Sample records for tree based method

  1. EEG feature selection method based on decision tree. (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun


    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  2. Column density estimation: Tree-based method implementation (United States)

    Valdivia, Valeska


    The radiative transfer plays a crucial role in several astrophysical processes. In particular for the star formation problem it is well established that stars form in the densest and coolest regions in molecular clouds then understanding the interstellar cycle becomes crucial. The physics of dense gas requires the knowledge of the UV radiation that regulates the physics and the chemistry within the molecular cloud. The numerical modelization needs the calculation of column densities in any direction for each resolution element. In numerical simulations the cost of solving the radiative transfer problem is of the order of N^5/3, where N is the number of resolution elements. The exact calculation is in general extremely expensive in terms of CPU time for relatively large simulations and impractical in parallel computing. We present our tree-based method for estimating column densities and the attenuation factor for the UV field. The method is inspired by the fact that any distant cell subtends a small angle and therefore its contribution to the screening will be diluted. This method is suitable for parallel computing and no communication is needed between different CPUs. It has been implemented into the RAMSES code, a grid-based solver with adaptive mesh refinement (AMR). We present the results of two tests and a discussion on the accuracy and the performance of this method. We show that the UV screening affects mainly the dense parts of molecular clouds, changing locally the Jeans mass and therefore affecting the fragmentation.

  3. A tree-based method of analysis for prospective studies. (United States)

    Zhang, H; Holford, T; Bracken, M B


    Prospective studies often involve rare events as study outcomes, and a primary concern is to identify risk factors and risk groups associated with the outcomes. We discuss practical solutions to risk factor analyses in prospective studies and address strategies to determine tree structures, to estimate relative risks, and to manage missing data in connection with some important epidemiologic problems. Some of the basic ideas for our strategies follow from work of Breiman, Friedman, Olshen, and Stone, although we propose extensions to their methods to resolve some practical problems that arise in implementation of these methods in epidemiologic studies. To illustrate these ideas, we analyse low birthweight associated risk factors with use of a data set from the Yale Pregnancy Outcome Study.

  4. Study on reliability analysis based on multilevel flow models and fault tree method

    International Nuclear Information System (INIS)

    Chen Qiang; Yang Ming


    Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)

  5. Integer programming-based method for grammar-based tree compression and its application to pattern extraction of glycan tree structures. (United States)

    Zhao, Yang; Hayashida, Morihiro; Akutsu, Tatsuya


    A bisection-type algorithm for the grammar-based compression of tree-structured data has been proposed recently. In this framework, an elementary ordered-tree grammar (EOTG) and an elementary unordered-tree grammar (EUTG) were defined, and an approximation algorithm was proposed. In this paper, we propose an integer programming-based method that finds the minimum context-free grammar (CFG) for a given string under the condition that at most two symbols appear on the right-hand side of each production rule. Next, we extend this method to find the minimum EOTG and EUTG grammars for given ordered and unordered trees, respectively. Then, we conduct computational experiments for the ordered and unordered artificial trees. Finally, we apply our methods to pattern extraction of glycan tree structures. We propose integer programming-based methods that find the minimum CFG, EOTG, and EUTG for given strings, ordered and unordered trees. Our proposed methods for trees are useful for extracting patterns of glycan tree structures.

  6. Family-Joining: A Fast Distance-Based Method for Constructing Generally Labeled Trees. (United States)

    Kalaghatgi, Prabhav; Pfeifer, Nico; Lengauer, Thomas


    The widely used model for evolutionary relationships is a bifurcating tree with all taxa/observations placed at the leaves. This is not appropriate if the taxa have been densely sampled across evolutionary time and may be in a direct ancestral relationship, or if there is not enough information to fully resolve all the branching points in the evolutionary tree. In this article, we present a fast distance-based agglomeration method called family-joining (FJ) for constructing so-called generally labeled trees in which taxa may be placed at internal vertices and the tree may contain polytomies. FJ constructs such trees on the basis of pairwise distances and a distance threshold. We tested three methods for threshold selection, FJ-AIC, FJ-BIC, and FJ-CV, which minimize Akaike information criterion, Bayesian information criterion, and cross-validation error, respectively. When compared with related methods on simulated data, FJ-BIC was among the best at reconstructing the correct tree across a wide range of simulation scenarios. FJ-BIC was applied to HIV sequences sampled from individuals involved in a known transmission chain. The FJ-BIC tree was found to be compatible with almost all transmission events. On average, internal branches in the FJ-BIC tree have higher bootstrap support than branches in the leaf-labeled bifurcating tree constructed using RAxML. 36% and 25% of the internal branches in the FJ-BIC tree and RAxML tree, respectively, have bootstrap support greater than 70%. To the best of our knowledge the method presented here is the first attempt at modeling evolutionary relationships using generally labeled trees. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  7. [Automatic classification method of star spectrum data based on classification pattern tree]. (United States)

    Zhao, Xu-Jun; Cai, Jiang-Hui; Zhang, Ji-Fu; Yang, Hai-Feng; Ma, Yang


    Frequent pattern, frequently appearing in the data set, plays an important role in data mining. For the stellar spectrum classification tasks, a classification rule mining method based on classification pattern tree is presented on the basis of frequent pattern. The procedures can be shown as follows. Firstly, a new tree structure, i. e., classification pattern tree, is introduced based on the different frequencies of stellar spectral attributes in data base and its different importance used for classification. The related concepts and the construction method of classification pattern tree are also described in this paper. Then, the characteristics of the stellar spectrum are mapped to the classification pattern tree. Two modes of top-to-down and bottom-to-up are used to traverse the classification pattern tree and extract the classification rules. Meanwhile, the concept of pattern capability is introduced to adjust the number of classification rules and improve the construction efficiency of the classification pattern tree. Finally, the SDSS (the Sloan Digital Sky Survey) stellar spectral data provided by the National Astronomical Observatory are used to verify the accuracy of the method. The results show that a higher classification accuracy has been got.

  8. Determining Accuracy of Thermal Dissipation Methods-based Sap Flux in Japanese Cedar Trees (United States)

    Su, Man-Ping; Shinohara, Yoshinori; Laplace, Sophie; Lin, Song-Jin; Kume, Tomonori


    Thermal dissipation method, one kind of sap flux measurement method that can estimate individual tree transpiration, have been widely used because of its low cost and uncomplicated operation. Although thermal dissipation method is widespread, the accuracy of this method is doubted recently because some tree species materials in previous studies were not suitable for its empirical formula from Granier due to difference of wood characteristics. In Taiwan, Cryptomeria japonica (Japanese cedar) is one of the dominant species in mountainous area, quantifying the transpiration of Japanese cedar trees is indispensable to understand water cycling there. However, no one have tested the accuracy of thermal dissipation methods-based sap flux for Japanese cedar trees in Taiwan. Thus, in this study we conducted calibration experiment using twelve Japanese cedar stem segments from six trees to investigate the accuracy of thermal dissipation methods-based sap flux in Japanese cedar trees in Taiwan. By pumping water from segment bottom to top and inserting probes into segments to collect data simultaneously, we compared sap flux densities calculated from real water uptakes (Fd_actual) and empirical formula (Fd_Granier). Exact sapwood area and sapwood depth of each sample were obtained from dying segment with safranin stain solution. Our results showed that Fd_Granier underestimated 39 % of Fd_actual across sap flux densities ranging from 10 to 150 (cm3m-2s-1); while applying sapwood depth corrected formula from Clearwater, Fd_Granier became accurately that only underestimated 0.01 % of Fd_actual. However, when sap flux densities ranging from 10 to 50 (cm3m-2s-1)which is similar with the field data of Japanese cedar trees in a mountainous area of Taiwan, Fd_Granier underestimated 51 % of Fd_actual, and underestimated 26 % with applying Clearwater sapwood depth corrected formula. These results suggested sapwood depth significantly impacted on the accuracy of thermal dissipation

  9. A tree based method for the rapid screening of chemical fingerprints

    DEFF Research Database (Denmark)

    Kristensen, Thomas Greve; Nielsen, Jesper; Pedersen, Christian Nørgaard Storm


    The fingerprint of a molecule is a bitstring based on its structure, constructed such that structurally similar molecules will have similar fingerprints. Molecular fingerprints can be used in an initial phase for identifying novel drug candidates by screening large databases for molecules...... with fingerprints similar to a query fingerprint. In this paper, we present a method which efficiently finds all fingerprints in a database with Tanimoto coefficient to the query fingerprint above a user defined threshold. The method is based on two novel data structures for rapid screening of large databases......: the kD grid and the Multibit tree. The kD grid is based on splitting the fingerprints into k shorter bitstrings and utilising these to compute bounds on the similarity of the complete bitstrings. The Multibit tree uses hierarchical clustering and similarity within each cluster to compute similar bounds...

  10. Orange Recognition on Tree Using Image Processing Method Based on Lighting Density Pattern

    Directory of Open Access Journals (Sweden)

    H. R Ahmadi


    Full Text Available Within the last few years, a new tendency has been created towards robotic harvesting of oranges and some of citrus fruits. The first step in robotic harvesting is accurate recognition and positioning of fruits. Detection through image processing by color cameras and computer is currently the most common method. Obviously, a harvesting robot faces with natural conditions and, therefore, detection must be done in various light conditions and environments. In this study, it was attempted to provide a suitable algorithm for recognizing the orange fruits on tree. In order to evaluate the proposed algorithm, 500 images were taken in different conditions of canopy, lighting and the distance to the tree. The algorithm included sub-routines for optimization, segmentation, size filtering, separation of fruits based on lighting density method and coordinates determination. In this study, MLP neural network (with 3 hidden layers was used for segmentation that was found to be successful with an accuracy of 88.2% in correct detection. As there exist a high percentage of the clustered oranges in images, any algorithm aiming to detect oranges on the trees successfully should offer a solution to separate these oranges first. A new method based on the light and shade density method was applied and evaluated in this research. Finally, the accuracies for differentiation and recognition were obtained to be 89.5% and 88.2%, respectively.

  11. Inferring regulatory networks from expression data using tree-based methods.

    Directory of Open Access Journals (Sweden)

    Vân Anh Huynh-Thu


    Full Text Available One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs using high throughput genomic data, in particular microarray gene expression data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge aims to evaluate the success of GRN inference algorithms on benchmarks of simulated data. In this article, we present GENIE3, a new algorithm for the inference of GRNs that was best performer in the DREAM4 In Silico Multifactorial challenge. GENIE3 decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene is predicted from the expression patterns of all the other genes (input genes, using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link. Putative regulatory links are then aggregated over all genes to provide a ranking of interactions from which the whole network is reconstructed. In addition to performing well on the DREAM4 In Silico Multifactorial challenge simulated data, we show that GENIE3 compares favorably with existing algorithms to decipher the genetic regulatory network of Escherichia coli. It doesn't make any assumption about the nature of gene regulation, can deal with combinatorial and non-linear interactions, produces directed GRNs, and is fast and scalable. In conclusion, we propose a new algorithm for GRN inference that performs well on both synthetic and real gene expression data. The algorithm, based on feature selection with tree-based ensemble methods, is simple and generic, making it adaptable to other types of genomic data and interactions.

  12. Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients. (United States)

    Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat


    Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

  13. Tree Biomass Estimation of Chinese fir (Cunninghamia lanceolata) Based on Bayesian Method (United States)

    Zhang, Jianguo


    Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass. PMID:24278198

  14. Tree biomass estimation of Chinese fir (Cunninghamia lanceolata based on Bayesian method.

    Directory of Open Access Journals (Sweden)

    Xiongqing Zhang

    Full Text Available Chinese fir (Cunninghamia lanceolata (Lamb. Hook. is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation W = a(D2Hb was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass.

  15. Investigation on electrical tree propagation in polyethylene based on etching method

    Directory of Open Access Journals (Sweden)

    Zexiang Shi


    Full Text Available To investigate the characteristic of electrical tree propagation in semi-crystalline polymers, the low-density polyethylene (LDPE samples containing electrical trees are cut into slices by using ultramicrotome. Then the slice samples are etched by potassium permanganate etchant. Finally, the crystalline structure and the electrical tree propagation path in samples are observed by polarized light microscopy (PLM. According to the observation, the LDPE spherocrystal structure model is established on the basis of crystallization kinetics and morphology of polymers. And the electrical tree growth process in LDPE is discussed based on the free volume breakdown theory, the molecular chain relaxation theory, the electromechanical force theory, the thermal expansion effect and the space charge shielding effect.


    Directory of Open Access Journals (Sweden)

    J. Zhang


    Full Text Available Tree detection and reconstruction is of great interest in large-scale city modelling. In this paper, we present a marked point process model to detect single trees from airborne laser scanning (ALS data. We consider single trees in ALS recovered canopy height model (CHM as a realization of point process of circles. Unlike traditional marked point process, we sample the model in a constraint configuration space by making use of image process techniques. A Gibbs energy is defined on the model, containing a data term which judge the fitness of the model with respect to the data, and prior term which incorporate the prior knowledge of object layouts. We search the optimal configuration through a steepest gradient descent algorithm. The presented hybrid framework was test on three forest plots and experiments show the effectiveness of the proposed method.

  17. A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space

    Directory of Open Access Journals (Sweden)

    Lothar Eysn


    Full Text Available In this study, eight airborne laser scanning (ALS-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.

  18. A tree-based method to price American options in the Heston model

    NARCIS (Netherlands)

    Vellekoop, M.; Nieuwenhuis, H.


    We develop an algorithm to price American options on assets that follow the stochastic volatility model defined by Heston. We use an approach which is based on a modification of a combined tree for stock prices and volatilities, where the number of nodes grows quadratically in the number of time

  19. Methods for estimating population density in data-limited areas: evaluating regression and tree-based models in Peru. (United States)

    Anderson, Weston; Guikema, Seth; Zaitchik, Ben; Pan, William


    Obtaining accurate small area estimates of population is essential for policy and health planning but is often difficult in countries with limited data. In lieu of available population data, small area estimate models draw information from previous time periods or from similar areas. This study focuses on model-based methods for estimating population when no direct samples are available in the area of interest. To explore the efficacy of tree-based models for estimating population density, we compare six different model structures including Random Forest and Bayesian Additive Regression Trees. Results demonstrate that without information from prior time periods, non-parametric tree-based models produced more accurate predictions than did conventional regression methods. Improving estimates of population density in non-sampled areas is important for regions with incomplete census data and has implications for economic, health and development policies.

  20. Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone

    Directory of Open Access Journals (Sweden)

    Kusworo Adi


    Full Text Available Beef is one of the animal food products that have high nutrition because it contains carbohydrates, proteins, fats, vitamins, and minerals. Therefore, the quality of beef should be maintained so that consumers get good beef quality. Determination of beef quality is commonly conducted visually by comparing the actual beef and reference pictures of each beef class. This process presents weaknesses, as it is subjective in nature and takes a considerable amount of time. Therefore, an automated system based on image processing that is capable of determining beef quality is required. This research aims to develop an image segmentation method by processing digital images. The system designed consists of image acquisition processes with varied distance, resolution, and angle. Image segmentation is done to separate the images of fat and meat using the Otsu thresholding method. Classification was carried out using the decision tree algorithm and the best accuracies were obtained at 90% for training and 84% for testing. Once developed, this system is then embedded into the android programming. Results show that the image processing technique is capable of proper marbling score identification.

  1. Stochastic Unit Commitment Based on Multi-Scenario Tree Method Considering Uncertainty

    Directory of Open Access Journals (Sweden)

    Kyu-Hyung Jo


    Full Text Available With the increasing penetration of renewable energy, it is difficult to schedule unit commitment (UC in a power system because of the uncertainty associated with various factors. In this paper, a new solution procedure based on a multi-scenario tree method (MSTM is presented and applied to the proposed stochastic UC problem. In this process, the initial input data of load and wind power are modeled as different levels using the mean absolute percentage error (MAPE. The load and wind scenarios are generated using Monte Carlo simulation (MCS that considers forecasting errors. These multiple scenarios are applied in the MSTM for solving the stochastic UC problem, including not only the load and wind power uncertainties, but also sudden outages of the thermal unit. When the UC problem has been formulated, the simulation is conducted for 24-h period by using the short-term UC model, and the operating costs and additional reserve requirements are thus obtained. The effectiveness of the proposed solution approach is demonstrated through a case study based on a modified IEEE-118 bus test system.

  2. A Hybrid Key Management Scheme for WSNs Based on PPBR and a Tree-Based Path Key Establishment Method. (United States)

    Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei


    With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes.

  3. A decision treebased method for the differential diagnosis of Aortic Stenosis from Mitral Regurgitation using heart sounds

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    Loukis Euripides N


    Full Text Available Abstract Background New technologies like echocardiography, color Doppler, CT, and MRI provide more direct and accurate evidence of heart disease than heart auscultation. However, these modalities are costly, large in size and operationally complex and therefore are not suitable for use in rural areas, in homecare and generally in primary healthcare set-ups. Furthermore the majority of internal medicine and cardiology training programs underestimate the value of cardiac auscultation and junior clinicians are not adequately trained in this field. Therefore efficient decision support systems would be very useful for supporting clinicians to make better heart sound diagnosis. In this study a rule-based method, based on decision trees, has been developed for differential diagnosis between "clear" Aortic Stenosis (AS and "clear" Mitral Regurgitation (MR using heart sounds. Methods For the purposes of our experiment we used a collection of 84 heart sound signals including 41 heart sound signals with "clear" AS systolic murmur and 43 with "clear" MR systolic murmur. Signals were initially preprocessed to detect 1st and 2nd heart sounds. Next a total of 100 features were determined for every heart sound signal and relevance to the differentiation between AS and MR was estimated. The performance of fully expanded decision tree classifiers and Pruned decision tree classifiers were studied based on various training and test datasets. Similarly, pruned decision tree classifiers were used to examine their differentiation capabilities. In order to build a generalized decision support system for heart sound diagnosis, we have divided the problem into sub problems, dealing with either one morphological characteristic of the heart-sound waveform or with difficult to distinguish cases. Results Relevance analysis on the different heart sound features demonstrated that the most relevant features are the frequency features and the morphological features that

  4. Estimating Surface Downward Shortwave Radiation over China Based on the Gradient Boosting Decision Tree Method

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    Lu Yang


    Full Text Available Downward shortwave radiation (DSR is an essential parameter in the terrestrial radiation budget and a necessary input for models of land-surface processes. Although several radiation products using satellite observations have been released, coarse spatial resolution and low accuracy limited their application. It is important to develop robust and accurate retrieval methods with higher spatial resolution. Machine learning methods may be powerful candidates for estimating the DSR from remotely sensed data because of their ability to perform adaptive, nonlinear data fitting. In this study, the gradient boosting regression tree (GBRT was employed to retrieve DSR measurements with the ground observation data in China collected from the China Meteorological Administration (CMA Meteorological Information Center and the satellite observations from the Advanced Very High Resolution Radiometer (AVHRR at a spatial resolution of 5 km. The validation results of the DSR estimates based on the GBRT method in China at a daily time scale for clear sky conditions show an R2 value of 0.82 and a root mean square error (RMSE value of 27.71 W·m−2 (38.38%. These values are 0.64 and 42.97 W·m−2 (34.57%, respectively, for cloudy sky conditions. The monthly DSR estimates were also evaluated using ground measurements. The monthly DSR estimates have an overall R2 value of 0.92 and an RMSE of 15.40 W·m−2 (12.93%. Comparison of the DSR estimates with the reanalyzed and retrieved DSR measurements from satellite observations showed that the estimated DSR is reasonably accurate but has a higher spatial resolution. Moreover, the proposed GBRT method has good scalability and is easy to apply to other parameter inversion problems by changing the parameters and training data.

  5. Method of reliability allocation based on fault tree analysis and fuzzy math in nuclear power plants

    International Nuclear Information System (INIS)

    Chen Zhaobing; Deng Jian; Cao Xuewu


    Reliability allocation is a kind of a difficult multi-objective optimization problem. It can not only be applied to determine the reliability characteristic of reactor systems, subsystem and main components but also be performed to improve the design, operation and maintenance of nuclear plants. The fuzzy math known as one of the powerful tools for fuzzy optimization and the fault analysis deemed to be one of the effective methods of reliability analysis can be applied to the reliability allocation model so as to work out the problems of fuzzy characteristic of some factors and subsystem's choice respectively in this paper. Thus we develop a failure rate allocation model on the basis of the fault tree analysis and fuzzy math. For the choice of the reliability constraint factors, we choose the six important ones according to practical need for conducting the reliability allocation. The subsystem selected by the top-level fault tree analysis is to avoid allocating reliability for all the equipment and components including the unnecessary parts. During the reliability process, some factors can be calculated or measured quantitatively while others only can be assessed qualitatively by the expert rating method. So we adopt fuzzy decision and dualistic contrast to realize the reliability allocation with the help of fault tree analysis. Finally the example of the emergency diesel generator's reliability allocation is used to illustrate reliability allocation model and improve this model simple and applicable. (authors)

  6. Genetic program based data mining of fuzzy decision trees and methods of improving convergence and reducing bloat (United States)

    Smith, James F., III; Nguyen, ThanhVu H.


    A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program (GP) is discussed. A GP is an algorithm that evolves other algorithms or mathematical expressions. Innovative methods for accelerating convergence of the data mining procedure and reducing bloat are given. In genetic programming, bloat refers to excessive tree growth. It has been observed that the trees in the evolving GP population will grow by a factor of three every 50 generations. When evolving mathematical expressions much of the bloat is due to the expressions not being in algebraically simplest form. So a bloat reduction method based on automated computer algebra has been introduced. The effectiveness of this procedure is discussed. Also, rules based on fuzzy logic have been introduced into the GP to accelerate convergence, reduce bloat and produce a solution more readily understood by the human user. These rules are discussed as well as other techniques for convergence improvement and bloat control. Comparisons between trees created using a genetic program and those constructed solely by interviewing experts are made. A new co-evolutionary method that improves the control logic evolved by the GP by having a genetic algorithm evolve pathological scenarios is discussed. The effect on the control logic is considered. Finally, additional methods that have been used to validate the data mining algorithm are referenced.

  7. Base tree property

    Czech Academy of Sciences Publication Activity Database

    Balcar, B.; Doucha, Michal; Hrušák, M.


    Roč. 32, č. 1 (2015), s. 69-81 ISSN 0167-8094 R&D Projects: GA AV ČR IAA100190902 Institutional support: RVO:67985840 Keywords : forcing * Boolean algebras * base tree Subject RIV: BA - General Mathematics Impact factor: 0.614, year: 2015

  8. AxML: a fast program for sequential and parallel phylogenetic tree calculations based on the maximum likelihood method. (United States)

    Stamatakis, Alexandros P; Ludwig, Thomas; Meier, Harald; Wolf, Marty J


    Heuristics for the NP-complete problem of calculating the optimal phylogenetic tree for a set of aligned rRNA sequences based on the maximum likelihood method are computationally expensive. In most existing algorithms the tree evaluation and branch length optimization functions, calculating the likelihood value for each tree topology examined in the search space, account for the greatest part of overall computation time. This paper introduces AxML, a program derived from fastDNAml, incorporating a fast topology evaluation function. The algorithmic optimizations introduced, represent a general approach for accelerating this function and are applicable to both sequential and parallel phylogeny programs, irrespective of their search space strategy. Therefore, their integration into three existing phylogeny programs rendered encouraging results. Experimental results on conventional processor architectures show a global run time improvement of 35% up to 47% for the various test sets and program versions we used.

  9. A Waterline Extraction Method from Remote Sensing Image Based on Quad-tree and Multiple Active Contour Model

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    YU Jintao


    Full Text Available After the characteristics of geodesic active contour model (GAC, Chan-Vese model(CV and local binary fitting model(LBF are analyzed, and the active contour model based on regions and edges is combined with image segmentation method based on quad-tree, a waterline extraction method based on quad-tree and multiple active contour model is proposed in this paper. Firstly, the method provides an initial contour according to quad-tree segmentation. Secondly, a new signed pressure force(SPF function based on global image statistics information of CV model and local image statistics information of LBF model has been defined, and then ,the edge stopping function(ESF is replaced by the proposed SPF function, which solves the problem such as evolution stopped in advance and excessive evolution. Finally, the selective binary and Gaussian filtering level set method is used to avoid reinitializing and regularization to improve the evolution efficiency. The experimental results show that this method can effectively extract the weak edges and serious concave edges, and owns some properties such as sub-pixel accuracy, high efficiency and reliability for waterline extraction.

  10. Fault diagnostics of dynamic system operation using a fault tree based method

    International Nuclear Information System (INIS)

    Hurdle, E.E.; Bartlett, L.M.; Andrews, J.D.


    For conventional systems, their availability can be considerably improved by reducing the time taken to restore the system to the working state when faults occur. Fault identification can be a significant proportion of the time taken in the repair process. Having diagnosed the problem the restoration of the system back to its fully functioning condition can then take place. This paper expands the capability of previous approaches to fault detection and identification using fault trees for application to dynamically changing systems. The technique has two phases. The first phase is modelling and preparation carried out offline. This gathers information on the effects that sub-system failure will have on the system performance. Causes of the sub-system failures are developed in the form of fault trees. The second phase is application. Sensors are installed on the system to provide information about current system performance from which the potential causes can be deduced. A simple system example is used to demonstrate the features of the method. To illustrate the potential for the method to deal with additional system complexity and redundancy, a section from an aircraft fuel system is used. A discussion of the results is provided.

  11. Entropy Estimation for Optical PUFs Based on Context-Tree Weighting Methods (United States)

    Tuyls, Pim; Skoric, Boris; Ignatenko, Tanya; Willems, Frans; Schrijen, Geert-Jan

    In this chapter we discuss estimation of the secrecy rate of fuzzy sources- more specifically of optical physical unclonable functions (PUFs)-using context-tree weighting (CTW) methods [291]. We show that the entropy of a stationary 2-D source is a limit of a series of conditional entropies [6] and extend this result to the conditional entropy of one 2-D source given another one. Furthermore, we show that the general CTW-method approaches the source entropy also in the 2-D stationary case. Moreover, we generalize Maurer's result [196] to the ergodic case, thus showing that we get realistic estimates of the achievable secrecy rate. Finally, we use these results to estimate the secrecy rate of speckle patterns from optical PUFs.

  12. VR-BFDT: A variance reduction based binary fuzzy decision tree induction method for protein function prediction. (United States)

    Golzari, Fahimeh; Jalili, Saeed


    In protein function prediction (PFP) problem, the goal is to predict function of numerous well-sequenced known proteins whose function is not still known precisely. PFP is one of the special and complex problems in machine learning domain in which a protein (regarded as instance) may have more than one function simultaneously. Furthermore, the functions (regarded as classes) are dependent and also are organized in a hierarchical structure in the form of a tree or directed acyclic graph. One of the common learning methods proposed for solving this problem is decision trees in which, by partitioning data into sharp boundaries sets, small changes in the attribute values of a new instance may cause incorrect change in predicted label of the instance and finally misclassification. In this paper, a Variance Reduction based Binary Fuzzy Decision Tree (VR-BFDT) algorithm is proposed to predict functions of the proteins. This algorithm just fuzzifies the decision boundaries instead of converting the numeric attributes into fuzzy linguistic terms. It has the ability of assigning multiple functions to each protein simultaneously and preserves the hierarchy consistency between functional classes. It uses the label variance reduction as splitting criterion to select the best "attribute-value" at each node of the decision tree. The experimental results show that the overall performance of the proposed algorithm is promising. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. A theory of game trees, based on solution trees

    NARCIS (Netherlands)

    W.H.L.M. Pijls (Wim); A. de Bruin (Arie); A. Plaat (Aske)


    textabstractIn this paper a complete theory of game tree algorithms is presented, entirely based upon the notion of a solution tree. Two types of solution trees are distinguished: max and min solution trees respectively. We show that most game tree algorithms construct a superposition of a max and a

  14. A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Hongxing Liu


    Full Text Available As an important component of urban vegetation, street trees play an important role in maintenance of environmental quality, aesthetic beauty of urban landscape, and social service for inhabitants. Acquiring accurate and up-to-date inventory information for street trees is required for urban horticultural planning, and municipal urban forest management. This paper presents a new Voxel-based Marked Neighborhood Searching (VMNS method for efficiently identifying street trees and deriving their morphological parameters from Mobile Laser Scanning (MLS point cloud data. The VMNS method consists of six technical components: voxelization, calculating values of voxels, searching and marking neighborhoods, extracting potential trees, deriving morphological parameters, and eliminating pole-like objects other than trees. The method is validated and evaluated through two case studies. The evaluation results show that the completeness and correctness of our method for street tree detection are over 98%. The derived morphological parameters, including tree height, crown diameter, diameter at breast height (DBH, and crown base height (CBH, are in a good agreement with the field measurements. Our method provides an effective tool for extracting various morphological parameters for individual street trees from MLS point cloud data.

  15. Decentralized cooperative unmanned aerial vehicles conflict resolution by neural network-based tree search method

    Directory of Open Access Journals (Sweden)

    Jian Yang


    Full Text Available In this article, a tree search algorithm is proposed to find the near optimal conflict avoidance solutions for unmanned aerial vehicles. In the dynamic environment, the unmodeled elements, such as wind, would make UAVs deviate from nominal traces. It brings about difficulties for conflict detection and resolution. The back propagation neural networks are utilized to approximate the unmodeled dynamics of the environment. To satisfy the online planning requirement, the search length of the tree search algorithm would be limited. Therefore, the algorithm may not be able to reach the goal states in search process. The midterm reward function for assessing each node is devised, with consideration given to two factors, namely, the safe separation requirement and the mission of each unmanned aerial vehicle. The simulation examples and the comparisons with previous approaches are provided to illustrate the smooth and convincing behaviours of the proposed algorithm.

  16. M-AMST: an automatic 3D neuron tracing method based on mean shift and adapted minimum spanning tree. (United States)

    Wan, Zhijiang; He, Yishan; Hao, Ming; Yang, Jian; Zhong, Ning


    Understanding the working mechanism of the brain is one of the grandest challenges for modern science. Toward this end, the BigNeuron project was launched to gather a worldwide community to establish a big data resource and a set of the state-of-the-art of single neuron reconstruction algorithms. Many groups contributed their own algorithms for the project, including our mean shift and minimum spanning tree (M-MST). Although M-MST is intuitive and easy to implement, the MST just considers spatial information of single neuron and ignores the shape information, which might lead to less precise connections between some neuron segments. In this paper, we propose an improved algorithm, namely M-AMST, in which a rotating sphere model based on coordinate transformation is used to improve the weight calculation method in M-MST. Two experiments are designed to illustrate the effect of adapted minimum spanning tree algorithm and the adoptability of M-AMST in reconstructing variety of neuron image datasets respectively. In the experiment 1, taking the reconstruction of APP2 as reference, we produce the four difference scores (entire structure average (ESA), different structure average (DSA), percentage of different structure (PDS) and max distance of neurons' nodes (MDNN)) by comparing the neuron reconstruction of the APP2 and the other 5 competing algorithm. The result shows that M-AMST gets lower difference scores than M-MST in ESA, PDS and MDNN. Meanwhile, M-AMST is better than N-MST in ESA and MDNN. It indicates that utilizing the adapted minimum spanning tree algorithm which took the shape information of neuron into account can achieve better neuron reconstructions. In the experiment 2, 7 neuron image datasets are reconstructed and the four difference scores are calculated by comparing the gold standard reconstruction and the reconstructions produced by 6 competing algorithms. Comparing the four difference scores of M-AMST and the other 5 algorithm, we can conclude that

  17. Preliminary hazard analysis using sequence tree method

    International Nuclear Information System (INIS)

    Huang Huiwen; Shih Chunkuan; Hung Hungchih; Chen Minghuei; Yih Swu; Lin Jiinming


    A system level PHA using sequence tree method was developed to perform Safety Related digital I and C system SSA. The conventional PHA is a brainstorming session among experts on various portions of the system to identify hazards through discussions. However, this conventional PHA is not a systematic technique, the analysis results strongly depend on the experts' subjective opinions. The analysis quality cannot be appropriately controlled. Thereby, this research developed a system level sequence tree based PHA, which can clarify the relationship among the major digital I and C systems. Two major phases are included in this sequence tree based technique. The first phase uses a table to analyze each event in SAR Chapter 15 for a specific safety related I and C system, such as RPS. The second phase uses sequence tree to recognize what I and C systems are involved in the event, how the safety related systems work, and how the backup systems can be activated to mitigate the consequence if the primary safety systems fail. In the sequence tree, the defense-in-depth echelons, including Control echelon, Reactor trip echelon, ESFAS echelon, and Indication and display echelon, are arranged to construct the sequence tree structure. All the related I and C systems, include digital system and the analog back-up systems are allocated in their specific echelon. By this system centric sequence tree based analysis, not only preliminary hazard can be identified systematically, the vulnerability of the nuclear power plant can also be recognized. Therefore, an effective simplified D3 evaluation can be performed as well. (author)

  18. Performance of a cavity-method-based algorithm for the prize-collecting Steiner tree problem on graphs (United States)

    Biazzo, Indaco; Braunstein, Alfredo; Zecchina, Riccardo


    We study the behavior of an algorithm derived from the cavity method for the prize-collecting steiner tree (PCST) problem on graphs. The algorithm is based on the zero temperature limit of the cavity equations and as such is formally simple (a fixed point equation resolved by iteration) and distributed (parallelizable). We provide a detailed comparison with state-of-the-art algorithms on a wide range of existing benchmarks, networks, and random graphs. Specifically, we consider an enhanced derivative of the Goemans-Williamson heuristics and the dhea solver, a branch and cut integer linear programming based approach. The comparison shows that the cavity algorithm outperforms the two algorithms in most large instances both in running time and quality of the solution. Finally we prove a few optimality properties of the solutions provided by our algorithm, including optimality under the two postprocessing procedures defined in the Goemans-Williamson derivative and global optimality in some limit cases.

  19. Comparison of complex networks and tree-based methods of phylogenetic analysis and proposal of a bootstrap method. (United States)

    Góes-Neto, Aristóteles; Diniz, Marcelo V C; Carvalho, Daniel S; Bomfim, Gilberto C; Duarte, Angelo A; Brzozowski, Jerzy A; Petit Lobão, Thierry C; Pinho, Suani T R; El-Hani, Charbel N; Andrade, Roberto F S


    Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits. In order to perform a close comparison to these methods, we selected Basidiomycota fungi as the taxonomic group and used a high-quality, manually curated and characterized database of chitin synthase sequences. This enzymatic protein plays a key role in the synthesis of one of the exclusive features of the fungal cell wall: the presence of chitin. The communities (modules) detected by the complex network method corresponded exactly to the groups retrieved by the phylogenetic inference methods. Additionally, we propose a bootstrap method for the complex network approach. The statistical results we have obtained with this method were also close to those obtained using traditional bootstrap methods.

  20. Method for Walking Gait Identification in a Lower Extremity Exoskeleton Based on C4.5 Decision Tree Algorithm

    Directory of Open Access Journals (Sweden)

    Qing Guo


    Full Text Available A gait identification method for a lower extremity exoskeleton is presented in order to identify the gait sub-phases in human-machine coordinated motion. First, a sensor layout for the exoskeleton is introduced. Taking the difference between human lower limb motion and human-machine coordinated motion into account, the walking gait is divided into five sub-phases, which are ‘double standing’, ‘right leg swing and left leg stance’, ‘double stance with right leg front and left leg back’, ‘right leg stance and left leg swing’, and ‘double stance with left leg front and right leg back’. The sensors include shoe pressure sensors, knee encoders, and thigh and calf gyroscopes, and are used to measure the contact force of the foot, and the knee joint angle and its angular velocity. Then, five sub-phases of walking gait are identified by a C4.5 decision tree algorithm according to the data fusion of the sensors' information. Based on the simulation results for the gait division, identification accuracy can be guaranteed by the proposed algorithm. Through the exoskeleton control experiment, a division of five sub-phases for the human-machine coordinated walk is proposed. The experimental results verify this gait division and identification method. They can make hydraulic cylinders retract ahead of time and improve the maximal walking velocity when the exoskeleton follows the person's motion.

  1. Success tree method of resources evaluation

    International Nuclear Information System (INIS)

    Chen Qinglan; Sun Wenpeng


    By applying the reliability theory in system engineering, the success tree method is used to transfer the expert's recognition on metallogenetic regularities into the form of the success tree. The aim of resources evaluation is achieved by means of calculating the metallogenetic probability or favorability of the top event of the success tree. This article introduces in detail, the source, principle of the success tree method and three kinds of calculation methods, expounds concretely how to establish the success tree of comprehensive uranium metallogenesis as well as the procedure from which the resources evaluation is performed. Because this method has not restrictions on the number of known deposits and calculated area, it is applicable to resources evaluation for different mineral species, types and scales and possesses good prospects of development

  2. A decision-tree-based method for reconstructing disturbance history in the Russia boreal forests over 30 years (United States)

    Chen, D.; Loboda, T. V.


    The boreal forest is one of the largest biomes on Earth and carries crucial significance in numerous aspects. Located in the high latitude region of the Northern Hemisphere, it is predicted that the boreal forest is subject to the highest level of influence under the changing climate, which may impose profound impacts on the global carbon and energy budget. Of the entire boreal biome, approximately two thirds consists of the Russian boreal forest, which is also the largest forested zone in the world. Fire and logging have been the predominant disturbance types in the Russian boreal forest, which accelerate the speed of carbon release into the atmosphere. To better understand these processes, records of past disturbance are in great need. However, there has been no comprehensive and unbiased multi-decadal record of forest disturbance in this region. This paper illustrates a method for reconstructing disturbance history in the Russia boreal forests over 30 years. This method takes advantage of data from both Landsat, which has a long data record but limited spatial coverage, and the Moderate Resolution Spectroradiometer (MODIS), which has wall-to-wall spatial coverage but limited period of observations. We developed a standardized and semi-automated approach to extract training and validation data samples from Landsat imagery. Landsat data, dating back to 1984, were used to generate maps of forest disturbance using temporal shifts in Disturbance Index through the multi-temporal stack of imagery in selected locations. The disturbed forests are attributed to logging or burning causes by means of visual examination. The Landsat-based disturbance maps are then used as reference data to train a decision tree classifier on 2003 MODIS data. This classifier utilizes multiple direct MODIS products including the BRDF-adjusted surface reflectance, a suite of vegetation indices, and land surface temperature. The algorithm also capitalizes on seasonal variability in class

  3. Decision tree methods: applications for classification and prediction. (United States)

    Song, Yan-Yan; Lu, Ying


    Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure.

  4. Dissimilarity-based classification of anatomical tree structures

    DEFF Research Database (Denmark)

    Sørensen, Lauge; Lo, Pechin Chien Pau; Dirksen, Asger


    A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment...... between the branch feature vectors representing those trees. Hereby, localized information in the branches is collectively used in classification and variations in feature values across the tree are taken into account. An approximate anatomical correspondence between matched branches can be achieved...... by including anatomical features in the branch feature vectors. The proposed approach is applied to classify airway trees in computed tomography images of subjects with and without chronic obstructive pulmonary disease (COPD). Using the wall area percentage (WA%), a common measure of airway abnormality in COPD...

  5. Statistically Consistent k-mer Methods for Phylogenetic Tree Reconstruction. (United States)

    Allman, Elizabeth S; Rhodes, John A; Sullivant, Seth


    Frequencies of k-mers in sequences are sometimes used as a basis for inferring phylogenetic trees without first obtaining a multiple sequence alignment. We show that a standard approach of using the squared Euclidean distance between k-mer vectors to approximate a tree metric can be statistically inconsistent. To remedy this, we derive model-based distance corrections for orthologous sequences without gaps, which lead to consistent tree inference. The identifiability of model parameters from k-mer frequencies is also studied. Finally, we report simulations showing that the corrected distance outperforms many other k-mer methods, even when sequences are generated with an insertion and deletion process. These results have implications for multiple sequence alignment as well since k-mer methods are usually the first step in constructing a guide tree for such algorithms.

  6. Age estimation of large trees: New method based on partial increment core tested on an example of veteran oaks

    Czech Academy of Sciences Publication Activity Database

    Altman, Jan; Doležal, Jiří; Čížek, Lukáš


    Roč. 380, č. 11 (2016), s. 82-89 ISSN 0378-1127 R&D Projects: GA ČR(CZ) GA14-12262S; GA ČR GAP504/12/1952 Institutional support: RVO:67985939 ; RVO:60077344 Keywords : Tree age estimation * Dendrochronology * Partial cores Subject RIV: EH - Ecology, Behaviour Impact factor: 3.064, year: 2016

  7. Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels

    Directory of Open Access Journals (Sweden)

    Ebtehaj Isa


    Full Text Available A vital topic regarding the optimum and economical design of rigid boundary open channels such as sewers and drainage systems is determining the movement of sediment particles. In this study, the incipient motion of sediment is estimated using three datasets from literature, including a wide range of hydraulic parameters. Because existing equations do not consider the effect of sediment bed thickness on incipient motion estimation, this parameter is applied in this study along with the multilayer perceptron (MLP, a hybrid method based on decision trees (DT (MLP-DT, to estimate incipient motion. According to a comparison with the observed experimental outcome, the proposed method performs well (MARE = 0.048, RMSE = 0.134, SI = 0.06, BIAS = -0.036. The performance of MLP and MLP-DT is compared with that of existing regression-based equations, and significantly higher performance over existing models is observed. Finally, an explicit expression for practical engineering is also provided.

  8. Advanced predictive methods for wine age prediction: Part I - A comparison study of single-block regression approaches based on variable selection, penalized regression, latent variables and tree-based ensemble methods. (United States)

    Rendall, Ricardo; Pereira, Ana Cristina; Reis, Marco S


    In this paper we test and compare advanced predictive approaches for estimating wine age in the context of the production of a high quality fortified wine - Madeira Wine. We consider four different data sets, namely, volatile, polyphenols, organic acids and the UV-vis spectra. Each one of these data sets contain chemical information of a different nature and present diverse data structures, namely a different dimensionality, level of collinearity and degree of sparsity. These different aspects may imply the use of different modelling approaches in order to better explore the data set's information content, namely their predictive potential for wine age. This happens to be so, because different regression methods have different prior assumptions regarding the predictors, response variable(s) and the data generating mechanism, which may or may not find good adherence to the case study under analysis. In order to cover a wide range of modelling domains, we have incorporated in this work methods belonging to four very distinct classes of approaches that cover most applications found in practice: linear regression with variable selection, penalized regression, latent variables regression and tree-based ensemble methods. We have also developed a rigorous comparison framework based on a double Monte Carlo cross-validation scheme, in order to perform the relative assessment of the performance of the various methods. Upon comparison, models built using the polyphenols and volatile composition data sets led to better wine age predictions, showing lower errors under testing conditions. Furthermore, the results obtained for the polyphenols data set suggest a more sparse structure that can be further explored in order to reduce the number of measured variables. In terms of regression methods, tree-based methods, and boosted regression trees in particular, presented the best results for the polyphenols, volatile and the organic acid data sets, suggesting a possible presence of a

  9. Consistency and inconsistency of consensus methods for inferring species trees from gene trees in the presence of ancestral population structure (United States)

    DeGiorgio, Michael; Rosenberg, Noah A.


    In the last few years, several statistically consistent consensus methods for species tree inference have been devised that are robust to the gene tree discordance caused by incomplete lineage sorting in unstructured ancestral populations. One source of gene tree discordance that has only recently been identified as a potential obstacle for phylogenetic inference is ancestral population structure. In this article, we describe a general model of ancestral population structure, and by relying on a single carefully constructed example scenario, we show that the consensus methods Democratic Vote, STEAC, STAR, R* Consensus, Rooted Triple Consensus, Minimize Deep Coalescences, and Majority-Rule Consensus are statistically inconsistent under the model. We find that among the consensus methods evaluated, the only method that is statistically consistent in the presence of ancestral population structure is GLASS/Maximum Tree. We use simulations to evaluate the behavior of the various consensus methods in a model with ancestral population structure, showing that as the number of gene trees increases, estimates on the basis of GLASS/Maximum Tree approach the true species tree topology irrespective of the level of population structure, whereas estimates based on the remaining methods only approach the true species tree topology if the level of structure is low. However, through simulations using species trees both with and without ancestral population structure, we show that GLASS/Maximum Tree performs unusually poorly on gene trees inferred from alignments with little information. This practical limitation of GLASS/Maximum Tree together with the inconsistency of other methods prompts the need for both further testing of additional existing methods and development of novel methods under conditions that incorporate ancestral population structure. PMID:27086043

  10. Spanning Tree Based Attribute Clustering

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Jorge, Cordero Hernandez


    inconsistent edges from a maximum spanning tree by starting appropriate initial modes, therefore generating stable clusters. It discovers sound clusters through simple graph operations and achieves significant computational savings. We compare the Star Discovery algorithm against earlier attribute clustering...

  11. Knowledge base image classification using P-trees (United States)

    Seetha, M.; Ravi, G.


    Image Classification is the process of assigning classes to the pixels in remote sensed images and important for GIS applications, since the classified image is much easier to incorporate than the original unclassified image. To resolve misclassification in traditional parametric classifier like Maximum Likelihood Classifier, the neural network classifier is implemented using back propagation algorithm. The extra spectral and spatial knowledge acquired from the ancillary information is required to improve the accuracy and remove the spectral confusion. To build knowledge base automatically, this paper explores a non-parametric decision tree classifier to extract knowledge from the spatial data in the form of classification rules. A new method is proposed using a data structure called Peano Count Tree (P-tree) for decision tree classification. The Peano Count Tree is a spatial data organization that provides a lossless compressed representation of a spatial data set and facilitates efficient classification than other data mining techniques. The accuracy is assessed using the parameters overall accuracy, User's accuracy and Producer's accuracy for image classification methods of Maximum Likelihood Classification, neural network classification using back propagation, Knowledge Base Classification, Post classification and P-tree Classifier. The results reveal that the knowledge extracted from decision tree classifier and P-tree data structure from proposed approach remove the problem of spectral confusion to a greater extent. It is ascertained that the P-tree classifier surpasses the other classification techniques.

  12. Evaluating a non-destructive method for calibrating tree biomass equations derived from tree branching architecture

    NARCIS (Netherlands)

    MacFarlane, D.W.; Kuyah, S.; Mulia, R.; Dietz, J.; Muthuri, C.; Noordwijk, van M.


    Functional branch analysis (FBA) is a promising non-destructive alternative to the standard destructive method of tree biomass equation development. In FBA, a theoretical model of tree branching architecture is calibrated with measurements of tree stems and branches to estimate the coefficients of

  13. Risk-based fault tree analysis method for identification, preliminary evaluation, and screening of potential accidental release sequences in nuclear fuel cycle operations

    Energy Technology Data Exchange (ETDEWEB)

    Smith, T.H.; Pelto, P.J.; Stevens, D.L.; Seybold, G.D.; Purcell, W.L.; Kimmel, L.V.


    A method is described for identification, preliminary evaluation, and screening of potential accident sequences leading to uncontrolled release of radioactive materials. Included is a procedure for estimating the risk sum of all identified sequences. In addition, portions of the procedures have been developed for detailed analysis of the dominant (highest risk) sequences so screened. This method was developed for the ERDA-sponsored risk analysis of systems for managing high-level waste, part of the Waste Fixation Program (WFP). The method begins with certain preliminary analyses. The facility and operation are described and analysis bounds are established. A type of fault tree construction, the ''to/through'' approach, was chosen for the WFP waste management system. The to/through fault tree approach offers advantages over others in several respects. The analysis is considered more complete because the system is treated as a whole. The screening process was successfully demonstrated on a conceptual waste management system for the Waste Fixation Program. Fault trees were constructed and evaluated for processing, handling, transporting, and storing high-level waste. Trees of up to 14,000,000 release sequences (BICS-Boolean-indicated cut sets) were screened and the top few hundred or thousand sequences preliminarily ranked. An estimate of the total risk represented in the fault tree was also obtained. (auth)

  14. Phylogeny of the cycads based on multiple single-copy nuclear genes: congruence of concatenated parsimony, likelihood and species tree inference methods. (United States)

    Salas-Leiva, Dayana E; Meerow, Alan W; Calonje, Michael; Griffith, M Patrick; Francisco-Ortega, Javier; Nakamura, Kyoko; Stevenson, Dennis W; Lewis, Carl E; Namoff, Sandra


    Despite a recent new classification, a stable phylogeny for the cycads has been elusive, particularly regarding resolution of Bowenia, Stangeria and Dioon. In this study, five single-copy nuclear genes (SCNGs) are applied to the phylogeny of the order Cycadales. The specific aim is to evaluate several gene tree-species tree reconciliation approaches for developing an accurate phylogeny of the order, to contrast them with concatenated parsimony analysis and to resolve the erstwhile problematic phylogenetic position of these three genera. DNA sequences of five SCNGs were obtained for 20 cycad species representing all ten genera of Cycadales. These were analysed with parsimony, maximum likelihood (ML) and three Bayesian methods of gene tree-species tree reconciliation, using Cycas as the outgroup. A calibrated date estimation was developed with Bayesian methods, and biogeographic analysis was also conducted. Concatenated parsimony, ML and three species tree inference methods resolve exactly the same tree topology with high support at most nodes. Dioon and Bowenia are the first and second branches of Cycadales after Cycas, respectively, followed by an encephalartoid clade (Macrozamia-Lepidozamia-Encephalartos), which is sister to a zamioid clade, of which Ceratozamia is the first branch, and in which Stangeria is sister to Microcycas and Zamia. A single, well-supported phylogenetic hypothesis of the generic relationships of the Cycadales is presented. However, massive extinction events inferred from the fossil record that eliminated broader ancestral distributions within Zamiaceae compromise accurate optimization of ancestral biogeographical areas for that hypothesis. While major lineages of Cycadales are ancient, crown ages of all modern genera are no older than 12 million years, supporting a recent hypothesis of mostly Miocene radiations. This phylogeny can contribute to an accurate infrafamilial classification of Zamiaceae.

  15. Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes (United States)

    Complex diseases are often difficult to diagnose, treat, and study due to the multi-factorial nature of the etiology. Significant challenges exist with regard to how to segregate indivdiuals into suitable subtypes of the disease. Here, we examine a range of methods for evaluati...

  16. Two tree-formation methods for fast pattern search using nearest-neighbour and nearest-centroid matching

    NARCIS (Netherlands)

    Schomaker, Lambertus; Mangalagiu, D.; Vuurpijl, Louis; Weinfeld, M.; Schomaker, Lambert; Vuurpijl, Louis


    This paper describes tree­based classification of character images, comparing two methods of tree formation and two methods of matching: nearest neighbor and nearest centroid. The first method, Preprocess Using Relative Distances (PURD) is a tree­based reorganization of a flat list of patterns,

  17. Classifiability-based omnivariate decision trees. (United States)

    Li, Yuanhong; Dong, Ming; Kothari, Ravi


    Top-down induction of decision trees is a simple and powerful method of pattern classification. In a decision tree, each node partitions the available patterns into two or more sets. New nodes are created to handle each of the resulting partitions and the process continues. A node is considered terminal if it satisfies some stopping criteria (for example, purity, i.e., all patterns at the node are from a single class). Decision trees may be univariate, linear multivariate, or nonlinear multivariate depending on whether a single attribute, a linear function of all the attributes, or a nonlinear function of all the attributes is used for the partitioning at each node of the decision tree. Though nonlinear multivariate decision trees are the most powerful, they are more susceptible to the risks of overfitting. In this paper, we propose to perform model selection at each decision node to build omnivariate decision trees. The model selection is done using a novel classifiability measure that captures the possible sources of misclassification with relative ease and is able to accurately reflect the complexity of the subproblem at each node. The proposed approach is fast and does not suffer from as high a computational burden as that incurred by typical model selection algorithms. Empirical results over 26 data sets indicate that our approach is faster and achieves better classification accuracy compared to statistical model select algorithms.

  18. New method for abbreviating the fault tree graphical representation

    International Nuclear Information System (INIS)

    Stewart, M.E.; Fussell, J.B.; Crump, R.J.


    Fault tree analysis is being widely used for reliability and safety analysis of systems encountered in the nuclear industry and elsewhere. A disadvantage of the fault tree method is the voluminous fault tree graphical representation that conventionally results from analysis of a complex system. Previous methods for shortening the fault tree graphical representation include (1) transfers within the fault tree, and (2) the use of the SAMPLE (K out of N logic) gate, the MATRIX gate, and the SUMMATION gate. The purpose of this presentation is to introduce TABULATION gates as a method to abbreviate the fault tree graphical representation. These new gates reduce the cost of analysis and generally increase the system behavior visibility that is inherent in the fault tree technique

  19. The shape of supertrees to come: tree shape related properties of fourteen supertree methods. (United States)

    Wilkinson, Mark; Cotton, James A; Creevey, Chris; Eulenstein, Oliver; Harris, Simon R; Lapointe, Francois-Joseph; Levasseur, Claudine; McInerney, James O; Pisani, Davide; Thorley, Joseph L


    Using a simple example and simulations, we explore the impact of input tree shape upon a broad range of supertree methods. We find that input tree shape can affect how conflict is resolved by several supertree methods and that input tree shape effects may be substantial. Standard and irreversible matrix representation with parsimony (MRP), MinFlip, duplication-only Gene Tree Parsimony (GTP), and an implementation of the average consensus method have a tendency to resolve conflict in favor of relationships in unbalanced trees. Purvis MRP and the average dendrogram method appear to have an opposite tendency. Biases with respect to tree shape are correlated with objective functions that are based upon unusual asymmetric tree-to-tree distance or fit measures. Split, quartet, and triplet fit, most similar supertree, and MinCut methods (provided the latter are interpreted as Adams consensus-like supertrees) are not revealed to have any bias with respect to tree shape by our example, but whether this holds more generally is an open problem. Future development and evaluation of supertree methods should consider explicitly the undesirable biases and other properties that we highlight. In the meantime, use of a single, arbitrarily chosen supertree method is discouraged. Use of multiple methods and/or weighting schemes may allow practical assessment of the extent to which inferences from real data depend upon methodological biases with respect to input tree shape or size.

  20. Optimization Method of Fusing Model Tree into Partial Least Squares

    Directory of Open Access Journals (Sweden)

    Yu Fang


    Full Text Available Partial Least Square (PLS can’t adapt to the characteristics of the data of many fields due to its own features multiple independent variables, multi-dependent variables and non-linear. However, Model Tree (MT has a good adaptability to nonlinear function, which is made up of many multiple linear segments. Based on this, a new method combining PLS and MT to analysis and predict the data is proposed, which build MT through the main ingredient and the explanatory variables(the dependent variable extracted from PLS, and extract residual information constantly to build Model Tree until well-pleased accuracy condition is satisfied. Using the data of the maxingshigan decoction of the monarch drug to treat the asthma or cough and two sample sets in the UCI Machine Learning Repository, the experimental results show that, the ability of explanation and predicting get improved in the new method.

