router of network to support hierarchical mobility management and seamless handover. The distance MAP selection in HMIPv6 causes MAP overloaded as the network grows. Approach: To address the issue in designing MAP selection scheme, we proposed a dynamic speed detection mechanism that integrates with the load control mechanism. Results: From the experimental results we obtained that the proposed scheme gives better distribution in MAP load and reduced binding update cost. Conclusion/Recommendations: The Next Generation Networks (NGN is expected to provide seamless handover in high speed wireless network environment. There is crucial need of very sophisticated protocols to support NGN QoS requirements.

  14. Update Legal Documents Using Hierarchical Ranking Models and Word Clustering

    OpenAIRE

    Pham, Minh Quang Nhat; Nguyen, Minh Le; Shimazu, Akira

    2010-01-01

    Our research addresses the task of updating legal documents when newinformation emerges. In this paper, we employ a hierarchical ranking model tothe task of updating legal documents. Word clustering features are incorporatedto the ranking models to exploit semantic relations between words. Experimentalresults on legal data built from the United States Code show that the hierarchicalranking model with word clustering outperforms baseline methods using VectorSpace Model, and word cluster-based ...

  15. Hierarchical Prisoner's Dilemma in Hierarchical Public-Goods Game

    CERN Document Server

    Fujimoto, Yuma; Kaneko, Kunihiko

    2016-01-01

    The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games. To study such a multi-level game, we introduce a hierarchical public-goods (HPG) game in which two groups compete for finite resources by utilizing costs collected from individuals in each group. Analyzing this HPG game, we found a hierarchical prisoner's dilemma, in which groups choose the defection policy (say, armaments) as a Nash strategy to optimize each group's benefit, while cooperation optimizes the total benefit. On the other hand, for each individual within a group, refusing to pay the cost (say, tax) is a Nash strategy, which turns to be a cooperation policy for the group, thus leading to a hierarchical d...

  16. A novel syndrome of paediatric cataract, dysmorphism, ectodermal features, and developmental delay in Australian Aboriginal family maps to 1p35.3-p36.32

    Directory of Open Access Journals (Sweden)

    Gecz Jozef

    2010-11-01

    Full Text Available Abstract Background A novel phenotype consisting of cataract, mental retardation, erythematous skin rash and facial dysmorphism was recently described in an extended pedigree of Australian Aboriginal descent. Large scale chromosomal re-arrangements had previously been ruled out. We have conducted a genome-wide scan to map the linkage region in this family. Methods Genome-wide linkage analysis using Single Nucleotide Polymorphism (SNP markers on the Affymetrix 10K SNP array was conducted and analysed using MERLIN. Three positional candidate genes (ZBTB17, EPHA2 and EPHB2 were sequenced to screen for segregating mutations. Results Under a fully penetrant, dominant model, the locus for this unique phenotype was mapped to chromosome 1p35.3-p36.32 with a maximum LOD score of 2.41. The critical region spans 48.7 cM between markers rs966321 and rs1441834 and encompasses 527 transcripts from 364 annotated genes. No coding mutations were identified in three positional candidate genes EPHA2, EPHB2 or ZBTB17. The region overlaps with a previously reported region for Volkmann cataract and the phenotype has similarity to that reported for 1p36 monosomy. Conclusions The gene for this syndrome is located in a 25.6 Mb region on 1p35.3-p36.32. The known cataract gene in this region (EPHA2 does not harbour mutations in this family, suggesting that at least one additional gene for cataract is present in this region.

  17. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

    Directory of Open Access Journals (Sweden)

    Rui Sun

    2016-08-01

    Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

  18. Generic Approach for Hierarchical Modulation Performance Analysis: Application to DVB-SH

    CERN Document Server

    Méric, Hugo; Amiot-Bazile, Caroline; Arnal, Fabrice; Boucheret, Marie-Laure

    2011-01-01

    Broadcasting systems have to deal with channel diversity in order to offer the best rate to the users. Hierarchical modulation is a practical solution to provide several rates in function of the channel quality. Unfortunately the performance evaluation of such modulations requires time consuming simulations. We propose in this paper a novel approach based on the channel capacity to avoid these simulations. The method allows to study the performance in terms of spectrum efficiency of hierarchical and also classical modulations combined with error correcting codes. Our method will be applied to the DVB-SH standard which considers hierarchical modulation as an optional feature.

  19. Classification of Flos Lonicerae Based on Self-Organizing Feature Map Neural Network%基于自组织特征映射神经网络的金银花分类研究

    Institute of Scientific and Technical Information of China (English)

    申明金

    2013-01-01

    自组织特征映射神经网络(SOM)以无监督方式进行网络训练,具有自组织功能.网络通过自身训练,自动对输入模式进行分类.中药药用价值与其所含微量元素有直接的关系,药材分类是中药质量控制的重要方法.将金银花中微量元素含量作为网络输入,利用自组织特征映射神经网络对不同产地金银花进行分类.结果表明分类效果较好,符合生产实际.%Self-organizing feature map neural network(SOM) trains the network in a way of unsupervised learning and it has the function of self-organising.The network can automatively sort the input pattern by self-training.Traiditional Chinese medicinal value is directly related to trace elements and classification is an important method for quality control.The trace element contents were used as the inputs of network,so the flos lonicerae of different producing area was classified by self-organizing feature map neural network.The results show that the effect of classification is good and according with practical production.

  20. Hierarchical structure of biological systems

    Science.gov (United States)

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

  1. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  2. Hierarchical Formation of Galactic Clusters

    CERN Document Server

    Elmegreen, B G

    2006-01-01

    Young stellar groupings and clusters have hierarchical patterns ranging from flocculent spiral arms and star complexes on the largest scale to OB associations, OB subgroups, small loose groups, clusters and cluster subclumps on the smallest scales. There is no obvious transition in morphology at the cluster boundary, suggesting that clusters are only the inner parts of the hierarchy where stars have had enough time to mix. The power-law cluster mass function follows from this hierarchical structure: n(M_cl) M_cl^-b for b~2. This value of b is independently required by the observation that the summed IMFs from many clusters in a galaxy equals approximately the IMF of each cluster.

  3. Hierarchical matrices algorithms and analysis

    CERN Document Server

    Hackbusch, Wolfgang

    2015-01-01

    This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

  4. Hierarchical Cont-Bouchaud model

    CERN Document Server

    Paluch, Robert; Holyst, Janusz A

    2015-01-01

    We extend the well-known Cont-Bouchaud model to include a hierarchical topology of agent's interactions. The influence of hierarchy on system dynamics is investigated by two models. The first one is based on a multi-level, nested Erdos-Renyi random graph and individual decisions by agents according to Potts dynamics. This approach does not lead to a broad return distribution outside a parameter regime close to the original Cont-Bouchaud model. In the second model we introduce a limited hierarchical Erdos-Renyi graph, where merging of clusters at a level h+1 involves only clusters that have merged at the previous level h and we use the original Cont-Bouchaud agent dynamics on resulting clusters. The second model leads to a heavy-tail distribution of cluster sizes and relative price changes in a wide range of connection densities, not only close to the percolation threshold.

  5. Optimising steel production schedules via a hierarchical genetic algorithm

    Directory of Open Access Journals (Sweden)

    Worapradya, Kiatkajohn

    2014-08-01

    Full Text Available This paper presents an effective scheduling in a steel-making continuous casting (SCC plant. The main contribution of this paper is the formulation of a new optimisation model that more closely represents real-world situations, and a hierarchical genetic algorithm (HGA tailored particularly for searching for an optimal SCC schedule. The optimisation model is developed by integrating two main planning phases of traditional scheduling: (1 planning cast sequence, and (2 scheduling of steel-making and timing of all jobs. A novel procedure is given for genetic algorithm (GA chromosome coding that maps Gantt chart and hierarchical chromosomes. The performance of the proposed methodology is illustrated and compared with a two-phase traditional scheduling and a standard GA toolbox. Both qualitative and quantitative performance measures are investigated.

  6. Analysis and Optimisation of Hierarchically Scheduled Multiprocessor Embedded Systems

    DEFF Research Database (Denmark)

    Pop, Traian; Pop, Paul; Eles, Petru;

    2008-01-01

    , they are organised in a hierarchy. In this paper, we first develop a holistic scheduling and schedulability analysis that determines the timing properties of a hierarchically scheduled system. Second, we address design problems that are characteristic to such hierarchically scheduled systems: assignment......We present an approach to the analysis and optimisation of heterogeneous multiprocessor embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource...... of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We also present several algorithms for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilisation of the system...

  7. Nonlinear robust hierarchical control for nonlinear uncertain systems

    Directory of Open Access Journals (Sweden)

    Leonessa Alexander

    1999-01-01

    Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.

  8. Hybrid Steepest-Descent Methods for Triple Hierarchical Variational Inequalities

    Directory of Open Access Journals (Sweden)

    L. C. Ceng

    2015-01-01

    Full Text Available We introduce and analyze a relaxed iterative algorithm by combining Korpelevich’s extragradient method, hybrid steepest-descent method, and Mann’s iteration method. We prove that, under appropriate assumptions, the proposed algorithm converges strongly to a common element of the fixed point set of infinitely many nonexpansive mappings, the solution set of finitely many generalized mixed equilibrium problems (GMEPs, the solution set of finitely many variational inclusions, and the solution set of general system of variational inequalities (GSVI, which is just a unique solution of a triple hierarchical variational inequality (THVI in a real Hilbert space. In addition, we also consider the application of the proposed algorithm for solving a hierarchical variational inequality problem with constraints of finitely many GMEPs, finitely many variational inclusions, and the GSVI. The results obtained in this paper improve and extend the corresponding results announced by many others.

  9. Using Concept Maps in Teaching Microbiology

    OpenAIRE

    Gary E. Kaiser

    2010-01-01

    This article is intended for faculty teaching microbiology and other biological science courses, and is applicable to both the classroom and the laboratory. Concept maps are graphical tools for presenting knowledge concepts and the relationship between these concepts in a graphical, hierarchical fashion. Cross-links are further used to illustrate the relationships between the various segments of the concept map.

  10. Using Concept Maps in Teaching Microbiology

    Directory of Open Access Journals (Sweden)

    Gary E. Kaiser

    2010-04-01

    Full Text Available This article is intended for faculty teaching microbiology and other biological science courses, and is applicable to both the classroom and the laboratory. Concept maps are graphical tools for presenting knowledge concepts and the relationship between these concepts in a graphical, hierarchical fashion. Cross-links are further used to illustrate the relationships between the various segments of the concept map.

  11. Hierarchical Clustering and Active Galaxies

    CERN Document Server

    Hatziminaoglou, E; Manrique, A

    2000-01-01

    The growth of Super Massive Black Holes and the parallel development of activity in galactic nuclei are implemented in an analytic code of hierarchical clustering. The evolution of the luminosity function of quasars and AGN will be computed with special attention paid to the connection between quasars and Seyfert galaxies. One of the major interests of the model is the parallel study of quasar formation and evolution and the History of Star Formation.

  12. Hybrid and hierarchical composite materials

    CERN Document Server

    Kim, Chang-Soo; Sano, Tomoko

    2015-01-01

    This book addresses a broad spectrum of areas in both hybrid materials and hierarchical composites, including recent development of processing technologies, structural designs, modern computer simulation techniques, and the relationships between the processing-structure-property-performance. Each topic is introduced at length with numerous  and detailed examples and over 150 illustrations.   In addition, the authors present a method of categorizing these materials, so that representative examples of all material classes are discussed.

  13. Structural mapping of the coiled-coil domain of a bacterial condensin and comparative analyses across all domains of life suggest conserved features of SMC proteins.

    Science.gov (United States)

    Waldman, Vincent M; Stanage, Tyler H; Mims, Alexandra; Norden, Ian S; Oakley, Martha G

    2015-06-01

    The structural maintenance of chromosomes (SMC) proteins form the cores of multisubunit complexes that are required for the segregation and global organization of chromosomes in all domains of life. These proteins share a common domain structure in which N- and C- terminal regions pack against one another to form a globular ATPase domain. This "head" domain is connected to a central, globular, "hinge" or dimerization domain by a long, antiparallel coiled coil. To date, most efforts for structural characterization of SMC proteins have focused on the globular domains. Recently, however, we developed a method to map interstrand interactions in the 50-nm coiled-coil domain of MukB, the divergent SMC protein found in γ-proteobacteria. Here, we apply that technique to map the structure of the Bacillus subtilis SMC (BsSMC) coiled-coil domain. We find that, in contrast to the relatively complicated coiled-coil domain of MukB, the BsSMC domain is nearly continuous, with only two detectable coiled-coil interruptions. Near the middle of the domain is a break in coiled-coil structure in which there are three more residues on the C-terminal strand than on the N-terminal strand. Close to the head domain, there is a second break with a significantly longer insertion on the same strand. These results provide an experience base that allows an informed interpretation of the output of coiled-coil prediction algorithms for this family of proteins. A comparison of such predictions suggests that these coiled-coil deviations are highly conserved across SMC types in a wide variety of organisms, including humans. © 2015 Wiley Periodicals, Inc.

