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Sample records for hierarchical ecosystem classification

  1. 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.

  2. Columbia River Estuary Ecosystem Classification Ecosystem Complex

    Science.gov (United States)

    Cannon, Charles M.; Ramirez, Mary F.; Heatwole, Danelle W.; Burke, Jennifer L.; Simenstad, Charles A.; O'Connor, Jim E.; Marcoe, Keith Marcoe

    2012-01-01

    Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these processes will aid in prioritization of restoration efforts. This hierarchical Columbia River Estuary Ecosystem Classification (henceforth "Classification") of the Columbia River estuary is a spatial database of the tidally-influenced reaches of the lower Columbia River, the tidally affected parts of its tributaries, and the landforms that make up their floodplains for the 230 kilometers between the Pacific Ocean and Bonneville Dam. This work is a collaborative effort between University of Washington School of Aquatic and Fishery Sciences (henceforth "UW"), U.S. Geological Survey (henceforth "USGS"), and the Lower Columbia Estuary Partnership (henceforth "EP"). Consideration of geomorphologic processes will improve the understanding of controlling physical factors that drive ecosystem evolution along the tidal Columbia River. The Classification is organized around six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. For Levels 4 and 5, we mapped landforms within the Holocene floodplain primarily by visual interpretation of Light Detection and Ranging (LiDAR) topography supplemented with aerial photographs, Natural Resources Conservation Service (NRCS) soils data, and historical maps. Mapped landforms are classified as to their current geomorphic function, the inferred process regime that formed them, and anthropogenic modification. Channels were classified primarily by a set of depth-based rules and geometric relationships. Classification Level 5 floodplain landforms ("geomorphic catenae") were further classified based on multivariate analysis of land-cover within the mapped landform area and attributed as "sub

  3. Columbia River Estuary Ecosystem Classification Ecosystem Complex

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these...

  4. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe...... an instance are conditionally independent given the class of that instance. When this assumption is violated (which is often the case in practice) it can reduce classification accuracy due to “information double-counting” and interaction omission. In this paper we focus on a relatively new set of models......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

  5. A hierarchical classification scheme of psoriasis images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    the normal skin in the second stage. These tools are the Expectation-Maximization Algorithm, the quadratic discrimination function and a classification window of optimal size. Extrapolation of classification parameters of a given image to other images of the set is evaluated by means of Cohen's Kappa......A two-stage hierarchical classification scheme of psoriasis lesion images is proposed. These images are basically composed of three classes: normal skin, lesion and background. The scheme combines conventional tools to separate the skin from the background in the first stage, and the lesion from...

  6. Columbia River Estuary Ecosystem Classification Hydrogeomorphic Reach

    Science.gov (United States)

    Cannon, Charles M.; Ramirez, Mary F.; Heatwole, Danelle W.; Burke, Jennifer L.; Simenstad, Charles A.; O'Connor, Jim E.; Marcoe, Keith

    2012-01-01

    Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these processes will aid in prioritization of restoration efforts. This hierarchical Columbia River Estuary Ecosystem Classification (henceforth "Classification") of the Columbia River estuary is a spatial database of the tidally-influenced reaches of the lower Columbia River, the tidally affected parts of its tributaries, and the landforms that make up their floodplains for the 230 kilometers between the Pacific Ocean and Bonneville Dam. This work is a collaborative effort between University of Washington School of Aquatic and Fishery Sciences (henceforth "UW"), U.S. Geological Survey (henceforth "USGS"), and the Lower Columbia Estuary Partnership (henceforth "EP"). Consideration of geomorphologic processes will improve the understanding of controlling physical factors that drive ecosystem evolution along the tidal Columbia River. The Classification is organized around six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. For Levels 4 and 5, we mapped landforms within the Holocene floodplain primarily by visual interpretation of Light Detection and Ranging (LiDAR) topography supplemented with aerial photographs, Natural Resources Conservation Service (NRCS) soils data, and historical maps. Mapped landforms are classified as to their current geomorphic function, the inferred process regime that formed them, and anthropogenic modification. Channels were classified primarily by a set of depth-based rules and geometric relationships. Classification Level 5 floodplain landforms ("geomorphic catenae") were further classified based on multivariate analysis of land-cover within the mapped landform area and attributed as "sub

  7. Columbia River Estuary Ecosystem Classification Geomorphic Catena

    Science.gov (United States)

    Cannon, Charles M.; Ramirez, Mary F.; Heatwole, Danelle W.; Burke, Jennifer L.; Simenstad, Charles A.; O'Connor, Jim E.; Marcoe, Keith

    2012-01-01

    Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these processes will aid in prioritization of restoration efforts. This hierarchical Columbia River Estuary Ecosystem Classification (henceforth "Classification") of the Columbia River estuary is a spatial database of the tidally-influenced reaches of the lower Columbia River, the tidally affected parts of its tributaries, and the landforms that make up their floodplains for the 230 kilometers between the Pacific Ocean and Bonneville Dam. This work is a collaborative effort between University of Washington School of Aquatic and Fishery Sciences (henceforth "UW"), U.S. Geological Survey (henceforth "USGS"), and the Lower Columbia Estuary Partnership (henceforth "EP"). Consideration of geomorphologic processes will improve the understanding of controlling physical factors that drive ecosystem evolution along the tidal Columbia River. The Classification is organized around six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. For Levels 4 and 5, we mapped landforms within the Holocene floodplain primarily by visual interpretation of Light Detection and Ranging (LiDAR) topography supplemented with aerial photographs, Natural Resources Conservation Service (NRCS) soils data, and historical maps. Mapped landforms are classified as to their current geomorphic function, the inferred process regime that formed them, and anthropogenic modification. Channels were classified primarily by a set of depth-based rules and geometric relationships. Classification Level 5 floodplain landforms ("geomorphic catenae") were further classified based on multivariate analysis of land-cover within the mapped landform area and attributed as "sub

  8. Columbia River Estuary Ecosystem Classification Hydrogeomorphic Reach

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these...

  9. Columbia River Estuary Ecosystem Classification Geomorphic Catena

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these...

  10. Columbia River Estuary Ecosystem Classification Cultural Features

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Estuarine ecosystems are controlled by a variety of processes that operate at multiple spatial and temporal scales. Understanding the hierarchical nature of these...

  11. Hierarchical Classification of Chinese Documents Based on N-grams

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    We explore the techniques of utilizing N-gram informatio n tocategorize Chinese text documents hierarchically so that the classifier can shak e off the burden of large dictionaries and complex segmentation processing, and subsequently be domain and time independent. A hierarchical Chinese text classif ier is implemented. Experimental results show that hierarchically classifying Chinese text documents based N-grams can achieve satisfactory performance and outperforms the other traditional Chinese text classifiers.

  12. A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification

    Directory of Open Access Journals (Sweden)

    Marín Ignacio

    2007-11-01

    Full Text Available Abstract Background Classification procedures are widely used in phylogenetic inference, the analysis of expression profiles, the study of biological networks, etc. Many algorithms have been proposed to establish the similarity between two different classifications of the same elements. However, methods to determine significant coincidences between hierarchical and non-hierarchical partitions are still poorly developed, in spite of the fact that the search for such coincidences is implicit in many analyses of massive data. Results We describe a novel strategy to compare a hierarchical and a dichotomic non-hierarchical classification of elements, in order to find clusters in a hierarchical tree in which elements of a given "flat" partition are overrepresented. The key improvement of our strategy respect to previous methods is using permutation analyses of ranked clusters to determine whether regions of the dendrograms present a significant enrichment. We show that this method is more sensitive than previously developed strategies and how it can be applied to several real cases, including microarray and interactome data. Particularly, we use it to compare a hierarchical representation of the yeast mitochondrial interactome and a catalogue of known mitochondrial protein complexes, demonstrating a high level of congruence between those two classifications. We also discuss extensions of this method to other cases which are conceptually related. Conclusion Our method is highly sensitive and outperforms previously described strategies. A PERL script that implements it is available at http://www.uv.es/~genomica/treetracker.

  13. Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

    Science.gov (United States)

    Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

    2016-02-01

    Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  14. An Experiment in Automatic Hierarchical Document Classification.

    Science.gov (United States)

    Garland, Kathleen

    1983-01-01

    Describes method of automatic document classification in which documents classed as QA by Library of Congress classification system were clustered at six thresholds by keyword using single link technique. Automatically generated clusters were compared to Library of Congress subclasses, and partial classified hierarchy was formed. Twelve references…

  15. GPCRTree: online hierarchical classification of GPCR function

    Directory of Open Access Journals (Sweden)

    Timmis Jon

    2008-08-01

    Full Text Available Abstract Background G protein-coupled receptors (GPCRs play important physiological roles transducing extracellular signals into intracellular responses. Approximately 50% of all marketed drugs target a GPCR. There remains considerable interest in effectively predicting the function of a GPCR from its primary sequence. Findings Using techniques drawn from data mining and proteochemometrics, an alignment-free approach to GPCR classification has been devised. It uses a simple representation of a protein's physical properties. GPCRTree, a publicly-available internet server, implements an algorithm that classifies GPCRs at the class, sub-family and sub-subfamily level. Conclusion A selective top-down classifier was developed which assigns sequences within a GPCR hierarchy. Compared to other publicly available GPCR prediction servers, GPCRTree is considerably more accurate at every level of classification. The server has been available online since March 2008 at URL: http://igrid-ext.cryst.bbk.ac.uk/gpcrtree/.

  16. Hierarchical discriminant manifold learning for dimensionality reduction and image classification

    Science.gov (United States)

    Chen, Weihai; Zhao, Changchen; Ding, Kai; Wu, Xingming; Chen, Peter C. Y.

    2015-09-01

    In the field of image classification, it has been a trend that in order to deliver a reliable classification performance, the feature extraction model becomes increasingly more complicated, leading to a high dimensionality of image representations. This, in turn, demands greater computation resources for image classification. Thus, it is desirable to apply dimensionality reduction (DR) methods for image classification. It is necessary to apply DR methods to relieve the computational burden as well as to improve the classification accuracy. However, traditional DR methods are not compatible with modern feature extraction methods. A framework that combines manifold learning based DR and feature extraction in a deeper way for image classification is proposed. A multiscale cell representation is extracted from the spatial pyramid to satisfy the locality constraints for a manifold learning method. A spectral weighted mean filtering is proposed to eliminate noise in the feature space. A hierarchical discriminant manifold learning is proposed which incorporates both category label and image scale information to guide the DR process. Finally, the image representation is generated by concatenating dimensionality reduced cell representations from the same image. Extensive experiments are conducted to test the proposed algorithm on both scene and object recognition datasets in comparison with several well-established and state-of-the-art methods with respect to classification precision and computational time. The results verify the effectiveness of incorporating manifold learning in the feature extraction procedure and imply that the multiscale cell representations may be distributed on a manifold.

  17. Hierarchical Maximum Margin Learning for Multi-Class Classification

    CERN Document Server

    Yang, Jian-Bo

    2012-01-01

    Due to myriads of classes, designing accurate and efficient classifiers becomes very challenging for multi-class classification. Recent research has shown that class structure learning can greatly facilitate multi-class learning. In this paper, we propose a novel method to learn the class structure for multi-class classification problems. The class structure is assumed to be a binary hierarchical tree. To learn such a tree, we propose a maximum separating margin method to determine the child nodes of any internal node. The proposed method ensures that two classgroups represented by any two sibling nodes are most separable. In the experiments, we evaluate the accuracy and efficiency of the proposed method over other multi-class classification methods on real world large-scale problems. The results show that the proposed method outperforms benchmark methods in terms of accuracy for most datasets and performs comparably with other class structure learning methods in terms of efficiency for all datasets.

  18. 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.

  19. 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.

  20. Hierarchical Real-time Network Traffic Classification Based on ECOC

    Directory of Open Access Journals (Sweden)

    Yaou Zhao

    2013-09-01

    Full Text Available Classification of network traffic is basic and essential for manynetwork researches and managements. With the rapid development ofpeer-to-peer (P2P application using dynamic port disguisingtechniques and encryption to avoid detection, port-based and simplepayload-based network traffic classification methods were diminished.An alternative method based on statistics and machine learning hadattracted researchers' attention in recent years. However, most ofthe proposed algorithms were off-line and usually used a single classifier.In this paper a new hierarchical real-time model was proposed which comprised of a three tuple (source ip, destination ip and destination portlook up table(TT-LUT part and layered milestone part. TT-LUT was used to quickly classify short flows whichneed not to pass the layered milestone part, and milestones in layered milestone partcould classify the other flows in real-time with the real-time feature selection and statistics.Every milestone was a ECOC(Error-Correcting Output Codes based model which was usedto improve classification performance. Experiments showed that the proposedmodel can improve the efficiency of real-time to 80%, and themulti-class classification accuracy encouragingly to 91.4% on the datasets which had been captured from the backbone router in our campus through a week.

  1. 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.

  2. A hierarchical approach for speech-instrumental-song classification.

    Science.gov (United States)

    Ghosal, Arijit; Chakraborty, Rudrasis; Dhara, Bibhas Chandra; Saha, Sanjoy Kumar

    2013-01-01

    Audio classification acts as the fundamental step for lots of applications like content based audio retrieval and audio indexing. In this work, we have presented a novel scheme for classifying audio signal into three categories namely, speech, music without voice (instrumental) and music with voice (song). A hierarchical approach has been adopted to classify the signals. At the first stage, signals are categorized as speech and music using audio texture derived from simple features like ZCR and STE. Proposed audio texture captures contextual information and summarizes the frame level features. At the second stage, music is further classified as instrumental/song based on Mel frequency cepstral co-efficient (MFCC). A classifier based on Random Sample and Consensus (RANSAC), capable of handling wide variety of data has been utilized. Experimental result indicates the effectiveness of the proposed scheme.

  3. Hierarchical stochastic image grammars for classification and segmentation.

    Science.gov (United States)

    Wang, Wiley; Pollak, Ilya; Wong, Tak-Shing; Bouman, Charles A; Harper, Mary P; Siskind, Jeffrey M

    2006-10-01

    We develop a new class of hierarchical stochastic image models called spatial random trees (SRTs) which admit polynomial-complexity exact inference algorithms. Our framework of multitree dictionaries is the starting point for this construction. SRTs are stochastic hidden tree models whose leaves are associated with image data. The states at the tree nodes are random variables, and, in addition, the structure of the tree is random and is generated by a probabilistic grammar. We describe an efficient recursive algorithm for obtaining the maximum a posteriori estimate of both the tree structure and the tree states given an image. We also develop an efficient procedure for performing one iteration of the expectation-maximization algorithm and use it to estimate the model parameters from a set of training images. We address other inference problems arising in applications such as maximization of posterior marginals and hypothesis testing. Our models and algorithms are illustrated through several image classification and segmentation experiments, ranging from the segmentation of synthetic images to the classification of natural photographs and the segmentation of scanned documents. In each case, we show that our method substantially improves accuracy over a variety of existing methods.

  4. Morse Set Classification and Hierarchical Refinement Using Conley Index

    KAUST Repository

    Guoning Chen,

    2012-05-01

    Morse decomposition provides a numerically stable topological representation of vector fields that is crucial for their rigorous interpretation. However, Morse decomposition is not unique, and its granularity directly impacts its computational cost. In this paper, we propose an automatic refinement scheme to construct the Morse Connection Graph (MCG) of a given vector field in a hierarchical fashion. Our framework allows a Morse set to be refined through a local update of the flow combinatorialization graph, as well as the connection regions between Morse sets. The computation is fast because the most expensive computation is concentrated on a small portion of the domain. Furthermore, the present work allows the generation of a topologically consistent hierarchy of MCGs, which cannot be obtained using a global method. The classification of the extracted Morse sets is a crucial step for the construction of the MCG, for which the Poincar index is inadequate. We make use of an upper bound for the Conley index, provided by the Betti numbers of an index pair for a translation along the flow, to classify the Morse sets. This upper bound is sufficiently accurate for Morse set classification and provides supportive information for the automatic refinement process. An improved visualization technique for MCG is developed to incorporate the Conley indices. Finally, we apply the proposed techniques to a number of synthetic and real-world simulation data to demonstrate their utility. © 2006 IEEE.

  5. A proposed ecosystem services classification system to support green accounting

    Science.gov (United States)

    There are a multitude of actual or envisioned, complete or incomplete, ecosystem service classification systems being proposed to support Green Accounting. Green Accounting is generally thought to be the formal accounting attempt to factor environmental production into National ...

  6. Hierarchical diagnostic classification models morphing into unidimensional 'diagnostic' classification models-a commentary.

    Science.gov (United States)

    von Davier, Matthias; Haberman, Shelby J

    2014-04-01

    This commentary addresses the modeling and final analytical path taken, as well as the terminology used, in the paper "Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies" by Templin and Bradshaw (Psychometrika, doi: 10.1007/s11336-013-9362-0, 2013). It raises several issues concerning use of cognitive diagnostic models that either assume attribute hierarchies or assume a certain form of attribute interactions. The issues raised are illustrated with examples, and references are provided for further examination.

  7. Incremental concept learning with few training examples and hierarchical classification

    Science.gov (United States)

    Bouma, Henri; Eendebak, Pieter T.; Schutte, Klamer; Azzopardi, George; Burghouts, Gertjan J.

    2015-10-01

    Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible with only a few training samples. Secondly, we show that novel objects can be added incrementally without retraining existing objects, which is important for fast interaction. Thirdly, we show that an unbalanced number of positive training samples leads to biased classifier scores that can be corrected by modifying weights. Fourthly, we show that the detector performance can deteriorate due to hard-negative mining for similar or closely related classes (e.g., for Barbie and dress, because the doll is wearing a dress). This can be solved by our hierarchical classification. We introduce a new dataset, which we call TOSO, and use it to demonstrate the effectiveness of the proposed method for the localization and recognition of multiple objects in images.

  8. OBIA based hierarchical image classification for industrial lake water.

    Science.gov (United States)

    Uca Avci, Z D; Karaman, M; Ozelkan, E; Kumral, M; Budakoglu, M

    2014-07-15

    Water management is very important in water mining regions for the sustainability of the natural environment and for industrial activities. This study focused on Acigol Lake, which is an important wetland for sodium sulphate (Na2SO4) production, a significant natural protection area and habitat for local bird species and endemic species of this saline environment, and a stopover for migrating flamingos. By a hierarchical classification method, ponds representing the industrial part were classified according to in-situ measured Baumé values, and lake water representing the natural part was classified according to in-situ measurements of water depth. The latter is directly related to the water level, which should not exceed a critical level determined by the regulatory authorities. The resulting data, produced at an accuracy of around 80%, illustrates the status in two main regions for a single date. The output of the analysis may be meaningful for firms and environmental researchers, and authorizations can provide a good perspective for decision making for sustainable resource management in the region which has uncommon and specific ecological characteristics.

  9. Ecosystem classification for EU habitat distribution assessment in sandy coastal environments: an application in central Italy.

    Science.gov (United States)

    Carranza, Maria Laura; Acosta, Alicia T R; Stanisci, Angela; Pirone, Gianfranco; Ciaschetti, Giampiero

    2008-05-01

    Many recent developments in coastal science have gone against the demands of European Union legislation. Coastal dune systems which cover small areas of the earth can host a high level of biodiversity. However, human pressure on coastal zones around the world has increased dramatically in the last 50 years. In addition to direct habitat loss, the rapid extinction of many species that are unique to these systems can be attributed to landscape deterioration through the lack of appropriate management. In this paper, we propose to use of an ecosystem classification technique that integrates potential natural vegetation distribution as a reference framework for coastal dune EU Habitats (92/43) distribution analysis and assessment. As an example, the present study analyses the EU Habitats distribution within a hierarchical ecosystem classification of the coastal dune systems of central Italy. In total, 24 land elements belonging to 8 land units, 5 land facets, 2 land systems and 2 land regions were identified for the coastal dunes of central Italy, based on diagnostic land attributes. In central Italy, coastal dune environments including all the beach area, mobile dunes and all the fixed-dune land elements contain or could potentially hold at least one EU habitat of interest. Almost all dune slack transitions present the potentiality for the spontaneous development of EU woodlands of interest. The precise information concerning these ecosystems distribution and ecological relationships that this method produces, makes it very effective in Natura 2000 European network assessment. This hierarchical ecosystem classification method facilitates the identification of areas to be surveyed and eventually bound, under the implementation of EU Habitat directive (92/43) including areas with highly disturbed coastal dune ecosystems.

  10. 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

  11. Hierarchical structure for audio-video based semantic classification of sports video sequences

    Science.gov (United States)

    Kolekar, M. H.; Sengupta, S.

    2005-07-01

    A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

  12. Coordinate Descent Based Hierarchical Interactive Lasso Penalized Logistic Regression and Its Application to Classification Problems

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2014-01-01

    Full Text Available We present the hierarchical interactive lasso penalized logistic regression using the coordinate descent algorithm based on the hierarchy theory and variables interactions. We define the interaction model based on the geometric algebra and hierarchical constraint conditions and then use the coordinate descent algorithm to solve for the coefficients of the hierarchical interactive lasso model. We provide the results of some experiments based on UCI datasets, Madelon datasets from NIPS2003, and daily activities of the elder. The experimental results show that the variable interactions and hierarchy contribute significantly to the classification. The hierarchical interactive lasso has the advantages of the lasso and interactive lasso.

  13. Joint Hierarchical Category Structure Learning and Large-Scale Image Classification

    Science.gov (United States)

    Qu, Yanyun; Lin, Li; Shen, Fumin; Lu, Chang; Wu, Yang; Xie, Yuan; Tao, Dacheng

    2017-09-01

    We investigate the scalable image classification problem with a large number of categories. Hierarchical visual data structures are helpful for improving the efficiency and performance of large-scale multi-class classification. We propose a novel image classification method based on learning hierarchical inter-class structures. Specifically, we first design a fast algorithm to compute the similarity metric between categories, based on which a visual tree is constructed by hierarchical spectral clustering. Using the learned visual tree, a test sample label is efficiently predicted by searching for the best path over the entire tree. The proposed method is extensively evaluated on the ILSVRC2010 and Caltech 256 benchmark datasets. Experimental results show that our method obtains significantly better category hierarchies than other state-of-the-art visual tree-based methods and, therefore, much more accurate classification.

  14. Hierarchical trie packet classification algorithm based on expectation-maximization clustering

    Science.gov (United States)

    Bi, Xia-an; Zhao, Junxia

    2017-01-01

    With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. PMID:28704476

  15. Unsupervised Classification of SAR Images using Hierarchical Agglomeration and EM

    NARCIS (Netherlands)

    Kayabol, K.; Krylov, V.; Zerubia, J.; Salerno, E.; Cetin, A.E.; Salvetti, O.

    2012-01-01

    We implement an unsupervised classification algorithm for high resolution Synthetic Aperture Radar (SAR) images. The foundation of algorithm is based on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the model order sel

  16. 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.

  17. Land cover classification of remotely sensed image with hierarchical iterative method

    Institute of Scientific and Technical Information of China (English)

    LI Peijun; HUANG Yingduan

    2005-01-01

    Based on the analysis of the single-stage classification results obtained by the multitemporal SPOT 5 and Landsat 7 ETM + multispectral images separately and the derived variogram texture, the best data combinations for each land cover class are selected, and the hierarchical iterative classification is then applied for land cover mapping. The proposed classification method combines the multitemporal images of different resolutions with the image texture, which can greatly improve the classification accuracy. The method and strategies proposed in the study can be easily transferred to other similar applications.

  18. Application of Numenta® Hierarchical Temporal Memory for land-use classification

    Directory of Open Access Journals (Sweden)

    J.E. Meroño

    2010-01-01

    Full Text Available The aim of this paper is to present the application of memoryprediction theory, implemented in the form of a Hierarchical Temporal Memory (HTM, for land-use classification. Numenta®HTM is a new computing technology that replicates the structure and function of the human neocortex. In this study, a photogram, received by a photogrammetric UltraCamD® sensor of Vexcel, and data on 1 513 plots in Manzanilla (Huelva, Spain were used to validate the classification, achieving an overall classification accuracy of 90.4%. The HTMapproach appears to hold promise for land-use classification.

  19. Concept and Classification of Coarse Woody Debris in Forest Ecosystems

    Institute of Scientific and Technical Information of China (English)

    Yan Enrong; Wang Xihua; Huang Jianjun

    2006-01-01

    Coarse woody debris (CWD) is generally considered as dead woody materials in various stages of decomposition,including sound and rotting logs,snags,and large branches.CWD is an important functional and structural component of forested ecosystems and plays an important role in nutrient cycling,long-term carbon storage,tree regeneration,and maintenance of heterogeneous environmental and biological diversity.However,the definition and classification of CWD have been the subject of a long debate in forest ecology.CWD has not been precisely defined.Recently,with the rapid development of landscape ecology in CWD,the USDA Forest Service and the Long Term Ecological Research (LTER)have provided a standardized definition and classification for CWD,which makes data comparison in landscape scale possible.Important characteristics of their definition include:(1) a minimum diameter (or an equivalent crosssection) of CWD≥10 cm at the widest point (the woody debris with a diameter from 1 to 10 cm should be defined as fine woody debris,and the rest is litterfall);and (2) sound and rotting logs,snags,stumps,and large branches (located above the soil),and coarse root debris (larger than 1 cm in diameter).This classification has greatly facilitated CWD studies.Therefore,it has been widely applied in some countries (particularly in North America).However,this classification has long been a source of confusion for forest ecologists in China.Furthermore,different definitions and criteria are still adopted in individual studies,which makes the interpretation and generalization of their work difficult.This article reviewed recent progress in classifying CWD,with an emphasis on introducing the classification system of the USDA Forest Service and the LTER.It is expected that this review will help facilitate the development of standardized definition and classification suitable to forest ecosystems in China.

  20. 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.

  1. 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.

  2. Intrusion Detection System with Hierarchical Different Parallel Classification

    Directory of Open Access Journals (Sweden)

    Behrouz Safaiezadeh

    2015-12-01

    Full Text Available Todays, lives integrated to networks and internet. The needed information is transmitted through networks. So, someone may attempt to abuse the information and attack and make changes by weakness of networks. Intrusion Detection System is a system capable to detect some attacks. The system detects attacks through classifier construction and considering IP in network. The recent researches showed that a fundamental classification cannot be effective lonely and due to its errors, but mixing some classifications provide better efficiency. So, the current study attempt to design three classes of support vector machine, the neural network of multilayer perceptron and parallel fuzzy system in which there are trained dataset and capability to detect two classes. Finally, decisions made by an intermediate network due to type of attack. In the present research, suggested system tested through dataset of KDD99 and results indicated appropriate efficiency 99.71% in average.

  3. HIERARCHICAL DEEP LEARNING ARCHITECTURE FOR 10K OBJECTS CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Atul Laxman Katole

    2015-08-01

    Full Text Available Evolution of visual object recognition architectures based on Convolutional Neural Networks & Convolutional Deep Belief Networks paradigms has revolutionized artificial Vision Science. These architectures extract & learn the real world hierarchical visual features utilizing supervised & unsupervised learning approaches respectively. Both the approaches yet cannot scale up realistically to provide recognition for a very large number of objects as high as 10K. We propose a two level hierarchical deep learning architecture inspired by divide & conquer principle that decomposes the large scale recognition architecture into root & leaf level model architectures. Each of the root & leaf level models is trained exclusively to provide superior results than possible by any 1-level deep learning architecture prevalent today. The proposed architecture classifies objects in two steps. In the first step the root level model classifies the object in a high level category. In the second step, the leaf level recognition model for the recognized high level category is selected among all the leaf models. This leaf level model is presented with the same input object image which classifies it in a specific category. Also we propose a blend of leaf level models trained with either supervised or unsupervised learning approaches. Unsupervised learning is suitable whenever labelled data is scarce for the specific leaf level models. Currently the training of leaf level models is in progress; where we have trained 25 out of the total 47 leaf level models as of now. We have trained the leaf models with the best case top-5 error rate of 3.2% on the validation data set for the particular leaf models. Also we demonstrate that the validation error of the leaf level models saturates towards the above mentioned accuracy as the number of epochs are increased to more than sixty. The top-5 error rate for the entire two-level architecture needs to be computed in conjunction with

  4. Classification errors in contingency tables analyzed with hierarchical log-linear models. Technical report No. 20

    Energy Technology Data Exchange (ETDEWEB)

    Korn, E L

    1978-08-01

    This thesis is concerned with the effect of classification error on contingency tables being analyzed with hierarchical log-linear models (independence in an I x J table is a particular hierarchical log-linear model). Hierarchical log-linear models provide a concise way of describing independence and partial independences between the different dimensions of a contingency table. The structure of classification errors on contingency tables that will be used throughout is defined. This structure is a generalization of Bross' model, but here attention is paid to the different possible ways a contingency table can be sampled. Hierarchical log-linear models and the effect of misclassification on them are described. Some models, such as independence in an I x J table, are preserved by misclassification, i.e., the presence of classification error will not change the fact that a specific table belongs to that model. Other models are not preserved by misclassification; this implies that the usual tests to see if a sampled table belong to that model will not be of the right significance level. A simple criterion will be given to determine which hierarchical log-linear models are preserved by misclassification. Maximum likelihood theory is used to perform log-linear model analysis in the presence of known misclassification probabilities. It will be shown that the Pitman asymptotic power of tests between different hierarchical log-linear models is reduced because of the misclassification. A general expression will be given for the increase in sample size necessary to compensate for this loss of power and some specific cases will be examined.

  5. Hierarchical Higher Order Crf for the Classification of Airborne LIDAR Point Clouds in Urban Areas

    Science.gov (United States)

    Niemeyer, J.; Rottensteiner, F.; Soergel, U.; Heipke, C.

    2016-06-01

    We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point level and utilises higher order cliques. Segments are generated from the labelling obtained in this way. They are the entities of the second layer, which incorporates larger scale context. The classification result of the segments is introduced as an energy term for the next iteration of the point-based layer. This framework iterates and mutually propagates context to improve the classification results. Potentially wrong decisions can be revised at later stages. The output is a labelled point cloud as well as segments roughly corresponding to object instances. Moreover, we present two new contextual features for the segment classification: the distance and the orientation of a segment with respect to the closest road. It is shown that the classification benefits from these features. In our experiments the hierarchical framework improve the overall accuracies by 2.3% on a point-based level and by 3.0% on a segment-based level, respectively, compared to a purely point-based classification.

  6. 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.

  7. HIERARCHICAL CLASSIFICATION OF POLARIMETRIC SAR IMAGE BASED ON STATISTICAL REGION MERGING

    Directory of Open Access Journals (Sweden)

    F. Lang

    2012-07-01

    Full Text Available Segmentation and classification of polarimetric SAR (PolSAR imagery are very important for interpretation of PolSAR data. This paper presents a new object-oriented classification method which is based on Statistical Region Merging (SRM segmentation algorithm and a two-level hierarchical clustering technique. The proposed method takes full advantage of the polarimetric information contained in the PolSAR data, and takes both effectiveness and efficiency into account according to the characteristic of PolSAR. A modification of over-merging to over-segmentation technique and a post processing of segmentation for SRM is proposed according to the application of classification. And a revised symmetric Wishart distance is derived from the Wishart PDF. Segmentation and classification results of AirSAR L-band PolSAR data over the Flevoland test site is shown to demonstrate the validity of the proposed method.

  8. Hierarchical Web Page Classification Based on a Topic Model and Neighboring Pages Integration

    OpenAIRE

    Sriurai, Wongkot; Meesad, Phayung; Haruechaiyasak, Choochart

    2010-01-01

    Most Web page classification models typically apply the bag of words (BOW) model to represent the feature space. The original BOW representation, however, is unable to recognize semantic relationships between terms. One possible solution is to apply the topic model approach based on the Latent Dirichlet Allocation algorithm to cluster the term features into a set of latent topics. Terms assigned into the same topic are semantically related. In this paper, we propose a novel hierarchical class...

  9. A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems

    Science.gov (United States)

    Collins, Scott L.; Belnap, Jayne; Grimm, N. B.; Rudgers, J. A.; Dahm, Clifford N.; D'Odorico, P.; Litvak, M.; Natvig, D. O.; Peters, Douglas C.; Pockman, W. T.; Sinsabaugh, R. L.; Wolf, B. O.

    2014-01-01

    Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.

  10. DATA CLASSIFICATION WITH NEURAL CLASSIFIER USING RADIAL BASIS FUNCTION WITH DATA REDUCTION USING HIERARCHICAL CLUSTERING

    Directory of Open Access Journals (Sweden)

    M. Safish Mary

    2012-04-01

    Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.

  11. Establishing a Supervised Classification of Global Blue Carbon Mangrove Ecosystems

    Science.gov (United States)

    Baltezar, P.

    2016-12-01

    Understanding change in mangroves over time will aid forest management systems working to protect them from over exploitation. Mangroves are one of the most carbon dense terrestrial ecosystems on the planet and are therefore a high priority for sustainable forest management. Although they represent 1% of terrestrial cover, they could account for about 10% of global carbon emissions. The foundation of this analysis uses remote sensing to establish a supervised classification of mangrove forests for discrete regions in the Zambezi Delta of Mozambique and the Rufiji Delta of Tanzania. Open-source mapping platforms provided a dynamic space for analyzing satellite imagery in the Google Earth Engine (GEE) coding environment. C-Band Synthetic Aperture Radar data from Sentinel 1 was used in the model as a mask by optimizing SAR parameters. Exclusion metrics identified within Global Land Surface Temperature data from MODIS and the Shuttle Radar Topography Mission were used to accentuate mangrove features. Variance was accounted for in exclusion metrics by statistically calculating thresholds for radar, thermal, and elevation data. Optical imagery from the Landsat 8 archive aided a quality mosaic in extracting the highest spectral index values most appropriate for vegetative mapping. The enhanced radar, thermal, and digital elevation imagery were then incorporated into the quality mosaic. Training sites were selected from Google Earth imagery and used in the classification with a resulting output of four mangrove cover map models for each site. The model was assessed for accuracy by observing the differences between the mangrove classification models to the reference maps. Although the model was over predicting mangroves in non-mangrove regions, it was more accurately classifying mangrove regions established by the references. Future refinements will expand the model with an objective degree of accuracy.

  12. 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...

  13. Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

    Science.gov (United States)

    Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

    2010-12-01

    The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. A Mirroring Theorem and its Application to a New Method of Unsupervised Hierarchical Pattern Classification

    Directory of Open Access Journals (Sweden)

    Dasika Ratna Deepthi

    2009-10-01

    Full Text Available 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 sub-classes 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 Kolmogrov’s 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 algorithm and (iv self-supervised. We have actually built the architecture, developed the tandem algorithm of such a hierarchical classifier and demonstrated it on an example problem.

  15. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

  16. A Survey of Hierarchical Classification Methods%层次分类方法综述

    Institute of Scientific and Technical Information of China (English)

    陆彦婷; 陆建峰; 杨静宇

    2013-01-01

    层次分类方法利用类别层次结构来分解问题和组织分类器,可有效解决多类分类问题。依据是否要求类别之间存在显式层次关系,层次分类方法可分为两大类。文中对不要求类别之间存在显式层次关系的层次分类方法进行综述。首先归纳和阐述此类方法所采用的基本框架,然后介绍和分析其中若干关键技术的研究进展,最后从算法和应用两个角度对国内外相关研究进行详细叙述,进而对现有方法进行总结,并给出进一步研究的方向。%Hierarchical classification ( HC ) , decomposing problem and organizing the classifiers according to the category hierarchy, is an efficient solution for multi-class classification problem. Depending on whether an explicit hierarchical relationship among categories is required, HC methods can be divided into two types. In this paper, the HC methods which do not require explicit hierarchical relationship among categories are reviewed systematically. Firstly, the basic framework of this type of methods is outlined. Then, the research progresses of several key techniques are elaborated and analyzed. Next, the related research work at home and abroad is described in detail from both algorithm and application perspectives. Finally, the existing methods are summarized and several future research directions are pointed out.