  1. New weighting methods for phylogenetic tree reconstruction using multiple loci. (United States)

    Misawa, Kazuharu; Tajima, Fumio


    Efficient determination of evolutionary distances is important for the correct reconstruction of phylogenetic trees. The performance of the pooled distance required for reconstructing a phylogenetic tree can be improved by applying large weights to appropriate distances for reconstructing phylogenetic trees and small weights to inappropriate distances. We developed two weighting methods, the modified Tajima-Takezaki method and the modified least-squares method, for reconstructing phylogenetic trees from multiple loci. By computer simulations, we found that both of the new methods were more efficient in reconstructing correct topologies than the no-weight method. Hence, we reconstructed hominoid phylogenetic trees from mitochondrial DNA using our new methods, and found that the levels of bootstrap support were significantly increased by the modified Tajima-Takezaki and by the modified least-squares method.

  2. Species Tree Inference from Gene Splits by Unrooted STAR Methods. (United States)

    Allman, Elizabeth S; Degnan, James H; Rhodes, John A


    The method was proposed by Liu and Yu to infer a species tree topology from unrooted topological gene trees. While its statistical consistency under the multispecies coalescent model was established only for a four-taxon tree, simulations demonstrated its good performance on gene trees inferred from sequences for many taxa. Here, we prove the statistical consistency of the method for an arbitrarily large species tree. Our approach connects to a generalization of the STAR method of Liu, Pearl, and Edwards, and a previous theoretical analysis of it. We further show utilizes only the distribution of splits in the gene trees, and not their individual topologies. Finally, we discuss how multiple samples per taxon per gene should be handled for statistical consistency.

  3. Comparing different methods to assess weaver ant abundance in plantation trees

    DEFF Research Database (Denmark)

    Wargui, Rosine; Offenberg, Joachim; Sinzogan, Antonio


    Weaver ants (Oecophylla spp.) are widely used as effective biological control agents. In order to optimize their use, ant abundance needs to be tracked. As several methods have been used to estimate ant abundance on plantation trees, abundances are not comparable between studies and no guideline...... is available on which method to apply in a particular study. This study compared four existing methods: three methods based on the number of ant trails on the main branches of a tree (called the Peng 1, Peng 2 and Offenberg index) and one method based on the number of ant nests per tree. Branch indices did...

  4. Individual tree detection based on densities of high points of high resolution airborne lidar

    NARCIS (Netherlands)

    Abd Rahman, M.Z.; Gorte, B.G.H.


    The retrieval of individual tree location from Airborne LiDAR has focused largely on utilizing canopy height. However, high resolution Airborne LiDAR offers another source of information for tree detection. This paper presents a new method for tree detection based on high points’ densities from a

  5. A Maze Game on Android Using Growing Tree Method (United States)

    Hendrawan, Y. F.


    A maze is a type of puzzle games where a player moves in complex and branched passages to find a particular target or location. One method to create a maze is the Growing Tree method. The method creates a tree that has branches which are the paths of a maze. This research explored three types of Growing Tree method implementations for maze generation on Android mobile devices. The layouts produced could be played in first and third-person perspectives. The experiment results showed that it took 17.3 seconds on average to generate 20 cells x 20 cells dynamic maze layouts.


    Directory of Open Access Journals (Sweden)

    C. Yao


    Full Text Available The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM by subtracting the Digital Terrain Model (DTM from the digital surface model (DSM. Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

  7. Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud (United States)

    Yao, C.; Zhang, X.; Liu, H.


    The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

  8. Improvement of testing and maintenance based on fault tree analysis

    International Nuclear Information System (INIS)

    Cepin, M.


    Testing and maintenance of safety equipment is an important issue, which significantly contributes to safe and efficient operation of a nuclear power plant. In this paper a method, which extends the classical fault tree with time, is presented. Its mathematical model is represented by a set of equations, which include time requirements defined in the house event matrix. House events matrix is a representation of house events switched on and off through the discrete points of time. It includes house events, which timely switch on and off parts of the fault tree in accordance with the status of the plant configuration. Time dependent top event probability is calculated by the fault tree evaluations. Arrangement of components outages is determined on base of minimization of mean system unavailability. The results show that application of the method may improve the time placement of testing and maintenance activities of safety equipment. (author)

  9. TreePM Method for Two-Dimensional Cosmological Simulations ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    paper. The 2d TreePM code is an accurate and efficient technique to carry out large two-dimensional N-body simulations in cosmology. This hybrid code combines the 2d Barnes and Hut Tree method and the 2d Particle– ..... ment, we need less than 75 MB of RAM for a simulation with 10242 particles on a. 10242 grid.

  10. Towards an optimized method of olive tree crown volume measurement. (United States)

    Miranda-Fuentes, Antonio; Llorens, Jordi; Gamarra-Diezma, Juan L; Gil-Ribes, Jesús A; Gil, Emilio


    Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (VE) and Tree Silhouette Volume method (VTS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended.

  11. Towards an Optimized Method of Olive Tree Crown Volume Measurement (United States)

    Miranda-Fuentes, Antonio; Llorens, Jordi; Gamarra-Diezma, Juan L.; Gil-Ribes, Jesús A.; Gil, Emilio


    Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (VE) and Tree Silhouette Volume method (VTS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended. PMID:25658396

  12. Towards an Optimized Method of Olive Tree Crown Volume Measurement

    Directory of Open Access Journals (Sweden)

    Antonio Miranda-Fuentes


    Full Text Available Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA, Ellipsoid Volume method (VE and Tree Silhouette Volume method (VTS. Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended.

  13. Anchoring quartet-based phylogenetic distances and applications to species tree reconstruction. (United States)

    Sayyari, Erfan; Mirarab, Siavash


    Inferring species trees from gene trees using the coalescent-based summary methods has been the subject of much attention, yet new scalable and accurate methods are needed. We introduce DISTIQUE, a new statistically consistent summary method for inferring species trees from gene trees under the coalescent model. We generalize our results to arbitrary phylogenetic inference problems; we show that two arbitrarily chosen leaves, called anchors, can be used to estimate relative distances between all other pairs of leaves by inferring relevant quartet trees. This results in a family of distance-based tree inference methods, with running times ranging between quadratic to quartic in the number of leaves. We show in simulated studies that DISTIQUE has comparable accuracy to leading coalescent-based summary methods and reduced running times.

  14. Reset Tree-Based Optical Fault Detection

    Directory of Open Access Journals (Sweden)

    Howon Kim


    Full Text Available In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit’s reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool.

  15. CUDT: A CUDA Based Decision Tree Algorithm

    Directory of Open Access Journals (Sweden)

    Win-Tsung Lo


    Full Text Available Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture, which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5∼55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set.

  16. Recovery of crown mass for energy with whole-tree skidding methods; Puupolttoaineen tuottaminen kokopuujuontomenetelmillae

    Energy Technology Data Exchange (ETDEWEB)

    Nousiainen, I. [Finntech Ltd Oy, Jyvaeskylae (Finland); Vesisenaho, T. [VTT Energy, Jyvaeskylae (Finland)


    The main aim of the project `Recovery of crown mass for energy with whole-tree skidding methods` was to develop the integrated harvesting method of wood raw material and wood fuel based on whole-tree skidding. The developed method gives also the possibility to deliver to sawmills raw material in the form of log section. In the harvesting chain under development whole-trees are felled and bunched with a normal one-grip harvester. The whole-trees are skidded to the roadside by a forwarder equipped with a clam bunk. At the roadside the trees are delimbed and cut with the one-grip harvester used for felling and bunching. According to the results of the field tests the harvesting costs of logging residues are in certain final cutting conditions even under 10 FIM/m{sup 3}, when the average stem size is over 0,500 m{sup 3}. In the developed method felling and bunching of whole trees with the one-grip harvester and skidding of whole-trees with the clam skidder succeeded well. The problems of the method concentrate on delimbing and bucking of whole-trees in landing site

  17. Comparing different methods to assess weaver ant abundance in plantation trees

    DEFF Research Database (Denmark)

    Wargui, Rosine; Offenberg, Joachim; Sinzogan, Antonio


    showed fluctuations throughout the season. The numbers of nests showed high fluctuations unlikely to reflect ant abundance, but rather reflected nest building behavior influenced by tree phenology. In conclusion, nest counting is not recommended, whereas the Peng 1 index can track dynamics at low ant......Weaver ants (Oecophylla spp.) are widely used as effective biological control agents. In order to optimize their use, ant abundance needs to be tracked. As several methods have been used to estimate ant abundance on plantation trees, abundances are not comparable between studies and no guideline...... is available on which method to apply in a particular study. This study compared four existing methods: three methods based on the number of ant trails on the main branches of a tree (called the Peng 1, Peng 2 and Offenberg index) and one method based on the number of ant nests per tree. Branch indices did...

  18. The Efficacy of Consensus Tree Methods for Summarizing Phylogenetic Relationships from a Posterior Sample of Trees Estimated from Morphological Data. (United States)

    O'Reilly, Joseph E; Donoghue, Philip C J


    Consensus trees are required to summarize trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths, and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are coestimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method. The MCC method assumes that the sampled, fully resolved topology with the highest clade credibility is an adequate summary of the most probable clades, with parameter estimates from compatible sampled trees used to obtain the marginal distributions of parameters such as clade ages and branch lengths. Using both simulated and empirical data, we demonstrate that MCC trees, and trees constructed using the similar maximum a posteriori (MAP) method, often include poorly supported and incorrect clades when summarizing diffuse posterior samples of trees. We demonstrate that the paucity of information in morphological data sets contributes to the inability of MCC and MAP trees to accurately summarise of the posterior distribution. Conversely, majority-rule consensus (MRC) trees represent a lower proportion of incorrect nodes when summarizing the same posterior samples of trees. Thus, we advocate the use of MRC trees, in place of MCC or MAP trees, in attempts to summarize the results of Bayesian phylogenetic analyses of morphological data.

  19. Multiset-based Tree Model for Membrane Computing

    Directory of Open Access Journals (Sweden)

    D. Singh


    Full Text Available In this paper, we introduce a new paradigm - multiset-based tree model. We show that trees can be represented in the form of wellfounded multisets. We also show that the conventional approach for this representation is not injective from a set of trees to the class of multisets representing such trees. We establish a one-to-one correspondence between trees and suitable permutations of a wellfounded multiset, which we call \\textit{tree structures}. We give formal definitions of a \\textit{tree structure} and a \\textit{subtree structure} of a tree structure. Finally, we represent membrane structures in the form of tree structures - a form in which membrane structures can suitably be represented at programming level.

  20. A Novel Method of Fault Diagnosis for Rolling Bearing Based on Dual Tree Complex Wavelet Packet Transform and Improved Multiscale Permutation Entropy

    Directory of Open Access Journals (Sweden)

    Guiji Tang


    Full Text Available A novel method of fault diagnosis for rolling bearing, which combines the dual tree complex wavelet packet transform (DTCWPT, the improved multiscale permutation entropy (IMPE, and the linear local tangent space alignment (LLTSA with the extreme learning machine (ELM, is put forward in this paper. In this method, in order to effectively discover the underlying feature information, DTCWPT, which has the attractive properties as nearly shift invariance and reduced aliasing, is firstly utilized to decompose the original signal into a set of subband signals. Then, IMPE, which is designed to reduce the variability of entropy measures, is applied to characterize the properties of each obtained subband signal at different scales. Furthermore, the feature vectors are constructed by combining IMPE of each subband signal. After the feature vectors construction, LLTSA is employed to compress the high dimensional vectors of the training and the testing samples into the low dimensional vectors with better distinguishability. Finally, the ELM classifier is used to automatically accomplish the condition identification with the low dimensional feature vectors. The experimental data analysis results validate the effectiveness of the presented diagnosis method and demonstrate that this method can be applied to distinguish the different fault types and fault degrees of rolling bearings.

  1. Applied Research of Decision Tree Method on Football Training

    Directory of Open Access Journals (Sweden)

    Liu Jinhui


    Full Text Available This paper will make an analysis of decision tree at first, and then offer a further analysis of CLS based on it. As CLS contains the most substantial and most primitive decision-making idea, it can provide the basis of decision tree establishment. Due to certain limitation in details, the ID3 decision tree algorithm is introduced to offer more details. It applies information gain as attribute selection metrics to provide reference for seeking the optimal segmentation point. At last, the ID3 algorithm is applied in football training. Verification is made on this algorithm and it has been proved effectively and reasonably.

  2. A Non-Reference Image Denoising Method for Infrared Thermal Image Based on Enhanced Dual-Tree Complex Wavelet Optimized by Fruit Fly Algorithm and Bilateral Filter

    Directory of Open Access Journals (Sweden)

    Yiwen Liu


    Full Text Available To eliminate the noise of infrared thermal image without reference and noise model, an improved dual-tree complex wavelet transform (DTCWT, optimized by an improved fruit-fly optimization algorithm (IFOA and bilateral filter (BF, is proposed in this paper. Firstly, the noisy image is transformed by DTCWT, and the noise variance threshold is optimized by the IFOA, which is enhanced through a fly step range with inertia weight. Then, the denoised image will be re-processed using bilateral filter to improve the denoising performance and enhance the edge information. In the experiment, the proposed method is applied to eliminate both addictive noise and multiplicative noise, and the denoising results are compared with other representative methods, such as DTCWT, block-matching and 3D filtering (BM3D, median filter, wiener filter, wavelet decomposition filter (WDF and bilateral filter. Moreover, the proposed method is applied as pre-processing utilization for infrared thermal images in a coal mining working face.

  3. Potential density and tree survival: an analysis based on South ...

    African Journals Online (AJOL)

    Finally, we present a tree survival analysis, based on the Weibull distribution function, for the Nelshoogte replicated CCT study, which has been observed for almost 40 years after planting and provides information about tree survival in response to planting espacements ranging from 494 to 2 965 trees per hectare.

  4. Multiple hypothesis tracking based extraction of airway trees from CT data

    DEFF Research Database (Denmark)

    Raghavendra, Selvan; Petersen, Jens; de Bruijne, Marleen

    Segmentation of airway trees from CT scans of lungs has important clinical applications, in relation to the diagnosis of chronic obstructive pulmonary disease (COPD). Here we present a method based on multiple hypothesis tracking (MHT) and template matching, originally devised for vessel...... segmentation, to extract airway trees. Idealized tubular templates are constructed and ranked using scores assigned based on the image data. Several such regularly spaced hypotheses are used in constructing a hypothesis tree, which is then traversed to obtain improved segmentation results....

  5. Tree Canopy Light Interception Estimates in Almond and a Walnut Orchards Using Ground, Low Flying Aircraft, and Satellite Based Methods to Improve Irrigation Scheduling Programs (United States)

    Rosecrance, Richard C.; Johnson, Lee; Soderstrom, Dominic


    Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

  6. Real Time Animation of Trees Based on BBSC in Computer Games

    Directory of Open Access Journals (Sweden)

    Xuefeng Ao


    Full Text Available That researchers in the field of computer games usually find it is difficult to simulate the motion of actual 3D model trees lies in the fact that the tree model itself has very complicated structure, and many sophisticated factors need to be considered during the simulation. Though there are some works on simulating 3D tree and its motion, few of them are used in computer games due to the high demand for real-time in computer games. In this paper, an approach of animating trees in computer games based on a novel tree model representation—Ball B-Spline Curves (BBSCs are proposed. By taking advantage of the good features of the BBSC-based model, physical simulation of the motion of leafless trees with wind blowing becomes easier and more efficient. The method can generate realistic 3D tree animation in real-time, which meets the high requirement for real time in computer games.

  7. Randomized Ensemble Methods for Classification Trees

    National Research Council Canada - National Science Library

    Kobayashi, Izumi


    ... proportional to the measure of goodness for a split We combine this method with a stopping rule which uses permutation of the outputs The other method perturbs the output and constructs a classifier...

  8. Ship Engine Room Casualty Analysis by Using Decision Tree Method

    Directory of Open Access Journals (Sweden)

    Ömür Yaşar SAATÇİOĞLU


    Full Text Available Ships may encounter undesirable conditions during operations. In consequence of a casualty, fire, explosion, flooding, grounding, injury even death may occur. Besides, these results can be avoidable with precautions and preventive operating processes. In maritime transportation, casualties depend on various factors. These were listed as misuse of the engine equipment and tools, defective machinery or equipment, inadequacy of operational procedure and measure of safety and force majeure effects. Casualty reports which were published in Australia, New Zealand, United Kingdom, Canada and United States until 2015 were examined and the probable causes and consequences of casualties were determined with their occurrence percentages. In this study, 89 marine investigation reports regarding engine room casualties were analyzed. Casualty factors were analyzed with their frequency percentages and also their main causes were constructed. This study aims to investigate engine room based casualties, frequency of each casualty type and main causes by using decision tree method.

  9. Comparison of event tree, fault tree and Markov methods for probabilistic safety assessment and application to accident mitigation

    International Nuclear Information System (INIS)

    James, H.; Harris, M.J.; Hall, S.F.


    Probabilistic safety assessment (PSA) is used extensively in the nuclear industry. The main stages of PSA and the traditional event tree method are described. Focussing on hydrogen explosions, an event tree model is compared to a novel Markov model and a fault tree, and unexpected implication for accident mitigation is revealed. (author)

  10. [The Application of the Fault Tree Analysis Method in Medical Equipment Maintenance]. (United States)

    Liu, Hongbin


    In this paper, the traditional fault tree analysis method is presented, detailed instructions for its application characteristics in medical instrument maintenance is made. It is made significant changes when the traditional fault tree analysis method is introduced into the medical instrument maintenance: gave up the logic symbolic, logic analysis and calculation, gave up its complicated programs, and only keep its image and practical fault tree diagram, and the fault tree diagram there are also differences: the fault tree is no longer a logical tree but the thinking tree in troubleshooting, the definition of the fault tree's nodes is different, the composition of the fault tree's branches is also different.

  11. Does propagation method affect the field performance of peach trees?

    Directory of Open Access Journals (Sweden)

    André Luiz Kulkamp de Souza


    Full Text Available Worldwide, peach propagation has been performed mainly by grafting scions of desirable cultivars on rootstocks obtained from seeds. There are, however, other potential propagation methods not widely adopted due to the limited reports on the field performance of the resultant trees. This study addressed this knowledge gap and investigated the field performance of peach trees of the cultivar Maciel that were established in an orchard (5.0 m × 1.4 m spacing in 2011. The trees were trained in a "Y" system, with seedlings from three propagation techniques: 1 Conventional System (CS - vegetative bud grafting of the scion on the rootstock of the Okinawa cultivar obtained from seed; 2 Rootstock by Minicutting (RM - vegetative bud grafting of the scion on the rootstock of the Okinawa cultivar obtained by minicutting in a semi-hydroponic system; 3 Self-Rooting (SR - self-rooting of the scion in a semi-hydroponic system. The vegetative, productive, and fruit quality parameters were assessed during 2012 and 2013. The Maciel peach trees that were propagated by the SR technique were found to have similar or even superior field performance to those propagated by the CS. The RM propagation method was also found to be an important potential alternative to peach propagation, since this it combines two techniques (cutting and grafting to reduce tree vigor, especially if the goal is high-density planting.

  12. Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Weijia Li


    Full Text Available Oil palm trees are important economic crops in Malaysia and other tropical areas. The number of oil palm trees in a plantation area is important information for predicting the yield of palm oil, monitoring the growing situation of palm trees and maximizing their productivity, etc. In this paper, we propose a deep learning based framework for oil palm tree detection and counting using high-resolution remote sensing images for Malaysia. Unlike previous palm tree detection studies, the trees in our study area are more crowded and their crowns often overlap. We use a number of manually interpreted samples to train and optimize the convolutional neural network (CNN, and predict labels for all the samples in an image dataset collected through the sliding window technique. Then, we merge the predicted palm coordinates corresponding to the same palm tree into one palm coordinate and obtain the final palm tree detection results. Based on our proposed method, more than 96% of the oil palm trees in our study area can be detected correctly when compared with the manually interpreted ground truth, and this is higher than the accuracies of the other three tree detection methods used in this study.

  13. Market-based approaches to tree valuation (United States)

    Geoffrey H. Donovan; David T. Butry


    A recent four-part series in Arborist News outlined different appraisal processes used to value urban trees. The final article in the series described the three generally accepted approaches to tree valuation: the sales comparison approach, the cost approach, and the income capitalization approach. The author, D. Logan Nelson, noted that the sales comparison approach...

  14. Method for estimating potential tree-grade distributions for northeastern forest species (United States)

    Daniel A. Yaussy; Daniel A. Yaussy


    Generalized logistic regression was used to distribute trees into four potential tree grades for 20 northeastern species groups. The potential tree grade is defined as the tree grade based on the length and amount of clear cuttings and defects only, disregarding minimum grading diameter. The algorithms described use site index and tree diameter as the predictive...

  15. Utilising Tree-Based Ensemble Learning for Speaker Segmentation

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll


    for a certain condition, the model becomes biased to the data used for training limiting the model’s generalisation ability. In this paper, we propose a BIC-based tuning-free approach for speaker segmentation through the use of ensemble-based learning. A forest of segmentation trees is constructed in which each...... points. The proposed approach is tested on artificially created conversations from the TIMIT database. The approach proposed show very accurate results comparable to those achieved by the-state-of-the-art methods with a 9% (absolute) higher F 1 compared with the standard ΔBIC with optimally tuned penalty...

  16. Collaborative multi-agent reinforcement learning based on a novel coordination tree frame with dynamic partition

    NARCIS (Netherlands)

    Fang, M.; Groen, F.C.A.; Li, H.; Zhang, J.


    In the research of team Markov games, computing the coordinate team dynamically and determining the joint action policy are the main problems. To deal with the first problem, a dynamic team partitioning method is proposed based on a novel coordinate tree frame. We build a coordinate tree with

  17. Tree detection in urban regions from aerial imagery and DSM based on local maxima points (United States)

    Korkmaz, Özgür; Yardımcı ćetin, Yasemin; Yilmaz, Erdal


    In this study, we propose an automatic approach for tree detection and classification in registered 3-band aerial images and associated digital surface models (DSM). The tree detection results can be used in 3D city modelling and urban planning. This problem is magnified when trees are in close proximity to each other or other objects such as rooftops in the scenes. This study presents a method for locating individual trees and estimation of crown size based on local maxima from DSM accompanied by color and texture information. For this purpose, segment level classifier trained for 10 classes and classification results are improved by analyzing the class probabilities of neighbour segments. Later, the tree classes under a certain height were eliminated using the Digital Terrain Model (DTM). For the tree classes, local maxima points are obtained and the tree radius estimate is made from the vertical and horizontal height profiles passing through these points. The final tree list containing the centers and radius of the trees is obtained by selecting from the list of tree candidates according to the overlapping and selection parameters. Although the limited number of train sets are used in this study, tree classification and localization results are competitive.

  18. Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology. (United States)

    Beck, Kirk A.


    This article describes ethnographic decision tree modeling (EDTM; C. H. Gladwin, 1989) as a mixed method design appropriate for counseling psychology research. EDTM is introduced and located within a postpositivist research paradigm. Decision theory that informs EDTM is reviewed, and the 2 phases of EDTM are highlighted. The 1st phase, model…

  19. Extending the dormant bud cryopreservation method to new tree species (United States)

    In cryopreservation of germplasm, using dormant winter buds (DB) as source plant material is economically favorable over tissue culture options. Although the DB cryopreservation method has been known for many years, the approach is feasible only for cryopreserving a select number of temperate tree s...

  20. Modeling and Optimization of a Tree Based on Virtual Reality for Immersive Virtual Landscape Generation

    Directory of Open Access Journals (Sweden)

    Jinmo Kim


    Full Text Available This study proposes a modeling method that can effectively generate multiple diverse digital trees for creating immersive virtual landscape based on virtual reality and an optimization method for real-time rendering. The proposed method simplifies a process of procedures from growth of tree models to the generation of the three-dimensional branch geometric model. Here, the procedural branch graph (PBG algorithm is proposed, which simultaneously and effectively generates diverse trees that have a similar branch pattern. Moreover, the optimization method is designed in a polygon-based branch model which controls the resolution of tree models according to the distance from the camera to generate a tree model structure that is appropriate for an immersive system based on virtual reality. Finally, a virtual reality system is established based on the Oculus SDK (Software Development Kit and Unity3D engine. In this process, the image processing-based pixel to tree (PTT method is proposed as a technique for easily and efficiently generating a virtual landscape by allocating multiple trees on terrain. An immersive virtual landscape that has a stereoscopic perception and spatial impression is created through the proposed method and whether it can deliver experience of nature in virtual reality to the users was checked through an experiment.

  1. Application of Goal Tree-Success Tree model as the knowledge-base of operator advisory systems

    International Nuclear Information System (INIS)

    Kim, I.S.; Modarres, M.


    The most important portion of an expert system development is the articulation of knowledge by the expert and its satisfactory formulation in a suitable knowledge representation scheme for mechanization by a computer. A 'deep knowledge' approach called Goal Tree-Success Tree model is devised to represent complex dynamic domain knowledge. This approach can hierarchically model the underlying principles of a given process domain (for example nuclear power plant operations domain). The Goal Tree-Success Tree can then be used to represent the knowledge-base and provide means of selecting an efficient search routine in the inference engine of an expert system. A prototype expert system has been developed to demonstrate the method. This expert system models the operation of a typical system used in the pressurized water reactors. The expert system is modeled for real-time operations if an interface between plant parameters and the expert system is established. The real-time operation provides an ability to quickly remedy minor disturbances that can quickly lead to a system malfunction or trip. A description of both the Goal Tree-Success Tree model and the prototype expert system is presented. (orig.)

  2. Estimating uncertainty in respondent-driven sampling using a tree bootstrap method. (United States)

    Baraff, Aaron J; McCormick, Tyler H; Raftery, Adrian E


    Respondent-driven sampling (RDS) is a network-based form of chain-referral sampling used to estimate attributes of populations that are difficult to access using standard survey tools. Although it has grown quickly in popularity since its introduction, the statistical properties of RDS estimates remain elusive. In particular, the sampling variability of these estimates has been shown to be much higher than previously acknowledged, and even methods designed to account for RDS result in misleadingly narrow confidence intervals. In this paper, we introduce a tree bootstrap method for estimating uncertainty in RDS estimates based on resampling recruitment trees. We use simulations from known social networks to show that the tree bootstrap method not only outperforms existing methods but also captures the high variability of RDS, even in extreme cases with high design effects. We also apply the method to data from injecting drug users in Ukraine. Unlike other methods, the tree bootstrap depends only on the structure of the sampled recruitment trees, not on the attributes being measured on the respondents, so correlations between attributes can be estimated as well as variability. Our results suggest that it is possible to accurately assess the high level of uncertainty inherent in RDS.

  3. Semi-Automatic Anatomical Tree Matching for Landmark-Based Elastic Registration of Liver Volumes

    Directory of Open Access Journals (Sweden)

    Klaus Drechsler


    Full Text Available One promising approach to register liver volume acquisitions is based on the branching points of the vessel trees as anatomical landmarks inherently available in the liver. Automated tree matching algorithms were proposed to automatically find pair-wise correspondences between two vessel trees. However, to the best of our knowledge, none of the existing automatic methods are completely error free. After a review of current literature and methodologies on the topic, we propose an efficient interaction method that can be employed to support tree matching algorithms with important pre-selected correspondences or after an automatic matching to manually correct wrongly matched nodes. We used this method in combination with a promising automatic tree matching algorithm also presented in this work. The proposed method was evaluated by 4 participants and a CT dataset that we used to derive multiple artificial datasets.

  4. Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description

    Directory of Open Access Journals (Sweden)

    Jan Hackenberg


    Full Text Available This paper presents a method for fitting cylinders into a point cloud, derived from a terrestrial laser-scanned tree. Utilizing high scan quality data as the input, the resulting models describe the branching structure of the tree, capable of detecting branches with a diameter smaller than a centimeter. The cylinders are stored as a hierarchical tree-like data structure encapsulating parent-child neighbor relations and incorporating the tree’s direction of growth. This structure enables the efficient extraction of tree components, such as the stem or a single branch. The method was validated both by applying a comparison of the resulting cylinder models with ground truth data and by an analysis between the input point clouds and the models. Tree models were accomplished representing more than 99% of the input point cloud, with an average distance from the cylinder model to the point cloud within sub-millimeter accuracy. After validation, the method was applied to build two allometric models based on 24 tree point clouds as an example of the application. Computation terminated successfully within less than 30 min. For the model predicting the total above ground volume, the coefficient of determination was 0.965, showing the high potential of terrestrial laser-scanning for forest inventories.

  5. Indoor Positioning Using Nonparametric Belief Propagation Based on Spanning Trees

    Directory of Open Access Journals (Sweden)

    Savic Vladimir


    Full Text Available Nonparametric belief propagation (NBP is one of the best-known methods for cooperative localization in sensor networks. It is capable of providing information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST created by breadth first search (BFS method. In addition, we propose a reliable indoor model based on obtained measurements in our lab. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks. Furthermore, the computational and communication costs are nearly constant with respect to the transmission radius. However, the drawbacks of proposed method are a little bit higher computational cost and poor performance in low-connected networks.

  6. Improved Frame Mode Selection for AMR-WB+ Based on Decision Tree (United States)

    Kim, Jong Kyu; Kim, Nam Soo

    In this letter, we propose a coding mode selection method for the AMR-WB+ audio coder based on a decision tree. In order to reduce computation while maintaining good performance, decision tree classifier is adopted with the closed loop mode selection results as the target classification labels. The size of the decision tree is controlled by pruning, so the proposed method does not increase the memory requirement significantly. Through an evaluation test on a database covering both speech and music materials, the proposed method is found to achieve a much better mode selection accuracy compared with the open loop mode selection module in the AMR-WB+.

  7. Methods for acquisition, storage, and evaluation of leguminous tree germplasm

    Energy Technology Data Exchange (ETDEWEB)

    Felker, P.


    Simple methods for establishing, maintaining, and planting of a small scale tree legume (Prosopis) germplasm collection by one or two people are described. Suggestions are included for: developing an understanding of the worldwide distribution of genus; becoming acquainted with basic and applied scientists working on the taxa; devising seed cleaning, fumigation, cataloging, and storage techniques; requesting seed from international seed collections; collecting seed from native populations; and for field designs for planting the germplasm collection.

  8. Methods to overcome dormancy in tree tomato (Solanum betaceum seeds

    Directory of Open Access Journals (Sweden)

    Carlos Kosera Neto


    Full Text Available The tree tomato (Solanum betaceum is a poorly known species that has fruits with great economic potential, as it can be consumed in natura or industrialized. However, for reaching this potential, it is necessary the development of technologies for seedlings production. The propagation of this species is mainly done by seeds, but the seed germination process is usually slow, especially under stress conditions. This study aimed at verifying whether tree tomato seeds have dormancy and which is the best method to obtain fast and uniform germination. A completely randomized design was adopted in a 5 x 2 factorial arrangement (methods to overcome dormancy x light, with four replications of 50 or 60 seeds, depending on the production cycle. The methods tested were cold stratification, hydropriming, priming with GA3 solution and control, with or without light. Seed germination and germination rate index, as well as the beginning and average time of germination, were also evaluated. The use of GA3 at a concentration of 100 mg L-1 or 300 mg L-1 is recommended to the germination of tree tomato seeds.

  9. Numerical implementation of the loop-tree duality method

    Energy Technology Data Exchange (ETDEWEB)

    Buchta, Sebastian; Rodrigo, German [Universitat de Valencia-Consejo Superior de Investigaciones Cientificas, Parc Cientific, Instituto de Fisica Corpuscular, Valencia (Spain); Chachamis, Grigorios [Universidad Autonoma de Madrid, Instituto de Fisica Teorica UAM/CSIC, Madrid (Spain); Draggiotis, Petros [Institute of Nuclear and Particle Physics, NCSR ' ' Demokritos' ' , Agia Paraskevi (Greece)


    We present a first numerical implementation of the loop-tree duality (LTD) method for the direct numerical computation of multi-leg one-loop Feynman integrals. We discuss in detail the singular structure of the dual integrands and define a suitable contour deformation in the loop three-momentum space to carry out the numerical integration. Then we apply the LTD method to the computation of ultraviolet and infrared finite integrals, and we present explicit results for scalar and tensor integrals with up to eight external legs (octagons). The LTD method features an excellent performance independently of the number of external legs. (orig.)

  10. A Method to Quantify Plant Availability and Initiating Event Frequency Using a Large Event Tree, Small Fault Tree Model

    International Nuclear Information System (INIS)

    Kee, Ernest J.; Sun, Alice; Rodgers, Shawn; Popova, ElmiraV; Nelson, Paul; Moiseytseva, Vera; Wang, Eric


    South Texas Project uses a large fault tree to produce scenarios (minimal cut sets) used in quantification of plant availability and event frequency predictions. On the other hand, the South Texas Project probabilistic risk assessment model uses a large event tree, small fault tree for quantifying core damage and radioactive release frequency predictions. The South Texas Project is converting its availability and event frequency model to use a large event tree, small fault in an effort to streamline application support and to provide additional detail in results. The availability and event frequency model as well as the applications it supports (maintenance and operational risk management, system engineering health assessment, preventive maintenance optimization, and RIAM) are briefly described. A methodology to perform availability modeling in a large event tree, small fault tree framework is described in detail. How the methodology can be used to support South Texas Project maintenance and operations risk management is described in detail. Differences with other fault tree methods and other recently proposed methods are discussed in detail. While the methods described are novel to the South Texas Project Risk Management program and to large event tree, small fault tree models, concepts in the area of application support and availability modeling have wider applicability to the industry. (authors)

  11. TREAT (TREe-based Association Test) (United States)

    TREAT is an R package for detecting complex joint effects in case-control studies. The test statistic is derived from a tree-structure model by recursive partitioning the data. Ultra-fast algorithm is designed to evaluate the significance of association between candidate gene and disease outcome

  12. Credibilistic multi-period portfolio optimization based on scenario tree (United States)

    Mohebbi, Negin; Najafi, Amir Abbas


    In this paper, we consider a multi-period fuzzy portfolio optimization model with considering transaction costs and the possibility of risk-free investment. We formulate a bi-objective mean-VaR portfolio selection model based on the integration of fuzzy credibility theory and scenario tree in order to dealing with the markets uncertainty. The scenario tree is also a proper method for modeling multi-period portfolio problems since the length and continuity of their horizon. We take the return and risk as well cardinality, threshold, class, and liquidity constraints into consideration for further compliance of the model with reality. Then, an interactive dynamic programming method, which is based on a two-phase fuzzy interactive approach, is employed to solve the proposed model. In order to verify the proposed model, we present an empirical application in NYSE under different circumstances. The results show that the consideration of data uncertainty and other real-world assumptions lead to more practical and efficient solutions.

  13. An Efficient Method of Vibration Diagnostics For Rotating Machinery Using a Decision Tree

    Directory of Open Access Journals (Sweden)

    Bo Suk Yang


    Full Text Available This paper describes an efficient method to automatize vibration diagnosis for rotating machinery using a decision tree, which is applicable to vibration diagnosis expert system. Decision tree is a widely known formalism for expressing classification knowledge and has been used successfully in many diverse areas such as character recognition, medical diagnosis, and expert systems, etc. In order to build a decision tree for vibration diagnosis, we have to define classes and attributes. A set of cases based on past experiences is also needed. This training set is inducted using a result-cause matrix newly developed in the present work instead of using a conventionally implemented cause-result matrix. This method was applied to diagnostics for various cases taken from published work. It is found that the present method predicts causes of the abnormal vibration for test cases with high reliability.

  14. A method to study response of large trees to different amounts of available soil water (United States)

    D.H. Marx; Shi-Jean S. Sung; J.S. Cunningham; M.D. Thompson; L.M. White


    A method was developed to manipulate available soil water on large trees by intercepting thrufall with gutters placed under tree canopies and irrigating the intercepted thrufall onto other trees. With this design, trees were exposed for 2 years to either 25% less thrufall, normal thrufall, or 25% additional thrufall.Undercanopy construction in these plots moderately...

  15. Impacts of Tree Height-Dbh Allometry on Lidar-Based Tree Aboveground Biomass Modeling (United States)

    Fang, R.


    Lidar has been widely used in tree aboveground biomass (AGB) estimation at plot or stand levels. Lidar-based AGB models are usually constructed with the ground AGB reference as the response variable and lidar canopy indices as predictor variables. Tree diameter at breast height (dbh) is the major variable of most allometric models for estimating reference AGB. However, lidar measurements are mainly related to tree vertical structure. Therefore, tree height-dbh allometric model residuals are expected to have a large impact on lidar-based AGB model performance. This study attempts to investigate sensitivity of lidar-based AGB model to the decreasing strength of height-dbh relationship using a Monte Carlo simulation approach. Striking decrease in R2 and increase in relative RMSE were found in lidar-based AGB model, as the variance of height-dbh model residuals grew. I, therefore, concluded that individual tree height-dbh model residuals fundamentally introduce errors to lidar-AGB models.

  16. Fast decision tree-based method to index large DNA-protein sequence databases using hybrid distributed-shared memory programming model. (United States)

    Jaber, Khalid Mohammad; Abdullah, Rosni; Rashid, Nur'Aini Abdul


    In recent times, the size of biological databases has increased significantly, with the continuous growth in the number of users and rate of queries; such that some databases have reached the terabyte size. There is therefore, the increasing need to access databases at the fastest rates possible. In this paper, the decision tree indexing model (PDTIM) was parallelised, using a hybrid of distributed and shared memory on resident database; with horizontal and vertical growth through Message Passing Interface (MPI) and POSIX Thread (PThread), to accelerate the index building time. The PDTIM was implemented using 1, 2, 4 and 5 processors on 1, 2, 3 and 4 threads respectively. The results show that the hybrid technique improved the speedup, compared to a sequential version. It could be concluded from results that the proposed PDTIM is appropriate for large data sets, in terms of index building time.

  17. Task-Management Method Using R-Tree Spatial Cloaking for Large-Scale Crowdsourcing

    Directory of Open Access Journals (Sweden)

    Yan Li


    Full Text Available With the development of sensor technology and the popularization of the data-driven service paradigm, spatial crowdsourcing systems have become an important way of collecting map-based location data. However, large-scale task management and location privacy are important factors for participants in spatial crowdsourcing. In this paper, we propose the use of an R-tree spatial cloaking-based task-assignment method for large-scale spatial crowdsourcing. We use an estimated R-tree based on the requested crowdsourcing tasks to reduce the crowdsourcing server-side inserting cost and enable the scalability. By using Minimum Bounding Rectangle (MBR-based spatial anonymous data without exact position data, this method preserves the location privacy of participants in a simple way. In our experiment, we showed that our proposed method is faster than the current method, and is very efficient when the scale is increased.

  18. Methods for estimating aboveground biomass and its components for Douglas-fir and lodgepole pine trees (United States)

    K.P. Poudel; H. Temesgen


    Estimating aboveground biomass and its components requires sound statistical formulation and evaluation. Using data collected from 55 destructively sampled trees in different parts of Oregon, we evaluated the performance of three groups of methods to estimate total aboveground biomass and (or) its components based on the bias and root mean squared error (RMSE) that...

  19. Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches

    Directory of Open Access Journals (Sweden)

    Maggi Kelly


    Full Text Available Light detection and ranging (lidar data is increasingly being used for ecosystem monitoring across geographic scales. This work concentrates on delineating individual trees in topographically-complex, mixed conifer forest across the California’s Sierra Nevada. We delineated individual trees using vector data and a 3D lidar point cloud segmentation algorithm, and using raster data with an object-based image analysis (OBIA of a canopy height model (CHM. The two approaches are compared to each other and to ground reference data. We used high density (9 pulses/m2, discreet lidar data and WorldView-2 imagery to delineate individual trees, and to classify them by species or species types. We also identified a new method to correct artifacts in a high-resolution CHM. Our main focus was to determine the difference between the two types of approaches and to identify the one that produces more realistic results. We compared the delineations via tree detection, tree heights, and the shape of the generated polygons. The tree height agreement was high between the two approaches and the ground data (r2: 0.93–0.96. Tree detection rates increased for more dominant trees (8–100 percent. The two approaches delineated tree boundaries that differed in shape: the lidar-approach produced fewer, more complex, and larger polygons that more closely resembled real forest structure.

  20. Weighted bootstrapping: a correction method for assessing the robustness of phylogenetic trees

    Directory of Open Access Journals (Sweden)

    Makarenkov Vladimir


    Full Text Available Abstract Background Non-parametric bootstrapping is a widely-used statistical procedure for assessing confidence of model parameters based on the empirical distribution of the observed data 1 and, as such, it has become a common method for assessing tree confidence in phylogenetics 2. Traditional non-parametric bootstrapping does not weigh each tree inferred from resampled (i.e., pseudo-replicated sequences. Hence, the quality of these trees is not taken into account when computing bootstrap scores associated with the clades of the original phylogeny. As a consequence, traditionally, the trees with different bootstrap support or those providing a different fit to the corresponding pseudo-replicated sequences (the fit quality can be expressed through the LS, ML or parsimony score contribute in the same way to the computation of the bootstrap support of the original phylogeny. Results In this article, we discuss the idea of applying weighted bootstrapping to phylogenetic reconstruction by weighting each phylogeny inferred from resampled sequences. Tree weights can be based either on the least-squares (LS tree estimate or on the average secondary bootstrap score (SBS associated with each resampled tree. Secondary bootstrapping consists of the estimation of bootstrap scores of the trees inferred from resampled data. The LS and SBS-based bootstrapping procedures were designed to take into account the quality of each "pseudo-replicated" phylogeny in the final tree estimation. A simulation study was carried out to evaluate the performances of the five weighting strategies which are as follows: LS and SBS-based bootstrapping, LS and SBS-based bootstrapping with data normalization and the traditional unweighted bootstrapping. Conclusions The simulations conducted with two real data sets and the five weighting strategies suggest that the SBS-based bootstrapping with the data normalization usually exhibits larger bootstrap scores and a higher robustness

  1. Bootstrap method of interior-branch test for phylogenetic trees. (United States)

    Sitnikova, T


    Statistical properties of the bootstrap test of interior branch lengths of phylogenetic trees have been studied and compared with those of the standard interior-branch test in computer simulations. Examination of the properties of the tests under the null hypothesis showed that both tests for an interior branch of a predetermined topology are quite reliable when the distribution of the branch length estimate approaches a normal distribution. Unlike the standard interior-branch test, the bootstrap test appears to retain this property even when the substitution rate varies among sites. In this case, the distribution of the branch length estimate deviates from a normal distribution, and the standard interior-branch test gives conservative confidence probability values. A simple correction method was developed for both interior-branch tests to be applied for testing the reliability of tree topologies estimated from sequence data. This correction for the standard interior-branch test appears to be as effective as that obtained in our previous study, though it is much simpler. The bootstrap and standard interior-branch tests for estimated topologies become conservative as the number of sequence groups in a star-like tree increases.

  2. Quantifying human and organizational factors in accident management using decision trees: the HORAAM method

    Energy Technology Data Exchange (ETDEWEB)

    Baumont, G.; Menage, F.; Schneiter, J.R.; Spurgin, A.; Vogel, A


    In the framework of the level 2 Probabilistic Safety Study (PSA 2) project, the Institute for Nuclear Safety and Protection (IPSN) has developed a method for taking into account Human and Organizational Reliability Aspects during accident management. Actions are taken during very degraded installation operations by teams of experts in the French framework of Crisis Organization (ONC). After describing the background of the framework of the Level 2 PSA, the French specific Crisis Organization and the characteristics of human actions in the Accident Progression Event Tree, this paper describes the method developed to introduce in PSA the Human and Organizational Reliability Analysis in Accident Management (HORAAM). This method is based on the Decision Tree method and has gone through a number of steps in its development. The first one was the observation of crisis center exercises, in order to identify the main influence factors (IFs) which affect human and organizational reliability. These IFs were used as headings in the Decision Tree method. Expert judgment was used in order to verify the IFs, to rank them, and to estimate the value of the aggregated factors to simplify the quantification of the tree. A tool based on Mathematica was developed to increase the flexibility and the efficiency of the study.

  3. [Research on living tree volume forecast based on PSO embedding SVM]. (United States)

    Jiao, You-Quan; Feng, Zhong-Ke; Zhao, Li-Xi; Xu, Wei-Heng; Cao, Zhong


    In order to establish volume model,living trees have to be fallen and be divided into many sections, which is a kind of destructive experiment. So hundreds of thousands of trees have been fallen down each year in China. To solve this problem, a new method called living tree volume accurate measurement without falling tree was proposed in the present paper. In the method, new measuring methods and calculation ways are used by using photoelectric theodolite and auxiliary artificial measurement. The diameter at breast height and diameter at ground was measured manually, and diameters at other heights were obtained by photoelectric theodolite. Tree volume and height of each tree was calculated by a special software that was programmed by the authors. Zhonglin aspens No. 107 were selected as experiment object, and 400 data records were obtained. Based on these data, a nonlinear intelligent living tree volume prediction model with Particle Swarm Optimization algorithm based on support vector machines (PSO-SVM) was established. Three hundred data records including tree height and diameter at breast height were randomly selected form a total of 400 data records as input data, tree volume as output data, using PSO-SVM tool box of Matlab7.11, thus a tree volume model was obtained. One hundred data records were used to test the volume model. The results show that the complex correlation coefficient (R2) between predicted and measured values is 0. 91, which is 2% higher than the value calculated by classic Spurr binary volume model, and the mean absolute error rates were reduced by 0.44%. Compared with Spurr binary volume model, PSO-SVM model has self-learning and self-adaption ability,moreover, with the characteristics of high prediction accuracy, fast learning speed,and a small sample size requirement, PSO-SVM model with well prospect is worth popularization and application.


    Directory of Open Access Journals (Sweden)

    K. T. Chang


    Full Text Available Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs. The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM from a digital surface model (DSM, and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC and a variable window filter (VWF, are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits" that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

  5. Species-Level Differences in Hyperspectral Metrics among Tropical Rainforest Trees as Determined by a Tree-Based Classifier

    Directory of Open Access Journals (Sweden)

    Dar A. Roberts


    Full Text Available This study explores a method to classify seven tropical rainforest tree species from full-range (400–2,500 nm hyperspectral data acquired at tissue (leaf and bark, pixel and crown scales using laboratory and airborne sensors. Metrics that respond to vegetation chemistry and structure were derived using narrowband indices, derivative- and absorption-based techniques, and spectral mixture analysis. We then used the Random Forests tree-based classifier to discriminate species with minimally-correlated, importance-ranked metrics. At all scales, best overall accuracies were achieved with metrics derived from all four techniques and that targeted chemical and structural properties across the visible to shortwave infrared spectrum (400–2500 nm. For tissue spectra, overall accuracies were 86.8% for leaves, 74.2% for bark, and 84.9% for leaves plus bark. Variation in tissue metrics was best explained by an axis of red absorption related to photosynthetic leaves and an axis distinguishing bark water and other chemical absorption features. Overall accuracies for individual tree crowns were 71.5% for pixel spectra, 70.6% crown-mean spectra, and 87.4% for a pixel-majority technique. At pixel and crown scales, tree structure and phenology at the time of image acquisition were important factors that determined species spectral separability.

  6. Community Phylogenetics: Assessing Tree Reconstruction Methods and the Utility of DNA Barcodes (United States)

    Boyle, Elizabeth E.; Adamowicz, Sarah J.


    Studies examining phylogenetic community structure have become increasingly prevalent, yet little attention has been given to the influence of the input phylogeny on metrics that describe phylogenetic patterns of co-occurrence. Here, we examine the influence of branch length, tree reconstruction method, and amount of sequence data on measures of phylogenetic community structure, as well as the phylogenetic signal (Pagel’s λ) in morphological traits, using Trichoptera larval communities from Churchill, Manitoba, Canada. We find that model-based tree reconstruction methods and the use of a backbone family-level phylogeny improve estimations of phylogenetic community structure. In addition, trees built using the barcode region of cytochrome c oxidase subunit I (COI) alone accurately predict metrics of phylogenetic community structure obtained from a multi-gene phylogeny. Input tree did not alter overall conclusions drawn for phylogenetic signal, as significant phylogenetic structure was detected in two body size traits across input trees. As the discipline of community phylogenetics continues to expand, it is important to investigate the best approaches to accurately estimate patterns. Our results suggest that emerging large datasets of DNA barcode sequences provide a vast resource for studying the structure of biological communities. PMID:26110886

  7. VMCast: A VM-Assisted Stability Enhancing Solution for Tree-Based Overlay Multicast.

    Directory of Open Access Journals (Sweden)

    Weidong Gu

    Full Text Available Tree-based overlay multicast is an effective group communication method for media streaming applications. However, a group member's departure causes all of its descendants to be disconnected from the multicast tree for some time, which results in poor performance. The above problem is difficult to be addressed because overlay multicast tree is intrinsically instable. In this paper, we proposed a novel stability enhancing solution, VMCast, for tree-based overlay multicast. This solution uses two types of on-demand cloud virtual machines (VMs, i.e., multicast VMs (MVMs and compensation VMs (CVMs. MVMs are used to disseminate the multicast data, whereas CVMs are used to offer streaming compensation. The used VMs in the same cloud datacenter constitute a VM cluster. Each VM cluster is responsible for a service domain (VMSD, and each group member belongs to a specific VMSD. The data source delivers the multicast data to MVMs through a reliable path, and MVMs further disseminate the data to group members along domain overlay multicast trees. The above approach structurally improves the stability of the overlay multicast tree. We further utilized CVM-based streaming compensation to enhance the stability of the data distribution in the VMSDs. VMCast can be used as an extension to existing tree-based overlay multicast solutions, to provide better services for media streaming applications. We applied VMCast to two application instances (i.e., HMTP and HCcast. The results show that it can obviously enhance the stability of the data distribution.

  8. VMCast: A VM-Assisted Stability Enhancing Solution for Tree-Based Overlay Multicast. (United States)

    Gu, Weidong; Zhang, Xinchang; Gong, Bin; Zhang, Wei; Wang, Lu


    Tree-based overlay multicast is an effective group communication method for media streaming applications. However, a group member's departure causes all of its descendants to be disconnected from the multicast tree for some time, which results in poor performance. The above problem is difficult to be addressed because overlay multicast tree is intrinsically instable. In this paper, we proposed a novel stability enhancing solution, VMCast, for tree-based overlay multicast. This solution uses two types of on-demand cloud virtual machines (VMs), i.e., multicast VMs (MVMs) and compensation VMs (CVMs). MVMs are used to disseminate the multicast data, whereas CVMs are used to offer streaming compensation. The used VMs in the same cloud datacenter constitute a VM cluster. Each VM cluster is responsible for a service domain (VMSD), and each group member belongs to a specific VMSD. The data source delivers the multicast data to MVMs through a reliable path, and MVMs further disseminate the data to group members along domain overlay multicast trees. The above approach structurally improves the stability of the overlay multicast tree. We further utilized CVM-based streaming compensation to enhance the stability of the data distribution in the VMSDs. VMCast can be used as an extension to existing tree-based overlay multicast solutions, to provide better services for media streaming applications. We applied VMCast to two application instances (i.e., HMTP and HCcast). The results show that it can obviously enhance the stability of the data distribution.

  9. Construction of a phylogenetic tree of photosynthetic prokaryotes based on average similarities of whole genome sequences.

    Directory of Open Access Journals (Sweden)

    Soichirou Satoh

    Full Text Available Phylogenetic trees have been constructed for a wide range of organisms using gene sequence information, especially through the identification of orthologous genes that have been vertically inherited. The number of available complete genome sequences is rapidly increasing, and many tools for construction of genome trees based on whole genome sequences have been proposed. However, development of a reasonable method of using complete genome sequences for construction of phylogenetic trees has not been established. We have developed a method for construction of phylogenetic trees based on the average sequence similarities of whole genome sequences. We used this method to examine the phylogeny of 115 photosynthetic prokaryotes, i.e., cyanobacteria, Chlorobi, proteobacteria, Chloroflexi, Firmicutes and nonphotosynthetic organisms including Archaea. Although the bootstrap values for the branching order of phyla were low, probably due to lateral gene transfer and saturated mutation, the obtained tree was largely consistent with the previously reported phylogenetic trees, indicating that this method is a robust alternative to traditional phylogenetic methods.

  10. Topologies of the conditional ancestral trees and full-likelihood-based inference in the general coalescent tree framework. (United States)

    Sargsyan, Ori


    The general coalescent tree framework is a family of models for determining ancestries among random samples of DNA sequences at a nonrecombining locus. The ancestral models included in this framework can be derived under various evolutionary scenarios. Here, a computationally tractable full-likelihood-based inference method for neutral polymorphisms is presented, using the general coalescent tree framework and the infinite-sites model for mutations in DNA sequences. First, an exact sampling scheme is developed to determine the topologies of conditional ancestral trees. However, this scheme has some computational limitations and to overcome these limitations a second scheme based on importance sampling is provided. Next, these schemes are combined with Monte Carlo integrations to estimate the likelihood of full polymorphism data, the ages of mutations in the sample, and the time of the most recent common ancestor. In addition, this article shows how to apply this method for estimating the likelihood of neutral polymorphism data in a sample of DNA sequences completely linked to a mutant allele of interest. This method is illustrated using the data in a sample of DNA sequences at the APOE gene locus.

  11. Exploring trees in three dimensions: VoxR, a novel voxel-based R package dedicated to analysing the complex arrangement of tree crowns. (United States)

    Lecigne, Bastien; Delagrange, Sylvain; Messier, Christian


    Interest in tree form assessments using the terrestrial laser scanner (TLS) has increased in recent years. Yet many existing methods are limited to small-sized trees, principally due to noise and occlusion phenomena. In this paper, a novel voxel-based program that is dedicated to the analyses of large tree structures is presented. The method is based on the assumption that architectural trait variations (i.e. branching angle, bifurcation ratio, biomass allocation, etc.) influence the way a tree explores space. This method uses the concept of space exploration that considers a voxel as a portion of space explored by the tree. Once the TLS scene is voxelized, the program provides tools that extract qualitative (geometrical) and quantitative (volumetric) metrics. These tools measure (1) voxel dispersion in three dimensions (3-D), (2) projections of the voxel cloud in 2-D and (3) multi-temporal changes within a single tree crown. To test algorithm capabilities of measuring larger tree architectural traits, two application studies were conducted using point clouds that were either generated by a tree growth simulation model, thereby allowing algorithm application in a perfectly controlled environment, or acquired in the field with a TLS device. The space exploration concept makes it possible to take advantage of the volumetric nature of voxels to compensate for occlusion. The hypothesis that large-sized voxels can be used to reduce occlusion in the original point cloud was tested, as well as the consequences of voxel size on quantification of tree volume and on precision of derived metrics. Results show that space exploration is well adapted to highlight architectural differences among trees. They also suggest that large-sized voxels are efficient for occlusion compensation at the expense of metrics precision in some cases. The best resolution to choose depending on the research objectives and quality of the TLS scan is discussed.

