Meta-learning in decision tree induction
Grąbczewski, Krzysztof
2014-01-01
The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimen...
Induction of Ordinal Decision Trees
J.C. Bioch (Cor); V. Popova (Viara)
2003-01-01
textabstractThis paper focuses on the problem of monotone decision trees from the point of view of the multicriteria decision aid methodology (MCDA). By taking into account the preferences of the decision maker, an attempt is made to bring closer similar research within machine learning and MCDA.
INDUCTION OF DECISION TREES BASED ON A FUZZY NEURAL NETWORK
Institute of Scientific and Technical Information of China (English)
Tang Bin; Hu Guangrui; Mao Xiaoquan
2002-01-01
Based on a fuzzy neural network, the letter presents an approach for the induction of decision trees. The approach makes use of the weights of fuzzy mappings in the fuzzy neural network which has been trained. It can realize the optimization of fuzzy decision trees by branch cutting, and improve the ratio of correctness and efficiency of the induction of decision trees.
Automatic design of decision-tree induction algorithms
Barros, Rodrigo C; Freitas, Alex A
2015-01-01
Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning, and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain o
Structural Equation Model Trees
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman
2013-01-01
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…
Modeling Induction Motor Imbalances
DEFF Research Database (Denmark)
Armah, Kabenla; Jouffroy, Jerome; Duggen, Lars
2016-01-01
This paper gives a study into the development of a generalized model for a three-phase induction motor that offers flexibility of simulating balanced and unbalanced parameter scenarios. By analyzing the interaction of forces within the motor, we achieve our main objective of deriving the system...
Distributed Decision-Tree Induction in Peer-to-Peer Systems
National Aeronautics and Space Administration — This paper offers a scalable and robust distributed algorithm for decision-tree induction in large peer-to-peer (P2P) environments. Computing a decision tree in such...
Modelling tree biomasses in Finland
Energy Technology Data Exchange (ETDEWEB)
Repola, J.
2013-06-01
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
National Research Council Canada - National Science Library
Goodwin, Adrian N
2009-01-01
A flexible tree taper model based on a cubic polynomial is described. It is algebraically invertible and integrable, and can be constrained by one or two diameters, neither of which need be diameter at breast height (DBH...
Kamphuis, C.; Mollenhorst, H.; Heesterbeek, J.A.P.; Hogeveen, H.
2010-01-01
The objective was to develop and validate a clinical mastitis (CM) detection model by means of decision-tree induction. For farmers milking with an automatic milking system (AMS), it is desirable that the detection model has a high level of sensitivity (Se), especially for more severe cases of CM,
Tree Modeling with Real Tree-Parts Examples.
Xie, Ke; Yan, Feilong; Sharf, Andrei; Deussen, Oliver; Huang, Hui; Chen, Baoquan
2016-12-01
We introduce a 3D tree modeling technique that utilizes examples of real trees to enhance tree creation with realistic structures and fine-level details. In contrast to previous works that use smooth generalized cylinders to represent tree branches, our method generates realistic looking tree models with complex branching geometry by employing an exemplar database consisting of real-life trees reconstructed from scanned data. These trees are sliced into representative parts (denoted as tree-cuts), representing trunk logs and branching structures. In the modeling process, tree-cuts are positioned in space in an intuitive manner, serving as efficient proxies that guide the creation of the complete tree. Allometry rules are taken into account to ensure reasonable relations between adjacent branches. Realism is further enhanced by automatically transferring geometric textures from our database onto tree branches as well as by guided growing of foliage. Our results demonstrate the complexity and variety of trees that can be generated with our method within few minutes. We carry a user study to test the effectiveness of our modeling technique.
Somatic Embryogenesis Induction and Plant Regeneration in Strawberry Tree (Arbutus unedo L.).
Martins, João F; Correia, Sandra I; Canhoto, Jorge M
2016-01-01
Somatic embryogenesis is a powerful tool both for cloning and studies of genetic transformation and embryo development. Most protocols for somatic embryogenesis induction start from zygotic embryos or embryonic-derived tissues which do not allow the propagation of elite trees. In the present study, a reliable protocol for somatic embryogenesis induction from adult trees of strawberry tree is described. Leaves from in vitro proliferating shoots were used to induce somatic embryo formation on a medium containing an auxin and a cytokinin. Somatic embryos germinated in a plant growth regulator-free medium.
Weighted Hybrid Decision Tree Model for Random Forest Classifier
Kulkarni, Vrushali Y.; Sinha, Pradeep K.; Petare, Manisha C.
2016-06-01
Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best split at each node of the decision tree. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation among them. The work presented in this paper is related to attribute split measures and is a two step process: first theoretical study of the five selected split measures is done and a comparison matrix is generated to understand pros and cons of each measure. These theoretical results are verified by performing empirical analysis. For empirical analysis, random forest is generated using each of the five selected split measures, chosen one at a time. i.e. random forest using information gain, random forest using gain ratio, etc. The next step is, based on this theoretical and empirical analysis, a new approach of hybrid decision tree model for random forest classifier is proposed. In this model, individual decision tree in Random Forest is generated using different split measures. This model is augmented by weighted voting based on the strength of individual tree. The new approach has shown notable increase in the accuracy of random forest.
Modelling Of Chlorine Inductive Discharges
Chabert P.; Despiau-Pujo, E.
2010-07-01
III-V compounds such as GaAs, InP or GaN-based materials are increasingly important for their use in optoelectronic applications, especially in the telecommunications and light detection industries. Photonic devices including lasers, photodetectors or LEDs, require reliable etching processes characterized by high etch rate, profile control and low damage. Although many problems remain to be understood, inductively coupled discharges seem to be promising to etch such materials, using Cl2/Ar, Cl2/N2 and Cl2/H2 gas chemistries. Inductively coupled plasma (ICP) sources meet most of the requirements for efficient plasma processing such as high etch rates, high ion densities and low controllable ion energies. However, the presence of a negative ion population in the plasma alters the positive ion flux, reduces the electron density, changes the electron temperature, modifies the spatial structure of the discharge and can cause unstable operation. Several experimental studies and numerical simulation results have been published on inductively coupled Cl2/Ar plasmas but relatively few systematic comparisons of model predictions and experimental data have been reported in given reactor geometries under a wide range of op- erating conditions. Validation of numerical predictions is essential for chemically complex plasma processing and there is a need to benchmark the models with as many measurements as possible. In this paper, comparisons of 2D fluid simulations with experimental measurements of Ar/Cl2 plasmas in a low pressure ICP reactor are reported (Corr et al. 2008). The electron density, negative ion fraction and Cl atom density are investigated for various conditions of Ar/Cl2 ratio, gas pressure and applied RF power in H mode. Simulations show that the wall recombination coefficient of Cl atom (?) is a key parameter of the model and that neutral densities are very sensitive to its variations. The best agreement between model and experiment is obtained for ? = 0
Mathematical model of induction heating
Rak, Josef
2017-07-01
One of mathematical models of induction heating can be described by a parabolic differential equation with the specific Joule looses in the body. Advantage of this method is that the detailed knowledge of the 3D-magnetic field is not necessary and move of the body or the inductor can be easily implemented. The specific Joule looses can computed by solving the Fredholm integral equation of the second kind for the eddy current of density by the Nyström method with the singularity subtraction.
Institute of Scientific and Technical Information of China (English)
Xing Li Zhang; Yang Yang Liu; Jian He Wei; Yun Yang; Zheng Zhang; Jun Qing Huang; Huai Qiong Chen; Yu Jun Liu
2012-01-01
We used whole-tree agarwood-induction technology to produce agarwood from Aquilaria sinensis trees within 20 months,and evaluated the quality of this agarwood.The results showed its characteristics were similar to those of high-grade wild agarwood in terms of texture,chemical constituents,essential oil content,and ethanol-soluble extract content,with the lattermost quality far surpassing the requirement of traditional Chinese medicine agarwood,as indicated in Chinese Pharmacopoeia 2010.To the best of our knowledge,this is first study to show that high-quality agarwood can be produced in whole A.sinensis trees via a chemically induced technology.
Verbeek, A. A.
The analysis of extracts from tree leaf, bark and wood samples for Ca, Mg, K, Na, P, Mn, Fe, Al, B, Cu and Zn by inductively coupled argon plasma sequential emission spectrometry is described. Recovery percentages for simulated tree extracts and for spiked tree samples are presented together with typical analysis values for a leaf and a wood sample. The choice of analytical line for each element is discussed and spectral interferences, not listed in the ICP tables of Boumans, of Cu on the 214.9 nm line of P and of Fe on the 249.7 nm line of B are noted.
Structured Statistical Models of Inductive Reasoning
Kemp, Charles; Tenenbaum, Joshua B.
2009-01-01
Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet…
Photosynthetic induction responses of two rainforest tree species in relation to light environment
Poorter, L.; Oberbauer, S.F.
1993-01-01
Photosynthetic induction of in situ saplings of two Costa Rican rainforest tree species wre compared in relation to their light environment, using infrared gas analysis and hemispherical photography. The species studied were Dipteryx panamensis, a climax species found in bright microsites, and
Photosynthetic induction responses of two rainforest tree species in relation to light environment
Poorter, L.; Oberbauer, S.F.
1993-01-01
Photosynthetic induction of in situ saplings of two Costa Rican rainforest tree species wre compared in relation to their light environment, using infrared gas analysis and hemispherical photography. The species studied were Dipteryx panamensis, a climax species found in bright microsites, and Cecro
Decision tree modeling with relational views
Bentayeb, Fadila
2002-01-01
Data mining is a useful decision support technique that can be used to discover production rules in warehouses or corporate data. Data mining research has made much effort to apply various mining algorithms efficiently on large databases. However, a serious problem in their practical application is the long processing time of such algorithms. Nowadays, one of the key challenges is to integrate data mining methods within the framework of traditional database systems. Indeed, such implementations can take advantage of the efficiency provided by SQL engines. In this paper, we propose an integrating approach for decision trees within a classical database system. In other words, we try to discover knowledge from relational databases, in the form of production rules, via a procedure embedding SQL queries. The obtained decision tree is defined by successive, related relational views. Each view corresponds to a given population in the underlying decision tree. We selected the classical Induction Decision Tree (ID3) a...
Inductive voltage divider modeling in Matlab
Andreev, S. A.; Kim, V. L.
2017-01-01
Inductive voltage dividers have the most appropriate metrological characteristics on alternative current and are widely used for converting physical signals. The model of a double-decade inductive voltage divider was designed with the help of Matlab/Simulink. The first decade is an inductive voltage divider with balanced winding, the second decade is a single-stage inductive voltage divider. In the paper, a new transfer function algorithm was given. The study shows errors and differences that appeared between the third degree reduced model and a twenty degree unreduced model. The obtained results of amplitude error differ no more than by 7 % between the reduced and unreduced model.
Modelling the afforested system: the forest/tree model
Heil, G.W.; Deursen, van W.; Elemans, M.; Mol, J.; Kros, H.
2007-01-01
A forest/tree model has been developed of which the main growth processes are based on the CENW model. The model links the flows of carbon (C)), energy, nutrients and water in trees and soil organic matter. Modelled tree growth depends on physiological plant factors, the size of plant pools, such as
Species Tree Inference Using a Mixture Model.
Ullah, Ikram; Parviainen, Pekka; Lagergren, Jens
2015-09-01
Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by coestimating gene trees and the species tree but this approach poses a scalability problem for larger data sets. We present MixTreEM-DLRS: A two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural expectation maximization algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model (Åkerborg O, Sennblad B, Arvestad L, Lagergren J. 2009. Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. Proc Natl Acad Sci U S A. 106(14):5714-5719), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad L, Lagergren J, Sennblad B. 2009. The gene evolution model and computing its associated probabilities. J ACM. 56(2):1-44). We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance with a recent genome-scale species tree reconstruction method PHYLDOG (Boussau B, Szöllősi GJ, Duret L, Gouy M, Tannier E, Daubin V. 2013. Genome-scale coestimation of species and gene trees. Genome Res. 23(2):323-330) as well as with a fast parsimony-based algorithm Duptree (Wehe A, Bansal MS, Burleigh JG, Eulenstein O. 2008. Duptree: a program for large-scale phylogenetic
Workflow Fault Tree Generation Through Model Checking
DEFF Research Database (Denmark)
Herbert, Luke Thomas; Sharp, Robin
2014-01-01
We present a framework for the automated generation of fault trees from models of realworld process workflows, expressed in a formalised subset of the popular Business Process Modelling and Notation (BPMN) language. To capture uncertainty and unreliability in workflows, we extend this formalism...... of the system being modelled. From these calculations, a comprehensive fault tree is generated. Further, we show that annotating the model with rewards (data) allows the expected mean values of reward structures to be calculated at points of failure....
Testing models of tree canopy structure
Energy Technology Data Exchange (ETDEWEB)
Martens, S.N. (Los Alamos National Laboratory, NM (United States))
1994-06-01
Models of tree canopy structure are difficult to test because of a lack of data which are suitability detailed. Previously, I have made three-dimensional reconstructions of individual trees from measured data. These reconstructions have been used to test assumptions about the dispersion of canopy elements in two- and three-dimensional space. Lacunarity analysis has also been used to describe the texture of the reconstructed canopies. Further tests regarding models of the nature of tree branching structures have been made. Results using probability distribution functions for branching measured from real trees show that branching in Juglans is not Markovian. Specific constraints or rules are necessary to achieve simulations of branching structure which are faithful to the originally measured trees.
Supersonic induction plasma jet modeling
Energy Technology Data Exchange (ETDEWEB)
Selezneva, S.E. E-mail: svetlana2@hermes.usherbS_Selezneva2@hermes.usherb; Boulos, M.I
2001-06-01
Numerical simulations have been applied to study the argon plasma flow downstream of the induction plasma torch. It is shown that by means of the convergent-divergent nozzle adjustment and chamber pressure reduction, a supersonic plasma jet can be obtained. We investigate the supersonic and a more traditional subsonic plasma jets impinging onto a normal substrate. Comparing to the subsonic jet, the supersonic one is narrower and much faster. Near-substrate velocity and temperature boundary layers are thinner, so the heat flux near the stagnation point is higher in the supersonic jet. The supersonic plasma jet is characterized by the electron overpopulation and the domination of the recombination over the dissociation, resulting into the heating of the electron gas. Because of these processes, the supersonic induction plasma permits to separate spatially different functions (dissociation and ionization, transport and deposition) and to optimize each of them. The considered configuration can be advantageous in some industrial applications, such as plasma-assisted chemical vapor deposition of diamond and polymer-like films and in plasma spraying of nanoscaled powders.
Guideliness for system modeling: fault tree [analysis
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Hwan; Yang, Joon Eon; Kang, Dae Il; Hwang, Mee Jeong
2004-07-01
This document, the guidelines for system modeling related to Fault Tree Analysis(FTA), is intended to provide the guidelines with the analyzer to construct the fault trees in the level of the capability category II of ASME PRA standard. Especially, they are to provide the essential and basic guidelines and the related contents to be used in support of revising the Ulchin 3 and 4 PSA model for risk monitor within the capability category II of ASME PRA standard. Normally the main objective of system analysis is to assess the reliability of system modeled by Event Tree Analysis (ETA). A variety of analytical techniques can be used for the system analysis, however, FTA method is used in this procedures guide. FTA is the method used for representing the failure logic of plant systems deductively using AND, OR or NOT gates. The fault tree should reflect all possible failure modes that may contribute to the system unavailability. This should include contributions due to the mechanical failures of the components, Common Cause Failures (CCFs), human errors and outages for testing and maintenance. This document identifies and describes the definitions and the general procedures of FTA and the essential and basic guidelines for reving the fault trees. Accordingly, the guidelines for FTA will be capable to guide the FTA to the level of the capability category II of ASME PRA standard.
Concept Tree Based Information Retrieval Model
Directory of Open Access Journals (Sweden)
Chunyan Yuan
2014-05-01
Full Text Available This paper proposes a novel concept-based query expansion technique named Markov concept tree model (MCTM, discovering term relationship through the concept tree deduced by term markov network. We address two important issues for query expansion: the selection and the weighting of expansion search terms. In contrast to earlier methods, queries are expanded by adding those terms that are most similar to the concept of the query, rather than selecting terms that are similar to a signal query terms. Utilizing Markov network which is constructed according to the co-occurrence information of the terms in collection, it generate concept tree for each original query term, remove the redundant and irrelevant nodes in concept tree, then adjust the weight of original query and the weight of expansion term based on a pruning algorithm. We use this model for query expansion and evaluate the effectiveness of the model by examining the accuracy and robustness of the expansion methods, Compared with the baseline model, the experiments on standard dataset reveal that this method can achieve a better query quality
Modeling huanglongbing transmission within a citrus tree.
Chiyaka, Christinah; Singer, Burton H; Halbert, Susan E; Morris, J Glenn; van Bruggen, Ariena H C
2012-07-24
The citrus disease huanglongbing (HLB), associated with an uncultured bacterial pathogen, is threatening the citrus industry worldwide. A mathematical model of the transmission of HLB between its psyllid vector and citrus host has been developed to characterize the dynamics of the vector and disease development, focusing on the spread of the pathogen from flush to flush (a newly developing cluster of very young leaves on the expanding terminal end of a shoot) within a tree. This approach differs from that of prior models for vector-transmitted plant diseases where the entire plant is the unit of analysis. Dynamics of vector and host populations are simulated realistically as the flush population approaches complete infection. Model analysis indicates that vector activity is essential for initial infection but is not necessary for continued infection because infection can occur from flush to flush through internal movement in the tree. Flush production, within-tree spread, and latent period are the most important parameters influencing HLB development. The model shows that the effect of spraying of psyllids depends on time of initial spraying, frequency, and efficacy of the insecticides. Similarly, effects of removal of symptomatic flush depend on the frequency of removal and the time of initiation of this practice since the start of the epidemic. Within-tree resistance to spread, possibly affected by inherent or induced resistance, is a major factor affecting epidemic development, supporting the notion that alternate routes of transmission besides that by the vector can be important for epidemic development.
Pesticide bioconcentration modelling for fruit trees.
Paraíba, Lourival Costa
2007-01-01
The model presented allows simulating the pesticide concentration evolution in fruit trees and estimating the pesticide bioconcentration factor in fruits. Pesticides are non-ionic organic compounds that are degraded in soils cropped with woody species, fruit trees and other perennials. The model allows estimating the pesticide uptake by plants through the water transpiration stream and also the time in which maximum pesticide concentration occur in the fruits. The equation proposed presents the relationships between bioconcentration factor (BCF) and the following variables: plant water transpiration volume (Q), pesticide transpiration stream concentration factor (TSCF), pesticide stem-water partition coefficient (K(Wood,W)), stem dry biomass (M) and pesticide dissipation rate in the soil-plant system (k(EGS)). The modeling started and was developed from a previous model "Fruit Tree Model" (FTM), reported by Trapp and collaborators in 2003, to which was added the hypothesis that the pesticide degradation in the soil follows a first order kinetic equation. The FTM model for pesticides (FTM-p) was applied to a hypothetic mango plant cropping (Mangifera indica) treated with paclobutrazol (growth regulator) added to the soil. The model fitness was evaluated through the sensitivity analysis of the pesticide BCF values in fruits with respect to the model entry data variability.
Toward a unified chromatic induction model.
Otazu, Xavier; Parraga, C Alejandro; Vanrell, Maria
2010-10-01
In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data.
Inductive modelling of an entrepreneurial system
Yearworth, M
2010-01-01
We describe the development of a novel approach to generating theory about the behaviour of an entrepreneurial or start-up system. The new technology business creation system in and around the cities of Bath and Bristol in the UK was analysed using an inductive modelling approach that hybridises grounded theory with system dynamics, a technique we have called grounded systems modelling. Three models that represent the stages of development of an idea through to successful exploitation have be...
Martínez, Gonzalo; Giraldez Cervera, Juan Vicente; Vanderlinden, Karl
2015-04-01
Soil moisture (θ) is a critical variable that exerts an important control on plant status and development. Soil sampling, neutron attenuation and electromagnetic methods such as TDR or FDR have been used widely to measure θ and provide point data at a possible range of temporal resolutions. However, these methods require either destructive sampling or permanently installed devices with often limiting measurement depths, or are extremely time-consuming. Moreover, the small support of such measurements compromises its value in heterogeneous soils. To overcome such limitations electromagnetic induction (EMI) can be tested to monitor θ at different spatial and temporal scales. This work investigates the potential of EMI to characterize the spatio-temporal variability of soil moisture from apparent electrical conductivity (ECa) under the canopy of individual olive trees. During one year we measured θ with a frequency of 5 min and ECa on an approximately weekly basis along transects from the tree trunk towards the inter-row area. CS-616 soil moisture sensors where horizontally installed in the walls of a trench at depths of 0.1, 0.2, 0.4, 0.6 and 0.8 m at five locations along the transect, with a separation of 0.8 m. The Dualem-21S sensor was used to measure weekly the ECa at 0.2 m increments, from the tree trunk to a distance of 4.4 m. The results showed similar drying and wetting patterns for θ and ECa. Both variables showed a decreasing pattern from the tree trunk towards the drip line, followed by a sharp increment and constant values towards the center of the inter-row space. This pattern reflects clearly the influence of root-zone water uptake under the tree canopy and higher θ values in the inter-row area where root-water uptake is smaller. Time-lapse ECa data responded to evaporation and infiltration fluxes with the highest sensitivity for the 1 and 1.5 m ECa signals, as compared to the 0.5 and 3.0 m signals. Overall these preliminary results revealed the
Modelling imperfect adherence to HIV induction therapy
Directory of Open Access Journals (Sweden)
Smith? Robert J
2010-01-01
Full Text Available Abstract Background Induction-maintenance therapy is a treatment regime where patients are prescribed an intense course of treatment for a short period of time (the induction phase, followed by a simplified long-term regimen (maintenance. Since induction therapy has a significantly higher chance of pill fatigue than maintenance therapy, patients might take drug holidays during this period. Without guidance, patients who choose to stop therapy will each be making individual decisions, with no scientific basis. Methods We use mathematical modelling to investigate the effect of imperfect adherence during the inductive phase. We address the following research questions: 1. Can we theoretically determine the maximal length of a possible drug holiday and the minimal number of doses that must subsequently be taken while still avoiding resistance? 2. How many drug holidays can be taken during the induction phase? Results For a 180 day therapeutic program, a patient can take several drug holidays, but then has to follow each drug holiday with a strict, but fairly straightforward, drug-taking regimen. Since the results are dependent upon the drug regimen, we calculated the length and number of drug holidays for all fifteen protease-sparing triple-drug cocktails that have been approved by the US Food and Drug Administration. Conclusions Induction therapy with partial adherence is tolerable, but the outcome depends on the drug cocktail. Our theoretical predictions are in line with recent results from pilot studies of short-cycle treatment interruption strategies and may be useful in guiding the design of future clinical trials.
Induction of decision trees and Bayesian classification applied to diagnosis of sport injuries.
Zelic, I; Kononenko, I; Lavrac, N; Vuga, V
1997-12-01
Machine learning techniques can be used to extract knowledge from data stored in medical databases. In our application, various machine learning algorithms were used to extract diagnostic knowledge which may be used to support the diagnosis of sport injuries. The applied methods include variants of the Assistant algorithm for top-down induction of decision trees, and variants of the Bayesian classifier. The available dataset was insufficient for reliable diagnosis of all sport injuries considered by the system. Consequently, expert-defined diagnostic rules were added and used as pre-classifiers or as generators of additional training instances for diagnoses for which only few training examples were available. Experimental results show that the classification accuracy and the explanation capability of the naive Bayesian classifier with the fuzzy discretization of numerical attributes were superior to other methods and estimated as the most appropriate for practical use.
A hierarchical linear model for tree height prediction.
Vicente J. Monleon
2003-01-01
Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...
Stator Fault Modelling of Induction Motors
DEFF Research Database (Denmark)
Thomsen, Jesper Sandberg; Kallesøe, Carsten
2006-01-01
measurements from a specially designed induction motor. With this motor it is possible to simulate both terminal disconnections, inter-turn and turn-turn short circuits. The results show good agreement between the measurements and the simulated signals obtained from the model. In the tests focus......In this paper a model of an induction motor affected by stator faults is presented. Two different types of faults are considered, these are; disconnection of a supply phase, and inter-turn and turn-turn short circuits inside the stator. The output of the derived model is compared to real...... is on the phase currents and the star point voltage as these signals are often used for fault detection....
Directory of Open Access Journals (Sweden)
Deptuła A.
2017-02-01
Full Text Available The article presents an innovative use of inductive algorithm for generating the decision tree for an analysis of the rank validity parameters of construction and maintenance of the gear pump with undercut tooth. It is preventet an alternative way of generating sets of decisions and determining the hierarchy of decision variables to existing the methods of discrete optimization.
Kamphuis, C; Mollenhorst, H; Heesterbeek, J A P; Hogeveen, H
2010-08-01
The objective was to develop and validate a clinical mastitis (CM) detection model by means of decision-tree induction. For farmers milking with an automatic milking system (AMS), it is desirable that the detection model has a high level of sensitivity (Se), especially for more severe cases of CM, at a very high specificity (Sp). In addition, an alert for CM should be generated preferably at the quarter milking (QM) at which the CM infection is visible for the first time. Data were collected from 9 Dutch dairy herds milking automatically during a 2.5-yr period. Data included sensor data (electrical conductivity, color, and yield) at the QM level and visual observations of quarters with CM recorded by the farmers. Visual observations of quarters with CM were combined with sensor data of the most recent automatic milking recorded for that same quarter, within a 24-h time window before the visual assessment time. Sensor data of 3.5 million QM were collected, of which 348 QM were combined with a CM observation. Data were divided into a training set, including two-thirds of all data, and a test set. Cows in the training set were not included in the test set and vice versa. A decision-tree model was trained using only clear examples of healthy (n=24,717) or diseased (n=243) QM. The model was tested on 105 QM with CM and a random sample of 50,000 QM without CM. While keeping the Se at a level comparable to that of models currently used by AMS, the decision-tree model was able to decrease the number of false-positive alerts by more than 50%. At an Sp of 99%, 40% of the CM cases were detected. Sixty-four percent of the severe CM cases were detected and only 12.5% of the CM that were scored as watery milk. The Se increased considerably from 40% to 66.7% when the time window increased from less than 24h before the CM observation, to a time window from 24h before to 24h after the CM observation. Even at very wide time windows, however, it was impossible to reach an Se of 100
Directory of Open Access Journals (Sweden)
Uttam Chauhan
2011-01-01
Full Text Available Many methods exist for the purpose of classification of an unknown dataset. Decision tree induction is one of the well-known methods for classification. Decision tree method operates under two different modes: nonadaptive and adaptive mode. The non adaptive mode of operation is applied when the data set is completely mature and available or the data set is static and their will be no changes in dataset attributes. However when the dataset is likely to have changes in the values and attributes leading to fluctuation i.e., monthly, quarterly or annually, then under the circumstances decision tree method operating under adaptive mode needs to be applied, as the conventional non-adaptive method fails, as it needs to be applied once again starting from scratch on the augmented dataset. This makes things expensive in terms of time and space. Sometimes attributesare added into the dataset, at the same time number of records also increases. This paper mainly studies the behavioral aspects of classification model particularly, when number of attr bute in dataset increase due to spontaneous changes in the value(s/attribute(s. Our investigative studies have shown that accuracy of decision tree model can be maintained when number of attributes including class increase in dataset which increases thenumber of records as well. In addition, accuracy also can be maintained when number of values increase in class attribute of dataset. The way Adaptive mode decision tree method operates is that it reads data instance by instance and incorporates the same through absorption to the said model; update the model according to valueof attribute particular and specific to the instance. As the time required to updating decision tree can be less than introducing it from scratch, thus eliminating the problem of introducing decision tree repeatedly from scratch and at the same time gaining upon memory and time.
Induction generator models in dynamic simulation tools
DEFF Research Database (Denmark)
Knudsen, Hans; Akhmatov, Vladislav
1999-01-01
For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained. It is fo......For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained....... It is found to be possible to include a transient model in dynamic stability tools and, then, obtain correct results also in dynamic tools. The representation of the rotating system influences on the voltage recovery shape which is an important observation in case of windmills, where a heavy mill is connected...
Pruning Chinese trees : an experimental and modelling approach
Zeng, Bo
2002-01-01
Pruning of trees, in which some branches are removed from the lower crown of a tree, has been extensively used in China in silvicultural management for many purposes. With an experimental and modelling approach, the effects of pruning on tree growth and on the harvest of plant material were studied.
Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data
Directory of Open Access Journals (Sweden)
Mathias Disney
2013-01-01
Full Text Available This paper presents a new method for constructing quickly and automatically precision tree models from point clouds of the trunk and branches obtained by terrestrial laser scanning. The input of the method is a point cloud of a single tree scanned from multiple positions. The surface of the visible parts of the tree is robustly reconstructed by making a flexible cylinder model of the tree. The thorough quantitative model records also the topological branching structure. In this paper, every major step of the whole model reconstruction process, from the input to the finished model, is presented in detail. The model is constructed by a local approach in which the point cloud is covered with small sets corresponding to connected surface patches in the tree surface. The neighbor-relations and geometrical properties of these cover sets are used to reconstruct the details of the tree and, step by step, the whole tree. The point cloud and the sets are segmented into branches, after which the branches are modeled as collections of cylinders. From the model, the branching structure and size properties, such as volume and branch size distributions, for the whole tree or some of its parts, can be approximated. The approach is validated using both measured and modeled terrestrial laser scanner data from real trees and detailed 3D models. The results show that the method allows an easy extraction of various tree attributes from terrestrial or mobile laser scanning point clouds.
Statistical Decision-Tree Models for Parsing
Magerman, D M
1995-01-01
Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text, as is evidenced by their poor performance on domains like the Wall Street Journal, and by the movement away from parsing-based approaches to text-processing in general. In this paper, I describe SPATTER, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sentence and achieves accuracy rates far better than any published result. This work is based on the following premises: (1) grammars are too complex and detailed to develop manually for most interesting domains; (2) parsing models must rely heavily on lexical and contextual information to analyze sentences accurately; and (3) existing {$n$}-gram modeling techniques are inadequate for parsing models. In experiments comparing SPATTER with IBM's computer manuals parser, SPATTER significantly outperforms the grammar-based parser. Evaluating SPATTER against the Penn Treebank Wall ...
Induction generator models in dynamic simulation tools
DEFF Research Database (Denmark)
Knudsen, Hans; Akhmatov, Vladislav
1999-01-01
. It is found to be possible to include a transient model in dynamic stability tools and, then, obtain correct results also in dynamic tools. The representation of the rotating system influences on the voltage recovery shape which is an important observation in case of windmills, where a heavy mill is connected......For AC network with large amount of induction generators (windmills) the paper demonstrates a significant discrepancy in the simulated voltage recovery after fault in weak networks when comparing dynamic and transient stability descriptions and the reasons of discrepancies are explained...
Heat transfer modeling an inductive approach
Sidebotham, George
2015-01-01
This innovative text emphasizes a "less-is-more" approach to modeling complicated systems such as heat transfer by treating them first as "1-node lumped models" that yield simple closed-form solutions. The author develops numerical techniques for students to obtain more detail, but also trains them to use the techniques only when simpler approaches fail. Covering all essential methods offered in traditional texts, but with a different order, Professor Sidebotham stresses inductive thinking and problem solving as well as a constructive understanding of modern, computer-based practice. Readers learn to develop their own code in the context of the material, rather than just how to use packaged software, offering a deeper, intrinsic grasp behind models of heat transfer. Developed from over twenty-five years of lecture notes to teach students of mechanical and chemical engineering at The Cooper Union for the Advancement of Science and Art, the book is ideal for students and practitioners across engineering discipl...
Growth models for tree stems and vines
Bressan, Alberto; Palladino, Michele; Shen, Wen
2017-08-01
The paper introduces a PDE model for the growth of a tree stem or a vine. The equations describe the elongation due to cell growth, and the response to gravity and to external obstacles. An additional term accounts for the tendency of a vine to curl around branches of other plants. When obstacles are present, the model takes the form of a differential inclusion with state constraints. At each time t, a cone of admissible reactions is determined by the minimization of an elastic deformation energy. The main theorem shows that local solutions exist and can be prolonged globally in time, except when a specific ;breakdown configuration; is reached. Approximate solutions are constructed by an operator-splitting technique. Some numerical simulations are provided at the end of the paper.
A spatial model of tree α-diversity and tree density for the Amazon
ter Steege, H.; Pitman, N.C.A.; Sabatier, D.; Castellanos, H.; van der Hout, P.; Daly, D.C.; Silveira, M.; Phillips, O.; Vasquez, R.; van Andel, T.; Duivenvoorden, J.; de Oliveira, A.A.; Ek, R.; Lilwah, R.; Thomas, R.; van Essen, J.; Baider, C.; Maas, P.; Mori, S.; Terborgh, J.; Nuñez-Vargas, P.; Mogollón, H.; Morawetz, W.
2003-01-01
Large-scale patterns of Amazonian biodiversity have until now been obscured by a sparse and scattered inventory record. Here we present the first comprehensive spatial model of tree α-diversity and tree density in Amazonian rainforests, based on the largest-yet compilation of forest inventories and
Inferring gene regression networks with model trees
Directory of Open Access Journals (Sweden)
Aguilar-Ruiz Jesus S
2010-10-01
Full Text Available Abstract Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear
Image-Based Modeling of Plants and Trees
Kang, Sing Bang
2009-01-01
Plants and trees are among the most complex natural objects. Much work has been done attempting to model them, with varying degrees of success. In this book, we review the various approaches in computer graphics, which we categorize as rule-based, image-based, and sketch-based methods. We describe our approaches for modeling plants and trees using images. Image-based approaches have the distinct advantage that the resulting model inherits the realistic shape and complexity of a real plant or tree. We use different techniques for modeling plants (with relatively large leaves) and trees (with re
Cognitive Trait Modelling: The Case of Inductive Reasoning Ability
Kinshuk, Taiyu Lin; McNab, Paul
2006-01-01
Researchers have regarded inductive reasoning as one of the seven primary mental abilities that account for human intelligent behaviours. Researchers have also shown that inductive reasoning ability is one of the best predictors for academic performance. Modelling of inductive reasoning is therefore an important issue for providing adaptivity in…
Mathematical Model of an Inductive Measuring Cell for Contactless Conductometry
Semenov, Yury S
2013-01-01
A research of inductive conductometric cell is presented. An equivalent circuit and a mathematical model of inductive cell are given in the article. The model takes into account sample-coil capacity (i.e. capacity formed by the coil and the sample under study) and eddy currents. It is sample-coil capacity that makes inductive cell applicable for measurement of electrical conductivity of low conductive samples (specific conductance is less than 1S/m). The model can be used to calculate impedance of inductive cell for different characteristics of sample, materials and dimensions of cell without numerical solving of partial differential equations. Results of numerical simulation were verified by experiment for several devices with inductive cell. Some features that an engineer has to hold in mind while designing a conductometer based on inductive cell are discussed. Presented model can be useful for those who study inductively coupled plasma.
Stochastic Models for Phylogenetic Trees on Higher-order Taxa
Aldous, David; Popovic, Lea
2007-01-01
Simple stochastic models for phylogenetic trees on species have been well studied. But much paleontology data concerns time series or trees on higher-order taxa, and any broad picture of relationships between extant groups requires use of higher-order taxa. A coherent model for trees on (say) genera should involve both a species-level model and a model for the classification scheme by which species are assigned to genera. We present a general framework for such models, and describe three alternate classification schemes. Combining with the species-level model of Aldous-Popovic (2005), one gets models for higher-order trees, and we initiate analytic study of such models. In particular we derive formulas for the lifetime of genera, for the distribution of number of species per genus, and for the offspring structure of the tree on genera.
A spatial model for sporadic tree species distribution in support of tree oriented silviculture
Directory of Open Access Journals (Sweden)
Davide Melini
2013-12-01
Full Text Available This technical note describes how a spatial model for sporadic tree species distribution in the territory of the Unione di Comuni Montana Colline Metallifere (UCMCM was built using the Random Forest (RF algorithm and 48 predictors, including reflectance values from ground cover - provided by satellite sensors - and ecological factors. The P.Pro.SPO.T. project - Policy and Protection of Sporadic tree species in Tuscany forest (LIFE 09 ENV/IT/000087 is currently carried out in this area with the purpose of initiating the implementation of tree oriented silviculture in the Tuscany forests. Tree oriented silviculture aims at obtaining both forest biodiversity protection and local production of valuable timber. After creating a map showing the probability of presence of sporadic tree species, it was possible to identify the most suitable areas for sporadic tree species which are under protection according to the regulation of the Tuscany Region.Using data and software provided free of charge, and applying the RF algorithm, distribution models could be developed in order to identify the most suitable areas for the application of tree oriented silviculture. This can provide a support to forestry planning that includes tree oriented silviculture, thus reducing its implementation cost.
Electrothermal Model of Kinetic Inductance Detectors
Thomas, Christopher N; Goldie, David J
2014-01-01
An electrothermal model of Kinetic Inductance Detectors (KIDs) is described. The non-equilibrium state of the resonator's quasiparticle system is characterized by an effective temperature, which because of readout-power heating is higher than that of the bath. By balancing the flow of energy into the quasiparticle system, it is possible to calculate the steady-state large-signal, small-signal and noise behaviour. Resonance-curve distortion and hysteretic switching appear naturally within the framework. It is shown that an electrothermal feedback process exists, which affects all aspects of behaviour. It is also shown that generation-recombination noise can be interpreted in terms of the thermal fluctuation noise in the effective thermal conductance that links the quasiparticle and phonon systems of the resonator. Because the scheme is based on electrothermal considerations, multiple elements can be added to simulate the behaviour of complex devices, such as resonators on membranes, again taking into account r...
Modeling a Cold Crucible Induction Heated Melter
Energy Technology Data Exchange (ETDEWEB)
Grant L. Hawkes
2003-06-01
FIDAP has been used to simulate melting of radioactive waste glass in a cold crucible induction heated melter. A model has been created that couples the magnetic vector potential (real and imaginary) to a transient startup of the melting process. This magnetic field is coupled to the mass, momentum, and energy equations that vary with time and position as the melt grows. The coupling occurs with the electrical conductivity of the glass as it rises above the melt temperature of the glass and heat is generated. Natural convection within the molten glass helps determine the shape of the melt as it progresses in time. An electromagnetic force is also implemented that is dependent on the electrical properties and frequency of the coil. This study shows the progression of the melt shape with time along with temperatures, power input, velocities, and magnetic vector potential. A power controller is implemented that controls the primary coil current and power.
Modeling a Cold Crucible Induction Heated Melter
Energy Technology Data Exchange (ETDEWEB)
Hawkes, G.L.
2003-05-09
FIDAP has been used to simulate melting of radioactive waste glass in a cold crucible induction heated melter. A model has been created that couples the magnetic vector potential (real and imaginary) to a transient startup of the melting process. This magnetic field is coupled with mass, momentum, and energy equations that vary with time and position as the melt grows. The coupling occurs with the electrical conductivity of the glass as it rises above the melt temperature of the glass and heat is generated. Natural convection within the molten glass helps determine the shape of the melt as it progresses in time. An electromagnetic force is also implemented that is dependent on the electrical properties and frequency of the coil. This study shows the progression of the melt shape with time along with temperatures, power input, velocities, and magnetic vector potential. A power controller is implemented that controls the primary coil current and power.
The reality model of the plum tree based on SpeedTree
Bai, Zhi-yong; Huang, Xin-yuan
2010-02-01
Plum Blossom as the Chinese traditional flowers may be unique all over the world and has the first right of access to international registry of flower. In this paper, the SpeedTree software is used to quickly build reality model of the plum tree. The graphics texture mapping techniques is used, and the plum tree image maps express the geometric model of the surface material, which constitutes a visual image of the graphic objects. It is significant for non-destructive study of plum and virtual garden.
Boosted Regression Tree Models to Explain Watershed ...
Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite-nitrate (NO2-NO3), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO2-NO3 concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed-use and heavily impacted watershed
Dynamic Model of Linear Induction Motor Considering the End Effects
Directory of Open Access Journals (Sweden)
H. A. Hairik
2009-01-01
Full Text Available In this paper the dynamic behavior of linear induction motor is described by a mathematical model taking into account the end effects and the core losses. The need for such a model rises due to the complexity of linear induction motors electromagnetic field theory. The end affects by introducing speed dependent scale factor to the magnetizing inductance and series resistance in the d-axis equivalent circuit. Simulation results are presented to show the validity of the model during both no-load and sudden load change intervals. This model can also be used directly in simulation researches for linear induction motor vector control drive systems.
A generalized item response tree model for psychological assessments.
Jeon, Minjeong; De Boeck, Paul
2016-09-01
A new item response theory (IRT) model with a tree structure has been introduced for modeling item response processes with a tree structure. In this paper, we present a generalized item response tree model with a flexible parametric form, dimensionality, and choice of covariates. The utilities of the model are demonstrated with two applications in psychological assessments for investigating Likert scale item responses and for modeling omitted item responses. The proposed model is estimated with the freely available R package flirt (Jeon et al., 2014b).
The Use of Models in Teaching Proof by Mathematical Induction
Ron, Gila; Dreyfus, Tommy
2004-01-01
Proof by mathematical induction is known to be conceptually difficult for high school students. This paper presents results from interviews with six experienced high school teachers, concerning the use of models in teaching mathematical induction. Along with creative and adequate use of models, we found explanations, models and examples that…
A Knowledge Tree Model for Managing Organizational Knowledge
Institute of Scientific and Technical Information of China (English)
BAO Zhen-qiang; WANG Ning-sheng
2002-01-01
According to the relation of organizational knowledge, this paper analyzes the structure of organizational knowledge at first. A concept of knowledge tree is introduced and a process model of knowledge management is described by a knowledge tree. In this paper a definition of value of knowledge is given and the life cycle of a knowledge tree is analyzed. Finally, some principles for knowledge management are presented.
Impacts of Tree Height-Dbh Allometry on Lidar-Based Tree Aboveground Biomass Modeling
Fang, R.
2016-06-01
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.
Motif Yggdrasil: sampling sequence motifs from a tree mixture model.
Andersson, Samuel A; Lagergren, Jens
2007-06-01
In phylogenetic foot-printing, putative regulatory elements are found in upstream regions of orthologous genes by searching for common motifs. Motifs in different upstream sequences are subject to mutations along the edges of the corresponding phylogenetic tree, consequently taking advantage of the tree in the motif search is an appealing idea. We describe the Motif Yggdrasil sampler; the first Gibbs sampler based on a general tree that uses unaligned sequences. Previous tree-based Gibbs samplers have assumed a star-shaped tree or partially aligned upstream regions. We give a probabilistic model (MY model) describing upstream sequences with regulatory elements and build a Gibbs sampler with respect to this model. The model allows toggling, i.e., the restriction of a position to a subset of nucleotides, but does not require aligned sequences nor edge lengths, which may be difficult to come by. We apply the collapsing technique to eliminate the need to sample nuisance parameters, and give a derivation of the predictive update formula. We show that the MY model improves the modeling of difficult motif instances and that the use of the tree achieves a substantial increase in nucleotide level correlation coefficient both for synthetic data and 37 bacterial lexA genes. We investigate the sensitivity to errors in the tree and show that using random trees MY sampler still has a performance similar to the original version.
Decision-tree induction from self-mapping space based on web
Institute of Scientific and Technical Information of China (English)
ZHANG Shu-yu; ZHU Zhong-ying
2007-01-01
An improved decision tree method for web information retrieval with self-mapping attributes is proposed. The self-mapping tree has a value of self-mapping attribute in its internal node, and information based on dissimilarity between a pair of mapping sequences. This method selects self-mapping which exists between data by exhaustive search based on relation and attribute information. Experimental results confirm that the improved method constructs comprehensive and accurate decision tree. Moreover, an example shows that the selfmapping decision tree is promising for data mining and knowledge discovery.
A Model of Inductive Bias Learning
Baxter, J
2011-01-01
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem being learnt, yet small enough to ensure reliable generalization from reasonably-sized training sets. Typically such bias is supplied by hand through the skill and insights of experts. In this paper a model for automatically learning bias is investigated. The central assumption of the model is that the learner is embedded within an environment of related learning tasks. Within such an environment the learner can sample from multiple tasks, and hence it can search for a hypothesis space that contains good solutions to many of the problems in the environment. Under certain restrictions on the set of all hypothesis spaces available to the learner, we show that a hypothesis space that performs well on a sufficiently large number of training tasks will also perform well when learning novel tasks in the same environment. Explicit bounds are also de...
Al-Khaja, Nawal
2007-01-01
This is a thematic lesson plan for young learners about palm trees and the importance of taking care of them. The two part lesson teaches listening, reading and speaking skills. The lesson includes parts of a tree; the modal auxiliary, can; dialogues and a role play activity.
Modeling of Lossy Inductance in Moving-Coil Loudspeakers
DEFF Research Database (Denmark)
Kong, Xiao-Peng; Agerkvist, Finn T.; Zeng, Xin-Wu
2015-01-01
The electrical impedance of moving-coil loudspeakers is dominated by the lossy inductance in high frequency range. Using the equivalent electrical circuit method, a new model for the lossy inductance based on separate functions for the magnitude and phase of the impedance is presented. The electr......The electrical impedance of moving-coil loudspeakers is dominated by the lossy inductance in high frequency range. Using the equivalent electrical circuit method, a new model for the lossy inductance based on separate functions for the magnitude and phase of the impedance is presented...
Massive-scale tree modelling from TLS data
Raumonen, P.; Casella, E.; Calders, K.; Murphy, S.; Åkerblom, M.; Kaasalainen, M.
2015-01-01
This paper presents a method for reconstructing automatically the quantitative structure model of every tree in a forest plot from terrestrial laser scanner data. A new feature is the automatic extraction of individual trees from the point cloud. The method is tested with a 30-m diameter English oak
Ising model on the generalized Bruhat-Tits tree
Zinoviev, Yu. M.
1991-08-01
The partition function and the correlation functions of the Ising model on the generalized Bruhat-Tits tree are calculated. We computed also the averages of these correlation functions when the corresponding vertices are attached to the boundary of the generalized Bruhat-Tits tree.
Maximum Leaf Spanning Trees of Growing Sierpinski Networks Models
Yao, Bing; Xu, Jin
2016-01-01
The dynamical phenomena of complex networks are very difficult to predict from local information due to the rich microstructures and corresponding complex dynamics. On the other hands, it is a horrible job to compute some stochastic parameters of a large network having thousand and thousand nodes. We design several recursive algorithms for finding spanning trees having maximal leaves (MLS-trees) in investigation of topological structures of Sierpinski growing network models, and use MLS-trees to determine the kernels, dominating and balanced sets of the models. We propose a new stochastic method for the models, called the edge-cumulative distribution, and show that it obeys a power law distribution.
Induction of hybrid decision tree based on post-discretization strategy
Institute of Scientific and Technical Information of China (English)
WANG Limin; YUAN Senmiao
2004-01-01
By redefining test selection measure, we propose in this paper a new algorithm, Flexible NBTree, which induces a hybrid of decision tree and Naive Bayes. Flexible NBTree mitigates the negative effect of information loss on test selection by applying postdiscretization strategy: at each internal node in the tree, we first select the test which is the most useful for improving classification accuracy, then apply discretization of continuous tests. The finial decision tree nodes contain univariate splits as regular decision trees, but the leaves contain Naive Bayesian classifiers. To evaluate the performance of Flexible NBTree, we compare it with NBTree and C4.5, both applying pre-discretization of continuous attributes. Experimental results on a variety of natural domains indicate that the classification accuracy of Flexible NBTree is substantially improved.
A generalized model for stability of trees under impact conditions
Dattola, Giuseppe; Crosta, Giovanni; Castellanza, Riccardo; di Prisco, Claudio; Canepa, Davide
2016-04-01
Stability of trees to external actions involve the combined effects of stem and tree root systems. A block impacting on the stem or an applied force pulling the stem can cause a tree instability involving stem bending or failure and tree root rotation. So different contributions are involved in the stability of the system. The rockfalls are common natural phenomena that can be unpredictable in terms of frequency and magnitude characteristics, and this makes difficult the estimate of potential hazard and risk for human lives and activities. In mountain areas a natural form of protection from rockfalls is provided by forest growing. The difficulties in the assessment of the real capability of this natural barrier by means of models is an open problem. Nevertheless, a large amount of experimental data are now available which provides support for the development of advanced theoretical framework and corresponding models. The aim of this contribution consists in presenting a model developed to predict the behavior of trees during a block impact. This model describes the tree stem by means of a linear elastic beam system consisting of two beams connected in series and with an equivalent geometry. The tree root system is described via an equivalent foundation, whose behavior is modelled through an elasto-plastic macro-element model. In order to calibrate the model parameters, simulations reproducing a series of winching tests, are performed. These numerical simulations confirm the capability of the model to predict the mechanical behavior of the stem-root system in terms of displacement vs force curves. Finally, numerical simulations of the impact of a boulder with a tree stem are carried out. These simulations, done under dynamic regime and with the model parameters obtained from the previous set of simulations, confirm the capability of the model to reproduce the effects on the stem-roots system generated by impulsive loads.
A new approach to modeling tree rainfall interception
Xiao, Qingfu; McPherson, E. Gregory; Ustin, Susan L.; Grismer, Mark E.
2000-12-01
A three-dimensional physically based stochastic model was developed to describe canopy rainfall interception processes at desired spatial and temporal resolutions. Such model development is important to understand these processes because forest canopy interception may exceed 59% of annual precipitation in old growth trees. The model describes the interception process from a single leaf, to a branch segment, and then up to the individual tree level. It takes into account rainfall, meteorology, and canopy architecture factors as explicit variables. Leaf and stem surface roughness, architecture, and geometric shape control both leaf drip and stemflow. Model predictions were evaluated using actual interception data collected for two mature open grown trees, a 9-year-old broadleaf deciduous pear tree (Pyrus calleryana "Bradford" or Callery pear) and an 8-year-old broadleaf evergreen oak tree (Quercus suber or cork oak). When simulating 18 rainfall events for the oak tree and 16 rainfall events for the pear tree, the model over estimated interception loss by 4.5% and 3.0%, respectively, while stemflow was under estimated by 0.8% and 3.3%, and throughfall was under estimated by 3.7% for the oak tree and over estimated by 0.3% for the pear tree. A model sensitivity analysis indicates that canopy surface storage capacity had the greatest influence on interception, and interception losses were sensitive to leaf and stem surface area indices. Among rainfall factors, interception losses relative to gross precipitation were most sensitive to rainfall amount. Rainfall incident angle had a significant effect on total precipitation intercepting the projected surface area. Stemflow was sensitive to stem segment and leaf zenith angle distributions. Enhanced understanding of interception loss dynamics should lead to improved urban forest ecosystem management.