  17. Statistical Classification of Terrestrial and Marine Ecosystems for Environmental Planning

    Directory of Open Access Journals (Sweden)

    W. Schröder

    2007-10-01

    Full Text Available E nvironmental planning is an instrument for the operationalisation of the precautionary principle in environmental law and, to this end, must rely on maps depicting the spatial patterns of ecological attributes of aquatic and terrestrial ecosystems and of environmental change effects, respectively. In this context, different mapping techniques are presented by example of three case studies covering terrestrial, coastal and marine environments. The first case study was selected to demonstrate how to compute an ecological land classification of Germany by means of CART. The resulting ecoregions were mapped by GIS. This CARTography enables to regionalise metal bioaccumulation data in terms of 21 ecological land categories and to prove the specifity of emission control measures as being part of environmental policies. The second investigation was chosen to applyfor the first time in Germany the regionalisation approach to the research of climate change effects in terms of past, recent and potential future incidences of Anopheles sp. and malaria in Lower Saxony. To investigate whether malaria might be transmitted due to increasing air temperatures, data sets on past and future air temperatures were used to spatially model malaria risk areas. The third example demonstrates the transfer of the CARTography approach presented in the first case study from terrestrial to marine environments. We analysed the statistical relations between data on benthic communities and physical properties of their marine environments by means of CART and applied these rules to geodata which only describe physical characteristics of the benthic habitats. By this, those parts of the sea ground could be predicted where certain benthic communities might occur.

  18. Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

    Science.gov (United States)

    Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

    2017-10-01

    Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

  19. Hierarchical Clustering of Large Databases and Classification of Antibiotics at High Noise Levels

    Directory of Open Access Journals (Sweden)

    Alexander V. Yarkov

    2008-12-01

    Full Text Available A new algorithm for divisive hierarchical clustering of chemical compounds based on 2D structural fragments is suggested. The algorithm is deterministic, and given a random ordering of the input, will always give the same clustering and can process a database up to 2 million records on a standard PC. The algorithm was used for classification of 1,183 antibiotics mixed with 999,994 random chemical structures. Similarity threshold, at which best separation of active and non active compounds took place, was estimated as 0.6. 85.7% of the antibiotics were successfully classified at this threshold with 0.4% of inaccurate compounds. A .sdf file was created with the probe molecules for clustering of external databases.

  20. Immunophenotype Discovery, Hierarchical Organization, and Template-based Classification of Flow Cytometry Samples

    Directory of Open Access Journals (Sweden)

    Ariful Azad

    2016-08-01

    Full Text Available We describe algorithms for discovering immunophenotypes from large collections of flow cytometry (FC samples, and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters, a template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples, while ignoring noise and small sample-specific variations.We have applied the template-base scheme to analyze several data setsincluding one representing a healthy immune system, and one of Acute Myeloid Leukemia (AMLsamples. The last task is challenging due to the phenotypic heterogeneity of the severalsubtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML, and were able to distinguish Acute Promyelocytic Leukemia from other subtypes of AML.

  1. Grass-Roots Cataloging and Classification: Food for Thought from World Wide Web Subject-Oriented Hierarchical Lists.

    Science.gov (United States)

    Dodd, David G.

    1996-01-01

    Examines the structure and principles of various hierarchical guides, or hotlists, which attempt to give subject access to World Wide Web resources on the Internet. The lists are compared to classification schemes and to Library of Congress subject headings, and browsing and search engines are compared. (Author/LRW)

  2. In-home hierarchical posture classification with a time-of-flight 3D sensor.

    Science.gov (United States)

    Diraco, Giovanni; Leone, Alessandro; Siciliano, Pietro

    2014-01-01

    A non-invasive technique for posture classification suitable to be used in several in-home scenarios is proposed and preliminary validation results are presented. 3D point cloud sequences were acquired using a single time-of-flight sensor working in a privacy preserving modality and they were processed with a low power embedded PC. In order to satisfy different application requirements (e.g. covered distance range, processing speed and discrimination capabilities), a twofold discrimination approach was investigated in which features were hierarchically arranged from coarse to fine by exploiting both topological and volumetric representations. The topological representation encoded the intrinsic topology of the body's shape using a skeleton-based structure, thus guaranteeing invariance to scale, rotations and postural changes and achieving a high level of detail with a moderate computational cost. On the other hand, using the volumetric representation features were described in terms of 3D cylindrical histograms working within a wider range of distances in a faster way and also guaranteeing good invariance properties. The discrimination capabilities were evaluated in four different real-home scenarios related with the fields of ambient assisted living and homecare, namely "dangerous event detection", "anomalous behaviour detection", "activities recognition" and "natural human-ambient interaction". For each mentioned scenario, the discrimination capabilities were evaluated in terms of invariance to viewpoint changes, representation capabilities and classification performance, achieving promising results. The two feature representation approaches exhibited complementary characteristics showing high reliability with classification rates greater than 97%. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

    Science.gov (United States)

    Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

    2008-06-01

    A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

  4. Page Layout Analysis of the Document Image Based on the Region Classification in a Decision Hierarchical Structure

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2010-10-01

    Full Text Available The conversion of document image to its electronic version is a very important problem in the saving, searching and retrieval application in the official automation system. For this purpose, analysis of the document image is necessary. In this paper, a hierarchical classification structure based on a two-stage segmentation algorithm is proposed. In this structure, image is segmented using the proposed two-stage segmentation algorithm. Then, the type of the image regions such as document and non-document image is determined using multiple classifiers in the hierarchical classification structure. The proposed segmentation algorithm uses two algorithms based on wavelet transform and thresholding. Texture features such as correlation, homogeneity and entropy that extracted from co-occurrenc matrix and also two new features based on wavelet transform are used to classifiy and lable the regions of the image. The hierarchical classifier is consisted of two Multilayer Perceptron (MLP classifiers and a Support Vector Machine (SVM classifier. The proposed algorithm is evaluated on a database consisting of document and non-document images that provides from Internet. The experimental results show the efficiency of the proposed approach in the region segmentation and classification. The proposed algorithm provides accuracy rate of 97.5% on classification of the regions.

  5. FINAL ECOSYSTEM GOODS AND SERVICES CLASSIFICATION SYSTEM (FEGS-CS)

    Science.gov (United States)

    This document defines and classifies 338 Final Ecosystem Goods and Services (FEGS), each defined and uniquely numbered by a combination of environmental class or sub-class and a beneficiary category or sub-category. The introductory section provides the rationale and conceptual ...

  6. Ecosystem services provided by a complex coastal region: challenges of classification and mapping.

    Science.gov (United States)

    Sousa, Lisa P; Sousa, Ana I; Alves, Fátima L; Lillebø, Ana I

    2016-03-11

    A variety of ecosystem services classification systems and mapping approaches are available in the scientific and technical literature, which needs to be selected and adapted when applied to complex territories (e.g. in the interface between water and land, estuary and sea). This paper provides a framework for addressing ecosystem services in complex coastal regions. The roadmap comprises the definition of the exact geographic boundaries of the study area; the use of CICES (Common International Classification of Ecosystem Services) for ecosystem services identification and classification; and the definition of qualitative indicators that will serve as basis to map the ecosystem services. Due to its complexity, the Ria de Aveiro coastal region was selected as case study, presenting an opportunity to explore the application of such approaches at a regional scale. The main challenges of implementing the proposed roadmap, together with its advantages are discussed in this research. The results highlight the importance of considering both the connectivity of natural systems and the complexity of the governance framework; the flexibility and robustness, but also the challenges when applying CICES at regional scale; and the challenges regarding ecosystem services mapping.

  7. Ecosystem services provided by a complex coastal region: challenges of classification and mapping

    Science.gov (United States)

    Sousa, Lisa P.; Sousa, Ana I.; Alves, Fátima L.; Lillebø, Ana I.

    2016-03-01

    A variety of ecosystem services classification systems and mapping approaches are available in the scientific and technical literature, which needs to be selected and adapted when applied to complex territories (e.g. in the interface between water and land, estuary and sea). This paper provides a framework for addressing ecosystem services in complex coastal regions. The roadmap comprises the definition of the exact geographic boundaries of the study area; the use of CICES (Common International Classification of Ecosystem Services) for ecosystem services identification and classification; and the definition of qualitative indicators that will serve as basis to map the ecosystem services. Due to its complexity, the Ria de Aveiro coastal region was selected as case study, presenting an opportunity to explore the application of such approaches at a regional scale. The main challenges of implementing the proposed roadmap, together with its advantages are discussed in this research. The results highlight the importance of considering both the connectivity of natural systems and the complexity of the governance framework; the flexibility and robustness, but also the challenges when applying CICES at regional scale; and the challenges regarding ecosystem services mapping.

  8. ‘Large Igneous Provinces (LIPs)’: Definition, recommended terminology, and a hierarchical classification

    Science.gov (United States)

    Sheth, Hetu C.

    2007-12-01

    This article is an appeal for the adoption of a correct and appropriate terminology with respect to the so-called Large Igneous Provinces (LIPs). The term LIP has been widely applied to large basaltic provinces such as the Deccan Traps, and the term Silicic Large Igneous Province (SLIP) to volcanic provinces of dominantly felsic composition, such as the Whitsunday Province. However, neither term (LIP, SLIP) has been applied to the large granitic batholiths of the world (e.g., Andes) to which both terms are perfectly applicable. LIP has also not been applied to broad areas of contemporaneous basalt magmatism (e.g., Indochina, Mongolia) and sizeable layered mafic intrusions (e.g., Bushveld) which in many significant respects may also be considered to represent 'Large Igneous Provinces'. Here, I suggest that the term LIP is used in its broadest sense and that it should designate igneous provinces with outcrop areas ≥ 50,000 km 2. I propose a simple hierarchical classification of LIPs that is independent of composition, tectonic setting, or emplacement mechanism. I suggest that provinces such as the Deccan and Whitsunday provinces should be called Large Volcanic Provinces (LVPs), whereas large intrusive provinces (mafic-ultramafic intrusions, dyke/sill swarms, granitic batholiths) should be called Large Plutonic Provinces (LPPs). LVPs and LPPs thus together cover all LIPs, which can be felsic, mafic, or ultramafic, of sub-alkalic or alkalic affinity, and emplaced in continental or oceanic settings. LVPs are subdivided here into four groups: (i) the dominantly/wholly mafic Large Basaltic Provinces (LBPs) (e.g., Deccan, Ontong Java); (ii) the dominantly felsic Large Rhyolitic Provinces (LRPs) (e.g., Whitsunday, Sierra Madre Occidental); (iii) the dominantly andesitic Large Andesitic Provinces (LAPs) (e.g., Andes, Indonesia, Cascades), and (iv) the bimodal Large Basaltic-Rhyolitic Provinces (LBRPs) (e.g., Snake River-High Lava Plains). The intrusive equivalents of LRPs

  9. The Homeland Security Ecosystem: An Analysis of Hierarchical and Ecosystem Models and Their Influence on Decision Makers

    Science.gov (United States)

    2012-12-01

    Gail F. Thomas, and Erik Jansen , “Building Collaborative Capacity: An Innovative Strategy for Homeland Security Preparedness,” in Advances in...Intelligence Analysis (Washington DC: CQ Press, 2011), 123. 184 Ropert Bood and Theo Postma, “Scenario Analysis as a Strategic Management Tool” (Groningen...World Mirrors Life of Ecosystems.” Computer Reseller News (February 1996): 36. Bood, Ropert and Theo Postma. “Scenario Analysis as a Strategic

  10. A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

    Science.gov (United States)

    Jung, Jinha; Pasolli, Edoardo; Prasad, Saurabh; Tilton, James C.; Crawford, Melba M.

    2014-01-01

    Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

  11. Hierarchical levels in agro-ecosystems: selective case studies on water and nitrogen.

    NARCIS (Netherlands)

    Ridder, de N.

    1997-01-01

    The subject of this thesisToday, agronomic research faces the triple challenge to develop knowledge and insight to manage agro-ecosystems which are inherently sustainable, to diminish the undesirable side effects and to meet the increasing demand of food of a still growing world population, without

  12. Hierarchical levels in agro-ecosystems : selective case studies on water and nitrogen

    NARCIS (Netherlands)

    Ridder, de N.

    1997-01-01


    The subject of this thesis

    Today, agronomic research faces the triple challenge to develop knowledge and insight to manage agro-ecosystems which are inherently sustainable, to diminish the undesirable side effects and to meet the increasing demand of food of a still growing world

  13. Hierarchical classification for the topography analysis of Asteroid (4179) Toutatis from the Chang'E-2 images

    Science.gov (United States)

    Zheng, Chen; Ping, Jinsong; Wang, Mingyuan

    2016-11-01

    High spatial resolution images of the near-Earth Asteroid (4179) Toutatis are provided by a successful flyby of the Chang'E-2 spacecraft. These optical images give us a chance to closely observe the surface of this asteroid. However, some local low-contrast regions in the Chang'E-2 images limit the accuracy of the topography recognition. To solve this problem, a hierarchical classification method is suggested and developed to assist the topography analysis for Toutatis based on the Chang'E-2 optical images. The proposed method first classifies the image at both the macro level and the micro level, respectively. Then, topography of Toutatis can be explored by using the hierarchical classification result. Experimental results demonstrate that the method cannot only provide a new perspective to analyze topography objects reported previously, but also reveal some new characteristics at low-contrast regions. Namely, two new topographic characteristics are revealed, one is a connection region with a particular spectral value locating at the corner of the large lobe, and the other is an object seeming like a fixed star at the background of the images.

  14. Optimization of Agricultural Crop Identification in SLAR Images: Hierarchic Classification and Texture Analysis

    NARCIS (Netherlands)

    Hoogeboom, P.

    1985-01-01

    In 1980 a large SLAR flight program was carried out over an agricultural area in The Netherlands. A classification study on this multitenporal dataset (Ref, l) showed that high accuracies are obtained from a simultaneous classification of 3 flights. In this paper the results of a follow on study wil

  15. Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2010-12-01

    Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

  16. The National Ecosystem Services Classification System: A Framework for Identifying and Reducing Relevant Uncertainties

    Science.gov (United States)

    Rhodes, C. R.; Sinha, P.; Amanda, N.

    2013-12-01

    In recent years the gap between what scientists know and what policymakers should appreciate in environmental decision making has received more attention, as the costs of the disconnect have become more apparent to both groups. Particularly for water-related policies, the EPA's Office of Water has struggled with benefit estimates held low by the inability to quantify ecological and economic effects that theory, modeling, and anecdotal or isolated case evidence suggest may prove to be larger. Better coordination with ecologists and hydrologists is being explored as a solution. The ecosystem services (ES) concept now nearly two decades old links ecosystem functions and processes to the human value system. But there remains no clear mapping of which ecosystem goods and services affect which individual or economic values. The National Ecosystem Services Classification System (NESCS, 'nexus') project brings together ecologists, hydrologists, and social scientists to do this mapping for aquatic and other ecosystem service-generating systems. The objective is to greatly reduce the uncertainty in water-related policy making by mapping and ultimately quantifying the various functions and products of aquatic systems, as well as how changes to aquatic systems impact the human economy and individual levels of non-monetary appreciation for those functions and products. Primary challenges to fostering interaction between scientists, social scientists, and policymakers are lack of a common vocabulary, and the need for a cohesive comprehensive framework that organizes concepts across disciplines and accommodates scientific data from a range of sources. NESCS builds the vocabulary and the framework so both may inform a scalable transdisciplinary policy-making application. This talk presents for discussion the process and progress in developing both this vocabulary and a classifying framework capable of bridging the gap between a newer but existing ecosystem services classification

  17. A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays

    Directory of Open Access Journals (Sweden)

    Piergiorgi Paolo

    2006-11-01

    Full Text Available Abstract Background Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. Results We propose an extension of the well-known Naïve Bayes classifier, which accounts for biological heterogeneity in a probabilistic framework, relying on Bayesian hierarchical models. The model, which can be efficiently learned from the training dataset, exploits a closed-form of classification equation, thus providing no additional computational cost with respect to the standard Naïve Bayes classifier. We validated the approach on several simulated datasets comparing its performances with the Naïve Bayes classifier. Moreover, we demonstrated that explicitly dealing with heterogeneity can improve classification accuracy on a TMA prostate cancer dataset. Conclusion The proposed Hierarchical Naïve Bayes classifier can be conveniently applied in problems where within sample heterogeneity must be taken into account, such as TMA experiments and biological contexts where several measurements (replicates are available for the same biological sample. The performance of the new approach is better than the standard Naïve Bayes model, in particular when the within sample heterogeneity is different in the different classes.

  18. Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

    Science.gov (United States)

    Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

    2010-01-01

    Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

  19. 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.

  20. Divisional compound hierarchical classification method for regionalization of high, medium and low yield croplands of China

    Science.gov (United States)

    Yuliang, Qiao; Ying, Wang; Jinchun, Liu

    This is an introduction to the method of classifying high, medium and low yield croplands by remote sensing and GIS, which is the result of a key project of The Scientific and Industry Technology Committee of National Defence. In the study, special information related to high, medium and low yield cropland was compounded with TM data. The development of the method of compound hierarchy classification improved accuracy of remote sensing classification greatly.

  1. Object-Based Tree Species Classification in Urban Ecosystems Using LiDAR and Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Zhongya Zhang

    2016-06-01

    Full Text Available In precision forestry, tree species identification is key to evaluating the role of forest ecosystems in the provision of ecosystem services, such as carbon sequestration and assessing their effects on climate regulation and climate change. In this study, we investigated the effectiveness of tree species classification of urban forests using aerial-based HyMap hyperspectral imagery and light detection and ranging (LiDAR data. First, we conducted an object-based image analysis (OBIA to segment individual tree crowns present in LiDAR-derived Canopy Height Models (CHMs. Then, hyperspectral values for individual trees were extracted from HyMap data for band reduction through Minimum Noise Fraction (MNF transformation which allowed us to reduce the data to 20 significant bands out of 118 bands acquired. Finally, we compared several different classifications using Random Forest (RF and Multi Class Classifier (MCC methods. Seven tree species were classified using all 118 bands which resulted in 46.3% overall classification accuracy for RF versus 79.6% for MCC. Using only the 20 optimal bands extracted through MNF, both RF and MCC achieved an increase in overall accuracy to 87.0% and 88.9%, respectively. Thus, the MNF band selection process is a preferable approach for tree species classification when using hyperspectral data. Further, our work also suggests that RF is heavily disadvantaged by the high-dimensionality and noise present in hyperspectral data, while MCC is more robust when handling high-dimensional datasets with small sample sizes. Our overall results indicated that individual tree species identification in urban forests can be accomplished with the fusion of object-based LiDAR segmentation of crowns and hyperspectral characterization.

  2. Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-the-art algorithms using a benchmark dataset.

    Science.gov (United States)

    Leutheuser, Heike; Schuldhaus, Dominik; Eskofier, Bjoern M

    2013-01-01

    Insufficient physical activity is the 4th leading risk factor for mortality. Methods for assessing the individual daily life activity (DLA) are of major interest in order to monitor the current health status and to provide feedback about the individual quality of life. The conventional assessment of DLAs with self-reports induces problems like reliability, validity, and sensitivity. The assessment of DLAs with small and light-weight wearable sensors (e.g. inertial measurement units) provides a reliable and objective method. State-of-the-art human physical activity classification systems differ in e.g. the number and kind of sensors, the performed activities, and the sampling rate. Hence, it is difficult to compare newly proposed classification algorithms to existing approaches in literature and no commonly used dataset exists. We generated a publicly available benchmark dataset for the classification of DLAs. Inertial data were recorded with four sensor nodes, each consisting of a triaxial accelerometer and a triaxial gyroscope, placed on wrist, hip, chest, and ankle. Further, we developed a novel, hierarchical, multi-sensor based classification system for the distinction of a large set of DLAs. Our hierarchical classification system reached an overall mean classification rate of 89.6% and was diligently compared to existing state-of-the-art algorithms using our benchmark dataset. For future research, the dataset can be used in the evaluation process of new classification algorithms and could speed up the process of getting the best performing and most appropriate DLA classification system.

  3. Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities

    NARCIS (Netherlands)

    Mucina, L.; Bültmann, Helga; Dierssen, Klaus; Theurillat, Jean-Paul; Raus, Thomas; Carni, Andraz; Šumberová, Kateřina; Willner, Wolfgang; Dengler, J.; Schaminee, J.H.J.; Hennekens, S.M.

    2016-01-01

    Aims: Vegetation classification consistent with the Braun-Blanquet approach is
    widely used in Europe for applied vegetation science, conservation planning
    and landmanagement. During the long history of syntaxonomy,many concepts
    and names of vegetation units have been proposed, but there

  4. Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities

    NARCIS (Netherlands)

    Mucina, L.; Bültmann, Helga; Dierssen, Klaus; Theurillat, Jean-Paul; Raus, Thomas; Carni, Andraz; Šumberová, Kateřina; Willner, Wolfgang; Dengler, J.; Schaminee, J.H.J.; Hennekens, S.M.

    2016-01-01

    Aims: Vegetation classification consistent with the Braun-Blanquet approach is
    widely used in Europe for applied vegetation science, conservation planning
    and landmanagement. During the long history of syntaxonomy,many concepts
    and names of vegetation units have been proposed, but there

  5. Hyperspectral band selection and classification of Hyperion image of Bhitarkanika mangrove ecosystem, eastern India

    Science.gov (United States)

    Ashokkumar, L.; Shanmugam, S.

    2014-10-01

    Tropical mangrove forests along the coast evolve dynamically due to constant changes in the natural ecosystem and ecological cycle. Remote sensing has paved the way for periodic monitoring and conservation of such floristic resources, compared to labour intensive in-situ observations. With the laboratory quality image spectra obtained from hyperspectral image data, species level discrimination in habitats and ecosystems is attainable. One of the essential steps before classification of hyperspectral image data is band selection. It is important to eliminate the redundant bands to mitigate the problems of Hughes effect that are likely to affect further image analysis and classification accuracy. This paper presents a methodology for the selection of appropriate hyperspectral bands from the EO-1 Hyperion image for the identification and mapping of mangrove species and coastal landcover types in the Bhitarkanika coastal forest region, eastern India. Band selection procedure follows class based elimination procedure and the separability of the classes are tested in the band selection process. Individual bands are de-correlated and redundant bands are removed from the bandwise correlation matrix. The percent contribution of class variance in each band is analysed from the factors of PCA component ranking. Spectral bands are selected from the wavelength groups and statistically tested. Further, the band selection procedure is compared with similar techniques (Band Index and Mutual information) for validation. The number of bands in the Hyperion image was reduced from 196 to 88 by the Factor-based ranking approach. Classification was performed by Support Vector Machine approach. It is observed that the proposed Factor-based ranking approach performed well in discriminating the mangrove species and other landcover units compared to the other statistical approaches. The predominant mangrove species Heritiera fomes, Excoecaria agallocha and Cynometra ramiflora are spectral

  6. Measuring diversity and coherence using hierarchical APS-PACS classification of sub fields of physics and their impact on citations

    Science.gov (United States)

    Jolad, Shivakumar; Enduri, Murali Krishna; Reddy, I. Vinod

    American Physical Society introduced Physics and Astronomy Classification Scheme (PACS) in 1975 to classify different subfields of physics in a hierarchical tree structure. Since 1985, almost all the physical review articles include the PACS code to refer different subfields it belongs to. In this work, we define the notion of diversity of articles and authors based on the PACS codes they are associated with, using Weitzamn diversity index, from 1985-2012. We find that the fraction of authors with high diversity is increasing with time, whereas the fraction of least diversity are decreasing, and moderate diversity authors have higher tendency to switch over to other diversity groups. By measuring the interconnectedness among the PACS codes, we define measures of coherence of papers and authors. The diversity and coherence captures the dimensions of Interdisciplinarity. Based on which we study the correlation between Interdisciplinarity (within sub fields of physics) and citations. We find that the diversity index of articles is correlated with the citations they received in a given time period from their publication year. Articles with lower and higher end of diversity index receive lesser citations than the moderate diversity papers.

  7. Automated morphological analysis of bone marrow cells in microscopic images for diagnosis of leukemia: nucleus-plasma separation and cell classification using a hierarchical tree model of hematopoesis

    Science.gov (United States)

    Krappe, Sebastian; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

    2016-03-01

    The morphological differentiation of bone marrow is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually under the use of bright field microscopy. This is a time-consuming, subjective, tedious and error-prone process. Furthermore, repeated examinations of a slide may yield intra- and inter-observer variances. For that reason a computer assisted diagnosis system for bone marrow differentiation is pursued. In this work we focus (a) on a new method for the separation of nucleus and plasma parts and (b) on a knowledge-based hierarchical tree classifier for the differentiation of bone marrow cells in 16 different classes. Classification trees are easily interpretable and understandable and provide a classification together with an explanation. Using classification trees, expert knowledge (i.e. knowledge about similar classes and cell lines in the tree model of hematopoiesis) is integrated in the structure of the tree. The proposed segmentation method is evaluated with more than 10,000 manually segmented cells. For the evaluation of the proposed hierarchical classifier more than 140,000 automatically segmented bone marrow cells are used. Future automated solutions for the morphological analysis of bone marrow smears could potentially apply such an approach for the pre-classification of bone marrow cells and thereby shortening the examination time.

  8. A CAD System for Identification and Classification of Breast Cancer Tumors in DCE-MR Images Based on Hierarchical Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Rastiboroujeni

    2015-06-01

    Full Text Available In this paper, we propose a computer aided diagnosis (CAD system based on hierarchical convolutional neural networks (HCNNs to discriminate between malignant and benign tumors in breast DCE-MRIs. A HCNN is a hierarchical neural network that operates on two-dimensional images. A HCNN integrates feature extraction and classification processes into one single and fully adaptive structure. It can extract two-dimensional key features automatically, and it is relatively tolerant to geometric and local distortions in input images. We evaluate CNN implementation learning and testing processes based on gradient descent (GD and resilient back-propagation (RPROP approaches. We show that, proposed HCNN with RPROP learning approach provide an effective and robust neural structure to design a CAD base system for breast MRI, and has potential as a mechanism for the evaluation of different types of abnormalities in medical images.

  9. A Hierarchical Object-oriented Urban Land Cover Classification Using WorldView-2 Imagery and Airborne LiDAR data

    Science.gov (United States)

    Wu, M. F.; Sun, Z. C.; Yang, B.; Yu, S. S.

    2016-11-01

    In order to reduce the “salt and pepper” in pixel-based urban land cover classification and expand the application of fusion of multi-source data in the field of urban remote sensing, WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data were used to improve the classification of urban land cover. An approach of object- oriented hierarchical classification was proposed in our study. The processing of proposed method consisted of two hierarchies. (1) In the first hierarchy, LiDAR Normalized Digital Surface Model (nDSM) image was segmented to objects. The NDVI, Costal Blue and nDSM thresholds were set for extracting building objects. (2) In the second hierarchy, after removing building objects, WorldView-2 fused imagery was obtained by Haze-ratio-based (HR) fusion, and was segmented. A SVM classifier was applied to generate road/parking lot, vegetation and bare soil objects. (3) Trees and grasslands were split based on an nDSM threshold (2.4 meter). The results showed that compared with pixel-based and non-hierarchical object-oriented approach, proposed method provided a better performance of urban land cover classification, the overall accuracy (OA) and overall kappa (OK) improved up to 92.75% and 0.90. Furthermore, proposed method reduced “salt and pepper” in pixel-based classification, improved the extraction accuracy of buildings based on LiDAR nDSM image segmentation, and reduced the confusion between trees and grasslands through setting nDSM threshold.

  10. 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...

  11. Benthic indicators to use in Ecological Quality classification of Mediterranean soft bottom marine ecosystems, including a new Biotic Index

    Directory of Open Access Journals (Sweden)

    N. SIMBOURA

    2002-12-01

    Full Text Available A general scheme for approaching the objective of Ecological Quality Status (EcoQ classification of zoobenthic marine ecosystems is presented. A system based on soft bottom benthic indicator species and related habitat types is suggested to be used for testing the typological definition of a given water body in the Mediterranean. Benthic indices including the Shannon-Wiener diversity index and the species richness are re-evaluated for use in classification. Ranges of values and of ecological quality categories are given for the diversity and species richness in different habitat types. A new biotic index (BENTIX is proposed based on the relative percentages of three ecological groups of species grouped according to their sensitivity or tolerance to disturbance factors and weighted proportionately to obtain a formula rendering a five step numerical scale of ecological quality classification. Its advantage against former biotic indices lies in the fact that it reduces the number of the ecological groups involved which makes it simpler and easier in its use. The Bentix index proposed is tested and validated with data from Greek and western Mediterranean ecosystems and examples are presented. Indicator species associated with specific habitat types and pollution indicator species, scored according to their degree of tolerance to pollution, are listed in a table. The Bentix index is compared and evaluated against the indices of diversity and species richness for use in classification. The advantages of the BENTIX index as a classification tool for ECoQ include independence from habitat type, sample size and taxonomic effort, high discriminative power and simplicity in its use which make it a robust, simple and effective tool for application in the Mediterranean Sea.

  12. Benthic indicators to use in Ecological Quality classification of Mediterranean soft bottom marine ecosystems, including a new Biotic Index

    Directory of Open Access Journals (Sweden)

    N. SIMBOURA

    2012-12-01

    Full Text Available A general scheme for approaching the objective of Ecological Quality Status (EcoQ classification of zoobenthic marine ecosystems is presented. A system based on soft bottom benthic indicator species and related habitat types is suggested to be used for testing the typological definition of a given water body in the Mediterranean. Benthic indices including the Shannon-Wiener diversity index and the species richness are re-evaluated for use in classification. Ranges of values and of ecological quality categories are given for the diversity and species richness in different habitat types. A new biotic index (BENTIX is proposed based on the relative percentages of three ecological groups of species grouped according to their sensitivity or tolerance to disturbance factors and weighted proportionately to obtain a formula rendering a five step numerical scale of ecological quality classification. Its advantage against former biotic indices lies in the fact that it reduces the number of the ecological groups involved which makes it simpler and easier in its use. The Bentix index proposed is tested and validated with data from Greek and western Mediterranean ecosystems and examples are presented. Indicator species associated with specific habitat types and pollution indicator species, scored according to their degree of tolerance to pollution, are listed in a table. The Bentix index is compared and evaluated against the indices of diversity and species richness for use in classification. The advantages of the BENTIX index as a classification tool for ECoQ include independence from habitat type, sample size and taxonomic effort, high discriminative power and simplicity in its use which make it a robust, simple and effective tool for application in the Mediterranean Sea.

  13. National Ecosystem Services Classification System (NESCS): Framework Design and Policy Application

    Science.gov (United States)

    Understanding the ways in which ecosystems provide flows of “services” to humans is critical for decision making in many contexts; however, relationships between natural and human systems are complex. A well-defined framework for classifying ecosystem services is essential for sy...

  14. Understanding ecosystem service preferences across residential classifications near Mt. Baker Snoqualmie National Forest, Washington (USA).

    Science.gov (United States)

    Katherine Williams; Kelly Biedenweg; Lee Cerveny

    2017-01-01

    Ecosystem services consistently group together both spatially and cognitively into “bundles”. Understanding socio-economic predictors of these bundles is essential to informing a management approach that emphasizes equitable distribution of ecosystem services. We received 1796 completed surveys from stakeholders of the Mt. Baker-Snoqualmie National Forest (WA, USA)...

  15. 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...

  16. Biocomplexity in Mangrove Ecosystems

    Science.gov (United States)

    Feller, I. C.; Lovelock, C. E.; Berger, U.; McKee, K. L.; Joye, S. B.; Ball, M. C.

    2010-01-01

    Mangroves are an ecological assemblage of trees and shrubs adapted to grow in intertidal environments along tropical coasts. Despite repeated demonstration of their economic and societal value, more than 50% of the world's mangroves have been destroyed, 35% in the past two decades to aquaculture and coastal development, altered hydrology, sea-level rise, and nutrient overenrichment. Variations in the structure and function of mangrove ecosystems have generally been described solely on the basis of a hierarchical classification of the physical characteristics of the intertidal environment, including climate, geomorphology, topography, and hydrology. Here, we use the concept of emergent properties at multiple levels within a hierarchical framework to review how the interplay between specialized adaptations and extreme trait plasticity that characterizes mangroves and intertidal environments gives rise to the biocomplexity that distinguishes mangrove ecosystems. The traits that allow mangroves to tolerate variable salinity, flooding, and nutrient availability influence ecosystem processes and ultimately the services they provide. We conclude that an integrated research strategy using emergent properties in empirical and theoretical studies provides a holistic approach for understanding and managing mangrove ecosystems.

  17. A typology for the classification, description and valuation of ecosystem function, goods and services

    NARCIS (Netherlands)

    Groot, de R.S.; Wilson, M.A.; Boumans, R.M.J.

    2002-01-01

    An increasing amount of information is being collected on the ecological and socio-economic value of goods and services provided by natural and semi-natural ecosystems. However, much of this information appears scattered throughout a disciplinary academic literature, unpublished government agency re

  18. Bioassay for aquatic ecosystems review and classification; Rassegna dei principali test di ecotossicologia acquatica

    Energy Technology Data Exchange (ETDEWEB)

    Sanci, Antonella; Rosa, Silvia [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Ambiente

    1997-09-01

    Bioassay play a crucial role in assessing the actual or potential impacts of anthropogenic agents on the natural environment. In this technical report, literature on bioassays for aquatic ecosystems has been reviewed and classified. Problems associated with the choice and application of bioassays are discussed.

  19. Ecosystem services classification: A systems ecology perspective of the cascade framework

    CSIR Research Space (South Africa)

    La Notte, A

    2017-03-01

    Full Text Available and Trade- ffs (InVEST) tool. The private sector have also adopted the concept hrough initiatives such as the Natural Capital Coalition (NCC), the orld Bank’s Wealth Accounting and the Valuation of Ecosystem ervices (WAVES), the accounting system developed...

  20. A comparison of time series similarity measures for classification and change detection of ecosystem dynamics

    NARCIS (Netherlands)

    Lhermitte, S.; Verbesselt, J.; Verstraeten, W.W.; Coppin, P.

    2011-01-01

    Time series of remote sensing imagery or derived vegetation indices and biophysical products have been shown particularly useful to characterize land ecosystem dynamics. Various methods have been developed based on temporal trajectory analysis to characterize, classify and detect changes in ecosyste

  1. 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.

  2. Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

    Directory of Open Access Journals (Sweden)

    TIMCHENKO, L.

    2012-11-01

    Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

  3. Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

    Science.gov (United States)

    Wildhaber, Mark L.; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.; Dey, Rima

    2017-01-01

    We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.

  4. Establishing the Injury Severity of Thoracolumbar Trauma : Confirmation of the Hierarchical Structure of the AOSpine Thoracolumbar Spine Injury Classification System

    NARCIS (Netherlands)

    Schroeder, Gregory D.; Vaccaro, Alexander R.; Kepler, Christopher K.; Koerner, John D.; Oner, F. Cumhur; Dvorak, Marcel F.; Vialle, Luiz R.; Aarabi, Bizhan; Bellabarba, Carlo; Fehlings, Michael G.; Schnake, Klaus J.; Kandziora, Frank

    2015-01-01

    Study Design. Survey of spine surgeons. Objective. To develop a validated regional and global injury severity scoring system for thoracolumbar trauma. Summary of Background Data. The AOSpine Thoracolumbar Spine Injury Classification System was recently published and combines elements of both the Mag

  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. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  7. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  8. Classification of Urban Vegetation Population Through Hierarchical Classification in Multi-descriptor Space%针对分层分类和多描述符空间的城镇植被群分类

    Institute of Scientific and Technical Information of China (English)

    蒋轩; 周坚华

    2015-01-01

    Constrained by limited urban land resources and the needs in artificial aesthetics,urban landscape vegetation is often characterized by scattered distribution,complex structure,various species and the shaded scene resulting in the severe challenges to the classification of vegetation population from remotely sensed imagery.To solve this problem,this paper presents an algorithm to classify vegetation populations such as the lawn,trees,broadleaf,conifers,deciduous and evergreen plants by using hierarchical classification (HC)in multi-descriptor space,that is,conducting multi-layer classifications in accordance with the hierarchical relationship of the classes and using different combinations of mathematical descriptors for the classifications. For example,the two classes of with and with no vegetation cover will firstly be separated.This will be followed by the classification between grass and trees (and/or shrubs)from the previous vegetation-covered class.After this the separation between broadleaf and conifers plants or between deciduous and evergreen plants from the above tree/shrub classes can be reached.By using the inheritance relationship between these classes in different layers,the accuracy of classification can further be improved because the boundary of a patch of a class in a certain layer can be replaced with a more accurate one of the same class in another layer.The whole algorithm was tested by MATLAB simulation.It is revealed that the overall accuracy (OA)is about 85% by using HC and has 5% to 10% better than that by using conventional single-layer classification.%针对城镇绿化植被受可用土地限制,具有分布零散、结构复杂、植被群类型繁多等特点,以及建筑物和其他设施的阴影遮挡等加剧了植被群分类的困难,经典分类方法常常难以适应需求的困境,该文提出了以分层分割/分类和多描述符空间分类对城镇绿化植被群分类的方法,即采用一次采样,多层

  9. Deriving structural and functional insights from a ligand-based hierarchical classification of G protein-coupled receptors.