  12. TreePM Method for Two-Dimensional Cosmological Simulations ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    of the 2d TreePM code. In a 2d Tree code the simulation area is taken to be a square. If this were to represent the stem of a tree, then it will be subdivided at each stage into smaller squares (branches) till we reach the particles (leaves). To construct the tree we add particles to the simulation area and subdivide any cell that ...

  13. Tree stability under wind: simulating uprooting with root breakage using a finite element method. (United States)

    Yang, Ming; Défossez, Pauline; Danjon, Frédéric; Fourcaud, Thierry


    Windstorms are the major natural hazard affecting European forests, causing tree damage and timber losses. Modelling tree anchorage mechanisms has progressed with advances in plant architectural modelling, but it is still limited in terms of estimation of anchorage strength. This paper aims to provide a new model for root anchorage, including the successive breakage of roots during uprooting. The model was based on the finite element method. The breakage of individual roots was taken into account using a failure law derived from previous work carried out on fibre metal laminates. Soil mechanical plasticity was considered using the Mohr-Coulomb failure criterion. The mechanical model for roots was implemented in the numerical code ABAQUS using beam elements embedded in a soil block meshed with 3-D solid elements. The model was tested by simulating tree-pulling experiments previously carried out on a tree of Pinus pinaster (maritime pine). Soil mechanical parameters were obtained from laboratory tests. Root system architecture was digitized and imported into ABAQUS while root material properties were estimated from the literature. Numerical simulations of tree-pulling tests exhibited realistic successive root breakages during uprooting, which could be seen in the resulting response curves. Broken roots could be visually located within the root system at any stage of the simulations. The model allowed estimation of anchorage strength in terms of the critical turning moment and accumulated energy, which were in good agreement with in situ measurements. This study provides the first model of tree anchorage strength for P. pinaster derived from the mechanical strength of individual roots. The generic nature of the model permits its further application to other tree species and soil conditions.

  14. The hydrological vulnerability of western North American boreal tree species based on ground-based observations of tree mortality (United States)

    Hember, R. A.; Kurz, W. A.; Coops, N. C.


    Several studies indicate that climate change has increased rates of tree mortality, adversely affecting timber supply and carbon storage in western North American boreal forests. Statistical models of tree mortality can play a complimentary role in detecting and diagnosing forest change. Yet, such models struggle to address real-world complexity, including expectations that hydrological vulnerability arises from both drought stress and excess-water stress, and that these effects vary by species, tree size, and competitive status. Here, we describe models that predict annual probability of tree mortality (Pm) of common boreal tree species based on tree height (H), biomass of larger trees (BLT), soil water content (W), reference evapotranspiration (E), and two-way interactions. We show that interactions among H and hydrological variables are consistently significant. Vulnerability to extreme droughts consistently increases as H approaches maximum observed values of each species, while some species additionally show increasing vulnerability at low H. Some species additionally show increasing vulnerability to low W under high BLT, or increasing drought vulnerability under low BLT. These results suggest that vulnerability of trees to increasingly severe droughts depends on the hydraulic efficiency, competitive status, and microclimate of individual trees. Static simulations of Pm across a 1-km grid (i.e., with time-independent inputs of H, BLT, and species composition) indicate complex spatial patterns in the time trends during 1965-2014 and a mean change in Pm of 42 %. Lastly, we discuss how the size-dependence of hydrological vulnerability, in concert with increasingly severe drought events, may shape future responses of stand-level biomass production to continued warming and increasing carbon dioxide concentration in the region.

  15. Uav-Based Automatic Tree Growth Measurement for Biomass Estimation (United States)

    Karpina, M.; Jarząbek-Rychard, M.; Tymków, P.; Borkowski, A.


    Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

  16. A LIDAR-Based Tree Canopy Characterization under Simulated Uneven Road Condition: Advance in Tree Orchard Canopy Profile Measurement

    Directory of Open Access Journals (Sweden)

    Yue Shen


    Full Text Available In real outdoor canopy profile detection, the accuracy of a LIDAR scanner to measure canopy structure is affected by a potentially uneven road condition. The level of error associated with attitude angles from undulations in the ground surface can be reduced by developing appropriate correction algorithm. This paper proposes an offline attitude angle offset correction algorithm based on a 3D affine coordinate transformation. The validity of the correction algorithm is verified by conducting an indoor experiment. The experiment was conducted on an especially designed canopy profile measurement platform. During the experiment, an artificial tree and a tree-shaped carved board were continuously scanned at constant laser scanner travel speed and detection distances under simulated bumpy road conditions. Acquired LIDAR laser scanner raw data was processed offline by exceptionally developed MATLAB program. The obtained results before and after correction method show that the single attitude angle offset correction method is able to correct the distorted data points in tree-shaped carved board profile measurement, with a relative error of 5%, while the compound attitude angle offset correction method is effective to reduce the error associated with compound attitude angle deviation from the ideal scanner pose, with relative error of 7%.

  17. Estimating species trees from unrooted gene trees. (United States)

    Liu, Liang; Yu, Lili


    In this study, we develop a distance method for inferring unrooted species trees from a collection of unrooted gene trees. The species tree is estimated by the neighbor joining (NJ) tree built from a distance matrix in which the distance between two species is defined as the average number of internodes between two species across gene trees, that is, average gene-tree internode distance. The distance method is named NJ(st) to distinguish it from the original NJ method. Under the coalescent model, we show that if gene trees are known or estimated correctly, the NJ(st) method is statistically consistent in estimating unrooted species trees. The simulation results suggest that NJ(st) and STAR (another coalescence-based method for inferring species trees) perform almost equally well in estimating topologies of species trees, whereas the Bayesian coalescence-based method, BEST, outperforms both NJ(st) and STAR. Unlike BEST and STAR, the NJ(st) method can take unrooted gene trees to infer species trees without using an outgroup. In addition, the NJ(st) method can handle missing data and is thus useful in phylogenomic studies in which data sets often contain missing loci for some individuals.

  18. Assessing statistical reliability of phylogenetic trees via a speedy double bootstrap method. (United States)

    Ren, Aizhen; Ishida, Takashi; Akiyama, Yutaka


    Evaluating the reliability of estimated phylogenetic trees is of critical importance in the field of molecular phylogenetics, and for other endeavors that depend on accurate phylogenetic reconstruction. The bootstrap method is a well-known computational approach to phylogenetic tree assessment, and more generally for assessing the reliability of statistical models. However, it is known to be biased under certain circumstances, calling into question the accuracy of the method. Several advanced bootstrap methods have been developed to achieve higher accuracy, one of which is the double bootstrap approach, but the computational burden of this method has precluded its application to practical problems of phylogenetic tree selection. We address this issue by proposing a simple method called the speedy double bootstrap, which circumvents the second-tier resampling step in the regular double bootstrap approach. We also develop an implementation of the regular double bootstrap for comparison with our speedy method. The speedy double bootstrap suffers no significant loss of accuracy compared with the regular double bootstrap, while performing calculations significantly more rapidly (at minimum around 371 times faster, based on analysis of mammalian mitochondrial amino acid sequences and 12S and 16S rRNA genes). Our method thus enables, for the first time, the practical application of the double bootstrap technique in the context of molecular phylogenetics. The approach can also be used more generally for model selection problems wherever the maximum likelihood criterion is used. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Socioeconomic determinants of menarche in rural Polish girls using the decision trees method. (United States)

    Matusik, Stanisław; Laska-Mierzejewska, Teresa; Chrzanowska, Maria


    The aim of this study was to assess the usefulness of the decision trees method as a research method of multidimensional associations between menarche and socioeconomic variables. The article is based on data collected from the rural area of Choszczno in the West Pomerania district of Poland between 1987 and 2001. Girls were asked about the appearance of first menstruation (a yes/no method). The average menarchal age was estimated by the probit analysis method, using second grade polynomials. The socioeconomic status of the girls' families was determined using five qualitative variables: fathers' and mothers' educational level, source of income, household appliances and the number of children in a family. For classification based on five socioeconomic variables, one of the most effective algorithms CART (Classification and Regression Trees) was used. In 2001 the menarchal age in 66% of examined girls was properly classified, while a higher efficiency of 70% was obtained for girls examined in 1987. The decision trees method enabled the definition of the hierarchy of socioeconomic variables influencing girls' biological development level. The strongest discriminatory power was attributed to the number of children in a family, and the mother's and then father's educational level. Using this method it is possible to detect differences in strength of socioeconomic variables associated with girls' pubescence before 1987 and after 2001 during the transformation of the economic and political systems in Poland. However, the decision trees method is infrequently applied in social sciences and constitutes a novelty; this article proves its usefulness in examining relations between biological processes and a population's living conditions.

  20. Practical optimization of Steiner trees via the cavity method (United States)

    Braunstein, Alfredo; Muntoni, Anna


    The optimization version of the cavity method for single instances, called Max-Sum, has been applied in the past to the minimum Steiner tree problem on graphs and variants. Max-Sum has been shown experimentally to give asymptotically optimal results on certain types of weighted random graphs, and to give good solutions in short computation times for some types of real networks. However, the hypotheses behind the formulation and the cavity method itself limit substantially the class of instances on which the approach gives good results (or even converges). Moreover, in the standard model formulation, the diameter of the tree solution is limited by a predefined bound, that affects both computation time and convergence properties. In this work we describe two main enhancements to the Max-Sum equations to be able to cope with optimization of real-world instances. First, we develop an alternative ‘flat’ model formulation that allows the relevant configuration space to be reduced substantially, making the approach feasible on instances with large solution diameter, in particular when the number of terminal nodes is small. Second, we propose an integration between Max-Sum and three greedy heuristics. This integration allows Max-Sum to be transformed into a highly competitive self-contained algorithm, in which a feasible solution is given at each step of the iterative procedure. Part of this development participated in the 2014 DIMACS Challenge on Steiner problems, and we report the results here. The performance on the challenge of the proposed approach was highly satisfactory: it maintained a small gap to the best bound in most cases, and obtained the best results on several instances in two different categories. We also present several improvements with respect to the version of the algorithm that participated in the competition, including new best solutions for some of the instances of the challenge.

  1. A single-probe heat pulse method for estimating sap velocity in trees. (United States)

    López-Bernal, Álvaro; Testi, Luca; Villalobos, Francisco J


    Available sap flow methods are still far from being simple, cheap and reliable enough to be used beyond very specific research purposes. This study presents and tests a new single-probe heat pulse (SPHP) method for monitoring sap velocity in trees using a single-probe sensor, rather than the multi-probe arrangements used up to now. Based on the fundamental conduction-convection principles of heat transport in sapwood, convective velocity (V h ) is estimated from the temperature increase in the heater after the application of a heat pulse (ΔT). The method was validated against measurements performed with the compensation heat pulse (CHP) technique in field trees of six different species. To do so, a dedicated three-probe sensor capable of simultaneously applying both methods was produced and used. Experimental measurements in the six species showed an excellent agreement between SPHP and CHP outputs for moderate to high flow rates, confirming the applicability of the method. In relation to other sap flow methods, SPHP presents several significant advantages: it requires low power inputs, it uses technically simpler and potentially cheaper instrumentation, the physical damage to the tree is minimal and artefacts caused by incorrect probe spacing and alignment are removed. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  2. Predicting metabolic syndrome using decision tree and support vector machine methods. (United States)

    Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh


    Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According

  3. Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

    Directory of Open Access Journals (Sweden)

    Esther I. Metting


    Full Text Available The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215. Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%. Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool.

  4. Applying of whole-tree harvesting method; Kokopuujuontomenetelmaen soveltaminen aines- ja energiapuun hankintaan

    Energy Technology Data Exchange (ETDEWEB)

    Vesisenaho, T. [VTT Energy, Jyvaeskylae (Finland); Liukkonen, S. [VTT Manufacturing Technology, Espoo (Finland)


    The objective of this project is to apply whole-tree harvesting method to Finnish timber harvesting conditions in order to lower the harvesting costs of energy wood and timber in spruce-dominant final cuttings. In Finnish conditions timber harvesting is normally based on the log-length method. Because of small landings and the high level of thinning cuttings, whole-tree skidding methods cannot be utilised extensively. The share of stands which could be harvested with whole-tree skidding method showed up to be about 10 % of the total harvesting amount of 50 mill. m{sup 3}. The corresponding harvesting potential of energy wood is 0,25 Mtoe. The aim of the structural measurements made in this project was to get information about the effect of different hauling methods into the structural response of the tractor, and thus reveal the possible special requirements that the new whole-tree skidding places forest tractor design. Altogether 7 strain gauge based sensors were mounted into the rear frame structures and drive shafts of the forest tractor. Five strain gauges measured local strains in some critical details and two sensors measured the torque moments of the front and rear bogie drive shafts. Also the revolution speed of the rear drive shaft was recorded. Signal time histories, maximum peaks, Time at Level distributions and Rainflow distributions were gathered in different hauling modes. From these, maximum values, average stress levels and fatigue life estimates were calculated for each mode, and a comparison of the different methods from the structural point of view was performed

  5. Extensions and applications of ensemble-of-trees methods in machine learning (United States)

    Bleich, Justin

    Ensemble-of-trees algorithms have emerged to the forefront of machine learning due to their ability to generate high forecasting accuracy for a wide array of regression and classification problems. Classic ensemble methodologies such as random forests (RF) and stochastic gradient boosting (SGB) rely on algorithmic procedures to generate fits to data. In contrast, more recent ensemble techniques such as Bayesian Additive Regression Trees (BART) and Dynamic Trees (DT) focus on an underlying Bayesian probability model to generate the fits. These new probability model-based approaches show much promise versus their algorithmic counterparts, but also offer substantial room for improvement. The first part of this thesis focuses on methodological advances for ensemble-of-trees techniques with an emphasis on the more recent Bayesian approaches. In particular, we focus on extensions of BART in four distinct ways. First, we develop a more robust implementation of BART for both research and application. We then develop a principled approach to variable selection for BART as well as the ability to naturally incorporate prior information on important covariates into the algorithm. Next, we propose a method for handling missing data that relies on the recursive structure of decision trees and does not require imputation. Last, we relax the assumption of homoskedasticity in the BART model to allow for parametric modeling of heteroskedasticity. The second part of this thesis returns to the classic algorithmic approaches in the context of classification problems with asymmetric costs of forecasting errors. First we consider the performance of RF and SGB more broadly and demonstrate its superiority to logistic regression for applications in criminology with asymmetric costs. Next, we use RF to forecast unplanned hospital readmissions upon patient discharge with asymmetric costs taken into account. Finally, we explore the construction of stable decision trees for forecasts of

  6. Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis. (United States)

    Panje, Cédric M; Glatzer, Markus; von Rappard, Joscha; Rothermundt, Christian; Hundsberger, Thomas; Zumstein, Valentin; Plasswilm, Ludwig; Putora, Paul Martin


    The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously. Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators. The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis. This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.

  7. The propagation-weighted priority immunization strategy based on propagation tree

    International Nuclear Information System (INIS)

    Nian, Fuzhong; Ren, Song; Dang, Zhongkai


    In this paper, we constructed the virus propagation tree for any infected node through improving the k-shell decomposition method. Supposing we determine the position of infected nodes, the root node of the propagation tree is an infected node and its children nodes are susceptible nodes. The virus can be diffused from the bottom to top along with the tree. Based on the analysis of the virus propagation tree, a propagation-weighted priority immunization strategy was proposed to vaccinate the influential nodes(the nodes are the several nodes of the most risky in the high-risk node and it is convenient for us to immune). The mathematical proof and the computer simulation on scale-free network are given. The results show that the propagation-weighted priority immunization is effective to prevent the virus from diffusing.

  8. Discrete Discriminant analysis based on tree-structured graphical models

    DEFF Research Database (Denmark)

    Perez de la Cruz, Gonzalo; Eslava, Guillermina

    The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...

  9. Methods of fault tree analysis and their limits

    International Nuclear Information System (INIS)

    Weber, G.G.


    Some recent methodological developments of fault tree analysis are discussed and limits of fault tree analysis and a criterion for admissibility of structure functions are given. It is shown that there are interesting relations to switching theory and to stochastic processes. (orig./HP) [de

  10. Connected Filtering on Tree-Based Shape-Spaces. (United States)

    Xu, Yongchao; Geraud, Thierry; Najman, Laurent


    Connected filters are well-known for their good contour preservation property. A popular implementation strategy relies on tree-based image representations: for example, one can compute an attribute characterizing the connected component represented by each node of the tree and keep only the nodes for which the attribute is sufficiently high. This operation can be seen as a thresholding of the tree, seen as a graph whose nodes are weighted by the attribute. Rather than being satisfied with a mere thresholding, we propose to expand on this idea, and to apply connected filters on this latest graph. Consequently, the filtering is performed not in the space of the image, but in the space of shapes built from the image. Such a processing of shape-space filtering is a generalization of the existing tree-based connected operators. Indeed, the framework includes the classical existing connected operators by attributes. It also allows us to propose a class of novel connected operators from the leveling family, based on non-increasing attributes. Finally, we also propose a new class of connected operators that we call morphological shapings. Some illustrations and quantitative evaluations demonstrate the usefulness and robustness of the proposed shape-space filters.

  11. Tree-structured method for LUT inverse halftoning and for image halftoning. (United States)

    Mese, Murat; Vaidyanathan, P P


    Recently, the authors proposed a Look Up Table (LUT) based method for inverse halftoning of images. The LUT for inverse halftoning is obtained from the histogram gathered from a few sample halftone images and corresponding original images. Many of the entries in the LUT are unused because the corresponding binary patterns hardly occur in commonly encountered halftones. These are called nonexistent patterns. In this paper, we propose a tree structure which will reduce the storage requirements of an LUT by avoiding nonexistent patterns. We will demonstrate the performance on error diffused images and ordered dither images. Then, we introduce LUT based halftoning and tree-structured LUT (TLUT) halftoning. Even though TLUT method is more complex than LUT halftoning, it produces better halftones and requires much less storage than LUT halftoning.We will demonstrate how error diffusion characteristics can be achieved with this method. Afterwards, our algorithm will bet rained on halftones obtained by Direct Binary Search (DBS).The complexity of TLUT halftoning is higher than error diffusion algorithm but much lower than DBS algorithm. Also, the halftone quality of TLUT halftoning increases if the size of TLUT gets bigger. Thus, halftone image quality between error diffusion and DBS will be achieved depending on the size of tree-structure in TLUT algorithm.

  12. Efficiencies of different genes and different tree-building methods in recovering a known vertebrate phylogeny. (United States)

    Russo, C A; Takezaki, N; Nei, M


    The relative efficiencies of different protein-coding genes of the mitochondrial genome and different tree-building methods in recovering a known vertebrate phylogeny (two whale species, cow, rat, mouse, opossum, chicken, frog, and three bony fish species) was evaluated. The tree-building methods examined were the neighbor joining (NJ), minimum evolution (ME), maximum parsimony (MP), and maximum likelihood (ML), and both nucleotide sequences and deduced amino acid sequences were analyzed. Generally speaking, amino acid sequences were better than nucleotide sequences in obtaining the true tree (topology) or trees close to the true tree. However, when only first and second codon positions data were used, nucleotide sequences produced reasonably good trees. Among the 13 genes examined, Nd5 produced the true tree in all tree-building methods or algorithms for both amino acid and nucleotide sequence data. Genes Cytb and Nd4 also produced the correct tree in most tree-building algorithms when amino acid sequence data were used. By contrast, Co2, Nd1, and Nd41 showed a poor performance. In general, large genes produced better results, and when the entire set of genes was used, all tree-building methods generated the true tree. In each tree-building method, several distance measures or algorithms were used, but all these distance measures or algorithms produced essentially the same results. The ME method, in which many different topologies are examined, was no better than the NJ method, which generates a single final tree. Similarly, an ML method, in which many topologies are examined, was no better than the ML star decomposition algorithm that generates a single final tree. In ML the best substitution model chosen by using the Akaike information criterion produced no better results than simpler substitution models. These results question the utility of the currently used optimization principles in phylogenetic construction. Relatively simple methods such as the NJ and ML

  13. Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks

    Directory of Open Access Journals (Sweden)

    Chang Jeong-Ho


    Full Text Available Abstract Background To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. Results To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. Conclusion By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway

  14. Stem mortality in surface fires: Part II, experimental methods for characterizing the thermal response of tree stems to heating by fires (United States)

    D. M. Jimenez; B. W. Butler; J. Reardon


    Current methods for predicting fire-induced plant mortality in shrubs and trees are largely empirical. These methods are not readily linked to duff burning, soil heating, and surface fire behavior models. In response to the need for a physics-based model of this process, a detailed model for predicting the temperature distribution through a tree stem as a function of...

  15. LifePrint: a novel k-tuple distance method for construction of phylogenetic trees

    Directory of Open Access Journals (Sweden)

    Fabián Reyes-Prieto


    Full Text Available Fabián Reyes-Prieto1, Adda J García-Chéquer1, Hueman Jaimes-Díaz1, Janet Casique-Almazán1, Juana M Espinosa-Lara1, Rosaura Palma-Orozco2, Alfonso Méndez-Tenorio1, Rogelio Maldonado-Rodríguez1, Kenneth L Beattie31Laboratory of Biotechnology and Genomic Bioinformatics, Department of Biochemistry, National School of Biological Sciences, 2Superior School of Computer Sciences, National Polytechnic Institute, Mexico City, Mexico; 3Amerigenics Inc, Crossville, Tennessee, USAPurpose: Here we describe LifePrint, a sequence alignment-independent k-tuple distance method to estimate relatedness between complete genomes.Methods: We designed a representative sample of all possible DNA tuples of length 9 (9-tuples. The final sample comprises 1878 tuples (called the LifePrint set of 9-tuples; LPS9 that are distinct from each other by at least two internal and noncontiguous nucleotide differences. For validation of our k-tuple distance method, we analyzed several real and simulated viroid genomes. Using different distance metrics, we scrutinized diverse viroid genomes to estimate the k-tuple distances between these genomic sequences. Then we used the estimated genomic k-tuple distances to construct phylogenetic trees using the neighbor-joining algorithm. A comparison of the accuracy of LPS9 and the previously reported 5-tuple method was made using symmetric differences between the trees estimated from each method and a simulated “true” phylogenetic tree.Results: The identified optimal search scheme for LPS9 allows only up to two nucleotide differences between each 9-tuple and the scrutinized genome. Similarity search results of simulated viroid genomes indicate that, in most cases, LPS9 is able to detect single-base substitutions between genomes efficiently. Analysis of simulated genomic variants with a high proportion of base substitutions indicates that LPS9 is able to discern relationships between genomic variants with up to 40% of nucleotide

  16. A Tree-based Approach for Modelling Interception Loss From Evergreen Oak Mediterranean Savannas (United States)

    Pereira, Fernando L.; Gash, John H. C.; David, Jorge S.; David, Teresa S.; Monteiro, Paulo R.; Valente, Fernanda


    Evaporation of rainfall intercepted by tree canopies is usually an important part of the overall water balance of forested catchments and there have been many studies dedicated to measuring and modelling rainfall interception loss. These studies have mainly been conducted in dense forests; there have been few studies on the very sparse forests which are common in dry and semi-arid areas. Water resources are scarce in these areas making sparse forests particularly important. Methods for modelling interception loss are thus required to support sustainable water management in those areas. In very sparse forests, trees occur as widely spaced individuals rather than as a continuous forest canopy. We therefore suggest that interception loss for this vegetation type can be more adequately modelled if the overall forest evaporation is derived by scaling up the evaporation from individual trees. The evaporation rate for a single tree can be estimated using a simple Dalton-type diffusion equation for water vapour as long as its surface temperature is known. From theory, this temperature is shown to be dependent upon the available energy and windspeed. However, the surface temperature of a fully saturated tree crown, under rainy conditions, should approach the wet bulb temperature as the radiative energy input to the tree reduces to zero. This was experimentally confirmed from measurements of the radiation balance and surface temperature of an isolated tree crown. Thus, evaporation of intercepted rainfall can be estimated using an equation which only requires knowledge of the air dry and wet bulb temperatures and of the bulk tree-crown aerodynamic conductance. This was taken as the basis of a new approach for modelling interception loss from savanna-type woodland, i.e. by combining the Dalton-type equation with the Gash's analytical model to estimate interception loss from isolated trees. This modelling approach was tested using data from two Mediterranean savanna-type oak

  17. Indirect methods of tree biomass estimation and their uncertainties ...

    African Journals Online (AJOL)

    Depending on data availability (dbh only or both dbh and total tree height) either of the models may be applied to generate satisfactory estimates of tree volume needed for planning and decision-making in management of mangrove forests. The study found an overall mean FF value of 0.65 ± 0.03 (SE), 0.56 ± 0.03 (SE) and ...


    Boha, Roland; Tóth Brigitta; Kardos, Zsófia; Bálint, File; Gaál, Zsófia Anna; Molnár, Márk


    In the present study basic arithmetic induced rearrangements in functional connections of the brain were investigated by using graph theoretical analysis what becomes increasingly important both in theoretical neuroscience and also in clinical investigations. During mental arithmetic operations (working) memory plays an important role, but there are only a few studies in which an attempt was made to separate this effect from the process of arithmetic operations themselves. The goal of our study was to separate the neural networks involved in cognitive functions. As an attempt to clarify this issue the graph-theoretical "minimal spanning tree" method was used for the analysis of EEG recorded during task performance. The effects of passive viewing, number recognition and mental arithmetic on PLI based minimal spanning trees (MST) were investigated on the EEG in young adults (adding task: 17 subjects; passive viewing and number recognition: 16 subjects) in the θ (4-8 Hz) frequency band. Occipital task relevant synchronization was found by using the different methods, probably related to the effect of visual stimulation. With respect to diameter, eccentricity and fraction of leafs different task-related changes were found. It was shown that the task related changes of various graph indices are capable to identify networks behind the various relevant dominant functions. Thus the "minimal spanning tree" method is suitable for the analysis of the reorganization of the brain with respect to cognitive functions.

  19. Use of the event tree method for evaluate the safety of radioactive facilities

    International Nuclear Information System (INIS)

    Hernandez S, A.; Cornejo D, N.; Callis F, E.


    The work shows the validity of the use of Trees of Events like a quantitative method appropriate to carry out evaluations of radiological safety. Its were took like base the evaluations of safety of five Radiotherapy Departments, carried out in the mark of the process of authorization of these facilities. The risk values were obtained by means of the combination of the probabilities of occurrence of the events with its consequences. The use of the method allowed to suggest improvements to the existent safety systems, as well as to confirm that the current regulator requirements for this type of facilities to lead to practices with acceptable risk levels. (Author)

  20. Lidar-based individual tree species classification using convolutional neural network (United States)

    Mizoguchi, Tomohiro; Ishii, Akira; Nakamura, Hiroyuki; Inoue, Tsuyoshi; Takamatsu, Hisashi


    Terrestrial lidar is commonly used for detailed documentation in the field of forest inventory investigation. Recent improvements of point cloud processing techniques enabled efficient and precise computation of an individual tree shape parameters, such as breast-height diameter, height, and volume. However, tree species are manually specified by skilled workers to date. Previous works for automatic tree species classification mainly focused on aerial or satellite images, and few works have been reported for classification techniques using ground-based sensor data. Several candidate sensors can be considered for classification, such as RGB or multi/hyper spectral cameras. Above all candidates, we use terrestrial lidar because it can obtain high resolution point cloud in the dark forest. We selected bark texture for the classification criteria, since they clearly represent unique characteristics of each tree and do not change their appearance under seasonable variation and aged deterioration. In this paper, we propose a new method for automatic individual tree species classification based on terrestrial lidar using Convolutional Neural Network (CNN). The key component is the creation step of a depth image which well describe the characteristics of each species from a point cloud. We focus on Japanese cedar and cypress which cover the large part of domestic forest. Our experimental results demonstrate the effectiveness of our proposed method.

  1. A dual growing method for the automatic extraction of individual trees from mobile laser scanning data (United States)

    Li, Lin; Li, Dalin; Zhu, Haihong; Li, You


    Street trees interlaced with other objects in cluttered point clouds of urban scenes inhibit the automatic extraction of individual trees. This paper proposes a method for the automatic extraction of individual trees from mobile laser scanning data, according to the general constitution of trees. Two components of each individual tree - a trunk and a crown can be extracted by the dual growing method. This method consists of coarse classification, through which most of artifacts are removed; the automatic selection of appropriate seeds for individual trees, by which the common manual initial setting is avoided; a dual growing process that separates one tree from others by circumscribing a trunk in an adaptive growing radius and segmenting a crown in constrained growing regions; and a refining process that draws a singular trunk from the interlaced other objects. The method is verified by two datasets with over 98% completeness and over 96% correctness. The low mean absolute percentage errors in capturing the morphological parameters of individual trees indicate that this method can output individual trees with high precision.

  2. Production analysis of two tree-bucking and product-sorting methods for hardwoods (United States)

    John E. Baumgras; Chris B. LeDoux


    This paper documents the results of a study to determine the cost and productivity of two tree-bucking and product-sorting methods used by West Virginia loggers harvesting three to four types of roundwood products. The methods include manual chainsaw bucking and bucking with a hydraulically powered chainsaw slasher. Results show that chain saw bucking of trees...

  3. Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree. (United States)

    Kim, Jaekwon; Lee, Jongsik; Lee, Youngho


    The importance of the prediction of coronary heart disease (CHD) has been recognized in Korea; however, few studies have been conducted in this area. Therefore, it is necessary to develop a method for the prediction and classification of CHD in Koreans. A model for CHD prediction must be designed according to rule-based guidelines. In this study, a fuzzy logic and decision tree (classification and regression tree [CART])-driven CHD prediction model was developed for Koreans. Datasets derived from the Korean National Health and Nutrition Examination Survey VI (KNHANES-VI) were utilized to generate the proposed model. The rules were generated using a decision tree technique, and fuzzy logic was applied to overcome problems associated with uncertainty in CHD prediction. The accuracy and receiver operating characteristic (ROC) curve values of the propose systems were 69.51% and 0.594, proving that the proposed methods were more efficient than other models.

  4. A fast method for calculating reliable event supports in tree reconciliations via Pareto optimality. (United States)

    To, Thu-Hien; Jacox, Edwin; Ranwez, Vincent; Scornavacca, Celine


    Given a gene and a species tree, reconciliation methods attempt to retrieve the macro-evolutionary events that best explain the discrepancies between the two tree topologies. The DTL parsimonious approach searches for a most parsimonious reconciliation between a gene tree and a (dated) species tree, considering four possible macro-evolutionary events (speciation, duplication, transfer, and loss) with specific costs. Unfortunately, many events are erroneously predicted due to errors in the input trees, inappropriate input cost values or because of the existence of several equally parsimonious scenarios. It is thus crucial to provide a measure of the reliability for predicted events. It has been recently proposed that the reliability of an event can be estimated via its frequency in the set of most parsimonious reconciliations obtained using a variety of reasonable input cost vectors. To compute such a support, a straightforward but time-consuming approach is to generate the costs slightly departing from the original ones, independently compute the set of all most parsimonious reconciliations for each vector, and combine these sets a posteriori. Another proposed approach uses Pareto-optimality to partition cost values into regions which induce reconciliations with the same number of DTL events. The support of an event is then defined as its frequency in the set of regions. However, often, the number of regions is not large enough to provide reliable supports. We present here a method to compute efficiently event supports via a polynomial-sized graph, which can represent all reconciliations for several different costs. Moreover, two methods are proposed to take into account alternative input costs: either explicitly providing an input cost range or allowing a tolerance for the over cost of a reconciliation. Our methods are faster than the region based method, substantially faster than the sampling-costs approach, and have a higher event-prediction accuracy on

  5. Quality-based Multimodal Classification Using Tree-Structured Sparsity (United States)


    ASI Series F, Computer and Systems Sciences, 163:446–456, 1999. 5 [7] D. Hall and J. Llinas. An introduction to multisensor data fusion . Proceedings of...advantages of in- formation fusion based on sparsity models for multi- modal classification. Among several sparsity models, tree- structured sparsity provides...rithm is proposed to solve the optimization problem, which is an efficient tool for feature-level fusion among either ho- mogeneous or heterogeneous

  6. Comparison of Different Methods for RNA Extraction from Floral Buds of Tree Peony (Paeonia suffruticosa Andr.)


    Yan GAO; Guangqi ZHAO; Changhua JIANG; Yao SONG; Kang YE; Shucheng FENG


    Tree peony (Paeonia suffruticosa Andr.), a species native to China, is one of the most important ornamental and medicinal plants. Like other tree species in temperate and boreal zones, the dormancy-activity transition of floral buds is critical for blooming time and fruit production. However, floral buds contain high levels of secondary metabolites, making the isolation of high quality RNA difficult. To obtain a method suitable for extracting RNA from floral buds of tree peony, we evaluated f...

  7. Bayesian and Classical Machine Learning Methods: A Comparison for Tree Species Classification with LiDAR Waveform Signatures

    Directory of Open Access Journals (Sweden)

    Tan Zhou


    Full Text Available A plethora of information contained in full-waveform (FW Light Detection and Ranging (LiDAR data offers prospects for characterizing vegetation structures. This study aims to investigate the capacity of FW LiDAR data alone for tree species identification through the integration of waveform metrics with machine learning methods and Bayesian inference. Specifically, we first conducted automatic tree segmentation based on the waveform-based canopy height model (CHM using three approaches including TreeVaW, watershed algorithms and the combination of TreeVaW and watershed (TW algorithms. Subsequently, the Random forests (RF and Conditional inference forests (CF models were employed to identify important tree-level waveform metrics derived from three distinct sources, such as raw waveforms, composite waveforms, the waveform-based point cloud and the combined variables from these three sources. Further, we discriminated tree (gray pine, blue oak, interior live oak and shrub species through the RF, CF and Bayesian multinomial logistic regression (BMLR using important waveform metrics identified in this study. Results of the tree segmentation demonstrated that the TW algorithms outperformed other algorithms for delineating individual tree crowns. The CF model overcomes waveform metrics selection bias caused by the RF model which favors correlated metrics and enhances the accuracy of subsequent classification. We also found that composite waveforms are more informative than raw waveforms and waveform-based point cloud for characterizing tree species in our study area. Both classical machine learning methods (the RF and CF and the BMLR generated satisfactory average overall accuracy (74% for the RF, 77% for the CF and 81% for the BMLR and the BMLR slightly outperformed the other two methods. However, these three methods suffered from low individual classification accuracy for the blue oak which is prone to being misclassified as the interior live oak due

  8. An efficient computational method for global sensitivity analysis and its application to tree growth modelling

    International Nuclear Information System (INIS)

    Wu, Qiong-Li; Cournède, Paul-Henry; Mathieu, Amélie


    Global sensitivity analysis has a key role to play in the design and parameterisation of functional–structural plant growth models which combine the description of plant structural development (organogenesis and geometry) and functional growth (biomass accumulation and allocation). We are particularly interested in this study in Sobol's method which decomposes the variance of the output of interest into terms due to individual parameters but also to interactions between parameters. Such information is crucial for systems with potentially high levels of non-linearity and interactions between processes, like plant growth. However, the computation of Sobol's indices relies on Monte Carlo sampling and re-sampling, whose costs can be very high, especially when model evaluation is also expensive, as for tree models. In this paper, we thus propose a new method to compute Sobol's indices inspired by Homma–Saltelli, which improves slightly their use of model evaluations, and then derive for this generic type of computational methods an estimator of the error estimation of sensitivity indices with respect to the sampling size. It allows the detailed control of the balance between accuracy and computing time. Numerical tests on a simple non-linear model are convincing and the method is finally applied to a functional–structural model of tree growth, GreenLab, whose particularity is the strong level of interaction between plant functioning and organogenesis. - Highlights: ► We study global sensitivity analysis in the context of functional–structural plant modelling. ► A new estimator based on Homma–Saltelli method is proposed to compute Sobol indices, based on a more balanced re-sampling strategy. ► The estimation accuracy of sensitivity indices for a class of Sobol's estimators can be controlled by error analysis. ► The proposed algorithm is implemented efficiently to compute Sobol indices for a complex tree growth model.

  9. Identifying Different Transportation Modes from Trajectory Data Using Tree-Based Ensemble Classifiers

    Directory of Open Access Journals (Sweden)

    Zhibin Xiao


    Full Text Available Recognition of transportation modes can be used in different applications including human behavior research, transport management and traffic control. Previous work on transportation mode recognition has often relied on using multiple sensors or matching Geographic Information System (GIS information, which is not possible in many cases. In this paper, an approach based on ensemble learning is proposed to infer hybrid transportation modes using only Global Position System (GPS data. First, in order to distinguish between different transportation modes, we used a statistical method to generate global features and extract several local features from sub-trajectories after trajectory segmentation, before these features were combined in the classification stage. Second, to obtain a better performance, we used tree-based ensemble models (Random Forest, Gradient Boosting Decision Tree, and XGBoost instead of traditional methods (K-Nearest Neighbor, Decision Tree, and Support Vector Machines to classify the different transportation modes. The experiment results on the later have shown the efficacy of our proposed approach. Among them, the XGBoost model produced the best performance with a classification accuracy of 90.77% obtained on the GEOLIFE dataset, and we used a tree-based ensemble method to ensure accurate feature selection to reduce the model complexity.

  10. Carbon Sequestration Estimation of Street Trees Based on Point Cloud from Vehicle-Borne Laser Scanning System (United States)

    Zhao, Y.; Hu, Q.


    Continuous development of urban road traffic system requests higher standards of road ecological environment. Ecological benefits of street trees are getting more attention. Carbon sequestration of street trees refers to the carbon stocks of street trees, which can be a measurement for ecological benefits of street trees. Estimating carbon sequestration in a traditional way is costly and inefficient. In order to solve above problems, a carbon sequestration estimation approach for street trees based on 3D point cloud from vehicle-borne laser scanning system is proposed in this paper. The method can measure the geometric parameters of a street tree, including tree height, crown width, diameter at breast height (DBH), by processing and analyzing point cloud data of an individual tree. Four Chinese scholartree trees and four camphor trees are selected for experiment. The root mean square error (RMSE) of tree height is 0.11m for Chinese scholartree and 0.02m for camphor. Crown widths in X direction and Y direction, as well as the average crown width are calculated. And the RMSE of average crown width is 0.22m for Chinese scholartree and 0.10m for camphor. The last calculated parameter is DBH, the RMSE of DBH is 0.5cm for both Chinese scholartree and camphor. Combining the measured geometric parameters and an appropriate carbon sequestration calculation model, the individual tree's carbon sequestration will be estimated. The proposed method can help enlarge application range of vehicle-borne laser point cloud data, improve the efficiency of estimating carbon sequestration, construct urban ecological environment and manage landscape.

  11. Algorithms, data structures, and numerics for likelihood-based phylogenetic inference of huge trees

    Directory of Open Access Journals (Sweden)

    Izquierdo-Carrasco Fernando


    Full Text Available Abstract Background The rapid accumulation of molecular sequence data, driven by novel wet-lab sequencing technologies, poses new challenges for large-scale maximum likelihood-based phylogenetic analyses on trees with more than 30,000 taxa and several genes. The three main computational challenges are: numerical stability, the scalability of search algorithms, and the high memory requirements for computing the likelihood. Results We introduce methods for solving these three key problems and provide respective proof-of-concept implementations in RAxML. The mechanisms presented here are not RAxML-specific and can thus be applied to any likelihood-based (Bayesian or maximum likelihood tree inference program. We develop a new search strategy that can reduce the time required for tree inferences by more than 50% while yielding equally good trees (in the statistical sense for well-chosen starting trees. We present an adaptation of the Subtree Equality Vector technique for phylogenomic datasets with missing data (already available in RAxML v728 that can reduce execution times and memory requirements by up to 50%. Finally, we discuss issues pertaining to the numerical stability of the Γ model of rate heterogeneity on very large trees and argue in favor of rate heterogeneity models that use a single rate or rate category for each site to resolve these problems. Conclusions We address three major issues pertaining to large scale tree reconstruction under maximum likelihood and propose respective solutions. Respective proof-of-concept/production-level implementations of our ideas are made available as open-source code.

  12. Model-Based Design of Tree WSNs for Decentralized Detection

    Directory of Open Access Journals (Sweden)

    Ashraf Tantawy


    Full Text Available The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches.

  13. A restricted Steiner tree problem is solved by Geometric Method II (United States)

    Lin, Dazhi; Zhang, Youlin; Lu, Xiaoxu


    The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. In this paper, we first put forward a restricted Steiner tree problem, which the fixed vertices are in the same side of one line L and we find a vertex on L such the length of the tree is minimal. By the definition and the complexity of the Steiner tree problem, we know that the complexity of this problem is also Np-complete. In the part one, we have considered there are two fixed vertices to find the restricted Steiner tree problem. Naturally, we consider there are three fixed vertices to find the restricted Steiner tree problem. And we also use the geometric method to solve such the problem.

  14. Evaluation methods to fertilizing apple trees using 15N

    International Nuclear Information System (INIS)

    Calvache, Marcelo


    Designing experiments with fruit trees, using isotopic techniques, is different from the classical isotopic field experiments. This article summarizes the procedures to set up such experiments, explains the necessary calculations and ways to relate the data. Several examples of already conducted experiments are presented

  15. Nondestructive evaluation of standing trees with a stress wave method. (United States)

    Xiping Wang; Robert J. Ross; Michael McClellan; R. James Barbour; John R. Erickson; John W. Forsman; Gary D. McGinnis


    The primary objective of this study was to investigate the usefulness of a stress wave technique for evaluating wood strength and stiffness of young-growth western hemlock and Sitka spruce in standing trees. A secondary objective was to determine if the effects of silvicultural practices on wood quality can be identified using this technique. Stress wave measurements...

  16. WASTK: A Weighted Abstract Syntax Tree Kernel Method for Source Code Plagiarism Detection

    Directory of Open Access Journals (Sweden)

    Deqiang Fu


    Full Text Available In this paper, we introduce a source code plagiarism detection method, named WASTK (Weighted Abstract Syntax Tree Kernel, for computer science education. Different from other plagiarism detection methods, WASTK takes some aspects other than the similarity between programs into account. WASTK firstly transfers the source code of a program to an abstract syntax tree and then gets the similarity by calculating the tree kernel of two abstract syntax trees. To avoid misjudgment caused by trivial code snippets or frameworks given by instructors, an idea similar to TF-IDF (Term Frequency-Inverse Document Frequency in the field of information retrieval is applied. Each node in an abstract syntax tree is assigned a weight by TF-IDF. WASTK is evaluated on different datasets and, as a result, performs much better than other popular methods like Sim and JPlag.

  17. Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods (United States)

    Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett


    Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

  18. A call to improve methods for estimating tree biomass for regional and national assessments (United States)

    Aaron R. Weiskittel; David W. MacFarlane; Philip J. Radtke; David L.R. Affleck; Hailemariam Temesgen; Christopher W. Woodall; James A. Westfall; John W. Coulston


    Tree biomass is typically estimated using statistical models. This review highlights five limitations of most tree biomass models, which include the following: (1) biomass data are costly to collect and alternative sampling methods are used; (2) belowground data and models are generally lacking; (3) models are often developed from small and geographically limited data...

  19. A critical analysis of methods for rapid and nondestructive determination of wood density in standing trees (United States)

    Shan Gao; Xiping Wang; Michael C. Wiemann; Brian K. Brashaw; Robert J. Ross; Lihai Wang


    Key message Field methods for rapid determination of wood density in trees have evolved from increment borer, torsiometer, Pilodyn, and nail withdrawal into sophisticated electronic tools of resistance drilling measurement. A partial resistance drilling approach coupled with knowledge of internal tree density distribution may...

  20. Tree-based solvers for adaptive mesh refinement code FLASH - I: gravity and optical depths (United States)

    Wünsch, R.; Walch, S.; Dinnbier, F.; Whitworth, A.


    We describe an OctTree algorithm for the MPI parallel, adaptive mesh refinement code FLASH, which can be used to calculate the gas self-gravity, and also the angle-averaged local optical depth, for treating ambient diffuse radiation. The algorithm communicates to the different processors only those parts of the tree that are needed to perform the tree-walk locally. The advantage of this approach is a relatively low memory requirement, important in particular for the optical depth calculation, which needs to process information from many different directions. This feature also enables a general tree-based radiation transport algorithm that will be described in a subsequent paper, and delivers excellent scaling up to at least 1500 cores. Boundary conditions for gravity can be either isolated or periodic, and they can be specified in each direction independently, using a newly developed generalization of the Ewald method. The gravity calculation can be accelerated with the adaptive block update technique by partially re-using the solution from the previous time-step. Comparison with the FLASH internal multigrid gravity solver shows that tree-based methods provide a competitive alternative, particularly for problems with isolated or mixed boundary conditions. We evaluate several multipole acceptance criteria (MACs) and identify a relatively simple approximate partial error MAC which provides high accuracy at low computational cost. The optical depth estimates are found to agree very well with those of the RADMC-3D radiation transport code, with the tree-solver being much faster. Our algorithm is available in the standard release of the FLASH code in version 4.0 and later.

  1. A stable RNA virus-based vector for citrus trees

    International Nuclear Information System (INIS)

    Folimonov, Alexey S.; Folimonova, Svetlana Y.; Bar-Joseph, Moshe; Dawson, William O.


    Virus-based vectors are important tools in plant molecular biology and plant genomics. A number of vectors based on viruses that infect herbaceous plants are in use for expression or silencing of genes in plants as well as screening unknown sequences for function. Yet there is a need for useful virus-based vectors for woody plants, which demand much greater stability because of the longer time required for systemic infection and analysis. We examined several strategies to develop a Citrus tristeza virus (CTV)-based vector for transient expression of foreign genes in citrus trees using a green fluorescent protein (GFP) as a reporter. These strategies included substitution of the p13 open reading frame (ORF) by the ORF of GFP, construction of a self-processing fusion of GFP in-frame with the major coat protein (CP), or expression of the GFP ORF as an extra gene from a subgenomic (sg) mRNA controlled either by a duplicated CTV CP sgRNA controller element (CE) or an introduced heterologous CE of Beet yellows virus. Engineered vector constructs were examined for replication, encapsidation, GFP expression during multiple passages in protoplasts, and for their ability to infect, move, express GFP, and be maintained in citrus plants. The most successful vectors based on the 'add-a-gene' strategy have been unusually stable, continuing to produce GFP fluorescence after more than 4 years in citrus trees

  2. Escaping Depressions in LRTS Based on Incremental Refinement of Encoded Quad-Trees

    Directory of Open Access Journals (Sweden)

    Yue Hu


    Full Text Available In the context of robot navigation, game AI, and so on, real-time search is extensively used to undertake motion planning. Though it satisfies the requirement of quick response to users’ commands and environmental changes, learning real-time search (LRTS suffers from the heuristic depressions where agents behave irrationally. There have introduced several effective solutions, such as state abstractions. This paper combines LRTS and encoded quad-tree abstraction which represent the search space in multiresolutions. When exploring the environments, agents are enabled to locally repair the quad-tree models and incrementally refine the spatial cognition. By virtue of the idea of state aggregation and heuristic generalization, our EQ LRTS (encoded quad-tree based LRTS possesses the ability of quickly escaping from heuristic depressions with less state revisitations. Experiments and analysis show that (a our encoding principle for quad-trees is a much more memory-efficient method than other data structures expressing quad-trees, (b EQ LRTS differs a lot in several characteristics from classical PR LRTS which represent the space and refine the paths hierarchically, and (c EQ LRTS substantially reduces the planning amount and curtails heuristic updates compared with LRTS on uniform cells.

  3. Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy. (United States)

    Gasparini, Patrizia; Di Cosmo, Lucio; Cenni, Enrico; Pompei, Enrico; Ferretti, Marco


    In the frame of a process aiming at harmonizing National Forest Inventory (NFI) and ICP Forests Level I Forest Condition Monitoring (FCM) in Italy, we investigated (a) the long-term consistency between FCM sample points (a subsample of the first NFI, 1985, NFI_1) and recent forest area estimates (after the second NFI, 2005, NFI_2) and (b) the effect of tree selection method (tree-based or plot-based) on sample composition and defoliation statistics. The two investigations were carried out on 261 and 252 FCM sites, respectively. Results show that some individual forest categories (larch and stone pine, Norway spruce, other coniferous, beech, temperate oaks and cork oak forests) are over-represented and others (hornbeam and hophornbeam, other deciduous broadleaved and holm oak forests) are under-represented in the FCM sample. This is probably due to a change in forest cover, which has increased by 1,559,200 ha from 1985 to 2005. In case of shift from a tree-based to a plot-based selection method, 3,130 (46.7%) of the original 6,703 sample trees will be abandoned, and 1,473 new trees will be selected. The balance between exclusion of former sample trees and inclusion of new ones will be particularly unfavourable for conifers (with only 16.4% of excluded trees replaced by new ones) and less for deciduous broadleaves (with 63.5% of excluded trees replaced). The total number of tree species surveyed will not be impacted, while the number of trees per species will, and the resulting (plot-based) sample composition will have a much larger frequency of deciduous broadleaved trees. The newly selected trees have-in general-smaller diameter at breast height (DBH) and defoliation scores. Given the larger rate of turnover, the deciduous broadleaved part of the sample will be more impacted. Our results suggest that both a revision of FCM network to account for forest area change and a plot-based approach to permit statistical inference and avoid bias in the tree sample

  4. Preparing investigation of methods for surveying tree seed demands among farmers in Tanzania

    DEFF Research Database (Denmark)

    Aabæk, Anders

    demand pattern in Tanzania, Uganda and Nicaragua are discussed and a choice of strategy for an extensive survey of seed demand and supply in Tanzania is made. Different data collection methods and tools, e.g. quantitative and qualitative surveys and rapid rural appraisals, are described in detail......Insufficient seed supplies is often a major constraint on tree planting activities in developing countries. A central problem is to assess the actual demands for tree seed. This report shall, as a part of a PhD-study, prepare an investigation of different methods for surveying tree seed demands...... and preferences among private farmers in Tanzania. A framework for investigating seed demand and supply is outlined. The role of a national tree seed project in a seed supply sector is discussed and data requirements for strategy on seed procurement and tree improvement are outlined. Earlier surveys on seed...

  5. Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar (United States)

    Chen, Qi


    Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

  6. Iterative multi-atlas-based multi-image segmentation with tree-based registration. (United States)

    Jia, Hongjun; Yap, Pew-Thian; Shen, Dinggang


    In this paper, we present a multi-atlas-based framework for accurate, consistent and simultaneous segmentation of a group of target images. Multi-atlas-based segmentation algorithms consider concurrently complementary information from multiple atlases to produce optimal segmentation outcomes. However, the accuracy of these algorithms relies heavily on the precise alignment of the atlases with the target image. In particular, the commonly used pairwise registration may result in inaccurate alignment especially between images with large shape differences. Additionally, when segmenting a group of target images, most current methods consider these images independently with disregard of their correlation, thus resulting in inconsistent segmentations of the same structures across different target images. We propose two novel strategies to address these limitations: 1) a novel tree-based groupwise registration method for concurrent alignment of both the atlases and the target images, and 2) an iterative groupwise segmentation method for simultaneous consideration of segmentation information propagated from all available images, including the atlases and other newly segmented target images. Evaluation based on various datasets indicates that the proposed multi-atlas-based multi-image segmentation (MABMIS) framework yields substantial improvements in terms of consistency and accuracy over methods that do not consider the group of target images holistically. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Hide and vanish: data sets where the most parsimonious tree is known but hard to find, and their implications for tree search methods. (United States)

    Goloboff, Pablo A


    Three different types of data sets, for which the uniquely most parsimonious tree can be known exactly but is hard to find with heuristic tree search methods, are studied. Tree searches are complicated more by the shape of the tree landscape (i.e. the distribution of homoplasy on different trees) than by the sheer abundance of homoplasy or character conflict. Data sets of Type 1 are those constructed by Radel et al. (2013). Data sets of Type 2 present a very rugged landscape, with narrow peaks and valleys, but relatively low amounts of homoplasy. For such a tree landscape, subjecting the trees to TBR and saving suboptimal trees produces much better results when the sequence of clipping for the tree branches is randomized instead of fixed. An unexpected finding for data sets of Types 1 and 2 is that starting a search from a random tree instead of a random addition sequence Wagner tree may increase the probability that the search finds the most parsimonious tree; a small artificial example where these probabilities can be calculated exactly is presented. Data sets of Type 3, the most difficult data sets studied here, comprise only congruent characters, and a single island with only one most parsimonious tree. Even if there is a single island, missing entries create a very flat landscape which is difficult to traverse with tree search algorithms because the number of equally parsimonious trees that need to be saved and swapped to effectively move around the plateaus is too large. Minor modifications of the parameters of tree drifting, ratchet, and sectorial searches allow travelling around these plateaus much more efficiently than saving and swapping large numbers of equally parsimonious trees with TBR. For these data sets, two new related criteria for selecting taxon addition sequences in Wagner trees (the "selected" and "informative" addition sequences) produce much better results than the standard random or closest addition sequences. These new methods for Wagner

  8. The new hybrid method for measuring transpiration sap flows in trees

    Directory of Open Access Journals (Sweden)

    G. P. Tikhova


    Full Text Available Sap flow measurements have become relevant in many physiological and ecological investigations. A variety of methods are used to estimate sap flow in trees in modern studies. However the determination of accuracy of commonly used techniques often presents a challenge. We analyzed advantages, pitfalls and restrictions of up-to-date methods that were implemented in commercially available devices. We proposed a new hybrid method for measuring linear sap flow velocity, which was designed on the base of different variants of heat-pulse velocity (HPV technique and thermal dissipation (TD technique developed by Granier. The method was created in order to increase accuracy and precision of sap flow velocity measurements. The mathematical model of the proposed method was developed. It allows to determine accuracy of measurements and potential limits of applying the new technique in the field studies. The model is based on the description of heat process dynamics in the volume of 1 cubic decimeter of sap tissue. The obtained relationships were used in developed software that allows to model reverse heat pulses distribution under the condition of shortened interval between their generations. The proposed algorithm enables verification of zero sap flow velocity measurement in tree trunk with given accuracy. The computer program was developed. It allows to define maximum acceptable time interval for a given accuracy of determined values when the velocity is close to zero as well as to demonstrate the shape of the heat signal depending of time in the given point of trunk. The model calculations showed that the new method improves the accuracy of sap flow velocity measurements at low and high flow rates when conventional techniques suffer from significant errors. The applying of the new method allows to detect zero sap flow without using any additional measuring procedures and devices.

  9. Statistical Sensitive Data Protection and Inference Prevention with Decision Tree Methods

    National Research Council Canada - National Science Library

    Chang, LiWu


    .... We consider inference as correct classification and approach it with decision tree methods. As in our previous work, sensitive data are viewed as classes of those test data and non-sensitive data are the rest attribute values...

  10. Identifying tree crown delineation shapes and need for remediation on high resolution imagery using an evidence based approach (United States)

    Leckie, Donald G.; Walsworth, Nicholas; Gougeon, François A.