Dynamics of 'abc' and 'qd' constant parameters induction generator model
DEFF Research Database (Denmark)
Fajardo-R, L.A.; Medina, A.; Iov, F.
2009-01-01
In this paper, parametric sensibility effects on dynamics of the induction generator in the presence of local perturbations are investigated. The study is conducted in a 3x2 MW wind park dealing with abc, qd0 and qd reduced order, induction generator model respectively, and with fluxes as state v...
A tree-based model for homogeneous groupings of multinomials.
Yang, Tae Young
2005-11-30
The motivation of this paper is to provide a tree-based method for grouping multinomial data according to their classification probability vectors. We produce an initial tree by binary recursive partitioning whereby multinomials are successively split into two subsets and the splits are determined by maximizing the likelihood function. If the number of multinomials k is too large, we propose to order the multinomials, and then build the initial tree based on a dramatically smaller number k-1 of possible splits. The tree is then pruned from the bottom up. The pruning process involves a sequence of hypothesis tests of a single homogeneous group against the alternative that there are two distinct, internally homogeneous groups. As pruning criteria, the Bayesian information criterion and the Wilcoxon rank-sum test are proposed. The tree-based model is illustrated on genetic sequence data. Homogeneous groupings of genetic sequences present new opportunities to understand and align these sequences.
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...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression....
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 a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression....
DEFF Research Database (Denmark)
Sprogøe, Jonas; Elkjaer, Bente
2010-01-01
The purpose of this paper is to explore how induction of newcomers can be understood as both organizational renewal and the maintenance of status quo, and to develop ways of describing this in terms of learning.......The purpose of this paper is to explore how induction of newcomers can be understood as both organizational renewal and the maintenance of status quo, and to develop ways of describing this in terms of learning....
A model of annular linear induction pumps
Energy Technology Data Exchange (ETDEWEB)
Momozaki, Yoichi [Argonne National Lab. (ANL), Argonne, IL (United States)
2016-10-27
The present work explains how the magnetic field and the induced current are obtained when the distributed coils are powered by a 3 phase power supply. From the magnetic field and the induced current, the thrust and the induction losses in the pump can be calculated to estimate the pump performance.
Demonstration Model of Self Inductance Using Relay
Indian Academy of Sciences (India)
2016-05-01
Using an electrical component like a relay, the phenomenonof self inductance caneasily be demonstrated to undergraduatestudents. By wiring simple electrical components like relay,neon bulb and a DC power supply, intermittent backelectromotive force (emf) can be generated in the range from60 to 100 volt. The glowing of neon bulb provides visualevidence for the generation of large back emf due to selfinductance.
SMOOTH TRANSITION LOGISTIC REGRESSION MODEL TREE
RODRIGO PINTO MOREIRA
2008-01-01
Este trabalho tem como objetivo principal adaptar o modelo STR-Tree, o qual é a combinação de um modelo Smooth Transition Regression com Classification and Regression Tree (CART), a fim de utilizá-lo em Classificação. Para isto algumas alterações foram realizadas em sua forma estrutural e na estimação. Devido ao fato de estarmos fazendo classificação de variáveis dependentes binárias, se faz necessária a utilização das técnicas empregadas em Regressão Logística, dessa forma a estimação dos pa...
Realistic Representation of Trees in an Urban Canopy Model
Ryu, Young-Hee; Bou-Zeid, Elie; Wang, Zhi-Hua; Smith, James A.
2016-05-01
A single-layer urban canopy model that captures sub-facet heterogeneity and various hydrological processes is further developed to explicitly incorporate trees within the urban canyon. The physical processes associated with trees are shortwave/longwave radiation exchange, including mutual interception and shading by trees and buildings and multiple reflections, sensible heat and latent heat (through transpiration) exchange, and root water uptake. A computationally-efficient geometric approach is applied to the radiation exchanges, requiring a priori knowledge of view factors. These view factors are first obtained from independent Monte Carlo ray-tracing simulations, and subsequently simple relations, which are functions of canyon aspect ratio and tree-crown ratio, are proposed to estimate them. The developed model is evaluated against field observations at two urban sites and one suburban site, showing improved performance for latent heat flux compared to the previous version that only includes ground vegetation. The trees in the urban canopy act to considerably decrease sensible heat flux and increase latent heat flux, and these effects are found to be more significant in the more dense urban site. Sensitivity tests are then performed to examine the effects of tree geometry relative to canyon geometry. The results indicate that the tree-crown size relative to canyon width is the most influential parameter to decrease sensible heat flux and increase latent heat flux, resulting in cooling of the urban area.
AIRWAY LABELING USING A HIDDEN MARKOV TREE MODEL
Ross, James C.; Díaz, Alejandro A.; Okajima, Yuka; Wassermann, Demian; Washko, George R.; Dy, Jennifer; San José Estépar, Raúl
2014-01-01
We present a novel airway labeling algorithm based on a Hidden Markov Tree Model (HMTM). We obtain a collection of discrete points along the segmented airway tree using particles sampling [1] and establish topology using Kruskal’s minimum spanning tree algorithm. Following this, our HMTM algorithm probabilistically assigns labels to each point. While alternative methods label airway branches out to the segmental level, we describe a general method and demonstrate its performance out to the subsubsegmental level (two generations further than previously published approaches). We present results on a collection of 25 computed tomography (CT) datasets taken from a Chronic Obstructive Pulmonary Disease (COPD) study. PMID:25436039
Modeling and Testing Landslide Hazard Using Decision Tree
Directory of Open Access Journals (Sweden)
Mutasem Sh. Alkhasawneh
2014-01-01
Full Text Available This paper proposes a decision tree model for specifying the importance of 21 factors causing the landslides in a wide area of Penang Island, Malaysia. These factors are vegetation cover, distance from the fault line, slope angle, cross curvature, slope aspect, distance from road, geology, diagonal length, longitude curvature, rugosity, plan curvature, elevation, rain perception, soil texture, surface area, distance from drainage, roughness, land cover, general curvature, tangent curvature, and profile curvature. Decision tree models are used for prediction, classification, and factors importance and are usually represented by an easy to interpret tree like structure. Four models were created using Chi-square Automatic Interaction Detector (CHAID, Exhaustive CHAID, Classification and Regression Tree (CRT, and Quick-Unbiased-Efficient Statistical Tree (QUEST. Twenty-one factors were extracted using digital elevation models (DEMs and then used as input variables for the models. A data set of 137570 samples was selected for each variable in the analysis, where 68786 samples represent landslides and 68786 samples represent no landslides. 10-fold cross-validation was employed for testing the models. The highest accuracy was achieved using Exhaustive CHAID (82.0% compared to CHAID (81.9%, CRT (75.6%, and QUEST (74.0% model. Across the four models, five factors were identified as most important factors which are slope angle, distance from drainage, surface area, slope aspect, and cross curvature.
Induction and direct resistance heating theory and numerical modeling
Lupi, Sergio; Aliferov, Aleksandr
2015-01-01
This book offers broad, detailed coverage of theoretical developments in induction and direct resistance heating and presents new material on the solution of problems in the application of such heating. The physical basis of induction and conduction heating processes is explained, and electromagnetic phenomena in direct resistance and induction heating of flat workpieces and cylindrical bodies are examined in depth. The calculation of electrical and energetic characteristics of induction and conduction heating systems is then thoroughly reviewed. The final two chapters consider analytical solutions and numerical modeling of problems in the application of induction and direct resistance heating, providing industrial engineers with the knowledge needed in order to use numerical tools in the modern design of installations. Other engineers, scientists, and technologists will find the book to be an invaluable reference that will assist in the efficient utilization of electrical energy.
Choosing appropriate subpopulations for modeling tree canopy cover nationwide
Gretchen G. Moisen; John W. Coulston; Barry T. Wilson; Warren B. Cohen; Mark V. Finco
2012-01-01
In prior national mapping efforts, the country has been divided into numerous ecologically similar mapping zones, and individual models have been constructed for each zone. Additionally, a hierarchical approach has been taken within zones to first mask out areas of nonforest, then target models of tree attributes within forested areas only. This results in many models...
Modeling Dynamic Height and Crown Growth in Trees
Franklin, O.; Fransson, P.; Brännström, Å.
2015-12-01
Previously we have shown how principles based on productivity maximization (e.g. maximization of net primary production, net growth maximization, or functional balance) can explain allocation responses to resources, such as nutrients and light (Franklin et al., 2012). However, the success of these approaches depend on how well they align with the ultimate driver of plant behavior, fitness, or life time reproductive success. Consequently, they may not fully explain how allocation changes during the life cycle of trees where not only growth but also survival and reproduction are important. In addition, maximizing instantaneous productivity does not account for path dependence of tree growth. For example, maximizing productivity during early growth in shade may delay emergence in the forest canopy and reduce lifetime fitness compared to a more height oriented strategy. Here we present an approach to model how growth of stem diameter and leaf area in relation to stem height dynamically responds to light conditions in a way that maximizes life-time fitness (rather than instantaneous growth). The model is able to predict growth of trees growing in different types of forests, including trees emerging under a closed canopy and seedlings planted in a clear-cut area. It can also predict the response to sudden changes in the light environment, due to disturbances or harvesting. We envisage two main applications of the model, (i) Modeling effects of forest management, including thinning and planting (ii) Elucidating height growth strategies in trees and how they can be represented in vegetation models. ReferenceFranklin O, Johansson J, Dewar RC, Dieckmann U, McMurtrie RE, Brännström Å, Dybzinski R. 2012. Modeling carbon allocation in trees: a search for principles. Tree Physiology 32(6): 648-666.
Letort, Veronique; Mathieu, Amélie; De Reffye, Philippe; Constant, Thiéry
2010-01-01
Functional-structural models provide detailed representations of tree growth and their application to forestry seems full of prospects. However, owing to the complexity of tree architecture, parametric identification of such models remains a critical issue. We present the GreenLab approach for modelling tree growth. It simulates tree growth plasticity in response to changes of their internal level of trophic competition, especially topological development and cambial growth. The model includes a simplified representation of tree architecture, based on a species-specific description of branching patterns. We study whether those simplifications allow enough flexibility to reproduce with the same set of parameters the growth of two observed understorey beech trees (Fagus sylvatica L.) of different ages in different environmental conditions. The parametric identification of the model is global, i.e. all parameters are estimated simultaneously, potentially providing a better description of interactions between sub...
Biomass models to estimate carbon stocks for hardwood tree species
Energy Technology Data Exchange (ETDEWEB)
Ruiz-Peinado, R.; Montero, G.; Rio, M. del
2012-11-01
To estimate forest carbon pools from forest inventories it is necessary to have biomass models or biomass expansion factors. In this study, tree biomass models were developed for the main hardwood forest species in Spain: Alnus glutinosa, Castanea sativa, Ceratonia siliqua, Eucalyptus globulus, Fagus sylvatica, Fraxinus angustifolia, Olea europaea var. sylvestris, Populus x euramericana, Quercus canariensis, Quercus faginea, Quercus ilex, Quercus pyrenaica and Quercus suber. Different tree biomass components were considered: stem with bark, branches of different sizes, above and belowground biomass. For each species, a system of equations was fitted using seemingly unrelated regression, fulfilling the additivity property between biomass components. Diameter and total height were explored as independent variables. All models included tree diameter whereas for the majority of species, total height was only considered in the stem biomass models and in some of the branch models. The comparison of the new biomass models with previous models fitted separately for each tree component indicated an improvement in the accuracy of the models. A mean reduction of 20% in the root mean square error and a mean increase in the model efficiency of 7% in comparison with recently published models. So, the fitted models allow estimating more accurately the biomass stock in hardwood species from the Spanish National Forest Inventory data. (Author) 45 refs.
Theory-based Bayesian models of inductive learning and reasoning.
Tenenbaum, Joshua B; Griffiths, Thomas L; Kemp, Charles
2006-07-01
Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction emphasize either the power of statistical learning, or the importance of strong constraints from structured domain knowledge, intuitive theories or schemas. We argue that both components are necessary to explain the nature, use and acquisition of human knowledge, and we introduce a theory-based Bayesian framework for modeling inductive learning and reasoning as statistical inferences over structured knowledge representations.
Henri Epstein
2016-01-01
An algebraic formalism, developed with V. Glaser and R. Stora for the study of the generalized retarded functions of quantum field theory, is used to prove a factorization theorem which provides a complete description of the generalized retarded functions associated with any tree graph. Integrating over the variables associated to internal vertices to obtain the perturbative generalized retarded functions for interacting fields arising from such graphs is shown to be possible for a large cate...
Epstein, Henri
2016-01-01
An algebraic formalism, developped with V. Glaser and R. Stora for the study of the generalized retarded functions of quantum field theory, is used to prove a factorization theorem which provides a complete description of the generalized retarded functions associated with any tree graph. Integrating over the variables associated to internal vertices to obtain the perturbative generalized retarded functions for interacting fields arising from such graphs is shown to be possible for a large cat...
Epstein, Henri
2016-01-01
An algebraic formalism, developped with V.~Glaser and R.~Stora for the study of the generalized retarded functions of quantum field theory, is used to prove a factorization theorem which provides a complete description of the generalized retarded functions associated with any tree graph. Integrating over the variables associated to internal vertices to obtain the perturbative generalized retarded functions for interacting fields arising from such graphs is shown to be possible for a large category of space-times.
Runtime Optimizations for Tree-Based Machine Learning Models
N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)
2014-01-01
htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression
Fruit tree model for uptake of organic compounds from soil
DEFF Research Database (Denmark)
Trapp, Stefan; Rasmussen, D.; Samsoe-Petersen, L.
2003-01-01
soils, regressions or models are in use, which were not intended to be used for tree fruits. A simple model for uptake of neutral organic contaminants into fruits is developed. It considers xylem and phloem transport to fruits through the stem. The mass balance is solved for the steady...
Directory of Open Access Journals (Sweden)
Stefanie M. Herrmann
2013-10-01
Full Text Available Field trees are an integral part of the farmed parkland landscape in West Africa and provide multiple benefits to the local environment and livelihoods. While field trees have received increasing interest in the context of strengthening resilience to climate variability and change, the actual extent of farmed parkland and spatial patterns of tree cover are largely unknown. We used the rule-based predictive modeling tool Cubist® to estimate field tree cover in the west-central agricultural region of Senegal. A collection of rules and associated multiple linear regression models was constructed from (1 a reference dataset of percent tree cover derived from very high spatial resolution data (2 m Orbview as the dependent variable, and (2 ten years of 10-day 250 m Moderate Resolution Imaging Spectrometer (MODIS Normalized Difference Vegetation Index (NDVI composites and derived phenological metrics as independent variables. Correlation coefficients between modeled and reference percent tree cover of 0.88 and 0.77 were achieved for training and validation data respectively, with absolute mean errors of 1.07 and 1.03 percent tree cover. The resulting map shows a west-east gradient from high tree cover in the peri-urban areas of horticulture and arboriculture to low tree cover in the more sparsely populated eastern part of the study area. A comparison of current (2000s tree cover along this gradient with historic cover as seen on Corona images reveals dynamics of change but also areas of remarkable stability of field tree cover since 1968. The proposed modeling approach can help to identify locations of high and low tree cover in dryland environments and guide ground studies and management interventions aimed at promoting the integration of field trees in agricultural systems.
Mathematical models applied in inductive non-destructive testing
Energy Technology Data Exchange (ETDEWEB)
Wac-Wlodarczyk, A.; Goleman, R.; Czerwinski, D. [Technical University of Lublin, 20 618 Lublin, Nadbystrzycka St 38a (Poland); Gizewski, T. [Technical University of Lublin, 20 618 Lublin, Nadbystrzycka St 38a (Poland)], E-mail: t.gizewski@pollub.pl
2008-10-15
Non-destructive testing are the wide group of investigative methods of non-homogenous material. Methods of computer tomography, ultrasonic, magnetic and inductive methods still developed are widely applied in industry. In apparatus used for non-destructive tests, the analysis of signals is made on the basis of complex system answers. The answer is linearized due to the model of research system. In this paper, the authors will discuss the applications of the mathematical models applied in investigations of inductive magnetic materials. The statistical models and other gathered in similarity classes will be taken into consideration. Investigation of mathematical models allows to choose the correct method, which in consequence leads to precise representation of the inner structure of examined object. Inductive research of conductive media, especially those with ferromagnetic properties, are run with high frequency magnetic field (eddy-currents method), which considerably decrease penetration depth.
Enhanced Simulink Induction Motor Model for Education and Maintenance Training
Directory of Open Access Journals (Sweden)
Manuel Pineda-Sanchez
2012-04-01
Full Text Available The training of technicians in maintenance requires the use of signals produced by faulty machines in different operating conditions, which are difficult to obtain either from the industry or through destructive testing. Some tasks in electricity and control courses can also be complemented by an interactive induction machine model having a wider internal parameter configuration. This paper presents a new analytical model of induction machine under fault, which is able to simulate induction machines with rotor asymmetries and eccentricity in different load conditions, both stationary and transient states and yielding magnitudes such as currents, speed and torque. This model is faster computationally than the traditional method of simulating induction machine faults based on the Finite Element Method and also than other analytical models due to the rapid calculation of the inductances. The model is presented in Simulink by Matlab for the comprehension and interactivity with the students or lecturers and also to allow the easy combination of the effect of the fault with external influences, studying their consequences on a determined load or control system. An associated diagnosis tool is also presented.
Modeling tree crown dynamics with 3D partial differential equations.
Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry
2014-01-01
We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
Modeling Tree Crown Dynamics with 3D Partial Differential Equations
Directory of Open Access Journals (Sweden)
Robert eBeyer
2014-07-01
Full Text Available We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth towards light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
Modelling of Parasitic Inductances of a High Precision Inductive Adder for CLIC
Holma, J; Ovaska, S J
2013-01-01
The CLIC study is exploring the scheme for an electron-positron collider with high luminosity and a nominal centre-of-mass energy of 3 TeV. The CLIC pre-damping rings and damping rings will produce, through synchrotron radiation, ultra-low emittance beam with high bunch charge. To avoid beam emittance increase, the damping ring kicker systems must provide extremely flat, high-voltage, pulses. The specifications for the extraction kickers of the DRs are particularly demanding: the flat-top of the pulses must be ±12.5 kV with a combined ripple and droop of not more than ±0.02 % (±2.5 V). An inductive adder is a very promising approach to meeting the specifications. However, the output impedance of the inductive adder needs to be well matched to the system impedance. The primary leakage inductance, which cannot be computed accurately analytically, has a significant effect upon the output impedance of the inductive adder. This paper presents predictions, obtained by modelling the 3D geometry of the adder struc...
Simulink Implementation of Indirect Vector Control of Induction Machine Model
Directory of Open Access Journals (Sweden)
V. Dhanunjayanaidu
2014-04-01
Full Text Available In this paper, a modular Simulink implementation of an induction machine model is described in a step-by-step approach. With the modular system, each block solves one of the model equations; therefore, unlike in black box models, all of the machine parameters are accessible for control and verification purposes.After the implementation, examples are given with the model used in different drive applications, such as open-loop constant V/Hz control and indirect vector control. To implement the induction machine model, the dynamic equivalent circuit of induction motor is taken and the model equations in flux linkage form are derived.Then the model is implemented in Simulink by transforming three phase voltages to d-q frame and the d-q currents back to three phase, also it includes unit vector calculation and induction machine d-q model.The inputs here are three phase voltages, load torque, speed of stator and the outputs are flux linkages and currents, electrical torque and speed of rotor.
Directory of Open Access Journals (Sweden)
M. Jung
2009-05-01
Full Text Available Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET. We present a new model TRee Induction ALgorithm (TRIAL that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time.
We evaluate the efficiency of the model tree ensemble approach using an artificial data set derived from the the Lund-Potsdam-Jena managed Land (LPJmL biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the model tree ensemble upscaling and associated problems of extrapolation capacity.
We show that the model tree ensemble is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively while the monthly interannual anomalies which occupy
Institute of Scientific and Technical Information of China (English)
DuLi; Zhou Suo; Bao Man-zhu
2007-01-01
A description of a successful direct somatic embryogenesis induction from immature zygotic embryos of a camphor tree (Cinnamomum camphora L. ) is presented. After a subculture of 2-3 years,embryogenic calli could be derived from primary somaticembryos. Immature zygotic embryos were cultured on a Murashige and Skoog (MS)basal medium supplemented with a range of combinations of cytokinins (BA) and auxins(2,4-D or NAA) for somatic embryo induction. Primary somatic embryos could be induced direly in almost all PGR combinations. A positive effect of 2,4-D On somatic embryo genesis from immature zygotic embryos of camphor tree was obtained. BA at appropriate concentrations (5mg·L-1) of BA had the effect of restraining somatic embryo induction. NAA had a less positive effect on somatic embryogenesis than 2,4-D.
Generating Counterexamples for Structural Inductions by Exploiting Nonstandard Models
Blanchette, Jasmin Christian; Claessen, Koen
Induction proofs often fail because the stated theorem is noninductive, in which case the user must strengthen the theorem or prove auxiliary properties before performing the induction step. (Counter)model finders are useful for detecting non-theorems, but they will not find any counterexamples for noninductive theorems. We explain how to apply a well-known concept from first-order logic, nonstandard models, to the detection of noninductive invariants. Our work was done in the context of the proof assistant Isabelle/HOL and the counterexample generator Nitpick.
Free energies of the Potts model on a Cayley tree
Rozikov, U. A.; Rakhmatullaev, M. M.
2017-01-01
For the Potts model on the Cayley tree, we obtain some explicit formulas for the free energies and entropies in the case of vector-valued boundary conditions. These formulas include translation-invariant, periodic, and Dobrushin-like boundary conditions and also those corresponding to weakly periodic Gibbs measures.
Towards Effective Elicitation of NIN-AND Tree Causal Models
Xiang, Yang; Li, Yu; Zhu, Zoe Jingyu
To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs assessed for each node. It generally has the complexity exponential on n. Noisy-OR reduces the complexity to linear, but can only represent reinforcing causal interactions. The non-impeding noisy-AND (NIN-AND) tree is the first causal model that explicitly expresses reinforcement, undermining, and their mixture. It has linear complexity, but requires elicitation of a tree topology for types of causal interactions. We study their topology space and develop two novel techniques for more effective elicitation.
Incorporating inductances in tissue-scale models of cardiac electrophysiology
Rossi, Simone; Griffith, Boyce E.
2017-09-01
In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and we examine the effect of intracellular and extracellular inductances on the virtual electrode phenomenon.
Modeling of thermal processes in waveguide tracts induction soldering
Murygin, A. V.; Tynchenko, V. S.; Laptenok, V. D.; Emilova, O. A.; Seregin, Yu N.
2017-02-01
The problem solving of the induction heating models development, which describe the heating of the separate structural assembly components of the waveguide path and product generally, is presented in this paper. Proposed mathematical models are based on the thermodynamics equation and on the heat balance law. The system of the heating process mathematical models, such as surge tube and flange heating, and the mathematical model of the energy distribution are presented. During the modeling process with Matlab system by using mathematical models graphs of the tube, flange and coupling heating were obtained. These design charts are confirmed by the results of the experimental study. During the experimental studies pyrometers for temperature control and a video camera for visual control of the process parameters were used. On the basis of obtained models the induction soldering process features analysis is carried out and the need of its automation by the using of the information control systems for thermal management between the connection elements is revealed.
Empirical genome evolution models root the tree of life.
Harish, Ajith; Kurland, Charles G
2017-07-01
A reliable phylogenetic reconstruction of the evolutionary history of contemporary species depends on a robust identification of the universal common ancestor (UCA) at the root of the Tree of Life (ToL). That root polarizes the tree so that the evolutionary succession of ancestors to descendants is discernable. In effect, the root determines the branching order and the direction of character evolution. Typically, conventional phylogenetic analyses implement time-reversible models of evolution for which character evolution is un-polarized. Such practices leave the root and the direction of character evolution undefined by the data used to construct such trees. In such cases, rooting relies on theoretic assumptions and/or the use of external data to interpret unrooted trees. The most common rooting method, the outgroup method is clearly inapplicable to the ToL, which has no outgroup. Both here and in the accompanying paper (Harish and Kurland, 2017) we have explored the theoretical and technical issues related to several rooting methods. We demonstrate (1) that Genome-level characters and evolution models are necessary for species phylogeny reconstructions. By the same token, standard practices exploiting sequence-based methods that implement gene-scale substitution models do not root species trees; (2) Modeling evolution of complex genomic characters and processes that are non-reversible and non-stationary is required to reconstruct the polarized evolution of the ToL; (3) Rooting experiments and Bayesian model selection tests overwhelmingly support the earlier finding that akaryotes and eukaryotes are sister clades that descend independently from UCA (Harish and Kurland, 2013); (4) Consistent ancestral state reconstructions from independent genome samplings confirm the previous finding that UCA features three fourths of the unique protein domain-superfamilies encoded by extant genomes. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie
Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E
2017-03-01
Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R (2) of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.
Jung, M.; Reichstein, M.; Bondeau, A.
2009-10-01
Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998-2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained
The Induction of Root Formation by Urea, IBA and Sheep Dung in Young Apple Tree
Institute of Scientific and Technical Information of China (English)
YANG Hong-qiang; JIE Yu-ling; HUANG Tian-dong; SHU Huai-rui
2002-01-01
The effect of plant growth substance and fertilizer on root formation was studied in a newly planted apple tree (Malus pumila Mill / Malus hupenensis Rhed). The results indicated that urea and IBA (indole butyric acid) and sheep dung all increased the total number and activity of new roots and changed the ratio of absorbing root to extensive roots obviously. Urea increased the number of extensive root and decreased the ratio of the root to shoot mostly. IBA lengthened the extensive root and increased the ratio of root to shoot obviously. Sheep dung increased the nu mber of absorbing root and increased the ratio of absorbing root to ex-tensive root, divided new root into many branches, increased the fresh weight of the root and thickened the extensive root. The fresh weight of root increased and the ratio of root to shoot declined after urea was added to sheep dung. Both the ratio of absorbing root to extensive root and root fresh weight was increased after IBA was added to sheep dung, then the ratio of root to shoot had no change obviously.
A CAD model for the inductive strip in finline
Knorr, Jeffrey B.
1988-01-01
This report describes a CAD compatible circuit model for an inductive strip centered in f inline with W/b=E r2 =1 . The circuit model is shown to predict, strip scattering coefficients which agree closly with those measured experimentally in X-band. By application of the scaling principle the model is generalized for use with any waveguide size over the normal frequency range for the dominant TE 10 mode. Prepared for: Naval Postgraduate School Monterey, CA http://archive.o...
Decision Tree Model for Non-Fatal Road Accident Injury
Directory of Open Access Journals (Sweden)
Fatin Ellisya Sapri
2017-02-01
Full Text Available Non-fatal road accident injury has become a great concern as it is associated with injury and sometimes leads to the disability of the victims. Hence, this study aims to develop a model that explains the factors that contribute to non-fatal road accident injury severity. A sample data of 350 non-fatal road accident cases of the year 2016 were obtained from Kota Bharu District Police Headquarters, Kelantan. The explanatory variables include road geometry, collision type, accident time, accident causes, vehicle type, age, airbag, and gender. The predictive data mining techniques of decision tree model and multinomial logistic regression were used to model non-fatal road accident injury severity. Based on accuracy rate, decision tree with CART algorithm was found to be more accurate as compared to the logistic regression model. The factors that significantly contribute to non-fatal traffic crashes injury severity are accident cause, road geometry, vehicle type, age and collision type.
Multitask Efficiencies in the Decision Tree Model
Drucker, Andrew
2008-01-01
In Direct Sum problems [KRW], one tries to show that for a given computational model, the complexity of computing a collection $F = \\{f_i\\}$ of functions on independent inputs is approximately the sum of their individual complexities. In this paper, by contrast, we study the diversity of ways in which the joint computational complexity can behave when all the $f_i$ are evaluated on a \\textit{common} input. Fixing some model of computational cost, let $C_F(X): \\{0, 1\\}^l \\to \\mathbf{R}$ give the cost of computing the subcollection $\\{f_i(x): X_i = 1\\}$, on common input $x$. What constraints do the functions $C_F(X)$ obey, when $F$ is chosen freely? $C_F(X)$ will, for reasonable models, obey nonnegativity, monotonicity, and subadditivity. We show that, in the deterministic, adaptive query model, these are `essentially' the only constraints: for any function $C(X)$ obeying these properties and any $\\epsilon > 0$, there exists a family $F$ of boolean functions and a $T > 0$ such that for all $X \\in \\{0, 1\\}^l$, \\...
Modeling Induction Motor Imbalances: A Non-DQ Approach
DEFF Research Database (Denmark)
Armah, Kabenla; Jouffroy, Jerome; Duggen, Lars
2016-01-01
This paper gives a study into the development of a generalized model for a three-phase induction motor that offers flexibility of simulating balanced and unbalanced parameter scenarios. By analyzing the interaction of forces within the motor, we achieve our main objective of deriving the system...
PKind: A parallel k-induction based model checker
Kahsai, Temesghen; 10.4204/EPTCS.72.6
2011-01-01
PKind is a novel parallel k-induction-based model checker of invariant properties for finite- or infinite-state Lustre programs. Its architecture, which is strictly message-based, is designed to minimize synchronization delays and easily accommodate the incorporation of incremental invariant generators to enhance basic k-induction. We describe PKind's functionality and main features, and present experimental evidence that PKind significantly speeds up the verification of safety properties and, due to incremental invariant generation, also considerably increases the number of provable ones.
Spherical Model on a Cayley Tree: Large Deviations
Patrick, A. E.
2017-01-01
We study the spherical model of a ferromagnet on a Cayley tree and show that in the case of empty boundary conditions a ferromagnetic phase transition takes place at the critical temperature T_c =6√{2}/5J, where J is the interaction strength. For any temperature the equilibrium magnetization, m_n, tends to zero in the thermodynamic limit, and the true order parameter is the renormalized magnetization r_n=n^{3/2}m_n, where n is the number of generations in the Cayley tree. Below T_c, the equilibrium values of the order parameter are given by ± ρ ^*, where ρ ^*=2π /(√{2-1)^2}√{1-T/T_c}. One more notable temperature in the model is the penetration temperature T_p=J/W_Cayley(3/2)( 1-1/√{2}( h/2J) ^2) . Below T_p the influence of homogeneous boundary field of magnitude h penetrates throughout the tree. The main new technical result of the paper is a complete set of orthonormal eigenvectors for the discrete Laplace operator on a Cayley tree.
Regional Mapping, Modelling, and Monitoring of Tree Aboveground Biomass Carbon
Hudak, Andrew
2016-04-01
Airborne lidar collections are preferred for mapping aboveground biomass carbon (AGBC), while historical Landsat imagery are preferred for monitoring decadal scale forest cover change. Our modelling approach tracks AGBC change regionally using Landsat time series metrics; training areas are defined by airborne lidar extents within which AGBC is accurately mapped with high confidence. Geospatial topographic and climate layers are also included in the predictive model. Validation is accomplished using systematically sampled Forest Inventory and Analysis (FIA) plot data that have been independently collected, processed and summarized at the county level. Our goal is to demonstrate that spatially and temporally aggregated annual AGBC map predictions show no bias when compared to annual county-level summaries across the Northwest USA. A prominent source of bias is trees outside forest; much of the more arid portions of our study area meet the FIA definition of non-forest because the tree cover does not exceed their minimum tree cover threshold. We employ detailed tree cover maps derived from high-resolution aerial imagery to extend our AGBC predictions into non-forest areas. We also employ Landsat-derived annual disturbance maps into our mapped AGBC predictions prior to aggregation and validation.
Robust linear parameter varying induction motor control with polytopic models
Directory of Open Access Journals (Sweden)
Dalila Khamari
2013-01-01
Full Text Available This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.
A Model of Induction for Specialised Residential Care
Directory of Open Access Journals (Sweden)
Ann McWilliams
2006-01-01
Full Text Available The Social Care Education and Training Project at the Dublin Institute of Technology is a four year project funded by the Department of Health and Children. The project has increased the number of students enrolled in social care courses at the Institute and delivers Continued Professional Development courses for workers in the specialised residential units. The article describes an induction model developed and delivered by the project team to new workers in the specialised residential units in the Dublin region although the course is suitable for all residential care settings. The evaluation suggests that the majority of participants found the induction module worthwhile because it had a positive effect on their professional practice and increased their self confidence. This supports the need for formal induction training for all new workers to ensure they perform their professional duties effectively as possible in their new working environment.
Modeling synchronized calling behavior of Japanese tree frogs
Aihara, Ikkyu
2009-07-01
We experimentally observed synchronized calling behavior of male Japanese tree frogs Hyla japonica; namely, while isolated single frogs called nearly periodically, a pair of interacting frogs called synchronously almost in antiphase or inphase. In this study, we propose two types of phase-oscillator models on different degrees of approximations, which can quantitatively explain the phase and frequency properties in the experiment. Moreover, it should be noted that, although the second model is obtained by fitting to the experimental data of the two synchronized states, the model can also explain the transitory dynamics in the interactive calling behavior, namely, the shift from a transient inphase state to a stable antiphase state. We also discuss the biological relevance of the estimated parameter values to calling behavior of Japanese tree frogs and the possible biological meanings of the synchronized calling behavior.
Dimensional Reduction for the General Markov Model on Phylogenetic Trees.
Sumner, Jeremy G
2017-03-01
We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.
Preliminary proteomics analysis of the total proteins of flower bud induction of apple trees
Institute of Scientific and Technical Information of China (English)
Shangyin CAO; Qiuming ZHANG; Zhiyong ZHU; Junying GUO; Yuling CHEN; Huabai XUE
2008-01-01
Apple is one of the most important fruit trees in the world. Nevertheless, mainly due to its long juvenile period, its breeding work constantly falls far behind other crops. So the aim of this study is to reveal the mechanism of apple flower bud differentiation, shorten the juvenile period and accelerate its breeding process. Proteomics technology (including two-dimensional gel electrophor-esis (2-DE), biomass spectrometry and bioinformatics) was applied to work on the specific protein of flower bud and leaf bud after the brachyblasts of 'Fuji' stopped growth for 3-9 weeks. The results showed that the mor-phodifferentiation of flower bud did not begin until the seventh week after the brachyblast stopped growth. Furthermore, compared with the leaf bud, flower bud had significant changes in the expression of 283 protein spots in quality and quantity on 2-DE maps. Among the 283 protein spots, four protein spots (16.4, 30.2, 40.3 and 65.1 kD) were characteristic of the flower bud in the archae-stage (initial inflorescence appeared) at the begin-ning of flower-bud differentiation, three (39.3, 60.2 and 66.3 kD) in the post-stage (Lateral-flower appears) and one (77.1 kD) in the sepal stage on 2-DE maps. Analysis by peptide mass fingerprinting and matrix-assisted laser desorption ionization time of flight mass spectrometry also identified and forecasted functionally by blasting dif-ferent databases. In the four specific proteins, it was found that spots No. 256 (16.4 kD) and 298 (30.2 kD) were unknown proteins, spot Nos. 327 (40.3 kD) was identified as the synthesis enzyme protein and spot No. 367 (40.3 kD) was identified as a RNA-binding protein involved in transcription. When flower bud started to dif-ferentiate morphologically, we detected four specific pro-teins which were 16.4, 30.2, 40.3 and 65.1 kD. Three specific proteins 39.3, 60.2 and 66.3 kD were observed at side flower-appearing stage. When calyx began to emerge, there was one specific protein: 77.1 kD. The
Ripe Fuji Apple Detection Model Analysis in Natural Tree Canopy
Directory of Open Access Journals (Sweden)
Dongjian He
2012-11-01
Full Text Available In this work we develop a novel approach for the automatic recognition of red Fuji apples within a tree canopy using three distinguishable color models in order to achieve automated harvesting. How to select the recognition model is important for the certain intelligent harvester employed to perform in real orchards. The L*a*b color model, HSI (Hue, Saturation and Intensity color model and LCD color difference model, which are insensitive to light conditions, are analyzed and applied to detect the fruit under the different lighting conditions because the fruit has the highest red color among the objects in the image. The fuzzy 2-partition entropy, which could discriminate the object and the background in grayscale images and is obtained from the histogram, is applied to the segment the Fuji apples under complex backgrounds. A series of mathematical morphological operations are used to eliminate segmental fragments after segmentation. Finally, the proposed approach is validated on apple images taken in natural tree canopies. A contribution reported in this work, is the voting scheme added to the natural tree canopy which recognizes apples under different light influences.
Shaltout, Abdallah A; Khoder, M I; El-Abssawy, A A; Hassan, S K; Borges, Daniel L G
2013-07-01
This work aims at monitoring the rare earth elements (REEs) and Th in dust deposited on tree leaves collected inside and outside Greater Cairo (GC), Egypt. Inductively coupled plasma mass spectrometry (ICP-MS) was employed. The concentration of REEs in the collected dust samples was found to be in the range from 1 to 60 μg g(-1). The highest concentration of REEs was found in dust samples collected outside GC, in the middle of the Nile Delta. This would refer to the availability of black sands, due to desert wind occurrence during the sample collection, and anthropogenic activities. The limits of detection of the REEs ranged from 0.02 ng g(-1) for Tm to 3 ng g(-1) for Yb. There was an obvious variation in the concentration of REEs inside and outside GC due to variations of natural and anthropogenic sources. Strong correlations among all the REEs were found.
Directory of Open Access Journals (Sweden)
Jörgen Wallerman
2013-04-01
Full Text Available Individual tree crowns may be delineated from airborne laser scanning (ALS data by segmentation of surface models or by 3D analysis. Segmentation of surface models benefits from using a priori knowledge about the proportions of tree crowns, which has not yet been utilized for 3D analysis to any great extent. In this study, an existing surface segmentation method was used as a basis for a new tree model 3D clustering method applied to ALS returns in 104 circular field plots with 12 m radius in pine-dominated boreal forest (64°14'N, 19°50'E. For each cluster below the tallest canopy layer, a parabolic surface was fitted to model a tree crown. The tree model clustering identified more trees than segmentation of the surface model, especially smaller trees below the tallest canopy layer. Stem attributes were estimated with k-Most Similar Neighbours (k-MSN imputation of the clusters based on field-measured trees. The accuracy at plot level from the k-MSN imputation (stem density root mean square error or RMSE 32.7%; stem volume RMSE 28.3% was similar to the corresponding results from the surface model (stem density RMSE 33.6%; stem volume RMSE 26.1% with leave-one-out cross-validation for one field plot at a time. Three-dimensional analysis of ALS data should also be evaluated in multi-layered forests since it identified a larger number of small trees below the tallest canopy layer.
Extraction method for parasitic capacitances and inductances of HEMT models
Zhang, HengShuang; Ma, PeiJun; Lu, Yang; Zhao, BoChao; Zheng, JiaXin; Ma, XiaoHua; Hao, Yue
2017-03-01
A new method to extract parasitic capacitances and inductances for high electron-mobility transistors (HEMTs) is proposed in this paper. Compared with the conventional extraction method, the depletion layer is modeled as a physically significant capacitance model and the extrinsic values obtained are much closer to the actual results. In order to simulate the high frequency behaviour with higher precision, series parasitic inductances are introduced into the cold pinch-off model which is used to extract capacitances at low frequency and the reactive elements can be determined simultaneously over the measured frequency range. The values obtained by this method can be used to establish a 16-elements small-signal equivalent circuit model under different bias conditions. The results show good agreements between the simulated and measured scattering parameters up to 30 GHz.
Modelling of windmill induction generators in dynamic simulation programs
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
. It is shown that it is possible to include a transient model in dynamic stability programs and thus obtain correct results also in dynamic stability programs. A mechanical model of the shaft system has also been included in the generator model...... with and without a model of the mechanical shaft. The reason for the discrepancies are explained, and it is shown that the phenomenon is due partly to the presence of DC offset currents in the induction machine stator, and partly to the mechanical shaft system of the wind turbine and the generator rotor......For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectively...
Modeling of a Stacked Power Module for Parasitic Inductance Extraction
2017-09-15
ARL-TR-8138 ● SEP 2017 US Army Research Laboratory Modeling of a Stacked Power Module for Parasitic Inductance Extraction by...not return it to the originator. ARL-TR-8138 ● SEP 2017 US Army Research Laboratory Modeling of a Stacked Power Module for...aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if
[A depression model of social defeat etiology using tree shrews].
Wang, Jing; Zhou, Qi-Xin; Lv, Long-Bao; Xu, Lin; Yang, Yue-Xiong
2012-02-01
Depression is a common neuropsychiatric disorder, marked by depressed mood for at least two weeks. The World Health Organization predicts that depression will be the number one leading cause of disease and injury burden by 2030. Clinical treatment faces at least three serious obstacles. First, the disease mechanism is not fully understood and thus there are no effective ways to predict and prevent depression and no biological method of diagnosis. Second, available antidepressants are based on monoamine mechanisms that commonly have a long delay of action and possibly cause a higher risk of suicide. Third, no other antidepressant mechanisms are available, with fast action and few side effects. Unfortunately, several decades of research based on rodent models of depression have not been successful in resolving these problems, at least partially due to the huge differences in brain function between rodents and people. Tree shrews are the closest sister to primates, and brain functions in these species are closer to those of humans. In this review, we discuss a tree shrew model of depression with social defeat etiology and aspects of construct, face and predicted validity of an animal model. Although a tree shrew model of depression has long been ignored and not fully established, its similarities to those aspects of depression in humans may open a new avenue to address this human condition.
Individual Tree Biomass Models for Plantation Grown American Sycamore
Regan B. Willson; Bryce E. Schlaegel; Harvey E. Kennedy
1982-01-01
Individual tree volume and green and dry weight equations are derived for American sycamore from a 5-year-old plantation in southeast Arkansas. Two trees have been destructively sampled each year from each of 20 plots. Observations from 168 trees are used to predict tree weight and volume as a function of dbh, total height, age, and initial number of trees. Separate...
Modeling of power control schemes in induction cooking devices
Beato, Alessio; Conti, Massimo; Turchetti, Claudio; Orcioni, Simone
2005-06-01
In recent years, with remarkable advancements of power semiconductor devices and electronic control systems, it becomes possible to apply the induction heating technique for domestic use. In order to achieve the supply power required by these devices, high-frequency resonant inverters are used: the force commutated, half-bridge series resonant converter is well suited for induction cooking since it offers an appropriate balance between complexity and performances. Power control is a key issue to attain efficient and reliable products. This paper describes and compares four power control schemes applied to the half-bridge series resonant inverter. The pulse frequency modulation is the most common control scheme: according to this strategy, the output power is regulated by varying the switching frequency of the inverter circuit. Other considered methods, originally developed for induction heating industrial applications, are: pulse amplitude modulation, asymmetrical duty cycle and pulse density modulation which are respectively based on variation of the amplitude of the input supply voltage, on variation of the duty cycle of the switching signals and on variation of the number of switching pulses. Each description is provided with a detailed mathematical analysis; an analytical model, built to simulate the circuit topology, is implemented in the Matlab environment in order to obtain the steady-state values and waveforms of currents and voltages. For purposes of this study, switches and all reactive components are modelled as ideal and the "heating-coil/pan" system is represented by an equivalent circuit made up of a series connected resistance and inductance.
Modeling of Earth's Gravity Fields Visualization Based on Quad Tree
Institute of Scientific and Technical Information of China (English)
LUO Zhicai; LI Zhenhai; ZHONG Bo
2010-01-01
The problems of the earth's gravity fields' visualization are both focus and puzzle currently. Aiming at multiresolution rendering, modeling of the Earth's gravity fields' data is discussed in the paper by using LOD algorithm based on Quad Tree. First,this paper employed the method of LOD based on Quad Tree to divide up the regional gravity anomaly data, introduced the combined node evaluation system that was composed of viewpoint related and roughness related systems, and then eliminated the T-cracks that appeared among the gravity anomaly data grids with different resolutions. The test results demonstrated that the gravity anomaly data grids' rendering effects were living, and the computational power was low. Therefore, the proposed algorithm was a suitable method for modeling the gravity anomaly data and has potential applications in visualization of the earth's gravity fields.
Alcobendas, Rosalía; Alarcón, Juan José; VALSESIA, Pierre; Génard, Michel; Nicolás, Emilio
2013-01-01
Low water availability has increased the use of regulated deficit irrigation strategies in fruit orchards.However, these water restrictions may have implications on fruit growth and quality. The current paperassesses the suitability of an existing fruit tree model (QualiTree) for describing the effects of water stresson peach fruit growth and quality. The model was parameterised and calibrated for a mid-late maturingpeach cultivar (‘Catherine’). Mean and variability over time of fruit and veg...
Stator Fault Detection in Induction Motors by Autoregressive Modeling
Directory of Open Access Journals (Sweden)
Francisco M. Garcia-Guevara
2016-01-01
Full Text Available This study introduces a novel methodology for early detection of stator short circuit faults in induction motors by using autoregressive (AR model. The proposed algorithm is based on instantaneous space phasor (ISP module of stator currents, which are mapped to α-β stator-fixed reference frame; then, the module is obtained, and the coefficients of the AR model for such module are estimated and evaluated by order selection criterion, which is used as fault signature. For comparative purposes, a spectral analysis of the ISP module by Discrete Fourier Transform (DFT is performed; a comparison of both methodologies is obtained. To demonstrate the suitability of the proposed methodology for detecting and quantifying incipient short circuit stator faults, an induction motor was altered to induce different-degree fault scenarios during experimentation.
Modeling of induction motors considering the thermal effect
Energy Technology Data Exchange (ETDEWEB)
Moreno, J.F. [Universidad de Jaen, Departemento de Ingenieria Electrica, Linares (Spain); Vargas Merino, F.; Perez Hidalgo, F.M. [Universidad de Malaga. Departamento de Ingenieria Electrica, Malaga (Spain)
2000-08-01
This paper presents a study about the thermal behaviour of a 3-phase induction machine and proposes a mathematical model with two differential equations. The parameters that implement these equations are obtained by experimental test with the motor. The model allows to know the temperatures and the updated values of the stator and rotor electric resistances. After that, a new system of vector control in oriented field coordinates is defined for the machine; it permits to estimate the reference to the spaces phasor with a better precision. The study and the tests have been realized with a phase squirrel cage induction motor of 380 V, 50 Hz and 1Kw of nominal values. To verify the validity of the hypothesis and the mode proposed, the complete system is simulated using the SIMULINK programme. (orig.)
Model-Based Design of Tree WSNs for Decentralized Detection.
Tantawy, Ashraf; Koutsoukos, Xenofon; Biswas, Gautam
2015-08-20
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.
Model-Based Design of Tree WSNs for Decentralized Detection
Directory of Open Access Journals (Sweden)
Ashraf Tantawy
2015-08-01
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.
Inductive Voltage Adder Network Analysis and Model Simplification
2007-06-01
ORGANIZATION NAME(S) AND ADDRESS(ES) Brookhaven National Laboratory Upton, NY 11973 USA 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/ MONITORING ... Kicker Pulser for DARHT-II”, Proceedings of the 20th International LINAC Conference, pp. 509-511, 2000. [4] Wang, G. J. Caporaso, E. G. Cook...Modeling of an Inductive Adder Kicker Pulser for a Proton Radiography System”, Digest of Technical Papers, Pulsed Power Plasma Science, 2001. PPPS-2001
A neural model of rule generation in inductive reasoning.
Rasmussen, Daniel; Eliasmith, Chris
2011-01-01
Inductive reasoning is a fundamental and complex aspect of human intelligence. In particular, how do subjects, given a set of particular examples, generate general descriptions of the rules governing that set? We present a biologically plausible method for accomplishing this task and implement it in a spiking neuron model. We demonstrate the success of this model by applying it to the problem domain of Raven's Progressive Matrices, a widely used tool in the field of intelligence testing. The model is able to generate the rules necessary to correctly solve Raven's items, as well as recreate many of the experimental effects observed in human subjects.
Modelling and Analysis of Dual-Stator Induction Motors
Razik, Hubert; Rezzoug, Abderrezak; Hadiouche, Djafar
In this paper, the analysis and the modelling of a Dual-Stator Induction Motor (DSIM) are presented. In particular, the effects of the shift angle between its three-phase windings are studied. A complex steady state model is first established in order to analyse its harmonic behavior when it is supplied by a non-sinusoidal voltage source. Then, a new transformation matrix is proposed to develop a suitable dynamic model. In both cases, the study is made using an arbitrary shift angle. Simulation results of its PWM control are also presented and compared in order to confirm our theoretical observations.
Data acquisition in modeling using neural networks and decision trees
Directory of Open Access Journals (Sweden)
R. Sika
2011-04-01
Full Text Available The paper presents a comparison of selected models from area of artificial neural networks and decision trees in relation with actualconditions of foundry processes. The work contains short descriptions of used algorithms, their destination and method of data preparation,which is a domain of work of Data Mining systems. First part concerns data acquisition realized in selected iron foundry, indicating problems to solve in aspect of casting process modeling. Second part is a comparison of selected algorithms: a decision tree and artificial neural network, that is CART (Classification And Regression Trees and BP (Backpropagation in MLP (Multilayer Perceptron networks algorithms.Aim of the paper is to show an aspect of selecting data for modeling, cleaning it and reducing, for example due to too strong correlationbetween some of recorded process parameters. Also, it has been shown what results can be obtained using two different approaches:first when modeling using available commercial software, for example Statistica, second when modeling step by step using Excel spreadsheetbasing on the same algorithm, like BP-MLP. Discrepancy of results obtained from these two approaches originates from a priorimade assumptions. Mentioned earlier Statistica universal software package, when used without awareness of relations of technologicalparameters, i.e. without user having experience in foundry and without scheduling ranks of particular parameters basing on acquisition, can not give credible basis to predict the quality of the castings. Also, a decisive influence of data acquisition method has been clearly indicated, the acquisition should be conducted according to repetitive measurement and control procedures. This paper is based on about 250 records of actual data, for one assortment for 6 month period, where only 12 data sets were complete (including two that were used for validation of neural network and useful for creating a model. It is definitely too
Inductive reasoning in medicine: lessons from Carl Gustav Hempel's 'inductive-statistical' model.