    Science.gov (United States)

    Attwood, T K; Croning, M D R; Gaulton, A

    2002-01-01

    G protein-coupled receptors (GPCRs) constitute the largest known family of cell-surface receptors. With hundreds of members populating the rhodopsin-like GPCR superfamily and many more awaiting discovery in the human genome, they are of interest to the pharmaceutical industry because of the opportunities they afford for yielding potentially lucrative drug targets. Typical sequence analysis strategies for identifying novel GPCRs tend to involve similarity searches using standard primary database search tools. This will reveal the most similar sequence, generally without offering any insight into its family or superfamily relationships. Conversely, searches of most 'pattern' or family databases are likely to identify the superfamily, but not the closest matching subtype. Here we describe a diagnostic resource that allows identification of GPCRs in a hierarchical fashion, based principally upon their ligand preference. This resource forms part of the PRINTS database, which now houses approximately 250 GPCR-specific fingerprints (http://www.bioinf.man.ac.uk/dbbrowser/gpcrPRINTS/). This collection of fingerprints is able to provide more sensitive diagnostic opportunities than have been realized by related approaches and is currently the only diagnostic tool for assigning GPCR subtypes. Mapping such fingerprints on to three-dimensional GPCR models offers powerful insights into the structural and functional determinants of subtype specificity.

  10. 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.

  11. Hierarchical Classification of Rock and Soil Based on Characteristic Multi-Band Image%一种基于多特征波段岩土层次分类方法

    Institute of Scientific and Technical Information of China (English)

    余先川; 周鑫; 康增基; 安卫杰; 胡丹; 王云涛; 韦京莲; 刘连刚

    2012-01-01

    岩土分类与一般地表的地物分类相比难度大得多,针对已有的分类方法(监督分类和非监督分类)对于岩土分类精度不高、分类效果欠佳问题提出一种基于多特征波段岩土层次分类方法.它是一种自顶向下、逐步求精的层次分类方法,该方法结合无监督分类和监督分类两种分类方法的优势,利用多个特征波段组合,有层次地将不同类型的岩土体逐步分开,实现对岩土的精确分类.对北京市怀柔山区附近的ASTER影像数据进行的岩土分类实验结果表明,基于多特征波段岩土层次分类识别方法能显著提高岩土分类精度,总体精度提高10%,Kappa系数提高了0.1,并且能识别以往分类识别方法难以区分的岩石阴影和水体等地物,能够有效地克服“同物异谱”现象.%The classification of soil and rock is more difficult than classification of general terrain surfaces. The traditional methods (supervised classification and unsupervised classification) often yield to low accuracies and poor classification effects when applied to soil and rock classification, a new hierarchical classification algorithm based on characteristic multi-band image is proposed. The new algorithm is a top-down, gradually refinement hierarchical classification method which combines with both advantages of supervised classification and unsupervised classification. The new proposed method achieved the high accurate classification of soil and rock by separating rock and soil step by step hierarchically while making use of several characteristic band groups. Experimental results show that the new proposed method has better performance in improving the classification accuracies, the overall accuracy increases 10% and Kappa coefficient improves 0.1. Also, the new method can overcome "same things with different spectrums" phenomenon effectively.

  12. A new map of standardized terrestrial ecosystems of Africa

    Science.gov (United States)

    Sayre, Roger G.; Comer, Patrick; Hak, Jon; Josse, Carmen; Bow, Jacquie; Warner, Harumi; Larwanou, Mahamane; Kelbessa, Ensermu; Bekele, Tamrat; Kehl, Harald; Amena, Ruba; Andriamasimanana, Rado; Ba, Taibou; Benson, Laurence; Boucher, Timothy; Brown, Matthew; Cress, Jill J.; Dassering, Oueddo; Friesen, Beverly A.; Gachathi, Francis; Houcine, Sebei; Keita, Mahamadou; Khamala, Erick; Marangu, Dan; Mokua, Fredrick; Morou, Boube; Mucina, Ladislav; Mugisha, Samuel; Mwavu, Edward; Rutherford, Michael; Sanou, Patrice; Syampungani, Stephen; Tomor, Bojoi; Vall, Abdallahi Ould Mohamed; Vande Weghe, Jean Pierre; Wangui, Eunice; Waruingi, Lucy

    2013-01-01

    Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In

  13. 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,

  14. 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

  15. The Revelation about the Information Network Planning and Construction by the Road Classification System and Hierarchical Planning Management Mode%道路分级体系和分层规划管理模式对信息管网规划及建设的启示

    Institute of Scientific and Technical Information of China (English)

    殷洁琰

    2013-01-01

    This paper condects a deep investigation about the road classification system and hierarchical planning management mode of China. It uses the characteristic of road classification system and hierarchical planning management mode for reference to analyzing the planning of information network. Based on the similarity between information network and road network, suggestions on the classification system and hierarchical planning management mode for information network are put forword.%  从信息网络与道路网络内涵的相关性、结构的相似性、建设的关联性出发,分析借鉴目前成熟的道路分级体系和分层规划管理模式,提出对信息管网在合理的等级体系和分层管理模式下进行统一规划建设的建议。

  16. USEPA'S FINAL ECOSYSTEM AND SERVICES (FEGS) CLASSIFICATION SYSTEM: Concept to Implementation and Links with EnviroAtlas

    Science.gov (United States)

    For the last decade ecosystem services have received increasing focus, yet the natural and social scientists working on mainstreaming these concepts are still struggling with the basic issues. One of such issue is developing a framework that avoids double counting, provides guid...

  17. Economics of ecosystem services: theoretical and methodological foundations

    Directory of Open Access Journals (Sweden)

    Ye.V. Mishenin

    2015-06-01

    such as: support of the food chain, harvesting of animals or plants, and the provision of clean water or scenic views. In order for an ecosystem to provide services to humans, some interaction with humans is required. Thus, functions of ecosystems are value-neutral, while their services have value to society. Thus, the term «ecosystem servicers» is determined as the flows of economic benefits and values that economic actors and other stakeholders receive from the use of existing ecosystem functions, as well as those resulting from the generation, reproduction, regulation of ecosystem processes and which are formed as a result of targeted activities of various entities with different types of the ownership and hierarchical levels of management. Conclusions and directions of further researches. Definition of ecosystem services as an economic category is the central element of a comprehensive system of relationships between the functioning of natural ecosystems, economic activities and prosperity of society. The interrelation between concepts, ecosystem services and natural capital, natural resources, ecosystem functions deepen the essence-conceptual apparatus of the environmental economics. It is expedient to use some individual criteria and groups of determinants during the classification of ecosystem servicers such as: functional and regulatory features, ecosystem features, time features and group of organizational and economic features. Further researches should be addressed to the management, reproduction and protection of ecosystems and ecosystem services from the perspectives of implementation of the mechanism of nature management at different hierarchical levels.

  18. 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.

  19. CLASSIFICATION AND TYPES OF PREFERENTIAL FLOW FOR A DARK CONIFEROUS FOREST ECOSYSTEM IN THE UPPER REACH AREA OF THE YANGTZE RIVER

    Institute of Scientific and Technical Information of China (English)

    Jianzhi NIU; Xinxiao YU; Zhiqiang ZHANG; Yutao ZHAO

    2007-01-01

    Preferential flow is the ordinary phenomenon of rapid and non-equilibrium transport of water and solutes occurring in most soil. It causes latent pollution of ground and surface waters and affects runoff yield and flow concentration. This paper studies preferential flow for a dark coniferous ecosystem in the upper reach area of the Yangtze River, establishes a classification for the preferential flow and discusses types of preferential flow with a soil column experiment using a homemade apparatus and dye-tracer analysis. The preferential flow is mainly unsaturated gravitational flow in the upper layer of the slope deposit for mature forest soil, which is dominated by a wetness front, and the flow gradually transforms to macroporous flow as the soil layer deepens. The observed preferential flow in the young, middle-aged and over-mature forests that have grown on glacial lateral moraines is macroporous flow. The purpose of this research is to analyze systemically the behavior of soil water movement for a dark coniferous forest ecosystem in the upper reach area of the Yangtze River and to provide a theoretical basis for effective watershed management.

  20. Ecosystem Service Valuation Assessments for Protected Area Management: A Case Study Comparing Methods Using Different Land Cover Classification and Valuation Approaches.

    Directory of Open Access Journals (Sweden)

    Charlotte E L Whitham

    Full Text Available Accurate and spatially-appropriate ecosystem service valuations are vital for decision-makers and land managers. Many approaches for estimating ecosystem service value (ESV exist, but their appropriateness under specific conditions or logistical limitations is not uniform. The most accurate techniques are therefore not always adopted. Six different assessment approaches were used to estimate ESV for a National Nature Reserve in southwest China, across different management zones. These approaches incorporated two different land-use land cover (LULC maps and development of three economic valuation techniques, using globally or locally-derived data. The differences in ESV across management zones for the six approaches were largely influenced by the classifications of forest and farmland and how they corresponded with valuation coefficients. With realistic limits on access to time, data, skills and resources, and using acquired estimates from globally-relevant sources, the Buffer zone was estimated as the most valuable (2.494 million ± 1.371 million CNY yr(-1 km(-2 and the Non-protected zone as the least valuable (770,000 ± 4,600 CNY yr(-1 km(-2. However, for both LULC maps, when using the locally-based and more time and skill-intensive valuation approaches, this pattern was generally reversed. This paper provides a detailed practical example of how ESV can differ widely depending on the availability and appropriateness of LULC maps and valuation approaches used, highlighting pitfalls for the managers of protected areas.

  1. Ecosystem Service Valuation Assessments for Protected Area Management: A Case Study Comparing Methods Using Different Land Cover Classification and Valuation Approaches.

    Science.gov (United States)

    Whitham, Charlotte E L; Shi, Kun; Riordan, Philip

    2015-01-01

    Accurate and spatially-appropriate ecosystem service valuations are vital for decision-makers and land managers. Many approaches for estimating ecosystem service value (ESV) exist, but their appropriateness under specific conditions or logistical limitations is not uniform. The most accurate techniques are therefore not always adopted. Six different assessment approaches were used to estimate ESV for a National Nature Reserve in southwest China, across different management zones. These approaches incorporated two different land-use land cover (LULC) maps and development of three economic valuation techniques, using globally or locally-derived data. The differences in ESV across management zones for the six approaches were largely influenced by the classifications of forest and farmland and how they corresponded with valuation coefficients. With realistic limits on access to time, data, skills and resources, and using acquired estimates from globally-relevant sources, the Buffer zone was estimated as the most valuable (2.494 million ± 1.371 million CNY yr(-1) km(-2)) and the Non-protected zone as the least valuable (770,000 ± 4,600 CNY yr(-1) km(-2)). However, for both LULC maps, when using the locally-based and more time and skill-intensive valuation approaches, this pattern was generally reversed. This paper provides a detailed practical example of how ESV can differ widely depending on the availability and appropriateness of LULC maps and valuation approaches used, highlighting pitfalls for the managers of protected areas.

  2. Proposta de classificação hierarquizada dos modelos de solução para o problema de job shop scheduling A proposition of hierarchical classification for solution models in the job shop scheduling problem

    Directory of Open Access Journals (Sweden)

    Ricardo Ferrari Pacheco

    1999-04-01

    Full Text Available Este artigo propõe uma classificação hierarquizada dos modelos utilizados na solução do problema de programação da produção intermitente do tipo job shop, incluindo tanto os que fornecem solução ótima, quanto os modelos heurísticos mais recentes baseados em métodos de busca estendida. Por meio dessa classificação obteve-se um painel amplo dos modelos existentes, evidenciando as diferentes abordagens do problema e suas soluções, com o objetivo de proporcionar uma orientação preliminar na escolha do modelo de job shop scheduling mais adequado.This paper proposes a hierarchical model classification used in the job shop scheduling problem, including those that provide an optimal solution and the more recent ones based on heuristics, called extended search methods. A panel with the existing models is obtained by this classification, and solutions and approach differences are highlighted with the aim of a preliminary orientation on the choice of a more adequate job shop scheduling model.

  3. 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

  4. 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.

  5. Hierarchical Matching Kernel for Buildings Classification in Remote Sensing Images%用于遥感图像建筑物目标分类的层次匹配核

    Institute of Scientific and Technical Information of China (English)

    田昊; 李国辉; 廉蔺; 贾立

    2011-01-01

    This paper proposes a kernel function - hierarchical log-polar matching kernel which making use of the feature spatial information for building classification in remote sensing images. It extracts image local features, uses traditional clustering methods to quantize all feature vectors into several different types, and then partitions the image into multi-level increasingly fine log-polar "sub-regions (bins)". By computing histograms of local features found inside each sub-region in each level, the weighted multi-scale histograms are formulated. By summing all weighted multi-level histograms of each feature vector, the final hierarchical log-polar kernel is established. The building classification is done with a support vector machine (SVM) trained by using the "one-versus-all" rule. The experimental results on Caltech-256 database and real remote sensing images demonstrate the efficiency and effectiveness of the proposed kernel.%提出了一种利用图像特征空间信息的核函数——层次对数极坐标匹配核,用于遥感图像建筑物目标的分类。对图像进行特征提取,并将特征映射到已聚类好的“码本”中,量化为有限个类别。将图像由粗到细划分为多个层次的对数极坐标系下的“子区域(单元格)”。比对落入同一层次、同一“子区域(单元格)”的每类特征的直方图交集,建立加权的多尺度直方图,将多个特征多尺度直方图合并,得到最终的核函数,并利用“一对多”的支持向量机(support vector machine,SVM)完成建筑物的分类。对标准数据库Caltech-256和自建遥感图像数据集进行实验,结果证明了该核函数的有效性。

  6. New hierarchical classification of food items for the assessment of exposure to packaging migrants: use of hub codes for different food groups.

    Science.gov (United States)

    Northing, P; Oldring, P K T; Castle, L; Mason, P A S S

    2009-04-01

    This paper describes development work undertaken to expand the capabilities of an existing two-dimensional probabilistic modelling approach for assessing dietary exposure to chemicals migrating out of food contact materials. A new three-level hub-coding system has been devised for coding different food groups with regards to their consumption by individuals. The hub codes can be used at three different levels representing a high, medium and low level of aggregation of individual food items. The hub codes were developed because they have a greater relevance to packaging migration than coding used (largely and historically) for nutritional purposes. Also, the hub codes will assist pan-europeanization of the exposure model in the future, when up to 27 or more different food coding systems from 27 European Union Member States will have to be assimilated into the modelling approach. The applicability of the model with the new coding system has been tested by incorporating newly released 2001 UK consumption data. The example used was exposure to a hypothetical migrant from coated metal packaging for foodstuffs. When working at the three hierarchical levels, it was found that the tiered approach gave conservative estimates at the cruder level of refinement and a more realistic assessment was obtained as the refinement progressed. The work overall revealed that changes in eating habits over time had a relatively small impact on estimates of exposure. More important impacts are changes over time in packaging usage, packaging composition and migration levels. For countries like the UK, which has sophisticated food consumption data, it is uncertainties in these other areas that need to be addressed by new data collection.

  7. TWO-STAGE CHARACTER CLASSIFICATION : A COMBINED APPROACH OF CLUSTERING AND SUPPORT VECTOR CLASSIFIERS

    NARCIS (Netherlands)

    Vuurpijl, L.; Schomaker, L.

    2000-01-01

    This paper describes a two-stage classification method for (1) classification of isolated characters and (2) verification of the classification result. Character prototypes are generated using hierarchical clustering. For those prototypes known to sometimes produce wrong classification results, a

  8. Learning Apache Mahout classification

    CERN Document Server

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  9. 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.

  10. Principles for ecological classification

    Science.gov (United States)

    Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

    1999-01-01

    The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

  11. 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

  12. 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...

  13. Hierarchical and dynamic seascapes: A quantitative framework for scaling pelagic biogeochemistry and ecology

    Science.gov (United States)

    Kavanaugh, Maria T.; Hales, Burke; Saraceno, Martin; Spitz, Yvette H.; White, Angelicque E.; Letelier, Ricardo M.

    2014-01-01

    Comparative analyses of oceanic ecosystems require an objective framework to define coherent study regions and scale the patterns and processes observed within them. We applied the hierarchical patch mosaic paradigm of landscape ecology to the study of the seasonal variability of the North Pacific to facilitate comparative analysis between pelagic ecosystems and provide spatiotemporal context for Eulerian time-series studies. Using 13-year climatologies of sea surface temperature (SST), photosynthetically active radiation (PAR), and chlorophyll a (chl-a), we classified seascapes in environmental space that were monthly-resolved, dynamic and nested in space and time. To test the assumption that seascapes represent coherent regions with unique biogeochemical function and to determine the hierarchical scale that best characterized variance in biogeochemical parameters, independent data sets were analyzed across seascapes using analysis of variance (ANOVA), nested-ANOVA and multiple linear regression (MLR) analyses. We also compared the classification efficiency (as defined by the ANOVA F-statistic) of resultant dynamic seascapes to a commonly-used static classification system. Variance of nutrients and net primary productivity (NPP) were well characterized in the first two levels of hierarchy of eight seascapes nested within three superseascapes (R2 = 0.5-0.7). Dynamic boundaries at this level resulted in a nearly 2-fold increase in classification efficiency over static boundaries. MLR analyses revealed differential forcing on pCO2 across seascapes and hierarchical levels and a 33% reduction in mean model error with increased partitioning (from 18.5 μatm to 12.0 μatm pCO2). Importantly, the empirical influence of seasonality was minor across seascapes at all hierarchical levels, suggesting that seascape partitioning minimizes the effect of non-hydrographic variables. As part of the emerging field of pelagic seascape ecology, this effort provides an improved means of

  14. ECOLOGICAL CLASSIFICATION OF LAND AND ECOSYSTEM MAPPING. TOWARDS THE IMPLEMENTATION OF ACTION 5 OF THE EUROPEAN BIODIVERSITY STRATEGY TO 2020 IN ITALY.

    Directory of Open Access Journals (Sweden)

    G. Capotorti

    2014-04-01

    Full Text Available The aim of the present paper is to illustrate the basic data and the methodological approach proposed for the implementation of Action 5 of the European Biodiversity Strategy in Italy. In particular, it focuses on a model for ecosystem mapping and characterisation at the country level that has been built with the interdisciplinary involvement of geobotanists, functional ecologists, forest scientists and zoologists. The first operational steps of the model are based on the cartographic integration between potential natural vegetation, biogeographic regions, and land cover maps. The final step entails characterising the mapped ecosystems in terms of Habitats Directive, local occurrence of threatened plant species and faunal components. The model is going to be tested in Italy, but should also be applied elsewhere in Mediterranean Europe, especially in those countries that have a comparable ecological complexity.

  15. Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDAR Data

    Directory of Open Access Journals (Sweden)

    Gregory P. Asner

    2012-11-01

    Full Text Available Mapping the spatial distribution of plant species in savannas provides insight into the roles of competition, fire, herbivory, soils and climate in maintaining the biodiversity of these ecosystems. This study focuses on the challenges facing large-scale species mapping using a fusion of Light Detection and Ranging (LiDAR and hyperspectral imagery. Here we build upon previous work on airborne species detection by using a two-stage support vector machine (SVM classifier to first predict species from hyperspectral data at the pixel scale. Tree crowns are segmented from the lidar imagery such that crown-level information, such as maximum tree height, can then be combined with the pixel-level species probabilities to predict the species of each tree. An overall prediction accuracy of 76% was achieved for 15 species. We also show that bidirectional reflectance distribution (BRDF effects caused by anisotropic scattering properties of savanna vegetation can result in flight line artifacts evident in species probability maps, yet these can be largely mitigated by applying a semi-empirical BRDF model to the hyperspectral data. We find that confronting these three challenges—reflectance anisotropy, integration of pixel- and crown-level data, and crown delineation over large areas—enables species mapping at ecosystem scales for monitoring biodiversity and ecosystem function.

  16. [Urban ecosystem services: A review].

    Science.gov (United States)

    Mao, Qi-zheng; Huang, Gan-lin; Wu, Jian-guo

    2015-04-01

    Maintaining and improving ecosystem services in urban areas and human well-being are essential for sustainable development and therefore constitute an important topic in urban ecology. Here we reviewed studies on ecosystem services in urban areas. Based on the concept and classification of urban ecosystem services, we summarized characteristics of urban ecosystem services, including the human domination, high demand of ecosystem services in urban areas, spatial heterogeneity and temporal dynamics of ecosystem services supply and demand in urban areas, multi-services of urban green infrastructures, the socio-economic dimension of ecosystem services supply and ecosystem disservices in urban areas. Among different urban ecosystem services, the regulating service and cultural service are particularly indispensable to benefit human health. We pointed out that tradeoffs among different types of ecosystem services mostly occur between supportive service and cultural service, as well as regulating service and cultural service. In particular, we emphasized the relationship between landscape design (i.e. green infrastructure) and ecosystem services supply. Finally, we discussed current gaps to link urban ecosystem services studies to landscape design and management and pointed out several directions for future research in urban ecosystem services.

  17. Formulating an ecosystem approach to environmental protection

    Science.gov (United States)

    Gonzalez, Otto J.

    1996-09-01

    The U.S. Environmental Protection Agency (EPA) has embraced a new strategy of environmental protection that is place-driven rather than program-driven. This new approach focuses on the protection of entire ecosystems. To develop an effective strategy of ecosystem protection, however, EPA will need to: (1) determine how to define and delineate ecosystems and (2) categorize threats to individual ecosystems and priority rank ecosystems at risk. Current definitions of ecosystem in use at EPA are inadequate for meaningful use in a management or regulatory context. A landscape-based definition that describes an ecosystem as a volumetric unit delineated by climatic and landscape features is suggested. Following this definition, ecosystems are organized hierarchically, from megaecosystems, which exist on a continental scale (e.g., Great Lakes), to small local ecosystems. Threats to ecosystems can generally be categorized as: (1) ecosystem degradation (occurs mainly through pollution) (2) ecosystem alteration (physical changes such as water diversion), and (3) ecosystem removal (e.g., conversion of wetlands or forest to urban or agricultural lands). Level of threat (i.e., how imminent), and distance from desired future condition are also important in evaluating threats to ecosystems. Category of threat, level of threat, and “distance” from desired future condition can be combined into a three-dimensional ranking system for ecosystems at risk. The purpose of the proposed ranking system is to suggest a preliminary framework for agencies such as EPA to prioritize responses to ecosystems at risk.

  18. Guidelines for a priori grouping of species in hierarchical community models

    Science.gov (United States)

    Pacifici, Krishna; Zipkin, Elise; Collazo, Jaime; Irizarry, Julissa I.; DeWan, Amielle A.

    2014-01-01

    Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species-level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community-level approaches is that parameter estimates for data-poor species are more precise as the estimation process borrows from data-rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group-level metrics, and individual-level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group-level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity

  19. Ecosystem services

    Science.gov (United States)

    Trista Patterson

    2014-01-01

    Since its inception, the ecosystem service approach has stimulated interest from numerous planning, management, and partnership perspectives. To date, however, research that quantifies ecosystem services in the study area (in the form of explicit ecosystem service studies) has been limited. This chapter reviews and synthesizes the concept of ecosystem services,...

  20. Hierarchical Approach for Online Mining--Emphasis towards Software Metrics

    CERN Document Server

    Saradhi, M V Vijaya; Satish, P

    2010-01-01

    Several multi-pass algorithms have been proposed for Association Rule Mining from static repositories. However, such algorithms are incapable of online processing of transaction streams. In this paper we introduce an efficient single-pass algorithm for mining association rules, given a hierarchical classification amongest items. Processing efficiency is achieved by utilizing two optimizations, hierarchy aware counting and transaction reduction, which become possible in the context of hierarchical classification. This paper considers the problem of integrating constraints that are Boolean expression over the presence or absence of items into the association discovery algorithm. This paper present three integrated algorithms for mining association rules with item constraints and discuss their tradeoffs. It is concluded that the variation of complexity depends on the measure of DIT (Depth of Inheritance Tree) and NOC (Number of Children) in the context of Hierarchical Classification.

  1. A Global Classification of Contemporary Fire Regimes

    Science.gov (United States)

    Norman, S. P.; Kumar, J.; Hargrove, W. W.; Hoffman, F. M.

    2014-12-01

    Fire regimes provide a sensitive indicator of changes in climate and human use as the concept includes fire extent, season, frequency, and intensity. Fires that occur outside the distribution of one or more aspects of a fire regime may affect ecosystem resilience. However, global scale data related to these varied aspects of fire regimes are highly inconsistent due to incomplete or inconsistent reporting. In this study, we derive a globally applicable approach to characterizing similar fire regimes using long geophysical time series, namely MODIS hotspots since 2000. K-means non-hierarchical clustering was used to generate empirically based groups that minimized within-cluster variability. Satellite-based fire detections are known to have shortcomings, including under-detection from obscuring smoke, clouds or dense canopy cover and rapid spread rates, as often occurs with flashy fuels or during extreme weather. Such regions are free from preconceptions, and the empirical, data-mining approach used on this relatively uniform data source allows the region structures to emerge from the data themselves. Comparing such an empirical classification to expectations from climate, phenology, land use or development-based models can help us interpret the similarities and differences among places and how they provide different indicators of changes of concern. Classifications can help identify where large infrequent mega-fires are likely to occur ahead of time such as in the boreal forest and portions of the Interior US West, and where fire reports are incomplete such as in less industrial countries.

  2. Classification of nanopolymers

    Energy Technology Data Exchange (ETDEWEB)

    Larena, A; Tur, A [Department of Chemical Industrial Engineering and Environment, Universidad Politecnica de Madrid, E.T.S. Ingenieros Industriales, C/ Jose Gutierrez Abascal, Madrid (Spain); Baranauskas, V [Faculdade de Engenharia Eletrica e Computacao, Departamento de Semicondutores, Instrumentos e Fotonica, Universidade Estadual de Campinas, UNICAMP, Av. Albert Einstein N.400, 13 083-852 Campinas SP Brasil (Brazil)], E-mail: alarena@etsii.upm.es

    2008-03-15

    Nanopolymers with different structures, shapes, and functional forms have recently been prepared using several techniques. Nanopolymers are the most promising basic building blocks for mounting complex and simple hierarchical nanosystems. The applications of nanopolymers are extremely broad and polymer-based nanotechnologies are fast emerging. We propose a nanopolymer classification scheme based on self-assembled structures, non self-assembled structures, and on the number of dimensions in the nanometer range (nD)

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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....

  9. 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...

  10. Ecosystem Jenga!

    Science.gov (United States)

    Umphlett, Natalie; Brosius, Tierney; Laungani, Ramesh; Rousseau, Joe; Leslie-Pelecky, Diandra L.

    2009-01-01

    To give students a tangible model of an ecosystem and have them experience what could happen if a component of that ecosystem were removed; the authors developed a hands-on, inquiry-based activity that visually demonstrates the concept of a delicately balanced ecosystem through a modification of the popular game Jenga. This activity can be…

  11. Natural ecosystems

    Science.gov (United States)

    Fleishman, Erica; Belnap, Jayne; Cobb, Neil; Enquist, Carolyn A.F.; Ford, Karl; MacDonald, Glen; Pellant, Mike; Schoennagel, Tania; Schmit, Lara M.; Schwartz, Mark; van Drunick, Suzanne; Westerling, Anthony LeRoy; Keyser, Alisa; Lucas, Ryan

    2013-01-01

    Natural Ecosystems analyzes the association of observed changes in climate with changes in the geographic distributions and phenology (the timing of blossoms or migrations of birds) for Southwestern ecosystems and their species, portraying ecosystem disturbances—such as wildfires and outbreaks of forest pathogens—and carbon storage and release, in relation to climate change.

  12. Ecosystem Jenga!

    Science.gov (United States)

    Umphlett, Natalie; Brosius, Tierney; Laungani, Ramesh; Rousseau, Joe; Leslie-Pelecky, Diandra L.

    2009-01-01

    To give students a tangible model of an ecosystem and have them experience what could happen if a component of that ecosystem were removed; the authors developed a hands-on, inquiry-based activity that visually demonstrates the concept of a delicately balanced ecosystem through a modification of the popular game Jenga. This activity can be…

  13. KLASTERISASI EKOSISTEM TAMAN NASIONAL GUNUNG MERBABU BERDASARKAN ASPEK BIOLOGIS DAN SOSIAL EKONOMI (Classification Ecosystem of the Gunung Merbabu National Park Based on Biological and Socioeconomic Aspects

    Directory of Open Access Journals (Sweden)

    Dwi Hastuti

    2011-07-01

    Full Text Available ABSTRAK Penelitian ini bertujuan untuk klasterisasi unit ekologis ekosistem Taman Nasional Gunung Merbabu (TNGMb berdasarkan aspek biologis dan sosial ekonomi masyarakat, mengetahui pola pemanfaatan masyarakat terhadap sumberdaya alam TNGMb. Sampel untuk sosial ekonomi sebanyak 310 KK, sedangkan sampel aspek biologis sebanyak 226 titik sampel. Analisis data menggunakan metode Minimum Variance Clustering (Ward Linkage berdasarkan Euclidean Distance dan analisis diskriminan. Hasil klasterisasi unit ekologis TNGMb sebanyak 8 klaster yaitu klaster I (2 responden, dominasi jenis C. sempervirens, klaster J (39 responden, dominasi jenis P. merkusii, A. lophanta, klaster F (210 responden, dominasi jenis P. merkusii, C. sempervirens, C. junghuniana, klaster O (96 responden, dominasi jenis P. merkusii, C. sempervirens, C. junghuniana, klaster Q (54 responden, dominasi jenis P.merkusii, A. lophanta, A. decurens, klaster P (158 responden, dominasi jenis P.merkusii, C. sempervirens, A.decurens, klaster H (34 responden, dominasi jenis P. merkusii, dan klaster R (46 responden, dominasi jenis P. merkusii. Pola pergerakan masyarakat mencakup seluruh klaster dan meliputi zona inti, zona rimba, dan zona pemanfaatan. Pergerakan masyarakat yang mencapai zona inti merupakan faktor yang terpenting untuk dipertimbangkan dalam pengelolaan TNGMb. ABSTRACT The aim of reseach was  clusterization of TNGMb ecosystem based on bioligical and sosio-economical aspect, studying  the pattern utilization of community in order to utilize nature resources in the Gunung Merbabu National Park.  Sosial-economical data was collacted through an interview on 310 KK , while biological data was done on 226 sampel set using systematic sampling. Analysis data using Minimum Variance Clustering (Ward linkage method with Euclidean Distance Measurement (EDM and discriminant analysis. The clusterization ecological unit Gunung Merbabu National Park resulted eight clusters, i.e. cluster I (2

  14. 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.

  15. Hierarchical model of vulnerabilities for emotional disorders.

    Science.gov (United States)

    Norton, Peter J; Mehta, Paras D

    2007-01-01

    Clark and Watson's (1991) tripartite model of anxiety and depression has had a dramatic impact on our understanding of the dispositional variables underlying emotional disorders. More recently, calls have been made to examine not simply the influence of negative affectivity (NA) but also mediating factors that might better explain how NA influences anxious and depressive syndromes (e.g. Taylor, 1998; Watson, 2005). Extending preliminary projects, this study evaluated two hierarchical models of NA, mediating factors of anxiety sensitivity and intolerance of uncertainty, and specific emotional manifestations. Data provided a very good fit to a model elaborated from preliminary studies, lending further support to hierarchical models of emotional vulnerabilities. Implications for classification and diagnosis are discussed.

  16. 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.

  17. 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.

  18. 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%.

  19. 山区LIDAR点云数据的阶层次粗差探测与分析%GROSS ERROR DETECTION AND ANALYSIS BY HIERARCHICAL CLASSIFICATION OF MOUNTAINOUS LIDAR DATA

    Institute of Scientific and Technical Information of China (English)

    李芸; 杨志强; 杨博

    2012-01-01

    Gross error detection is one of the important data processing steps of mountainous LIDAR point cloud data. Through analysing the features of gross error distribution, original LIDAR point cloud data can be divided into extreme outliers, outlier clusters and isolated points. On this basis, the idea of hierarchical gross error detection of mountainous LIDAR point cloud data is proposed, and an example of experimental data is verified. Experimental results show that the method can effectively remove gross errors from original mountainous LIDAR point cloud data, and, to a certain extent, improving the effect of pre-processing of point cloud.%针对山区LIDAR原始点云数据粗差的空间分布特性,将粗差分为极值粗差、粗差簇群和孤立点,在此基础上提出了山区机载LIDAR点云数据粗差探测的阶层次处理,并用实验数据进行了验证.实验结果表明,该方法可以有效地去除山区机载LIDAR原始点云数据中的粗差,在一定程度上提高了点云预处理的效果.

  20. Towards Business Process Management in networked ecosystems

    NARCIS (Netherlands)

    Grondelle, Jeroen; Zoet, Martijn; Versendaal, Johan

    2014-01-01

    Managing and supporting the collaboration between different actors is key in any organizational context, whether of a hierarchical or a networked nature. In the networked context of ecosystems of service providers and other stakeholders, BPM is faced with different challenges than in a conventional

  1. 面向环境卫星变换的分级水系提取研究%Hierarchical Water Extraction from HJ Data Based on Object-oriented Classification

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    以获取干旱半干旱区精准水域分布信息为目标,利用水域的水文特征,采用水系分级化处理方法,分级识别水域信息从而开展基于环境减灾卫星 HJ的水环境遥感识别监测研究。首先对影像进行预处理,构建环境卫星的归一化差异综合水体指数,利用阈值法粗区分水体影像中的面域水体和细小线性水体。构建分离背景条件分离山体阴影、植被、荒漠、裸地等大部分背景信息;然后对影像进行 L BV变化增强;结合 L BV特征与粗提取结果,面向对象分割进行精细化提取面状水体和细小水系;最后利用区域生长算法修复水系断流现象获得最终完整的水体分布情况。结果表明,该方法能够准确识别面域和细小支流水体边界,显著减少植被和阴影对水系边界的影响,基本消除背景值对水体识别的干扰,水系识别完整度为91.3%,用户精度为92%。比常用水体提取方法提取效果好,且同样适用于其他水系。%In order to obtain accurate water distribution information in arid and semi-arid areas ,utilize hydrological characteristics of waters and method of hierarchical hydrography ,and carry out the Remote Sensing Monitoring of Huanjing (HJ) ,First ,the image that is founding the normalized water index extraction of HJ is pre-processd and threshold segmentation is used to differentiate be‐tween water region and narrow water branch .The conditions to separate background information are constructed :hill shade ,vegeta‐tion ,desert ,bare land and so on .Then the images with LBV characteristics are enhanced .LBV features are combined with the crude extraction results .In order to solve the problem of cutoff areas in the river ,the last step is repairing hydrographic net along the growth direction by applying regional growth algorithm .Results show that this method makes full use of hierarchical division of the extraction ,can identify

  2. Guidelines for phytosociological classifications and descriptions of vegetation in southern Africa

    Directory of Open Access Journals (Sweden)

    Leslie R. Brown

    2013-02-01

    Full Text Available Changes in the environment are first observed in changes in the vegetation. Vegetation survey, classification and mapping form the basis on which informed and scientifically defendable decisions on the environment can be taken. The classification and mapping of vegetation is one of the most widely used tools for interpreting complex ecosystems. By identifying different plant communities we are essentially identifying different ecosystems at a particular hierarchical level. Phytosociologists in Europe have been involved in such studies following, in particular, the Braun-Blanquet approach since the early 1900s. In South Africa, such studies were undertaken on a limited basis from the early 1970s and have since then steadily increased. The surveying of the enormous diversity of South African vegetation is one of the objectives of phytosociological studies. The demand for such data has steadily increased over the past few years to guide conservation policies, biodiversity studies and ecosystem management. In South Africa, numerous publications on the vegetation of conservation and other areas in the different biomes have been produced over the last few decades. However, vegetation scientists in South Africa experience unique problems. The purpose of this article is therefore to provide an overview of the history and the specific focus of phytosociological studies in South Africa and to recommend minimum requirements and methods to be followed when conducting such studies. It is believed that the incorporation of these requirements will result in scientifically justifiable research of high quality by phytosociologists in South Africa.Conservation implications: Effective conservation cannot be obtained without a thorough knowledge of the ecosystems present in an area. Consistent vegetation classifications and descriptions form the basis of conservation and monitoring exercises to maintain biodiversity. The incorporation of these guidelines and

  3. 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...