    In order to fully realize the benefits of automated individual tree mapping for tree species, health, forest inventory attribution and forest management decision making, the tree delineations should be as good as possible. The concept of identifying poorly delineated tree crowns and suggesting likely types of remediation was investigated. Delineations (isolations or isols) were classified into shape types reflecting whether they were realistic tree shapes and the likely kind of remediation needed. Shape type was classified by an evidence based rules approach using primitives based on isol size, shape indices, morphology, the presence of local maxima, and matches with template models representing trees of different sizes. A test set containing 50,000 isols based on an automated tree delineation of 40 cm multispectral airborne imagery of a diverse temperate-boreal forest site was used. Isolations representing single trees or several trees were the focus, as opposed to cases where a tree is split into several isols. For eight shape classes from regular through to convolute, shape classification accuracy was in the order of 62%; simplifying to six classes accuracy was 83%. Shape type did give an indication of the type of remediation and there were 6% false alarms (i.e., isols classed as needing remediation but did not). Alternately, there were 5% omissions (i.e., isols of regular shape and not earmarked for remediation that did need remediation). The usefulness of the concept of identifying poor delineations in need of remediation was demonstrated and one suite of methods developed and shown to be effective.

  11. A Family-Based Evolutional Approach for Kernel Tree Selection in SVMs (United States)

    Methasate, Ithipan; Theeramunkong, Thanaruk

    Finding a kernel mapping function for support vector machines (SVMs) is a key step towards construction of a high-performanced SVM-based classifier. While some recent methods exploited an evolutional approach to construct a suitable multifunction kernel, most of them searched randomly and diversely. In this paper, the concept of a family of identical-structured kernel trees is proposed to enable exploration of structure space using genetic programming whereas to pursue investigation of parameter space on a certain tree using evolution strategy. To control balance between structure and parameter search towards an optimal kernel, simulated annealing is introduced. By experiments on a number of benchmark datasets in the UCI and text classification collection, the proposed method is shown to be able to find a better optimal solution than other search methods, including grid search and gradient search.

  12. Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods

    Directory of Open Access Journals (Sweden)

    Chao Yang


    Full Text Available Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D Terrain model, which was created using an image fusion digital elevation model (DEM, to select training samples (ROIs, and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.


    Directory of Open Access Journals (Sweden)

    S. H. Chiang


    Full Text Available Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface

  14. Heat unit-based crop coefficient for grapefruit trees

    International Nuclear Information System (INIS)

    Martin, E.C.; Hla, A.K.; Waller, P.M.; Slack, D.C.


    The onset and rate of sap moving up the branches of grapefruit (Citrus paradisi Macfadyen) trees were monitored hourly using portable sap flow sensors at Waddell, Arizona. Hourly reference evapotranspiration (ETo) estimates were calculated using data from a nearby weather station. Crop water use was estimated from soil moisture measurements using a neutron probe. These data were used to first delineate the upper and lower temperature threshold values for the determination of heat units. A heat unit-based crop coefficient was then derived from a correlation of the crop coefficient with heat units over a crop year. The heat unit-based crop coefficient was found to be similar to crop coefficients derived by other reseachers

  15. Climate Based Predictability of Oil Palm Tree Yield in Malaysia. (United States)

    Oettli, Pascal; Behera, Swadhin K; Yamagata, Toshio


    The influence of local conditions and remote climate modes on the interannual variability of oil palm fresh fruit bunches (FFB) total yields in Malaysia and two major regions (Peninsular Malaysia and Sabah/Sarawak) is explored. On a country scale, the state of sea-surface temperatures (SST) in the tropical Pacific Ocean during the previous boreal winter is found to influence the regional climate. When El Niño occurs in the Pacific Ocean, rainfall in Malaysia reduces but air temperature increases, generating a high level of water stress for palm trees. As a result, the yearly production of FFB becomes lower than that of a normal year since the water stress during the boreal spring has an important impact on the total annual yields of FFB. Conversely, La Niña sets favorable conditions for palm trees to produce more FFB by reducing chances of water stress risk. The region of the Leeuwin current also seems to play a secondary role through the Ningaloo Niño/ Niña in the interannual variability of FFB yields. Based on these findings, a linear model is constructed and its ability to reproduce the interannual signal is assessed. This model has shown some skills in predicting the total FFB yield.

  16. Comparing forest measurements from tree rings and a space-based index of vegetation activity in Siberia

    International Nuclear Information System (INIS)

    Bunn, Andrew G; Hughes, Malcolm K; Losleben, Mark; Kirdyanov, Alexander V; Shishov, Vladimir V; Vaganov, Eugene A; Berner, Logan T; Oltchev, Alexander


    Different methods have been developed for measuring carbon stocks and fluxes in the northern high latitudes, ranging from intensively measured small plots to space-based methods that use reflectance data to drive production efficiency models. The field of dendroecology has used samples of tree growth from radial increments to quantify long-term variability in ecosystem productivity, but these have very limited spatial domains. Since the cambium material in tree cores is itself a product of photosynthesis in the canopy, it would be ideal to link these two approaches. We examine the associations between the normalized differenced vegetation index (NDVI) and tree growth using 19 pairs of tree-ring widths (TRW) and maximum latewood density (MXD) across much of Siberia. We find consistent correlations between NDVI and both measures of tree growth and no systematic difference between MXD and TRW. At the regional level we note strong correspondence between the first principal component of tree growth and NDVI for MXD and TRW in a temperature-limited bioregion, indicating that canopy reflectance and cambial production are broadly linked. Using a network of 21 TRW chronologies from south of Lake Baikal, we find a similarly strong regional correspondence with NDVI in a markedly drier region. We show that tree growth is dominated by variation at decadal and multidecadal time periods, which the satellite record is incapable of recording given its relatively short record. (letter)

  17. Rockfall hazard assessment by coupling three-dimensional, process based models and field-based tree-ring data (United States)

    Trappmann, Daniel; Stoffel, Markus; Corona, Christophe


    A realistic evaluation of the spatial and temporal patterns of rockfalls is fundamental for the management of this very common hazard in mountain environments. Process-based, three-dimensional simulation models are nowadays capable to reproduce the spatial probability of rockfalls with reasonable accuracy through the simulation of numerous individual trajectories on highly-resolved digital terrain models. At the same time, however, simulation models typically fail to quantify the real frequency of rockfalls. The analysis of impact scars on trees, in contrast, yields empirical rockfall frequencies but, trees may not be present at the location of interest and rare trajectories may not necessarily be captured due to the limited age of forest stands on rockfall slopes. In this article, we demonstrate that the coupling of modeling with tree-ring techniques may overcome the limitations inherent to both approaches. Based on the analysis of 64 cells (40 × 40 m) of a rockfall slope located above a 1631-m long road section in the Swiss Alps, we illustrate results from 488 rockfalls detected in 1260 trees. We illustrate that tree impact data cannot only be used (i) to reconstruct the frequency of rockfalls for individual cells, but that they also serve (ii) the calibration of the rockfall model Rockyfor3D, as well as (iii) the transformation of simulated trajectories into real empirical frequencies. Calibrated simulation results are in good agreement with empirical rockfall frequencies and exhibit significant differences in rockfall activity between the cells (zones) along the road section. Empirical frequencies, expressed as rock passages per meter road section, also enable quantification and direct comparison of the hazard potential between the zones. The contribution provides an approach for hazard zoning procedures that complements traditional methods with a quantification of rockfall frequencies through a systematic inclusion of impact records in trees.

  18. Surface-based geometric modelling using teaching trees for advanced robots

    International Nuclear Information System (INIS)

    Nakamura, Akira; Ogasawara, Tsukasa; Tsukune, Hideo; Oshima, Masaki


    Geometric modelling of the environment is important in robot motion planning. Generally, shapes can be stored in a data base, so the elements that need to be decided are positions and orientations. In this paper, surface-based geometric modelling using a teaching tree is proposed. In this modelling, combinations of surfaces are considered in order to decide positions and orientations of objects. The combinations are represented by a depth-first tree, which makes it easy for the operator to select one combination out of several. This method is effective not only in the case when perfect data can be obtained, but also when conditions for measurement of three-dimensional data are unfavorable, which often occur in the environment of a working robot. (author)

  19. Applying multi-perspective spatial method to designing tree and shrub composition

    Directory of Open Access Journals (Sweden)

    Stoycheva M. S.


    Full Text Available the process of designing a harmonious tree and shrub composition requires multi-perspective painting. Not all the landscape designer’s artistic conceptions might be expressed by placing the tallest trees to the center of a room. We suggest a few simple steps, such as using a spatial method of painting and the multi-perspective system, in order to design a good looking composition from two perspectives at an angle 180° relative to each other.

  20. Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

    International Nuclear Information System (INIS)

    Purba, Julwan Hendry; Sony Tjahyani, D.T.; Ekariansyah, Andi Sofrany; Tjahjono, Hendro


    Highlights: • Fuzzy probability based fault tree analysis is to evaluate epistemic uncertainty in fuzzy fault tree analysis. • Fuzzy probabilities represent likelihood occurrences of all events in a fault tree. • A fuzzy multiplication rule quantifies epistemic uncertainty of minimal cut sets. • A fuzzy complement rule estimate epistemic uncertainty of the top event. • The proposed FPFTA has successfully evaluated the U.S. Combustion Engineering RPS. - Abstract: A number of fuzzy fault tree analysis approaches, which integrate fuzzy concepts into the quantitative phase of conventional fault tree analysis, have been proposed to study reliabilities of engineering systems. Those new approaches apply expert judgments to overcome the limitation of the conventional fault tree analysis when basic events do not have probability distributions. Since expert judgments might come with epistemic uncertainty, it is important to quantify the overall uncertainties of the fuzzy fault tree analysis. Monte Carlo simulation is commonly used to quantify the overall uncertainties of conventional fault tree analysis. However, since Monte Carlo simulation is based on probability distribution, this technique is not appropriate for fuzzy fault tree analysis, which is based on fuzzy probabilities. The objective of this study is to develop a fuzzy probability based fault tree analysis to overcome the limitation of fuzzy fault tree analysis. To demonstrate the applicability of the proposed approach, a case study is performed and its results are then compared to the results analyzed by a conventional fault tree analysis. The results confirm that the proposed fuzzy probability based fault tree analysis is feasible to propagate and quantify epistemic uncertainties in fault tree analysis

  1. Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models

    DEFF Research Database (Denmark)

    Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith


    ) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME......) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME ¼ 29.5%; N¼ 54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME¼ 31.5%; N ¼ 14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation...

  2. Deconvolution of the tree ring based delta13C record

    International Nuclear Information System (INIS)

    Peng, T.; Broecker, W.S.; Freyer, H.D.; Trumbore, S.


    We assumed that the tree-ring based 13 C/ 12 C record constructed by Freyer and Belacy (1983) to be representative of the fossil fuel and forest-soil induced 13 C/ 12 C change for atmospheric CO 2 . Through the use of a modification of the Oeschger et al. ocean model, we have computed the contribution of the combustion of coal, oil, and natural gas to this observed 13 C/ 12 C change. A large residual remains when the tree-ring-based record is corrected for the contribution of fossil fuel CO 2 . A deconvolution was performed on this residual to determine the time history and magnitude of the forest-soil reservoir changes over the past 150 years. Several important conclusions were reached. (1) The magnitude of the integrated CO 2 input from these sources was about 1.6 times that from fossil fuels. (2) The forest-soil contribution reached a broad maximum centered at about 1900. (3) Over the 2 decade period covered by the Mauna Loa atmospheric CO 2 content record, the input from forests and soils was about 30% that from fossil fuels. (4) The 13 C/ 12 C trend over the last 20 years was dominated by the input of fossil fuel CO 2 . (5) The forest-soil release did not contribute significantly to the secular increase in atmospheric CO 2 observed over the last 20 years. (6) The pre-1850 atmospheric p2 values must have been in the range 245 to 270 x 10 -6 atmospheres

  3. A New Tree-Type Fracturing Method for Stimulating Coal Seam Gas Reservoirs

    Directory of Open Access Journals (Sweden)

    Qian Li


    Full Text Available Hydraulic fracturing is used widely to stimulate coalbed methane production in coal mines. However, some factors associated with conventional hydraulic fracturing, such as the simple morphology of the fractures it generates and inhomogeneous stress relief, limit its scope of application in coal mines. These problems mean that gas extraction efficiency is low. Conventional fracturing may leave hidden pockets of gas, which will be safety hazards for subsequent coal mining operations. Based on a new drilling technique applicable to drilling boreholes in coal seams, this paper proposes a tree-type fracturing technique for stimulating reservoir volumes. Tree-type fracturing simulation experiments using a large-scale triaxial testing apparatus were conducted in the laboratory. In contrast to the single hole drilled for conventional hydraulic fracturing, the tree-type sub-boreholes induce radial and tangential fractures that form complex fracture networks. These fracture networks can eliminate the “blank area” that may host dangerous gas pockets. Gas seepage in tree-type fractures was analyzed, and gas seepage tests after tree-type fracturing showed that permeability was greatly enhanced. The equipment developed for tree-type fracturing was tested in the Fengchun underground coal mine in China. After implementing tree-type fracturing, the gas extraction rate was around 2.3 times greater than that for traditional fracturing, and the extraction rate remained high for a long time during a 30-day test. This shortened the gas drainage time and improved gas extraction efficiency.

  4. From a tree to a stand in Finnish boreal forests - biomass estimation and comparison of methods

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Chunjiang


    There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61deg50' N, 24deg22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg yr-1 for understorey spruce to 7 kg yr-1 for dominant pine) when the trees were 100 years old). Tree biomass was estimated to be about 70 Mg ha-1 in Young-Stand and about 220 Mg ha-1 in Mature-Stand. In the region (58.00-62.13 degN, 14-34 degE, <= 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg ha-1 at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg ha-1 with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg ha-1. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach. (orig.)


    Directory of Open Access Journals (Sweden)

    R. J. L. Argamosa


    Full Text Available The generation of high resolution canopy height model (CHM from LiDAR makes it possible to delineate individual tree crown by means of a fully-automated method using the CHM’s curvature through its slope. The local maxima are obtained by taking the maximum raster value in a 3 m x 3 m cell. These values are assumed as tree tops and therefore considered as individual trees. Based on the assumptions, thiessen polygons were generated to serve as buffers for the canopy extent. The negative profile curvature is then measured from the slope of the CHM. The results show that the aggregated points from a negative profile curvature raster provide the most realistic crown shape. The absence of field data regarding tree crown dimensions require accurate visual assessment after the appended delineated tree crown polygon was superimposed to the hill shaded CHM.

  6. DAG-based attack and defense modeling: don’t miss the forest for the attack trees

    NARCIS (Netherlands)

    Kordy, Barbara; Piètre-Cambacédès, Ludovic; Schweitzer, Patrick


    This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and

  7. a Comparison of Tree Segmentation Methods Using Very High Density Airborne Laser Scanner Data (United States)

    Pirotti, F.; Kobal, M.; Roussel, J. R.


    Developments of LiDAR technology are decreasing the unit cost per single point (e.g. single-photo counting). This brings to the possibility of future LiDAR datasets having very dense point clouds. In this work, we process a very dense point cloud ( 200 points per square meter), using three different methods for segmenting single trees and extracting tree positions and other metrics of interest in forestry, such as tree height distribution and canopy area distribution. The three algorithms are tested at decreasing densities, up to a lowest density of 5 point per square meter. Accuracy assessment is done using Kappa, recall, precision and F-Score metrics comparing results with tree positions from groundtruth measurements in six ground plots where tree positions and heights were surveyed manually. Results show that one method provides better Kappa and recall accuracy results for all cases, and that different point densities, in the range used in this study, do not affect accuracy significantly. Processing time is also considered; the method with better accuracy is several times slower than the other two methods and increases exponentially with point density. Best performer gave Kappa = 0.7. The implications of metrics for determining the accuracy of results of point positions' detection is reported. Motives for the different performances of the three methods is discussed and further research direction is proposed.

  8. FB-Tree: A B+-Tree for Flash-Based SSDs

    DEFF Research Database (Denmark)

    Jørgensen, Martin V.; Rasmussen, René B.; Saltenis, Simonas


    a modified index node is written, it is written to a new address, clustered with some other nodes that are written together. While this constantly frees index nodes, the FB-tree does not introduce any garbage-collection overhead, instead relying on naturally occurring free-space segments of sufficient size...

  9. Sequence comparison alignment-free approach based on suffix tree and L-words frequency. (United States)

    Soares, Inês; Goios, Ana; Amorim, António


    The vast majority of methods available for sequence comparison rely on a first sequence alignment step, which requires a number of assumptions on evolutionary history and is sometimes very difficult or impossible to perform due to the abundance of gaps (insertions/deletions). In such cases, an alternative alignment-free method would prove valuable. Our method starts by a computation of a generalized suffix tree of all sequences, which is completed in linear time. Using this tree, the frequency of all possible words with a preset length L-L-words--in each sequence is rapidly calculated. Based on the L-words frequency profile of each sequence, a pairwise standard Euclidean distance is then computed producing a symmetric genetic distance matrix, which can be used to generate a neighbor joining dendrogram or a multidimensional scaling graph. We present an improvement to word counting alignment-free approaches for sequence comparison, by determining a single optimal word length and combining suffix tree structures to the word counting tasks. Our approach is, thus, a fast and simple application that proved to be efficient and powerful when applied to mitochondrial genomes. The algorithm was implemented in Python language and is freely available on the web.

  10. Sequence Comparison Alignment-Free Approach Based on Suffix Tree and L-Words Frequency

    Directory of Open Access Journals (Sweden)

    Inês Soares


    Full Text Available The vast majority of methods available for sequence comparison rely on a first sequence alignment step, which requires a number of assumptions on evolutionary history and is sometimes very difficult or impossible to perform due to the abundance of gaps (insertions/deletions. In such cases, an alternative alignment-free method would prove valuable. Our method starts by a computation of a generalized suffix tree of all sequences, which is completed in linear time. Using this tree, the frequency of all possible words with a preset length L—L-words—in each sequence is rapidly calculated. Based on the L-words frequency profile of each sequence, a pairwise standard Euclidean distance is then computed producing a symmetric genetic distance matrix, which can be used to generate a neighbor joining dendrogram or a multidimensional scaling graph. We present an improvement to word counting alignment-free approaches for sequence comparison, by determining a single optimal word length and combining suffix tree structures to the word counting tasks. Our approach is, thus, a fast and simple application that proved to be efficient and powerful when applied to mitochondrial genomes. The algorithm was implemented in Python language and is freely available on the web.

  11. Water and forests in the Mediterranean hot climate zone: a review based on a hydraulic interpretation of tree functioning

    Energy Technology Data Exchange (ETDEWEB)

    Soares David, T.; Assunção Pinto, C.; Nadezhdina, N.; Soares David, J.


    Aim of the study: Water scarcity is the main limitation to forest growth and tree survival in the Mediterranean hot climate zone. This paper reviews literature on the relations between water and forests in the region, and their implications on forest and water resources management. The analysis is based on a hydraulic interpretation of tree functioning. Area of the study: The review covers research carried out in the Mediterranean hot climate zone, put into perspective of wider/global research on the subject. The scales of analysis range from the tree to catchment levels. Material and Methods: For literature review we used Sc opus, Web of Science and Go ogle Scholar as bibliographic databases. Data from two Quercus suber sites in Portugal were used for illustrative purposes. Main results: We identify knowledge gaps and discuss options to better adapt forest management to climate change under a tree water use/availability perspective. Forest management is also discussed within the wider context of catchment water balance: water is a constraint for biomass production, but also for other human activities such as urban supply, industry and irrigated agriculture. Research highlights: Given the scarce and variable (in space and in time) water availability in the region, further research is needed on: mapping the spatial heterogeneity of water availability to trees; adjustment of tree density to local conditions; silviculture practices that do not damage soil properties or roots; irrigation of forest plantations in some specific areas; tree breeding. Also, a closer cooperation between forest and water managers is needed. (Author)

  12. A method of detecting carbonyl compounds in tree leaves in China. (United States)

    Huang, Juan; Feng, Yanli; Fu, Jiamo; Sheng, Guoying


    Carbonyl compounds have been paid more and more attention because some carbonyl species have been proven to be carcinogenic or a risk for human health. Plant leaves are both an important emission source and an important sink of carbonyl compounds. But the research on carbonyl compounds from plant leaves is very scarce. In order to make an approach to the emission mechanism of plant leaves, a new method was established to extract carbonyl compounds from fresh plant leaves. The procedure combining derivatization with ultrasonication was developed for the fast extraction of carbonyl compounds from tree leaves. Fresh leaves (trees, i.e., camphor tree (Cinnamomum camphora), sweet olive (Osmanthus fragrans), cedar (Cedrus deodara), and dawn redwood (Metasequoia glyptostroboides), were selected and extracted by this method. Seven carbonyl compounds, including formaldehyde, acetaldehyde, acetone, acrolein, p-tolualdehyde, m/o-tolualdehyde, and hexaldehyde were determined and quantified. The most common carbonyl species of the four tree leaves were formaldehyde, acrolein, and m/o-tolualdehyde. They accounted for 67.3% in cedar, 50.8% in sweet olive, 45.8% in dawn redwood, and 44.6% in camphor tree, respectively. Camphor tree had the highest leaf level of m/o-tolualdehyde with 15.0 +/- 3.4 microg g(-1)(fresh leaf weight), which indicated that camphor tree may be a bioindicator of the level of tolualdehyde or xylene in the atmosphere. By analyzing carbonyl compounds from different tree leaves, it is not only helpful for further studying the relationship between sink and emission of carbonyls from plants, but also helpful for exploring optimum plant population in urban greening.

  13. Dissimilarity-based classification of anatomical tree structures

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs; Lo, Pechin Chien Pau; Dirksen, Asger


    between the branch feature vectors representing those trees. Hereby, localized information in the branches is collectively used in classification and variations in feature values across the tree are taken into account. An approximate anatomical correspondence between matched branches can be achieved...

  14. Abstract interpretation over non-deterministic finite tree automate for set-based analysis of logic programs

    DEFF Research Database (Denmark)

    Gallagher, John Patrick; Puebla, G.


    Set-based program analysis has many potential applications, including compiler optimisations, type-checking, debugging, verification and planning. One method of set-based analysis is to solve a set of {\\it set constraints} derived directly from the program text. Another approach is based...... constraint analysis of a particular program $P$ could be understood as an abstract interpretation over a finite domain of regular tree grammars, constructed from $P$. In this paper we define such an abstract interpretation for logic programs, formulated over a domain of non-deterministic finite tree automata...

  15. f-treeGC: a questionnaire-based family tree-creation software for genetic counseling and genome cohort studies. (United States)

    Tokutomi, Tomoharu; Fukushima, Akimune; Yamamoto, Kayono; Bansho, Yasushi; Hachiya, Tsuyoshi; Shimizu, Atsushi


    The Tohoku Medical Megabank project aims to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the areas affected by the Great East Japan Earthquake. We collected medical and genomic information for developing a biobank to be used for this healthcare system. We designed a questionnaire-based pedigree-creation software program named "f-treeGC," which enables even less experienced medical practitioners to accurately and rapidly collect family health history and create pedigree charts. f-treeGC may be run on Adobe AIR. Pedigree charts are created in the following manner: 1) At system startup, the client is prompted to provide required information on the presence or absence of children; f-treeGC is capable of creating a pedigree up to three generations. 2) An interviewer fills out a multiple-choice questionnaire on genealogical information. 3) The information requested includes name, age, gender, general status, infertility status, pregnancy status, fetal status, and physical features or health conditions of individuals over three generations. In addition, information regarding the client and the proband, and birth order information, including multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included. 4) f-treeGC shows only marriages between first cousins via the overlay function. 5) f-treeGC automatically creates a pedigree chart, and the chart-creation process is visible for inspection on the screen in real time. 6) The genealogical data may be saved as a file in the original format. The created/modified date and time may be changed as required, and the file may be password-protected and/or saved in read-only format. To enable sorting or searching from the database, the file name automatically contains the terms typed into the entry fields, including physical features or health conditions, by default. 7

  16. Calibration of the Diameter Distribution Derived from the Area-based Approach with Individual Tree-based Diameter Estimates Using the Airborne Laser Scanning (United States)

    Xu, Q.; Hou, Z.; Maltamo, M.; Tokola, T.


    Diameter distributions of trees are important indicators of current forest stand structure and future dynamics. A new method was proposed in the study to combine the diameter distributions derived from the area-based approach (ABA) and the diameter distribution derived from the individual tree detection (ITD) in order to obtain more accurate forest stand attributes. Since dominant trees can be reliably detected and measured by the Lidar data via the ITD, the focus of the study is to retrieve the suppressed trees (trees that were missed by the ITD) from the ABA. Replacement and histogram matching were respectively employed at the plot level to retrieve the suppressed trees. Cut point was detected from the ITD-derived diameter distribution for each sample plot to distinguish dominant trees from the suppressed trees. The results showed that calibrated diameter distributions were more accurate in terms of error index and the entire growing stock estimates. Compared with the best performer between the ABA and the ITD, calibrated diameter distributions decreased the relative RMSE of the estimated entire growing stock, saw log and pulpwood fractions by 2.81%, 3.05% and 7.73% points respectively. Calibration improved the estimation of pulpwood fraction significantly, resulting in a negligible bias of the estimated entire growing stock.

  17. Computer-aided event tree analysis by the impact vector method

    International Nuclear Information System (INIS)

    Lima, J.E.P.


    In the development of the Probabilistic Risk Analysis of Angra I, the ' large event tree/small fault tree' approach was adopted for the analysis of the plant behavior in an emergency situation. In this work, the event tree methodology is presented along with the adaptations which had to be made in order to attain a correct description of the safety system performances according to the selected analysis method. The problems appearing in the application of the methodology and their respective solutions are presented and discussed, with special emphasis to the impact vector technique. A description of the ETAP code ('Event Tree Analysis Program') developed for constructing and quantifying event trees is also given in this work. A preliminary version of the small-break LOCA analysis for Angra 1 is presented as an example of application of the methodology and of the code. It is shown that the use of the ETAP code sigmnificantly contributes to decreasing the time spent in event tree analyses, making it viable the practical application of the analysis approach referred above. (author) [pt

  18. Analytical method for the evaluation of the outdoor air contamination by emerging pollutants using tree leaves as bioindicators. (United States)

    Barroso, Pedro José; Martín, Julia; Santos, Juan Luis; Aparicio, Irene; Alonso, Esteban


    In this work, an analytical method, based on sonication-assisted extraction, clean-up by dispersive solid-phase extraction and determination by liquid chromatography-tandem mass spectrometry, has been developed and validated for the simultaneous determination of 15 emerging pollutants in leaves from four ornamental tree species. Target compounds include perfluorinated organic compounds, plasticizers, surfactants, brominated flame retardant, and preservatives. The method was optimized using Box-Behnken statistical experimental design with response surface methodology and validated in terms of recovery, accuracy, precision, and method detection and quantification limits. Quantification of target compounds was carried out using matrix-matched calibration curves. The highest recoveries were achieved for the perfluorinated organic compounds (mean values up to 87%) and preservatives (up to 88%). The lowest recoveries were achieved for plasticizers (51%) and brominated flame retardant (63%). Method detection and quantification limits were in the ranges 0.01-0.09 ng/g dry matter (dm) and 0.02-0.30 ng/g dm, respectively, for most of the target compounds. The method was successfully applied to the determination of the target compounds on leaves from four tree species used as urban ornamental trees (Citrus aurantium, Celtis australis, Platanus hispanica, and Jacaranda mimosifolia). Graphical abstract Analytical method for the biomonitorization of emerging pollutants in outdoor air.


    Directory of Open Access Journals (Sweden)

    Breno Rodrigues Mendes


    Full Text Available This study generate individual tree non-linear models from differential equation and evaluated the adjustment quality to express the basal area growth. The data base is from continuous forest inventory of clonal Eucalyptus spp. plantations, given by Aracruz Cellulose Company, located in the Brazilian costal region, Bahia and Espirito Santo states. The model precision was verified by ratio likelihood test, by mean square error (MSE and by graphical residual analysis. The results showed that the complete model with 3 parameters, developed from the original model with one regressor, was superior to the other models, due to the inclusion of stand based variables, such as: clone, total height (HT, dominant height (HD, quadratic diameter (Dg, Basal Area (G, site index (IS and Density (N, generating a new model, called Complete Model III. The improvement of the precision was highly significant when compared to another models. Consequently, this model provides information with a high degree of precision and accuracy for the forest companies planning.

  20. Water and forests in the Mediterranean hot climate zone: a review based on a hydraulic interpretation of tree functioning

    Directory of Open Access Journals (Sweden)

    Teresa Soares David


    Full Text Available Aim of the study: Water scarcity is the main limitation to forest growth and tree survival in the Mediterranean hot climate zone. This paper reviews literature on the relations between water and forests in the region, and their implications on forest and water resources management. The analysis is based on a hydraulic interpretation of tree functioning. Area of the study: The review covers research carried out in the Mediterranean hot climate zone, put into perspective of wider/global research on the subject. The scales of analysis range from the tree to catchment levels. Material and Methods: For literature review we used Scopus, Web of Science and Google Scholar as bibliographic databases. Data from two Quercus suber sites in Portugal were used for illustrative purposes. Main results: We identify knowledge gaps and discuss options to better adapt forest management to climate change under a tree water use/availability perspective. Forest management is also discussed within the wider context of catchment water balance: water is a constraint for biomass production, but also for other human activities such as urban supply, industry and irrigated agriculture. Research highlights: Given the scarce and variable (in space and in time water availability in the region, further research is needed on: mapping the spatial heterogeneity of water availability to trees; adjustment of tree density to local conditions; silvicultural practices that do not damage soil properties or roots; irrigation of forest plantations in some specific areas; tree breeding. Also, a closer cooperation between forest and water managers is needed. Keywords: tree hydraulics; tree mortality; climate change; forest management; water resources.

  1. Logistic Regression-Based Trichotomous Classification Tree and Its Application in Medical Diagnosis. (United States)

    Zhu, Yanke; Fang, Jiqian


    The classification tree is a valuable methodology for predictive modeling and data mining. However, the current existing classification trees ignore the fact that there might be a subset of individuals who cannot be well classified based on the information of the given set of predictor variables and who might be classified with a higher error rate; most of the current existing classification trees do not use the combination of variables in each step. An algorithm of a logistic regression-based trichotomous classification tree (LRTCT) is proposed that employs the trichotomous tree structure and the linear combination of predictor variables in the recursive partitioning process. Compared with the widely used classification and regression tree through the applications on a series of simulated data and 2 real data sets, the LRTCT performed better in several aspects and does not require excessive complicated calculations. © The Author(s) 2016.

  2. Estimating Uncertainty of Point-Cloud Based Single-Tree Segmentation with Ensemble Based Filtering

    Directory of Open Access Journals (Sweden)

    Matthew Parkan


    Full Text Available Individual tree crown segmentation from Airborne Laser Scanning data is a nodal problem in forest remote sensing. Focusing on single layered spruce and fir dominated coniferous forests, this article addresses the problem of directly estimating 3D segment shape uncertainty (i.e., without field/reference surveys, using a probabilistic approach. First, a coarse segmentation (marker controlled watershed is applied. Then, the 3D alpha hull and several descriptors are computed for each segment. Based on these descriptors, the alpha hulls are grouped to form ensembles (i.e., groups of similar tree shapes. By examining how frequently regions of a shape occur within an ensemble, it is possible to assign a shape probability to each point within a segment. The shape probability can subsequently be thresholded to obtain improved (filtered tree segments. Results indicate this approach can be used to produce segmentation reliability maps. A comparison to manually segmented tree crowns also indicates that the approach is able to produce more reliable tree shapes than the initial (unfiltered segmentation.

  3. Research Note A novel method for estimating tree dimensions and ...

    African Journals Online (AJOL)

    The method requires a photograph be taken of the measuring staff placed next to an object whose measurements are to be determined. The two objects must be adjacent to one another in the photograph. For rapid analysis, multiple photographs of different objects can be taken over a short period of time using the ...

  4. A method for generating stochastic 3D tree models with Python in Autodesk Maya

    Directory of Open Access Journals (Sweden)

    Nemanja Stojanović


    Full Text Available This paper introduces a method for generating 3D tree models using stochastic L-systems with stochastic parameters and Perlin noise. L-system is the most popular method for plant modeling and Perlin noise is extensively used for generating high detailed textures. Our approach is probabilistic. L-systems with a random choice of parameters can represent observed objects quite well and they are used for modeling and generating realistic plants. Textures and normal maps are generated with combinations of Perlin noises what make these trees completely unique. Script for generating these trees, textures and normal maps is written with Python/PyMEL/NumPy in Autodesk Maya.

  5. Incident sequence analysis; event trees, methods and graphical symbols

    International Nuclear Information System (INIS)


    When analyzing incident sequences, unwanted events resulting from a certain cause are looked for. Graphical symbols and explanations of graphical representations are presented. The method applies to the analysis of incident sequences in all types of facilities. By means of the incident sequence diagram, incident sequences, i.e. the logical and chronological course of repercussions initiated by the failure of a component or by an operating error, can be presented and analyzed simply and clearly

  6. A quantitative analysis of secondary RNA structure using domination based parameters on trees

    Directory of Open Access Journals (Sweden)

    Zou Yue


    Full Text Available Abstract Background It has become increasingly apparent that a comprehensive database of RNA motifs is essential in order to achieve new goals in genomic and proteomic research. Secondary RNA structures have frequently been represented by various modeling methods as graph-theoretic trees. Using graph theory as a modeling tool allows the vast resources of graphical invariants to be utilized to numerically identify secondary RNA motifs. The domination number of a graph is a graphical invariant that is sensitive to even a slight change in the structure of a tree. The invariants selected in this study are variations of the domination number of a graph. These graphical invariants are partitioned into two classes, and we define two parameters based on each of these classes. These parameters are calculated for all small order trees and a statistical analysis of the resulting data is conducted to determine if the values of these parameters can be utilized to identify which trees of orders seven and eight are RNA-like in structure. Results The statistical analysis shows that the domination based parameters correctly distinguish between the trees that represent native structures and those that are not likely candidates to represent RNA. Some of the trees previously identified as candidate structures are found to be "very" RNA like, while others are not, thereby refining the space of structures likely to be found as representing secondary RNA structure. Conclusion Search algorithms are available that mine nucleotide sequence databases. However, the number of motifs identified can be quite large, making a further search for similar motif computationally difficult. Much of the work in the bioinformatics arena is toward the development of better algorithms to address the computational problem. This work, on the other hand, uses mathematical descriptors to more clearly characterize the RNA motifs and thereby reduce the corresponding search space. These

  7. Use of casual tree method for investigation of incidents and accidents involving radioactive materials

    International Nuclear Information System (INIS)

    Vasconcelos, Vanderley de; Senne Junior, Murillo; Marques, Raissa Oliveira


    There are many methodologies used for investigation of accidents to facilitate the search of the factors that cause these events in different areas of industry. These can be called proactive methods, if they are used before the occurrence of the events, or reactive methods that are applied after the occurrence of the incident or accident, and are used as a basis of information to prevent further events. One of these methods is the Causal Tree Method (CTM). The basic idea of this technique is that incidents and accidents result from variations in usual processes. These variations can be related to the individual, the task, the material or the environment. The tree starts with the end event (incident or accident) and works backwards. The facts relating to the end event are used in the construction of the causal tree. The end event is the starting point and only the facts that contributed to the incident or accident should be selected. The analyst has to identify and list the variations and then display them in the analytic tree, showing causal relations. The objective of this paper is to test the application of the CTM method in investigation of incidents and accidents involving radioactive materials, in order to evaluate its efficiency on finding the typical factors causing these events. (author)

  8. BTNET : boosted tree based gene regulatory network inference algorithm using time-course measurement data. (United States)

    Park, Sungjoon; Kim, Jung Min; Shin, Wonho; Han, Sung Won; Jeon, Minji; Jang, Hyun Jin; Jang, Ik-Soon; Kang, Jaewoo


    Identifying gene regulatory networks is an important task for understanding biological systems. Time-course measurement data became a valuable resource for inferring gene regulatory networks. Various methods have been presented for reconstructing the networks from time-course measurement data. However, existing methods have been validated on only a limited number of benchmark datasets, and rarely verified on real biological systems. We first integrated benchmark time-course gene expression datasets from previous studies and reassessed the baseline methods. We observed that GENIE3-time, a tree-based ensemble method, achieved the best performance among the baselines. In this study, we introduce BTNET, a boosted tree based gene regulatory network inference algorithm which improves the state-of-the-art. We quantitatively validated BTNET on the integrated benchmark dataset. The AUROC and AUPR scores of BTNET were higher than those of the baselines. We also qualitatively validated the results of BTNET through an experiment on neuroblastoma cells treated with an antidepressant. The inferred regulatory network from BTNET showed that brachyury, a transcription factor, was regulated by fluoxetine, an antidepressant, which was verified by the expression of its downstream genes. We present BTENT that infers a GRN from time-course measurement data using boosting algorithms. Our model achieved the highest AUROC and AUPR scores on the integrated benchmark dataset. We further validated BTNET qualitatively through a wet-lab experiment and showed that BTNET can produce biologically meaningful results.

  9. Automated Tree Crown Delineation and Biomass Estimation from Airborne LiDAR data: A Comparison of Statistical and Machine Learning Methods (United States)

    Gleason, C. J.; Im, J.


    Airborne LiDAR remote sensing has been used effectively in assessing forest biomass because of its canopy penetrating effects and its ability to accurately describe the canopy surface. Current research in assessing biomass using airborne LiDAR focuses on either the individual tree as a base unit of study or statistical representations of a small aggregation of trees (i.e., plot level), and both methods usually rely on regression against field data to model the relationship between the LiDAR-derived data (e.g., volume) and biomass. This study estimates biomass for mixed forests and coniferous plantations (Picea Abies) within Heiberg Memorial Forest, Tully, NY, at both the plot and individual tree level. Plots are regularly spaced with a radius of 13m, and field data include diameter at breast height (dbh), tree height, and tree species. Field data collection and LiDAR data acquisition were seasonally coincident and both obtained in August of 2010. Resulting point cloud density was >5pts/m2. LiDAR data were processed to provide a canopy height surface, and a combination of watershed segmentation, active contouring, and genetic algorithm optimization was applied to delineate individual trees from the surface. This updated delineation method was shown to be more accurate than traditional watershed segmentation. Once trees had been delineated, four biomass estimation models were applied and compared: support vector regression (SVR), linear mixed effects regression (LME), random forest (RF), and Cubist regression. Candidate variables to be used in modeling were derived from the LiDAR surface, and include metrics of height, width, and volume per delineated tree footprint. Previously published allometric equations provided field estimates of biomass to inform the regressions and calculate their accuracy via leave-one-out cross validation. This study found that for forests such as found in the study area, aggregation of individual trees to form a plot-based estimate of

  10. Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia. (United States)

    Henrard, S; Speybroeck, N; Hermans, C


    Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.


    Directory of Open Access Journals (Sweden)

    E. I. Kobysh


    Full Text Available In this paper was developed the control system of group of hot blast stoves, which operates on the basis of the packing heating control subsystem and subsystem of forecasting of modes duration in the hot blast stoves APCS of iron smelting in a blast furnace. With the use of multi-criteria optimization methods, implemented the adjustment of control system conduct, which takes into account the current production situation that has arisen in the course of the heating packing of each hot blast stove group. Developed a situation recognition algorithm and the choice of scenarios of control based on a decision tree.

  12. Genetic diversity among coffee tree progenies Big Coffee VL based on growth traits and production. (United States)

    Silva, J A; Carvalho, S P; Bruzi, A T; Guimarães, R J; Oliveira, L L; Simões, L C


    In a coffee plantation of a coffee 'Acaiá' cultivar (Coffea arabica), on the Midwest of Minas Gerais in Capitólio city, a different kind of coffee tree was found (1989), possibly due to a mutation. It presented larger leaves and grains than those of conventional coffee trees and was named as "Big Coffee VL." The aim of this study was to estimate the genetic diversity of Big Coffee VL progenies cultivated at Universidade Federal de Lavras, by evaluating growth and production traits, based on genetic distances and clusters. The experiment was established in a lattice design with 100 progenies of this coffee tree and 23 repetitions. Traits evaluated were vigor, plant height, stem diameter, node number of plagiotropic branches, pair numbers of plagiotropic branches, and productivity. Genetic divergence was evaluated by multivariate procedures: Mahalanobis generalized distance, clustering methods, and principal component analysis. Genetic distances were estimated using Mahalanobis distance and presented variations from 0.04 to 18.70. The most similar progenies were P23 and P29 and the most dissimilar progenies were G8 and P14. The progenies were divided into three groups, with P14 present as an isolated group. Thus, it was possible to observe the existence of genetic variability among the progenies of Big Coffee VL, which can be used in breeding programs to increase grain size. Progenies G8 and P14 presented the highest genetic distance, and were the most suitable for future integration of crossings in plant breeding programs.

  13. Genealogical tree study as screening method in the Lynch syndrome prior to genetic test. (United States)

    Delgado-Plasencia, Luciano; Medina-Arana, Vicente; Barrios Del Pino, Ysamar; Fernández-Peralta, Antonia; González-Aguilera, Juan J


    Despite genetic advances in the study of Lynch syndrome (LS), difficulties remain in the diagnosis of the syndrome. The aim of this study was to assess the usefulness of a detailed genealogical tree as a screening method to identify Tenerife island families with a high probability of LS. We elaborated complete genealogical trees of the families. According to the degree of fulfillment of the Amsterdam Criteria II, the genealogical trees were classified as high or low probability of LS. Additionally, we analyzed the level of tumor microsatellite instability (MSI+) and identified a mutation in exon 13 of the MSH2 gene by single-strand conformation polymorphism, sequencing, and PCR-RFLP. According the genealogical trees, we found 10 families with high probability of LS and 30 families with low probability of LS. The families with high probability of LS showed high MSI+ in all cases. Conversely, families with low probability were MSS (microsatellite stable). In 5 of the 10 families with high probability, we discovered a T-->G mutation in position 688 of exon 13 of MSH2, which appeared in all the family members with the tumor, except 1 patient with a retinoblastoma. Our results indicate that genealogical tree is a highly effective tool for classifying families with a high probability of Lynch Syndrome prior to genetic test.

  14. CoVennTree: A new method for the comparative analysis of large datasets

    Directory of Open Access Journals (Sweden)

    Steffen C. Lott


    Full Text Available The visualization of massive datasets, such as those resulting from comparative metatranscriptome analyses or the analysis of microbial population structures using ribosomal RNA sequences, is a challenging task. We developed a new method called CoVennTree (Comparative weighted Venn Tree that simultaneously compares up to three multifarious datasets by aggregating and propagating information from the bottom to the top level and produces a graphical output in Cytoscape. With the introduction of weighted Venn structures, the contents and relationships of various datasets can be correlated and simultaneously aggregated without losing information. We demonstrate the suitability of this approach using a dataset of 16S rDNA sequences obtained from microbial populations at three different depths of the Gulf of Aqaba in the Red Sea. CoVennTree has been integrated into the Galaxy ToolShed and can be directly downloaded and integrated into the user instance.

  15. Understanding the Roles of Forests and Tree-based Systems in Food Provision

    NARCIS (Netherlands)

    Jamnadass, R.; McMullin, S.; Dawson, M.I.I.K.; Powell, B.; Termote, C.; Lckowitz, A.; Kehlenbeck, K.; Vinceti, B.; Vliet, van N.; Keding, G.; Stadlmayr, B.; Damme, van P.; Carsan, S.; Sunderland, T.; Njenga, M.; Gyau, A.; Cerutti, P.; Schure, J.M.; Kouame, C.; Obiri, B.D.; Ofori, D.; Agarwal, B.; Neufeldt, H.; Degrande, A.; Serban, A.


    Forests and other tree-based systems such as agroforestry contribute to food and nutritional security in myriad ways. Directly, trees provide a variety of healthy foods including fruits, leafy vegetables, nuts, seeds and edible oils that can diversify diets and address seasonal food and nutritional

  16. A structurally based analytic model for estimation of biomass and fuel loads of woodland trees (United States)

    Robin J. Tausch


    Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of...

  17. Detecting Difference between Process Models Based on the Refined Process Structure Tree

    Directory of Open Access Journals (Sweden)

    Jing Fan


    Full Text Available The development of mobile workflow management systems (mWfMS leads to large number of business process models. In the meantime, the location restriction embedded in mWfMS may result in different process models for a single business process. In order to help users quickly locate the difference and rebuild the process model, detecting the difference between different process models is needed. Existing detection methods either provide a dissimilarity value to represent the difference or use predefined difference template to generate the result, which cannot reflect the entire composition of the difference. Hence, in this paper, we present a new approach to solve this problem. Firstly, we parse the process models to their corresponding refined process structure trees (PSTs, that is, decomposing a process model into a hierarchy of subprocess models. Then we design a method to convert the PST to its corresponding task based process structure tree (TPST. As a consequence, the problem of detecting difference between two process models is transformed to detect difference between their corresponding TPSTs. Finally, we obtain the difference between two TPSTs based on the divide and conquer strategy, where the difference is described by an edit script and we make the cost of the edit script close to minimum. The extensive experimental evaluation shows that our method can meet the real requirements in terms of precision and efficiency.

  18. Geodesic atlas-based labeling of anatomical trees

    DEFF Research Database (Denmark)

    Feragen, Aasa; Petersen, Jens; Owen, Megan


    topology and geometry change continuously, giving a natural automatic handling of anatomical differences and noise. A hierarchical approach makes the algorithm efficient, assigning labels from the trachea and downwards. Only the airway centerline tree is used, which is relatively unaffected by pathology....... The algorithm is evaluated on 80 segmented airway trees from 40 subjects at two time points, labeled by 3 medical experts each, testing accuracy, reproducibility and robustness in patients with Chronic Obstructive Pulmonary Disease (COPD). The accuracy of the algorithm is statistically similar...... to that of the experts and not significantly correlated with COPD severity. The reproducibility of the algorithm is significantly better than that of the experts, and negatively correlated with COPD severity. Evaluation of the algorithm on a longitudinal set of 8724 trees from a lung cancer screening trial shows...

  19. An application of the explicit method for analysing intersystem dependencies in the evaluation of event trees

    International Nuclear Information System (INIS)

    Oliveira, L.F.S. de; Frutuoso e Melo, P.F.F.; Lima, J.E.P.; Stal, I.L.


    A computacional application of the explicit method for analyzing event trees in the context of probabilistic risk assessments is discussed. A detailed analysis of the explicit method is presented, including the train level analysis (TLA) of safety systems and the impact vector method. It is shown that the penalty for not adopting TLA is that in some cases non-conservative results may be reached. The impact vector method can significantly reduce the number of sequences to be considered, and its use has inspired the definition of a dependency matrix, which enables the proper running of a computer code especially developed for analysing event trees. The code has been extensively used in the Angra 1 PRA currently underway. In its present version it gives as output the dominant sequences for each given initiator, properly classiying them in core-degradation classes as specified by the user. (Author) [pt

  20. MASSAHAKE whole tree harvesting method for pulp raw-material and fuel -- R&D in 1993--1998

    Energy Technology Data Exchange (ETDEWEB)

    Asplund, D.A.; Ahonen, M.A. [Technical Research Centre of Finland, Jyvaeskylae (Finland)


    In Finland biofuels and hydropower are the only indigenous fuels available. Peat, wood and wood derived fuels form about 18% of total primary energy requirement. The largest wood and wood fuel user in Finland is wood processing industry, paper, pulp, sawmills. Due to silvicultural activities the growth of forests has developed an instant need for first thinnings. This need is about 12% of total stem wood growth. With conventional harvesting methods this would produce about 8 mill. m{sup 3} pulp raw material and 2 mill. m{sup 3} wood fuel. By using integrated harvesting methods about 12 mill. m{sup 3} pulp raw material and 8 mill. m{sup 3} (about 1, 3 mill. toe) fuel could be produced. At the moment, there is no economically profitable method for harvesting first thinning trees for industrial use or energy production. Hence, there are a few ongoing research projects aiming at solving the question of integrated harvesting. MASSAHAKE chip purification method has been under R&D since 1987. Research with continuous experimental line (capacity 5--10 loose-m{sup 3}) has been done in 1991 and 1992. The research has concentrated on pine whole tree chip treatment, but preliminary tests with birch whole tree chips has been done. The experiment line will be modified for birth whole tree chips during 1993. Based on the research results more than 60% of the whole tree chips can be separated to pulp raw material with < 1% bark content. This amount is 1.5--2 times more than with present technology. The yield of fuel fraction is 2--4 times higher compared to present methods. Fuel fraction is homogeneous and could be used in most furnaces for energy production. By replacing fossil fuels with wood fuel in energy production it is possible to reduce CO{sub 2}-emissions significantly. This paper presents the wood fuel research areas in Finland and technical potential of MASSAHAKE-method including the plant for building a demonstration plant based on this technology.

  1. Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B. (United States)

    Chen, Xiao Yu; Ma, Li Zhuang; Chu, Na; Zhou, Min; Hu, Yiyang


    Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.

  2. A Novel Path Planning for Robots Based on Rapidly-Exploring Random Tree and Particle Swarm Optimizer Algorithm

    Directory of Open Access Journals (Sweden)

    Zhou Feng


    Full Text Available A based on Rapidly-exploring Random Tree(RRT and Particle Swarm Optimizer (PSO for path planning of the robot is proposed.First the grid method is built to describe the working space of the mobile robot,then the Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path,and the Particle Swarm Optimizer algorithm is adopted to get the better path.Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment.The successful obstacle avoidance is achieved,and the model is robust and performs reliably.

  3. Identification of Potential Sources of Mercury (Hg in Farmland Soil Using a Decision Tree Method in China

    Directory of Open Access Journals (Sweden)

    Taiyang Zhong


    Full Text Available Identification of the sources of soil mercury (Hg on the provincial scale is helpful for enacting effective policies to prevent further contamination and take reclamation measurements. The natural and anthropogenic sources and their contributions of Hg in Chinese farmland soil were identified based on a decision tree method. The results showed that the concentrations of Hg in parent materials were most strongly associated with the general spatial distribution pattern of Hg concentration on a provincial scale. The decision tree analysis gained an 89.70% total accuracy in simulating the influence of human activities on the additions of Hg in farmland soil. Human activities—for example, the production of coke, application of fertilizers, discharge of wastewater, discharge of solid waste, and the production of non-ferrous metals—were the main external sources of a large amount of Hg in the farmland soil.

  4. Identification of Potential Sources of Mercury (Hg) in Farmland Soil Using a Decision Tree Method in China. (United States)

    Zhong, Taiyang; Chen, Dongmei; Zhang, Xiuying


    Identification of the sources of soil mercury (Hg) on the provincial scale is helpful for enacting effective policies to prevent further contamination and take reclamation measurements. The natural and anthropogenic sources and their contributions of Hg in Chinese farmland soil were identified based on a decision tree method. The results showed that the concentrations of Hg in parent materials were most strongly associated with the general spatial distribution pattern of Hg concentration on a provincial scale. The decision tree analysis gained an 89.70% total accuracy in simulating the influence of human activities on the additions of Hg in farmland soil. Human activities-for example, the production of coke, application of fertilizers, discharge of wastewater, discharge of solid waste, and the production of non-ferrous metals-were the main external sources of a large amount of Hg in the farmland soil.

  5. Applying and Individual-Based Model to Simultaneously Evaluate Net Ecosystem Production and Tree Diameter Increment (United States)

    Fang, F. J.


    Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.

  6. Contemporary Trends in Farmer-Based Tree Management and ...

    African Journals Online (AJOL)

    This paper examines the contemporary trends in tree growing and management in the context of changing farmer livelihood systems in southeastern Nigeria. Data were collected in 1998-99 through a field survey involving interviews with 160 households drawn from 8 rural communities across the different agroecological ...

  7. Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics (United States)

    Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)


    This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

  8. Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level

    Directory of Open Access Journals (Sweden)

    Roope Näsi


    Full Text Available Low-cost, miniaturized hyperspectral imaging technology is becoming available for small unmanned aerial vehicle (UAV platforms. This technology can be efficient in carrying out small-area inspections of anomalous reflectance characteristics of trees at a very high level of detail. Increased frequency and intensity of insect induced forest disturbance has established a new demand for effective methods suitable in mapping and monitoring tasks. In this investigation, a novel miniaturized hyperspectral frame imaging sensor operating in the wavelength range of 500–900 nm was used to identify mature Norway spruce (Picea abies L. Karst. trees suffering from infestation, representing a different outbreak phase, by the European spruce bark beetle (Ips typographus L.. We developed a new processing method for analyzing spectral characteristic for high spatial resolution photogrammetric and hyperspectral images in forested environments, as well as for identifying individual anomalous trees. The dense point clouds, measured using image matching, enabled detection of single trees with an accuracy of 74.7%. We classified the trees into classes of healthy, infested and dead, and the results were promising. The best results for the overall accuracy were 76% (Cohen’s kappa 0.60, when using three color classes (healthy, infested, dead. For two color classes (healthy, dead, the best overall accuracy was 90% (kappa 0.80. The survey methodology based on high-resolution hyperspectral imaging will be of a high practical value for forest health management, indicating a status of bark beetle outbreak in time.

  9. Low frequency full waveform seismic inversion within a tree based Bayesian framework (United States)

    Ray, Anandaroop; Kaplan, Sam; Washbourne, John; Albertin, Uwe


    Limited illumination, insufficient offset, noisy data and poor starting models can pose challenges for seismic full waveform inversion. We present an application of a tree based Bayesian inversion scheme which attempts to mitigate these problems by accounting for data uncertainty while using a mildly informative prior about subsurface structure. We sample the resulting posterior model distribution of compressional velocity using a trans-dimensional (trans-D) or Reversible Jump Markov chain Monte Carlo method in the wavelet transform domain of velocity. This allows us to attain rapid convergence to a stationary distribution of posterior models while requiring a limited number of wavelet coefficients to define a sampled model. Two synthetic, low frequency, noisy data examples are provided. The first example is a simple reflection + transmission inverse problem, and the second uses a scaled version of the Marmousi velocity model, dominated by reflections. Both examples are initially started from a semi-infinite half-space with incorrect background velocity. We find that the trans-D tree based approach together with parallel tempering for navigating rugged likelihood (i.e. misfit) topography provides a promising, easily generalized method for solving large-scale geophysical inverse problems which are difficult to optimize, but where the true model contains a hierarchy of features at multiple scales.

  10. A family tree of methyl oleate-based compounds (United States)

    A family of compounds starting with potentially bio-based methyl oleate have been synthesized through a variety of chemical methods. Grandpa EMO (Epoxidized Methyl Oleate) is the most well represented in terms of ancestors, but other catalytic cousins are also presented. Featured material on aunt Et...