Gandjour, Afschin; Lauterbach, Karl Wilhelm
2003-05-01
The purpose of this paper is to discuss both the fundamental requirements of sound scientific explanations and predictions and common fallacies that occur in explaining and predicting medical problems. To this end, the paper presents Carl Gustav Hempel's 'covering-law' model (1948 and 1962) and reviews some of the criticism of the model. The strength of Hempel's model is that it shows that inductive arguments, when applied with the requirement of maximal specificity, can serve as explanations as well as predictions. The major weakness of the 'covering-law' model, its inability to portray causal relatedness, has been addressed by philosophers such as Wesley Salmon. While few philosophers today agree with the 'covering-law' model in its original formulation, there is widespread consensus that the law has made a central contribution to describing the fundamental requirements of sound scientific explanations. Applying this model and its revisions in the medical context may help uncover potentially undetected fallacies in reasoning when explaining and predicting medical problems.
Köhler, Peter; Huth, A.
1998-01-01
Due to high biodiversity in tropical rainforests, tree species are aggregatedinto functional groups for modelling purposes. In this article the influencesof two different classifications of tropical tree species into functionalgroups on the output of a rainforest model are analysed. The FORMIND modelis documented. FORMIND simulates the tree growth of tropical rainforests.The model is individual-based and developed from the FORMIX3 model. In themodel, trees compete for light and space in plots...
pHMM-tree: phylogeny of profile hidden Markov models.
Huo, Luyang; Zhang, Han; Huo, Xueting; Yang, Yasong; Li, Xueqiong; Yin, Yanbin
2017-04-01
Protein families are often represented by profile hidden Markov models (pHMMs). Homology between two distant protein families can be determined by comparing the pHMMs. Here we explored the idea of building a phylogeny of protein families using the distance matrix of their pHMMs. We developed a new software and web server (pHMM-tree) to allow four major types of inputs: (i) multiple pHMM files, (ii) multiple aligned protein sequence files, (iii) mixture of pHMM and aligned sequence files and (iv) unaligned protein sequences in a single file. The output will be a pHMM phylogeny of different protein families delineating their relationships. We have applied pHMM-tree to build phylogenies for CAZyme (carbohydrate active enzyme) classes and Pfam clans, which attested its usefulness in the phylogenetic representation of the evolutionary relationship among distant protein families. This software is implemented in C/C ++ and is available at http://cys.bios.niu.edu/pHMM-Tree/source/. zhanghan@nankai.edu.cn or yyin@niu.edu. Supplementary data are available at Bioinformatics online.
HTS axial flux induction motor with analytic and FEA modeling
Energy Technology Data Exchange (ETDEWEB)
Li, S., E-mail: alexlee.zn@gmail.com; Fan, Y.; Fang, J.; Qin, W.; Lv, G.; Li, J.H.
2013-11-15
Highlights: •A high temperature superconductor axial flux induction motor and a novel maglev scheme are presented. •Analytic method and finite element method have been adopted to model the motor and to calculate the force. •Magnetic field distribution in HTS coil is calculated by analytic method. •An effective method to improve the critical current of HTS coil is presented. •AC losses of HTS coils in the HTS axial flux induction motor are estimated and tested. -- Abstract: This paper presents a high-temperature superconductor (HTS) axial-flux induction motor, which can output levitation force and torque simultaneously. In order to analyze the character of the force, analytic method and finite element method are adopted to model the motor. To make sure the HTS can carry sufficiently large current and work well, the magnetic field distribution in HTS coil is calculated. An effective method to improve the critical current of HTS coil is presented. Then, AC losses in HTS windings in the motor are estimated and tested.
Modelling of Closed Loop Class E Inverter Based Induction Heater
Directory of Open Access Journals (Sweden)
S. Arumugam
2011-01-01
Full Text Available This study presents simulation of class E inverter based induction heater system using simulink. DC is converted into high frequency AC using class E inverter. This high frequency AC is used for induction heating. Closed loop systems are modeled and they are simulated using Mat lab Simulink.The results of closed loop systems are presented. The proposed amplifier with two series-parallel resonant load networks will allow sinusoidal output voltage to be achieved by associating with the positive and negative quasi-sinusoidal waveforms. The complementarily activated configuration will provide continuous high-ripple-frequency inputcurrent waveforms; this approach significantly reduces electromagnetic interference and requires very little filtering. With the symmetry of the push-pull Class-E Circuit, there is the additional benefit that the even harmonics are suppressed at the load, and thus there are fewer harmonic distortions.
Pre-growth mortality of Abies cilicica trees and mortality models performance.
Carus, Serdar
2010-05-01
In this study, we compared tree-growth rates (basal area increment) from recently dead and living Taurus fir (Abies cilicica Carr.) trees in the Kovada lake Forest of Isparta, Turkey. For each dead tree, tree-growth rates were analyzed for the presence of pre-death growth depressions in the study area (number of sample plots = 11) in 2006. However, we compared both the magnitude and rate of growth prior to death to a control (living) group of trees. Basal area increment (BAI) averaged substantially less during the last 10 years before death than for control trees. Trees that died started diverging in growth, on average, 50-60 years before death. About 18% of trees that died had chronically slow growth, 46% had pronounced declines in growth, whereas 36% had good growth up to death. However, tree-ring-based growth patterns of dead and living Taurus fir trees were compared and used 12 mortality models that were derived using logistic regression from growth patterns of tree-ring series as predictor variables. The four models with the highest overall performance correctly classified 43.8-56.3% of all dead trees and 75.0-87.5% of all living trees, and they predicted 25.0-43.8% of all dead trees to die within 0-15 years prior to the actual year of death.
A Hybrid Windkessel Model of Blood Flow in Arterial Tree Using Velocity Profile Method
Aboelkassem, Yasser; Virag, Zdravko
2016-11-01
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.
A Cayley Tree Immune Network Model with Antibody Dynamics
Anderson, R W; Perelson, A S; Anderson, Russell W.; Neumann, Avidan U.; Perelson, Alan S.
1993-01-01
Abstract: A Cayley tree model of idiotypic networks that includes both B cell and antibody dynamics is formulated and analyzed. As in models with B cells only, localized states exist in the network with limited numbers of activated clones surrounded by virgin or near-virgin clones. The existence and stability of these localized network states are explored as a function of model parameters. As in previous models that have included antibody, the stability of immune and tolerant localized states are shown to depend on the ratio of antibody to B cell lifetimes as well as the rate of antibody complex removal. As model parameters are varied, localized steady-states can break down via two routes: dynamically, into chaotic attractors, or structurally into percolation attractors. For a given set of parameters, percolation and chaotic attractors can coexist with localized attractors, and thus there do not exist clear cut boundaries in parameter space that separate regions of localized attractors from regions of percola...
Induction Heating Process: 3D Modeling and Optimisation
Naar, R.; Bay, F.
2011-05-01
An increasing number of problems in mechanics and physics involves multiphysics coupled problems. Among these problems, we can often find electromagnetic coupled problems. Electromagnetic couplings may be involved through the use of direct or induced currents for thermal purposes—in order to generate heat inside a work piece in order to get either a prescribed temperature field or some given mechanical or metallurgical properties through an accurate control of temperature evolution with respect to time-, or for solid or fluid mechanics purposes—in order to create magnetic forces such as in fluid mechanics (electromagnetic stirring,…) or solid mechanics (magnetoforming,…). Induction heat treatment processes is therefore quite difficult to control; trying for instance to minimize distortions generated by such a process is not easy. In order to achieve these objectives, we have developed a computational tool which includes an optimsation stage. A 3D finite element modeling tool for local quenching after induction heating processes has already been developed in our laboratory. The modeling of such a multiphysics coupled process needs taking into account electromagnetic, thermal, mechanical and metallurgical phenomenon—as well as their mutual interactions during the whole process: heating and quenching. The model developed is based on Maxwell equations, heat transfer equation, mechanical equilibrium computations, Johnson-Mehl-Avrami and Koistinen-Marburger laws. All these equations and laws may be coupled but some coupling may be neglected. In our study, we will also focus on induction heating process aiming at optimising the Heat Affected Zone (HAZ). Thus problem is formalized as an optimization problem—minimizing a cost function which measures the difference between computed and optimal temperatures—along with some constraints on process parameters. The optimization algorithms may be of two kinds—either zero-order or first-order algorithms. First
A deterministic model for the growth of non-conducting electrical tree structures
Dodd, S J
2003-01-01
Electrical treeing is of interest to the electrical generation, transmission and distribution industries as it is one of the causes of insulation failure in electrical machines, switchgear and transformer bushings. In this paper a deterministic electrical tree growth model is described. The model is based on electrostatics and local electron avalanches to model partial discharge activity within the growing tree structure. Damage to the resin surrounding the tree structure is dependent on the local electrostatic energy dissipation by partial discharges within the tree structure and weighted by the magnitudes of the local electric fields in the resin surrounding the tree structure. The model is successful in simulating the formation of branched structures without the need of a random variable, a requirement of previous stochastic models. Instability in the spatial development of partial discharges within the tree structure takes the role of the stochastic element as used in previous models to produce branched t...
Wind tunnel experiment of drag of isolated tree models in surface boundary layer
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
For very sparse tree land individual tree was the basic element of interaction between atmosphere and the surface. Drag of isolated tree was preliminary aerodynamic index for analyzing the atmospheric boundary layer of this kind of surface. A simple pendulum method was designed and carried out in wind tunnel to measure drag of isolated tree models according to balance law of moment of force. The method was easy to conduct and with small error. The results showed that the drag and drag coefficient of isolated tree increased with decreasing of its permeability or porosity. Relationship between drag coefficient and permeability of isolated tree empirically was expressed by quadric curve.
Optimum Binary Search Trees on the Hierarchical Memory Model
Thite, Shripad
2008-01-01
The Hierarchical Memory Model (HMM) of computation is similar to the standard Random Access Machine (RAM) model except that the HMM has a non-uniform memory organized in a hierarchy of levels numbered 1 through h. The cost of accessing a memory location increases with the level number, and accesses to memory locations belonging to the same level cost the same. Formally, the cost of a single access to the memory location at address a is given by m(a), where m: N -> N is the memory cost function, and the h distinct values of m model the different levels of the memory hierarchy. We study the problem of constructing and storing a binary search tree (BST) of minimum cost, over a set of keys, with probabilities for successful and unsuccessful searches, on the HMM with an arbitrary number of memory levels, and for the special case h=2. While the problem of constructing optimum binary search trees has been well studied for the standard RAM model, the additional parameter m for the HMM increases the combinatorial comp...
DEFF Research Database (Denmark)
Rasmussen, Mads Olander; Goettsche, Frank-M.; Diop, Doudou
2011-01-01
radius, and diameter at breast height (DBH), for which allometric models were determined. An object-based classification method was used to determine tree crown cover (TCC) from Quickbird data. The average TCC from the tree survey and the respective TCC from remote sensing were both about 3.0 For areas...... beyond the surveyed areas TCC varied between 3.0% and 4.5 Furthermore, an empirical correction factor for tree clumping was obtained, which considerably improved the estimated number of trees and the estimated average tree crown area and radius. An allometric model linking TCC to tree stem crosssectional...
Engineering of Algorithms for Hidden Markov models and Tree Distances
DEFF Research Database (Denmark)
Sand, Andreas
grown exponentially because of drastic improvements in the technology behind DNA and RNA sequencing, and focus on the research field has increased due to its potential to expand our knowledge about biological mechanisms and to improve public health. There has therefore been a continuously growing demand...... of the algorithms to exploit the parallel architecture of modern computers. In this PhD dissertation, I present my work with algorithmic optimizations and parallelizations in primarily two areas in algorithmic bioinformatics: algorithms for analyzing hidden Markov models and algorithms for computing distance...... measures between phylogenetic trees. Hidden Markov models is a class of probabilistic models that is used in a number of core applications in bioinformatics such as modeling of proteins, gene finding and reconstruction of species and population histories. I show how a relatively simple parallelization can...
Allowed Parameter Regions for a Tree-Level Inflation Model
Institute of Scientific and Technical Information of China (English)
MENG Xin-He
2001-01-01
The early universe inflation is well known as a promising theory to explain the origin of large-scale structure of universe and to solve the early universe pressing problems. For a reasonable inflation model, the potential during inflation must be very flat, at least, in the direction of the inflaton. To construct the inflaton potential all the known related astrophysics observations should be included. For a general tree-level hybrid inflation potential, which is notdiscussed fully so far, the parameters in it are shown how to be constrained via the astrophysics data observed and to be obtained to the expected accuracy, and to be consistent with cosmology requirements.``
Inferring tree causal models of cancer progression with probability raising.
Directory of Open Access Journals (Sweden)
Loes Olde Loohuis
Full Text Available Existing techniques to reconstruct tree models of progression for accumulative processes, such as cancer, seek to estimate causation by combining correlation and a frequentist notion of temporal priority. In this paper, we define a novel theoretical framework called CAPRESE (CAncer PRogression Extraction with Single Edges to reconstruct such models based on the notion of probabilistic causation defined by Suppes. We consider a general reconstruction setting complicated by the presence of noise in the data due to biological variation, as well as experimental or measurement errors. To improve tolerance to noise we define and use a shrinkage-like estimator. We prove the correctness of our algorithm by showing asymptotic convergence to the correct tree under mild constraints on the level of noise. Moreover, on synthetic data, we show that our approach outperforms the state-of-the-art, that it is efficient even with a relatively small number of samples and that its performance quickly converges to its asymptote as the number of samples increases. For real cancer datasets obtained with different technologies, we highlight biologically significant differences in the progressions inferred with respect to other competing techniques and we also show how to validate conjectured biological relations with progression models.
Spatially dependent polya tree modeling for survival data.
Zhao, Luping; Hanson, Timothy E
2011-06-01
With the proliferation of spatially oriented time-to-event data, spatial modeling in the survival context has received increased recent attention. A traditional way to capture a spatial pattern is to introduce frailty terms in the linear predictor of a semiparametric model, such as proportional hazards or accelerated failure time. We propose a new methodology to capture the spatial pattern by assuming a prior based on a mixture of spatially dependent Polya trees for the baseline survival in the proportional hazards model. Thanks to modern Markov chain Monte Carlo (MCMC) methods, this approach remains computationally feasible in a fully hierarchical Bayesian framework. We compare the spatially dependent mixture of Polya trees (MPT) approach to the traditional spatial frailty approach, and illustrate the usefulness of this method with an analysis of Iowan breast cancer survival data from the Surveillance, Epidemiology, and End Results (SEER) program of the National Cancer Institute. Our method provides better goodness of fit over the traditional alternatives as measured by log pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and full sample score (FSS) statistics. © 2010, The International Biometric Society.
Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies
Directory of Open Access Journals (Sweden)
P. Breitenmoser
2013-07-01
Full Text Available We investigate the relationship between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin–Lite (VSL forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a to examine the relations between simulated and observed growth at 2287 globally distributed sites and (b to evaluate the potential of the VSL model to reconstruct past climate. The assessment of the growth-onset threshold temperature of approximately 4–6 °C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level tree-ring series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yields notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model's ability to skilfully capture the climatic signal contained in tree-series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate.
Susan L. King
2003-01-01
The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...
Brown, Molly E.; McGroddy, Megan; Spence, Caitlin; Flake, Leah; Sarfraz, Amna; Nowak, David J.; Milesi, Cristina
2012-01-01
As the world becomes increasingly urban, the need to quantify the effect of trees in urban environments on energy usage, air pollution, local climate and nutrient run-off has increased. By identifying, quantifying and valuing the ecological activity that provides services in urban areas, stronger policies and improved quality of life for urban residents can be obtained. Here we focus on two radically different models that can be used to characterize urban forests. The i-Tree Eco model (formerly UFORE model) quantifies ecosystem services (e.g., air pollution removal, carbon storage) and values derived from urban trees based on field measurements of trees and local ancillary data sets. Biome-BGC (Biome BioGeoChemistry) is used to simulate the fluxes and storage of carbon, water, and nitrogen in natural environments. This paper compares i-Tree Eco's methods to those of Biome-BGC, which estimates the fluxes and storage of energy, carbon, water and nitrogen for vegetation and soil components of the ecosystem. We describe the two models and their differences in the way they calculate similar properties, with a focus on carbon and nitrogen. Finally, we discuss the implications of further integration of these two communities for land managers such as those in Maryland.
Combining an additive and tree-based regression model simultaneously: STIMA
Dusseldorp, E.; Conversano, C.; Os, B.J. van
2010-01-01
Additive models and tree-based regression models are two main classes of statistical models used to predict the scores on a continuous response variable. It is known that additive models become very complex in the presence of higher order interaction effects, whereas some tree-based models, such as
Using Some Coupled Numerical Models in Problems of Designing an Inductive Electrothermal Equipment
Directory of Open Access Journals (Sweden)
LEUCA Teodor
2014-05-01
Full Text Available This paper focuses on the numerical modeling of coupling the electromagnetic and the thermal field, in the process of inductive heating, for inductive electrothermal equipments. Numerical results are carried out by using a FLUX2D application.
Saturation model for squirrel-cage induction motors
Energy Technology Data Exchange (ETDEWEB)
Pedra, J. [Department of Electrical Engineering, ETSEIB-UPC, Av. Diagonal 647, 08028 Barcelona (Spain); Candela, I. [Department of Electrical Engineering, ETSEIT-UPC, Colom 1, 08222 Terrassa (Spain); Barrera, A. [Asea Brown Boveri, S.A. Fabrica de Motores, Poligono Industrial S.O., 08192 Sant Quirze del Valles, Barcelona (Spain)
2009-07-15
An induction motor model which includes stator leakage reactance saturation, rotor leakage reactance saturation and magnetizing reactance saturation is presented. This improved model is based on experimental data from 96 motors. The power range of the motors is between 11 and 90 kW. The effects on the torque-speed and current-speed curves of each kind of saturation have been studied. In addition, the parameters of magnetizing reactance saturation and stator leakage reactance saturation have been studied for each motor, and an average value and its dispersion for each parameter are given. This model is considerably more accurate than other models. In particular, it explains the significant differences between theoretical and experimental torque-speed curves in the braking regime (s > 1). (author)
Groundwater Level Prediction using M5 Model Trees
Nalarajan, Nitha Ayinippully; Mohandas, C.
2015-01-01
Groundwater is an important resource, readily available and having high economic value and social benefit. Recently, it had been considered a dependable source of uncontaminated water. During the past two decades, increased rate of extraction and other greedy human actions have resulted in the groundwater crisis, both qualitatively and quantitatively. Under prevailing circumstances, the availability of predicted groundwater levels increase the importance of this valuable resource, as an aid in the planning of groundwater resources. For this purpose, data-driven prediction models are widely used in the present day world. M5 model tree (MT) is a popular soft computing method emerging as a promising method for numeric prediction, producing understandable models. The present study discusses the groundwater level predictions using MT employing only the historical groundwater levels from a groundwater monitoring well. The results showed that MT can be successively used for forecasting groundwater levels.
An invisible axion model with controlled FCNCs at tree level
Directory of Open Access Journals (Sweden)
Alejandro Celis
2015-02-01
Full Text Available We derive the necessary conditions to build a class of invisible axion models with Flavor Changing Neutral Currents at tree-level controlled by the fermion mixing matrices and present an explicit model implementation. A horizontal Peccei–Quinn symmetry provides a solution to the strong CP problem via the Peccei–Quinn mechanism and predicts a cold dark mater candidate, the invisible axion or familon. The smallness of active neutrino masses can be explained via a type I seesaw mechanism, providing a dynamical origin for the heavy seesaw scale. The possibility to avoid the domain wall problem stands as one of the most interesting features of the type of models considered. Experimental limits relying on the axion–photon coupling, astrophysical considerations and familon searches in rare kaon and muon decays are discussed.
An invisible axion model with controlled FCNCs at tree level
Energy Technology Data Exchange (ETDEWEB)
Celis, Alejandro, E-mail: alejandro.celis@ific.uv.es [Departament de Física Teòrica and IFIC, Universitat de València-CSIC, E-46100, Burjassot (Spain); Fuentes-Martín, Javier, E-mail: javier.fuentes@ific.uv.es [Departament de Física Teòrica and IFIC, Universitat de València-CSIC, E-46100, Burjassot (Spain); Department of Physics, National Tsing Hua University, Hsinchu 300, Taiwan (China); Serôdio, Hugo, E-mail: hserodio@kaist.ac.kr [Departament de Física Teòrica and IFIC, Universitat de València-CSIC, E-46100, Burjassot (Spain); Department of Physics, Korea Advanced Institute of Science and Technology, 335 Gwahak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)
2015-02-04
We derive the necessary conditions to build a class of invisible axion models with Flavor Changing Neutral Currents at tree-level controlled by the fermion mixing matrices and present an explicit model implementation. A horizontal Peccei–Quinn symmetry provides a solution to the strong CP problem via the Peccei–Quinn mechanism and predicts a cold dark mater candidate, the invisible axion or familon. The smallness of active neutrino masses can be explained via a type I seesaw mechanism, providing a dynamical origin for the heavy seesaw scale. The possibility to avoid the domain wall problem stands as one of the most interesting features of the type of models considered. Experimental limits relying on the axion–photon coupling, astrophysical considerations and familon searches in rare kaon and muon decays are discussed.
HTS axial flux induction motor with analytic and FEA modeling
Li, S.; Fan, Y.; Fang, J.; Qin, W.; Lv, G.; Li, J. H.
2013-11-01
This paper presents a high-temperature superconductor (HTS) axial-flux induction motor, which can output levitation force and torque simultaneously. In order to analyze the character of the force, analytic method and finite element method are adopted to model the motor. To make sure the HTS can carry sufficiently large current and work well, the magnetic field distribution in HTS coil is calculated. An effective method to improve the critical current of HTS coil is presented. Then, AC losses in HTS windings in the motor are estimated and tested.
Spatially-explicit models of global tree density
Glick, Henry B.; Bettigole, Charlie; Maynard, Daniel S.; Covey, Kristofer R.; Smith, Jeffrey R.; Crowther, Thomas W.
2016-08-01
Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.
Macroscopic Models of Clique Tree Growth for Bayesian Networks
National Aeronautics and Space Administration — In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to...
Tree cover bistability in the MPI Earth system model due to fire-vegetation feedback
Lasslop, Gitta; Brovkin, Victor; Kloster, Silvia; Reick, Christian
2015-04-01
The global distribution of tree cover is mainly limited by precipitation and temperature. Within tropical ecosystems different tree cover values have been observed in regions with similar climate. Satellite data even revealed a lack of ecosystems with tree coverage around 60% and dominant tree covers of 20% and 80%. Conceptual models have been used to explain this tree cover distribution and base it on a bistability in tree cover caused by fire-vegetation interactions or competition between trees and grasses. Some ecological models also show this property of multiple stable tree covers, but it remains unclear which mechanism is the cause for this behaviour. Vegetation models used in climate simulations usually use simple approaches and were criticised to neglect such ecological theories and misrepresent tropical tree cover distribution and dynamics. Here we show that including the process based fire model SPITFIRE generated a bistability in tree cover in the land surface model JSBACH. Previous model versions showed only one stable tree cover state. Using a conceptual model we can show that a bistability can occur due to a feedback between grasses and fire. Grasses and trees are represented in the model based on plant functional types. With respect to fire the main difference between grasses and trees is the fuel characteristics. Grass fuels are smaller in size, and have a higher surface area to volume ratio. These grass fuels dry faster increasing their flammability which leads to a higher fire rate of spread. Trees are characterized by coarse fuels, which are less likely to ignite and rather suppress fire. Therefore a higher fraction of grasses promotes fire, fire kills trees and following a fire, grasses establish faster. This feedback can stabilize ecosystems with low tree cover in a low tree cover state and systems with high tree cover in a high tree cover state. In previous model versions this feedback was absent. Based on the new JSBACH model driven with
Seera, Manjeevan; Lim, Chee Peng; Ishak, Dahaman; Singh, Harapajan
2012-01-01
In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min-max (FMM) neural network and classification and regression tree (CART) is proposed. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. A series of real experiments is conducted, whereby the motor current signature analysis method is applied to form a database comprising stator current signatures under different motor conditions. The signal harmonics from the power spectral density are extracted as discriminative input features for fault detection and classification with FMM-CART. A comprehensive list of induction motor fault conditions, viz., broken rotor bars, unbalanced voltages, stator winding faults, and eccentricity problems, has been successfully classified using FMM-CART with good accuracy rates. The results are comparable, if not better, than those reported in the literature. Useful explanatory rules in the form of a decision tree are also elicited from FMM-CART to analyze and understand different fault conditions of induction motors.
Directory of Open Access Journals (Sweden)
Srđan G. Aćimović
2015-02-01
Full Text Available Management of fire blight is complicated by limitations on use of antibiotics in agriculture, antibiotic resistance development, and limited efficacy of alternative control agents. Even though successful in control, preventive antibiotic sprays also affect non-target bacteria, aiding the selection for resistance which could ultimately be transferred to the pathogen Erwinia amylovora. Trunk injection is a target-precise pesticide delivery method that utilizes tree xylem to distribute injected compounds. Trunk injection could decrease antibiotic usage in the open environment and increase the effectiveness of compounds in fire blight control. In field experiments, after 1-2 apple tree injections of either streptomycin, potassium phosphites (PH or acibenzolar-S-methyl (ASM, significant reduction of blossom and shoot blight symptoms was observed compared to water- or non-injected control trees. Overall disease suppression with streptomycin was lower than typically observed following spray applications to flowers. Trunk injection of oxytetracycline resulted in excellent control of shoot blight severity, suggesting that injection is a superior delivery method for this antibiotic. Injection of both ASM and PH resulted in the significant induction of PR-1, PR-2 and PR-8 protein genes in apple leaves indicating induction of systemic acquired resistance (SAR under field conditions. The time separating SAR induction and fire blight symptom suppression indicated that various defensive compounds within the SAR response were synthesized and accumulated in the canopy. ASM and PH suppressed fire blight even after cessation of induced gene expression. With the development of injectable formulations and optimization of doses and injection schedules, the injection of protective compounds could serve as an effective option for fire blight control.
[Tree shrews under the spot light: emerging model of human diseases].
Xu, Lin; Zhang, Yun; Liang, Bin; Lü, Long-Bao; Chen, Ce-Shi; Chen, Yong-Bin; Zhou, Ju-Min; Yao, Yong-Gang
2013-04-01
Animal models are indispensible in biomedical research and have made tremendous contributions to answer fundamental questions on human biology, disease mechanisms, and to the development of new drugs and diagnostic tools. Due to the limitations of rodent models in translational medicine, tree shrews (Tupaia belangeri chinensis), the closest relative of primates, have attracted increasing attention in modeling human diseases and therapeutic responses. Here we discuss the recent progress in tree shrew biology and the development of tree shrews as human disease models including infectious diseases, metabolic diseases, neurological and psychiatric diseases, and cancers. Meanwhile, the current problems and future perspectives of the tree shrew model are explored.
Prediction model based on decision tree analysis for laccase mediators.
Medina, Fabiola; Aguila, Sergio; Baratto, Maria Camilla; Martorana, Andrea; Basosi, Riccardo; Alderete, Joel B; Vazquez-Duhalt, Rafael
2013-01-10
A Structure Activity Relationship (SAR) study for laccase mediator systems was performed in order to correctly classify different natural phenolic mediators. Decision tree (DT) classification models with a set of five quantum-chemical calculated molecular descriptors were used. These descriptors included redox potential (ɛ°), ionization energy (E(i)), pK(a), enthalpy of formation of radical (Δ(f)H), and OH bond dissociation energy (D(O-H)). The rationale for selecting these descriptors is derived from the laccase-mediator mechanism. To validate the DT predictions, the kinetic constants of different compounds as laccase substrates, their ability for pesticide transformation as laccase-mediators, and radical stability were experimentally determined using Coriolopsis gallica laccase and the pesticide dichlorophen. The prediction capability of the DT model based on three proposed descriptors showed a complete agreement with the obtained experimental results. Copyright © 2012 Elsevier Inc. All rights reserved.
Mixtures of Polya trees for flexible spatial frailty survival modelling.
Zhao, Luping; Hanson, Timothy E; Carlin, Bradley P
2009-06-01
Mixtures of Polya trees offer a very flexible nonparametric approach for modelling time-to-event data. Many such settings also feature spatial association that requires further sophistication, either at the point level or at the lattice level. In this paper, we combine these two aspects within three competing survival models, obtaining a data analytic approach that remains computationally feasible in a fully hierarchical Bayesian framework using Markov chain Monte Carlo methods. We illustrate our proposed methods with an analysis of spatially oriented breast cancer survival data from the Surveillance, Epidemiology and End Results program of the National Cancer Institute. Our results indicate appreciable advantages for our approach over competing methods that impose unrealistic parametric assumptions, ignore spatial association or both.
Hernández, I; Celestino, C; Toribio, M
2003-04-01
Somatic embryogenesis was induced in expanding leaves from epicormic shoots forced to sprout from segments of branches collected from several hundred-year-old cork oak trees. Following a basic protocol previously defined for leaves taken from seedlings of this species, several factors were studied to improve the response. The induction frequency was significantly higher when the length of exposure to growth regulators was increased from 7 to 30 days. The combined application of NAA and BAP was essential for induction. Although both regulators had a very significant influence, their interaction was not significant, suggesting independent roles. Leaf size had a crucial effect, because beyond a certain threshold, embryogenesis could not be obtained. Embryogenic lines were maintained via repetitive embryogenesis on hormone-free medium for more than 2 years.
Bayesian nonparametric meta-analysis using Polya tree mixture models.
Branscum, Adam J; Hanson, Timothy E
2008-09-01
Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.
Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model
Jeon, Minjeong; De Boeck, Paul; van der Linden, Wim
2017-01-01
We present a novel application of a generalized item response tree model to investigate test takers' answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated…
U.S. Environmental Protection Agency — Spreadsheets are included here to support the manuscript "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition". This...
Yield curve event tree construction for multi stage stochastic programming models
DEFF Research Database (Denmark)
Rasmussen, Kourosh Marjani; Poulsen, Rolf
by the quality and size of the event trees representing the underlying uncertainty. Most often the DSP literature assumes existence of ``appropriate'' event trees without defining and examining qualities that must be met (ex--ante) in such an event tree in order for the results of the DSP model to be reliable....... Indeed defining a universal and tractable framework for fully ``appropriate'' event trees is in our opinion an impossible task. A problem specific approach to designing such event trees is the way ahead. In this paper we propose a number of desirable properties which should be present in an event tree...... of yield curves. Such trees may then be used to represent the underlying uncertainty in DSP models of fixed income risk and portfolio management....
A 2D model to design MHD induction pumps
Stieglitz, R.; Zeininger, J.
2006-09-01
Technical liquid metal systems accompanied by a thermal transfer of energy such as reactor systems, metallurgical processes, metal refinement, casting, etc., require a forced convection of the fluid. The increased temperatures and more often the environmental conditions as, e.g., in a nuclear environment, pumping principles are required, in which rotating parts are absent. Additionally, in many applications a controlled atmosphere is indispensable, in order to ensure the structural integrity of the duct walls. An interesting option to overcome the sealing problem of a mechanical pump towards the surrounding is offered by induction systems. Although their efficiency compared to that of turbo machines is quite low, they have several advantages, which are attractive to the specific requirements in liquid metal applications such as: - low maintenance costs due to the absence of sealings, bearings and moving parts; - low degradation rate of the structural material; - simple replacement of the inductor without cut of the piping system; - fine regulation of flow rate by different inductor connections; - change of pump characteristics without change of the mechanical set-up. Within the article, general design requirements of electromagnetic pumps (EMP) are elaborated. The design of two annular linear induction pumps operating with sodium and lead-bismuth are presented and the calculated pump characteristics and experimentally obtained data are compared. In this context, physical effects leading to deviations between the model and the real data are addressed. Finally, the main results are summarized. Tables 4, Figs 4, Refs 12.
USAHA PENINGKATAN PRODUKTIVITAS DENGAN PRODUCTIVITY EVALUATION TREE (PET MODELS
Directory of Open Access Journals (Sweden)
Muchlison Anis
2007-04-01
Full Text Available Usaha peningkatan produktivitas merupakan suatu langkah menuju perbaikan perusahaan dimasa yang akan datang. Model perencanaan produktivitas Productivity Evaluation Tree (PET memberikan kemudahan bagi perusahaan dalam mengembangkan dan menilai seluruh alternatif yang mungkin dilakukan dalam menetapkan target peningkatan produktivitas dan usaha peningkatan produktivitas. Dalam penelitian ini alternatif perencanaan ada tiga. Pertama, meningkatkan standart penggunaan bahan baku dari 20% menjadi 30%. Kedua, pengeluaran bahan baku diusulkan sama dengan bulan lalu dengan menerapkan peningkatan standart penggunaan bahan baku sama seperti dengan alternatif pertama, Ketiga, menstimulasi alternatif 2 dengan melakukan manajemen motivasi terhadap tenaga kerja. Dari hasil evaluasi pohon produktivitas maka dapat diketahui estimasi peningkatan produktivitas yang tertinggi adalah alternatif ke tiga dengan perubahan tingkat produktivitas sebesar 0,39.
Factor models on locally tree-like graphs
Dembo, Amir; Sun, Nike
2011-01-01
We consider homogeneous factor models on uniformly sparse graph sequences converging locally to a (unimodular) random tree T, and study the existence of the free energy density phi, the limit of the log-partition function divided by the number of vertices n as n tends to infinity. We provide a new interpolation scheme and use it to prove existence of, and to explicitly compute, the quantity phi subject to uniqueness of a relevant Gibbs measure for the factor model on T. By way of example we compute phi for the independent set (or hard-core) model at low fugacity, for the ferromagnetic Ising model at all parameter values, and for the ferromagnetic Potts model with both weak enough and strong enough interactions. Even beyond uniqueness our interpolation provides useful explicit bounds on phi. In the regimes in which we establish existence of the limit, we show that it coincides with the Bethe free energy functional evaluated at a suitable fixed point of the belief propagation recursions on T. In the special cas...
Institute of Scientific and Technical Information of China (English)
KESHAN－ZHE; QIANJUN－LONG; 等
1994-01-01
The chemical element contents in tree rings are correlated with those in the soils near the tree roots,The results in the present study showed that the correlation between them could be described using the following logarithmic linear correlation model:lgC'(Z)=a(Z)+b(Z)lgC(Z).Therefor,by determining the chrono-sequence C(Z,t),where Z is the atomic number and t the year,of elemental contents in the annual growth rings of trees,we could get the chrono-sequence C'(Z,t) of elemental contents in the soil,thus inferring the dynaminc variations of relevant elemental contents in the soil.
Linking individual-tree and whole-stand models for forest growth and yield prediction
Directory of Open Access Journals (Sweden)
Quang V Cao
2014-10-01
Full Text Available Background Different types of growth and yield models provide essential information for making informed decisions on how to manage forests. Whole-stand models often provide well-behaved outputs at the stand level, but lack information on stand structures. Detailed information from individual-tree models and size-class models typically suffers from accumulation of errors. The disaggregation method, in assuming that predictions from a whole-stand model are reliable, partitions these outputs to individual trees. On the other hand, the combination method seeks to improve stand-level predictions from both whole-stand and individual-tree models by combining them. Methods Data from 100 plots randomly selected from the Southwide Seed Source Study of loblolly pine (Pinus taeda L. were used to evaluate the unadjusted individual-tree model against the disaggregation and combination methods. Results Compared to the whole-stand model, the combination method did not show improvements in predicting stand attributes in this study. The combination method also did not perform as well as the disaggregation method in tree-level predictions. The disaggregation method provided the best predictions of tree- and stand-level survival and growth. Conclusions The disaggregation approach provides a link between individual-tree models and whole-stand models, and should be considered as a better alternative to the unadjusted tree model.
Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen
2006-01-01
We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...
Ziv, Dafna; Zviran, Tali; Zezak, Oshrat; Samach, Alon; Irihimovitch, Vered
2014-01-01
In many perennials, heavy fruit load on a shoot decreases the ability of the plant to undergo floral induction in the following spring, resulting in a pattern of crop production known as alternate bearing. Here, we studied the effects of fruit load on floral determination in 'Hass' avocado (Persea americana). De-fruiting experiments initially confirmed the negative effects of fruit load on return to flowering. Next, we isolated a FLOWERING LOCUS T-like gene, PaFT, hypothesized to act as a phloem-mobile florigen signal and examined its expression profile in shoot tissues of on (fully loaded) and off (fruit-lacking) trees. Expression analyses revealed a strong peak in PaFT transcript levels in leaves of off trees from the end of October through November, followed by a return to starting levels. Moreover and concomitant with inflorescence development, only off buds displayed up-regulation of the floral identity transcripts PaAP1 and PaLFY, with significant variation being detected from October and November, respectively. Furthermore, a parallel microscopic study of off apical buds revealed the presence of secondary inflorescence axis structures that only appeared towards the end of November. Finally, ectopic expression of PaFT in Arabidopsis resulted in early flowering transition. Together, our data suggests a link between increased PaFT expression observed during late autumn and avocado flower induction. Furthermore, our results also imply that, as in the case of other crop trees, fruit-load might affect flowering by repressing the expression of PaFT in the leaves. Possible mechanism(s) by which fruit crop might repress PaFT expression, are discussed.
Ziv, Dafna; Zviran, Tali; Zezak, Oshrat; Samach, Alon; Irihimovitch, Vered
2014-01-01
In many perennials, heavy fruit load on a shoot decreases the ability of the plant to undergo floral induction in the following spring, resulting in a pattern of crop production known as alternate bearing. Here, we studied the effects of fruit load on floral determination in ‘Hass' avocado (Persea americana). De-fruiting experiments initially confirmed the negative effects of fruit load on return to flowering. Next, we isolated a FLOWERING LOCUS T-like gene, PaFT, hypothesized to act as a phloem-mobile florigen signal and examined its expression profile in shoot tissues of on (fully loaded) and off (fruit-lacking) trees. Expression analyses revealed a strong peak in PaFT transcript levels in leaves of off trees from the end of October through November, followed by a return to starting levels. Moreover and concomitant with inflorescence development, only off buds displayed up-regulation of the floral identity transcripts PaAP1 and PaLFY, with significant variation being detected from October and November, respectively. Furthermore, a parallel microscopic study of off apical buds revealed the presence of secondary inflorescence axis structures that only appeared towards the end of November. Finally, ectopic expression of PaFT in Arabidopsis resulted in early flowering transition. Together, our data suggests a link between increased PaFT expression observed during late autumn and avocado flower induction. Furthermore, our results also imply that, as in the case of other crop trees, fruit-load might affect flowering by repressing the expression of PaFT in the leaves. Possible mechanism(s) by which fruit crop might repress PaFT expression, are discussed. PMID:25330324
Directory of Open Access Journals (Sweden)
Dafna Ziv
Full Text Available In many perennials, heavy fruit load on a shoot decreases the ability of the plant to undergo floral induction in the following spring, resulting in a pattern of crop production known as alternate bearing. Here, we studied the effects of fruit load on floral determination in 'Hass' avocado (Persea americana. De-fruiting experiments initially confirmed the negative effects of fruit load on return to flowering. Next, we isolated a FLOWERING LOCUS T-like gene, PaFT, hypothesized to act as a phloem-mobile florigen signal and examined its expression profile in shoot tissues of on (fully loaded and off (fruit-lacking trees. Expression analyses revealed a strong peak in PaFT transcript levels in leaves of off trees from the end of October through November, followed by a return to starting levels. Moreover and concomitant with inflorescence development, only off buds displayed up-regulation of the floral identity transcripts PaAP1 and PaLFY, with significant variation being detected from October and November, respectively. Furthermore, a parallel microscopic study of off apical buds revealed the presence of secondary inflorescence axis structures that only appeared towards the end of November. Finally, ectopic expression of PaFT in Arabidopsis resulted in early flowering transition. Together, our data suggests a link between increased PaFT expression observed during late autumn and avocado flower induction. Furthermore, our results also imply that, as in the case of other crop trees, fruit-load might affect flowering by repressing the expression of PaFT in the leaves. Possible mechanism(s by which fruit crop might repress PaFT expression, are discussed.
Dynamics models and modeling of tree stand development
Directory of Open Access Journals (Sweden)
M. V. Rogozin
2015-04-01
Full Text Available Brief analysis of scientific works in Russia and in the CIS over the past 100 years. Logical and mathematical models consider the conceptual and show some of the results of their verification. It was found that the models include different laws and the parameters, the sum of which allows you to divide them into four categories: models of static states, development models, models of care for the natural forest and models of cultivation. Each category has fulfilled and fulfills its tasks in economic management. Thus, the model states in statics (table traverse growth played a prominent role in figuring out what may be the most productive (full stands in different regions of the country. However, they do not answer the question of what the initial states lead to the production of complete stands. In a study of the growth of stands used system analysis, and it is observed dominance of works studying static state, snatched from the biological time. Therefore, the real drama of the growth of stands remained almost unexplored. It is no accident there were «chrono-forestry» «plantation forestry» and even «non-traditional forestry», where there is a strong case of a number of new concepts of development stands. That is quite in keeping with Kuhn (Kuhn, 2009 in the forestry crisis began – there were alternative theories and coexist conflicting scientific schools. To develop models of stand development, it is proposed to use a well-known method of repeated observations within 10–20 years, in conjunction with the explanation of the history of the initial density. It mounted on the basis of studying the dynamics of its indicators: the trunk, crown overlap coefficient, the sum of volumes of all crowns and the relative length of the crown. According to these indicators, the researcher selects natural series of development stands with the same initial density. As a theoretical basis for the models it is possible to postulate the general properties of
Best-first Model Merging for Hidden Markov Model Induction
Stolcke, A; Stolcke, Andreas; Omohundro, Stephen M.
1994-01-01
This report describes a new technique for inducing the structure of Hidden Markov Models from data which is based on the general `model merging' strategy (Omohundro 1992). The process begins with a maximum likelihood HMM that directly encodes the training data. Successively more general models are produced by merging HMM states. A Bayesian posterior probability criterion is used to determine which states to merge and when to stop generalizing. The procedure may be considered a heuristic search for the HMM structure with the highest posterior probability. We discuss a variety of possible priors for HMMs, as well as a number of approximations which improve the computational efficiency of the algorithm. We studied three applications to evaluate the procedure. The first compares the merging algorithm with the standard Baum-Welch approach in inducing simple finite-state languages from small, positive-only training samples. We found that the merging procedure is more robust and accurate, particularly with a small a...
Statistical modeling and design in forestry : The case of single tree models
2008-01-01
Forest quantification methods have evolved from a simple graphical approach to complex regression models with stochastic structural components. Currently, mixed effects models methodology is receiving attention in the forestry literature. However, the review work (Paper I) indicates a tendency to overlook appropriate covariance structures in the NLME modeling process. A nonlinear mixed effects modeling process is demonstrated in Paper II using Cupressus lustanica tree merchantable volume data...
Modeling the effectiveness of tree planting to mitigate habitat loss in blue oak woodlands
Richard B. Standiford; Douglas McCreary; William Frost
2002-01-01
Many local conservation policies have attempted to mitigate the loss of oak woodland habitat resulting from conversion to urban or intensive agricultural land uses through tree planting. This paper models the development of blue oak (Quercus douglasii) stand structure attributes over 50 years after planting. The model uses a single tree, distance...
A Model of Desired Performance in Phylogenetic Tree Construction for Teaching Evolution.
Brewer, Steven D.
This research paper examines phylogenetic tree construction-a form of problem solving in biology-by studying the strategies and heuristics used by experts. One result of the research is the development of a model of desired performance for phylogenetic tree construction. A detailed description of the model and the sample problems which illustrate…
A modeling study of the impact of urban trees on ozone
David J. Nowak; Kevin L. Civerolo; S. Trivikrama Rao; Gopal Sistla; Christopher J. Luley; Daniel E. Crane
2000-01-01
Modeling the effects of increased urban tree cover on ozone concentrations (July 13-15, 1995) from Washington, DC, to central Massachusetts reveals that urban trees generally reduce ozone concentrations in cities, but tend to increase average ozone concentrations in the overall modeling domain. During the daytime, average ozone reductions in urban areas (1 ppb) were...
Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments
Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.
2009-01-01
The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…
Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments
Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.
2009-01-01
The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…
A carbon balance model of peach tree growth and development for studying the pruning response.
Génard, Michel; Pagès, Loïc; Kervella, Jocelyne
1998-06-01
We modeled tree responses to pruning on the basis of growth rules established on unpruned trees and a simple principle governing root-shoot interactions. The model, which integrates architectural and ecophysiological approaches, distinguishes four types of anatomical organs in a tree: rootstock, main axis, secondary axes and new roots. Tree structure is described by the position of secondary axes on the main axis. The main processes considered are plastochronal activity, branching, assimilate production, respiration and assimilate partitioning. Growth and development rules were based on measurements of two unpruned trees. The model was used to simulate growth of peach trees (Prunus persica (L.) Batsch) in their first growing season. Assuming that the equilibrium between roots and shoots tends to be restored after pruning, the response to removal of the main axis above the twentieth internode in mid-July was simulated and compared to the response measured in three pruned trees. The model fit the unpruned tree data reasonably well and predicted the main traits of tree behavior after pruning. Dry matter growth of the secondary axes of pruned trees was increased so that shoot seasonal carbon balance was hardly modified by pruning. Rhythmicity of growth was enhanced by pruning, and might result from variations induced in the root:shoot ratio. Variation in pruning severity had greater effects than variation in pruning date. A sensitivity analysis indicated that: (1) root-shoot partitioning was a critical process of the model; (2) tree growth was mainly dependent on assimilate availability; and (3) tree shape was highly dependent on the branching process.
Induction Heating Model of Cermet Fuel Element Environmental Test (CFEET)
Gomez, Carlos F.; Bradley, D. E.; Cavender, D. P.; Mireles, O. R.; Hickman, R. R.; Trent, D.; Stewart, E.
2013-01-01
Deep space missions with large payloads require high specific impulse and relatively high thrust to achieve mission goals in reasonable time frames. Nuclear Thermal Rockets (NTR) are capable of producing a high specific impulse by employing heat produced by a fission reactor to heat and therefore accelerate hydrogen through a rocket nozzle providing thrust. Fuel element temperatures are very high (up to 3000 K) and hydrogen is highly reactive with most materials at high temperatures. Data covering the effects of high-temperature hydrogen exposure on fuel elements are limited. The primary concern is the mechanical failure of fuel elements due to large thermal gradients; therefore, high-melting-point ceramics-metallic matrix composites (cermets) are one of the fuels under consideration as part of the Nuclear Cryogenic Propulsion Stage (NCPS) Advance Exploration System (AES) technology project at the Marshall Space Flight Center. The purpose of testing and analytical modeling is to determine their ability to survive and maintain thermal performance in a prototypical NTR reactor environment of exposure to hydrogen at very high temperatures and obtain data to assess the properties of the non-nuclear support materials. The fission process and the resulting heating performance are well known and do not require that active fissile material to be integrated in this testing. A small-scale test bed; Compact Fuel Element Environmental Tester (CFEET), designed to heat fuel element samples via induction heating and expose samples to hydrogen is being developed at MSFC to assist in optimal material and manufacturing process selection without utilizing fissile material. This paper details the analytical approach to help design and optimize the test bed using COMSOL Multiphysics for predicting thermal gradients induced by electromagnetic heating (Induction heating) and Thermal Desktop for radiation calculations.
Achieving Convergence in Galaxy Formation Models by Augmenting N-body Merger Trees
Benson, Andrew J; Cole, Shaun
2016-01-01
Accurate modeling of galaxy formation in a hierarchical, cold dark matter universe requires the use of sufficiently high-resolution merger trees to obtain convergence in the predicted properties of galaxies. When semi-analytic galaxy formation models are applied to cosmological N-body simulation merger trees, it is often the case that those trees have insufficient resolution to give converged galaxy properties. We demonstrate a method to augment the resolution of N-body merger trees by grafting in branches of Monte Carlo merger trees with higher resolution, but which are consistent with the pre-existing branches in the N-body tree. We show that this approach leads to converged galaxy properties.
Golzari, Fahimeh; Jalili, Saeed
2015-07-21
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.
Parallel family trees for transfer matrices in the Potts model
Navarro, Cristobal A; Kahler, Nancy Hitschfeld; Navarro, Gonzalo
2013-01-01
The computational cost of transfer matrix methods for the Potts model is directly related to the problem of \\textit{into how many ways can two adjacent blocks of a lattice be connected}. Answering this question leads to the generation of a combinatorial set of lattice configurations. This set defines the \\textit{configuration space} of the problem, and the smaller it is, the faster the transfer matrix method can be. The configuration space of generic transfer matrix methods for strip lattices in the Potts model is in the order of the Catalan numbers, leading to an asymptotic cost of $O(4^m)$ with $m$ being the width of the strip. Transfer matrix methods with a smaller configuration space indeed exist but they make assumptions on the temperature, number of spin states, or restrict the topology of the lattice in order to work. In this paper we propose a general and parallel transfer matrix method, based on family trees, that uses a sub-Catalan configuration space of size $O(3^m)$. The improvement is achieved by...
Invasion percolation on a tree and queueing models.
Gabrielli, A; Caldarelli, G
2009-04-01
We study the properties of the Barabási model of queuing [A.-L. Barabási, Nature (London) 435, 207 (2005); J. G. Oliveira and A.-L. Barabási, Nature (London) 437, 1251 (2005)] in the hypothesis that the number of tasks grows with time steadily. Our analytical approach is based on two ingredients. First we map exactly this model into an invasion percolation dynamics on a Cayley tree. Second we use the theory of biased random walks. In this way we obtain the following results: the stationary-state dynamics is a sequence of causally and geometrically connected bursts of execution activities with scale-invariant size distribution. We recover the correct waiting-time distribution PW(tau) approximately tau(-3/2) at the stationary state (as observed in different realistic data). Finally we describe quantitatively the dynamics out of the stationary state quantifying the power-law slow approach to stability both in single dynamical realization and in average. These results can be generalized to the case of a stochastic increase in the queue length in time with limited fluctuations. As a limit case we recover the situation in which the queue length fluctuates around a constant average value.