  4. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  5. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    Science.gov (United States)

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  6. 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.

  7. 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).

  8. 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.

  9. 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...

  10. Ecosystem functioning

    National Research Council Canada - National Science Library

    Jax, Kurt

    2010-01-01

    "In the face of decreasing biodiversity and ongoing global changes, maintaining ecosystem functioning is seen both as a means to preserve biological diversity as well as for safeguarding human well...

  11. Ecosystem, Nigeria

    African Journals Online (AJOL)

    Trend of Heavy Metal Concentrations in Lagos Lagoon. Ecosystem ... these various factors, Oyewo (1998) estimated levels of ... Measurement of some physico-chemical parameters ... Further analysis was carried out only where there was a ...

  12. A hierarchical approach to forest landscape pattern characterization.

    Science.gov (United States)

    Wang, Jialing; Yang, Xiaojun

    2012-01-01

    Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

  13. Uncovering ecosystem service bundles through social preferences.

    Directory of Open Access Journals (Sweden)

    Berta Martín-López

    Full Text Available Ecosystem service assessments have increasingly been used to support environmental management policies, mainly based on biophysical and economic indicators. However, few studies have coped with the social-cultural dimension of ecosystem services, despite being considered a research priority. We examined how ecosystem service bundles and trade-offs emerge from diverging social preferences toward ecosystem services delivered by various types of ecosystems in Spain. We conducted 3,379 direct face-to-face questionnaires in eight different case study sites from 2007 to 2011. Overall, 90.5% of the sampled population recognized the ecosystem's capacity to deliver services. Formal studies, environmental behavior, and gender variables influenced the probability of people recognizing the ecosystem's capacity to provide services. The ecosystem services most frequently perceived by people were regulating services; of those, air purification held the greatest importance. However, statistical analysis showed that socio-cultural factors and the conservation management strategy of ecosystems (i.e., National Park, Natural Park, or a non-protected area have an effect on social preferences toward ecosystem services. Ecosystem service trade-offs and bundles were identified by analyzing social preferences through multivariate analysis (redundancy analysis and hierarchical cluster analysis. We found a clear trade-off among provisioning services (and recreational hunting versus regulating services and almost all cultural services. We identified three ecosystem service bundles associated with the conservation management strategy and the rural-urban gradient. We conclude that socio-cultural preferences toward ecosystem services can serve as a tool to identify relevant services for people, the factors underlying these social preferences, and emerging ecosystem service bundles and trade-offs.

  14. SCOR: a structural classification of RNA database.

    Energy Technology Data Exchange (ETDEWEB)

    Klosterman, Peter S.; Tamura, Makio; Holbrook, Stephen R.; Brenner, Steven E.

    2001-10-10

    The Structural Classification of RNA (SCOR) database provides a survey of the three-dimensional motifs contained in 259 NMR and X-ray RNA structures. In one classification, the structures are grouped according to function. The RNA motifs, including internal and external loops, are also organized in a hierarchical classification. The 259 database entries contain 223 internal and 203 external loops; 52 entries consist of fully complementary duplexes. A classification of the well-characterized tertiary interactions found in the larger RNA structures is also included along with examples. The SCOR database is accessible at http://scor.lbl.gov.

  15. SCOR: a Structural Classification of RNA database.

    Science.gov (United States)

    Klosterman, Peter S; Tamura, Makio; Holbrook, Stephen R; Brenner, Steven E

    2002-01-01

    The Structural Classification of RNA (SCOR) database provides a survey of the three-dimensional motifs contained in 259 NMR and X-ray RNA structures. In one classification, the structures are grouped according to function. The RNA motifs, including internal and external loops, are also organized in a hierarchical classification. The 259 database entries contain 223 internal and 203 external loops; 52 entries consist of fully complementary duplexes. A classification of the well-characterized tertiary interactions found in the larger RNA structures is also included along with examples. The SCOR database is accessible at http://scor.lbl.gov.

  16. 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....

  17. 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.

  18. 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.

  19. Designer ecosystems

    NARCIS (Netherlands)

    Awasthi, Ashutosh; Singh, Kripal; O'Grady, Audrey; Courtney, Ronan; Kalra, Alok; Singh, Rana Pratap; Cerda Bolinches, Artemio; Steinberger, Yosef; Patra, D.D.

    2016-01-01

    Increase in human population is accelerating the rate of land use change, biodiversity loss and habitat degradation, triggering a serious threat to life supporting ecosystem services. Existing strategies for biological conservation remain insufficient to achieve a sustainable human-nature relatio

  20. The use of ecological classification in management

    Science.gov (United States)

    Constance A. Carpenter; Wolf-Dieter Busch; David T. Cleland; Juan Gallegos; Rick Harris; ray Holm; Chris Topik; Al Williamson

    1999-01-01

    Ecological classificafion systems range over a variety of scales and reflect a variety of scientific viewpoints. They incorporate or emphasize varied arrays of environmental factors. Ecological classifications have been developed for marine, wetland, lake, stream, and terrestrial ecosystems. What are the benefits of ecological classification for natural resource...

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Uncovering Ecosystem Service Bundles through Social Preferences

    Science.gov (United States)

    Martín-López, Berta; Iniesta-Arandia, Irene; García-Llorente, Marina; Palomo, Ignacio; Casado-Arzuaga, Izaskun; Amo, David García Del; Gómez-Baggethun, Erik; Oteros-Rozas, Elisa; Palacios-Agundez, Igone; Willaarts, Bárbara; González, José A.; Santos-Martín, Fernando; Onaindia, Miren; López-Santiago, Cesar; Montes, Carlos

    2012-01-01

    Ecosystem service assessments have increasingly been used to support environmental management policies, mainly based on biophysical and economic indicators. However, few studies have coped with the social-cultural dimension of ecosystem services, despite being considered a research priority. We examined how ecosystem service bundles and trade-offs emerge from diverging social preferences toward ecosystem services delivered by various types of ecosystems in Spain. We conducted 3,379 direct face-to-face questionnaires in eight different case study sites from 2007 to 2011. Overall, 90.5% of the sampled population recognized the ecosystem’s capacity to deliver services. Formal studies, environmental behavior, and gender variables influenced the probability of people recognizing the ecosystem’s capacity to provide services. The ecosystem services most frequently perceived by people were regulating services; of those, air purification held the greatest importance. However, statistical analysis showed that socio-cultural factors and the conservation management strategy of ecosystems (i.e., National Park, Natural Park, or a non-protected area) have an effect on social preferences toward ecosystem services. Ecosystem service trade-offs and bundles were identified by analyzing social preferences through multivariate analysis (redundancy analysis and hierarchical cluster analysis). We found a clear trade-off among provisioning services (and recreational hunting) versus regulating services and almost all cultural services. We identified three ecosystem service bundles associated with the conservation management strategy and the rural-urban gradient. We conclude that socio-cultural preferences toward ecosystem services can serve as a tool to identify relevant services for people, the factors underlying these social preferences, and emerging ecosystem service bundles and trade-offs. PMID:22720006

  9. Subject Access to Education Literature; Dewey Decimal Classification.

    Science.gov (United States)

    Dickey, Eve M.; Custer, Benjamin A.

    Because of its hierarchical notation, the Dewey Decimal Classification is advantageous for machine searching. However, the increased volume of topics in recent years has made recoding in the system necessary. Education, for example, is a rapidly changing field, and the Dewey Decimal Classification system has not kept pace. As a result subject…

  10. 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.

  11. Biogeographic classification of the Caspian Sea

    DEFF Research Database (Denmark)

    Fendereski, F.; Vogt, M.; Payne, Mark

    2014-01-01

    using the Hierarchical Agglomerative Clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total...... confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics....

  12. 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...

  13. The Multifaceted Aspects of Ecosystem Integrity

    Directory of Open Access Journals (Sweden)

    Simon A. Levin

    1997-06-01

    Full Text Available The need to reduce human impacts on ecosystems creates pressure for adequate response, but the rush to solutions fosters the oversimplification of such notions as sustainable development and ecosystem health. Hence, it favors the tendency to ignore the complexity of natural systems. In this paper, after a brief analysis of the use and abuse of the notion of ecosystem health, we address the problem of a sound definition of ecosystem integrity, critically review the different methodological and conceptual approaches to the management of natural resources, and sketch the practical implications stemming from their implementation. We show thatthere are merits and limitations in different definitions of ecosystem integrity, for each acknowledges different aspects of ecosystem structure and functioning and reflects the subjective perspectives of humans on the value, importance, and role of biological diversity. This evaluation is based on a brief sketch of the links among biodiversity, ecosystem functioning and resilience, and a description of the problems that arise in distinguishing between natural and anthropogenic disturbance. We also emphasize the difficulty of assessing the economic value of species and habitats and the need to use adaptive management policies to deal with uncertainty and ecosystem complexity. In conclusion, while acknowledging that environmental legislation requires objective statements on ecosystem status and trends, we stress that the notion of ecological integrity is so complex that its measure cannot be expressed through a single indicator, but rather requires a set of indicators at different spatial, temporal, and hierarchical levels of ecosystem organization. Ecosystem integrity is not an absolute, monolithic concept. The existence of different sets of values regarding biological diversity and environmental risks must be explicitly accounted for and incorporated in the decision process, rather than ignored or averaged out.

  14. 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...

  15. 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

  16. 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...

  17. Priming Effects Associated with the Hierarchical Levels of Classification Systems

    Science.gov (United States)

    Loehrlein, Aaron J.

    2012-01-01

    The act of categorization produces conceptual representations in memory while knowledge organization (KO) systems provide conceptual representations that are used in information storage and retrieval systems. Previous research has explored how KO systems can be designed to resemble the user's internal conceptual structures. However, the more…

  18. Plant functional group classifications and a generalized hierarchical ...

    African Journals Online (AJOL)

    Yomi

    2010-12-27

    Dec 27, 2010 ... many real world applications in the field of ecological conservation .... recruitment abilities, sensitivity to pollutants, and other .... agriculture promotes evenness and natural pest control. Nature ... Challenging urban ... pulses, soil water, and plant responses. ... The niche exploration pattern of the blue grey.

  19. Priming Effects Associated with the Hierarchical Levels of Classification Systems

    Science.gov (United States)

    Loehrlein, Aaron J.

    2012-01-01

    The act of categorization produces conceptual representations in memory while knowledge organization (KO) systems provide conceptual representations that are used in information storage and retrieval systems. Previous research has explored how KO systems can be designed to resemble the user's internal conceptual structures. However, the more…

  20. Incremental concept learning with few training examples and hierarchical classification

    NARCIS (Netherlands)

    Bouma, H.; Eendebak, P.T.; Schutte, K.; Azzopardi, G.; Burghouts, G.J.

    2015-01-01

    Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible

  1. Incremental concept learning with few training examples and hierarchical classification

    NARCIS (Netherlands)

    Bouma, H.; Eendebak, P.T.; Schutte, K.; Azzopardi, G.; Burghouts, G.J.

    2015-01-01

    Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible w

  2. 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...

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Hierarchical clusters of phytoplankton variables in dammed water bodies

    Science.gov (United States)

    Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

    2017-06-01

    In this paper a dataset containing biological variables of the water column of several Portuguese reservoirs is analyzed. Hierarchical cluster analysis is used to obtain clusters of phytoplankton variables of the phylum Cyanophyta, with the objective of validating the classification of Portuguese reservoirs previewly presented in [1] which were divided into three clusters: (1) Interior Tagus and Aguieira; (2) Douro; and (3) Other rivers. Now three new clusters of Cyanophyta variables were found. Kruskal-Wallis and Mann-Whitney tests are used to compare the now obtained Cyanophyta clusters and the previous Reservoirs clusters, in order to validate the classification of the water quality of reservoirs. The amount of Cyanophyta algae present in the reservoirs from the three clusters is significantly different, which validates the previous classification.

  8. A receptor-based analysis of local ecosystems in the human brain.

    Science.gov (United States)

    Janušonis, Skirmantas

    2017-03-20

    As a complex system, the brain is a self-organizing entity that depends on local interactions among cells. Its regions (anatomically defined nuclei and areas) can be conceptualized as cellular ecosystems, but the similarity of their functional profiles is poorly understood. The study used the Allen Human Brain Atlas to classify 169 brain regions into hierarchically-organized environments based on their expression of 100 G protein-coupled neurotransmitter receptors, with no a priori reference to the regions' positions in the brain's anatomy or function. The analysis was based on hierarchical clustering, and multiscale bootstrap resampling was used to estimate the reliability of detected clusters. The study presents the first unbiased, hierarchical tree of functional environments in the human brain. The similarity of brain regions was strongly influenced by their anatomical proximity, even when they belonged to different functional systems. Generally, spatial vicinity trumped long-range projections or network connectivity. The main cluster of brain regions excluded the dentate gyrus of the hippocampus. The nuclei of the amygdala formed a cluster irrespective of their striatal or pallial origin. In its receptor profile, the hypothalamus was more closely associated with the midbrain than with the thalamus. The cerebellar cortical areas formed a tight and exclusive cluster. Most of the neocortical areas (with the exception of some occipital areas) clustered in a large, statistically well supported group that included no other brain regions. This study adds a new dimension to the established classifications of brain divisions. In a single framework, they are reconsidered at multiple scales-from individual nuclei and areas to their groups to the entire brain. The analysis provides support for predictive models of brain self-organization and adaptation.

  9. Monitoring Post Disturbance Forest Regeneration with Hierarchical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    L. Monika Moskal

    2013-10-01

    Full Text Available The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT in image segmentation, and to apply the object-based image analysis (OBIA approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a methodology to classify hyperspatial (high-spatial imagery to fine detail level of tree crowns, shadows and understory, while still allowing discrimination between density classes and mature forest versus burn classes. At the most detailed hierarchical Level I classification accuracies reached 78.8%, a Level II stand density classification produced accuracies of 89.1% and the same accuracy was achieved by the coarse general classification at Level III. Our interpretation of these results suggests hyperspatial imagery can be applied to post-fire forest density and regeneration mapping.

  10. Terrestrial ecosystems - Isobioclimates of the conterminous United States

    Science.gov (United States)

    Cress, Jill J.; Sayre, Roger G.; Comer, Patrick; Warner, Harumi

    2009-01-01

    As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated isobioclimate classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America (Sayre and others, 2008) and now being implemented globally, was used to model the ecosystem distributions. Bioclimate regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and are therefore one of the key input layers in this biophysical stratification.

  11. Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery

    Science.gov (United States)

    Mahdianpari, Masoud; Salehi, Bahram; Mohammadimanesh, Fariba; Motagh, Mahdi

    2017-08-01

    Wetlands are important ecosystems around the world, although they are degraded due both to anthropogenic and natural process. Newfoundland is among the richest Canadian province in terms of different wetland classes. Herbaceous wetlands cover extensive areas of the Avalon Peninsula, which are the habitat of a number of animal and plant species. In this study, a novel hierarchical object-based Random Forest (RF) classification approach is proposed for discriminating between different wetland classes in a sub-region located in the north eastern portion of the Avalon Peninsula. Particularly, multi-polarization and multi-frequency SAR data, including X-band TerraSAR-X single polarized (HH), L-band ALOS-2 dual polarized (HH/HV), and C-band RADARSAT-2 fully polarized images, were applied in different classification levels. First, a SAR backscatter analysis of different land cover types was performed by training data and used in Level-I classification to separate water from non-water classes. This was followed by Level-II classification, wherein the water class was further divided into shallow- and deep-water classes, and the non-water class was partitioned into herbaceous and non-herbaceous classes. In Level-III classification, the herbaceous class was further divided into bog, fen, and marsh classes, while the non-herbaceous class was subsequently partitioned into urban, upland, and swamp classes. In Level-II and -III classifications, different polarimetric decomposition approaches, including Cloude-Pottier, Freeman-Durden, Yamaguchi decompositions, and Kennaugh matrix elements were extracted to aid the RF classifier. The overall accuracy and kappa coefficient were determined in each classification level for evaluating the classification results. The importance of input features was also determined using the variable importance obtained by RF. It was found that the Kennaugh matrix elements, Yamaguchi, and Freeman-Durden decompositions were the most important parameters

  12. Hierarchical modelling of temperature and habitat size effects on population dynamics of North Atlantic cod

    DEFF Research Database (Denmark)

    Mantzouni, Irene; Sørensen, Helle; O'Hara, Robert B.;

    2010-01-01

    and Beverton and Holt stock–recruitment (SR) models were extended by applying hierarchical methods, mixed-effects models, and Bayesian inference to incorporate the influence of these ecosystem factors on model parameters representing cod maximum reproductive rate and carrying capacity. We identified...

  13. How plant functional traits cascade to microbial function and ecosystem services in mountain grasslands

    Science.gov (United States)

    Lavorel, S.; Grigulis, K.; Krainer, U.; Legay, N.; Turner, C.; Dumont, M.; Kastl, E.; Arnoldi, C.; Bardgett, R.; Poly, F.; Pommier, T.; Schloter, M.; Tappeiner, U.; Bahn, M.; Clément, J.-C.

    2012-04-01

    1. There is growing evidence that plant functional diversity and microbial communities of soil are tightly coupled, and that this coupling influences a range of ecosystem functions. Moreover, it has been hypothesized that changes in the nature of interactions between plant functional diversity and microbial communities along environmental gradients contributes to variation in the delivery of ecosystem services. Although there is empirical support for such relationships using broad plant and microbial functional classifications, or from studies of plant monocultures, such relationships and their consequences for ecosystem services have not been quantified under complex field conditions with diverse plant communities. 2. We aimed to provide an explicit quantification of how plant and microbial functional properties interplay to determine key ecosystem functions underlying ecosystem services provided by grasslands. At three mountain grassland sites in the French Alps, Austrian Tyrol and northern England, we quantified, along gradients of management intensity, (i) plant functional diversity, (ii) soil microbial community composition and parameters associated with nitrogen cycling, and (iii) key ecosystem processes related to the carbon and nitrogen cycles including aboveground biomass production, standing litter, litter decomposition, soil organic matter and nitrate and ammonium leaching . Considering that plants strongly determine microbial communities, we used a hierarchical approach that considered first direct effects of plant traits and then effects of soil microorganisms on processes, to determine the relative effects of plant and microbial functional parameters on key ecosystem properties. 3. We identified a gradient of relative effects of plant and microbial traits from properties controlled mostly by aboveground processes, such as plant biomass production and standing litter, to properties controlled mostly by microbial processes, such as soil leaching of

  14. Conceptual hierarchical modeling to describe wetland plant community organization

    Science.gov (United States)

    Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.

    2010-01-01

    Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.

  15. 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.

  16. Microbial Ecosystems, Protection of

    NARCIS (Netherlands)

    Bodelier, P.L.E.; Nelson, K.E.

    2014-01-01

    Synonyms Conservation of microbial diversity and ecosystem functions provided by microbes; Preservation of microbial diversity and ecosystem functions provided by microbes Definition The use, management, and conservation of ecosystems in order to preserve microbial diversity and functioning.

  17. Net Ecosystem Carbon Flux

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Net Ecosystem Carbon Flux is defined as the year-over-year change in Total Ecosystem Carbon Stock, or the net rate of carbon exchange between an ecosystem and the...

  18. Microbial Ecosystems, Protection of

    NARCIS (Netherlands)

    Bodelier, P.L.E.; Nelson, K.E.

    2014-01-01

    Synonyms Conservation of microbial diversity and ecosystem functions provided by microbes; Preservation of microbial diversity and ecosystem functions provided by microbes Definition The use, management, and conservation of ecosystems in order to preserve microbial diversity and functioning. Introdu

  19. 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...

  20. 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...

  1. Gene function prediction based on the Gene Ontology hierarchical structure.

    Science.gov (United States)

    Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

    2014-01-01

    The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

  2. Astronomical Ecosystems

    Science.gov (United States)

    Neuenschwander, D. E.; Finkenbinder, L. R.

    2004-05-01

    Just as quetzals and jaguars require specific ecological habitats to survive, so too must planets occupy a tightly constrained astronomical habitat to support life as we know it. With this theme in mind we relate the transferable features of our elementary astronomy course, "The Astronomical Basis of Life on Earth." Over the last five years, in a team-taught course that features a spring break field trip to Costa Rica, we have introduced astronomy through "astronomical ecosystems," emphasizing astronomical constraints on the prospects for life on Earth. Life requires energy, chemical elements, and long timescales, and we emphasize how cosmological, astrophysical, and geological realities, through stabilities and catastrophes, create and eliminate niches for biological life. The linkage between astronomy and biology gets immediate and personal: for example, studies in solar energy production are followed by hikes in the forest to examine the light-gathering strategies of photosynthetic organisms; a lesson on tides is conducted while standing up to our necks in one on a Pacific beach. Further linkages between astronomy and the human timescale concerns of biological diversity, cultural diversity, and environmental sustainability are natural and direct. Our experience of teaching "astronomy as habitat" strongly influences our "Astronomy 101" course in Oklahoma as well. This "inverted astrobiology" seems to transform our student's outlook, from the universe being something "out there" into something "we're in!" We thank the SNU Science Alumni support group "The Catalysts," and the SNU Quetzal Education and Research Center, San Gerardo de Dota, Costa Rica, for their support.

  3. Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks

    Science.gov (United States)

    Zuo, Zhen; Shuai, Bing; Wang, Gang; Liu, Xiao; Wang, Xingxing; Wang, Bing; Chen, Yushi

    2016-07-01

    Existing deep convolutional neural networks (CNNs) have shown their great success on image classification. CNNs mainly consist of convolutional and pooling layers, both of which are performed on local image areas without considering the dependencies among different image regions. However, such dependencies are very important for generating explicit image representation. In contrast, recurrent neural networks (RNNs) are well known for their ability of encoding contextual information among sequential data, and they only require a limited number of network parameters. General RNNs can hardly be directly applied on non-sequential data. Thus, we proposed the hierarchical RNNs (HRNNs). In HRNNs, each RNN layer focuses on modeling spatial dependencies among image regions from the same scale but different locations. While the cross RNN scale connections target on modeling scale dependencies among regions from the same location but different scales. Specifically, we propose two recurrent neural network models: 1) hierarchical simple recurrent network (HSRN), which is fast and has low computational cost; and 2) hierarchical long-short term memory recurrent network (HLSTM), which performs better than HSRN with the price of more computational cost. In this manuscript, we integrate CNNs with HRNNs, and develop end-to-end convolutional hierarchical recurrent neural networks (C-HRNNs). C-HRNNs not only make use of the representation power of CNNs, but also efficiently encodes spatial and scale dependencies among different image regions. On four of the most challenging object/scene image classification benchmarks, our C-HRNNs achieve state-of-the-art results on Places 205, SUN 397, MIT indoor, and competitive results on ILSVRC 2012.

  4. Assessment of Heart Disease using Fuzzy Classification Techniques

    Directory of Open Access Journals (Sweden)

    Horia F. Pop

    2001-01-01

    Full Text Available In this paper we discuss the classification results of cardiac patients of ischemical cardiopathy, valvular heart disease, and arterial hypertension, based on 19 characteristics (descriptors including ECHO data, effort testings, and age and weight. In this order we have used different fuzzy clustering algorithms, namely hierarchical fuzzy clustering, hierarchical and horizontal fuzzy characteristics clustering, and a new clustering technique, fuzzy hierarchical cross-classification. The characteristics clustering techniques produce fuzzy partitions of the characteristics involved and, thus, are useful tools for studying the similarities between different characteristics and for essential characteristics selection. The cross-classification algorithm produces not only a fuzzy partition of the cardiac patients analyzed, but also a fuzzy partition of their considered characteristics. In this way it is possible to identify which characteristics are responsible for the similarities or dissimilarities observed between different groups of patients.

  5. 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

  6. 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…

  7. 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.

  8. Cancer Therapy (Preclinical and Clinical): A Decimal Classification, (Categories 51.1, 51.2, and 51.3).

    Science.gov (United States)

    Schneider, John H.

    This hierarchical decimal classification of information related to cancer therapy in humans and animals (preceeded by a few general categories) is a working draft of categories taken from an extensive classification of biomedical information. Because the classification identifies very small areas of cancer information, it can be used for precise…

  9. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  10. Remote sensing/vegetation classification. [California

    Science.gov (United States)

    Parker, I. E.

    1981-01-01

    The CALVEG classification system for identification of vegetation is described. This hierarchical system responds to classification requirements and to interpretation of vegetation at various description levels, from site description to broad identification levels. The system's major strength is its flexibility in application of remote sensing technology to assess, describe and communicate data relative to vegetative resources on a state-wide basis. It is concluded that multilevel remote sensing is a cost effective tool for assessment of the natural resource base. The CLAVEG system is found to be an economically efficient tool for both existing and potential vegetation.

  11. 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...

  12. Ecosystem services in sustainable groundwater management.

    Science.gov (United States)

    Tuinstra, Jaap; van Wensem, Joke

    2014-07-01

    The ecosystem services concept seems to get foothold in environmental policy and management in Europe and, for instance, The Netherlands. With respect to groundwater management there is a challenge to incorporate this concept in such a way that it contributes to the sustainability of decisions. Groundwater is of vital importance to societies, which is reflected in the presented overview of groundwater related ecosystem services. Classifications of these services vary depending on the purpose of the listing (valuation, protection, mapping et cetera). Though the scientific basis is developing, the knowledge-availability still can be a critical factor in decision making based upon ecosystem services. The examples in this article illustrate that awareness of the value of groundwater can result in balanced decisions with respect to the use of ecosystem services. The ecosystem services concept contributes to this awareness and enhances the visibility of the groundwater functions in the decision making process. The success of the ecosystem services concept and its contribution to sustainable groundwater management will, however, largely depend on other aspects than the concept itself. Local and actual circumstances, policy ambitions and knowledge availability will play an important role. Solutions can be considered more sustainable when more of the key elements for sustainable groundwater management, as defined in this article, are fully used and the presented guidelines for long term use of ecosystem services are respected.

  13. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  14. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  15. 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

  16. 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.

  17. 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 ...

  18. 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.

  19. 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.

  20. 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.

  1. Transformation of Digital Ecosystems

    DEFF Research Database (Denmark)

    Henningsson, Stefan; Hedman, Jonas

    2014-01-01

    In digital ecosystems, the fusion relation between business and technology means that the decision of technical compatibility of the offering is also the decision of how to position the firm relative to the coopetive relations that characterize business ecosystems. In this article we develop...... the Digital Ecosystem Technology Transformation (DETT) framework for explaining technology-based transformation of digital ecosystems by integrating theories of business and technology ecosystems. The framework depicts ecosystem transformation as distributed and emergent from micro-, meso-, and macro- level...... coopetition. The DETT framework consists an alternative to the existing explanations of digital ecosystem transformation as the rational management of one central actor balancing ecosystem tensions. We illustrate the use of the framework by a case study of transformation in the digital payment ecosystem...

  2. 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.

  3. UNCERTAINTY HANDLING IN DISASTER MANAGEMENT USING HIERARCHICAL ROUGH SET GRANULATION

    Directory of Open Access Journals (Sweden)

    H. Sheikhian

    2015-08-01

    Full Text Available Uncertainty is one of the main concerns in geospatial data analysis. It affects different parts of decision making based on such data. In this paper, a new methodology to handle uncertainty for multi-criteria decision making problems is proposed. It integrates hierarchical rough granulation and rule extraction to build an accurate classifier. Rough granulation provides information granules with a detailed quality assessment. The granules are the basis for the rule extraction in granular computing, which applies quality measures on the rules to obtain the best set of classification rules. The proposed methodology is applied to assess seismic physical vulnerability in Tehran. Six effective criteria reflecting building age, height and material, topographic slope and earthquake intensity of the North Tehran fault have been tested. The criteria were discretized and the data set was granulated using a hierarchical rough method, where the best describing granules are determined according to the quality measures. The granules are fed into the granular computing algorithm resulting in classification rules that provide the highest prediction quality. This detailed uncertainty management resulted in 84% accuracy in prediction in a training data set. It was applied next to the whole study area to obtain the seismic vulnerability map of Tehran. A sensitivity analysis proved that earthquake intensity is the most effective criterion in the seismic vulnerability assessment of Tehran.

  4. A hierarchical approach to ecological assessment of contaminated soils at Aberdeen Proving Ground, USA

    Energy Technology Data Exchange (ETDEWEB)

    Kuperman, R.G.

    1995-12-31

    Despite the expansion of environmental toxicology studies over the past decade, soil ecosystems have largely been ignored in ecotoxicological studies in the United States. The objective of this project was to develop and test the efficacy of a comprehensive methodology for assessing ecological impacts of soil contamination. A hierarchical approach that integrates biotic parameters and ecosystem processes was used to give insight into the mechanisms that lead to alterations in the structure and function of soil ecosystems in contaminated areas. This approach involved (1) a thorough survey of the soil biota to determine community structure, (2) laboratory and field tests on critical ecosystem processes, (3) toxicity trials, and (4) the use of spatial analyses to provide input to the decision-making, process. This methodology appears to, offer an efficient and potentially cost-saving tool for remedial investigations of contaminated sites.

  5. FWS Ecosystem Regions

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Digital ecosystem information portraying the location and boundaries of the ecosystems. The Service originally chose the U.S. Geological Survey's Hydrologic Unit Map...

  6. Coral reefs - Specialized ecosystems

    Digital Repository Service at National Institute of Oceanography (India)

    Wafar, M.V.M.

    This paper discusses briefly some aspects that characterize and differentiate coral reef ecosystems from other tropical marine ecosystems. A brief account on the resources that are extractable from coral reefs, their susceptibility to natural...

  7. Preservice Mathematics Teachers' Personal Figural Concepts and Classifications about Quadrilaterals

    Science.gov (United States)

    Erdogan, Emel Ozdemir; Dur, Zeliha

    2014-01-01

    The aim of this study was to determine preservice mathematics teachers' personal figural concepts and hierarchical classifications about quadrilaterals and to investigate the relationships between them. The participants were 57 preservice primary mathematics teachers in their senior year at a state university in Turkey. The preservice mathematics…

  8. Spatial Patterns in Biofilm Diversity across Hierarchical Levels of River-Floodplain Landscapes.

    Directory of Open Access Journals (Sweden)

    Marc Peipoch

    Full Text Available River-floodplain systems are among the most diverse and productive ecosystems, but the effects of biophysical complexity at multiple scales on microbial biodiversity have not been studied. Here, we investigated how the hierarchical organization of river systems (i.e., region, floodplain, zone, habitats, and microhabitats influences epilithic biofilm community assemblage patterns by characterizing microbial communities using 16S rRNA gene sequence data and analyzing bacterial species distribution across local and regional scales. Results indicate that regional and local environmental filters concurrently sort bacterial species, suggesting that spatial configuration of epilithic biofilms resembles patterns of larger organisms in floodplain ecosystems. Along the hierarchical organization of fluvial systems, floodplains constitute a vector of maximum environmental heterogeneity and consequently act as a major landscape filter for biofilm species. Thus, river basins and associated floodplains may simply reflect very large scale 'patches' within which environmental conditions select for community composition of epilithic biofilms.

  9. Global Ecosystem Restoration Index

    DEFF Research Database (Denmark)

    Fernandez, Miguel; Garcia, Monica; Fernandez, Nestor

    2015-01-01

    The Global ecosystem restoration index (GERI) is a composite index that integrates structural and functional aspects of the ecosystem restoration process. These elements are evaluated through a window that looks into a baseline for degraded ecosystems with the objective to assess restoration...

  10. Rights to ecosystem services

    NARCIS (Netherlands)

    Davidson, M.

    2014-01-01

    Ecosystem services are the benefits people obtain from ecosystems. Many of these services are provided outside the borders of the land where they are produced; this article investigates who is entitled to these non-excludable ecosystem services from two libertarian perspectives. Taking a

  11. Towards ecosystem accounting

    NARCIS (Netherlands)

    Duku, C.; Rathjens, H.; Zwart, S.J.; Hein, L.

    2015-01-01

    Ecosystem accounting is an emerging field that aims to provide a consistent approach to analysing environment-economy interactions. One of the specific features of ecosystem accounting is the distinction between the capacity and the flow of ecosystem services. Ecohydrological modelling to support

  12. 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...

  13. Comparative analysis of marine ecosystems: international production modelling workshop.

    Science.gov (United States)

    Link, Jason S; Megrey, Bernard A; Miller, Thomas J; Essington, Tim; Boldt, Jennifer; Bundy, Alida; Moksness, Erlend; Drinkwater, Ken F; Perry, R Ian

    2010-12-23

    Understanding the drivers that dictate the productivity of marine ecosystems continues to be a globally important issue. A vast literature identifies three main processes that regulate the production dynamics of such ecosystems: biophysical, exploitative and trophodynamic. Exploring the prominence among this 'triad' of drivers, through a synthetic analysis, is critical for understanding how marine ecosystems function and subsequently produce fisheries resources of interest to humans. To explore this topic further, an international workshop was held on 10-14 May 2010, at the National Academy of Science's Jonsson Center in Woods Hole, MA, USA. The workshop compiled the data required to develop production models at different hierarchical levels (e.g. species, guild, ecosystem) for many of the major Northern Hemisphere marine ecosystems that have supported notable fisheries. Analyses focused on comparable total system biomass production, functionally equivalent species production, or simulation studies for 11 different marine fishery ecosystems. Workshop activities also led to new analytical tools. Preliminary results suggested common patterns driving overall fisheries production in these ecosystems, but also highlighted variation in the relative importance of each among ecosystems.

  14. 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.

  15. Classification of anemia for gastroenterologists.

    Science.gov (United States)

    Moreno Chulilla, Jose Antonio; Romero Colás, Maria Soledad; Gutiérrez Martín, Martín

    2009-10-07

    Most anemia is related to the digestive system by dietary deficiency, malabsorption, or chronic bleeding. We review the World Health Organization definition of anemia, its morphological classification (microcytic, macrocytic and normocytic) and pathogenic classification (regenerative and hypo regenerative), and integration of these classifications. Interpretation of laboratory tests is included, from the simplest (blood count, routine biochemistry) to the more specific (iron metabolism, vitamin B12, folic acid, reticulocytes, erythropoietin, bone marrow examination and Schilling test). In the text and various algorithms, we propose a hierarchical and logical way to reach a diagnosis as quickly as possible, by properly managing the medical interview, physical examination, appropriate laboratory tests, bone marrow examination, and other complementary tests. The prevalence is emphasized in all sections so that the gastroenterologist can direct the diagnosis to the most common diseases, although the tables also include rare diseases. Digestive diseases potentially causing anemia have been studied in preference, but other causes of anemia have been included in the text and tables. Primitive hematological diseases that cause anemia are only listed, but are not discussed in depth. The last section is dedicated to simplifying all items discussed above, using practical rules to guide diagnosis and medical care with the greatest economy of resources and time.