  11. Compressed Sensing-Based MRI Reconstruction Using Complex Double-Density Dual-Tree DWT

    Directory of Open Access Journals (Sweden)

    Zangen Zhu


    Full Text Available Undersampling k-space data is an efficient way to speed up the magnetic resonance imaging (MRI process. As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS allows signal acquisition using fewer samples than what is specified by Nyquist-Shannon sampling theorem whenever the signal is sparse. As a result, CS has great potential in reducing data acquisition time in MRI. In traditional compressed sensing MRI methods, an image is reconstructed by enforcing its sparse representation with respect to a basis, usually wavelet transform or total variation. In this paper, we propose an improved compressed sensing-based reconstruction method using the complex double-density dual-tree discrete wavelet transform. Our experiments demonstrate that this method can reduce aliasing artifacts and achieve higher peak signal-to-noise ratio (PSNR and structural similarity (SSIM index.

  12. Use of the heat dissipation method for sap flow measurement in citrus nursery trees1

    Directory of Open Access Journals (Sweden)

    Eduardo Augusto Girardi


    Full Text Available Sap flow could be used as physiological parameter to assist irrigation of screen house citrus nursery trees by continuous water consumption estimation. Herein we report a first set of results indicating the potential use of the heat dissipation method for sap flow measurement in containerized citrus nursery trees. 'Valencia' sweet orange [Citrus sinensis (L. Osbeck] budded on 'Rangpur' lime (Citrus limonia Osbeck was evaluated for 30 days during summer. Heat dissipation probes and thermocouple sensors were constructed with low-cost and easily available materials in order to improve accessibility of the method. Sap flow showed high correlation to air temperature inside the screen house. However, errors due to natural thermal gradient and plant tissue injuries affected measurement precision. Transpiration estimated by sap flow measurement was four times higher than gravimetric measurement. Improved micro-probes, adequate method calibration, and non-toxic insulating materials should be further investigated.

  13. Model checking software for phylogenetic trees using distribution and database methods. (United States)

    Requeno, José Ignacio; Colom, José Manuel


    Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence) and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.

  14. Model checking software for phylogenetic trees using distribution and database methods

    Directory of Open Access Journals (Sweden)

    Requeno José Ignacio


    Full Text Available Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.

  15. Olive Plantation Mapping on a Sub-Tree Scale with Object-Based Image Analysis of Multispectral UAV Data; Operational Potential in Tree Stress Monitoring

    Directory of Open Access Journals (Sweden)

    Christos Karydas


    Full Text Available The objective of this study was to develop a methodology for mapping olive plantations on a sub-tree scale. For this purpose, multispectral imagery of an almost 60-ha plantation in Greece was acquired with an Unmanned Aerial Vehicle. Objects smaller than the tree crown were produced with image segmentation. Three image features were indicated as optimum for discriminating olive trees from other objects in the plantation, in a rule-based classification algorithm. After limited manual corrections, the final output was validated by an overall accuracy of 93%. The overall processing chain can be considered as suitable for operational olive tree monitoring for potential stresses.

  16. Effectiveness of phylogenomic data and coalescent species-tree methods for resolving difficult nodes in the phylogeny of advanced snakes (Serpentes: Caenophidia). (United States)

    Pyron, R Alexander; Hendry, Catriona R; Chou, Vincent M; Lemmon, Emily M; Lemmon, Alan R; Burbrink, Frank T


    Next-generation genomic sequencing promises to quickly and cheaply resolve remaining contentious nodes in the Tree of Life, and facilitates species-tree estimation while taking into account stochastic genealogical discordance among loci. Recent methods for estimating species trees bypass full likelihood-based estimates of the multi-species coalescent, and approximate the true species-tree using simpler summary metrics. These methods converge on the true species-tree with sufficient genomic sampling, even in the anomaly zone. However, no studies have yet evaluated their efficacy on a large-scale phylogenomic dataset, and compared them to previous concatenation strategies. Here, we generate such a dataset for Caenophidian snakes, a group with >2500 species that contains several rapid radiations that were poorly resolved with fewer loci. We generate sequence data for 333 single-copy nuclear loci with ∼100% coverage (∼0% missing data) for 31 major lineages. We estimate phylogenies using neighbor joining, maximum parsimony, maximum likelihood, and three summary species-tree approaches (NJst, STAR, and MP-EST). All methods yield similar resolution and support for most nodes. However, not all methods support monophyly of Caenophidia, with Acrochordidae placed as the sister taxon to Pythonidae in some analyses. Thus, phylogenomic species-tree estimation may occasionally disagree with well-supported relationships from concatenated analyses of small numbers of nuclear or mitochondrial genes, a consideration for future studies. In contrast for at least two diverse, rapid radiations (Lamprophiidae and Colubridae), phylogenomic data and species-tree inference do little to improve resolution and support. Thus, certain nodes may lack strong signal, and larger datasets and more sophisticated analyses may still fail to resolve them. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. The Study of Address Tree Coding Based on the Maximum Matching Algorithm in Courier Business (United States)

    Zhou, Shumin; Tang, Bin; Li, Wen

    As an important component of EMS monitoring system, address is different from user name with great uncertainty because there are many ways to represent it. Therefore, address standardization is a difficult task. Address tree coding has been trying to resolve that issue for many years. Zip code, as its most widely used algorithm, can only subdivide the address down to a designated post office, not the recipients' address. This problem needs artificial identification method to be accurately delivered. This paper puts forward a new encoding algorithm of the address tree - the maximum matching algorithm to solve the problem. This algorithm combines the characteristics of the address tree and the best matching theory, and brings in the associated layers of tree nodes to improve the matching efficiency. Taking the variability of address into account, the thesaurus of address tree should be updated timely by increasing new nodes automatically through intelligent tools.

  18. Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods. (United States)

    Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi


    Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p logistic regression model for the classification of risk groups for PTB.

  19. Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree Discrete Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Shanshan Chen


    Full Text Available Compressed sensing (CS has been applied to accelerate magnetic resonance imaging (MRI for many years. Due to the lack of translation invariance of the wavelet basis, undersampled MRI reconstruction based on discrete wavelet transform may result in serious artifacts. In this paper, we propose a CS-based reconstruction scheme, which combines complex double-density dual-tree discrete wavelet transform (CDDDT-DWT with fast iterative shrinkage/soft thresholding algorithm (FISTA to efficiently reduce such visual artifacts. The CDDDT-DWT has the characteristics of shift invariance, high degree, and a good directional selectivity. In addition, FISTA has an excellent convergence rate, and the design of FISTA is simple. Compared with conventional CS-based reconstruction methods, the experimental results demonstrate that this novel approach achieves higher peak signal-to-noise ratio (PSNR, larger signal-to-noise ratio (SNR, better structural similarity index (SSIM, and lower relative error.

  20. From process to proxy: Ecological challenges and opportunities of tree-ring based environmental reconstructions (United States)

    Wilmking, Martin; Buras, Allan; Heinrich, Ingo; Scharnweber, Tobias; Simard, Sonia; Smiljanic, Marko; van der Maaten, Ernst; van der Maaten-Theunissen, Marieke


    Trees are sessile, long-living organisms and as such constantly need to adapt to changing environmental conditions. Accordingly, they often show high phenotypic plasticity (the ability to change phenotypic traits, such as allocation of resources) in response to environmental change. This high phenotypic plasticity is generally considered as one of the main ingredients for a sessile organism to survive and reach high ages. Precisely because of the ability of trees to reach old age and their in-ability to simply run away when conditions get worse, growth information recorded in tree rings has long been used as a major environmental proxy, covering time scales from decades to millennia. Past environmental conditions (e.g. climate) are recorded in i.e. annual tree-ring width, early- and latewood width, wood density, isotopic concentrations, cell anatomy or wood chemistry. One prerequisite for a reconstruction is that the relationship between the environmental variable influencing tree growth and the tree-growth variable itself is stable through time. This, however, might contrast the ecological theory of high plasticity and the trees ability to adapt to change. To untangle possible mechanisms leading to stable or unstable relationships between tree growth and environmental variables, it is helpful to have exact site information and several proxy variables of each tree-ring series available. Although we gain insight into the environmental history of a sampling site when sampling today, this is extremely difficult when using archeological wood. In this latter case, we face the additional challenge of unknown origin, provenance and (or) site conditions, making it even more important to use multiple proxy time-series from the same sample. Here, we review typical examples, where the relationship between tree growth and environmental variables seems 1) stable and 2) instable through time, and relate these two cases to ecological theory. Based on ecological theory, we then

  1. Fault tree synthesis for software design analysis of PLC based safety-critical systems

    Energy Technology Data Exchange (ETDEWEB)

    Koo, S. R.; Cho, C. H. [Corporate R and D Inst., Doosan Heavy Industries and Construction Co., Ltd., 39-3, Seongbok-Dong, Yongin-Si, Gyeonggi-Do 449-795 (Korea, Republic of); Seong, P. H. [Dept. of Nuclear and Quantum Engineering, Korea Advanced Inst. of Science and Technology, 373-3 Guseong-dong, Yuseong-gu, Daejeon, 305-701 (Korea, Republic of)


    As a software verification and validation should be performed for the development of PLC based safety-critical systems, a software safety analysis is also considered in line with entire software life cycle. In this paper, we propose a technique of software safety analysis in the design phase. Among various software hazard analysis techniques, fault tree analysis is most widely used for the safety analysis of nuclear power plant systems. Fault tree analysis also has the most intuitive notation and makes both qualitative and quantitative analyses possible. To analyze the design phase more effectively, we propose a technique of fault tree synthesis, along with a universal fault tree template for the architecture modules of nuclear software. Consequently, we can analyze the safety of software on the basis of fault tree synthesis. (authors)

  2. Detecting Structural Metadata with Decision Trees and Transformation-Based Learning

    National Research Council Canada - National Science Library

    Kim, Joungbum; Schwarm, Sarah E; Ostendorf, Mari


    .... Specifically, combinations of decision trees and language models are used to predict sentence ends and interruption points and given these events transformation based learning is used to detect edit...

  3. An application of the explicit method for analysing intersystem dependencies in the evaluation of event trees

    International Nuclear Information System (INIS)

    Oliveira, L.F.S.; Frutuoso e Melo, P.F.; Lima, J.E.P.; Stal, I.L.


    We discuss in this paper a computational application of the explicit method for analyzing event trees in the context of probabilistic risk assessments. A detailed analysis of the explicit method is presented, including the train level analysis (TLA) of safety systems and the impact vector method. It is shown that the penalty for not adopting TLA is that in some cases non-conservative results may be reached. The impact vector method can significantly reduce the number of sequences to be considered, and its use has inspired the definition of a dependency matrix, which enables the proper running of a computer code especially developed for analysing event trees. This code constructs and quantifies the event trees in the fashion just discussed, by receiving as input the construction and quantification dependencies defined in the dependency matrix. The code has been extensively used in the Angra 1 PRA currently underway. In its present version it gives as output the dominant sequences for each given initiator, properly classifying them in core-degradation classes as specified by the user. This calculation is made in a pointwise fashion. Extensions of this code are being developed in order to perform uncertainty analyses on the dominant sequences and also risk importance measures of the safety systems envolved. (orig.)

  4. A MongoDB-Based Management of Planar Spatial Data with a Flattened R-Tree

    Directory of Open Access Journals (Sweden)

    Longgang Xiang


    Full Text Available This paper addresses how to manage planar spatial data using MongoDB, a popular NoSQL database characterized as a document-oriented, rich query language and high availability. The core idea is to flatten a hierarchical R-tree structure into a tabular MongoDB collection, during which R-tree nodes are represented as collection documents and R-tree pointers are expressed as document identifiers. By following this strategy, a storage schema to support R-tree-based create, read, update, and delete (CRUD operations is designed and a module to manage planar spatial data by consuming and maintaining flattened R-tree structure is developed. The R-tree module is then seamlessly integrated into MongoDB, so that users could manipulate planar spatial data with existing command interfaces oriented to geodetic spatial data. The experimental evaluation, using real-world datasets with diverse coverage, types, and sizes, shows that planar spatial data can be effectively managed by MongoDB with our flattened R-tree and, therefore, the application extent of MongoDB will be greatly enlarged. Our work resulted in a MongoDB branch with R-tree support, which has been released on GitHub for open access.

  5. A joint individual-based model coupling growth and mortality reveals that tree vigor is a key component of tropical forest dynamics. (United States)

    Aubry-Kientz, Mélaine; Rossi, Vivien; Boreux, Jean-Jacques; Hérault, Bruno


    Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20-year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait-based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests.

  6. Robust B+ -Tree-Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Tiesyte, Dalia; Tradisauskas, Nerius


    With the emergence of an infrastructure that enables the geo-positioning of on-line, mobile users, the management of so-called moving objects has emerged as an active area of research. Among the indexing techniques for efficiently answering predictive queries on moving-object positions, the recen...... predecessor?it significantly reduces the number of I/O operations per query for the workloads considered. In many settings, the TPR-tree is outperformed as well....

  7. New flux based dose–response relationships for ozone for European forest tree species

    International Nuclear Information System (INIS)

    Büker, P.; Feng, Z.; Uddling, J.; Briolat, A.; Alonso, R.; Braun, S.; Elvira, S.; Gerosa, G.; Karlsson, P.E.; Le Thiec, D.


    To derive O 3 dose–response relationships (DRR) for five European forest trees species and broadleaf deciduous and needleleaf tree plant functional types (PFTs), phytotoxic O 3 doses (PODy) were related to biomass reductions. PODy was calculated using a stomatal flux model with a range of cut-off thresholds (y) indicative of varying detoxification capacities. Linear regression analysis showed that DRR for PFT and individual tree species differed in their robustness. A simplified parameterisation of the flux model was tested and showed that for most non-Mediterranean tree species, this simplified model led to similarly robust DRR as compared to a species- and climate region-specific parameterisation. Experimentally induced soil water stress was not found to substantially reduce PODy, mainly due to the short duration of soil water stress periods. This study validates the stomatal O 3 flux concept and represents a step forward in predicting O 3 damage to forests in a spatially and temporally varying climate. - Highlights: • We present new ozone flux based dose–response relationships for European trees. • The model-based study accounted for the soil water effect on stomatal flux. • Different statistically derived ozone flux thresholds were applied. • Climate region specific parameterisation often outperformed simplified parameterisation. • Findings could help redefining critical levels for ozone effects on trees. - New stomatal flux based ozone dose–response relationships for tree species are derived for the regional risk assessment of ozone effects on European forest ecosystems.

  8. A Python-based Interface for Wide Coverage Lexicalized Tree-adjoining Grammars

    Directory of Open Access Journals (Sweden)

    Wang Ziqi


    Full Text Available This paper describes the design and implementation of a Python-based interface for wide coverage Lexicalized Tree-adjoining Grammars. The grammars are part of the XTAG Grammar project at the University of Pennsylvania, which were hand-written and semi-automatically curated to parse real-world corpora. We provide an interface to the wide coverage English and Korean XTAG grammars. Each XTAG grammar is lexicalized, which means at least one word selects a tree fragment (called an elementary tree or etree. Derivations for sentences are built by combining etrees using substitution (replacement of a tree node with an etree at the frontier of another etree and adjunction (replacement of an internal tree node in an etree by another etree. Each etree is associated with a feature structure representing constraints on substitution and adjunction. Feature structures are combined using unification during the combination of etrees. We plan to integrate our toolkit for XTAG grammars into the Python-based Natural Language Toolkit (NLTK: We have provided an API capable of searching the lexicalized etrees for a given word or multiple words, searching for a etree by name or function, display the lexicalized etrees to the user using a graphical view, display the feature structure associated with each tree node in an etree, hide or highlight features based on a regular expression, and browsing the entire tree database for each XTAG grammar.

  9. Tree compression with top trees

    DEFF Research Database (Denmark)

    Bille, Philip; Gørtz, Inge Li; Landau, Gad M.


    We introduce a new compression scheme for labeled trees based on top trees [3]. Our compression scheme is the first to simultaneously take advantage of internal repeats in the tree (as opposed to the classical DAG compression that only exploits rooted subtree repeats) while also supporting fast...

  10. Tree compression with top trees

    DEFF Research Database (Denmark)

    Bille, Philip; Gørtz, Inge Li; Landau, Gad M.


    We introduce a new compression scheme for labeled trees based on top trees. Our compression scheme is the first to simultaneously take advantage of internal repeats in the tree (as opposed to the classical DAG compression that only exploits rooted subtree repeats) while also supporting fast...

  11. Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers

    Directory of Open Access Journals (Sweden)

    Dawei Li


    Full Text Available This study develops a tree augmented naive Bayesian (TAN classifier based incident detection algorithm. Compared with the Bayesian networks based detection algorithms developed in the previous studies, this algorithm has less dependency on experts’ knowledge. The structure of TAN classifier for incident detection is learned from data. The discretization of continuous attributes is processed using an entropy-based method automatically. A simulation dataset on the section of the Ayer Rajah Expressway (AYE in Singapore is used to demonstrate the development of proposed algorithm, including wavelet denoising, normalization, entropy-based discretization, and structure learning. The performance of TAN based algorithm is evaluated compared with the previous developed Bayesian network (BN based and multilayer feed forward (MLF neural networks based algorithms with the same AYE data. The experiment results show that the TAN based algorithms perform better than the BN classifiers and have a similar performance to the MLF based algorithm. However, TAN based algorithm would have wider vista of applications because the theory of TAN classifiers is much less complicated than MLF. It should be found from the experiment that the TAN classifier based algorithm has a significant superiority over the speed of model training and calibration compared with MLF.

  12. Advocating the broad use of the decision tree method in education


    Almeida, Leandro S.; Gomes, Cristiano Mauro Assis


    Predictive studies have been widely undertaken in the field of education to provide strategic information about the extensive set of processes related to teaching and learning, as well as about what variables predict certain educational outcomes, such as academic achievement or dropout. As in any other area, there is a set of standard techniques that is usually used in predictive studies in the field education. Even though the Decision Tree Method is a well-known and standard approach in Data...

  13. Temperature Effect on Electrical Treeing and Partial Discharge Characteristics of Silicone Rubber-Based Nanocomposites

    Directory of Open Access Journals (Sweden)

    Mohd Hafizi Ahmad


    Full Text Available This study investigated electrical treeing and its associated phase-resolved partial discharge (PD activities in room-temperature, vulcanized silicone rubber/organomontmorillonite nanocomposite sample materials over a range of temperatures in order to assess the effect of temperature on different filler concentrations under AC voltage. The samples were prepared with three levels of nanofiller content: 0% by weight (wt, 1% by wt, and 3% by wt. The electrical treeing and PD activities of these samples were investigated at temperatures of 20°C, 40°C, and 60°C. The results show that the characteristics of the electrical tree changed with increasing temperature. The tree inception times decreased at 20°C due to space charge dynamics, and the tree growth time increased at 40°C due to the increase in the number of cross-link network structures caused by the vulcanization process. At 60°C, more enhanced and reinforced properties of the silicone rubber-based nanocomposite samples occurred. This led to an increase in electrical tree inception time and electrical tree growth time. However, the PD characteristics, particularly the mean phase angle of occurrence of the positive and negative discharge distributions, were insensitive to variations in temperature. This reflects an enhanced stability in the nanocomposite electrical properties compared with the base polymer.

  14. Horn clause verification with convex polyhedral abstraction and tree automata-based refinement

    DEFF Research Database (Denmark)

    Kafle, Bishoksan; Gallagher, John Patrick


    In this paper we apply tree-automata techniques to refinement of abstract interpretation in Horn clause verification. We go beyond previous work on refining trace abstractions; firstly we handle tree automata rather than string automata and thereby can capture traces in any Horn clause derivations...... underlying the Horn clauses. Experiments using linear constraint problems and the abstract domain of convex polyhedra show that the refinement technique is practical and that iteration of abstract interpretation with tree automata-based refinement solves many challenging Horn clause verification problems. We...... compare the results with other state-of-the-art Horn clause verification tools....

  15. Tree automata-based refinement with application to Horn clause verification

    DEFF Research Database (Denmark)

    Kafle, Bishoksan; Gallagher, John Patrick


    In this paper we apply tree-automata techniques to refinement of abstract interpretation in Horn clause verification. We go beyond previous work on refining trace abstractions; firstly we handle tree automata rather than string automata and thereby can capture traces in any Horn clause derivations...... underlying the Horn clauses. Experiments using linear constraint problems and the abstract domain of convex polyhedra show that the refinement technique is practical and that iteration of abstract interpretation with tree automata-based refinement solves many challenging Horn clause verification problems. We...... compare the results with other state of the art Horn clause verification tools....

  16. Intrusion Detection System Based on Decision Tree over Big Data in Fog Environment

    Directory of Open Access Journals (Sweden)

    Kai Peng


    Full Text Available Fog computing, as the supplement of cloud computing, can provide low-latency services between mobile users and the cloud. However, fog devices may encounter security challenges as a result of the fog nodes being close to the end users and having limited computing ability. Traditional network attacks may destroy the system of fog nodes. Intrusion detection system (IDS is a proactive security protection technology and can be used in the fog environment. Although IDS in tradition network has been well investigated, unfortunately directly using them in the fog environment may be inappropriate. Fog nodes produce massive amounts of data at all times, and, thus, enabling an IDS system over big data in the fog environment is of paramount importance. In this study, we propose an IDS system based on decision tree. Firstly, we propose a preprocessing algorithm to digitize the strings in the given dataset and then normalize the whole data, to ensure the quality of the input data so as to improve the efficiency of detection. Secondly, we use decision tree method for our IDS system, and then we compare this method with Naïve Bayesian method as well as KNN method. Both the 10% dataset and the full dataset are tested. Our proposed method not only completely detects four kinds of attacks but also enables the detection of twenty-two kinds of attacks. The experimental results show that our IDS system is effective and precise. Above all, our IDS system can be used in fog computing environment over big data.

  17. RENT+: an improved method for inferring local genealogical trees from haplotypes with recombination. (United States)

    Mirzaei, Sajad; Wu, Yufeng


    : Haplotypes from one or multiple related populations share a common genealogical history. If this shared genealogy can be inferred from haplotypes, it can be very useful for many population genetics problems. However, with the presence of recombination, the genealogical history of haplotypes is complex and cannot be represented by a single genealogical tree. Therefore, inference of genealogical history with recombination is much more challenging than the case of no recombination. : In this paper, we present a new approach called RENT+  for the inference of local genealogical trees from haplotypes with the presence of recombination. RENT+  builds on a previous genealogy inference approach called RENT , which infers a set of related genealogical trees at different genomic positions. RENT+  represents a significant improvement over RENT in the sense that it is more effective in extracting information contained in the haplotype data about the underlying genealogy than RENT . The key components of RENT+  are several greatly enhanced genealogy inference rules. Through simulation, we show that RENT+  is more efficient and accurate than several existing genealogy inference methods. As an application, we apply RENT+  in the inference of population demographic history from haplotypes, which outperforms several existing methods. : RENT+  is implemented in Java, and is freely available for download from: . : or : Supplementary data are available at Bioinformatics online.

  18. Analysis of tree stand horizontal structure using random point field methods

    Directory of Open Access Journals (Sweden)

    O. P. Sekretenko


    Full Text Available This paper uses the model approach to analyze the horizontal structure of forest stands. The main types of models of random point fields and statistical procedures that can be used to analyze spatial patterns of trees of uneven and even-aged stands are described. We show how modern methods of spatial statistics can be used to address one of the objectives of forestry – to clarify the laws of natural thinning of forest stand and the corresponding changes in its spatial structure over time. Studying natural forest thinning, we describe the consecutive stages of modeling: selection of the appropriate parametric model, parameter estimation and generation of point patterns in accordance with the selected model, the selection of statistical functions to describe the horizontal structure of forest stands and testing of statistical hypotheses. We show the possibilities of a specialized software package, spatstat, which is designed to meet the challenges of spatial statistics and provides software support for modern methods of analysis of spatial data. We show that a model of stand thinning that does not consider inter-tree interaction can project the size distribution of the trees properly, but the spatial pattern of the modeled stand is not quite consistent with observed data. Using data of three even-aged pine forest stands of 25, 55, and 90-years old, we demonstrate that the spatial point process models are useful for combining measurements in the forest stands of different ages to study the forest stand natural thinning.

  19. Fault tree construction of hybrid system requirements using qualitative formal method

    International Nuclear Information System (INIS)

    Lee, Jang-Soo; Cha, Sung-Deok


    When specifying requirements for software controlling hybrid systems and conducting safety analysis, engineers experience that requirements are often known only in qualitative terms and that existing fault tree analysis techniques provide little guidance on formulating and evaluating potential failure modes. In this paper, we propose Causal Requirements Safety Analysis (CRSA) as a technique to qualitatively evaluate causal relationship between software faults and physical hazards. This technique, extending qualitative formal method process and utilizing information captured in the state trajectory, provides specific guidelines on how to identify failure modes and relationship among them. Using a simplified electrical power system as an example, we describe step-by-step procedures of conducting CRSA. Our experience of applying CRSA to perform fault tree analysis on requirements for the Wolsong nuclear power plant shutdown system indicates that CRSA is an effective technique in assisting safety engineers

  20. Multiscale singularity trees

    DEFF Research Database (Denmark)

    Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter


    We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexity...... of our algorithm only allows for the comparison of small trees, and that the results of our method are comparable with state-of-the-art using much fewer parameters for image representation....

  1. Development of a computer-generated model for the coronary arterial tree based on multislice CT and morphometric data (United States)

    Fung, George S. K.; Segars, W. Paul; Taguchi, Katsuyuki; Fishman, Elliot K.; Tsui, Benjamin M. W.


    A detailed four-dimensional model of the coronary artery tree has great potential in a wide variety of applications especially in biomedical imaging. We developed a computer generated three-dimensional model for the coronary arterial tree based on two datasets: (1) gated multi-slice computed tomography (MSCT) angiographic data obtained from a normal human subject and (2) statistical morphometric data obtained from porcine hearts. The main coronary arteries and heart structures were segmented from the MSCT data to define the initial segments of the vasculature and geometrical details of the boundaries. An iterative rule-based computer generation algorithm was then developed to extend the coronary artery tree beyond the initial segmented branches. The algorithm was governed by the following factors: (1) the statistical morphometric measurements of the connectivities, lengths, and diameters of the arterial segments, (2) repelling forces from other segments and boundaries, and (3) optimality principles to minimize the drag force at each bifurcation in the generated tree. Using this algorithm, the segmented coronary artery tree from the MSCT data was optimally extended to create a 3D computational model of the largest six orders of the coronary arterial tree. The new method for generating the 3D model is effective in imposing the constraints of anatomical and physiological characteristics of coronary vasculature. When combined with the 4D NCAT phantom, a computer model for the human anatomy and cardiac and respiratory motions, the new model will provide a unique tool to study cardiovascular characteristics and diseases through direct and medical imaging simulation studies.

  2. Localization value of seizure semiology analyzed by the conditional inference tree method. (United States)

    Kim, Dong Wook; Jung, Ki-Young; Chu, Kon; Park, So-Hee; Lee, Seo-Young; Lee, Sang Kun


    Although accurate interpretation of seizures is important for the management of patients with epilepsy, studies on the localizing value of seizure semiology and the reliability of the semiology descriptions are scarce. The objective of our study is to investigate the accuracy of video-recorded seizure semiology in the classification and localization of epileptic seizures. We also evaluated the reliability of the semiology descriptions provided by the patients or their caregivers. Video-recorded clinical seizures from 831 consecutive patients (391 females; 31.7 ± 11.6 years) were analyzed retrospectively. Epileptic seizures were classified as generalized and partial seizures, and patients with partial seizures were further divided into five ictal onset areas. In order to analyze the diagnostic value of individual semiologic features for clinical diagnosis, we used the conditional inference tree method. Generalized and partial seizures were differentiated with high accuracy (97.1%), but the accuracy of localization among the five ictal onset areas was relatively low (56.1%), which was largely attributed to the difficulty in the discrimination between mesial and lateral temporal onset seizures. Lateralization of the ictal onset area in partial seizures was possible in 427 (55.1%) patients based on video analysis, nevertheless it was possible in only 158 (20.4%) patients based on historical semiology descriptions. The results of our study suggest that careful observation of seizure semiology may be useful for the differentiation of ictal onset areas. However, the semiologic differentiation between mesial and lateral temporal onset seizures is difficult, and historical semiologic descriptions should be interpreted carefully because of their low reliability. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Classification tree methods for development of decision rules for botulism and cyanide poisoning. (United States)

    Sasser, Howell; Nussbaum, Marcy; Beuhler, Michael; Ford, Marsha


    Identification of predictors of potential mass poisonings may increase the speed and accuracy with which patients are recognized, potentially reducing the number ultimately exposed and the degree to which they are affected. This analysis used a decision-tree method to sort such potential predictors. Data from the Toxic Exposure Surveillance System were used to select cyanide and botulism cases from 1993 to 2005 for analysis. Cases of other poisonings from a single poison center were used as controls. After duplication was omitted and removal of cases from the control sample was completed, there remained 1,122 cyanide cases, 262 botulism cases, and 70,804 controls available for both analyses. Classification trees for each poisoning type were constructed, using 131 standardized clinical effects. These decision rules were compared with the current case surveillance definitions of one active poison center and the American Association of Poison Control Centers (AAPCC). The botulism analysis produced a 4-item decision rule with sensitivity (Se) of 68% and specificity (Sp) of 90%. Use of the single poison center and AAPCC definitions produced Se of 19.5% and 16.8%, and Sp of 99.5% and 83.2%, respectively. The cyanide analysis produced a 9-item decision rule with Se of 74% and Sp of 77%. The single poison center and AAPCC case definitions produced Se of 10.2% and 8.6%, and Sp of 99.8% and 99.8%, respectively. These results suggest the possibility of improved poisoning case surveillance sensitivity using classification trees. This method produced substantially higher sensitivities, but not specificities, for both cyanide and botulism. Despite limitations, these results show the potential of a classification-tree approach in the detection of poisoning events.

  4. Development of a portable spectroscopy-based device to detect nutrient status of apple tree (United States)

    Zhang, Yao; Zheng, Lihua; Li, Minzan; Deng, Xiaolei; An, Xiaofei


    In order to detect apple tree growth status fast and accurately, four sensitive wavebands (364nm, 652nm, 766nm, 810nm) were obtained by analyzing the correlation between the apple leaves spectra and their nitrogen contents plus adopting the segment reduced precise sampling methods. A rapid determination model of apple leaf nitrogen content suitable for portable detector was built. Then a portable spectroscopy-based device was developed. It consists of an optical unit and a control unit. The optical channel was consisted of convex lens, optical filter, photoelectric detector and airtight mechanical exine. The optical unit was used to capture, transit, transform and submit the optical signal. The controller was consisted of operation, input, display, data storage and power control unit adopting JN5139 as main control unit. Controller was the coordinator in building the wireless network. And it was also responsible for receiving the measured data from sensor, calculating vegetation index, and displaying and storing the calculated results. The experiments showed that the correlation coefficient between the measured nitrogen content and the predicted nitrogen content reached to 0.857. It illustrated that the apple tree nitrogen detector was practical and could be used to detect leaf nitrogen content in apple orchard.

  5. MRI-based decision tree model for diagnosis of biliary atresia. (United States)

    Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung


    To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

  6. A System to Derive Optimal Tree Diameter Increment Models from the Eastwide Forest Inventory Data Base (EFIDB) (United States)

    Don C. Bragg


    This article is an introduction to the computer software used by the Potential Relative Increment (PRI) approach to optimal tree diameter growth modeling. These DOS programs extract qualified tree and plot data from the Eastwide Forest Inventory Data Base (EFIDB), calculate relative tree increment, sort for the highest relative increments by diameter class, and...

  7. Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover (United States)

    Ranson, K. J.; Montesano, P. M.; Nelson, R.


    The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

  8. Component-based modeling of systems for automated fault tree generation

    International Nuclear Information System (INIS)

    Majdara, Aref; Wakabayashi, Toshio


    One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented

  9. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography. (United States)

    Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano


    Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

  10. Using and comparing two nonparametric methods (CART and RF and SPOT-HRG satellite data to predictive tree diversity distribution

    Directory of Open Access Journals (Sweden)



    Full Text Available Kalbi S, Fallah A, Hojjati SM. 2014. Using and comparing two nonparametric methods (CART and RF and SPOT-HRG satellite data to predictive tree diversity distribution. Nusantara Bioscience 6: 57-62. The prediction of spatial distributions of tree species by means of survey data has recently been used for conservation planning. Numerous methods have been developed for building species habitat suitability models. The present study was carried out to find the possible proper relationships between tree species diversity indices and SPOT-HRG reflectance values in Hyrcanian forests, North of Iran. Two different modeling techniques, Classification and Regression Trees (CART and Random Forest (RF, were fitted to the data in order to find the most successfully model. Simpson, Shannon diversity and the reciprocal of Simpson indices were used for estimating tree diversity. After collecting terrestrial information on trees in the 100 samples, the tree diversity indices were calculated in each plot. RF with determinate coefficient and RMSE from 56.3 to 63.9 and RMSE from 0.15 to 0.84 has better results than CART algorithms with determinate coefficient 42.3 to 63.3 and RMSE from 0.188 to 0.88. Overall the results showed that the SPOT-HRG satellite data and nonparametric regression could be useful for estimating tree diversity in Hyrcanian forests, North of Iran.

  11. Comparison of T-Square, Point Centered Quarter, and N-Tree Sampling Methods in Pittosporum undulatum Invaded Woodlands

    Directory of Open Access Journals (Sweden)

    Lurdes Borges Silva


    Full Text Available Tree density is an important parameter affecting ecosystems functions and management decisions, while tree distribution patterns affect sampling design. Pittosporum undulatum stands in the Azores are being targeted with a biomass valorization program, for which efficient tree density estimators are required. We compared T-Square sampling, Point Centered Quarter Method (PCQM, and N-tree sampling with benchmark quadrat (QD sampling in six 900 m2 plots established at P. undulatum stands in São Miguel Island. A total of 15 estimators were tested using a data resampling approach. The estimated density range (344–5056 trees/ha was found to agree with previous studies using PCQM only. Although with a tendency to underestimate tree density (in comparison with QD, overall, T-Square sampling appeared to be the most accurate and precise method, followed by PCQM. Tree distribution pattern was found to be slightly aggregated in 4 of the 6 stands. Considering (1 the low level of bias and high precision, (2 the consistency among three estimators, (3 the possibility of use with aggregated patterns, and (4 the possibility of obtaining a larger number of independent tree parameter estimates, we recommend the use of T-Square sampling in P. undulatum stands within the framework of a biomass valorization program.

  12. [RS estimation of inventory parameters and carbon storage of moso bamboo forest based on synergistic use of object-based image analysis and decision tree]. (United States)

    Du, Hua Qiang; Sun, Xiao Yan; Han, Ning; Mao, Fang Jie


    By synergistically using the object-based image analysis (OBIA) and the classification and regression tree (CART) methods, the distribution information, the indexes (including diameter at breast, tree height, and crown closure), and the aboveground carbon storage (AGC) of moso bamboo forest in Shanchuan Town, Anji County, Zhejiang Province were investigated. The results showed that the moso bamboo forest could be accurately delineated by integrating the multi-scale ima ge segmentation in OBIA technique and CART, which connected the image objects at various scales, with a pretty good producer's accuracy of 89.1%. The investigation of indexes estimated by regression tree model that was constructed based on the features extracted from the image objects reached normal or better accuracy, in which the crown closure model archived the best estimating accuracy of 67.9%. The estimating accuracy of diameter at breast and tree height was relatively low, which was consistent with conclusion that estimating diameter at breast and tree height using optical remote sensing could not achieve satisfactory results. Estimation of AGC reached relatively high accuracy, and accuracy of the region of high value achieved above 80%.

  13. Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance (United States)

    Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang


    In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

  14. Multiple self-protected spanning-trees-based architecture for fast recovery and load balance in metro ethernet (United States)

    Chen, Wentao; Zhong, Xian; Jin, Depeng; Zeng, Lieguang


    Ethernet is now expanding into the metro area networks. To address the fast recovery and load balance issues in Metro Ethernet, we propose a multiple self-protected spanning trees based architecture. A self-protected spanning tree can recover from the link failure without the help the other spanning trees, which is different from the spanning trees in all the previously advocated Multiple Spanning Tree Protocol (MSTP) based architectures. The Single Link Replace Mechanism (SLRM) is the essential of the proposed architecture. The SLRM transforms a self-protected spanning tree into another spanning tree by only replacing one link in the tree with another link out of the tree. The SLRM provides a recovery mechanism by replacing the failed link in the self-protected spanning tree with the normal link out of the tree, and makes a two-edge connected network survives any single link failure. It also provides an additional load balance mechanism by changing the topology of the spanning tree, which can not be implemented in the traditional MSTP-based architectures. The recovery and load balance mechanisms using the SLRM are detailed illustrated and evaluated using the sample networks. Simulation results demonstrate the effectiveness of the SLRM in achieving fast recovery and dynamic load balance.

  15. The effect of the times and the budding methods on the quality of young trees and the nursery efficiency of cherry trees cv. 'Łutówka'

    Directory of Open Access Journals (Sweden)

    Piotr Baryła


    Full Text Available The studies concerning the effect of the times and the methods of budding on the growth of young cherry trees were conducted in the years 1997-2000 at Felin Experimental Farm of Lublin Agricultural University. The objects of investigations were the young cherry trees obtained as a result of budding of mahaleb cherry (Prunus mahaleb L. and sweet cherry (Prunus avium L. seedlings in the way by the chip budding-15th July and T-budding-on the 15th July and the 1st September. The used terms and budding methods did not affect the bud taking and the quality of cherry trees during three years studies. Chip budding of the sweet cherry on the 15th July was the most effective way of this seedling budding. Late budding-on the 1st September-did not change the efficiency of the nursery only in case of mahaleb cherry. The highest number-33 000 of the young trees, average per 1 ha was got as a result of the chip and "T" mahaleb cherry budding on the 1st September.

  16. Hierarchical Segmentation Using Tree-Based Shape Spaces. (United States)

    Xu, Yongchao; Carlinet, Edwin; Geraud, Thierry; Najman, Laurent


    Current trends in image segmentation are to compute a hierarchy of image segmentations from fine to coarse. A classical approach to obtain a single meaningful image partition from a given hierarchy is to cut it in an optimal way, following the seminal approach of the scale-set theory. While interesting in many cases, the resulting segmentation, being a non-horizontal cut, is limited by the structure of the hierarchy. In this paper, we propose a novel approach that acts by transforming an input hierarchy into a new saliency map. It relies on the notion of shape space: a graph representation of a set of regions extracted from the image. Each region is characterized with an attribute describing it. We weigh the boundaries of a subset of meaningful regions (local minima) in the shape space by extinction values based on the attribute. This extinction-based saliency map represents a new hierarchy of segmentations highlighting regions having some specific characteristics. Each threshold of this map represents a segmentation which is generally different from any cut of the original hierarchy. This new approach thus enlarges the set of possible partition results that can be extracted from a given hierarchy. Qualitative and quantitative illustrations demonstrate the usefulness of the proposed method.


    Directory of Open Access Journals (Sweden)

    T. Celine Therese Jenny


    Full Text Available The Embedded Zero-tree Wavelet (EZW is a lossy compression method that allows for progressive transmission of a compressed image. By exploiting the natural zero-trees found in a wavelet decomposed image, the EZW algorithm is able to encode large portions of insignificant regions of an still image with a minimal number of bits. The upshot of this encoding is an algorithm that is able to achieve relatively high peak signal to noise ratios (PSNR for high compression levels. The EZW algorithm is to encode large portions of insignificant regions of an image with a minimal number of bits. Vector Quantization (VQ method can be performed as a post processing step to reduce the coded file size. Vector Quantization (VQ method can be reduces redundancy of the image data in order to be able to store or transmit data in an efficient form. It is demonstrated by experimental results that the proposed method outperforms several well-known lossless image compression techniques for still images that contain 256 colors or less.

  18. Combined prediction model for supply risk in nuclear power equipment manufacturing industry based on support vector machine and decision tree

    International Nuclear Information System (INIS)

    Shi Chunsheng; Meng Dapeng


    The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)

  19. Typology of Ohio, USA, tree farmers based upon forestry outreach needs. (United States)

    Starr, S E; McConnell, T E; Bruskotter, J S; Williams, R A


    This study differentiated groups of Ohio tree farmers through multivariate clustering of their perceived needs for forest management outreach. Tree farmers were surveyed via a mailed questionnaire. Respondents were asked to rate, on a 1-7 scale, their informational needs for 26 outreach topics, which were reduced to six factors. Based on these factors, three clusters were identified-holistic managers, environmental stewards, and pragmatic tree farmers. Cluster assignment of individuals was dependent upon a tree farmer's age, acreage owned, and number of years enrolled in the American Tree Farm System. Holistic managers showed a greater interest in the outreach topics while pragmatic tree farmers displayed an overall lesser interest. Across clusters, print media and in-person workshops were preferred over emails and webinars for receiving forest management information. In-person workshops should be no more than 1 day events, held on a weekday, during the daytime, at a cost not exceeding $35. Programming related to environmental influences, which included managing for forest insects and diseases, was concluded to have the greater potential to impact clientele among all outreach factors due to the information being applicable across demographics and/or management objectives.

  20. Application of modified Spatial K’luster Analysis by Tree Edge Removal Method (SKATER on the level of Crime data in Way Kanan district, Lampung

    Directory of Open Access Journals (Sweden)

    kadek yama rinaldi


    Full Text Available Modification of method Spatial K'luster Analysis by Tree Edge Removal (SKATER is one of the regionalization method for clustering based on the location by spatial autocorrelation and spatial patterns. This method uses graph theory approach to identify the homogeneous location is the minimum spanning tree. In addition to clustering objects based on similarity characteristics, in everyday life, often found that there are significant spatial clustering that affect specific object. This study was conducted to determine the relationship of the crime rate between districts in Way Kanan, Lampung. Based on these results, the characteristics of the crime rate in terms of spoliation, robbery and gambling have spatial autocorrelation and spatial patterns. Further applied modifications of SKATER. Generate 4 cluster (k graded of the 14 districts. on average k1 (17.67%  k2 (10.09%   k3 (7.80%  k4 (4.28%.

  1. Tolerance Levels of Roadside Trees to Air Pollutants Based on Relative Growth Rate and Air Pollution Tolerance Index

    Directory of Open Access Journals (Sweden)



    Full Text Available Motor vehicles release carbon monoxide, nitrogen dioxide, sulphur dioxide, and particulate matters to the air as pollutants. Vegetation can absorb these pollutants through gas exchange processes. The objective of this study was to examine the combination of the relative growth rate (RGR and physiological responses in determining tolerance levels of plant species to air pollutants. Physiological responses were calculated as air pollution tolerance index (APTI. Eight roadside tree species were placed at polluted (Jagorawi highway and unpolluted (Sindangbarang field area. Growth and physiological parameters of the trees were recorded, including plant height, leaf area, total ascorbate, total chlorophyll, leaf-extract pH, and relative water content. Scoring criteria for the combination of RGR and APTI method was given based on means of the two areas based on two-sample t test. Based on the total score of RGR and APTI, Lagerstroemia speciosa was categorized as a tolerant species; and Pterocarpus indicus, Delonix regia, Swietenia macrophylla were categorized as moderately tolerant species. Gmelina arborea, Cinnamomum burmanii, and Mimusops elengi were categorized as intermediate tolerant species. Lagerstroemia speciosa could be potentially used as roadside tree. The combination of RGR and APTI value was better to determinate tolerance level of plant to air pollutant than merely APTI method.

  2. Human action analysis with randomized trees

    CERN Document Server

    Yu, Gang; Liu, Zicheng


    This book will provide a comprehensive overview on human action analysis with randomized trees. It will cover both the supervised random trees and the unsupervised random trees. When there are sufficient amount of labeled data available, supervised random trees provides a fast method for space-time interest point matching. When labeled data is minimal as in the case of example-based action search, unsupervised random trees is used to leverage the unlabelled data. We describe how the randomized trees can be used for action classification, action detection, action search, and action prediction.

  3. A voting-based statistical cylinder detection framework applied to fallen tree mapping in terrestrial laser scanning point clouds (United States)

    Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe


    This paper introduces a statistical framework for detecting cylindrical shapes in dense point clouds. We target the application of mapping fallen trees in datasets obtained through terrestrial laser scanning. This is a challenging task due to the presence of ground vegetation, standing trees, DTM artifacts, as well as the fragmentation of dead trees into non-collinear segments. Our method shares the concept of voting in parameter space with the generalized Hough transform, however two of its significant drawbacks are improved upon. First, the need to generate samples on the shape's surface is eliminated. Instead, pairs of nearby input points lying on the surface cast a vote for the cylinder's parameters based on the intrinsic geometric properties of cylindrical shapes. Second, no discretization of the parameter space is required: the voting is carried out in continuous space by means of constructing a kernel density estimator and obtaining its local maxima, using automatic, data-driven kernel bandwidth selection. Furthermore, we show how the detected cylindrical primitives can be efficiently merged to obtain object-level (entire tree) semantic information using graph-cut segmentation and a tailored dynamic algorithm for eliminating cylinder redundancy. Experiments were performed on 3 plots from the Bavarian Forest National Park, with ground truth obtained through visual inspection of the point clouds. It was found that relative to sample consensus (SAC) cylinder fitting, the proposed voting framework can improve the detection completeness by up to 10 percentage points while maintaining the correctness rate.

  4. Molecular Phylogenetic: Organism Taxonomy Method Based on Evolution History

    Directory of Open Access Journals (Sweden)

    N.L.P Indi Dharmayanti


    Full Text Available Phylogenetic is described as taxonomy classification of an organism based on its evolution history namely its phylogeny and as a part of systematic science that has objective to determine phylogeny of organism according to its characteristic. Phylogenetic analysis from amino acid and protein usually became important area in sequence analysis. Phylogenetic analysis can be used to follow the rapid change of a species such as virus. The phylogenetic evolution tree is a two dimensional of a species graphic that shows relationship among organisms or particularly among their gene sequences. The sequence separation are referred as taxa (singular taxon that is defined as phylogenetically distinct units on the tree. The tree consists of outer branches or leaves that represents taxa and nodes and branch represent correlation among taxa. When the nucleotide sequence from two different organism are similar, they were inferred to be descended from common ancestor. There were three methods which were used in phylogenetic, namely (1 Maximum parsimony, (2 Distance, and (3 Maximum likehoood. Those methods generally are applied to construct the evolutionary tree or the best tree for determine sequence variation in group. Every method is usually used for different analysis and data.

  5. T-BAS: Tree-Based Alignment Selector toolkit for phylogenetic-based placement, alignment downloads and metadata visualization: an example with the Pezizomycotina tree of life. (United States)

    Carbone, Ignazio; White, James B; Miadlikowska, Jolanta; Arnold, A Elizabeth; Miller, Mark A; Kauff, Frank; U'Ren, Jana M; May, Georgiana; Lutzoni, François


    High-quality phylogenetic placement of sequence data has the potential to greatly accelerate studies of the diversity, systematics, ecology and functional biology of diverse groups. We developed the Tree-Based Alignment Selector (T-BAS) toolkit to allow evolutionary placement and visualization of diverse DNA sequences representing unknown taxa within a robust phylogenetic context, and to permit the downloading of highly curated, single- and multi-locus alignments for specific clades. In its initial form, T-BAS v1.0 uses a core phylogeny of 979 taxa (including 23 outgroup taxa, as well as 61 orders, 175 families and 496 genera) representing all 13 classes of largest subphylum of Fungi-Pezizomycotina (Ascomycota)-based on sequence alignments for six loci (nr5.8S, nrLSU, nrSSU, mtSSU, RPB1, RPB2 ). T-BAS v1.0 has three main uses: (i) Users may download alignments and voucher tables for members of the Pezizomycotina directly from the reference tree, facilitating systematics studies of focal clades. (ii) Users may upload sequence files with reads representing unknown taxa and place these on the phylogeny using either BLAST or phylogeny-based approaches, and then use the displayed tree to select reference taxa to include when downloading alignments. The placement of unknowns can be performed for large numbers of Sanger sequences obtained from fungal cultures and for alignable, short reads of environmental amplicons. (iii) User-customizable metadata can be visualized on the tree. T-BAS Version 1.0 is available online at . Registration is required to access the CIPRES Science Gateway and NSF XSEDE's large computational resources. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail:

  6. Decision tree based knowledge acquisition and failure diagnosis using a PWR loop vibration model

    International Nuclear Information System (INIS)

    Bauernfeind, V.; Ding, Y.


    An analytical vibration model of the primary system of a 1300 MW PWR was used for simulating mechanical faults. Deviations in the calculated power density spectra and coherence functions are determined and classified. The decision tree technique is then used for a personal computer supported knowledge presentation and for optimizing the logical relationships between the simulated faults and the observed symptoms. The optimized decision tree forms the knowledge base and can be used to diagnose known cases as well as to include new data into the knowledge base if new faults occur. (author)

  7. Scalable Tool Infrastructure for the Cray XT Using Tree-Based Overlay Networks

    Energy Technology Data Exchange (ETDEWEB)

    Roth, Philip C [ORNL; Vetter, Jeffrey S [ORNL


    Performance, debugging, and administration tools are critical for the effective use of parallel computing platforms, but traditional tools have failed to overcome several problems that limit their scalability, such as communication between a large number of tool processes and the management and processing of the volume of data generated on a large number of compute nodes. A tree-based overlay network has proven effective for overcoming these challenges. In this paper, we present our experiences in bringing our MRNet tree-based overlay network infrastructure to the Cray XT platform, including a description of proof-of-concept tools that use MRNet on the Cray XT.

  8. Method of decision tree applied in adopting the decision for promoting a company

    Directory of Open Access Journals (Sweden)

    Cezarina Adina TOFAN


    Full Text Available The decision can be defined as the way chosen from several possible to achieve an objective. An important role in the functioning of the decisional-informational system is held by the decision-making methods. Decision trees are proving to be very useful tools for taking financial decisions or regarding the numbers, where a large amount of complex information must be considered. They provide an effective structure in which alternative decisions and the implications of their choice can be assessed, and help to form a correct and balanced vision of the risks and rewards that may result from a certain choice. For these reasons, the content of this communication will review a series of decision-making criteria. Also, it will analyse the benefits of using the decision tree method in the decision-making process by providing a numerical example. On this basis, it can be concluded that the procedure may prove useful in making decisions for companies operating on markets where competition intensity is differentiated.

  9. Papaya Tree Detection with UAV Images Using a GPU-Accelerated Scale-Space Filtering Method

    Directory of Open Access Journals (Sweden)

    Hao Jiang


    Full Text Available The use of unmanned aerial vehicles (UAV can allow individual tree detection for forest inventories in a cost-effective way. The scale-space filtering (SSF algorithm is commonly used and has the capability of detecting trees of different crown sizes. In this study, we made two improvements with regard to the existing method and implementations. First, we incorporated SSF with a Lab color transformation to reduce over-detection problems associated with the original luminance image. Second, we ported four of the most time-consuming processes to the graphics processing unit (GPU to improve computational efficiency. The proposed method was implemented using PyCUDA, which enabled access to NVIDIA’s compute unified device architecture (CUDA through high-level scripting of the Python language. Our experiments were conducted using two images captured by the DJI Phantom 3 Professional and a most recent NVIDIA GPU GTX1080. The resulting accuracy was high, with an F-measure larger than 0.94. The speedup achieved by our parallel implementation was 44.77 and 28.54 for the first and second test image, respectively. For each 4000 × 3000 image, the total runtime was less than 1 s, which was sufficient for real-time performance and interactive application.

  10. Comparative measurements of growth rings in trees using a microscopic method and digital X-ray density images

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Mary Lucia da [Pontificia Univ. Catolica do Rio de Janeiro, RJ (Brazil). Dept. de Quimica]. E-mail:; Wagener, Klaus [Universidade Federal, Rio de Janeiro, RJ (Brazil). Inst. de Quimica. Dept. de Quimica Analitica]. E-mail:; Ferreira, Rubemar [Instituto de Radioprotecao e Dosimetria (IRD), Rio de Janeiro, RJ (Brazil)]. E-mail:


    As is well-known, the systematic analysis of the annual radial increase in the stem diameter of ring-forming trees gives quantitative information about varying climatic conditions in the past. These investigations became of high actual interest to verify present climatic changes. The traditional method for measuring ring widths in radially extracted tree samples is by microscopic observation, using an ABBE comparator. For documenting the recent climatic changes, as recorded in the changing sizes of the tree rings, dozens of trees have to be analyzed, and normally with four samples per each tree. This situation stimulated the interest in modern methods with fast data processing. However, to make use of them, needs also a fast way of recording the data. For the present purpose, this is the digital X-ray image showing the density differences in each ring has, resulting from 'early wood' and 'late wood' produced in different seasons of the year. To check the reliability of this new method, the same samples have also been measured with the microscopic method. It turned out that there are no systematic differences in the results, thus opening the way for much faster tree ring research. (author)

  11. Comparative measurements of growth rings in trees using a microscopic method and digital X-ray density images

    International Nuclear Information System (INIS)

    Silva, Mary Lucia da


    As is well-known, the systematic analysis of the annual radial increase in the stem diameter of ring-forming trees gives quantitative information about varying climatic conditions in the past. These investigations became of high actual interest to verify present climatic changes. The traditional method for measuring ring widths in radially extracted tree samples is by microscopic observation, using an ABBE comparator. For documenting the recent climatic changes, as recorded in the changing sizes of the tree rings, dozens of trees have to be analyzed, and normally with four samples per each tree. This situation stimulated the interest in modern methods with fast data processing. However, to make use of them, needs also a fast way of recording the data. For the present purpose, this is the digital X-ray image showing the density differences in each ring has, resulting from 'early wood' and 'late wood' produced in different seasons of the year. To check the reliability of this new method, the same samples have also been measured with the microscopic method. It turned out that there are no systematic differences in the results, thus opening the way for much faster tree ring research. (author)

  12. Diagnosis of Constant Faults in Read-Once Contact Networks over Finite Bases using Decision Trees

    KAUST Repository

    Busbait, Monther I.


    We study the depth of decision trees for diagnosis of constant faults in read-once contact networks over finite bases. This includes diagnosis of 0-1 faults, 0 faults and 1 faults. For any finite basis, we prove a linear upper bound on the minimum depth of decision tree for diagnosis of constant faults depending on the number of edges in a contact network over that basis. Also, we obtain asymptotic bounds on the depth of decision trees for diagnosis of each type of constant faults depending on the number of edges in contact networks in the worst case per basis. We study the set of indecomposable contact networks with up to 10 edges and obtain sharp coefficients for the linear upper bound for diagnosis of constant faults in contact networks over bases of these indecomposable contact networks. We use a set of algorithms, including one that we create, to obtain the sharp coefficients.