Zaremotlagh, S.; Hezarkhani, A.
2017-04-01
Some evidences of rare earth elements (REE) concentrations are found in iron oxide-apatite (IOA) deposits which are located in Central Iranian microcontinent. There are many unsolved problems about the origin and metallogenesis of IOA deposits in this district. Although it is considered that felsic magmatism and mineralization were simultaneous in the district, interaction of multi-stage hydrothermal-magmatic processes within the Early Cambrian volcano-sedimentary sequence probably caused some epigenetic mineralizations. Secondary geological processes (e.g., multi-stage mineralization, alteration, and weathering) have affected on variations of major elements and possible redistribution of REE in IOA deposits. Hence, the geochemical behaviors and distribution patterns of REE are expected to be complicated in different zones of these deposits. The aim of this paper is recognizing LREE distribution patterns based on whole-rock chemical compositions and automatic discovery of their geochemical rules. For this purpose, the pattern recognition techniques including decision tree and neural network were applied on a high-dimensional geochemical dataset from Choghart IOA deposit. Because some data features were irrelevant or redundant in recognizing the distribution patterns of each LREE, a greedy attribute subset selection technique was employed to select the best subset of predictors used in classification tasks. The decision trees (CART algorithm) were pruned optimally to more accurately categorize independent test data than unpruned ones. The most effective classification rules were extracted from the pruned tree to describe the meaningful relationships between the predictors and different concentrations of LREE. A feed-forward artificial neural network was also applied to reliably predict the influence of various rock compositions on the spatial distribution patterns of LREE with a better performance than the decision tree induction. The findings of this study could be
Analytical Model and Algorithm of Fuzzy Fault Tree
Institute of Scientific and Technical Information of China (English)
杨艺; 何学秋; 王恩元; 刘贞堂
2002-01-01
In the past, the probabilities of basic events were described as triangular or trapezoidal fuzzy number that cannot characterize the common distribution of the primary events in engineering, and the fault tree analyzed by fuzzy set theory did not include repeated basic events. This paper presents a new method to a nalyze the fault tree by using normal fuzzy number to describe the fuzzy probability of each basic event which is more suitably used to analyze the reliability in safety systems, and then the formulae of computing the fuzzy probability of the top event of the fault tree which includes repeated events are derived. Finally, an example is given.
Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.
Guangyi, Mei; Yujun, Sun; Saeed, Sajjad
2017-01-01
Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * (ln(H))2 + d * (ln(H))3 + e * ln(WD) had the best fit for estimating the tree biomass of Chinese Fir stands. Furthermore, we observed that variables D(diameter at breast height), H (height), and WD(wood density)were significantly correlated with the total tree biomass estimation model. As a result, a natural logarithm structure gave the best estimates for the tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the tree biomass model with Tree volume(TV), WD and biomass wood density conversion factor (BECF),achieved the highest simulation accuracy, expressed as ln(TB) = -0.0703 + 0.9780 * ln(TV) + 0.0213 * ln(WD) + 1.0166 * ln(BECF). Therefore, when TV, WD and BECF were combined with tree biomass volume coefficient bi for Chinese Fir, the stand biomass (SB)model included both volume(SV) and coefficient bi variables of the stand as follows: bi = Exp(-0.0703+0.9780*ln(TV)+0.0213 * ln(WD)+1.0166*ln(BECF)). The stand biomass model is SB = SV/TV * bi.
Imaging cerebral haemorrhage with magnetic induction tomography: numerical modelling.
Zolgharni, M; Ledger, P D; Armitage, D W; Holder, D S; Griffiths, H
2009-06-01
Magnetic induction tomography (MIT) is a new electromagnetic imaging modality which has the potential to image changes in the electrical conductivity of the brain due to different pathologies. In this study the feasibility of detecting haemorrhagic cerebral stroke with a 16-channel MIT system operating at 10 MHz was investigated. The finite-element method combined with a realistic, multi-layer, head model comprising 12 different tissues, was used for the simulations in the commercial FE package, Comsol Multiphysics. The eddy-current problem was solved and the MIT signals computed for strokes of different volumes occurring at different locations in the brain. The results revealed that a large, peripheral stroke (volume 49 cm(3)) produced phase changes that would be detectable with our currently achievable instrumentation phase noise level (17 m degrees ) in 70 (27%) of the 256 exciter/sensor channel combinations. However, reconstructed images showed that a lower noise level than this, of 1 m degrees , was necessary to obtain good visualization of the strokes. The simulated MIT measurements were compared with those from an independent transmission-line-matrix model in order to give confidence in the results.
DEFF Research Database (Denmark)
Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith
2010-01-01
the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature...... field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v......) 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...
Biomechanics of Growing Trees: Mathematical Model, Numerical Resolution and Perspectives
Fourcaud, Thierry; Guillon, Thomas; Dumont, Yves
2011-09-01
The growth of trees is characterized by the elongation and thickening of its axes. New cells are formed at the periphery of the existing body, the properties of the older inner material being unchanged. The calculation of the progressive deflection of a growing stem is not a classical problem in mechanics for three main reasons: 1- the hypothesis of mass conservation is not valid; 2- the new material added at the periphery of the existing and deformed structure does not participate retroactively to the total equilibrium and tends to "fix" the actual shape; 3- an initial reference configuration corresponding to the unloaded structure cannot be classically defined to formulate the equilibrium equations. This paper proposes a theoretical framework that allows bypassing these difficulties. Equations adapted from the beam theory and considering the strong dependencies between space and time are given. A numerical scheme based on the finite element method is proposed to solve these equations. The model opens new research perspectives both in mathematics and plant biology.
Interaction of tea tree oil with model and cellular membranes.
Giordani, Cristiano; Molinari, Agnese; Toccacieli, Laura; Calcabrini, Annarica; Stringaro, Annarita; Chistolini, Pietro; Arancia, Giuseppe; Diociaiuti, Marco
2006-07-27
Tea tree oil (TTO) is the essential oil steam-distilled from Melaleuca alternifolia, a species of northern New South Wales, Australia. It exhibits a broad-spectrum antimicrobial activity and an antifungal activity. Only recently has TTO been shown to inhibit the in vitro growth of multidrug resistant (MDR) human melanoma cells. It has been suggested that the effect of TTO on tumor cells could be mediated by its interaction with the plasma membrane, most likely by inducing a reorganization of lipid architecture. In this paper we report biophysical and structural results obtained using simplified planar model membranes (Langmuir films) mimicking lipid "rafts". We also used flow cytometry analysis (FCA) and freeze-fracturing transmission electron microscopy to investigate the effects of TTO on actual MDR melanoma cell membranes. Thermodynamic (compression isotherms and adsorption kinetics) and structural (Brewster angle microscopy) investigation of the lipid monolayers clearly indicates that TTO interacts preferentially with the less ordered DPPC "sea" and that it does not alter the more ordered lipid "rafts". Structural observations, performed by freeze fracturing, confirm that TTO interacts with the MDR melanoma cell plasma membrane. Moreover, experiments performed by FCA demonstrate that TTO does not interfere with the function of the MDR drug transporter P-gp. We therefore propose that the effect exerted on MDR melanoma cells is mediated by the interaction with the fluid DPPC phase, rather than with the more organized "rafts" and that this interaction preferentially influences the ATP-independent antiapoptotic activity of P-gp likely localized outside "rafts".
Reconstructing 3D Tree Models Using Motion Capture and Particle Flow
Directory of Open Access Journals (Sweden)
Jie Long
2013-01-01
Full Text Available Recovering tree shape from motion capture data is a first step toward efficient and accurate animation of trees in wind using motion capture data. Existing algorithms for generating models of tree branching structures for image synthesis in computer graphics are not adapted to the unique data set provided by motion capture. We present a method for tree shape reconstruction using particle flow on input data obtained from a passive optical motion capture system. Initial branch tip positions are estimated from averaged and smoothed motion capture data. Branch tips, as particles, are also generated within a bounding space defined by a stack of bounding boxes or a convex hull. The particle flow, starting at branch tips within the bounding volume under forces, creates tree branches. The forces are composed of gravity, internal force, and external force. The resulting shapes are realistic and similar to the original tree crown shape. Several tunable parameters provide control over branch shape and arrangement.
Using New Approaches to obtain Gibbs Measures of Vannimenus model on a Cayley tree
2015-01-01
In this paper, we consider Vannimenus model with competing nearest-neighbors and prolonged next-nearest-neighbors interactions on a Cayley tree. For this model we define Markov random fields with memory of length 2. By using a new approach, we obtain new sets of Gibbs measures of Ising-Vannimenus model on Cayley tree of order 2. We construct the recurrence equations corresponding Ising-Vannimenus model. We prove the Kolmogorov consistency condition. We investigate the translation-invariant an...
Gibbs Properties of the Fuzzy Potts Model on Trees and in Mean Field
Häggström, O.; Külske, C.
2004-01-01
We study Gibbs properties of the fuzzy Potts model in the mean field case (i.e. on a complete graph) and on trees. For the mean field case, a complete characterization of the set of temperatures for which non-Gibbsianness happens is given. The results for trees are somewhat less explicit, but we do
Being While Doing: An Inductive Model of Mindfulness at Work
Lyddy, Christopher J.; Good, Darren J.
2017-01-01
Mindfulness at work has drawn growing interest as empirical evidence increasingly supports its positive workplace impacts. Yet theory also suggests that mindfulness is a cognitive mode of “Being” that may be incompatible with the cognitive mode of “Doing” that undergirds workplace functioning. Therefore, mindfulness at work has been theorized as “being while doing,” but little is known regarding how people experience these two modes in combination, nor the influences or outcomes of this interaction. Drawing on a sample of 39 semi-structured interviews, this study explores how professionals experience being mindful at work. The relationship between Being and Doing modes demonstrated changing compatibility across individuals and experience, with two basic types of experiences and three types of transitions. We labeled experiences when informants were unable to activate Being mode while engaging Doing mode as Entanglement, and those when informants reported simultaneous co-activation of Being and Doing modes as Disentanglement. This combination was a valuable resource for offsetting important limitations of the typical reliance on the Doing cognitive mode. Overall our results have yielded an inductive model of mindfulness at work, with the core experience, outcomes, and antecedent factors unified into one system that may inform future research and practice. PMID:28270775
EMTP Simulation Model of a Wind Turbine Generator using Induction Generator
Tokunaga, Yoshitaka; Iio, Naotaka; Tanomura, Kenichi; Shinohara, Hirofumi
This paper presents an EMTP simulation model for the wind turbine generator using induction generator. This model was developed to add the model of a wind turbine portion to the precision model using the standard specification data and operation data of induction generator. It verified that the inrush current at starting and the residual voltage at islanding state were analyzed, and measured data could be reproduced by this model.
A defeasible reasoning model of inductive concept learning from examples and communication
Ontañón, Santiago; Dellunde, Pilar; Godo, Lluís; Plaza, Enric
2012-01-01
This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing which hypotheses can be induced from given sets of examples, and study its properties, showing they correspond to a rather well-behaved non-monotonic logic. We will also show that with the addition of a...
Temperature analysis of induction motors using a hybrid thermal model with distributed heat sources
Mukhopadhyay, S. C.; Pal, S. K.
1998-06-01
The article presents a hybrid thermal model for the accurate estimation of temperature distribution of induction motors. The developed model is a combination of lumped and distributed thermal parameters which are obtained from motor dimensions and other constants such as material density, specific heats, thermal conductivity, etc. The model is especially suited for the derating of induction motors operating under distorted and unbalanced supply condition. The model have been applied to a small (2hp, 415 V, 3-phase) cage rotor induction motor. The performance of the model is confirmed by experimental temperature data from the body and the conductor inside the slots of the motor.
Fabian C.C. Uzoh; William W. Oliver
2008-01-01
A diameter increment model is developed and evaluated for individual trees of ponderosa pine throughout the species range in the United States using a multilevel linear mixed model. Stochastic variability is broken down among period, locale, plot, tree and within-tree components. Covariates acting at tree and stand level, as breast height diameter, density, site index...
Mirfenderesgi, Golnazalsadat; Bohrer, Gil; Matheny, Ashley M.; Fatichi, Simone; Moraes Frasson, Renato Prata; Schäfer, Karina V. R.
2016-07-01
The finite difference ecosystem-scale tree crown hydrodynamics model version 2 (FETCH2) is a tree-scale hydrodynamic model of transpiration. The FETCH2 model employs a finite difference numerical methodology and a simplified single-beam conduit system to explicitly resolve xylem water potentials throughout the vertical extent of a tree. Empirical equations relate water potential within the stem to stomatal conductance of the leaves at each height throughout the crown. While highly simplified, this approach brings additional realism to the simulation of transpiration by linking stomatal responses to stem water potential rather than directly to soil moisture, as is currently the case in the majority of land surface models. FETCH2 accounts for plant hydraulic traits, such as the degree of anisohydric/isohydric response of stomata, maximal xylem conductivity, vertical distribution of leaf area, and maximal and minimal xylem water content. We used FETCH2 along with sap flow and eddy covariance data sets collected from a mixed plot of two genera (oak/pine) in Silas Little Experimental Forest, NJ, USA, to conduct an analysis of the intergeneric variation of hydraulic strategies and their effects on diurnal and seasonal transpiration dynamics. We define these strategies through the parameters that describe the genus level transpiration and xylem conductivity responses to changes in stem water potential. Our evaluation revealed that FETCH2 considerably improved the simulation of ecosystem transpiration and latent heat flux in comparison to more conventional models. A virtual experiment showed that the model was able to capture the effect of hydraulic strategies such as isohydric/anisohydric behavior on stomatal conductance under different soil-water availability conditions.
Modeling an RF Cold Crucible Induction Heated Melter with Subsidence
Energy Technology Data Exchange (ETDEWEB)
Grant L. Hawkes
2004-07-01
A method to reduce radioactive waste volume that includes melting glass in a cold crucible radio frequency induction heated melter has been investigated numerically. The purpose of the study is to correlate the numerical investigation with an experimental apparatus that in the above mentioned melter. Unique to this model is the subsidence of the glass as it changes from a powder to molten glass and drastically changes density. A model has been created that couples the magnetic vector potential (real and imaginary) to a transient startup of the melter process. This magnetic field is coupled to the mass, momentum, and energy equations that vary with time and position as the melt grows. The coupling occurs with the electrical conductivity of the glass as it rises above the melt temperature of the glass and heat is generated. Natural convection within the molten glass helps determine the shape of the melt as it progresses in time. An electromagnetic force is also implemented that is dependent on the electrical properties and frequency of the coil. This study shows the progression of the melt shape with time along with temperatures, power input, velocities and magnetic vector potential. Coupled to all of this is a generator that will be used for this lab sized experiment. The coupling with the 60 kW generator occurs with the impedance of the melt as it progresses and changes with time. A power controller has been implemented that controls the primary coil current depending on the power that is induced into the molten glass region.
Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling
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S. Galelli
2013-02-01
Full Text Available Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modeling. In this paper we investigate the prediction capability of extremely randomized trees (Extra-Trees, in terms of accuracy, explanation ability and computational efficiency, in a streamflow modeling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i alleviates the poor generalization property and tendency to overfitting of traditional standalone decision trees (e.g. CART; (ii is computationally very efficient; and, (iii allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analyzed on two real-world case studies (Marina catchment (Singapore and Canning River (Western Australia representing two different morphoclimatic contexts comparatively with other tree-based methods (CART and M5 and parametric data-driven approaches (ANNs and multiple linear regression. Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5 in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.
Assessing the predictive capability of randomized tree-based ensembles in streamflow modelling
Galelli, S.; Castelletti, A.
2013-07-01
Combining randomization methods with ensemble prediction is emerging as an effective option to balance accuracy and computational efficiency in data-driven modelling. In this paper, we investigate the prediction capability of extremely randomized trees (Extra-Trees), in terms of accuracy, explanation ability and computational efficiency, in a streamflow modelling exercise. Extra-Trees are a totally randomized tree-based ensemble method that (i) alleviates the poor generalisation property and tendency to overfitting of traditional standalone decision trees (e.g. CART); (ii) is computationally efficient; and, (iii) allows to infer the relative importance of the input variables, which might help in the ex-post physical interpretation of the model. The Extra-Trees potential is analysed on two real-world case studies - Marina catchment (Singapore) and Canning River (Western Australia) - representing two different morphoclimatic contexts. The evaluation is performed against other tree-based methods (CART and M5) and parametric data-driven approaches (ANNs and multiple linear regression). Results show that Extra-Trees perform comparatively well to the best of the benchmarks (i.e. M5) in both the watersheds, while outperforming the other approaches in terms of computational requirement when adopted on large datasets. In addition, the ranking of the input variable provided can be given a physically meaningful interpretation.
Directory of Open Access Journals (Sweden)
Jinmo Kim
2016-09-01
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.
Mechanisms and models which govern bending and reconfiguring of trees under water flow action
Wilson, Catherine; Whittaker, Peter; Hydroenvironmental Research Centre Team
2015-11-01
A model for predicting the drag and reconfiguration of flexible vegetation under hydrodynamic loading is presented. The model is based on a refined ``vegetative'' Cauchy number to incorporate the magnitude and rate of a tree's reconfiguration. In addition, analysis of data from a tree drag force study conducted at the Canal de Experiencias Hidrodinamicas de El Pardo, Madrid, is also presented. This data enables the analysis of the frontal projected and the side-view areas as well as the bending angle of the main tree stems over a full range of velocities. New physical mechanisms which link tree posture, permeability, and the Reconfiguration number-Cauchy number relationship for various key stages of reconfiguration are proposed. These mechanisms are mainly developed for multi-stem trees in their foliated state. In addition direct comparisons of mechanisms for foliated and defoliated states are also presented.
ORPOM model for optimum distribution of tree ring sampling based on the climate observation network
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
Tree ring dating plays an important role in obtaining past climate information.The fundamental study of obtaining tree ring samples in typical climate regions is particularly essential.The optimum distribution of tree ring sampling sites based on climate information from the Climate Observation Network(ORPOM model) is presented in this article.In this setup,the tree rings in a typical region are used for surface representation,by applying excellent correlation with the climate information as the main principle.Taking the Horqin Sandy Land in the cold and arid region of China as an example,the optimum distribution range of the tree ring sampling sites was obtained through the application of the ORPOM model,which is considered a reasonably practical scheme.
Topology of correlation-based minimal spanning trees in real and model markets.
Bonanno, Giovanni; Caldarelli, Guido; Lillo, Fabrizio; Mantegna, Rosario N
2003-10-01
We compare the topological properties of the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the widespread one-factor model.
Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model
Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.
2015-11-01
In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.
Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model
Directory of Open Access Journals (Sweden)
M. Fader
2015-06-01
Full Text Available Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL: nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry, and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.
Mulder, Willem H; Crawford, Forrest W
2015-01-01
Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees.
Maximizing Adaptivity in Hierarchical Topological Models Using Cancellation Trees
Energy Technology Data Exchange (ETDEWEB)
Bremer, P; Pascucci, V; Hamann, B
2008-12-08
We present a highly adaptive hierarchical representation of the topology of functions defined over two-manifold domains. Guided by the theory of Morse-Smale complexes, we encode dependencies between cancellations of critical points using two independent structures: a traditional mesh hierarchy to store connectivity information and a new structure called cancellation trees to encode the configuration of critical points. Cancellation trees provide a powerful method to increase adaptivity while using a simple, easy-to-implement data structure. The resulting hierarchy is significantly more flexible than the one previously reported. In particular, the resulting hierarchy is guaranteed to be of logarithmic height.
Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
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Pavel Brandstetter
2013-01-01
Full Text Available The paper deals with a speed estimation of the induction motor using observer with Model Reference Adaptive System and Kalman Filter. For simulation, Hardware in Loop Simulation method is used. The first part of the paper includes the mathematical description of the observer for the speed estimation of the induction motor. The second part describes Kalman filter. The third part describes Hardware in Loop Simulation method and its realization using multifunction card MF 624. In the last section of the paper, simulation results are shown for different changes of the induction motor speed which confirm high dynamic properties of the induction motor drive with sensorless control.
Using Unlabeled Data to Improve Inductive Models by Incorporating Transductive Models
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ShengJun Cheng
2014-02-01
Full Text Available This paper shows how to use labeled and unlabeled data to improve inductive models with the help of transductivemodels.We proposed a solution for the self-training scenario. Self- training is an effective semi-supervised wrapper method which can generalize any type of supervised inductive model to the semi-supervised settings. it iteratively refines a inductive model by bootstrap from unlabeled data. Standard self-training uses the classifier model(trained on labeled examples to label and select candidates from the unlabeled training set, which may be problematic since the initial classifier may not be able to provide highly confident predictions as labeled training data is always rare. As a result, it could always suffer from introducing too much wrongly labeled candidates to the labeled training set, which may severely degrades performance. To tackle this problem, we propose a novel self-training style algorithm which incorporate a graph-based transductive model in the self-labeling process. Unlike standard self-training, our algorithm utilizes labeled and unlabeled data as a whole to label and select unlabeled examples for training set augmentation. A robust transductive model based on graph markov random walk is proposed, which exploits manifold assumption to output reliable predictions on unlabeled data using noisy labeled examples. The proposed algorithm can greatly minimize the risk of performance degradation due to accumulated noise in the training set. Experiments show that the proposed algorithm can effectively utilize unlabeled data to improve classification performance.
Modeling the Effects of Argument Length and Validity on Inductive and Deductive Reasoning
Rotello, Caren M.; Heit, Evan
2009-01-01
In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a common set of stimuli. Two distinct effects were…
Propagation of action potentials along complex axonal trees. Model and implementation.
Manor, Y; Gonczarowski, J; Segev, I
1991-01-01
Axonal trees are typically morphologically and physiologically complicated structures. Because of this complexity, axonal trees show a large repertoire of behavior: from transmission lines with delay, to frequency filtering devices in both temporal and spatial domains. Detailed theoretical exploration of the electrical behavior of realistically complex axonal trees is notably lacking, mainly because of the absence of a simple modeling tool. AXONTREE is an attempt to provide such a simulator. It is written in C for the SUN workstation and implements both a detailed compartmental modeling of Hodgkin and Huxley-like kinetics, and a more abstract, event-driven, modeling approach. The computing module of AXONTREE is introduced together with its input/output features. These features allow graphical construction of arbitrary trees directly on the computer screen, and superimposition of the results on the simulated structure. Several numerical improvements that increase the computational efficiency by a factor of 5-10 are presented; most notable is a novel method of dynamic lumping of the modeled tree into simpler representations ("equivalent cables"). AXONTREE's performance is examined using a reconstructed terminal of an axon from a Y cell in cat visual cortex. It is demonstrated that realistically complicated axonal trees can be handled efficiently. The application of AXONTREE for the study of propagation delays along axonal trees is presented in the companion paper (Manor et al., 1991). Images FIGURE 4 PMID:1777566
Modeling of velocity field for vacuum induction melting process
Institute of Scientific and Technical Information of China (English)
CHEN Bo; JIANG Zhi-guo; LIU Kui; LI Yi-yi
2005-01-01
The numerical simulation for the recirculating flow of melting of an electromagnetically stirred alloy in a cylindrical induction furnace crucible was presented. Inductive currents and electromagnetic body forces in the alloy under three different solenoid frequencies and three different melting powers were calculated, and then the forces were adopted in the fluid flow equations to simulate the flow of the alloy and the behavior of the free surface. The relationship between the height of the electromagnetic stirring meniscus, melting power, and solenoid frequency was derived based on the law of mass conservation. The results show that the inductive currents and the electromagnetic forces vary with the frequency, melting power, and the physical properties of metal. The velocity and the height of the meniscus increase with the increase of the melting power and the decrease of the solenoid frequency.
Translation-invariant and periodic Gibbs measures for the Potts model on a Cayley tree
Khakimov, R. M.; Khaydarov, F. Kh.
2016-11-01
We study translation-invariant Gibbs measures on a Cayley tree of order k = 3 for the ferromagnetic three-state Potts model. We obtain explicit formulas for translation-invariant Gibbs measures. We also consider periodic Gibbs measures on a Cayley tree of order k for the antiferromagnetic q-state Potts model. Moreover, we improve previously obtained results: we find the exact number of periodic Gibbs measures with the period two on a Cayley tree of order k ≥ 3 that are defined on some invariant sets.
Mechanical properties of tree roots for soil reinforcement models
Cofie, P.
2001-01-01
Evidence from forestry has shown that part of the forest floor bearing capacity is delivered by tree roots. The beneficial effect however varies and diminishes with increasing number of vehicle passes. Roots potential for reinforcing the soil is known to depend among others on root mechanical proper
Mechanical properties of tree roots for soil reinforcement models
Cofie, P.
2001-01-01
Evidence from forestry has shown that part of the forest floor bearing capacity is delivered by tree roots. The beneficial effect however varies and diminishes with increasing number of vehicle passes. Roots potential for reinforcing the soil is known to depend among others on root
Soil Organic Matter Mapping by Decision Tree Modeling
Institute of Scientific and Technical Information of China (English)
ZHOU Bin; ZHANG Xing-Gang; WANG Fan; WANG Ren-Chao
2005-01-01
Based on a case study of Longyou County, Zhejiang Province, the decision tree, a data mining method, was used to analyze the relationships between soil organic matter (SOM) and other environmental and satellite sensing spatial data.The decision tree associated SOM content with some extensive easily observable landscape attributes, such as landform,geology, land use, and remote sensing images, thus transforming the SOM-related information into a clear, quantitative,landscape factor-associated regular system. This system could be used to predict continuous SOM spatial distribution.By analyzing factors such as elevation, geological unit, soil type, land use, remotely sensed data, upslope contributing area, slope, aspect, planform curvature, and profile curvature, the decision tree could predict distribution of soil organic matter levels. Among these factors, elevation, land use, aspect, soil type, the first principle component of bitemporal Landsat TM, and upslope contributing area were considered the most important variables for predicting SOM. Results of the prediction between SOM content and landscape types sorted by the decision tree showed a close relationship with an accuracy of 81.1%.
Initial Algebra Semantics for Cyclic Sharing Tree Structures
Hamana, Makoto
2010-01-01
Terms are a concise representation of tree structures. Since they can be naturally defined by an inductive type, they offer data structures in functional programming and mechanised reasoning with useful principles such as structural induction and structural recursion. However, for graphs or "tree-like" structures -- trees involving cycles and sharing -- it remains unclear what kind of inductive structures exists and how we can faithfully assign a term representation of them. In this paper we propose a simple term syntax for cyclic sharing structures that admits structural induction and recursion principles. We show that the obtained syntax is directly usable in the functional language Haskell and the proof assistant Agda, as well as ordinary data structures such as lists and trees. To achieve this goal, we use a categorical approach to initial algebra semantics in a presheaf category. That approach follows the line of Fiore, Plotkin and Turi's models of abstract syntax with variable binding.
Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition
Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on ...
Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition
Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on ...
Marković, D Z; Kalauzi, A; Radenović, C N
2001-09-01
The paper deals with mathematical modelling of the transients obtained by fitting of delayed fluorescence (DF) induction trace. The transients are in certain, doubtless connection with electrochemical gradient (ECG) formed across thylakoid membranes upon illumination. The fitting of the C and D transients by using consecutive model for first-order reactions (A --> B --> C) showed that they might play a role of the intermediate (B), according to scheme down bellow: ("A1 state")ECG (k1(C transient))--> C transient (k2(C transient))--> products, ("A2 state")ECG (k1(D transient))--> D transient (k2(D transient))--> products. The two ECG controlled "states" (A1 & A2) are not the same, which does not exclude some sort of proportionality. On the other hand, the E band, contributing mainly to the stationary level of DF induction trace, may be fitted by parallel model of at least two first-order reactions.
Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description
Directory of Open Access Journals (Sweden)
Jan Hackenberg
2014-05-01
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.
CT-based geometry analysis and finite element models of the human and ovine bronchial tree.
Tawhai, Merryn H; Hunter, Peter; Tschirren, Juerg; Reinhardt, Joseph; McLennan, Geoffrey; Hoffman, Eric A
2004-12-01
The interpretation of experimental results from functional medical imaging is complicated by intersubject and interspecies differences in airway geometry. The application of computational models in understanding the significance of these differences requires methods for generation of subject-specific geometric models of the bronchial airway tree. In the current study, curvilinear airway centerline and diameter models have been fitted to human and ovine bronchial trees using detailed data segmented from multidetector row X-ray-computed tomography scans. The trees have been extended to model the entire conducting airway system by using a volume-filling algorithm to generate airway centerline locations within detailed volume descriptions of the lungs or lobes. Analysis of the geometry of the scan-based and model-based airways has verified their consistency with measures from previous anatomic studies and has provided new anatomic data for the ovine bronchial tree. With the use of an identical parameter set, the volume-filling algorithm has produced airway trees with branching asymmetry appropriate for the human and ovine lung, demonstrating the dependence of the method on the shape of the lung or lobe volume. The modeling approach that has been developed can be applied to any level of detail of the airway tree and into any volume shape for the lung; hence it can be used directly for different individuals or animals and for any number of scan-based airways. The resulting models are subject-specific computational meshes with anatomically consistent geometry, suitable for application in simulation studies.
Baudena, Mara; D'Andrea, Fabio; Provenzale, A.
2010-01-01
1. We discuss a simple implicit-space model for the competition of trees and grasses in an idealized savanna environment. The model represents patch occupancy dynamics within the habitat and introduces life stage structure in the tree population, namely adults and seedlings. A tree can be out-compet
iTree-Hydro: Snow hydrology update for the urban forest hydrology model
Yang Yang; Theodore A. Endreny; David J. Nowak
2011-01-01
This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest EffectsâHydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...
Parametric Generation of Polygonal Tree Models for Rendering on Tessellation-Enabled Hardware
Nystad, Jørgen
2010-01-01
The main contribution of this thesis is a parametric method for generation of single-mesh polygonal tree models that follow natural rules as indicated by da Vinci in his notebooks. Following these rules allow for a relatively simple scheme of connecting branches to parent branches. Proper branch connection is a requirement for gaining the benefits of subdivision. Techniques for proper texture coordinate generation and subdivision are also explored.The result is a tree model generation scheme ...
A Tree-based Approach for Modelling Interception Loss From Evergreen Oak Mediterranean Savannas
Pereira, Fernando L.; Gash, John H. C.; David, Jorge S.; David, Teresa S.; Monteiro, Paulo R.; Valente, Fernanda
2010-05-01
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
Accounting for Epistemic Uncertainty in PSHA: Logic Tree and Ensemble Model
Taroni, M.; Marzocchi, W.; Selva, J.
2014-12-01
The logic tree scheme is the probabilistic framework that has been widely used in the last decades to take into account epistemic uncertainties in probabilistic seismic hazard analysis (PSHA). Notwithstanding the vital importance for PSHA to incorporate properly the epistemic uncertainties, we argue that the use of the logic tree in a PSHA context has conceptual and practical drawbacks. Despite some of these drawbacks have been reported in the past, a careful evaluation of their impact on PSHA is still lacking. This is the goal of the present work. In brief, we show that i) PSHA practice does not meet the assumptions that stand behind the logic tree scheme; ii) the output of a logic tree is often misinterpreted and/or misleading, e.g., the use of percentiles (median included) in a logic tree scheme raises theoretical difficulties from a probabilistic point of view; iii) in case the assumptions that stand behind a logic tree are actually met, this leads to several problems in testing any PSHA model. We suggest a different strategy - based on ensemble modeling - to account for epistemic uncertainties in a more proper probabilistic framework. Finally, we show that in many PSHA practical applications, the logic tree is de facto loosely applied to build sound ensemble models.
Comparing M5 Model Trees and Neural Networks for River Level Forecasting
Khan, S.; See, L.
2005-12-01
Artificial neural networks (ANNs) have been the subject of much research activity in hydrological modelling over the last decade yet this represents only one data-driven modelling approach from among a very rich set. M5 model trees are an example of a technique that has had little application in the hydrological domain yet the results are promising (Solomatine and Xue, 2004). They are a machine learning approach that combines regression trees and classification. The input space is partitioned into subsets based on entropy measures, and regression equations are then fit to these subsets. The advantages over ANNs are (a) their ability to provide knowledge in the form of a decision tree and (b) much faster training times. This has important implications for operational use as they are not black box models. In this study ANNs, M5 model trees and time series analysis have been used to develop models to predict river levels at a gauging station in the River Ouse catchment in Northern England. Two lead times have been used: t+6 and t+24 hours. The input data consisted of historical levels at the gauging stations, upstream level data and rainfall from five rain gauges across the catchment, determined by correlation with the output. The results of the study showed that the ANNs outperformed both the M5 model trees and time series approaches when considering global goodness-of-fit measures such as root mean squared error and coefficient of efficiency. However, the difference in performance between the ANNs and M5 model trees was not large, e.g. 1 percent difference in coefficient of efficiency for t+6 hours. When considering the longer lead time of t+24 hours, the performance of the ANNs and M5 model trees almost converged. The M5 model tree, however, also provides the rules of operation. The first partition for both the t+6 and t+24 hour models was determined by the value of the river level at one of the upstream stations. The individual regression equations associated with
Graduate Induction Training Techniques: A New Model for Fostering Creativity
Education & Training, 2002
2002-01-01
Describes research into the way graduates are inducted into an organization. Investigates, in particular, the extent to which organizations encourage innovation among their future managers. Contends that, while there is much talk about fostering innovation, creativity and entrepreneurship, the approaches used tend to be counter-productive. Puts…
Donor chimera model for tolerance induction in transplantation
Rezaee, F.; Peppelenbosch, M.; Dashty, M.
Tolerance induction is the basis of a successful transplantation with the goal being the re-establishment of homeostasis after transplantation. Non-autograft transplantation disrupts this maintenance drastically which would be avoided by administration of a novel procedure. At present, the blood
Complex Model of Induction Heating - Demounting of Shaft Flange
Directory of Open Access Journals (Sweden)
Milan Krasl
2004-01-01
Full Text Available This paper deals with exemplary solutions of one specifies problem of induction heating. This problem was partly determined by means of numerical method as a light-coupling problem. Numerical solutions were calculated with the help of professional programs (Ansys, Fluent, QuickField. Results of the solution and comparison with measurements are discussed in conclusion.
Yu, Kailiang; Foster, Adrianna
2016-04-01
Past studies have largely focused on hydraulic redistribution (HR) in trees, shrubs, and grasses, and recognized its role in interspecies interactions. HR in plants that conduct crassulacean acid metabolism (CAM), however, remains poorly investigated, as does the effect of HR on transpiration in different vegetation associations (i.e., tree-grass, CAM-grass, and tree-CAM associations). We have developed a mechanistic model to investigate the net direction and magnitude of HR at the patch scale for tree-grass, CAM-grass, and tree-CAM associations at the growing season to yearly timescale. The modeling results show that deep-rooted CAM plants in CAM-grass associations could perform hydraulic lift at a higher rate than trees in tree-grass associations in a relatively wet environment, as explained by a significant increase in grass transpiration rate in the shallow soil layer, balancing a lower transpiration rate by CAM plants. By comparison, trees in tree-CAM associations may perform hydraulic descent at a higher rate than those in tree-grass associations in a dry environment. Model simulations also show that hydraulic lift increases the transpiration of shallow-rooted plants, while hydraulic descent increases that of deep-rooted plants. CAM plants transpire during the night and thus perform HR during the day. Based on these model simulations, we suggest that the ability of CAM plants to perform HR at a higher rate may have different effects on the surrounding plant community than those of plants with C3 or C4 photosynthetic pathways (i.e., diurnal transpiration).
A simple model of trees for unicellular maps
Chapuy, Guillaume; Fusy, Eric
2012-01-01
We consider unicellular maps, or polygon gluings, of fixed genus. A few years ago the first author gave a recursive bijection transforming unicellular maps into trees, explaining the presence of Catalan numbers in counting formulas for these objects. In this paper, we give another bijection that explicitly describes the "recursive part" of the first bijection. As a result we obtain a very simple description of unicellular maps as pairs made by a plane tree and a permutation-like structure. All the previously known formulas follow as an immediate corollary or easy exercise, thus giving a bijective proof for each of them, in a unified way. For some of these formulas, this is the first bijective proof, e.g. the Harer-Zagier recurrence formula, or the Lehman-Walsh/Goupil-Schaeffer formulas. Thanks to previous work of the second author this also leads us to a new expression for Stanley character polynomials, which evaluate irreducible characters of the symmetric group.
Directory of Open Access Journals (Sweden)
Rohulla Kosari Langari
2014-02-01
Full Text Available Change the world through information technology and Internet development, has created competitive knowledge in the field of electronic commerce, lead to increasing in competitive potential among organizations. In this condition The increasing rate of commercial deals developing guaranteed with speed and light quality is due to provide dynamic system of electronic banking until by using modern technology to facilitate electronic business process. Internet banking is enumerate as a potential opportunity the fundamental pillars and determinates of e-banking that in cyber space has been faced with various obstacles and threats. One of this challenge is complete uncertainty in security guarantee of financial transactions also exist of suspicious and unusual behavior with mail fraud for financial abuse. Now various systems because of intelligence mechanical methods and data mining technique has been designed for fraud detection in users’ behaviors and applied in various industrial such as insurance, medicine and banking. Main of article has been recognizing of unusual users behaviors in e-banking system. Therefore, detection behavior user and categories of emerged patterns to paper the conditions for predicting unauthorized penetration and detection of suspicious behavior. Since detection behavior user in internet system has been uncertainty and records of transactions can be useful to understand these movement and therefore among machine method, decision tree technique is considered common tool for classification and prediction, therefore in this research at first has determinate banking effective variable and weight of everything in internet behaviors production and in continuation combining of various behaviors manner draw out such as the model of inductive rules to provide ability recognizing of different behaviors. At least trend of four algorithm Chaid, ex_Chaid, C4.5, C5.0 has compared and evaluated for classification and detection of exist
Truth-telling and Nash equilibria in minimum cost spanning tree models
DEFF Research Database (Denmark)
Hougaard, Jens Leth; Tvede, Mich
2012-01-01
In this paper we consider the minimum cost spanning tree model. We assume that a central planner aims at implementing a minimum cost spanning tree not knowing the true link costs. The central planner sets up a game where agents announce link costs, a tree is chosen and costs are allocated according...... to the rules of the game. We characterize ways of allocating costs such that true announcements constitute Nash equilibria both in case of full and incomplete information. In particular, we find that the Shapley rule based on the irreducible cost matrix is consistent with truthful announcements while a series...
Development of Motor Model of Rotor Slot Harmonics for Speed Sensorless Control of Induction Motor
Okubo, Tatsuya; Ishida, Muneaki; Doki, Shinji
This paper proposes a novel mathematical dynamic model to represent steady-state and transient-state characteristics of rotor slot harmonics of an induction motor for sensorless control. Although it is well known that the rotor slot harmonics originate from the mechanical structure of the induction motor, a mathematical model that describes the relationship between stator/rotor currents of the induction motor and the slot harmonics has not yet been proposed. Therefore, in this paper, a three-phase model of the induction motor that depicts the rotor slot harmonics is developed by taking into consideration the magnetomotive force harmonics and the change in the magnetic air gap caused by the rotor slots. Moreover, the validity of the proposed model is verified by comparing the experimental results and the calculated values.
The tree shrews: adjuncts and alternatives to primates as models for biomedical research.
Cao, J; Yang, E-B; Su, J-J; Li, Y; Chow, P
2003-06-01
The tree shrews are non-rodent, primate-like, small animals. There is increasing interest in using them to establish animal models for medical and biological research. This review focuses on the use of the tree shrews in in vivo studies on viral hepatitis, hepatocellular carcinoma (HCC), myopia, and psychosocial stress. Because of the susceptibility of the tree shrews (Tupaia belangeri) and their hepatocytes to infection with human hepatitis B virus (HBV) in vivo and in vitro, these animals have been used to establish human hepatitis virus-induced hepatitis and human HBV- and aflatoxin B1-associated HCC models. As these animals are phylogenetically close to primates in evolution and have a well-developed visual system and color vision in some species, they have been utilized to establish myopia models. Because dramatic behavioral, physiological, and neuroendocrine changes in subordinate male tree shrews are similar to those observed in depressed human patients, the tree shrews have been successfully employed to experimentally study psychosocial stress. However, the tree shrews holds significant promise as research models and great use could be made of these animals in biomedical research.
THE critical exponent of the tree lattice generating function in the eden model
Zobov, V. E.
2010-11-01
We consider the increase in the number of trees as their size increases in the Eden growth model on simple and face-centered hypercubic lattices in different space dimensions. We propose a first-order partial differential equation for the tree generating function, which allows relating the exponent at the critical point of this function to the perimeter of the most probable tree. We estimate tree perimeters for the lattices considered. The theoretical values of the exponents agree well with the values previously obtained by computer modeling. We thus explain the closeness of the dimension dependences of the exponents of the simple and face-centered lattices and their difference from the results in the Bethe lattice approximation.
The effect of tea tree oil (Melaleuca alternifolia) on wound healing using a dressing model.
Chin, Karen B; Cordell, Barbara
2013-12-01
Numerous studies have shown the promising antibacterial effects of Melaleuca alternifolia, or tea tree essential oil. The study detailed here replicates in humans a 2004 in vitro study that used a dressing model over Petri dishes to determine the antimicrobial effects of the fumes of tea tree essential oil. The current study used the same dressing model with patients who had wounds infected with Staphylococcus aureus. Ten participants volunteered for the quasi-experimental study, and four of the 10 were used as matched participants to compare wound healing times between conventional treatment alone and conventional treatment plus fumes of tea tree essential oil. The results demonstrated decreased healing time in all but one of the participants treated with tea tree oil. The differences between the matched participants were striking. The results of this small investigational study indicate that additional study is warranted.
Effect of different tree mortality patterns on stand development in the forest model SIBYLA
Directory of Open Access Journals (Sweden)
Trombik Jiří
2016-09-01
Full Text Available Forest mortality critically affects stand structure and the quality of ecosystem services provided by forests. Spruce bark beetle (Ips typographus generates rather complex infestation and mortality patterns, and implementation of such patterns in forest models is challenging. We present here the procedure, which allows to simulate the bark beetle-related tree mortality in the forest dynamics model Sibyla. We explored how sensitive various production and stand structure indicators are to tree mortality patterns, which can be generated by bark beetles. We compared the simulation outputs for three unmanaged forest stands with 40, 70 and 100% proportion of spruce as affected by the disturbance-related mortality that occurred in a random pattern and in a patchy pattern. The used tree species and age class-specific mortality rates were derived from the disturbance-related mortality records from Slovakia. The proposed algorithm was developed in the SQLite using the Python language, and the algorithm allowed us to define the degree of spatial clustering of dead trees ranging from a random distribution to a completely clustered distribution; a number of trees that died in either mode is set to remain equal. We found significant differences between the long-term developments of the three investigated forest stands, but we found very little effect of the tested mortality modes on stand increment, tree species composition and diversity, and tree size diversity. Hence, our hypothesis that the different pattern of dead trees emergence should affect the competitive interactions between trees and regeneration, and thus affect selected productivity and stand structure indicators was not confirmed.
Modelling of Random Textured Tandem Silicon Solar Cells Characteristics: Decision Tree Approach
Directory of Open Access Journals (Sweden)
R.S. Kamath
2016-11-01
Full Text Available We report decision tree (DT modeling of randomly textured tandem silicon solar cells characteristics. The photovoltaic modules of silicon-based solar cells are extremely popular due to their high efficiency and longer lifetime. Decision tree model is one of the most common data mining models can be used for predictive analytics. The reported investigation depicts optimum decision tree architecture achieved by tuning parameters such as Min split, Min bucket, Max depth and Complexity. DT model, thus derived is easy to understand and entails recursive partitioning approach implemented in the “rpart” package. Moreover the performance of the model is evaluated with reference Mean Square Error (MSE estimate of error rate. The modeling of the random textured silicon solar cells reveals strong correlation of efficiency with “Fill factor” and “thickness of a-Si layer”.
Modeling and Simulation of Five Phase Induction Motor using MATLAB/Simulink
Directory of Open Access Journals (Sweden)
Kiran S. Aher
2016-05-01
Full Text Available Three phase Induction motors are invariably used in many residential, commercial, industrial & utility applications because of low cost, reliable operation, robust operation and low maintenance. Multiphase motor drives with phase number greater than three phase leads to an improvement in the medium to high power drives application. The multiphase induction motor find application in special and critical area where high reliability is demanded such as Electric vehicles/Hybrid Electric vehicles, aerospace application, ship propulsion and locomotive traction and in high power application. This paper presents the MATLAB/Simulink implementation of Induction motor. Reference frame theory is used for simulation of the five phase induction motor. Dynamic model are employed to better understand the behavior of the induction motor in both steady state and transient state.
Modeling transcriptional networks regulating secondary growth and wood formation in forest trees.
Liu, Lijun; Filkov, Vladimir; Groover, Andrew
2014-06-01
The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary growth), but a comprehensive understanding of how these genes interact to influence woody growth is currently lacking. Modeling transcriptional networks has recently been made tractable by next-generation sequencing-based technologies that can comprehensively catalog gene expression and transcription factor-binding genome-wide, but has not yet been extensively applied to undomesticated tree species or woody growth. Here we discuss basic features of transcriptional networks, approaches for modeling biological networks, and examples of biological network models developed for forest trees to date. We discuss how transcriptional network research is being developed in the model forest tree genus, Populus, and how this research area can be further developed and applied. Transcriptional network models for forest tree secondary growth and wood formation could ultimately provide new predictive models to accelerate hypothesis-driven research and develop new breeding applications.
Don C. Bragg
2002-01-01
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...
Sterck, F.J.; Schieving, F.; Lemmens, A.; Pons, T.L.
2005-01-01
Here we present a functional-structural plant model that integrates the growth of metamers into a growing, three-dimensional tree structure, and study the effects of different constraints and strategies on tree performance in different canopies. The tree is a three-dimensional system of connected me
Chen, W. J.; Tan, X. J.; Cai, M.
2017-07-01
Parameter identification method of equivalent circuit models for Li-ion batteries using the advanced tree seeds algorithm is proposed. On one hand, since the electrochemical models are not suitable for the design of battery management system, the equivalent circuit models are commonly adopted for on-board applications. On the other hand, by building up the objective function for optimization, the tree seeds algorithm can be used to identify the parameters of equivalent circuit models. Experimental verifications under different profiles demonstrate the suggested method can achieve a better result with lower complexity, more accuracy and robustness, which make it a reasonable alternative for other identification algorithms.
Modeling the survival kinetics of Salmonella in tree nuts for use in risk assessment.
Santillana Farakos, Sofia M; Pouillot, Régis; Anderson, Nathan; Johnson, Rhoma; Son, Insook; Van Doren, Jane
2016-06-16
Salmonella has been shown to survive in tree nuts over long periods of time. This survival capacity and its variability are key elements for risk assessment of Salmonella in tree nuts. The aim of this study was to develop a mathematical model to predict survival of Salmonella in tree nuts at ambient storage temperatures that considers variability and uncertainty separately and can easily be incorporated into a risk assessment model. Data on Salmonella survival on raw almonds, pecans, pistachios and walnuts were collected from the peer reviewed literature. The Weibull model was chosen as the baseline model and various fixed effect and mixed effect models were fit to the data. The best model identified through statistical analysis testing was then used to develop a hierarchical Bayesian model. Salmonella in tree nuts showed slow declines at temperatures ranging from 21°C to 24°C. A high degree of variability in survival was observed across tree nut studies reported in the literature. Statistical analysis results indicated that the best applicable model was a mixed effect model that included a fixed and random variation of δ per tree nut (which is the time it takes for the first log10 reduction) and a fixed variation of ρ per tree nut (parameter which defines the shape of the curve). Higher estimated survival rates (δ) were obtained for Salmonella on pistachios, followed in decreasing order by pecans, almonds and walnuts. The posterior distributions obtained from Bayesian inference were used to estimate the variability in the log10 decrease levels in survival for each tree nut, and the uncertainty of these estimates. These modeled uncertainty and variability distributions of the estimates can be used to obtain a complete exposure assessment of Salmonella in tree nuts when including time-temperature parameters for storage and consumption data. The statistical approach presented in this study may be applied to any studies that aim to develop predictive models to be
Cochrane, John. H.; Longstaff, Francis A.; Santa-Clara, Pedro
2004-01-01
We solve a model with two â€œLucas trees.â€ Each tree has i.i.d. dividend growth. The investor has log utility and consumes the sum of the two treesâ€™ dividends. This model produces interesting asset-pricing dynamics, despite its simple ingredients. Investors want to rebalance their portfolios after any change in value. Since the size of the trees is fixed, however, prices must adjust to oï¬€set this desire. As a result, expected returns, excess returns, and return volatility all vary throug...
Inverse modeling and animation of growing single-stemmed trees at interactive rates
S. Rudnick; L. Linsen; E.G. McPherson
2007-01-01
For city planning purposes, animations of growing trees of several species can be used to deduce which species may best fit a particular environment. The models used for the animation must conform to real measured data. We present an approach for inverse modeling to fit global growth parameters. The model comprises local production rules, which are iteratively and...
An object-oriented forest landscape model and its representation of tree species
Hong S. He; David J. Mladenoff; Joel Boeder
1999-01-01
LANDIS is a forest landscape model that simulates the interaction of large landscape processes and forest successional dynamics at tree species level. We discuss how object-oriented design (OOD) approaches such as modularity, abstraction and encapsulation are integrated into the design of LANDIS. We show that using OOD approaches, model decisions (olden as model...
Hayes, Brett K; Heit, Evan; Swendsen, Haruka
2010-03-01
Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.
Development of a model of the coronary arterial tree for the 4D XCAT phantom
Fung, George S. K.; Segars, W. Paul; Gullberg, Grant T.; Tsui, Benjamin M. W.