  16. Ecosystem services in ECOCLIM

    DEFF Research Database (Denmark)

    Sørensen, Lise Lotte; Boegh, Eva; Bendtsen, J;

    that actions initiated to reduce anthropogenic GHG emissions are sustainable and not destructive to existing ecosystem services. Therefore it is important to address i.e. land use change in relation to the regulating services of the ecosystems, such as carbon sequestration and climate regulation. At present...... a thorough understanding of the ecosystem processes controlling the uptake or emissions of GHG is fundamental. Here we present ECOCLIM in the context of ecosystem services and the experimental studies within ECOCLIM which will lead to an enhanced understanding of Danish ecosystems....

  17. 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.

  18. Fishing for ecosystem services.

    Science.gov (United States)

    Pope, Kevin L; Pegg, Mark A; Cole, Nicholas W; Siddons, Stephen F; Fedele, Alexis D; Harmon, Brian S; Ruskamp, Ryan L; Turner, Dylan R; Uerling, Caleb C

    2016-12-01

    Ecosystems are commonly exploited and manipulated to maximize certain human benefits. Such changes can degrade systems, leading to cascading negative effects that may be initially undetected, yet ultimately result in a reduction, or complete loss, of certain valuable ecosystem services. Ecosystem-based management is intended to maintain ecosystem quality and minimize the risk of irreversible change to natural assemblages of species and to ecosystem processes while obtaining and maintaining long-term socioeconomic benefits. We discuss policy decisions in fishery management related to commonly manipulated environments with a focus on influences to ecosystem services. By focusing on broader scales, managing for ecosystem services, and taking a more proactive approach, we expect sustainable, quality fisheries that are resilient to future disturbances. To that end, we contend that: (1) management always involves tradeoffs; (2) explicit management of fisheries for ecosystem services could facilitate a transition from reactive to proactive management; and (3) adaptive co-management is a process that could enhance management for ecosystem services. We propose adaptive co-management with an ecosystem service framework where actions are implemented within ecosystem boundaries, rather than political boundaries, through strong interjurisdictional relationships. Published by Elsevier Ltd.

  19. Fishing for ecosystem services

    Science.gov (United States)

    Pope, Kevin L.; Pegg, Mark A.; Cole, Nicholas W.; Siddons, Stephen F.; Fedele, Alexis D.; Harmon, Brian S.; Ruskamp, Ryan L.; Turner, Dylan R.; Uerling, Caleb C.

    2016-01-01

    Ecosystems are commonly exploited and manipulated to maximize certain human benefits. Such changes can degrade systems, leading to cascading negative effects that may be initially undetected, yet ultimately result in a reduction, or complete loss, of certain valuable ecosystem services. Ecosystem-based management is intended to maintain ecosystem quality and minimize the risk of irreversible change to natural assemblages of species and to ecosystem processes while obtaining and maintaining long-term socioeconomic benefits. We discuss policy decisions in fishery management related to commonly manipulated environments with a focus on influences to ecosystem services. By focusing on broader scales, managing for ecosystem services, and taking a more proactive approach, we expect sustainable, quality fisheries that are resilient to future disturbances. To that end, we contend that: (1) management always involves tradeoffs; (2) explicit management of fisheries for ecosystem services could facilitate a transition from reactive to proactive management; and (3) adaptive co-management is a process that could enhance management for ecosystem services. We propose adaptive co-management with an ecosystem service framework where actions are implemented within ecosystem boundaries, rather than political boundaries, through strong interjurisdictional relationships.

  20. A theoretical model for assessing the sustainability Of ecosystem services

    Institute of Scientific and Technical Information of China (English)

    Feng Ling; Cheng Shengkui; Su Hua; Min Qingwen

    2008-01-01

    The Value of the World's Ecosystem Services and Natural Capital by Costanza in 1997 is generally regarded as a monument for the research of valuing ecosystem services. However, the classification of ecosystem services, the method of various services summation and the purpose for static global value had be confronted by many criticisms. Based on the summary of these criticisms, suggestions, related function assessment and further study direction, the sustainability of ecosystem services is presented The two basic indicators in ecology, productivity and biodiversity, respectively charactering the ability of producing and self-organizing, not only represent the internal function of ecosystem, but also are proportioned to its external function of supporting and providing for human life On presenting the general form of ecosystem services assessment, this paper improves the mathematical formula giving a function adjusting coefficient composed of productivity and biodiversity. Theoretically, the integration of the two indicators reflects the changes of ecosystem services at spatial and temporal scales, can physically assess the sustability of ecosystem services, and build a firm scientific fundament of value assessment for ecosystem services Objectively, its application should be strictly tested in next step.Ecosystem services; theoretical model; Sustainability; Bio-productivity; Biodiversity

  1. Review of Wetland Ecosystem Services Valuation in China

    Directory of Open Access Journals (Sweden)

    Fang Chen

    2014-11-01

    Full Text Available The wetland ecosystem not only supplies human with the production of ecosystem goods, such as pharmaceuticals, food, but also is one of the foundations of civilization and life support systems. With the in-depth understanding of the wetland ecosystem functions, the research of wetland ecosystem services evaluation has attracted much attention. This study summarizes connotation, classification and assessment methods of wetland ecosystem services. The several commonly used the methods of wetland ecosystem services valuation were chose, including market value, forestation cost, carbon tax, shadow project costs and travel cost. On this basis, the existing problem and the future development of wetland ecosystem service evaluation in China were discussed. Some suggestions were proposed in the future wetland ecosystem valuation and management in China. More attention should be paid to the systematic, integrity evaluation system establishment of wetland ecosystem service. Automatic continuous online monitoring system of wetland should be established, in order to provide more detailed and reliable dynamic data for the evaluation of wetland ecosystem service.

  2. HD-RNAS: An automated hierarchical database of RNA structures

    Directory of Open Access Journals (Sweden)

    Shubhra Sankar eRay

    2012-04-01

    Full Text Available One of the important goals of most biological investigations is to classify and organize the experimental findings so that they are readily useful for deriving generalized rules. Although there is a huge amount of information on RNA structures in PDB, there are redundant files, ambiguous synthetic sequences etc. Moreover, a systematic hierarchical organization, reflecting RNA classification, is missing in PDB. In this investigation, we have classified all the available RNA crystal structures from PDB through a programmatic approach. Hence, it would be now a simple assignment to regularly update the classification as and when new structures are released. The classification can further determine (i a non-redundant set of RNA structures and (ii if available, a set of structures of identical sequence and function, which can highlight structural polymorphism, ligand-induced conformational alterations etc. Presently, we have classified the available structures (2095 PDB entries having RNA chain longer than 9 nucleotides solved by X-ray crystallography or NMR spectroscopy into nine functional classes. The structures of same function and same source are mostly seen to be similar with subtle differences depending on their functional complexation. The web-server is available online at http://www.saha.ac.in/biop/www/HD-RNAS.html and is updated regularly.

  3. 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

  4. 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...

  5. 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.…

  6. 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.

  7. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  8. Classification in Australia.

    Science.gov (United States)

    McKinlay, John

    Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

  9. 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.

  10. 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.

  11. 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.

  12. 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 ...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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

  19. 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.

  20. 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...

  1. 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 ...

  2. Emergy and ecosystem complexity

    Science.gov (United States)

    Ulgiati, Sergio; Brown, Mark T.

    2009-01-01

    The question "What drives complexity?" is addressed in this paper. To answer this question, we explore the way energy and material resources of different quality flow through ecosystems and support, directly and indirectly, ecosystems growth and development. Processes of resource transformation throughout the ecosystem build order, cycle materials, generate and sustain information. Energy drives all these processes and energetic principles explain much of what is observed, including energy degradation according to the laws of thermodynamics. Emergy, a quantitative measure of the global environmental work supporting ecosystem dynamics, is used here in order to provide a deeper understanding of complexity growth and decline in ecosystems. Ecosystem complexity is discussed in this paper in relation to changes in structure, organization and functional capacity, as explained by changes in emergy, empower, and transformity.

  3. Hierarchical traits distances explain grassland Fabaceae species’ ecological niches distances

    Directory of Open Access Journals (Sweden)

    Florian eFort

    2015-02-01

    Full Text Available Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e. ecological niches. We measured a wide range of functional traits (root traits, leaf traits and whole plant traits in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species’ ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance.

  4. A gap analysis and comprehensive conservation strategy for riverine ecosystems of Missouri

    Science.gov (United States)

    Sowa, Scott P.; Annis, Gust; Morey, Michael E.; Diamond, David D.

    2007-01-01

    North America harbors an astounding proportion of the world's freshwater species, but it is facing a freshwater biodiversity crisis. A first step to slowing the loss of biodiversity involves identifying gaps in existing efforts to conserve biodiversity and prioritizing opportunities to fill these gaps. In this monograph we detail two separate, but complementary, conservation planning efforts - a Gap Analysis (GAP) and a State Wildlife Action Plan (WAP) - for Missouri that address this first step. The goal of the Missouri Aquatic GAP Project was to identify riverine ecosystems, habitats, and species not adequately represented (i.e., gaps) within existing conservation lands. The goal of the freshwater component of the Missouri Wildlife Action Plan was to identify and map a set of conservation-opportunity areas (COAs) that holistically represent all riverine ecosystems, habitats, and species in Missouri. Since conservation planning is a geographical exercise, both efforts utilized geographic information systems (GIS). Four principal GIS data sets were used in each planning effort: (1) a hierarchical riverine ecosystem classification, (2) predicted species distributions, (3) public ownership/stewardship, and (4) a human-threat index. Results of the gap analyses are not encouraging. Forty five, mostly rare, threatened, or endangered, species are not represented in lands set aside for conserving biodiversity. Results also illustrate the fragmented nature of conservation lands, which are mainly situated in the uplands and fail to provide connectivity among riverine habitats. Furthermore, many conservation lands are severely threatened by an array of human disturbances. In contrast, results of the WAP provide hope that relatively intact riverine ecosystems still exist. A total of 158 COAs, representing ∼6% of the total kilometers of stream in Missouri, were selected for the WAP. This illustrates that a wide spectrum of biodiversity can be represented within a small

  5. Managed island ecosystems

    Science.gov (United States)

    McEachern, Kathryn; Atwater, Tanya; Collins, Paul W.; Faulkner, Kate R.; Richards, Daniel V.

    2016-01-01

    This long-anticipated reference and sourcebook for California’s remarkable ecological abundance provides an integrated assessment of each major ecosystem type—its distribution, structure, function, and management. A comprehensive synthesis of our knowledge about this biologically diverse state, Ecosystems of California covers the state from oceans to mountaintops using multiple lenses: past and present, flora and fauna, aquatic and terrestrial, natural and managed. Each chapter evaluates natural processes for a specific ecosystem, describes drivers of change, and discusses how that ecosystem may be altered in the future. This book also explores the drivers of California’s ecological patterns and the history of the state’s various ecosystems, outlining how the challenges of climate change and invasive species and opportunities for regulation and stewardship could potentially affect the state’s ecosystems. The text explicitly incorporates both human impacts and conservation and restoration efforts and shows how ecosystems support human well-being. Edited by two esteemed ecosystem ecologists and with overviews by leading experts on each ecosystem, this definitive work will be indispensable for natural resource management and conservation professionals as well as for undergraduate or graduate students of California’s environment and curious naturalists.

  6. Application of distances between terms for flat and hierarchical data

    CERN Document Server

    Bedoya-Puerta, Jorge-Alonso

    2011-01-01

    In machine learning, distance-based algorithms, and other approaches, use information that is represented by propositional data. However, this kind of representation can be quite restrictive and, in many cases, it requires more complex structures in order to represent data in a more natural way. Terms are the basis for functional and logic programming representation. Distances between terms are a useful tool not only to compare terms, but also to determine the search space in many of these applications. This dissertation applies distances between terms, exploiting the features of each distance and the possibility to compare from propositional data types to hierarchical representations. The distances between terms are applied through the k-NN (k-nearest neighbor) classification algorithm using XML as a common language representation. To be able to represent these data in an XML structure and to take advantage of the benefits of distance between terms, it is necessary to apply some transformations. These transf...

  7. Low-Level Hierarchical Multiscale Segmentation Statistics of Natural Images.

    Science.gov (United States)

    Akbas, Emre; Ahuja, Narendra

    2014-09-01

    This paper is aimed at obtaining the statistics as a probabilistic model pertaining to the geometric, topological and photometric structure of natural images. The image structure is represented by its segmentation graph derived from the low-level hierarchical multiscale image segmentation. We first estimate the statistics of a number of segmentation graph properties from a large number of images. Our estimates confirm some findings reported in the past work, as well as provide some new ones. We then obtain a Markov random field based model of the segmentation graph which subsumes the observed statistics. To demonstrate the value of the model and the statistics, we show how its use as a prior impacts three applications: image classification, semantic image segmentation and object detection.

  8. Hierarchical minutiae matching for fingerprint and palmprint identification.

    Science.gov (United States)

    Chen, Fanglin; Huang, Xiaolin; Zhou, Jie

    2013-12-01

    Fingerprints and palmprints are the most common authentic biometrics for personal identification, especially for forensic security. Previous research have been proposed to speed up the searching process in fingerprint and palmprint identification systems, such as those based on classification or indexing, in which the deterioration of identification accuracy is hard to avert. In this paper, a novel hierarchical minutiae matching algorithm for fingerprint and palmprint identification systems is proposed. This method decomposes the matching step into several stages and rejects many false fingerprints or palmprints on different stages, thus it can save much time while preserving a high identification rate. Experimental results show that the proposed algorithm can save almost 50% searching time compared with traditional methods and illustrate its effectiveness.

  9. A hierarchical community occurrence model for North Carolina stream fish

    Science.gov (United States)

    Midway, S.R.; Wagner, Tyler; Tracy, B.H.

    2016-01-01

    The southeastern USA is home to one of the richest—and most imperiled and threatened—freshwater fish assemblages in North America. For many of these rare and threatened species, conservation efforts are often limited by a lack of data. Drawing on a unique and extensive data set spanning over 20 years, we modeled occurrence probabilities of 126 stream fish species sampled throughout North Carolina, many of which occur more broadly in the southeastern USA. Specifically, we developed species-specific occurrence probabilities from hierarchical Bayesian multispecies models that were based on common land use and land cover covariates. We also used index of biotic integrity tolerance classifications as a second level in the model hierarchy; we identify this level as informative for our work, but it is flexible for future model applications. Based on the partial-pooling property of the models, we were able to generate occurrence probabilities for many imperiled and data-poor species in addition to highlighting a considerable amount of occurrence heterogeneity that supports species-specific investigations whenever possible. Our results provide critical species-level information on many threatened and imperiled species as well as information that may assist with re-evaluation of existing management strategies, such as the use of surrogate species. Finally, we highlight the use of a relatively simple hierarchical model that can easily be generalized for similar situations in which conventional models fail to provide reliable estimates for data-poor groups.

  10. BUSINESS ECOSYSTEMS VS BUSINESS DIGITAL ECOSYSTEMS

    Directory of Open Access Journals (Sweden)

    Marinela Lazarica

    2006-05-01

    Full Text Available E-business is often described as the small organisations’ gateway to global business and markets. The adoption of Internet-based technologies for e-business is a continuous process, with sequential steps of evolution. The latter step in the adoption of Internet-based technologies for business, where the business services and the software components are supported by a pervasive software environment, which shows an evolutionary and self-organising behaviour are named digital business ecosystems. The digital business ecosystems are characterized by intelligent software components and services, knowledge transfer, interactive training frameworks and integration of business processes and e-government models.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. On the Karst Ecosystem

    Institute of Scientific and Technical Information of China (English)

    袁道先

    2001-01-01

    In this paper the author gives a definition of the karst ecosystem and discusses the characteristics of the karst environment and karst ecosystem and the relationship between life and the karst environment. Finally he clarifies the structure, driving force and functions of the karst system.``

  16. Developing an ecosystem diversity framework for landscape assessment

    Science.gov (United States)

    Robert D. Pfister; Michael D. Sweet

    2000-01-01

    Ecological diversity is being addressed in various research and management efforts, but a common foundation is not explicitly defined or displayed. A formal Ecosystem Diversity Framework (EDF) would improve landscape analysis and communication across multiple scales. The EDF represents a multiple-component vegetation classification system with inherent flexibility for...

  17. Ecosystem Viable Yields

    CERN Document Server

    De Lara, Michel; Oliveros-Ramos, Ricardo; Tam, Jorge

    2011-01-01

    The World Summit on Sustainable Development (Johannesburg, 2002) encouraged the application of the ecosystem approach by 2010. However, at the same Summit, the signatory States undertook to restore and exploit their stocks at maximum sustainable yield (MSY), a concept and practice without ecosystemic dimension, since MSY is computed species by species, on the basis of a monospecific model. Acknowledging this gap, we propose a definition of "ecosystem viable yields" (EVY) as yields compatible i) with biological viability levels for all time and ii) with an ecosystem dynamics. To the difference of MSY, this notion is not based on equilibrium, but on viability theory, which offers advantages for robustness. For a generic class of multispecies models with harvesting, we provide explicit expressions for the EVY. We apply our approach to the anchovy--hake couple in the Peruvian upwelling ecosystem between the years 1971 and 1981.

  18. 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.

  19. 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.

  20. 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...

  1. Process-based principles for restoring river ecosystems

    Science.gov (United States)

    Beechie, T. J.

    2010-12-01

    Process-based restoration aims to re-establish normative rates and magnitudes of physical, chemical, and biological processes that sustain river and floodplain ecosystems. Ecosystem conditions at any site are governed by hierarchical regional, watershed, and reach-scale processes controlling hydrologic and sediment regimes, floodplain and aquatic habitat dynamics, and riparian and aquatic biota. To help guide river restoration toward sustainable actions, we outline and illustrate four process-based principles that ensure actions: (1) address root causes of degradation, (2) are consistent with the physical and biological potential of the site, (3) are at a scale commensurate with environmental problems, and (4) have clearly articulated expected outcomes for ecosystem dynamics. Applying these principles will help avoid common pitfalls in river restoration, such as creating habitat types that are outside the range of a site’s natural potential, attempting to build static habitats in dynamic environments, or constructing habitat features that are ultimately overwhelmed by untreated system drivers.

  2. Ecosystem approach in education

    Science.gov (United States)

    Nabiullin, Iskander

    2017-04-01

    Environmental education is a base for sustainable development. Therefore, in our school we pay great attention to environmental education. Environmental education in our school is based on ecosystem approach. What is an ecosystem approach? Ecosystem is a fundamental concept of ecology. Living organisms and their non-living environments interact with each other as a system, and the biosphere planet functions as a global ecosystem. Therefore, it is necessary for children to understand relationships in ecosystems, and we have to develop systems thinking in our students. Ecosystem approach and systems thinking should help us to solve global environmental problems. How do we implement the ecosystem approach? Students must understand that our biosphere functions as a single ecosystem and even small changes can lead to environmental disasters. Even the disappearance of one plant or animal species can lead to irreversible consequences. So in the classroom we learn the importance of each living organism for the nature. We pay special attention to endangered species, which are listed in the Red Data List. Kids are doing projects about these organisms, make videos, print brochures and newspapers. Fieldwork also plays an important role for ecosystem approach. Every summer, we go out for expeditions to study species of plants and animals listed in the Red Data List of Tatarstan. In class, students often write essays on behalf of any endangered species of plants or animals, this also helps them to understand the importance of each living organism in nature. Each spring we organise a festival of environmental projects among students. Groups of 4-5 students work on a solution of environmental problems, such as water, air or soil pollution, waste recycling, the loss of biodiversity, etc. Participants shoot a clip about their project, print brochures. Furthermore, some of the students participate in national and international scientific Olympiads with their projects. In addition to

  3. 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.

  4. 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.

  5. 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.

  6. 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 ...

  7. 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.

  8. 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....

  9. 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...

  10. 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...

  11. 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.

  12. 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...

  13. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...

  14. 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...

  15. 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...

  16. Hierarchical self-organization of tectonic plates

    OpenAIRE

    2010-01-01

    The Earth's surface is subdivided into eight large tectonic plates and many smaller ones. We reconstruct the plate tessellation history and demonstrate that both large and small plates display two distinct hierarchical patterns, described by different power-law size-relationships. While small plates display little organisational change through time, the structure of the large plates oscillate between minimum and maximum hierarchical tessellations. The organization of large plates rapidly chan...

  17. Angelic Hierarchical Planning: Optimal and Online Algorithms

    Science.gov (United States)

    2008-12-06

    restrict our attention to plans in I∗(Act, s0). Definition 2. ( Parr and Russell , 1998) A plan ah∗ is hierarchically optimal iff ah∗ = argmina∈I∗(Act,s0):T...Murdock, Dan Wu, and Fusun Yaman. SHOP2: An HTN planning system. JAIR, 20:379–404, 2003. Ronald Parr and Stuart Russell . Reinforcement Learning with...Angelic Hierarchical Planning: Optimal and Online Algorithms Bhaskara Marthi Stuart J. Russell Jason Wolfe Electrical Engineering and Computer

  18. Hierarchical Needs, Income Comparisons and Happiness Levels

    OpenAIRE

    Drakopoulos, Stavros

    2011-01-01

    The cornerstone of the hierarchical approach is that there are some basic human needs which must be satisfied before non-basic needs come into the picture. The hierarchical structure of needs implies that the satisfaction of primary needs provides substantial increases to individual happiness compared to the subsequent satisfaction of secondary needs. This idea can be combined with the concept of comparison income which means that individuals compare rewards with individuals with similar char...

  19. Rivers and streams: Ecosystem dynamics and integrating paradigms

    Science.gov (United States)

    Cummins, K.W.; Wilzbach, M.A.

    2008-01-01

    Full understanding of running waters requires an ecosystem perspective, which encompasses the physical and chemical setting in interaction with dependent biological communities. Several conceptual models or paradigms of river and stream ecosystems that capture critical components of lotic ecosystems have been developed, including the ‘river continuum concept’, to describe fluxes of matter and energy within the stream or river channel together with exchanges between the channel and its terrestrial setting. A complete ecosystem perspective includes consideration of hierarchical spatial scales in a temporal context. Flow of energy in lotic ecosystems is driven by two alternative energy sources: sunlight regulating in-stream photosynthesis and plant litter derived from the stream-side riparian corridor or floodplain. Energy transfers within the ecosystem pass through micro- and macroproducers (algae and vascular hydrophytes) and micro- and macroconsumers (microorganisms, invertebrates, and vertebrates). Material fluxes encompass the cycling of key nutrients, such as nitrogen and phosphorus, and the transport, storage, and metabolism of dissolved (DOM) and particulate (POM) organic matter (OM). Growth of lotic periphyton (algae and associated microbes, microzoans, and detritus) and coarse (CPOM) and fine (FPOM) particulate organic matter constitute the food resources of nonpredaceous running-water invertebrates (e.g., shredders that consume CPOM and collectors that feed on FPOM and associated microbes of both).

  20. An ecosystem-based understanding and analysis for SENCE toward sustainable development

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    There is a need to find a comprehensive approach focusing on the conflicts between economical growth and environmental protection.Chinese scholars advocate a comprehensive ecosystem viewpoint named social-economic-natural complex ecosystem(SENCE). The kernel of the concept lies in the hierarchical structure of SENCE, through which methods from ecological network can be useful to the compound system. The author gives a schema depicting its structure, following a model analysis to help understand the reliance of economy on ecosystem. It is obvious that more actions should be done to strive for sustainable development.

  1. Quantum and Ecosystem Entropies

    Directory of Open Access Journals (Sweden)

    A. D. Kirwan

    2008-06-01

    Full Text Available Ecosystems and quantum gases share a number of superficial similarities including enormous numbers of interacting elements and the fundamental role of energy in such interactions. A theory for the synthesis of data and prediction of new phenomena is well established in quantum statistical mechanics. The premise of this paper is that the reason a comparable unifying theory has not emerged in ecology is that a proper role for entropy has yet to be assigned. To this end, a phase space entropy model of ecosystems is developed. Specification of an ecosystem phase space cell size based on microbial mass, length, and time scales gives an ecosystem uncertainty parameter only about three orders of magnitude larger than Planck’s constant. Ecosystem equilibria is specified by conservation of biomass and total metabolic energy, along with the principle of maximum entropy at equilibria. Both Bose - Einstein and Fermi - Dirac equilibrium conditions arise in ecosystems applications. The paper concludes with a discussion of some broader aspects of an ecosystem phase space.

  2. 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.

  3. 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.

  4. Hierarchical Nanoceramics for Industrial Process Sensors

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, James, A.; Brosnan, Kristen, H.; Striker, Todd; Ramaswamy, Vidya; Aceto, Steven, C.; Gao, Yan; Willson, Patrick, D.; Manoharan, Mohan; Armstrong, Eric, N., Wachsman, Eric, D.; Kao, Chi-Chang

    2011-07-15

    This project developed a robust, tunable, hierarchical nanoceramics materials platform for industrial process sensors in harsh-environments. Control of material structure at multiple length scales from nano to macro increased the sensing response of the materials to combustion gases. These materials operated at relatively high temperatures, enabling detection close to the source of combustion. It is anticipated that these materials can form the basis for a new class of sensors enabling widespread use of efficient combustion processes with closed loop feedback control in the energy-intensive industries. The first phase of the project focused on materials selection and process development, leading to hierarchical nanoceramics that were evaluated for sensing performance. The second phase focused on optimizing the materials processes and microstructures, followed by validation of performance of a prototype sensor in a laboratory combustion environment. The objectives of this project were achieved by: (1) synthesizing and optimizing hierarchical nanostructures; (2) synthesizing and optimizing sensing nanomaterials; (3) integrating sensing functionality into hierarchical nanostructures; (4) demonstrating material performance in a sensing element; and (5) validating material performance in a simulated service environment. The project developed hierarchical nanoceramic electrodes for mixed potential zirconia gas sensors with increased surface area and demonstrated tailored electrocatalytic activity operable at high temperatures enabling detection of products of combustion such as NOx close to the source of combustion. Methods were developed for synthesis of hierarchical nanostructures with high, stable surface area, integrated catalytic functionality within the structures for gas sensing, and demonstrated materials performance in harsh lab and combustion gas environments.

  5. Ecosystem Services Tradeoffs: A Case Study of Chiang Khong, Thailand

    Directory of Open Access Journals (Sweden)

    Apisom Intralawan

    2016-07-01

    Full Text Available The recent transformation of land in the Mekong River Basin has been dramatic. The changes have contributed to an increased standard of living resulting from economic and agricultural expansion, increasing urbanization and modernization. However, the changes have also resulted in major degradation of ecosystems and the services which ecosystems provide. Despite acknowledgement of the loss of the ecosystem benefits, the integration of ecosystem services tradeoffs into land use decisions is still limited. Land managers and policy makers are facing challenges in balancing the positive effects of economic development and the long term negative impacts on the environment. This paper is based on a case study of one of the fastest growing towns along the Mekong River, namely Chiang Khong, Chiang Rai Province, Thailand. Data on the change of land use and land cover for different biomes over the past 40 years have been obtained from satellite image classification. The valuation of ecosystem services of different biomes has been quantified in monetary terms. During the last four decades, the estimated change in the value of ecosystem services in Chiang Khong shows a net decline of roughly US$ 440 million - from US$ 1,896 million/year in 1976 to US$ 1,455 million/year in 2015. There is a risk that this decline in ecosystem services will further increase if ecosystem services valuations are not included in decision making processes related to the planned economic development (infrastructure expansion, new industrial park development in Chiang Khong.

  6. HIERARCHICAL OPTIMIZATION MODEL ON GEONETWORK

    Directory of Open Access Journals (Sweden)

    Z. Zha

    2012-07-01

    Full Text Available In existing construction experience of Spatial Data Infrastructure (SDI, GeoNetwork, as the geographical information integrated solution, is an effective way of building SDI. During GeoNetwork serving as an internet application, several shortcomings are exposed. The first one is that the time consuming of data loading has been considerately increasing with the growth of metadata count. Consequently, the efficiency of query and search service becomes lower. Another problem is that stability and robustness are both ruined since huge amount of metadata. The final flaw is that the requirements of multi-user concurrent accessing based on massive data are not effectively satisfied on the internet. A novel approach, Hierarchical Optimization Model (HOM, is presented to solve the incapability of GeoNetwork working with massive data in this paper. HOM optimizes the GeoNetwork from these aspects: internal procedure, external deployment strategies, etc. This model builds an efficient index for accessing huge metadata and supporting concurrent processes. In this way, the services based on GeoNetwork can maintain stable while running massive metadata. As an experiment, we deployed more than 30 GeoNetwork nodes, and harvest nearly 1.1 million metadata. From the contrast between the HOM-improved software and the original one, the model makes indexing and retrieval processes more quickly and keeps the speed stable on metadata amount increasing. It also shows stable on multi-user concurrent accessing to system services, the experiment achieved good results and proved that our optimization model is efficient and reliable.

  7. Search techniques in intelligent classification systems

    CERN Document Server

    Savchenko, Andrey V

    2016-01-01

    A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

  8. A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

    Science.gov (United States)

    Wang, Lizhu; Riseng, Catherine M.; Mason, Lacey; Werhrly, Kevin; Rutherford, Edward; McKenna, James E.; Castiglione, Chris; Johnson, Lucinda B.; Infante, Dana M.; Sowa, Scott P.; Robertson, Mike; Schaeffer, Jeff; Khoury, Mary; Gaiot, John; Hollenhurst, Tom; Brooks, Colin N.; Coscarelli, Mark

    2015-01-01

    Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database — Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

  9. Revisiting software ecosystems research

    DEFF Research Database (Denmark)

    Manikas, Konstantinos

    2016-01-01

    ‘Software ecosystems’ is argued to first appear as a concept more than 10 years ago and software ecosystem research started to take off in 2010. We conduct a systematic literature study, based on the most extensive literature review in the field up to date, with two primarily aims: (a) to provide...... an updated overview of the field and (b) to document evolution in the field. In total, we analyze 231 papers from 2007 until 2014 and provide an overview of the research in software ecosystems. Our analysis reveals a field that is rapidly growing both in volume and empirical focus while becoming more mature...... from evolving. We propose means for future research and the community to address them. Finally, our analysis shapes the view of the field having evolved outside the existing definitions of software ecosystems and thus propose the update of the definition of software ecosystems....

  10. Chinese Ecosystem Research Network

    Institute of Scientific and Technical Information of China (English)

    Huang Tieqing; Liu Jian; Chen Panqin; Fu Bojie

    2002-01-01

    The article analyzes the development of the Chinese Ecosystem Research Network, and its mission, mandate, and management mechanisms, with examples of research, demonstration and consultation for policy-setting.

  11. Formation of Service Ecosystems

    DEFF Research Database (Denmark)

    Jonas, Julia M.; Sörhammar, David; Satzger, Gerhard

    Purpose: Researchers in several different academic disciplines (such as marketing, information systems, and organization) have focused on investigating service and business ecosystems (e.g. Lusch and Nambisan, 2015; Gawer and Cusumano, 2014; Kude et al. 2012). We reviewed 69 papers in service...... – i.e. the “birth phase” (Moore, 2009) of a service ecosystem. This paper, therefore, aims to explore how the somewhat “magic” processes of service ecosystem formation that are being taken for granted actually occur. Methodology/Approach: Building on a review of core elements in the definitions...... proposition; a value proposition (e.g., a business opportunity or a business idea) may form the starting point for actors to collaborate and integrate resources in order realize the value proposition. The initiator of a service ecosystem could for example be an actor (Mark Zuckerberg), resources (website...

  12. Total Ecosystem Carbon Stock

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Total ecosystem carbon includes above- and below-ground live plant components (such as leaf, branch, stem and root), dead biomass (such as standing dead wood, down...

  13. Global change and climate-vegetation classification

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Three phrases of the quantitative study of climate-vegetation classification and their characteristics are presented based on the review of advance in climate-vegetation interaction, a key issue of "global change and terrestrial ecosystems (GCTE)" which is the core project of International Geosphere-Biosphere Programme (IGBP): (ⅰ) characterized by the correlation between natural vegetation types and climate; (ⅱ) characterized by climatic indices which have obviously been restricted to plant ecophysiology; (ⅲ) characterized by coupling both structure and function of vegetation. Thus, the prospective of climate-vegetation classification for global change study in China was proposed, especially the study coupling climate-vegetation classification models with atmospheric general circulation models (GCMs) was emphasized.

  14. What Are Ecosystem Services?

    OpenAIRE

    Boyd, James; Banzhaf, H. Spencer

    2006-01-01

    This paper advocates consistently defined units of account to measure the contributions of nature to human welfare. We argue that such units have to date not been defined by environmental accounting advocates and that the term “ecosystem services” is too ad hoc to be of practical use in welfare accounting. We propose a definition, rooted in economic principles, of ecosystem service units. A goal of these units is comparability with the definition of conventional goods and services found in GD...

  15. Signal Classification in Fading Channels Using Cyclic Spectral Analysis

    Directory of Open Access Journals (Sweden)

    Eric Like

    2009-01-01

    Full Text Available Cognitive Radio (CR, a hierarchical Dynamic Spectrum Access (DSA model, has been considered as a strong candidate for future communication systems improving spectrum efficiency utilizing unused spectrum of opportunity. However, to ensure the effectiveness of dynamic spectrum access, accurate signal classification in fading channels at low signal to noise ratio is essential. In this paper, a hierarchical cyclostationary-based classifier is proposed to reliably identify the signal type of a wide range of unknown signals. The proposed system assumes no a priori knowledge of critical signal statistics such as carrier frequency, carrier phase, or symbol rate. The system is designed with a multistage approach to minimize the number of samples required to make a classification decision while simultaneously ensuring the greatest reliability in the current and previous stages. The system performance is demonstrated in a variety of multipath fading channels, where several multiantenna-based combining schemes are implemented to exploit spatial diversity.

  16. Hierarchical eco-restoration: a systematical approach to removal of COD and dissolved nutrients from an intensive agricultural area.

    Science.gov (United States)

    Wu, Yonghong; Hu, Zhengyi; Yang, Linzhang

    2010-10-01

    A systematical approach based on hierarchical eco-restoration system for the simultaneous removal of COD and dissolved nutrients was proposed and applied in a complex residential-cropland area in Kunming, China from August 2006 to August 2008, where the self-purifying capacity of the agricultural ecosystem had been lost. The system includes four main parts: (1) fertilizer management and agricultural structure optimization, (2) nutrients reuse, (3) wastewater treatment, and (4) catchment restoration. The results showed that the average removal efficiencies were 90% for COD, 93% for ammonia, 94% for nitrate and 71% for total dissolved phosphorus (TDP) when the hierarchical eco-restoration agricultural system was in a relatively steady-state condition. The emergence of 14 species of macrophytes and 4 species of zoobenthos indicated that the growth conditions for the plankton were improved. The results demonstrated that this promising and environmentally benign hierarchical eco-restoration system could decrease the output of nutrients and reduce downstream eutrophication risk.

  17. 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.

  18. Classification of sources of municipal solid wastes in developing countries

    Energy Technology Data Exchange (ETDEWEB)

    Buenrostro, O. [Instituto de Investigaciones sobre los Recursos Naturales, Universidad Michoacana de San Nicolas de Hidalgo, Apartado Postal 2-105, 58400, Michoacan, Morelia (Mexico); Bocco, G. [Departamento de Ecologia de los Recursos Naturales, Instituto de Ecologia, Universidad Nacional Autonoma de Mexico, Campus Morelia, Apartado Postal 27-3 Xangari, 58089, Michoacan, Morelia (Mexico); Cram, S. [Departamento de Geografia Fisica, Instituto de Geografia, Universidad Nacional Autonoma de Mexico, Circuito Exterior, C.P. 04510 Ciudad Universitaria, Mexico City (Mexico)

    2001-05-01

    The existence of different classifications of municipal solid waste (MSW) creates confusion and makes it difficult to interpret and compare the results of generation analyses. In this paper, MSW is conceptualized as the solid waste generated within the territorial limits of a municipality, independently of its source of generation. Grounded on this assumption, and based on the economic activity that generates a solid waste with determinate physical and chemical characteristics, a hierarchical source classification of MSW is suggested. Thus, a connection between the source and the type of waste is established. The classification categorizes the sources into three divisions and seven classes of sources: residential, commercial, institutional, construction/demolition, agricultural-animal husbandry, industrial, and special. When applied at different geographical scales, this classification enables the assessment of the volume of MSW generated, and provides an overview of the types of residues expected to be generated in a municipality, region or state.