  13. A UGV-based laser scanner system for measuring tree geometric characteristics (United States)

    Wang, Yonghui; Lan, Yubin; Zheng, Yongjun; Lee, Kevin; Cui, Suxia; Lian, Jian-ao


    This paper introduces a laser scanner based measurement system for measuring crop/tree geometric characteristics. The measurement system, which is mounted on a Unmanned Ground Vehicle (UGV), contains a SICK LMS511 PRO laser scanner, a GPS, and a computer. The LMS511 PRO scans objects within distance up to 80 meters with a scanning frequency of 25 up to 100Hz and with an angular resolution of 0.1667° up to 1°. With an Ethernet connection, this scanner can output the measured values in real time. The UGV is a WIFI based remotely controlled agricultural robotics system. During field tests, the laser scanner was mounted on the UGV vertically to scan crops or trees. The UGV moved along the row direction with certain average travel speed. The experimental results show that the UGV's travel speed significantly affects the measurement accuracy. A slower speed produces more accurate measuring results. With the developed measurement system, crop/tree canopy height, width, and volume can be accurately measured in a real-time manner. With a higher spatial resolution, the original data set may even provide useful information in predicting crop/tree growth and productivity. In summary, the UGV based measurement system developed in this research can measure the crop/tree geometric characteristics with good accuracy and will work as a step stone for our future UGV based intelligent agriculture system, which will include variable rate spray and crop/tree growth and productivity prediction through analyzing the measured results of the laser scanner system.

  14. Tomographic Image Reconstruction Using an Interpolation Method for Tree Decay Detection (United States)

    Hailin Feng; Guanghui Li; Sheng Fu; Xiping Wang


    Stress wave velocity has been traditionally regarded as an indicator of the extent of damage inside wood. This paper aimed to detect internal decay of urban trees through reconstructing tomographic image of the cross section of a tree trunk. A grid model covering the cross section area of a tree trunk was defined with some assumptions. Stress wave data were processed...

  15. Modularization of fault trees: a method to reduce the cost of analysis

    International Nuclear Information System (INIS)

    Chatterjee, P.


    The problem of analyzing large fault trees is considered. The concept of the finest modular representation of a fault tree is introduced and an algorithm is presented for finding this representation. The algorithm will also identify trees which cannot be modularized. Applications of such modularizations are discussed

  16. Predicting number of hospitalization days based on health insurance claims data using bagged regression trees. (United States)

    Xie, Yang; Schreier, Günter; Chang, David C W; Neubauer, Sandra; Redmond, Stephen J; Lovell, Nigel H


    Healthcare administrators worldwide are striving to both lower the cost of care whilst improving the quality of care given. Therefore, better clinical and administrative decision making is needed to improve these issues. Anticipating outcomes such as number of hospitalization days could contribute to addressing this problem. In this paper, a method was developed, using large-scale health insurance claims data, to predict the number of hospitalization days in a population. We utilized a regression decision tree algorithm, along with insurance claim data from 300,000 individuals over three years, to provide predictions of number of days in hospital in the third year, based on medical admissions and claims data from the first two years. Our method performs well in the general population. For the population aged 65 years and over, the predictive model significantly improves predictions over a baseline method (predicting a constant number of days for each patient), and achieved a specificity of 70.20% and sensitivity of 75.69% in classifying these subjects into two categories of 'no hospitalization' and 'at least one day in hospital'.

  17. Assessing alternative measures of tree canopy cover: Photo-interpreted NAIP and ground-based estimates (United States)

    Chris Toney; Greg Liknes; Andy Lister; Dacia Meneguzzo


    In preparation for the development of the National Land Cover Database (NLCD) 2011 tree canopy cover layer, a pilot project for research and method development was completed in 2010 by the USDA Forest Service Forest Inventory and Analysis (FIA) program and Remote Sensing Applications Center (RSAC).This paper explores one of several topics investigated during the NLCD...

  18. Improved appearance-based matching in similar and dynamic environments using a vocabulary tree

    CSIR Research Space (South Africa)

    Sabatta, D


    Full Text Available , and uses this information to update the feature weights in the tree to suppress further associations from these features. Two methods of adjusting these feature entropies are proposed, one decreasing entropy related to incorrect features in a uniform manner...

  19. A Distributed Election and Spanning Tree Algorithm Based on Depth First Search Traversals

    DEFF Research Database (Denmark)

    Skyum, Sven

    The existence of an effective distributed traversal algorithm for a class of graphs has proven useful in connection with election problems for those classes. In this paper we show how a general traversal algorithm, such as depth first search, can be turned into an effective election algorithm using...... modular techniques. The presented method also constructs a spanning tree for the graph....

  20. Fast and frugal trees: translating population-based pharmacogenomics to medication prioritization

    NARCIS (Netherlands)

    Rooij, T. van; Roederer, M.; Wareham, H.T.; Rooij, I.J.E.I. van; McLeod, H.L.; Marsh, S.


    Aim: Fast and frugal decision trees (FFTs) can simplify clinical decision making by providing a heuristic approach to contextual guidance. We wanted to use FFTs for pharmacogenomic knowledge translation at point-of-care. Materials & Methods: The Pharmacogenomics for Every Nation Initiative (PGENI),


    Directory of Open Access Journals (Sweden)

    C. Zhang


    Full Text Available Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP, which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

  2. a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification (United States)

    Zhang, C.; Pan, X.; Zhang, S. Q.; Li, H. P.; Atkinson, P. M.


    Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR) images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP), which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

  3. A modified decision tree algorithm based on genetic algorithm for mobile user classification problem. (United States)

    Liu, Dong-sheng; Fan, Shu-jiang


    In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity.

  4. PCA based feature reduction to improve the accuracy of decision tree c4.5 classification (United States)

    Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.


    Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

  5. Query and Update Efficient B+-Tree Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lin, Dan; Ooi, Beng Chin


    are streamed to a database. Indexes for moving objects must support queries efficiently, but must also support frequent updates. Indexes based on minimum bounding regions (MBRs) such as the R-tree exhibit high concurrency overheads during node splitting, and each individual update is known to be quite costly...

  6. Dominant height-based height-diameter equations for trees in southern Indiana (United States)

    John A., Jr. Kershaw; Robert C. Morrissey; Douglass F. Jacobs; John R. Seifert; James B. McCarter


    Height-diameter equations are developed based on dominant tree data collected in 1986 in 8- to 17-year-old clearcuts and the phase 2 Forest Inventory and Analysis plots on the Hoosier National Forest in south central Indiana. Two equation forms are explored: the basic, three-parameter Chapman-Richards function, and a modification of the three-parameter equation...

  7. Canopy Fuel Load Mapping of Mediterranean Pine Sites Based on Individual Tree-Crown Delineation

    Directory of Open Access Journals (Sweden)

    Giorgos Mallinis


    Full Text Available This study presents an individual tree-crown-based approach for canopy fuel load estimation and mapping in two Mediterranean pine stands. Based on destructive sampling, an allometric equation was developed for the estimation of crown fuel weight considering only pine crown width, a tree characteristic that can be estimated from passive imagery. Two high resolution images were used originally for discriminating Aleppo and Calabrian pines crown regions through a geographic object based image analysis approach. Subsequently, the crown region images were segmented using a watershed segmentation algorithm and crown width was extracted. The overall accuracy of the tree crown isolation expressed through a perfect match between the reference and the delineated crowns was 34.00% for the Kassandra site and 48.11% for the Thessaloniki site, while the coefficient of determination between the ground measured and the satellite extracted crown width was 0.5. Canopy fuel load values estimated in the current study presented mean values from 1.29 ± 0.6 to 1.65 ± 0.7 kg/m2 similar to other conifers worldwide. Despite the modest accuracies attained in this first study of individual tree crown fuel load mapping, the combination of the allometric equations with satellite-based extracted crown width information, can contribute to the spatially explicit mapping of canopy fuel load in Mediterranean areas. These maps can be used among others in fire behavior prediction, in fuel reduction treatments prioritization and during active fire suppression.

  8. A Walk-based Semantically Enriched Tree Kernel Over Distributed Word Representations

    DEFF Research Database (Denmark)

    Srivastava, Shashank; Hovy, Dirk


    We propose a walk-based graph kernel that generalizes the notion of tree-kernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations, such ...... diverse NLP tasks, showing state-of-the-art results....

  9. Packets distribution in a tree-based topology wireless sensor networks

    CSIR Research Space (South Africa)

    Akpakwu, GA


    Full Text Available The concept of data distribution within cluster of sensor nodes to the source sink has resulted to intense research in Wireless Sensor Networks (WSNs). In this paper, in order to determine the scheduling length of packet distribution, a tree-based...

  10. Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods

    Directory of Open Access Journals (Sweden)

    Chun-Wei Tung


    Full Text Available Esophageal squamous cell cancer (ESCC is one of the most common fatal human cancers. The identification of biomarkers for early detection could be a promising strategy to decrease mortality. Previous studies utilized microarray techniques to identify more than one hundred genes; however, it is desirable to identify a small set of biomarkers for clinical use. This study proposes a sequential forward feature selection algorithm to design decision tree models for discriminating ESCC from normal tissues. Two potential biomarkers of RUVBL1 and CNIH were identified and validated based on two public available microarray datasets. To test the discrimination ability of the two biomarkers, 17 pairs of expression profiles of ESCC and normal tissues from Taiwanese male patients were measured by using microarray techniques. The classification accuracies of the two biomarkers in all three datasets were higher than 90%. Interpretable decision tree models were constructed to analyze expression patterns of the two biomarkers. RUVBL1 was consistently overexpressed in all three datasets, although we found inconsistent CNIH expression possibly affected by the diverse major risk factors for ESCC across different areas.

  11. Methods in Logic Based Control

    DEFF Research Database (Denmark)

    Christensen, Georg Kronborg


    Desing and theory of Logic Based Control systems.Boolean Algebra, Karnaugh Map, Quine McClusky's algorithm. Sequential control design. Logic Based Control Method, Cascade Control Method. Implementation techniques: relay, pneumatic, TTL/CMOS,PAL and PLC- and Soft_PLC implementation. PLC...

  12. Prospective identification of adolescent suicide ideation using classification tree analysis: Models for community-based screening. (United States)

    Hill, Ryan M; Oosterhoff, Benjamin; Kaplow, Julie B


    Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation. Participants were N = 4,799 youth (Mage = 16.15 years, SD = 1.63) who completed both Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health. CTA was used to generate a series of decision rules for identifying adolescents at risk for reporting suicide ideation at Wave 2. Findings revealed 3 distinct solutions with varying sensitivity and specificity for identifying adolescents who reported suicide ideation. Sensitivity of the classification trees ranged from 44.6% to 77.6%. The tree with greatest specificity and lowest sensitivity was based on a history of suicide ideation. The tree with moderate sensitivity and high specificity was based on depressive symptoms, suicide attempts or suicide among family and friends, and social support. The most sensitive but least specific tree utilized these factors and gender, ethnicity, hours of sleep, school-related factors, and future orientation. These classification trees offer community organizations options for instituting large-scale screenings for suicide ideation risk depending on the available resources and modality of services to be provided. This study provides a theoretically and empirically driven model for prospectively identifying adolescents at risk for suicide ideation and has implications for preventive interventions among at-risk youth. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  13. Activity based costing (ABC Method

    Directory of Open Access Journals (Sweden)

    Prof. Ph.D. Saveta Tudorache


    Full Text Available In the present paper the need and advantages are presented of using the Activity BasedCosting method, need arising from the need of solving the information pertinence issue. This issue has occurreddue to the limitation of classic methods in this field, limitation also reflected by the disadvantages ofsuch classic methods in establishing complete costs.

  14. Minimum variance rooting of phylogenetic trees and implications for species tree reconstruction. (United States)

    Mai, Uyen; Sayyari, Erfan; Mirarab, Siavash


    Phylogenetic trees inferred using commonly-used models of sequence evolution are unrooted, but the root position matters both for interpretation and downstream applications. This issue has been long recognized; however, whether the potential for discordance between the species tree and gene trees impacts methods of rooting a phylogenetic tree has not been extensively studied. In this paper, we introduce a new method of rooting a tree based on its branch length distribution; our method, which minimizes the variance of root to tip distances, is inspired by the traditional midpoint rerooting and is justified when deviations from the strict molecular clock are random. Like midpoint rerooting, the method can be implemented in a linear time algorithm. In extensive simulations that consider discordance between gene trees and the species tree, we show that the new method is more accurate than midpoint rerooting, but its relative accuracy compared to using outgroups to root gene trees depends on the size of the dataset and levels of deviations from the strict clock. We show high levels of error for all methods of rooting estimated gene trees due to factors that include effects of gene tree discordance, deviations from the clock, and gene tree estimation error. Our simulations, however, did not reveal significant differences between two equivalent methods for species tree estimation that use rooted and unrooted input, namely, STAR and NJst. Nevertheless, our results point to limitations of existing scalable rooting methods.

  15. Tree-based indexing for real-time ConvNet landmark-based visual place recognition

    Directory of Open Access Journals (Sweden)

    Yi Hou


    Full Text Available Recent impressive studies on using ConvNet landmarks for visual place recognition take an approach that involves three steps: (a detection of landmarks, (b description of the landmarks by ConvNet features using a convolutional neural network, and (c matching of the landmarks in the current view with those in the database views. Such an approach has been shown to achieve the state-of-the-art accuracy even under significant viewpoint and environmental changes. However, the computational burden in step (c significantly prevents this approach from being applied in practice, due to the complexity of linear search in high-dimensional space of the ConvNet features. In this article, we propose two simple and efficient search methods to tackle this issue. Both methods are built upon tree-based indexing. Given a set of ConvNet features of a query image, the first method directly searches the features’ approximate nearest neighbors in a tree structure that is constructed from ConvNet features of database images. The database images are voted on by features in the query image, according to a lookup table which maps each ConvNet feature to its corresponding database image. The database image with the highest vote is considered the solution. Our second method uses a coarse-to-fine procedure: the coarse step uses the first method to coarsely find the top-N database images, and the fine step performs a linear search in Hamming space of the hash codes of the ConvNet features to determine the best match. Experimental results demonstrate that our methods achieve real-time search performance on five data sets with different sizes and various conditions. Most notably, by achieving an average search time of 0.035 seconds/query, our second method improves the matching efficiency by the three orders of magnitude over a linear search baseline on a database with 20,688 images, with negligible loss in place recognition accuracy.

  16. Patch-based image segmentation of satellite imagery using minimum spanning tree construction

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory


    We present a method for hierarchical image segmentation and feature extraction. This method builds upon the combination of the detection of image spectral discontinuities using Canny edge detection and the image Laplacian, followed by the construction of a hierarchy of segmented images of successively reduced levels of details. These images are represented as sets of polygonized pixel patches (polygons) attributed with spectral and structural characteristics. This hierarchy forms the basis for object-oriented image analysis. To build fine level-of-detail representation of the original image, seed partitions (polygons) are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on the top of the detected spectral discontinuities that form a network of constraints for the Delaunay triangulation. A polygonized image is represented as a spatial network in the form of a graph with vertices which correspond to the polygonal partitions and graph edges reflecting pairwise partitions relations. Image graph partitioning is based on the iterative graph oontraction using Boruvka's Minimum Spanning Tree algorithm. An important characteristic of the approach is that the agglomeration of partitions is constrained by the detected spectral discontinuities; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects.

  17. The effect of organic acids on base cation leaching from the forest floor under six North American tree species

    NARCIS (Netherlands)

    Dijkstra, F.A.; Geibe, C.; Holmstrom, S.; Lundstrom, U.S.; Breemen, van N.


    Organic acidity and its degree of neutralization in the forest floor can have large consequences for base cation leaching under different tree species. We investigated the effect of organic acids on base cation leaching from the forest floor under six common North American tree species. Forest floor

  18. Intrathoracic Airway Tree Segmentation from CT Images Using a Fuzzy Connectivity Method

    Directory of Open Access Journals (Sweden)

    Fereshteh Yousefi Rizi


    Full Text Available Introduction: Virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. The segmentation of airways from CT images is a critical step for numerous virtual bronchoscopy applications. Materials and Methods: To overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy C-mean (FC-FCM, utilized the FCM algorithm. Then, hanging-togetherness of pixels was handled by employing a spatial membership function. Another problem in airway segmentation that had to be overcome was the leakage into the extra-luminal regions due to the thinness of the airway walls during the process of segmentation. Results:   The result shows an accuracy of 92.92% obtained for segmentation of the airway tree up to the fourth generation. Conclusion:  We have presented a new segmentation method that is not only robust regarding the leakage problem but also functions more efficiently than the traditional FC method.

  19. Multiple alignment analysis on phylogenetic tree of the spread of SARS epidemic using distance method (United States)

    Amiroch, S.; Pradana, M. S.; Irawan, M. I.; Mukhlash, I.


    Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

  20. Computing Refined Buneman Trees in Cubic Time

    DEFF Research Database (Denmark)

    Brodal, G.S.; Fagerberg, R.; Östlin, A.


    in the underlying distance data. Distance based methods based on the theory of Buneman trees and refined Buneman trees avoid this problem by only proposing evolutionary trees whose edges satisfy a number of constraints. These trees might not be fully resolved but there is strong combinatorial evidence for each...... proposed edge. The currently best algorithm for computing the refined Buneman tree from a given distance measure has a running time of O(n 5) and a space consumption of O(n 4). In this paper, we present an algorithm with running time O(n 3) and space consumption O(n 2). The improved complexity of our...

  1. Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume. (United States)

    Meng, Qier; Kitasaka, Takayuki; Nimura, Yukitaka; Oda, Masahiro; Ueno, Junji; Mori, Kensaku


    Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3D airway tree structure from a CT volume is quite a challenging task. Several researchers have proposed automated airway segmentation algorithms basically based on region growing and machine learning techniques. However, these methods fail to detect the peripheral bronchial branches, which results in a large amount of leakage. This paper presents a novel approach for more accurate extraction of the complex airway tree. This proposed segmentation method is composed of three steps. First, Hessian analysis is utilized to enhance the tube-like structure in CT volumes; then, an adaptive multiscale cavity enhancement filter is employed to detect the cavity-like structure with different radii. In the second step, support vector machine learning will be utilized to remove the false positive (FP) regions from the result obtained in the previous step. Finally, the graph-cut algorithm is used to refine the candidate voxels to form an integrated airway tree. A test dataset including 50 standard-dose chest CT volumes was used for evaluating our proposed method. The average extraction rate was about 79.1 % with the significantly decreased FP rate. A new method of airway segmentation based on local intensity structure and machine learning technique was developed. The method was shown to be feasible for airway segmentation in a computer-aided diagnosis system for a lung and bronchoscope guidance system.

  2. Explicit area-based accuracy assessment for mangrove tree crown delineation using Geographic Object-Based Image Analysis (GEOBIA) (United States)

    Kamal, Muhammad; Johansen, Kasper


    Effective mangrove management requires spatially explicit information of mangrove tree crown map as a basis for ecosystem diversity study and health assessment. Accuracy assessment is an integral part of any mapping activities to measure the effectiveness of the classification approach. In geographic object-based image analysis (GEOBIA) the assessment of the geometric accuracy (shape, symmetry and location) of the created image objects from image segmentation is required. In this study we used an explicit area-based accuracy assessment to measure the degree of similarity between the results of the classification and reference data from different aspects, including overall quality (OQ), user's accuracy (UA), producer's accuracy (PA) and overall accuracy (OA). We developed a rule set to delineate the mangrove tree crown using WorldView-2 pan-sharpened image. The reference map was obtained by visual delineation of the mangrove tree crowns boundaries form a very high-spatial resolution aerial photograph (7.5cm pixel size). Ten random points with a 10 m radius circular buffer were created to calculate the area-based accuracy assessment. The resulting circular polygons were used to clip both the classified image objects and reference map for area comparisons. In this case, the area-based accuracy assessment resulted 64% and 68% for the OQ and OA, respectively. The overall quality of the calculation results shows the class-related area accuracy; which is the area of correctly classified as tree crowns was 64% out of the total area of tree crowns. On the other hand, the overall accuracy of 68% was calculated as the percentage of all correctly classified classes (tree crowns and canopy gaps) in comparison to the total class area (an entire image). Overall, the area-based accuracy assessment was simple to implement and easy to interpret. It also shows explicitly the omission and commission error variations of object boundary delineation with colour coded polygons.

  3. Image reconstruction of fluorescent molecular tomography based on the tree structured Schur complement decomposition

    Directory of Open Access Journals (Sweden)

    Wang Jiajun


    Full Text Available Abstract Background The inverse problem of fluorescent molecular tomography (FMT often involves complex large-scale matrix operations, which may lead to unacceptable computational errors and complexity. In this research, a tree structured Schur complement decomposition strategy is proposed to accelerate the reconstruction process and reduce the computational complexity. Additionally, an adaptive regularization scheme is developed to improve the ill-posedness of the inverse problem. Methods The global system is decomposed level by level with the Schur complement system along two paths in the tree structure. The resultant subsystems are solved in combination with the biconjugate gradient method. The mesh for the inverse problem is generated incorporating the prior information. During the reconstruction, the regularization parameters are adaptive not only to the spatial variations but also to the variations of the objective function to tackle the ill-posed nature of the inverse problem. Results Simulation results demonstrate that the strategy of the tree structured Schur complement decomposition obviously outperforms the previous methods, such as the conventional Conjugate-Gradient (CG and the Schur CG methods, in both reconstruction accuracy and speed. As compared with the Tikhonov regularization method, the adaptive regularization scheme can significantly improve ill-posedness of the inverse problem. Conclusions The methods proposed in this paper can significantly improve the reconstructed image quality of FMT and accelerate the reconstruction process.

  4. Direct chromatographic methods for the rapid determination of homogentisic acid in strawberry tree (Arbutus unedo L.) honey. (United States)

    Scanu, Roberta; Spano, Nadia; Panzanelli, Angelo; Pilo, Maria I; Piu, Paola C; Sanna, Gavino; Tapparo, Andrea


    Two rapid and direct chromatographic methods based on reverse phase-high performance liquid chromatography (RP-HPLC) and ion chromatography (IC) were developed for the determination of homogentisic acid (HA) in honey. This is the marker of the botanic origin of strawberry tree honey. The methods were validated and tested using 22 samples from Sardinia, Italy. The IC method is faster than the RP-HPLC one (6 min versus 13 min of total run), but it is slightly less sensitive (the limit of detection (LOD), is 26 mg kg(-1) versus 15 mg kg(-1)) and reproducible (relative standard deviation, RSD, of 10.4 and 4.4%, respectively). The whole dataset of validation parameters allows both the proposed methods to be considered as bias-free (by recovery tests, comparison of analytical results of the two independent methods and analysis of a synthetic sample) and precise (both the techniques show a repeatability better than 2% repeatability in the range between 70 and 600 mg kg(-1)).

  5. QoS Supported IPTV Service Architecture over Hybrid-Tree-Based Explicit Routed Multicast Network

    Directory of Open Access Journals (Sweden)

    Chih-Chao Wen


    Full Text Available With the rapid advance in multimedia streaming and multicast transport technology, current IP multicast protocols, especially PIM-SM, become the major channel delivery mechanism for IPTV system over Internet. The goals for IPTV service are to provide two-way interactive services for viewers to select popular program channel with high quality for watching during fast channel surfing period. However, existing IP multicast protocol cannot meet above QoS requirements for IPTV applications between media server and subscribers. Therefore, we propose a cooperative scheme of hybrid-tree based on explicit routed multicast, called as HT-ERM to combine the advantages of shared tree and source tree for QoS-supported IPTV service. To increase network utilization, the constrained shortest path first (CSPF routing algorithm is designed for construction of hybrid tree to deliver the high-quality video stream over watching channel and standard quality over surfing channel. Furthermore, the Resource Reservation Protocol- Traffic Engineering (RSVP-TE is used as signaling mechanism to set up QoS path for multicast channel admission control. Our simulation results demonstrated that the proposed HT-ERM scheme outperforms other multicast QoS-based delivery scheme in terms of channel switching delay, resource utilization, and blocking ratio for IPTV service.

  6. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets. (United States)

    Doubravsky, Karel; Dohnal, Mirko


    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

  7. Towards a common methodology to simulate tree mortality based on ring-width data (United States)

    Cailleret, Maxime; Bigler, Christof; Bugmann, Harald; Davi, Hendrik; Minunno, Francesco; Peltoniemi, Mikko; Martínez-Vilalta, Jordi


    Individual mortality is a key process of population and community dynamics, especially for long-lived species such as trees. As the rates of vegetation background mortality and of massive diebacks accelerated during the last decades and would continue in the future due to rising temperature and increasing drought, there is a growing demand of early warning signals that announce that the likelihood of death is very high. If physiological indicators have a high potential to predict tree mortality, their development requires an intensive tree monitoring which cannot be currently done on a representative sample of a population and on several species. An easier approach is to use radial growth data such as tree ring-widths measurements. During the last decades, an increasing number of studies aimed to derive these growth-mortality functions. However, as they followed different approaches concerning the choice of the sampling strategy (number of dead and living trees), of the type of growth explanatory variables (growth level, growth trend variables…), and of the length of the time-window (number of rings before death) used to calculate them, it makes difficult to compare results among studies and a subsequent biological interpretation. We detailed a new methodology for assessing reliable tree-ring based growth-mortality relationships using binomial logistic regression models. As examples we used published tree-ring datasets from Abies alba growing in 13 different sites, and from Nothofagus dombeyi and Quercus petraea located in one single site. Our first approach, based on constant samplings, aims to (1) assess the dependency of growth-mortality relationships on the statistical sampling scheme used; (2) determine the best length of the time-window used to calculate each growth variable; and (3) reveal the presence of intra-specific shifts in growth-mortality relationships. We also followed a Bayesian approach to build the best multi-variable logistic model considering

  8. A comparison of two suffix tree-based document clustering algorithms


    Rafi, Muhammad; Maujood, M.; Fazal, M. M.; Ali, S. M.


    Document clustering as an unsupervised approach extensively used to navigate, filter, summarize and manage large collection of document repositories like the World Wide Web (WWW). Recently, focuses in this domain shifted from traditional vector based document similarity for clustering to suffix tree based document similarity, as it offers more semantic representation of the text present in the document. In this paper, we compare and contrast two recently introduced approaches to document clus...

  9. Genome Trees from Conservation Profiles.

    Directory of Open Access Journals (Sweden)


    Full Text Available The concept of the genome tree depends on the potential evolutionary significance in the clustering of species according to similarities in the gene content of their genomes. In this respect, genome trees have often been identified with species trees. With the rapid expansion of genome sequence data it becomes of increasing importance to develop accurate methods for grasping global trends for the phylogenetic signals that mutually link the various genomes. We therefore derive here the methodological concept of genome trees based on protein conservation profiles in multiple species. The basic idea in this derivation is that the multi-component "presence-absence" protein conservation profiles permit tracking of common evolutionary histories of genes across multiple genomes. We show that a significant reduction in informational redundancy is achieved by considering only the subset of distinct conservation profiles. Beyond these basic ideas, we point out various pitfalls and limitations associated with the data handling, paving the way for further improvements. As an illustration for the methods, we analyze a genome tree based on the above principles, along with a series of other trees derived from the same data and based on pair-wise comparisons (ancestral duplication-conservation and shared orthologs. In all trees we observe a sharp discrimination between the three primary domains of life: Bacteria, Archaea, and Eukarya. The new genome tree, based on conservation profiles, displays a significant correspondence with classically recognized taxonomical groupings, along with a series of departures from such conventional clusterings.

  10. Comparison of methods for uncertainty analysis of nuclear-power-plant safety-system fault-tree models

    International Nuclear Information System (INIS)

    Martz, H.F.; Beckman, R.J.; Campbell, K.; Whiteman, D.E.; Booker, J.M.


    A comparative evaluation is made of several methods for propagating uncertainties in actual coupled nuclear power plant safety system faults tree models. The methods considered are Monte Carlo simulation, the method of moments, a discrete distribution method, and a bootstrap method. The Monte Carlo method is found to be superior. The sensitivity of the system unavailability distribution to the choice of basic event unavailability distribution is also investigated. The system distribution is also investigated. The system distribution is especially sensitive to the choice of symmetric versus asymmetric basic event distributions. A quick-and dirty method for estimating percentiles of the system unavailability distribution is developed. The method identifies the appropriate basic event distribution percentiles that should be used in evaluating the Boolean system equivalent expression for a given fault tree model to arrive directly at the 5th, 10th, 50th, 90th, and 95th percentiles of the system unavailability distribution

  11. Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling. (United States)

    Jiménez-Brenes, F M; López-Granados, F; de Castro, A I; Torres-Sánchez, J; Serrano, N; Peña, J M


    Tree pruning is a costly practice with important implications for crop harvest and nutrition, pest and disease control, soil protection and irrigation strategies. Investigations on tree pruning usually involve tedious on-ground measurements of the primary tree crown dimensions, which also might generate inconsistent results due to the irregular geometry of the trees. As an alternative to intensive field-work, this study shows a innovative procedure based on combining unmanned aerial vehicle (UAV) technology and advanced object-based image analysis (OBIA) methodology for multi-temporal three-dimensional (3D) monitoring of hundreds of olive trees that were pruned with three different strategies (traditional, adapted and mechanical pruning). The UAV images were collected before pruning, after pruning and a year after pruning, and the impacts of each pruning treatment on the projected canopy area, tree height and crown volume of every tree were quantified and analyzed over time. The full procedure described here automatically identified every olive tree on the orchard and computed their primary 3D dimensions on the three study dates with high accuracy in the most cases. Adapted pruning was generally the most aggressive treatment in terms of the area and volume (the trees decreased by 38.95 and 42.05% on average, respectively), followed by trees under traditional pruning (33.02 and 35.72% on average, respectively). Regarding the tree heights, mechanical pruning produced a greater decrease (12.15%), and these values were minimal for the other two treatments. The tree growth over one year was affected by the pruning severity and by the type of pruning treatment, i.e., the adapted-pruning trees experienced higher growth than the trees from the other two treatments when pruning intensity was low (UAV-based images and an OBIA procedure allowed measuring tree dimensions and quantifying the impacts of three different pruning treatments on hundreds of trees with minimal field

  12. Process-based modeling of tree-ring formation and their relationships with climate data on the Tibetan Plateau (United States)

    He, Minhui; Shishov, Vladimir; Kaparova, Nazgul; Yang, Bao; Bräuning, Achim; Grießinger, Jussi


    Response of climate warming on tree-ring formation has attracted much attention during recent years. However, most studies are based on statistical analysis, lacking understanding of tree-physiological processes, especially on the mountainous region of the Tibetan Plateau (TP). Herein, we firstly use an updated new version of the tree-ring process-based Vaganov-Shashkin model (VS-oscilloscope) to simulate tree-ring formation and its relationships with climate factors during the past six decades. Our analysis covered 341 sampled trees, with elevation ranges from 2750 to 4575 m a.s.l. at five sampling sites from southern to northern part of the TP. Simulated tree-ring width series are significantly (p interval periods. Starting dates of tree-ring width formation are all determined by temperature at the five sampling sites. After the initiation of tree stem cambial activity, soil moisture content has a significant effect on tree-ring growth. Ending dates are driven by temperature in the study region. Simulated results indicate the difference between wide and narrow tree-ring formation is mostly induced by soil moisture content, especially at the first half of the growing season, while effect from temperature is minor. Interestingly, we detected significantly (p the year 1985 at the five sampling sites. However, the variability of mean relative growth rate due to temperature (GrT) is negligible before and after that. Based on the successful application of VS-oscilloscope modeling on the high-elevation tree stands of the TP, our study provides a new perspective of tree radial growth process and their relationships with climate data during the past six decades.

  13. MixtureTree annotator: a program for automatic colorization and visual annotation of MixtureTree.

    Directory of Open Access Journals (Sweden)

    Shu-Chuan Chen

    Full Text Available The MixtureTree Annotator, written in JAVA, allows the user to automatically color any phylogenetic tree in Newick format generated from any phylogeny reconstruction program and output the Nexus file. By providing the ability to automatically color the tree by sequence name, the MixtureTree Annotator provides a unique advantage over any other programs which perform a similar function. In addition, the MixtureTree Annotator is the only package that can efficiently annotate the output produced by MixtureTree with mutation information and coalescent time information. In order to visualize the resulting output file, a modified version of FigTree is used. Certain popular methods, which lack good built-in visualization tools, for example, MEGA, Mesquite, PHY-FI, TreeView, treeGraph and Geneious, may give results with human errors due to either manually adding colors to each node or with other limitations, for example only using color based on a number, such as branch length, or by taxonomy. In addition to allowing the user to automatically color any given Newick tree by sequence name, the MixtureTree Annotator is the only method that allows the user to automatically annotate the resulting tree created by the MixtureTree program. The MixtureTree Annotator is fast and easy-to-use, while still allowing the user full control over the coloring and annotating process.

  14. Rooted triple consensus and anomalous gene trees

    Directory of Open Access Journals (Sweden)

    Schmidt Heiko A


    Full Text Available Abstract Background Anomalous gene trees (AGTs are gene trees with a topology different from a species tree that are more probable to observe than congruent gene trees. In this paper we propose a rooted triple approach to finding the correct species tree in the presence of AGTs. Results Based on simulated data we show that our method outperforms the extended majority rule consensus strategy, while still resolving the species tree. Applying both methods to a metazoan data set of 216 genes, we tested whether AGTs substantially interfere with the reconstruction of the metazoan phylogeny. Conclusion Evidence of AGTs was not found in this data set, suggesting that erroneously reconstructed gene trees are the most significant challenge in the reconstruction of phylogenetic relationships among species with current data. The new method does however rule out the erroneous reconstruction of deep or poorly resolved splits in the presence of lineage sorting.

  15. Advanced hybrid query tree algorithm based on slotted backoff mechanism in RFID

    Directory of Open Access Journals (Sweden)

    XIE Xiaohui


    Full Text Available The merits of performance quality for a RFID system are determined by the effectiveness of tag anti-collision algorithm.Many algorithms for RFID system of tag identification have been proposed,but they all have obvious weaknesses,such as slow speed of identification,unstable and so on.The existing algorithms can be divided into two groups,one is based on ALOHA and another is based on query tree.This article is based on the hybrid query tree algorithm,combined with a slotted backoff mechanism and a specific encoding (Manchester encoding.The number of value“1” in every three consecutive bits of tags is used to determine the tag response time slots,which will greatly reduce the time slot of the collision and improve the recognition efficiency.

  16. Sources of error inherent in species-tree estimation: impact of mutational and coalescent effects on accuracy and implications for choosing among different methods. (United States)

    Huang, Huateng; He, Qixin; Kubatko, Laura S; Knowles, L Lacey


    Discord in the estimated gene trees among loci can be attributed to both the process of mutation and incomplete lineage sorting. Effectively modeling these two sources of variation--mutational and coalescent variance--provides two distinct challenges for phylogenetic studies. Despite extensive investigation on mutational models for gene-tree estimation over the past two decades and recent attention to modeling of the coalescent process for phylogenetic estimation, the effects of these two variances have yet to be evaluated simultaneously. Here, we partition the effects of mutational and coalescent processes on phylogenetic accuracy by comparing the accuracy of species trees estimated from gene trees (i.e., the actual coalescent genealogies) with that of species trees estimated from estimated gene trees (i.e., trees estimated from nucleotide sequences, which contain both coalescent and mutational variance). Not only is there a significant contribution of both mutational and coalescent variance to errors in species-tree estimates, but the relative magnitude of the effects on the accuracy of species-tree estimation also differs systematically depending on 1) the timing of divergence, 2) the sampling design, and 3) the method used for species-tree estimation. These findings explain why using more information contained in gene trees (e.g., topology and branch lengths as opposed to just topology) does not necessarily translate into pronounced gains in accuracy, highlighting the strengths and limits of different methods for species-tree estimation. Differences in accuracy scores between methods for different sampling regimes also emphasize that it would be a mistake to assume more computationally intensive species-tree estimation procedures that will always provide better estimates of species trees. To the contrary, the performance of a method depends not only on the method per se but also on the compatibilities between the input genetic data and the method as determined

  17. Accurate phylogenetic tree reconstruction from quartets: a heuristic approach. (United States)

    Reaz, Rezwana; Bayzid, Md Shamsuzzoha; Rahman, M Sohel


    Supertree methods construct trees on a set of taxa (species) combining many smaller trees on the overlapping subsets of the entire set of taxa. A 'quartet' is an unrooted tree over 4 taxa, hence the quartet-based supertree methods combine many 4-taxon unrooted trees into a single and coherent tree over the complete set of taxa. Quartet-based phylogeny reconstruction methods have been receiving considerable attentions in the recent years. An accurate and efficient quartet-based method might be competitive with the current best phylogenetic tree reconstruction methods (such as maximum likelihood or Bayesian MCMC analyses), without being as computationally intensive. In this paper, we present a novel and highly accurate quartet-based phylogenetic tree reconstruction method. We performed an extensive experimental study to evaluate the accuracy and scalability of our approach on both simulated and biological datasets.

  18. Chemical composition of virgin olive oils from the Chemlali cultivar with regard to the method of the olive tree propagation

    Directory of Open Access Journals (Sweden)

    Guerfel, M.


    Full Text Available This paper reports for the first time a discrimination study based on the antioxidant compounds, oxidative stability and volatile compounds of virgin olive oil samples obtained from fruits of the main Tunisian olive cultivar (Chemlali using two methods of olive tree propagation (suckers and cuttings. There were significant differences between the oils from the two methods. Olive oil samples obtained from the fruits of trees from suckers had a higher content of oleic acid (63.8%, higher contents of chlorophyll and carotenoids (3.01 mg/ kg and 1.9 mg/kg respectively, a higher content of (E-2 hexenal (66.1% and a higher content in total phenols (890 mg/kg. Interestingly, more stable oil was obtained from the olives from suckers compared to the olives from cuttings. These results can be used to discriminate and to characterize the Chemlali olive oils from each origin of olive tree.

    En este trabajo se presenta por primera vez un estudio de discriminación basado en compuestos antioxidantes, estabilidad oxidativa y compuestos volátiles de muestras de aceites de oliva virgen obtenidos de frutos de la principal variedad de aceitunas tunecinas (Chemlali a partir de dos métodos de propagación del olivo (chupones y estaquillas herbáceas. Se han encontrado diferencias significativas entre los aceites obtenidos por los dos métodos. Las muestras de aceites de oliva obtenidas de frutos de árboles de chupones tenían una mayor proporción de ácido oleico (63,8%, un mayor contenido de clorofila y de carotenoides (3,01 mg/kg y 1,9 mg/kg, respectivamente, un mayor contenido de (E-2 hexenal (66,1% y un mayor contenido en fenoles totales (890 mg/kg. Curiosamente, el aceite más estable se ha obtenido de las aceitunas de árboles de chupones, en comparación con las aceitunas de árboles de estaquillas herbáceas. Estos resultados pueden ser utilizados para discriminar y caracterizar los aceites de oliva Chamlali según el origen del olivo.

  19. An application based on the decision tree to classify the marbling of beef by hyperspectral imaging. (United States)

    Velásquez, Lía; Cruz-Tirado, J P; Siche, Raúl; Quevedo, Roberto


    The aim of this study was to develop a system to classify the marbling of beef using the hyperspectral imaging technology. The Japanese standard classification of the degree of marbling of beef was used as reference and twelve standards were digitized to obtain the parameters of shape and spatial distribution of marbling of each class. A total of 35 samples M. longissmus dorsi muscle were scanned by the hyperspectral imaging system of 400-1000 nm in reflectance mode. The wavelength of 528nm was selected to segment the sample and the background, and 440nm was used for classified the samples. Processing algorithms on image, based on decision tree method, were used in the region of interest obtaining a classification error of 0.08% in the building stage. The results showed that the proposed technique has a great potential, as a non-destructive and fast technique, that can be used to classify beef with respect to the degree of marbling. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization. (United States)

    Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma; Alonso-González, Itziar


    Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have.

  1. An FMM based on dual tree traversal for many-core architectures

    KAUST Repository

    Yokota, Rio


    The present work attempts to integrate the independent efforts in the fast N-body community to create the fastest N-body library for many-core and heterogenous architectures. Focus is placed on low accuracy optimizations, in response to the recent interest to use FMM as a preconditioner for sparse linear solvers. A direct comparison with other state-of-the-art fast N-body codes demonstrates that orders of magnitude increase in performance can be achieved by careful selection of the optimal algorithm and low-level optimization of the code. The current N-body solver uses a fast multipole method with an efficient strategy for finding the list of cell-cell interactions by a dual tree traversal. A task-based threading model is used to maximize thread-level parallelism and intra-node load-balancing. In order to extract the full potential of the SIMD units on the latest CPUs, the inner kernels are optimized using AVX instructions.

  2. Improving reliability of state estimation programming and computing suite based on analyzing a fault tree

    Directory of Open Access Journals (Sweden)

    Kolosok Irina


    Full Text Available Reliable information on the current state parameters obtained as a result of processing the measurements from systems of the SCADA and WAMS data acquisition and processing through methods of state estimation (SE is a condition that enables to successfully manage an energy power system (EPS. SCADA and WAMS systems themselves, as any technical systems, are subject to failures and faults that lead to distortion and loss of information. The SE procedure enables to find erroneous measurements, therefore, it is a barrier for the distorted information to penetrate into control problems. At the same time, the programming and computing suite (PCS implementing the SE functions may itself provide a wrong decision due to imperfection of the software algorithms and errors. In this study, we propose to use a fault tree to analyze consequences of failures and faults in SCADA and WAMS and in the very SE procedure. Based on the analysis of the obtained measurement information and on the SE results, we determine the state estimation PCS fault tolerance level featuring its reliability.

  3. Efficient shortest-path-tree computation in network routing based on pulse-coupled neural networks. (United States)

    Qu, Hong; Yi, Zhang; Yang, Simon X


    Shortest path tree (SPT) computation is a critical issue for routers using link-state routing protocols, such as the most commonly used open shortest path first and intermediate system to intermediate system. Each router needs to recompute a new SPT rooted from itself whenever a change happens in the link state. Most commercial routers do this computation by deleting the current SPT and building a new one using static algorithms such as the Dijkstra algorithm at the beginning. Such recomputation of an entire SPT is inefficient, which may consume a considerable amount of CPU time and result in a time delay in the network. Some dynamic updating methods using the information in the updated SPT have been proposed in recent years. However, there are still many limitations in those dynamic algorithms. In this paper, a new modified model of pulse-coupled neural networks (M-PCNNs) is proposed for the SPT computation. It is rigorously proved that the proposed model is capable of solving some optimization problems, such as the SPT. A static algorithm is proposed based on the M-PCNNs to compute the SPT efficiently for large-scale problems. In addition, a dynamic algorithm that makes use of the structure of the previously computed SPT is proposed, which significantly improves the efficiency of the algorithm. Simulation results demonstrate the effective and efficient performance of the proposed approach.

  4. Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Jiang; Guo, Hanqi; Yuan, Xiaoru; Hong, Fan; Peterka, Tom


    Particle tracing is a fundamental technique in flow field data visualization. In this work, we present a novel dynamic load balancing method for parallel particle tracing. Specifically, we employ a constrained k-d tree decomposition approach to dynamically redistribute tasks among processes. Each process is initially assigned a regularly partitioned block along with duplicated ghost layer under the memory limit. During particle tracing, the k-d tree decomposition is dynamically performed by constraining the cutting planes in the overlap range of duplicated data. This ensures that each process is reassigned particles as even as possible, and on the other hand the new assigned particles for a process always locate in its block. Result shows good load balance and high efficiency of our method.

  5. Determination of N2 -fixation ability of legume trees using the 15N method

    International Nuclear Information System (INIS)

    Wemay, Johannis; Syaukat, Sriharti; Sisworo, Elsje L


    A sequence field experiment has been conducted for determining the capability of N 2 -fixation by several legume trees. The experiment was designed using a randomize design with 4 replicates. Each replicate was planted with 100 legume trees and 100 non legume trees. The isotope plot, where 15 N was applied with 18 legume trees and 18 non legume trees. The planting distance was 1m x 1m. For the calculation of N 2 -fixation each legume and standard tree (Eucalypthus alba) was applied with 12.52g in the from of ammonium sulfate with 10.12% 15 N. The 15 N AS was applied in three splits 11 month earlier. Data obtained from this experiment showed that percentage of N derived from fixation (%N-dfF) of all legume trees was reasonable high. The legume trees used in this experiment were, Leucaena leucocephala, Acacia mangium, Caliandra tetragona, Flemengia congesta and Gliriciadia sepium with potential fixation from 62.31% to 90,68%. (author)

  6. A rigorous assessment of tree height measurements obtained using airborne LIDAR and conventional field methods. (United States)

    Hans-Erik Andersen; Stephen E. Reutebuch; Robert J. McGaughey


    Tree height is an important variable in forest inventory programs but is typically time-consuming and costly to measure in the field using conventional techniques. Airborne light detection and ranging (LIDAR) provides individual tree height measurements that are highly correlated with field-derived measurements, but the imprecision of conventional field techniques does...

  7. Inventory methods for trees in nonforest areas in the Great Plains States (United States)

    Andrew J. Lister; Charles T. Scott; Steven. Rasmussen


    The US Forest Service's Forest Inventory and Analysis (FIA) program collects information on trees in areas that meet its definition of forest. However, the inventory excludes trees in areas that do not meet this definition, such as those found in urban areas, in isolated patches, in areas with sparse or predominantly herbaceous vegetation, in narrow strips (e.g.,...

  8. A 9111 year long conifer tree-ring chronology for the European Alps : a base for environmental and climatic investigations

    NARCIS (Netherlands)

    Nicolussi, K.; Kaufmann, M.; Melvin, Thomas M.; van der Plicht, J.; Schiessling, P.; Thurner, A.

    An ultra-long tree-ring width chronology (9111 years long, 7109 BC to AD 2002) has been established based on the analysis and dating of 1432 subfossil/dry dead wood samples and cores from 335 living trees. The material was collected from treeline or near-treeline sites (c. 2000 to 2400 m a.s.l.)

  9. An indicator based 'traffic light' model to pro-actively assess the occurrence of mycotoxins in tree nuts

    NARCIS (Netherlands)

    Jeurissen, S.M.F.; Seyhan, F.; Kandhai, M.C.; Dekkers, S.; Booij, C.J.H.; Bos, P.M.J.; Fels, van der H.J.


    This paper proposes an indicator based 'traffic light' model as a tool to pro-actively assess the occurrence of mycotoxins in tree nuts. The model is built using a holistic approach and, consequently, uses indicators from inside and outside the tree nut production chain as the basic elements.

  10. Developing a national and international research community in tree breeding through a web-based information system

    CSIR Research Space (South Africa)

    Hohls, DR


    Full Text Available CSIR research group has developed a web-based information system on tree breeding, which will link national and international partners, which data dating back more than 80 years. Tree breeding relies heavily on managing and exploiting data. While...

  11. Process-based rainfall interception by small trees in Northern China: The effect of rainfall traits and crown structure characteristics (United States)

    Xiang Li; Qingfu Xiao; Jianzhi Niu; Salli Dymond; Natalie S. van Doorn; Xinxiao Yu; Baoyuan Xie; Xizhi Lv; Kebin Zhang; Jiao Li


    Rainfall interception by a tree's crown is one of the most important hydrological processes in an ecosystem, yet the mechanisms of interception are not well understood. A process-based experiment was conducted under five simulated rainfall intensities (from 10 to 150 mm h−1) to directly quantify tree crown interception and examine the effect...

  12. Numerical study of magneto-optical traps through a hierarchical tree method

    International Nuclear Information System (INIS)

    Oliveira, R.S. de; Raposo, E.P.; Vianna, S.S.


    We approach the problem of N atoms in a magneto-optical trap through a hierarchical tree method, using an algorithm originally developed by Barnes and Hut (BH) in the astrophysical context. Such an algorithm numerically takes care of the particle-particle interaction by controlling the approximation level in a way that offers more physical fidelity than the mean-field treatment and considerably less time consumption (τ∼N log 10 N in the hierarchical BH method, in contrast with the τ∼N 2 and τ∼N 3/2 dependences found in direct and mean-field approaches, respectively). Our results reproduce the experimentally reported single-ring orbital mode for N 6 atoms and also find indication of a double-ring structure for N∼10 7 , a situation mimicked by a N=10 6 system with enhanced radiative force, in agreement with experimental observations. We stress that this high-density regime is not accessed by direct integration of the equations of motion, due to the enormous computing times required, and is not suitably described through mean-field approaches, due to the rather unphysical enhancement of the particle-particle interactions and the presence of a spurious numerical grid dependence

  13. Regression Tree-Based Methodology for Customizing Building Energy Benchmarks to Individual Commercial Buildings (United States)

    Kaskhedikar, Apoorva Prakash

    According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI

  14. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J


    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  15. Multiobjective Optimization for the Forecasting Models on the Base of the Strictly Binary Trees


    Nadezhda Astakhova; Liliya Demidova; Evgeny Nikulchev


    The optimization problem dealing with the development of the forecasting models on the base of strictly binary trees has been considered. The aim of paper is the comparative analysis of two optimization variants which are applied for the development of the forecasting models. Herewith the first optimization variant assumes the application of one quality indicator of the forecasting model named as the affinity indicator and the second variant realizes the application of two quality indicators ...

  16. Using the House-Tree-Person (H-T-P) as a Method to Understanding Individual Cultural Differences among Children. (United States)

    Lambeth, Pauline J.

    Finding innovative and effective methods to infer the ability of culturally diverse students continues to present a problem for educators. This paper proposes the House-Tree-Person (HTP) projective technique as a way for school educators to gather important data about student functioning without the use of culturally biased instruments. This…

  17. Tree shelters and other methods for reducing deer damage to hardwood regeneration in the eastern United States (United States)

    Gary W. Miller


    This report summarizes the basic silvicultural problems associated with regenerating commercial hardwood (broadleaf) species in the eastern United States and includes a review of current methods used to reduce the impact of deer browsing. The following topics are discussed: 1) the biological requirements and regeneration mechanism associated with several important tree...

  18. Acoustic-Based Non-Destructive Estimation of Wood Quality Attributes within Standing Red Pine Trees

    Directory of Open Access Journals (Sweden)

    Peter F. Newton


    Full Text Available The relationship between acoustic velocity (vd and the dynamic modulus of elasticity (me, wood density (wd, microfibril angle, tracheid wall thickness (wt,, radial and tangential diameters, fibre coarseness (co and specific surface area (sa, within standing red pine (Pinus resinosa Ait. trees, was investigated. The data acquisition phase involved 3 basic steps: (1 random selection of 54 sample trees from 2 intensively-managed 80-year-old plantations in central Canada; (2 attainment of cardinal-based vd measurements transecting the breast-height position on each sample tree; and (3 felling, sectioning and obtaining cross-sectional samples from the first 5.3 m sawlog from which Silviscan-based area-weighted mean attribute estimates were determined. The data analysis phase consisted of applying graphical and correlation analyses to specify regression models for each of the 8 attribute-acoustic velocity relationships. Results indicated that viable relationships were obtained for me, wd, wt, co and sa based on a set of statistical measures: goodness-of-fit (42%, 14%, 45%, 27% and 43% of the variability explained, respectively, lack-of-fit (unbiasedness and predictive precision (±12%, ±8%, ±7%, ±8% and ±6% error tolerance intervals, respectively. Non-destructive approaches for estimating the prerequisite wd value when deploying the analytical framework were also empirically evaluated. Collectively, the proposed approach and associated results provide the foundation for the development of a comprehensive and precise end-product segregation strategy for use in red pine management.

  19. Design and Analysis of Self-Healing Tree-Based Hybrid Spectral Amplitude Coding OCDMA System

    Directory of Open Access Journals (Sweden)

    Waqas A. Imtiaz


    Full Text Available This paper presents an efficient tree-based hybrid spectral amplitude coding optical code division multiple access (SAC-OCDMA system that is able to provide high capacity transmission along with fault detection and restoration throughout the passive optical network (PON. Enhanced multidiagonal (EMD code is adapted to elevate system’s performance, which negates multiple access interference and associated phase induced intensity noise through efficient two-matrix structure. Moreover, system connection availability is enhanced through an efficient protection architecture with tree and star-ring topology at the feeder and distribution level, respectively. The proposed hybrid architecture aims to provide seamless transmission of information at minimum cost. Mathematical model based on Gaussian approximation is developed to analyze performance of the proposed setup, followed by simulation analysis for validation. It is observed that the proposed system supports 64 subscribers, operating at the data rates of 2.5 Gbps and above. Moreover, survivability and cost analysis in comparison with existing schemes show that the proposed tree-based hybrid SAC-OCDMA system provides the required redundancy at minimum cost of infrastructure and operation.

  20. Multiple enhanced self-protected spanning trees based architecture for recovery from single failure in metro ethernet (United States)

    Li, Yong; Chen, Wentao; Jin, Depeng; Su, Li; Zeng, Lieguang


    Carriers and service providers are rushing to provide Ethernet-based virtual private network services in metro area network (MAN) as the most cost effective way to address the needs of the enterprise network market. To address the fast recovery from any signal failure issue in the Metro Ethernet, we propose a metro Ethernet architecture based on multiple Enhanced Self-protected Spanning Trees (ESST). The recovery mechanism, named Birthday-based Link Replacing Mechanism (BLRM), in this architecture is able to transform a self-protected spanning tree into another spanning tree after any signal link or node failure. Simulation result demonstrates the effectiveness of the BLRM in achieving fast recovery.

  1. A method to improve tree water use estimates by distinguishing sapwood from heartwood using Electrical Resistivity Tomography (United States)

    Guyot, A.; Ostergaard, K.; Lenkopane, M.; Fan, J.; Lockington, D. A.


    Estimating whole-plant water use in trees requires reliable and accurate methods. Measuring sap velocity and extrapolating to tree water use is seen as the most commonly used. However, deducing the tree water use from sap velocity requires an estimate of the sapwood area. This estimate is the highest cause of uncertainty, and can reach more than 50 % of the uncertainty in the estimate of water use per day. Here, we investigate the possibility of using Electrical Resistivity Tomography to evaluate the sapwood area distribution in a plantation of Pinus elliottii. Electric resistivity tomographs of Pinus elliottii show a very typical pattern of electrical resistivity, which is highly correlated to sapwood and heartwood distribution. To identify the key factors controlling the variation of electrical resistivity, cross sections at breast height for ten trees have been monitored with electrical resistivity tomography. Trees have been cut down after the experiment to identify the heartwood/sapwood boundaries and to extract wood and sap samples. pH, electrolyte concentration and wood moisture content have then been analysed for these samples. Results show that the heartwood/sapwood patterns are highly correlated with electrical resistivity, and that the wood moisture content is the most influencing factor controlling the variability of the patterns. These results show that electric resistivity tomography could be used as a powerful tool to identify the sapwood area, and thus be used in combination with sapflow sensors to map tree water use at stand scale. However, if Pinus elliottii shows typical patterns, further work is needed to identify to see if there are species - specific characterictics as shown in previous works (, electrolyte gradients from the bark to the heartwood). Also, patterns of high resistivity in between needles positions, which are not correlated with either wood moisture content or sapwood, appear to be artifacts. Thus, inversion methods have also to

  2. Effective Prediction of Errors by Non-native Speakers Using Decision Tree for Speech Recognition-Based CALL System (United States)

    Wang, Hongcui; Kawahara, Tatsuya

    CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.

  3. Urban tree growth modeling (United States)

    E. Gregory McPherson; Paula J. Peper


    This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...

  4. A Hybrid Windkessel Model of Blood Flow in Arterial Tree Using Velocity Profile Method (United States)

    Aboelkassem, Yasser; Virag, Zdravko


    For the study of pulsatile blood flow in the arterial system, we derived a coupled Windkessel-Womersley mathematical model. Initially, a 6-elements Windkessel model is proposed to describe the hemodynamics transport in terms of constant resistance, inductance and capacitance. This model can be seen as a two compartment model, in which the compartments are connected by a rigid pipe, modeled by one inductor and resistor. The first viscoelastic compartment models proximal part of the aorta, the second elastic compartment represents the rest of the arterial tree and aorta can be seen as the connection pipe. Although the proposed 6-elements lumped model was able to accurately reconstruct the aortic pressure, it can't be used to predict the axial velocity distribution in the aorta and the wall shear stress and consequently, proper time varying pressure drop. We then modified this lumped model by replacing the connection pipe circuit elements with a vessel having a radius R and a length L. The pulsatile flow motions in the vessel are resolved instantaneously along with the Windkessel like model enable not only accurate prediction of the aortic pressure but also wall shear stress and frictional pressure drop. The proposed hybrid model has been validated using several in-vivo aortic pressure and flow rate data acquired from different species such as, humans, dogs and pigs. The method accurately predicts the time variation of wall shear stress and frictional pressure drop. Institute for Computational Medicine, Dept. Biomedical Engineering.

  5. Investigation of a Random-Fractal Antenna Based on a Natural Tree-Leaf Geometry

    Directory of Open Access Journals (Sweden)

    Hatem Rmili


    Full Text Available In this paper, we investigate a new printed antenna based on the 2D image of a fractal tree-leaf geometry by studying the effect of the irregular boundary of the proposed antenna on its radiation characteristics. Both the impedance matching properties and the radiation patterns of the antenna are studied over the frequency band 1–6 GHz. Four configurations are designed by increasing the complexity of the structure, which ranges from iteration 0 to iteration 3. The fractal properties of the proposed tree-leaf antenna are then compared to those of a conventional fractal antenna with smooth edges. Following this, the proposed antennas are fabricated and characterized experimentally. Finally, results are analyzed and discussed, and a practical application for this new type of antennas is proposed.

  6. Immunizations on small worlds of tree-based wireless sensor networks

    International Nuclear Information System (INIS)

    Li Qiao; Zhang Bai-Hai; Cui Ling-Guo; Fan Zhun; Vasilakos Athanasios, V.


    The sensor virus is a serious threat, as an attacker can simply send a single packet to compromise the entire sensor network. Epidemics become drastic with link additions among sensors when the small world phenomena occur. Two immunization strategies, uniform immunization and temporary immunization, are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses. With the former strategy, the infection extends exponentially, although the immunization effectively reduces the contagion speed. With the latter strategy, recurrent contagion oscillations occur in the small world when the spatial-temporal dynamics of the epidemic are considered. The oscillations come from the small-world structure and the temporary immunization. Mathematical analyses on the small world of the Cayley tree are presented to reveal the epidemic dynamics with the two immunization strategies. (general)

  7. Using tree diversity to compare phylogenetic heuristics. (United States)

    Sul, Seung-Jin; Matthews, Suzanne; Williams, Tiffani L


    Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time. We develop new techniques to evaluate phylogenetic heuristics based on both tree scores and topologies to compare Pauprat and Rec-I-DCM3, two popular Maximum Parsimony search algorithms. Our results show that although Pauprat and Rec-I-DCM3 find the trees with the same best scores, topologically these trees are quite different. Furthermore, the Rec-I-DCM3 trees cluster distinctly from the Pauprat trees. In addition to our heatmap visualizations of using parsimony scores and the Robinson-Foulds distance to compare best-scoring trees found by the two heuristics, we also develop entropy-based methods to show the diversity of the trees found. Overall, Pauprat identifies more diverse trees than Rec-I-DCM3. Overall, our work shows that there is value to comparing heuristics beyond the parsimony scores that they find. Pauprat is a slower heuristic than Rec-I-DCM3. However, our work shows that there is tremendous value in using Pauprat to reconstruct trees-especially since it finds identical scoring but topologically distinct trees. Hence, instead of discounting Pauprat, effort should go in improving its implementation. Ultimately, improved performance measures lead to better phylogenetic heuristics and will result in better approximations of the true evolutionary history of the organisms of interest.

  8. Automated coronary artery tree segmentation in X-ray angiography using improved Hessian based enhancement and statistical region merging. (United States)

    Wan, Tao; Shang, Xiaoqing; Yang, Weilin; Chen, Jianhui; Li, Deyu; Qin, Zengchang


    Coronary artery segmentation is a fundamental step for a computer-aided diagnosis system to be developed to assist cardiothoracic radiologists in detecting coronary artery diseases. Manual delineation of the vasculature becomes tedious or even impossible with a large number of images acquired in the daily life clinic. A new computerized image-based segmentation method is presented for automatically extracting coronary arteries from angiography images. A combination of a multiscale-based adaptive Hessian-based enhancement method and a statistical region merging technique provides a simple and effective way to improve the complex vessel structures as well as thin vessel delineation which often missed by other segmentation methods. The methodology was validated on 100 patients who underwent diagnostic coronary angiography. The segmentation performance was assessed via both qualitative and quantitative evaluations. Quantitative evaluation shows that our method is able to identify coronary artery trees with an accuracy of 93% and outperforms other segmentation methods in terms of two widely used segmentation metrics of mean absolute difference and dice similarity coefficient. The comparison to the manual segmentations from three human observers suggests that the presented automated segmentation method is potential to be used in an image-based computerized analysis system for early detection of coronary artery disease. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. A Slicing Tree Representation and QCP-Model-Based Heuristic Algorithm for the Unequal-Area Block Facility Layout Problem

    Directory of Open Access Journals (Sweden)

    Mei-Shiang Chang


    Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.

  10. A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Sebastian Lamprecht


    Full Text Available Determining the exact position of a forest inventory plot—and hence the position of the sampled trees—is often hampered by a poor Global Navigation Satellite System (GNSS signal quality beneath the forest canopy. Inaccurate geo-references hamper the performance of models that aim to retrieve useful information from spatially high remote sensing data (e.g., species classification or timber volume estimation. This restriction is even more severe on the level of individual trees. The objective of this study was to develop a post-processing strategy to improve the positional accuracy of GNSS-measured sample-plot centers and to develop a method to automatically match trees within a terrestrial sample plot to aerial detected trees. We propose a new method which uses a random forest classifier to estimate the matching probability of each terrestrial-reference and aerial detected tree pair, which gives the opportunity to assess the reliability of the results. We investigated 133 sample plots of the Third German National Forest Inventory (BWI, 2011–2012 within the German federal state of Rhineland-Palatinate. For training and objective validation, synthetic forest stands have been modeled using the Waldplaner 2.0 software. Our method has achieved an overall accuracy of 82.7% for co-registration and 89.1% for tree matching. With our method, 60% of the investigated plots could be successfully relocated. The probabilities provided by the algorithm are an objective indicator of the reliability of a specific result which could be incorporated into quantitative models to increase the performance of forest attribute estimations.

  11. Use of the event tree method for evaluate the safety of radioactive facilities; Utilizacion del metodo de arboles de eventos para evaluar la seguridad de instalaciones radiactivas

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez S, A.; Cornejo D, N.; Callis F, E. [CPHR, Calle 20 No. 4113, e/41 y 47 Playa, CP 11300, La Habana (Cuba)]. e-mail:


    The work shows the validity of the use of Trees of Events like a quantitative method appropriate to carry out evaluations of radiological safety. Its were took like base the evaluations of safety of five Radiotherapy Departments, carried out in the mark of the process of authorization of these facilities. The risk values were obtained by means of the combination of the probabilities of occurrence of the events with its consequences. The use of the method allowed to suggest improvements to the existent safety systems, as well as to confirm that the current regulator requirements for this type of facilities to lead to practices with acceptable risk levels. (Author)

  12. Individual based, long term monitoring of acacia trees in hyper arid zone: Integration of a field survey and a remote sensing approach (United States)

    Isaacson, Sivan; Blumberg, Dan G.; Ginat, Hanan; Shalmon, Benny


    Vegetation in hyper arid zones is very sparse as is. Monitoring vegetation changes in hyper arid zones is important because any reduction in the vegetation cover in these areas can lead to a considerable reduction in the carrying capacity of the ecological system. This study focuses on the impact of climate fluctuations on the acacia population in the southern Arava valley, Israel. The period of this survey includes a sequence of dry years with no flashfloods in most of the plots that ended in two years with vast floods. Arid zone acacia trees play a significant role in the desert ecosystem by moderating the extreme environmental conditions including radiation, temperature, humidity and precipitation. The trees also provide nutrients for the desert dwellers. Therefore, acacia trees in arid zones are considered to be `keystone species', because they have major influence over both plants and animal species, i.e., biodiversity. Long term monitoring of the acacia tree population in this area can provide insights into long term impacts of climate fluctuations on ecosystems in arid zones. Since 2000, a continuous yearly based survey on the three species of acacia population in seven different plots is conducted in the southern Arava (established by Shalmon, ecologist of the Israel nature and parks authority). The seven plots representing different ecosystems and hydrological regimes. A yearly based population monitoring enabled us to determine the mortality and recruitment rate of the acacia populations as well as growing rates of individual trees. This survey provides a unique database of the acacia population dynamics during a sequence of dry years that ended in a vast flood event during the winter of 2010. A lack of quantitative, nondestructive methods to estimate and monitor stress status of the acacia trees, led us to integrate remote sensing tools (ground and air-based) along with conventional field measurements in order to develop a long term monitoring of acacia

  13. Timber tree-based contour hedgerow system on sloping acid upland soils: the use of 15N in quantifying tree-crop interaction in agroforestry system

    International Nuclear Information System (INIS)

    Rosales, Crispina M.; Pailagao, Charmaine; Grafia, Alfonso O.; Rivera, Faye G.; Mercado, Agustin R. Jr.


    As the population pressures in the upland increase, agroforestry is inevitably the most appropriate technology to enhance the productive and protective functions of farming systems to benefit both the people living inside and outside the watersheds in a suitable manner. Contour hedgerow is one of the agroforestry systems suitable for sloping uplands where farmers grow tree crops as hedgerows and food crops as alleycrops. Smallholder farmers in Southeast Asia have begun farming timber trees in association with food crops on infertile soils as the dominant enterprise using their own capital resources. A collaborative study between the International Centre for Research in Agroforestry (ICRAF) and Philippine Nuclear Research Institute (PNRI) was established to evaluate the performance of fast growing timber trees as hedgerows on subsistence cereal based farming systems, and the role of N-fixing trees as interplant in enhancing the growth of the trees as well as the cereal crops. There were 4 fast growing timber trees being compared: Acacia mangium (N-fixing), Gmelina arborea (non-N-fixing), Euclyptus deglupta (non-N-fixing), and Swietenia macrophylla (non-N-fixing). A mangium was also used as interplant to determine its influence on the growth of the non-N-fixing trees as well as to the cereal crops. Ammonium sulfate enriched with 10.12 15 N atom percent was applied in solution to the upland rice, as alleycrop, at the rate of 69 kgN/ha in the isotope subplot in 2 splits: 30 days after emergence and at panicle initiation stage. This study was conducted in acid upland soil in Claveria, Misamis Oriental. Acacia mangium grew faster compared with G. arborea, E. deglupta, while S. macrophylla grew lower. The growth of E. deglupta and G. arborea was positively affected by N-fixing interplant in low soil fertility environment. G. arborea and A. mangium produced the highest lateral pruning biomass supplying organic nutrients to the associated annual crops. The amount of

  14. It Takes A Stewardship Village: Is Community-Based Urban Tree Stewardship Effective?

    Directory of Open Access Journals (Sweden)

    Steven E. Boyce


    Full Text Available It is believed that involving the public in street tree (i.e. curbside or sidewalk tree stewardship is an essential part of achieving urban forest canopy goals. However, the incremental benefits of such involvement have not been well studied. Because urban forest stewards contend with many factors that can reduce street tree longevity and offset the benefits of stewardship, quantifying and communicating the overall benefits may help spur stewards’ commitment. To assess the net effect of volunteer street tree stewardship, this article summarizes the development of a community-wide street tree stewardship program and the impact of stewardship on street tree mortality rates over a span of five years. Binary yes-or-no data on whether a steward cared for a street tree were collected for 3,083 growth years, 1,036 of which were for street trees assigned to street tree stewards. The street trees tracked encompassed every street tree within the highly urbanized TriBeCa* neighborhood in lower Manhattan. It was found that significant differences in street tree mortality rates were observed when street trees were stewarded. Odds ratios show an expectation of substantially reduced street tree mortality rates when tree stewards are caring for trees. Other factors regarding where the data was collected, especially specific neighborhood characteristics that may have had an effect on the study, are discussed.

  15. jsPhyloSVG: a javascript library for visualizing interactive and vector-based phylogenetic trees on the web.

    Directory of Open Access Journals (Sweden)

    Samuel A Smits

    Full Text Available BACKGROUND: Many software packages have been developed to address the need for generating phylogenetic trees intended for print. With an increased use of the web to disseminate scientific literature, there is a need for phylogenetic trees to be viewable across many types of devices and feature some of the interactive elements that are integral to the browsing experience. We propose a novel approach for publishing interactive phylogenetic trees. METHODS/PRINCIPAL FINDINGS: We present a javascript library, jsPhyloSVG, which facilitates constructing interactive phylogenetic trees from raw Newick or phyloXML formats directly within the browser in Scalable Vector Graphics (SVG format. It is designed to work across all major browsers and renders an alternative format for those browsers that do not support SVG. The library provides tools for building rectangular and circular phylograms with integrated charting. Interactive features may be integrated and made to respond to events such as clicks on any element of the tree, including labels. CONCLUSIONS/SIGNIFICANCE: jsPhyloSVG is an open-source solution for rendering dynamic phylogenetic trees. It is capable of generating complex and interactive phylogenetic trees across all major browsers without the need for plugins. It is novel in supporting the ability to interpret the tree inference formats directly, exposing the underlying markup to data-mining services. The library source code, extensive documentation and live examples are freely accessible at

  16. Knowledge Based Synthesis of Efficient Structures for Concurrent Computation Using Fat-Trees and Pipelining. (United States)


    based on the proof is feasible. KES.U.86.11 AFO -Th, 87-0 791 Kestrel Institute Knowledge Based Synthesis of Efficient Structures for Concurrent...its own index and those of its children . lAn unbalanced tree can be described by specifying a connection between the root of some subtrees and chosen...node T.internal-, it is assumed that t" = (concat j", k), where 7 and are the subscripts of the children . No other information can be supplied for the

  17. Employing Measures of Heterogeneity and an Object-Based Approach to Extrapolate Tree Species Distribution Data

    Directory of Open Access Journals (Sweden)

    Trevor G. Jones


    Full Text Available Information derived from high spatial resolution remotely sensed data is critical for the effective management of forested ecosystems. However, high spatial resolution data-sets are typically costly to acquire and process and usually provide limited geographic coverage. In contrast, moderate spatial resolution remotely sensed data, while not able to provide the spectral or spatial detail required for certain types of products and applications, offer inexpensive, comprehensive landscape-level coverage. This study assessed using an object-based approach to extrapolate detailed tree species heterogeneity beyond the extent of hyperspectral/LiDAR flightlines to the broader area covered by a Landsat scene. Using image segments, regression trees established ecologically decipherable relationships between tree species heterogeneity and the spectral properties of Landsat segments. The spectral properties of Landsat bands 4 (i.e., NIR: 0.76–0.90 µm, 5 (i.e., SWIR: 1.55–1.75 µm and 7 (SWIR: 2.08–2.35 µm were consistently selected as predictor variables, explaining approximately 50% of variance in richness and diversity. Results have important ramifications for ongoing management initiatives in the study area and are applicable to wide range of applications.

  18. Attack tree based cyber security analysis of nuclear digital instrumentation and control systems

    International Nuclear Information System (INIS)

    Khand, P.A.


    To maintain the cyber security, nuclear digital Instrumentation and Control (I and C) systems must be analyzed for security risks because a single security breach due to a cyber attack can cause system failure, which can have catastrophic consequences on the environment and staff of a Nuclear Power Plant (NPP). Attack trees have been widely used to analyze the cyber security of digital systems due to their ability to capture system specific as well as attacker specific details. Therefore, a methodology based on attack trees has been proposed to analyze the cyber security of the systems. The methodology has been applied for the Cyber Security Analysis (CSA) of a Bistable Processor (BP) of a Reactor Protection System (RPS). Threats have been described according to their source. Attack scenarios have been generated using the attack tree and possible counter measures according to the Security Risk Level (SRL) of each scenario have been suggested. Moreover, cyber Security Requirements (SRs) have been elicited, and suitability of the requirements has been checked. (author)

  19. Carbon Sequestration and Carbon Markets for Tree-Based Intercropping Systems in Southern Quebec, Canada

    Directory of Open Access Journals (Sweden)

    Kiara S. Winans


    Full Text Available Since agriculture directly contributes to global anthropogenic greenhouse gas (GHG emissions, integrating trees into agricultural landscapes through agroforestry systems is a viable adaptive strategy for climate change mitigation. The objective of this study was to evaluate the carbon (C sequestration and financial benefits of C sequestration according to Quebec’s Cap-and-Trade System for Greenhouse Gas Emissions Allowances (C & T System or the Système de plafonnement et d’échange de droits d’émission de gaz à effet de serre du Québec (SPEDE program for two experimental 10-year-old tree-based intercropping (TBI systems in southern Quebec, Canada. We estimated total C stored in the two TBI systems with hybrid poplar and hardwoods and adjacent non-TBI systems under agricultural production, considering soil, crop and crop roots, litterfall, tree and tree roots as C stocks. The C sequestration of the TBI and adjacent non-TBI systems were compared and the market value of the C payment was evaluated using the net present value (NPV approach. The TBI systems had 33% to 36% more C storage than adjacent non-TBI systems. The financial benefits of C sequestration after 10 years of TBI practices amounted to of $2,259–$2,758 CAD ha−1 and $1,568–$1,913 CAD ha−1 for St. Edouard and St. Paulin sites, respectively. We conclude that valorizing the C sequestration of TBI systems could be an incentive to promote the establishment of TBI for the purpose of GHG mitigation in Quebec, Canada.

  20. [Tree-crown information extraction of farmland returned to forests using QuickBird image based on object-oriented approach]. (United States)

    Wu, Jian; Peng, Dao-li


    The improvement of segmentation algorithm and the optimization of feature space are the key factors of improving the accuracy of tree-crown information extraction, and are also the urgent problems of tree-crown information extraction using high resolution images. In the present study, the spectral threshold method was used on the first-class segmentation of QuickBird multi-spectral image to obtain vegetation regions. On the second-class segmentation, the improved algorithm based on edge wa used to segment the panchromatic image, which was processed by the non-linear filtering. Afterwards, the feature space consisting of spectrum, shape and texture features was selected to extract tree-crown information. Finally, 300 random samples and an error matrix were applied to undertake the accuracy assessment of identification. Although errors and confusion exist, this method shows satisfying results with an overall accuracy of 84.67% and a KAPPA coefficient of 0.7953. The corresponding results of the traditional method are 67.67% and 0.6273. The method in this paper can achieve a more precise information extraction of the tree-crown and the results can meet the demand of accurate monitoring and decision-making.

  1. Quartet-based methods to reconstruct phylogenetic networks. (United States)

    Yang, Jialiang; Grünewald, Stefan; Xu, Yifei; Wan, Xiu-Feng


    Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate. We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China. QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses.

  2. Dissimilarity between two skeletal trees in a context

    DEFF Research Database (Denmark)

    Baseski, Emre; Erdem, Aykut; Tari, Sibel


    Skeletal trees are commonly used in order to express geometric properties of the shape. Accordingly, tree-edit distance is used to compute a dissimilarity between two given shapes. We present a new tree-edit based shape matching method which uses a recent coarse skeleton representation. The coars...

  3. Modelling tree biomasses in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Repola, J.


    Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands. These stands (44 Scots pine, 34 Norway spruce and 24 birch stands) were located mainly on mineral soil sites representing a large part of Finland. The biomass models were based on data measured from 1648 sample trees, comprising 908 pine, 613 spruce and 127 birch trees. Biomass equations were derived for the total above-ground biomass and for the individual tree components: stem wood, stem bark, living and dead branches, needles, stump, and roots, as dependent variables. Three multivariate models with different numbers of independent variables for above-ground biomass and one for below-ground biomass were constructed. Variables that are normally measured in forest inventories were used as independent variables. The simplest model formulations, multivariate models (1) were mainly based on tree diameter and height as independent variables. In more elaborated multivariate models, (2) and (3), additional commonly measured tree variables such as age, crown length, bark thickness and radial growth rate were added. Tree biomass modelling includes consecutive phases, which cause unreliability in the prediction of biomass. First, biomasses of sample trees should be determined reliably to decrease the statistical errors caused by sub-sampling. In this study, methods to improve the accuracy of stem biomass estimates of the sample trees were developed. In addition, the reliability of the method applied to estimate sample-tree crown biomass was tested, and no systematic error was detected. Second, the whole information content of data should be utilized in order to achieve reliable parameter estimates and applicable and flexible model structure. In the modelling approach, the basic assumption was that the biomasses of

  4. A rapid method for the production of robust millennial length stable isotope tree ring series for climate reconstruction (United States)

    Gagen, M.; McCarroll, D.; Jalkanen, R.; Loader, N. J.; Robertson, I.; Young, G. H. F.


    We developed a millennial length tree ring δ13C chronology from Pinus sylvestris at a site known as Laanila, in northern Finnish Lapland. In order to measure this series rapidly and with adequate replication, we adapted a multiple year pooling system. Using a combination of offset cut 5-year blocks, plus a novel method of joining tree cohorts together without the loss of a reliable absolute mean, allowed for the preservation of low frequency information in the series. Our 'Join-Point' method addressed systematic error in δ13C between trees and allowed the development of a robust millennial length chronology with a considerably lower number of measurements when compared to annual sampling. Our pooled chronology retains a replication at each year of n = 5 such that it is produced from just ~ 1000 mass spectrometry measurements. The Join-Point verification of the absolute δ13C value, at periods where cohorts of different aged trees meet, requires the analysis of a much larger number of trees at 8 Join-Points. We term this methodology offset-pool plus Join-Point, and describe the characteristics of the series it produces. Use of this method required an assessment of age-related trends in δ13C at the site and an investigation of potential differences between the living and sub-fossil wood material used, prior to the implementation of the method. With the assumption that δ13C series produce robust climate reconstructions, the emphasis has shifted to producing well-replicated series for palaeoclimate purposes. With this aim the analytical precision of a single measurement is considerably less important than the confidence attached to the mean value for each time step. The most efficient way to increase the precision of the estimate of mean δ13C is by increasing replication. Here we have demonstrated a novel method for doing this without the analysis of an unrealistic number of measurements and without the offset in δ13C between trees causing error to accrue back in

  5. Revealing critical mechanisms of BR-mediated apple nursery tree growth using iTRAQ-based proteomic analysis. (United States)

    Zheng, Liwei; Ma, Juanjuan; Zhang, Lizhi; Gao, Cai; Zhang, Dong; Zhao, Caiping; Han, Mingyu


    Brassinosteroid is identified as an important hormone. However, information about brassinosteroid has not been fully elucidated, and few studies concerned its role in apple. The aim of this work was to study the role of brassinosteroid for apple tree growth. In our study, the effect of brassinosteroid on apple nursery tree was analyzed. The biomass, cell size and xylem content of apple nursery tree were obviously evaluated by brassinosteroid treatment; mineral elements contents, photosynthesis indexes, carbohydrate level and hormone contents were significantly high in brassinosteroid treated trees. To explore the molecular mechanisms of these phenotypic differences, iTRAQ-based quantitative proteomics were used to identify the expression profiles of proteins in apple nursery tree shoot tips in response to brassinosteroid at a key period (14days after brassinosteroid treatment). A total of 175 differentially expressed proteins were identified. They were mainly involved in chlorophyII biosynthesis, photosynthesis, carbohydrate metabolism, glycolysis, citric acid cycle, respiratory action, hormone signal, cell growth and ligin metabolism. The findings in this study indicate that brassinosteroid mediating apple nursery tree growth may be mainly through energy metabolism. Important biological processes identified here can be useful theoretical basis and provide new insights into the molecular mechanisms of brassinosteroid. Brassinosteroid is very important for plant growth and development. However, the molecular mechanism of brassinosteroid mediating growth process is not perfectly clear in plant, especially in apple nursery tree. We used a combination of physiological and bioinformatics analysis to investigate the effects of brassinosteroid on apple nursery tree growth and development. The data reported here demonstrated that brassinosteroid regulates apple nursery tree growth mainly through energy metabolism. Therefore it can provide a theoretical basis from energy

  6. Vessel tree extraction using locally optimal paths

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; van Ginneken, Bram; de Bruijne, Marleen


    This paper proposes a method to extract vessel trees by continually extending detected branches with locally optimal paths. Our approach uses a cost function from a multi scale vessel enhancement filter. Optimal paths are selected based on rules that take into account the geometric characteristics...... of the vessel tree. Experiments were performed on 10 low dose chest CT scans for which the pulmonary vessel trees were extracted. The proposed method is shown to extract a better connected vessel tree and extract more of the small peripheral vessels in comparison to applying a threshold on the output...

  7. K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method (United States)

    Sirait, Kamson; Tulus; Budhiarti Nababan, Erna


    Clustering methods that have high accuracy and time efficiency are necessary for the filtering process. One method that has been known and applied in clustering is K-Means Clustering. In its application, the determination of the begining value of the cluster center greatly affects the results of the K-Means algorithm. This research discusses the results of K-Means Clustering with starting centroid determination with a random and KD-Tree method. The initial determination of random centroid on the data set of 1000 student academic data to classify the potentially dropout has a sse value of 952972 for the quality variable and 232.48 for the GPA, whereas the initial centroid determination by KD-Tree has a sse value of 504302 for the quality variable and 214,37 for the GPA variable. The smaller sse values indicate that the result of K-Means Clustering with initial KD-Tree centroid selection have better accuracy than K-Means Clustering method with random initial centorid selection.

  8. TreeVector: scalable, interactive, phylogenetic trees for the web.

    Directory of Open Access Journals (Sweden)

    Ralph Pethica


    Full Text Available Phylogenetic trees are complex data forms that need to be graphically displayed to be human-readable. Traditional techniques of plotting phylogenetic trees focus on rendering a single static image, but increases in the production of biological data and large-scale analyses demand scalable, browsable, and interactive trees.We introduce TreeVector, a Scalable Vector Graphics-and Java-based method that allows trees to be integrated and viewed seamlessly in standard web browsers with no extra software required, and can be modified and linked using standard web technologies. There are now many bioinformatics servers and databases with a range of dynamic processes and updates to cope with the increasing volume of data. TreeVector is designed as a framework to integrate with these processes and produce user-customized phylogenies automatically. We also address the strengths of phylogenetic trees as part of a linked-in browsing process rather than an end graphic for print.TreeVector is fast and easy to use and is available to download precompiled, but is also open source. It can also be run from the web server listed below or the user's own web server. It has already been deployed on two recognized and widely used database Web sites.

  9. The integration methods of fuzzy fault mode and effect analysis and fault tree analysis for risk analysis of yogurt production (United States)

    Aprilia, Ayu Rizky; Santoso, Imam; Ekasari, Dhita Murita


    Yogurt is a product based on milk, which has beneficial effects for health. The process for the production of yogurt is very susceptible to failure because it involves bacteria and fermentation. For an industry, the risks may cause harm and have a negative impact. In order for a product to be successful and profitable, it requires the analysis of risks that may occur during the production process. Risk analysis can identify the risks in detail and prevent as well as determine its handling, so that the risks can be minimized. Therefore, this study will analyze the risks of the production process with a case study in CV.XYZ. The method used in this research is the Fuzzy Failure Mode and Effect Analysis (fuzzy FMEA) and Fault Tree Analysis (FTA). The results showed that there are 6 risks from equipment variables, raw material variables, and process variables. Those risks include the critical risk, which is the risk of a lack of an aseptic process, more specifically if starter yogurt is damaged due to contamination by fungus or other bacteria and a lack of sanitation equipment. The results of quantitative analysis of FTA showed that the highest probability is the probability of the lack of an aseptic process, with a risk of 3.902%. The recommendations for improvement include establishing SOPs (Standard Operating Procedures), which include the process, workers, and environment, controlling the starter of yogurt and improving the production planning and sanitation equipment using hot water immersion.

  10. A New Architecture for Making Moral Agents Based on C4.5 Decision Tree Algorithm


    Meisam Azad-Manjiri


    Regarding to the influence of robots in the various fields of life, the issue of trusting to them is important, especially when a robot deals with people directly. One of the possible ways to get this confidence is adding a moral dimension to the robots. Therefore, we present a new architecture in order to build moral agents that learn from demonstrations. This agent is based on Beauchamp and Childress’s principles of biomedical ethics (a type of deontological theory) and uses decision tree a...

  11. Dynamic Security Assessment of Danish Power System Based on Decision Trees: Today and Tomorrow

    DEFF Research Database (Denmark)

    Rather, Zakir Hussain; Liu, Leo; Chen, Zhe


    Danish Power System. Results from offline time domain simulation for large number of possible operating conditions (OC) and critical contingencies are organized to build up the database, which is then used to predict the security of present and future power system. The mentioned approach is implemented......The research work presented in this paper analyzes the impact of wind energy, phasing out of central power plants and cross border power exchange on dynamic security of Danish Power System. Contingency based decision tree (DT) approach is used to assess the dynamic security of present and future...... significant impact on dynamic security of Danish power system in future, if alternative measures are not considered seriously....

  12. Immunizations on small worlds of tree-based wireless sensor networks

    DEFF Research Database (Denmark)

    Li, Qiao; Zhang, Bai-Hai; Cui, Ling-Guo


    The sensor virus is a serious threat, as an attacker can simply send a single packet to compromise the entire sensor network. Epidemics become drastic with link additions among sensors when the small world phenomena occur. Two immunization strategies, uniform immunization and temporary immunization......, are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses. With the former strategy, the infection extends exponentially, although the immunization effectively reduces the contagion speed. With the latter strategy, recurrent contagion oscillations occur in the small world...

  13. Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices

    Directory of Open Access Journals (Sweden)

    Liao Li


    Full Text Available Abstract Background Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-evolutionary information of the interacting partners, e.g., correlations between distance matrices, where each matrix stores the pairwise distances between a protein and its orthologs from a group of reference genomes. Results We proposed a novel, simple method to account for some of the intra-matrix correlations in improving the prediction accuracy. Specifically, the phylogenetic species tree of the reference genomes is used as a guide tree for hierarchical clustering of the orthologous proteins. The distances between these clusters, derived from the original pairwise distance matrix using the Neighbor Joining algorithm, form intermediate distance matrices, which are then transformed and concatenated into a super phylogenetic vector. A support vector machine is trained and tested on pairs of proteins, represented as super phylogenetic vectors, whose interactions are known. The performance, measured as ROC score in cross validation experiments, shows significant improvement of our method (ROC score 0.8446 over that of using Pearson correlations (0.6587. Conclusion We have shown that the phylogenetic tree can be used as a guide to extract intra-matrix correlations in the distance matrices of orthologous proteins, where these correlations are represented as intermediate distance matrices of the ancestral orthologous proteins. Both the unsupervised and supervised learning paradigms benefit from the explicit inclusion of these intermediate distance matrices, and particularly so in the latter case, which offers a better balance between sensitivity and specificity in the prediction of protein-protein interactions.

  14. Mapping mangrove forests using multi-tidal remotely-sensed data and a decision-tree-based procedure (United States)

    Zhang, Xuehong; Treitz, Paul M.; Chen, Dongmei; Quan, Chang; Shi, Lixin; Li, Xinhui


    Mangrove forests grow in intertidal zones in tropical and subtropical regions and have suffered a dramatic decline globally over the past few decades. Remote sensing data, collected at various spatial resolutions, provide an effective way to map the spatial distribution of mangrove forests over time. However, the spectral signatures of mangrove forests are significantly affected by tide levels. Therefore, mangrove forests may not be accurately mapped with remote sensing data collected during a single-tidal event, especially if not acquired at low tide. This research reports how a decision-tree -based procedure was developed to map mangrove forests using multi-tidal Landsat 5 Thematic Mapper (TM) data and a Digital Elevation Model (DEM). Three indices, including the Normalized Difference Moisture Index (NDMI), the Normalized Difference Vegetation Index (NDVI) and NDVIL·NDMIH (the multiplication of NDVIL by NDMIH, L: low tide level, H: high tide level) were used in this algorithm to differentiate mangrove forests from other land-cover and land-use types in Fangchenggang City, China. Additionally, the recent Landsat 8 OLI (Operational Land Imager) data were selected to validate the results and compare if the methodology is reliable. The results demonstrate that short-term multi-tidal remotely-sensed data better represent the unique nearshore coastal wetland habitats of mangrove forests than single-tidal data. Furthermore, multi-tidal remotely-sensed data has led to improved accuracies using two classification approaches: i.e. decision trees and the maximum likelihood classification (MLC). Since mangrove forests are typically found at low elevations, the inclusion of elevation data in the two classification procedures was tested. Given the decision-tree method does not assume strict data distribution parameters, it was able to optimize the application of multi-tidal and elevation data, resulting in higher classification accuracies of mangrove forests. When using multi

  15. Activity – based costing method

    Directory of Open Access Journals (Sweden)

    Èuchranová Katarína


    Full Text Available Activity based costing is a method of identifying and tracking the operating costs directly associated with processing items. It is the practice of focusing on some unit of output, such as a purchase order or an assembled automobile and attempting to determine its total as precisely as poccible based on the fixed and variable costs of the inputs.You use ABC to identify, quantify and analyze the various cost drivers (such as labor, materials, administrative overhead, rework. and to determine which ones are candidates for reduction.A processes any activity that accepts inputs, adds value to these inputs for customers and produces outputs for these customers. The customer may be either internal or external to the organization. Every activity within an organization comprimes one or more processes. Inputs, controls and resources are all supplied to the process.A process owner is the person responsible for performing and or controlling the activity.The direction of cost through their contact to partial activity and processes is a new modern theme today. Beginning of this method is connected with very important changes in the firm processes.ABC method is a instrument , that bring a competitive advantages for the firm.

  16. Species delimitation in the lichenized fungal genus Vulpicida (Parmeliaceae, Ascomycota) using gene concatenation and coalescent-based species tree approaches. (United States)

    Saag, Lauri; Mark, Kristiina; Saag, Andres; Randlane, Tiina


    • Species boundaries in many organism groups are still in a state of flux, and for empirical species delimitation, finding appropriate character sets and analytical tools are among the greatest challenges. In the lichenized fungal genus Vulpicida, six morphologically circumscribed species have been distinguished, but phenotypic characters partly overlap for three of these and intermediate forms occur. We used a combination of phylogenetic strategies to delimit the species in this genus.• Five DNA loci were sequenced and analyzed. Single-locus gene trees and a five-locus concatenated phylogeny were constructed to assess current Vulpicida species. Species boundaries were inferred from molecular data using two coalescent-based species delimitation methods (BP&P and Brownie) and from species trees reconstructed with three different algorithms (*BEAST, BEST, and STEM).• The two species restricted to North America, Vulpicida canadensis and V. viridis, are clearly distinct in all analyses. The four other traditionally accepted species form two strongly supported, closely related species-level lineages within the core group of the genus. On the basis of these results, we propose four instead of the current six species in the genus: V. canadensis, V. juniperinus, V. pinastri, and V. viridis, while V. tilesii and V. tubulosus are reduced to synonymy under V. juniperinus.• Coalescent species delimitation and tree inference give consistent results for fully distinct Vulpicida species but not for diverging populations. Even the inconsistent results were informative, revealing developing isolation despite a complex history of recombination and incomplete lineage sorting. © 2014 Botanical Society of America, Inc.

  17. Influence of the methods of budding on growth and quality of one-year-old trees of apple cv. Red Elstar 'Elshof'

    Directory of Open Access Journals (Sweden)

    Stanisław Wociór


    Full Text Available The experiment was carried out during 1995-1997 in the experimental nursery field of the Agricultural University of Lublin, Poland, in Lublin-Felin. M.9 (EMLA apple rootstocks were planted at 0,9 - 0,3 (m. No significant differences in tree trunk diameter, tree height and total extension growth of one-year-old shoots between chipand T-budded apple maiden trees of 'Red Elstar Elshof' were found. Chip budding increased the number of trees of first quality about twofold in comparison with T-budding, however, this difference was not significant. Either method of budding considerably influenced the rate of growth of apple trees in nursery. The highest rate of tree growth was observed in May and June.

  18. Chinese Sign Language Recognition Based on an Optimized Tree-Structure Framework. (United States)

    Yang, Xidong; Chen, Xiang; Cao, Xiang; Wei, Shengjing; Zhang, Xu


    Chinese Sign Language (CSL) subword recognition based on surface electromyography (sEMG), accelerometer (ACC), and gyroscope (GYRO) sensors was explored in this paper. In order to fuse effectively the information of these three kinds of sensors, the classification abilities of sEMG, ACC, GYRO, and their combinations in three common sign components (one or two handed, hand orientation, and hand amplitude) were evaluated first and then an optimized tree-structure classification framework was proposed for CSL subword recognition. Eight subjects participated in this study and recognition experiments under different testing conditions were implemented on a target set consisting of 150 CSL subwords. The proposed optimized tree-structure classification framework based on sEMG, ACC, and GYRO obtained the best performance among seven different testing conditions with single sensor, paired-sensor fusion, and three-sensor fusion, and the overall recognition accuracies of 94.31% and 87.02% were obtained for 150 CSL subwords in a user-specific test and user-independent test, respectively. Our study could lay a basis for the implementation of large-vocabulary sign language recognition system based on sEMG, ACC, and GYRO sensors.

  19. Predicting apple tree leaf nitrogen content based on hyperspectral applying wavelet and wavelet packet analysis (United States)

    Zhang, Yao; Zheng, Lihua; Li, Minzan; Deng, Xiaolei; Sun, Hong


    The visible and NIR spectral reflectance were measured for apple leaves by using a spectrophotometer in fruit-bearing, fruit-falling and fruit-maturing period respectively, and the nitrogen content of each sample was measured in the lab. The analysis of correlation between nitrogen content of apple tree leaves and their hyperspectral data was conducted. Then the low frequency signal and high frequency noise reduction signal were extracted by using wavelet packet decomposition algorithm. At the same time, the original spectral reflectance was denoised taking advantage of the wavelet filtering technology. And then the principal components spectra were collected after PCA (Principal Component Analysis). It was known that the model built based on noise reduction principal components spectra reached higher accuracy than the other three ones in fruit-bearing period and physiological fruit-maturing period. Their calibration R2 reached 0.9529 and 0.9501, and validation R2 reached 0.7285 and 0.7303 respectively. While in the fruit-falling period the model based on low frequency principal components spectra reached the highest accuracy, and its calibration R2 reached 0.9921 and validation R2 reached 0.6234. The results showed that it was an effective way to improve ability of predicting apple tree nitrogen content based on hyperspectral analysis by using wavelet packet algorithm.

  20. Rich Interfaces for Dependability: Compositional Methods for Dynamic Fault Trees and Arcade models

    NARCIS (Netherlands)

    Boudali, H.; Crouzen, Pepijn; Haverkort, Boudewijn R.H.M.; Kuntz, G.W.M.; Stoelinga, Mariëlle Ida Antoinette

    This paper discusses two behavioural interfaces for reliability analysis: dynamic fault trees, which model the system reliability in terms of the reliability of its components and Arcade, which models the system reliability at an architectural level. For both formalisms, the reliability is analyzed

  1. Methods to Evaluate Host Tree Suitability to the Asian Long horned Beetle, Anoplophora glabripennis (United States)

    Scott W. Ludwig; Laura Lazarus; Deborah G. McCullough; Kelli Hoover; Silvia Montero; James C. Sellmer


    Two procedures were evaluated for assessing tree susceptibility to Anaplophora glabripennis. In the first procedure, adult beetles were caged with a section of sugar maple, northern red oak, white oak, honeylocust, eastern cottonwood, sycamore or tulip poplar wood Results showed that females laid viable eggs on sugar maple, red oak, white oak and...

  2. Seed germination methods for native Caribbean trees and shrubs : with emphasis on species relevant for Bonaire

    NARCIS (Netherlands)

    Burg, van der W.J.; Freitas, J.; Debrot, A.O.


    This paper is intended as a basis for nature restoration activities using seeds of trees and (larger) shrubs native to Bonaire with the aim of reforestation. It describes the main seed biology issues relevant for species from this region, to facilitate decisions on time and stage of harvesting, safe

  3. Late summer temperature reconstruction based on tree-ring density for Sygera Mountain, southeastern Tibetan Plateau (United States)

    Li, Mingyong; Duan, Jianping; Wang, Lily; Zhu, Haifeng


    Although several tree-ring density-based summer/late summer temperature reconstructions have been developed on the Tibetan Plateau (TP), the understanding of the local/regional characteristics of summer temperature fluctuations on a long-term scale in some regions is still limited. To improve our understanding in these aspects, more local or regional summer temperature reconstructions extending back over several centuries are required. In this study, a new mean latewood density (LWD) chronology from Abies georgei var. smithii from the upper tree line of Sygera Mountain on the southeastern TP was developed to reconstruct the late summer temperature variability since 1820 CE. The bootstrapped correlation analysis showed that the LWD chronology index was significantly and positively correlated with the late summer (August-September) mean temperatures (r1950-2008 = 0.63, p < 0.001) recorded at the nearest meteorological station and that this reconstruction has considerable potential to represent the late summer temperature variability at the regional scale. Our late summer temperature reconstruction revealed three obvious cold periods (i.e., 1872-1908, 1913-1937 and 1941-1966) and two relatively warm phases (i.e., 1821-1871 and 1970-2008) over the past two centuries. Comparisons of our reconstruction with other independent tree-ring-based temperature reconstructions, glacier fluctuations and historical documental records from neighboring regions showed good agreement in these relatively cold and warm intervals. Our reconstruction exhibits an overall increasing temperature trend since the 1960s, providing new evidence supporting the recent warming of the TP. Moreover, our results also indicate that the late summer temperature variability of Sygera Mountain on the southeastern TP has potential links with the Pacific Decadal Oscillation (PDO).

  4. Energy spectra unfolding of fast neutron sources using the group method of data handling and decision tree algorithms (United States)

    Hosseini, Seyed Abolfazl; Afrakoti, Iman Esmaili Paeen


    Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). The developed computational codes based on the GMDH and DT algorithms use some data for training, testing and validation steps. In order to prepare the required data, 4000 randomly generated energy spectra distributed over 52 bins are used. The randomly generated energy spectra and the simulated neutron pulse height distributions by MCNPX-ESUT for each energy spectrum are used as the output and input data. Since there is no need to solve the inverse problem with an ill-conditioned response matrix, the unfolded energy spectrum has the highest accuracy. The 241Am-9Be and 252Cf neutron sources are used in the validation step of the calculation. The unfolded energy spectra for the used fast neutron sources have an excellent agreement with the reference ones. Also, the accuracy of the unfolded energy spectra obtained using the GMDH is slightly better than those obtained from the DT. The results obtained in the present study have good accuracy in comparison with the previously published paper based on the logsig and tansig transfer functions.

  5. Distributed primal–dual interior-point methods for solving tree-structured coupled convex problems using message-passing

    DEFF Research Database (Denmark)

    Khoshfetrat Pakazad, Sina; Hansson, Anders; Andersen, Martin S.


    In this paper, we propose a distributed algorithm for solving coupled problems with chordal sparsity or an inherent tree structure which relies on primal–dual interior-point methods. We achieve this by distributing the computations at each iteration, using message-passing. In comparison to existing...... distributed algorithms for solving such problems, this algorithm requires far fewer iterations to converge to a solution with high accuracy. Furthermore, it is possible to compute an upper-bound for the number of required iterations which, unlike existing methods, only depends on the coupling structure...... in the problem. We illustrate the performance of our proposed method using a set of numerical examples....

  6. Compression of multispectral fluorescence microscopic images based on a modified set partitioning in hierarchal trees (United States)

    Mansoor, Awais; Robinson, J. Paul; Rajwa, Bartek


    Modern automated microscopic imaging techniques such as high-content screening (HCS), high-throughput screening, 4D imaging, and multispectral imaging are capable of producing hundreds to thousands of images per experiment. For quick retrieval, fast transmission, and storage economy, these images should be saved in a compressed format. A considerable number of techniques based on interband and intraband redundancies of multispectral images have been proposed in the literature for the compression of multispectral and 3D temporal data. However, these works have been carried out mostly in the elds of remote sensing and video processing. Compression for multispectral optical microscopy imaging, with its own set of specialized requirements, has remained under-investigated. Digital photography{oriented 2D compression techniques like JPEG (ISO/IEC IS 10918-1) and JPEG2000 (ISO/IEC 15444-1) are generally adopted for multispectral images which optimize visual quality but do not necessarily preserve the integrity of scientic data, not to mention the suboptimal performance of 2D compression techniques in compressing 3D images. Herein we report our work on a new low bit-rate wavelet-based compression scheme for multispectral fluorescence biological imaging. The sparsity of signicant coefficients in high-frequency subbands of multispectral microscopic images is found to be much greater than in natural images; therefore a quad-tree concept such as Said et al.'s SPIHT1 along with correlation of insignicant wavelet coefficients has been proposed to further exploit redundancy at high-frequency subbands. Our work propose a 3D extension to SPIHT, incorporating a new hierarchal inter- and intra-spectral relationship amongst the coefficients of 3D wavelet-decomposed image. The new relationship, apart from adopting the parent-child relationship of classical SPIHT, also brought forth the conditional "sibling" relationship by relating only the insignicant wavelet coefficients of subbands


    Directory of Open Access Journals (Sweden)



    Full Text Available The continuous expansion of built-up areas in the urban environment at the expense of green spaces brings up numerous environmental problems, for which accurate and efficient solutions should be found. The assessment of ecosystem services developed within the field of landscape ecology is playing an ever more important role in environmental sciences and thus may offer suitable answers. Such assessments can be carried out by developing indicators. Accordingly, in the case of urban trees, an accurate quantitative characterization of their services (such as e.g. carbon sequestration, pollutant removal and microclimate regulation is also needed. The aim of this study is to establish a generally applicable method based on indicator development, using widely available data. In the case of urban green spaces there are several services for which the development of proper indicators and evaluation methods requires a delineation of tree crowns, or at least the crown projection area. Accordingly, in our work, we map the crown projection area of a large and popular urban park of Szeged, Széchenyi square, using object-based image analysis on UltraCamD digital orthophotos. Following a multiresolution segmentation the classification of the resulting objects was carried out, using the eCognition image analysis software. Besides fulfilling the policy objectives related to the evaluation of urban ecosystem services, the produced crown base can also be used in several other types of urban ecological and urban climatological studies (e.g. urban climate modelling, human-comfort assessment. In this paper the first results are presented.

  8. Decision trees in epidemiological research

    Directory of Open Access Journals (Sweden)

    Ashwini Venkatasubramaniam


    Full Text Available Abstract Background In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. Main text We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART technique and the newer Conditional Inference tree (CTree technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Conclusions Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

  9. Decision trees in epidemiological research. (United States)

    Venkatasubramaniam, Ashwini; Wolfson, Julian; Mitchell, Nathan; Barnes, Timothy; JaKa, Meghan; French, Simone


    In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

  10. Decision-Tree Program (United States)

    Buntine, Wray


    IND computer program introduces Bayesian and Markov/maximum-likelihood (MML) methods and more-sophisticated methods of searching in growing trees. Produces more-accurate class-probability estimates important in applications like diagnosis. Provides range of features and styles with convenience for casual user, fine-tuning for advanced user or for those interested in research. Consists of four basic kinds of routines: data-manipulation, tree-generation, tree-testing, and tree-display. Written in C language.

  11. [Work accidents in Brazil. A study in São Paulo state, Brazil, the Botucatu region, using the causal tree method]. (United States)

    Binder, M C; Almeida, I M


    This paper discusses, within the prevailing Brazilian situation, the possibility of applying "causal tree" (CT) method in investigating occupational accidents by safety personnel in the public health services and workers' unions. The method was developed during the seventies in France, for use by plant safety personnel. The authors used this method in Botucatu, state of São Paulo, Brazil, in order to investigate 40 serious occupational accidents that occurred in industrial plants during the second half of 1993, that had been registered by social security. In these cases, the predominance of situations in which the lack of safety measures were identified by inspection indicates that in most instances, the use of CT is unnecessary. However, the authors discuss its use by safety personnel from the public health services and workers' unions to investigate certain accidents to contribute to the knowledge base and help overcome the cultural based guilt which, in Brazil, has turned the victim into the person responsible for the accident.

  12. A Tree Based Self-routing Scheme for Mobility Support in Wireless Sensor Networks (United States)

    Kim, Young-Duk; Yang, Yeon-Mo; Kang, Won-Seok; Kim, Jin-Wook; An, Jinung

    Recently, WSNs (Wireless Sensor Networks) with mobile robot is a growing technology that offer efficient communication services for anytime and anywhere applications. However, the tiny sensor node has very limited network resources due to its low battery power, low data rate, node mobility, and channel interference constraint between neighbors. Thus, in this paper, we proposed a tree based self-routing protocol for autonomous mobile robots based on beacon mode and implemented in real test-bed environments. The proposed scheme offers beacon based real-time scheduling for reliable association process between parent and child nodes. In addition, it supports smooth handover procedure by reducing flooding overhead of control packets. Throughout the performance evaluation by using a real test-bed system and simulation, we illustrate that our proposed scheme demonstrates promising performance for wireless sensor networks with mobile robots.

  13. Improvement of adequate use of warfarin for the elderly using decision tree-based approaches. (United States)

    Liu, K E; Lo, C-L; Hu, Y-H


    Due to the narrow therapeutic range and high drug-to-drug interactions (DDIs), improving the adequate use of warfarin for the elderly is crucial in clinical practice. This study examines whether the effectiveness of using warfarin among elderly inpatients can be improved when machine learning techniques and data from the laboratory information system are incorporated. Having employed 288 validated clinical cases in the DDI group and 89 cases in the non-DDI group, we evaluate the prediction performance of seven classification techniques, with and without an Adaptive Boosting (AdaBoost) algorithm. Measures including accuracy, sensitivity, specificity and area under the curve are used to evaluate model performance. Decision tree-based classifiers outperform other investigated classifiers in all evaluation measures. The classifiers supplemented with AdaBoost can generally improve the performance. In addition, weight, congestive heart failure, and gender are among the top three critical variables affecting prediction accuracy for the non-DDI group, while age, ALT, and warfarin doses are the most influential factors for the DDI group. Medical decision support systems incorporating decision tree-based approaches improve predicting performance and thus may serve as a supplementary tool in clinical practice. Information from laboratory tests and inpatients' history should not be ignored because related variables are shown to be decisive in our prediction models, especially when the DDIs exist.

  14. Testing digital safety system software with a testability measure based on a software fault tree

    International Nuclear Information System (INIS)

    Sohn, Se Do; Hyun Seong, Poong


    Using predeveloped software, a digital safety system is designed that meets the quality standards of a safety system. To demonstrate the quality, the design process and operating history of the product are reviewed along with configuration management practices. The application software of the safety system is developed in accordance with the planned life cycle. Testing, which is a major phase that takes a significant time in the overall life cycle, can be optimized if the testability of the software can be evaluated. The proposed testability measure of the software is based on the entropy of the importance of basic statements and the failure probability from a software fault tree. To calculate testability, a fault tree is used in the analysis of a source code. With a quantitative measure of testability, testing can be optimized. The proposed testability can also be used to demonstrate whether the test cases based on uniform partitions, such as branch coverage criteria, result in homogeneous partitions that is known to be more effective than random testing. In this paper, the testability measure is calculated for the modules of a nuclear power plant's safety software. The module testing with branch coverage criteria required fewer test cases if the module has higher testability. The result shows that the testability measure can be used to evaluate whether partitions have homogeneous characteristics

  15. Research on the discharge characteristics for water tree in crosslinked polyethylene cable based on plasma-chemical model (United States)

    Fan, Yang; Qi, Yang; Bing, Gao; Rong, Xia; Yanjie, Le; Iroegbu, Paul Ikechukwu


    Water tree is the predominant defect in high-voltage crosslinked polyethylene cables. The microscopic mechanism in the discharge process is not fully understood; hence, a drawback is created towards an effective method to evaluate the insulation status. In order to investigate the growth of water tree, a plasma-chemical model is developed. The dynamic characteristics of the discharge process including voltage waveform, current waveform, electron density, electric potential, and electric field intensity are analyzed. Our results show that the distorted electric field is the predominant contributing factor of electron avalanche formation, which inevitably leads to the formation of pulse current. In addition, it is found that characteristic parameters such as the pulse width and pulse number have a great relevance to the length of water tree. Accordingly, the growth of water tree can be divided into the initial stage, development stage, and pre-breakdown stage, which provides a reference for evaluating the deteriorated stages of crosslinked polyethylene cables.

  16. Planting sentinel European trees in eastern Asia as a novel method to identify potential insect pest invaders.

    Directory of Open Access Journals (Sweden)

    Alain Roques

    Full Text Available Quarantine measures to prevent insect invasions tend to focus on well-known pests but a large proportion of the recent invaders were not known to cause significant damage in their native range, or were not even known to science before their introduction. A novel method is proposed to detect new potential pests of woody plants in their region of origin before they are introduced to a new continent. Since Asia is currently considered to be the main supplier of insect invaders to Europe, sentinel trees were planted in China during 2007-2011 as an early warning tool to identify the potential for additional Asian insect species to colonize European trees. Seedlings (1-1.5 m tall of five broadleaved (Quercus petraea, Q. suber, Q. ilex, Fagus sylvatica, and Carpinus betulus and two conifer species (Abies alba and Cupressus sempervirens were planted in blocks of 100 seedlings at two widely separated sites (one in a nursery near Beijing and the other in a forest environment near Fuyang in eastern China, and then regularly surveyed for colonization by insects. A total of 104 insect species, mostly defoliators, were observed on these new hosts, and at least six species were capable of larval development. Although a number of the insects observed were probably incidental feeders, 38 species had more than five colonization events, mostly infesting Q. petraea, and could be considered as being capable of switching to European trees if introduced to Europe. Three years was shown to be an appropriate duration for the experiment, since the rate of colonization then tended to plateau. A majority of the identified species appeared to have switched from agricultural crops and fruit trees rather than from forest trees. Although these results are promising, the method is not appropriate for xylophagous pests and other groups developing on larger trees. Apart from the logistical problems, the identification to species level of the specimens collected was a major

  17. Equations for predicting uncompacted crown ratio based on compacted crown ratio and tree attributes. (United States)

    Vicente J. Monleon; David Azuma; Donald. Gedney


    Equations to predict uncompacted crown ratio as a function of compacted crown ratio, tree diameter, and tree height are developed for the main tree species in Oregon, Washington, and California using data from the Forest Health Monitoring Program, USDA Forest Service. The uncompacted crown ratio was modeled with a logistic function and fitted using weighted, nonlinear...