2011-09-01
A detailed three-dimensional (3D) model of the coronary artery tree with cardiac motion has great potential for applications in a wide variety of medical imaging research areas. In this work, we first developed a computer-generated 3D model of the coronary arterial tree for the heart in the extended cardiac-torso (XCAT) phantom, thereby creating a realistic computer model of the human anatomy. The coronary arterial tree model was based on two datasets: (1) a gated cardiac dual-source computed tomography (CT) angiographic dataset obtained from a normal human subject and (2) statistical morphometric data of porcine hearts. The initial proximal segments of the vasculature and the anatomical details of the boundaries of the ventricles were defined by segmenting the CT data. An iterative rule-based generation method was developed and applied to extend the coronary arterial tree beyond the initial proximal segments. The algorithm was governed by three factors: (1) statistical morphometric measurements of the connectivity, lengths and diameters of the arterial segments; (2) avoidance forces from other vessel segments and the boundaries of the myocardium, and (3) optimality principles which minimize the drag force at the bifurcations of the generated tree. Using this algorithm, the 3D computational model of the largest six orders of the coronary arterial tree was generated, which spread across the myocardium of the left and right ventricles. The 3D coronary arterial tree model was then extended to 4D to simulate different cardiac phases by deforming the original 3D model according to the motion vector map of the 4D cardiac model of the XCAT phantom at the corresponding phases. As a result, a detailed and realistic 4D model of the coronary arterial tree was developed for the XCAT phantom by imposing constraints of anatomical and physiological characteristics of the coronary vasculature. This new 4D coronary artery tree model provides a unique simulation tool that can be
Exact finite-size corrections for the spanning-tree model under different boundary conditions
Izmailian, N. Sh.; Kenna, R.
2015-02-01
We express the partition functions of the spanning tree on finite square lattices under five different sets of boundary conditions in terms of a principal partition function with twisted-boundary conditions. Based on these expressions, we derive the exact asymptotic expansions of the logarithm of the partition function for each case. We have also established several groups of identities relating spanning-tree partition functions for the different boundary conditions. We also explain an apparent discrepancy between logarithmic correction terms in the free energy for a two-dimensional spanning-tree model with periodic and free-boundary conditions and conformal field theory predictions. We have obtained corner free energy for the spanning tree under free-boundary conditions in full agreement with conformal field theory predictions.
Extraction of tree crowns from mobile laser scanning data using a marked point process model
Li, Jonathan; Yu, Yongtao; Guan, Haiyan; Gong, Zheng
2016-03-01
For the purpose of realistic visualisation in 3D city models, we present a marked point process based method for extracting tree-crowns from mobile laser scanning (MLS) data. First, we apply a modified IDW interpolation to generate a geo-referenced feature image, by which a histogram analysis is applied to separate high objects(e.g. trees and lightpoles) from low objects(e.g. road, ground, low vegetation). Next, we calculate grey differences of each pixel with its neighbors to find the local maxima as potential tree-crown seeds, and then use a grouping-and-centralizing procedure to remove the redundants from the seeds. Finally, we employ a marked point process to the generated geo-referenced image via the seeds. Two experiments have been conducted to test the efficiency and feasibility of our tree-extraction algorithm using RIEGL VMX-450 MLS data.
A Method of Eliminating Noises in Web Pages by Style Tree Model and Its Applications
Institute of Scientific and Technical Information of China (English)
ZHAO Cheng-li; YI Dong-yun
2004-01-01
A Web page typically contains many information blocks.Apart from the main content blocks, it usually has such blocks as navigation panels, copyright and privacy notices, and advertisements.We call these blocks the noisy blocks.The noises in Web pages can seriously harm Web data mining.To the question of eliminating these noises, we introduce a new tree structure, called Style Tree, and study an algorithm how to construct a site style tree.The Style Tree Model is employed to detect and eliminate noises in any Web pages of the site.An information based measure to determine which element node is noisy is also constructed.In addition, the applications of this method are discussed in detail.Experimental results show that our noises elimination technique is able to improve the mining results significantly.
Directory of Open Access Journals (Sweden)
Marijke van Kuijk
2014-07-01
Full Text Available Excessive growth of non-woody plants and shrubs on degraded lands can strongly hamper tree growth and thus secondary forest succession. A common method to accelerate succession, called liberation, involves opening up the vegetation canopy around young target trees. This can increase growth of target trees by reducing competition for light with neighboring plants. However, liberation has not always the desired effect, likely due to differences in light requirement between tree species. Here we present a 3D-model, which calculates photosynthetic rate of individual trees in a vegetation stand. It enables us to examine how stature, crown structure and physiological traits of target trees and characteristics of the surrounding vegetation together determine effects of light on tree growth. The model was applied to a liberation experiment conducted with three pioneer species in a young secondary forest in Vietnam. Species responded differently to the treatment depending on their height, crown structure and their shade-tolerance level. Model simulations revealed practical thresholds over which the tree growth response is heavily influenced by the height and density of surrounding vegetation and gap radius. There were strong correlations between calculated photosynthetic rates and observed growth: the model was well able to predict growth of trees in young forests and the effects of liberation there upon. Thus our model serves as a useful tool to analyze light competition between young trees and surrounding vegetation and may help assess the potential effect of tree liberation.
Model Based Automatic Segmentation Of Tree Stems From Single Scan Data
Boesch, R.
2013-10-01
Forest inventories collect feature data manually on terrestrial field plots. Measuring large amounts of breast height diameters and tree positions is time consuming. Terrestrial laser scanning could be an additional instrument to collect precise and full inventory data in the 3D space. As a preliminary assumption single scan data is used to evaluate a minimal data acquisition scheme. To extract features like trees and diameter from the scanned point cloud, a simple geometric model world is defined in 3D. Trees are cylinder shapes vertically located on a plane. Using a RANSAC-based segmentation approach, cylinders are fitted iteratively in the point cloud. Several threshold parameters increase the robustness of the segmentation model and extract point clouds of single trees, which still contain branches and the tree crown. Fitting circles along the stem using point cloud slices allows to refine the effective diameter for customized heights. The cross section of a single tree point cloud covers only the semi circle towards the scan location, but is still contiguous enough to estimate diameters by using a robust circle fitting method.
Exploring the 'divergence' problem using a simple process-based model of tree growth
Li, Guangqi; Harrison, Sandy P.; Prentice, I. Colin
2016-04-01
There has been an apparent change in the sensitivity of tree rings to temperature in northern extratropical regions since the 1980s - a phenomenon often referred to as the divergence problem. Several potential explanations have been suggested to explain the decoupling between ring width (or density) and temperature, including exceedance of limiting temperature thresholds with global warming, changes in light availability with global dimming, the increasing importance of soil or atmospheric drought as a limitation to tree growth, or the CO2 'fertilization effect'. Here we use a simple, process-based tree-growth and carbon allocation model to explore these hypotheses. While changes in light availability and drought contribute to explain the declining influence of temperature on tree growth, the most important factor is changes in carbon allocation to roots and mycorrhizae in response to increasing [CO2] and the demand for increased nutrients to support photosynthesis. The magnitude of the increase in below-ground allocation, and hence the relative importance of this mechanism versus climate in controlling tree radial growth, appears to be influenced by nutrient and water availability. The potential importance of changes in carbon allocation challenges the use of statistical models for climate reconstructions from tree rings during intervals when [CO2] was different from historical values.
Towards a portable, scalable, open source model of tree cover derived from Landsat spectra
Greenberg, J. A.; Xu, Q.; Morrison, B. D.; Xu, Z.; Man, A.; Fredrickson, M. M.; Ramirez, C.; Li, B.
2016-12-01
Tree cover is a key parameter used in a variety of applications, including ecosystem and fire behavior modeling, wildlife management, and is the primary way by which a variety of biomes are classified. At large scales, quantification of tree cover can help elucidate changes in deforestation and forest recovery and understand the relationship between climate and forest distributions. To determine tree cover at large scales, remote sensing-based methods are required. There exist a variety of products at various scales and extents, including two global products, Hansen et al.'s treecover2000 product and Sexton et al.'s Landsat Vegetation Continuous Fields (VCF) product. While these products serve an important role, they are only available for a limited set of dates: treecover2000 is available for the year 2000, and Landsat VCF for 2000 and 2005. In this analysis, we created a single model of tree cover as a function of Landsat spectra that is both calibrated and validated using small footprint LiDAR estimates of tree cover, trained across multiple Landsat scenes. Our model was found to be accurate and portable across space and time largely due to using a large amount of LiDAR - Landsat pixel pairs across multiple Landsat scenes to capture both sensor and scene heterogeneity. We will be releasing the model itself, rather than time-limited products, to allow other users to apply the model to any reflectance-calibrated Landsat scene from any time period.
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
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Yu Liang
Full Text Available Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance. We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
Risk Modelling of Late Spring Frost Damage on Fruit Trees, Case Study; Apple Tree, Mashhad Plain
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M Rahimi
2012-02-01
Full Text Available Mashhad plain is one of the most important regions of Apple cultivated areas. Occurring spring late frost creates a lot of damages on bud and decreasing the yield of Apple in this region. Assessment and risk modeling of frost damage would be useful to manage and decrease the damage. The study area is a part of Khorasan Razavi province which is located in Mashhad plain. This region is located in Northeast Iran (36º to 37 º N, 58 º 30' to 60 º E. The area of this region is about 13000 square km which is about one tenth of Khorasan province area. In order to modeling frost damage risk 12 affective parameters including climatological(Minimum temperature, temperature decreasing rate, temperature Increasing rate, Julian days of frost, cumulative degree days, Area under zero line, and frost duration and geographical parameters (Elevation, Longitude, Latitude, Aspect, and slope were selected. 3 damage full radiative frosts were selected in the period of Apple flowering time which was dated 20 April 2003, 8 April 2005, and 28 March 2005. Required meteorological data were collected from 9 meteorological standard stations inside and outside of study area. Linear multiple regression were used to modeling the relationship. The map for each parameter was plotted by using suitable interpolation method including IDW; Spline; Kriging. A grid map was defined with 5 by 5 kilometers to extract enough data for entering to the model. The regression equation was significant at the level of 99% significance. By using this equation the predicted amounts of frost risk damage were calculated for each point of grid and also the map was plotted. The regression equation of observed and predicted frost damage risk was provided by correlation of 0.93 and the error map also was prepared. According to this study in frost of 31 Farvardin 1388 South West parts of the plain estimated as the most frost risk areas by %53.19 and the southeast parts were estimated as the least
Investigation of the Effect of Traffic Parameters on Road Hazard Using Classification Tree Model
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Md. Mahmud Hasan
2012-09-01
Full Text Available This paper presents a method for the identification of hazardous situations on the freeways. For this study, about 18 km long section of Eastern Freeway in Melbourne, Australia was selected as a test bed. Three categories of data i.e. traffic, weather and accident record data were used for the analysis and modelling. In developing the crash risk probability model, classification tree based model was developed in this study. In formulating the models, it was found that weather conditions did not have significant impact on accident occurrence so the classification tree was built using two traffic indices; traffic flow and vehicle speed only. The formulated classification tree is able to identify the possible hazard and non-hazard situations on freeway. The outcome of the study will aid the hazard mitigation strategies.
Improved allometric models to estimate the aboveground biomass of tropical trees.
Chave, Jérôme; Réjou-Méchain, Maxime; Búrquez, Alberto; Chidumayo, Emmanuel; Colgan, Matthew S; Delitti, Welington B C; Duque, Alvaro; Eid, Tron; Fearnside, Philip M; Goodman, Rosa C; Henry, Matieu; Martínez-Yrízar, Angelina; Mugasha, Wilson A; Muller-Landau, Helene C; Mencuccini, Maurizio; Nelson, Bruce W; Ngomanda, Alfred; Nogueira, Euler M; Ortiz-Malavassi, Edgar; Pélissier, Raphaël; Ploton, Pierre; Ryan, Casey M; Saldarriaga, Juan G; Vieilledent, Ghislain
2014-10-01
Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.
Directory of Open Access Journals (Sweden)
Xiliang Ni
2014-04-01
Full Text Available The ultimate goal of our multi-article series is to demonstrate the Allometric Scaling and Resource Limitation (ASRL approach for mapping tree heights and biomass. This third article tests the feasibility of the optimized ASRL model over China at both site (14 meteorological stations and continental scales. Tree heights from the Geoscience Laser Altimeter System (GLAS waveform data are used for the model optimizations. Three selected ASRL parameters (area of single leaf, α; exponent for canopy radius, η; and root absorption efficiency, γ are iteratively adjusted to minimize differences between the references and predicted tree heights. Key climatic variables (e.g., temperature, precipitation, and solar radiation are needed for the model simulations. We also exploit the independent GLAS and in situ tree heights to examine the model performance. The predicted tree heights at the site scale are evaluated against the GLAS tree heights using a two-fold cross validation (RMSE = 1.72 m; R2 = 0.97 and bootstrapping (RMSE = 4.39 m; R2 = 0.81. The modeled tree heights at the continental scale (1 km spatial resolution are compared to both GLAS (RMSE = 6.63 m; R2 = 0.63 and in situ (RMSE = 6.70 m; R2 = 0.52 measurements. Further, inter-comparisons against the existing satellite-based forest height maps have resulted in a moderate degree of agreements. Our results show that the optimized ASRL model is capable of satisfactorily retrieving tree heights over continental China at both scales. Subsequent studies will focus on the estimation of woody biomass after alleviating the discussed limitations.
A Com-Gis Based Decision Tree Model Inagricultural Application
Cheng, Wei; Wang, Ke; Zhang, Xiuying
The problem of agricultural soil pollution by heavy metals has been receiving an increasing attention in the last few decades. Geostatistics module in ArcGIS, could not however efficiently simulate the spatial distribution of heavy metals with satisfied accuracy when the spatial autocorrelation of the study area severely destroyed by human activities. In this study, the classificationand regression tree (CART) has been integrated into ArcGIS using ArcObjects and Visual Basic for Application (VBA) to predict the spatial distribution of soil heavy metals contents in the area severely polluted. This is a great improvement comparing with ordinary Kriging method in ArcGIS. The integrated approach allows for relatively easy, fast, and cost-effective estimation of spatially distributed soil heavy metals pollution.
Transient Model Validation of Fixed-Speed Induction Generator Using Wind Farm Measurements
DEFF Research Database (Denmark)
Rogdakis, Georgios; Garcia-Valle, Rodrigo; Arana Aristi, Iván
2012-01-01
In this paper, an electromagnetic transient model for fixed-speed wind turbines equipped with induction generators is developed and implemented in PSCAD/EMTDC. The model is comprised by: an induction generator, aerodynamic rotor, and a two-mass representation of the shaft system. Model validation...... is conducted by measurement comparison using recordings obtained from switching operations performed at the Nysted OffshoreWind Farm in Denmark. A sensitivity analysis is performed to determine the impact of different model parameters on the simulated response as compared with measurements. This validated...
An Advanced simulation Code for Modeling Inductive Output Tubes
Energy Technology Data Exchange (ETDEWEB)
Thuc Bui; R. Lawrence Ives
2012-04-27
During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing current density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.
Behavior and sensitivity of an optimal tree diameter growth model under data uncertainty
Don C. Bragg
2005-01-01
Using loblolly pine, shortleaf pine, white oak, and northern red oak as examples, this paper considers the behavior of potential relative increment (PRI) models of optimal tree diameter growth under data uncertainity. Recommendations on intial sample size and the PRI iteractive curve fitting process are provided. Combining different state inventories prior to PRI model...
A method for generating stochastic 3D tree models with Python in Autodesk Maya
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Nemanja Stojanović
2016-12-01
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.
Tree-Structured Models for Efficient Multi-Cue Scene Labeling.
Cordts, Marius; Rehfeld, Timo; Enzweiler, Markus; Franke, Uwe; Roth, Stefan
2016-07-19
We propose a novel approach to semantic scene labeling in urban scenarios, which aims to combine excellent recognition performance with highest levels of computational efficiency. To that end, we exploit efficient tree-structured models on two levels: pixels and superpixels. At the pixel level, we propose to unify pixel labeling and the extraction of semantic texton features within a single architecture, so-called encode-and-classify trees. At the superpixel level, we put forward a multi-cue segmentation tree that groups superpixels at multiple granularities. Through learning, the segmentation tree effectively exploits and aggregates a wide range of complementary information present in the data. A tree-structured CRF is then used to jointly infer the labels of all regions across the tree. Finally, we introduce a novel object-centric evaluation method that specifically addresses the urban setting with its strongly varying object scales. Our experiments demonstrate competitive labeling performance compared to the state of the art, while achieving near real-time frame rates of up to 20 fps.
Modelling Water Uptake Provides a New Perspective on Grass and Tree Coexistence.
Mazzacavallo, Michael G; Kulmatiski, Andrew
2015-01-01
Root biomass distributions have long been used to infer patterns of resource uptake. These patterns are used to understand plant growth, plant coexistence and water budgets. Root biomass, however, may be a poor indicator of resource uptake because large roots typically do not absorb water, fine roots do not absorb water from dry soils and roots of different species can be difficult to differentiate. In a sub-tropical savanna, Kruger Park, South Africa, we used a hydrologic tracer experiment to describe the abundance of active grass and tree roots across the soil profile. We then used this tracer data to parameterize a water movement model (Hydrus 1D). The model accounted for water availability and estimated grass and tree water uptake by depth over a growing season. Most root biomass was found in shallow soils (0-20 cm) and tracer data revealed that, within these shallow depths, half of active grass roots were in the top 12 cm while half of active tree roots were in the top 21 cm. However, because shallow soils provided roots with less water than deep soils (20-90 cm), the water movement model indicated that grass and tree water uptake was twice as deep as would be predicted from root biomass or tracer data alone: half of grass and tree water uptake occurred in the top 23 and 43 cm, respectively. Niche partitioning was also greater when estimated from water uptake rather than tracer uptake. Contrary to long-standing assumptions, shallow grass root distributions absorbed 32% less water than slightly deeper tree root distributions when grasses and trees were assumed to have equal water demands. Quantifying water uptake revealed deeper soil water uptake, greater niche partitioning and greater benefits of deep roots than would be estimated from root biomass or tracer uptake data alone.
Donmez, Cenk; Berberoglu, Suha; Erdogan, Mehmet Akif; Tanriover, Anil Akin; Cilek, Ahmet
2015-02-01
Percent tree cover is the percentage of the ground surface area covered by a vertical projection of the outermost perimeter of the plants. It is an important indicator to reveal the condition of forest systems and has a significant importance for ecosystem models as a main input. The aim of this study is to estimate the percent tree cover of various forest stands in a Mediterranean environment based on an empirical relationship between tree coverage and remotely sensed data in Goksu Watershed located at the Eastern Mediterranean coast of Turkey. A regression tree algorithm was used to simulate spatial fractions of Pinus nigra, Cedrus libani, Pinus brutia, Juniperus excelsa and Quercus cerris using multi-temporal LANDSAT TM/ETM data as predictor variables and land cover information. Two scenes of high resolution GeoEye-1 images were employed for training and testing the model. The predictor variables were incorporated in addition to biophysical variables estimated from the LANDSAT TM/ETM data. Additionally, normalised difference vegetation index (NDVI) was incorporated to LANDSAT TM/ETM band settings as a biophysical variable. Stepwise linear regression (SLR) was applied for selecting the relevant bands to employ in regression tree process. SLR-selected variables produced accurate results in the model with a high correlation coefficient of 0.80. The output values ranged from 0 to 100 %. The different tree species were mapped in 30 m resolution in respect to elevation. Percent tree cover map as a final output was derived using LANDSAT TM/ETM image over Goksu Watershed and the biophysical variables. The results were tested using high spatial resolution GeoEye-1 images. Thus, the combination of the RT algorithm and higher resolution data for percent tree cover mapping were tested and examined in a complex Mediterranean environment.
Majority rule has transition ratio 4 on Yule trees under a 2-state symmetric model.
Mossel, Elchanan; Steel, Mike
2014-11-01
Inferring the ancestral state at the root of a phylogenetic tree from states observed at the leaves is a problem arising in evolutionary biology. The simplest technique - majority rule - estimates the root state by the most frequently occurring state at the leaves. Alternative methods - such as maximum parsimony - explicitly take the tree structure into account. Since either method can outperform the other on particular trees, it is useful to consider the accuracy of the methods on trees generated under some evolutionary null model, such as a Yule pure-birth model. In this short note, we answer a recently posed question concerning the performance of majority rule on Yule trees under a symmetric 2-state Markovian substitution model of character state change. We show that majority rule is accurate precisely when the ratio of the birth (speciation) rate of the Yule process to the substitution rate exceeds the value 4. By contrast, maximum parsimony has been shown to be accurate only when this ratio is at least 6. Our proof relies on a second moment calculation, coupling, and a novel application of a reflection principle.
Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models
Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel
2016-01-01
Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.
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Sailesh Ranjitkar
2014-08-01
Full Text Available The tree rhododendrons include the most widely distributed Himalayan Rhododendron species belonging to the subsection Arborea. Distributions of two members of this sub-species were modelled using bioclimatic data for current conditions (1950–2000. A subset of the least correlated bioclimatic variables was used for ecological niche modelling (ENM. We used an ENM ensemble method in the BiodiversityR R-package to map the suitable climatic space for tree rhododendrons based on 217 point location records. Ensemble bioclimatic models for tree rhododendrons had high predictive power with bioclimatic variables, which also separated the climatic spaces for the two species. Tree rhododendrons were found occurring in a wide range of climate and the distributional limits were associated with isothermality, temperature ranges, temperature of the wettest quarter, and precipitation of the warmest quarter of the year. The most suitable climatic space for tree rhododendrons was predicted to be in western Yunnan, China, with suitability declining towards the west and east. Its occurrence in a wide range of climatic settings with highly dissected habitats speaks to the adaptive capacity of the species, which might open up future options for their conservation planning in regions where they are listed as threatened.
Can plasticity make spatial structure irrelevant in individual-tree models?
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Oscar García
2014-08-01
Full Text Available Background Distance-dependent individual-tree models have commonly been found to add little predictive power to that of distance-independent ones. One possible reason is plasticity, the ability of trees to lean and to alter crown and root development to better occupy available growing space. Being able to redeploy foliage (and roots into canopy gaps and less contested areas can diminish the importance of stem ground locations. Methods Plasticity was simulated for 3 intensively measured forest stands, to see to what extent and under what conditions the allocation of resources (e.g., light to the individual trees depended on their ground coordinates. The data came from 50 × 60 m stem-mapped plots in natural monospecific stands of jack pine, trembling aspen and black spruce from central Canada. Explicit perfect-plasticity equations were derived for tessellation-type models. Results Qualitatively similar simulation results were obtained under a variety of modelling assumptions. The effects of plasticity varied somewhat with stand uniformity and with assumed plasticity limits and other factors. Stand-level implications for canopy depth, distribution modelling and total productivity were examined. Conclusions Generally, under what seem like conservative maximum plasticity constraints, spatial structure accounted for less than 10% of the variance in resource allocation. The perfect-plasticity equations approximated well the simulation results from tessellation models, but not those from models with less extreme competition asymmetry. Whole-stand perfect plasticity approximations seem an attractive alternative to individual-tree models.
Diagnosis of Wind Energy System Faults Part I : Modeling of the Squirrel Cage Induction Generator
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Lahcène Noureddine
2015-08-01
Full Text Available Generating electrical power from wind energy is becoming increasingly important throughout the world. This fast development has attracted many researchers and electrical engineers to work on this field. The authors develop a dynamic model of the squirrel cage induction generator exists usually on wind energy systems, for the diagnosis of broken rotor bars defects from an approach of magnetically coupled multiple circuits. The generalized model is established on the base of mathematical recurrences. The winding function theory is used for determining the rotor resistances and the inductances in the case of n- broken bars. Simulation results, in Part. II of this paper, confirm the validity of the proposed model.
Measurements and modelling of low-frequency disturbances in induction machines
Energy Technology Data Exchange (ETDEWEB)
Thiringer, T. [Chalmers Univ. of Technology, Goeteborg (Sweden). Dept. of Electric Power Engineering
1996-12-01
The thesis deals with the dynamic response of the induction machine to low frequency perturbations in the shaft torque, supply voltage and supply frequency. Also the response of a two-machine group connected to a weak grid is investigated. The results predicted by various induction models are compared with measurements performed on a laboratory set-up. Furthermore, the influence of machine and grid parameters, machine temperature, phase compensating capacitors, skin effect, saturation level and operating points is studied. The results predicted by the fifth-order non-linear Park model agree well with the measured induction machine responses to shaft torque, supply frequency and voltage magnitude perturbations. To determine the electric power response to very low-frequency perturbations in the magnitude of the supply voltage, the Park model must be modified to take varying iron losses into account. The temperature and supply frequency affect the low frequency dynamics of the induction machine significantly. The static shaft torque is, however, of importance for determining the responses to voltage magnitude perturbations. The performance of reduced-order induction machine models depends on the type of induction machine investigated. Best suited to be represented by reduced-order models are high-slip machines as well as machines that have a low ratio between the stator resistance and leakage reactances. A first-order model can predict the rotor speed, electrodynamic torque and electric power responses to shaft torque and supply frequency perturbations up to a perturbation frequency of at least 1 Hz. A second-order model can determine the same responses also for higher perturbation frequencies, at least up to 3 Hz. Using a third-order model all the responses can be determined up to at least 10 Hz. 48 refs, 45 figs, 14 tabs
The algebra of the general Markov model on phylogenetic trees and networks.
Sumner, J G; Holland, B R; Jarvis, P D
2012-04-01
It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the associated Hadamard transformation, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper, we rectify this shortcoming by showing how to extend the general Markov model on trees to include incompatible edges; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the “splitting” operator that generates the branching process on phylogenetic trees. For simplicity, we proceed by discussing the two state case and then show that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the Hadamard approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give an argument that our extension to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications.
Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad; Matthew P. Peters; Paul G. Rodewald
2011-01-01
Species distribution models (SDMs) to evaluate trees' potential responses to climate change are essential for developing appropriate forest management strategies. However, there is a great need to better understand these models' limitations and evaluate their uncertainties. We have previously developed statistical models of suitable habitat, based on both...
Wang, Yunsheng; Weinacker, Holger; Koch, Barbara
2008-06-12
A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived.
Advanced induction machine model in phase coordinates for wind turbine applications
DEFF Research Database (Denmark)
Fajardo, L.A.; Iov, F.; Hansen, Anca Daniela
2007-01-01
In this paper an advanced phase coordinates squirrel cage induction machine model with time varying electrical parameters affected by magnetic saturation and rotor deep bar effects, is presented. The model uses standard data sheet for characterization of the electrical parameters, it is developed...
DEFF Research Database (Denmark)
Ruano, Luis Alberto Fajardo; Iov, Florin; Medina Reos, J. Aurelio
2007-01-01
A phase coordinates induction generator model with time varying electrical parameters as influenced by magnetic saturation and rotor deep bar effects, is presented in this paper. The model exhibits a per-phase formulation, uses standard data sheet for characterization of the electrical parameters...
Modelling and simulation of multiple single - phase induction motor in parallel connection
Directory of Open Access Journals (Sweden)
Sujitjorn, S.
2006-11-01
Full Text Available A mathematical model for parallel connected n-multiple single-phase induction motors in generalized state-space form is proposed in this paper. The motor group draws electric power from one inverter. The model is developed by the dq-frame theory and was tested against four loading scenarios in which satisfactory results were obtained.
Allometric models for aboveground biomass of ten tree species in northeast China
Directory of Open Access Journals (Sweden)
Shuo Cai
2013-05-01
Full Text Available China contains 119 million hectares of natural forest, much of whichis secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB. The parameter values of the diameter at breast height (DBH, tree height (H, and crown length (CL were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage in 120 trees, which substantially ease the field works. The mean AGB was110,729 kg ha–1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 ≥ 0.939, SEE 0.167. At the latitude level, the estimated AGB of secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise.
Allometric models for aboveground biomass of ten tree species in northeast China
Directory of Open Access Journals (Sweden)
Shuo Cai
2013-07-01
Full Text Available China contains 119 million hectares of natural forest, much of which is secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB. The parameter values of the diameter at breast height (DBH, tree height (H, and crown length (CL were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage in 120 trees, which substantially easy the field works. The mean AGB was 110,729 kg ha1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 = 0.939, SEE 0.167. At the latitude level, the estimated AGBof secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise.
Institute of Scientific and Technical Information of China (English)
Hui-Yong Jiang; Zhong-Xi Huang; Xue-Feng Zhang; Richard Desper; Tong Zhao
2007-01-01
AIM: To construct tree models for classification of diffuse large B-cell lymphomas (DLBCL) by chromosome copy numbers, to compare them with cDNA microarray classification, and to explore models of multi-gene, multi-step and multi-pathway processes of DLBCL tumorigenesis.METHODS: Maximum-weight branching and distance based models were constructed based on the comparative genomic hybridization (CGH) data of 123 DLBCL samples using the established methods and software of Desper et al. A maximum likelihood tree model was also used to analyze the data. By comparing with the results reported in literature, values of tree models in the classification of DLBCL were elucidated.RESULTS: Both the branching and the distance-based trees classified DLBCL into three groups. We combined the classification methods of the two models and classified DLBCL into three categories according to their characteristics. The first group was marked by +Xq, +Xp, -17p and +13q; the second group by +3q, +18q and +18p; and the third group was marked by -6q and +6p. This chromosomal classification was consistent with cDNA classification. It indicated that -6q and +3q were two main events in the tumorigenesis of lymphoma.CONCLUSION: Tree models of lymphoma established from CGH data can be used in the classification of DLBCL. These models can suggest multi-gene, multi-step and multi-pathway processes of tumorigenesis.Two pathways, -6q preceding +6q and +3q preceding +18q, may be important in understanding tumorigenesis of DLBCL. The pathway, -6q preceding +6q, may have a close relationship with the tumorigenesis of non-GCB DLBCL.
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Zulkarnain Lubis
2009-01-01
Full Text Available Problem statement: With emphasis on a cleaner environment and efficient operation, vehicles today rely more and more heavily on electrical power generation for success. Approach: Mathematical modeling the components of the HEV as the three phase induction motor couple to DC motor in hybrid electric vehicle was introduced. The controller of Induction Motor (IM was designed based on input-output feedback linearization technique. It allowed greater electrical generation capacity and the fuel economy and emissions benefits of hybrid electric automotive propulsion. Results: A typical series hybrid electric vehicle was modeled and investigated. Conclusion: Various tests, such as acceleration traversing ramp and fuel consumption and emission were performed on the proposed model of 3 phase induction motor coupler DC motor in electric hybrid vehicles drive.
The multivariate beta process and an extension of the Polya tree model.
Trippa, Lorenzo; Müller, Peter; Johnson, Wesley
2011-03-01
We introduce a novel stochastic process that we term the multivariate beta process. The process is defined for modelling-dependent random probabilities and has beta marginal distributions. We use this process to define a probability model for a family of unknown distributions indexed by covariates. The marginal model for each distribution is a Polya tree prior. An important feature of the proposed prior is the easy centring of the nonparametric model around any parametric regression model. We use the model to implement nonparametric inference for survival distributions. The nonparametric model that we introduce can be adopted to extend the support of prior distributions for parametric regression models.
A Reordering Model Using a Source-Side Parse-Tree for Statistical Machine Translation
Hashimoto, Kei; Yamamoto, Hirofumi; Okuma, Hideo; Sumita, Eiichiro; Tokuda, Keiichi
This paper presents a reordering model using a source-side parse-tree for phrase-based statistical machine translation. The proposed model is an extension of IST-ITG (imposing source tree on inversion transduction grammar) constraints. In the proposed method, the target-side word order is obtained by rotating nodes of the source-side parse-tree. We modeled the node rotation, monotone or swap, using word alignments based on a training parallel corpus and source-side parse-trees. The model efficiently suppresses erroneous target word orderings, especially global orderings. Furthermore, the proposed method conducts a probabilistic evaluation of target word reorderings. In English-to-Japanese and English-to-Chinese translation experiments, the proposed method resulted in a 0.49-point improvement (29.31 to 29.80) and a 0.33-point improvement (18.60 to 18.93) in word BLEU-4 compared with IST-ITG constraints, respectively. This indicates the validity of the proposed reordering model.
Development of a dynamic model for the lung lobes and airway tree in the NCAT phantom
Garrity, J. M.; Segars, W. P.; Knisley, S. B.; Tsui, B. M. W.
2003-06-01
The four-dimensional (4-D) NCAT phantom was developed to realistically model human anatomy based on the visible human data and cardiac and respiratory motions based on 4-D tagged magnetic resonance imaging and respiratory-gated CT data from normal human subjects. Currently, the 4-D NCAT phantom does not include the airway tree or its motion within the lungs. Also, each lung is defined with a single surface; the individual lobes are not distinguished. The authors further the development of the phantom by creating dynamic models for the individual lung lobes and for the airway tree in each lobe. NURBS surfaces for the lobes and an initial airway tree model (/spl sim/ 4 generations) were created through manual segmentation of the visible human data. A mathematical algorithm with physiological constraints was used to extend the original airway model to fill each lobe. For each parent airway branch inside a lobe, the algorithm extends the airway tree by creating two daughter branches modeled with cylindrical tubes. Parameters for the cylindrical tubes such as diameter, length, and angle are constrained based on flow parameters and available lung space.
Modelling Inductive Charging of Battery Electric Vehicles using an Agent-Based Approach
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Zain Ul Abedin
2014-09-01
Full Text Available The introduction of battery electric vehicles (BEVs could help to reduce dependence on fossil fuels and emissions from transportation and as such increase energy security and foster sustainable use of energy resources. However a major barrier to the introduction of BEVs is their limited battery capacity and long charging durations. To address these issues of BEVs several solutions are proposed such as battery swapping and fast charging stations. However apart from these stationary modes of charging, recently a new mode of charging has been introduced which is called inductive charging. This allows charging of BEVs as they drive along roads without the need of plugs, using induction. But it is unclear, if and how such technology could be utilized best. In order to investigate the possible impact of the introduction of such inductive charging infrastructure, its potential and its optimal placement, a framework for simulating BEVs using a multi-agent transport simulation was used. This framework was extended by an inductive charging module and initial test runs were performed. In this paper we present the simulation results of these preliminary tests together with analysis which suggests that battery sizes of BEVs could be reduced even if inductive charging technology is implemented only at a small number of high traffic volume links. The paper also demonstrates that our model can effectively support policy and decision making for deploying inductive charging infrastructure.
IMPACT OF LEVEL OF DETAILS IN THE 3D RECONSTRUCTION OF TREES FOR MICROCLIMATE MODELING
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E. Bournez
2016-06-01
Full Text Available In the 21st century, urban areas undergo specific climatic conditions like urban heat islands which frequency and intensity increase over the years. Towards the understanding and the monitoring of these conditions, vegetation effects on urban climate are studied. It appears that a natural phenomenon, the evapotranspiration of trees, generates a cooling effect in urban environment. In this work, a 3D microclimate model is used to quantify the evapotranspiration of trees in relation with their architecture, their physiology and the climate. These three characteristics are determined with field measurements and data processing. Based on point clouds acquired with terrestrial laser scanner (TLS, the 3D reconstruction of the tree wood architecture is performed. Then the 3D reconstruction of leaves is carried out from the 3D skeleton of vegetative shoots and allometric statistics. With the aim of extending the simulation on several trees simultaneously, it is necessary to apply the 3D reconstruction process on each tree individually. However, as well for the acquisition as for the processing, the 3D reconstruction approach is time consuming. Mobile laser scanners could provide point clouds in a faster way than static TLS, but this implies a lower point density. Also the processing time could be shortened, but under the assumption that a coarser 3D model is sufficient for the simulation. In this context, the criterion of level of details and accuracy of the tree 3D reconstructed model must be studied. In this paper first tests to assess their impact on the determination of the evapotranspiration are presented.
Impact of Level of Details in the 3d Reconstruction of Trees for Microclimate Modeling
Bournez, E.; Landes, T.; Saudreau, M.; Kastendeuch, P.; Najjar, G.
2016-06-01
In the 21st century, urban areas undergo specific climatic conditions like urban heat islands which frequency and intensity increase over the years. Towards the understanding and the monitoring of these conditions, vegetation effects on urban climate are studied. It appears that a natural phenomenon, the evapotranspiration of trees, generates a cooling effect in urban environment. In this work, a 3D microclimate model is used to quantify the evapotranspiration of trees in relation with their architecture, their physiology and the climate. These three characteristics are determined with field measurements and data processing. Based on point clouds acquired with terrestrial laser scanner (TLS), the 3D reconstruction of the tree wood architecture is performed. Then the 3D reconstruction of leaves is carried out from the 3D skeleton of vegetative shoots and allometric statistics. With the aim of extending the simulation on several trees simultaneously, it is necessary to apply the 3D reconstruction process on each tree individually. However, as well for the acquisition as for the processing, the 3D reconstruction approach is time consuming. Mobile laser scanners could provide point clouds in a faster way than static TLS, but this implies a lower point density. Also the processing time could be shortened, but under the assumption that a coarser 3D model is sufficient for the simulation. In this context, the criterion of level of details and accuracy of the tree 3D reconstructed model must be studied. In this paper first tests to assess their impact on the determination of the evapotranspiration are presented.
Aspects of Numerical Modeling of the Induction Heating Process of Non-Ferromagnetic Parts
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STANCIU Bogdan
2012-05-01
Full Text Available The paper presents the numerical modeling of the volume induction heating process for nonferromagnetic semi-products with rectangular (or cylindrical cross-section. We analyze the couplet electromagnetic and thermal phenomena (variation of temperature, frequency, power consumption, etc.. Numerical modeling can offer precise information about several interdependent linear and non-linearparameters that can influence the transient and final thermal conditions of the semi-product, and how to optimize the design of induction heating systems in order to grow the efficiency of the heating process and to obtain the wanted temperature profile.
An axisymmetrical non-linear finite element model for induction heating in injection molding tools
DEFF Research Database (Denmark)
Guerrier, Patrick; Nielsen, Kaspar Kirstein; Menotti, Stefano;
2016-01-01
To analyze the heating and cooling phase of an induction heated injection molding tool accurately, the temperature dependent magnetic properties, namely the non-linear B-H curves, need to be accounted for in an induction heating simulation. Hence, a finite element model has been developed...... in to the injection molding tool. The model shows very good agreement with the experimental temperature measurements. It is also shown that the non-linearity can be used without the temperature dependency in some cases, and a proposed method is presented of how to estimate an effective linear permeability to use...
Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.
2014-12-01
Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents
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A. Rammig
2014-02-01
Full Text Available Climate extremes can trigger exceptional responses in terrestrial ecosystems, for instance by altering growth or mortality rates. Effects of this kind are often manifested in reductions of the local net primary production (NPP. Investigating a set of European long-term data on annual radial tree growth confirms this pattern: we find that 53% of tree ring width (TRW indices are below one standard deviation, and up to 16% of the TRW values are below two standard deviations in years with extremely high temperatures and low precipitation. Based on these findings we investigate if climate driven patterns in long-term tree growth data may serve as benchmarks for state-of-the-art dynamic vegetation models such as LPJmL. The model simulates NPP but not explicitly the radial tree ring growth, hence requiring a generic method to ensure an objective comparison. Here we propose an analysis scheme that quantifies the coincidence rate of climate extremes with some biotic responses (here TRW or simulated NPP. We find that the reduction in tree-ring width during drought extremes is lower than the corresponding reduction of simulated NPP. We identify ten extreme years during the 20th century in which both, model and measurements indicate high coincidence rates across Europe. However, we detect substantial regional differences in simulated and observed responses to extreme events. One explanation for this discrepancy could be that the tree-ring data have preferentially been sampled at more climatically stressed sites. The model-data difference is amplified by the fact that dynamic vegetation models are designed to simulate mean ecosystem responses at landscape or regional scale. However, we find that both model-data and measurements display carry-over effects from the previous year. We conclude that using radial tree growth is a good basis for generic model-benchmarks if the data are analyzed by scale-free measures such as coincidence analysis. Our study shows
Modeling stem increment in individual Pinus occidentalis Sw. trees in La Sierra, Dominican Republic
Energy Technology Data Exchange (ETDEWEB)
Bueno, S.; Bevilacqua, E.
2010-07-01
One of the most common and important tree characteristics used in forest management decision-making is tree diameter-at-breast height (DBH). This paper presents results on an evaluation of two growth functions developed to model stem diameter increases in individual Pinus occidentalis Sw. trees in La Sierra, Dominican Republic. The first model was developed in order to predict future DBH (FDM) at different intervals of time and the other for predicting growth, that is, periodic annual diameter increment (PADIM). Each model employed two statistical techniques for fitting model parameters: stepwise ordinary least squares (OLS) regression, and mixed models. The two statistical approaches varied in how they accounted for the repeated measurements on individual trees over time, affecting standard error estimates and statistical inference of model parameters. Each approach was evaluated based on six goodness of- fit statistics, using both calibration and validation data sets. The objectives were 1) to determine the best model for predicting future tree DBH; 2) to determine the best model for predicting periodic annual diameter increment, both models using tree size, age, site index and different indices of competitive status; and 3) compare which of these two modeling approaches predicts better the future DBH. OLS provided a better fit for both of the growth functions, especially in regards to bias. Both models showed advantages and disadvantages when they were used to predict growth and future diameter. For the prediction of future diameter with FDM, accuracy of predictions were within one centimeter for a five-year projection interval. The PADIM presented negligible bias in estimating future diameter, although there was a small increase in bias as time of prediction increased. As expected, each model was the best in estimating the response variable it was developed for.. However, a closer examination of the distribution of errors showed a slight advantage of the FDM
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E. Brito-Rocha
Full Text Available Abstract Individual leaf area (LA is a key variable in studies of tree ecophysiology because it directly influences light interception, photosynthesis and evapotranspiration of adult trees and seedlings. We analyzed the leaf dimensions (length – L and width – W of seedlings and adults of seven Neotropical rainforest tree species (Brosimum rubescens, Manilkara maxima, Pouteria caimito, Pouteria torta, Psidium cattleyanum, Symphonia globulifera and Tabebuia stenocalyx with the objective to test the feasibility of single regression models to estimate LA of both adults and seedlings. In southern Bahia, Brazil, a first set of data was collected between March and October 2012. From the seven species analyzed, only two (P. cattleyanum and T. stenocalyx had very similar relationships between LW and LA in both ontogenetic stages. For these two species, a second set of data was collected in August 2014, in order to validate the single models encompassing adult and seedlings. Our results show the possibility of development of models for predicting individual leaf area encompassing different ontogenetic stages for tropical tree species. The development of these models was more dependent on the species than the differences in leaf size between seedlings and adults.
Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model
2014-09-01
IT TO THE ORIGINATOR . ERDC/CERL TR-14-18 iii Contents Abstract... original pixel size of 0.25m, the following segmenta- tion parameters seemed to generate the best (visually compared to origi- nal imagery...Penelope Morgan. 2006. “Regression Modeling and Mapping of Coniferous Forest Basal Area and Tree Density from Discrete- Return LIDAR and
A model for the inverse 1-median problem on trees under uncertain costs
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Kien Trung Nguyen
2016-01-01
Full Text Available We consider the problem of justifying vertex weights of a tree under uncertain costs so that a prespecified vertex become optimal and the total cost should be optimal in the uncertainty scenario. We propose a model which delivers the information about the optimal cost which respect to each confidence level \\(\\alpha \\in [0,1]\\. To obtain this goal, we first define an uncertain variable with respect to the minimum cost in each confidence level. If all costs are independently linear distributed, we present the inverse distribution function of this uncertain variable in \\(O(n^{2}\\log n\\ time, where \\(n\\ is the number of vertices in the tree.
Fader, Marianela; von Bloh, Werner; Shi, Sinan; Bondeau, Alberte; Cramer, Wolfgang
2016-04-01
In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall and direct degradation of ecosystems. Human population growth and socioeconomic changes, notably on the Eastern and Southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive ecohydrological model. Here we present here the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL, "Lund-Potsdam-Jena managed Land"): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was then successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. A first application of the model indicates that, currently, agricultural trees consume in average more irrigation water per hectare than annual crops. Also, different crops show different magnitude of changes in net irrigation requirements due to climate change, being the increases most pronounced in agricultural trees. This is very relevant since the Mediterranean area as a whole might face an increase in gross irrigation requirements between 4% and 74% from climate change and population growth if irrigation systems and conveyance are not improved. Additionally, future water scarcity might pose further challenges to the agricultural sector: Algeria, Libya, Israel, Jordan, Lebanon, Syria, Serbia, Morocco, Tunisia and Spain have a high risk of not being able to sustainably meet future irrigation water requirements in some scenarios by the end of the century (1). The importance of including agricultural trees in the ecohydrological models is also shown in the results concerning soil organic carbon (SOC). Since in former model
Modelling Transformations of Quadratic Functions: A Proposal of Inductive Inquiry
Sokolowski, Andrzej
2013-01-01
This paper presents a study about using scientific simulations to enhance the process of mathematical modelling. The main component of the study is a lesson whose major objective is to have students mathematise a trajectory of a projected object and then apply the model to formulate other trajectories by using the properties of function…
van Mantgem, P.J.; Stephenson, N.L.
2005-01-01
1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.
A Knowledge Tree Model and Its Application for Continuous Management Improvement
Lu, Yun; Bao, Zhen-Qiang; Zhao, Yu-Qin; Wang, Yan; Wang, Gui-Jun
This chapter analyzes the relationship of organizational knowledge and brings forward that organizational knowledge consists of three layers: core knowledge, structural knowledge, and implicit knowledge. According to the principle of knowledge maps, a dynamic management model of organizational knowledge based on knowledge tree is introduced and the definition of the value of knowledge node is given so that the quantitative management on knowledge is realized, which lays a foundation for performance evaluation of knowledge management. We also carefully study the application of knowledge tree in service quality management of hospital organizations and management innovation process and give the example of cooperation in endoscopic surgery to establish a knowledge tree about operational cooperation degree, which states the principle of organizational knowledge management and the knowledge innovation process of continuous management improvement.
Multiscale model of a freeze-thaw process for tree sap exudation
Graf, Isabell; Stockie, John M
2015-01-01
Sap transport in trees has long fascinated scientists, and a vast literature exists on experimental and modelling studies of trees during the growing season when large negative stem pressures are generated by transpiration from leaves. Much less attention has been paid to winter months when trees are largely dormant but nonetheless continue to exhibit interesting flow behaviour. A prime example is sap exudation, which refers to the peculiar ability of sugar maple (Acer saccharum) and related species to generate positive stem pressure while in a leafless state. Experiments demonstrate that ambient temperatures must oscillate about the freezing point before significantly heightened stem pressures are observed, but the precise causes of exudation remain unresolved. The prevailing hypothesis attributes exudation to a physical process combining freeze-thaw and osmosis, which has some support from experimental studies but remains a subject of active debate. We address this knowledge gap by developing the first math...
David W. MacFarlane
2015-01-01
Accurately assessing forest biomass potential is contingent upon having accurate tree biomass models to translate data from forest inventories. Building generality into these models is especially important when they are to be applied over large spatial domains, such as regional, national and international scales. Here, new, generalized whole-tree mass / volume...
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Ramakrishna R. Nemani
2013-01-01
Full Text Available A methodology to generate spatially continuous fields of tree heights with an optimized Allometric Scaling and Resource Limitations (ASRL model is reported in this first of a multi-part series of articles. Model optimization is performed with the Geoscience Laser Altimeter System (GLAS waveform data. This methodology is demonstrated by mapping tree heights over forested lands in the continental USA (CONUS at 1 km spatial resolution. The study area is divided into 841 eco-climatic zones based on three forest types, annual total precipitation classes (30 mm intervals and annual average temperature classes (2 °C intervals. Three model parameters (area of single leaf, α, exponent for canopy radius, η, and root absorption efficiency, γ were selected for optimization, that is, to minimize the difference between actual and potential tree heights in each of the eco-climatic zones over the CONUS. Tree heights predicted by the optimized model were evaluated against GLAS heights using a two-fold cross validation approach (R2 = 0.59; RMSE = 3.31 m. Comparison at the pixel level between GLAS heights (mean = 30.6 m; standard deviation = 10.7 and model predictions (mean = 30.8 m; std. = 8.4 were also performed. Further, the model predictions were compared to existing satellite-based forest height maps. The optimized ASRL model satisfactorily reproduced the pattern of tree heights over the CONUS. Subsequent articles in this series will document further improvements with the ultimate goal of mapping tree heights and forest biomass globally.
MODELLING AND CONTROLLING OF INDUCTION MOTOR BY USING LINEAR ADRC
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CH. NAGA KOTI KUMAR,
2011-04-01
Full Text Available In this paper we present a new novel approach for the speed control of an IM using Linear Active Disturbance Rejection Controller [LADRC]. The field oriented control of IM needs the accuratemathematical model of IM, but it is very difficult to develop an accurate mathematical model. The LADRC does depend on the mathematical model so it is very robust to changes in plant parameters. This controller can also estimate and compensate the general disturbances which include the unknown internal dynamics and external disturbances by using the Extended State Observer, which can reduce the system to a linear one.
A Test of Carbon and Oxygen Stable Isotope Ratio Process Models in Tree Rings.
Roden, J. S.; Farquhar, G. D.
2008-12-01
Stable isotopes ratios of carbon and oxygen in tree ring cellulose have been used to infer environmental change. Process-based models have been developed to clarify the potential of historic tree ring records for meaningful paleoclimatic reconstructions. However, isotopic variation can be influenced by multiple environmental factors making simplistic interpretations problematic. Recently, the dual isotope approach, where the variation in one stable isotope ratio (e.g. oxygen) is used to constrain the interpretation of variation in another (e.g. carbon), has been shown to have the potential to de-convolute isotopic analysis. However, this approach requires further testing to determine its applicability for paleo-reconstructions using tree-ring time series. We present a study where the information needed to parameterize mechanistic models for both carbon and oxygen stable isotope ratios were collected in controlled environment chambers for two species (Pinus radiata and Eucalyptus globulus). The seedlings were exposed to treatments designed to modify leaf temperature, transpiration rates, stomatal conductance and photosynthetic capacity. Both species were grown for over 100 days under two humidity regimes that differed by 20%. Stomatal conductance was significantly different between species and for seedlings under drought conditions but not between other treatments or humidity regimes. The treatments produced large differences in transpiration rate and photosynthesis. Treatments that effected photosynthetic rates but not stomatal conductance influenced carbon isotope discrimination more than those that influenced primarily conductance. The various treatments produced a range in oxygen isotope ratios of 7 ‰. Process models predicted greater oxygen isotope enrichment in tree ring cellulose than observed. The oxygen isotope ratios of bulk leaf water were reasonably well predicted by current steady-state models. However, the fractional difference between models that
Comparison of tree types of models for the prediction of final academic achievement
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Silvana Gasar
2002-12-01
Full Text Available For efficient prevention of inappropriate secondary school choices and by that academic failure, school counselors need a tool for the prediction of individual pupil's final academic achievements. Using data mining techniques on pupils' data base and expert modeling, we developed several models for the prediction of final academic achievement in an individual high school educational program. For data mining, we used statistical analyses, clustering and two machine learning methods: developing classification decision trees and hierarchical decision models. Using an expert system shell DEX, an expert system, based on a hierarchical multi-attribute decision model, was developed manually. All the models were validated and evaluated from the viewpoint of their applicability. The predictive accuracy of DEX models and decision trees was equal and very satisfying, as it reached the predictive accuracy of an experienced counselor. With respect on the efficiency and difficulties in developing models, and relatively rapid changing of our education system, we propose that decision trees are used in further development of predictive models.