  14. Real-Time Speech/Music Classification With a Hierarchical Oblique Decision Tree

    Science.gov (United States)

    2008-04-01

    REAL-TIME SPEECH/ MUSIC CLASSIFICATION WITH A HIERARCHICAL OBLIQUE DECISION TREE Jun Wang, Qiong Wu, Haojiang Deng, Qin Yan Institute of Acoustics...time speech/ music classification with a hierarchical oblique decision tree. A set of discrimination features in frequency domain are selected...handle signals without discrimination and can not work properly in the existence of multimedia signals. This paper proposes a real-time speech/ music

  15. Treatment Protocols as Hierarchical Structures

    Science.gov (United States)

    Ben-Bassat, Moshe; Carlson, Richard W.; Puri, Vinod K.; Weil, Max Harry

    1978-01-01

    We view a treatment protocol as a hierarchical structure of therapeutic modules. The lowest level of this structure consists of individual therapeutic actions. Combinations of individual actions define higher level modules, which we call routines. Routines are designed to manage limited clinical problems, such as the routine for fluid loading to correct hypovolemia. Combinations of routines and additional actions, together with comments, questions, or precautions organized in a branching logic, in turn, define the treatment protocol for a given disorder. Adoption of this modular approach may facilitate the formulation of treatment protocols, since the physician is not required to prepare complex flowcharts. This hierarchical approach also allows protocols to be updated and modified in a flexible manner. By use of such a standard format, individual components may be fitted together to create protocols for multiple disorders. The technique is suited for computer implementation. We believe that this hierarchical approach may facilitate standarization of patient care as well as aid in clinical teaching. A protocol for acute pancreatitis is used to illustrate this technique.

  16. Fabrication and analysis of gecko-inspired hierarchical polymer nanosetae.

    Science.gov (United States)

    Ho, Audrey Yoke Yee; Yeo, Lip Pin; Lam, Yee Cheong; Rodríguez, Isabel

    2011-03-22

    A gecko's superb ability to adhere to surfaces is widely credited to the large attachment area of the hierarchical and fibrillar structure on its feet. The combination of these two features provides the necessary compliance for the gecko toe-pad to effectively engage a high percentage of the spatulae at each step to any kind of surface topography. With the use of multi-tiered porous anodic alumina template and capillary force assisted nanoimprinting, we have successfully fabricated a gecko-inspired hierarchical topography of branched nanopillars on a stiff polymer. We also demonstrated that the hierarchical topography improved the shear adhesion force over a topography of linear structures by 150%. A systematic analysis to understand the phenomenon was performed. It was determined that the effective stiffness of the hierarchical branched structure was lower than that of the linear structure. The reduction in effective stiffness favored a more efficient bending of the branched topography and a better compliance to a test surface, hence resulting in a higher area of residual deformation. As the area of residual deformation increased, the shear adhesion force emulated. The branched pillar topography also showed a marked increase in hydrophobicity, which is an essential property in the practical applications of these structures for good self-cleaning in dry adhesion conditions.

  17. HIERARCHICAL FRAGMENTATION OF THE ORION MOLECULAR FILAMENTS

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Satoko; Ho, Paul T. P.; Su, Yu-Nung [Academia Sinica Institute of Astronomy and Astrophysics, P.O. Box 23-141, Taipei 10617, Taiwan (China); Teixeira, Paula S. [Institut fuer Astrophysik, Universitaet Wien, Tuerkenschanzstrasse 17, A-1180, Wien (Austria); Zapata, Luis A., E-mail: satoko_t@asiaa.sinica.edu.tw [Centro de Radioastronomia y Astrofisica, Universidad Nacional Autonoma de Mexico, Morelia, Michoacan 58090 (Mexico)

    2013-01-20

    We present a high angular resolution map of the 850 {mu}m continuum emission of the Orion Molecular Cloud-3 (OMC 3) obtained with the Submillimeter Array (SMA); the map is a mosaic of 85 pointings covering an approximate area of 6.'5 Multiplication-Sign 2.'0 (0.88 Multiplication-Sign 0.27 pc). We detect 12 spatially resolved continuum sources, each with an H{sub 2} mass between 0.3-5.7 M {sub Sun} and a projected source size between 1400-8200 AU. All the detected sources are on the filamentary main ridge (n{sub H{sub 2}}{>=}10{sup 6} cm{sup -3}), and analysis based on the Jeans theorem suggests that they are most likely gravitationally unstable. Comparison of multi-wavelength data sets indicates that of the continuum sources, 6/12 (50%) are associated with molecular outflows, 8/12 (67%) are associated with infrared sources, and 3/12 (25%) are associated with ionized jets. The evolutionary status of these sources ranges from prestellar cores to protostar phase, confirming that OMC-3 is an active region with ongoing embedded star formation. We detect quasi-periodical separations between the OMC-3 sources of Almost-Equal-To 17''/0.035 pc. This spatial distribution is part of a large hierarchical structure that also includes fragmentation scales of giant molecular cloud ( Almost-Equal-To 35 pc), large-scale clumps ( Almost-Equal-To 1.3 pc), and small-scale clumps ( Almost-Equal-To 0.3 pc), suggesting that hierarchical fragmentation operates within the Orion A molecular cloud. The fragmentation spacings are roughly consistent with the thermal fragmentation length in large-scale clumps, while for small-scale cores it is smaller than the local fragmentation length. These smaller spacings observed with the SMA can be explained by either a helical magnetic field, cloud rotation, or/and global filament collapse. Finally, possible evidence for sequential fragmentation is suggested in the northern part of the OMC-3 filament.

  18. Hierarchical structures in fully developed turbulence

    Science.gov (United States)

    Liu, Li

    Analysis of the probability density functions (PDFs) of the velocity increment dvl and of their deformation is used to reveal the statistical structure of the intermittent energy cascade dynamics of turbulence. By analyzing a series of turbulent data sets including that of an experiment of fully developed low temperature helium turbulent gas flow (Belin, Tabeling, & Willaime, Physica D 93, 52, 1996), of a three-dimensional isotropic Navier-Stokes simulation with a resolution of 2563 (Cao, Chen, & She, Phys. Rev. Lett. 76, 3711, 1996) and of a GOY shell model simulation (Leveque & She, Phys. Rev. E 55, 1997) of a very big sample size (up to 5 billions), the validity of the Hierarchical Structure model (She & Leveque, Phys. Rev. Lett. 72, 366, 1994) for the inertial-range is firmly demonstrated. Furthermore, it is shown that parameters in the Hierarchical Structure model can be reliably measured and used to characterize the cascade process. The physical interpretations of the parameters then allow to describe differential changes in different turbulent systems so as to address non-universal features of turbulent systems. It is proposed that the above study provides a framework for the study of non-homogeneous turbulence. A convergence study of moments and scaling exponents is also carried out with detailed analysis of effects of finite statistical sample size. A quantity Pmin is introduced to characterize the resolution of a PDF, and hence the sample size. The fact that any reported scaling exponent depends on the PDF resolution suggests that the validation (or rejection) of a model of turbulence needs to carry out a resolution dependence analysis on its scaling prediction.

  19. Modelling of habitat conditions by self-organizing feature maps using relations between soil, plant chemical properties and type of basaltoides

    Directory of Open Access Journals (Sweden)

    Piotr Kosiba

    2011-01-01

    Full Text Available The paper shows the use of Kohonen's network for classification of basaltoides on the base of chemical properties of soils and Polypodium vulgare L. The study area was Lower Silesia (Poland. The archival data were: chemical composition of types of basaltoides from 89 sites (Al2O3, CaO, FeO, Fe2O3, K2O, MgO, MnO, Na2O, P2O5, SiO2 and TiO2, elements contents in soils (Cd, Co, Cu, Fe, Mn, Mo, Ni, Pb, S, Ti and Zn and leaves of P. vulgare (Ca, Cd, Co, Cu, Fe, K, Mg, Mn, Mo, N, Ni, P, Pb, S, Ti and Zn from 20 sites. Descriptive statistical parameters of soils and leaves chemical properties have been shown, statistical analyses using ANOVA and relationships between chemical elements were carried out, and SOFM models have been constructed. The study revealed that the ordination of individuals and groups of neurons in topological maps of plant and soil chemical properties are similar. The constructed models are related with significantly different contents of elements in plants and soils. These models represent different chemical types of soils and are connected with ordination of types of basaltoides worked out by SOFM model of TAS division. The SOFM appeared to be a useful technique for ordination of ecological data and provides a novel framework for the discovery and forecasting of ecosystem properties.

  20. Properties of dust in the Galactic center region probed by AKARI far-infrared spectral mapping - detection of a dust feature

    CERN Document Server

    Kaneda, H; Onaka, T; Kawada, M; Murakami, N; Nakagawa, T; Okada, Y; Takahashi, H

    2012-01-01

    We investigate the properties of interstellar dust in the Galactic center region toward the Arches and Quintuplet clusters. With the Fourier Transform Spectrometer of the AKARI/Far-Infrared Surveyor, we performed the far-infrared (60 - 140 cm^-1) spectral mapping of an area of about 10' x 10' which includes the two clusters to obtain a low-resolution (R = 1.2 cm^-1) spectrum at every spatial bin of 30" x 30". We derive the spatial variations of dust continuum emission at different wavenumbers, which are compared with those of the [O III] 88 micron (113 cm^-1) emission and the OH 119 micron (84 cm^-1) absorption. The spectral fitting shows that two dust modified blackbody components with temperatures of ~20 K and ~50 K can reproduce most of the continuum spectra. For some spectra, however, we find that there exists a significant excess on top of a modified blackbody continuum around 80 - 90 cm^-1 (110 - 130 microns). The warmer dust component is spatially correlated well with the [O III] emission and hence lik...

  1. Water Features

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The National Flood Hazard Layer (NFHL) data incorporates all Digital Flood Insurance Rate Map(DFIRM) databases published by FEMA, and any Letters Of Map Revision...

  2. Mapping with the Masses: Google Map Maker

    Science.gov (United States)

    Pfund, J.

    2008-12-01

    After some 15,000 years of map making, which saw the innovations of cardinal directions, map projections for a spherical earth, and GIS analysis, many parts of the world still appear as the "Dark Continent" on modern maps. Google Map Maker intends to shine a light on these areas by tapping into the power of the GeoWeb. Google Map Maker is a website which allows you to collaborate with others on one unified map to add, edit, locate, describe, and moderate map features, such as roads, cities, businesses, parks, schools and more, for certain regions of the world using Google Maps imagery. In this session, we will show some examples of how people are mapping with this powerful tool as well as what they are doing with the data. With Google Map Maker, you can become a citizen cartographer and join the global network of users helping to improve the quality of maps and local information in your region of interest. You are invited to map the world with us!

  3. GoMapMan: integration, consolidation and visualization of plant gene annotations within the MapMan ontology.

    Science.gov (United States)

    Ramsak, Živa; Baebler, Špela; Rotter, Ana; Korbar, Matej; Mozetic, Igor; Usadel, Björn; Gruden, Kristina

    2014-01-01

    GoMapMan (http://www.gomapman.org) is an open web-accessible resource for gene functional annotations in the plant sciences. It was developed to facilitate improvement, consolidation and visualization of gene annotations across several plant species. GoMapMan is based on the MapMan ontology, organized in the form of a hierarchical tree of biological concepts, which describe gene functions. Currently, genes of the model species Arabidopsis and three crop species (potato, tomato and rice) are included. The main features of GoMapMan are (i) dynamic and interactive gene product annotation through various curation options; (ii) consolidation of gene annotations for different plant species through the integration of orthologue group information; (iii) traceability of gene ontology changes and annotations; (iv) integration of external knowledge about genes from different public resources; and (v) providing gathered information to high-throughput analysis tools via dynamically generated export files. All of the GoMapMan functionalities are openly available, with the restriction on the curation functions, which require prior registration to ensure traceability of the implemented changes.

  4. Music Emotion Detection Using Hierarchical Sparse Kernel Machines

    Directory of Open Access Journals (Sweden)

    Yu-Hao Chin

    2014-01-01

    Full Text Available For music emotion detection, this paper presents a music emotion verification system based on hierarchical sparse kernel machines. With the proposed system, we intend to verify if a music clip possesses happiness emotion or not. There are two levels in the hierarchical sparse kernel machines. In the first level, a set of acoustical features are extracted, and principle component analysis (PCA is implemented to reduce the dimension. The acoustical features are utilized to generate the first-level decision vector, which is a vector with each element being a significant value of an emotion. The significant values of eight main emotional classes are utilized in this paper. To calculate the significant value of an emotion, we construct its 2-class SVM with calm emotion as the global (non-target side of the SVM. The probability distributions of the adopted acoustical features are calculated and the probability product kernel is applied in the first-level SVMs to obtain first-level decision vector feature. In the second level of the hierarchical system, we merely construct a 2-class relevance vector machine (RVM with happiness as the target side and other emotions as the background side of the RVM. The first-level decision vector is used as the feature with conventional radial basis function kernel. The happiness verification threshold is built on the probability value. In the experimental results, the detection error tradeoff (DET curve shows that the proposed system has a good performance on verifying if a music clip reveals happiness emotion.

  5. A hierarchical view of grounded, embodied, and situated numerical cognition.

    Science.gov (United States)

    Fischer, Martin H

    2012-08-01

    There is much recent interest in the idea that we represent our knowledge together with the sensory and motor features that were activated during its acquisition. This paper reviews the evidence for such "embodiment" in the domain of numerical cognition, a traditional stronghold of abstract theories of knowledge representation. The focus is on spatial-numerical associations, such as the SNARC effect (small numbers are associated with left space, larger numbers with right space). Using empirical evidence from behavioral research, I first describe sensory and motor biases induced by SNARC, thus identifying numbers as embodied concepts. Next, I propose a hierarchical relationship between grounded, embodied, and situated aspects of number knowledge. This hierarchical conceptualization helps to understand the variety of SNARC-related findings and yields testable predictions about numerical cognition. I report several such tests, ranging from cross-cultural comparisons of horizontal and vertical SNARC effects (Shaki and Fischer in J Exp Psychol Hum Percept Perform 38(3):804-809, 2012) to motor cortical activation studies in adults with left- and right-hand counting preferences (Tschentscher et al. in NeuroImage 59:3139-3148, 2012). It is concluded that the diagnostic features for each level of the proposed hierarchical knowledge representation, together with the spatial associations of numbers, make the domain of numerical knowledge an ideal testing ground for embodied cognition research.

  6. Hierarchical structure and biomineralization in cricket tooth

    CERN Document Server

    Xing, Xueqing; Cai, Quan; Mo, Guang; Du, Rong; Chen, Zhongjun; Wu, Zhonghua

    2012-01-01

    Cricket is a truculent insect with stiff and sharp teeth as a fighting weapon. The structure and possible biomineralization of the cricket teeth are always interested. Synchrotron radiation X-ray fluorescence, X-ray diffraction and small angle X-ray scattering techniques were used to probe the element distribution, possible crystalline structures and size distribution of scatterers in cricket teeth. Scanning electron microscope was used to observe the nanoscaled structure. The results demonstrate that Zn is the main heavy element in cricket teeth. The surface of the cricket teeth has a crystalline compound like ZnFe2(AsO4)2(OH)2(H2O)4. While, the interior of the teeth has a crystalline compound like ZnCl2, which is from the biomineralization. The ZnCl2-like biomineral forms nanoscaled microfibrils and their axial direction points at the top of tooth cusp. The microfibrils aggregate random into intermediate filaments, forming a hierarchical structure. A sketch map of the cricket tooth cusp was proposed and a d...

  7. Meso(topoclimatic maps and mapping

    Directory of Open Access Journals (Sweden)

    Ladislav Plánka

    2007-06-01

    Full Text Available The atmospheric characteristics can be studied from many points of view, most often we talk about time and spatial standpoint. Application of time standpoint leads either to different kinds of the synoptic and prognostic maps production, which presents actual state of atmosphere in short time section in the past or in the near future or to the climatic maps production which presents longterm weather regime. Spatial standpoint then differs map works according to natural phenomenon proportions, whereas the scale of their graphic presentation can be different. It depends on production purpose of each work.In the paper there are analysed methods of mapping and climatic maps production, which display longterm regime of chosen atmospheric features. These athmosphere features are formed in interaction with land surface and also have direct influence on people and their activities throughout the country. At the same time they’re influenced by anthropogenic intervention to the landscape.

  8. Hierarchical Control for Smart Grids

    DEFF Research Database (Denmark)

    Trangbæk, K; Bendtsen, Jan Dimon; Stoustrup, Jakob

    2011-01-01

    This paper deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high level MPC controller, a second level of so-called aggregators, which reduces the computational and communication-related load on the high-level control, and a lower level...... of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The objective is to accommodate the load variation on the grid, arising...

  9. Mapping out structural features in clinical care calling for ethical sensitivity: a theoretical approach to promote ethical competence in healthcare personnel and clinical ethical support services (CESS).

    Science.gov (United States)

    Baerøe, Kristine; Norheim, Ole Frithjof

    2011-09-01

    Clinical ethical support services (CESS) represent a multifaceted field of aims, consultancy models, and methodologies. Nevertheless, the overall aim of CESS can be summed up as contributing to healthcare of high ethical standards by improving ethically competent decision-making in clinical healthcare. In order to support clinical care adequately, CESS must pay systematic attention to all real-life ethical issues, including those which do not fall within the 'favourite' ethical issues of the day. In this paper we attempt to capture a comprehensive overview of categories of ethical tensions in clinical care. We present an analytical exposition of ethical structural features in judgement-based clinical care predicated on the assumption of the moral equality of human beings and the assessment of where healthcare contexts pose a challenge to achieving moral equality. The account and the emerging overview is worked out so that it can be easily contextualized with regards to national healthcare systems and specific branches of healthcare, as well as local healthcare institutions. By considering how the account and the overview can be applied to i) improve the ethical competence of healthcare personnel and consultants by broadening their sensitivity to ethical tensions, ii) identify neglected areas for ethical research, and iii) clarify the ethical responsibility of healthcare institutions' leadership, as well as specifying required institutionalized administration, we conclude that the proposed account should be considered useful for CESS.

  10. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    Science.gov (United States)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  11. Research on Deep Web Classification Approach Based on Quantum Self-organization Feature Mapping Network%基于量子自组织神经网络的Deep Web分类方法研究

    Institute of Scientific and Technical Information of China (English)

    张亮; 陆余良; 房珊瑶

    2011-01-01

    In order to solve the problem of Deep Web data sources classification, this paper firstly researched how features in different position could effect the domain of Deep Web interfaces, and proposed a feature selection method RankFW which is based on Ranked weights.Then, a quantum self-organization feature mapping network model was proposed with a classification algorithm.This model relies on the feature vectors and target vectors incoordinately in different phases of training, making a more centralized distribution of winner neurons in competition layer and more obvious boundaries among clusters.Finally, some experiments were designed and carried out on the expanded TEL-8 dataset to test the validity of RankFW and DR-QSOFM.%针对Deep Web数据源主题分类问题,首先研究了不同位置的特征项对Deep Web接口领域分类的影响,提出一种基于分级权重的特征选择方法RankFW;然后提出一种依赖领域知识的量子自组织特征映射神经网络模型DR-QSOFM及其分类算法,该模型在训练的不同阶段对特征向量和目标向量产生不同程度的依赖,使竞争层中获胜神经元的分布更为集中,簇的区域划分更为明显;最后,在扩展后的TEL-8数据集上进行的实验验证了RankFW和DR-QSOFM的有效性.

  12. High-resolution shipboard measurements of phytoplankton: a way forward for enhancing the utility of satellite SST and chlorophyll for mapping microscale features and frontal zones in coastal waters

    Science.gov (United States)

    Jenkins, Christy A.; Goes, Joaquim I.; McKee, Kali; Gomes, Helga do R.; Arnone, Robert; Wang, Menghua; Ondrusek, Michael; Nagamani, P. V.; Preethi Latha, T.; Rao, K. H.; Dadhwal, V. K.

    2016-05-01

    Coastal eddies, frontal zones and microscale oceanographic features are now easily observable from satellite measurements of SST and Chl a. Enhancing the utility of these space-borne measurements for biological productivity, biogeochemical cycling and fisheries investigations will require novel bio-optical methods capable of providing information on the community structure, biomass and photo-physiology of phytoplankton associated on spatial scales that match these features. This study showcases high-resolution in-situ measurements of sea water hydrography (SeaBird CTD®), CDOM (WetLabs ALF®), phytoplankton functional types (PFTs, FlowCAM®), biomass (bbe Moldaenke AlgaeOnlineAnalyzer® and WetLabs ALF®) and phytoplankton photosynthetic competency (mini-FIRe) across microscale features encountered during a recent (Nov. 2014) cruise in support of NOAA's VIIRS ocean color satellite calibration and validation activities. When mapped against binned daily, Level 2 satellite images of Chl a, Kd490 and SST over the cruise period, these high-resolution in-situ data showed great correspondence with the satellite data, but more importantly allowed for identification of PFTs and water types associated with microscale features. Large assemblages of phytoplankton communities comprising of diatoms and diatom-diazotroph associations (DDAs), were found in mesohaline frontal zones. Despite their high biomass, these populations were characterized by low photosynthetic competency, indicative of a bloom at the end of its active growth possibly due to nitrogen depletion in the water. Other prominent PFTs such as Trichodesmium spp., Synechococcus spp. and cryptophytes, were also associated with specific water masses offering the promise and potential that ocean remote sensing reflectance bands when examined in the context of water types also measurable from space, could greatly enhance the utility of satellite measurements for biological oceanographic, carbon cycling and fisheries

  13. Fish Springs National Wildlife Refuge National Vegetation Classification (NVC) map

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — National Vegetation Classification (NVC) map for Fish Springs National Wildlife Refuge. NVC provides a standardized hierarchical approach to classifying vegetation...

  14. Hierarchical model-based interferometric synthetic aperture radar image registration

    Science.gov (United States)

    Wang, Yang; Huang, Haifeng; Dong, Zhen; Wu, Manqing

    2014-01-01

    With the rapid development of spaceborne interferometric synthetic aperture radar technology, classical image registration methods are incompetent for high-efficiency and high-accuracy masses of real data processing. Based on this fact, we propose a new method. This method consists of two steps: coarse registration that is realized by cross-correlation algorithm and fine registration that is realized by hierarchical model-based algorithm. Hierarchical model-based algorithm is a high-efficiency optimization algorithm. The key features of this algorithm are a global model that constrains the overall structure of the motion estimated, a local model that is used in the estimation process, and a coarse-to-fine refinement strategy. Experimental results from different kinds of simulated and real data have confirmed that the proposed method is very fast and has high accuracy. Comparing with a conventional cross-correlation method, the proposed method provides markedly improved performance.

  15. Hierarchical Multiclass Decompositions with Application to Authorship Determination

    CERN Document Server

    El-Yaniv, Ran

    2010-01-01

    This paper is mainly concerned with the question of how to decompose multiclass classification problems into binary subproblems. We extend known Jensen-Shannon bounds on the Bayes risk of binary problems to hierarchical multiclass problems and use these bounds to develop a heuristic procedure for constructing hierarchical multiclass decomposition for multinomials. We test our method and compare it to the well known "all-pairs" decomposition. Our tests are performed using a new authorship determination benchmark test of machine learning authors. The new method consistently outperforms the all-pairs decomposition when the number of classes is small and breaks even on larger multiclass problems. Using both methods, the classification accuracy we achieve, using an SVM over a feature set consisting of both high frequency single tokens and high frequency token-pairs, appears to be exceptionally high compared to known results in authorship determination.

  16. Hierarchical supramolecules and organization using boronic acid building blocks.

    Science.gov (United States)

    Kubo, Yuji; Nishiyabu, Ryuhei; James, Tony D

    2015-02-07

    Current progress on hierarchical supramolecules using boronic acids has been highlighted in this feature article. Boronic acids can participate in "click reactions" with diols and their congeners with dynamic covalent functionality. By comprehensively exploring versatile sequential boronate esterification linkages between plural boronic acid-appended molecules and multiple hydroxyl counterparts, not only versatile supramolecular polymers but also structurally well-defined network nanostructures have been developed. In addition orthogonal interactions such as dative bonds of the boron center with Lewis bases have led to the formation of hierarchical nano/microstructures. Boronate systems have the potential to be used as materials for smart gels, chemosensors, active architectures for electronics, heterogeneous catalysts, chemical-stimulus responsive systems for drug delivery, etc. Here, we fully discuss the feasibility of the structure-directing ability of boronic acids from the standpoint of the generation of new smart materials.

  17. Hierarchy concepts: classification and preparation strategies for zeolite containing materials with hierarchical porosity.

    Science.gov (United States)

    Schwieger, Wilhelm; Machoke, Albert Gonche; Weissenberger, Tobias; Inayat, Amer; Selvam, Thangaraj; Klumpp, Michael; Inayat, Alexandra

    2016-06-13

    'Hierarchy' is a property which can be attributed to a manifold of different immaterial systems, such as ideas, items and organisations or material ones like biological systems within living organisms or artificial, man-made constructions. The property 'hierarchy' is mainly characterised by a certain ordering of individual elements relative to each other, often in combination with a certain degree of branching. Especially mass-flow related systems in the natural environment feature special hierarchically branched patterns. This review is a survey into the world of hierarchical systems with special focus on hierarchically porous zeolite materials. A classification of hierarchical porosity is proposed based on the flow distribution pattern within the respective pore systems. In addition, this review might serve as a toolbox providing several synthetic and post-synthetic strategies to prepare zeolitic or zeolite containing material with tailored hierarchical porosity. Very often, such strategies with their underlying principles were developed for improving the performance of the final materials in different technical applications like adsorptive or catalytic processes. In the present review, besides on the hierarchically porous all-zeolite material, special focus is laid on the preparation of zeolitic composite materials with hierarchical porosity capable to face the demands of industrial application.

  18. Object recognition with hierarchical discriminant saliency networks

    Directory of Open Access Journals (Sweden)

    Sunhyoung eHan

    2014-09-01

    Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

  19. Hierarchical Structures in Hypertext Learning Environments

    NARCIS (Netherlands)

    Bezdan, Eniko; Kester, Liesbeth; Kirschner, Paul A.

    2011-01-01

    Bezdan, E., Kester, L., & Kirschner, P. A. (2011, 9 September). Hierarchical Structures in Hypertext Learning Environments. Presentation for the visit of KU Leuven, Open University, Heerlen, The Netherlands.

  20. How Hierarchical Topics Evolve in Large Text Corpora.

    Science.gov (United States)

    Cui, Weiwei; Liu, Shixia; Wu, Zhuofeng; Wei, Hao

    2014-12-01

    Using a sequence of topic trees to organize documents is a popular way to represent hierarchical and evolving topics in text corpora. However, following evolving topics in the context of topic trees remains difficult for users. To address this issue, we present an interactive visual text analysis approach to allow users to progressively explore and analyze the complex evolutionary patterns of hierarchical topics. The key idea behind our approach is to exploit a tree cut to approximate each tree and allow users to interactively modify the tree cuts based on their interests. In particular, we propose an incremental evolutionary tree cut algorithm with the goal of balancing 1) the fitness of each tree cut and the smoothness between adjacent tree cuts; 2) the historical and new information related to user interests. A time-based visualization is designed to illustrate the evolving topics over time. To preserve the mental map, we develop a stable layout algorithm. As a result, our approach can quickly guide users to progressively gain profound insights into evolving hierarchical topics. We evaluate the effectiveness of the proposed method on Amazon's Mechanical Turk and real-world news data. The results show that users are able to successfully analyze evolving topics in text data.

  1. Power margin improvement for OFDMA-PON using hierarchical modulation.

    Science.gov (United States)

    Cao, Pan; Hu, Xiaofeng; Zhuang, Zhiming; Zhang, Liang; Chang, Qingjiang; Yang, Qi; Hu, Rong; Su, Yikai

    2013-04-08

    We propose and experimentally demonstrate a hierarchical modulation scheme to improve power margin for orthogonal frequency division multiple access-passive optical networks (OFDMA-PONs). In a PON system, under the same launched optical power, optical network units (ONUs) have different power margins due to unequal distribution fiber lengths. The power margin of the PON system is determined by the ONU with the lowest power margin. In our proposed scheme, ONUs with long and short distribution fibers are grouped together, and downstream signals for the paired ONUs are mapped onto the same OFDM subcarriers using hierarchical modulation. In a pair of ONUs, part of the power margin of the ONU with short distribution fiber is re-allocated to the ONU with long distribution fiber. Therefore, the power margin of the ONU with the longest distribution fiber can be increased, leading to the power margin improvement of the PON system. Experimental results show that the hierarchical modulation scheme improves the power margin by 2.7 dB for an OFDMA-PON system, which can be used to support more users or extend transmission distance.

  2. Dynamic Organization of Hierarchical Memories.

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2016-01-01

    In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a "dynamic categorization"; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity.

  3. Dimensionality reduction in nonlinear optical datasets via diffusion mapping: case study of short-pulse second harmonic generation

    Science.gov (United States)

    Romanov, Dmitri; Smith, Stanley; Brady, John; Levis, Robert J.

    2008-02-01

    We have studied the application of the diffusion mapping technique to dimensionality reduction and clustering in multidimensional optical datasets. The combinational (input-output) data were obtained by sampling search spaces related to optimization of a nonlinear physical process, short-pulse second harmonic generation. The diffusion mapping technique hierarchically reduces the dimensionality of the data set and unifies the statistics of input (the pulse shape) and output (the integral output intensity) parameters. The information content of the emerging clustered pattern can be optimized by modifying the parameters of the mapping procedure. The low-dimensional pattern captures essential features of the nonlinear process, based on a finite sampling set. In particular, the apparently parabolic two-dimensional projection of this pattern exhibits regular evolution with the increase of higher-intensity data in the sampling set. The basic shape of the pattern and the evolution are relatively insensitive to the size of the sampling set, as well as to the details of the mapping procedure. Moreover, the experimental data sets and the sets produced numerically on the basis of a theoretical model are mapped into patterns of remarkable similarity (as quantified by the similarity of the related quadratic-form coefficients). The diffusion mapping method is robust and capable of predicting higher-intensity points from a set of low-intensity points. With these attractive features, diffusion mapping stands poised to become a helpful statistical tool for preprocessing analysis of vast and multidimensional combinational optical datasets.

  4. Fabrication of micro/nano hierarchical structures with analysis on the surface mechanics

    Science.gov (United States)

    Jheng, Yu-Sheng; Lee, Yeeu-Chang

    2016-10-01

    Biomimicry refers to the imitation of mechanisms and features found in living creatures using artificial methods. This study used optical lithography, colloidal lithography, and dry etching to mimic the micro/nano hierarchical structures covering the soles of gecko feet. We measured the static contact angle and contact angle hysteresis to reveal the behavior of liquid drops on the hierarchical structures. Pulling tests were also performed to measure the resistance of movement between the hierarchical structures and a testing plate. Our results reveal that hierarchical structures at the micro-/nano-scale are considerably hydrophobic, they provide good flow characteristics, and they generate more contact force than do surfaces with micro-scale cylindrical structures.

  5. Hydrothermal synthesis of self-assembled hierarchical tungsten oxides hollow spheres and their gas sensing properties.

    Science.gov (United States)

    Li, Jinwei; Liu, Xin; Cui, Jiashan; Sun, Jianbo

    2015-05-20

    Hierarchical self-assembled hollow spheres (HS) of tungsten oxide nanosheets have been synthesized via a template-free hydrothermal method. Morphology evolution of the products is determined by the amount of H2C2O4 (oxalic acid) which serves as chelating agent. Structural features of the products were characterized by X-ray diffraction (XRD), and morphology was investigated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). In addition, the porous structure was analyzed using the Brunauer-Emmett-Teller (BET) approach. The synthesis mechanism of the products with self-assembled hierarchical structures was proposed. The NO2 gas sensing properties of self-assembled hierarchical WO3 HS materials were investigated, the gas sensing properties of WO3 synthesized by a variety of formulations were compared, and the possible gas sensing mechanism was discussed. The obvious enhancement of the gas sensing properties was ascribed to the structure of the hierarchical HS.

  6. Hierarchical self-organization of non-cooperating individuals.

    Directory of Open Access Journals (Sweden)

    Tamás Nepusz

    Full Text Available Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks.

  7. Evolutionary optimization of a hierarchical object recognition model.

    Science.gov (United States)

    Schneider, Georg; Wersing, Heiko; Sendhoff, Bernhard; Körner, Edgar

    2005-06-01

    A major problem in designing artificial neural networks is the proper choice of the network architecture. Especially for vision networks classifying three-dimensional (3-D) objects this problem is very challenging, as these networks are necessarily large and therefore the search space for defining the needed networks is of a very high dimensionality. This strongly increases the chances of obtaining only suboptimal structures from standard optimization algorithms. We tackle this problem in two ways. First, we use biologically inspired hierarchical vision models to narrow the space of possible architectures and to reduce the dimensionality of the search space. Second, we employ evolutionary optimization techniques to determine optimal features and nonlinearities of the visual hierarchy. Here, we especially focus on higher order complex features in higher hierarchical stages. We compare two different approaches to perform an evolutionary optimization of these features. In the first setting, we directly code the features into the genome. In the second setting, in analogy to an ontogenetical development process, we suggest the new method of an indirect coding of the features via an unsupervised learning process, which is embedded into the evolutionary optimization. In both cases the processing nonlinearities are encoded directly into the genome and are thus subject to optimization. The fitness of the individuals for the evolutionary selection process is computed by measuring the network classification performance on a benchmark image database. Here, we use a nearest-neighbor classification approach, based on the hierarchical feature output. We compare the found solutions with respect to their ability to generalize. We differentiate between a first- and a second-order generalization. The first-order generalization denotes how well the vision system, after evolutionary optimization of the features and nonlinearities using a database A, can classify previously unseen test

  8. Hierarchical Phased Array Antenna Focal Plane for Cosmic Microwave Background Polarization and Sub-mm Observations

    Science.gov (United States)

    Lee, Adrian

    We propose to develop planar-antenna-coupled superconducting bolometer arrays for observations at sub-millimeter to millimeter wavelengths. Our pixel architecture features a dual-polarization, log-periodic antenna with a 5:1 bandwidth ratio, followed by a filter bank that divides the total bandwidth into several broad photometric bands. We propose to develop an hierarchical phased array of our basic pixel type that gives optimal mapping speed (sensitivity) over a much broader range of frequencies. The advantage of this combination of an intrinsically broadband pixel with hierarchical phase arraying include a combination of greatly reduced focal-plane mass, higher array sensitivity, and a larger number of spectral bands compared to focal-plane designs using conventional single-color pixels. These advantages have the potential to greatly reduce cost and/or increase performance of NASA missions in the sub-millimeter to millimeter bands. For CMB polarization, a wide frequency range of about 30 to 400 GHz is required to subtract galactic foregrounds. As an example, the multichroic architecture we propose could reduce the focal plane mass of the EPIC-IM CMB polarization mission study concept by a factor of 4, with great savings in required cryocooler performance and therefore cost. We have demonstrated the lens-coupled antenna concept in the POLARBEAR groundbased CMB polarization experiment which is now operating in Chile. That experiment uses a single-band planar antenna that gives excellent beam properties and optical efficiency. POLARBEAR recently succeeded in detecting gravitational lensing B-modes in the CMB polarization. In the laboratory, we have measured two octaves of total bandwidth in the log-periodic sinuous antenna. We have built filter banks of 2, 3, and 7 bands with 4, 6, and 14 bolometers per pixel for two linear polarizations. Pixels of this type are slated to be deployed on the ground in POLARBEAR and SPT-3G and proposed to be used on a balloon by EBEX

  9. Diffusion Based Photon Mapping

    DEFF Research Database (Denmark)

    Schjøth, Lars; Sporring, Jon; Fogh Olsen, Ole

    2008-01-01

    . To address this problem, we introduce a photon mapping algorithm based on nonlinear anisotropic diffusion. Our algorithm adapts according to the structure of the photon map such that smoothing occurs along edges and structures and not across. In this way, we preserve important illumination features, while...

  10. Discovering hierarchical structure in normal relational data

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Herlau, Tue; Mørup, Morten

    2014-01-01

    Hierarchical clustering is a widely used tool for structuring and visualizing complex data using similarity. Traditionally, hierarchical clustering is based on local heuristics that do not explicitly provide assessment of the statistical saliency of the extracted hierarchy. We propose a non-param...

  11. Discursive Hierarchical Patterning in Economics Cases

    Science.gov (United States)

    Lung, Jane

    2011-01-01

    This paper attempts to apply Lung's (2008) model of the discursive hierarchical patterning of cases to a closer and more specific study of Economics cases and proposes a model of the distinct discursive hierarchical patterning of the same. It examines a corpus of 150 Economics cases with a view to uncovering the patterns of discourse construction.…

  12. A Model of Hierarchical Key Assignment Scheme

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhigang; ZHAO Jing; XU Maozhi

    2006-01-01

    A model of the hierarchical key assignment scheme is approached in this paper, which can be used with any cryptography algorithm. Besides, the optimal dynamic control property of a hierarchical key assignment scheme will be defined in this paper. Also, our scheme model will meet this property.

  13. Hierarchical Object Parsing from Noisy Point Clouds

    CERN Document Server

    Barbu, Adrian

    2011-01-01

    Object parsing and segmentation from point clouds are challenging tasks because the relevant data is available only as thin structures along object boundaries or other object features and is corrupted by large amounts of noise. One way to handle this kind of data is by employing shape models that can accurately follow the object boundaries. Popular models such as Active Shape and Active Appearance models lack the necessary flexibility for this task. While more flexible models such as Recursive Compositional Models have been proposed, this paper builds on the Active Shape models and makes three contributions. First, it presents a flexible, mid-entropy, hierarchical generative model of object shape and appearance in images. The input data is explained by an object parsing layer, which is a deformation of a hidden PCA shape model with Gaussian prior. Second, it presents a novel efficient inference algorithm that uses a set of informed data-driven proposals to initialize local searches for the hidden variables. T...

  14. Hierarchical Bayesian inference in the visual cortex

    Science.gov (United States)

    Lee, Tai Sing; Mumford, David

    2003-07-01

    Traditional views of visual processing suggest that early visual neurons in areas V1 and V2 are static spatiotemporal filters that extract local features from a visual scene. The extracted information is then channeled through a feedforward chain of modules in successively higher visual areas for further analysis. Recent electrophysiological recordings from early visual neurons in awake behaving monkeys reveal that there are many levels of complexity in the information processing of the early visual cortex, as seen in the long-latency responses of its neurons. These new findings suggest that activity in the early visual cortex is tightly coupled and highly interactive with the rest of the visual system. They lead us to propose a new theoretical setting based on the mathematical framework of hierarchical Bayesian inference for reasoning about the visual system. In this framework, the recurrent feedforward/feedback loops in the cortex serve to integrate top-down contextual priors and bottom-up observations so as to implement concurrent probabilistic inference along the visual hierarchy. We suggest that the algorithms of particle filtering and Bayesian-belief propagation might model these interactive cortical computations. We review some recent neurophysiological evidences that support the plausibility of these ideas. 2003 Optical Society of America

  15. Automatic Construction of Hierarchical Road Networks

    Science.gov (United States)

    Yang, Weiping

    2016-06-01

    This paper describes an automated method of constructing a hierarchical road network given a single dataset, without the presence of thematic attributes. The method is based on a pattern graph which maintains nodes and paths as junctions and through-traffic roads. The hierarchy is formed incrementally in a top-down fashion for highways, ramps, and major roads directly connected to ramps; and bottom-up for the rest of major and minor roads. Through reasoning and analysis, ramps are identified as unique characteristics for recognizing and assembling high speed roads. The method makes distinctions on the types of ramps by articulating their connection patterns with highways. Major and minor roads will be identified by both quantitative and qualitative analysis of spatial properties and by discovering neighbourhood patterns revealed in the data. The result of the method would enrich data description and support comprehensive queries on sorted exit or entry points on highways and their related roads. The enrichment on road network data is important to a high successful rate of feature matching for road networks and to geospatial data integration.

  16. Galaxy formation through hierarchical clustering

    Science.gov (United States)

    White, Simon D. M.; Frenk, Carlos S.

    1991-01-01

    Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

  17. Groups possessing extensive hierarchical decompositions

    CERN Document Server

    Januszkiewicz, T; Leary, I J

    2009-01-01

    Kropholler's class of groups is the smallest class of groups which contains all finite groups and is closed under the following operator: whenever $G$ admits a finite-dimensional contractible $G$-CW-complex in which all stabilizer groups are in the class, then $G$ is itself in the class. Kropholler's class admits a hierarchical structure, i.e., a natural filtration indexed by the ordinals. For example, stage 0 of the hierarchy is the class of all finite groups, and stage 1 contains all groups of finite virtual cohomological dimension. We show that for each countable ordinal $\\alpha$, there is a countable group that is in Kropholler's class which does not appear until the $\\alpha+1$st stage of the hierarchy. Previously this was known only for $\\alpha= 0$, 1 and 2. The groups that we construct contain torsion. We also review the construction of a torsion-free group that lies in the third stage of the hierarchy.

  18. Quantum transport through hierarchical structures.

    Science.gov (United States)

    Boettcher, S; Varghese, C; Novotny, M A

    2011-04-01

    The transport of quantum electrons through hierarchical lattices is of interest because such lattices have some properties of both regular lattices and random systems. We calculate the electron transmission as a function of energy in the tight-binding approximation for two related Hanoi networks. HN3 is a Hanoi network with every site having three bonds. HN5 has additional bonds added to HN3 to make the average number of bonds per site equal to five. We present a renormalization group approach to solve the matrix equation involved in this quantum transport calculation. We observe band gaps in HN3, while no such band gaps are observed in linear networks or in HN5. We provide a detailed scaling analysis near the edges of these band gaps.

  19. Hierarchical networks of scientific journals

    CERN Document Server

    Palla, Gergely; Mones, Enys; Pollner, Péter; Vicsek, Tamás

    2015-01-01

    Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific topics, journals can also be categorised into groups using various metrics. In addition to the set of topics characteristic for a journal, they can also be ranked regarding their relevance from the point of overall influence. One widespread measure is impact factor, but in the present paper we intend to reconstruct a much more detailed description by studying the hierarchical relations between the journals based on citation data. We use a measure related to the notion of m-reaching centrality and find a network which shows the level of influence of a journal from the point of the direction and efficiency with which information spreads through the network. We can also obtain an alternative network using a suitably modified nested hierarchy extraction method applied ...

  20. Adaptive Sampling in Hierarchical Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Knap, J; Barton, N R; Hornung, R D; Arsenlis, A; Becker, R; Jefferson, D R

    2007-07-09

    We propose an adaptive sampling methodology for hierarchical multi-scale simulation. The method utilizes a moving kriging interpolation to significantly reduce the number of evaluations of finer-scale response functions to provide essential constitutive information to a coarser-scale simulation model. The underlying interpolation scheme is unstructured and adaptive to handle the transient nature of a simulation. To handle the dynamic construction and searching of a potentially large set of finer-scale response data, we employ a dynamic metric tree database. We study the performance of our adaptive sampling methodology for a two-level multi-scale model involving a coarse-scale finite element simulation and a finer-scale crystal plasticity based constitutive law.

  1. Multicollinearity in hierarchical linear models.

    Science.gov (United States)

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model.

  2. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Science.gov (United States)

    Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

    2013-11-01

    This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  3. A neural signature of hierarchical reinforcement learning.

    Science.gov (United States)

    Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

    2011-07-28

    Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

  4. Hierarchical Identity-Based Lossy Trapdoor Functions

    CERN Document Server

    Escala, Alex; Libert, Benoit; Rafols, Carla

    2012-01-01

    Lossy trapdoor functions, introduced by Peikert and Waters (STOC'08), have received a lot of attention in the last years, because of their wide range of applications in theoretical cryptography. The notion has been recently extended to the identity-based scenario by Bellare et al. (Eurocrypt'12). We provide one more step in this direction, by considering the notion of hierarchical identity-based lossy trapdoor functions (HIB-LTDFs). Hierarchical identity-based cryptography generalizes identitybased cryptography in the sense that identities are organized in a hierarchical way; a parent identity has more power than its descendants, because it can generate valid secret keys for them. Hierarchical identity-based cryptography has been proved very useful both for practical applications and to establish theoretical relations with other cryptographic primitives. In order to realize HIB-LTDFs, we first build a weakly secure hierarchical predicate encryption scheme. This scheme, which may be of independent interest, is...

  5. Hierarchically nanostructured materials for sustainable environmental applications

    Science.gov (United States)

    Ren, Zheng; Guo, Yanbing; Liu, Cai-Hong; Gao, Pu-Xian

    2013-01-01

    This review presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions, and multiple functionalities toward water remediation, biosensing, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing, and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology. PMID:24790946

  6. Hierarchically Nanostructured Materials for Sustainable Environmental Applications

    Directory of Open Access Journals (Sweden)

    Zheng eRen

    2013-11-01

    Full Text Available This article presents a comprehensive overview of the hierarchical nanostructured materials with either geometry or composition complexity in environmental applications. The hierarchical nanostructures offer advantages of high surface area, synergistic interactions and multiple functionalities towards water remediation, environmental gas sensing and monitoring as well as catalytic gas treatment. Recent advances in synthetic strategies for various hierarchical morphologies such as hollow spheres and urchin-shaped architectures have been reviewed. In addition to the chemical synthesis, the physical mechanisms associated with the materials design and device fabrication have been discussed for each specific application. The development and application of hierarchical complex perovskite oxide nanostructures have also been introduced in photocatalytic water remediation, gas sensing and catalytic converter. Hierarchical nanostructures will open up many possibilities for materials design and device fabrication in environmental chemistry and technology.

  7. Hierarchically Nanoporous Bioactive Glasses for High Efficiency Immobilization of Enzymes

    DEFF Research Database (Denmark)

    He, W.; Min, D.D.; Zhang, X.D.

    2014-01-01

    Bioactive glasses with hierarchical nanoporosity and structures have been heavily involved in immobilization of enzymes. Because of meticulous design and ingenious hierarchical nanostructuration of porosities from yeast cell biotemplates, hierarchically nanostructured porous bioactive glasses can...

  8. Automatic detection of the optimal ejecting direction based on a discrete Gauss map

    Directory of Open Access Journals (Sweden)

    Masatomo Inui

    2014-01-01

    Full Text Available In this paper, the authors propose a system for assisting mold designers of plastic parts. With a CAD model of a part, the system automatically determines the optimal ejecting direction of the part with minimum undercuts. Since plastic parts are generally very thin, many rib features are placed on the inner side of the part to give sufficient structural strength. Our system extracts the rib features from the CAD model of the part, and determines the possible ejecting directions based on the geometric properties of the features. The system then selects the optimal direction with minimum undercuts. Possible ejecting directions are represented as discrete points on a Gauss map. Our new point distribution method for the Gauss map is based on the concept of the architectural geodesic dome. A hierarchical structure is also introduced in the point distribution, with a higher level “rough” Gauss map with rather sparse point distribution and another lower level “fine” Gauss map with much denser point distribution. A system is implemented and computational experiments are performed. Our system requires less than 10 seconds to determine the optimal ejecting direction of a CAD model with more than 1 million polygons.

  9. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    CERN Document Server

    Perotti, Juan Ignacio; Caldarelli, Guido

    2015-01-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical ...

  10. Hierarchical Representation Learning for Kinship Verification.

    Science.gov (United States)

    Kohli, Naman; Vatsa, Mayank; Singh, Richa; Noore, Afzel; Majumdar, Angshul

    2017-01-01

    Kinship verification has a number of applications such as organizing large collections of images and recognizing resemblances among humans. In this paper, first, a human study is conducted to understand the capabilities of human mind and to identify the discriminatory areas of a face that facilitate kinship-cues. The visual stimuli presented to the participants determine their ability to recognize kin relationship using the whole face as well as specific facial regions. The effect of participant gender and age and kin-relation pair of the stimulus is analyzed using quantitative measures such as accuracy, discriminability index d' , and perceptual information entropy. Utilizing the information obtained from the human study, a hierarchical kinship verification via representation learning (KVRL) framework is utilized to learn the representation of different face regions in an unsupervised manner. We propose a novel approach for feature representation termed as filtered contractive deep belief networks (fcDBN). The proposed feature representation encodes relational information present in images using filters and contractive regularization penalty. A compact representation of facial images of kin is extracted as an output from the learned model and a multi-layer neural network is utilized to verify the kin accurately. A new WVU kinship database is created, which consists of multiple images per subject to facilitate kinship verification. The results show that the proposed deep learning framework (KVRL-fcDBN) yields the state-of-the-art kinship verification accuracy on the WVU kinship database and on four existing benchmark data sets. Furthermore, kinship information is used as a soft biometric modality to boost the performance of face verification via product of likelihood ratio and support vector machine based approaches. Using the proposed KVRL-fcDBN framework, an improvement of over 20% is observed in the performance of face verification.