  19. Semantic Document Image Classification Based on Valuable Text Pattern

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2011-01-01

    Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

  20. Knowledge-based sea ice classification by polarimetric SAR

    DEFF Research Database (Denmark)

    Skriver, Henning; Dierking, Wolfgang

    2004-01-01

    Polarimetric SAR images acquired at C- and L-band over sea ice in the Greenland Sea, Baltic Sea, and Beaufort Sea have been analysed with respect to their potential for ice type classification. The polarimetric data were gathered by the Danish EMISAR and the US AIRSAR which both are airborne...... systems. A hierarchical classification scheme was chosen for sea ice because our knowledge about magnitudes, variations, and dependences of sea ice signatures can be directly considered. The optimal sequence of classification rules and the rules themselves depend on the ice conditions/regimes. The use...... of the polarimetric phase information improves the classification only in the case of thin ice types but is not necessary for thicker ice (above about 30 cm thickness)...

  1. A Hybrid Ensemble Learning Approach to Star-Galaxy Classification

    CERN Document Server

    Kim, Edward J; Kind, Matias Carrasco

    2015-01-01

    There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template fitting method. Using data from the CFHTLenS survey, we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2, SDSS, VIPERS, and VVDS, and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, s...

  2. Method study of classification and gradation of earthquake disasters

    Institute of Scientific and Technical Information of China (English)

    MAO Guo-min; GU Jian-hua; WU Xin-yan

    2007-01-01

    Based on data of earthquake disaster events during 1954~2005 in the Chinese mainland, the classification and gradation of earthquake disasters have been studied by multivariate statistical analysis. Three fundamental structures of earthquake disasters have been found and an FAPE (factor analysis-principal component-equamax rotation) classification model and an HCWS (hierarchical cluster-ward method-seuclid) gradation model have been constructed. Earthquake disasters are divided into eight classes and five grades respectively in the models, which give a reasonable explanation to the phenomenon of earthquake disasters.

  3. Typology and indicators of ecosystem services for marine spatial planning and management.

    Science.gov (United States)

    Böhnke-Henrichs, Anne; Baulcomb, Corinne; Koss, Rebecca; Hussain, S Salman; de Groot, Rudolf S

    2013-11-30

    The ecosystem services concept provides both an analytical and communicative tool to identify and quantify the link between human welfare and the environment, and thus to evaluate the ramifications of management interventions. Marine spatial planning (MSP) and Ecosystem-based Management (EBM) are a form of management intervention that has become increasingly popular and important globally. The ecosystem service concept is rarely applied in marine planning and management to date which we argue is due to the lack of a well-structured, systematic classification and assessment of marine ecosystem services. In this paper we not only develop such a typology but also provide guidance to select appropriate indicators for all relevant ecosystem services. We apply this marine-specific ecosystem service typology to MSP and EBM. We thus provide not only a novel theoretical construct but also show how the ecosystem services concept can be used in marine planning and management.

  4. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases th...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  5. Monetary accounting of ecosystem services

    NARCIS (Netherlands)

    Remme, R.P.; Edens, Bram; Schröter, Matthias; Hein, Lars

    2015-01-01

    Ecosystem accounting aims to provide a better understanding of ecosystem contributions to the economy in a spatially explicit way. Ecosystem accounting monitors ecosystem services and measures their monetary value using exchange values consistent with the System of National Accounts (SNA). We pil

  6. Monetary accounting of ecosystem services

    NARCIS (Netherlands)

    Remme, R.P.; Edens, Bram; Schröter, Matthias; Hein, Lars

    2015-01-01

    Ecosystem accounting aims to provide a better understanding of ecosystem contributions to the economy in a spatially explicit way. Ecosystem accounting monitors ecosystem services and measures their monetary value using exchange values consistent with the System of National Accounts (SNA). We

  7. Building the United States National Vegetation Classification

    Science.gov (United States)

    Franklin, S.B.; Faber-Langendoen, D.; Jennings, M.; Keeler-Wolf, T.; Loucks, O.; Peet, R.; Roberts, D.; McKerrow, A.

    2012-01-01

    The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.

  8. The International Classification of Headache Disorders.

    Science.gov (United States)

    Olesen, Jes

    2008-05-01

    A set of related medical disorders that lack a proper classification system and diagnostic criteria is like a society without laws. The result is incoherence at best, chaos at worst. For this reason, the International Classification of Headache Disorders (ICHD) is arguably the single most important breakthrough in headache medicine over the last 50 years. The ICHD identifies and categorizes more than a hundred different kinds of headache in a logical, hierarchal system. Even more important, it has provided explicit diagnostic criteria for all of the headache disorders listed. The ICHD quickly became universally accepted, and criticism of the classification has been minor relative to that directed at other disease classification systems. Over the 20 years following publication of the first edition of the ICHD, headache research has rapidly accelerated despite sparse allocation of resources to that effort. In summary, the ICHD has attained widespread acceptance at the international level and has substantially facilitated both clinical research and clinical care in the field of headache medicine.

  9. Self-assembled biomimetic superhydrophobic hierarchical arrays.

    Science.gov (United States)

    Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

    2013-09-01

    Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

    The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

  11. Hierarchical models and chaotic spin glasses

    Science.gov (United States)

    Berker, A. Nihat; McKay, Susan R.

    1984-09-01

    Renormalization-group studies in position space have led to the discovery of hierarchical models which are exactly solvable, exhibiting nonclassical critical behavior at finite temperature. Position-space renormalization-group approximations that had been widely and successfully used are in fact alternatively applicable as exact solutions of hierarchical models, this realizability guaranteeing important physical requirements. For example, a hierarchized version of the Sierpiriski gasket is presented, corresponding to a renormalization-group approximation which has quantitatively yielded the multicritical phase diagrams of submonolayers on graphite. Hierarchical models are now being studied directly as a testing ground for new concepts. For example, with the introduction of frustration, chaotic renormalization-group trajectories were obtained for the first time. Thus, strong and weak correlations are randomly intermingled at successive length scales, and a new microscopic picture and mechanism for a spin glass emerges. An upper critical dimension occurs via a boundary crisis mechanism in cluster-hierarchical variants developed to have well-behaved susceptibilities.

  12. The theory, direction, and magnitude of ecosystem fire probability as constrained by precipitation and temperature.

    Science.gov (United States)

    Guyette, Richard; Stambaugh, Michael C; Dey, Daniel; Muzika, Rose Marie

    2017-01-01

    The effects of climate on wildland fire confronts society across a range of different ecosystems. Water and temperature affect the combustion dynamics, irrespective of whether those are associated with carbon fueled motors or ecosystems, but through different chemical, physical, and biological processes. We use an ecosystem combustion equation developed with the physical chemistry of atmospheric variables to estimate and simulate fire probability and mean fire interval (MFI). The calibration of ecosystem fire probability with basic combustion chemistry and physics offers a quantitative method to address wildland fire in addition to the well-studied forcing factors such as topography, ignition, and vegetation. We develop a graphic analysis tool for estimating climate forced fire probability with temperature and precipitation based on an empirical assessment of combustion theory and fire prediction in ecosystems. Climate-affected fire probability for any period, past or future, is estimated with given temperature and precipitation. A graphic analyses of wildland fire dynamics driven by climate supports a dialectic in hydrologic processes that affect ecosystem combustion: 1) the water needed by plants to produce carbon bonds (fuel) and 2) the inhibition of successful reactant collisions by water molecules (humidity and fuel moisture). These two postulates enable a classification scheme for ecosystems into three or more climate categories using their position relative to change points defined by precipitation in combustion dynamics equations. Three classifications of combustion dynamics in ecosystems fire probability include: 1) precipitation insensitive, 2) precipitation unstable, and 3) precipitation sensitive. All three classifications interact in different ways with variable levels of temperature.

  13. A Hybrid P2P Overlay Network for Non-strictly Hierarchically Categorized Content

    Science.gov (United States)

    Wan, Yi; Asaka, Takuya; Takahashi, Tatsuro

    In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

  14. Classification of cultivated plants.

    NARCIS (Netherlands)

    Brandenburg, W.A.

    1986-01-01

    Agricultural practice demands principles for classification, starting from the basal entity in cultivated plants: the cultivar. In establishing biosystematic relationships between wild, weedy and cultivated plants, the species concept needs re-examination. Combining of botanic classification, based

  15. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    Meifeng Dai; Jie Liu; Feng Zhu

    2014-10-01

    In this paper, we present trapping issues of weight-dependent walks on weighted hierarchical networks which are based on the classic scale-free hierarchical networks. Assuming that edge’s weight is used as local information by a random walker, we introduce a biased walk. The biased walk is that a walker, at each step, chooses one of its neighbours with a probability proportional to the weight of the edge. We focus on a particular case with the immobile trap positioned at the hub node which has the largest degree in the weighted hierarchical networks. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping issue. Let parameter (0 < < 1) be the weight factor. We show that the efficiency of the trapping process depends on the parameter a; the smaller the value of a, the more efficient is the trapping process.

  16. 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.

  17. Incentive Mechanisms for Hierarchical Spectrum Markets

    CERN Document Server

    Iosifidis, George; Alpcan, Tansu; Koutsopoulos, Iordanis

    2011-01-01

    We study spectrum allocation mechanisms in hierarchical multi-layer markets which are expected to proliferate in the near future based on the current spectrum policy reform proposals. We consider a setting where a state agency sells spectrum to Primary Operators (POs) and in turn these resell it to Secondary Operators (SOs) through auctions. We show that these hierarchical markets do not result in a socially efficient spectrum allocation which is aimed by the agency, due to lack of coordination among the entities in different layers and the inherently selfish revenue-maximizing strategy of POs. In order to reconcile these opposing objectives, we propose an incentive mechanism which aligns the strategy and the actions of the POs with the objective of the agency, and thus it leads to system performance improvement in terms of social welfare. This pricing based mechanism constitutes a method for hierarchical market regulation and requires the feedback provision from SOs. A basic component of the proposed incenti...

  18. Hierarchical self-organization of tectonic plates

    CERN Document Server

    Morra, Gabriele; Müller, R Dietmar

    2010-01-01

    The Earth's surface is subdivided into eight large tectonic plates and many smaller ones. We reconstruct the plate tessellation history and demonstrate that both large and small plates display two distinct hierarchical patterns, described by different power-law size-relationships. While small plates display little organisational change through time, the structure of the large plates oscillate between minimum and maximum hierarchical tessellations. The organization of large plates rapidly changes from a weak hierarchy at 120-100 million years ago (Ma) towards a strong hierarchy, which peaked at 65-50, Ma subsequently relaxing back towards a minimum hierarchical structure. We suggest that this fluctuation reflects an alternation between top and bottom driven plate tectonics, revealing a previously undiscovered tectonic cyclicity at a timescale of 100 million years.

  19. Towards a sustainable manufacture of hierarchical zeolites.

    Science.gov (United States)

    Verboekend, Danny; Pérez-Ramírez, Javier

    2014-03-01

    Hierarchical zeolites have been established as a superior type of aluminosilicate catalysts compared to their conventional (purely microporous) counterparts. An impressive array of bottom-up and top-down approaches has been developed during the last decade to design and subsequently exploit these exciting materials catalytically. However, the sustainability of the developed synthetic methods has rarely been addressed. This paper highlights important criteria to ensure the ecological and economic viability of the manufacture of hierarchical zeolites. Moreover, by using base leaching as a promising case study, we verify a variety of approaches to increase reactor productivity, recycle waste streams, prevent the combustion of organic compounds, and minimize separation efforts. By reducing their synthetic footprint, hierarchical zeolites are positioned as an integral part of sustainable chemistry. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Hierarchical Neural Network Structures for Phoneme Recognition

    CERN Document Server

    Vasquez, Daniel; Minker, Wolfgang

    2013-01-01

    In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a  Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.

  1. 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...

  2. Static and dynamic friction of hierarchical surfaces

    Science.gov (United States)

    Costagliola, Gianluca; Bosia, Federico; Pugno, Nicola M.

    2016-12-01

    Hierarchical structures are very common in nature, but only recently have they been systematically studied in materials science, in order to understand the specific effects they can have on the mechanical properties of various systems. Structural hierarchy provides a way to tune and optimize macroscopic mechanical properties starting from simple base constituents and new materials are nowadays designed exploiting this possibility. This can be true also in the field of tribology. In this paper we study the effect of hierarchical patterned surfaces on the static and dynamic friction coefficients of an elastic material. Our results are obtained by means of numerical simulations using a one-dimensional spring-block model, which has previously been used to investigate various aspects of friction. Despite the simplicity of the model, we highlight some possible mechanisms that explain how hierarchical structures can significantly modify the friction coefficients of a material, providing a means to achieve tunability.

  3. Arbuscular, ecto-related, orchid mycorrhizas--three independent structural lineages towards mycoheterotrophy: implications for classification?

    Science.gov (United States)

    Imhof, Stephan

    2009-08-01

    The classification of mycorrhizas in seven equally ranked types glosses over differences and similarities and, in particular, does not acknowledge the structural diversity of arbuscular mycorrhizas. This article emphasizes the parallel continua of ecto-related mycorrhizas and arbuscular mycorrhizas, exemplified within Ericaceae and Gentianales, respectively, as well as the proprietary development of orchid mycorrhizas, all three of which have independently developed mycoheterotrophic plants. A hierarchical classification according to structural similarities is suggested.

  4. Consequences of more extreme precipitation regimes for terrestrial ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, Alan [Colorado State University, Fort Collins; Beier, Claus [Riso National Laboratory, Roskilde, Denmark; Briske, David [Texas A& M University; Classen, Aimee T [ORNL; Luo, Yiqi [University of Oklahoma; Reichstein, Markus [Max Planck Institute for Biogeochemistry; Smith, Melinda D [Yale University; Smith, Stanley D [University of Nevada, Las Vegas; Bell, Jesse E [University of Oklahoma; Fay, Philip [ORNL; Heisler, Jana A [Colorado State University, Fort Collins; Leavitt, Steven W [unknown; Sherry, Rebecca [University of Oklahoma; Smith, Ben [unknown; Weng, Ensheng [University of Oklahoma, Norman; Norby, Richard J [ORNL

    2008-09-01

    Amplification of the hydrological cycle, as a consequence of global warming, is forecast to be manifest not only by alterations in total annual precipitation, but also through more extreme precipitation regimes characterized by larger rainfall events and more severe intervening drought periods. Based on past studies and theory, we present a conceptual framework for predicting the consequences of this projected change in intra-annual rainfall patterns for terrestrial ecosystems arrayed along a broad gradient in water availability. More extreme rainfall regimes are predicted to increase the occurrence of periodic soil water stress in mesic ecosystems due to prolonged dry periods between rainfall events. In contrast, xeric ecosystems may exhibit the opposite response because a shift to a greater proportion of rainfall delivered in large precipitation events will result in reduced proportional evaporative losses per storm event and greater soil water storage, alleviating soil water stress for longer periods of time. Hydric ecosystems may experience reduced periods of anoxia if intervals between rainfall events increase. This contingent effect of the overall soil water balance on ecosystem responses will likely cascade through all hierarchical levels of ecological processes and interact in ways currently unknown with related global change drivers such as elevated atmospheric temperatures and CO2 concentrations. Thus, multi-factor comparative experiments and systems modeling approaches are needed to more fully understand and forecast the potential ecological consequences of this underappreciated aspect of climate change.

  5. Automated compound classification using a chemical ontology

    Directory of Open Access Journals (Sweden)

    Bobach Claudia

    2012-12-01

    Full Text Available Abstract Background Classification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds. Results In the present work we implement principles and methods to construct a chemical ontology of classes that shall support the automated, high-quality compound classification in chemical databases or text documents. While SMARTS expressions have already been used to define chemical structure class concepts, in the present work we have extended the expressive power of such class definitions by expanding their structure-based reasoning logic. Thus, to achieve the required precision and granularity of chemical class definitions, sets of SMARTS class definitions are connected by OR and NOT logical operators. In addition, AND logic has been implemented to allow the concomitant use of flexible atom lists and stereochemistry definitions. The resulting chemical ontology is a multi-hierarchical taxonomy of concept nodes connected by directed, transitive relationships. Conclusions A proposal for a rule based definition of chemical classes has been made that allows to define chemical compound classes more precisely than before. The proposed structure-based reasoning

  6. Hierarchical control of electron-transfer

    DEFF Research Database (Denmark)

    Westerhoff, Hans V.; Jensen, Peter Ruhdal; Egger, Louis;

    1997-01-01

    In this chapter the role of electron transfer in determining the behaviour of the ATP synthesising enzyme in E. coli is analysed. It is concluded that the latter enzyme lacks control because of special properties of the electron transfer components. These properties range from absence of a strong...... back pressure by the protonmotive force on the rate of electron transfer to hierarchical regulation of the expression of the gens that encode the electron transfer proteins as a response to changes in the bioenergetic properties of the cell.The discussion uses Hierarchical Control Analysis...

  7. Genetic Algorithm for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sajid Hussain

    2007-09-01

    Full Text Available Large scale wireless sensor networks (WSNs can be used for various pervasive and ubiquitous applications such as security, health-care, industry automation, agriculture, environment and habitat monitoring. As hierarchical clusters can reduce the energy consumption requirements for WSNs, we investigate intelligent techniques for cluster formation and management. A genetic algorithm (GA is used to create energy efficient clusters for data dissemination in wireless sensor networks. The simulation results show that the proposed intelligent hierarchical clustering technique can extend the network lifetime for different network deployment environments.

  8. DC Hierarchical Control System for Microgrid Applications

    OpenAIRE

    Lu, Xiaonan; Sun, Kai; Guerrero, Josep M.; Huang, Lipei

    2013-01-01

    In order to enhance the DC side performance of AC-DC hybrid microgrid,a DC hierarchical control system is proposed in this paper.To meet the requirement of DC load sharing between the parallel power interfaces,droop method is adopted.Meanwhile,DC voltage secondary control is employed to restore the deviation in the DC bus voltage.The hierarchical control system is composed of two levels.DC voltage and AC current controllers are achieved in the primary control level.

  9. Hierarchical social networks and information flow

    Science.gov (United States)

    López, Luis; F. F. Mendes, Jose; Sanjuán, Miguel A. F.

    2002-12-01

    Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders, because the global influence each actor has within the network is completely determined by the hierarchical level occupied.

  10. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  11. Hierarchic Models of Turbulence, Superfluidity and Superconductivity

    CERN Document Server

    Kaivarainen, A

    2000-01-01

    New models of Turbulence, Superfluidity and Superconductivity, based on new Hierarchic theory, general for liquids and solids (physics/0102086), have been proposed. CONTENTS: 1 Turbulence. General description; 2 Mesoscopic mechanism of turbulence; 3 Superfluidity. General description; 4 Mesoscopic scenario of fluidity; 5 Superfluidity as a hierarchic self-organization process; 6 Superfluidity in 3He; 7 Superconductivity: General properties of metals and semiconductors; Plasma oscillations; Cyclotron resonance; Electroconductivity; 8. Microscopic theory of superconductivity (BCS); 9. Mesoscopic scenario of superconductivity: Interpretation of experimental data in the framework of mesoscopic model of superconductivity.

  12. Hierarchical Analysis of the Omega Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Paulson, Patrick R.

    2009-12-01

    Initial delivery for mathematical analysis of the Omega Ontology. We provide an analysis of the hierarchical structure of a version of the Omega Ontology currently in use within the US Government. After providing an initial statistical analysis of the distribution of all link types in the ontology, we then provide a detailed order theoretical analysis of each of the four main hierarchical links present. This order theoretical analysis includes the distribution of components and their properties, their parent/child and multiple inheritance structure, and the distribution of their vertical ranks.

  13. Mapping cultural ecosystem services:

    DEFF Research Database (Denmark)

    Paracchini, Maria Luisa; Zulian, Grazia; Kopperoinen, Leena

    2014-01-01

    is required to address the issue, since by definition cultural services (encompassing physical, intellectual, spiritual interactions with biota) need to be analysed from multiple perspectives (i.e. ecological, social, behavioural). A second reason is the lack of data for large-scale assessments, as detailed......Research on ecosystem services mapping and valuing has increased significantly in recent years. However, compared to provisioning and regulating services, cultural ecosystem services have not yet been fully integrated into operational frameworks. One reason for this is that transdisciplinarity...... surveys are a main source of information. Among cultural ecosystem services, assessment of outdoor recreation can be based on a large pool of literature developed mostly in social and medical science, and landscape and ecology studies. This paper presents a methodology to include recreation...

  14. Nutrient budget in ecosystems

    Science.gov (United States)

    Titlyanova, A. A.

    2007-12-01

    Methods to calculate nutrient budgets in forest and grassland ecosystems are analyzed on the basis of a large number of published materials and original data. New estimates of the belowground production in forest ecosystems with due account for the growth of fine roots are suggested. Nutrient retranslocation from senescent plant tissues to growing plant tissues and nutrient leaching from the forest canopy are discussed. The budgets of major nutrients (N, P, K, and Ca) in tundra, forest, and steppe ecosystems are calculated. Nutrient cycles in two forest ecosystems—a coniferous stand dominated by Picea abies and a broad-leaved stand dominated by Quercus robur—are analyzed in detail. It is shown that the more intensive turnover of nutrients in the oak stand is also characterized by a more closed character of the nutrient cycles.

  15. A Classification of Landscape Services to Support Local Landscape Planning

    Directory of Open Access Journals (Sweden)

    2014-03-01

    Full Text Available The ecosystem services approach has been proven successful to measure the contributions of nature and greenery to human well-being. Ecosystems have an effect on quality of life, but landscapes also, as a broader concept, may contribute to people's well-being. The concept of landscape services, compared to ecosystem services, involves the social dimension of landscape and the spatial pattern resulting from both natural and human processes in the provision of benefits for human-well being. Our aim is to develop a classification for landscape services. The proposed typology of services is built on the Common International Classification of Ecosystem Services (CICES and on a critical review of existing literature on human well-being dimensions, existing ecosystem service classifications, and landscape perception. Three themes of landscape services are defined, each divided into several groups: provisioning, regulation and maintenance, cultural and social life fulfillment, with the latter focusing on health, enjoyment, and personal and social fulfillment. A special emphasis is made on cultural services, which are especially important when applied to landscape and which have received less attention.

  16. Catastrophic shifts in ecosystems

    Science.gov (United States)

    Scheffer, Marten; Carpenter, Steve; Foley, Jonathan A.; Folke, Carl; Walker, Brian

    2001-10-01

    All ecosystems are exposed to gradual changes in climate, nutrient loading, habitat fragmentation or biotic exploitation. Nature is usually assumed to respond to gradual change in a smooth way. However, studies on lakes, coral reefs, oceans, forests and arid lands have shown that smooth change can be interrupted by sudden drastic switches to a contrasting state. Although diverse events can trigger such shifts, recent studies show that a loss of resilience usually paves the way for a switch to an alternative state. This suggests that strategies for sustainable management of such ecosystems should focus on maintaining resilience.

  17. Bioenergetics in ecosystems

    Science.gov (United States)

    Madenjian, Charles P.; Farrell, Anthony P.

    2011-01-01

    A bioenergetics model for a fish can be defined as a quantitative description of the fish’s energy budget. Bioenergetics modeling can be applied to a fish population in a lake, river, or ocean to estimate the annual consumption of food by the fish population; such applications have proved to be useful in managing fisheries. In addition, bioenergetics models have been used to better understand fish growth and consumption in ecosystems, to determine the importance of the role of fish in cycling nutrients within ecosystems, and to identify the important factors regulating contaminant accumulation in fish from lakes, rivers, and oceans.

  18. A software tool for ecosystem services assessments

    Science.gov (United States)

    Riegels, Niels; Klinting, Anders; Butts, Michael; Middelboe, Anne Lise; Mark, Ole

    2017-04-01

    The EU FP7 DESSIN project is developing methods and tools for assessment of ecosystem services (ESS) and associated economic values, with a focus on freshwater ESS in urban settings. Although the ESS approach has gained considerable visibility over the past ten years, operationalizing the approach remains a challenge. Therefore, DESSSIN is also supporting development of a free software tool to support users implementing the DESSIN ESS evaluation framework. The DESSIN ESS evaluation framework is a structured approach to measuring changes in ecosystem services. The main purpose of the framework is to facilitate the application of the ESS approach in the appraisal of projects that have impacts on freshwater ecosystems and their services. The DESSIN framework helps users evaluate changes in ESS by linking biophysical, economic, and sustainability assessments sequentially. It was developed using the Common International Classification of Ecosystem Services (CICES) and the DPSIR (Drivers, Pressures, States, Impacts, Responses) adaptive management cycle. The former is a standardized system for the classification of ESS developed by the European Union to enhance the consistency and comparability of ESS assessments. The latter is a well-known concept to disentangle the biophysical and social aspects of a system under study. As part of its analytical component, the DESSIN framework also integrates elements of the Final Ecosystem Goods and Services-Classification System (FEGS-CS) of the US Environmental Protection Agency (USEPA). As implemented in the software tool, the DESSIN framework consists of five parts: • In part I of the evaluation, the ecosystem is defined and described and the local stakeholders are identified. In addition, administrative details and objectives of the assessment are defined. • In part II, drivers and pressures are identified. Once these first two elements of the DPSIR scheme have been characterized, the claimed/expected capabilities of a

  19. Classification of refrigerants; Classification des fluides frigorigenes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

  20. Cancer Biochemistry and Host-Tumor Interactions: A Decimal Classification, (Categories 51.6, 51.7, and 51.8).

    Science.gov (United States)

    Schneider, John H.

    This is a hierarchical decimal classification of information related to cancer biochemistry, to host-tumor interactions (including cancer immunology), and to occurrence of cancer in special types of animals and plants. It is a working draft of categories taken from an extensive classification of many fields of biomedical information. Because the…

  1. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

  2. Hierarchical machining materials and their performance

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Levashov, Evgeny

    2016-01-01

    as nanoparticles in the binder, or polycrystalline, aggregate-like reinforcements, also at several scale levels). Such materials can ensure better productivity, efficiency, and lower costs of drilling, cutting, grinding, and other technological processes. This article reviews the main groups of hierarchical...

  3. Hierarchical Optimization of Material and Structure

    DEFF Research Database (Denmark)

    Rodrigues, Helder C.; Guedes, Jose M.; Bendsøe, Martin P.

    2002-01-01

    This paper describes a hierarchical computational procedure for optimizing material distribution as well as the local material properties of mechanical elements. The local properties are designed using a topology design approach, leading to single scale microstructures, which may be restricted...... in various ways, based on design and manufacturing criteria. Implementation issues are also discussed and computational results illustrate the nature of the procedure....

  4. Hierarchical structure of nanofibers by bubbfil spinning

    Directory of Open Access Journals (Sweden)

    Liu Chang

    2015-01-01

    Full Text Available A polymer bubble is easy to be broken under a small external force, various different fragments are formed, which can be produced to different morphologies of products including nanofibers and plate-like strip. Polyvinyl-alcohol/honey solution is used in the experiment to show hierarchical structure by the bubbfil spinning.

  5. Sharing the proceeds from a hierarchical venture

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Moreno-Ternero, Juan D.; Tvede, Mich;

    2017-01-01

    We consider the problem of distributing the proceeds generated from a joint venture in which the participating agents are hierarchically organized. We introduce and characterize a family of allocation rules where revenue ‘bubbles up’ in the hierarchy. The family is flexible enough to accommodate...

  6. Metal oxide nanostructures with hierarchical morphology

    Science.gov (United States)

    Ren, Zhifeng; Lao, Jing Yu; Banerjee, Debasish

    2007-11-13

    The present invention relates generally to metal oxide materials with varied symmetrical nanostructure morphologies. In particular, the present invention provides metal oxide materials comprising one or more metallic oxides with three-dimensionally ordered nanostructural morphologies, including hierarchical morphologies. The present invention also provides methods for producing such metal oxide materials.

  7. Hierarchical Scaling in Systems of Natural Cities

    CERN Document Server

    Chen, Yanguang

    2016-01-01

    Hierarchies can be modeled by a set of exponential functions, from which we can derive a set of power laws indicative of scaling. These scaling laws are followed by many natural and social phenomena such as cities, earthquakes, and rivers. This paper is devoted to revealing the scaling patterns in systems of natural cities by reconstructing the hierarchy with cascade structure. The cities of America, Britain, France, and Germany are taken as examples to make empirical analyses. The hierarchical scaling relations can be well fitted to the data points within the scaling ranges of the size and area of the natural cities. The size-number and area-number scaling exponents are close to 1, and the allometric scaling exponent is slightly less than 1. The results suggest that natural cities follow hierarchical scaling laws and hierarchical conservation law. Zipf's law proved to be one of the indications of the hierarchical scaling, and the primate law of city-size distribution represents a local pattern and can be mer...

  8. Semiparametric Quantile Modelling of Hierarchical Data

    Institute of Scientific and Technical Information of China (English)

    Mao Zai TIAN; Man Lai TANG; Ping Shing CHAN

    2009-01-01

    The classic hierarchical linear model formulation provides a considerable flexibility for modelling the random effects structure and a powerful tool for analyzing nested data that arise in various areas such as biology, economics and education. However, it assumes the within-group errors to be independently and identically distributed (i.i.d.) and models at all levels to be linear. Most importantly, traditional hierarchical models (just like other ordinary mean regression methods) cannot characterize the entire conditional distribution of a dependent variable given a set of covariates and fail to yield robust estimators. In this article, we relax the aforementioned and normality assumptions, and develop a so-called Hierarchical Semiparametric Quantile Regression Models in which the within-group errors could be heteroscedastic and models at some levels are allowed to be nonparametric. We present the ideas with a 2-level model. The level-l model is specified as a nonparametric model whereas level-2 model is set as a parametric model. Under the proposed semiparametric setting the vector of partial derivatives of the nonparametric function in level-1 becomes the response variable vector in level 2. The proposed method allows us to model the fixed effects in the innermost level (i.e., level 2) as a function of the covariates instead of a constant effect. We outline some mild regularity conditions required for convergence and asymptotic normality for our estimators. We illustrate our methodology with a real hierarchical data set from a laboratory study and some simulation studies.

  9. 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.

  10. Managing Clustered Data Using Hierarchical Linear Modeling

    Science.gov (United States)

    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  11. Strategic games on a hierarchical network model

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Among complex network models, the hierarchical network model is the one most close to such real networks as world trade web, metabolic network, WWW, actor network, and so on. It has not only the property of power-law degree distribution, but growth based on growth and preferential attachment, showing the scale-free degree distribution property. In this paper, we study the evolution of cooperation on a hierarchical network model, adopting the prisoner's dilemma (PD) game and snowdrift game (SG) as metaphors of the interplay between connected nodes. BA model provides a unifying framework for the emergence of cooperation. But interestingly, we found that on hierarchical model, there is no sign of cooperation for PD game, while the frequency of cooperation decreases as the common benefit decreases for SG. By comparing the scaling clustering coefficient properties of the hierarchical network model with that of BA model, we found that the former amplifies the effect of hubs. Considering different performances of PD game and SG on complex network, we also found that common benefit leads to cooperation in the evolution. Thus our study may shed light on the emergence of cooperation in both natural and social environments.

  12. Endogenous Effort Norms in Hierarchical Firms

    NARCIS (Netherlands)

    J. Tichem (Jan)

    2013-01-01

    markdownabstract__Abstract__ This paper studies how a three-layer hierarchical firm (principal-supervisor-agent) optimally creates effort norms for its employees. The key assumption is that effort norms are affected by the example of superiors. In equilibrium, norms are eroded as one moves down

  13. Complex Evaluation of Hierarchically-Network Systems

    CERN Document Server

    Polishchuk, Dmytro; Yadzhak, Mykhailo

    2016-01-01

    Methods of complex evaluation based on local, forecasting, aggregated, and interactive evaluation of the state, function quality, and interaction of complex system's objects on the all hierarchical levels is proposed. Examples of analysis of the structural elements of railway transport system are used for illustration of efficiency of proposed approach.

  14. A Hierarchical Grouping of Great Educators

    Science.gov (United States)

    Barker, Donald G.

    1977-01-01

    Great educators of history were categorized on the basis of their: aims of education, fundamental ideas, and educational theories. They were classed by Ward's method of hierarchical analysis into six groupings: Socrates, Ausonius, Jerome, Abelard; Quintilian, Origen, Melanchthon, Ascham, Loyola; Alciun, Comenius; Vittorino, Basedow, Pestalozzi,…

  15. Ultrafast Hierarchical OTDM/WDM Network

    Directory of Open Access Journals (Sweden)

    Hideyuki Sotobayashi

    2003-12-01

    Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

  16. Hierarchical fuzzy identification of MR damper

    Science.gov (United States)

    Wang, Hao; Hu, Haiyan

    2009-07-01

    Magneto-rheological (MR) dampers, recently, have found many successful applications in civil engineering and numerous area of mechanical engineering. When an MR damper is to be used for vibration suppression, an inevitable problem is to determine the input voltage so as to gain the desired restoring force determined from the control law. This is the so-called inverse problem of MR dampers and is always an obstacle in the application of MR dampers to vibration control. It is extremely difficult to get the inverse model of MR damper because MR dampers are highly nonlinear and hysteretic. When identifying the inverse model of MR damper with simple fuzzy system, there maybe exists curse of dimensionality of fuzzy system. Therefore, it will take much more time, and even the inverse model may not be identifiable. The paper presents two-layer hierarchical fuzzy system, that is, two-layer hierarchical ANFIS to deal with the curse of dimensionality of the fuzzy identification of MR damper and to identify the inverse model of MR damper. Data used for training the model are generated from numerical simulation of nonlinear differential equations. The numerical simulation proves that the proposed hierarchical fuzzy system can model the inverse model of MR damper much more quickly than simple fuzzy system without any reduction of identification precision. Such hierarchical ANFIS shows the higher priority for the complicated system, and can also be used in system identification and system control for the complicated system.

  17. Statistical theory of hierarchical avalanche ensemble

    OpenAIRE

    Olemskoi, Alexander I.

    1999-01-01

    The statistical ensemble of avalanche intensities is considered to investigate diffusion in ultrametric space of hierarchically subordinated avalanches. The stationary intensity distribution and the steady-state current are obtained. The critical avalanche intensity needed to initiate the global avalanche formation is calculated depending on noise intensity. The large time asymptotic for the probability of the global avalanche appearance is derived.

  18. Managing Clustered Data Using Hierarchical Linear Modeling

    Science.gov (United States)

    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  19. 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....

  20. Evaluation Model of Design for Operation and Architecture of Hierarchical Virtual Simulation for Flight Vehicle Design

    Institute of Scientific and Technical Information of China (English)

    LIU Hu; TIAN Yongliang; ZHANG Chaoying; YIN Jiao; SUN Yijie

    2012-01-01

    In order to take requirements for commercial operations or military missions into better consideration in new flight vehicle design,a tri-hierarchical task classification model of "design for operation" is proposed,which takes basic man-object interaction task,complex collaborative operation and large-scale joint operation into account.The corresponding general architecture of evaluation criteria is also depicted.Then a virtual simulation-based approach to implement the evaluations at three hierarchy levels is mainly analyzed with a detailed example,which validates the feasibility and effectiveness of evaluation architecture.Finally,extending the virtual simulation architecture from design to operation training is discussed.