Biogeochemical modelling vs. tree-ring data - comparison of forest ecosystem productivity estimates
Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Hidy, Dóra; Paladinić, Elvis; Kern, Anikó; Marjanović, Hrvoje
2017-04-01
Forest ecosystems are sensitive to environmental changes as well as human-induce disturbances, therefore process-based models with integrated management modules represent valuable tool for estimating and forecasting forest ecosystem productivity under changing conditions. Biogeochemical model Biome-BGC simulates carbon, nitrogen and water fluxes, and it is widely used for different terrestrial ecosystems. It was modified and parameterised by many researchers in the past to meet the specific local conditions. In this research, we used recently published improved version of the model Biome-BGCMuSo (BBGCMuSo), with multilayer soil module and integrated management module. The aim of our research is to validate modelling results of forest ecosystem productivity (NPP) from BBGCMuSo model with observed productivity estimated from an extensive dataset of tree-rings. The research was conducted in two distinct forest complexes of managed Pedunculate oak in SE Europe (Croatia), namely Pokupsko basin and Spačva basin. First, we parameterized BBGCMuSo model at a local level using eddy-covariance (EC) data from Jastrebarsko EC site. Parameterized model was used for the assessment of productivity on a larger scale. Results of NPP assessment with BBGCMuSo are compared with NPP estimated from tree ring data taken from trees on over 100 plots in both forest complexes. Keywords: Biome-BGCMuSo, forest productivity, model parameterization, NPP, Pedunculate oak
Process based model sheds light on climate sensitivity of Mediterranean tree-ring width
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R. Touchan
2012-03-01
Full Text Available We use the process-based VS (Vaganov-Shashkin model to investigate whether a regional Pinus halepensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959–2004 from a climate station to ring-width variations. We check performance of the model on independent data by a validation exercise in which the model's parameters are tuned using data for 1982–2004 and the model is applied to generate tree-ring indices for 1959–1981. The validation exercise yields a highly significant positive correlation between the residual chronology and estimated growth curve (r=0.76 p<0.0001, n=23. The model shows that the average duration of the growing season is 191 days, with considerable variation from year to year. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. Model results depend on chosen values of parameters, in particular a parameter specifying a balance ratio between soil moisture and precipitation. Future work in the Mediterranean region should include multi-year natural experiments to verify patterns of cambial-growth variation suggested by the VS model.
Estimating Tree Height-Diameter Models with the Bayesian Method
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Xiongqing Zhang
2014-01-01
Full Text Available Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS and the maximum likelihood method (ML. The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the “best” model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2.
Energy Technology Data Exchange (ETDEWEB)
Chadoeuf, J.; Joannes, H.; Nandris, D.; Pierrat, J.C.
1988-12-01
The spread of root diseases in rubber tree (Hevea brasiliensis) due to Rigidoporus lignosus and Phellinus noxius was investigated epidemiologically using data collected every 6 month during a 6-year survey in a plantation. The aim of the present study is to see what factors could predict whether a given tree would be infested at the following inspection. Using a qualitative regression method we expressed the probability of pathogenic attack on a tree in terms of three factors: the state of health of the surrounding trees, the method used to clear the forest prior to planting, and evolution with time. The effects of each factor were ranked, and the roles of the various classes of neighbors were established and quantified. Variability between successive inspections was small, and the method of forest clearing was important only while primary inocula in the soil were still infectious. The state of health of the immediate neighbors was most significant; more distant neighbors in the same row had some effect; interrow spread was extremely rare. This investigation dealt only with trees as individuals, and further study of the interrelationships of groups of trees is needed.
Model checking software for phylogenetic trees using distribution and database methods.
Requeno, José Ignacio; Colom, José Manuel
2013-11-14
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.
An Integrated Approach of Model checking and Temporal Fault Tree for System Safety Analysis
Energy Technology Data Exchange (ETDEWEB)
Koh, Kwang Yong; Seong, Poong Hyun [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)
2009-10-15
Digitalization of instruments and control systems in nuclear power plants offers the potential to improve plant safety and reliability through features such as increased hardware reliability and stability, and improved failure detection capability. It however makes the systems and their safety analysis more complex. Originally, safety analysis was applied to hardware system components and formal methods mainly to software. For software-controlled or digitalized systems, it is necessary to integrate both. Fault tree analysis (FTA) which has been one of the most widely used safety analysis technique in nuclear industry suffers from several drawbacks as described in. In this work, to resolve the problems, FTA and model checking are integrated to provide formal, automated and qualitative assistance to informal and/or quantitative safety analysis. Our approach proposes to build a formal model of the system together with fault trees. We introduce several temporal gates based on timed computational tree logic (TCTL) to capture absolute time behaviors of the system and to give concrete semantics to fault tree gates to reduce errors during the analysis, and use model checking technique to automate the reasoning process of FTA.
Modeling geomagnetic induction hazards using a 3-D electrical conductivity model of Australia
Wang, Liejun; Lewis, Andrew M.; Ogawa, Yasuo; Jones, William V.; Costelloe, Marina T.
2016-12-01
The surface electric field induced by external geomagnetic source fields is modeled for a continental-scale 3-D electrical conductivity model of Australia at periods of a few minutes to a few hours. The amplitude and orientation of the induced electric field at periods of 360 s and 1800 s are presented and compared to those derived from a simplified ocean-continent (OC) electrical conductivity model. It is found that the induced electric field in the Australian region is distorted by the heterogeneous continental electrical conductivity structures and surrounding oceans. On the northern coastlines, the induced electric field is decreased relative to the simple OC model due to a reduced conductivity contrast between the seas and the enhanced conductivity structures inland. In central Australia, the induced electric field is less distorted with respect to the OC model as the location is remote from the oceans, but inland crustal high-conductivity anomalies are the major source of distortion of the induced electric field. In the west of the continent, the lower conductivity of the Western Australia Craton increases the conductivity contrast between the deeper oceans and land and significantly enhances the induced electric field. Generally, the induced electric field in southern Australia, south of latitude -20°, is higher compared to northern Australia. This paper provides a regional indicator of geomagnetic induction hazards across Australia.
Flow regulation in coronary vascular tree: a model study.
Directory of Open Access Journals (Sweden)
Xinzhou Xie
Full Text Available Coronary blood flow can always be matched to the metabolic demand of the myocardium due to the regulation of vasoactive segments. Myocardial compressive forces play an important role in determining coronary blood flow but its impact on flow regulation is still unknown. The purpose of this study was to develop a coronary specified flow regulation model, which can integrate myocardial compressive forces and other identified regulation factors, to further investigate the coronary blood flow regulation behavior.A theoretical coronary flow regulation model including the myogenic, shear-dependent and metabolic responses was developed. Myocardial compressive forces were included in the modified wall tension model. Shear-dependent response was estimated by using the experimental data from coronary circulation. Capillary density and basal oxygen consumption were specified to corresponding to those in coronary circulation. Zero flow pressure was also modeled by using a simplified capillary model.Pressure-flow relations predicted by the proposed model are consistent with previous experimental data. The predicted diameter changes in small arteries are in good agreement with experiment observations in adenosine infusion and inhibition of NO synthesis conditions. Results demonstrate that the myocardial compressive forces acting on the vessel wall would extend the auto-regulatory range by decreasing the myogenic tone at the given perfusion pressure.Myocardial compressive forces had great impact on coronary auto-regulation effect. The proposed model was proved to be consistent with experiment observations and can be employed to investigate the coronary blood flow regulation effect in physiological and pathophysiological conditions.
Energy Technology Data Exchange (ETDEWEB)
Razik, H. [Universite Henri Poincare, GREEN, CNRS-UMR 7037, BP 239, F-54506 Vandoeuvre-les-Nancy Cedex (France); Henao, H. [University of Picardie, CREA, 33 rue Saint Leu, F-80039 Amiens Cedex 1 (France); Carlson, R. [GRUCAD/CTC/UFSC, Campus Universitario, C.P. 436, Florianopolis - SC, 88040-900 (Brazil)
2009-01-15
This paper presents a mathematical model of a three-phase induction motor taking into consideration the interbar contacts. Several models have been available in the references. However, they consider the rotor of the induction motor as being constituted either a three-phase or a squirrel cage even if it operates under stator and/or rotor faults condition. Nonetheless, the contact between a bar and the iron core for the machine has to be considered, especially when a rotor fault occurs. It is obvious that rotor currents are under the influence of rotor constitution materials. So, the paper aim's concerns a transient model of the induction motors which can consider the rotor broken bars defect. Despite its increasing complexity, it could be able to provide with useful indications for diagnostic purposes. This model is advocated for the simulation of motors behavior under rotor defect which takes into account the interbar currents. The proposed technique is based on the mesh model analysis of the squirrel cage. As low power induction motors are prevalent in industrial plants, we pay a special attention on them. Notwithstanding, additional currents are due to the contact between the non-insulated bar constituting the squirrel cage to the rotor iron core. The monitoring of induction motors is predominantly made through the stator current analysis of the motor when it operates at nominal condition. Moreover, this one is observed in steady state operating system, knowing that the motor is generally fed by a sinusoidal supply. Consequently, simulation results showed in this paper prove the effectiveness of the proposed approach, and the impact of interbar resistance both on the model and the line current spectrum for the diagnostic. An experimental test proves the effectiveness of this model. (author)
Past and ongoing shifts in Joshua tree distribution support future modeled range contraction
Cole, Kenneth L.; Ironside, Kirsten; Eischeid, Jon K.; Garfin, Gregg; Duffy, Phil; Toney, Chris
2011-01-01
The future distribution of the Joshua tree (Yucca brevifolia) is projected by combining a geostatistical analysis of 20th-century climates over its current range, future modeled climates, and paleoecological data showing its response to a past similar climate change. As climate rapidly warmed ;11 700 years ago, the range of Joshua tree contracted, leaving only the populations near what had been its northernmost limit. Its ability to spread northward into new suitable habitats after this time may have been inhibited by the somewhat earlier extinction of megafaunal dispersers, especially the Shasta ground sloth. We applied a model of climate suitability for Joshua tree, developed from its 20th-century range and climates, to future climates modeled through a set of six individual general circulation models (GCM) and one suite of 22 models for the late 21st century. All distribution data, observed climate data, and future GCM results were scaled to spatial grids of ;1 km and ;4 km in order to facilitate application within this topographically complex region. All of the models project the future elimination of Joshua tree throughout most of the southern portions of its current range. Although estimates of future monthly precipitation differ between the models, these changes are outweighed by large increases in temperature common to all the models. Only a few populations within the current range are predicted to be sustainable. Several models project significant potential future expansion into new areas beyond the current range, but the species' Historical and current rates of dispersal would seem to prevent natural expansion into these new areas. Several areas are predicted to be potential sites for relocation/ assisted migration. This project demonstrates how information from paleoecology and modern ecology can be integrated in order to understand ongoing processes and future distributions.
Binary tree models of high-Reynolds-number turbulence
Aurell, Erik; Dormy, Emmanuel; Frick, Peter
1997-08-01
We consider hierarchical models for turbulence, that are simple generalizations of the standard Gledzer-Ohkitani-Yamada shell models (E. B. Gledzer, Dokl, Akad. Nauk SSSR 209, 5 (1973) [Sov. Phys. Dokl. 18, 216 (1973)]; M. Yamada and K. Ohkitani, J. Phys. Soc. Jpn. 56, 4210 (1987)). The density of degrees of freedom is constant in wave-number space. Looking only at this behavior and at the quadratic invariants in the inviscid unforced limit, the models can be thought of as systems living naturally in one spatial dimension, but being qualitatively similar to hydrodynamics in two (2D) and three dimensions. We investigated cascade phenomena and intermittency in the different cases. We observed and studied a forward cascade of enstrophy in the 2D case.
Modelling of a double star induction motor for space vector PWM control
Energy Technology Data Exchange (ETDEWEB)
Hadiouche, D.; Razik, H.; Rezzoug, A. [Groupe de Recherche en Electrotechnique et Electronique de Nancy, G.R.E.E.N. - CNRS UPRES, University H. Poincare, Vandoeuvre-les-Nancy (France)
2000-08-01
In this paper, we present the analysis and the modelling of a Double-Star Induction Motor (DSIM). A steady-state model is first established in order to analyse its harmonic behaviour. Then, a new transformation matrix is proposed in order to develop a suitable dynamic model. In both cases, the study is made using an arbitrary shift angle between the two stars. At last, a space vector Pulse Width Modulation (PWM) control or the DSIM is simulated. (orig.)
A Bayesian Mixture Model for PoS Induction Using Multiple Features
Christodoulopoulos, Christos; Goldwater, Sharon; Steedman, Mark
2011-01-01
In this paper we present a fully unsupervised syntactic class induction system formulated as a Bayesian multinomial mixture model, where each word type is constrained to belong to a single class. By using a mixture model rather than a sequence model (e.g., HMM), we are able to easily add multiple kinds of features, including those at both the type level (morphology features) and token level (context and alignment features, the latter from parallel corpora). Using only context features, our sy...
A coupled model tree genetic algorithm scheme for flow and water quality predictions in watersheds
Preis, Ami; Ostfeld, Avi
2008-02-01
SummaryThe rapid advance in information processing systems along with the increasing data availability have directed research towards the development of intelligent systems that evolve models of natural phenomena automatically. This is the discipline of data driven modeling which is the study of algorithms that improve automatically through experience. Applications of data driven modeling range from data mining schemes that discover general rules in large data sets, to information filtering systems that automatically learn users' interests. This study presents a data driven modeling algorithm for flow and water quality load predictions in watersheds. The methodology is comprised of a coupled model tree-genetic algorithm scheme. The model tree predicts flow and water quality constituents while the genetic algorithm is employed for calibrating the model tree parameters. The methodology is demonstrated through base runs and sensitivity analysis for daily flow and water quality load predictions on a watershed in northern Israel. The method produced close fits in most cases, but was limited in estimating the peak flows and water quality loads.
Process based model sheds light on climate sensitivity of Mediterranean tree-ring width
Touchan, R.; Shishov, V. V.; Meko, D. M.; Nouiri, I.; Grachev, A.
2012-03-01
We use the process-based VS (Vaganov-Shashkin) model to investigate whether a regional Pinus halepensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959-2004) from a climate station to ring-width variations. We check performance of the model on independent data by a validation exercise in which the model's parameters are tuned using data for 1982-2004 and the model is applied to generate tree-ring indices for 1959-1981. The validation exercise yields a highly significant positive correlation between the residual chronology and estimated growth curve (r=0.76 pseason is 191 days, with considerable variation from year to year. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days. Model results depend on chosen values of parameters, in particular a parameter specifying a balance ratio between soil moisture and precipitation. Future work in the Mediterranean region should include multi-year natural experiments to verify patterns of cambial-growth variation suggested by the VS model.
Process based model sheds light on climate signal of mediterranean tree rings
Directory of Open Access Journals (Sweden)
R. Touchan
2011-11-01
Full Text Available We use the process-based VS (Vaganov-Shashkin model to investigate whether a regional Pinus halapensis tree-ring chronology from Tunisia can be simulated as a function of climate alone by employing a biological model linking day length and daily temperature and precipitation (AD 1959–2004 from a climate station to ring-width variations. We use two periods to calibrate (1982–2004 and verify (1959–1981 the model. We have obtained highly significant positive correlation between the residual chronology and estimated growth curve (r = 0.76 p < 0.001. The model shows that the average duration of the growing season is 191 days. On average, soil moisture limits tree-ring growth for 128 days and temperature for 63 days.
Comparison of data mining and allometric model in estimation of tree biomass.
Sanquetta, Carlos R; Wojciechowski, Jaime; Dalla Corte, Ana P; Behling, Alexandre; Péllico Netto, Sylvio; Rodrigues, Aurélio L; Sanquetta, Mateus N I
2015-08-07
The traditional method used to estimate tree biomass is allometry. In this method, models are tested and equations fitted by regression usually applying ordinary least squares, though other analogous methods are also used for this purpose. Due to the nature of tree biomass data, the assumptions of regression are not always accomplished, bringing uncertainties to the inferences. This article demonstrates that the Data Mining (DM) technique can be used as an alternative to traditional regression approach to estimate tree biomass in the Atlantic Forest, providing better results than allometry, and demonstrating simplicity, versatility and flexibility to apply to a wide range of conditions. Various DM approaches were examined regarding distance, number of neighbors and weighting, by using 180 trees coming from environmental restoration plantations in the Atlantic Forest biome. The best results were attained using the Chebishev distance, 1/d weighting and 5 neighbors. Increasing number of neighbors did not improve estimates. We also analyze the effect of the size of data set and number of variables in the results. The complete data set and the maximum number of predicting variables provided the best fitting. We compare DM to Schumacher-Hall model and the results showed a gain of up to 16.5% in reduction of the standard error of estimate. It was concluded that Data Mining can provide accurate estimates of tree biomass and can be successfully used for this purpose in environmental restoration plantations in the Atlantic Forest. This technique provides lower standard error of estimate than the Schumacher-Hall model and has the advantage of not requiring some statistical assumptions as do the regression models. Flexibility, versatility and simplicity are attributes of DM that corroborates its great potential for similar applications.
Wang, Ling; Zhao, Geng-xing; Zhu, Xi-cun; Lei, Tong; Dong, Fang
2010-10-01
Hyperspectral technique has become the basis of quantitative remote sensing. Hyperspectrum of apple tree canopy at prosperous fruit stage consists of the complex information of fruits, leaves, stocks, soil and reflecting films, which was mostly affected by component features of canopy at this stage. First, the hyperspectrum of 18 sample apple trees with reflecting films was compared with that of 44 trees without reflecting films. It could be seen that the impact of reflecting films on reflectance was obvious, so the sample trees with ground reflecting films should be separated to analyze from those without ground films. Secondly, nine indexes of canopy components were built based on classified digital photos of 44 apple trees without ground films. Thirdly, the correlation between the nine indexes and canopy reflectance including some kinds of conversion data was analyzed. The results showed that the correlation between reflectance and the ratio of fruit to leaf was the best, among which the max coefficient reached 0.815, and the correlation between reflectance and the ratio of leaf was a little better than that between reflectance and the density of fruit. Then models of correlation analysis, linear regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the hyperspectral reflectance and the ratio of fruit to leaf with the softwares of DPS and LIBSVM. It was feasible that all of the four models in 611-680 nm characteristic band are feasible to be used to predict, while the model accuracy of BP neural network and support vector regression was better than one-variable linear regression and multi-variable regression, and the accuracy of support vector regression model was the best. This study will be served as a reliable theoretical reference for the yield estimation of apples based on remote sensing data.
Sokalski, Krzysztof Z
2015-01-01
Recently introduced model of magnetic hysteresis was extended into set of the following features: frequency, pick of induction and temperature of specimen. Group theoretical classification of hysteresis loops' sets is presented. An effect analogous to the Zeeman splitting has been revealed in the set of the all hysteresis loops.
Suryana, N.
1997-01-01
Three main aspects of the research, namely the concept of object orientation, the development of an Inductive Erosion Model (IEM) and the development of a framework for handling uncertainty in the data or information resulting from a GIS are interwoven in this thesis. The first and the second aspect
A validated model for induction heating of shape memory alloy actuators
Saunders, Robert N.; Boyd, James G.; Hartl, Darren J.; Brown, Jonathan K.; Calkins, Frederick T.; Lagoudas, Dimitris C.
2016-04-01
Shape memory alloy (SMA) actuators deliver high forces while being compact and reliable, making them ideal for consideration in aerospace applications. One disadvantage of these thermally driven actuators is their slow cyclic time response compared to conventional actuators. Induction heating has recently been proposed to quickly heat SMA components. However efforts to date have been purely empirical. The present work approachs this problem in a computational manner by developing a finite element model of induction heating in which the time-harmonic electromagnetic equations are solved for the Joule heat power field, the energy equation is solved for the temperature field, and the linear momentum equations are solved to find the stress, displacement, and internal state variable fields. The combined model was implemented in Abaqus using a Python script approach and applied to SMA torque tube and beam actuators. The model has also been used to examine magnetic flux concentrators to improve the induction systems performance. Induction heating experiments were performed using the SMA torque tube, and the model agreed well with the experiments.
Experimental models for induction of liver cirrhosis in animals: a review
Directory of Open Access Journals (Sweden)
Cristiane Carlin Passos
2010-06-01
Full Text Available The liver plays a key role in the homeostatic balance of many biological processes. Cirrhosis is a syndrome in which chronic liver diseases converge, leading to hepatocellular injury, the exacerbated deposition of fibrous tissue, and eventually the disruption of the tissue architecture. The liver is subject to potential injury by a large quantity of pharmacological agents, toxic and/or microbiological. For the study of possible treatments for cirrhosis, it is necessary to establish animal models of induction of cirrhosis, especially in laboratory rodents which mimic the cirrhotic process found in animals and humans, that have high reproducibility and uniformity, with a low mortality rate. Thus, the induction of liver cirrhosis becomes essential to the investigation of chronic liver diseases, as well as to test possible therapeutic treatments for subsequent use in human and veterinary clinics. Currently, experimental studies have been conducted to collect data about the various hepatotoxic drug effects. Carbon tetrachloride -CCl4, Thioacetamide –TAA and dimethylnitrosamine -DMN were the drugs of choice for cirrhosis induction in experimental models in this study. The model using cirrhotic TAA seems to be the best model for the reason that it produces a histological pattern closest to that of human cirrhosis, leading to lower mortality with higher reproducibility and security, despite the longer period of induction (14 weeks.
Using a cylindrical vortex model to assess the induction zone infront of aligned and yawed rotors
DEFF Research Database (Denmark)
Branlard, Emmanuel Simon Pierre; Meyer Forsting, Alexander Raul
2015-01-01
Analytical formulae for the velocity field induced by a cylindrical vortex wake model areapplied to assess the induction zone in front of aligned and yawed rotors. The results arecompared to actuator disk (AD) simulations for different operating conditions, includingfinite tip-speed ratios...
Lessons from Mr. Larson: An Inductive Model of Teaching for Orchestrating Discourse
Truxaw, Mary P.; DeFranco, Thomas C.
2007-01-01
The National Council of Teachers of Mathematics (NCTM) has consistently recognized communication as essential to reform-oriented mathematics teaching (NCTM 1991, 2000). In this article, the authors propose a strategic mix of univocal and dialogic discourse that, when used in conjunction with an "inductive model of teaching," can promote…
Mathematical Model of Linear Switched Reluctance Motor with Mutual Inductance Consideration
Directory of Open Access Journals (Sweden)
Nikolay Grebennikov
2015-06-01
Full Text Available This paper presents developing an mathematical model for linear switched reluctance motor (LSRM with account of the mutual inductance between the phases. Mutual interaction between the phases of LSRM gives the positive effect, as a rule the power of the machine is increased by 5-15%.
Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree
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S. Samadianfard
2017-01-01
Full Text Available Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23 presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21 used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13 proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16 used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11 evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities. Materials and Methods: Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned
Neural-network-based speed controller for induction motors using inverse dynamics model
Ahmed, Hassanein S.; Mohamed, Kamel
2016-08-01
Artificial Neural Networks (ANNs) are excellent tools for controller design. ANNs have many advantages compared to traditional control methods. These advantages include simple architecture, training and generalization and distortion insensitivity to nonlinear approximations and nonexact input data. Induction motors have many excellent features, such as simple and rugged construction, high reliability, high robustness, low cost, minimum maintenance, high efficiency, and good self-starting capabilities. In this paper, we propose a neural-network-based inverse model for speed controllers for induction motors. Simulation results show that the ANNs have a high tracing capability.
Directory of Open Access Journals (Sweden)
C. O. MOLNAR
2008-05-01
Full Text Available The paper presents the numerical modeling ofelectromagnetic field within the induction hardening ofinner cylindrical surface. The numerical computation hasbeen done by means of finite element method in order tosolve the coupled electromagnetic and thermal fieldquestion. The obtained results provide informationregarding the heating process taking into account therelative movement between the inductor and workpiece,the over heating of thin layers, the geometricalconfiguration of the inductor as well the technologicalrequirements correlated with electrical parameters andrepresents an active tool to setup the induction heatingequipment in order to get best results during hardeningprocess .
Verification of the Model of Inductive Coupling between a Josephson Oscillator and a Stripline
Kudo, Keisuke; Yoshida, Keiji; Enpuku, Keiji; Yamafuji, Kaoru
1993-01-01
In order to realize an efficient coupling between a flux-flow-type Josephson oscillator (FFO) and a stripline, we have carried out experiments to verify the mathematical model of the inductive coupling scheme between FFO and a stripline resonator in the frequency range between 50 GHz and 350 GHz. It is shown that the simulation using the proposed equivalent circuit for the inductive coupling scheme well explains the experimental results. The experimentally obtained center frequency and the bandwidth of the matching circuit were as large as 120 GHz and 40 GHz, respectively, which are also in reasonable agreement with those obtained in the simulation.
Hallock, Ashley K.; Polzin, Kurt A.
2011-01-01
A two-dimensional semi-empirical model of pulsed inductive thrust efficiency is developed to predict the effect of such a geometry on thrust efficiency. The model includes electromagnetic and gas-dynamic forces but excludes energy conversion from radial motion to axial motion, with the intention of characterizing thrust efficiency loss mechanisms that result from a conical versus a at inductive coil geometry. The range of conical pulsed inductive thruster geometries to which this model can be applied is explored with the use of finite element analysis. A semi-empirical relation for inductance as a function of current sheet radial and axial position is the limiting feature of the model, restricting the applicability as a function of half cone angle to a range from ten degrees to about 60 degrees. The model is nondimensionalized, yielding a set of dimensionless performance scaling parameters. Results of the model indicate that radial current sheet motion changes the axial dynamic impedance parameter at which thrust efficiency is maximized. This shift indicates that when radial current sheet motion is permitted in the model longer characteristic circuit timescales are more efficient, which can be attributed to a lower current sheet axial velocity as the plasma more rapidly decouples from the coil through radial motion. Thrust efficiency is shown to increase monotonically for decreasing values of the radial dynamic impedance parameter. This trend indicates that to maximize the radial decoupling timescale should be long compared to the characteristic circuit timescale.
Directory of Open Access Journals (Sweden)
Hyun-Joo Oh
2017-09-01
Full Text Available The main purpose of this paper is to present some potential applications of sophisticated data mining techniques, such as artificial neural network (ANN and boosted tree (BT, for landslide susceptibility modeling in the Yongin area, Korea. Initially, landslide inventory was detected from visual interpretation using digital aerial photographic maps with a high resolution of 50 cm taken before and after the occurrence of landslides. The debris flows were randomly divided into two groups: training and validation sets with a 50:50 proportion. Additionally, 18 environmental factors related to landslide occurrence were derived from the topography, soil, and forest maps. Subsequently, the data mining techniques were applied to identify the influence of environmental factors on landslide occurrence of the training set and assess landslide susceptibility. Finally, the landslide susceptibility indexes from ANN and BT were compared with a validation set using a receiver operating characteristics curve. The slope gradient, topographic wetness index, and timber age appear to be important factors in landslide occurrence from both models. The validation result of ANN and BT showed 82.25% and 90.79%, which had reasonably good performance. The study shows the benefit of selecting optimal data mining techniques in landslide susceptibility modeling. This approach could be used as a guideline for choosing environmental factors on landslide occurrence and add influencing factors into landslide monitoring systems. Furthermore, this method can rank landslide susceptibility in urban areas, thus providing helpful information when selecting a landslide monitoring site and planning land-use.
Model of the double-rotor induction motor in terms of electromagnetic differential
Directory of Open Access Journals (Sweden)
Adamczyk Dominik
2016-12-01
Full Text Available The paper presents a concept, a construction, a circuit model and experimental results of the double-rotor induction motor. This type of a motor is to be implemented in the concept of the electromagnetic differential. At the same time it should fulfill the function of differential mechanism and the vehicle drive. One of the motor shafts is coupled to the direction changing mechanical transmission. The windings of the external rotor are powered by slip rings and brushes. The inner rotor has the squirrel-cage windings. The circuit model parameters were calculated based on the 7.5 kW real single-rotor induction motor (2p = 4. Experimental verification of the model was based on comparison between the mentioned single-rotor motor and double-rotor model with the outer rotor blocked. The presented results showed relatively good compliance between the model and real motor.
Dynamic Average-Value Modeling of Doubly-Fed Induction Generator Wind Energy Conversion Systems
Shahab, Azin
In a Doubly-fed Induction Generator (DFIG) wind energy conversion system, the rotor of a wound rotor induction generator is connected to the grid via a partial scale ac/ac power electronic converter which controls the rotor frequency and speed. In this research, detailed models of the DFIG wind energy conversion system with Sinusoidal Pulse-Width Modulation (SPWM) scheme and Optimal Pulse-Width Modulation (OPWM) scheme for the power electronic converter are developed in detail in PSCAD/EMTDC. As the computer simulation using the detailed models tends to be computationally extensive, time consuming and even sometimes not practical in terms of speed, two modified approaches (switching-function modeling and average-value modeling) are proposed to reduce the simulation execution time. The results demonstrate that the two proposed approaches reduce the simulation execution time while the simulation results remain close to those obtained using the detailed model simulation.
Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model
Acevedo, Walter; Fallah, Bijan; Reich, Sebastian; Cubasch, Ulrich
2017-05-01
Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.
Institute of Scientific and Technical Information of China (English)
徐会静; 赵书霞; 高飞; 张钰如; 李雪春; 王友年
2015-01-01
A new type of two-dimensional self-consistent fluid model that couples an equivalent circuit module is used to in-vestigate the mode transition characteristics and hysteresis in hydrogen inductively coupled plasmas at different pressures, by varying the series capacitance of the matching box. The variations of the electron density, temperature, and the cir-cuit electrical properties are presented. As cycling the matching capacitance, at high pressure both the discontinuity and hysteresis appear for the plasma parameters and the transferred impedances of both the inductive and capacitive discharge components, while at low pressure only the discontinuity is seen. The simulations predict that the sheath plays a determi-native role on the presence of discontinuity and hysteresis at high pressure, by influencing the inductive coupling efficiency of applied power. Moreover, the values of the plasma transferred impedances at different pressures are compared, and the larger plasma inductance at low pressure due to less collision frequency, as analyzed, is the reason why the hysteresis is not seen at low pressure, even with a wider sheath. Besides, the behaviors of the coil voltage and current parameters during the mode transitions are investigated. They both increase (decrease) at the E to H (H to E) mode transition, indicating an improved (worsened) inductive power coupling efficiency.
Xu, Hui-Jing; Zhao, Shu-Xia; Fei, Gao; Yu-Ru, Zhang; Xue-Chun, Li; You-Nian, Wang
2015-11-01
A new type of two-dimensional self-consistent fluid model that couples an equivalent circuit module is used to investigate the mode transition characteristics and hysteresis in hydrogen inductively coupled plasmas at different pressures, by varying the series capacitance of the matching box. The variations of the electron density, temperature, and the circuit electrical properties are presented. As cycling the matching capacitance, at high pressure both the discontinuity and hysteresis appear for the plasma parameters and the transferred impedances of both the inductive and capacitive discharge components, while at low pressure only the discontinuity is seen. The simulations predict that the sheath plays a determinative role on the presence of discontinuity and hysteresis at high pressure, by influencing the inductive coupling efficiency of applied power. Moreover, the values of the plasma transferred impedances at different pressures are compared, and the larger plasma inductance at low pressure due to less collision frequency, as analyzed, is the reason why the hysteresis is not seen at low pressure, even with a wider sheath. Besides, the behaviors of the coil voltage and current parameters during the mode transitions are investigated. They both increase (decrease) at the E to H (H to E) mode transition, indicating an improved (worsened) inductive power coupling efficiency. Project supported by the National Natural Science Foundation of China (Grant Nos. 11175034, 11205025, 11305023, and 11075029).
Numerical Modelling of Induction Heating for a Molten Salts Pyrochemical Process
Energy Technology Data Exchange (ETDEWEB)
Vu, Xuan-Tuyen; Feraud, Jean-Pierre; Ode, Denis [CEA Marcoule: DTEC/SGCS/LGCI Bat. 57 B17171, 30207 Bagnols/Ceze (France); Du Terrail Couvat, Yves [SIMaP, Grenoble INP, CNRS: ENSEEG, BP 75, 38402 Saint Martin d' Heres Cedex (France)
2008-07-01
Technological developments in the pyro-chemistry program are required to allow choices for a reprocessing experiment on 100 g of spent nuclear fuel. In this context, a special device must be designed for the solid/gas reaction phases followed by actinide extraction and stripping in molten salt. This paper discusses a modelling approach for designing an induction furnace. Using this numerical approach is a good way to improve thermal performance of the device in terms of magnetic/thermal coupling phenomena. The influence of current frequency is also studied to give another view of the possibilities of an induction furnace. Electromagnetic forces are taken into account in a computational fluid dynamics code derived from a specifically developed exchange library. Induction heating systems are an example of a typical multi-physics problem involving numerically coupled equations. (authors)
Electromagnetic, complex image model of a large area RF resonant antenna as inductive plasma source
Guittienne, Ph; Jacquier, R.; Howling, A. A.; Furno, I.
2017-03-01
A large area antenna generates a plasma by both inductive and capacitive coupling; it is an electromagnetically coupled plasma source. In this work, experiments on a large area planar RF antenna source are interpreted in terms of a multi-conductor transmission line coupled to the plasma. This electromagnetic treatment includes mutual inductive coupling using the complex image method, and capacitive matrix coupling between all elements of the resonant network and the plasma. The model reproduces antenna input impedance measurements, with and without plasma, on a 1.2× 1.2 m2 antenna used for large area plasma processing. Analytic expressions are given, and results are obtained by computation of the matrix solution. This method could be used to design planar inductive sources in general, by applying the termination impedances appropriate to each antenna type.
Institute of Scientific and Technical Information of China (English)
Henrique Ferraco Scolforo; Jose Roberto Soares Scolforo; Jose Marcio de Mello; Antonio Carlos Ferraz Filho; Diogo Francisco Rossoni; Thiza Falqueto Altoe; Antonio Donizette Oliveira; Renato Ribeiro de Lima
2016-01-01
The objectives of this study were to apply statistical techniques to discriminate fertilization treat-ments of Eremanthus erythropappus (DC.) MacLeish. through autoregressive modeling, and to develop individual tree models for diameter and crown area (CA) projection to define management strategies for candeia plantations sub-jected to different fertilization treatments. This is an important tree species originating from the Brazilian Atlantic Rain forest and Savannah biomes, intensively used in the cosmetic industry. Nonetheless, to date, research has not addressed the management of natural stands or plan-tations of the species. Our experiment was located in Baependi, Minas Gerais, Brazil, and comprised of four randomized blocks and 13 treatments. The treatments consisted of 12 different regimes of fertilization plus a control. Each sample plot was composed of 50 plants plus two border plants in a planting spacing of 2.5 9 2.0 m and undergoing pruning at 5 and 6 years of age. Starting in the second year, total tree height (H) and circumference (at 1.30 m from the ground or breast height, CBH) were measured every 6 months. Starting in the fifth year CA was measured. Tree growth varied by fertilization strategy. Differences were detected by using an autoregressive approach, considering that standard statistical methods were not powerful enough to detect significant differences. Three growth groups were formed, and maximum growth was obtained for treatment 10 (NPK, 8-28-16). Manage-ment guidelines are provided based on individual tree models for different fertilization levels.
Thermal Modeling for Pulsed Inductive FRC Plasmoid Thrusters
Pfaff, Michael
Due to the rising importance of space based infrastructure, long-range robotic space missions, and the need for active attitude control for spacecraft, research into Electric Propulsion is becoming increasingly important. Electric Propulsion (EP) systems utilize electric power to accelerate ions in order to produce thrust. Unlike traditional chemical propulsion, this means that thrust levels are relatively low. The trade-off is that EP thrusters have very high specific impulses (Isp), and can therefore make do with far less onboard propellant than cold gas, monopropellant, or bipropellant engines. As a consequence of the high power levels used to accelerate the ionized propellant, there is a mass and cost penalty in terms of solar panels and a power processing unit. Due to the large power consumption (and waste heat) from electric propulsion thrusters, accurate measurements and predictions of thermal losses are needed. Excessive heating in sensitive locations within a thruster may lead to premature failure of vital components. Between the fixed cost required to purchase these components, as well as the man-hours needed to assemble (or replace) them, attempting to build a high-power thruster without reliable thermal modeling can be expensive. This paper will explain the usage of FEM modeling and experimental tests in characterizing the ElectroMagnetic Plasmoid Thruster (EMPT) and the Electrodeless Lorentz Force (ELF) thruster at the MSNW LLC facility in Redmond, Washington. The EMPT thruster model is validated using an experimental setup, and steady state temperatures are predicted for vacuum conditions. Preliminary analysis of the ELF thruster indicates possible material failure in absence of an active cooling system for driving electronics and for certain power levels.
Markov-Tree model of intrinsic transport in Hamiltonian systems
Meiss, J. D.; Ott, E.
1985-01-01
A particle in a chaotic region of phase space can spend a long time near the boundary of a regular region since transport there is slow. This 'stickiness' of regular regions is thought to be responsible for previous observations in numerical experiments of a long-time algebraic decay of the particle survival probability, i.e., survival probability approximately t to the (-z) power for large t. This paper presents a global model for transport in such systems and demonstrates the essential role of the infinite hierarchy of small islands interspersed in the chaotic region. Results for z are discussed.
Baños, Hector; Bushek, Nathaniel; Davidson, Ruth; Gross, Elizabeth; Harris, Pamela E.; Krone, Robert; Long, Colby; Stewart, Allen; WALKER, Robert
2016-01-01
We introduce the package PhylogeneticTrees for Macaulay2 which allows users to compute phylogenetic invariants for group-based tree models. We provide some background information on phylogenetic algebraic geometry and show how the package PhylogeneticTrees can be used to calculate a generating set for a phylogenetic ideal as well as a lower bound for its dimension. Finally, we show how methods within the package can be used to compute a generating set for the join of any two ideals.
Karabulut, Esra Mahsereci; Ibrikci, Turgay
2014-05-01
This study develops a logistic model tree based automation system based on for accurate recognition of types of vertebral column pathologies. Six biomechanical measures are used for this purpose: pelvic incidence, pelvic tilt, lumbar lordosis angle, sacral slope, pelvic radius and grade of spondylolisthesis. A two-phase classification model is employed in which the first step is preprocessing the data by use of Synthetic Minority Over-sampling Technique (SMOTE), and the second one is feeding the classifier Logistic Model Tree (LMT) with the preprocessed data. We have achieved an accuracy of 89.73 %, and 0.964 Area Under Curve (AUC) in computer based automatic detection of the pathology. This was validated via a 10-fold-cross-validation experiment conducted on clinical records of 310 patients. The study also presents a comparative analysis of the vertebral column data with the use of several machine learning algorithms.
Model based optimization of wind erosion control by tree shelterbelt for suitable land management
Bartus, M.; Farsang, A.; Szatmári, J.; Barta, K.
2012-04-01
The degradation of soil by wind erosion causes huge problem in many parts of the world. The wind erodes the upper, nutrition rich part of the soil, therefore erosion causes soil productivity loss. The length of tree shelterbelts was significantly reduced by the collectivisation (1960-1989) and the wind erosion affected areas expanded in Hungary. The tree shelterbelt is more than just a tool of wind erosion control; by good planning it can increase the yield. The tree shelterbelt reduces the wind speed and changes the microclimate providing better condition to plant growth. The aim of our work is to estimate wind erosion risk and to find the way to reduce it by tree shelterbelts. A GIS based model was created to calculate the risk and the optimal windbreak position was defined to reduce the wind erosion risk to the minimum. The model is based on the DIN 19706 (Ermitlung der Erosiongefährdung von Böden durch Wind, Estimation of Wind Erosion Risk) German standard. The model uses five input data: structure and carbon content of soil, average yearly wind speed at 10 meters height, the cultivated plants and the height and position of windbreak. The study field (16km2) was chosen near Szeged (SE Hungary). In our investigation, the cultivated plant species and the position and height of windbreaks were modified. Different scenarios were made using the data of the land management in the last few years. The best case scenario (zero wind erosion) and the worst case scenario (with no tree shelter belt and the worst land use) were made to find the optimal windbreak position. Finally, the research proved that the tree shelterbelts can provide proper protection against wind erosion, but for optimal land management the cultivated plant types should also controlled. As a result of the research, a land management plan was defined to reduce the wind erosion risk on the study field, which contains the positions of new tree shelterbelts planting and the optimal cultivation.
Directory of Open Access Journals (Sweden)
Kei Takahashi
Full Text Available Induction of the immune response is a major problem in replacement therapies for inherited protein deficiencies. Tolerance created in utero can facilitate postnatal treatment. In this study, we aimed to induce immune tolerance towards a foreign protein with early gestational cell transplantation into the chorionic villi under ultrasound guidance in the murine model.Pregnant C57BL/6 (B6 mice on day 10 of gestation were anesthetized and imaged by high resolution ultrasound. Murine embryos and their placenta were positioned to get a clear view in B-mode with power mode of the labyrinth, which is the equivalent of chorionic villi in the human. Bone marrow cells (BMCs from B6-Green Fluorescence Protein (B6GFP transgenic mice were injected into the fetal side of the placenta which includes the labyrinth with glass microcapillary pipettes. Each fetal mouse received 2 x 105 viable GFP-BMCs. After birth, we evaluated the humoral and cell-mediated immune response against GFP.Bone marrow transfer into fetal side of placenta efficiently distributed donor cells to the fetal mice. The survival rate of this procedure was 13.5%(5 out of 37. Successful engraftment of the B6-GFP donor skin grafts was observed in all recipient (5 out of 5 mice 6 weeks after birth. Induction of anti-GFP antibodies was completely inhibited. Cytotoxic immune reactivity of thymic cells against cells harboring GFP was suppressed by ELISPOT assay.In this study, we utilized early gestational placental injection targeting the murine fetus, to transfer donor cells carrying a foreign protein into the fetal circulation. This approach is sufficient to induce both humoral and cell-mediated immune tolerance against the foreign protein.
Phase Transitions for Quantum Markov Chains Associated with Ising Type Models on a Cayley Tree
Mukhamedov, Farrukh; Barhoumi, Abdessatar; Souissi, Abdessatar
2016-05-01
The main aim of the present paper is to prove the existence of a phase transition in quantum Markov chain (QMC) scheme for the Ising type models on a Cayley tree. Note that this kind of models do not have one-dimensional analogous, i.e. the considered model persists only on trees. In this paper, we provide a more general construction of forward QMC. In that construction, a QMC is defined as a weak limit of finite volume states with boundary conditions, i.e. QMC depends on the boundary conditions. Our main result states the existence of a phase transition for the Ising model with competing interactions on a Cayley tree of order two. By the phase transition we mean the existence of two distinct QMC which are not quasi-equivalent and their supports do not overlap. We also study some algebraic property of the disordered phase of the model, which is a new phenomena even in a classical setting.
DEFF Research Database (Denmark)
Gunabalan, R.; Sanjeevikumar, P.; Blaabjerg, Frede
2015-01-01
This paper presents the transfer function modeling and stability analysis of two induction motors of same ratings and parameters connected in parallel. The induction motors are controlled by a single inverter and the entire drive system is modeled using transfer function in LabView. Further, the ...
Advanced simulation model for IPM motor drive with considering phase voltage and stator inductance
Lee, Dong-Myung; Park, Hyun-Jong; Lee, Ju
2016-10-01
This paper proposes an advanced simulation model of driving system for Interior Permanent Magnet (IPM) BrushLess Direct Current (BLDC) motors driven by 120-degree conduction method (two-phase conduction method, TPCM) that is widely used for sensorless control of BLDC motors. BLDC motors can be classified as SPM (Surface mounted Permanent Magnet) and IPM motors. Simulation model of driving system with SPM motors is simple due to the constant stator inductance regardless of the rotor position. Simulation models of SPM motor driving system have been proposed in many researches. On the other hand, simulation models for IPM driving system by graphic-based simulation tool such as Matlab/Simulink have not been proposed. Simulation study about driving system of IPMs with TPCM is complex because stator inductances of IPM vary with the rotor position, as permanent magnets are embedded in the rotor. To develop sensorless scheme or improve control performance, development of control algorithm through simulation study is essential, and the simulation model that accurately reflects the characteristic of IPM is required. Therefore, this paper presents the advanced simulation model of IPM driving system, which takes into account the unique characteristic of IPM due to the position-dependent inductances. The validity of the proposed simulation model is validated by comparison to experimental and simulation results using IPM with TPCM control scheme.
Directory of Open Access Journals (Sweden)
Mohamed Mostafa R.
2016-01-01
Full Text Available Self-Excited Permanent Magnet Induction Generator (PMIG is commonly used in wind energy generation systems. The difficulty of Self-Excited Permanent Magnet Induction Generator (SEPMIG modeling is the circuit parameters of the generator vary at each load conditions due to the a change in the frequency and stator voltage. The paper introduces a new modeling for SEPMIG using Gauss-sidle relaxation method. The SEPMIG characteristics using the proposed method are studied at different load conditions according to the wind speed variation, load impedance changes and different shunted capacitor values. The system modeling is investigated due to the magnetizing current variation, the efficiency variation, the power variation and power factor variation. The proposed modeling system satisfies high degree of simplicity and accuracy.
Modelling and Analysis of Variable Speed Wind Turbines with Induction Generator during Grid Fault
DEFF Research Database (Denmark)
Bolik, Sigrid Mechthild
operators as well as the challenges wind turbine manufacturers such as Vestas faced. Modelling has an important role in the research and development of system changes because it allows many difficult questions to be answered. The varieties of challenges that must be addressed in such modelling are not met...... by any single modelling software program. In addition a huge range of in-house programs from different companies exist, the most widely known software for current research on the power grid are PSS/E, EMTDC/PSCAD and DigSilent. In general research and especially for control developments the software....... The improvement of the large doubly-fed induction generator model as an interface between the mechanical and electrical characteristics of a wind turbine takes a central part in this research process. Chapter 3 presents the development and implementation of a detailed analytical three-phase induction machine...
Energy Technology Data Exchange (ETDEWEB)
Hemmateenejad, Bahram, E-mail: hemmatb@sums.ac.ir [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of); Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz (Iran, Islamic Republic of); Shamsipur, Mojtaba [Department of Chemistry, Razi University, Kermanshah (Iran, Islamic Republic of); Zare-Shahabadi, Vali [Young Researchers Club, Mahshahr Branch, Islamic Azad University, Mahshahr (Iran, Islamic Republic of); Akhond, Morteza [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of)
2011-10-17
Highlights: {yields} Ant colony systems help to build optimum classification and regression trees. {yields} Using of genetic algorithm operators in ant colony systems resulted in more appropriate models. {yields} Variable selection in each terminal node of the tree gives promising results. {yields} CART-ACS-GA could model the melting point of organic materials with prediction errors lower than previous models. - Abstract: The classification and regression trees (CART) possess the advantage of being able to handle large data sets and yield readily interpretable models. A conventional method of building a regression tree is recursive partitioning, which results in a good but not optimal tree. Ant colony system (ACS), which is a meta-heuristic algorithm and derived from the observation of real ants, can be used to overcome this problem. The purpose of this study was to explore the use of CART and its combination with ACS for modeling of melting points of a large variety of chemical compounds. Genetic algorithm (GA) operators (e.g., cross averring and mutation operators) were combined with ACS algorithm to select the best solution model. In addition, at each terminal node of the resulted tree, variable selection was done by ACS-GA algorithm to build an appropriate partial least squares (PLS) model. To test the ability of the resulted tree, a set of approximately 4173 structures and their melting points were used (3000 compounds as training set and 1173 as validation set). Further, an external test set containing of 277 drugs was used to validate the prediction ability of the tree. Comparison of the results obtained from both trees showed that the tree constructed by ACS-GA algorithm performs better than that produced by recursive partitioning procedure.
Analysis of Decision Trees in Context Clustering of Hidden Markov Model Based Thai Speech Synthesis
Directory of Open Access Journals (Sweden)
Suphattharachai Chomphan
2011-01-01
Full Text Available Problem statement: In Thai speech synthesis using Hidden Markov model (HMM based synthesis system, the tonal speech quality is degraded due to tone distortion. This major problem must be treated appropriately to preserve the tone characteristics of each syllable unit. Since tone brings about the intelligibility of the synthesized speech. It is needed to establish the tone questions and other phonetic questions in tree-based context clustering process accordingly. Approach: This study describes the analysis of questions in tree-based context clustering process of an HMM-based speech synthesis system for Thai language. In the system, spectrum, pitch or F0 and state duration are modeled simultaneously in a unified framework of HMM, their parameter distributions are clustered independently by using a decision-tree based context clustering technique. The contextual factors which affect spectrum, pitch and duration, i.e., part of speech, position and number of phones in a syllable, position and number of syllables in a word, position and number of words in a sentence, phone type and tone type, are taken into account for constructing the questions of the decision tree. All in all, thirteen sets of questions are analyzed in comparison. Results: In the experiment, we analyzed the decision trees by counting the number of questions in each node coming from those thirteen sets and by calculating the dominance score given to each question as the reciprocal of the distance from the root node to the question node. The highest number and dominance score are of the set of phonetic type, while the second, third highest ones are of the set of part of speech and tone type. Conclusion: By counting the number of questions in each node and calculating the dominance score, we can set the priority of each question set. All in all, the analysis results bring about further development of Thai speech synthesis with efficient context clustering process in
Cytokines and VEGF Induction in Orthodontic Movement in Animal Models
Directory of Open Access Journals (Sweden)
M. Di Domenico
2012-01-01
Full Text Available Orthodontics is a branch of dentistry that aims at the resolution of dental malocclusions. The specialist carries out the treatment using intraoral or extraoral orthodontic appliances that require forces of a given load level to obtain a tooth movement in a certain direction in dental arches. Orthodontic tooth movement is dependent on efficient remodeling of periodontal ligament and alveolar bone, correlated with several biological and mechanical responses of the tissues surrounding the teeth. A periodontal ligament placed under pressure will result in bone resorption whereas a periodontal ligament under tension results in bone formation. In the primary stage of the application of orthodontic forces, an acute inflammation occurs in periodontium. Several proinflammatory cytokines are produced by immune-competent cells migrating by means of dilated capillaries. In this paper we summarize, also through the utilization of animal models, the role of some of these molecules, namely, interleukin-1β and vascular endothelial growth factor, that are some proliferation markers of osteoclasts and osteoblasts, and the macrophage colony stimulating factor.
Advanced modelling of doubly fed induction generator wind turbine under network disturbance
DEFF Research Database (Denmark)
Seman, S.; Iov, Florin; Niiranen, J.;
and the drive train model. The Doubly Fed Induction Generator (DFIG) is represented by an analytical two-axis model with constant lumped parameters and by Finite Element Method (FEM) based model. The model of the DFIG is coupled with the model of the passive crowbar protected and DTC controlled frequency......This paper presents a variable speed wind turbine simulator. The simulator is used for a 2 MW wind turbine transient behavior study during a short-term symmetrical network disturbance. The mechanical part of wind turbine model consists of the rotor aerodynamic model, the wind turbine control...... converter, the model of the main transformer and a simple model of the grid. The simulation results obtained by means of the detailed wind turbine model are compared with the results obtained from a simplified simulator with an analytical model and FEM model of DFIG. The comparison of the results shows...
Comparison between 2D and 3D Modelling of Induction Machine Using Finite Element Method
Directory of Open Access Journals (Sweden)
Zelmira Ferkova
2015-01-01
Full Text Available The paper compares two different ways (2D and 3D of modelling of two-phase squirrel-cage induction machine using the finite element method (FEM. It focuses mainly on differences between starting characteristics given from both types of the model. It also discusses influence of skew rotor slots on harmonic content in air gap flux density and summarizes some issues of both approaches.
A conceptual approach to approximate tree root architecture in infinite slope models
Schmaltz, Elmar; Glade, Thomas
2016-04-01
Vegetation-related properties - particularly tree root distribution and coherent hydrologic and mechanical effects on the underlying soil mantle - are commonly not considered in infinite slope models. Indeed, from a geotechnical point of view, these effects appear to be difficult to be reproduced reliably in a physically-based modelling approach. The growth of a tree and the expansion of its root architecture are directly connected with both intrinsic properties such as species and age, and extrinsic factors like topography, availability of nutrients, climate and soil type. These parameters control four main issues of the tree root architecture: 1) Type of rooting; 2) maximum growing distance to the tree stem (radius r); 3) maximum growing depth (height h); and 4) potential deformation of the root system. Geometric solids are able to approximate the distribution of a tree root system. The objective of this paper is to investigate whether it is possible to implement root systems and the connected hydrological and mechanical attributes sufficiently in a 3-dimensional slope stability model. Hereby, a spatio-dynamic vegetation module should cope with the demands of performance, computation time and significance. However, in this presentation, we focus only on the distribution of roots. The assumption is that the horizontal root distribution around a tree stem on a 2-dimensional plane can be described by a circle with the stem located at the centroid and a distinct radius r that is dependent on age and species. We classified three main types of tree root systems and reproduced the species-age-related root distribution with three respective mathematical solids in a synthetic 3-dimensional hillslope ambience. Thus, two solids in an Euclidian space were distinguished to represent the three root systems: i) cylinders with radius r and height h, whilst the dimension of latter defines the shape of a taproot-system or a shallow-root-system respectively; ii) elliptic
On phase transitions of the Potts model with three competing interactions on Cayley tree
Directory of Open Access Journals (Sweden)
S. Temir
2011-06-01
Full Text Available In the present paper we study a phase transition problem for the Potts model with three competing interactions, the nearest neighbors, the second neighbors and triples of neighbors and non-zero external field on Cayley tree of order two. We prove that for some parameter values of the model there is phase transition. We reduce the problem of describing by limiting Gibbs measures to the problem of solving a system of nonlinear functional equations. We extend the results obtained by Ganikhodjaev and Rozikov [Math. Phys. Anal. Geom., 2009, vol. 12, No. 2, 141-156] on phase transition for the Ising model to the Potts model setting.
Four competing interactions for models with an uncountable set of spin values on a Cayley tree
Rozikov, U. A.; Haydarov, F. H.
2017-06-01
We consider models with four competing interactions ( external field, nearest neighbor, second neighbor, and three neighbors) and an uncountable set [0, 1] of spin values on the Cayley tree of order two. We reduce the problem of describing the splitting Gibbs measures of the model to the problem of analyzing solutions of a nonlinear integral equation and study some particular cases for Ising and Potts models. We also show that periodic Gibbs measures for the given models either are translation invariant or have the period two. We present examples where periodic Gibbs measures with the period two are not unique.
Liu, Tao; Im, Jungho; Quackenbush, Lindi J.
2015-12-01
This study provides a novel approach to individual tree crown delineation (ITCD) using airborne Light Detection and Ranging (LiDAR) data in dense natural forests using two main steps: crown boundary refinement based on a proposed Fishing Net Dragging (FiND) method, and segment merging based on boundary classification. FiND starts with approximate tree crown boundaries derived using a traditional watershed method with Gaussian filtering and refines these boundaries using an algorithm that mimics how a fisherman drags a fishing net. Random forest machine learning is then used to classify boundary segments into two classes: boundaries between trees and boundaries between branches that belong to a single tree. Three groups of LiDAR-derived features-two from the pseudo waveform generated along with crown boundaries and one from a canopy height model (CHM)-were used in the classification. The proposed ITCD approach was tested using LiDAR data collected over a mountainous region in the Adirondack Park, NY, USA. Overall accuracy of boundary classification was 82.4%. Features derived from the CHM were generally more important in the classification than the features extracted from the pseudo waveform. A comprehensive accuracy assessment scheme for ITCD was also introduced by considering both area of crown overlap and crown centroids. Accuracy assessment using this new scheme shows the proposed ITCD achieved 74% and 78% as overall accuracy, respectively, for deciduous and mixed forest.
Directory of Open Access Journals (Sweden)
Drew W Purves
Full Text Available BACKGROUND: Canopy structure, which can be defined as the sum of the sizes, shapes and relative placements of the tree crowns in a forest stand, is central to all aspects of forest ecology. But there is no accepted method for deriving canopy structure from the sizes, species and biomechanical properties of the individual trees in a stand. Any such method must capture the fact that trees are highly plastic in their growth, forming tessellating crown shapes that fill all or most of the canopy space. METHODOLOGY/PRINCIPAL FINDINGS: We introduce a new, simple and rapidly-implemented model--the Ideal Tree Distribution, ITD--with tree form (height allometry and crown shape, growth plasticity, and space-filling, at its core. The ITD predicts the canopy status (in or out of canopy, crown depth, and total and exposed crown area of the trees in a stand, given their species, sizes and potential crown shapes. We use maximum likelihood methods, in conjunction with data from over 100,000 trees taken from forests across the coterminous US, to estimate ITD model parameters for 250 North American tree species. With only two free parameters per species--one aggregate parameter to describe crown shape, and one parameter to set the so-called depth bias--the model captures between-species patterns in average canopy status, crown radius, and crown depth, and within-species means of these metrics vs stem diameter. The model also predicts much of the variation in these metrics for a tree of a given species and size, resulting solely from deterministic responses to variation in stand structure. CONCLUSIONS/SIGNIFICANCE: This new model, with parameters for US tree species, opens up new possibilities for understanding and modeling forest dynamics at local and regional scales, and may provide a new way to interpret remote sensing data of forest canopies, including LIDAR and aerial photography.
Purves, Drew W; Lichstein, Jeremy W; Pacala, Stephen W
2007-09-12
Canopy structure, which can be defined as the sum of the sizes, shapes and relative placements of the tree crowns in a forest stand, is central to all aspects of forest ecology. But there is no accepted method for deriving canopy structure from the sizes, species and biomechanical properties of the individual trees in a stand. Any such method must capture the fact that trees are highly plastic in their growth, forming tessellating crown shapes that fill all or most of the canopy space. We introduce a new, simple and rapidly-implemented model--the Ideal Tree Distribution, ITD--with tree form (height allometry and crown shape), growth plasticity, and space-filling, at its core. The ITD predicts the canopy status (in or out of canopy), crown depth, and total and exposed crown area of the trees in a stand, given their species, sizes and potential crown shapes. We use maximum likelihood methods, in conjunction with data from over 100,000 trees taken from forests across the coterminous US, to estimate ITD model parameters for 250 North American tree species. With only two free parameters per species--one aggregate parameter to describe crown shape, and one parameter to set the so-called depth bias--the model captures between-species patterns in average canopy status, crown radius, and crown depth, and within-species means of these metrics vs stem diameter. The model also predicts much of the variation in these metrics for a tree of a given species and size, resulting solely from deterministic responses to variation in stand structure. This new model, with parameters for US tree species, opens up new possibilities for understanding and modeling forest dynamics at local and regional scales, and may provide a new way to interpret remote sensing data of forest canopies, including LIDAR and aerial photography.
Orientation measurement based on magnetic inductance by the extended distributed multi-pole model.
Wu, Fang; Moon, Seung Ki; Son, Hungsun
2014-06-27
This paper presents a novel method to calculate magnetic inductance with a fast-computing magnetic field model referred to as the extended distributed multi-pole (eDMP) model. The concept of mutual inductance has been widely applied for position/orientation tracking systems and applications, yet it is still challenging due to the high demands in robust modeling and efficient computation in real-time applications. Recently, numerical methods have been utilized in design and analysis of magnetic fields, but this often requires heavy computation and its accuracy relies on geometric modeling and meshing that limit its usage. On the other hand, an analytical method provides simple and fast-computing solutions but is also flawed due to its difficulties in handling realistic and complex geometries such as complicated designs and boundary conditions, etc. In this paper, the extended distributed multi-pole model (eDMP) is developed to characterize a time-varying magnetic field based on an existing DMP model analyzing static magnetic fields. The method has been further exploited to compute the mutual inductance between coils at arbitrary locations and orientations. Simulation and experimental results of various configurations of the coils are presented. Comparison with the previously published data shows not only good performance in accuracy, but also effectiveness in computation.
Regional deposition of thoron progeny in models of the human tracheobronchial tree
Energy Technology Data Exchange (ETDEWEB)
Smith, S.M.; Cheng, Yung-Sung; Yeh, Hsu-Chi
1995-12-01
Models of the human tracheobronchial tree have been used to determine total and regional aerosol deposition of inhaled particles. Particle sizes measured in these studies have all been > 40 nm in diameter. The deposition of aerosols < 40 nm in diameter has not been measured. Particles in the ultrafine aerosol size range include some combustion aerosols and indoor radon progeny. Also, the influence of reduced lung size and airflow rates on particle deposition in young children has not been determined. With their smaller lung size and smaller minute volumes, children may be at increased risk from ultrafine pollutants. In order to accurately determine dose of inhaled aerosols, the effects of particle size, minute volume, and age at exposure must be quantified. The purpose of this study was to determine the deposition efficiency of ultrafine aerosols smaller than 40 nm in diameter in models of the human tracheobronchia tree. This study demonstrates that the deposition efficiency of aerosols in the model of the child`s tracheobronchial tree may be slightly higher than in the adult models.
Directory of Open Access Journals (Sweden)
Elias .
2011-03-01
Full Text Available The case study was conducted in the area of Acacia mangium plantation at BKPH Parung Panjang, KPH Bogor. The objective of the study was to formulate equation models of tree root carbon mass and root to shoot carbon mass ratio of the plantation. It was found that carbon content in the parts of tree biomass (stems, branches, twigs, leaves, and roots was different, in which the highest and the lowest carbon content was in the main stem of the tree and in the leaves, respectively. The main stem and leaves of tree accounted for 70% of tree biomass. The root-shoot ratio of root biomass to tree biomass above the ground and the root-shoot ratio of root biomass to main stem biomass was 0.1443 and 0.25771, respectively, in which 75% of tree carbon mass was in the main stem and roots of tree. It was also found that the root-shoot ratio of root carbon mass to tree carbon mass above the ground and the root-shoot ratio of root carbon mass to tree main stem carbon mass was 0.1442 and 0.2034, respectively. All allometric equation models of tree root carbon mass of A. mangium have a high goodness-of-fit as indicated by its high adjusted R2.Keywords: Acacia mangium, allometric, root-shoot ratio, biomass, carbon mass
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Claudiu MICH-VANCEA
2008-05-01
Full Text Available The most propitious projection of inductiveelectrothermic installation requires a deep study ofcoupled electrothermic and circuits problems; thereforethe present paper follows the same line. Research inspecific literature have emphasized that induction heatinghas a much higher efficiency if the supply of the charge(inductor – piece is done at frequencies other thatindustrial one. [1]. Due to material alter depending ontemperature and, implicitly, the variation of the electricalparameters of the heating installation it is necessary totackle the projection of these inductive electrothermicinstallation projected through coupled numericalmodeling of the inverter circuit and of the heatingthrough induction process. The paper presents thenumerical modeling of the continuous current –alternating current conversion bridge (inverter withelements of static switch – over, the type of commandsignal (PWM of elements of static switch of power, thenumerical modeling of the heating throughelectromagnetic induction process and aspects ofcorrelation regarding the functioning/ working of theinstallation depending on the parameters of the load. Theparameters get modified due to material alter dependingon temperature during the heating process.
Fu, Liyong; Zhang, Huiru; Lu, Jun; Zang, Hao; Lou, Minghua; Wang, Guangxing
2015-01-01
In this study, an individual tree crown ratio (CR) model was developed with a data set from a total of 3134 Mongolian oak (Quercus mongolica) trees within 112 sample plots allocated in Wangqing Forest Bureau of northeast China. Because of high correlation among the observations taken from the same sampling plots, the random effects at levels of both blocks defined as stands that have different site conditions and plots were taken into account to develop a nested two-level nonlinear mixed-effect model. Various stand and tree characteristics were assessed to explore their contributions to improvement of model prediction. Diameter at breast height, plot dominant tree height and plot dominant tree diameter were found to be significant predictors. Exponential model with plot dominant tree height as a predictor had a stronger ability to account for the heteroskedasticity. When random effects were modeled at block level alone, the correlations among the residuals remained significant. These correlations were successfully reduced when random effects were modeled at both block and plot levels. The random effects from the interaction of blocks and sample plots on tree CR were substantially large. The model that took into account both the block effect and the interaction of blocks and sample plots had higher prediction accuracy than the one with the block effect and population average considered alone. Introducing stand density into the model through dummy variables could further improve its prediction. This implied that the developed method for developing tree CR models of Mongolian oak is promising and can be applied to similar studies for other tree species.
Loss Current Analysis of Water Tree Degradation in Polyethylene using Equivalent Circuit Model
Suzuki, Masafumi; Itoh, Atsushi; Yoshimura, Noboru
It is well known that the degradation of XLPE cable by water tree gives rise to harmonics in the loss current. Many researches by simulation and experiment have been carried out for the purpose of the elucidation of the mechanism of the harmonics in the loss current generation. In the present study, the loss current was calculated from the equivalent circuit model composed of voltage-dependent resistance and condenser. These elements are being connected with the matrix state. As a result, we were able to obtain the good agreement between the experimental value and the calculated value by appropriately choosing the characteristics of the voltage-dependent resistance. The equivalent circuit model determined in this study can consider not only the electrical characteristic of water tree but also its shape.
DEFF Research Database (Denmark)
Goussanou, Cédric A.; Guendehou, Sabin; Assogbadjo, Achille E.
2016-01-01
The quantification of the contribution of tropical forests to global carbon stocks and climate change mitigation requires availability of data and tools such as allometric equations. This study made available volume and biomass models for eighteen tree species in a semi-deciduous tropical forest...... in West Africa. Generic models were also developed for the forest ecosystem, and basic wood density determined for the tree species. Non-destructive sampling approach was carried out on five hundred and one sample trees to analyse stem volume and biomass. From the modelling of volume and biomass...... predictive ability for biomass. Given tree species richness of tropical forests, the study demonstrated the hypothesis that species-specific models are preferred to generic models, and concluded that further research should be oriented towards development of specific models to cover the full range...
Effect Of Turbulence Modelling In Numerical Analysis Of Melting Process In An Induction Furnace
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Buliński P.
2015-09-01
Full Text Available In this paper, the velocity field and turbulence effects that occur inside a crucible of a typical induction furnace were investigated. In the first part of this work, a free surface shape of the liquid metal was measured in a ceramic crucible. Then a numerical model of aluminium melting process was developed. It took into account coupling of electromagnetic and thermofluid fields that was performed using commercial codes. In the next step, the sensitivity analysis of turbulence modelling in the liquid domain was performed. The obtained numerical results were compared with the measurement data. The performed analysis can be treated as a preliminary approach for more complex mathematical modelling for the melting process optimisation in crucible induction furnaces of different types.
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T. Sghaier
2013-12-01
Full Text Available Aim of study: The aim of the work was to develop an individual tree diameter-increment model for Thuya (Tetraclinis articulata in Tunisia.Area of study: The natural Tetraclinis articulata stands at Jbel Lattrech in north-eastern of Tunisia.Material and methods: Data came from 200 trees located in 50 sample plots. The diameter at age t and the diameter increment for the last five years obtained from cores taken at breast height were measured for each tree. Four difference equations derived from the base functions of Richards, Lundqvist, Hossfeld IV and Weibull were tested using the age-independent formulations of the growth functions. Both numerical and graphical analyses were used to evaluate the performance of the candidate models.Main results: Based on the analysis, the age-independent difference equation derived from the base function Richards model was selected. Two of the three parameters (growth rate and shape parameter of the retained model were related to site quality, represented by a Growth Index, stand density and the basal area in larger trees divided by diameter of the subject tree expressing the inter-tree competition.Research highlights: The proposed model can be useful for predicting the diameter growth of Tetraclinis articulata in Tunisia when age is not available or for trees growing in uneven-aged stands.Keywords: Age-independent growth model; difference equations; Tetraclinis articulata; Tunisia.
CFD modelling of the aerodynamic effect of trees on urban air pollution dispersion.
Amorim, J H; Rodrigues, V; Tavares, R; Valente, J; Borrego, C
2013-09-01
The current work evaluates the impact of urban trees over the dispersion of carbon monoxide (CO) emitted by road traffic, due to the induced modification of the wind flow characteristics. With this purpose, the standard flow equations with a kε closure for turbulence were extended with the capability to account for the aerodynamic effect of trees over the wind field. Two CFD models were used for testing this numerical approach. Air quality simulations were conducted for two periods of 31h in selected areas of Lisbon and Aveiro, in Portugal, for distinct relative wind directions: approximately 45° and nearly parallel to the main avenue, respectively. The statistical evaluation of modelling performance and uncertainty revealed a significant improvement of results with trees, as shown by the reduction of the NMSE from 0.14 to 0.10 in Lisbon, and from 0.14 to 0.04 in Aveiro, which is independent from the CFD model applied. The consideration of the plant canopy allowed to fulfil the data quality objectives for ambient air quality modelling established by the Directive 2008/50/EC, with an important decrease of the maximum deviation between site measurements and CFD results. In the non-aligned wind situation an average 12% increase of the CO concentrations in the domain was observed as a response to the aerodynamic action of trees over the vertical exchange rates of polluted air with the above roof-level atmosphere; while for the aligned configuration an average 16% decrease was registered due to the enhanced ventilation of the street canyon. These results show that urban air quality can be optimised based on knowledge-based planning of green spaces.
Analysis of a Model for the Morphological Structure of Renal Arterial Tree: Fractal Structure
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Aurora Espinoza-Valdez
2013-01-01
experimental data measurements of the rat kidneys. The fractal dimension depends on the probability of sprouting angiogenesis in the development of the arterial vascular tree of the kidney, that is, of the distribution of blood vessels in the morphology generated by the analytical model. The fractal dimension might determine whether a suitable renal vascular structure is capable of performing physiological functions under appropriate conditions. The analysis can describe the complex structures of the development vasculature in kidney.
B-tree search reinforcement learning for model based intelligent agent
Bhuvaneswari, S.; Vignashwaran, R.
2013-03-01
Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.
Boundary Conditions for Translation-Invariant Gibbs Measures of the Potts Model on Cayley Trees
Gandolfo, D.; Rahmatullaev, M. M.; Rozikov, U. A.
2017-06-01
We consider translation-invariant splitting Gibbs measures (TISGMs) for the q-state Potts model on a Cayley tree of order two. Recently a full description of the TISGMs was obtained, and it was shown in particular that at sufficiently low temperatures their number is 2q-1. In this paper for each TISGM μ we explicitly give the set of boundary conditions such that limiting Gibbs measures with respect to these boundary conditions coincide with μ.
Study and ranking of determinants of Taenia solium infections by classification tree models
Mwape, Kabemba E.; Phiri, Isaac K.; Praet, Nicolas; Dorny, Pierre; Muma, John B; Zulu, Gideon; Speybroeck, Niko; Gabriël, Sarah
2015-01-01
Taenia solium taeniasis/cysticercosis is an important public health problem occurring mainly in developing countries. This work aimed to study the determinants of human T. solium infections in the Eastern province of Zambia and rank them in order of importance. A household (HH)-level questionnaire was administered to 680 HHs from 53 villages in two rural districts and the taeniasis and cysticercosis status determined. A classification tree model (CART) was used to define the relative importan...
Modeling tree growth and stable isotope ratios of white spruce in western Alaska.
Boucher, Etienne; Andreu-Hayles, Laia; Field, Robert; Oelkers, Rose; D'Arrigo, Rosanne
2017-04-01
Summer temperatures are assumed to exert a dominant control on physiological processes driving forest productivity in interior Alaska. However, despite the recent warming of the last few decades, numerous lines of evidence indicate that the enhancing effect of summer temperatures on high latitude forest populations has been weakening. First, satellite-derived indices of photosynthetic activity, such as the Normalized-Difference Vegetation Index (NDVI, 1982-2005), show overall declines in productivity in the interior boreal forests. Second, some white spruce tree ring series strongly diverge from summer temperatures during the second half of the 20th century, indicating a persistent loss of temperature sensitivity of tree ring proxies. Thus, the physiological response of treeline forests to ongoing climate change cannot be accurately predicted, especially from correlation analysis. Here, we make use of a process-based dendroecological model (MAIDENiso) to elucidate the complex linkages between global warming and increases in atmospheric CO2 concentration [CO2] with the response of treeline white spruce stands in interior Alaska (Seward). In order to fully capture the array of processes controlling tree growth in the area, multiple physiological indicators of white spruce productivity are used as target variables: NDVI images, ring widths (RW), maximum density (MXD) and newly measured carbon and oxygen stable isotope ratios from ring cellulose. Based on these data, we highlight the processes and mechanisms responsible for the apparent loss of sensitivity of white spruce trees to recent climate warming and [CO2] increase in order to elucidate the sensitivity and vulnerability of these trees to climate change.
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Dan A. MacIsaac
2011-09-01
Full Text Available We investigated the relationship of stem diameter to tree, site and stand characteristics for six major tree species (trembling aspen, white birch, balsam fir, lodgepole pine, black spruce, and white spruce in Alberta (Canada with data from Alberta Sustainable Resource Development Permanent Sample Plots. Using non-linear mixed effects modeling techniques, we developed models to estimate diameter at breast height using height, crown and stand attributes. Mixed effects models (with plot as subject using height, crown area, and basal area of the larger trees explained on average 95% of the variation in diameter at breast height across the six species with a root mean square error of 2.0 cm (13.4% of mean diameter. Fixed effects models (without plot as subject including the Natural Sub-Region (NSR information explained on average 90% of the variation in diameter at breast height across the six species with a root mean square error equal to 2.8 cm (17.9% of mean diameter. Selected climate variables provided similar results to models with NSR information. The inclusion of nutrient regime and moisture regime did not significantly improve the predictive ability of these models.
Transient flow model and pressure dynamic features of tree-shaped fractal re- servoirs
Institute of Scientific and Technical Information of China (English)
TAN Xiao-hua; LI Xiao-ping
2014-01-01
A transient flow model of tree-shaped fractal reservoirs is built by embedding a fracture network simulated by a tree-shaped fractal network into a matrix system. The model can be solved using the Laplace conversion method. The dimensionless bottom hole pressure can be obtained using the Stehfest numerical inversion method. The bi-logarithmic type curves for the tree-shaped fractal reservoirs are thus obtained. The pressure transient responses under different fractal factors are discussed. The factors with a primary effect on the inter-porosity flow regime include the initial branch numberN, the length ratioα, and the branch angleθ. The diameter ratioβ has a significant effect on the fracture radial flow, the inter-porosity and the total system radial flow regimes. The total branch levelM of the network mainly influences the total system radial flow regime. The model presented in this paper provides a new methodology for analyzing and predicting the pressure dynamic characteristics of naturally fractured reservoirs.
A New Model for Size-Dependent Tree Growth in Forests.
Ishihara, Masae Iwamoto; Konno, Yasuo; Umeki, Kiyoshi; Ohno, Yasuyuki; Kikuzawa, Kihachiro
2016-01-01
Tree growth, especially diameter growth of tree stems, is an important issue for understanding the productivity and dynamics of forest stands. Metabolic scaling theory predicted that the 2/3 power of stem diameter at a certain time is a linear function of the 2/3 power of the initial diameter and that the diameter growth rate scales to the 1/3 power of the initial diameter. We tested these predictions of the metabolic scaling theory for 11 Japanese secondary forests at various growth stages. The predictions were not supported by the data, especially in younger stands. Alternatively, we proposed a new theoretical model for stem diameter growth on the basis of six assumptions. All these assumptions were supported by the data. The model produced a nearly linear to curvilinear relationship between the 2/3 power of stem diameters at two different times. It also fitted well to the curvilinear relationship between diameter growth rate and the initial diameter. Our model fitted better than the metabolic scaling theory, suggesting the importance of asymmetric competition among trees, which has not been incorporated in the metabolic scaling theory.
Reduced models of doubly fed induction generator system for wind turbine simulations
DEFF Research Database (Denmark)
Sørensen, Poul Ejnar; Hansen, Anca Daniela; Lund, Torsten
2005-01-01
This article compares three reduced models with a detailed model of a doubly fed induction generator system for wind turbine applications. The comparisons are based on simulations only. The main idea is to provide reduced generator models which are appropriate to simulate normal wind turbine...... operation in aeroelastic wind turbine models, e.g. for control system design or structural design of the wind turbine. The electrical behaviour such as grid influence will therefore not be considered. The work presented in this article shows that with an ideal, undisturbed grid the dynamics of the doubly...
Analytical modelling of soil effects on electromagnetic induction sensor for humanitarian demining
Vasić, D.; Ambruš, D.; Bilas, V.
2013-06-01
Accurate compensation of the soil effect is essential for a new generation of sensitive classification-based electromagnetic induction landmine detectors. We present an analytical model for evaluation of the soil effect suitable for straightforward numerical implementation. The modelled soil consists of arbitrary number of conductive and magnetic layers. The solution region is truncated leading to the solution in form of a series rather than infinite integrals. Frequency-dependent permeability is inherent to the model, and time domain analysis can be made using DFT. In order to illustrate the model usage, we evaluate performances of three metal detector designs.
Forecasting Low-Visibility Conditions at Vienna Airport with Tree-Based Statistical Models
Dietz, Sebastian; Kneringer, Philipp; Mayr, Georg J.; Zeileis, Achim
2016-04-01
Low visibility conditions at airports can lead to capacity problems and therefore to delays or cancelation of arriving and departing airplanes. To keep the capacity as high as possible, accurate visibility forecasts are required. Therefore tree-based statistical nowcasting models were developed, which split the data in the sense of decision rules by recursive partitioning. Benefits of this models are fast update cycles and low computation times. Highly-resolved meteorological observation data at the airport form the large pool of input variables for the models. In this study we identify the most important predictors for different lead times to create the most accurate forecasts.
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Roozbeh Hasanzadeh Nafari
2016-07-01
Full Text Available Flood is a frequent natural hazard that has significant financial consequences for Australia. In Australia, physical losses caused by floods are commonly estimated by stage-damage functions. These methods usually consider only the depth of the water and the type of buildings at risk. However, flood damage is a complicated process, and it is dependent on a variety of factors which are rarely taken into account. This study explores the interaction, importance, and influence of water depth, flow velocity, water contamination, precautionary measures, emergency measures, flood experience, floor area, building value, building quality, and socioeconomic status. The study uses tree-based models (regression trees and bagging decision trees and a dataset collected from 2012 to 2013 flood events in Queensland, which includes information on structural damages, impact parameters, and resistance variables. The tree-based approaches show water depth, floor area, precautionary measures, building value, and building quality to be important damage-influencing parameters. Furthermore, the performance of the tree-based models is validated and contrasted with the outcomes of a multi-parameter loss function (FLFArs from Australia. The tree-based models are shown to be more accurate than the stage-damage function. Consequently, considering more parameters and taking advantage of tree-based models is recommended. The outcome is important for improving established Australian flood loss models and assisting decision-makers and insurance companies dealing with flood risk assessment.
Population based model of human embryonic stem cell (hESC differentiation during endoderm induction.
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Keith Task
Full Text Available The mechanisms by which human embryonic stem cells (hESC differentiate to endodermal lineage have not been extensively studied. Mathematical models can aid in the identification of mechanistic information. In this work we use a population-based modeling approach to understand the mechanism of endoderm induction in hESC, performed experimentally with exposure to Activin A and Activin A supplemented with growth factors (basic fibroblast growth factor (FGF2 and bone morphogenetic protein 4 (BMP4. The differentiating cell population is analyzed daily for cellular growth, cell death, and expression of the endoderm proteins Sox17 and CXCR4. The stochastic model starts with a population of undifferentiated cells, wherefrom it evolves in time by assigning each cell a propensity to proliferate, die and differentiate using certain user defined rules. Twelve alternate mechanisms which might describe the observed dynamics were simulated, and an ensemble parameter estimation was performed on each mechanism. A comparison of the quality of agreement of experimental data with simulations for several competing mechanisms led to the identification of one which adequately describes the observed dynamics under both induction conditions. The results indicate that hESC commitment to endoderm occurs through an intermediate mesendoderm germ layer which further differentiates into mesoderm and endoderm, and that during induction proliferation of the endoderm germ layer is promoted. Furthermore, our model suggests that CXCR4 is expressed in mesendoderm and endoderm, but is not expressed in mesoderm. Comparison between the two induction conditions indicates that supplementing FGF2 and BMP4 to Activin A enhances the kinetics of differentiation than Activin A alone. This mechanistic information can aid in the derivation of functional, mature cells from their progenitors. While applied to initial endoderm commitment of hESC, the model is general enough to be applicable
Task, Keith; Jaramillo, Maria; Banerjee, Ipsita
2012-01-01
The mechanisms by which human embryonic stem cells (hESC) differentiate to endodermal lineage have not been extensively studied. Mathematical models can aid in the identification of mechanistic information. In this work we use a population-based modeling approach to understand the mechanism of endoderm induction in hESC, performed experimentally with exposure to Activin A and Activin A supplemented with growth factors (basic fibroblast growth factor (FGF2) and bone morphogenetic protein 4 (BMP4)). The differentiating cell population is analyzed daily for cellular growth, cell death, and expression of the endoderm proteins Sox17 and CXCR4. The stochastic model starts with a population of undifferentiated cells, wherefrom it evolves in time by assigning each cell a propensity to proliferate, die and differentiate using certain user defined rules. Twelve alternate mechanisms which might describe the observed dynamics were simulated, and an ensemble parameter estimation was performed on each mechanism. A comparison of the quality of agreement of experimental data with simulations for several competing mechanisms led to the identification of one which adequately describes the observed dynamics under both induction conditions. The results indicate that hESC commitment to endoderm occurs through an intermediate mesendoderm germ layer which further differentiates into mesoderm and endoderm, and that during induction proliferation of the endoderm germ layer is promoted. Furthermore, our model suggests that CXCR4 is expressed in mesendoderm and endoderm, but is not expressed in mesoderm. Comparison between the two induction conditions indicates that supplementing FGF2 and BMP4 to Activin A enhances the kinetics of differentiation than Activin A alone. This mechanistic information can aid in the derivation of functional, mature cells from their progenitors. While applied to initial endoderm commitment of hESC, the model is general enough to be applicable either to a system of
A new circuit-oriented model for the analysis of six-phase induction machine performances
Energy Technology Data Exchange (ETDEWEB)
Aroquiadassou, Gerard; Henao, Humberto; Capolino, Gerard-Andre [University of Picardie Jules Verne, Department of Electrical Engineering, 33 rue Saint Leu, 80039 Amiens Cedex 1 (France); Cavagnino, Andrea; Boglietti, Aldo [Politecnico di Torino, Department of Electrical Engineering, C.so Duca degli Abruzzi 24, 10129 Torino (Italy)
2008-10-15
This paper deals with a six-phase induction machine design for 42 V embedded applications such as electrical power steering. This machine has symmetrical 60 displacement windings which allow fault-tolerant modes. In fact, when one or more phases are opened, the machine is able to rotate with a torque reduction. A simple circuit-oriented model has been proposed in order to simulate the six-phase squirrel-cage induction machine and to predict its performances. The proposed method consists in the elaboration of an electric equivalent circuit obtained from minimal dimensional knowledge of stator and rotor parts. It takes into account only the magnetic circuit dimensions and the airgap length. A six-phase squirrel-cage induction machine of 0.09 kW, 17 V, 50 Hz, two poles has been used for the experimental set-up. A design program including the non-linear electromagnetic model has been also used with a complete description of stator and rotor cores using the iron non-linear characteristic for the final verification. The simulation results given by the two models are compared with the experimental tests in order to verify their accuracy. The harmonic analyses of stator currents are also compared to go further in the model validations. (author)
Advanced Model of Squirrel Cage Induction Machine for Broken Rotor Bars Fault Using Multi Indicators
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Ilias Ouachtouk
2016-01-01
Full Text Available Squirrel cage induction machine are the most commonly used electrical drives, but like any other machine, they are vulnerable to faults. Among the widespread failures of the induction machine there are rotor faults. This paper focuses on the detection of broken rotor bars fault using multi-indicator. However, diagnostics of asynchronous machine rotor faults can be accomplished by analysing the anomalies of machine local variable such as torque, magnetic flux, stator current and neutral voltage signature analysis. The aim of this research is to summarize the existing models and to develop new models of squirrel cage induction motors with consideration of the neutral voltage and to study the effect of broken rotor bars on the different electrical quantities such as the park currents, torque, stator currents and neutral voltage. The performance of the model was assessed by comparing the simulation and experimental results. The obtained results show the effectiveness of the model, and allow detection and diagnosis of these defects.
Institute of Scientific and Technical Information of China (English)
T. R. Chandrasekhar
2012-01-01
No attempt has been made to date to model growth in girth of rubber tree (Hevea brasiliansis).We evaluated the few widely used growth functions to identify the most parsimonious and biologically reasonable model for describing the girth growth of young rubber trees based on an incomplete set of young age measurements.Monthly data for girth of immature trees (age 2 to 12 years) from two locations were subjected to modelling.Re-parameterized,unconstrained and constrained growth functions of Richards (RM),Gompertz (GM) and the monomolecular model (MM) were fitted to data.Duration of growth was the constraint introduced.In the first stage,we attempted a population average (PA) model to capture the trend in growth.The best PA model was fitted as a subject specific (SS) model.We used appropriate error variance-covariance structure to account for correlation due to repeated measurements over time.Unconstrained functions underestimated the asymptotic maximum that did not reflect the carrying capacity of the locations.Underestimations were attributed to the partial set of measurements made during the early growth phase of the trees.MM proved superior to RM and GM.In the random coefficient models,both Gf and G0 appeared to be influenced by tree level effects.Inclusion of diagonal definite positive matrix removed the correlation between random effects.The results were similar at both locations.In the overall assessment MM appeared as the candidate model for studying the girth-age relationships in Hevea trees.Based on the fitted model we conclude that,in Hevea trees,growth rate is maintained at maximum value at t0,then decreases until the final state at dG/dt ≥ 0,resulting in yield curve with no period of accelerating growth.One physiological explanation is that photosynthetic activity in Hevea trees decreases as girth increases and constructive metabolism is larger than destructive metabolism.
Proof-irrelevant model of CC with predicative induction and judgmental equality
Lee, Gyesik
2011-01-01
We present a set-theoretic, proof-irrelevant model for Calculus of Constructions (CC) with predicative induction and judgmental equality in Zermelo-Fraenkel set theory with an axiom for countably many inaccessible cardinals. We use Aczel's trace encoding which is universally defined for any function type, regardless of being impredicative. Direct and concrete interpretations of simultaneous induction and mutually recursive functions are also provided by extending Dybjer's interpretations on the basis of Aczel's rule sets. Our model can be regarded as a higher-order generalization of the truth-table methods. We provide a relatively simple consistency proof of type theory, which can be used as the basis for a theorem prover.
Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise
Wu, Fuqiang; Wang, Chunni; Jin, Wuyin; Ma, Jun
2017-03-01
Complex electrical activities in neuron can induce time-varying electromagnetic field and the effect of various electromagnetic inductions should be considered in dealing with electrical activities of neuron. Based on an improved neuron model, the effect of electromagnetic induction is described by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. Furthermore, additive phase noise is imposed on the neuron to detect the dynamical response of neuron and phase transition in modes. The dynamical properties of electrical activities are detected and discussed, and double coherence resonance behavior is observed, respectively. Furthermore, multiple modes of electrical activities can be observed in the sampled time series for membrane potential of the neuron model.
Kane, Jeffrey M.; van Mantgem, Phillip J.; Lalemand, Laura; Keifer, MaryBeth
2017-01-01
Managers require accurate models to predict post-fire tree mortality to plan prescribed fire treatments and examine their effectiveness. Here we assess the performance of a common post-fire tree mortality model with an independent dataset of 11 tree species from 13 National Park Service units in the western USA. Overall model discrimination was generally strong, but performance varied considerably among species and sites. The model tended to have higher sensitivity (proportion of correctly classified dead trees) and lower specificity (proportion of correctly classified live trees) for many species, indicating an overestimation of mortality. Variation in model accuracy (percentage of live and dead trees correctly classified) among species was not related to sample size or percentage observed mortality. However, we observed a positive relationship between specificity and a species-specific bark thickness multiplier, indicating that overestimation was more common in thin-barked species. Accuracy was also quite low for thinner bark classes (<1 cm) for many species, leading to poorer model performance. Our results indicate that a common post-fire mortality model generally performs well across a range of species and sites; however, some thin-barked species and size classes would benefit from further refinement to improve model specificity.
Fault Tree Model for Failure Path Prediction of Bolted Steel Tension Member in a Structural System
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Biswajit Som
2015-06-01
Full Text Available Fault tree is a graphical representation of various sequential combinations of events which leads to the failure of any system, such as a structural system. In this paper it is shown that a fault tree model is also applicable to a critical element of a complex structural system. This will help to identify the different failure mode of a particular structural element which might eventually triggered a progressive collapse of the whole structural system. Non-redundant tension member generally regarded as a Fracture Critical Member (FCM in a complex structural system, especially in bridge, failure of which may lead to immediate collapse of the structure. Limit state design is governed by the failure behavior of a structural element at its ultimate state. Globally, condition assessment of an existing structural system, particularly for bridges, Fracture Critical Inspection becomes very effective and mandatory in some countries. Fault tree model of tension member, presented in this paper can be conveniently used to identify the flaws in FCM if any, in an existing structural system and also as a check list for new design of tension member.
Soner Yorgun, M; Rood, Richard B
2016-12-01
An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smooth topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.
The tree shrews: useful animal models for the viral hepatitis and hepatocellular carcinoma.
Yang, Er-Bin; Cao, Ji; Su, Jian-Jia; Chow, Pierce
2005-01-01
Hepatitis B virus (HBV)-induced hepatitis and hepatocellular carcinoma (HCC) are major diseases worldwide. HBV infection and chemical carcinogens such as aflatoxin B1 are known to be two key factors in the development of HCC. Animal models for hepatitis and HCC are very useful in the in vivo studies of mechanism involved in the development and prevention of these diseases and the pre-clinical research of drugs for the treatment of these diseases. Now, several animals, such as woodchucks, ground squirrels, chimpanzees, ducks and tree shrews, have been used to establish hepatitis and HCC models. HCC occurs in some woodchucks and ground squirrels that are infected with their own hepatitis viruses and exposed to carcinogens. Chimpanzees and ducks can be infected with human and duck hepatitis B viruses, respectively, but HCC is rarely observed in these animals. The tree shrews are non-rodent, small animals and close to primates in evolution. This review focuses on the establishment of human HBV-induced hepatitis and human HBV-associated HCC in tree shrews and their applications in the study of HCC development.
A Model-Driven Parser Generator, from Abstract Syntax Trees to Abstract Syntax Graphs
Quesada, Luis; Cubero, Juan-Carlos
2012-01-01
Model-based parser generators decouple language specification from language processing. The model-driven approach avoids the limitations that conventional parser generators impose on the language designer. Conventional tools require the designed language grammar to conform to the specific kind of grammar supported by the particular parser generator (being LL and LR parser generators the most common). Model-driven parser generators, like ModelCC, do not require a grammar specification, since that grammar can be automatically derived from the language model and, if needed, adapted to conform to the requirements of the given kind of parser, all of this without interfering with the conceptual design of the language and its associated applications. Moreover, model-driven tools such as ModelCC are able to automatically resolve references between language elements, hence producing abstract syntax graphs instead of abstract syntax trees as the result of the parsing process. Such graphs are not confined to directed ac...
Approximate group context tree: applications to dynamic programming and dynamic choice models
Belloni, Alexandre
2011-01-01
The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities. We propose a new model selection and estimation method, develop oracle inequalities and model selection properties for the estimator. These results also provide conditions under which the use of the group structure can lead to improvements in the overall estimation. Our work is also motivated by two methodological applications: discrete stochastic dynamic programming and dynamic discrete choice models. We analyze the uniform estimation of the value function for dynamic programming and the uniform estimation of average dynamic marginal effects for dynamic discrete choice models accounting for possible imperfect model selection. We also derive the typical behavior of our estimator when applied to polynomially $\\beta$-mixing stochastic processes. For parametric models, we derive uniform rate of convergence for the estimation...
Study of airflow during respiratory cycle in semi-realistic model of human tracheobronchial tree
Elcner, Jakub; Zaremba, M.; Maly, M.; Jedelsky, J.; Lizal, F.; Jicha, M.
2016-06-01
This article deals with study of airflow under breathing process, which is characteristic by unsteady behavior. Simulations provided by computational fluid dynamics (CFD) was compared with experiments performed on similar geometry of human upper airways. This geometry was represented by mouth cavity of realistic shape connected to an idealized tracheobronchial tree up to fourth generation of branching. Commercial CFD software Star-CCM+ was used to calculate airflow inside investigated geometry and method of Reynolds averaging of Navier-Stokes equations was used for subscribing the turbulent behavior through model geometry. Conditions corresponding to resting state were considered. Comparisons with experiments were provided on several points through trachea and bronchial tree and results with respect to inspiratory and respiratory part of breathing cycle was discussed.
Directory of Open Access Journals (Sweden)
Gang WU
2016-01-01
Full Text Available Objective To analyze the risk factors for prognosis in intracerebral hemorrhage using decision tree (classification and regression tree, CART model and logistic regression model. Methods CART model and logistic regression model were established according to the risk factors for prognosis of patients with cerebral hemorrhage. The differences in the results were compared between the two methods. Results Logistic regression analyses showed that hematoma volume (OR-value 0.953, initial Glasgow Coma Scale (GCS score (OR-value 1.210, pulmonary infection (OR-value 0.295, and basal ganglia hemorrhage (OR-value 0.336 were the risk factors for the prognosis of cerebral hemorrhage. The results of CART analysis showed that volume of hematoma and initial GCS score were the main factors affecting the prognosis of cerebral hemorrhage. The effects of two models on the prognosis of cerebral hemorrhage were similar (Z-value 0.402, P=0.688. Conclusions CART model has a similar value to that of logistic model in judging the prognosis of cerebral hemorrhage, and it is characterized by using transactional analysis between the risk factors, and it is more intuitive. DOI: 10.11855/j.issn.0577-7402.2015.12.13
Malik, Naveed ur Rehman
2015-01-01
This thesis deals with the modeling, analysis and control of a novel brushlessgenerator for wind power application. The generator is named as rotatingpower electronic brushless doubly-fed induction machine/generator (RPEBDFIM/G). A great advantage of the RPE-BDFIG is that the slip power recoveryis realized in a brushless manner. This is achieved by introducing an additionalmachine termed as exciter together with the rotating power electronicconverters, which are mounted on the shaft of a DFIG...
A Tightly Coupled Non-Equilibrium Magneto-Hydrodynamic Model for Inductively Coupled RF Plasmas
2016-02-29
effects are described based on a hybrid State-to-State (StS) approach. A multi-temperature formulation is used to account for thermal non-equilibrium...for Inductively Coupled Radio-Frequency (RF) Plasmas. Non Local Thermodynamic Equilibrium (NLTE) effects are described based on a hybrid State-to-State...usually obtained through quantum chemistry calculations51–56 or through phenomenological models providing a simplified descrip- tion of the kinetic
Numerical modeling of magnetic induction and heating in injection molding tools
DEFF Research Database (Denmark)
Guerrier, Patrick; Hattel, Jesper Henri
2013-01-01
Injection molding of parts with special requirements or features such as micro- or nanostructures on the surface, a good surface finish, or long and thin features results in the need of a specialized technique to ensure proper filling and acceptable cycle time. The aim of this study is to increase...... numerical modeling of the induction heating in the mold to investigate how the temperature in the mold will be distributed and how it is affected by different material properties....
Spanning trees of the World Trade Web: real-world data and the gravity model of trade
Skowron, Patryk; Fronczak, Agata; Fronczak, Piotr
2014-01-01
In this paper, we investigate the statistical features of the weighted international-trade network. By finding the maximum weight spanning trees for this network we make the extraction of the truly relevant connections forming the network's backbone. We discuss the role of large-sized countries (strongest economies) in the tree. Finally, we compare the topological properties of this backbone to the maximum weight spanning trees obtained from the gravity model of trade. We show that the model correctly reproduces the backbone of the real-world economy.
Sensorless Modeling of Varying Pulse Width Modulator Resolutions in Three-Phase Induction Motors
Marko, Matthew David; Shevach, Glenn
2017-01-01
A sensorless algorithm was developed to predict rotor speeds in an electric three-phase induction motor. This sensorless model requires a measurement of the stator currents and voltages, and the rotor speed is predicted accurately without any mechanical measurement of the rotor speed. A model of an electric vehicle undergoing acceleration was built, and the sensorless prediction of the simulation rotor speed was determined to be robust even in the presence of fluctuating motor parameters and significant sensor errors. Studies were conducted for varying pulse width modulator resolutions, and the sensorless model was accurate for all resolutions of sinusoidal voltage functions. PMID:28076418
Ohtaki, M; Niwa, O
2001-11-01
We developed a mathematical model of carcinogenesis that incorporates genomic instability, a feature characterized by long-term destabilization of the genome in irradiated cells that leads to an increase in cancer risk in the exposed individuals at the cancer-prone age. This model also considers the induction of cell death, another important effect of radiation on cells. It is assumed that cell killing by radiation may occur at all stages of the carcinogenic process. The resulting model can explain not only the paradoxical relationship between low mutation rates and high cancer incidence but also the low-order dose-response relationship of cancer risk.
Evaluation of a model for induction of periodontal disease in dogs
Directory of Open Access Journals (Sweden)
Rodrigo V. Sepúlveda
2014-06-01
Full Text Available There are several methods for inducing periodontal disease in animal models, being the bone defect one of the most reported. This study aimed to evaluate this model, through clinical, radiographic, tomographic and histological analyzes, thus providing standardized data for future regenerative works. Twelve dogs were subjected to the induction protocol. In a first surgical procedure, a mucoperiosteal flap was made on the buccal aspect of the right third and fourth premolars and a defect was produced exposing the furcation and mesial and distal roots, with dimensions: 5mm coronoapical, 5mm mesiodistal, and 3mm buccolingual. Periodontal ligament and cementum were curetted and the defect was filled with molding polyester, which was removed after 21 days on new surgical procedure. Clinical and radiographic examinations were performed after the two surgeries and before the collection of parts for dental tomography and histological analysis. All animals showed grade II furcation exposure in both teeth. Clinical attachment level increased after induction. Defect size did not change for coronoapical and buccolingual measurements, while mesiodistal size was significantly higher than at the time of defect production. Radiographic analysis showed decreased radiopacity and discontinuity of lamina dura in every tooth in the furcation area. The horizontal progression of the disease was evident in micro-computed tomography and defect content in the histological analysis. Therefore, it is concluded that this method promotes the induction of periodontal disease in dogs in a standardized way, thus being a good model for future work.
Energy Technology Data Exchange (ETDEWEB)
Kushner, M.J.; Collison, W.Z.; Grapperhaus, M.J. [Univ. of Illinois, Urbana, IL (United States). Dept. of Electrical and Computer Engineering
1996-12-31
Inductively Coupled Plasma (ICP) reactors are being developed as high plasma density, low gas pressure sources for etching and deposition of semiconductor materials. In this paper, the authors describe a 3-dimensional, time dependent model for ICP reactors whose intent is to provide an infrastructure to investigate asymmetries in plasma etching and deposition tools. The model is a 3-dimensional extension of a previously described 2-dimensional simulation called the Hybrid Plasma Equipment Model (HPEM). HPEM-3D consists of an electromagnetics module (EMM), a Boltzmann-electron energy module (BEM) and a fluid-chemical kinetics simulation (FKS). The inductively coupled electromagnetic fields are produced by the EMM. Results from HPEM-3D will be discussed for reactors using etching (Cl{sub 2}, BCl{sub 3}) and non-etching (Ar, Ar/N{sub 2}) gas mixtures, and which have geometrical asymmetries such as wafer clamps and load-lock bays. The authors show how details in the design of the coil, such as the value of the termination capacitance or number of turns, lead to azimuthal variations in the inductive electric field.
Institute of Scientific and Technical Information of China (English)
CHEN Shu-yong; CHEN Quan-shi; SUN Feng-chun
2007-01-01
The principle of rotor flux-orientation vector control on 100/150 kW three-phase AC induction motor for electric drive tracked vehicles is analyzed, and the mathematic model is deduced. The drive system of induction motor is modeled and simulated by Matlab/Simulink. The characteristics of motor and drive system are analyzed and evaluated by practical bench test. The simulation and bench test results show that the model is valid, and the driving control system has constant torque under rated speed, constant torque above rated speed, widely variable speed range and better dynamic characteristics. In order to evaluate the practical applications of high power induction motor driving system in electric drive tracked vehicles, a collaborative simulation based on interface technology of Matlab/Simulink and multi-body dynamic analysis software known as RecurDyn is done, the vehicle performances are predicted in the acceleration time (0-32 km/h) and turning characteristic (v=10 km/h, R=B).
Modeling of Spatial and Temporal Variations of Phosphorous Cycling in Tree Islands of the Everglades
Lago, M.; Miralles-Wilhelm, F. R.
2008-05-01
A model to study the temporal and spatial variations on the phosphorous cycle around tree islands in Shark River Slough in the Everglades has been developed. It is based in a conceptual model that considers the convective and diffusive transport of dissolved phosphorous, adsorption on to soil, input from rainfall and animal activity, and the phosphorous cycle in biomass that includes uptake, release as litter, transport as suspended litter and release from the decomposition of the deposited litter. The developed model solved governing equations for water, phosphorous and biomass balances. The parameterization of the model was conducted by using the data collected in three tree islands of Shark River Slough, the time series data downloaded mainly from SFWMD's DBHYDRO, among other parameters reported the literature. The model was calibrated in three stages. Initially, Manning coefficients were adjusted from surface water velocity data. Then, calibration of several groundwater flow parameters was performed from water table data collected at wells by. Finally, the phosphorous input rate from animal activity and the initial concentration of phosphorous were calibrated. This study concluded that an external input rate of Phosphorous (e.g. from animal activity) is necessary to maintain the phosphorous levels in the areas around the head of the tree islands, to counteract losses from rainfall driven transport and suspended litter transport. This result points to the importance of the preservation of the wading birds and other wild life forms in the Everglades. The model also suggests an explanation for the sawgrass die-off events observed in the Everglades as well as a cyclic succession between marsh and tall sawgrass.
Photoperiodic growth control in perennial trees.
Azeez, Abdul; Sane, Aniruddha P
2015-01-01
Plants have to cope with changing seasons and adverse environmental conditions. Being sessile, plants have developed elaborate mechanisms for their survival that allow them to sense and adapt to the environment and reproduce successfully. A major adaptive trait for the survival of trees of temperate and boreal forests is the induction of growth cessation in anticipation of winters. In the last few years enormous progress has been made to elucidate the molecular mechanisms underlying SDs induced growth cessation in model perennial tree hybrid aspen (Populus tremula × P. tremuloides). In this review we discuss the molecular mechanism underlying photoperiodic control of growth cessation and adaptive responses.
Inductive Pulsed Plasma Thruster Model with Time-Evolution of Energy and State Properties
Polzin, Kurt A.; Sankaran, Kamesh
2012-01-01
A model for pulsed inductive plasma acceleration is presented that consists of a set of circuit equations coupled to both a one-dimensional equation of motion and an equation governing the partitioning of energy. The latter two equations are obtained for the plasma current sheet by treating it as a single element of finite volume and integrating the governing equations over that volume. The integrated terms are replaced where necessary by physically-equivalent quantities that are calculated through the solution of other parts of the governing equation set. The model improves upon previous one-dimensional performance models by permitting the time-evolution of the energy and state properties of the plasma, the latter allowing for the tailoring of the model to different gases that may be chosen as propellants. The time evolution of the various energy modes in the system and the associated plasma properties, calculated for argon propellant, are presented to demonstrate the efficacy of the model. The model produces a result where efficiency is maximized at a given value of the electrodynamic scaling term known as the dynamic impedance parameter. Qualitatively and quantitatively, the model compares favorably with performance measured for two separate inductive pulsed plasma thrusters, with disagreements attributable to simplifying assumptions employed in the generation of the model solution.
Recursion relations for tree-level amplitudes in the SU(N) nonlinear sigma model
Kampf, Karol; Novotný, Jiří; Trnka, Jaroslav
2013-04-01
It is well-known that the standard Britto-Cachazo-Feng-Witten construction cannot be used for on-shell amplitudes in effective field theories due to bad behavior for large shifts. We show how to solve this problem in the case of the SU(N) nonlinear sigma model, i.e., nonrenormalizable model with an infinite number of interaction vertices, using scaling properties of the semi-on-shell currents, and we present new on-shell recursion relations for all on-shell tree-level amplitudes in this theory.
Tree-level metastability bounds for the most general two Higgs doublet model
Ivanov, I P
2015-01-01
Within two Higgs doublet models, it is possible that the current vacuum is not the global minimum, in which case it could possibly decay at a later stage. We discuss the tree-level conditions which must be obeyed by the most general scalar potential in order to preclude that possibility. We propose a new procedure which is not only more general but also easier to implement than the previously published one, including CP conserving as well as CP violating scalar sectors. We illustrate these conditions within the context of the Z2 model, softly broken by a complex, CP violating parameter.
A New Method of Chinese Address Extraction Based on Address Tree Model
Directory of Open Access Journals (Sweden)
KANG Mengjun
2015-01-01
Full Text Available Address is a spatial location encoding method of individual geographical area. In China, address planning is relatively backward due to the rapid development of the city, resulting in the presence of large number of non-standard address. The space constrain relationship of standard address model is analyzed in this paper and a new method of standard address extraction based on the tree model is proposed, which regards topological relationship as consistent criteria of space constraints. With this method, standard address can be extracted and errors can be excluded from non-standard address. Results indicate that higher math rate can be obtained with this method.
Directory of Open Access Journals (Sweden)
Petras Rupšys
2015-01-01
Full Text Available A stochastic modeling approach based on the Bertalanffy law gained interest due to its ability to produce more accurate results than the deterministic approaches. We examine tree crown width dynamic with the Bertalanffy type stochastic differential equation (SDE and mixed-effects parameters. In this study, we demonstrate how this simple model can be used to calculate predictions of crown width. We propose a parameter estimation method and computational guidelines. The primary goal of the study was to estimate the parameters by considering discrete sampling of the diameter at breast height and crown width and by using maximum likelihood procedure. Performance statistics for the crown width equation include statistical indexes and analysis of residuals. We use data provided by the Lithuanian National Forest Inventory from Scots pine trees to illustrate issues of our modeling technique. Comparison of the predicted crown width values of mixed-effects parameters model with those obtained using fixed-effects parameters model demonstrates the predictive power of the stochastic differential equations model with mixed-effects parameters. All results were implemented in a symbolic algebra system MAPLE.
Trimming a hazard logic tree with a new model-order-reduction technique
Porter, Keith; Field, Ned; Milner, Kevin R
2017-01-01
The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.
Fast Tree Search for A Triangular Lattice Model of Protein Folding
Institute of Scientific and Technical Information of China (English)
Xiaomei Li; Nengchao Wang
2004-01-01
Using a triangular lattice model to study the designability of protein folding, we overcame the parity problem of previous cubic lattice model and enumerated all the sequences and compact structures on a simple two-dimensional triangular lattice model of size 4+5+6+5+4. We used two types of amino acids, hydrophobic and polar, to make up the sequences, and achieved 223+212 different sequences excluding the reverse symmetry sequences. The total string number of distinct compact structures was 219,093, excluding reflection symmetry in the self-avoiding path of length 24 triangular lattice model. Based on this model, we applied a fast search algorithm by constructing a cluster tree. The algorithm decreased the computation by computing the objective energy of non-leaf nodes. The parallel experiments proved that the fast tree search algorithm yielded an exponential speed-up in the model of size 4+5+6+5+4. Designability analysis was performed to understand the search result.
Making Tree Ensembles Interpretable
Hara, Satoshi; Hayashi, Kohei
2016-01-01
Tree ensembles, such as random forest and boosted trees, are renowned for their high prediction performance, whereas their interpretability is critically limited. In this paper, we propose a post processing method that improves the model interpretability of tree ensembles. After learning a complex tree ensembles in a standard way, we approximate it by a simpler model that is interpretable for human. To obtain the simpler model, we derive the EM algorithm minimizing the KL divergence from the ...
Friedland, Werner; Kundrat, Pavel; Schmitt, Elke
2016-07-01
Detailed understanding of the enhanced relative biological effectiveness (RBE) of ions, in particular at high linear energy transfer (LET) values, is needed to fully explore the radiation risk of manned space missions. It is generally accepted that the enhanced RBE of high-LET particles results from the DNA lesion patterns, in particular DNA double-strand breaks (DSB), due to the spatial clustering of energy deposits around their trajectories. In conventional experiments on biological effects of radiation types of diverse quality, however, clustering of energy deposition events on nanometer scale that is relevant for the induction and local complexity of DSB is inherently interlinked with regional (sub-)micrometer-scale DSB clustering along the particle tracks. Due to this limitation, the role of both (nano- and micrometer) scales on the induction of diverse biological endpoints cannot be frankly separated. To address this issue in a unique way, experiments at the ion microbeam SNAKE [1] and corresponding track-structure based model calculations of DSB induction and subsequent repair with the biophysical code PARTRAC [2] have been performed. In the experiments, hybrid human-hamster A_{L} cells were irradiated with 20 MeV (2.6 keV/μm) protons, 45 MeV (60 keV/μm) lithium ions or 55 MeV (310 keV/μm) carbon ions. The ions were either quasi-homogeneously distributed or focused to 0.5 x 1 μm^{2} spots on regular matrix patterns of 5.4 μm, 7.6 μm and 10.6 μm grid size, with pre-defined particle numbers per spot so as to deposit a mean dose of 1.7 Gy for all irradiation patterns. As expected, the induction of dicentrics by homogeneous irradiation increased with LET: lithium and carbon ions induced about two- and four-fold higher yields of dicentrics than protons. The induction of dicentrics is, however, affected by µm-scale, too: focusing 20 lithium ions or 451 protons per spot on a 10.6 μm grid induced two or three times more dicentrics, respectively, than a
Texture Segmentation Using Laplace Distribution-Based Wavelet-Domain Hidden Markov Tree Models
Directory of Open Access Journals (Sweden)
Yulong Qiao
2016-11-01
Full Text Available Multiresolution models such as the wavelet-domain hidden Markov tree (HMT model provide a powerful approach for image modeling and processing because it captures the key features of the wavelet coefficients of real-world data. It is observed that the Laplace distribution is peakier in the center and has heavier tails compared with the Gaussian distribution. Thus we propose a new HMT model based on the two-state, zero-mean Laplace mixture model (LMM, the LMM-HMT, which provides significantly potential for characterizing real-world textures. By using the HMT segmentation framework, we develop LMM-HMT based segmentation methods for image textures and dynamic textures. The experimental results demonstrate the effectiveness of the introduced model and segmentation methods.
Algorithm for Tree Growth Modeling Based on Random Parameters and ARMA
Directory of Open Access Journals (Sweden)
Lichun Jiang
2013-08-01
Full Text Available Chapman-Richards function is used to model growth data of dahurian larch (Larix gmelinii Rupr. from longitudinal measurements using nonlinear mixed-effects modeling approach. The parameter variation in the model was divided into random effects, fixed effects and variance-covariance structure. The values for fixed effects parameters and the variance-covariance matrix of random effects were estimated using NLME function in S-plus software. Autocorrelation structure was considered for explaining the dependency among multiple measurements within the individuals. Information criterion statistics (AIC, BIC and Likelihood ratio test are used for comparing different structures of the random effects components. These methods are illustrated using the nonlinear mixed-effects methods in S-Plus software. Results showed that the Chapman-Richards model with three random parameters could typically depict the dahurian larch tree growth in northeastern China. The mixed-effects model provided better performance and more precise estimations than the fixed-effects model.
Van Looy, Kris; Piffady, Jérémy
2017-11-01
Floodplain landscapes are highly fragmented by river regulation resulting in habitat degradation and flood regime perturbation, posing risks to population persistence. Climate change is expected to pose supplementary risks in this context of fragmented landscapes, and especially for river systems adaptation management programs are developed. The association of habitat quality and quantity with the landscape dynamics and resilience to human-induced disturbances is still poorly understood in the context of species survival and colonization processes, but essential to prioritize conservation and restoration actions. We present a modelling approach that elucidates network connectivity and landscape dynamics in spatial and temporal context to identify vital corridors and conservation priorities in the Loire river and its tributaries. Alteration of flooding and flow regimes is believed to be critical to population dynamics in river ecosystems. Still, little is known of critical levels of alteration both spatially and temporally. We applied metapopulation modelling approaches for a dispersal-limited tree species, white elm; and a recruitment-limited tree species, black poplar. In different model steps the connectivity and natural dynamics of the river landscape are confronted with physical alterations (dams/dykes) to species survival and then future scenarios for climatic changes and potential adaptation measures are entered in the model and translated in population persistence over the river basin. For the two tree species we highlighted crucial network zones in relation to habitat quality and connectivity. Where the human impact model already shows currently restricted metapopulation development, climate change is projected to aggravate this persistence perspective substantially. For both species a significant drawback to the basin population is observed, with 1/3 for elm and ¼ for poplar after 25 years already. But proposed adaptation measures prove effective to even
A thermal network model for induction motors of hermetic reciprocating compressors
Dutra, T.; Deschamps, C. J.
2015-08-01
This paper describes a simulation model for small reciprocating compressors with emphasis on the electrical motor modelling. Heat transfer is solved through algebraic equations derived from lumped thermal energy balances applied to the compressor components. Thermal conductances between the motor components are characterized via a thermal network model. The single-phase induction motor is modelled via an equivalent circuit, allowing predictions for the motor performance and distributed losses. The predicted temperature distribution is used to evaluate the stator and rotor windings resistances. The thermal and electric models are solved in a coupled manner with a model for the compression cycle. Predictions of temperature distribution, motor efficiency, as well as isentropic and volumetric efficiencies, are compared with experimental data at different operating conditions. The model is then applied to analyse the motor temperature as a function of input voltage and stator wire diameter.
Directory of Open Access Journals (Sweden)
Huajie Duan
2016-01-01
Full Text Available Groundwater plays an important role in global climate change and satisfying human needs. In the study, RS (remote sensing and GIS (geographic information system were utilized to generate five thematic layers, lithology, lineament density, topology, slope, and river density considered as factors influencing the groundwater potential. Then, the multicriteria decision model (MCDM was integrated with C5.0 and CART, respectively, to generate the decision tree with 80 surveyed tube wells divided into four classes on the basis of the yield. To test the precision of the decision tree algorithms, the 10-fold cross validation and kappa coefficient were adopted and the average kappa coefficient for C5.0 and CART was 90.45% and 85.09%, respectively. After applying the decision tree to the whole study area, four classes of groundwater potential zones were demarcated. According to the classification result, the four grades of groundwater potential zones, “very good,” “good,” “moderate,” and “poor,” occupy 4.61%, 8.58%, 26.59%, and 60.23%, respectively, with C5.0 algorithm, while occupying the percentages of 4.68%, 10.09%, 26.10%, and 59.13%, respectively, with CART algorithm. Therefore, we can draw the conclusion that C5.0 algorithm is more appropriate than CART for the groundwater potential zone prediction.
Directory of Open Access Journals (Sweden)
Steven S. W. Lee
2015-01-01
Full Text Available We propose a multitree based fast failover scheme for Ethernet networks. In our system, only few spanning trees are used to carry working traffic in the normal state. As a failure happens, the nodes adjacent to the failure redirect traffic to the preplanned backup VLAN trees to realize fast failure recovery. In the proposed scheme, a new leaf constraint is enforced on the backup trees. It enables the network being able to provide 100% survivability against any single link and any single node failure. Besides fast failover, we also take load balancing into consideration. We model an Ethernet network as a twolayered graph and propose an Integer Linear Programming (ILP formulation for the problem. We further propose a heuristic algorithm to provide solutions to large networks. The simulation results show that the proposed scheme can achieve high survivability while maintaining load balancing at the same time. In addition, we have implemented the proposed scheme in an FPGA system. The experimental results show that it takes only few μsec to recover a network failure. This is far beyond the 50 msec requirement used in telecommunication networks for network protection.
Modelling of Peach Tree (Prunus persica) Full Blooming Dates Using APCC MME Seasonal Forecasts
Chun, Jong; Kim, Sung; Lee, Hyojin; Han, Hyun-Hee; Son, In-Chang; Cho, Kyung Hwa
2016-04-01
Due to global warming, recently, bud-burst and flowering dates of fruit crops have become earlier and the abnormal climate increases the variabilities of temperature in spring, suggesting that the risk of frost damage has increased. However, the full blooming date prediction model for peach tree used by the Rural Developmental Administration (RDA) were developed using only one cultivar (Youmyeong) and observations from a station (Suwon). This model might not adequately reflect the characteristics of peach cultivars or local orchards. the objectives of this study were to develops the site-and cultivar-specific blooming date prediction models for major peach cultivation regions and cultivars and presents a framework for applications of the APEC Climate Center Multimodel Ensemble (APCC MME) seasonal datasets.Developmental rate (DVR), and Sequential dormancy models (Chill day, New chill day, and fraction-time models) were used to develop the locally tailored full blooming date prediction models for major peach cultivars. For the development of these models, bud-burst and full blooming dates of peach tree for 5 cultivars (Cheonhong, Youmyeong, Changbangjosaeng, Cheonjoongdo, and Janghowon) were collected from the 6 major peach cultivation sites: Chuncheon, Suwon, Cheongwon, Cheongdo, Naju, and Jinju. For the chill day model, those measures for the entire dataset regardless the location and cultivar were 2.31%, 0.79, and 3.36 day for MAPE, R2, RMSE, respectively. For the new chill day model, those values (2.19%, 0.82, and 3.16 day for MAPE, R2, RMSE, respectively) were slightly better than those of the chill day model. The model results showed that the new chill day model was found slightly highest performance than others. Based on the considerations of the predictability of the statistical downscaling method and the observed periods of the full blooming dates at each site, we determined that the APCC MME seasonal datasets were applied for the new chill day model for the
Induction policy and missed post-term pregnancies: a mathematical model.
Mongelli, M; Wong, Y C; Venkat, A; Chua, T M
2001-02-01
The aim of this study was to compare the clinical performance of ultrasound dates and ultrasound dates combined with menstrual dates for the detection of post-maturity. A computer model was designed which uses the statistical distributions of the duration of normal pregnancy, day of ovulation in relation to the menstrual cycle and ultrasound error for estimating gestational age. The clinical performance of the different dating methods was then analysed from these variables, on simulations of 30,000 cases. The efficacy of different dating methods for detecting post-maturity was determined by generating receiver-operator characteristics (ROC) curves. The proportion of post-term pregnancies (294 days and over) predicted by the model (3.5%) agrees with published values. There is a steep rise in missed cases if induction is delayed beyond 10 days from the expected date of delivery, reaching 20% on day 294. Elective delivery on day 290 will detect 98.9% of cases destined to deliver post-term, with an induction rate of 10%; the respective figures for induction on day 294 are 79% and 3.8%. The ROC curves for the detection of post-maturity suggest that use of the mid-trimester biparietal diameter (BPD) is better than a 7-day or 10-day rule. Timing of elective delivery is the most important variable affecting the detection rate for post-maturity There is no advantage in using menstrual dates when ultrasound biometry is available.
Gao, Jie; Xu, Chenhao; Xiao, Jiaqi
2013-10-01
Multi-component induction logging provides great assistance in the exploration of thinly laminated reservoirs. The 1D parametric inversion following an adaptive borehole correction is the key step in the data processing of multi-component induction logging responses. To make the inversion process reasonably fast, an efficient forward modelling method is necessary. In this paper, a modelling method has been developed to simulate the multi-component induction tools in deviated wells drilled in layered anisotropic formations. With the introduction of generalized reflection coefficients, the analytic expressions of magnetic field in the form of a Sommerfeld integral were derived. The fast numerical computation of the integral has been completed by using the fast Fourier-Hankel transform and fast Hankel transform methods. The latter is so time efficient that it is competent enough for real-time multi-parameter inversion. In this paper, some simulated results have been presented and they are in excellent agreement with the finite difference method code's solution.
Directory of Open Access Journals (Sweden)
Aaron Smith
2014-12-01
Full Text Available The accurate characterization of three-dimensional (3D root architecture, volume, and biomass is important for a wide variety of applications in forest ecology and to better understand tree and soil stability. Technological advancements have led to increasingly more digitized and automated procedures, which have been used to more accurately and quickly describe the 3D structure of root systems. Terrestrial laser scanners (TLS have successfully been used to describe aboveground structures of individual trees and stand structure, but have only recently been applied to the 3D characterization of whole root systems. In this study, 13 recently harvested Norway spruce root systems were mechanically pulled from the soil, cleaned, and their volumes were measured by displacement. The root systems were suspended, scanned with TLS from three different angles, and the root surfaces from the co-registered point clouds were modeled with the 3D Quantitative Structure Model to determine root architecture and volume. The modeling procedure facilitated the rapid derivation of root volume, diameters, break point diameters, linear root length, cumulative percentages, and root fraction counts. The modeled root systems underestimated root system volume by 4.4%. The modeling procedure is widely applicable and easily adapted to derive other important topological and volumetric root variables.
Directory of Open Access Journals (Sweden)
M. Saki
2013-03-01
Full Text Available The relationship between plant species and environmental factors has always been a central issue in plant ecology. With rising power of statistical techniques, geo-statistics and geographic information systems (GIS, the development of predictive habitat distribution models of organisms has rapidly increased in ecology. This study aimed to evaluate the ability of Logistic Regression Tree model to create potential habitat map of Astragalus verus. This species produces Tragacanth and has economic value. A stratified- random sampling was applied to 100 sites (50 presence- 50 absence of given species, and produced environmental and edaphic factors maps by using Kriging and Inverse Distance Weighting methods in the ArcGIS software for the whole study area. Relationships between species occurrence and environmental factors were determined by Logistic Regression Tree model and extended to the whole study area. The results indicated species occurrence has strong correlation with environmental factors such as mean daily temperature and clay, EC and organic carbon content of the soil. Species occurrence showed direct relationship with mean daily temperature and clay and organic carbon, and inverse relationship with EC. Model accuracy was evaluated both by Cohen’s kappa statistics (κ and by area under Receiver Operating Characteristics curve based on independent test data set. Their values (kappa=0.9, Auc of ROC=0.96 indicated the high power of LRT to create potential habitat map on local scales. This model, therefore, can be applied to recognize potential sites for rangeland reclamation projects.
Modeling and Simulating of Single Side Short Stator Linear Induction Motor with the End Effect
Hamzehbahmani, Hamed
2011-09-01
Linear induction motors are under development for a variety of demanding applications including high speed ground transportation and specific industrial applications. These applications require machines that can produce large forces, operate at high speeds, and can be controlled precisely to meet performance requirements. The design and implementation of these systems require fast and accurate techniques for performing system simulation and control system design. In this paper, a mathematical model for a single side short stator linear induction motor with a consideration of the end effects is presented; and to study the dynamic performance of this linear motor, MATLAB/SIMULINK based simulations are carried out, and finally, the experimental results are compared to simulation results.
Spatial modeling of the carbon stock of forest trees in Heilongjiang Province, China
Institute of Scientific and Technical Information of China (English)
Chang Liu; Lianjun Zhang; Fengri Li; Xingji Jin
2014-01-01
Heilongjiang province is the largest forest zone in China and the forest coverage rate is 46%. Forests of Heilongjiang province play an important role in the forest ecosystem of China. In this study we investi-gated the spatial distribution of forest carbon storage in Heilongjiang province using 3083 plots sampled in 2010. We attempted to fit two global models, ordinary least squares model (OLS) , linear mixed model (LMM), and a local model, geographically weighted regression model (GWR), to the relationship between forest carbon content and stand, environment, and climate factors. Five predictors significantly affected forest carbon storage and spatial distribution, viz. average diameter of stand (DBH), number of trees per hectare (TPH), elevation (Elev), slope (Slope) and the product of precipitation and temperature (Rain_Temp). The GWR model outperformed the two global models in both model fitting and prediction because it successfully reduced both spatial auto-correlation and heterogeneity in model residuals. More importantly, the GWR model provided localized model coefficients for each location in the study area, which allowed us to evaluate the influences of local stand conditions and topographic features on tree and stand growth, and forest carbon stock. It also helped us to better understand the impacts of silvi-cultural and management activities on the amount and changes of forest carbon storage across the province. The detailed information can be readily incorporated with the mapping ability of GIS software to provide excellent tools for assessing the distribution and dynamics of the for-est-carbon stock in the next few years.
Wang, Feng; Kang, Mengzhen; Lu, Qi; Letort, Véronique; Han, Hui; Guo, Yan; de Reffye, Philippe; Li, Baoguo
2011-04-01
Mongolian Scots pine (Pinus sylvestris var. mongolica) is one of the principal species used for windbreak and sand stabilization in arid and semi-arid areas in northern China. A model-assisted analysis of its canopy architectural development and functions is valuable for better understanding its behaviour and roles in fragile ecosystems. However, due to the intrinsic complexity and variability of trees, the parametric identification of such models is currently a major obstacle to their evaluation and their validation with respect to real data. The aim of this paper was to present the mathematical framework of a stochastic functional-structural model (GL2) and its parameterization for Mongolian Scots pines, taking into account inter-plant variability in terms of topological development and biomass partitioning. In GL2, plant organogenesis is determined by the realization of random variables representing the behaviour of axillary or apical buds. The associated probabilities are calibrated for Mongolian Scots pines using experimental data including means and variances of the numbers of organs per plant in each order-based class. The functional part of the model relies on the principles of source-sink regulation and is parameterized by direct observations of living trees and the inversion method using measured data for organ mass and dimensions. The final calibration accuracy satisfies both organogenetic and morphogenetic processes. Our hypothesis for the number of organs following a binomial distribution is found to be consistent with the real data. Based on the calibrated parameters, stochastic simulations of the growth of Mongolian Scots pines in plantations are generated by the Monte Carlo method, allowing analysis of the inter-individual variability of the number of organs and biomass partitioning. Three-dimensional (3D) architectures of young Mongolian Scots pines were simulated for 4-, 6- and 8-year-old trees. This work provides a new method for characterizing
Numerical modeling and design of a disk-type rotating permanent magnet induction pump
Energy Technology Data Exchange (ETDEWEB)
Koroteeva, E., E-mail: koroteeva@physics.msu.ru [Institute of Physics of University of Latvia, Salaspils 2169 (Latvia); Lomonosov Moscow State University, Moscow 119991 (Russian Federation); Ščepanskis, M. [Laboratory for Mathematical Modelling of Environmental and Technological Processes, University of Latvia, Rīga 1002 (Latvia); Bucenieks, I.; Platacis, E. [Institute of Physics of University of Latvia, Salaspils 2169 (Latvia)
2016-05-15
Highlights: • The design and performance of a disk-type induction pump are described. • A 3D numerical model based on an iterative coupling between EM and hydrodynamic solvers is developed. • The model is verified by comparing with the experiments in a Pb-Bi loop facility. • The suggestions are given to estimate the pump performance in a Pb-Li loop at high pressures. - Abstract: Electromagnetic induction pumps with rotating permanent magnets appear to be the most promising devices to transport liquid metals in high-temperature applications. Here we present a numerical methodology to simulate the operation of one particular modification of these types of pumps: a disk-type induction pump. The numerical model allows for the calculation and analysis of the flow parameters, including the pressure–flow rate characteristics of the pump. The simulations are based on an iterative fully coupled scheme for electromagnetic and hydrodynamic solvers. The developed model is verified by comparing with experimental data obtained using a Pb-Bi loop test facility, for pressures up to 4 bar and flow rates up to 9 kg/s. The verified model is then expanded to higher pressures, beyond the limits of the experimental loop. Based on the numerical simulations, suggestions are given to extrapolate experimental data to higher (industrially important) pressure ranges. Using the numerical model and analytical estimation, the pump performance for the Pb-Li loop is also examined, and the ability of the designed pump to develop pressure heads over 6 bar and to provide flow rates over 15 kg/s is shown.
Hammecker, Claude; Seltacho, Siwaporn; Suvanang, Nopmanee; Do, Frederic; Angulo-Jaramillo, Rafael
2015-04-01
Northeast of Thailand, is a plateau at 200 m AMSL with a typical undulating landscape. Traditionally the lowlands were dedicated to paddy fields and the uplands covered by Dipterocarpus forest. However development of cash crops during the last decades has led to intensive land clearing in the uplands and to modifications at a regional scale of the water balance in the critical zone with increasing runoff and soil erosion. Recent international demand increase for natural rubber motivated many local farmers to shift from these cash crops towards rubber-tree (Heva Brasiliensis) plantations. However these land use changes have been undertaken without considering the climatic and edaphic specificity of the region, which are not well adapted to the growth of rubber tree (rainfall lower than recommended and sandy soils with low fertility). Therefore, in order to assess and try to predict the environmental consequences (water resources, water-table, ..) of the development of rubber tree plantations in this area, a small watershed in the region ok Khon Kaen has been selected to follow the infiltration and to monitor the different components of the water balance along a toposequence. A six years monitoring of the main components of water balance along a toposequence associated to numerical simulation were used to quantify and try to forecast the evolution of the water use and water resources. Unsaturated soil properties were determined at different depths, in various positions along the toposequence. Experimental results supported by modeling of 2D water flow with HYDRUS3D show clearly that infiltration is blocked by a clayey layer on top of the bedrock and conditioned the occurrence of a perched watertable during the rainy seasons. Most of the soil water flow was found to be directed laterally during the rainy season. The deep groundwater was found to be fed from the lower part of toposequence in the thalweg. The transpiration rate measured on the trees at this stage of
Sachdeva, Neha; Kumar, G Dinesh; Gupta, Ravi Prakash; Mathur, Anshu Shankar; Manikandan, B; Basu, Biswajit; Tuli, Deepak Kumar
2016-10-01
The aim of the present work was to develop a mathematical model to describe the biomass and (total) lipid productivity of Chlorella pyrenoidosa NCIM 2738 under heterotrophic conditions. Biomass growth rate was predicted by Droop's cell quota model, while changes observed in cell quota (utilization) under carbon excess conditions were used for the modeling and predicting the lipid accumulation rate. The model was simulated under non-limiting (excess) carbon and limiting nitrate concentration and validated with experimental data for the culture grown in batch (flask) mode under different nitrate concentrations. The present model incorporated two modes (growth and stressed) for the prediction of endogenous lipid synthesis/induction and aimed to predict the effect and response of the microalgae under nutrient starvation (stressed) conditions. MATLAB and Genetic Algorithm were employed for the prediction and validation of the model parameters.
Engelfriet, Joost; Vogler, Heiko
1985-01-01
Macro tree transducers are a combination of top-down tree transducers and macro grammars. They serve as a model for syntax-directed semantics in which context information can be handled. In this paper the formal model of macro tree transducers is studied by investigating typical automata theoretical
Engelfriet, Joost; Vogler, Heiko
1985-01-01
Macro tree transducers are a combination of top-down tree transducers and macro grammars. They serve as a model for syntax-directed semantics in which context information can be handled. In this paper the formal model of macro tree transducers is studied by investigating typical automata theoretical
Mathematical modeling of intrinsic Josephson junctions with capacitive and inductive couplings
Rahmonov, I. R.; Shukrinov, Yu M.; Zemlyanaya, E. V.; Sarhadov, I.; Andreeva, O.
2012-11-01
We investigate the current voltage characteristics (CVC) of intrinsic Josephson junctions (IJJ) with two types of couplings between junctions: capacitive and inductive. The IJJ model is described by a system of coupled sine-Gordon equations which is solved numerically by the 4th order Runge-Kutta method. The method of numerical simulation and numerical results are presented. The magnetic field distribution is calculated as the function of coordinate and time at different values of the bias current. The influence of model parameters on the CVC is studied. The behavior of the IJJ in dependence on coupling parameters is discussed.
Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems
DEFF Research Database (Denmark)
Becker, Bernd; Behle, Markus; Eisenbrand, Fritz
2004-01-01
We present a concept to signicantly advance the state of the art for bounded model checking (BMC) and inductive verication (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from dierent domains, like hybrid systems modeling and digital circuit...... verication, bounded plan- ning and heuristic search, combinatorial optimization and integer programming. Af- ter sketching the overall verication ow we present rst results indicating that the combination and tight integration of dierent verication engines is a rst step to pave the way to fully automated BMC...
Modeling and Compensation of Thermal Effects on an Ironless Inductive Position Sensor
Danisi, Alessandro; Losito, Roberto; Perriard, Yves
2014-01-01
The ironless inductive position sensor can be the ideal candidate for linear position sensing in harsh environment and in the presence of external magnetic fields. Starting from the validated electromagnetic characteristics, this paper presents a model of thermal effects influencing the sensor's position reading and an effective algorithm to compensate them. The compensation is performed without affecting the nominal sensor's functioning and without using additional temperature probes, which would complicate the sensor's assembly. The model constitutes the basis of this algorithm, which is then validated through experimental measurements on a custom ironless position sensor prototype.
Directory of Open Access Journals (Sweden)
Bin Mao
2015-06-01
Full Text Available The relationship between scenic beauty grade and measured tree indicators was studied through evaluation of 427 photos of individual Pinus tabulaeformis trees by using the scenic beauty estimation (SBE method. Thirteen indices to reflect trunk, crown and stem-to-canopy ratios of individual trees were evaluated by invited students. Results showed that students preferred large diameters at breast height, full canopies and straight stems or some trees with minor crook stems. Tree height had a minor contribution to individual tree quality. Correlation analysis and factor analysis were employed to select indices and to integrate them into a comprehensive index. The stepwise method of nonlinear model incorporation of four comprehensive indices—tree crown form, stem-crown coordination, tree growth and stem for—were proven valuable in order to evaluate the scenic beauty of individual trees.
Predictive model for risk of cesarean section in pregnant women after induction of labor.
Hernández-Martínez, Antonio; Pascual-Pedreño, Ana I; Baño-Garnés, Ana B; Melero-Jiménez, María R; Tenías-Burillo, José M; Molina-Alarcón, Milagros
2016-03-01
To develop a predictive model for risk of cesarean section in pregnant women after induction of labor. A retrospective cohort study was conducted of 861 induced labors during 2009, 2010, and 2011 at Hospital "La Mancha-Centro" in Alcázar de San Juan, Spain. Multivariate analysis was used with binary logistic regression and areas under the ROC curves to determine predictive ability. Two predictive models were created: model A predicts the outcome at the time the woman is admitted to the hospital (before the decision to of the method of induction); and model B predicts the outcome at the time the woman is definitely admitted to the labor room. The predictive factors in the final model were: maternal height, body mass index, nulliparity, Bishop score, gestational age, macrosomia, gender of fetus, and the gynecologist's overall cesarean section rate. The predictive ability of model A was 0.77 [95% confidence interval (CI) 0.73-0.80] and model B was 0.79 (95% CI 0.76-0.83). The predictive ability for pregnant women with previous cesarean section with model A was 0.79 (95% CI 0.64-0.94) and with model B was 0.80 (95% CI 0.64-0.96). For a probability of estimated cesarean section ≥80%, the models A and B presented a positive likelihood ratio (+LR) for cesarean section of 22 and 20, respectively. Also, for a likelihood of estimated cesarean section ≤10%, the models A and B presented a +LR for vaginal delivery of 13 and 6, respectively. These predictive models have a good discriminative ability, both overall and for all subgroups studied. This tool can be useful in clinical practice, especially for pregnant women with previous cesarean section and diabetes.
Bittner, S.; Priesack, E.
2012-04-01
We apply a functional-structural model of tree water flow to single old-growth trees in a temperate broad-leaved forest stand. Roots, stems and branches are represented by connected porous cylinder elements further divided into the inner heartwood cylinders surrounded by xylem and phloem. Xylem water flow is simulated by applying a non-linear Darcy flow in porous media driven by the water potential gradient according to the cohesion-tension theory. The flow model is based on physiological input parameters such as the hydraulic conductivity, stomatal response to leaf water potential and root water uptake capability and, thus, can reflect the different properties of tree species. The actual root water uptake is calculated using also a non-linear Darcy law based on the gradient between root xylem water potential and rhizosphere soil water potential and by the simulation of soil water flow applying Richards equation. A leaf stomatal conductance model is combined with the hydrological tree and soil water flow model and a spatially explicit three-dimensional canopy light model. The structure of the canopy and the tree architectures are derived by applying an automatic tree skeleton extraction algorithm from point clouds obtained by use of a terrestrial laser scanner allowing an explicit representation of the water flow path in the stem and branches. The high spatial resolution of the root and branch geometry and their connectivity makes the detailed modelling of the water use of single trees possible and allows for the analysis of the interaction between single trees and the influence of the canopy light regime (including different fractions of direct sunlight and diffuse skylight) on the simulated sap flow and transpiration. The model can be applied at various sites and to different tree species, enabling the up-scaling of the water usage of single trees to the total transpiration of mixed stands. Examples are given to reveal differences between diffuse- and ring
Hyyti, Heikki; Visala, Arto
2013-01-01
This paper presents a novel approach to measure tree trunks and to model the ground using a 3D laser scanner. The 3D scanner, self-build using two 2D Sick scanners on a rotating base, measures each scan line approximately at 45° angle towards the ground and the trees. Single scan lines are segmented to find ground and tree returns. 3D point clouds from the surrounding forest are recorded while the measuring vehicle is moving. Sequential scan lines are joined together as the pose changes are r...
Naghibi, Seyed Amir; Pourghasemi, Hamid Reza; Dixon, Barnali
2016-01-01
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.
Yamamoto, Shu; Yamaguchi, Tomonobu; Hirahara, Hideaki; Ara, Takahiro
This paper presents asymmetric circuit models and an inductance parameter measurement method for Permanent Magnet Linear Synchronous Motors (PMLSMs). The reason why the tested PMLSM with surface permanent magnet structure exhibits both asymmetry and salient pole natures is investigated. Asymmetric circuit models considering the saliency and inductance harmonic effects are discussed for PMLSM fed by three-phase three-wire power source systems. All fundamental and harmonic inductance parameters are easily determined by a standstill test using a single-phase commercial source. Experimental and simulation results on a single-sided PMLSM with a 3-phase, 4-pole and 14-slot mover demonstrate the validity of the proposed method.
Directory of Open Access Journals (Sweden)
Felix Morsdorf
2013-10-01
Full Text Available Extracting 3D tree models based on terrestrial laser scanning (TLS point clouds is a challenging task as trees are complex objects. Current TLS devices acquire high-density data that allow a detailed reconstruction of the tree topology. However, in dense forests a fully automatic reconstruction of trees is often limited by occlusion, wind influences and co-registration issues. In this paper, a semi-automatic method for extracting branching and stem structure based on equirectangular projections (range and intensity maps is presented. The digitization of branches and stems is based on 2D maps, which enables simple navigation and raster processing. The modeling is performed for each viewpoint individually instead of using a registered point cloud. Previously reconstructed 2D-skeletons are transformed between the maps. Therefore, wind influences, orientation imperfections of scans and data gaps can be overcome. The method is applied to a TLS dataset acquired in a forest in Germany. In total 34 scans were carried out within a managed forest to measure approximately 90 spruce trees with minimal occlusions. The results demonstrate the feasibility of the presented approach to extract tree models with a high completeness and correctness and provide an excellent input for further modeling applications.
Berdanier, Aaron B; Miniat, Chelcy F; Clark, James S
2016-08-01
Accurately scaling sap flux observations to tree or stand levels requires accounting for variation in sap flux between wood types and by depth into the tree. However, existing models for radial variation in axial sap flux are rarely used because they are difficult to implement, there is uncertainty about their predictive ability and calibration measurements are often unavailable. Here we compare different models with a diverse sap flux data set to test the hypotheses that radial profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in the new settings. We develop a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Puentes, Juan G; Mateo, Soledad; Fonseca, Bruno G; Roberto, Inês C; Sánchez, Sebastián; Moya, Alberto J
2013-12-01
Statistical modeling and optimization of dilute sulfuric acid hydrolysis of olive tree pruning biomass has been performed using response surface methodology. Central composite rotatable design was applied to assess the effect of acid concentration, reaction time and temperature on efficiency and selectivity of hemicellulosic monomeric carbohydrates to d-xylose. Second-order polynomial model was fitted to experimental data to find the optimum reaction conditions by multiple regression analysis. The monomeric d-xylose recovery 85% (as predicted by the model) was achieved under optimized hydrolysis conditions (1.27% acid concentration, 96.5°C and 138 min), confirming the high validity of the developed model. The content of d-glucose (8.3%) and monosaccharide degradation products (0.1% furfural and 0.04% 5-hydroxymethylfurfural) provided a high quality subtract, ready for subsequent biochemical conversion to value-added products.
Fault tree modeling of AAC power source in multi-unit nuclear power plants PSA
Energy Technology Data Exchange (ETDEWEB)
Han, Sang Hoon; Lim, Ho-Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2015-10-15
Dependencies between units are important to estimate a risk of a multi-unit site. One of dependencies is a shared system such as an alternating AC (AAC) power source. Because one AAC can support a single unit, it is necessary to appropriately treat such behavior of the AAC in multi-unit probabilistic safety assessment (PSA). The behavior of AAC in multi-unit site would show dynamic characteristics. For example, several units require the AAC at the same time. It is hard to decide which unit the AAC is connected to. It can vary depending on timing of station blackout (SBO), with time delay when emergency diesel generators fail while running. It is not easy to handle dynamic behavior using the static fault tree methodology. Typical way of estimating risk for multi-unit regarding to AAC is to assume that only one unit has AAC and the others does not. KIM calculates the risk for each unit and uses the average value from the results. Jung derives an equation to calculate the SBO frequency by considering all the combination of loss of offsite power and failure of emergency diesel generators in multi-unit site. It is also assumed that the AAC is connected to a pre-decided unit. We are developing a PSA model for multi-unit site for internal and external events. An extreme external hazard may result in loss of all offsite power in a site, where the appropriate modeling of an AAC becomes important. The static fault tree methodology is not good for dynamic situation. But, it can turn into a simple problem if an assumption is made: - The connecting order of AAC is pre-decided. This study provides an idea how to model AAC for each unit in the form of a fault tree, assuming the connecting order of AAC is given. This study illustrates how to model a fault tree for AAC in a multi-unit site. It provides an idea how to handle a shared system in multi-unit PSA, for such a case as loss of all offsite power in a site due to an extreme external hazard.
Kilbane, J.; Polzin, K. A.
2014-01-01
An annular linear induction pump (ALIP) that could be used for circulating liquid-metal coolant in a fission surface power reactor system is modeled in the present work using the computational COMSOL Multiphysics package. The pump is modeled using a two-dimensional, axisymmetric geometry and solved under conditions similar to those used during experimental pump testing. Real, nonlinear, temperature-dependent material properties can be incorporated into the model for both the electrically-conducting working fluid in the pump (NaK-78) and structural components of the pump. The intricate three-phase coil configuration of the pump is implemented in the model to produce an axially-traveling magnetic wave that is qualitatively similar to the measured magnetic wave. The model qualitatively captures the expected feature of a peak in efficiency as a function of flow rate.
Energy Technology Data Exchange (ETDEWEB)
Radany, E.H.; Pu, A.T. [Univ. of Michigan School of Medicine, Ann Arbor, MI (United States)
1997-10-01
Exposure of mammalian cells to ionizing radiations (IR) produces a plethora of damages in DNA and non-DNA targets. Although DNA double strand breaks (DSB) are thought to be the critical lesion generated by IR with respect to conventional cytotoxicity, it is clear that signaling events regulating cellular responses to IR arise from multiple other lesions in addition to these. The authors are interested in identifying cellular signaling events that derive from DSB specifically, as well as the distal effects (e.g., repair, apoptosis, cell cycle delay) of such signaling. Although electroporation of restriction enzymes might afford an approach to such studies, serious concerns would be raised by the non-uniformity of enzyme transfer and general disruption of the intracellular environment (with the possibility of associated signaling processes) when using this method. The authors have established a radiomimetic model for DSB induction, based upon expression of a hybrid steroid hormone receptor: this system is subject to tight, rapid postranslational regulation of endonuclease activity via addition or withdrawl of the cognate hormone ligand. In preliminary experiments, The authors have demonstrated ligand dose and exposure time-dependent cytotoxicity and DSB induction (the latter assayed by PFGE). Cytogenetic characterization of this system, as well as studies of the interaction between enzyme- and IR-generated DSB are in progress. RNA differential display and subtractive enrichment cloning approaches will ultimately be used to identify genes whose expression changes as a consequence of isolated DSB induction.
Ma, Jianyong; Shugart, Herman H; Yan, Xiaodong; Cao, Cougui; Wu, Shuang; Fang, Jing
2017-02-14
The carbon budget of forest ecosystems, an important component of the terrestrial carbon cycle, needs to be accurately quantified and predicted by ecological models. As a preamble to apply the model to estimate global carbon uptake by forest ecosystems, we used the CO2 flux measurements from 37 forest eddy-covariance sites to examine the individual tree-based FORCCHN model's performance globally. In these initial tests, the FORCCHN model simulated gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) with correlations of 0.72, 0.70 and 0.53, respectively, across all forest biomes. The model underestimated GPP and slightly overestimated ER across most of the eddy-covariance sites. An underestimation of NEP arose primarily from the lower GPP estimates. Model performance was better in capturing both the temporal changes and magnitude of carbon fluxes in deciduous broadleaf forest than in evergreen broadleaf forest, and it performed less well for sites in Mediterranean climate. We then applied the model to estimate the carbon fluxes of forest ecosystems on global scale over 1982-2011. This application of FORCCHN gave a total GPP of 59.41±5.67 and an ER of 57.21±5.32PgCyr(-1) for global forest ecosystems during 1982-2011. The forest ecosystems over this same period contributed a large carbon storage, with total NEP being 2.20±0.64PgCyr(-1). These values are comparable to and reinforce estimates reported in other studies. This analysis highlights individual tree-based model FORCCHN could be used to evaluate carbon fluxes of forest ecosystems on global scale.
Graff, Mario; Poli, Riccardo; Flores, Juan J
2013-01-01
Modeling the behavior of algorithms is the realm of evolutionary algorithm theory. From a practitioner's point of view, theory must provide some guidelines regarding which algorithm/parameters to use in order to solve a particular problem. Unfortunately, most theoretical models of evolutionary algorithms are difficult to apply to realistic situations. However, in recent work (Graff and Poli, 2008, 2010), where we developed a method to practically estimate the performance of evolutionary program-induction algorithms (EPAs), we started addressing this issue. The method was quite general; however, it suffered from some limitations: it required the identification of a set of reference problems, it required hand picking a distance measure in each particular domain, and the resulting models were opaque, typically being linear combinations of 100 features or more. In this paper, we propose a significant improvement of this technique that overcomes the three limitations of our previous method. We achieve this through the use of a novel set of features for assessing problem difficulty for EPAs which are very general, essentially based on the notion of finite difference. To show the capabilities or our technique and to compare it with our previous performance models, we create models for the same two important classes of problems-symbolic regression on rational functions and Boolean function induction-used in our previous work. We model a variety of EPAs. The comparison showed that for the majority of the algorithms and problem classes, the new method produced much simpler and more accurate models than before. To further illustrate the practicality of the technique and its generality (beyond EPAs), we have also used it to predict the performance of both autoregressive models and EPAs on the problem of wind speed forecasting, obtaining simpler and more accurate models that outperform in all cases our previous performance models.
Differential induction of muscle atrophy pathways in two mouse models of spinal muscular atrophy
Deguise, Marc-Olivier; Boyer, Justin G.; McFall, Emily R.; Yazdani, Armin; De Repentigny, Yves; Kothary, Rashmi
2016-01-01
Motor neuron loss and neurogenic atrophy are hallmarks of spinal muscular atrophy (SMA), a leading genetic cause of infant deaths. Previous studies have focused on deciphering disease pathogenesis in motor neurons. However, a systematic evaluation of atrophy pathways in muscles is lacking. Here, we show that these pathways are differentially activated depending on severity of disease in two different SMA model mice. Although proteasomal degradation is induced in skeletal muscle of both models, autophagosomal degradation is present only in Smn2B/− mice but not in the more severe Smn−/−; SMN2 mice. Expression of FoxO transcription factors, which regulate both proteasomal and autophagosomal degradation, is elevated in Smn2B/− muscle. Remarkably, administration of trichostatin A reversed all molecular changes associated with atrophy. Cardiac muscle also exhibits differential induction of atrophy between Smn2B/− and Smn−/−; SMN2 mice, albeit in the opposite direction to that of skeletal muscle. Altogether, our work highlights the importance of cautious analysis of different mouse models of SMA as distinct patterns of atrophy induction are at play depending on disease severity. We also revealed that one of the beneficial impacts of trichostatin A on SMA model mice is via attenuation of muscle atrophy through reduction of FoxO expression to normal levels. PMID:27349908
Functional interpretation and inductive definitions
Avigad, Jeremy
2008-01-01
Extending G\\"odel's \\emph{Dialectica} interpretation, we provide a functional interpretation of classical theories of positive arithmetic inductive definitions, reducing them to theories of finite-type functionals defined using transfinite recursion on well-founded trees.
Far-end Crosstalk Modeling Based on Capacitive and Inductive Unbalances Between Pairs in a Cable
Directory of Open Access Journals (Sweden)
Pavel Lafata
2011-01-01
Full Text Available This article deals with new ways of far-end crosstalk (FEXT modeling in multi-pair and multi-quad metallic cables. Current standard modeling methods provide only rough estimations of FEXT characteristics based on average values of crosstalk for the whole cable. However, for practical implementation of vector discrete multi-tone modulation (VDMT is necessary to predict and simulate FEXT characteristics with sufficient accuracy and simulate FEXT transfer functions individually for each combination of symmetrical pairs in a cable. This article contains a theoretical analysis and description of the problem and suggests a new method for modeling of FEXT crosstalk using capacitive and inductive unbalances between pairs in a cable. This proposed model offers more accurate and realistic results of crosstalk. Theoretical simulations and results are also compared with the measured characteristics for specific metallic cable.