  11. A Mirroring Theorem and its Application to a New Method of Unsupervised Hierarchical Pattern Classification

    CERN Document Server

    Deepthi, Dasika Ratna

    2009-01-01

    In this paper, we prove a crucial theorem called Mirroring Theorem which affirms that given a collection of samples with enough information in it such that it can be classified into classes and subclasses then (i) There exists a mapping which classifies and subclassifies these samples (ii) There exists a hierarchical classifier which can be constructed by using Mirroring Neural Networks (MNNs) in combination with a clustering algorithm that can approximate this mapping. Thus, the proof of the Mirroring theorem provides a theoretical basis for the existence and a practical feasibility of constructing hierarchical classifiers, given the maps. Our proposed Mirroring Theorem can also be considered as an extension to Kolmogrovs theorem in providing a realistic solution for unsupervised classification. The techniques we develop, are general in nature and have led to the construction of learning machines which are (i) tree like in structure, (ii) modular (iii) with each module running on a common algorithm (tandem a...

  12. Continuum damage modeling and simulation of hierarchical dental enamel

    Science.gov (United States)

    Ma, Songyun; Scheider, Ingo; Bargmann, Swantje

    2016-05-01

    Dental enamel exhibits high fracture toughness and stiffness due to a complex hierarchical and graded microstructure, optimally organized from nano- to macro-scale. In this study, a 3D representative volume element (RVE) model is adopted to study the deformation and damage behavior of the fibrous microstructure. A continuum damage mechanics model coupled to hyperelasticity is developed for modeling the initiation and evolution of damage in the mineral fibers as well as protein matrix. Moreover, debonding of the interface between mineral fiber and protein is captured by employing a cohesive zone model. The dependence of the failure mechanism on the aspect ratio of the mineral fibers is investigated. In addition, the effect of the interface strength on the damage behavior is studied with respect to geometric features of enamel. Further, the effect of an initial flaw on the overall mechanical properties is analyzed to understand the superior damage tolerance of dental enamel. The simulation results are validated by comparison to experimental data from micro-cantilever beam testing at two hierarchical levels. The transition of the failure mechanism at different hierarchical levels is also well reproduced in the simulations.

  13. Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

    Science.gov (United States)

    Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

    Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

  14. 基于曲率特征的自主车辆地图匹配定位方法%A Novel Localization Approach for Autonomous Vehicles Based on Map Matching with Curvature Features

    Institute of Scientific and Technical Information of China (English)

    苏奎峰; 邓志东; 黄振

    2012-01-01

    提出了一种新的基于曲率特征的自主车辆地图匹配定位方法,该方法通过计算自主车辆行驶轨迹和参考轨迹的尺度不变曲率积分特征及其相关性进行匹配,可以有效地消除因航迹推算(DR)传感器标定参数偏差和航向角估计偏差而引起的错误匹配问题.文中首先采用扩展卡尔曼滤波器融合惯性测量单元输出、方向盘转角和4个ABS(防抱死刹车系统)传感器测量的轮速,估计自主车辆的位姿状态,并据此从数字地图中选择匹配的候选路段.然后利用本文提出的曲率空间特征地图匹配算法实现路段匹配,并根据曲率和航向角变化确定匹配点,最后将其作为无迹卡尔曼滤波器的观测值更新滤波器,从而实现高精度的位姿估计.现场道路实验结果表明,该法能够有效地实现地图匹配,降低自主车辆DR产生的累积误差,从而能够在GPS(全球定位系统)信号失效情况下实现长距离精确定位.%Using the curvature features, a novel map-matching based localization approach for autonomous vehicles is proposed. By computing the scale-invariant curvature integral and its correlation of autonomous vehicle's historical and reference trajectories for matching, the proposed approach can effectively eliminate the mismatch problem caused by odometer calibration parameters bias and azimuth estimation errors in dead-reckoning (DR). Firstly, we integrate the inertial measurement unit output, steering angles, and wheel speed measurements from four ABS (anti-lock braking system) sensors by using the extended Kalman filter in order to estimate the autonomous vehicle's position and orientation, which are then used to select the candidate matching segments from digital maps. Then, a map matching algorithm based on spatial curvature features is proposed to accomplish segment matching, and matching points are determined according to the changes in curvature and yaw. Finally, these matching points

  15. Triple Hierarchical Variational Inequalities with Constraints of Mixed Equilibria, Variational Inequalities, Convex Minimization, and Hierarchical Fixed Point Problems

    Directory of Open Access Journals (Sweden)

    Lu-Chuan Ceng

    2014-01-01

    Full Text Available We introduce and analyze a hybrid iterative algorithm by virtue of Korpelevich's extragradient method, viscosity approximation method, hybrid steepest-descent method, and averaged mapping approach to the gradient-projection algorithm. It is proven that under appropriate assumptions, the proposed algorithm converges strongly to a common element of the fixed point set of infinitely many nonexpansive mappings, the solution set of finitely many generalized mixed equilibrium problems (GMEPs, the solution set of finitely many variational inequality problems (VIPs, the solution set of general system of variational inequalities (GSVI, and the set of minimizers of convex minimization problem (CMP, which is just a unique solution of a triple hierarchical variational inequality (THVI in a real Hilbert space. In addition, we also consider the application of the proposed algorithm to solve a hierarchical fixed point problem with constraints of finitely many GMEPs, finitely many VIPs, GSVI, and CMP. The results obtained in this paper improve and extend the corresponding results announced by many others.

  16. Retrieval capabilities of hierarchical networks: from Dyson to Hopfield.

    Science.gov (United States)

    Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

    2015-01-16

    We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.

  17. (18)F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

    Science.gov (United States)

    Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

    2017-08-16

    The aims of our study were to find the textural features on (18)F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between (18)F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment (18)F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. (18)F-FDG PET textural features might reflect

  18. Clafer: Unifying Class and Feature Modeling

    DEFF Research Database (Denmark)

    Bąk, Kacper; Diskin, Zinovy; Antkiewicz, Michal;

    2015-01-01

    of hierarchical models whereby properties can be arbitrarily nested in the presence of inheritance and feature modeling constructs. The semantics also enables building consistent automated reasoning support for the language: To date, we implemented three reasoners for Clafer based on Alloy, Z3 SMT, and Choco3 CSP...

  19. Hierarchical clustering techniques for image database organization and summarization

    Science.gov (United States)

    Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    This paper investigates clustering techniques as a method of organizing image databases to support popular visual management functions such as searching, browsing and navigation. Different types of hierarchical agglomerative clustering techniques are studied as a method of organizing features space as well as summarizing image groups by the selection of a few appropriate representatives. Retrieval performance using both single and multiple level hierarchies are experimented with and the algorithms show an interesting relationship between the top k correct retrievals and the number of comparisons required. Some arguments are given to support the use of such cluster-based techniques for managing distributed image databases.

  20. Hierarchical Non-linear Image Registration Integrating Deformable Segmentation

    Institute of Scientific and Technical Information of China (English)

    RAN Xin; QI Fei-hu

    2005-01-01

    A hierarchical non-linear method for image registration was presented, which integrates image segmentation and registration under a variational framework. An improved deformable model is used to simultaneously segment and register feature from multiple images. The objects in the image pair are segmented by evolving a single contour and meanwhile the parameters of affine registration transformation are found out. After that, a contour-constrained elastic registration is applied to register the images correctly. The experimental results indicate that the proposed approach is effective to segment and register medical images.

  1. Metal dendrimers: synthesis of hierarchically stellated nanocrystals by sequential seed-directed overgrowth.

    Science.gov (United States)

    Weiner, Rebecca G; Skrabalak, Sara E

    2015-01-19

    Hierarchically organized structures are prevalent in nature, where such features account for the adhesion properties of gecko feet and the brilliant color variation of butterfly wings. Achieving artificial structures with multiscale features is of interest for metamaterials and biomimetic applications. However, the fabrication of such structures relies heavily on lithographic approaches, although self-assembly routes to superstructures are promising. Sequential seed-directed overgrowth is now demonstrated as a route to metal dendrimers, which are hierarchically branched nanocrystals (NCs) with a three-dimensional order analogous to that of molecular dendrimers. This method was applied to a model Au/Pd NC system; in general, the principle of sequential seed-directed overgrowth should enable the synthesis of new hierarchical inorganic structures with high symmetry.

  2. Concept maps representing knowledge of physics: Connecting structure and content in the context of electricity and magnetism

    Directory of Open Access Journals (Sweden)

    Maija Nousiainen

    2010-09-01

    Full Text Available Many assume that the quality of students’ content knowledge can be connected to certain structural characteristics of concept maps, such as the clustering of concepts around other concepts, cyclical paths between concepts and the hierarchical ordering of concepts. In order to study this relationship, we examine concept maps in electricity and magnetism drawn by physics teacher students and their instructors. The structural analysis of the maps is based on the operationalisation of important structural features (i.e. the features of interest are recognised and made measurable. A quantitative analysis of 43 concept maps was carried out on this basis. The results show that structure and content are closely connected; the structural features of clustering, cyclicity and hierarchy can serve as quantitative measures in characterising structural quality as well as the quality of content knowledge in concept maps. These findings have educational implications in regard to fostering the teacher student’s organisation of knowledge and in monitoring the process of such organisation.

  3. About wave field modeling in hierarchic medium with fractal inclusions

    Science.gov (United States)

    Hachay, Olga; Khachay, Andrey

    2014-05-01

    The processes of oil gaseous deposits outworking are linked with moving of polyphase multicomponent media, which are characterized by no equilibrium and nonlinear rheological features. The real behavior of layered systems is defined as complicated rheology moving liquids and structural morphology of porous media. It is eargently needed to account those factors for substantial description of the filtration processes. Additionally we must account also the synergetic effects. That allows suggesting new methods of control and managing of complicated natural systems, which can research these effects. Thus our research is directed to the layered system, from which we have to outwork oil and which is a complicated hierarchic dynamical system with fractal inclusions. In that paper we suggest the algorithm of modeling of 2-d seismic field distribution in the heterogeneous medium with hierarchic inclusions. Also we can compare the integral 2-D for seismic field in a frame of local hierarchic heterogeneity with a porous inclusion and pure elastic inclusion for the case when the parameter Lame is equal to zero for the inclusions and the layered structure. For that case we can regard the problem for the latitude and longitudinal waves independently. Here we shall analyze the first case. The received results can be used for choosing criterions of joined seismic methods for high complicated media research.If the boundaries of the inclusion of the k rank are fractals, the surface and contour integrals in the integral equations must be changed to repeated fractional integrals of Riman-Liuvill type .Using the developed earlier 3-d method of induction electromagnetic frequency geometric monitoring we showed the opportunity of defining of physical and structural features of hierarchic oil layer structure and estimating of water saturating by crack inclusions. For visualization we had elaborated some algorithms and programs for constructing cross sections for two hierarchic structural

  4. Modeling urban air pollution with optimized hierarchical fuzzy inference system.

    Science.gov (United States)

    Tashayo, Behnam; Alimohammadi, Abbas

    2016-10-01

    Environmental exposure assessments (EEA) and epidemiological studies require urban air pollution models with appropriate spatial and temporal resolutions. Uncertain available data and inflexible models can limit air pollution modeling techniques, particularly in under developing countries. This paper develops a hierarchical fuzzy inference system (HFIS) to model air pollution under different land use, transportation, and meteorological conditions. To improve performance, the system treats the issue as a large-scale and high-dimensional problem and develops the proposed model using a three-step approach. In the first step, a geospatial information system (GIS) and probabilistic methods are used to preprocess the data. In the second step, a hierarchical structure is generated based on the problem. In the third step, the accuracy and complexity of the model are simultaneously optimized with a multiple objective particle swarm optimization (MOPSO) algorithm. We examine the capabilities of the proposed model for predicting daily and annual mean PM2.5 and NO2 and compare the accuracy of the results with representative models from existing literature. The benefits provided by the model features, including probabilistic preprocessing, multi-objective optimization, and hierarchical structure, are precisely evaluated by comparing five different consecutive models in terms of accuracy and complexity criteria. Fivefold cross validation is used to assess the performance of the generated models. The respective average RMSEs and coefficients of determination (R (2)) for the test datasets using proposed model are as follows: daily PM2.5 = (8.13, 0.78), annual mean PM2.5 = (4.96, 0.80), daily NO2 = (5.63, 0.79), and annual mean NO2 = (2.89, 0.83). The obtained results demonstrate that the developed hierarchical fuzzy inference system can be utilized for modeling air pollution in EEA and epidemiological studies.

  5. Depth Map Super-Resolution Based on the Local Structural Features of Color Image%基于彩色图像局部结构特征的深度图超分辨率算法

    Institute of Scientific and Technical Information of China (English)

    杨宇翔; 汪增福

    2013-01-01

      运用飞行时间相机来获取场景深度图像非常方便,但由于硬件的限制,得到的深度图像分辨率非常低,无法满足实际的需要。文中结合同场景的高分辨率彩色图像来制定优化框架,将深度图超分辨率问题转化为最优化问题来求解。具体来说,将彩色图像和深度图像在局部小窗口内具有的近似线性关系通过拉普拉斯矩阵的方式融合到目标函数的正则约束项中,运用彩色图像的局部结构参数模型,将该参数模型融入到正则约束项中对深度图的局部边缘结构提供更进一步的约束,再通过最速下降法有效地求解该优化问题。实验表明文中算法较其它算法无论在视觉效果还是客观评价指标下都可得到更好的结果。%  It is convenient for time of flight camera to get the scene depth image, the resolution of depth image is very low due to limitations of the hardware, which can not meet the actual needs. In this paper, a method is proposed for solving depth map super-resolution problem. With a low resolution depth image as input, a high resolution depth map is recovered by using a registered and potentially high resolution camera image of the same scene. The depth map super-resolution problem is solved by developing an optimization framework. Specifically, the reconstruction constraint is applied to get the data term, and based on the fact that discontinuities in range and coloring tend to co-align, laplacian matrix and local structural features of high resolution camera images are used to construct the regularization term. The experimental results demonstrate that the proposed approach gets high resolution range image in terms of both its spatial resolution and depth precision.

  6. Perception of hierarchical boundaries in music and its modulation by expertise.

    Science.gov (United States)

    Zhang, Jingjing; Jiang, Cunmei; Zhou, Linshu; Yang, Yufang

    2016-10-01

    Hierarchical structure with units of different timescales is a key feature of music. For the perception of such structures, the detection of each boundary is crucial. Here, using electroencephalography (EEG), we explore the perception of hierarchical boundaries in music, and test whether musical expertise modifies such processing. Musicians and non-musicians were presented with musical excerpts containing boundaries at three hierarchical levels, including section, phrase and period boundaries. Non-boundary was chosen as a baseline condition. Recordings from musicians showed CPS (closure positive shift) was evoked at all the three boundaries, and their amplitude increased as the hierarchical level became higher, which suggest that musicians could represent music events at different timescales in a hierarchical way. For non-musicians, the CPS was only elicited at the period boundary and undistinguishable negativities were induced at all the three boundaries. The results indicate that a different and less clear way was used by non-musicians in boundary perception. Our findings reveal, for the first time, an ERP correlate of perceiving hierarchical boundaries in music, and show that the phrasing ability could be enhanced by musical expertise. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Dynamic Self-Organizing Landmark Extraction Method Based on 2-Dimensional Growing Dynamic Self-Organizing Feature Map%基于二维GDSOM的路标动态自组织提取方法

    Institute of Scientific and Technical Information of China (English)

    王作为; 张汝波

    2012-01-01

    A dynamic self-organizing structural feature extraction method is presented based on distance sensor. The procedure consists of three parts; design of active exploration behavior, dimensionality reduction process of spatio-temporal information and self-organizing landmark extraction method. In this paper, active exploration behavior based on follow-wall is designed to obtain high correlative spatio-temporal sequence information. Activity neurons based on variety detection and activation intensity are used to reduce the dimensionality of spatio-temporal sequence. Finally, a method of 2-Dimensional growing dynamic self-organizing feature map (2-Dimensional GDSOM) is proposed to achieve self-organizing extraction and identification of environmental landmarks. The experimental results demonstrate the effectiveness of the method.%提出一种基于距离传感器的结构化特征的动态、自组织提取方法.该方法由3个部分组成:主动感知行为的设计,时空信息的降维处理及路标的自组织提取.设计基于沿墙走的“主动感知行为”来获得高相关性的感知时空序列信息;给出基于变化检测和激活强度的活性神经元来对时空序列信息降维;最后提出一种二维动态增长自组织特征图方法,实现环境路标的自组织提取和识别.实验结果验证该方法的有效性.

  8. 一种增长型自组织特征映射文本聚类方法%A Growing Self-organizing Feature Map Text-based Clustering Method

    Institute of Scientific and Technical Information of China (English)

    张颖超; 李继扬

    2012-01-01

    To build a harmonious and civilized Internet environment, poor text messages on the network to enhance the recognition and response capabilities. Article uses a novel method based on growing self-organizing feature map (GSOFM) and latent semantic indexing (LSI) method for performing a combination of text clustering.The combination of these two algorithms to find global and local features of the model. Experiments under the same conditions used in this new model and a single GSOFM and compared. Experimental results show that: The new combination of two technologies compared with the single GSOFM method improves the accuracy of clustering results, reducing the computation time for performing text clustering network provides a better way.%为建设和谐文明的网络环境,提升对网络不良文本信息的识别和应对能力.文章使用一种新颖的基于增长型自组织特征映射(GSOFM)和潜在语义索引(LSI)相结合方法用于不良文本聚类.这两种算法的结合能够发现全局和局部的模式特点.实验在相同的条件下使用了这种新颖的模式并和单一的GSOFM相比较.实验结果证明:这种新的两种技术的结合与单一的GSOFM方法相比提高了聚类结果的精确性,缩短了计算时问,为网络不良文本聚类提供了一种较好的方法.

  9. Hierarchically structured, nitrogen-doped carbon membranes

    KAUST Repository

    Wang, Hong

    2017-08-03

    The present invention is a structure, method of making and method of use for a novel macroscopic hierarchically structured, nitrogen-doped, nano-porous carbon membrane (HNDCMs) with asymmetric and hierarchical pore architecture that can be produced on a large-scale approach. The unique HNDCM holds great promise as components in separation and advanced carbon devices because they could offer unconventional fluidic transport phenomena on the nanoscale. Overall, the invention set forth herein covers a hierarchically structured, nitrogen-doped carbon membranes and methods of making and using such a membranes.

  10. Hierarchical analysis of acceptable use policies

    Directory of Open Access Journals (Sweden)

    P. A. Laughton

    2008-01-01

    Full Text Available Acceptable use policies (AUPs are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.

  11. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  12. Information Structuring and Retrieval with Topic Maps for Medical E-Learning

    Directory of Open Access Journals (Sweden)

    STANESCU, L.

    2009-10-01

    Full Text Available The paper presents original ways of using topic maps for information structuring and retrieval in medical e-learning domain. The topic map is mainly used for graphical visualization of the MeSH thesaurus containing medical terms. The hierarchical structure of the descriptors from MeSH thesaurus that has also multiple associative and equivalence relationships between medical terms can be properly visualized in this way. The topic map is built and populated using an original algorithm, by mapping an xml file that can be downloaded for free to an xtm file that contains the topic map. The paper also presents how to use the topic map for semantic querying of a multimedia database with medical images that are accompanied by diagnosis and treatment as important information. For retrieving the interest information for student, this access path can be combined with another modern solution: the content-based visual query on the multimedia medical database using primitive features like color and texture.

  13. Hierarchical Data Formats (HDF) Update

    Science.gov (United States)

    Pourmal, Elena

    2017-01-01

    In this presentation, we will talk about the latest releases of HDF4 and HDF5 software and tools, new features available in HDF5, and roadmap for the HDF software. We will also solicit feedback from the users of HDF data and HDF application developers on new features and new tools. The talk will cover: Difference between 1.8 and 1.10 releases and how and when to move to the latest release Features of the recent HDF5 1.8.19, 1.10.1 and HDF 4.2.13 Overview of HDF View 3.0 and other enhancements to tools Supported compilers and systems Open discussion of new requirements and wish list of the HDF features Compression library for interoperability with h5py and Pandas and better floating-point data compression.

  14. Evaluation of the Coastal Features Mapping System for Shoreline Mapping

    Science.gov (United States)

    1991-09-01

    participating in the report preparation included: Ms. Karen Pitchford , Atlantic Research Corporation, who provided technical assistance and helped...40 Tanner, William F., 1978. "Standards for Measuring Shoreline Change", Proceedings of a Workshop, Florida State Univ., 85 pg. Wolf, Paul R., 1983

  15. Object recognition with hierarchical discriminant saliency networks.

    Science.gov (United States)

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  16. Hierarchical Route Optimization By Using Memetic Algorithm In A Mobile Networks

    Directory of Open Access Journals (Sweden)

    K .K. Gautam

    2011-02-01

    Full Text Available The networks Mobility (NEMO Protocol is a way of managing the mobility of an entire network, and mobile internet protocol is the basic solution for networks Mobility. A hierarchical route optimization system for mobile network is proposed to solve management of hierarchical route optimization problems. In present paper we study hierarchical Route Optimization scheme using memetic algorithm(HROSMA The concept of optimization- finding the extreme of a function that maps candidate ‘solution’ to scalar values of ‘quality’ – is an extremely general and useful idea. For solving this problem, we use a few salient adaptations, and we also extend HROSMA perform routing between the mobile networks.

  17. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems

    CERN Document Server

    Rosvall, M

    2010-01-01

    To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation that reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network, the optimal number of levels and modular partition at each level, with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines:...

  18. UV-assisted capillary force lithography for engineering biomimetic multiscale hierarchical structures: From lotus leaf to gecko foot hairs

    KAUST Repository

    Jeong, Hoon Eui

    2009-01-01

    This feature article provides an overview of the recently developed two-step UV-assisted capillary force lithography and its application to fabricating well-defined micro/nanoscale hierarchical structures. This method utilizes an oxygen inhibition effect in the course of UV irradiation curing and a two-step moulding process, to form multiscale hierarchical or suspended nanobridge structures in a rapid and reproducible manner. After a brief description of the fabrication principles, several examples of the two-step UV-assisted moulding technique are presented. In addition, emerging applications of the multiscale hierarchical structures are briefly described. © The Royal Society of Chemistry 2009.

  19. Image meshing via hierarchical optimization

    Institute of Scientific and Technical Information of China (English)

    Hao XIE; Ruo-feng TONG‡

    2016-01-01

    Vector graphic, as a kind of geometric representation of raster images, has many advantages, e.g., defi nition independence and editing facility. A popular way to convert raster images into vector graphics is image meshing, the aim of which is to fi nd a mesh to represent an image as faithfully as possible. For traditional meshing algorithms, the crux of the problem resides mainly in the high non-linearity and non-smoothness of the objective, which makes it difficult to fi nd a desirable optimal solution. To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from coarser levels to fi ner ones, providing initialization for each level with its coarser ascent. To further simplify the problem, the original non-convex problem is converted to a linear least squares one, and thus becomes convex, which makes the problem much easier to solve. A dictionary learning framework is used to combine geometry and topology elegantly. Then an alternating scheme is employed to solve both parts. Experiments show that our algorithm runs fast and achieves better results than existing ones for most images.

  20. Image meshing via hierarchical optimization*

    Institute of Scientific and Technical Information of China (English)

    Hao XIE; Ruo-feng TONGS

    2016-01-01

    Vector graphic, as a kind of geometric representation of raster images, has many advantages, e.g., definition independence and editing facility. A popular way to convert raster images into vector graphics is image meshing, the aim of which is to find a mesh to represent an image as faithfully as possible. For traditional meshing algorithms, the crux of the problem resides mainly in the high non-linearity and non-smoothness of the objective, which makes it difficult to find a desirable optimal solution. To ameliorate this situation, we present a hierarchical optimization algorithm solving the problem from coarser levels to finer ones, providing initialization for each level with its coarser ascent. To further simplify the problem, the original non-convex problem is converted to a linear least squares one, and thus becomes convex, which makes the problem much easier to solve. A dictionary learning framework is used to combine geometry and topology elegantly. Then an alternating scheme is employed to solve both parts. Experiments show that our algorithm runs fast and achieves better results than existing ones for most images.

  1. Hierarchical Bayes Ensemble Kalman Filtering

    CERN Document Server

    Tsyrulnikov, Michael

    2015-01-01

    Ensemble Kalman filtering (EnKF), when applied to high-dimensional systems, suffers from an inevitably small affordable ensemble size, which results in poor estimates of the background error covariance matrix ${\\bf B}$. The common remedy is a kind of regularization, usually an ad-hoc spatial covariance localization (tapering) combined with artificial covariance inflation. Instead of using an ad-hoc regularization, we adopt the idea by Myrseth and Omre (2010) and explicitly admit that the ${\\bf B}$ matrix is unknown and random and estimate it along with the state (${\\bf x}$) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components ${\\bf P}$ and ${\\bf Q}$ of the ${\\bf B}$ matrix into the extended control vector $({\\bf x},{\\bf P},{\\bf Q})$. Similarly, we break the traditional backgrou...

  2. A Novel Hierarchical Semi-centralized Telemedicine Network Architecture Proposition for Bangladesh

    DEFF Research Database (Denmark)

    Choudhury, Samiul; Peterson, Carrie Beth; Kyriazakos, Sofoklis

    2011-01-01

    where there are extreme paucities of efficient healthcare professionals and equipments, specifically in the rural areas. In this paper a novel, hierarchical and semi-centralized telemedicine network architecture has been proposed holisti-cally focusing on the rural underdeveloped areas of Bangladesh...... of Bangladesh. Finally, some features and services associated with the model have also been proposed which are pragmatic and easily implementable....

  3. Facile synthesis of magnetic hierarchical copper silicate hollow nanotubes for efficient adsorption and removal of hemoglobin.

    Science.gov (United States)

    Zhang, Min; Wang, Baoyu; Zhang, Yanwei; Li, Weizhen; Gan, Wenjun; Xu, Jingli

    2016-01-21

    This study reports the fabrication of magnetic copper silicate hierarchical hollow nanotubes, which are featured by a tailored complex wall structure and high surface area. Moreover, they exhibit excellent performance as an easily recycled adsorbent for protein separation. Particularly, this strategy can be extended as a general method to prepare other magnetic metal silicate hollow nanotubes.

  4. Hierarchical ensemble of background models for PTZ-based video surveillance.

    Science.gov (United States)

    Liu, Ning; Wu, Hefeng; Lin, Liang

    2015-01-01

    In this paper, we study a novel hierarchical background model for intelligent video surveillance with the pan-tilt-zoom (PTZ) camera, and give rise to an integrated system consisting of three key components: background modeling, observed frame registration, and object tracking. First, we build the hierarchical background model by separating the full range of continuous focal lengths of a PTZ camera into several discrete levels and then partitioning the wide scene at each level into many partial fixed scenes. In this way, the wide scenes captured by a PTZ camera through rotation and zoom are represented by a hierarchical collection of partial fixed scenes. A new robust feature is presented for background modeling of each partial scene. Second, we locate the partial scenes corresponding to the observed frame in the hierarchical background model. Frame registration is then achieved by feature descriptor matching via fast approximate nearest neighbor search. Afterwards, foreground objects can be detected using background subtraction. Last, we configure the hierarchical background model into a framework to facilitate existing object tracking algorithms under the PTZ camera. Foreground extraction is used to assist tracking an object of interest. The tracking outputs are fed back to the PTZ controller for adjusting the camera properly so as to maintain the tracked object in the image plane. We apply our system on several challenging scenarios and achieve promising results.

  5. Mobile Robot Hierarchical Simultaneous Localization and Mapping Based on Active Loop Closure Constraint%基于主动环形闭合约束的移动机器人分层同时定位和地图创建

    Institute of Scientific and Technical Information of China (English)

    黄庆成; 洪炳熔; 厉茂海; 罗荣华

    2007-01-01

    基于Rao-Blackwellized粒子滤波器提出了一种基于主动闭环策略的移动机器人分层同时定位和地图创建(simultaneous localization and mapping,SLAM)方法,基于信息熵的主动闭环策略同时考虑机器人位姿和地图的不确定性;局部几何特征地图之间的相对关系通过一致性算法估计,并通过环形闭合约束的最小化过程回溯修正.在仅有单目视觉和里程计的基础上,建立了鲁棒的感知模型;通过有效的尺度不变特征变换(scale invariant feature transform,SIFT)方法提取环境特征,基于KD-Tree的最近邻搜索算法实现特征匹配.实际实验表明该方法为实现SLAM提供了一种有效可靠的途径.

  6. Sparsey™: event recognition via deep hierarchical sparse distributed codes.

    Science.gov (United States)

    Rinkus, Gerard J

    2014-01-01

    The visual cortex's hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally) and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes) in each representational field (which we equate with the cortical macrocolumn, "mac"), at each level. In localism, each represented feature/concept/event (hereinafter "item") is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC) in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac's units. The SDCs of different items can overlap and the size of overlap between items can be used to represent their similarity. The difference between localism and SDC is crucial because SDC allows the two essential operations of associative memory, storing a new item and retrieving the best-matching stored item, to be done in fixed time for the life of the model. Since the model's core algorithm, which does both storage and retrieval (inference), makes a single pass over all macs on each time step, the overall model's storage/retrieval operation is also fixed-time, a criterion we consider essential for scalability to the huge ("Big Data") problems. A 2010 paper described a nonhierarchical version of this model in the context of purely spatial pattern processing. Here, we elaborate a fully hierarchical model (arbitrary numbers of levels and macs per level), describing novel model principles like progressive critical periods, dynamic modulation of principal cells' activation functions based on a mac-level familiarity measure, representation of multiple simultaneously active hypotheses, a novel method of time warp invariant recognition, and we report results showing learning/recognition of spatiotemporal patterns.

  7. An Automatic Hierarchical Delay Analysis Tool

    Institute of Scientific and Technical Information of China (English)

    FaridMheir-El-Saadi; BozenaKaminska

    1994-01-01

    The performance analysis of VLSI integrated circuits(ICs) with flat tools is slow and even sometimes impossible to complete.Some hierarchical tools have been developed to speed up the analysis of these large ICs.However,these hierarchical tools suffer from a poor interaction with the CAD database and poorly automatized operations.We introduce a general hierarchical framework for performance analysis to solve these problems.The circuit analysis is automatic under the proposed framework.Information that has been automatically abstracted in the hierarchy is kept in database properties along with the topological information.A limited software implementation of the framework,PREDICT,has also been developed to analyze the delay performance.Experimental results show that hierarchical analysis CPU time and memory requirements are low if heuristics are used during the abstraction process.

  8. Packaging glass with hierarchically nanostructured surface

    KAUST Repository

    He, Jr-Hau

    2017-08-03

    An optical device includes an active region and packaging glass located on top of the active region. A top surface of the packaging glass includes hierarchical nanostructures comprised of honeycombed nanowalls (HNWs) and nanorod (NR) structures extending from the HNWs.

  9. Generation of hierarchically correlated multivariate symbolic sequences

    CERN Document Server

    Tumminello, Mi; Mantegna, R N

    2008-01-01

    We introduce an algorithm to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities. The target hierarchical structure of similarities is arbitrary, for instance the one obtained by some hierarchical clustering procedure as applied to an empirical matrix of Hamming distances. The algorithm can be interpreted as the finite alphabet equivalent of the recently introduced hierarchically nested factor model (M. Tumminello et al. EPL 78 (3) 30006 (2007)). The algorithm is based on a generating mechanism that is different from the one used in the mutation rate approach. We apply the proposed methodology for investigating the relationship between the bootstrap value associated with a node of a phylogeny and the probability of finding that node in the true phylogeny.

  10. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...

  11. HIERARCHICAL ORGANIZATION OF INFORMATION, IN RELATIONAL DATABASES

    Directory of Open Access Journals (Sweden)

    Demian Horia

    2008-05-01

    Full Text Available In this paper I will present different types of representation, of hierarchical information inside a relational database. I also will compare them to find the best organization for specific scenarios.

  12. Hierarchical Network Design Using Simulated Annealing

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Clausen, Jens

    2002-01-01

    The hierarchical network problem is the problem of finding the least cost network, with nodes divided into groups, edges connecting nodes in each groups and groups ordered in a hierarchy. The idea of hierarchical networks comes from telecommunication networks where hierarchies exist. Hierarchical...... networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub......-algorithm uses a construction algorithm to determine edges and route the demand. Performance for different versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to find solutions of reasonable quality in approximately 1 hour for networks with 100 nodes....

  13. When to Use Hierarchical Linear Modeling

    National Research Council Canada - National Science Library

    Veronika Huta

    2014-01-01

    Previous publications on hierarchical linear modeling (HLM) have provided guidance on how to perform the analysis, yet there is relatively little information on two questions that arise even before analysis...

  14. An introduction to hierarchical linear modeling

    National Research Council Canada - National Science Library

    Woltman, Heather; Feldstain, Andrea; MacKay, J. Christine; Rocchi, Meredith

    2012-01-01

    This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis...

  15. Conservation Laws in the Hierarchical Model

    NARCIS (Netherlands)

    Beijeren, H. van; Gallavotti, G.; Knops, H.

    1974-01-01

    An exposition of the renormalization-group equations for the hierarchical model is given. Attention is drawn to some properties of the spin distribution functions which are conserved under the action of the renormalization group.

  16. Hierarchical DSE for multi-ASIP platforms

    DEFF Research Database (Denmark)

    Micconi, Laura; Corvino, Rosilde; Gangadharan, Deepak;

    2013-01-01

    This work proposes a hierarchical Design Space Exploration (DSE) for the design of multi-processor platforms targeted to specific applications with strict timing and area constraints. In particular, it considers platforms integrating multiple Application Specific Instruction Set Processors (ASIPs...

  17. Nanodesigning of Hierarchical Multifunctional Ceramics

    Science.gov (United States)

    1993-09-28

    conditions by reacting nanosized titanium oxide or titanium alkoxides with a solution of barium hydroxide. The powders produced by this approach range in...14 1.2.5 Density of Colloidal Aggregated Network Near a Hard Wall ...... 15 1.2.6 Synthesis of Lead- Zirconium -Titanate (Pb(Zr0.5 2Tio.4 8)0 3 ) (PZT...6 Figure 4: Spinnability map for poly(ethylene oxide )-based a-A120 3 suspensions ......... 9 Figure 5: High

  18. A GIS-Enabled, Michigan-Specific, Hierarchical Groundwater Modeling and Visualization System

    Science.gov (United States)

    Liu, Q.; Li, S.; Mandle, R.; Simard, A.; Fisher, B.; Brown, E.; Ross, S.

    2005-12-01

    Efficient management of groundwater resources relies on a comprehensive database that represents the characteristics of the natural groundwater system as well as analysis and modeling tools to describe the impacts of decision alternatives. Many agencies in Michigan have spent several years compiling expensive and comprehensive surface water and groundwater inventories and other related spatial data that describe their respective areas of responsibility. However, most often this wealth of descriptive data has only been utilized for basic mapping purposes. The benefits from analyzing these data, using GIS analysis functions or externally developed analysis models or programs, has yet to be systematically realized. In this talk, we present a comprehensive software environment that allows Michigan groundwater resources managers and frontline professionals to make more effective use of the available data and improve their ability to manage and protect groundwater resources, address potential conflicts, design cleanup schemes, and prioritize investigation activities. In particular, we take advantage of the Interactive Ground Water (IGW) modeling system and convert it to a customized software environment specifically for analyzing, modeling, and visualizing the Michigan statewide groundwater database. The resulting Michigan IGW modeling system (IGW-M) is completely window-based, fully interactive, and seamlessly integrated with a GIS mapping engine. The system operates in real-time (on the fly) providing dynamic, hierarchical mapping, modeling, spatial analysis, and visualization. Specifically, IGW-M allows water resources and environmental professionals in Michigan to: * Access and utilize the extensive data from the statewide groundwater database, interactively manipulate GIS objects, and display and query the associated data and attributes; * Analyze and model the statewide groundwater database, interactively convert GIS objects into numerical model features

  19. Hierarchical organization versus self-organization

    OpenAIRE

    Busseniers, Evo

    2014-01-01

    In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

  20. Hierarchical decision making for flood risk reduction

    DEFF Research Database (Denmark)

    Custer, Rocco; Nishijima, Kazuyoshi

    2013-01-01

    . In current practice, structures are often optimized individually without considering benefits of having a hierarchy of protection structures. It is here argued, that the joint consideration of hierarchically integrated protection structures is beneficial. A hierarchical decision model is utilized to analyze...... and compare the benefit of large upstream protection structures and local downstream protection structures in regard to epistemic uncertainty parameters. Results suggest that epistemic uncertainty influences the outcome of the decision model and that, depending on the magnitude of epistemic uncertainty...