  1. A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions

    Directory of Open Access Journals (Sweden)

    Nabil Sabor

    2017-01-01

    Full Text Available Introducing mobility to Wireless Sensor Networks (WSNs puts new challenges particularly in designing of routing protocols. Mobility can be applied to the sensor nodes and/or the sink node in the network. Many routing protocols have been developed to support the mobility of WSNs. These protocols are divided depending on the routing structure into hierarchical-based, flat-based, and location-based routing protocols. However, the hierarchical-based routing protocols outperform the other routing types in saving energy, scalability, and extending lifetime of Mobile WSNs (MWSNs. Selecting an appropriate hierarchical routing protocol for specific applications is an important and difficult task. Therefore, this paper focuses on reviewing some of the recently hierarchical-based routing protocols that are developed in the last five years for MWSNs. This survey divides the hierarchical-based routing protocols into two broad groups, namely, classical-based and optimized-based routing protocols. Also, we present a detailed classification of the reviewed protocols according to the routing approach, control manner, mobile element, mobility pattern, network architecture, clustering attributes, protocol operation, path establishment, communication paradigm, energy model, protocol objectives, and applications. Moreover, a comparison between the reviewed protocols is investigated in this survey depending on delay, network size, energy-efficiency, and scalability while mentioning the advantages and drawbacks of each protocol. Finally, we summarize and conclude the paper with future directions.

  2. Classification of shoulder complaints in general practice by means of nonmetric multidimensional scaling

    NARCIS (Netherlands)

    Groenier, KH; Winters, JC; Meyboom-de Jong, B

    2003-01-01

    Objectives: To determine if a classification of shoulder complaints in general practice can be made from variables of medical history and physical examination with nonmetric multidimensional scaling and to investigate the reproducibility of results from an earlier hierarchical cluster analysis. Desi

  3. Classification and Diagnostic Output Prediction of Cancer Using Gene Expression Profiling and Supervised Machine Learning Algorithms

    DEFF Research Database (Denmark)

    Yoo, C.; Gernaey, Krist

    2008-01-01

    In this paper, a new supervised clustering and classification method is proposed. First, the application of discriminant partial least squares (DPLS) for the selection of a minimum number of key genes is applied on a gene expression microarray data set. Second, supervised hierarchical clustering ...

  4. Governing ecosystem services

    NARCIS (Netherlands)

    Verburg, René; Selnes, Trond; Verweij, Pita

    2016-01-01

    The TEEB approach to the use of ecosystem services has found its way to policy as a means to biodiversity conservation and greening of the economy. In this paper we analysed the uptake of the TEEB approach at national and local levels by applying a framework that revolves around the problem, appr

  5. Shelf-sea ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Walsh, J J

    1980-01-01

    An analysis of the food chain dynamics of the Oregon, Alaskan, and New York shelves is made with respect to differences in physical forcing of these ecosystems. The world's shelves are 10% of the area of the ocean, yield 99% of the world's fish catch, and may be a major sink in the global CO/sub 2/ budget.

  6. Environmental Impacts - Coastal Ecosystems

    NARCIS (Netherlands)

    Bakker, J.P.; Baas, Andreas C.W.; Bartholdy, Jesper; Jones, Laurence; Ruessink, B.G.; Temmerman, Stijn; van de Pol, Martijn

    2016-01-01

    This chapter examines the impacts of climate change on the natural coastal ecosystems in the North Sea region. These comprise sandy shores and dunes and salt marshes in estuaries and along the coast. The chapter starts by describing the characteristic geomorphological features of these systems and t

  7. Governance of Ecosystem Services

    NARCIS (Netherlands)

    Primmer, Eeva; Jokinen, Pekka; Blicharska, Malgorzata; Barton, David N.; Bugter, Rob; Potschin, Marion

    2015-01-01

    Biodiversity conservation policies justified with science and intrinsic value arguments have produced disappointing outcomes, and the need for conservation is now being additionally justified with the concept of ecosystem services. However, little, if any empirical attention is paid to ways in wh

  8. Partitioning ecosystems for sustainability.

    Science.gov (United States)

    Murray, Martyn G

    2016-03-01

    Decline in the abundance of renewable natural resources (RNRs) coupled with increasing demands of an expanding human population will greatly intensify competition for Earth's natural resources during this century, yet curiously, analytical approaches to the management of productive ecosystems (ecological theory of wildlife harvesting, tragedy of the commons, green economics, and bioeconomics) give only peripheral attention to the driving influence of competition on resource exploitation. Here, I apply resource competition theory (RCT) to the exploitation of RNRs and derive four general policies in support of their sustainable and equitable use: (1) regulate resource extraction technology to avoid damage to the resource base; (2) increase efficiency of resource use and reduce waste at every step in the resource supply chain and distribution network; (3) partition ecosystems with the harvesting niche as the basic organizing principle for sustainable management of natural resources by multiple users; and (4) increase negative feedback between consumer and resource to bring about long-term sustainable use. A simple policy framework demonstrates how RCT integrates with other elements of sustainability science to better manage productive ecosystems. Several problem areas of RNR management are discussed in the light of RCT, including tragedy of the commons, overharvesting, resource collapse, bycatch, single species quotas, and simplification of ecosystems.

  9. Generic hierarchical engine for mask data preparation

    Science.gov (United States)

    Kalus, Christian K.; Roessl, Wolfgang; Schnitker, Uwe; Simecek, Michal

    2002-07-01

    Electronic layouts are usually flattened on their path from the hierarchical source downstream to the wafer. Mask data preparation has certainly been identified as a severe bottleneck since long. Data volumes are not only doubling every year along the ITRS roadmap. With the advent of optical proximity correction and phase-shifting masks data volumes are escalating up to non-manageable heights. Hierarchical treatment is one of the most powerful means to keep memory and CPU consumption in reasonable ranges. Only recently, however, has this technique acquired more public attention. Mask data preparation is the most critical area calling for a sound infrastructure to reduce the handling problem. Gaining more and more attention though, are other applications such as large area simulation and manufacturing rule checking (MRC). They all would profit from a generic engine capable to efficiently treat hierarchical data. In this paper we will present a generic engine for hierarchical treatment which solves the major problem, steady transitions along cell borders. Several alternatives exist how to walk through the hierarchy tree. They have, to date, not been thoroughly investigated. One is a bottom-up attempt to treat cells starting with the most elementary cells. The other one is a top-down approach which lends itself to creating a new hierarchy tree. In addition, since the variety, degree of hierarchy and quality of layouts extends over a wide range a generic engine has to take intelligent decisions when exploding the hierarchy tree. Several applications will be shown, in particular how far the limits can be pushed with the current hierarchical engine.

  10. Hierarchical organisation in perception of orientation.

    Science.gov (United States)

    Spinelli, D; Antonucci, G; Daini, R; Martelli, M L; Zoccolotti, P

    1999-01-01

    According to Rock [1990, in The Legacy of Solomon Asch (Hillsdale, NJ: Lawrence Erlbaum Associates)], hierarchical organisation of perception describes cases in which the orientation of an object is affected by the immediately surrounding elements in the visual field. Various experiments were performed to study the hierarchical organisation of orientation perception. In most of them the rod-and-frame-illusion (RFI: change of the apparent vertical measured on a central rod surrounded by a tilted frame) was measured in the presence/absence of a second inner frame. The first three experiments showed that, when the inner frame is vertical, the direction and size of the illusion are consistent with expectancies based on the hierarchical organisation hypothesis. An analysis of published and unpublished data collected on a large number of subjects showed that orientational hierarchical effects are independent from the absolute size of the RFI. In experiments 4 to 7 we examined the perceptual conditions of the inner stimulus (enclosure, orientation, and presence of luminance borders) critical for obtaining a hierarchical organisation effect. Although an inner vertical square was effective in reducing the illusion (experiment 3), an inner circle enclosing the rod was ineffective (experiment 4). This indicates that definite orientation is necessary to modulate the illusion. However, orientational information provided by a vertical or horizontal rectangle presented near the rod, but not enclosing it, did not modulate the RFI (experiment 5). This suggests that the presence of a figure with oriented contours enclosing the rod is critical. In experiments 6 and 7 we studied whether the presence of luminance borders is important or whether the inner upright square might be effective also if made of subjective contours. When the subjective contour figure was salient and the observers perceived it clearly, its effectiveness in modulating the RFI was comparable to that observed with

  11. Classification of mangroves vegetation species using texture analysis on Rapideye satellite imagery

    Science.gov (United States)

    Roslani, M. A.; Mustapha, M. A.; Lihan, T.; Juliana, W. A. Wan

    2013-11-01

    Mangroves are unique ecosystem structures that are typically made up of salt tolerant species of vegetation that can be found in tropical and subtropical climate country. Mangrove ecosystem plays important role and also is known as highly productive ecosystem with high diversity of flora and fauna. However, these ecosystems have been declining over time due to the various kinds of direct and indirect pressures. Thus, there is an increasing need to monitor and assess this ecosystem for better conservation and management efforts. The multispectral RapidEye satellite image was used to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia using texture analysis. Classification was implemented using the maximum likelihood classifier (MLC) method. Total of eleven main mangrove species were found in the satellite image of the study site which includes Rhizophora mucronata, Rhizophora apiculata, Bruguiera parviflora, Bruguiera cylindrica, Bruguiera gymnorrhiza, Avicennia alba, Avicennia officinalis, Sonneratia alba, Sonneratia caseolaris, Sonneratia ovata and Xylocarpus granatum. The classification results showed that the textured image produced high overall classification assessment recorded at 84% and kappa statistic of 0.8016. Meanwhile, the non-textured image produces 80% of overall accuracy and kappa statistic of 0.7061. The classification result indicated the capability of high resolution satellite image to classify the mangrove species and inclusion of texture information in the classification increased the classification accuracy.

  12. Does Biodiversity-Ecosystem Function Literature Neglect Tropical Ecosystems?

    Science.gov (United States)

    Clarke, David A; York, Paul H; Rasheed, Michael A; Northfield, Tobin D

    2017-05-01

    Current evidence suggests that there is a positive relationship between biodiversity and ecosystem functioning, but few studies have addressed tropical ecosystems where the highest levels of biodiversity occur. We develop two hypotheses for the implications of generalizing from temperate studies to tropical ecosystems, and discuss the need for more tropical research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  14. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1989-09-01

    Certain governmental information must be classified for national security reasons. However, the national security benefits from classifying information are usually accompanied by significant costs -- those due to a citizenry not fully informed on governmental activities, the extra costs of operating classified programs and procuring classified materials (e.g., weapons), the losses to our nation when advances made in classified programs cannot be utilized in unclassified programs. The goal of a classification system should be to clearly identify that information which must be protected for national security reasons and to ensure that information not needing such protection is not classified. This document was prepared to help attain that goal. This document is the first of a planned four-volume work that comprehensively discusses the security classification of information. Volume 1 broadly describes the need for classification, the basis for classification, and the history of classification in the United States from colonial times until World War 2. Classification of information since World War 2, under Executive Orders and the Atomic Energy Acts of 1946 and 1954, is discussed in more detail, with particular emphasis on the classification of atomic energy information. Adverse impacts of classification are also described. Subsequent volumes will discuss classification principles, classification management, and the control of certain unclassified scientific and technical information. 340 refs., 6 tabs.

  15. Economic viewpoints on ecosystem services

    NARCIS (Netherlands)

    Silvis, H.J.; Heide, van der C.M.

    2013-01-01

    to help determine the different values of ecosystems. Ecosystem services are usually divided into four categories: provisioning services, regulating services, cultural services and habitat services (previously denoted as supporting services). This overview highlights economic theories about

  16. Economic viewpoints on ecosystem services

    NARCIS (Netherlands)

    Silvis, H.J.; Heide, van der C.M.

    2013-01-01

    to help determine the different values of ecosystems. Ecosystem services are usually divided into four categories: provisioning services, regulating services, cultural services and habitat services (previously denoted as supporting services). This overview highlights economic theories about ecosyste

  17. Automatic figure classification in bioscience literature.

    Science.gov (United States)

    Kim, Daehyun; Ramesh, Balaji Polepalli; Yu, Hong

    2011-10-01

    Millions of figures appear in biomedical articles, and it is important to develop an intelligent figure search engine to return relevant figures based on user entries. In this study we report a figure classifier that automatically classifies biomedical figures into five predefined figure types: Gel-image, Image-of-thing, Graph, Model, and Mix. The classifier explored rich image features and integrated them with text features. We performed feature selection and explored different classification models, including a rule-based figure classifier, a supervised machine-learning classifier, and a multi-model classifier, the latter of which integrated the first two classifiers. Our results show that feature selection improved figure classification and the novel image features we explored were the best among image features that we have examined. Our results also show that integrating text and image features achieved better performance than using either of them individually. The best system is a multi-model classifier which combines the rule-based hierarchical classifier and a support vector machine (SVM) based classifier, achieving a 76.7% F1-score for five-type classification. We demonstrated our system at http://figureclassification.askhermes.org/.

  18. Some Basic Elements in Clustering and Classification

    Science.gov (United States)

    Grégoire, G.

    2016-05-01

    This chapter deals with basic tools useful in clustering and classification and present some commonly used approaches for these two problems. Since several chapters in these proceedings are devoted to approaches to deal with classification, we give more attention in this chapter to clustering issues. We are first concerned with notions of distances or dissimilarities between objects we are to group in clusters. Then based on these inter-objects distances we define distances between sets of objects, such as single linkage, complete linkage or Ward distance. Three clustering algorithms are presented with some details and compared: Kmeans, Ascendant Hierarchical and DBSCAN algorithms. The comparison between partitions and the issue of choosing the correct number of clusters are investigated and the proposed procedures are tested on two data sets. We emphasize the fact that the results provided by the numerous indices available in the literature for selecting the number of clusters is largely depending upon the shape and the dispersion we are assuming for these clusters. Finally the last section is devoted to classification. Some basic notions such as training sets, test sets and cross-validation are discussed. Two particular approaches are detailed, the K-nearest neighbors method and the logistic regression, and comparisons with LDA (Linear Discriminant Analysis) and QDA (Quadratic Discriminant Analysis) are analyzed.

  19. Investigating Ecosystems in a Biobottle

    Science.gov (United States)

    Breene, Arnica; Gilewski, Donna

    2008-01-01

    Biobottles are miniature ecosystems made from 2-liter plastic soda bottles. They allow students to explore how organisms in an ecosystem are connected to each other, examine how biotic and abiotic factors influence plant and animal growth and development, and discover how important biodiversity is to an ecosystem. This activity was inspired by an…

  20. The Coevolution of Digital Ecosystems

    Science.gov (United States)

    SungYong, Um

    2016-01-01

    Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among…

  1. Ecosystems in the Learning Environment

    Science.gov (United States)

    Louviere, Gregory

    2011-01-01

    Habitats, ecology and evolution are a few of the many metaphors commonly associated with the domain of biological ecosystems. Surprisingly, these and other similar biological metaphors are proving to be equally associated with a phenomenon known as digital ecosystems. Digital ecosystems make a direct connection between biological properties and…

  2. Ecosystems in the Learning Environment

    Science.gov (United States)

    Louviere, Gregory

    2011-01-01

    Habitats, ecology and evolution are a few of the many metaphors commonly associated with the domain of biological ecosystems. Surprisingly, these and other similar biological metaphors are proving to be equally associated with a phenomenon known as digital ecosystems. Digital ecosystems make a direct connection between biological properties and…

  3. The Coevolution of Digital Ecosystems

    Science.gov (United States)

    SungYong, Um

    2016-01-01

    Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among…

  4. Investigating Ecosystems in a Biobottle

    Science.gov (United States)

    Breene, Arnica; Gilewski, Donna

    2008-01-01

    Biobottles are miniature ecosystems made from 2-liter plastic soda bottles. They allow students to explore how organisms in an ecosystem are connected to each other, examine how biotic and abiotic factors influence plant and animal growth and development, and discover how important biodiversity is to an ecosystem. This activity was inspired by an…

  5. Hierarchical clusters in families with type 2 diabetes

    Science.gov (United States)

    García-Solano, Beatriz; Gallegos-Cabriales, Esther C; Gómez-Meza, Marco V; García-Madrid, Guillermina; Flores-Merlo, Marcela; García-Solano, Mauro

    2015-01-01

    Families represent more than a set of individuals; family is more than a sum of its individual members. With this classification, nurses can identify the family health-illness beliefs obey family as a unit concept, and plan family inclusion into the type 2 diabetes treatment, whom is not considered in public policy, despite families share diet, exercise, and self-monitoring with a member who suffers type 2 diabetes. The aim of this study was to determine whether the characteristics, functionality, routines, and family and individual health in type 2 diabetes describes the differences and similarities between families to consider them as a unit. We performed an exploratory, descriptive hierarchical cluster analysis of 61 families using three instruments and a questionnaire, in addition to weight, height, body fat percentage, hemoglobin A1c, total cholesterol, triglycerides, low-density lipoprotein and high-density lipoprotein. The analysis produced three groups of families. Wilk’s lambda demonstrated statistically significant differences provided by age (Λ = 0.778, F = 2.098, p = 0.010) and family health (Λ = 0.813, F = 2.650, p = 0.023). A post hoc Tukey test coincided with the three subsets. Families with type 2 diabetes have common elements that make them similar, while sharing differences that make them unique. PMID:27347419

  6. Hierarchical segmentation-assisted multimodal registration for MR brain images.

    Science.gov (United States)

    Lu, Huanxiang; Beisteiner, Roland; Nolte, Lutz-Peter; Reyes, Mauricio

    2013-04-01

    Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

  7. Hierarchical extraction of urban objects from mobile laser scanning data

    Science.gov (United States)

    Yang, Bisheng; Dong, Zhen; Zhao, Gang; Dai, Wenxia

    2015-01-01

    Point clouds collected in urban scenes contain a huge number of points (e.g., billions), numerous objects with significant size variability, complex and incomplete structures, and variable point densities, raising great challenges for the automated extraction of urban objects in the field of photogrammetry, computer vision, and robotics. This paper addresses these challenges by proposing an automated method to extract urban objects robustly and efficiently. The proposed method generates multi-scale supervoxels from 3D point clouds using the point attributes (e.g., colors, intensities) and spatial distances between points, and then segments the supervoxels rather than individual points by combining graph based segmentation with multiple cues (e.g., principal direction, colors) of the supervoxels. The proposed method defines a set of rules for merging segments into meaningful units according to types of urban objects and forms the semantic knowledge of urban objects for the classification of objects. Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by the saliency of the segments. Experiments show that the proposed method is efficient and robust for extracting buildings, streetlamps, trees, telegraph poles, traffic signs, cars, and enclosures from mobile laser scanning (MLS) point clouds, with an overall accuracy of 92.3%.

  8. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta d...... classification systems and meta data taxonomies, should be based on ontologies.......What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...

  9. On the geostatistical characterization of hierarchical media

    Science.gov (United States)

    Neuman, Shlomo P.; Riva, Monica; Guadagnini, Alberto

    2008-02-01

    The subsurface consists of porous and fractured materials exhibiting a hierarchical geologic structure, which gives rise to systematic and random spatial and directional variations in hydraulic and transport properties on a multiplicity of scales. Traditional geostatistical moment analysis allows one to infer the spatial covariance structure of such hierarchical, multiscale geologic materials on the basis of numerous measurements on a given support scale across a domain or "window" of a given length scale. The resultant sample variogram often appears to fit a stationary variogram model with constant variance (sill) and integral (spatial correlation) scale. In fact, some authors, who recognize that hierarchical sedimentary architecture and associated log hydraulic conductivity fields tend to be nonstationary, nevertheless associate them with stationary "exponential-like" transition probabilities and variograms, respectively, the latter being a consequence of the former. We propose that (1) the apparent ability of stationary spatial statistics to characterize the covariance structure of nonstationary hierarchical media is an artifact stemming from the finite size of the windows within which geologic and hydrologic variables are ubiquitously sampled, and (2) the artifact is eliminated upon characterizing the covariance structure of such media with the aid of truncated power variograms, which represent stationary random fields obtained upon sampling a nonstationary fractal over finite windows. To support our opinion, we note that truncated power variograms arise formally when a hierarchical medium is sampled jointly across all geologic categories and scales within a window; cite direct evidence that geostatistical parameters (variance and integral scale) inferred on the basis of traditional variograms vary systematically with support and window scales; demonstrate the ability of truncated power models to capture these variations in terms of a few scaling parameters

  10. Classification of Spreadsheet Errors

    OpenAIRE

    Rajalingham, Kamalasen; Chadwick, David R.; Knight, Brian

    2008-01-01

    This paper describes a framework for a systematic classification of spreadsheet errors. This classification or taxonomy of errors is aimed at facilitating analysis and comprehension of the different types of spreadsheet errors. The taxonomy is an outcome of an investigation of the widespread problem of spreadsheet errors and an analysis of specific types of these errors. This paper contains a description of the various elements and categories of the classification and is supported by appropri...

  11. Information gathering for CLP classification

    OpenAIRE

    Ida Marcello; Felice Giordano; Francesca Marina Costamagna

    2011-01-01

    Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP). If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requireme...

  12. Payment for ecosystem services

    DEFF Research Database (Denmark)

    Zandersen, Marianne; Oddershede, Jakob Stoktoft; Pedersen, Anders Branth;

    Research question: Northern Europe experiences an increasingly wet climate, leading to more frequent and severe fluvial flood events. Ecosystem-based Adaptation (EbA) is becoming recognised as a valuable yet under-utilised means to alleviating negative effects of a changing climate. This however...... that would allow the local municipality to periodically flood farmland in order to avoid or limit urban flooding from Storåen. The experiment aims to estimate the costs of getting farmers to participate in the scheme, which would represent (some of) the costs of reducing climate change problems in the town...... and based on individual negotiation would on average require a yearly payment of 309euro/ha. Significance for practical solutions: This type of analysis investigates attitudes and preferences of land owners, which are essential when dealing with Ecosystem-based Adaptation. Past experience shows that without...

  13. Stress in ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Jerneloev, A.; Wahlgren, U.

    1981-03-01

    A stress concept which relates to energy flows through eco-systems is suggested. The concept is introduced after discussion of observed phenomena. The need of quantifying of responses to external pressure is printed out. The efficiency of the systems may be defined as the degree of utilization of the available energy, and such factors may used for definitions of stress. The concepts are visualized in terms of quantities obtained from simple Lotka-Volterra-type equations.

  14. Marine Ecosystem Services

    DEFF Research Database (Denmark)

    Hasler, Berit; Ahtiainen, Heini; Hasselström, Linus

    MARECOS (Marine Ecosystem Services) er et tværfagligt studie, der har haft til formål at tilvejebringe information vedrørende kortlægning og værdisætning af økosystemtjenester, som kan anvendes i forbindelse med udformning af regulering på det marine område såvel nationalt, som regionalt og...

  15. Marine Ecosystem Services

    DEFF Research Database (Denmark)

    Hasler, Berit; Ahtiainen, Heini; Hasselström, Linus

    MARECOS (Marine Ecosystem Services) er et tværfagligt studie, der har haft til formål at tilvejebringe information vedrørende kortlægning og værdisætning af økosystemtjenester, som kan anvendes i forbindelse med udformning af regulering på det marine område såvel nationalt, som regionalt og inter...

  16. Global biogeographical pattern of ecosystem functional types derived from earth observation data

    DEFF Research Database (Denmark)

    Ivits, Eva; Cherlet, Michael; Horion, Stéphanie Marie Anne F;

    2013-01-01

    % of the variation in global ecosystems. EFTs were created based on Isodata classification of the spatial patterns of the Principal Components and were interpreted via gradient analysis using the selected remote sensing variables and climatic constraints (radiation, temperature, and water) of vegetation growth...... of global ecosystems. Climatic constraints of vegetation growth explained 50% of variation in the phenological data along the EFTs showing that part of the variation in the global phenological gradient is not climate related but is unique to the Earth Observation derived variables. DCA demonstrated good...... correspondence of the EFTs to global climate and also to land use classification. The results show the great potential of Earth Observation derived parameters for the quantification of ecosystem functional dynamics and for providing reference status information for future assessments of ecosystem changes....

  17. Toward a Global Classification of Coastal Anthromes

    Directory of Open Access Journals (Sweden)

    Eli D. Lazarus

    2017-02-01

    Full Text Available Given incontrovertible evidence that humans are the most powerful agents of environmental change on the planet, research has begun to acknowledge and integrate human presence and activity into updated descriptions of the world’s biomes as “anthromes”. Thus far, a classification system for anthromes is limited to the terrestrial biosphere. Here, I present a case for the consideration and validity of coastal anthromes. Every coastal environment on Earth is subject to direct and indirect human modification and disturbance. Despite the legacy, ubiquity, and pervasiveness of human interactions with coastal ecosystems, coastal anthromes still lack formal definition. Following the original argument and framework for terrestrial anthromes, I outline a set of coastal anthrome classifications that dovetail with terrestrial and marine counterparts. Recognising coastal environments as complex and increasingly vulnerable anthropogenic systems is a fundamental step toward understanding their modern dynamics—and, by extension, realising opportunities for and limits to their resilience.

  18. A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

    Directory of Open Access Journals (Sweden)

    Huai Yu

    2016-03-01

    Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

  19. Sagebrush Ecosystems Under Fire

    Energy Technology Data Exchange (ETDEWEB)

    Downs, Janelle L.

    2014-12-30

    Since settlement of the western United States began, sagebrush (Artemisia L. spp.) ecosystems have decreased both in quantity and quality. Originally encompassing up to 150 million acres in the West, the “interminable fields” of sage described by early explorers (Fremont 1845) have been degraded and often eliminated by conversion to agriculture, urbanization, livestock grazing, invasion by alien plants, and alteration of wildfire cycles (Hann et al. 1997; West 1999). More than half of the original sagebrush steppe ecosystems in Washington have been converted to agriculture and many of the remaining stands of sagebrush are degraded by invasion of exotic annuals such as cheatgrass (Bromus tectorum L.). Today, sagebrush ecosystems are considered to be one of the most imperiled in the United States (Noss, LeRoe and Scott 1995), and more than 350 sagebrush-associated plants and animals have been identified as species of conservation concern (Suring et al. 2005; Wisdom et al. 2005). The increasing frequency of wildfire in sagebrush-dominated landscapes is one of the greatest threats to these habitats and also presents one of the most difficult to control.

  20. Application of hierarchical matrices for partial inverse

    KAUST Repository

    Litvinenko, Alexander

    2013-11-26

    In this work we combine hierarchical matrix techniques (Hackbusch, 1999) and domain decomposition methods to obtain fast and efficient algorithms for the solution of multiscale problems. This combination results in the hierarchical domain decomposition (HDD) method, which can be applied for solution multi-scale problems. Multiscale problems are problems that require the use of different length scales. Using only the finest scale is very expensive, if not impossible, in computational time and memory. Domain decomposition methods decompose the complete problem into smaller systems of equations corresponding to boundary value problems in subdomains. Then fast solvers can be applied to each subdomain. Subproblems in subdomains are independent, much smaller and require less computational resources as the initial problem.

  1. First-passage phenomena in hierarchical networks

    CERN Document Server

    Tavani, Flavia

    2016-01-01

    In this paper we study Markov processes and related first passage problems on a class of weighted, modular graphs which generalize the Dyson hierarchical model. In these networks, the coupling strength between two nodes depends on their distance and is modulated by a parameter $\\sigma$. We find that, in the thermodynamic limit, ergodicity is lost and the "distant" nodes can not be reached. Moreover, for finite-sized systems, there exists a threshold value for $\\sigma$ such that, when $\\sigma$ is relatively large, the inhomogeneity of the coupling pattern prevails and "distant" nodes are hardly reached. The same analysis is carried on also for generic hierarchical graphs, where interactions are meant to involve $p$-plets ($p>2$) of nodes, finding that ergodicity is still broken in the thermodynamic limit, but no threshold value for $\\sigma$ is evidenced, ultimately due to a slow growth of the network diameter with the size.

  2. An Hierarchical Approach to Big Data

    CERN Document Server

    Allen, M G; Boch, T; Durand, D; Oberto, A; Merin, B; Stoehr, F; Genova, F; Pineau, F-X; Salgado, J

    2016-01-01

    The increasing volumes of astronomical data require practical methods for data exploration, access and visualisation. The Hierarchical Progressive Survey (HiPS) is a HEALPix based scheme that enables a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. We highlight the decisions and approaches that have been taken to make this scheme a practical solution for managing large volumes of heterogeneous data. Early implementors of this system have formed a network of HiPS nodes, with some 250 diverse data sets currently available, with multiple mirror implementations for important data sets. This hierarchical approach can be adapted to expose Big Data in different ways. We describe how the ease of implementation, and local customisation of the Aladin Lite embeddable HiPS visualiser have been keys for promoting collaboration on HiPS.

  3. Non-homogeneous fractal hierarchical weighted networks.

    Science.gov (United States)

    Dong, Yujuan; Dai, Meifeng; Ye, Dandan

    2015-01-01

    A model of fractal hierarchical structures that share the property of non-homogeneous weighted networks is introduced. These networks can be completely and analytically characterized in terms of the involved parameters, i.e., the size of the original graph Nk and the non-homogeneous weight scaling factors r1, r2, · · · rM. We also study the average weighted shortest path (AWSP), the average degree and the average node strength, taking place on the non-homogeneous hierarchical weighted networks. Moreover the AWSP is scrupulously calculated. We show that the AWSP depends on the number of copies and the sum of all non-homogeneous weight scaling factors in the infinite network order limit.

  4. Noise enhances information transfer in hierarchical networks.

    Science.gov (United States)

    Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

    2013-01-01

    We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

  5. Design of Hierarchical Structures for Synchronized Deformations

    Science.gov (United States)

    Seifi, Hamed; Javan, Anooshe Rezaee; Ghaedizadeh, Arash; Shen, Jianhu; Xu, Shanqing; Xie, Yi Min

    2017-01-01

    In this paper we propose a general method for creating a new type of hierarchical structures at any level in both 2D and 3D. A simple rule based on a rotate-and-mirror procedure is introduced to achieve multi-level hierarchies. These new hierarchical structures have remarkably few degrees of freedom compared to existing designs by other methods. More importantly, these structures exhibit synchronized motions during opening or closure, resulting in uniform and easily-controllable deformations. Furthermore, a simple analytical formula is found which can be used to avoid collision of units of the structure during the closing process. The novel design concept is verified by mathematical analyses, computational simulations and physical experiments.

  6. Hierarchical Self-organization of Complex Systems

    Institute of Scientific and Technical Information of China (English)

    CHAI Li-he; WEN Dong-sheng

    2004-01-01

    Researches on organization and structure in complex systems are academic and industrial fronts in modern sciences. Though many theories are tentatively proposed to analyze complex systems, we still lack a rigorous theory on them. Complex systems possess various degrees of freedom, which means that they should exhibit all kinds of structures. However, complex systems often show similar patterns and structures. Then the question arises why such similar structures appear in all kinds of complex systems. The paper outlines a theory on freedom degree compression and the existence of hierarchical self-organization for all complex systems is found. It is freedom degree compression and hierarchical self-organization that are responsible for the existence of these similar patterns or structures observed in the complex systems.

  7. Bayesian hierarchical modeling of drug stability data.

    Science.gov (United States)

    Chen, Jie; Zhong, Jinglin; Nie, Lei

    2008-06-15

    Stability data are commonly analyzed using linear fixed or random effect model. The linear fixed effect model does not take into account the batch-to-batch variation, whereas the random effect model may suffer from the unreliable shelf-life estimates due to small sample size. Moreover, both methods do not utilize any prior information that might have been available. In this article, we propose a Bayesian hierarchical approach to modeling drug stability data. Under this hierarchical structure, we first use Bayes factor to test the poolability of batches. Given the decision on poolability of batches, we then estimate the shelf-life that applies to all batches. The approach is illustrated with two example data sets and its performance is compared in simulation studies with that of the commonly used frequentist methods. (c) 2008 John Wiley & Sons, Ltd.

  8. Hierarchical Boltzmann simulations and model error estimation

    Science.gov (United States)

    Torrilhon, Manuel; Sarna, Neeraj

    2017-08-01

    A hierarchical simulation approach for Boltzmann's equation should provide a single numerical framework in which a coarse representation can be used to compute gas flows as accurately and efficiently as in computational fluid dynamics, but a subsequent refinement allows to successively improve the result to the complete Boltzmann result. We use Hermite discretization, or moment equations, for the steady linearized Boltzmann equation for a proof-of-concept of such a framework. All representations of the hierarchy are rotationally invariant and the numerical method is formulated on fully unstructured triangular and quadrilateral meshes using a implicit discontinuous Galerkin formulation. We demonstrate the performance of the numerical method on model problems which in particular highlights the relevance of stability of boundary conditions on curved domains. The hierarchical nature of the method allows also to provide model error estimates by comparing subsequent representations. We present various model errors for a flow through a curved channel with obstacles.

  9. Hierarchical State Machines as Modular Horn Clauses

    Directory of Open Access Journals (Sweden)

    Pierre-Loïc Garoche

    2016-07-01

    Full Text Available In model based development, embedded systems are modeled using a mix of dataflow formalism, that capture the flow of computation, and hierarchical state machines, that capture the modal behavior of the system. For safety analysis, existing approaches rely on a compilation scheme that transform the original model (dataflow and state machines into a pure dataflow formalism. Such compilation often result in loss of important structural information that capture the modal behaviour of the system. In previous work we have developed a compilation technique from a dataflow formalism into modular Horn clauses. In this paper, we present a novel technique that faithfully compile hierarchical state machines into modular Horn clauses. Our compilation technique preserves the structural and modal behavior of the system, making the safety analysis of such models more tractable.

  10. Hierarchical community structure in complex (social) networks

    CERN Document Server

    Massaro, Emanuele

    2014-01-01

    The investigation of community structure in networks is a task of great importance in many disciplines, namely physics, sociology, biology and computer science where systems are often represented as graphs. One of the challenges is to find local communities from a local viewpoint in a graph without global information in order to reproduce the subjective hierarchical vision for each vertex. In this paper we present the improvement of an information dynamics algorithm in which the label propagation of nodes is based on the Markovian flow of information in the network under cognitive-inspired constraints \\cite{Massaro2012}. In this framework we have introduced two more complex heuristics that allow the algorithm to detect the multi-resolution hierarchical community structure of networks from a source vertex or communities adopting fixed values of model's parameters. Experimental results show that the proposed methods are efficient and well-behaved in both real-world and synthetic networks.

  11. 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.

  12. Assembling hierarchical cluster solids with atomic precision.

    Science.gov (United States)

    Turkiewicz, Ari; Paley, Daniel W; Besara, Tiglet; Elbaz, Giselle; Pinkard, Andrew; Siegrist, Theo; Roy, Xavier

    2014-11-12

    Hierarchical solids created from the binary assembly of cobalt chalcogenide and iron oxide molecular clusters are reported. Six different molecular clusters based on the octahedral Co6E8 (E = Se or Te) and the expanded cubane Fe8O4 units are used as superatomic building blocks to construct these crystals. The formation of the solid is driven by the transfer of charge between complementary electron-donating and electron-accepting clusters in solution that crystallize as binary ionic compounds. The hierarchical structures are investigated by single-crystal X-ray diffraction, providing atomic and superatomic resolution. We report two different superstructures: a superatomic relative of the CsCl lattice type and an unusual packing arrangement based on the double-hexagonal close-packed lattice. Within these superstructures, we demonstrate various compositions and orientations of the clusters.

  13. Hierarchical Robot Control In A Multisensor Environment

    Science.gov (United States)

    Bhanu, Bir; Thune, Nils; Lee, Jih Kun; Thune, Mari

    1987-03-01

    Automatic recognition, inspection, manipulation and assembly of objects will be a common denominator in most of tomorrow's highly automated factories. These tasks will be handled by intelligent computer controlled robots with multisensor capabilities which contribute to desired flexibility and adaptability. The control of a robot in such a multisensor environment becomes of crucial importance as the complexity of the problem grows exponentially with the number of sensors, tasks, commands and objects. In this paper we present an approach which uses CAD (Computer-Aided Design) based geometric and functional models of objects together with action oriented neuroschemas to recognize and manipulate objects by a robot in a multisensor environment. The hierarchical robot control system is being implemented on a BBN Butterfly multi processor. Index terms: CAD, Hierarchical Control, Hypothesis Generation and Verification, Parallel Processing, Schemas

  14. Ecosystem Management. A Management View

    DEFF Research Database (Denmark)

    Ravn-Jonsen, Lars

    The need for management of the marine ecosystem using a broad perspective has been recommended under a variety of names. This paper uses the term Ecosystem Management, which is seen as a convergence between the ecological idea of an organisational hierarchy and the idea of strategic planning...... with a planning hierarchy---with the ecosystem being the strategic planning level. Management planning requires, in order to establish a quantifiable means and ends chain, that the goals at the ecosystem level can be linked to operational levels; ecosystem properties must therefore be reducible to lower...