  18. Effects of lightning on trees: A predictive model based on in situ electrical resistivity. (United States)

    Gora, Evan M; Bitzer, Phillip M; Burchfield, Jeffrey C; Schnitzer, Stefan A; Yanoviak, Stephen P


    The effects of lightning on trees range from catastrophic death to the absence of observable damage. Such differences may be predictable among tree species, and more generally among plant life history strategies and growth forms. We used field-collected electrical resistivity data in temperate and tropical forests to model how the distribution of power from a lightning discharge varies with tree size and identity, and with the presence of lianas. Estimated heating density (heat generated per volume of tree tissue) and maximum power (maximum rate of heating) from a standardized lightning discharge differed 300% among tree species. Tree size and morphology also were important; the heating density of a hypothetical 10 m tall Alseis blackiana was 49 times greater than for a 30 m tall conspecific, and 127 times greater than for a 30 m tall Dipteryx panamensis . Lianas may protect trees from lightning by conducting electric current; estimated heating and maximum power were reduced by 60% (±7.1%) for trees with one liana and by 87% (±4.0%) for trees with three lianas. This study provides the first quantitative mechanism describing how differences among trees can influence lightning-tree interactions, and how lianas can serve as natural lightning rods for trees.

  19. Reliability Analysis of Main-axis Control System of the Equatorial Antarctica Astronomical Telescope Based on Fault Tree (United States)

    LI, Y.; Yang, S. H.


    The Antarctica astronomical telescopes work chronically on the top of the unattended South Pole, and they have only one chance to maintain every year. Due to the complexity of the optical, mechanical, and electrical systems, the telescopes are hard to be maintained and need multi-tasker expedition teams, which means an excessive awareness is essential for the reliability of the Antarctica telescopes. Based on the fault mechanism and fault mode of the main-axis control system for the equatorial Antarctica astronomical telescope AST3-3 (Antarctic Schmidt Telescopes 3-3), the method of fault tree analysis is introduced in this article, and we obtains the importance degree of the top event from the importance degree of the bottom event structure. From the above results, the hidden problems and weak links can be effectively found out, which will indicate the direction for promoting the stability of the system and optimizing the design of the system.

  20. A Survey on Robotic Coconut Tree Climbers - Existing Methods and Techniques (United States)

    Kannan Megalingam, Rajesh; Sakthiprasad, K. M.; Sreekanth, M. M.; Vamsy Vivek, Gedela


    As the coconut palm growers are struggling with the acute shortage of human coconut tree climbers to climb and harvest the coconuts, many are working towards possible alternatives to help them handle this situation. In this study paper we analyse the problems associated with the shortage of human coconut tree climbers in -depth. We also present details of various existing mechanical models available in the market and have not yet solved this issue. Along with this we discuss how robotics and automation could be a possible solution for this entire problem. In this context we discuss about the features of such robotic system and also give suggestions on various unmanned robotic models that can be designed and implemented.

  1. PREP KITT, System Reliability by Fault Tree Analysis. PREP, Min Path Set and Min Cut Set for Fault Tree Analysis, Monte-Carlo Method. KITT, Component and System Reliability Information from Kinetic Fault Tree Theory

    International Nuclear Information System (INIS)

    Vesely, W.E.; Narum, R.E.


    1 - Description of problem or function: The PREP/KITT computer program package obtains system reliability information from a system fault tree. The PREP program finds the minimal cut sets and/or the minimal path sets of the system fault tree. (A minimal cut set is a smallest set of components such that if all the components are simultaneously failed the system is failed. A minimal path set is a smallest set of components such that if all of the components are simultaneously functioning the system is functioning.) The KITT programs determine reliability information for the components of each minimal cut or path set, for each minimal cut or path set, and for the system. Exact, time-dependent reliability information is determined for each component and for each minimal cut set or path set. For the system, reliability results are obtained by upper bound approximations or by a bracketing procedure in which various upper and lower bounds may be obtained as close to one another as desired. The KITT programs can handle independent components which are non-repairable or which have a constant repair time. Any assortment of non-repairable components and components having constant repair times can be considered. Any inhibit conditions having constant probabilities of occurrence can be handled. The failure intensity of each component is assumed to be constant with respect to time. The KITT2 program can also handle components which during different time intervals, called phases, may have different reliability properties. 2 - Method of solution: The PREP program obtains minimal cut sets by either direct deterministic testing or by an efficient Monte Carlo algorithm. The minimal path sets are obtained using the Monte Carlo algorithm. The reliability information is obtained by the KITT programs from numerical solution of the simple integral balance equations of kinetic tree theory. 3 - Restrictions on the complexity of the problem: The PREP program will obtain the minimal cut and

  2. Fault tree handbook

    International Nuclear Information System (INIS)

    Haasl, D.F.; Roberts, N.H.; Vesely, W.E.; Goldberg, F.F.


    This handbook describes a methodology for reliability analysis of complex systems such as those which comprise the engineered safety features of nuclear power generating stations. After an initial overview of the available system analysis approaches, the handbook focuses on a description of the deductive method known as fault tree analysis. The following aspects of fault tree analysis are covered: basic concepts for fault tree analysis; basic elements of a fault tree; fault tree construction; probability, statistics, and Boolean algebra for the fault tree analyst; qualitative and quantitative fault tree evaluation techniques; and computer codes for fault tree evaluation. Also discussed are several example problems illustrating the basic concepts of fault tree construction and evaluation

  3. Automated estimation of leaf distribution for individual trees based on TLS point clouds (United States)

    Koma, Zsófia; Rutzinger, Martin; Bremer, Magnus


    Light Detection and Ranging (LiDAR) especially the ground based LiDAR (Terrestrial Laser Scanning - TLS) is an operational used and widely available measurement tool supporting forest inventory updating and research in forest ecology. High resolution point clouds from TLS already represent single leaves which can be used for a more precise estimation of Leaf Area Index (LAI) and for higher accurate biomass estimation. However, currently the methodology for extracting single leafs from the unclassified point clouds for individual trees is still missing. The aim of this study is to present a novel segmentation approach in order to extract single leaves and derive features related to leaf morphology (such as area, slope, length and width) of each single leaf from TLS point cloud data. For the study two exemplary single trees were scanned in leaf-on condition on the university campus of Innsbruck during calm wind conditions. A northern red oak (Quercus rubra) was scanned by a discrete return recording Optech ILRIS-3D TLS scanner and a tulip tree (Liliodendron tulpifera) with Riegl VZ-6000 scanner. During the scanning campaign a reference dataset was measured parallel to scanning. In this case 230 leaves were randomly collected around the lower branches of the tree and photos were taken. The developed workflow steps were the following: in the first step normal vectors and eigenvalues were calculated based on the user specified neighborhood. Then using the direction of the largest eigenvalue outliers i.e. ghost points were removed. After that region growing segmentation based on the curvature and angles between normal vectors was applied on the filtered point cloud. On each segment a RANSAC plane fitting algorithm was applied in order to extract the segment based normal vectors. Using the related features of the calculated segments the stem and branches were labeled as non-leaf and other segments were classified as leaf. The validation of the different segmentation

  4. The effect of the time and the budding method on the growth of young cherry trees cv. 'Łutówka'

    Directory of Open Access Journals (Sweden)

    Piotr Baryła


    Full Text Available The studies concerning the effect of the time and the methods of budding on the growth of young cherry trees were conducted in the years at Felin Experimental Farm of Lublin Agricultural University. The objects of investigations were the young cherry trees obtained as a result of budding of mahaleb cherry (Prunus mahaleb L. and sweet cherry (Prunus avium L. seedlings in the way by the chip budding-15th July and T-graft-15th July and 1st September. The used methods and the times of budding insignificantly affected the growth of young cherry trees cv. «Łutówka» in a nursery. There was showed that quality features of the trees were dependet on stock used type. Cherry trees obtained on mahaleb cherry were thicker, higher and better branched than on sweet cherry.

  5. Effects of Electrode Material on the Voltage of a Tree-Based Energy Generator.

    Directory of Open Access Journals (Sweden)

    Zhibin Hao

    Full Text Available The voltage between a standing tree and its surrounding soil is regarded as an innovative renewable energy source. This source is expected to provide a new power generation system for the low-power electrical equipment used in forestry. However, the voltage is weak, which has caused great difficulty in application. Consequently, the development of a method to increase the voltage is a key issue that must be addressed in this area of applied research. As the front-end component for energy harvesting, a metal electrode has a material effect on the level and stability of the voltage obtained. This study aimed to preliminarily ascertain the rules and mechanisms that underlie the effects of electrode material on voltage. Electrodes of different materials were used to measure the tree-source voltage, and the data were employed in a comparative analysis. The results indicate that the conductivity of the metal electrode significantly affects the contact resistance of the electrode-soil and electrode-trunk contact surfaces, thereby influencing the voltage level. The metal reactivity of the electrode has no significant effect on the voltage. However, passivation of the electrode materials markedly reduces the voltage. Suitable electrode materials are demonstrated and recommended.

  6. A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks. (United States)

    Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il


    Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new ( m , k )-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the ( m , k )-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured ( m , k )-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.

  7. Flowering Trees

    Indian Academy of Sciences (India)

    narrow towards base. Flowers are large and attrac- tive, but emit unpleasant foetid smell. They appear in small numbers on erect terminal clusters and open at night. Stamens are numerous, pink or white. Style is slender and long, terminating in a small stigma. Fruit is green, ovoid and indistinctly lobed. Flowering Trees.

  8. Flowering Trees

    Indian Academy of Sciences (India)


    . (6-10m high) evergreen tree with a straight trunk and broad open crown. Leaves are clustered at the end of twigs. They are dark green, broadest near the rounded apex and tapering towards the base with a short stalk. Flowers are greenish or ...

  9. Efficient parsimony-based methods for phylogenetic network reconstruction. (United States)

    Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir


    Phylogenies--the evolutionary histories of groups of organisms-play a major role in representing relationships among biological entities. Although many biological processes can be effectively modeled as tree-like relationships, others, such as hybrid speciation and horizontal gene transfer (HGT), result in networks, rather than trees, of relationships. Hybrid speciation is a significant evolutionary mechanism in plants, fish and other groups of species. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Maximum parsimony is one of the most commonly used criteria for phylogenetic tree inference. Roughly speaking, inference based on this criterion seeks the tree that minimizes the amount of evolution. In 1990, Jotun Hein proposed using this criterion for inferring the evolution of sequences subject to recombination. Preliminary results on small synthetic datasets. Nakhleh et al. (2005) demonstrated the criterion's application to phylogenetic network reconstruction in general and HGT detection in particular. However, the naive algorithms used by the authors are inapplicable to large datasets due to their demanding computational requirements. Further, no rigorous theoretical analysis of computing the criterion was given, nor was it tested on biological data. In the present work we prove that the problem of scoring the parsimony of a phylogenetic network is NP-hard and provide an improved fixed parameter tractable algorithm for it. Further, we devise efficient heuristics for parsimony-based reconstruction of phylogenetic networks. We test our methods on both synthetic and biological data (rbcL gene in bacteria) and obtain very promising results.

  10. Automated detection of microcalcification clusters in digital mammograms based on wavelet domain hidden Markov tree modeling

    International Nuclear Information System (INIS)

    Regentova, E.; Zhang, L.; Veni, G.; Zheng, J.


    A system is designed for detecting microcalcification clusters (MCC) in digital mammograms. The system is intended for computer-aided diagnostic prompting. Further discrimination of MCC as benign or malignant is assumed to be performed by radiologists. Processing of mammograms is based on the statistical modeling by means of wavelet domain hidden markov trees (WHMT). Segmentation is performed by the weighted likelihood evaluation followed by the classification based on spatial filters for a single microcalcification (MC) and a cluster of MC detection. The analysis is carried out on FROC curves for 40 mammograms from the mini-MIAS database and for 100 mammograms with 50 cancerous and 50 benign cases from DDSM database. The designed system is capable to detect 100% of true positive cases in these sets. The rate of false positives is 2.9 per case for mini-MIAS dataset; and 0.01 for the DDSM images. (orig.)

  11. New, national bottom-up estimate for tree-based biological ... (United States)

    Nitrogen is a limiting nutrient in many ecosystems, but is also a chief pollutant from human activity. Quantifying human impacts on the nitrogen cycle and investigating natural ecosystem nitrogen cycling both require an understanding of the magnitude of nitrogen inputs from biological nitrogen fixation (BNF). A bottom-up approach to estimating BNF—scaling rates up from measurements to broader scales—is attractive because it is rooted in actual BNF measurements. However, bottom-up approaches have been hindered by scaling difficulties, and a recent top-down approach suggested that the previous bottom-up estimate was much too large. Here, we used a bottom-up approach for tree-based BNF, overcoming scaling difficulties with the systematic, immense (>70,000 N-fixing trees) Forest Inventory and Analysis (FIA) database. We employed two approaches to estimate species-specific BNF rates: published ecosystem-scale rates (kg N ha-1 yr-1) and published estimates of the percent of N derived from the atmosphere (%Ndfa) combined with FIA-derived growth rates. Species-specific rates can vary for a variety of reasons, so for each approach we examined how different assumptions influenced our results. Specifically, we allowed BNF rates to vary with stand age, N-fixer density, and canopy position (since N-fixation is known to require substantial light).Our estimates from this bottom-up technique are several orders of magnitude lower than previous estimates indicating

  12. A web-based decision support system to enhance IPM programs in Washington tree fruit. (United States)

    Jones, Vincent P; Brunner, Jay F; Grove, Gary G; Petit, Brad; Tangren, Gerald V; Jones, Wendy E


    Integrated pest management (IPM) decision-making has become more information intensive in Washington State tree crops in response to changes in pesticide availability, the development of new control tactics (such as mating disruption) and the development of new information on pest and natural enemy biology. The time-sensitive nature of the information means that growers must have constant access to a single source of verified information to guide management decisions. The authors developed a decision support system for Washington tree fruit growers that integrates environmental data [140 Washington State University (WSU) stations plus weather forecasts from NOAA], model predictions (ten insects, four diseases and a horticultural model), management recommendations triggered by model status and a pesticide database that provides information on non-target impacts on other pests and natural enemies. A user survey in 2008 found that the user base was providing recommendations for most of the orchards and acreage in the state, and that users estimated the value at $ 16 million per year. The design of the system facilitates education on a range of time-sensitive topics and will make it possible easily to incorporate other models, new management recommendations or information from new sensors as they are developed.

  13. Methods and equations for estimating aboveground volume, biomass, and carbon for trees in the U.S. forest inventory, 2010 (United States)

    Christopher W. Woodall; Linda S. Heath; Grant M. Domke; Michael C. Nichols


    The U.S. Forest Service, Forest Inventory and Analysis (FIA) program uses numerous models and associated coefficients to estimate aboveground volume, biomass, and carbon for live and standing dead trees for most tree species in forests of the United States. The tree attribute models are coupled with FIA's national inventory of sampled trees to produce estimates of...

  14. Development of hybrid genetic-algorithm-based neural networks using regression trees for modeling air quality inside a public transportation bus. (United States)

    Kadiyala, Akhil; Kaur, Devinder; Kumar, Ashok


    The present study developed a novel approach to modeling indoor air quality (IAQ) of a public transportation bus by the development of hybrid genetic-algorithm-based neural networks (also known as evolutionary neural networks) with input variables optimized from using the regression trees, referred as the GART approach. This study validated the applicability of the GART modeling approach in solving complex nonlinear systems by accurately predicting the monitored contaminants of carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), sulfur dioxide (SO2), 0.3-0.4 microm sized particle numbers, 0.4-0.5 microm sized particle numbers, particulate matter (PM) concentrations less than 1.0 microm (PM10), and PM concentrations less than 2.5 microm (PM2.5) inside a public transportation bus operating on 20% grade biodiesel in Toledo, OH. First, the important variables affecting each monitored in-bus contaminant were determined using regression trees. Second, the analysis of variance was used as a complimentary sensitivity analysis to the regression tree results to determine a subset of statistically significant variables affecting each monitored in-bus contaminant. Finally, the identified subsets of statistically significant variables were used as inputs to develop three artificial neural network (ANN) models. The models developed were regression tree-based back-propagation network (BPN-RT), regression tree-based radial basis function network (RBFN-RT), and GART models. Performance measures were used to validate the predictive capacity of the developed IAQ models. The results from this approach were compared with the results obtained from using a theoretical approach and a generalized practicable approach to modeling IAQ that included the consideration of additional independent variables when developing the aforementioned ANN models. The hybrid GART models were able to capture majority of the variance in the monitored in-bus contaminants. The genetic-algorithm-based

  15. Energy-efficient multicast traffic grooming strategy based on light-tree splitting for elastic optical networks (United States)

    Liu, Huanlin; Yin, Yarui; Chen, Yong


    In order to address the problem of optimizing the spectrum resources and power consumption in elastic optical networks (EONs), we investigate the potential gains by jointly employing the light-tree splitting and traffic grooming for multicast requests. An energy-efficient multicast traffic grooming strategy based on light-tree splitting (EED-MTGS-LS) is proposed in this paper. Firstly, we design a traffic pre-processing mechanism to decide the multicast requests' routing order, which considers the request's bandwidth requirement and physical hops synthetically. Then, by dividing a light-tree to some sub-light-trees and grooming the request to these sub-light-trees, the light-tree sharing ratios of multicast requests can be improved. What's more, a priority scheduling vector is constructed, which aims to improve the success rate of spectrum assignment for grooming requests. Finally, a grooming strategy is designed to optimize the total power consumption by reducing the use of transponders and IP routers during routing. Simulation results show that the proposed strategy can significantly improve the spectrum utilization and save the power consumption.

  16. Biological methods for assessment of budbreak in apple trees for modeling dormancy

    Directory of Open Access Journals (Sweden)

    Rafael Anzanello


    Full Text Available A biological method was developed to evaluate the dormancy state of apple buds under controlled conditions. Cuttings (20-25 cm long of ‘Castel Gala’ and ‘Royal Gala’ were sampled during the winter period, evaluating different cold and heat regimes to induce budbreak. Contrasts were tested in plant material processing (single node x intact cuttings, cold storage method to break dormancy in incubator chambers (planted in pots with floral foam x wrapped in plastic film, vertically or horizontally and budbreak method in plant growth chambers (base immersed in water x planted in floral foam. Intact cuttings stored vertically in the cold represented better the natural interactions between buds than single node cuttings. Budbreak of lateral buds was strongly influenced by apical dominance. Wrapping cuttings in plastic film optimized internal space usage in the incubators and the number of evaluated buds, compared to planting cuttings in pots. During the warm period in the growth chambers, intact cuttings on floral foam resulted in better bud preservation and survival throughout the evaluation period, compared to cuttings with bases immersed in water. The most suitable conditions to evaluate dormancy evolution in apple buds used plastic-wrapped intact cuttings stored vertically during the cold period, with budbreak evaluation in the warm period after planting the cuttings in floral foam. Standardization of methodology helps to obtain better results in the development of physiological models of dormancy.

  17. Evaluation of fast enantioselective multidimensional gas chromatography methods for monoterpenic compounds: Authenticity control of Australian tea tree oil. (United States)

    Wong, Yong Foo; West, Rachel N; Chin, Sung-Tong; Marriott, Philip J


    This work demonstrates the potential of fast multiple heart-cut enantioselective multidimensional gas chromatography (GC-eGC) and enantioselective comprehensive two-dimensional gas chromatography (eGC×GC), to perform the stereoisomeric analysis of three key chiral monoterpenes (limonene, terpinen-4-ol and α-terpineol) present in tea tree oil (TTO). In GC-eGC, separation was conducted using a combination of mid-polar first dimension ((1)D) column and a chiral second dimension ((2)D) column, providing interference-free enantioresolution of the individual antipodes of each optically active component. A combination of (1)D chiral column and (2)D polar columns (ionic liquid and wax phases) were tested for the eGC×GC study. Quantification was proposed based on summation of two major modulated peaks for each antipode, displaying comparable results with those derived from GC-eGC. Fast chiral separations were achieved within 25min for GC-eGC andauthentic TTOs was proposed by analysing a representative number of pure TTOs sourced directly from plantations of known provenance in Australia. Consistent enantiomeric fractions of 61.6±1.5% (+):38.4±1.5% (-) for limonene, 61.7±1.6% (+):38.3±1.6% (-) for terpinen-4-ol and 79.6±1.4% (+):20.4±1.4% (-) for α-terpineol were obtained for the 57 authentic Australian TTOs. The results were compared (using principle component analysis) with commercial TTOs (declared as derived from Melaleuca alternifolia) obtained from different continents. Assessing these data to determine adulteration, or additives that affect the enantiomeric ratios, in commercially sourced TTOs is discussed. The proposed method offers distinct advantages over eGC, especially in terms of analysis times and selectivity which can serve as a reliable platform for authenticity control of TTO. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. ETE: a python Environment for Tree Exploration. (United States)

    Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni


    Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from

  19. Combination of individual tree detection and area-based approach in imputation of forest variables using airborne laser data (United States)

    Vastaranta, Mikko; Kankare, Ville; Holopainen, Markus; Yu, Xiaowei; Hyyppä, Juha; Hyyppä, Hannu


    The two main approaches to deriving forest variables from laser-scanning data are the statistical area-based approach (ABA) and individual tree detection (ITD). With ITD it is feasible to acquire single tree information, as in field measurements. Here, ITD was used for measuring training data for the ABA. In addition to automatic ITD (ITD auto), we tested a combination of ITD auto and visual interpretation (ITD visual). ITD visual had two stages: in the first, ITD auto was carried out and in the second, the results of the ITD auto were visually corrected by interpreting three-dimensional laser point clouds. The field data comprised 509 circular plots ( r = 10 m) that were divided equally for testing and training. ITD-derived forest variables were used for training the ABA and the accuracies of the k-most similar neighbor ( k-MSN) imputations were evaluated and compared with the ABA trained with traditional measurements. The root-mean-squared error (RMSE) in the mean volume was 24.8%, 25.9%, and 27.2% with the ABA trained with field measurements, ITD auto, and ITD visual, respectively. When ITD methods were applied in acquiring training data, the mean volume, basal area, and basal area-weighted mean diameter were underestimated in the ABA by 2.7-9.2%. This project constituted a pilot study for using ITD measurements as training data for the ABA. Further studies are needed to reduce the bias and to determine the accuracy obtained in imputation of species-specific variables. The method could be applied in areas with sparse road networks or when the costs of fieldwork must be minimized.

  20. Undergraduate Students’ Difficulties in Reading and Constructing Phylogenetic Tree (United States)

    Sa'adah, S.; Tapilouw, F. S.; Hidayat, T.


    Representation is a very important communication tool to communicate scientific concepts. Biologists produce phylogenetic representation to express their understanding of evolutionary relationships. The phylogenetic tree is visual representation depict a hypothesis about the evolutionary relationship and widely used in the biological sciences. Phylogenetic tree currently growing for many disciplines in biology. Consequently, learning about phylogenetic tree become an important part of biological education and an interesting area for biology education research. However, research showed many students often struggle with interpreting the information that phylogenetic trees depict. The purpose of this study was to investigate undergraduate students’ difficulties in reading and constructing a phylogenetic tree. The method of this study is a descriptive method. In this study, we used questionnaires, interviews, multiple choice and open-ended questions, reflective journals and observations. The findings showed students experiencing difficulties, especially in constructing a phylogenetic tree. The students’ responds indicated that main reasons for difficulties in constructing a phylogenetic tree are difficult to placing taxa in a phylogenetic tree based on the data provided so that the phylogenetic tree constructed does not describe the actual evolutionary relationship (incorrect relatedness). Students also have difficulties in determining the sister group, character synapomorphy, autapomorphy from data provided (character table) and comparing among phylogenetic tree. According to them building the phylogenetic tree is more difficult than reading the phylogenetic tree. Finding this studies provide information to undergraduate instructor and students to overcome learning difficulties of reading and constructing phylogenetic tree.

  1. Extraction of Urban Trees from Integrated Airborne Based Digital Image and LIDAR Point Cloud Datasets - Initial Results (United States)

    Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.


    Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.

  2. Drivers of forests and tree-based systems for food security and nutrition

    DEFF Research Database (Denmark)

    Kleinschmit, Daniela; Sijapati Basnett, Bimbika; Martin, Adrian


    In the context of this chapter, drivers are considered to be natural or anthropogenic developments affecting forests and tree-based systems for food security and nutrition. They can improve and contribute to food security and nutrition, but they can also lead to food insecurity and malnutrition......, commercialisation of agriculture, industrialisation of forest resources, gender imbalances, conflicts, formalisation of tenure rights, rising food prices and increasing per capita income) were identified within these four categories. They affect food security and nutrition through land use and management; through...... consumption, income and livelihood; or through both. These drivers are interrelated and can have different consequences depending on the social structure; for example, they can support food security for elite groups but can increase the vulnerability of other groups....

  3. Novel Degree Constrained Minimum Spanning Tree Algorithm Based on an Improved Multicolony Ant Algorithm

    Directory of Open Access Journals (Sweden)

    Xuemei Sun


    Full Text Available Degree constrained minimum spanning tree (DCMST refers to constructing a spanning tree of minimum weight in a complete graph with weights on edges while the degree of each node in the spanning tree is no more than d (d ≥ 2. The paper proposes an improved multicolony ant algorithm for degree constrained minimum spanning tree searching which enables independent search for optimal solutions among various colonies and achieving information exchanges between different colonies by information entropy. Local optimal algorithm is introduced to improve constructed spanning tree. Meanwhile, algorithm strategies in dynamic ant, random perturbations ant colony, and max-min ant system are adapted in this paper to optimize the proposed algorithm. Finally, multiple groups of experimental data show the superiority of the improved algorithm in solving the problems of degree constrained minimum spanning tree.

  4. Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest (United States)

    Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.


    The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest

  5. Unequal Probability Marking Approach to Enhance Security of Traceback Scheme in Tree-Based WSNs. (United States)

    Huang, Changqin; Ma, Ming; Liu, Xiao; Liu, Anfeng; Zuo, Zhengbang


    Fog (from core to edge) computing is a newly emerging computing platform, which utilizes a large number of network devices at the edge of a network to provide ubiquitous computing, thus having great development potential. However, the issue of security poses an important challenge for fog computing. In particular, the Internet of Things (IoT) that constitutes the fog computing platform is crucial for preserving the security of a huge number of wireless sensors, which are vulnerable to attack. In this paper, a new unequal probability marking approach is proposed to enhance the security performance of logging and migration traceback (LM) schemes in tree-based wireless sensor networks (WSNs). The main contribution of this paper is to overcome the deficiency of the LM scheme that has a higher network lifetime and large storage space. In the unequal probability marking logging and migration (UPLM) scheme of this paper, different marking probabilities are adopted for different nodes according to their distances to the sink. A large marking probability is assigned to nodes in remote areas (areas at a long distance from the sink), while a small marking probability is applied to nodes in nearby area (areas at a short distance from the sink). This reduces the consumption of storage and energy in addition to enhancing the security performance, lifetime, and storage capacity. Marking information will be migrated to nodes at a longer distance from the sink for increasing the amount of stored marking information, thus enhancing the security performance in the process of migration. The experimental simulation shows that for general tree-based WSNs, the UPLM scheme proposed in this paper can store 1.12-1.28 times the amount of stored marking information that the equal probability marking approach achieves, and has 1.15-1.26 times the storage utilization efficiency compared with other schemes.

  6. Recent progress in paleontological methods for dating the Tree of Life

    Directory of Open Access Journals (Sweden)

    Michel eLaurin


    Full Text Available Dating the Tree of Life (abbreviated TOL below has become a major goal of biological research. Beyond the intrinsic interest of reconstructing the history of taxonomic diversification, time-calibrated trees (timetrees for short, as used throughout below are required in many types of comparative analyses, where branch lengths are used to assess the conservation importance of lineages, correlation between characters, or to assess phylogenetic niche conservatism, among other uses. Improvements in dating the TOL would thus benefit large segments of the biological community, ranging from conservation biology and ecology through functional biology and paleontology. Recently, progress has been made on several fronts: in compiling databases and supertrees incorporating paleontological data, in computing confidence intervals on the true stratigraphic range of taxa, and in using birth and death processes to assess the probability distribution of the time of origin of specified taxa. Combined paleontological and molecular dating has also progressed through the insertion of extinct taxa into data matrices, which allows incorporation of their phylogenetic uncertainty into the dating analysis.

  7. Data Fusion Research of Triaxial Human Body Motion Gesture based on Decision Tree

    Directory of Open Access Journals (Sweden)

    Feihong Zhou


    Full Text Available The development status of human body motion gesture data fusion domestic and overseas has been analyzed. A triaxial accelerometer is adopted to develop a wearable human body motion gesture monitoring system aimed at old people healthcare. On the basis of a brief introduction of decision tree algorithm, the WEKA workbench is adopted to generate a human body motion gesture decision tree. At last, the classification quality of the decision tree has been validated through experiments. The experimental results show that the decision tree algorithm could reach an average predicting accuracy of 97.5 % with lower time cost.

  8. Decision tree modeling using R. (United States)

    Zhang, Zhongheng


    In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.

  9. Energy spectra unfolding of fast neutron sources using the group method of data handling and decision tree algorithms

    International Nuclear Information System (INIS)

    Hosseini, Seyed Abolfazl; Afrakoti, Iman Esmaili Paeen


    Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). The developed computational codes based on the GMDH and DT algorithms use some data for training, testing and validation steps. In order to prepare the required data, 4000 randomly generated energy spectra distributed over 52 bins are used. The randomly generated energy spectra and the simulated neutron pulse height distributions by MCNPX-ESUT for each energy spectrum are used as the output and input data. Since there is no need to solve the inverse problem with an ill-conditioned response matrix, the unfolded energy spectrum has the highest accuracy. The 241 Am- 9 Be and 252 Cf neutron sources are used in the validation step of the calculation. The unfolded energy spectra for the used fast neutron sources have an excellent agreement with the reference ones. Also, the accuracy of the unfolded energy spectra obtained using the GMDH is slightly better than those obtained from the DT. The results obtained in the present study have good accuracy in comparison with the previously published paper based on the logsig and tansig transfer functions. - Highlights: • The neutron pulse height distribution was simulated using MCNPX-ESUT. • The energy spectrum of the neutron source was unfolded using GMDH. • The energy spectrum of the neutron source was unfolded using

  10. Energy spectra unfolding of fast neutron sources using the group method of data handling and decision tree algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Hosseini, Seyed Abolfazl, E-mail: [Department of Energy Engineering, Sharif University of Technology, Tehran 8639-11365 (Iran, Islamic Republic of); Afrakoti, Iman Esmaili Paeen [Faculty of Engineering & Technology, University of Mazandaran, Pasdaran Street, P.O. Box: 416, Babolsar 47415 (Iran, Islamic Republic of)


    Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). The developed computational codes based on the GMDH and DT algorithms use some data for training, testing and validation steps. In order to prepare the required data, 4000 randomly generated energy spectra distributed over 52 bins are used. The randomly generated energy spectra and the simulated neutron pulse height distributions by MCNPX-ESUT for each energy spectrum are used as the output and input data. Since there is no need to solve the inverse problem with an ill-conditioned response matrix, the unfolded energy spectrum has the highest accuracy. The {sup 241}Am-{sup 9}Be and {sup 252}Cf neutron sources are used in the validation step of the calculation. The unfolded energy spectra for the used fast neutron sources have an excellent agreement with the reference ones. Also, the accuracy of the unfolded energy spectra obtained using the GMDH is slightly better than those obtained from the DT. The results obtained in the present study have good accuracy in comparison with the previously published paper based on the logsig and tansig transfer functions. - Highlights: • The neutron pulse height distribution was simulated using MCNPX-ESUT. • The energy spectrum of the neutron source was unfolded using GMDH. • The energy spectrum of the neutron source was

  11. [Prediction of the total Japanese cedar pollen counts based on male flower-setting conditions of standard trees]. (United States)

    Yuta, Atsushi; Ukai, Kotaro; Sakakura, Yasuo; Tani, Hideshi; Matsuda, Fukiko; Yang, Tian-qun; Majima, Yuichi


    We made a prediction of the Japanese cedar (Cryptomeria japonica) pollen counts at Tsu city based on male flower-setting conditions of standard trees. The 69 standard trees from 23 kinds of clones, planted at Mie Prefecture Science and Technology Promotion Center (Hakusan, Mie) in 1964, were selected. Male flower-setting conditions for 276 faces (69 trees x 4 points of the compass) were scored from 0 to 3. The average of scores and total pollen counts from 1988 to 2000 was analyzed. As the results, the average scores from standard trees and total pollen counts except two mass pollen-scattered years in 1995 and 2000 had a positive correlation (r = 0.914) by linear function. On the mass pollen-scattered years, pollen counts were influenced from the previous year. Therefore, the score of the present year minus that of the previous year were used for analysis. The average scores from male flower-setting conditions and pollen counts had a strong positive correlation (r = 0.994) when positive scores by taking account of the previous year were analyzed. We conclude that prediction of pollen counts are possible based on the male flower-setting conditions of standard trees.

  12. GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran. (United States)

    Naghibi, Seyed Amir; Pourghasemi, Hamid Reza; Dixon, Barnali


    Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learning models: boosted regression tree (BRT), classification and regression tree (CART), and random forest (RF). Thirteen hydrological-geological-physiographical (HGP) factors that influence locations of springs were considered in this research. These factors include slope degree, slope aspect, altitude, topographic wetness index (TWI), slope length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, lithology, land use, drainage density, and fault density. Subsequently, groundwater spring potential was modeled and mapped using CART, RF, and BRT algorithms. The predicted results from the three models were validated using the receiver operating characteristics curve (ROC). From 864 springs identified, 605 (≈70 %) locations were used for the spring potential mapping, while the remaining 259 (≈30 %) springs were used for the model validation. The area under the curve (AUC) for the BRT model was calculated as 0.8103 and for CART and RF the AUC were 0.7870 and 0.7119, respectively. Therefore, it was concluded that the BRT model produced the best prediction results while predicting locations of springs followed by CART and RF models, respectively. Geospatially integrated BRT, CART, and RF methods proved to be useful in generating the spring potential map (SPM) with reasonable accuracy.

  13. Detecting surface coal mining areas from remote sensing imagery: an approach based on object-oriented decision trees (United States)

    Zeng, Xiaoji; Liu, Zhifeng; He, Chunyang; Ma, Qun; Wu, Jianguo


    Detecting surface coal mining areas (SCMAs) using remote sensing data in a timely and an accurate manner is necessary for coal industry management and environmental assessment. We developed an approach to effectively extract SCMAs from remote sensing imagery based on object-oriented decision trees (OODT). This OODT approach involves three main steps: object-oriented segmentation, calculation of spectral characteristics, and extraction of SCMAs. The advantage of this approach lies in its effective integration of the spectral and spatial characteristics of SCMAs so as to distinguish the mining areas (i.e., the extracting areas, stripped areas, and dumping areas) from other areas that exhibit similar spectral features (e.g., bare soils and built-up areas). We implemented this method to extract SCMAs in the eastern part of Ordos City in Inner Mongolia, China. Our results had an overall accuracy of 97.07% and a kappa coefficient of 0.80. As compared with three other spectral information-based methods, our OODT approach is more accurate in quantifying the amount and spatial pattern of SCMAs in dryland regions.

  14. Integrated system fault diagnostics utilising digraph and fault tree-based approaches

    International Nuclear Information System (INIS)

    Bartlett, L.M.; Hurdle, E.E.; Kelly, E.M.


    With the growing intolerance to failures within systems, the issue of fault diagnosis has become ever prevalent. Information concerning these possible failures can help to minimise the disruption to the functionality of the system by allowing quick rectification. Traditional approaches to fault diagnosis within engineering systems have focused on sequential testing procedures and real-time mechanisms. Both methods have been predominantly limited to single fault causes. Latest approaches also consider the issue of multiple faults in reflection to the characteristics of modern day systems designed for high reliability. In addition, a diagnostic capability is required in real time and for changeable system functionality. This paper focuses on two approaches which have been developed to cater for the demands of diagnosis within current engineering systems, namely application of the fault tree analysis technique and the method of digraphs. Both use a comparative approach to consider differences between actual system behaviour and that expected. The procedural guidelines are discussed for each method, with an experimental aircraft fuel system used to test and demonstrate the features of the techniques. The effectiveness of the approaches is compared and their future potential highlighted

  15. Tree Contractions and Evolutionary Trees


    Kao, Ming-Yang


    An evolutionary tree is a rooted tree where each internal vertex has at least two children and where the leaves are labeled with distinct symbols representing species. Evolutionary trees are useful for modeling the evolutionary history of species. An agreement subtree of two evolutionary trees is an evolutionary tree which is also a topological subtree of the two given trees. We give an algorithm to determine the largest possible number of leaves in any agreement subtree of two trees T_1 and ...

  16. Bayesian updating of reliability of civil infrastructure facilities based on condition-state data and fault-tree model

    International Nuclear Information System (INIS)

    Ching Jianye; Leu, S.-S.


    This paper considers a difficult but practical circumstance of civil infrastructure management-deterioration/failure data of the infrastructure system are absent while only condition-state data of its components are available. The goal is to develop a framework for estimating time-varying reliabilities of civil infrastructure facilities under such a circumstance. A novel method of analyzing time-varying condition-state data that only reports operational/non-operational status of the components is proposed to update the reliabilities of civil infrastructure facilities. The proposed method assumes that the degradation arrivals can be modeled as a Poisson process with unknown time-varying arrival rate and damage impact and that the target system can be represented as a fault-tree model. To accommodate large uncertainties, a Bayesian algorithm is proposed, and the reliability of the infrastructure system can be quickly updated based on the condition-state data. Use of the new method is demonstrated with a real-world example of hydraulic spillway gate system.

  17. Investigating the limitations of tree species classification using the Combined Cluster and Discriminant Analysis method for low density ALS data from a dense forest region in Aggtelek (Hungary) (United States)

    Koma, Zsófia; Deák, Márton; Kovács, József; Székely, Balázs; Kelemen, Kristóf; Standovár, Tibor


    Airborne Laser Scanning (ALS) is a widely used technology for forestry classification applications. However, single tree detection and species classification from low density ALS point cloud is limited in a dense forest region. In this study we investigate the division of a forest into homogenous groups at stand level. The study area is located in the Aggtelek karst region (Northeast Hungary) with a complex relief topography. The ALS dataset contained only 4 discrete echoes (at 2-4 pt/m2 density) from the study area during leaf-on season. Ground-truth measurements about canopy closure and proportion of tree species cover are available for every 70 meter in 500 square meter circular plots. In the first step, ALS data were processed and geometrical and intensity based features were calculated into a 5×5 meter raster based grid. The derived features contained: basic statistics of relative height, canopy RMS, echo ratio, openness, pulse penetration ratio, basic statistics of radiometric feature. In the second step the data were investigated using Combined Cluster and Discriminant Analysis (CCDA, Kovács et al., 2014). The CCDA method first determines a basic grouping for the multiple circle shaped sampling locations using hierarchical clustering and then for the arising grouping possibilities a core cycle is executed comparing the goodness of the investigated groupings with random ones. Out of these comparisons difference values arise, yielding information about the optimal grouping out of the investigated ones. If sub-groups are then further investigated, one might even find homogeneous groups. We found that low density ALS data classification into homogeneous groups are highly dependent on canopy closure, and the proportion of the dominant tree species. The presented results show high potential using CCDA for determination of homogenous separable groups in LiDAR based tree species classification. Aggtelek Karst/Slovakian Karst Caves" (HUSK/1101/221/0180, Aggtelek NP

  18. Comparing alternative tree canopy cover estimates derived from digital aerial photography and field-based assessments (United States)

    Tracey S. Frescino; Gretchen G. Moisen


    A spatially-explicit representation of live tree canopy cover, such as the National Land Cover Dataset (NLCD) percent tree canopy cover layer, is a valuable tool for many applications, such as defining forest land, delineating wildlife habitat, estimating carbon, and modeling fire risk and behavior. These layers are generated by predictive models wherein their accuracy...

  19. Relating FIA data to habitat classifications via tree-based models of canopy cover (United States)

    Mark D. Nelson; Brian G. Tavernia; Chris Toney; Brian F. Walters


    Wildlife species-habitat matrices are used to relate lists of species with abundance of their habitats. The Forest Inventory and Analysis Program provides data on forest composition and structure, but these attributes may not correspond directly with definitions of wildlife habitats. We used FIA tree data and tree crown diameter models to estimate canopy cover, from...

  20. Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis. (United States)

    Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji


    The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

  1. Support-vector-machine tree-based domain knowledge learning toward automated sports video classification (United States)

    Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin


    We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

  2. Methodical bases of geodemographic forecasting

    Directory of Open Access Journals (Sweden)

    Катерина Сегіда


    Full Text Available The article deals with methodological features of the forecast of population size and composition. The essence and features of probabilistic demographic forecasting, methods, a component and dynamic ranks are considered; requirements to initial indicators for each type of the forecast are provided. It is noted that geo-demographic forecast is an important component of regional geo-demographic characteristic. Features of the demographic forecast development by component method (recursors of age are given, basic formulae of calculation, including the equation of demographic balance, a formula recursors taking into account gender and age indicators, survival coefficient are presented. The basic methodical principles of the demographic forecast are given by an extrapolation method (dynamic ranks, calculation features by means of the generalized indicators, such as extrapolation on the basis of indicators of an average pure gain, average growth rate and average rate of a gain are presented. To develop population forecast, the method of retrospective extrapolation (for the short-term forecast and a component method (for the mid-term forecast are mostly used. The example of such development by component method for gender and age structure of the population of Kharkiv region with step-by-step explanation of calculation is provided. The example of Kharkiv region’s population forecast development is provided by the method of dynamic ranks. Having carried out calculations of the main forecast indicators by administrative units, it is possible to determine features of further regional demographic development, to reveal internal territorial distinctions in demographic development. Application of separate forecasting methods allows to develop the forecast for certain indicators, however essential a variety, nonlinearity and not stationarity of the processes constituting demographic development forces to look +for new approaches and

  3. BpWrapper: BioPerl-based sequence and tree utilities for rapid prototyping of bioinformatics pipelines. (United States)

    Hernández, Yözen; Bernstein, Rocky; Pagan, Pedro; Vargas, Levy; McCaig, William; Ramrattan, Girish; Akther, Saymon; Larracuente, Amanda; Di, Lia; Vieira, Filipe G; Qiu, Wei-Gang


    Automated bioinformatics workflows are more robust, easier to maintain, and results more reproducible when built with command-line utilities than with custom-coded scripts. Command-line utilities further benefit by relieving bioinformatics developers to learn the use of, or to interact directly with, biological software libraries. There is however a lack of command-line utilities that leverage popular Open Source biological software toolkits such as BioPerl ( ) to make many of the well-designed, robust, and routinely used biological classes available for a wider base of end users. Designed as standard utilities for UNIX-family operating systems, BpWrapper makes functionality of some of the most popular BioPerl modules readily accessible on the command line to novice as well as to experienced bioinformatics practitioners. The initial release of BpWrapper includes four utilities with concise command-line user interfaces, bioseq, bioaln, biotree, and biopop, specialized for manipulation of molecular sequences, sequence alignments, phylogenetic trees, and DNA polymorphisms, respectively. Over a hundred methods are currently available as command-line options and new methods are easily incorporated. Performance of BpWrapper utilities lags that of precompiled utilities while equivalent to that of other utilities based on BioPerl. BpWrapper has been tested on BioPerl Release 1.6, Perl versions 5.10.1 to 5.25.10, and operating systems including Apple macOS, Microsoft Windows, and GNU/Linux. Release code is available from the Comprehensive Perl Archive Network (CPAN) at . Source code is available on GitHub at . BpWrapper improves on existing sequence utilities by following the design principles of Unix text utilities such including a concise user interface, extensive command-line options, and standard input/output for serialized operations. Further, dozens of novel methods for

  4. A decision-tree-based model for evaluating the thermal comfort of horses

    Directory of Open Access Journals (Sweden)

    Ana Paula de Assis Maia


    Full Text Available Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S. This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. T S was obtained using infrared thermography image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The variables of armpit, croup, breast and groin T S of horses and the predicted classes were then subjected to a machine learning process. All variables in the dataset were considered relevant for the classification problem and the decision-tree model yielded an accuracy rate of 74 %. The feature selection methods used to reduce computational cost and simplify predictive learning decreased model accuracy to 70 %; however, the model became simpler with easily interpretable rules. For both these selection methods and for the classification using all attributes, armpit and breast T S had a higher power rating for predicting thermal comfort. Data mining techniques show promise in the discovery of new variables associated with the thermal comfort of horses.

  5. Evaluating methods to detect bark beetle-caused tree mortality using single-date and multi-date Landsat imagery (United States)

    Arjan J. H. Meddens; Jeffrey A. Hicke; Lee A. Vierling; Andrew T. Hudak


    Bark beetles cause significant tree mortality in coniferous forests across North America. Mapping beetle-caused tree mortality is therefore important for gauging impacts to forest ecosystems and assessing trends. Remote sensing offers the potential for accurate, repeatable estimates of tree mortality in outbreak areas. With the advancement of multi-temporal disturbance...

  6. Assessment of imputation methods using varying ecological information to fill the gaps in a tree functional trait database (United States)

    Poyatos, Rafael; Sus, Oliver; Vilà-Cabrera, Albert; Vayreda, Jordi; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi


    Plant functional traits are increasingly being used in ecosystem ecology thanks to the growing availability of large ecological databases. However, these databases usually contain a large fraction of missing data because measuring plant functional traits systematically is labour-intensive and because most databases are compilations of datasets with different sampling designs. As a result, within a given database, there is an inevitable variability in the number of traits available for each data entry and/or the species coverage in a given geographical area. The presence of missing data may severely bias trait-based analyses, such as the quantification of trait covariation or trait-environment relationships and may hamper efforts towards trait-based modelling of ecosystem biogeochemical cycles. Several data imputation (i.e. gap-filling) methods have been recently tested on compiled functional trait databases, but the performance of imputation methods applied to a functional trait database with a regular spatial sampling has not been thoroughly studied. Here, we assess the effects of data imputation on five tree functional traits (leaf biomass to sapwood area ratio, foliar nitrogen, maximum height, specific leaf area and wood density) in the Ecological and Forest Inventory of Catalonia, an extensive spatial database (covering 31900 km2). We tested the performance of species mean imputation, single imputation by the k-nearest neighbors algorithm (kNN) and a multiple imputation method, Multivariate Imputation with Chained Equations (MICE) at different levels of missing data (10%, 30%, 50%, and 80%). We also assessed the changes in imputation performance when additional predictors (species identity, climate, forest structure, spatial structure) were added in kNN and MICE imputations. We evaluated the imputed datasets using a battery of indexes describing departure from the complete dataset in trait distribution, in the mean prediction error, in the correlation matrix

  7. Generalising tree traversals and tree transformations to DAGs

    DEFF Research Database (Denmark)

    Bahr, Patrick; Axelsson, Emil


    We present a recursion scheme based on attribute grammars that can be transparently applied to trees and acyclic graphs. Our recursion scheme allows the programmer to implement a tree traversal or a tree transformation and then apply it to compact graph representations of trees instead...

  8. Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets. (United States)

    Sankari, E Siva; Manimegalai, D


    Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Modelling individual tree height to crown base of Norway spruce (Picea abies (L. Karst. and European beech (Fagus sylvatica L..

    Directory of Open Access Journals (Sweden)

    Ram P Sharma

    Full Text Available Height to crown base (HCB of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L. Karst. and European beech (Fagus sylvatica L. on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM, basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure or Hegyi's competition index (HCI-spatially explicit measure, and basal area proportion of a species of interest (BAPOR, respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset. The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce, 0.85 (beech] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce, 0.83 (beech]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed

  10. Three-dimensional design methodologies for tree-based FPGA architecture

    CERN Document Server

    Pangracious, Vinod; Mehrez, Habib


    This book focuses on the development of 3D design and implementation methodologies for Tree-based FPGA architecture. It also stresses the needs for new and augmented 3D CAD tools to support designs such as, the design for 3D, to manufacture high performance 3D integrated circuits and reconfigurable FPGA-based systems. This book was written as a text that covers the foundations of 3D integrated system design and FPGA architecture design. It was written for the use in an elective or core course at the graduate level in field of Electrical Engineering, Computer Engineering and Doctoral Research programs. No previous background on 3D integration is required, nevertheless fundamental understanding of 2D CMOS VLSI design is required. It is assumed that reader has taken the core curriculum in Electrical Engineering or Computer Engineering, with courses like CMOS VLSI design, Digital System Design and Microelectronics Circuits being the most important. It is accessible for self-study by both senior students and profe...

  11. Analyzing dynamic fault trees derived from model-based system architectures

    International Nuclear Information System (INIS)

    Dehlinger, Josh; Dugan, Joanne Bechta


    Dependability-critical systems, such as digital instrumentation and control systems in nuclear power plants, necessitate engineering techniques and tools to provide assurances of their safety and reliability. Determining system reliability at the architectural design phase is important since it may guide design decisions and provide crucial information for trade-off analysis and estimating system cost. Despite this, reliability and system engineering remain separate disciplines and engineering processes by which the dependability analysis results may not represent the designed system. In this article we provide an overview and application of our approach to build architecture-based, dynamic system models for dependability-critical systems and then automatically generate Dynamic Fault Trees (DFT) for comprehensive, toolsupported reliability analysis. Specifically, we use the Architectural Analysis and Design Language (AADL) to model the structural, behavioral and failure aspects of the system in a composite architecture model. From the AADL model, we seek to derive the DFT(s) and use Galileo's automated reliability analyses to estimate system reliability. This approach alleviates the dependability engineering - systems engineering knowledge expertise gap, integrates the dependability and system engineering design and development processes and enables a more formal, automated and consistent DFT construction. We illustrate this work using an example based on a dynamic digital feed-water control system for a nuclear reactor

  12. A classification method based on principal components of SELDI spectra to diagnose of lung adenocarcinoma.

    Directory of Open Access Journals (Sweden)

    Qiang Lin

    Full Text Available Lung cancer is the leading cause of cancer death worldwide, but techniques for effective early diagnosis are still lacking. Proteomics technology has been applied extensively to the study of the proteins involved in carcinogenesis. In this paper, a classification method was developed based on principal components of surface-enhanced laser desorption/ionization (SELDI spectral data. This method was applied to SELDI spectral data from 71 lung adenocarcinoma patients and 24 healthy individuals. Unlike other peak-selection-based methods, this method takes each spectrum as a unity. The aim of this paper was to demonstrate that this unity-based classification method is more robust and powerful as a method of diagnosis than peak-selection-based methods.The results showed that this classification method, which is based on principal components, has outstanding performance with respect to distinguishing lung adenocarcinoma patients from normal individuals. Through leaving-one-out, 19-fold, 5-fold and 2-fold cross-validation studies, we found that this classification method based on principal components completely outperforms peak-selection-based methods, such as decision tree, classification and regression tree, support vector machine, and linear discriminant analysis.The classification method based on principal components of SELDI spectral data is a robust and powerful means of diagnosing lung adenocarcinoma. We assert that the high efficiency of this classification method renders it feasible for large-scale clinical use.

  13. The risk of disabling, surgery and reoperation in Crohn’s disease – A decision tree-based approach to prognosis (United States)

    Dias, Cláudia Camila; Pereira Rodrigues, Pedro; Fernandes, Samuel; Portela, Francisco; Ministro, Paula; Martins, Diana; Sousa, Paula; Lago, Paula; Rosa, Isadora; Correia, Luis; Moura Santos, Paula


    Introduction Crohn’s disease (CD) is a chronic inflammatory bowel disease known to carry a high risk of disabling and many times requiring surgical interventions. This article describes a decision-tree based approach that defines the CD patients’ risk or undergoing disabling events, surgical interventions and reoperations, based on clinical and demographic variables. Materials and methods This multicentric study involved 1547 CD patients retrospectively enrolled and divided into two cohorts: a derivation one (80%) and a validation one (20%). Decision trees were built upon applying the CHAIRT algorithm for the selection of variables. Results Three-level decision trees were built for the risk of disabling and reoperation, whereas the risk of surgery was described in a two-level one. A receiver operating characteristic (ROC) analysis was performed, and the area under the curves (AUC) Was higher than 70% for all outcomes. The defined risk cut-off values show usefulness for the assessed outcomes: risk levels above 75% for disabling had an odds test positivity of 4.06 [3.50–4.71], whereas risk levels below 34% and 19% excluded surgery and reoperation with an odds test negativity of 0.15 [0.09–0.25] and 0.50 [0.24–1.01], respectively. Overall, patients with B2 or B3 phenotype had a higher proportion of disabling disease and surgery, while patients with later introduction of pharmacological therapeutic (1 months after initial surgery) had a higher proportion of reoperation. Conclusions The decision-tree based approach used in this study, with demographic and clinical variables, has shown to be a valid and useful approach to depict such risks of disabling, surgery and reoperation. PMID:28225800

  14. Magnesium nutrition of apple trees. III. Comparison of different methods of magnesium fertilization

    Directory of Open Access Journals (Sweden)

    A. Sadowski


    Full Text Available In the period 1969-1973 two experiments were performed in young orchards in Central Poland: a four-year experiment at Julianów, on sandy loamy soil on underlying sand and one-year experiment at Kośmin, on sandy loam soil on clay loam. At Kosmin, in spite of a high Mg content in the subsoil, Mg deficiency symptoms appeared, because of shallow rooting owing to poor aeration. In both experiments, foliar sprays with epsomite were less effective than fertilization to the soil; at Kośmin even eight sprays were less effective than soil dressings. Mg losses from a sandy soil due to leaching were high, particularly where sand was present in the whole profile; under these conditions the least losses of Mg were from split doses of epsomite (Mg3x120. Single doses of epsomite were the most effective in increasing leaf Mg content, reducing Mg deficiency symptoms and promoting growth of trees in the first year after application; in the later years split doses of epsomite and a single initial dose of magnesium lime were more effective. Effects of Mg fertilization on growth and yields of apples were rather slight, when K fe