  15. Concepts of Classification and Taxonomy. Phylogenetic Classification

    CERN Document Server

    Fraix-Burnet, Didier

    2016-01-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works. 1 Why phylogenetic tools in astrophysics? 1.1 History of classification The need for classifying living organisms is very ancient, and the first classification system can be dated back to the Greeks. The goal was very practical since it was intended to distinguish between eatable and toxic aliments, or kind and dangerous animals. Simple resemblance was used and has been used for centuries. Basically, until the XVIIIth...

  16. 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.

  17. Wholeness as a Hierarchical Graph to Capture the Nature of Space

    CERN Document Server

    Jiang, Bin

    2015-01-01

    According to Christopher Alexander's theory of centers, a whole comprises numerous, recursively defined centers for things or spaces surrounding us. Wholeness is a type of global structure or life-giving order emerging from the whole as a field of the centers. The wholeness is an essential part of any complex system and exists, to some degree or other, in spaces. This paper defines wholeness as a hierarchical graph, in which individual centers are represented as the nodes and their relationships as the directed links. The hierarchical graph gets its name from the inherent scaling hierarchy revealed by the head/tail breaks, which is a classification scheme and visualization tool for data with a heavy-tailed distribution. We suggest that (1) the degrees of wholeness for individual centers should be measured by PageRank (PR) scores based on the notion that high-degree-of-life centers are those to which many high-degree-of-life centers point, and (2) that the hierarchical levels, or the ht-index of the PR scores ...

  18. Building hierarchical models of avian distributions for the State of Georgia

    Science.gov (United States)

    Howell, J.E.; Peterson, J.T.; Conroy, M.J.

    2008-01-01

    To predict the distributions of breeding birds in the state of Georgia, USA, we built hierarchical models consisting of 4 levels of nested mapping units of decreasing area: 90,000 ha, 3,600 ha, 144 ha, and 5.76 ha. We used the Partners in Flight database of point counts to generate presence and absence data at locations across the state of Georgia for 9 avian species: Acadian flycatcher (Empidonax virescens), brownheaded nuthatch (Sitta pusilla), Carolina wren (Thryothorus ludovicianus), indigo bunting (Passerina cyanea), northern cardinal (Cardinalis cardinalis), prairie warbler (Dendroica discolor), yellow-billed cuckoo (Coccyxus americanus), white-eyed vireo (Vireo griseus), and wood thrush (Hylocichla mustelina). At each location, we estimated hierarchical-level-specific habitat measurements using the Georgia GAP Analysis18 class land cover and other Geographic Information System sources. We created candidate, species-specific occupancy models based on previously reported relationships, and fit these using Markov chain Monte Carlo procedures implemented in OpenBugs. We then created a confidence model set for each species based on Akaike's Information Criterion. We found hierarchical habitat relationships for all species. Three-fold cross-validation estimates of model accuracy indicated an average overall correct classification rate of 60.5%. Comparisons with existing Georgia GAP Analysis models indicated that our models were more accurate overall. Our results provide guidance to wildlife scientists and managers seeking predict avian occurrence as a function of local and landscape-level habitat attributes.

  19. 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.

  20. 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.

  1. The Infinite Hierarchical Factor Regression Model

    CERN Document Server

    Rai, Piyush

    2009-01-01

    We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.

  2. Superhydrophobicity of Hierarchical and ZNO Nanowire Coatings

    Science.gov (United States)

    2014-01-01

    KOH (3 wt%), distilled water and isopropyl alcohol (10% vol%) at 95 C for 50 min. Subsequently, a 10 nm ZnO seed layer wasThis journal is © The Royal...ZnO have been widely used in sensors, piezo-nanogenerators, and solar cells. The hierarchical structures of ZnO nanowires grown on Si pyramid surfaces...exhibiting superhydrophobicity in this work will have promising applications in the next generation photovoltaic devices and solar cells

  3. Hierarchical Parallel Evaluation of a Hamming Code

    Directory of Open Access Journals (Sweden)

    Shmuel T. Klein

    2017-04-01

    Full Text Available The Hamming code is a well-known error correction code and can correct a single error in an input vector of size n bits by adding logn parity checks. A new parallel implementation of the code is presented, using a hierarchical structure of n processors in logn layers. All the processors perform similar simple tasks, and need only a few bytes of internal memory.

  4. 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...

  5. Classification of LiDAR Data with Point Based Classification Methods

    Science.gov (United States)

    Yastikli, N.; Cetin, Z.

    2016-06-01

    LiDAR is one of the most effective systems for 3 dimensional (3D) data collection in wide areas. Nowadays, airborne LiDAR data is used frequently in various applications such as object extraction, 3D modelling, change detection and revision of maps with increasing point density and accuracy. The classification of the LiDAR points is the first step of LiDAR data processing chain and should be handled in proper way since the 3D city modelling, building extraction, DEM generation, etc. applications directly use the classified point clouds. The different classification methods can be seen in recent researches and most of researches work with the gridded LiDAR point cloud. In grid based data processing of the LiDAR data, the characteristic point loss in the LiDAR point cloud especially vegetation and buildings or losing height accuracy during the interpolation stage are inevitable. In this case, the possible solution is the use of the raw point cloud data for classification to avoid data and accuracy loss in gridding process. In this study, the point based classification possibilities of the LiDAR point cloud is investigated to obtain more accurate classes. The automatic point based approaches, which are based on hierarchical rules, have been proposed to achieve ground, building and vegetation classes using the raw LiDAR point cloud data. In proposed approaches, every single LiDAR point is analyzed according to their features such as height, multi-return, etc. then automatically assigned to the class which they belong to. The use of un-gridded point cloud in proposed point based classification process helped the determination of more realistic rule sets. The detailed parameter analyses have been performed to obtain the most appropriate parameters in the rule sets to achieve accurate classes. The hierarchical rule sets were created for proposed Approach 1 (using selected spatial-based and echo-based features) and Approach 2 (using only selected spatial-based features

  6. SCOR: Structural Classification of RNA, version 2.0.

    Science.gov (United States)

    Tamura, Makio; Hendrix, Donna K; Klosterman, Peter S; Schimmelman, Nancy R B; Brenner, Steven E; Holbrook, Stephen R

    2004-01-01

    SCOR, the Structural Classification of RNA (http://scor.lbl.gov), is a database designed to provide a comprehensive perspective and understanding of RNA motif three-dimensional structure, function, tertiary interactions and their relationships. SCOR 2.0 represents a major expansion and introduces a new classification organization. The new version represents the classification as a Directed Acyclic Graph (DAG), which allows a classification node to have multiple parents, in contrast to the strictly hierarchical classification used in SCOR 1.2. SCOR 2.0 supports three types of query terms in the updated search engine: PDB or NDB identifier, nucleotide sequence and keyword. We also provide parseable XML files for all information. This new release contains 511 RNA entries from the PDB as of 15 May 2003. A total of 5880 secondary structural elements are classified: 2104 hairpin loops and 3776 internal loops. RNA motifs reported in the literature, such as 'Kink turn' and 'GNRA loops', are now incorporated into the structural classification along with definitions and descriptions.

  7. SCOR: Structural classification of RNA, Version 2.0

    Energy Technology Data Exchange (ETDEWEB)

    Tamura, Makio; Hendrix, Donna K.; Klosterman, Peter

    2003-10-03

    SCOR (http://scor.lbl.gov), the Structural Classification of RNA, is a database designed to provide a comprehensive perspective and understanding of RNA motif three-dimensional structure, function, tertiary interactions, and their relationships. SCOR 2.0 represents a major expansion and introduces a wholly new classification system. The new version represents the classification as a Directed Acyclic Graph (DAG), which allows a classification node to have multiple parents, in contrast to the strictly hierarchical classification used in SCOR 1.2. SCOR 2.0 supports three types of query terms in the updated search engine: PDB or NDB identifier, nucleotide sequence, and keyword. We also provide parseable XML files for all information. This new release contains 511RNA entries from the PDB as of 15 May 2003. A total of 5,880 secondary structural elements are classified; 2,104 hairpin loops and 3,776 internal loops. RNA motifs reported in the literature, such as ''Kinkturn'' and ''GNRA loops,'' are now incorporated into the structural classification along with definitions and descriptions.

  8. Measuring spatial patterns in floodplains: A step towards understanding the complexity of floodplain ecosystems: Chapter 6

    Science.gov (United States)

    Murray Scown,; Martin Thoms,; DeJager, Nathan R.; Gilvear, David J.; Greenwood, Malcolm T.; Thoms, Martin C.; Wood, Paul J.

    2016-01-01

    natural and anthropogenic disturbances therefore require quantification of spatial pattern (Asselman and Middelkoop, 1995; Walling and He, 1998). Quantifying these patterns also provides insights into the spatial and temporal domains of structuring processes as well as enabling the detection of self-emergent phenomena, environmental constraints or anthropogenic interference (Turner et al., 1990; Holling, 1992; De Jager and Rohweder, 2012). Thus, quantifying spatial pattern is an important building block on which to examine floodplains as complex adaptive systems (Levin, 1998). Approaches to measuring spatial pattern in floodplains must be cognisant of scale, self-emergent phenomena, spatial organisation, and location. Fundamental problems may arise when patterns observed at a site or transect scale are scaled-up to infer processes and patterns over entire floodplain surfaces (Wiens, 2002; Thorp et al., 2008). Likewise, patterns observed over the entire spatial extent of a landscape can mask important variation and detail at finer scales (Riitters et al., 2002). Indeed, different patterns often emerge at different scales (Turner et al., 1990) because of hierarchical structuring processes (O'Neill et al., 1991). Categorising data into discrete, homogeneous and predefined spatial units at a particular scale (e.g. polygons) creates issues and errors associated with scale and subjective classification (McGarigal et al., 2009; Cushman et al., 2010). These include, loss of information within classified ‘patches’, as well as the ability to detect the emergence of new features that do not fit the original classification scheme. Many of these issues arise because floodplains are highly heterogeneous and have complex spatial organizations (Carbonneau et al., 2012; Legleiter, 2013). As a result, the scale and location at which measurements are made can influence the observed spatial patterns; and patterns may not be scale independent or applicable in different geomorp

  9. Metal hierarchical patterning by direct nanoimprint lithography.

    Science.gov (United States)

    Radha, Boya; Lim, Su Hui; Saifullah, Mohammad S M; Kulkarni, Giridhar U

    2013-01-01

    Three-dimensional hierarchical patterning of metals is of paramount importance in diverse fields involving photonics, controlling surface wettability and wearable electronics. Conventionally, this type of structuring is tedious and usually involves layer-by-layer lithographic patterning. Here, we describe a simple process of direct nanoimprint lithography using palladium benzylthiolate, a versatile metal-organic ink, which not only leads to the formation of hierarchical patterns but also is amenable to layer-by-layer stacking of the metal over large areas. The key to achieving such multi-faceted patterning is hysteretic melting of ink, enabling its shaping. It undergoes transformation to metallic palladium under gentle thermal conditions without affecting the integrity of the hierarchical patterns on micro- as well as nanoscale. A metallic rice leaf structure showing anisotropic wetting behavior and woodpile-like structures were thus fabricated. Furthermore, this method is extendable for transferring imprinted structures to a flexible substrate to make them robust enough to sustain numerous bending cycles.

  10. Hierarchical unilamellar vesicles of controlled compositional heterogeneity.

    Directory of Open Access Journals (Sweden)

    Maik Hadorn

    Full Text Available Eukaryotic life contains hierarchical vesicular architectures (i.e. organelles that are crucial for material production and trafficking, information storage and access, as well as energy production. In order to perform specific tasks, these compartments differ among each other in their membrane composition and their internal cargo and also differ from the cell membrane and the cytosol. Man-made structures that reproduce this nested architecture not only offer a deeper understanding of the functionalities and evolution of organelle-bearing eukaryotic life but also allow the engineering of novel biomimetic technologies. Here, we show the newly developed vesicle-in-water-in-oil emulsion transfer preparation technique to result in giant unilamellar vesicles internally compartmentalized by unilamellar vesicles of different membrane composition and internal cargo, i.e. hierarchical unilamellar vesicles of controlled compositional heterogeneity. The compartmentalized giant unilamellar vesicles were subsequently isolated by a separation step exploiting the heterogeneity of the membrane composition and the encapsulated cargo. Due to the controlled, efficient, and technically straightforward character of the new preparation technique, this study allows the hierarchical fabrication of compartmentalized giant unilamellar vesicles of controlled compositional heterogeneity and will ease the development of eukaryotic cell mimics that resemble their natural templates as well as the fabrication of novel multi-agent drug delivery systems for combination therapies and complex artificial microreactors.

  11. 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.

  12. A secure solution on hierarchical access control

    CERN Document Server

    Wei, Chuan-Sheng; Huang, Tone-Yau; Ong, Yao Lin

    2011-01-01

    Hierarchical access control is an important and traditional problem in information security. In 2001, Wu et.al. proposed an elegant solution for hierarchical access control by the secure-filter. Jeng and Wang presented an improvement of Wu et. al.'s method by the ECC cryptosystem. However, secure-filter method is insecure in dynaminc access control. Lie, Hsu and Tripathy, Paul pointed out some secure leaks on the secure-filter and presented some improvements to eliminate these secure flaws. In this paper, we revise the secure-filter in Jeng-Wang method and propose another secure solutions in hierarchical access control problem. CA is a super security class (user) in our proposed method and the secure-filter of $u_i$ in our solutions is a polynomial of degree $n_i+1$ in $\\mathbb{Z}_p^*$, $f_i(x)=(x-h_i)(x-a_1)...(x-a_{n_i})+L_{l_i}(K_i)$. Although the degree of our secure-filter is larger than others solutions, our solution is secure and efficient in dynamics access control.

  13. SORM applied to hierarchical parallel system

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager

    2006-01-01

    The old hierarchical stochastic load combination model of Ferry Borges and Castanheta and the corresponding problem of determining the distribution of the extreme random load effect is the inspiration to this paper. The evaluation of the distribution function of the extreme value by use of a part......The old hierarchical stochastic load combination model of Ferry Borges and Castanheta and the corresponding problem of determining the distribution of the extreme random load effect is the inspiration to this paper. The evaluation of the distribution function of the extreme value by use...... of a particular first order reliability method (FORM) was first described in a celebrated paper by Rackwitz and Fiessler more than a quarter of a century ago. The method has become known as the Rackwitz-Fiessler algorithm. The original RF-algorithm as applied to a hierarchical random variable model...... is recapitulated so that a simple but quite effective accuracy improving calculation can be explained. A limit state curvature correction factor on the probability approximation is obtained from the final stop results of the RF-algorithm. This correction factor is based on Breitung’s asymptotic formula for second...

  14. 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.

  15. 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.

  16. The Hourglass Effect in Hierarchical Dependency Networks

    CERN Document Server

    Sabrin, Kaeser M

    2016-01-01

    Many hierarchically modular systems are structured in a way that resembles a bow-tie or hourglass. This "hourglass effect" means that the system generates many outputs from many inputs through a relatively small number of intermediate modules that are critical for the operation of the entire system (the waist of the hourglass). We investigate the hourglass effect in general (not necessarily layered) hierarchical dependency networks. Our analysis focuses on the number of source-to-target dependency paths that traverse each vertex, and it identifies the core of a dependency network as the smallest set of vertices that collectively cover almost all dependency paths. We then examine if a given network exhibits the hourglass property or not, comparing its core size with a "flat" (i.e., non-hierarchical) network that preserves the source dependencies of each target in the original network. As a possible explanation for the hourglass effect, we propose the Reuse Preference (RP) model that captures the bias of new mo...

  17. Semantic Image Segmentation with Contextual Hierarchical Models.

    Science.gov (United States)

    Seyedhosseini, Mojtaba; Tasdizen, Tolga

    2016-05-01

    Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

  18. Ecosystem Management. A Management View

    DEFF Research Database (Denmark)

    Ravn-Jonsen, Lars

    The need for management of the marine ecosystem using a broad perspective has been recommended under a variety of names. This paper uses the term Ecosystem Management, which is seen as a convergence between the ecological idea of an organisational hierarchy and the idea of strategic planning...... with a planning hierarchy---with the ecosystem being the strategic planning level. Management planning requires, in order to establish a quantifiable means and ends chain, that the goals at the ecosystem level can be linked to operational levels; ecosystem properties must therefore be reducible to lower...... genetic relation. The population structure is below the ecosystem in terms of the planning level, and goals for the community's genetic structure cannot be meaningful defined without setting strategic goals at the ecosystem level for functional groups....

  19. Ecosystem-based management and the wealth of ecosystems.

    Science.gov (United States)

    Yun, Seong Do; Hutniczak, Barbara; Abbott, Joshua K; Fenichel, Eli P

    2017-06-20

    We merge inclusive wealth theory with ecosystem-based management (EBM) to address two challenges in the science of sustainable management of ecosystems. First, we generalize natural capital theory to approximate realized shadow prices for multiple interacting natural capital stocks (species) making up an ecosystem. These prices enable ecosystem components to be better included in wealth-based sustainability measures. We show that ecosystems are best envisioned as portfolios of assets, where the portfolio's performance depends on the performance of the underlying assets influenced by their interactions. Second, changes in ecosystem wealth provide an attractive headline index for EBM, regardless of whether ecosystem wealth is ultimately included in a broader wealth index. We apply our approach to the Baltic Sea ecosystem, focusing on the interacting community of three commercially important fish species: cod, herring, and sprat. Our results incorporate supporting services embodied in the shadow price of a species through its trophic interactions. Prey fish have greater shadow prices than expected based on market value, and predatory fish have lower shadow prices than expected based on market value. These results are because correctly measured shadow prices reflect interdependence and limits to substitution. We project that ecosystem wealth in the Baltic Sea fishery ecosystem generally increases conditional on the EBM-inspired multispecies maximum sustainable yield management beginning in 2017, whereas continuing the current single-species management generally results in declining wealth.

  20. Hierarchical reproductive allocation and allometry within a perennial bunchgrass after 11 years of nutrient addition.

    Science.gov (United States)

    Tian, Dashuan; Pan, Qingmin; Simmons, Matthew; Chaolu, Hada; Du, Baohong; Bai, Yongfei; Wang, Hong; Han, Xingguo

    2012-01-01

    Bunchgrasses are one of the most important plant functional groups in grassland ecosystems. Reproductive allocation (RA) for a bunchgrass is a hierarchical process; however, how bunchgrasses adjust their RAs along hierarchical levels in response to nutrient addition has never been addressed. Here, utilizing an 11-year nutrient addition experiment, we examined the patterns and variations in RA of Agropyron cristatum at the individual, tiller and spike levels. We evaluated the reproductive allometric relationship at each level by type II regression analysis to determine size-dependent and size-independent effects on plant RA variations. Our results indicate that the proportion of reproductive individuals in A. cristatum increased significantly after 11 years of nutrient addition. Adjustments in RA in A. cristatum were mainly occurred at the individual and tiller levels but not at the spike level. A size-dependent effect was a dominant mechanism underlying the changes in plant RA at both individual and tiller levels. Likewise, the distribution of plant size was markedly changed with large individuals increasing after nutrient addition. Tiller-level RA may be a limiting factor for the adjustment of RA in A. cristatum. To the best of our knowledge, this study is the first to examine plant responses in terms of reproductive allocation and allometry to nutrient enrichment within a bunchgrass population from a hierarchical view. Our findings have important implications for understanding the mechanisms underlying bunchgrass responses in RA to future eutrophication due to human activities. In addition, we developed a hierarchical analysis method for disentangling the mechanisms that lead to variation in RA for perennial bunchgrasses.

  1. Hierarchical reproductive allocation and allometry within a perennial bunchgrass after 11 years of nutrient addition.

    Directory of Open Access Journals (Sweden)

    Dashuan Tian

    Full Text Available Bunchgrasses are one of the most important plant functional groups in grassland ecosystems. Reproductive allocation (RA for a bunchgrass is a hierarchical process; however, how bunchgrasses adjust their RAs along hierarchical levels in response to nutrient addition has never been addressed. Here, utilizing an 11-year nutrient addition experiment, we examined the patterns and variations in RA of Agropyron cristatum at the individual, tiller and spike levels. We evaluated the reproductive allometric relationship at each level by type II regression analysis to determine size-dependent and size-independent effects on plant RA variations. Our results indicate that the proportion of reproductive individuals in A. cristatum increased significantly after 11 years of nutrient addition. Adjustments in RA in A. cristatum were mainly occurred at the individual and tiller levels but not at the spike level. A size-dependent effect was a dominant mechanism underlying the changes in plant RA at both individual and tiller levels. Likewise, the distribution of plant size was markedly changed with large individuals increasing after nutrient addition. Tiller-level RA may be a limiting factor for the adjustment of RA in A. cristatum. To the best of our knowledge, this study is the first to examine plant responses in terms of reproductive allocation and allometry to nutrient enrichment within a bunchgrass population from a hierarchical view. Our findings have important implications for understanding the mechanisms underlying bunchgrass responses in RA to future eutrophication due to human activities. In addition, we developed a hierarchical analysis method for disentangling the mechanisms that lead to variation in RA for perennial bunchgrasses.

  2. Obscuring ecosystem function with application of the ecosystem services concept.

    Science.gov (United States)

    Peterson, Markus J; Hall, Damon M; Feldpausch-Parker, Andrea M; Peterson, Tarla Rai

    2010-02-01

    Conservationists commonly have framed ecological concerns in economic terms to garner political support for conservation and to increase public interest in preserving global biodiversity. Beginning in the early 1980s, conservation biologists adapted neoliberal economics to reframe ecosystem functions and related biodiversity as ecosystem services to humanity. Despite the economic success of programs such as the Catskill/Delaware watershed management plan in the United States and the creation of global carbon exchanges, today's marketplace often fails to adequately protect biodiversity. We used a Marxist critique to explain one reason for this failure and to suggest a possible, if partial, response. Reframing ecosystem functions as economic services does not address the political problem of commodification. Just as it obscures the labor of human workers, commodification obscures the importance of the biota (ecosystem workers) and related abiotic factors that contribute to ecosystem functions. This erasure of work done by ecosystems impedes public understanding of biodiversity. Odum and Odum's radical suggestion to use the language of ecosystems (i.e., emergy or energy memory) to describe economies, rather than using the language of economics (i.e., services) to describe ecosystems, reverses this erasure of the ecosystem worker. Considering the current dominance of economic forces, however, implementing such solutions would require social changes similar in magnitude to those that occurred during the 1960s. Niklas Luhmann argues that such substantive, yet rapid, social change requires synergy among multiple societal function systems (i.e., economy, education, law, politics, religion, science), rather than reliance on a single social sphere, such as the economy. Explicitly presenting ecosystem services as discreet and incomplete aspects of ecosystem functions not only allows potential economic and environmental benefits associated with ecosystem services, but also

  3. INVENTORY OF IRRIGATED RICE ECOSYSTEM USING POLARIMETRIC SAR DATA

    Directory of Open Access Journals (Sweden)

    P. Srikanth

    2012-08-01

    Full Text Available An attempt has been made in the current study to assess the potential of polarimetric SAR data for inventory of kharif rice and the major competing crop like cotton. In the process, physical process of the scattering mechanisms occurring in rice and cotton crops at different phonological stages was studied through the use of temporal Radarsat 2 Fine quadpol SAR data. The temporal dynamics of the volume, double and odd bounce, entropy, anisotropy, alpha parameters and polarimertic signatures, classification through isodata clustering and Wishart techniques were assessed. The Wishart (H-a classification showed higher overall as well as rice and cotton crop accuracies compared to the isodata clustering from Freeman 3-component decomposition. The classification of temporal SAR data sets independently showed that the rice crop forecasting can be advanced with the use of appropriate single date polarimetric SAR data rather than using temporal SAR amplitude data sets with the single polarization in irrigated rice ecosystems

  4. Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

    Science.gov (United States)

    Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

    2014-09-30

    This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. SYSTEM ANALYSIS OF THE STRUCTURE OF CULTURAL ECOSYSTEM SERVICES ENERATION AND INTAKE USING ONE HUNDRED WAKA POEMS

    Science.gov (United States)

    Matsui, Takanori; Ikeno, Yuko

    It is needed to evaluate ecosystem services in order to make appropriate decision for ecosystem management. In this background the purpose of this study is to analyze structural processes of human enjoying culture-related ecosystem services. As a database including processes of enjoying cultural ecosystem services, "one hundred waka poems" was selected and coded from the context of symbiotic systems conce pts. To the dataset SOM (self organizational map) and agglomerative hierarchical clustering method, which were kinds of data mining method, were conducted. As the result, seven structures as design knowledge of cultural ecosystem services generation and in take, and for detail, (1) cultural ecosystem services are based on the visual contact to environmental objects, (2) there is a possibility of interaction between ecosystems, climate conditions, weather phenomena and activity modes of human system under the process of generating and taking cultural ecosystem services, and (3) it is possible that not only the presence of ecosystem but also products made of natural resources generate cultural ecosystem services.

  6. [Psychological classification of functional voice disorders].

    Science.gov (United States)

    Kiese-Himmel, C; Kruse, E

    1997-01-01

    In an explorative study the classification of a collective of patients with different voice disorders by discriminant and cluster analysis was tried. 21 variables, obtained from 128 patients with various diagnoses of voice disorders, were used. A first discriminant analysis on the basis of diagnoses-groups permitted no differentiation. A subsequent hierarchical cluster analysis indicated a four-cluster-solution. The clusters showed only little association with the phoniatric diagnoses. Cluster 1 is characterized by patients with non-organic voice disorders. Cluster 2 is marked by emotional unstable patients with organic dysphonia. Cluster 3 consists of patients with psychosomatic dysphonia by laryngeal contact granuloma, and cluster 4 contains emotional stable patients suffering from organic dysphonia and from spasmodic dysphonia. Thirteen psychological variables discriminated the clusters significantly: Anxiety about appearing in public, emotionality (neuroticism), life satisfaction, aggressiveness, anxiety, about physical injuries, extraversion.

  7. Nonparametric Transient Classification using Adaptive Wavelets

    CERN Document Server

    Varughese, Melvin M; Stephanou, Michael; Bassett, Bruce A

    2015-01-01

    Classifying transients based on multi band light curves is a challenging but crucial problem in the era of GAIA and LSST since the sheer volume of transients will make spectroscopic classification unfeasible. Here we present a nonparametric classifier that uses the transient's light curve measurements to predict its class given training data. It implements two novel components: the first is the use of the BAGIDIS wavelet methodology - a characterization of functional data using hierarchical wavelet coefficients. The second novelty is the introduction of a ranked probability classifier on the wavelet coefficients that handles both the heteroscedasticity of the data in addition to the potential non-representativity of the training set. The ranked classifier is simple and quick to implement while a major advantage of the BAGIDIS wavelets is that they are translation invariant, hence they do not need the light curves to be aligned to extract features. Further, BAGIDIS is nonparametric so it can be used for blind ...

  8. Segregation of vowels and consonants in human auditory cortex: Evidence for distributed hierarchical organization

    Directory of Open Access Journals (Sweden)

    Jonas eObleser

    2010-12-01

    Full Text Available The speech signal consists of a continuous stream of consonants and vowels, which must be de– and encoded in human auditory cortex to ensure the robust recognition and categorization of speech sounds. We used small-voxel functional magnetic resonance imaging (fMRI to study information encoded in local brain activation patterns elicited by consonant-vowel syllables, and by a control set of noise bursts.First, activation of anterior–lateral superior temporal cortex was seen when controlling for unspecific acoustic processing (syllables versus band-passed noises, in a classic subtraction-based design. Second, a classifier algorithm, which was trained and tested iteratively on data from all subjects to discriminate local brain activation patterns, yielded separations of cortical patches discriminative of vowel category versus patches discriminative of stop-consonant category across the entire superior temporal cortex, yet with regional differences in average classification accuracy. Overlap (voxels correctly classifying both speech sound categories was surprisingly sparse. Third, lending further plausibility to the results, classification of speech–noise differences was generally superior to speech–speech classifications, with the notable exception of a left anterior region, where speech–speech classification accuracies were significantly better.These data demonstrate that acoustic-phonetic features are encoded in complex yet sparsely overlapping local patterns of neural activity distributed hierarchically across different regions of the auditory cortex. The redundancy apparent in these multiple patterns may partly explain the robustness of phonemic representations.

  9. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  10. Multiple sparse representations classification

    NARCIS (Netherlands)

    E. Plenge (Esben); S.K. Klein (Stefan); W.J. Niessen (Wiro); E. Meijering (Erik)

    2015-01-01

    textabstractSparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In t

  11. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  12. Classifier in Age classification

    Directory of Open Access Journals (Sweden)

    B. Santhi

    2012-12-01

    Full Text Available Face is the important feature of the human beings. We can derive various properties of a human by analyzing the face. The objective of the study is to design a classifier for age using facial images. Age classification is essential in many applications like crime detection, employment and face detection. The proposed algorithm contains four phases: preprocessing, feature extraction, feature selection and classification. The classification employs two class labels namely child and Old. This study addresses the limitations in the existing classifiers, as it uses the Grey Level Co-occurrence Matrix (GLCM for feature extraction and Support Vector Machine (SVM for classification. This improves the accuracy of the classification as it outperforms the existing methods.

  13. LOCAL WEATHER CLASSIFICATIONS FOR ENVIRONMENTAL APPLICATIONS

    Directory of Open Access Journals (Sweden)

    Katarzyna PIOTROWICZ

    2013-03-01

    Full Text Available Two approaches of local weather type definitions are presented and illustrated for selected stations of Poland and Hungary. The subjective classification, continuing long traditions, especially in Poland, relies on diurnal values of local weather elements. The main types are defined according to temperature with some sub-types considering relative sunshine duration, diurnal precipitation totals, relative humidity and wind speed. The classification does not make a difference between the seasons of the year, but the occurrence of the classes obviously reflects the annual cycle. Another important feature of this classification is that only a minor part of the theoretically possible combination of the various types and sub-types occurs in all stations of both countries. The objective version of the classification starts from ten possible weather element which are reduced to four according to factor analysis, based on strong correlation between the elements. This analysis yields 3 to 4 factors depending on the specific criteria of selection. The further cluster analysis uses four selected weather elements belonging to different rotated factors. They are the diurnal mean values of temperature, of relative humidity, of cloudiness and of wind speed. From the possible ways of hierarchical cluster analysis (i.e. no a priori assumption on the number of classes, the method of furthest neighbours is selected, indicating the arguments of this decision in the paper. These local weather types are important tools in understanding the role of weather in various environmental indicators, in climatic generalisation of short samples by stratified sampling and in interpretation of the climate change.

  14. [Management of large marine ecosystem based on ecosystem approach].

    Science.gov (United States)

    Chu, Jian-song

    2011-09-01

    Large marine ecosystem (LME) is a large area of ocean characterized by distinct oceanology and ecology. Its natural characteristics require management based on ecosystem approach. A series of international treaties and regulations definitely or indirectly support that it should adopt ecosystem approach to manage LME to achieve the sustainable utilization of marine resources. In practices, some countries such as Canada, Australia, and U.S.A. have adopted ecosystem-based approach to manage their oceans, and some international organizations such as global environment fund committee have carried out a number of LME programs based on ecosystem approach. Aiming at the sustainable development of their fisheries, the regional organizations such as Caribbean Community have established regional fisheries mechanism. However, the adoption of ecosystem approach to manage LME is not only a scientific and legal issue, but also a political matter largely depending on the political will and the mutual cooperation degree of related countries.

  15. Loss Function Based Ranking in Two-Stage, Hierarchical Models

    Science.gov (United States)

    Lin, Rongheng; Louis, Thomas A.; Paddock, Susan M.; Ridgeway, Greg

    2009-01-01

    Performance evaluations of health services providers burgeons. Similarly, analyzing spatially related health information, ranking teachers and schools, and identification of differentially expressed genes are increasing in prevalence and importance. Goals include valid and efficient ranking of units for profiling and league tables, identification of excellent and poor performers, the most differentially expressed genes, and determining “exceedances” (how many and which unit-specific true parameters exceed a threshold). These data and inferential goals require a hierarchical, Bayesian model that accounts for nesting relations and identifies both population values and random effects for unit-specific parameters. Furthermore, the Bayesian approach coupled with optimizing a loss function provides a framework for computing non-standard inferences such as ranks and histograms. Estimated ranks that minimize Squared Error Loss (SEL) between the true and estimated ranks have been investigated. The posterior mean ranks minimize SEL and are “general purpose,” relevant to a broad spectrum of ranking goals. However, other loss functions and optimizing ranks that are tuned to application-specific goals require identification and evaluation. For example, when the goal is to identify the relatively good (e.g., in the upper 10%) or relatively poor performers, a loss function that penalizes classification errors produces estimates that minimize the error rate. We construct loss functions that address this and other goals, developing a unified framework that facilitates generating candidate estimates, comparing approaches and producing data analytic performance summaries. We compare performance for a fully parametric, hierarchical model with Gaussian sampling distribution under Gaussian and a mixture of Gaussians prior distributions. We illustrate approaches via analysis of standardized mortality ratio data from the United States Renal Data System. Results show that SEL

  16. Technology ecosystems and digital business ecosystems for business

    OpenAIRE

    Marjamaa-Mankinen, L. (Liisa)

    2016-01-01

    The purpose of this study was to find out the progress in the research of technology ecosystems and digital business ecosystems and to combine that information for business purposes by the utilization of information about business ecosystems. The need for this information emerged at the Department of Information Processing Science in the context of European Union research projects. The information gained is expected to assist to increase possibilities both for the research and for the persona...

  17. Sustainable web ecosystem design

    CERN Document Server

    O'Toole, Greg

    2013-01-01

    This book is about the process of creating web-based systems (i.e., websites, content, etc.) that consider each of the parts, the modules, the organisms - binary or otherwise - that make up a balanced, sustainable web ecosystem. In the current media-rich environment, a website is more than a collection of relative html documents of text and images on a static desktop computer monitor. There is now an unlimited combination of screens, devices, platforms, browsers, locations, versions, users, and exabytes of data with which to interact. Written in a highly approachable, practical style, this boo

  18. Kappa Coefficients for Circular Classifications

    NARCIS (Netherlands)

    Warrens, Matthijs J.; Pratiwi, Bunga C.

    2016-01-01

    Circular classifications are classification scales with categories that exhibit a certain periodicity. Since linear scales have endpoints, the standard weighted kappas used for linear scales are not appropriate for analyzing agreement between two circular classifications. A family of kappa coefficie

  19. Classification and Identification of Over-voltage Based on HHT and SVM

    Institute of Scientific and Technical Information of China (English)

    WANG Jing; YANG Qing; CHEN Lin; SIMA Wenxia

    2012-01-01

    This paper proposes an effective method for over-voltage classification based on the Hilbert-Huang transform(HHT) method.Hilbert-Huang transform method is composed of empirical mode decomposition(EMD) and Hilbert transform.Nine kinds of common power system over-voltages are calculated and analyzed by HHT.Based on the instantaneous amplitude spectrum,Hilbert marginal spectrum and Hilbert time-frequency spectrum,three kinds of over-voltage characteristic quantities are obtained.A hierarchical classification system is built based on HHT and support vector machine(SVM).This classification system is tested by 106 field over-voltage signals,and the average classification rate is 94.3%.This research shows that HHT is an effective time-frequency analysis algorithms in the application of over-voltage classification and identification.

  20. SCOWLP classification: Structural comparison and analysis of protein binding regions

    Directory of Open Access Journals (Sweden)

    Anders Gerd

    2008-01-01

    Full Text Available Abstract Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions