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...
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
E. Gregory McPherson; Paula J. Peper
2012-01-01
This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...
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...
Structural Equation Model Trees
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman
2015-01-01
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 structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789
Decision tree induction in the diagnosis of otoneurological diseases.
Viikki, K; Kentala, E; Juhola, M; Pyykkö, I
1999-01-01
Expert systems have been applied in medicine as diagnostic aids and education tools. The construction of a knowledge base for an expert system may be a difficult task; to automate this task several machine learning methods have been developed. These methods can be also used in the refinement of knowledge bases for removing inconsistencies and redundancies, and for simplifying decision rules. In this study, decision tree induction was employed to acquire diagnostic knowledge for otoneurological diseases and to extract relevant parameters from the database of an otoneurological expert system ONE. The records of patients with benign positional vertigo, Meniere's disease, sudden deafness, traumatic vertigo, vestibular neuritis and vestibular schwannoma were retrieved from the database of ONE, and for each disease, decision trees were constructed. The study shows that decision tree induction is a useful technique for acquiring diagnostic knowledge for otoneurological diseases and for extracting relevant parameters from a large set of parameters.
Decision-tree induction to detect clinical mastitis with automatic milking
Kamphuis, C.; Mollenhorst, H.; Feelders, A.; Pietersma, D.; Hogeveen, H.
2010-01-01
a b s t r a c t This study explored the potential of using decision-tree induction to develop models for the detection of clinical mastitis with automatic milking. Sensor data (including electrical conductivity and colour) of over 711,000 quarter milkings were collected from December 2006 till
Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.
Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto
2012-11-21
This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.
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
Decision tree modeling using R.
Zhang, Zhongheng
2016-08-01
In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.
Interpretable decision-tree induction in a big data parallel framework
Directory of Open Access Journals (Sweden)
Weinberg Abraham Itzhak
2017-12-01
Full Text Available When running data-mining algorithms on big data platforms, a parallel, distributed framework, such asMAPREDUCE, may be used. However, in a parallel framework, each individual model fits the data allocated to its own computing node without necessarily fitting the entire dataset. In order to induce a single consistent model, ensemble algorithms such as majority voting, aggregate the local models, rather than analyzing the entire dataset directly. Our goal is to develop an efficient algorithm for choosing one representative model from multiple, locally induced decision-tree models. The proposed SySM (syntactic similarity method algorithm computes the similarity between the models produced by parallel nodes and chooses the model which is most similar to others as the best representative of the entire dataset. In 18.75% of 48 experiments on four big datasets, SySM accuracy is significantly higher than that of the ensemble; in about 43.75% of the experiments, SySM accuracy is significantly lower; in one case, the results are identical; and in the remaining 35.41% of cases the difference is not statistically significant. Compared with ensemble methods, the representative tree models selected by the proposed methodology are more compact and interpretable, their induction consumes less memory, and, as confirmed by the empirical results, they allow faster classification of new records.
Anatomical modeling of the bronchial tree
Hentschel, Gerrit; Klinder, Tobias; Blaffert, Thomas; Bülow, Thomas; Wiemker, Rafael; Lorenz, Cristian
2010-02-01
The bronchial tree is of direct clinical importance in the context of respective diseases, such as chronic obstructive pulmonary disease (COPD). It furthermore constitutes a reference structure for object localization in the lungs and it finally provides access to lung tissue in, e.g., bronchoscope based procedures for diagnosis and therapy. This paper presents a comprehensive anatomical model for the bronchial tree, including statistics of position, relative and absolute orientation, length, and radius of 34 bronchial segments, going beyond previously published results. The model has been built from 16 manually annotated CT scans, covering several branching variants. The model is represented as a centerline/tree structure but can also be converted in a surface representation. Possible model applications are either to anatomically label extracted bronchial trees or to improve the tree extraction itself by identifying missing segments or sub-trees, e.g., if located beyond a bronchial stenosis. Bronchial tree labeling is achieved using a naïve Bayesian classifier based on the segment properties contained in the model in combination with tree matching. The tree matching step makes use of branching variations covered by the model. An evaluation of the model has been performed in a leaveone- out manner. In total, 87% of the branches resulting from preceding airway tree segmentation could be correctly labeled. The individualized model enables the detection of missing branches, allowing a targeted search, e.g., a local rerun of the tree-segmentation segmentation.
Finite Element Model of Gear Induction Hardening
Hodek, J; Zemko, M; Shykula, P
2015-01-01
International audience; This paper presents a finite element model of a gear induction hardening process. The gear was surface-heated by an induction coil and quickly cooled by spraying water. The finite element model was developed as a three-dimensional model. The electromagnetic field, temperature field, stress distribution and microstructure distribution were examined. Temperature and microstructural characteristics were measured and used. The gear material data was obtained in part by mea...
Boundary expansion algorithm of a decision tree induction for an imbalanced dataset
Directory of Open Access Journals (Sweden)
Kesinee Boonchuay
2017-10-01
Full Text Available A decision tree is one of the famous classifiers based on a recursive partitioning algorithm. This paper introduces the Boundary Expansion Algorithm (BEA to improve a decision tree induction that deals with an imbalanced dataset. BEA utilizes all attributes to define non-splittable ranges. The computed means of all attributes for minority instances are used to find the nearest minority instance, which will be expanded along all attributes to cover a minority region. As a result, BEA can successfully cope with an imbalanced dataset comparing with C4.5, Gini, asymmetric entropy, top-down tree, and Hellinger distance decision tree on 25 imbalanced datasets from the UCI Repository.
Modeling and analysis with induction generators
Simões, M Godoy
2014-01-01
ForewordPrefaceAcknowledgmentsAuthorsPrinciples of Alternative Sources of Energy and Electric GenerationScope of This ChapterLegal DefinitionsPrinciples of Electrical ConversionBasic Definitions of Electrical PowerCharacteristics of Primary SourcesCharacteristics of Remote Industrial, Commercial, and Residential Sites and Rural EnergySelection of the Electric GeneratorInterfacing Primary Source, Generator, and LoadExample of a Simple Integrated Generating and Energy-Storing SystemSolved ProblemsSuggested ProblemsReferencesSteady-State Model of Induction GeneratorsScope of This ChapterInterconnection and Disconnection of the Electric Distribution NetworkRobustness of Induction GeneratorsClassical Steady-State Representation of the Asynchronous MachineGenerated PowerInduced TorqueRepresentation of Induction Generator LossesMeasurement of Induction Generator ParametersBlocked Rotor Test (s = 1)No-Load Test (s = 0)Features of Induction Machines Working as Generators Interconnected to the Distribution NetworkHigh-...
Interactive wood combustion for botanical tree models
Pirk, Sören
2017-11-22
We present a novel method for the combustion of botanical tree models. Tree models are represented as connected particles for the branching structure and a polygonal surface mesh for the combustion. Each particle stores biological and physical attributes that drive the kinetic behavior of a plant and the exothermic reaction of the combustion. Coupled with realistic physics for rods, the particles enable dynamic branch motions. We model material properties, such as moisture and charring behavior, and associate them with individual particles. The combustion is efficiently processed in the surface domain of the tree model on a polygonal mesh. A user can dynamically interact with the model by initiating fires and by inducing stress on branches. The flames realistically propagate through the tree model by consuming the available resources. Our method runs at interactive rates and supports multiple tree instances in parallel. We demonstrate the effectiveness of our approach through numerous examples and evaluate its plausibility against the combustion of real wood samples.
Supersonic induction plasma jet modeling
International Nuclear Information System (INIS)
Selezneva, S.E.; Boulos, M.I.
2001-01-01
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
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.
Stator Fault Modelling of Induction Motors
DEFF Research Database (Denmark)
Thomsen, Jesper Sandberg; Kallesøe, Carsten
2006-01-01
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 measurem......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...... 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...
Comprehensive decision tree models in bioinformatics.
Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter
2012-01-01
Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly
Comprehensive decision tree models in bioinformatics.
Directory of Open Access Journals (Sweden)
Gregor Stiglic
Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets
Cell lineage tree models of neurogenesis.
Slater, Jennifer L; Landman, Kerry A; Hughes, Barry D; Shen, Qin; Temple, Sally
2009-01-21
The production of neurons to form the mammalian cortex, known as embryonic cortical neurogenesis, is a complex developmental process. Insight into the process of cell division during neurogenesis is provided by murine cortical cell lineage trees, recorded through experimental observation. Recurring patterns within cell lineage trees may be indicative of predetermined cell behaviour. The application of mathematical modelling to this process requires careful consideration and identification of the key features to be incorporated into the model. A biologically plausible stochastic model of evolution of cell lineage trees is developed, based on the most important known features of neurogenesis. Tractable means of measuring lineage tree shape are discussed. Symmetry is identified as a significant feature of shape and is measured using Colless's Index of Imbalance. Distributions of tree size and imbalance for large tree sizes are computed and results compared to experimental data. Several refinements to the model are investigated, when the cell division probabilities are weighted according to cell generation. Two models involving generation-dependent cell division probabilities produce imbalance distributions which are the most consistent with the available experimental results. The results indicate that a stochastic cell division mechanism is a plausible basis of mammalian neurogenesis.
Stator Fault Modelling of Induction Motors
DEFF Research Database (Denmark)
Thomsen, Jesper Sandberg; Kallesøe, Carsten
2006-01-01
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....
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.
Modelling and Identification of Induction Machines
Energy Technology Data Exchange (ETDEWEB)
Nestli, T.F.
1995-12-01
To obtain high quality control of the induction machine, field orientation is probably the most frequently used control strategy. Using this strategy requires that one of the flux space vectors be known. Since this cannot be measured, many predictor models for calculation of the rotor flux space vector in real time have been developed. This doctoral thesis presents an analysis method for evaluating and comparing predictor models for flux calculation with respect to sensitivity to parameter deviations and measurement errors and with respect to dynamics. It is concluded that the best predictor models in the minimum sensitivity sense should have properties similar to the current and voltage models at lower and higher frequencies, respectively. To further reduce flux estimation errors, a new saturation model for the Inverse {Gamma}-formulation of the induction machine is developed. It is shown that the leakage reactance varies mainly with stator current, and the magnetizing reactance depends both on stator flux and rotor current magnitudes, i.e., both on magnetization and load. The reactance models are verified by experiments. An off-line identification algorithm is developed to identify the parameters of the reactance model and initial values for the stator and rotor resistances. The algorithm is verified in laboratory experiments, which also demonstrate the temperature dependence of the resistances. 36 refs., 49 figs., 6 tabs.
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
Random trinomial tree models and vanilla options
Ganikhodjaev, Nasir; Bayram, Kamola
2013-09-01
In this paper we introduce and study random trinomial model. The usual trinomial model is prescribed by triple of numbers (u, d, m). We call the triple (u, d, m) an environment of the trinomial model. A triple (Un, Dn, Mn), where {Un}, {Dn} and {Mn} are the sequences of independent, identically distributed random variables with 0 < Dn < 1 < Un and Mn = 1 for all n, is called a random environment and trinomial tree model with random environment is called random trinomial model. The random trinomial model is considered to produce more accurate results than the random binomial model or usual trinomial model.
Tree taper models for Cupressus lusitanica plantations in Ethiopia ...
African Journals Online (AJOL)
... found to vary from tree to tree and also appear to depend on tree size. The results from both the Monte Carlo and mixed effects modeling study seem to indicate the need to estimate p from the data. Keywords: Cupressus lusitanica; mixed effects modeling; Monte Carlo; tree taper. Southern Forests 2008, 70(3): 193–203 ...
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...... to calculate the probabilities of reaching each non-error system state. Each generated error state is assigned a variable indicating its individual probability of occurrence. Our method can determine the probability of combined faults occurring, while accounting for the basic probabilistic structure...... 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....
Emilie Bigorgne,; Custer, Thomas W.; Dummer, Paul; Erickson, Richard A.; Karouna-Renier, Natalie K.; Schultz, Sandra; Custer, Christine M.; Thogmartin, Wayne E.; Cole W. Matson,
2015-01-01
The health of tree swallows, Tachycineta bicolor, on the Upper Mississippi River (UMR) was assessed in 2010 and 2011 using biomarkers at six sites downriver of Minneapolis/St. Paul, MN metropolitan area, a tributary into the UMR, and a nearby lake. Chromosomal damage was evaluated in nestling blood by measuring the coefficient of variation of DNA content (DNA CV) using flow cytometry. Cytochrome P450 1A activity in nestling liver was measured using the ethoxyresorufin-O-dealkylase (EROD) assay, and oxidative stress was estimated in nestling livers via determination of thiobarbituric acid reacting substances (TBARS), reduced glutathione (GSH), oxidized glutathione (GSSG), the ratio GSSG/GSH, total sulfhydryl, and protein bound sulfhydryl (PBSH). A multilevel regression model (DNA CV) and simple regressions (EROD and oxidative stress) were used to evaluate biomarker responses for each location. Chromosomal damage was significantly elevated at two sites on the UMR (Pigs Eye and Pool 2) relative to the Green Mountain Lake reference site, while the induction of EROD activity was only observed at Pigs Eye. No measures of oxidative stress differed among sites. Multivariate analysis confirmed an increased DNA CV at Pigs Eye and Pool 2, and elevated EROD activity at Pigs Eye. These results suggest that the health of tree swallows has been altered at the DNA level at Pigs Eye and Pool 2 sites, and at the physiological level at Pigs Eye site only.
Decision tree models for data mining in hit discovery.
Hammann, Felix; Drewe, Juergen
2012-04-01
Decision tree induction (DTI) is a powerful means of modeling data without much prior preparation. Models are readable by humans, robust and easily applied in real-world applications, features that are mutually exclusive in other commonly used machine learning paradigms. While DTI is widely used in disciplines ranging from economics to medicine, they are an intriguing option in pharmaceutical research, especially when dealing with large data stores. This review covers the automated technologies available for creating decision trees and other rules efficiently, even from large datasets such as chemical libraries. The authors discuss the need for properly documented and validated models. Lastly, the authors cover several case studies in hit discovery, drug metabolism and toxicology, and drug surveillance, and compare them with other established techniques. DTI is a competitive and easy-to-use tool in basic research as well as in hit and drug discovery. Its strengths lie in its ability to handle all sorts of different data formats, the visual nature of the models, and the small computational effort needed for implementation in real-world systems. Limitations include lack of robustness and over-fitted models for certain types of data. As with any modeling technique, proper validation and quality measures are of utmost importance. © 2012 Informa UK, Ltd.
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...
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.
Deptuła, A.; Partyka, M. A.
2017-02-01
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.
Modeling induction heater temperature distribution in polymeric material
Sorokin, A. G.; Filimonova, O. V.
2017-10-01
An induction heating system has a number of inherent benefits compared to traditional heating systems due to a non-contact heating process. The main interesting area of the induction heating process is the efficiency of the usage of energy, choice of the plate material and different coil configurations based on application. Correctly designed, manufactured and maintained induction coils are critical to the overall efficiency of induction heating solutions. The paper describes how the induction heating system in plastic injection molding is designed. The use of numerical simulation in order to get the optimum design of the induction coil is shown. The purpose of this work is to consider various coil configurations used in the induction heating process, which is widely used in plastic molding. Correctly designed, manufactured and maintained induction coils are critical to the overall efficiency of induction heating solutions. The results of calculation are in the numerical model.
Luo, Jia; Zhang, Min; Zhou, Xiaoling; Chen, Jianhua; Tian, Yuxin
2018-01-01
Taken 4 main tree species in the Wuling mountain small watershed as research objects, 57 typical sample plots were set up according to the stand type, site conditions and community structure. 311 goal diameter-class sample trees were selected according to diameter-class groups of different tree-height grades, and the optimal fitting models of tree height and DBH growth of main tree species were obtained by stem analysis using Richard, Logistic, Korf, Mitscherlich, Schumacher, Weibull theoretical growth equations, and the correlation coefficient of all optimal fitting models reached above 0.9. Through the evaluation and test, the optimal fitting models possessed rather good fitting precision and forecast dependability.
Energy Efficiency Model for Induction Furnace
Dey, Asit Kr
2018-01-01
In this paper, a system of a solar induction furnace unit was design to find out a new solution for the existing AC power consuming heating process through Supervisory control and data acquisition system. This unit can be connected directly to the DC system without any internal conversion inside the device. The performance of the new system solution is compared with the existing one in terms of power consumption and losses. This work also investigated energy save, system improvement, process control model in a foundry induction furnace heating framework corresponding to PV solar power supply. The results are analysed for long run in terms of saving energy and integrated process system. The data acquisition system base solar foundry plant is an extremely multifaceted system that can be run over an almost innumerable range of operating conditions, each characterized by specific energy consumption. Determining ideal operating conditions is a key challenge that requires the involvement of the latest automation technologies, each one contributing to allow not only the acquisition, processing, storage, retrieval and visualization of data, but also the implementation of automatic control strategies that can expand the achievement envelope in terms of melting process, safety and energy efficiency.
Modeling a Cold Crucible Induction Heated Melter
International Nuclear Information System (INIS)
Hawkes, G.L.
2003-01-01
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 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
Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods
Soroush, Masoud; Weinberger, Charles B.
2010-01-01
This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…
Constructing Dynamic Event Trees from Markov Models
International Nuclear Information System (INIS)
Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood
2006-01-01
In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system. These event trees can be integrated into an existing PRA using software tools such as SAPHIRE. To implement our approach, we first construct a discrete-time Markov chain modeling the system of interest by: (a) partitioning the process variable state space into magnitude intervals (cells), (b) using analytical equations or a system simulator to determine the transition probabilities between the cells through the cell-to-cell mapping technique, and, (c) using given failure/repair data for all the components of interest. The Markov transition matrix thus generated can be thought of as a process model describing the stochastic dynamic behavior of the finite-state system. We can therefore search the state space starting from a set of initial states to explore all possible paths to failure (scenarios) with associated probabilities. We can also construct event trees of arbitrary depth by tracing paths from a chosen initiating event and recording the following events while keeping track of the probabilities associated with each branch in the tree. As an example of our approach, we use the simple level control system often used as benchmark in the literature with one process variable (liquid level in a tank), and three control units: a drain unit and two supply units. Each unit includes a separate level sensor to observe the liquid level in the tank
Assessment and modeling of inductive and non-inductive scenarios for ITER
International Nuclear Information System (INIS)
Boucher, D.; Vayakis, G.; Moreau, D.
1999-01-01
This paper presents recent developments in modeling and simulations of ITER performances and scenarios. The first part presents an improved modeling of coupled divertor/main plasma operation including the simulation of the measurements involved in the control loop. The second part explores the fusion performances predicted under non-inductive operation with internal transport barrier. The final part covers a detailed scenario for non-inductive operation using a reverse shear configuration with lower hybrid and fast wave current drive. (author)
Multiset-based Tree Model for Membrane Computing
Directory of Open Access Journals (Sweden)
D. Singh
2011-06-01
Full Text Available In this paper, we introduce a new paradigm - multiset-based tree model. We show that trees can be represented in the form of wellfounded multisets. We also show that the conventional approach for this representation is not injective from a set of trees to the class of multisets representing such trees. We establish a one-to-one correspondence between trees and suitable permutations of a wellfounded multiset, which we call \\textit{tree structures}. We give formal definitions of a \\textit{tree structure} and a \\textit{subtree structure} of a tree structure. Finally, we represent membrane structures in the form of tree structures - a form in which membrane structures can suitably be represented at programming level.
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...
Pruning Chinese trees : an experimental and modelling approach
Zeng, Bo
2001-01-01
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.
Phalla, Thuch; Ota, Tetsuji; Mizoue, Nobuya; Kajisa, Tsuyoshi; Yoshida, Shigejiro; Vuthy, Ma; Heng, Sokh
2018-01-01
This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estima...
Shavit Grievink, Liat; Penny, David; Hendy, Michael D; Holland, Barbara R
2010-05-01
Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction.
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
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...... to a tunny generator through a shaft....
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...
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.
Computational model of a whole tree combustor
Energy Technology Data Exchange (ETDEWEB)
Bryden, K.M.; Ragland, K.W. [Univ. of Wisconsin, Madison, WI (United States)
1993-12-31
A preliminary computational model has been developed for the whole tree combustor and compared to test results. In the simulation model presented hardwood logs, 15 cm in diameter are burned in a 4 m deep fuel bed. Solid and gas temperature, solid and gas velocity, CO, CO{sub 2}, H{sub 2}O, HC and O{sub 2} profiles are calculated. This deep, fixed bed combustor obtains high energy release rates per unit area due to the high inlet air velocity and extended reaction zone. The lowest portion of the overall bed is an oxidizing region and the remainder of the bed acts as a gasification and drying region. The overfire air region completes the combustion. Approximately 40% of the energy is released in the lower oxidizing region. The wood consumption rate obtained from the computational model is 4,110 kg/m{sup 2}-hr which matches well the consumption rate of 3,770 kg/m{sup 2}-hr observed during the peak test period of the Aurora, MN test. The predicted heat release rate is 16 MW/m{sup 2} (5.0*10{sup 6} Btu/hr-ft{sup 2}).
Study of linear induction motor characteristics : the Oberretl model
1975-05-30
The Oberretl theory of the double-sided linear induction motor (LIM) is examined, starting with the idealized model and accompanying assumptions, and ending with relations for predicted thrust, airgap power, and motor efficiency. The effect of varyin...
Study of linear induction motor characteristics : the Mosebach model
1976-05-31
This report covers the Mosebach theory of the double-sided linear induction motor, starting with the ideallized model and accompanying assumptions, and ending with relations for thrust, airgap power, and motor efficiency. Solutions of the magnetic in...
A Beta-splitting model for evolutionary trees.
Sainudiin, Raazesh; Véber, Amandine
2016-05-01
In this article, we construct a generalization of the Blum-François Beta-splitting model for evolutionary trees, which was itself inspired by Aldous' Beta-splitting model on cladograms. The novelty of our approach allows for asymmetric shares of diversification rates (or diversification 'potential') between two sister species in an evolutionarily interpretable manner, as well as the addition of extinction to the model in a natural way. We describe the incremental evolutionary construction of a tree with n leaves by splitting or freezing extant lineages through the generating, organizing and deleting processes. We then give the probability of any (binary rooted) tree under this model with no extinction, at several resolutions: ranked planar trees giving asymmetric roles to the first and second offspring species of a given species and keeping track of the order of the speciation events occurring during the creation of the tree, unranked planar trees, ranked non-planar trees and finally (unranked non-planar) trees. We also describe a continuous-time equivalent of the generating, organizing and deleting processes where tree topology and branch lengths are jointly modelled and provide code in SageMath/Python for these algorithms.
Modeling Caribbean tree stem diameters from tree height and crown width measurements
Thomas Brandeis; KaDonna Randolph; Mike Strub
2009-01-01
Regression models to predict diameter at breast height (DBH) as a function of tree height and maximum crown radius were developed for Caribbean forests based on data collected by the U.S. Forest Service in the Commonwealth of Puerto Rico and Territory of the U.S. Virgin Islands. The model predicting DBH from tree height fit reasonably well (R2 = 0.7110), with...
Derivation of Output Power of Induction Heater Model
Directory of Open Access Journals (Sweden)
Riyadh K. Chillab
2016-12-01
Full Text Available The work is concerned with the study of the single phase cylindrical induction heating systems and derive equation power. The presented analysis is analytical and a multi-layer model using cylindrical geometry which is used to obtain the theoretical results. To validate the theoretical results, a practical model is constructed, tested and the results are compared with the theoretical ones. Comparison showed that the adopted analytical method is efficient in describing the performance of such induction heater systems
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.
Modelling diameter growth, mortality and recruitment of trees in ...
African Journals Online (AJOL)
Miombo woodlands cover large areas in Tanzania but very little reliable data on forest dynamics for the woodlands exist. The main objective of this study was to develop a model system describing such dynamics based on easily measurable tree variables. Individual tree diameter growth and mortality models, and ...
Total tree, merchantable stem and branch volume models for ...
African Journals Online (AJOL)
Total tree, merchantable stem and branch volume models for miombo woodlands of Malawi. Daud J Kachamba, Tron Eid. Abstract. The objective of this study was to develop general (multispecies) models for prediction of total tree, merchantable stem and branch volume including options with diameter at breast height (dbh) ...
Inductively Modeling Parallel, Normal, and Frictional Forces
Wyrembeck, Edward P.
2005-02-01
This year, instead of resolving the weight mg of an object resting on an incline into force components parallel and perpendicular to the surface of the incline, I asked my students to actually measure these forces at various angles of inclination and graph the data. I wanted my students to inductively discover mg sin θ and mg cos θ, and to use these graphs to confront the passive nature of the static frictional force. I believe the graphs themselves are very powerful conceptual tools that are often never discovered and used by students who only learn to use equations at specific angles to solve specific quantitative problems.
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.
Modelling of asymmetrical interconnect T-tree laminated on flexible substrate
Ravelo, Blaise
2015-11-01
A fast and accurate behavioral modelling of asymmetrical microstrip tree printed on plastic substrate is investigated. The methodology for extracting the asymmetrical tree transfer responses based on the ABCD-matrix analysis is presented. The elements of the interconnect T-tree are constituted by transmission lines (TLs) defined by their characteristic impedance and physical length. The distributed tree network can be assumed as a single input multiple output (SIMO) topology. By considering the circuit equivalent between the electrical path from the tree input and output, the single input single output (SISO) simplified circuit can be established. In order to determine the frequency response of the interconnect tree system, the elementary TLs constituting the tree branches are modelled with their equivalent frequency dependent RLCG network. The novelty of the present paper is the application of the model to the microstrip structure printed on the plastic substrate by analyzing the influence of the metallization conductivity. As proof of concept (POC), a single input and three output distributed interconnect T-tree having branches presented physical lengths from 3 cm to 20 cm was designed. The POC was printed on the Cu metal deposited plastic Kapton substrate. Then, the frequency dependent per unit length resistance, inductance, capacitance and conductance of the elementary branches of the T-tree from DC to 10 GHz were extracted. By implementing the behavioral model of the circuit, the frequency- and time-domain responses of the proposed asymmetrical T-tree are computed. Then, the analyses of the asymmetrical T-tree responses in function of the thin film conductivity of the microstrip interconnect lines were discussed. In addition, time domain analysis enabling to predict the influence of the deposited metallic ink conductivity on the signal integrity is realized by considering a mixed signal corresponding to the digital data "010110000" having 0.5 Gbps rate
Developing Models to Forcast Sales of Natural Christmas Trees
Lawrence D. Garrett; Thomas H. Pendleton
1977-01-01
A study of practices for marketing Christmas trees in Winston-Salem, North Carolina, and Denver, Colorado, revealed that such factors as retail lot competition, tree price, consumer traffic, and consumer income were very important in determining a particular retailer's sales. Analyses of 4 years of market data were used in developing regression models for...
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
Development of a Predictive Model for Induction Success of Labour
Directory of Open Access Journals (Sweden)
Cristina Pruenza
2018-03-01
Full Text Available Induction of the labour process is an extraordinarily common procedure used in some pregnancies. Obstetricians face the need to end a pregnancy, for medical reasons usually (maternal or fetal requirements or less frequently, social (elective inductions for convenience. The success of induction procedure is conditioned by a multitude of maternal and fetal variables that appear before or during pregnancy or birth process, with a low predictive value. The failure of the induction process involves performing a caesarean section. This project arises from the clinical need to resolve a situation of uncertainty that occurs frequently in our clinical practice. Since the weight of clinical variables is not adequately weighted, we consider very interesting to know a priori the possibility of success of induction to dismiss those inductions with high probability of failure, avoiding unnecessary procedures or postponing end if possible. We developed a predictive model of induced labour success as a support tool in clinical decision making. Improve the predictability of a successful induction is one of the current challenges of Obstetrics because of its negative impact. The identification of those patients with high chances of failure, will allow us to offer them better care improving their health outcomes (adverse perinatal outcomes for mother and newborn, costs (medication, hospitalization, qualified staff and patient perceived quality. Therefore a Clinical Decision Support System was developed to give support to the Obstetricians. In this article, we had proposed a robust method to explore and model a source of clinical information with the purpose of obtaining all possible knowledge. Generally, in classification models are difficult to know the contribution that each attribute provides to the model. We had worked in this direction to offer transparency to models that may be considered as black boxes. The positive results obtained from both the
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.
A discrete element modelling approach for block impacts on trees
Toe, David; Bourrier, Franck; Olmedo, Ignatio; Berger, Frederic
2015-04-01
These past few year rockfall models explicitly accounting for block shape, especially those using the Discrete Element Method (DEM), have shown a good ability to predict rockfall trajectories. Integrating forest effects into those models still remain challenging. This study aims at using a DEM approach to model impacts of blocks on trees and identify the key parameters controlling the block kinematics after the impact on a tree. A DEM impact model of a block on a tree was developed and validated using laboratory experiments. Then, key parameters were assessed using a global sensitivity analyse. Modelling the impact of a block on a tree using DEM allows taking into account large displacements, material non-linearities and contacts between the block and the tree. Tree stems are represented by flexible cylinders model as plastic beams sustaining normal, shearing, bending, and twisting loading. Root soil interactions are modelled using a rotation stiffness acting on the bending moment at the bottom of the tree and a limit bending moment to account for tree overturning. The crown is taken into account using an additional mass distribute uniformly on the upper part of the tree. The block is represented by a sphere. The contact model between the block and the stem consists of an elastic frictional model. The DEM model was validated using laboratory impact tests carried out on 41 fresh beech (Fagus Sylvatica) stems. Each stem was 1,3 m long with a diameter between 3 to 7 cm. Wood stems were clamped on a rigid structure and impacted by a 149 kg charpy pendulum. Finally an intensive simulation campaign of blocks impacting trees was done to identify the input parameters controlling the block kinematics after the impact on a tree. 20 input parameters were considered in the DEM simulation model : 12 parameters were related to the tree and 8 parameters to the block. The results highlight that the impact velocity, the stem diameter, and the block volume are the three input
Thermo-hydrodynamic and inductive modelling of a glass melt elaborated in cold inductive crucible
International Nuclear Information System (INIS)
Sauvage, E.
2009-11-01
Within the context of a search for a new vitrification process for nuclear wastes with a replacement of the presently used metallic pot by an inductive cold crucible, this research thesis deals with the numerical modelling of this technology. After having recalled the interest of nuclear waste vitrification, this report presents the new process based on the use of a cold crucible, describing principles and objectives of this method, and the characteristic physical phenomena associated with the flow and the thermodynamics of the glassy melt in such a crucible. It also recalls and comments the existing works on modelling. The main objective of this research is then to demonstrate the feasibility of 3D thermo-hydraulic and inductive simulations. He describes and analyses the glass physical properties (electrical properties, viscosity, thermal properties), the electromagnetic, hydrodynamic and thermal phenomena. He presents in detail the bubbling mixing modelling, reports 3D induction and fluid mechanical coupling calculations, and specific thermal investigations (radiating transfers, thermal limit conditions)
Maximum parsimony, substitution model, and probability phylogenetic trees.
Weng, J F; Thomas, D A; Mareels, I
2011-01-01
The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.
International Nuclear Information System (INIS)
Henkel, Charles; Muley, Pranjali D.; Abdollahi, Kamran K.; Marculescu, Cosmin; Boldor, Dorin
2016-01-01
Highlights: • Energy cane & Chinese tallow tree (CTT) biomass was pyrolyzed via induction heating. • Increasing temperature (500–700°C) increased gas yield & decreased liquid yield. • Highest liquid yield was achieved for energy cane at 500 °C. • Nitrogen and hydrogen content of CTT bio-oil increased as the temperature increased. • CTT bio-oil had higher % fatty alcohols; energy cane bio-oil was richer in phenols. - Abstract: The growing demand for energy and the increasing opposition to fossil fuels has given rise to the need for alternative fuels. The pyrolysis process is one viable option that converts lignocellulosic biomass into liquid fuel. This study focuses, for the first time, on the use of an induction heating mechanism to pyrolyze biomass from energy cane (Saccharum complex) bagasse and invasive Chinese tallow trees (Triadica sebifera L.). Energy cane and tallow wood were pyrolyzed at 500, 550, 600, 650, and 700 °C at atmospheric pressure in a laboratory scale batch process with an initial loading of 15 g and 30 g for energy cane bagasse and CTT respectively. The results indicate that the highest liquid yield was obtained at 500 °C for both biomasses. The yields of char declined and the gas yields increased as the reaction temperature increased, as the biomass was more thoroughly decomposed at the higher reaction temperatures. GC–MS results show that the liquid product was rich in oxygenated compounds such as phenols, ketones and alcohols for biomasses at all temperatures. Bio-oil obtained from pyrolysis of Chinese tallow tree showed small concentration of fatty alcohols. Concentration of smaller compounds in the liquid product increased as the reaction temperature increased. Highest energy content and liquid yields (34 MJ/kg and 35.4%) amongst the tested temperatures was obtained at 500 °C for both energy cane and tallow wood pyrolysis. Higher heating values were obtained for bio-oil from energy cane compared to tallow tree biomass.
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.
Modelling Wind Turbine Inflow: The Induction Zone
DEFF Research Database (Denmark)
Meyer Forsting, Alexander Raul
to the rotor, but requires exact knowledge of the flow deceleration to estimate the available, undis- turbed kinetic energy. Thus this thesis explores, mostly numerically, any wind turbine or environmental dependencies of this deceleration. The computational fluid dynamics model (CFD) employed is validated......A wind turbine decelerates the wind in front of its rotor by extracting kinetic energy. The wind speed reduction is maximal at the rotor and negligible more than five rotor radii upfront. By measuring wind speed this far from the rotor, the turbine’s performance is determined without any rotor bias...... significant parameter. Exploiting this singu- lar dependency, a fast semi-empirical model is devised that accurately predicts the velocity deficit upstream of a single turbine. Near-rotor mea-surements in combination with this model are able to retrieve the kinetic energy available to the turbine in flat...
Challenges in Species Tree Estimation Under the Multispecies Coalescent Model.
Xu, Bo; Yang, Ziheng
2016-12-01
The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the
Context Tree Estimation in Variable Length Hidden Markov Models
Dumont, Thierry
2011-01-01
We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...
Modelling of Continual Induction Hardening in Quasi-Coupled Formulation
Czech Academy of Sciences Publication Activity Database
Barglik, J.; Doležel, Ivo; Karban, P.; Ulrych, B.
2005-01-01
Roč. 24, č. 1 (2005), s. 251-260 ISSN 0332-1649 Grant - others:PSRC(PL) 4T08C 04823 Institutional research plan: CEZ:AV0Z20570509 Keywords : mathematical modelling * electromagnetism * induction Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 0.188, year: 2005
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.
Modelling of windmill induction generators in dynamic simulation programs
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
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...... 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...
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.
Processing tree point clouds using Gaussian Mixture Models
Directory of Open Access Journals (Sweden)
D. Belton
2013-10-01
Full Text Available While traditionally used for surveying and photogrammetric fields, laser scanning is increasingly being used for a wider range of more general applications. In addition to the issues typically associated with processing point data, such applications raise a number of new complications, such as the complexity of the scenes scanned, along with the sheer volume of data. Consequently, automated procedures are required for processing, and analysing such data. This paper introduces a method for modelling multi-modal, geometrically complex objects in terrestrial laser scanning point data; specifically, the modelling of trees. The model method comprises a number of geometric features in conjunction with a multi-modal machine learning technique. The model can then be used for contextually dependent region growing through separating the tree into its component part at the point level. Subsequently object analysis can be performed, for example, performing volumetric analysis of a tree by removing points associated with leaves. The workflow for this process is as follows: isolate individual trees within the scanned scene, train a Gaussian mixture model (GMM, separate clusters within the mixture model according to exemplar points determined by the GMM, grow the structure of the tree, and then perform volumetric analysis on the structure.
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.
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 neurodynamical model of brightness induction in v1.
Directory of Open Access Journals (Sweden)
Olivier Penacchio
Full Text Available Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.
Fruit tree model for uptake of organic compounds from soil
DEFF Research Database (Denmark)
Trapp, Stefan; Rasmussen, D.; Samsoe-Petersen, L.
2003-01-01
rences: 20 [ view related records ] Citation Map Abstract: Apples and other fruits are frequently cultivated in gardens and are part of our daily diet. Uptake of pollutants into apples may therefore contribute to the human daily intake of toxic substances. In current risk assessment of polluted...... 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......-state, and an example calculation is given. The Fruit Tree Model is compared to the empirical equation of Travis and Arms (T&A), and to results from fruits, collected in contaminated areas. For polar compounds, both T&A and the Fruit Tree Model predict bioconcentration factors fruit to soil (BCF, wet weight based...
Massive-Scale Tree Modelling from Tls Data
Raumonen, P.; Casella, E.; Calders, K.; Murphy, S.; Åkerbloma, , M.; Kaasalainen, M.
2015-03-01
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 plot and a 80-m diameter Australian eucalyptus plot. For the oak plot the total biomass was overestimated by about 17 %, when compared to allometry (N = 15), and the modelling time was about 100 min with a laptop. For the eucalyptus plot the total biomass was overestimated by about 8.5 %, when compared to a destructive reference (N = 27), and the modelling time was about 160 min. The method provides accurate and fast tree modelling abilities for, e.g., biomass estimation and ground truth data for airborne measurements at a massive ground scale.
Dynamic Ising model: reconstruction of evolutionary trees
International Nuclear Information System (INIS)
De Oliveira, P M C
2013-01-01
An evolutionary tree is a cascade of bifurcations starting from a single common root, generating a growing set of daughter species as time goes by. ‘Species’ here is a general denomination for biological species, spoken languages or any other entity which evolves through heredity. From the N currently alive species within a clade, distances are measured through pairwise comparisons made by geneticists, linguists, etc. The larger is such a distance that, for a pair of species, the older is their last common ancestor. The aim is to reconstruct the previously unknown bifurcations, i.e. the whole clade, from knowledge of the N(N − 1)/2 quoted distances, which are taken for granted. A mechanical method is presented and its applicability is discussed. (paper)
Verification of Fault Tree Models with RBDGG Methodology
International Nuclear Information System (INIS)
Kim, Man Cheol
2010-01-01
Currently, fault tree analysis is widely used in the field of probabilistic safety assessment (PSA) of nuclear power plants (NPPs). To guarantee the correctness of fault tree models, which are usually manually constructed by analysts, a review by other analysts is widely used for verifying constructed fault tree models. Recently, an extension of the reliability block diagram was developed, which is named as RBDGG (reliability block diagram with general gates). The advantage of the RBDGG methodology is that the structure of a RBDGG model is very similar to the actual structure of the analyzed system and, therefore, the modeling of a system for a system reliability and unavailability analysis becomes very intuitive and easy. The main idea of the development of the RBDGG methodology is similar to that of the development of the RGGG (Reliability Graph with General Gates) methodology. The difference between the RBDGG methodology and RGGG methodology is that the RBDGG methodology focuses on the block failures while the RGGG methodology focuses on the connection line failures. But, it is also known that an RGGG model can be converted to an RBDGG model and vice versa. In this paper, a new method for the verification of the constructed fault tree models using the RBDGG methodology is proposed and demonstrated
International Nuclear Information System (INIS)
Kee, Ernest J.; Sun, Alice; Rodgers, Shawn; Popova, ElmiraV; Nelson, Paul; Moiseytseva, Vera; Wang, Eric
2006-01-01
South Texas Project uses a large fault tree to produce scenarios (minimal cut sets) used in quantification of plant availability and event frequency predictions. On the other hand, the South Texas Project probabilistic risk assessment model uses a large event tree, small fault tree for quantifying core damage and radioactive release frequency predictions. The South Texas Project is converting its availability and event frequency model to use a large event tree, small fault in an effort to streamline application support and to provide additional detail in results. The availability and event frequency model as well as the applications it supports (maintenance and operational risk management, system engineering health assessment, preventive maintenance optimization, and RIAM) are briefly described. A methodology to perform availability modeling in a large event tree, small fault tree framework is described in detail. How the methodology can be used to support South Texas Project maintenance and operations risk management is described in detail. Differences with other fault tree methods and other recently proposed methods are discussed in detail. While the methods described are novel to the South Texas Project Risk Management program and to large event tree, small fault tree models, concepts in the area of application support and availability modeling have wider applicability to the industry. (authors)
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.
UML Statechart Fault Tree Generation By Model Checking
DEFF Research Database (Denmark)
Herbert, Luke Thomas; Herbert-Hansen, Zaza Nadja Lee
Creating fault tolerant and efficient process work-flows poses a significant challenge. Individual faults, defined as an abnormal conditions or defects in a component, equipment, or sub-process, must be handled so that the system may continue to operate, and are typically addressed by implementing...... engineers imagine what undesirable events can occur under which conditions. Fault Tree Analysis (FTA) attempts to analyse the failure of systems by composing logic diagrams of separate individual faults to determine the probabil-ity of larger compound faults occurring. FTA is a commonly used method......-pleteness). To avoid these deficiencies, our approach derives the fault tree directly from the formal system model, under the assumption that any state can fail. We present a framework for the automated gener-ation of fault trees from models of real-world pro-cess workflows, expressed in a formalised subset...
River flow modelling using fuzzy decision trees
Han, D.; Cluckie, I. D.; Karbassioun, D.; Lawry, J.; Krauskopf, B.
2002-01-01
A modern real time flood forecasting system requires its mathematical model(s) to handle highly complex rainfall runoff processes. Uncertainty in real time flood forecasting will involve a variety of components such as measurement noise from telemetry systems, inadequacy of the models, insufficiency
Fractal approach to computer-analytical modelling of tree crown
International Nuclear Information System (INIS)
Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.
1993-09-01
In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs
HTS axial flux induction motor with analytic and FEA modeling
International Nuclear Information System (INIS)
Li, S.; Fan, Y.; Fang, J.; Qin, W.; Lv, G.; Li, J.H.
2013-01-01
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
Approximate dynamic fault tree calculations for modelling water supply risks
International Nuclear Information System (INIS)
Lindhe, Andreas; Norberg, Tommy; Rosén, Lars
2012-01-01
Traditional fault tree analysis is not always sufficient when analysing complex systems. To overcome the limitations dynamic fault tree (DFT) analysis is suggested in the literature as well as different approaches for how to solve DFTs. For added value in fault tree analysis, approximate DFT calculations based on a Markovian approach are presented and evaluated here. The approximate DFT calculations are performed using standard Monte Carlo simulations and do not require simulations of the full Markov models, which simplifies model building and in particular calculations. It is shown how to extend the calculations of the traditional OR- and AND-gates, so that information is available on the failure probability, the failure rate and the mean downtime at all levels in the fault tree. Two additional logic gates are presented that make it possible to model a system's ability to compensate for failures. This work was initiated to enable correct analyses of water supply risks. Drinking water systems are typically complex with an inherent ability to compensate for failures that is not easily modelled using traditional logic gates. The approximate DFT calculations are compared to results from simulations of the corresponding Markov models for three water supply examples. For the traditional OR- and AND-gates, and one gate modelling compensation, the errors in the results are small. For the other gate modelling compensation, the error increases with the number of compensating components. The errors are, however, in most cases acceptable with respect to uncertainties in input data. The approximate DFT calculations improve the capabilities of fault tree analysis of drinking water systems since they provide additional and important information and are simple and practically applicable.
Modelling mite dynamics on apple trees in eastern North America
Hartman, J.M.; Werf, van der W.; Nyrop, J.P.
1999-01-01
The model described in this paper simulates seasonal dynamics of Panonychus ulmi and the phytoseiid predator Typhlodromus pyri on apple trees in Eastern North America. It was originally developed to understand the effect of weather, predation, cannibalism, alternate food for the predator, and uneven
tree crown ratio models for tropical rainforests in oban division
African Journals Online (AJOL)
DR ADESOPE
habitat variable. It is often estimated using allometry. Modified versions of Logistics,. Richards, Weibull and Exponential functions were used to predict CR for ..... (ANOVA) were carried out to investigate significant differences in tree growth variables under different canopy layers. The mathematical model for the design is: 9.
The Abelian Sandpile Model on a Random Binary Tree
Redig, F.; Ruszel, W.M.; Saada, E.
2012-01-01
We study the abelian sandpile model on a random binary tree. Using a transfer matrix approach introduced by Dhar and Majumdar, we prove exponential decay of correlations, and in a small supercritical region (i.e., where the branching process survives with positive probability) exponential decay of
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...
Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology.
Beck, Kirk A.
2005-01-01
This article describes ethnographic decision tree modeling (EDTM; C. H. Gladwin, 1989) as a mixed method design appropriate for counseling psychology research. EDTM is introduced and located within a postpositivist research paradigm. Decision theory that informs EDTM is reviewed, and the 2 phases of EDTM are highlighted. The 1st phase, model…
Modelling dimensional growth of three street tree species in the ...
African Journals Online (AJOL)
The results could also be used in the process of modelling energy use reduction, air pollution uptake, rainfall interception, carbon sequestration and microclimate modification of urban forests such as those found in the City of Tshwane. Keywords: allometry; regression; size relationships; tree growth; urban forests. Southern ...
Steppe, Kathy; von der Crone, Jonas S; De Pauw, Dirk J W
2016-01-01
TreeWatch.net is an initiative that has been developed to watch trees grow and function in real-time. It is a water- and carbon-monitoring and modeling network, in which high-quality measurements of sap flow and stem diameter variation are collected on individual trees. Automated data processing using a cloud service enables instant visualization of water movement and radial stem growth. This can be used to demonstrate the sensitivity of trees to changing weather conditions, such as drought, heat waves, or heavy rain showers. But TreeWatch.net's true innovation lies in its use of these high-precision harmonized data to also parameterize process-based tree models in real-time, which makes displaying the much-needed mechanisms underlying tree responses to climate change possible. Continuous simulation of turgor to describe growth processes and long-term time series of hydraulic resistance to assess drought-vulnerability in real-time are only a few of the opportunities our approach offers. TreeWatch.net has been developed with the view to be complementary to existing forest monitoring networks and with the aim to contribute to existing dynamic global vegetation models. It provides high-quality data and real-time simulations in order to advance research on the impact of climate change on the biological response of trees and forests. Besides its application in natural forests to answer climate-change related scientific and political questions, we also envision a broader societal application of TreeWatch.net by selecting trees in nature reserves, public areas, cities, university areas, schoolyards, and parks to teach youngsters and create public awareness on the effects of changing weather conditions on trees and forests in this era of climate change.
Water-Tree Modelling and Detection for Underground Cables
Chen, Qi
In recent years, aging infrastructure has become a major concern for the power industry. Since its inception in early 20th century, the electrical system has been the cornerstone of an industrial society. Stable and uninterrupted delivery of electrical power is now a base necessity for the modern world. As the times march-on, however, the electrical infrastructure ages and there is the inevitable need to renew and replace the existing system. Unfortunately, due to time and financial constraints, many electrical systems today are forced to operate beyond their original design and power utilities must find ways to prolong the lifespan of older equipment. Thus, the concept of preventative maintenance arises. Preventative maintenance allows old equipment to operate longer and at better efficiency, but in order to implement preventative maintenance, the operators must know minute details of the electrical system, especially some of the harder to assess issues such water-tree. Water-tree induced insulation degradation is a problem typically associated with older cable systems. It is a very high impedance phenomenon and it is difficult to detect using traditional methods such as Tan-Delta or Partial Discharge. The proposed dissertation studies water-tree development in underground cables, potential methods to detect water-tree location and water-tree severity estimation. The dissertation begins by developing mathematical models of water-tree using finite element analysis. The method focuses on surface-originated vented tree, the most prominent type of water-tree fault in the field. Using the standard operation parameters of North American electrical systems, the water-tree boundary conditions are defined. By applying finite element analysis technique, the complex water-tree structure is broken down to homogeneous components. The result is a generalized representation of water-tree capacitance at different stages of development. The result from the finite element analysis
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.
Sequential and Parallel Attack Tree Modelling
Arnold, Florian; Guck, Dennis; Kumar, Rajesh; Stoelinga, Mariëlle Ida Antoinette; Koornneef, Floor; van Gulijk, Coen
The intricacy of socio-technical systems requires a careful planning and utilisation of security resources to ensure uninterrupted, secure and reliable services. Even though many studies have been conducted to understand and model the behaviour of a potential attacker, the detection of crucial
Systems analysis approach to probabilistic modeling of fault trees
International Nuclear Information System (INIS)
Bartholomew, R.J.; Qualls, C.R.
1985-01-01
A method of probabilistic modeling of fault tree logic combined with stochastic process theory (Markov modeling) has been developed. Systems are then quantitatively analyzed probabilistically in terms of their failure mechanisms including common cause/common mode effects and time dependent failure and/or repair rate effects that include synergistic and propagational mechanisms. The modeling procedure results in a state vector set of first order, linear, inhomogeneous, differential equations describing the time dependent probabilities of failure described by the fault tree. The solutions of this Failure Mode State Variable (FMSV) model are cumulative probability distribution functions of the system. A method of appropriate synthesis of subsystems to form larger systems is developed and applied to practical nuclear power safety systems
Tree Memory Networks for Modelling Long-term Temporal Dependencies
Fernando, Tharindu; Denman, Simon; McFadyen, Aaron; Sridharan, Sridha; Fookes, Clinton
2017-01-01
In the domain of sequence modelling, Recurrent Neural Networks (RNN) have been capable of achieving impressive results in a variety of application areas including visual question answering, part-of-speech tagging and machine translation. However this success in modelling short term dependencies has not successfully transitioned to application areas such as trajectory prediction, which require capturing both short term and long term relationships. In this paper, we propose a Tree Memory Networ...
Analogue model studies of induction effects at auroral latitudes
Directory of Open Access Journals (Sweden)
A. Viljanen
1995-11-01
Full Text Available In addition to field observations and numerical models, geomagnetic induction effects can be studied by scaled analogue model experiments. We present here results of analogue model studies of the auroral electrojet with an Earth model simulating the Arctic Ocean and inland conductivity structures in northern Fennoscandia. The main elements of the analogue model used were salt water simulating the host rock, an aluminium plate corresponding to the ocean and graphite pieces producing the inland highly conducting anomalies. The electrojet was a time-harmonic line current flowing at a (simulated height of 100 km above northern Fennoscandia. The period simulated was 9 min. The analogue model results confirmed the well-known rapid increase of the vertical field when the coast is approached from the continent. The increase of the horizontal field due to induced ocean currents was demonstrated above the ocean, as well as the essentially negligible effect of these currents on the horizontal field on the continent. The behaviour of the magnetic field is explained with a simple two-dimensional thin-sheet model. The range, or the adjustment distance, of the ocean effect inland was found to be some hundreds of kilometers, which also agrees with earlier results of the Siebert-Kertz separation of IMAGE magnetometer data. The modelled inland anomalies evidently had too large conductivities, but on the other hand, their influence decayed on scales of only some tens of kilometers. Analogue model results, thin-sheet calculations, and field observations show that the induction effect on the horizontal magnetic field Bx near the electrojet is negligible. On the other hand, the vertical component Bz is clearly affected by induced currents in the ocean. Evidence of this is the shift of the zero point of Bz 0-1° southwards from the maximum of Bx. The importance of these results are discussed, emphasizing the determination of ionospheric currents.
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)
Geometric Modelling of Tree Roots with Different Levels of Detail
Guerrero Iñiguez, J. I.
2017-09-01
This paper presents a geometric approach for modelling tree roots with different Levels of Detail, suitable for analysis of the tree anchoring, potentially occupied underground space, interaction with urban elements and damage produced and taken in the built-in environment. Three types of tree roots are considered to cover several species: tap root, heart shaped root and lateral roots. Shrubs and smaller plants are not considered, however, a similar approach can be considered if the information is available for individual species. The geometrical approach considers the difficulties of modelling the actual roots, which are dynamic and almost opaque to direct observation, proposing generalized versions. For each type of root, different geometric models are considered to capture the overall shape of the root, a simplified block model, and a planar or surface projected version. Lower detail versions are considered as compatibility version for 2D systems while higher detail models are suitable for 3D analysis and visualization. The proposed levels of detail are matched with CityGML Levels of Detail, enabling both analysis and aesthetic views for urban modelling.
Modelling Single Tree Structure with Terrestrial Laser Scanner
Yurtseven, H.; Akgül, M.; Gülci, S.
2017-11-01
Recent technological developments, which has reliable accuracy and quality for all engineering works, such as remote sensing tools have wide range use in forestry applications. Last decade, sustainable use and management opportunities of forest resources are favorite topics. Thus, precision of obtained data plays an important role in evaluation of current status of forests' value. The use of aerial and terrestrial laser technology has more reliable and effective models to advance the appropriate natural resource management. This study investigates the use of terrestrial laser scanner (TLS) technology in forestry, and also the methodological data processing stages for tree volume extraction is explained. Z+F Imager 5010C TLS system was used for measure single tree information such as tree height, diameter of breast height, branch volume and canopy closure. In this context more detailed and accurate data can be obtained than conventional inventory sampling in forestry by using TLS systems. However the accuracy of obtained data is up to the experiences of TLS operator in the field. Number of scan stations and its positions are other important factors to reduce noise effect and accurate 3D modelling. The results indicated that the use of point cloud data to extract tree information for forestry applications are promising methodology for precision forestry.
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.
Hierarchical models for informing general biomass equations with felled tree data
Brian J. Clough; Matthew B. Russell; Christopher W. Woodall; Grant M. Domke; Philip J. Radtke
2015-01-01
We present a hierarchical framework that uses a large multispecies felled tree database to inform a set of general models for predicting tree foliage biomass, with accompanying uncertainty, within the FIA database. Results suggest significant prediction uncertainty for individual trees and reveal higher errors when predicting foliage biomass for larger trees and for...
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.
An induction Linac driven heavy-ion fusion systems model
International Nuclear Information System (INIS)
Zuckerman, D.S.; Driemeyer, D.E.; Waganer, L.M.; Dudziak, D.J.
1988-01-01
A computerized systems model of a heavy-ion fusion (HIF) reactor power plant is presented. The model can be used to analyze the behavior and projected costs of a commercial power plant using an induction linear accelerator (Linac) as a driver. Each major component of the model (targets, reactor cavity, Linac, beam transport, power flow, balance of plant, and costing) is discussed. Various target, reactor cavity, Linac, and beam transport schemes are examined and compared. The preferred operating regime for such a power plant is also examined. The results show that HIF power plants can compete with other advanced energy concepts at the 1000-MW (electric) power level [cost of electricity (COE) -- 50 mill/kW . h] provided that the cost savings predicted for Linacs using higher charge-state ions (+3) can be realized
Populus: arabidopsis for forestry. Do we need a model tree?
Taylor, Gail
2002-12-01
Trees are used to produce a variety of wood-based products including timber, pulp and paper. More recently, their use as a source of renewable energy has also been highlighted, as has their value for carbon mitigation within the Kyoto Protocol. Relative to food crops, the domestication of trees has only just begun; the long generation time and complex nature of juvenile and mature growth forms are contributory factors. To accelerate domestication, and to understand further some of the unique processes that occur in woody plants such as dormancy and secondary wood formation, a 'model' tree is needed. Here it is argued that Populus is rapidly becoming accepted as the 'model' woody plant and that such a 'model' tree is necessary to complement the genetic resource being developed in arabidopsis. The genus Populus (poplars, cottonwoods and aspens) contains approx. 30 species of woody plant, all found in the Northern hemisphere and exhibiting some of the fastest growth rates observed in temperate trees. Populus is fulfilling the 'model' role for a number of reasons. First, and most important, is the very recent commitment to sequence the Populus genome, a project initiated in February 2002. This will be the first woody plant to be sequenced. Other reasons include the relatively small genome size (450-550 Mbp) of Populus, the large number of molecular genetic maps and the ease of genetic transformation. Populus may also be propagated vegetatively, making mapping populations immortal and facilitating the production of large amounts of clonal material for experimentation. Hybridization occurs routinely and, in these respects, Populus has many similarities to arabidopsis. However, Populus also differs from arabidopsis in many respects, including being dioecious, which makes selfing and back-cross manipulations impossible. The long time-to-flower is also a limitation, whilst physiological and biochemical experiments are more readily conducted in Populus compared with the
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.
Optimization Method of Fusing Model Tree into Partial Least Squares
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Yu Fang
2017-01-01
Full Text Available Partial Least Square (PLS can’t adapt to the characteristics of the data of many fields due to its own features multiple independent variables, multi-dependent variables and non-linear. However, Model Tree (MT has a good adaptability to nonlinear function, which is made up of many multiple linear segments. Based on this, a new method combining PLS and MT to analysis and predict the data is proposed, which build MT through the main ingredient and the explanatory variables(the dependent variable extracted from PLS, and extract residual information constantly to build Model Tree until well-pleased accuracy condition is satisfied. Using the data of the maxingshigan decoction of the monarch drug to treat the asthma or cough and two sample sets in the UCI Machine Learning Repository, the experimental results show that, the ability of explanation and predicting get improved in the new method.
A diagnostic tree model for polytomous responses with multiple strategies.
Ma, Wenchao
2018-04-23
Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students' problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students' partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM. © 2018 The British Psychological Society.
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.
MODELING SPATIAL TREE PATTERNS IN THE TAPAJÓS FOREST USING INTERFEROMETRIC HEIGHT
Directory of Open Access Journals (Sweden)
João R. dos Santos
2005-04-01
Full Text Available The spatial distribution of very large trees in primary Amazon forest is extracted from a digital model of interferometric forest height by an approach of local maximum filtering. The spatial point patterns of very large trees are modeled by a series of Markov point process models. Spatial distribution is regular, and interaction decreases with distance; very large trees are shown to exert repulsive interaction with their neighboring very large trees.
Model for the induction of bone cancer by 224Ra
International Nuclear Information System (INIS)
Groer, P.G.; Marshall, J.H.
1976-01-01
A mathematical model for the transformation of normal endosteal cells into malignant tumor cells by α irradiation is applied to 224 Ra. The model postulates that a normal endosteal cell near the bone surface is transformed into a malignant cell by three consecutive events. The first two events are the initiation events. The probability of their occurrence is proportional to the absorbed endosteal dose and they generate dormant tumor cells. These dormant tumor cells are promoted by the third event, the promotion event. The probability of this last event is proportional to the rate of bone remodeling but independent of the radiation dose. In competition with these transforming events is the killing of any endosteal cell by α irradiation. Killing is balanced by replacement of killed endosteal cells by normal stem cells. This model provides the following interesting predictions for the human 224 Ra cases: after the decay of 224 Ra the tumor rate decreases exponentially at a rate proportional to the bone turnover rate; for exposure to the same dose the model predicts an increased number of tumors for protracted exposure (i.e., exposure at a lower dose rate). Implications of this model for the therapy of ankylosing spondylitis are discussed. Statistical procedures are suggested for comparison of this theoretical model with the existing data on the induction of osteosarcomas by 224 Ra in man
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.
Tree Contractions and Evolutionary Trees
Kao, Ming-Yang
2001-01-01
An evolutionary tree is a rooted tree where each internal vertex has at least two children and where the leaves are labeled with distinct symbols representing species. Evolutionary trees are useful for modeling the evolutionary history of species. An agreement subtree of two evolutionary trees is an evolutionary tree which is also a topological subtree of the two given trees. We give an algorithm to determine the largest possible number of leaves in any agreement subtree of two trees T_1 and ...
Application of Goal Tree-Success Tree model as the knowledge-base of operator advisory systems
International Nuclear Information System (INIS)
Kim, I.S.; Modarres, M.
1987-01-01
The most important portion of an expert system development is the articulation of knowledge by the expert and its satisfactory formulation in a suitable knowledge representation scheme for mechanization by a computer. A 'deep knowledge' approach called Goal Tree-Success Tree model is devised to represent complex dynamic domain knowledge. This approach can hierarchically model the underlying principles of a given process domain (for example nuclear power plant operations domain). The Goal Tree-Success Tree can then be used to represent the knowledge-base and provide means of selecting an efficient search routine in the inference engine of an expert system. A prototype expert system has been developed to demonstrate the method. This expert system models the operation of a typical system used in the pressurized water reactors. The expert system is modeled for real-time operations if an interface between plant parameters and the expert system is established. The real-time operation provides an ability to quickly remedy minor disturbances that can quickly lead to a system malfunction or trip. A description of both the Goal Tree-Success Tree model and the prototype expert system is presented. (orig.)
Estimating and modeling charge transfer from the SAPT induction energy.
Deng, Shi; Wang, Qiantao; Ren, Pengyu
2017-10-05
Recent studies using quantum mechanics energy decomposition methods, for example, SAPT and ALMO, have revealed that the charge transfer energy may play an important role in short ranged inter-molecular interactions, and have a different distance dependence comparing with the polarization energy. However, the charge transfer energy component has been ignored in most current polarizable or non-polarizable force fields. In this work, first, we proposed an empirical decomposition of SAPT induction energy into charge transfer and polarization energy that mimics the regularized SAPT method (ED-SAPT). This empirical decomposition is free of the divergence issue, hence providing a good reference for force field development. Then, we further extended this concept in the context of AMOEBA polarizable force field, proposed a consistent approach to treat the charge transfer phenomenon. Current results show a promising application of this charge transfer model in future force field development. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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.
Modeling of urban trees' effects on reducing human exposure to UV radiation in Seoul, Korea
Hang Ryeol Na; Gordon M. Heisler; David J. Nowak; Richard H. Grant
2014-01-01
A mathematical model isconstructed for quantifying urban treesâ effects on mitigating the intensity of ultraviolet (UV) radiation on the ground within different landuse types across a city. The model is based upon local field data, meteorological data and equations designed to predict the reduced UV fraction due to trees at the ground level. Trees in Seoul, Korea (2010...
[Sectional structure of a tree. Model analysis of the vertical biomass distribution].
Galitskiĭ, V V
2010-01-01
A model has been proposed for the architecture of a tree in which virtual trees appear rhythmically on the treetop. Each consecutive virtual tree is a part of the previous tree. The difference between two adjacent virtual trees is a section--an element of the real tree structure. In case of a spruce, the section represents a verticil of a stem with the corresponding internode. Dynamics of a photosynthesizing part of the physiologically active biomass of each section differ from the corresponding dynamics of the virtual trees and the whole real tree. If the tree biomass dynamics has a sigma-shaped form, then the section dynamics have to be bell-shaped. It means that the lower stem should accordingly become bare, which is typically observed in nature. Model analysis reveals the limiting, in the age, form of trees to be an "umbrella". It can be observed in nature and is an outcome of physical limitation of the tree height combined with the sigma-shaped form of the tree biomass dynamics. Variation of model parameters provides for various forms of the tree biomass distribution along the height, which can be associated with certain biological species of trees.
A deterministic model for the growth of non-conducting electrical tree structures
International Nuclear Information System (INIS)
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 tree structures. The simulated electrical trees conform to the experimentally observed behaviour; tree length versus time and electrical tree growth rate as a function of applied voltage for non-conducting electrical trees. The phase synchronous partial discharge activity and the spatial distribution of emitted light from the tree structure are also in agreement with experimental data for non-conducting trees as grown in a flexible epoxy resin and in polyethylene. The fact that similar tree growth behaviour is found using pure amorphous (epoxy resin) and semicrystalline (polyethylene) materials demonstrate that neither annealed or quenched noise, representing material inhomogeneity, is required for the formation of irregular branched structures (electrical trees). Instead, as shown in this paper, branched growth can occur due to the instability of individual discharges within the tree structure
Exponet taper-shape models to describe tree trunks
Directory of Open Access Journals (Sweden)
Valdir Carlos Lima de Andrade
2014-12-01
Full Text Available This study evaluated exponent taper-shape models and other types applied in Brazil. Data from 270 sample trees scaled-hybrid Eucalyptus urophylla and Eucalyptus grandis were used as a studying case with 18 taper types models: simple (2, biomathematics (4, segmented (2 and exponent-form (10. It was adopted the analysis of the residual distribution and statistics: multiple linear correlation, residual standard error, percentage of no significant parcels in a completely randomized split plot and average error Dunnett, both at the level of 5% significance level. It was concluded that models of taper-shape exponents, in general, are superior to other types, the segmented model of Clark et al. is superior to Max and Burkhart biomathematics and the model developed in this paper, is better than the other biomathematics evaluated.
Multifrequency spiral vector model for the brushless doubly-fed induction machine
DEFF Research Database (Denmark)
Han, Peng; Cheng, Ming; Zhu, Xinkai
2017-01-01
This paper presents a multifrequency spiral vector model for both steady-state and dynamic performance analysis of the brushless doubly-fed induction machine (BDFIM) with a nested-loop rotor. Winding function theory is first employed to give a full picture of the inductance characteristics...... analytically, revealing the underlying relationship between harmonic components of stator-rotor mutual inductances and the airgap magnetic field distribution. Different from existing vector models, which only model the fundamental components of mutual inductances, the proposed vector model takes...
Aćimović, Srđan G; Zeng, Quan; McGhee, Gayle C; Sundin, George W; Wise, John C
2015-01-01
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 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.
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.
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...
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.
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...
Study on competitive interaction models in Cayley tree
International Nuclear Information System (INIS)
Moreira, J.G.M.A.
1987-12-01
We propose two kinds of models in the Cayley tree to simulate Ising models with axial anisotropy in the cubic lattice. The interaction in the direction of the anisotropy is simulated by the interaction along the branches of the tree. The interaction in the planes perpendicular to the anisotropy direction, in the first model, is simulated by interactions between spins in neighbour branches of the same generation arising from same site of the previous generation. In the second model, the simulation of the interaction in the planes are produced by mean field interactions among all spins in sites of the same generation arising from the same site of the previous generations. We study these models in the limit of infinite coordination number. First, we analyse a situation with antiferromagnetic interactions along the branches between first neighbours only, and we find the analogous of a metamagnetic Ising model. In the following, we introduce competitive interactions between first and second neighbours along the branches, to simulate the ANNNI model. We obtain one equation of differences which relates the magnetization of one generation with the magnetization of the two previous generations, to permit a detailed study of the modulated phase region. We note that the wave number of the modulation, for one fixed temperature, changes with the competition parameter to form a devil's staircase with a fractal dimension which increases with the temperature. We discuss the existence of strange atractors, related to a possible caothic phase. Finally, we show the obtained results when we consider interactions along the branches with three neighbours. (author)
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.
Spatially-explicit models of global tree density
Glick, Henry B.; Bettigole, Charlie; Maynard, Daniel S.; Covey, Kristofer R.; Smith, Jeffrey R.; Crowther, Thomas W.
2016-01-01
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. PMID:27529613
DEVELOPMENT OF INDIVIDUAL TREE GROWTH MODELS BASED ON DIFFERENTIAL EQUATIONS
Directory of Open Access Journals (Sweden)
Breno Rodrigues Mendes
2006-09-01
Full Text Available This study generate individual tree non-linear models from differential equation and evaluated the adjustment quality to express the basal area growth. The data base is from continuous forest inventory of clonal Eucalyptus spp. plantations, given by Aracruz Cellulose Company, located in the Brazilian costal region, Bahia and Espirito Santo states. The model precision was verified by ratio likelihood test, by mean square error (MSE and by graphical residual analysis. The results showed that the complete model with 3 parameters, developed from the original model with one regressor, was superior to the other models, due to the inclusion of stand based variables, such as: clone, total height (HT, dominant height (HD, quadratic diameter (Dg, Basal Area (G, site index (IS and Density (N, generating a new model, called Complete Model III. The improvement of the precision was highly significant when compared to another models. Consequently, this model provides information with a high degree of precision and accuracy for the forest companies planning.
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...
Directory of Open Access Journals (Sweden)
Sean M. Lamb
2018-03-01
Full Text Available A method to forecast forest inventory variables derived from light detection and ranging (LiDAR would increase the usefulness of such data in future forest management. We evaluated the accuracy of forecasted inventory from imputed tree lists for LiDAR grid cells (20 × 20 m in spruce (Picea sp. plantations and tree growth predicted using a locally calibrated tree-list growth model. Tree lists were imputed by matching measurements from a library of sample plots with grid cells based on planted species and the smallest sum of squared difference between six inventory variables. Total and merchantable basal area, total and merchantable volume, Lorey’s height, and quadratic mean diameter increments predicted using imputed tree lists were highly correlated (0.75–0.86 with those from measured tree lists in 98 validation plots. Percent root mean squared error ranged from 12.8–49.0% but was much lower (4.9–13.5% for plots with ≤10% LiDAR-derived error for all plot-matched variables. When compared with volumes from 15 blocks harvested 3–5 years after LiDAR acquisition, average forecasted volume differed by only 1.5%. To demonstrate the novel application of this method for operational management decisions, annual commercial thinning was planned at grid-cell resolution from 2018–2020 using forecasted inventory variables and commercial thinning eligibility rules.
Validation of models that predict Cesarean section after induction of labor
Verhoeven, C. J. M.; Oudenaarden, A.; Hermus, M. A. A.; Porath, M. M.; Oei, S. G.; Mol, B. W. J.
2009-01-01
Objective Models for the prediction of Cesarean delivery after induction of labor can be used to improve clinical decision-making. The objective of this study was to validate two existing models, published by Peregrine et al. and Rane et al., for the prediction of Cesarean section after induction of
The Use of Function/Means Trees for Modelling Technical, Semantic and Business Functions
DEFF Research Database (Denmark)
Robotham, Antony John
2000-01-01
This paper considers the feasibility of using the function/means tree to create a single tree for a complete motor vehicle. It is argued that function/means trees can be used for modelling technical and semantic functions, but it is an inappropriate method for business functions when one tree...... of the vehicle is required. Life cycle modelling provides an effective means for determining all the required purpose functions and is considered a more effective method than the function/means tree for this task when the structure and mode of operation of the vehicle is well defined and understood....
Wang, Jing; Li, Man; Hu, Yun-tao; Zhu, Yu
2009-09-14
In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients. Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes. After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model. ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.
Directory of Open Access Journals (Sweden)
Hu Yun-tao
2009-09-01
Full Text Available Abstract Background In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients. Methods Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes. Results After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608 and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806. The predictive ability and adaptive capacity of ANN model were better than those of decision tree model. Conclusion ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.
Being While Doing: An Inductive Model of Mindfulness at Work.
Lyddy, Christopher J; Good, Darren J
2016-01-01
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.
Dynamic Model Based Vector Control of Linear Induction Motor
2012-05-01
sensorless control is critical for LIM control in some special case. Reference [13] introduces a direct torque and flux control based on space...Industry Applications, IEEE Transactions on, vol. 28, no. 5, pp. 1054–1061, 1992. [4] J. Nash, “ Direct torque control , induction motor vector ...13] C. Lascu, I. Boldea, and F. Blaabjerg, “A modified direct torque control for induction motor sensorless drive,” Industry Applications,
Modeling effects of overstory density and competing vegetation on tree height growth
Christian Salas; Albert R. Stage; Andrew P. Robinson
2007-01-01
We developed and evaluated an individual-tree height growth model for Douglas-fir [Pseudotsuga menziesii (Mirbel) Franco] in the Inland Northwest United States. The model predicts growth for all tree sizes continuously, rather than requiring a transition between independent models for juvenile and mature growth phases. The model predicts the effects...
Model of inductive plasma production assisted by radio-frequency wave in tokamaks
International Nuclear Information System (INIS)
Hasegawa, Makoto; Hanada, Kazuaki; Sato, Kohnosuke
2007-01-01
For initial plasma production, an induction electric field generated by applying voltage to a poloidal field (PF) coil system is used to produce a Townsend avalanche breakdown. When the avalanche margins are small, as for the International Thermonuclear Experimental Reactor (ITER) in which the induction electric field is about 0.3 V/m, the assistance of radio-frequency waves (RF) is provided to reduce the induction electric field required for reliable breakdown. However, the conditions of RF-assisted breakdown are not clear. Here, the effects of both RF and induction electric field on the RF-assisted breakdown are evaluated considering the electron loss. When traveling loss is the dominant loss, a simple model of an extended Townsend avalanche is proposed. In this model, the induction electric field required for RF-assisted breakdown can be decreased to half that required for induction breakdown. (author)
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.
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.
Efficient speed control of induction motor using RBF based model reference adaptive control method
Kilic, Erdal; Ozcalik, Hasan Riza; Yilmaz, Saban
2017-01-01
This paper proposes a model reference adaptive speed controller based on artificial neural network for induction motor drives. The performance of traditional feedback controllers has been insufficient in speed control of induction motors due to nonlinear structure of the system, changing environmental conditions, and disturbance input effects. A successful speed control of induction motor requires a nonlinear control system. On the other hand, in recent years, it has been demonstrated that ar...
MODELLING AND SIMULATION OF HIGH FREQUENCY INVERTER FOR INDUCTION HEATING APPLICATION
SACHIN S. BANKAR; Dr. PRASAD M. JOSHI
2016-01-01
This paper presents modelling and simulation of high frequency inverter for induction heating applications. Induction heating has advantages like higher efficiency, controlled heating, safety and pollution free therefore this technology is used in industrial, domestic and medical applications. The high frequency full bridge inverter is used for induction heating, also MOSFET is used as a switching device for inverter and the control strategy used for inverter is Bipolar PWM control. The size ...
Allometric Models for Estimating Tree Volume and Aboveground Biomass in Lowland Forests of Tanzania
Directory of Open Access Journals (Sweden)
Wilson Ancelm Mugasha
2016-01-01
Full Text Available Models to assist management of lowland forests in Tanzania are in most cases lacking. Using a sample of 60 trees which were destructively harvested from both dry and wet lowland forests of Dindili in Morogoro Region (30 trees and Rondo in Lindi Region (30 trees, respectively, this study developed site specific and general models for estimating total tree volume and aboveground biomass. Specifically the study developed (i height-diameter (ht-dbh models for trees found in the two sites, (ii total, merchantable, and branches volume models, and (iii total and sectional aboveground biomass models of trees found in the two study sites. The findings show that site specific ht-dbh model appears to be suitable in estimating tree height since the tree allometry was found to differ significantly between studied forests. The developed general volume models yielded unbiased mean prediction error and hence can adequately be applied to estimate tree volume in dry and wet lowland forests in Tanzania. General aboveground biomass model appears to yield biased estimates; hence, it is not suitable when accurate results are required. In this case, site specific biomass allometric models are recommended. Biomass allometric models which include basic wood density are highly recommended for improved estimates accuracy when such information is available.
Tree Branching: Leonardo da Vinci's Rule versus Biomechanical Models
Minamino, Ryoko; Tateno, Masaki
2014-01-01
This study examined Leonardo da Vinci's rule (i.e., the sum of the cross-sectional area of all tree branches above a branching point at any height is equal to the cross-sectional area of the trunk or the branch immediately below the branching point) using simulations based on two biomechanical models: the uniform stress and elastic similarity models. Model calculations of the daughter/mother ratio (i.e., the ratio of the total cross-sectional area of the daughter branches to the cross-sectional area of the mother branch at the branching point) showed that both biomechanical models agreed with da Vinci's rule when the branching angles of daughter branches and the weights of lateral daughter branches were small; however, the models deviated from da Vinci's rule as the weights and/or the branching angles of lateral daughter branches increased. The calculated values of the two models were largely similar but differed in some ways. Field measurements of Fagus crenata and Abies homolepis also fit this trend, wherein models deviated from da Vinci's rule with increasing relative weights of lateral daughter branches. However, this deviation was small for a branching pattern in nature, where empirical measurements were taken under realistic measurement conditions; thus, da Vinci's rule did not critically contradict the biomechanical models in the case of real branching patterns, though the model calculations described the contradiction between da Vinci's rule and the biomechanical models. The field data for Fagus crenata fit the uniform stress model best, indicating that stress uniformity is the key constraint of branch morphology in Fagus crenata rather than elastic similarity or da Vinci's rule. On the other hand, mechanical constraints are not necessarily significant in the morphology of Abies homolepis branches, depending on the number of daughter branches. Rather, these branches were often in agreement with da Vinci's rule. PMID:24714065
Characterization of an alpine tree line using airborne LiDAR data and physiological modeling.
Coops, Nicholas C; Morsdorf, Felix; Schaepman, Michael E; Zimmermann, Niklaus E
2013-12-01
Understanding what environmental drivers control the position of the alpine tree line is important for refining our understanding of plant stress and tree development, as well as for climate change studies. However, monitoring the location of the tree line position and potential movement is difficult due to cost and technical challenges, as well as a lack of a clear boundary. Advanced remote sensing technologies such as Light Detection and Ranging (LiDAR) offer significant potential to map short individual tree crowns within the transition zone despite the lack of predictive capacity. Process-based forest growth models offer a complementary approach by quantifying the environmental stresses trees experience at the tree line, allowing transition zones to be defined and ultimately mapped. In this study, we investigate the role remote sensing and physiological, ecosystem-based modeling can play in the delineation of the alpine tree line. To do so, we utilize airborne LiDAR data to map tree height and stand density across a series of altitudinal gradients from below to above the tree line within the Swiss National Park (SNP), Switzerland. We then utilize a simple process-based model to assess the importance of seasonal variations on four climatically related variables that impose non-linear constraints on photosynthesis. Our results indicate that all methods predict the tree line to within a 50 m altitudinal zone and indicate that aspect is not a driver of significant variations in tree line position in the region. Tree cover, rather than tree height is the main discriminator of the tree line at higher elevations. Temperatures in fall and spring are responsible for the major differences along altitudinal zones, however, changes in evaporative demand also control plant growth at lower altitudes. Our results indicate that the two methods provide complementary information on tree line location and, when combined, provide additional insights into potentially endangered
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...
International Nuclear Information System (INIS)
Ko, S.; Aoki, T.; Kawabata, Y.; Takada, J.; Katayama, Y.
2003-01-01
Mn, Zn and Al concentrations of ume, sakura and sugi stems determined by ICP-MS using a simple pretreatment were compared with those determined by INAA. Considerably good agreement was obtained between the two methods. ICP-MS using simple pretreatment was found to be useful in analyzing the elements in tree stems. (author)
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.
Tree-Based Global Model Tests for Polytomous Rasch Models
Komboz, Basil; Strobl, Carolin; Zeileis, Achim
2018-01-01
Psychometric measurement models are only valid if measurement invariance holds between test takers of different groups. Global model tests, such as the well-established likelihood ratio (LR) test, are sensitive to violations of measurement invariance, such as differential item functioning and differential step functioning. However, these…
DEFF Research Database (Denmark)
Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith
2010-01-01
) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME......) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME ¼ 29.5%; N¼ 54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME¼ 31.5%; N ¼ 14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation...
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.
Effects of uncertainty in model predictions of individual tree volume on large area volume estimates
Ronald E. McRoberts; James A. Westfall
2014-01-01
Forest inventory estimates of tree volume for large areas are typically calculated by adding model predictions of volumes for individual trees. However, the uncertainty in the model predictions is generally ignored with the result that the precision of the large area volume estimates is overestimated. The primary study objective was to estimate the effects of model...
Case Study on High Dimensional Data Analysis Using Decision Tree Model
Smitha.T; V.Sundaram
2012-01-01
The major aspire of this paper is to build a model to predict the chances of occurrences of disease in an area. This paper mainly concentrating the data mining technique-Decision tree model to identify the significant parameters for prediction process. The decision tree model created with the help of ID3 algorithm.
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
Effects of lightning on trees: A predictive model based on in situ electrical resistivity.
Gora, Evan M; Bitzer, Phillip M; Burchfield, Jeffrey C; Schnitzer, Stefan A; Yanoviak, Stephen P
2017-10-01
The effects of lightning on trees range from catastrophic death to the absence of observable damage. Such differences may be predictable among tree species, and more generally among plant life history strategies and growth forms. We used field-collected electrical resistivity data in temperate and tropical forests to model how the distribution of power from a lightning discharge varies with tree size and identity, and with the presence of lianas. Estimated heating density (heat generated per volume of tree tissue) and maximum power (maximum rate of heating) from a standardized lightning discharge differed 300% among tree species. Tree size and morphology also were important; the heating density of a hypothetical 10 m tall Alseis blackiana was 49 times greater than for a 30 m tall conspecific, and 127 times greater than for a 30 m tall Dipteryx panamensis . Lianas may protect trees from lightning by conducting electric current; estimated heating and maximum power were reduced by 60% (±7.1%) for trees with one liana and by 87% (±4.0%) for trees with three lianas. This study provides the first quantitative mechanism describing how differences among trees can influence lightning-tree interactions, and how lianas can serve as natural lightning rods for trees.
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...
Model and performance of current sensor observers for a doubly fed induction generator
DEFF Research Database (Denmark)
Li, Hui; Yang, Chao; Hu, Yaogang
2014-01-01
This article presents a stator and rotor current observer for a doubly fed induction generator. First, the dynamic models of the wind turbine drive train are presented, and the vector control strategies of a doubly fed induction generator for the rotor-side and grid-side converters are described....... A stator and rotor current observer model, which is based on the state-space models of doubly fed induction generators, is then derived by using the stator and rotor voltage signals as inputs. To demonstrate the effectiveness of the proposed current observer, its dynamic performance is simulated using...... a MATLAB/Simulink software platform under the conditions of active power change of doubly fed induction generators and grid voltage dip fault. Furthermore, the robustness of the proposed current observer is investigated when the doubly fed induction generator rotor resistance is changed. Results show...
Modelling and analysis of an open-loop induction motor drive ...
Indian Academy of Sciences (India)
... study the influence of inverter dead-time on steady as well as dynamic operation of an open-loop induction motor drive fed from a voltage source inverter (VSI). Towards this goal, this paper presents a systematic derivation of a dynamic model for an inverter-fed induction motor, incorporating the effect of inverter dead-time, ...
Modelling the influence of tree removal on embankment slope hydrology
Briggs, Kevin; Smethurst, Joel; Powrie, William
2014-01-01
Trees cover the slopes of many railway earthworks supporting the UK’s transport network. Root water uptake by trees can cause seasonal shrinkage and swelling of the embankment soil, affecting the line and level of the railway track. This requires continual maintenance to maintain the serviceability of the track and reduce train speed restrictions. However, the removal of trees from railway embankment slopes and the loss of soil suctions generated by root water uptake may negatively impact emb...
Implementation of feedback-linearization-modelled induction motor ...
Indian Academy of Sciences (India)
RABI NARAYAN MISHRA
2017-11-27
Nov 27, 2017 ... single input introduced here is an error (speed and torque) instead of two inputs, error and change in error, as in the conventional NFC. ... Feedback linearization; induction motor; neuro-fuzzy controller; stationary reference frame. 1. Introduction ... replacing costly, heavy DC motor drive. However, FOC.
Evaluation of linear induction motor characteristics : the Yamamura model
1975-04-30
The Yamamura theory of the double-sided linear induction motor (LIM) excited by a constant current source is discussed in some detail. The report begins with a derivation of thrust and airgap power using the method of vector potentials and theorem of...
Implementation of feedback-linearization-modelled induction motor ...
Indian Academy of Sciences (India)
RABI NARAYAN MISHRA
2017-11-27
Nov 27, 2017 ... It is evident from the comparative results that the system performance is not deteriorated using the proposed simple NFC as compared to the conventional NFC; rather, it shows superior performance over PI-controller-based drive. Keywords. Feedback linearization; induction motor; neuro-fuzzy controller; ...
Mathematical model of five-phase induction machine
Czech Academy of Sciences Publication Activity Database
Schreier, Luděk; Bendl, Jiří; Chomát, Miroslav
2011-01-01
Roč. 56, č. 2 (2011), s. 141-157 ISSN 0001-7043 R&D Projects: GA ČR GA102/08/0424 Institutional research plan: CEZ:AV0Z20570509 Keywords : five-phase induction machines * symmetrical components * spatial wave harmonics Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering
Complex Model of Induction Heating - Demounting of Shaft Flange
Directory of Open Access Journals (Sweden)
Rostislav Vlk
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.
Modeling carbon allocation in trees: a search for principles.
Franklin, Oskar; Johansson, Jacob; Dewar, Roderick C; Dieckmann, Ulf; McMurtrie, Ross E; Brännström, Ake; Dybzinski, Ray
2012-06-01
We review approaches to predicting carbon and nitrogen allocation in forest models in terms of their underlying assumptions and their resulting strengths and limitations. Empirical and allometric methods are easily developed and computationally efficient, but lack the power of evolution-based approaches to explain and predict multifaceted effects of environmental variability and climate change. In evolution-based methods, allocation is usually determined by maximization of a fitness proxy, either in a fixed environment, which we call optimal response (OR) models, or including the feedback of an individual's strategy on its environment (game-theoretical optimization, GTO). Optimal response models can predict allocation in single trees and stands when there is significant competition only for one resource. Game-theoretical optimization can be used to account for additional dimensions of competition, e.g., when strong root competition boosts root allocation at the expense of wood production. However, we demonstrate that an OR model predicts similar allocation to a GTO model under the root-competitive conditions reported in free-air carbon dioxide enrichment (FACE) experiments. The most evolutionarily realistic approach is adaptive dynamics (AD) where the allocation strategy arises from eco-evolutionary dynamics of populations instead of a fitness proxy. We also discuss emerging entropy-based approaches that offer an alternative thermodynamic perspective on allocation, in which fitness proxies are replaced by entropy or entropy production. To help develop allocation models further, the value of wide-ranging datasets, such as FLUXNET, could be greatly enhanced by ancillary measurements of driving variables, such as water and soil nitrogen availability.
Modeled distributions of 12 tree species in New York
Rachel I. Riemann; Barry T. Wilson; Andrew J. Lister; Oren Cook; Sierra. Crane-Murdoch
2014-01-01
These maps depict the distribution of 12 tree species across the state of New York. The maps show where these trees do not occur (gray), occasionally occur (pale green), are a minor component (medium green), are a major component (dark green), or are the dominant species (black) in the forest, as determined by that species' total basal area. Basal area is the area...
Stem biomass and volume models of selected tropical tree species ...
African Journals Online (AJOL)
Estimating tree volume and biomass constitutes an essential part of the forest resources assessment and the evaluation of the climate change mitigation potential of forests through biomass accumulation and carbon sequestration. This research article provides stem volume and biomass equations applicable to five tree ...
A. Morani; D. Nowak; S. Hirabayashi; G. Guidolotti; M. Medori; V. Muzzini; S. Fares; G. Scarascia Mugnozza; C. Calfapietra
2014-01-01
Ozone flux estimates from the i-Tree model were compared with ozone flux measurements using the Eddy Covariance technique in a periurban Mediterranean forest near Rome (Castelporziano). For the first time i-Tree model outputs were compared with field measurements in relation to dry deposition estimates. Results showed generally a...
Incorporating additional tree and environmental variables in a lodgepole pine stem profile model
John C. Byrne
1993-01-01
A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements 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…
Models for estimation of tree volume in the miombo woodlands of ...
African Journals Online (AJOL)
Volume of trees is an important parameter in forest management, but only volume models with limited geographical and tree size coverage have previously been developed for Tanzanian miombo woodlands. This study developed models for estimating total, merchantable stem and branches volume applicable for the entire ...
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...
A stochastic model of nanoparticle self-assembly on Cayley trees
International Nuclear Information System (INIS)
Mazilu, I; Schwen, E M; Banks, W E; Pope, B K; Mazilu, D A
2015-01-01
Nanomedicine is an emerging area of medical research that uses innovative nanotechnologies to improve the delivery of therapeutic and diagnostic agents with maximum clinical benefit. We present a versatile stochastic model that can be used to capture the basic features of drug encapsulation of nanoparticles on tree-like synthetic polymers called dendrimers. The geometry of a dendrimer is described mathematically as a Cayley tree. We use our stochastic model to study the dynamics of deposition and release of monomers (simulating the drug molecules) on Cayley trees (simulating dendrimers). We present analytical and Monte Carlo simulation results for the particle density on Cayley trees of coordination number three and four
International Nuclear Information System (INIS)
Modarres, Mohammad; Cheon, Se Woo
1999-01-01
Most of the complex systems are formed through some hierarchical evolution. Therefore, those systems can be best described through hierarchical frameworks. This paper describes some fundamental attributes of complex physical systems and several hierarchies such as functional, behavioral, goal/condition, and event hierarchies, then presents a function-centered approach to system modeling. Based on the function-centered concept, this paper describes the joint goal tree-success tree (GTST) and the master logic diagram (MLD) as a framework for developing models of complex physical systems. A function-based lexicon for classifying the most common elements of engineering systems for use in the GTST-MLD framework has been proposed. The classification is based on the physical conservation laws that govern the engineering systems. Functional descriptions based on conservation laws provide a simple and rich vocabulary for modeling complex engineering systems
Modeling of rotational induction heating of nonmagnetic cylindrical billets
Czech Academy of Sciences Publication Activity Database
Karban, P.; Mach, F.; Doležel, Ivo
2013-01-01
Roč. 219, č. 13 (2013), s. 7170-7180 ISSN 0096-3003 Grant - others:GA ČR(CZ) GAP102/10/0216 Program:GA Institutional support: RVO:61388998 Keywords : induction heating * magnetic field * temperature field Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.600, year: 2013 http://www.journals.elsevier.com/applied-mathematics- and -computation/
Isoprene Emission Factors for Subtropical Street Trees for Regional Air Quality Modeling.
Dunn-Johnston, Kristina A; Kreuzwieser, Jürgen; Hirabayashi, Satoshi; Plant, Lyndal; Rennenberg, Heinz; Schmidt, Susanne
2016-01-01
Evaluating the environmental benefits and consequences of urban trees supports their sustainable management in cities. Models such as i-Tree Eco enable decision-making by quantifying effects associated with particular tree species. Of specific concern are emissions of biogenic volatile organic compounds, particularly isoprene, that contribute to the formation of photochemical smog and ground level ozone. Few studies have quantified these potential disservices of urban trees, and current models predominantly use emissions data from trees that differ from those in our target region of subtropical Australia. The present study aimed (i) to quantify isoprene emission rates of three tree species that together represent 16% of the inventoried street trees in the target region; (ii) to evaluate outputs of the i-Tree Eco model using species-specific versus currently used, generic isoprene emission rates; and (iii) to evaluate the findings in the context of regional air quality. Isoprene emission rates of (Myrtaceae) and (Proteaceae) were 2.61 and 2.06 µg g dry leaf weight h, respectively, whereas (Sapindaceae) was a nonisoprene emitter. We substituted the generic isoprene emission rates with these three empirical values in i-Tree Eco, resulting in a 182 kg yr (97%) reduction in isoprene emissions, totaling 6284 kg yr when extrapolated to the target region. From these results we conclude that care has to be taken when using generic isoprene emission factors for urban tree models. We recommend that emissions be quantified for commonly planted trees, allowing decision-makers to select tree species with the greatest overall benefit for the urban environment. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Corredoira, E; Ballester, A; Ibarra, M; Vieitez, A M
2015-06-01
A reproducible procedure for induction of somatic embryogenesis (SE) from adult trees of Eucalyptus globulus Labill. and the hybrid E. saligna Smith × E. maidenii has been developed for the first time. Somatic embryos were obtained from both shoot apex and leaf explants of all three genotypes evaluated, although embryogenic frequencies were significantly influenced by the species/genotype, auxin and explant type. Picloram was more efficient for somatic embryo induction than naphthaleneacetic acid (NAA), with the highest frequency of induction being obtained in Murashige and Skoog medium containing 40 µM picloram and 40 mg l(-1) gum Arabic, in which 64% of the shoot apex explants and 68.8% of the leaf explants yielded somatic embryos. The embryogenic response of the hybrid was higher than that of the E. globulus, especially when NAA was used. The cultures initiated on picloram-containing medium consisted of nodular embryogenic structures surrounded by a mucilaginous coating layer that emerged from a watery callus developed from the initial explants. Cotyledonary somatic embryos were differentiated after subculture of these nodular embryogenic structures on a medium lacking plant growth regulators. Histological analysis confirmed the bipolar organization of the somatic embryos, with shoot and root meristems and closed procambial tissue that bifurcated into small cotyledons. The root pole was more differentiated than the shoot pole, which appeared to be formed by a few meristematic layers. Maintenance of the embryogenic lines by secondary SE was attained by subculturing individual cotyledonary embryos or small clusters of globular and torpedo embryos on medium with 16.11 µM NAA at 4- to 5-week intervals. Somatic embryos converted into plantlets after being transferred to liquid germination medium although plant regeneration remained poor. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email
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.
A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.
De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David
2016-05-01
Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.
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. Copyright © 2010 John Wiley & Sons, Ltd.
Symbolic Solution Approach to Wind Turbine based on Doubly Fed Induction Generator Model
DEFF Research Database (Denmark)
Cañas–Carretón, M.; Gómez–Lázaro, E.; Martín–Martínez, S.
2015-01-01
This paper describes an alternative approach based on symbolic computations to simulate wind turbines equipped with Doubly–Fed Induction Generator (DFIG). The actuator disk theory is used to represent the aerodynamic part, and the one-mass model simulates the mechanical part. The 5th–order induct......This paper describes an alternative approach based on symbolic computations to simulate wind turbines equipped with Doubly–Fed Induction Generator (DFIG). The actuator disk theory is used to represent the aerodynamic part, and the one-mass model simulates the mechanical part. The 5th......–order induction generator is selected to model the electric machine, being this approach suitable to estimate the DFIG performance under transient conditions. The corresponding non–linear integro-differential equation system has been reduced to a linear state-space system by using an ad-hoc local linearization...
Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne
2018-01-01
Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology-light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.
Directory of Open Access Journals (Sweden)
Yi Lin
2018-02-01
Full Text Available Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology—light detection and ranging (LiDAR. Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.
Estimating tree bole volume using artificial neural network models for four species in Turkey.
Ozçelik, Ramazan; Diamantopoulou, Maria J; Brooks, John R; Wiant, Harry V
2010-01-01
Tree bole volumes of 89 Scots pine (Pinus sylvestris L.), 96 Brutian pine (Pinus brutia Ten.), 107 Cilicica fir (Abies cilicica Carr.) and 67 Cedar of Lebanon (Cedrus libani A. Rich.) trees were estimated using Artificial Neural Network (ANN) models. Neural networks offer a number of advantages including the ability to implicitly detect complex nonlinear relationships between input and output variables, which is very helpful in tree volume modeling. Two different neural network architectures were used and produced the Back propagation (BPANN) and the Cascade Correlation (CCANN) Artificial Neural Network models. In addition, tree bole volume estimates were compared to other established tree bole volume estimation techniques including the centroid method, taper equations, and existing standard volume tables. An overview of the features of ANNs and traditional methods is presented and the advantages and limitations of each one of them are discussed. For validation purposes, actual volumes were determined by aggregating the volumes of measured short sections (average 1 meter) of the tree bole using Smalian's formula. The results reported in this research suggest that the selected cascade correlation artificial neural network (CCANN) models are reliable for estimating the tree bole volume of the four examined tree species since they gave unbiased results and were superior to almost all methods in terms of error (%) expressed as the mean of the percentage errors. 2009 Elsevier Ltd. All rights reserved.
Modeled PM2.5 removal by trees in ten US cities and associated health effects
David J. Nowak; Satoshi Hirabayashi; Allison Bodine; Robert. Hoehn
2013-01-01
Urban particulate air pollution is a serious health issue. Trees within cities can remove ﬁne particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM2.5 removed annually by...
Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett
2009-01-01
Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....
Relating FIA data to habitat classifications via tree-based models of canopy cover
Mark D. Nelson; Brian G. Tavernia; Chris Toney; Brian F. Walters
2012-01-01
Wildlife species-habitat matrices are used to relate lists of species with abundance of their habitats. The Forest Inventory and Analysis Program provides data on forest composition and structure, but these attributes may not correspond directly with definitions of wildlife habitats. We used FIA tree data and tree crown diameter models to estimate canopy cover, from...
A structurally based analytic model for estimation of biomass and fuel loads of woodland trees
Robin J. Tausch
2009-01-01
Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of...
Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H
2017-10-25
Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.
Past and ongoing shifts in Joshua tree distribution support future modeled range contraction
Kenneth L. Cole; Kirsten Ironside; Jon Eischeid; Gregg Garfin; Phillip B. Duffy; Chris Toney
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...
An individual-tree basal area growth model for loblolly pine stands
Paul A. Murphy; Michael G. Shelton
1996-01-01
Tree basal area growth has been modeled as a combination of a potential growth function and a modifier function, in which the potential function is fitted separately from open-grown tree data or a subset of the data and the modifier function includes stand and site variables. We propose a modification of this by simultaneously fitting both a growth component and a...
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...
Component-based modeling of systems for automated fault tree generation
International Nuclear Information System (INIS)
Majdara, Aref; Wakabayashi, Toshio
2009-01-01
One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented
Fang, F. J.
2017-12-01
Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.
Zheng Zhao; Yaoqi Zhang; Yali Wen
2018-01-01
Urban trees are more about people than trees. Urban trees programs need public support and engagement, from the intentions to support to implement actions in supporting the programs. Built upon the theory of planned behavior and Structural Equation Modeling (SEM), this study uses Beijing as a case study to investigate how subjective norm (cognition of urban trees), attitude (benefits residents’ believe urban trees can provide), and perceived behavioral control (the believed ability of what re...
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.
The Prediction of Drought-Related Tree Mortality in Vegetation Models
Schwinning, S.; Jensen, J.; Lomas, M. R.; Schwartz, B.; Woodward, F. I.
2013-12-01
Drought-related tree die-off events at regional scales have been reported from all wooded continents and it has been suggested that their frequency may be increasing. The prediction of these drought-related die-off events from regional to global scales has been recognized as a critical need for the conservation of forest resources and improving the prediction of climate-vegetation interactions. However, there is no conceptual consensus on how to best approach the quantitative prediction of tree mortality. Current models use a variety of mechanisms to represent demographic events. Mortality is modeled to represent a number of different processes, including death by fire, wind throw, extreme temperatures, and self-thinning, and each vegetation model differs in the emphasis they place on specific mechanisms. Dynamic global vegetation models generally operate on the assumption of incremental vegetation shift due to changes in the carbon economy of plant functional types and proportional effects on recruitment, growth, competition and mortality, but this may not capture sudden and sweeping tree death caused by extreme weather conditions. We tested several different approaches to predicting tree mortality within the framework of the Sheffield Dynamic Global Vegetation Model. We applied the model to the state of Texas, USA, which in 2011 experienced extreme drought conditions, causing the death of an estimated 300 million trees statewide. We then compared predicted to actual mortality to determine which algorithms most accurately predicted geographical variation in tree mortality. We discuss implications regarding the ongoing debate on the causes of tree death.
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.
A simple model of the wind turbine induction zone derived from numerical simulations
DEFF Research Database (Denmark)
Troldborg, Niels; Meyer Forsting, Alexander Raul
2017-01-01
The induction zone in front of different wind turbine rotors is studied by means of steady-state Navier-Stokes simulations combined with an actuator disk approach. It is shown that, for distances beyond 1 rotor radius upstream of the rotors, the induced velocity is self-similar and independent of...... of the rotor geometry. On the basis of these findings, a simple analytical model of the induction zone of wind turbines is proposed....
Failed oceanic transform models: experience of shaking the tree
Gerya, Taras
2017-04-01
very same time, some pseudo-2D "side-models" with initial strait ridge and ad-hock strain weakened rheology, which were run for curiosity, suddenly showed spontaneous development of ridge curvature… Fraction of these models showed spontaneous development of orthogonal ridge-transform patterns by rotation of oblique ridge sections toward extension-parallel direction to accommodate asymmetric plate accretion. The later was controlled by detachment faults stabilized by strain weakening. Further exploration of these "side-models" resulted in complete changing of my concept for oceanic transforms: they are not plate fragmentation but rather plate growth structures stabilized by continuous plate accretion and rheological weakening of deforming rocks (Gerya, 2010, 2013). The conclusion is - keep shaking the tree and banana will fall… Gerya, T. (2010) Dynamical instability produces transform faults at mid-ocean ridges. Science, 329, 1047-1050. Gerya, T.V. (2013) Three-dimensional thermomechanical modeling of oceanic spreading initiation and evolution. Phys. Earth Planet. Interiors, 214, 35-52.
Cheaib, Alissar; Badeau, Vincent; Boe, Julien; Chuine, Isabelle; Delire, Christine; Dufrêne, Eric; François, Christophe; Gritti, Emmanuel S; Legay, Myriam; Pagé, Christian; Thuiller, Wilfried; Viovy, Nicolas; Leadley, Paul
2012-06-01
Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion. © 2012 Blackwell Publishing Ltd/CNRS.
Surgical induction of choroidal neovascularization in a porcine model
DEFF Research Database (Denmark)
Lassota, Nathan; Kiilgaard, Jens Folke; Prause, Jan Ulrik
2007-01-01
PURPOSE: To develop a reproducible surgical technique for the induction of choroidal neovascularization (CNV) in the subretinal space of porcine eyes and to analyse the resulting CNV clinically and histologically. METHODS: Two different modifications of a surgical technique previously described...... were compared with the original method. In ten porcine eyes retinal pigment epithelial (RPE) cells were removed using a silicone tipped cannula, in ten porcine eyes Bruch's membrane was perforated once with a retinal perforator without prior RPE removal and in ten eyes RPE removal was followed...... by a single perforation of Bruch's membrane. Fifteen of the eyes, five from each group, were enucleated 30 minutes after surgery, while the remaining eyes were enucleated after 14 days. Prior to enucleation, at day 14, fundus photographs and fluorescein angiograms were obtained. Eyes were examined by light...
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.
Study on reliability analysis based on multilevel flow models and fault tree method
International Nuclear Information System (INIS)
Chen Qiang; Yang Ming
2014-01-01
Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)
Mulder, Willem H; Crawford, Forrest W
2015-01-07
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. Copyright © 2014 Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Guerrier, Patrick; Tosello, Guido; Nielsen, Kaspar Kirstein
2016-01-01
Using elevated mold temperature is known to have a positive influence of final injection molded parts. Induction heating is a method that allow obtaining a rapid thermal cycle, so the overall molding cycle time is not increased. In the present research work, an integrated multi-turn induction...... heating coil has been developed and assembled into an injection molding tool provided with a glass window, so the effect of induction heating can directly be captured by a high speed camera. In addition, thermocouples and pressure sensors are also installed, and together with the high speed videos......, comparison of the induction heating and filling of the cavity is compared and validated with simulations. Two polymer materials ABS and HVPC were utilized during the injection molding experiments carried out in this work. A nonlinear electromagnetic model was employed to establish an effective linear...
A Modified Strip-Yield-Saturation-Induction Model Solution for Cracked Piezoelectromagnetic Plate
Directory of Open Access Journals (Sweden)
R. R. Bhargava
2014-01-01
Full Text Available A strip-yield-saturation-induction model is proposed for an impermeable crack embedded in piezoelectromagnetic plate. The developed slide-yield, saturation, and induction zones are arrested by distributing, respectively, mechanical, electrical, and magnetic loads over their rims. Two cases are considered: when saturation zone exceeds induction zone and vice-versa. It is assumed that developed slide-yield zone is the smallest because of the brittle nature of piezoelectromagnetic material. Fourier integral transform technique is employed to obtain the solution. Closed form analytic expressions are derived for developed zones lengths, crack sliding displacement, crack opening potential drop, crack opening induction drop, and energy release rate. Case study presented for BaTiO3–CoFe2O4 shows that crack arrest is possible under small-scale mechanical, electrical, and magnetic yielding.
An improved model to predict bandwidth enhancement in an inductively tuned common source amplifier.
Reza, Ashif; Misra, Anuraag; Das, Parnika
2016-05-01
This paper presents an improved model for the prediction of bandwidth enhancement factor (BWEF) in an inductively tuned common source amplifier. In this model, we have included the effect of drain-source channel resistance of field effect transistor along with load inductance and output capacitance on BWEF of the amplifier. A frequency domain analysis of the model is performed and a closed-form expression is derived for BWEF of the amplifier. A prototype common source amplifier is designed and tested. The BWEF of amplifier is obtained from the measured frequency response as a function of drain current and load inductance. In the present work, we have clearly demonstrated that inclusion of drain-source channel resistance in the proposed model helps to estimate the BWEF, which is accurate to less than 5% as compared to the measured results.
Propagation of action potentials along complex axonal trees. Model and implementation.
Manor, Y; Gonczarowski, J; Segev, I
1991-12-01
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).
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
Casuarina glauca: A model tree for basic research in actinorhizal ...
Indian Academy of Sciences (India)
Casuarina glauca is a fast-growing multipurpose tree belonging to the Casuarinaceae family and native to Australia. It requires limited use of chemical fertilizers due to the symbiotic association with the nitrogen-fixing actinomycete Frankia and with mycorrhizal fungi, which help improve phosphorous and water uptake by ...
On the Ising model with competing interactions on a Cayley tree: Gibbs measures, free energy
International Nuclear Information System (INIS)
Mukhamedov, Farruh; Rozikov, Utkir
2003-05-01
In the present paper the Ising model with competing binary J and J 1 interactions with spin values ± 1, on a Cayley tree is considered. We study translation-invariant Gibbs measures and corresponding free energies ones. (author)
Maria Theresa I. Cabaraban; Charles N. Kroll; Satoshi Hirabayashi; David J. Nowak
2013-01-01
A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature...
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.
3D modeling of olive tree and simulating the harvesting forces
Directory of Open Access Journals (Sweden)
Glăvan Dan Ovidiu
2017-01-01
Full Text Available The paper presents the results of the study regarding the influence of shaking forces on olive tree harvesting systems. Shaking forces can be released through several methods. Important is the end result, namely the shaking force and the cadence of shaking speed. Mechanical and automatic harvesting methods collect more olives than traditional methods but may damage the olive trees. In order to prevent this damage, we need to calculate the necessary shaking force. An original research method is proposed to simulate shaking forces using a 3D olive tree model with Autodesk Inventor software. In the experiments, we use different shaking forces and various shaking speeds. We also use different diameters of the olive tree trunk. We analyze the results from this experiment to determine the optimal shaking force for harvesting olives without damaging the olive tree.
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 ...
Baudena, Mara|info:eu-repo/dai/nl/340303867; 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
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
Gouin O'Shaughnessey, P.; Dube, M; Fernandez Villegas, I.
2016-01-01
A three-dimensional finite element model of the induction welding of carbon fiber/polyphenylene sulfide thermoplastic composites is developed. The model takes into account a stainless steel mesh heating element located at the interface of the two composite adherends to be welded. This heating
Lee, Saro; Park, Inhye
2013-09-30
Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. Copyright © 2013. Published by Elsevier Ltd.
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
Modelling Inductive Charging of Battery Electric Vehicles using an Agent-Based Approach
Directory of Open Access Journals (Sweden)
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.
Asad, Amjad; Bauer, Katrin; Chattopadhyay, Kinnor; Schwarze, Rüdiger
2018-02-01
In the paper, a new water model of the turbulent recirculating flow in an induction furnace is introduced. The water model was based on the principle of the stirred vessel used in process engineering. The flow field in the water model was measured by means of particle image velocimetry in order to verify the model's performance. Here, it is indicated that the flow consists of two toroidal vortices similar to the flow in the induction crucible furnace. Furthermore, the turbulent flow in the water model is investigated numerically by adopting eddy-resolving turbulence modeling. The two toroidal vortices occur in the simulations as well. The numerical approaches provide identical time-averaged flow patterns. Moreover, a good qualitative agreement is observed on comparing the experimental and numerical results. In addition, a numerical simulation of the melt flow in a real induction crucible furnace was performed. The turbulent kinetic energy spectrum of the flow in the water model was compared to that of the melt flow in the induction crucible furnace to show the similarity in the nature of turbulence.
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...
Generalized two axes model of a squirrel-cage induction motor for rotor fault diagnosis
Directory of Open Access Journals (Sweden)
Samir Hamdani
2008-01-01
Full Text Available A generalized two axes model of a squirrel-cage induction motor is developed This model is based on a winding function approach and the coupled magnetic circuit theory and takes into account the stator and the rotor asymmetries due to faults. This paper presents a computer simulation and experimental dynamic characteristics for a healthy induction machine, machine with one broken bar and a machine with two broken bars. The results illustrate good agreement between both simulated and experimental results. Also, the power spectral density PSD was performed to obtain a stator current spectrum.
Induction, bounding, weak combinatorial principles, and the homogeneous model theorem
Hirschfeldt, Denis R; Shore, Richard A
2017-01-01
Goncharov and Peretyat'kin independently gave necessary and sufficient conditions for when a set of types of a complete theory T is the type spectrum of some homogeneous model of T. Their result can be stated as a principle of second order arithmetic, which is called the Homogeneous Model Theorem (HMT), and analyzed from the points of view of computability theory and reverse mathematics. Previous computability theoretic results by Lange suggested a close connection between HMT and the Atomic Model Theorem (AMT), which states that every complete atomic theory has an atomic model. The authors show that HMT and AMT are indeed equivalent in the sense of reverse mathematics, as well as in a strong computability theoretic sense and do the same for an analogous result of Peretyat'kin giving necessary and sufficient conditions for when a set of types is the type spectrum of some model.
Non-Equilibrium Modeling of Inductively Coupled RF Plasmas
2015-01-01
purpose of the present work is the development of a magneto -hydrodynamic NLTE model for an ICP torch. The flow model has to be simple enough to allow... elastic collisions with heavy-particles (Ωel), (ii) in- elastic electron induced excitation, ionization and disso- ciation processes (Ωin) and (iii) Joule...sections for elastic scattering do not depend on the inter- nal quantum states. In view of the last assumption, the di- mension of the transport
[Biomass dynamics of tree branches of higher order. A model analysis].
Galitskiĭ, V V
2012-01-01
The sectional model of biomass dynamics of freely growing tree brahcnes of all orders is presented. The model is an extension of the sectional tree biomass model proposed earlier. The branches model showed bell-shaped dynamics of a branches biomass and, accordingly, boundedness of branch orders number. The important element of the model of branches system is the inter-verticil green biomass. The model is parameterized on the basis of published data on lifespan of branches of different orders and age in which the biomass of skeletal branches of spruce, Picea abies (L.) Karst, reaches the maximum. When adding known peculiarities of spruce growth (such as the initial growth inhibiton and presence of the inter-verticil branches) to the model of biomass dynamics of regular branches system, good appproximation of all natural data by model values is obtained. The possible mechanism of inter-verticil branches appearance in response to improvement of a tree growth conditions, and also their function in a tree growth process, namely replacement of regular branches incapable of appropriate response, is described. Initiation of appearing and/or waking of the sleeping (adventive) buds which give rise to inter-verticil branches is probably caused by rise of pressure of photosynthates in a tree phloem what the published results of experiments on a decapitaion of branches of Wollemia nobilis (Araucariaceae) also testify.
MRI-based decision tree model for diagnosis of biliary atresia.
Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung
2018-02-23
To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.
Numerical study of a cylinder model of the diffusion MRI signal for neuronal dendrite trees
Van Nguyen, Dang; Grebenkov, Denis; Le Bihan, Denis; Li, Jing-Rebecca
2015-03-01
We study numerically how the neuronal dendrite tree structure can affect the diffusion magnetic resonance imaging (dMRI) signal in brain tissue. For a large set of randomly generated dendrite trees, synthetic dMRI signals are computed and fitted to a cylinder model to estimate the effective longitudinal diffusivity DL in the direction of neurites. When the dendrite branches are short compared to the diffusion length, DL depends significantly on the ratio between the average branch length and the diffusion length. In turn, DL has very weak dependence on the distribution of branch lengths and orientations of a dendrite tree, and the number of branches per node. We conclude that the cylinder model which ignores the connectivity of the dendrite tree, can still be adapted to describe the apparent diffusion coefficient in brain tissue.
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.
Dong, Li-hu; Li, Feng-ri; Jia, Wei-wei; Liu, Fu-xiang; Wang, He-zhi
2011-10-01
Based on the biomass data of 516 sampling trees, and by using non-linear error-in-variable modeling approach, the compatible models for the total biomass and the biomass of six components including aboveground part, underground part, stem, crown, branch, and foliage of 15 major tree species (or groups) in Heilongjiang Province were established, and the best models for the total biomass and components biomass were selected. The compatible models based on total biomass were developed by adopting the method of joint control different level ratio function. The heteroscedasticity of the models for total biomass was eliminated with log transformation, and the weighted regression was applied to the models for each individual component. Among the compatible biomass models established for the 15 major species (or groups) , the model for total biomass had the highest prediction precision (90% or more), followed by the models for aboveground part and stem biomass, with a precision of 87.5% or more. The prediction precision of the biomass models for other components was relatively low, but it was still greater than 80% for most test tree species. The modeling efficiency (EF) values of the total, aboveground part, and stem biomass models for all the tree species (or groups) were over 0.9, and the EF values of the underground part, crown, branch, and foliage biomass models were over 0.8.
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. © 2013 Scandinavian Plant Physiology Society.
Above- and Belowground Biomass Models for Trees in the Miombo Woodlands of Malawi
Directory of Open Access Journals (Sweden)
Daud J. Kachamba
2016-02-01
Full Text Available In this study we present general (multiple tree species from several sites above- and belowground biomass models for trees in the miombo woodlands of Malawi. Such models are currently lacking in the country. The modelling was based on 74 trees comprising 33 different species with diameters at breast height (dbh and total tree height (ht ranging from 5.3 to 2 cm and from 3.0 to 25.0 m, respectively. Trees were collected from four silvicultural zones covering a wide range of conditions. We tested different models including dbh, ht and wood specific gravity ( ρ as independent variables. We evaluated model performance using pseudo-R2, root mean square error (RMSE, a covariance matrix for the parameter estimates, mean prediction error (MPE and relative mean prediction error (MPE%. Computation of MPE% was based on leave-one-out cross-validation. Values of pseudo-R2 and MPE% ranged 0.82–0.97 and 0.9%–2.8%, respectively. Model performance indicated that the models can be used over a wide range of geographical and ecological conditions in Malawi.
DEFF Research Database (Denmark)
King, Alexander Weider; Agerkvist, Finn T.
2017-01-01
Commonly used models of moving-coil loudspeaker voice coils, which include effects from eddy current losses, are either inaccurate or contain an abundance of parameters, and are difficult to extend to the nonlinear domain. On the contrary, fractional derivative models accurately describe...... order derivative approaches a value of 1, corresponding to an ideal inductance, when the voice coil is completely outside the magnetic system. Finally, the developed model reveals details about the effect of conductive voice coil formers...
Advanced modelling of doubly fed induction generator wind turbine under network disturbance
DEFF Research Database (Denmark)
Seman, S.; Iov, Florin; Niiranen, J.
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...... 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...
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...
Estimating the weight of Douglas-fir tree boles and logs with an iterative computer model.
Dale R. Waddell; Dale L Weyermann; Michael B. Lambert
1987-01-01
A computer model that estimates the green weights of standing trees was developed and validated for old-growth Douglas-fir. The model calculates the green weight for the entire bole, for the bole to any merchantable top, and for any log length within the bole. The model was validated by estimating the bias and accuracy of an independent subsample selected from the...
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...
Zinc in calcium phosphate mediates bone induction: in vitro and in vivo model
Luo, Xiaoman; Barbieri, D.; Davison, N.; Yan, Y.; de Bruijn, Joost Dick; Yuan, Huipin
2014-01-01
Zinc-containing tricalcium phosphate (Zn-TCP) was synthesized to investigate the role of zinc in osteoblastogenesis, osteoclastogenesis and in vivo bone induction in an ectopic implantation model. Zinc ions were readily released in the culture medium. Zn-TCP with the highest zinc content enhanced
Modeling and control of V/f controlled induction motor using genetic-ANFIS algorithm
International Nuclear Information System (INIS)
Ustun, Seydi Vakkas; Demirtas, Metin
2009-01-01
This paper deals with modeling and performance analysis of the voltage/frequency (V/f) control of induction motor drives. The V/f control, which realizes a low cost and simple design, is advantageous in the middle to high-speed range. Its torque response depends on the electrical time constant of the motor and adjustments of the control parameters are not need. Therefore, V/f control of induction motor is carried out. Space vector pulse width modulation is used for controlling the motor because of including minimum harmonics according to the other PWM techniques. Proportional Integral (PI) controller is used to control speed of induction motor. In this work, optimization of PI coefficients is carried out by Ziegler-Nichols model and Genetic-Adaptive Neuro-Fuzzy Inference System (ANFIS) model. These controllers are applied to drive system with 0.55 kW induction motor. A digital signal processor controller (dsPIC30F6010) is used to carry out control applications. The proposed method is compared Ziegler-Nichols model. Experimental results show the effectiveness of the proposed control method
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.
A validated model for induction heating of shape memory alloy actuators
International Nuclear Information System (INIS)
Saunders, Robert N; Boyd, James G; Hartl, Darren J; Lagoudas, Dimitris C; Brown, Jonathan K; Calkins, Frederick T
2016-01-01
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. (paper)
Global model of instabilities in low-pressure inductively coupled chlorine plasmas
Despiau-Pujo, Emilie; Chabert, Pascal
2009-10-01
Experimental studies have shown that low-pressure inductive discharges operating with electronegative gases are subject to instabilities near the transition between capacitive (E) and inductive (H) modes. A global model, consisting of two particle balance equations and one energy balance equation, has been previously proposed to describe the instability mechanism in SF6/ArSF6 [1]. This model, which agrees qualitatively well with experimental observations, leaves significant quantitative differences. In this paper, the model is revisited with Cl2 as the feedstock gas. An alternative treatment of the inductive power deposition is evaluated and chlorine chemistry is included. Old and new models are systematically compared. The alternative inductive coupling description slightly modifies the results. The effect of gas chemistry is even more pronounced. The instability window is smaller in pressure and larger in absorbed power, the frequency is higher and the amplitudes of oscillations are reduced. The feedstock gas is weakly dissociated ( 16%) and Cl2^+ is the dominant positive ion, which is consistent with the moderate electron density during the instability cycle. [1] M.A. Lieberman, A.J. Lichtenberg, and A.M. Marakhtanov, Appl. Phys. Lett. 75 (1999) 3617
A geo-information theoretical approach to inductive erosion modelling based on terrain mapping units
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
Czech Academy of Sciences Publication Activity Database
Donátová, M.; Karban, P.; Doležel, Ivo; Ulrych, B.
2009-01-01
Roč. 85, č. 4 (2009), s. 16-18 ISSN 0033-2097 R&D Projects: GA ČR(CZ) GA102/07/0496 Institutional research plan: CEZ:AV0Z20570509 Keywords : induction heating * integrodifferential model * electromagnetic field Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 0.196, year: 2009
International Nuclear Information System (INIS)
Mukhamedov, Farrukh; Saburov, Mansoor
2010-06-01
In the present paper we study forward Quantum Markov Chains (QMC) defined on a Cayley tree. Using the tree structure of graphs, we give a construction of quantum Markov chains on a Cayley tree. By means of such constructions we prove the existence of a phase transition for the XY-model on a Cayley tree of order three in QMC scheme. By the phase transition we mean the existence of two distinct QMC for the given family of interaction operators {K }. (author)
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 .
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
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...... fed induction generator system is very well represented by the dynamics due to the generator inertia and the generator control system, whereas the electromagnetic characteristics of the generator can be represented by the steady state relations. The parameters for the proposed models are derived from...... parameters typically available from the generator data sheet and from the controller settings. Thus the models are simple to apply in any case where the generator data sheet is available....
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.
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
and the proposed ABC/abc phase coordinate with varying parameters model, in the presence of external faults. The results are promising for protection and control applications of fixed speed active stall controlled wind turbines. This new approach is useful to support control and planning of wind turbines......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...... in C-code and interfaced with Matlab/Simulink through an S-Function. The investigation is conducted in the way to study the ride through capability of Squirrel Cage Induction Generators and compares the behavior of the classical DQ0 model, ABC/abc model in phase coordinate with constant parameters...
Modeling And Simulation Of Highly Advanced Multilevel Inverter For Speed Control Of Induction Motor
Directory of Open Access Journals (Sweden)
Ravi Raj
2017-02-01
Full Text Available In this Paper the problem of removing Power dissipation from single phase Induction Motor with DC sources is considered by the speed control of Induction Motor with highly advanced 9-Level multi-level Inverter which having approximate zero Harmonics. As the demand of power is increasing day by day. So that we must introduced very advanced Electrical Instruments which having high efficiency and less dissipation of power. The requirement of very advanced Inverter is necessary. Here we are designing a Multi-level Inverter up to the 9-level using IGBT Insulated-gate bipolar transistor by Mat lab which having negligible total harmonic distortion THD thats why it will control the speed of single phase Induction motor which is presently widely used in our daily needs. Also several informative Simulation results verify the authority and truthiness of the proposed Model.
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)
Modeling non-linear growth responses to temperature and hydrology in wetland trees
Keim, R.; Allen, S. T.
2016-12-01
Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.
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.
van Kuijk, Marijke; Anten, Niels P R; Oomen, Roelof J; Schieving, Feike
2014-01-01
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 had 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.
Efficient modelling of foliage distribution and crown dynamics in monolayer tree species.
Beyer, Robert
2017-12-01
In response to the computational limitations of individual leaf-based tree growth models, this article presents a new approach for the efficient characterisation of the spatial distribution of foliage in monolayered trees in terms of 2D foliage surfaces. Much like the recently introduced 3D leaf area density, this concept accommodates local crown plasticity, which is a common weak point in large-scale growth models. Recognizing phototropism as the predominant driver of spatial crown expansion, we define the local light gradient on foliage surfaces. We consider the partial differential equation describing the evolution of a curve expanding along the light gradient and present an explicit solution. The article concludes with an illustration of the incorporation of foliage surfaces in a simple tree growth model for European beech (Fagus sylvatica L.), and discusses perspectives for applications in functional-structural models.
Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree.
Kim, Jaekwon; Lee, Jongsik; Lee, Youngho
2015-07-01
The importance of the prediction of coronary heart disease (CHD) has been recognized in Korea; however, few studies have been conducted in this area. Therefore, it is necessary to develop a method for the prediction and classification of CHD in Koreans. A model for CHD prediction must be designed according to rule-based guidelines. In this study, a fuzzy logic and decision tree (classification and regression tree [CART])-driven CHD prediction model was developed for Koreans. Datasets derived from the Korean National Health and Nutrition Examination Survey VI (KNHANES-VI) were utilized to generate the proposed model. The rules were generated using a decision tree technique, and fuzzy logic was applied to overcome problems associated with uncertainty in CHD prediction. The accuracy and receiver operating characteristic (ROC) curve values of the propose systems were 69.51% and 0.594, proving that the proposed methods were more efficient than other models.
Risk Modelling of Late Spring Frost Damage on Fruit Trees, Case Study; Apple Tree, Mashhad Plain
Directory of Open Access Journals (Sweden)
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
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.
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.
Bernardes, Juliana S; Carbone, Alessandra; Zaverucha, Gerson
2011-03-23
Remote homology detection is a hard computational problem. Most approaches have trained computational models by using either full protein sequences or multiple sequence alignments (MSA), including all positions. However, when we deal with proteins in the "twilight zone" we can observe that only some segments of sequences (motifs) are conserved. We introduce a novel logical representation that allows us to represent physico-chemical properties of sequences, conserved amino acid positions and conserved physico-chemical positions in the MSA. From this, Inductive Logic Programming (ILP) finds the most frequent patterns (motifs) and uses them to train propositional models, such as decision trees and support vector machines (SVM). We use the SCOP database to perform our experiments by evaluating protein recognition within the same superfamily. Our results show that our methodology when using SVM performs significantly better than some of the state of the art methods, and comparable to other. However, our method provides a comprehensible set of logical rules that can help to understand what determines a protein function. The strategy of selecting only the most frequent patterns is effective for the remote homology detection. This is possible through a suitable first-order logical representation of homologous properties, and through a set of frequent patterns, found by an ILP system, that summarizes essential features of protein functions.
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. © 2014 John Wiley & Sons Ltd.
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.
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.
Two models for identification and predicting behaviour of an induction motor system
Kuo, Chien-Hsun
2018-01-01
System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.
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Branko Blanuša
2013-01-01
Full Text Available New hybrid model for efficiency optimization of induction motor drives (IMD is presented in this paper. It combines two strategies for efficiency optimization: loss model control and search control. Search control technique is used in a steady state of drive and loss model during transient processes. As a result, power and energy losses are reduced, especially when load torque is significant less related to its rated value. Also, this hybrid method gives fast convergence to operating point of minimal power losses and shows negligible sensitivity to motor parameter changes regarding other published optimization strategies. This model is implemented in vector control induction motor drive. Simulations and experimental tests are performed. Results are presented in this paper.
Coupled 0D-1D CFD Modeling of Right Heart and Pulmonary Artery Morphometry Tree
Dong, Melody; Yang, Weiguang; Feinstein, Jeffrey A.; Marsden, Alison
2017-11-01
Pulmonary arterial hypertension (PAH) is characterized by elevated pulmonary artery (PA) pressure and remodeling of the distal PAs resulting in right ventricular (RV) dysfunction and failure. It is hypothesized that patients with untreated ventricular septal defects (VSD) may develop PAH due to elevated flows and pressures in the PAs. Wall shear stress (WSS), due to elevated flows, and circumferential stress, due to elevated pressures, are known to play a role in vascular mechanobiology. Thus, simulating VSD hemodynamics and wall mechanics may facilitate our understanding of mechanical stimuli leading to PAH initiation and progression. Although 3D CFD models can capture detailed hemodynamics in the proximal PAs, they cannot easily model hemodynamics and wave propagation in the distal PAs, where remodeling occurs. To improve current PA models, we will present a new method that couples distal PA hemodynamics with RV function. Our model couples a 0D lumped parameter model of the RV to a 1D model of the PA tree, based on human PA morphometry data, to characterize RV performance and WSS changes in the PA tree. We will compare a VSD 0D-1D model and a 0D-3D model coupled to a mathematical morphometry tree model to quantify WSS in the entire PA vascular tree.
McNeil, Mary E.; Hood, Antonette W.; Kurtz, Patricia Y.; Thousand, Jacqueline S.; Nevin, Ann
2006-01-01
The authors examine the literature that sets the foundation for a self-actualization model for teacher induction. The model is analyzed in light of data from a successful induction program designed to keep special education teachers in the profession. (Contains 1 table and 1 figure.)
3D Analytical Model for a Tubular Linear Induction Generator in a Stirling Cogeneration System
Francois , Pierre; Garcia Burel , Isabelle; BEN AHMED , Hamid; Prevond , Laurent; Multon , Bernard
2007-01-01
International audience; This article sets forth a 3D analytical model of a tubular linear induction generator. In the intended application, the slot and edge effects as well as induced current penetration phenomena within the solid mover cannot be overlooked. Moreover, generator optimization within the present context of cogeneration has necessitated a systemic strategy. Reliance upon an analytical modeling approach that incorporates the array of typically-neglected phenomena has proven essen...
Simple Prediction of Type 2 Diabetes Mellitus via Decision Tree Modeling
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Mehrab Sayadi
2017-06-01
Full Text Available Background: Type 2 Diabetes Mellitus (T2DM is one of the most important risk factors in cardiovascular disorders considered as a common clinical and public health problem. Early diagnosis can reduce the burden of the disease. Decision tree, as an advanced data mining method, can be used as a reliable tool to predict T2DM. Objectives: This study aimed to present a simple model for predicting T2DM using decision tree modeling. Materials and Methods: This analytical model-based study used a part of the cohort data obtained from a database in Healthy Heart House of Shiraz, Iran. The data included routine information, such as age, gender, Body Mass Index (BMI, family history of diabetes, and systolic and diastolic blood pressure, which were obtained from the individuals referred for gathering baseline data in Shiraz cohort study from 2014 to 2015. Diabetes diagnosis was used as binary datum. Decision tree technique and J48 algorithm were applied using the WEKA software (version 3.7.5, New Zealand. Additionally, Receiver Operator Characteristic (ROC curve and Area Under Curve (AUC were used for checking the goodness of fit. Results: The age of the 11302 cases obtained after data preparation ranged from 18 to 89 years with the mean age of 48.1 ± 11.4 years. Additionally, 51.1% of the cases were male. In the tree structure, blood pressure and age were placed where most information was gained. In our model, however, gender was not important and was placed on the final branch of the tree. Total precision and AUC were 87% and 89%, respectively. This indicated that the model had good accuracy for distinguishing patients from normal individuals. Conclusions: The results showed that T2DM could be predicted via decision tree model without laboratory tests. Thus, this model can be used in pre-clinical and public health screening programs.
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...
Rich Interfaces for Dependability: Compositional Methods for Dynamic Fault Trees and Arcade models
Boudali, H.; Crouzen, Pepijn; Haverkort, Boudewijn R.H.M.; Kuntz, G.W.M.; Stoelinga, Mariëlle Ida Antoinette
This paper discusses two behavioural interfaces for reliability analysis: dynamic fault trees, which model the system reliability in terms of the reliability of its components and Arcade, which models the system reliability at an architectural level. For both formalisms, the reliability is analyzed
Tree root systems competing for soil moisture in a 3D soil–plant model
Gabriele Manoli; Sara Bonetti; Jean-Christophe Domec; Mario Putti; Gabriel Katul; Marco Marani
2014-01-01
Competition for water among multiple tree rooting systems is investigated using a soilâplant model that accounts for soil moisture dynamics and root water uptake (RWU), whole plant transpiration, and leaflevel photosynthesis. The model is based on a numerical solution to the 3D Richards equation modified to account for a 3D RWU, trunk xylem, and stomatal conductances....
New efficient utility upper bounds for the fully adaptive model of attack trees
Buldas, Ahto; Lenin, Aleksandr
2013-01-01
We present a new fully adaptive computational model for attack trees that allows attackers to repeat atomic attacks if they fail and to play on if they are caught and have to pay penalties. The new model allows safer conclusions about the security of real-life systems and is somewhat
Compilation of information on modeling of inductively heated cold crucible melters
International Nuclear Information System (INIS)
Lessor, D.L.
1996-03-01
The objective of this communication, Phase B of a two-part report, is to present information on modeling capabilities for inductively heated cold crucible melters, a concept applicable to waste immobilization. Inductively heated melters are those in which heat is generated using coils around, rather than electrodes within, the material to be heated. Cold crucible or skull melters are those in which the melted material is confined within unmelted material of the same composition. This phase of the report complements and supplements Phase A by Loren Eyler, specifically by giving additional information on modeling capabilities for the inductively heated melter concept. Eyler discussed electrically heated melter modeling capabilities, emphasizing heating by electrodes within the melt or on crucible walls. Eyler also discussed requirements and resources for the computational fluid dynamics, heat flow, radiation effects, and boundary conditions in melter modeling; the reader is referred to Eyler's discussion of these. This report is intended for use in the High Level Waste (HLW) melter program at Hanford. We sought any modeling capabilities useful to the HLW program, whether through contracted research, code license for operation by Department of Energy laboratories, or existing codes and modeling expertise within DOE
Hipsometric relationship modeling using data sampled in tree scaling and inventory plots
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Valdir Carlos Lima de Andrade
2011-02-01
Full Text Available This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, residual standard error between real and estimated heights and the graybill f test were adopted. The identity of the hypsometric models was also verified by applying the F(Ho test on the plot data grouped to the scaling data. It was concluded that better accuracy can be obtained by using the model prodan, with h and d1,3 data measured in 10 trees by plots grouped into these scaling data measurements of even-aged forest stands.
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.
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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.
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X. Zhou
2017-12-01
Full Text Available Forest plantations have been widely used as an effective measure for increasing soil carbon (C, and nitrogen (N stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species–enzyme–C∕N model to investigate how temperature and tree species influence soil C∕N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG, N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP and phosphorus acquisition enzymes (acid phosphatases. The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01–2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99–2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii and hoop pine (Araucaria cunninghamii Ait., increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22–1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native
Zhou, Xiaoqi; Wang, Shen S. J.; Chen, Chengrong
2017-12-01
Forest plantations have been widely used as an effective measure for increasing soil carbon (C), and nitrogen (N) stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA) to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species-enzyme-C/N model to investigate how temperature and tree species influence soil C/N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG), N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) and phosphorus acquisition enzymes (acid phosphatases). The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01-2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99-2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii) and hoop pine (Araucaria cunninghamii Ait.), increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22-1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native coniferous tree species like hoop pine and
Event and fault tree model for reliability analysis of the greek research reactor
International Nuclear Information System (INIS)
Fault trees and event trees are widely used in industry to model and to evaluate the reliability of safety systems. Detailed analyzes in nuclear installations require the combination of these two techniques. This work uses the methods of fault tree (FT) and event tree (ET) to perform the Probabilistic Safety Assessment (PSA) in research reactors. The PSA according to IAEA (International Atomic Energy Agency) is divided into Level 1, Level 2 and level 3. At Level 1, conceptually safety systems act to prevent the accident, at Level 2, the accident occurred and seeks to minimize the consequences, known as stage management of the accident, and at Level 3 are determined consequences. This paper focuses on Level 1 studies, and searches through the acquisition of knowledge consolidation of methodologies for future reliability studies. The Greek Research Reactor, GRR - 1, was used as a case example. The LOCA (Loss of Coolant Accident) was chosen as the initiating event and from there were developed the possible accident sequences, using event tree, which could lead damage to the core. Furthermore, for each of the affected systems, the possible accidents sequences were made fault tree and evaluated the probability of each event top of the FT. The studies were conducted using a commercial computational tool SAPHIRE. The results thus obtained, performance or failure to act of the systems analyzed were considered satisfactory. This work is directed to the Greek Research Reactor due to data availability. (author)
Modelling Water Uptake Provides a New Perspective on Grass and Tree Coexistence.
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Michael G Mazzacavallo
Full Text Available 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.
Predictive models of tree-growth: preliminary results in the French Alps
Tessier, Lucien; Keller, Thierry; Guiot, Joel; Edouard, Jean-Louis; Guibal, Frédéric
The analysis of tree-ring-climate relationships provides models (response functions) of tree-growth calibrated on the inter-annual variability of climate. Output of GCMs can be used as inputs of these models in order to evaluate the change in radial growth induced by climatic change. A spatiotemporal approach applied to a large data set of ring-width chronologies and meteorological data allows the response of trees to be evaluated for different populations of various species in numerous habitats. Such a study was carried out, firstly on ten populations in south-eastern France, then on populations at high-altitude sites. The species involved were Larix decidua, Mill., Pinus sylvestris, L., Abies alba, Mill., and Picea abies Karst. The calibration of tree ring to climate relationships was based on the monthly values of precipitation and temperature provided by meteorological stations more or less distant from the tree sites. Outputs of GCMs were obtained from the ARPEGE model of Météo-France with a simulation on a large grid (2°79 in latitude and 3° in longitude) for the hypothesis of a CO2 doubling. Results show that climatic change can induce either an increase or a decrease in the mean radial growth. For most of the tree-populations, no significant change was apparent. The results suffer from insufficient data related to the spatial representation of climate (i.e. stations that are too far from the tree populations, only two grid points available from the GCMs, etc.).
Lee, Seung-Mi; Kang, Jin-Oh; Suh, Yong-Moo
2004-10-01
Analysis and prediction of the care charges related to colorectal cancer in Korea are important for the allocation of medical resources and the establishment of medical policies because the incidence and the hospital charges for colorectal cancer are rapidly increasing. But the previous studies based on statistical analysis to predict the hospital charges for patients did not show satisfactory results. Recently, data mining emerges as a new technique to extract knowledge from the huge and diverse medical data. Thus, we built models using data mining techniques to predict hospital charge for the patients. A total of 1,022 admission records with 154 variables of 492 patients were used to build prediction models who had been treated from 1999 to 2002 in the Kyung Hee University Hospital. We built an artificial neural network (ANN) model and a classification and regression tree (CART) model, and compared their prediction accuracy. Linear correlation coefficients were high in both models and the mean absolute errors were similar. But ANN models showed a better linear correlation than CART model (0.813 vs. 0.713 for the hospital charge paid by insurance and 0.746 vs. 0.720 for the hospital charge paid by patients). We suggest that ANN model has a better performance to predict charges of colorectal cancer patients.
Electrical Activity in a Time-Delay Four-Variable Neuron Model under Electromagnetic Induction
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Keming Tang
2017-11-01
Full Text Available To investigate the effect of electromagnetic induction on the electrical activity of neuron, the variable for magnetic flow is used to improve Hindmarsh–Rose neuron model. Simultaneously, due to the existence of time-delay when signals are propagated between neurons or even in one neuron, it is important to study the role of time-delay in regulating the electrical activity of the neuron. For this end, a four-variable neuron model is proposed to investigate the effects of electromagnetic induction and time-delay. Simulation results suggest that the proposed neuron model can show multiple modes of electrical activity, which is dependent on the time-delay and external forcing current. It means that suitable discharge mode can be obtained by selecting the time-delay or external forcing current, which could be helpful for further investigation of electromagnetic radiation on biological neuronal system.
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.
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.
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.
Proxy system modeling of tree-ring isotope chronologies over the Common Era
Anchukaitis, K. J.; LeGrande, A. N.
2017-12-01
The Asian monsoon can be characterized in terms of both precipitation variability and atmospheric circulation across a range of spatial and temporal scales. While multicentury time series of tree-ring widths at hundreds of sites across Asia provide estimates of past rainfall, the oxygen isotope ratios of annual rings may reveal broader regional hydroclimate and atmosphere-ocean dynamics. Tree-ring oxygen isotope chronologies from Monsoon Asia have been interpreted to reflect a local 'amount effect', relative humidity, source water and seasonality, and winter snowfall. Here, we use an isotope-enabled general circulation model simulation from the NASA Goddard Institute for Space Science (GISS) Model E and a proxy system model of the oxygen isotope composition of tree-ring cellulose to interpret the large-scale and local climate controls on δ 18O chronologies. Broad-scale dominant signals are associated with a suite of covarying hydroclimate variables including growing season rainfall amounts, relative humidity, and vapor pressure deficit. Temperature and source water influences are region-dependent, as are the simulated tree-ring isotope signals associated with the El Nino Southern Oscillation (ENSO) and large-scale indices of the Asian monsoon circulation. At some locations, including southern coastal Viet Nam, local precipitation isotope ratios and the resulting simulated δ 18O tree-ring chronologies reflect upstream rainfall amounts and atmospheric circulation associated with monsoon strength and wind anomalies.
Irrgang, C.; Saynisch, J.; Thomas, M.
2016-01-01
Carrying high concentrations of dissolved salt, ocean water is a good electrical conductor. As seawater flows through the Earth's ambient geomagnetic field, electric fields are generated, which in turn induce secondary magnetic fields. In current models for ocean-induced magnetic fields, a realistic consideration of seawater conductivity is often neglected and the effect on the variability of the ocean-induced magnetic field unknown. To model magnetic fields that are induced by non-tidal global ocean currents, an electromagnetic induction model is implemented into the Ocean Model for Circulation and Tides (OMCT). This provides the opportunity to not only model ocean-induced magnetic signals but also to assess the impact of oceanographic phenomena on the induction process. In this paper, the sensitivity of the induction process due to spatial and temporal variations in seawater conductivity is investigated. It is shown that assuming an ocean-wide uniform conductivity is insufficient to accurately capture the temporal variability of the magnetic signal. Using instead a realistic global seawater conductivity distribution increases the temporal variability of the magnetic field up to 45 %. Especially vertical gradients in seawater conductivity prove to be a key factor for the variability of the ocean-induced magnetic field. However, temporal variations of seawater conductivity only marginally affect the magnetic signal.
Modeling the temporal dynamics of nonstructural carbohydrate pools in forest trees
Energy Technology Data Exchange (ETDEWEB)
Richardson, Andrew [Northern Arizona Univ., Flagstaff, AZ (United States); Harvard Univ., Cambridge, MA (United States)
2017-11-09
Trees store carbohydrates, in the form of sugars and starch, as reserves to be used to power both future growth as well as to support day-to-day metabolic functions. These reserves are particularly important in the context of how trees cope with disturbance and stress—for example, as related to pest outbreaks, wind or ice damage, and extreme climate events. In this project, we measured the size of carbon reserves in forest trees, and determined how quickly these reserves are used and replaced—i.e., their “turnover time”. Our work was conducted at Harvard Forest, a temperate deciduous forest in central Massachusetts. Through field sampling, laboratory-based chemical analyses, and allometric modeling, we scaled these measurements up to whole-tree NSC budgets. We used these data to test and improve computer simulation models of carbon flow through forest ecosystems. Our modeling focused on the mathematical representation of these stored carbon reserves, and we examined the sensitivity of model performance to different model structures. This project contributes to DOE’s goal to improve next-generation models of the earth system, and to understand the impacts of climate change on terrestrial ecosystems.
MB3-Miner: efficiently mining eMBedded subTREEs using Tree Model Guided candidate generation
Tan, H.; Dillon, T.; Hadzic, F.; Chang, E.; Feng, L.
2005-01-01
Tree mining has many useful applications in areas such as Bioinformatics, XML mining, Web mining, etc. In general, most of the formally represented information in these domains is a tree structured form. In this paper we focus on mining frequent embedded subtrees from databases of rooted labeled
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.
Rahmati, Mitra; Mirás-Avalos, José M; Valsesia, Pierre; Lescourret, Françoise; Génard, Michel; Davarynejad, Gholam H; Bannayan, Mohammad; Azizi, Majid; Vercambre, Gilles
2018-01-01
Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree) was adapted for describing the water stress effects on peach ( Prunus persica L. Batsch) vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar ("Elberta") under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on its sink strength
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Mitra Rahmati
2018-01-01
Full Text Available Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree was adapted for describing the water stress effects on peach (Prunus persica L. Batsch vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar (“Elberta” under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on
Allometric models for aboveground biomass of ten tree species in northeast China
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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.
Hydrodynamics of isohydric and anisohydric trees: insights from models and measurements
Novick, K. A.; Oishi, A. C.; Roman, D. T.; Benson, M. C.; Miniat, C.
2016-12-01
In an effort to understand and predict the mechanisms that govern tree response to hydrologic stress, plant hydraulic theory, which classifies trees along a continuum of isohydric to anisohydric water use strategies, is increasingly being used. Isohydry maintains relatively constant leaf water potential during periods of water stress, promoting wide hydraulic safety margins that reduce the risk of xylem cavitation. In contrast, anisohydry allows leaf water potential to fall as soil water potential falls, but in doing so trees incur a greater risk of hydraulic failure. As a result, unique patterns of stomatal functioning between isohydric and anisohydric species are both predicted and observed in leaf-, tree-, and stand-level water use. We use a novel model formulation to examine the dynamics of three mechanisms that are potentially limiting to leaf-level gas exchange in trees during drought: (1) a `demand limitation' driven by an assumption of stomatal optimization of water loss and carbon uptake; (2) `hydraulic limitation' of water movement from the roots to the leaves; and (3) `non-stomatal' limitations imposed by declining leaf water status within the leaf. Model results suggest that species-specific `economics' of stomatal behavior may play an important role in differentiating species along the continuum of isohydric to anisohydric behavior; specifically, we show that non-stomatal and demand limitations may reduce stomatal conductance and increase leaf water potential, promoting wide safety margins characteristic of isohydric species. Direct comparisons of modeled and measured stomatal conductance further indicated that non-stomatal and demand limitations reproduced observed patterns of tree water use well for an isohydric species but that a hydraulic limitation likely applies in the case of an anisohydric species. This modeling framework used in concert with climate data may help land managers and scientists predict when and what forest species and communities
Modeling of squirrel induction machine by modified magnetic equivalent circuit approach
International Nuclear Information System (INIS)
Milimonfared, J.; Meshgin Kelk, H.
2002-01-01
In this paper a modified magnetic equivalent circuit approach is presented for steady state and transient analysis of squirrel cage induction motor. The effects of all spatial harmonics, stator and rotor tooth reluctance, saturation effects, rotor skewing, air gap permanencies and leakage perveance of slots, and type of winging connection are taken into account. Since there is no restriction on stator winding, rotor bar and air gap length symmetry this approach is able to model the induction motor under both healthy and faulty conditions. In the proposed model, by considering the actual dimensions of stator and rotor laminations, some simplifications have been considered. Hence, the number of variables in the system of algebraic of the system of algebraic equations improves and this leads to better convergence of numerical solution
Energy Technology Data Exchange (ETDEWEB)
Nemmour, A.L.; Khezzar, A.; Hacil, M.; Louze, L. [Laboratoire d' Electrotechnique LEC, Universite Mentouri, Constantine (Algeria); Mehazzem, F. [Groupe ESIEE, Paris Est University (France); Abdessemed, R. [Laboratoire d' Electrotechnique LEB, Universite El Hadj Lakhdar, Batna (Algeria)
2010-10-15
This paper presents a new non-linear control Algorithm based on the Backstepping approach for an isolated induction generator (IG) driven by a wind turbine. For this purpose and in order to reduce the complexity of the real induction machine mathematical model, the multi-scalar machine model is exploited. The machine delivers an active power to the load via a converter connected to a single capacitor on the dc-side. So, during the voltage build-up process, the necessary stator currents references to be injected by the converter are calculated from the desired active power to be sent to the load and the rotor flux magnitude. Simulation results show that the proposed control provides perfect tracking performances of the DC-bus voltage and the rotor flux magnitude to their reference trajectories. (author)
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.
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
International Nuclear Information System (INIS)
Kirillov, I.R.; Obukhov, D.M.
2005-01-01
One introduces a completely two-dimensional mathematical model to calculate characteristics of induction magnetohydrodynamic (MHD) machines with a cylindrical channel. On the basis of the numerical analysis one obtained a pattern of liquid metal flow in a electromagnetic pump at presence of the MHD-instability characterized by initiation of large-scale vortices propagating longitudinally and azimuthally. Comparison of the basic calculated characteristics of pump with the experiment shows their adequate qualitative and satisfactory quantitative coincidence [ru
MODELING DEEP BAR INDUCTION MOTORS FOR SUGAR FACTORY ELECTRICAL POWER SUPPLY SYSTEMS
Korobeinikov B. A.; Ishtchenko A. I.; Smagliev A. M.; Olyshanskaya I. V.
2016-01-01
The article is devoted to solving the urgent task, which is improving the accuracy of transient simulation modes of power supply systems of sugar factories. The material of the article is exploratory in nature, manifested in the fact that we have studied various mathematical models designed for the analysis of symmetric modes of deep bar induction motors. A number of the provisions of article have scientific novelty, which lies in the approach to the choice of the coordinate system for modeli...
A Tightly Coupled Non-Equilibrium Magneto-Hydrodynamic Model for Inductively Coupled RF Plasmas
2016-02-29
Journal Article 3. DATES COVERED (From - To) 12 May 2015 – 06 Oct 2015 4. TITLE AND SUBTITLE A Tightly Coupled Non- Equilibrium Magneto-Hydrodynamic...development a tightly coupled magneto-hydrodynamic model for Inductively Coupled Radio- Frequency (RF) Plasmas. Non Local Thermodynamic Equilibrium (NLTE...effects are described based on a hybrid State-to-State (StS) approach. A multi-temperature formulation is used to account for thermal non- equilibrium
Numerical modeling of a small recirculating induction accelerator for heavy-ion fusion
International Nuclear Information System (INIS)
Sharp, W.M.; Barnard, J.J.; Friedman, A.; Grote, D.P.; Lund, S.M.; Newton, M.A.; Fessenden, T.J.; Yu, S.S.
1994-01-01
A series of small-scale experiments has been proposed to study critical physics issues of a circular induction accelerator for heavy-ion fusion. Because the beam dynamics will be dominated by space charge, the experiments require careful design of the lattice and acceleration schedule. A hierarchy of codes has been developed for modeling the experiments at different levels of detail. The codes are discussed briefly, and examples of the output are presented
Ottolenghi, A.; Ballarini, F.; Biaggi, M.
Several advances have been achieved in the knowledge of nuclear architecture and functions during the last decade, thus allowing the identification of interphase chromosome territories and sub-chromosomal domains (e.g. arm and band domains). This is an important step in the study of radiation-induced chromosome aberrations; indeed, the coupling between track-structure simulations and reliable descriptions of the geometrical properties of the target is one of the main tasks in modelling aberration induction by radiation, since it allows one to clarify the role of the initial positioning of two DNA lesions in determining their interaction probability. In the present paper, the main recent findings on nuclear and chromosomal architecture are summarised. A few examples of models based on different descriptions of interphase chromosome organisation (random-walk models, domain models and static models) are presented, focussing on how the approach adopted in modelling the target nuclei and chromosomes can influence the simulation of chromosomal aberration yields. Each model is discussed by taking into account available experimental data on chromosome aberration induction and/or interphase chromatin organisation. Preliminary results from a mechanistic model based on a coupling between radiation track-structure features and explicitly-modelled, non-overlapping chromosome territories are presented.
Modeling and analysis of variable speed single phase induction motors with iron loss
International Nuclear Information System (INIS)
Vaez-Zadeh, S.; Zahedi, B.
2009-01-01
Despite their usual low power ratings of single phase induction motors, they consume a considerable part of total motors energy consumption due to their large and ever-increasing quantity. The recent rising of oil prices and environmental crises has fortified the idea of energy saving practices in all applications; particularly in single phase induction motors due to their typical low efficiency. An essential requirement for this practice is the modeling and analysis of machine electrical losses under variable frequency operation. In this paper an improved steady state model of single phase induction motors is derived to investigate major motor characteristics like torque-speed, input power, output power, etc. A special emphasis is placed on accurately representing core losses at variable frequency. The winding currents phase difference is reintroduced as a fundamental motor variable to determine motor performances including losses and efficiency. An advanced computerized motor test setup is designed and built for on-line measurement of motor characteristics at different supply and operating conditions. The extensive experimental results, in good agreement with the simulation results based on the mentioned analysis, confirm the validity of the proposed model.
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.
Modeling and Simulation of a Wind Turbine Driven Induction Generator Using Bond Graph
Directory of Open Access Journals (Sweden)
Lachouri Abderrazak
2015-12-01
Full Text Available The objective of this paper is to investigate the modelling and simulation of wind turbine applied on induction generator with bond graph methodology as a graphical and multi domain approach. They provide a precise and unambiguous modelling tool, which allows for the specification of hierarchical physical structures. The paper begins with an introduction to the bond graphs technique, followed by an implementation of the wind turbine model. Simulation results illustrate the simplified system response obtained using the 20-sim software.
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.
Yield curve event tree construction for multi stage stochastic programming models
DEFF Research Database (Denmark)
Rasmussen, Kourosh Marjani; Poulsen, Rolf
Dynamic stochastic programming (DSP) provides an intuitive framework for modelling of financial portfolio choice problems where market frictions are present and dynamic re--balancing has a significant effect on initial decisions. The application of these models in practice, however, is limited by...... of yield curves. Such trees may then be used to represent the underlying uncertainty in DSP models of fixed income risk and portfolio management....
Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model
2014-09-01
Penelope Morgan. 2006. “Regression Modeling and Mapping of Coniferous Forest Basal Area and Tree Density from Discrete- Return LIDAR and... Basal Area Relationships of Open-Grown Southern Pines for Modeling Competition and Growth.” Canadian Journal of of Forest Research 22: 341–347... Forest Growth and Yield Model Co ns tr uc tio n En gi ne er in g R es ea rc h La bo ra to ry Scott A. Tweddale, Patrick J. Guertin, and
Multiobjective Optimization for the Forecasting Models on the Base of the Strictly Binary Trees
Nadezhda Astakhova; Liliya Demidova; Evgeny Nikulchev
2016-01-01
The optimization problem dealing with the development of the forecasting models on the base of strictly binary trees has been considered. The aim of paper is the comparative analysis of two optimization variants which are applied for the development of the forecasting models. Herewith the first optimization variant assumes the application of one quality indicator of the forecasting model named as the affinity indicator and the second variant realizes the application of two quality indicators ...
Assessing the Cooling Benefits of Tree Shade by an Outdoor Urban Physical Scale Model at Tempe, AZ
Directory of Open Access Journals (Sweden)
Qunshan Zhao
2018-01-01
Full Text Available Urban green infrastructure, especially shade trees, offers benefits to the urban residential environment by mitigating direct incoming solar radiation on building facades, particularly in hot settings. Understanding the impact of different tree locations and arrangements around residential properties has the potential to maximize cooling and can ultimately guide urban planners, designers, and homeowners on how to create the most sustainable urban environment. This research measures the cooling effect of tree shade on building facades through an outdoor urban physical scale model. The physical scale model is a simulated neighborhood consisting of an array of concrete cubes to represent houses with identical artificial trees. We tested and compared 10 different tree densities, locations, and arrangement scenarios in the physical scale model. The experimental results show that a single tree located at the southeast of the building can provide up to 2.3 °C hourly cooling benefits to east facade of the building. A two-tree cluster arrangement provides more cooling benefits (up to 6.6 °C hourly cooling benefits to the central facade when trees are located near the south and southeast sides of the building. The research results confirm the cooling benefits of tree shade and the importance of wisely designing tree locations and arrangements in the built environment.
Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris
2016-09-01
Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have
Modeling transcriptional networks regulating secondary growth and wood formation in forest trees
Lijun Liu; Vladimir Filkov; Andrew Groover
2013-01-01
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...
The Statistical Analysis of General Processing Tree Models with the EM Algorithm.
Hu, Xiangen; Batchelder, William H.
1994-01-01
The statistical analysis of processing tree models is advanced by showing how the parameters of estimation and hypothesis testing, based on the likelihood functions, can be accomplished by adapting the expectation-maximization (EM) algorithm. The adaptation makes it easy to program a personal computer to accomplish the stages of statistical…
International Nuclear Information System (INIS)
Koh, Kwang Yong; Seong, Poong Hyun
2010-01-01
Fault tree analysis (FTA) has suffered from several drawbacks such that it uses only static gates and hence can not capture dynamic behaviors of the complex system precisely, and it is in lack of rigorous semantics, and reasoning process which is to check whether basic events really cause top events is done manually and hence very labor-intensive and time-consuming for the complex systems while it has been one of the most widely used safety analysis technique in nuclear industry. Although several attempts have been made to overcome this problem, they can not still do absolute or actual time modeling because they adapt relative time concept and can capture only sequential behaviors of the system. 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
Theory and Programs for Dynamic Modeling of Tree Rings from Climate
Paul C. van Deusen; Jennifer Koretz
1988-01-01
Computer programs written in GAUSS(TM) for IBM compatible personal computers are described that perform dynamic tree ring modeling with climate data; the underlying theory is also described. The programs and a separate users manual are available from the authors, although users must have the GAUSS software package on their personal computer. An example application of...
Modeling potential climate change impacts on the trees of the northeastern United States
Louis Iverson; Anantha Prasad; Stephen Matthews
2008-01-01
We evaluated 134 tree species from the eastern United States for potential response to several scenarios of climate change, and summarized those responses for nine northeastern United States. We modeled and mapped each species individually and show current and potential future distributions for two emission scenarios (A1fi [higher emission] and B1 [lower emission]) and...
A tree-based method to price American options in the Heston model
Vellekoop, M.; Nieuwenhuis, H.
2009-01-01
We develop an algorithm to price American options on assets that follow the stochastic volatility model defined by Heston. We use an approach which is based on a modification of a combined tree for stock prices and volatilities, where the number of nodes grows quadratically in the number of time
A quasi-steady state shrinking core model of "whole tree" combustion
African Journals Online (AJOL)
Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. A quasi-steady state shrinking core model of "whole tree" combustion. A. Ouédraogo, JC Mulligan, JG Cleland. Abstract. (J. de la Recherche Scientifique de l'Université de Lomé, 2000, 4(2): 199-208) ...
Generic linear mixed-effects individual-tree biomass models for ...
African Journals Online (AJOL)
Quantification of forest biomass is important for practical forestry and for scientific purposes. It is fundamental to develop generic individual-tree biomass models suitable for large-scale forest biomass estimation. However, compatibility of forest biomass estimates at different scales may become a problem. We developed ...
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
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
Lapp, M S; Malinek, J; Coffey, M
1996-04-01
We developed a protocol for the production of shoots from bud explants from 1- to 7-year-old trees of western white pine (Pinus monticola Dougl.). The best explant was a 2-mm-thick cross-sectional slice of the early winter bud. Genotype of the donor tree was a significant factor affecting shoot production, but more than 80% of the genotypes tested produced shoots. Of the media tested, bud slices from 1- to 3-year-old trees grew best in Litvay's medium containing N(6)-benzyladenine in the range of 1 to 30 micro M, whereas bud slices from older trees grew best in Gupta and Durzan's DCR medium with zeatin riboside. Up to 400 shoots more than 3 mm in height were obtained from 100 bud-slice explants taken from 7-year-old western white pine trees.
Decision tree based knowledge acquisition and failure diagnosis using a PWR loop vibration model
International Nuclear Information System (INIS)
Bauernfeind, V.; Ding, Y.
1993-01-01
An analytical vibration model of the primary system of a 1300 MW PWR was used for simulating mechanical faults. Deviations in the calculated power density spectra and coherence functions are determined and classified. The decision tree technique is then used for a personal computer supported knowledge presentation and for optimizing the logical relationships between the simulated faults and the observed symptoms. The optimized decision tree forms the knowledge base and can be used to diagnose known cases as well as to include new data into the knowledge base if new faults occur. (author)
A model for the inverse 1-median problem on trees under uncertain costs
Directory of Open Access Journals (Sweden)
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.
Tandon, K.; Egbert, G.; Siripunvaraporn, W.
2003-12-01
We are developing a modular system for three-dimensional inversion of electromagnetic (EM) induction data, using an object oriented programming approach. This approach allows us to modify the individual components of the inversion scheme proposed, and also reuse the components for variety of problems in earth science computing howsoever diverse they might be. In particular, the modularity allows us to (a) change modeling codes independently of inversion algorithm details; (b) experiment with new inversion algorithms; and (c) modify the way prior information is imposed in the inversion to test competing hypothesis and techniques required to solve an earth science problem. Our initial code development is for EM induction equations on a staggered grid, using iterative solution techniques in 3D. An example illustrated here is an experiment with the sensitivity of 3D magnetotelluric inversion to uncertainties in the boundary conditions required for regional induction problems. These boundary conditions should reflect the large-scale geoelectric structure of the study area, which is usually poorly constrained. In general for inversion of MT data, one fixes boundary conditions at the edge of the model domain, and adjusts the earth?s conductivity structure within the modeling domain. Allowing for errors in specification of the open boundary values is simple in principle, but no existing inversion codes that we are aware of have this feature. Adding a feature such as this is straightforward within the context of the modular approach. More generally, a modular approach provides an efficient methodology for setting up earth science computing problems to test various ideas. As a concrete illustration relevant to EM induction problems, we investigate the sensitivity of MT data near San Andreas Fault at Parkfield (California) to uncertainties in the regional geoelectric structure.
International Nuclear Information System (INIS)
Paretzke, H.G.; Ballarini, F.; Brugmans, M.
2000-01-01
The overall project is organised into seven work packages. WP1 concentrates on the development of mechanistic, quantitative models for radiation oncogenesis using selected data sets from radiation epidemiology and from experimental animal studies. WP2 concentrates on the development of mechanistic, mathematical models for the induction of chromosome aberrations. WP3 develops mechanistic models for radiation mutagenesis, particularly using the HPRT-mutation as a paradigm. WP4 will develop mechanistic models for damage and repair of DNA, and compare these with experimentally derived data. WP5 concentrates on the improvement of our knowledge on the chemical reaction pathways of initial radiation chemical species in particular those that migrate to react with the DNA and on their simulation in track structure codes. WP6 models by track structure simulation codes the production of initial physical and chemical species, within DNA, water and other components of mammalian cells, in the tracks of charged particles following the physical processes of energy transfer, migration, absorption, and decay of excited states. WP7 concentrates on the determination of the start spectra of those tracks considered in WP6 for different impinging radiation fields and different irradiated biological objects. (orig.)
Modeling time-to-event (survival) data using classification tree analysis.
Linden, Ariel; Yarnold, Paul R
2017-12-01
Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.
Singh, Gyanendra; Sachdeva, S N; Pal, Mahesh
2016-11-01
This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2-6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
Chakra B. Budhathoki; Thomas B. Lynch; James M. Guldin
2010-01-01
Nonlinear mixed-modeling methods were used to estimate parameters in an individual-tree basal area growth model for shortleaf pine (Pinus echinata Mill.). Shortleaf pine individual-tree growth data were available from over 200 permanently established 0.2-acre fixed-radius plots located in naturally-occurring even-aged shortleaf pine forests on the...
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...
Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen. Fitzgerald
2012-01-01
Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...
Jeurissen, S.M.F.; Seyhan, F.; Kandhai, M.C.; Dekkers, S.; Booij, C.J.H.; Bos, P.M.J.; Fels, van der H.J.
2011-01-01
This paper proposes an indicator based 'traffic light' model as a tool to pro-actively assess the occurrence of mycotoxins in tree nuts. The model is built using a holistic approach and, consequently, uses indicators from inside and outside the tree nut production chain as the basic elements.
Comparison of tree types of models for the prediction of final academic achievement
Directory of Open Access Journals (Sweden)
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
Flow regulation in coronary vascular tree: a model study.
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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.
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
Widlowski, J.; Cote, J.; Beland, M.
2013-12-01
Current operational retrieval algorithms of terrestrial essential climate variables, like LAI and FAPAR, rely on simulations from physically based radiative transfer models that possess inherent assumptions regarding the structure of the vegetation. This work investigates the biases that can be expected when validated Monte Carlo ray-tracing models are used to simulated bi-directional reflectance properties of Savanna environments using different levels of architectural realism. More specifically, tree crowns will be gradually abstracted with voxels that increase in size from 0.1m to 0.9m sidelength. This will reduce the spatial variability of the foliage density in the tree crown, alter the outer silhouette of the tree, and change its directional cross-sectional area. To assess the impact of such structural changes on the radiative properties of Savanna environments, very detailed 3-D tree reconstructions are made use of that were originally derived from terrestrial LIDAR scans acquired in Mali. Canopy reflectance simulations of these reference targets are then compared with the same data from the voxelised canopy representations (with and without woody structures) at multiple spatial resolutions, spectral domains, as well as illumination and viewing configurations. The goal of this study is to find the least detailed tree architecture representations that are still suitable for the interpretation of space borne data. Graphical depiction of the Savanna trees (top left) that served as architectural reference for canopy reflectance simulations that were then compared to the same quantities for crown abstractions based on different voxel sizes (middle and right panels) as well as ellipsoids (bottom left).
Hill, Ryan M; Oosterhoff, Benjamin; Kaplow, Julie B
2017-07-01
Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation. Participants were N = 4,799 youth (Mage = 16.15 years, SD = 1.63) who completed both Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health. CTA was used to generate a series of decision rules for identifying adolescents at risk for reporting suicide ideation at Wave 2. Findings revealed 3 distinct solutions with varying sensitivity and specificity for identifying adolescents who reported suicide ideation. Sensitivity of the classification trees ranged from 44.6% to 77.6%. The tree with greatest specificity and lowest sensitivity was based on a history of suicide ideation. The tree with moderate sensitivity and high specificity was based on depressive symptoms, suicide attempts or suicide among family and friends, and social support. The most sensitive but least specific tree utilized these factors and gender, ethnicity, hours of sleep, school-related factors, and future orientation. These classification trees offer community organizations options for instituting large-scale screenings for suicide ideation risk depending on the available resources and modality of services to be provided. This study provides a theoretically and empirically driven model for prospectively identifying adolescents at risk for suicide ideation and has implications for preventive interventions among at-risk youth. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
A Root water uptake model to compensate disease stress in citrus trees
Peddinti, S. R.; Kambhammettu, B. P.; Lad, R. S.; Suradhaniwar, S.
2017-12-01
Plant root water uptake (RWU) controls a number of hydrologic fluxes in simulating unsaturated flow and transport processes. Variable saturated models that simulate soil-water-plant interactions within the rizhosphere do not account for the health of the tree. This makes them difficult to analyse RWU patterns for diseased trees. Improper irrigation management activities on diseased (Phytopthora spp. affected) citrus trees of central India has resulted in a significant reduction in crop yield accompanied by disease escalation. This research aims at developing a quantitative RWU model that accounts for the reduction in water stress as a function of plant disease level (hereafter called as disease stress). A total of four research plots with varying disease severity were considered for our field experimentation. A three-dimensional electrical resistivity tomography (ERT) was performed to understand spatio-temporal distribution in soil moisture following irrigation. Evaporation and transpiration were monitored daily using micro lysimeter and sap flow meters respectively. Disease intensity was quantified (on 0 to 9 scale) using pathological analysis on soil samples. Pedo-physocal and pedo-electric relations were established under controlled laboratory conditions. A non-linear disease stress response function for citrus trees was derived considering phonological, hydrological, and pathological parameters. Results of numerical simulations conclude that the propagation of error in RWU estimates by ignoring the health condition of the tree is significant. The developed disease stress function was then validated in the presence of deficit water and nutrient stress conditions. Results of numerical analysis showed a good agreement with experimental data, corroborating the need for alternate management practices for disease citrus trees.
Infante, J M; Mauchamp, A; Fernández-Alé, R; Joffre, R; Rambal, S
2001-04-01
Within-tree variation in sap flow density (SFD) was measured in two isolated evergreen oak (Quercus ilex L.) trees growing in an oak savannah (dehesa) in southwest Spain. Sap flow was estimated by the constant heating method. Three sensors were installed in the trunk of each tree in three orientations: northeast (NE), northwest (NW) and south (S). Sap flow density was monitored continuously from May 18 to September 27, 1993. Daily values of SFD ranged between 500 and 4500 mm3 mm-2 day-1. There were significant differences in SFD between orientations; SFD was higher in the NE and NW orientations than in the S orientation. These differences were noted on both a daily and seasonal time scale, and were less pronounced on cloudy days and at the end of the drought period, when SFD was relatively low. Our results support the idea that branches of trees can be viewed as a collection of small independent plants.
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...... the temperatures as close as possible to the cavity surface, by means of an integrated induction heating system in the injection molding tool, to improve the fluidity of the polymer melt hereby ensuring that the polymer melt will continue to flow until the mold cavity is completely filled. The presented work uses...... 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....
Simulating local adaptation to climate of forest trees with a Physio-Demo-Genetics model.
Oddou-Muratorio, Sylvie; Davi, Hendrik
2014-04-01
One challenge of evolutionary ecology is to predict the rate and mechanisms of population adaptation to environmental variations. The variations in most life history traits are shaped both by individual genotypic and by environmental variation. Forest trees exhibit high levels of genetic diversity, large population sizes, and gene flow, and they also show a high level of plasticity for life history traits. We developed a new Physio-Demo-Genetics model (denoted PDG) coupling (i) a physiological module simulating individual tree responses to the environment; (ii) a demographic module simulating tree survival, reproduction, and pollen and seed dispersal; and (iii) a quantitative genetics module controlling the heritability of key life history traits. We used this model to investigate the plastic and genetic components of the variations in the timing of budburst (TBB) along an elevational gradient of Fagus sylvatica (the European beech). We used a repeated 5 years climatic sequence to show that five generations of natural selection were sufficient to develop nonmonotonic genetic differentiation in the TBB along the local climatic gradient but also that plastic variation among different elevations and years was higher than genetic variation. PDG complements theoretical models and provides testable predictions to understand the adaptive potential of tree populations.
Model checking software for phylogenetic trees using distribution and database methods.
Requeno, José Ignacio; Colom, José Manuel
2013-12-01
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.
Model checking software for phylogenetic trees using distribution and database methods
Directory of Open Access Journals (Sweden)
Requeno José Ignacio
2013-12-01
Full Text Available Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.
Engineering of Algorithms for Hidden Markov models and Tree Distances
DEFF Research Database (Denmark)
Sand, Andreas
speed up all the classical algorithms for analyses and training of hidden Markov models. And I show how two particularly important algorithms, the forward algorithm and the Viterbi algorithm, can be accelerated through a reformulation of the algorithms and a somewhat more complicated parallelization....... Lastly, I show how hidden Markov models can be trained orders of magnitude faster on a given input by rethinking the forward algorithm such that it can automatically adapt itself to the input. Together, these optimization have enabled us to perform analysis of full genomes in a few minutes and thereby...
Dynamic model of cage induction motor with number of rotor bars as parameter
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Gojko Joksimović
2017-05-01
Full Text Available A dynamic mathematical model, using number of rotor bars as parameter, is reached for cage induction motors through the use of coupled-circuits and the concept of winding functions. The exact MMFs waveforms are accounted for by the model which is derived in natural frames of reference. By knowing the initial motor parameters for a priori adopted number of stator slots and rotor bars model allows change of rotor bars number what results in new model parameters. During this process, the rated machine power, number of stator slots and stator winding scheme remain the same. Although presented model has a potentially broad application area it is primarily suitable for the analysis of the different stator/rotor slot combination on motor behaviour during the transients or in steady-state regime. The model is significant in its potential to provide analysis of dozen of different number of rotor bars in a few tens of minutes. Numerical example on cage rotor induction motor exemplifies this application, including three variants of number of rotor bars.
DEFF Research Database (Denmark)
King, Alexander Weider; Agerkvist, Finn T.
2017-01-01
Commonly used models of moving-coil loudspeaker voice coils, which include effects from eddy current losses, are either inaccurate or contain an abundance of parameters, and are difficult to extend to the nonlinear domain. On the contrary, fractional derivative models accurately describe the freq......Commonly used models of moving-coil loudspeaker voice coils, which include effects from eddy current losses, are either inaccurate or contain an abundance of parameters, and are difficult to extend to the nonlinear domain. On the contrary, fractional derivative models accurately describe...... the frequency and position dependence of the lossy inductance, with meaningful connections to the underlying physics, while keeping the number of parameters low. These fractional derivatives are also compatible with state-space polynomial methods of modeling nonlinear behavior. It is shown that the fractional...... order derivative approaches a value of 1, corresponding to an ideal inductance, when the voice coil is completely outside the magnetic system. Finally, the developed model reveals details about the effect of conductive voice coil formers...
Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems
DEFF Research Database (Denmark)
Becker, Bernd; Behle, Markus; Eisenbrand, Fritz
2004-01-01
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......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...
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.
New advances in tree shrew model in experimental studies of hepatitis B virus
Directory of Open Access Journals (Sweden)
JIN Xiong
2015-09-01
Full Text Available Hepatitis B virus (HBV infection is the main cause of liver fibrosis, cirrhosis, and hepatocellular carcinoma, and it is also a major health problem around the world. How to establish an efficient, reliable, and standardized animal model of chronic HBV infection is essential to the study of the pathogenesis and prevention strategies for HBV infection. This review summarizes the general research and new advances in using tree shrews as the model of HBV infection. We believe that tree shrews, as lower primates, will provide a vital platform and have a huge potential for building a proper animal model in the future, and could become the essential animal model for simulating the process of HBV infection in humans.
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.
Application of Decision-Tree Model to Groundwater Productivity-Potential Mapping
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Saro Lee
2015-09-01
Full Text Available For the sustainable use of groundwater, this study analyzed groundwater productivity-potential using a decision-tree approach in a geographic information system (GIS in Boryeong and Pohang cities, Korea. The model was based on the relationship between groundwater-productivity data, including specific capacity (SPC, and its related hydrogeological factors. SPC data which is measured and calculated for groundwater productivity and data about related factors, including topography, lineament, geology, forest and soil data, were collected and input into a spatial database. A decision-tree model was applied and decision trees were constructed using the chi-squared automatic interaction detector (CHAID and the quick, unbiased, and efficient statistical tree (QUEST algorithms. The resulting groundwater-productivity-potential (GPP maps were validated using area-under-the-curve (AUC analysis with the well data that had not been used for training the model. In the Boryeong city, the CHAID and QUEST algorithms had accuracies of 83.31% and 79.47%, and in the Pohang city, the CHAID and QUEST algorithms had accuracies of 86.18% and 80.00%. As another validation, the GPP maps were validated by comparing the actual SPC data. As the result, in the Boryeong city, the CHAID and QUEST algorithms had accuracies of 96.55% and 94.92% and in the Pohang city, the CHAID and QUEST algorithms had accuracies of 87.88% and 87.50%. These results indicate that decision-tree models can be useful for development of groundwater resources.
Enrique Orellana; Afonso Figueiredo Filho; Sylvio Péllico Netto; Jerome Klaas Vanclay
2016-01-01
Background: In recent decades, native Araucaria forests in Brazil have become fragmented due to the conversion of forest to agricultural lands and commercial tree plantations. Consequently, the forest dynamics in this forest type have been poorly investigated, as most fragments are poorly structured in terms of tree size and diversity. Methods: We developed a distance-independent individual tree-growth model to simulate the forest dynamics in a native Araucaria forest located pred...
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.
Diameter-growth model across shortleaf pine range using regression tree analysis
Daniel Yaussy; Louis Iverson; Anantha Prasad
1999-01-01
Diameter growth of a tree in most gap-phase models is limited by light, nutrients, moisture, and temperature. Growing-season temperature is represented by growing degree days (gdd), which is the sum of the average daily temperatures above a baseline temperature. Gap-phase models determine the north-south range of a species by the gdd limits at the north and south...
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
International Nuclear Information System (INIS)
Meziani, T.; Colpo, P.; Rossi, F.
2006-01-01
The magnetic pole enhanced inductively coupled source (MaPE-ICP) is an innovative low-pressure plasma source that allows for high plasma density and high plasma uniformity, as well as large-area plasma generation. This article presents an electrical characterization of this source, and the experimental measurements are compared to the results obtained after modeling the source by the equivalent circuit of the transformer. In particular, the method applied consists in performing a reverse electromagnetic modeling of the source by providing the measured plasma parameters such as plasma density and electron temperature as an input, and computing the total impedance seen at the primary of the transformer. The impedance results given by the model are compared to the experimental results. This approach allows for a more comprehensive refinement of the electrical model in order to obtain a better fitting of the results. The electrical characteristics of the system, and in particular the total impedance, were measured at the inductive coil antenna (primary of the transformer). The source was modeled electrically by a finite element method, treating the plasma as a conductive load and taking into account the complex plasma conductivity, the value of which was calculated from the electron density and electron temperature measurements carried out previously. The electrical characterization of the inductive excitation source itself versus frequency showed that the source cannot be treated as purely inductive and that the effect of parasitic capacitances must be taken into account in the model. Finally, considerations on the effect of the magnetic core addition on the capacitive component of the coupling are made
Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas
2015-08-01
In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m(-2)). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. The model comprises three sub-models for predicting: (1) the spatial heterogeneity - RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum - the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile - the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. © The Author 2015. Published by Oxford University Press on behalf of the
Ornelas, Argentina; McCullough, Christopher R; Lu, Zhen; Zacharias, Niki M; Kelderhouse, Lindsay E; Gray, Joshua; Yang, Hailing; Engel, Brian J; Wang, Yan; Mao, Weiqun; Sutton, Margie N; Bhattacharya, Pratip K; Bast, Robert C; Millward, Steven W
2016-10-26
Autophagy is a bulk catabolic process that modulates tumorigenesis, therapeutic resistance, and dormancy. The tumor suppressor ARHI (DIRAS3) is a potent inducer of autophagy and its expression results in necroptotic cell death in vitro and tumor dormancy in vivo. ARHI is down-regulated or lost in over 60 % of primary ovarian tumors yet is dramatically up-regulated in metastatic disease. The metabolic changes that occur during ARHI induction and their role in modulating death and dormancy are unknown. We employed Nuclear Magnetic Resonance (NMR)-based metabolomic strategies to characterize changes in key metabolic pathways in both cell culture and xenograft models of ARHI expression and autophagy. These pathways were further interrogated by cell-based immunofluorescence imaging, tracer uptake studies, targeted metabolic inhibition, and in vivo PET/CT imaging. Induction of ARHI in cell culture models resulted in an autophagy-dependent increase in lactate production along with increased glucose uptake and enhanced sensitivity to glycolytic inhibitors. Increased uptake of glutamine was also dependent on autophagy and dramatically sensitized cultured ARHI-expressing ovarian cancer cell lines to glutaminase inhibition. Induction of ARHI resulted in a reduction in mitochondrial respiration, decreased mitochondrial membrane potential, and decreased Tom20 staining suggesting an ARHI-dependent loss of mitochondrial function. ARHI induction in mouse xenograft models resulted in an increase in free amino acids, a transient increase in [ 18 F]-FDG uptake, and significantly altered choline metabolism. ARHI expression has previously been shown to trigger autophagy-associated necroptosis in cell culture. In this study, we have demonstrated that ARHI expression results in decreased cellular ATP/ADP, increased oxidative stress, and decreased mitochondrial function. While this bioenergetic shock is consistent with programmed necrosis, our data indicates that the accompanying up
Ultrasonographic diagnosis of biliary atresia based on a decision-making tree model
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Lee, So Mi; Cheon, Jung Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun Hye; Kim, In One; You, Sun Kyoung [Dept. of Radiology, Seoul National University College of Medicine, Seoul (Korea, Republic of)
2015-12-15
To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.
Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.
Lee, So Mi; Cheon, Jung-Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun-Hae; Cho, Hyun-Hye; Kim, In-One; You, Sun Kyoung
2015-01-01
To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.
Nine-Phase Induction Motor Dynamic Model Based On 3x9 Transformation Matrix
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Mauridhi Heri Purnomo
2013-07-01
Full Text Available A dynamic model of multi-phase induction motors in term qdn is used to simplify analysis and separate armature and field of the motor. However, to generate dynamic model qdn, square matrices are always applied to all the analysis and based on two reference frames and a circuit of magnetically coupled transformer. In order to gain the qdn dynamic model of the nine-phase induction motors in easy, simple, quick and consistent way, the analysis is done through the equivalent circuit T model until it obtains the equations in matrix form. The 3x9 transformation matrix qdn is substituted into the equation form abc so that the matrix equation of qdn is obtained. Then qdn equation results a similar qd equivalent circuit, which has different methods n that is, based the circuit of magnetically coupled transformer. Simulation results show that the two-bases circuit is magnetically coupled into the transformer model and has similar angular speed and torque response to the motor though the load changes.
Lestner, Jodi; McEntee, Laura; Johnson, Adam; Livermore, Joanne; Whalley, Sarah; Schwartz, Julie; Perfect, John R; Harrison, Thomas; Hope, William
2017-06-01
Cryptococcal meningoencephalitis is a rapidly lethal infection in immunocompromised patients. Induction regimens are usually administered for 2 weeks. The shortest effective period of induction therapy with liposomal amphotericin B (LAMB) is unknown. The pharmacodynamics of LAMB were studied in murine and rabbit models of cryptococcal meningoencephalitis. The concentrations of LAMB in the plasma and brains of mice were measured using high-performance liquid chromatography (HPLC). Histopathological changes were determined. The penetration of LAMB into the brain was determined by immunohistochemistry using an antibody directed to amphotericin B. A dose-dependent decline in fungal burden was observed in the brains of mice, with near-maximal efficacy achieved with LAMB at 10 to 20 mg/kg/day. The terminal elimination half-life in the brain was 133 h. The pharmacodynamics of a single dose of 20 mg/kg was the same as that of 20 mg/kg/day administered for 2 weeks. Changes in quantitative counts were reflected by histopathological changes in the brain. Three doses of LAMB at 5 mg/kg/day in rabbits were required to achieve fungicidal activity in cerebrospinal fluid (cumulative area under the concentration-time curve, 2,500 mg · h/liter). Amphotericin B was visible in the intra- and perivascular spaces, the leptomeninges, and the choroid plexus. The prolonged mean residence time of amphotericin B in the brain suggests that abbreviated induction regimens of LAMB are possible for cryptococcal meningoencephalitis. Copyright © 2017 Lestner et al.
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.
Directory of Open Access Journals (Sweden)
Zheng Zhao
2018-01-01
Full Text Available Urban trees are more about people than trees. Urban trees programs need public support and engagement, from the intentions to support to implement actions in supporting the programs. Built upon the theory of planned behavior and Structural Equation Modeling (SEM, this study uses Beijing as a case study to investigate how subjective norm (cognition of urban trees, attitude (benefits residents’ believe urban trees can provide, and perceived behavioral control (the believed ability of what residents can do affect intention and its transformation into implemented of supporting action. A total of 800 residents were interviewed in 2016 and asked about their opinion of neighborhood trees, park trees, and historical trees, and analyzed, respectively. The results show that subjective norm has a significant positive effect on intentions pertaining to historical and neighborhood trees. Attitudes influence intentions, but its overall influence is much lower than that of the subjective norm, indicating that residents are more likely to be influenced by external factors. The perceived behavioral control has the strongest effect among the three, suggesting the importance of public participation in strengthening intention. The transformation from intention to behavior seems relatively small, especially regarding neighborhood trees, suggesting that perceptions and participation need to be strengthened.
International Nuclear Information System (INIS)
Meloni, S.
1998-01-01
To simulate transmitted radiation in agroforestry systems, radiative transfer models usually require a detailed three-dimensional description of the tree canopy. We propose here a simplification of the description of the three-dimensional structure of wild cherry trees (Prunus avium). The simplified tree description was tested against the detailed one for five-year-old wild cherry. It allowed accurate simulation of transmitted radiation and avoided tedious measurements of tree structure. The simplified description was then applied to older trees. Allometric relationships were used to compute the parameters not available on free-grown trees. The transmitted radiation in an agroforestry system was simulated at four different ages: 5, 10, 15 and 20 years. The trees were planted on a 5 m square grid. Two row orientations, chosen to provide different transmitted radiation patterns, were tested: north/south and north- east/south-west. The simulations showed that the daily mean transmitted radiation was reduced from 92% of incident radiation under five-year-old trees to 37% under 20-year-old trees. The variability of transmitted radiation increased with tree growth. The row orientation had only small effects on the shaded area at the beginning and end of the day when solar elevation was low. (author)
Surface-based geometric modelling using teaching trees for advanced robots
International Nuclear Information System (INIS)
Nakamura, Akira; Ogasawara, Tsukasa; Tsukune, Hideo; Oshima, Masaki
2000-01-01
Geometric modelling of the environment is important in robot motion planning. Generally, shapes can be stored in a data base, so the elements that need to be decided are positions and orientations. In this paper, surface-based geometric modelling using a teaching tree is proposed. In this modelling, combinations of surfaces are considered in order to decide positions and orientations of objects. The combinations are represented by a depth-first tree, which makes it easy for the operator to select one combination out of several. This method is effective not only in the case when perfect data can be obtained, but also when conditions for measurement of three-dimensional data are unfavorable, which often occur in the environment of a working robot. (author)
Sakschewski, B.; Kirsten, T.; von Bloh, W.; Poorter, L.; Pena-Claros, M.; Boit, A.
2016-12-01
Functional diversity of ecosystems has been found to increase ecosystem functions and therefore enhance ecosystem resilience against environmental stressors. However, global carbon-cycle and biosphere models still classify the global vegetation into a relatively small number of distinct plant functional types (PFT) with constant features over space and time. Therefore, those models might underestimate the resilience and adaptive capacity of natural vegetation under climate change by ignoring positive effects that functional diversity might bring about. We diversified a set a of selected tree traits in a dynamic global vegetation model (LPJmL). In the new subversion, called LPJmL-FIT, Amazon region biomass stocks and forest structure appear significantly more resilient against climate change. Enhanced tree trait diversity enables the simulated rainforests to adjust to new environmental conditions via ecological sorting. These results may stimulate a new debate on the value of biodiversity for climate change mitigation.
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.
Mathematical Modeling of Eddy-Current Loss for a New Induction Heating Device
Directory of Open Access Journals (Sweden)
Hai Du
2014-01-01
Full Text Available A new induction heating device is presented in this paper. This device can convert mechanical energy into heat energy by utilizing eddy currents, which are induced by rotating permanent magnets. A mathematical model is established for estimating eddy-current loss of the device. The distribution of induced currents and the resultant magnetic field intensity are considered in the process of modeling the eddy-current loss and so is the mutual influence of the electric field between neighborhood pole projection areas. Particularly, the skin effect is considered by correcting the numerical integral domain of eddy current density, which has great effect on the calculating results. Based on specific examples, the effectiveness and correctness of proposed model are proved by finite element analysis. The results show that the mathematical model can provide important reference for design and structure optimization of the device.
Complementary models of tree species-soil relationships in old-growth temperate forests
Cross, Alison; Perakis, Steven S.
2011-01-01
Ecosystem level studies identify plant soil feed backs as important controls on soil nutrient availability,particularly for nitrogen and phosphorus. Although site and species specific studies of tree species soil relationships are relatively common,comparatively fewer studies consider multiple coexisting speciesin old-growth forests across a range of sites that vary underlying soil fertility. We characterized patterns in forest floor and mineral soil nutrients associated with four common tree species across eight undisturbed old-growth forests in Oregon, USA, and used two complementary conceptual models to assess tree species soil relationships. Plant soil feedbacks that could reinforce sitelevel differences in nutrient availability were assessed using the context dependent relationships model, where by relative species based differences in each soil nutrient divergedorconvergedas nutrient status changed across sites. Tree species soil relationships that did not reflect strong feedbacks were evaluated using a site independent relationships model, where by forest floor and surface mineral soil nutrient tools differed consistently by tree species across sites,without variation in deeper mineral soils. We found that theorganically cycled elements carbon, nitrogen, and phosphorus exhibited context-dependent differences among species in both forest floor and mineral soil, and most of ten followed adivergence model,where by species differences were greatest at high-nutrient sites. These patterns are consistent with the oryemphasizing biotic control of these elements through plant soil feedback mechanisms. Site independent species differences were strongest for pool so if the weather able cations calcium, magnesium, potassium,as well as phosphorus, in mineral soils. Site independent species differences in forest floor nutrients we reattributable too nespecies that displayed significant greater forest floor mass accumulation. Our finding confirmed that site-independent and
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
He, Minhui; Shishov, Vladimir; Kaparova, Nazgul; Yang, Bao; Bräuning, Achim; Grießinger, Jussi
2017-04-01
Response of climate warming on tree-ring formation has attracted much attention during recent years. However, most studies are based on statistical analysis, lacking understanding of tree-physiological processes, especially on the mountainous region of the Tibetan Plateau (TP). Herein, we firstly use an updated new version of the tree-ring process-based Vaganov-Shashkin model (VS-oscilloscope) to simulate tree-ring formation and its relationships with climate factors during the past six decades. Our analysis covered 341 sampled trees, with elevation ranges from 2750 to 4575 m a.s.l. at five sampling sites from southern to northern part of the TP. Simulated tree-ring width series are significantly (p interval periods. Starting dates of tree-ring width formation are all determined by temperature at the five sampling sites. After the initiation of tree stem cambial activity, soil moisture content has a significant effect on tree-ring growth. Ending dates are driven by temperature in the study region. Simulated results indicate the difference between wide and narrow tree-ring formation is mostly induced by soil moisture content, especially at the first half of the growing season, while effect from temperature is minor. Interestingly, we detected significantly (p the year 1985 at the five sampling sites. However, the variability of mean relative growth rate due to temperature (GrT) is negligible before and after that. Based on the successful application of VS-oscilloscope modeling on the high-elevation tree stands of the TP, our study provides a new perspective of tree radial growth process and their relationships with climate data during the past six decades.
Don C. Bragg; Jeffrey L. Kershner
2004-01-01
Riparian large woody debris (LWD) recruitment simulations have traditionally applied a random angle of tree fall from two well-forested stream banks. We used a riparian LWD recruitment model (CWD, version 1.4) to test the validity these assumptions. Both the number of contributing forest banks and predominant tree fall direction significantly influenced simulated...
Eric M. Pfeifer; Jeffrey A. Hicke; Arjan J.H. Meddens
2011-01-01
Bark beetle epidemics result in tree mortality across millions of hectares in North America. However, few studies have quantified impacts on carbon (C) cycling. In this study, we quantified the immediate response and subsequent trajectories of stand-level aboveground tree C stocks and fluxes using field measurements and modeling for a location in central Idaho, USA...
International Nuclear Information System (INIS)
Vichev, S.; Bogdanov, D.
2000-01-01
The purpose of this paper is to introduce the fault tree analysis method as a tool for unit protection reliability estimation. The constant failure rate model applies for making reliability assessment, and especially availability assessment. For that purpose an example for unit primary equipment structure and fault tree example for simplified unit protection system is presented (author)
Hülsmann, Lisa; Bugmann, Harald; Cailleret, Maxime; Brang, Peter
2018-03-01
Dynamic Vegetation Models (DVMs) are designed to be suitable for simulating forest succession and species range dynamics under current and future conditions based on mathematical representations of the three key processes regeneration, growth, and mortality. However, mortality formulations in DVMs are typically coarse and often lack an empirical basis, which increases the uncertainty of projections of future forest dynamics and hinders their use for developing adaptation strategies to climate change. Thus, sound tree mortality models are highly needed. We developed parsimonious, species-specific mortality models for 18 European tree species using >90,000 records from inventories in Swiss and German strict forest reserves along a considerable environmental gradient. We comprehensively evaluated model performance and incorporated the new mortality functions in the dynamic forest model ForClim. Tree mortality was successfully predicted by tree size and growth. Only a few species required additional covariates in their final model to consider aspects of stand structure or climate. The relationships between mortality and its predictors reflect the indirect influences of resource availability and tree vitality, which are further shaped by species-specific attributes such as maximum longevity and shade tolerance. Considering that the behavior of the models was biologically meaningful, and that their performance was reasonably high and not impacted by changes in the sampling design, we suggest that the mortality algorithms developed here are suitable for implementation and evaluation in DVMs. In the DVM ForClim, the new mortality functions resulted in simulations of stand basal area and species composition that were generally close to historical observations. However, ForClim performance was poorer than when using the original, coarse mortality formulation. The difficulties of simulating stand structure and species composition, which were most evident for Fagus sylvatica L
Protective effects of Resveratrol in an experimental model of abdominal aortic aneurysm induction
Directory of Open Access Journals (Sweden)
D. Palmieri
2011-01-01
Full Text Available Resveratrol (Rsv is a natural antioxidant polyphenol with vasoprotective properties. We evaluated whether Rsv affects the inflammatory response in an experimental model of elastase-induced abdominal aortic aneurysm. Thirty male rats were subjected to aneurysm induction and treated or not with Rsv. Circulating levels of CD62L-monocyte subset, monocyte CD I 43 surface expression, MMP-9 plasma activity and TNFα serum levels were lower in Rsv-treated rats. In conclusion. Rsv acts as an anti-inflammatory compound and could be of great revelance to improve the immune response in AAA patients.
A closed-loop power controller model of series-resonant-inverter-fitted induction heating system
Directory of Open Access Journals (Sweden)
Pal Palash
2016-12-01
Full Text Available This paper presents a mathematical model of a power controller for a high-frequency induction heating system based on a modified half-bridge series resonant inverter. The output real power is precise over the heating coil, and this real power is processed as a feedback signal that contends a closed-loop topology with a proportional-integral-derivative controller. This technique enables both control of the closed-loop power and determination of the stability of the high-frequency inverter. Unlike the topologies of existing power controllers, the proposed topology enables direct control of the real power of the high-frequency inverter.
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
Non-robust Phase Transitions in the Generalized Clock Model on Trees
Külske, C.; Schriever, P.
2018-01-01
Pemantle and Steif provided a sharp threshold for the existence of a robust phase transition (RPT) for the continuous rotator model and the Potts model in terms of the branching number and the second eigenvalue of the transfer matrix whose kernel describes the nearest neighbor interaction along the edges of the tree. Here a RPT is said to occur if an arbitrarily weak coupling with symmetry-breaking boundary conditions suffices to induce symmetry breaking in the bulk. They further showed that for the Potts model RPT occurs at a different threshold than PT (phase transition in the sense of multiple Gibbs measures), and conjectured that RPT and PT should occur at the same threshold in the continuous rotator model. We consider the class of four- and five-state rotation-invariant spin models with reflection symmetry on general trees which contains the Potts model and the clock model with scalarproduct-interaction as limiting cases. The clock model can be viewed as a particular discretization which is obtained from the classical rotator model with state space S^1. We analyze the transition between PT=RPT and PT≠ RPT, in terms of the eigenvalues of the transfer matrix of the model at the critical threshold value for the existence of RPT. The transition between the two regimes depends sensitively on the third largest eigenvalue.
Gürsoy, Doğa; Scharfetter, Hermann
2011-01-01
Magnetic induction tomography (MIT) is a noninvasive imaging modality that aims to reconstruct the interior electrical conductivity distribution of the human body. It uses magnetic induction to excite eddy currents in the body and an array of sensor coils to detect the perturbations in the magnetic field. Image reconstruction in MIT is usually carried out by minimizing the residuals between the estimated and measured quantities assuming a structurally correct model. Thus, any mismatch between the simulated and the true experimental coil setup alters the data and may cause artifacts in the images. In this paper, a simulation study was performed to investigate the effect of modeling mismatches on measurements and corresponding reconstructed images. It was found that slight distortions of the receivers may cause up to 20% deviations in the data considering a local and small perturbation in conductivity. Unless the geometry is modeled correctly, these artifacts may spoil the images particularly for the case of flexible systems that have many degrees of freedom and systems that require different adjustments for different imaging sessions. If the system does not need calibration, for instance as in the case of head applications, then a rigid mechanical support appears to be an important design issue to achieve a better image quality.
International Nuclear Information System (INIS)
Gürsoy, Doğa; Scharfetter, Hermann
2011-01-01
Magnetic induction tomography (MIT) is a noninvasive imaging modality that aims to reconstruct the interior electrical conductivity distribution of the human body. It uses magnetic induction to excite eddy currents in the body and an array of sensor coils to detect the perturbations in the magnetic field. Image reconstruction in MIT is usually carried out by minimizing the residuals between the estimated and measured quantities assuming a structurally correct model. Thus, any mismatch between the simulated and the true experimental coil setup alters the data and may cause artifacts in the images. In this paper, a simulation study was performed to investigate the effect of modeling mismatches on measurements and corresponding reconstructed images. It was found that slight distortions of the receivers may cause up to 20% deviations in the data considering a local and small perturbation in conductivity. Unless the geometry is modeled correctly, these artifacts may spoil the images particularly for the case of flexible systems that have many degrees of freedom and systems that require different adjustments for different imaging sessions. If the system does not need calibration, for instance as in the case of head applications, then a rigid mechanical support appears to be an important design issue to achieve a better image quality
Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts
Hamid, R.; Pabunga, D. B.
2017-09-01
The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.
Babanatsas, T.; Glăvan, D. O.; Babanatis Merce, R. M.; Maris, S. A.
2018-01-01
The purpose of this study is to bring as much as possible, close to real situation the 3D modelling for the olive trees in order to establish the necessary forces for automatic harvesting (harvesting robots). To fulfil our goal we have at our disposal different ways to do modelling very close to the real situation. One way is to use reality capture software (its results being photos) that are converted into a real 3D model, the disadvantage of the method being a mesh model that is not accurate enough. The reasonable alternative is to develop an experiment by measuring a sample orchard of olive trees (experiment who took place in Halkidiki, Greece, measuring over 120 trees). After establishing the real dimensions, we adopted as model the media that we have measured (the height of the tree, the thickness of branches, number of branches, etc.), model which we consider closer to the reality and therefor more suitable for our simulation.
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.
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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.
Yang, Ziheng; Zhu, Tianqi
2018-02-20
The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this overconfidence are unknown. In general, the performance of Bayesian selection of misspecified models is poorly understood, even though this is of great scientific interest since models are never true in real data analysis. Here we characterize the asymptotic behavior of Bayesian model selection and show that when the competing models are equally wrong, Bayesian model selection exhibits surprising and polarized behaviors in large datasets, supporting one model with full force while rejecting the others. If one model is slightly less wrong than the other, the less wrong model will eventually win when the amount of data increases, but the method may become overconfident before it becomes reliable. We suggest that this extreme behavior may be a major factor for the spuriously high posterior probabilities for evolutionary trees. The philosophical implications of our results to the application of Bayesian model selection to evaluate opposing scientific hypotheses are yet to be explored, as are the behaviors of non-Bayesian methods in similar situations.
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R. K. Tiwari
2011-08-01
Full Text Available A novel technique based on the Bayesian neural network (BNN theory is developed and employed to model the temperature variation record from the Western Himalayas. In order to estimate an a posteriori probability function, the BNN is trained with the Hybrid Monte Carlo (HMC/Markov Chain Monte Carlo (MCMC simulations algorithm. The efficacy of the new algorithm is tested on the well known chaotic, first order autoregressive (AR and random models and then applied to model the temperature variation record decoded from the tree-ring widths of the Western Himalayas for the period spanning over 1226–2000 AD. For modeling the actual tree-ring temperature data, optimum network parameters are chosen appropriately and then cross-validation test is performed to ensure the generalization skill of the network on the new data set. Finally, prediction result based on the BNN model is compared with the conventional artificial neural network (ANN and the AR linear models results. The comparative results show that the BNN based analysis makes better prediction than the ANN and the AR models. The new BNN modeling approach provides a viable tool for climate studies and could also be exploited for modeling other kinds of environmental data.
International Nuclear Information System (INIS)
Land, C.E.; Tokunaga, M.
1984-01-01
Induction period is the temporal aspect of the excess cancer risk that follows an exposure to ionizing radiation. Operationally, it can be thought of as the time from an exposure of brief duration to the diagnosis of any resultant cancer. Whereas the magnitude of excess risk can be described by a single number, such as the average yearly excess risk over some fixed time interval after exposure, the temporal distribution requires a histogram or a curve, that is, an array or continuum of numbers. The study of induction period involves a search for a simple way of describing the temporal distribution of risk, that is, a way of describing a continuum by using only one or two numbers. In other words, the goal is to describe induction period probabilistically, using a parametric model with a few parameters
Perceived Organizational Support for Enhancing Welfare at Work: A Regression Tree Model
Giorgi, Gabriele; Dubin, David; Perez, Javier Fiz
2016-01-01
When trying to examine outcomes such as welfare and well-being, research tends to focus on main effects and take into account limited numbers of variables at a time. There are a number of techniques that may help address this problem. For example, many statistical packages available in R provide easy-to-use methods of modeling complicated analysis such as classification and tree regression (i.e., recursive partitioning). The present research illustrates the value of recursive partitioning in the prediction of perceived organizational support in a sample of more than 6000 Italian bankers. Utilizing the tree function party package in R, we estimated a regression tree model predicting perceived organizational support from a multitude of job characteristics including job demand, lack of job control, lack of supervisor support, training, etc. The resulting model appears particularly helpful in pointing out several interactions in the prediction of perceived organizational support. In particular, training is the dominant factor. Another dimension that seems to influence organizational support is reporting (perceived communication about safety and stress concerns). Results are discussed from a theoretical and methodological point of view. PMID:28082924
An Assessment for A Filtered Containment Venting Strategy Using Decision Tree Models
International Nuclear Information System (INIS)
Shin, Hoyoung; Jae, Moosung
2016-01-01
In this study, a probabilistic assessment of the severe accident management strategy through a filtered containment venting system was performed by using decision tree models. In Korea, the filtered containment venting system has been installed for the first time in Wolsong unit 1 as a part of Fukushima follow-up steps, and it is planned to be applied gradually for all the remaining reactors. Filtered containment venting system, one of severe accident countermeasures, prevents a gradual pressurization of the containment building exhausting noncondensable gas and vapor to the outside of the containment building. In this study, a probabilistic assessment of the filtered containment venting strategy, one of the severe accident management strategies, was performed by using decision tree models. Containment failure frequencies of each decision were evaluated by the developed decision tree model. The optimum accident management strategies were evaluated by comparing the results. Various strategies in severe accident management guidelines (SAMG) could be improved by utilizing the methodology in this study and the offsite risk analysis methodology
Inductive Monitoring System (IMS)
National Aeronautics and Space Administration — IMS: Inductive Monitoring System The Inductive Monitoring System (IMS) is a tool that uses a data mining technique called clustering to extract models of normal...
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
Wu, Qiong-Li; Cournède, Paul-Henry; Mathieu, Amélie
2012-01-01
Global sensitivity analysis has a key role to play in the design and parameterisation of functional–structural plant growth models which combine the description of plant structural development (organogenesis and geometry) and functional growth (biomass accumulation and allocation). We are particularly interested in this study in Sobol's method which decomposes the variance of the output of interest into terms due to individual parameters but also to interactions between parameters. Such information is crucial for systems with potentially high levels of non-linearity and interactions between processes, like plant growth. However, the computation of Sobol's indices relies on Monte Carlo sampling and re-sampling, whose costs can be very high, especially when model evaluation is also expensive, as for tree models. In this paper, we thus propose a new method to compute Sobol's indices inspired by Homma–Saltelli, which improves slightly their use of model evaluations, and then derive for this generic type of computational methods an estimator of the error estimation of sensitivity indices with respect to the sampling size. It allows the detailed control of the balance between accuracy and computing time. Numerical tests on a simple non-linear model are convincing and the method is finally applied to a functional–structural model of tree growth, GreenLab, whose particularity is the strong level of interaction between plant functioning and organogenesis. - Highlights: ► We study global sensitivity analysis in the context of functional–structural plant modelling. ► A new estimator based on Homma–Saltelli method is proposed to compute Sobol indices, based on a more balanced re-sampling strategy. ► The estimation accuracy of sensitivity indices for a class of Sobol's estimators can be controlled by error analysis. ► The proposed algorithm is implemented efficiently to compute Sobol indices for a complex tree growth model.
Detecting Difference between Process Models Based on the Refined Process Structure Tree
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Jing Fan
2017-01-01
Full Text Available The development of mobile workflow management systems (mWfMS leads to large number of business process models. In the meantime, the location restriction embedded in mWfMS may result in different process models for a single business process. In order to help users quickly locate the difference and rebuild the process model, detecting the difference between different process models is needed. Existing detection methods either provide a dissimilarity value to represent the difference or use predefined difference template to generate the result, which cannot reflect the entire composition of the difference. Hence, in this paper, we present a new approach to solve this problem. Firstly, we parse the process models to their corresponding refined process structure trees (PSTs, that is, decomposing a process model into a hierarchy of subprocess models. Then we design a method to convert the PST to its corresponding task based process structure tree (TPST. As a consequence, the problem of detecting difference between two process models is transformed to detect difference between their corresponding TPSTs. Finally, we obtain the difference between two TPSTs based on the divide and conquer strategy, where the difference is described by an edit script and we make the cost of the edit script close to minimum. The extensive experimental evaluation shows that our method can meet the real requirements in terms of precision and efficiency.
Oh, Hyo-Sook; Park, Hyeoun-Ae
2006-06-01
This study was performed to develop and test a decision-tree model of treatment-seeking behaviors about when Korean patients visit a doctor after experiencing stroke symptoms. The study used methodological triangulation. The model was developed based on qualitative data collected from in-depth interviews with 18 stroke patients. The model was tested using quantitative data collected from interviews and a structured questionnaire involving 150 stroke patients. The predictability of the decision-tree model was quantified as the proportion of participants who followed the pathway predicted by the model. Decision outcomes of the model were categorized into immediate and delayed treatment-seeking behavior. The model was influenced by lowered consciousness, social-group influences, perceived seriousness of symptoms, past history of hypertension or stroke, and barriers to hospital visits. The predictability of the model was found to be 90.7%. The results from this study can help healthcare personnel understand the education needs of stroke patients regarding treatment-seeking behaviors, and hence aid in the development of educational strategies for stroke patients.
International Nuclear Information System (INIS)
Dongiovanni, Danilo Nicola; Iesmantas, Tomas
2016-01-01
Highlights: • RAMI (Reliability, Availability, Maintainability and Inspectability) assessment of secondary heat transfer loop for a DEMO nuclear fusion plant. • Definition of a fault tree for a nuclear steam turbine operated in pulsed mode. • Turbine failure rate models update by mean of a Bayesian network reflecting the fault tree analysis in the considered scenario. • Sensitivity analysis on system availability performance. - Abstract: Availability will play an important role in the Demonstration Power Plant (DEMO) success from an economic and safety perspective. Availability performance is commonly assessed by Reliability Availability Maintainability Inspectability (RAMI) analysis, strongly relying on the accurate definition of system components failure modes (FM) and failure rates (FR). Little component experience is available in fusion application, therefore requiring the adaptation of literature FR to fusion plant operating conditions, which may differ in several aspects. As a possible solution to this problem, a new methodology to extrapolate/estimate components failure rate under different operating conditions is presented. The DEMO Balance of Plant nuclear steam turbine component operated in pulse mode is considered as study case. The methodology moves from the definition of a fault tree taking into account failure modes possibly enhanced by pulsed operation. The fault tree is then translated into a Bayesian network. A statistical model for the turbine system failure rate in terms of subcomponents’ FR is hence obtained, allowing for sensitivity analyses on the structured mixture of literature and unknown FR data for which plausible value intervals are investigated to assess their impact on the whole turbine system FR. Finally, the impact of resulting turbine system FR on plant availability is assessed exploiting a Reliability Block Diagram (RBD) model for a typical secondary cooling system implementing a Rankine cycle. Mean inherent availability
Energy Technology Data Exchange (ETDEWEB)
Dongiovanni, Danilo Nicola, E-mail: danilo.dongiovanni@enea.it [ENEA, Nuclear Fusion and Safety Technologies Department, via Enrico Fermi 45, Frascati 00040 (Italy); Iesmantas, Tomas [LEI, Breslaujos str. 3 Kaunas (Lithuania)
2016-11-01
Highlights: • RAMI (Reliability, Availability, Maintainability and Inspectability) assessment of secondary heat transfer loop for a DEMO nuclear fusion plant. • Definition of a fault tree for a nuclear steam turbine operated in pulsed mode. • Turbine failure rate models update by mean of a Bayesian network reflecting the fault tree analysis in the considered scenario. • Sensitivity analysis on system availability performance. - Abstract: Availability will play an important role in the Demonstration Power Plant (DEMO) success from an economic and safety perspective. Availability performance is commonly assessed by Reliability Availability Maintainability Inspectability (RAMI) analysis, strongly relying on the accurate definition of system components failure modes (FM) and failure rates (FR). Little component experience is available in fusion application, therefore requiring the adaptation of literature FR to fusion plant operating conditions, which may differ in several aspects. As a possible solution to this problem, a new methodology to extrapolate/estimate components failure rate under different operating conditions is presented. The DEMO Balance of Plant nuclear steam turbine component operated in pulse mode is considered as study case. The methodology moves from the definition of a fault tree taking into account failure modes possibly enhanced by pulsed operation. The fault tree is then translated into a Bayesian network. A statistical model for the turbine system failure rate in terms of subcomponents’ FR is hence obtained, allowing for sensitivity analyses on the structured mixture of literature and unknown FR data for which plausible value intervals are investigated to assess their impact on the whole turbine system FR. Finally, the impact of resulting turbine system FR on plant availability is assessed exploiting a Reliability Block Diagram (RBD) model for a typical secondary cooling system implementing a Rankine cycle. Mean inherent availability
Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
2016-10-01
The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.
Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects
International Nuclear Information System (INIS)
Nowak, David J.; Hirabayashi, Satoshi; Bodine, Allison; Hoehn, Robert
2013-01-01
Urban particulate air pollution is a serious health issue. Trees within cities can remove fine particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM 2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM 2.5 removed annually by trees varied from 4.7 tonnes in Syracuse to 64.5 tonnes in Atlanta, with annual values varying from $1.1 million in Syracuse to $60.1 million in New York City. Most of these values were from the effects of reducing human mortality. Mortality reductions were typically around 1 person yr −1 per city, but were as high as 7.6 people yr −1 in New York City. Average annual percent air quality improvement ranged between 0.05% in San Francisco and 0.24% in Atlanta. Understanding the impact of urban trees on air quality can lead to improved urban forest management strategies to sustain human health in cities. -- Highlights: •Paper provides the first broad-scale estimates of city-wide tree impacts on PM 2.5 . •Trees improve overall air quality by intercepting particulate matter. •Particle resuspension can lead to short-term increases in pollutant concentrations. •Urban trees produce substantial health improvements and values. -- Air pollution modeling reveals broad-scale impacts of pollution removal by urban trees on PM 2.5 concentrations and human health
Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width
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S. E. Tolwinski-Ward
2013-07-01
Full Text Available We present a Bayesian model for estimating the parameters of the VS-Lite forward model of tree-ring width for a particular chronology and its local climatology. The scheme also provides information about the uncertainty of the parameter estimates, as well as the model error in representing the observed proxy time series. By inferring VS-Lite's parameters independently for synthetically generated ring-width series at several hundred sites across the United States, we show that the algorithm is skillful. We also infer optimal parameter values for modeling observed ring-width data at the same network of sites. The estimated parameter values covary in physical space, and their locations in multidimensional parameter space provide insight into the dominant climatic controls on modeled tree-ring growth at each site as well as the stability of those controls. The estimation procedure is useful for forward and inverse modeling studies using VS-Lite to quantify the full range of model uncertainty stemming from its parameterization.
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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
Reconstruction of 3D tree stem models from low-cost terrestrial laser scanner data
Kelbe, Dave; Romanczyk, Paul; van Aardt, Jan; Cawse-Nicholson, Kerry
2013-05-01
With the development of increasingly advanced airborne sensing systems, there is a growing need to support sensor system design, modeling, and product-algorithm development with explicit 3D structural ground truth commensurate to the scale of acquisition. Terrestrial laser scanning is one such technique which could provide this structural information. Commercial instrumentation to suit this purpose has existed for some time now, but cost can be a prohibitive barrier for some applications. As such we recently developed a unique laser scanning system from readily-available components, supporting low cost, highly portable, and rapid measurement of below-canopy 3D forest structure. Tools were developed to automatically reconstruct tree stem models as an initial step towards virtual forest scene generation. The objective of this paper is to assess the potential of this hardware/algorithm suite to reconstruct 3D stem information for a single scan of a New England hardwood forest site. Detailed tree stem structure (e.g., taper, sweep, and lean) is recovered for trees of varying diameter, species, and range from the sensor. Absolute stem diameter retrieval accuracy is 12.5%, with a 4.5% overestimation bias likely due to the LiDAR beam divergence.
Capacitance Regression Modelling Analysis on Latex from Selected Rubber Tree Clones
Rosli, A. D.; Hashim, H.; Khairuzzaman, N. A.; Mohd Sampian, A. F.; Baharudin, R.; Abdullah, N. E.; Sulaiman, M. S.; Kamaru'zzaman, M.
2015-11-01
This paper investigates the capacitance regression modelling performance of latex for various rubber tree clones, namely clone 2002, 2008, 2014 and 3001. Conventionally, the rubber tree clones identification are based on observation towards tree features such as shape of leaf, trunk, branching habit and pattern of seeds texture. The former method requires expert persons and very time-consuming. Currently, there is no sensing device based on electrical properties that can be employed to measure different clones from latex samples. Hence, with a hypothesis that the dielectric constant of each clone varies, this paper discusses the development of a capacitance sensor via Capacitance Comparison Bridge (known as capacitance sensor) to measure an output voltage of different latex samples. The proposed sensor is initially tested with 30ml of latex sample prior to gradually addition of dilution water. The output voltage and capacitance obtained from the test are recorded and analyzed using Simple Linear Regression (SLR) model. This work outcome infers that latex clone of 2002 has produced the highest and reliable linear regression line with determination coefficient of 91.24%. In addition, the study also found that the capacitive elements in latex samples deteriorate if it is diluted with higher volume of water.
Capacitance Regression Modelling Analysis on Latex from Selected Rubber Tree Clones
International Nuclear Information System (INIS)
Rosli, A D; Baharudin, R; Hashim, H; Khairuzzaman, N A; Mohd Sampian, A F; Abdullah, N E; Kamaru'zzaman, M; Sulaiman, M S
2015-01-01
This paper investigates the capacitance regression modelling performance of latex for various rubber tree clones, namely clone 2002, 2008, 2014 and 3001. Conventionally, the rubber tree clones identification are based on observation towards tree features such as shape of leaf, trunk, branching habit and pattern of seeds texture. The former method requires expert persons and very time-consuming. Currently, there is no sensing device based on electrical properties that can be employed to measure different clones from latex samples. Hence, with a hypothesis that the dielectric constant of each clone varies, this paper discusses the development of a capacitance sensor via Capacitance Comparison Bridge (known as capacitance sensor) to measure an output voltage of different latex samples. The proposed sensor is initially tested with 30ml of latex sample prior to gradually addition of dilution water. The output voltage and capacitance obtained from the test are recorded and analyzed using Simple Linear Regression (SLR) model. This work outcome infers that latex clone of 2002 has produced the highest and reliable linear regression line with determination coefficient of 91.24%. In addition, the study also found that the capacitive elements in latex samples deteriorate if it is diluted with higher volume of water. (paper)
Modeling of High-Frequency Electromagnetic Effects on an Ironless Inductive Position Sensor
Danisi, Alessandro; Masi, Alessandro; Perriard, Yves
2013-01-01
The ironless inductive position sensor (I2PS) is a five-coil air-cored structure that senses the variation of flux linkage between supply and sense coils and relates it to the linear position of a moving coil. In air-cored structures, the skin and proximity effect can bring substantial variations of the electrical resistance, leading to important deviations from the low-frequency functioning. In this paper, an analysis of the effect of high-frequency phenomena on the I2PS functioning is described. The key-element is the modeling of the resistance as a function of the frequency, which starts from the analytical resolution of Maxwell's equations in the coil's geometry. The analysis is validated by means of experimental measurements on custom sensor coils. The resulting model is integrated with the existing low-frequency analysis and represents a complete tool for the design of an I2PS sensor, framing its electromagnetic behavior.
Problem of simulating the Earth's induction effects in modeling polar magnetic substorms
International Nuclear Information System (INIS)
Mareschal, M.
1976-01-01
A major problem encountered in trying to model the current system associated with a polar magnetic substorm from ground-based magnetic observations is the difficulty of adequately evaluating the earth's induction effects. Two methods for simulating these effects are reviewed here. Method 1 simply reduces the earth to a perfect conductor and leads to very simple field equations. Method 2 considers the earth as a ''horizontally'' layered body of finite conductivity but requires a large amount of computational time. The performances of both methods are compared when the substorm current system can be approximated by an infinitely long electrojet flowing over a flat earth. In this case it appears that for most substorm modeling problems it is sufficient to treat the earth as a perfect conductor. The depth of this perfect conductor below the earth's surface should be selected in function of the source frequency content
Stella, J. C.; Battles, J. J.; McBride, J. R.; Orr, B. K.
2007-12-01
In the Central Valley of California, pioneer cottonwood and willow species dominate the near-river forests. Historically, seedling recruitment for these disturbance-adapted species coincided with spring floods. Changes in flow timing and magnitude due to river regulation have decreased the success of seedling cohorts and contributed to the decline of these riparian tree populations. In order to address gaps in our understanding of these species and potential restoration strategies, we field-calibrated a conceptual model of seedling recruitment for the dominant pioneer woody species, Populus fremontii, Salix gooddingii, and S. exigua. We conducted experiments to identify seedling desiccation thresholds and seed longevity, used field studies to measure seedling competition and seasonal seed release patterns, and modeled interannual differences in dispersal timing using a degree-day model. These studies were integrated into a recruitment model that generates annual estimates of seedling density and bank elevation based on inputs of seasonal river discharge, seed dispersal timing, and seedling mortality from desiccation. The model predictions successfully captured interannual and species-level patterns in recruitment observed independently throughout a 20-km reach of the lower Tuolumne River from 2002-04. The model correctly predicted that seedling densities were highest in 2004 and lowest in 2003, and that S. exigua recruitment would be less extensive than for the two tree species. This work shows promise as both a quantitative approach linking hydrology, climate and plant community dynamics, and as a process-based framework for guiding flow releases and other management actions to restore riparian tree population along Central Valley rivers.
Pan, Xing-Hua; Zhu, Lu; Yao, Xiang; Liu, Ju-Fen; Li, Zi-An; Yang, Jian-Yong; Pang, Rong-Qing; Ruan, Guang-Ping
2016-12-01
The aim of this study was to establish a tree shrew metabolic syndrome model and demonstrate the utility of MSCs in treating metabolic syndrome. We used tree shrew umbilical cord mesenchymal stem cell (TS-UC-MSC) transplantation for the treatment of metabolic syndrome to demonstrate the clinical application of these stem cells and to provide a theoretical basis and reference methods for this treatment. Tree shrew metabolic syndrome model showed significant insulin resistance, high blood sugar, lipid metabolism disorders, and hypertension, consistent with the diagnostic criteria. TS-UC-MSC transplantation at 16 weeks significantly reduced blood sugar and lipid levels, improved insulin resistance and the regulation of insulin secretion, and reduced the expression levels of the pro-inflammatory cytokines IL-1 and IL-6 (P metabolic syndrome model and showed that MSC migrate in diseased organs and can attenuate metabolic syndrome severity in a tree shrew model.
Observability analysis for model-based fault detection and sensor selection in induction motors
International Nuclear Information System (INIS)
Nakhaeinejad, Mohsen; Bryant, Michael D
2011-01-01
Sensors in different types and configurations provide information on the dynamics of a system. For a specific task, the question is whether measurements have enough information or whether the sensor configuration can be changed to improve the performance or to reduce costs. Observability analysis may answer the questions. This paper presents a general algorithm of nonlinear observability analysis with application to model-based diagnostics and sensor selection in three-phase induction motors. A bond graph model of the motor is developed and verified with experiments. A nonlinear observability matrix based on Lie derivatives is obtained from state equations. An observability index based on the singular value decomposition of the observability matrix is obtained. Singular values and singular vectors are used to identify the most and least observable configurations of sensors and parameters. A complex step derivative technique is used in the calculation of Jacobians to improve the computational performance of the observability analysis. The proposed algorithm of observability analysis can be applied to any nonlinear system to select the best configuration of sensors for applications of model-based diagnostics, observer-based controller, or to determine the level of sensor redundancy. Observability analysis on induction motors provides various sensor configurations with corresponding observability indices. Results show the redundancy levels for different sensors, and provide a sensor selection guideline for model-based diagnostics, and for observer-based controllers. The results can also be used for sensor fault detection and to improve the reliability of the system by increasing the redundancy level in measurements
A simplified cervix model in response to induction balloon in pre-labour
2013-01-01
Background Induction of labour is poorly understood even though it is performed in 20% of births in the United States. One method of induction, the balloon dilator applied with traction to the interior os of the cervix, engages a softening process, permitting dilation and effacement to proceed until the beginning of active labour. The purpose of this work is to develop a simple model capable of reproducing the dilation and effacement effect in the presence of a balloon. Methods The cervix, anchored by the uterus and the endopelvic fascia was modelled in pre-labour. The spring-loaded, double sliding-joint, double pin-joint mechanism model was developed with a Modelica-compatible system, MapleSoft MapleSim 6.1, with a stiff Rosenbrock solver and 1E-4 absolute and relative tolerances. Total simulation time for pre-labour was seven hours and simulations ended at 4.50 cm dilation diameter and 2.25 cm effacement. Results Three spring configurations were tested: one pin joint, one sliding joint and combined pin-joint-sliding-joint. Feedback, based on dilation speed modulated the spring values, permitting controlled dilation. Dilation diameter speed was maintained at 0.692 cm·hr-1 over the majority of the simulation time. In the sliding-joint-only mode the maximum spring constant value was 23800 N·m-1. In pin-joint-only the maximum spring constant value was 0.41 N·m·rad-1. With a sliding-joint-pin-joint pair the maximum spring constants are 2000 N·m-1 and 0.41 N·m·rad-1, respectively. Conclusions The model, a simplified one-quarter version of the cervix, is capable of maintaining near-constant dilation rates, similar to published clinical observations for pre-labour. Lowest spring constant values are achieved when two springs are used, but nearly identical tracking of dilation speed can be achieved with only a pin joint spring. Initial and final values for effacement and dilation also match published clinical observations. These results provide a framework for
de Blas, J.; Criado, J. C.; Pérez-Victoria, M.; Santiago, J.
2018-03-01
We compute all the tree-level contributions to the Wilson coefficients of the dimension-six Standard-Model effective theory in ultraviolet completions with general scalar, spinor and vector field content and arbitrary interactions. No assumption about the renormalizability of the high-energy theory is made. This provides a complete ultraviolet/infrared dictionary at the classical level, which can be used to study the low-energy implications of any model of interest, and also to look for explicit completions consistent with low-energy data.
Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar
Chen, Qi
2015-08-01
Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.
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.
Forest, Loïc; Demongeot, Jacques; Demongeota, Jacques
2006-05-01
The radial growth of conifer trees proceeds from the dynamics of a merismatic tissue called vascular cambium or cambium. Cambium is a thin layer of active proliferating cells. The purpose of this paper was to model the main characteristics of cambial activity and its consecutive radial growth. Cell growth is under the control of the auxin hormone indole-3-acetic. The model is composed of a discrete part, which accounts for cellular proliferation, and a continuous part involving the transport of auxin. Cambium is modeled in a two-dimensional cross-section by a cellular automaton that describes the set of all its constitutive cells. Proliferation is defined as growth and division of cambial cells under neighbouring constraints, which can eliminate some cells from the cambium. The cell-growth rate is determined from auxin concentration, calculated with the continuous model. We studied the integration of each elementary cambial cell activity into the global coherent movement of macroscopic morphogenesis. Cases of normal and abnormal growth of Pinus radiata (D. Don) are modelled. Abnormal growth includes deformed trees where gravity influences auxin transport, producing heterogeneous radial growth. Cross-sectional microscopic views are also provided to validate the model's hypothesis and results.
Trimming a hazard logic tree with a new model-order-reduction technique
Porter, Keith; Field, Edward; 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.
Energy Technology Data Exchange (ETDEWEB)
Walaszek, Damian [University of Warsaw, Faculty of Chemistry, Biological and Chemical Research Centre, Żwirki i Wigury 101, 02-089 Warszawa (Poland); Laboratory for Analytical Chemistry, Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland); Senn, Marianne; Wichser, Adrian [Laboratory for Analytical Chemistry, Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland); Faller, Markus [Laboratory for Jointing Technology and Corrosion, Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland); Wagner, Barbara; Bulska, Ewa [University of Warsaw, Faculty of Chemistry, Biological and Chemical Research Centre, Żwirki i Wigury 101, 02-089 Warszawa (Poland); Ulrich, Andrea [Laboratory for Analytical Chemistry, Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, CH-8600 Dübendorf (Switzerland)
2014-09-01
This work describes an evaluation of a strategy for multi-elemental analysis of typical ancient bronzes (copper, lead bronze and tin bronze) by means of laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS).The samples originating from archeological experiments on ancient metal smelting processes using direct reduction in a ‘bloomery’ furnace as well as historical casting techniques were investigated with the use of the previously proposed analytical procedure, including metallurgical observation and preliminary visual estimation of the homogeneity of the samples. The results of LA-ICPMS analysis were compared to the results of bulk composition obtained by X-ray fluorescence spectrometry (XRF) and by inductively coupled plasma mass spectrometry (ICPMS) after acid digestion. These results were coherent for most of the elements confirming the usefulness of the proposed analytical procedure, however the reliability of the quantitative information about the content of the most heterogeneously distributed elements was also discussed in more detail. - Highlights: • The previously proposed procedure was evaluated by analysis of model copper alloys. • The LA-ICPMS results were comparable to the obtained by means of XRF and ICPMS. • LA-ICPMS results indicated the usefulness of the proposed analytical procedure.
International Nuclear Information System (INIS)
Ghoggal, A.; Zouzou, S.E.; Razik, H.; Sahraoui, M.; Khezzar, A.
2009-01-01
This paper describes an improved method for the modeling of axial and radial eccentricities in induction motors (IM). The model is based on an extension of the modified winding function approach (MWFA) which allows for all harmonics of the magnetomotive force (MMF) to be taken into account. It is shown that a plane view of IM gets easily the motor inductances and reduces considerably the calculation process. The described technique includes accurately the slot skewing effect and leads to pure analytical expressions of the inductances in case of radial eccentricity. In order to model the static, dynamic or mixed axial eccentricity, three suitable alternatives are explained. Unlike the previous proposals, the discussed alternatives take into account all the harmonics of the inverse of air-gap function without any development in Fourier series. Simulation results as well as experimental verifications prove the usefulness and the effectiveness of the proposed 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 model for the induction of bone cancer by 224Ra
International Nuclear Information System (INIS)
Groer, P.G.; Marshall, J.H.
1976-01-01
A mathematical model for the transformation of normal endosteal cells into malignant tumor cells by α-irradiation is applied to 224 Ra. The model postulates that a normal endosteal cell near the bone surface is transformed into a malignant cell by three consecutive events. The first two events are the initiation events. The probability of their occurrence is proportional to the absorbed endosteal dose and they generate dormant tumor cells. These dormant tumor cells are promoted by the third event, the promotion event. The probability of this last event is proportional to the rate of bone remodeling but independent of the radiation dose. In competition with these transformig events is the killing of any endosteal cell by α-irradiation. Killing is balanced by replacement of killed endosteal cells by normal stem cells. This model provides the following interesting predictions for the human 224 Ra cases. 1) After the decay of 224 Ra the tumor rate decreases exponentially at a rate proportional to the bone turnover rate. 2) For exposure to the same dose the model predicts an increased number of tumors for protacted exposure (i.e. exposure at a lower dose rate). Implications of this model for the therapy of ankylosing spondylitis are discussed. Statistical procedures are suggested for comparison of this theoretical model with the existing data on the induction of osteosarcomas by 224 Ra in man. (orig.) [de
Classifiability-based omnivariate decision trees.
Li, Yuanhong; Dong, Ming; Kothari, Ravi
2005-11-01
Top-down induction of decision trees is a simple and powerful method of pattern classification. In a decision tree, each node partitions the available patterns into two or more sets. New nodes are created to handle each of the resulting partitions and the process continues. A node is considered terminal if it satisfies some stopping criteria (for example, purity, i.e., all patterns at the node are from a single class). Decision trees may be univariate, linear multivariate, or nonlinear multivariate depending on whether a single attribute, a linear function of all the attributes, or a nonlinear function of all the attributes is used for the partitioning at each node of the decision tree. Though nonlinear multivariate decision trees are the most powerful, they are more susceptible to the risks of overfitting. In this paper, we propose to perform model selection at each decision node to build omnivariate decision trees. The model selection is done using a novel classifiability measure that captures the possible sources of misclassification with relative ease and is able to accurately reflect the complexity of the subproblem at each node. The proposed approach is fast and does not suffer from as high a computational burden as that incurred by typical model selection algorithms. Empirical results over 26 data sets indicate that our approach is faster and achieves better classification accuracy compared to statistical model select algorithms.
Ebrahimi, Mehregan; Ebrahimie, Esmaeil; Bull, C Michael
2015-08-01
The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision-tree models for species' translocation, we used data on the short-term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision-tree algorithms (decision tree, decision-tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. © 2015 Society for Conservation Biology.
Diamantopoulou, Maria J.; Milios, Elias; Doganos, Dimitrios; Bistinas, Ioannis
2009-01-01
In the management of restoration reforestations or recreational reforestations of trees, the density of the planted trees and the site conditions can influence the growth and bole volume of the dominant tree. The ability to influence growth of these trees in a reforestation contributes greatly to
van Veen, S H C M; van Kleef, R C; van de Ven, W P M M; van Vliet, R C J A
2018-02-01
This study explores the predictive power of interaction terms between the risk adjusters in the Dutch risk equalization (RE) model of 2014. Due to the sophistication of this RE-model and the complexity of the associations in the dataset (N = ~16.7 million), there are theoretically more than a million interaction terms. We used regression tree modelling, which has been applied rarely within the field of RE, to identify interaction terms that statistically significantly explain variation in observed expenses that is not already explained by the risk adjusters in this RE-model. The interaction terms identified were used as additional risk adjusters in the RE-model. We found evidence that interaction terms can improve the prediction of expenses overall and for specific groups in the population. However, the prediction of expenses for some other selective groups may deteriorate. Thus, interactions can reduce financial incentives for risk selection for some groups but may increase them for others. Furthermore, because regression trees are not robust, additional criteria are needed to decide which interaction terms should be used in practice. These criteria could be the right incentive structure for risk selection and efficiency or the opinion of medical experts. Copyright © 2017 John Wiley & Sons, Ltd.
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.
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.
Shentu, Nanying; Zhang, Hongjian; Li, Qing; Zhou, Hongliang; Tong, Renyuan; Li, Xiong
2012-01-01
Deep displacement observation is one basic means of landslide dynamic study and early warning monitoring and a key part of engineering geological investigation. In our previous work, we proposed a novel electromagnetic induction-based deep displacement sensor (I-type) to predict deep horizontal displacement and a theoretical model called equation-based equivalent loop approach (EELA) to describe its sensing characters. However in many landslide and related geological engineering cases, both horizontal displacement and vertical displacement vary apparently and dynamically so both may require monitoring. In this study, a II-type deep displacement sensor is designed by revising our I-type sensor to simultaneously monitor the deep horizontal displacement and vertical displacement variations at different depths within a sliding mass. Meanwhile, a new theoretical modeling called the numerical integration-based equivalent loop approach (NIELA) has been proposed to quantitatively depict II-type sensors' mutual inductance properties with respect to predicted horizontal displacements and vertical displacements. After detailed examinations and comparative studies between measured mutual inductance voltage, NIELA-based mutual inductance and EELA-based mutual inductance, NIELA has verified to be an effective and quite accurate analytic model for characterization of II-type sensors. The NIELA model is widely applicable for II-type sensors' monitoring on all kinds of landslides and other related geohazards with satisfactory estimation accuracy and calculation efficiency.
Directory of Open Access Journals (Sweden)
Xiong Li
2011-12-01
Full Text Available Deep displacement observation is one basic means of landslide dynamic study and early warning monitoring and a key part of engineering geological investigation. In our previous work, we proposed a novel electromagnetic induction-based deep displacement sensor (I-type to predict deep horizontal displacement and a theoretical model called equation-based equivalent loop approach (EELA to describe its sensing characters. However in many landslide and related geological engineering cases, both horizontal displacement and vertical displacement vary apparently and dynamically so both may require monitoring. In this study, a II-type deep displacement sensor is designed by revising our I-type sensor to simultaneously monitor the deep horizontal displacement and vertical displacement variations at different depths within a sliding mass. Meanwhile, a new theoretical modeling called the numerical integration-based equivalent loop approach (NIELA has been proposed to quantitatively depict II-type sensors’ mutual inductance properties with respect to predicted horizontal displacements and vertical displacements. After detailed examinations and comparative studies between measured mutual inductance voltage, NIELA-based mutual inductance and EELA-based mutual inductance, NIELA has verified to be an effective and quite accurate analytic model for characterization of II-type sensors. The NIELA model is widely applicable for II-type sensors’ monitoring on all kinds of landslides and other related geohazards with satisfactory estimation accuracy and calculation efficiency.
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
Identifying type 1 and type 2 diabetic cases using administrative data: a tree-structured model.
Lo-Ciganic, Weihsuan; Zgibor, Janice C; Ruppert, Kristine; Arena, Vincent C; Stone, Roslyn A
2011-05-01
To date, few administrative diabetes mellitus (DM) registries have distinguished type 1 diabetes mellitus (T1DM) from type 2 diabetes mellitus (T2DM). Using a classification tree model, a prediction rule was developed to distinguish T1DM from T2DM in a large administrative database. The Medical Archival Retrieval System at the University of Pittsburgh Medical Center included administrative and clinical data from January 1, 2000, through September 30, 2009, for 209,647 DM patients aged ≥18 years. Probable cases (8,173 T1DM and 125,111 T2DM) were identified by applying clinical criteria to administrative data. Nonparametric classification tree models were fit using TIBCO Spotfire S+ 8.1 (TIBCO Software), with model size based on 10-fold cross validation. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of T1DM were estimated. The main predictors that distinguished T1DM from T2DM are age <40 years; International Classification of Disease, 9th revision, codes of T1DM or T2DM diagnosis; inpatient oral hypoglycemic agent use; inpatient insulin use; and episode(s) of diabetic ketoacidosis diagnosis. Compared with a complex clinical algorithm, the tree-structured model to predict T1DM had 92.8% sensitivity, 99.3% specificity, 89.5% PPV, and 99.5% NPV. The preliminary predictive rule appears to be promising. Being able to distinguish between DM subtypes in administrative databases will allow large-scale subtype-specific analyses of medical care costs, morbidity, and mortality. © 2011 Diabetes Technology Society.
The risk factors of laryngeal pathology in Korean adults using a decision tree model.
Byeon, Haewon
2015-01-01
The purpose of this study was to identify risk factors affecting laryngeal pathology in the Korean population and to evaluate the derived prediction model. Cross-sectional study. Data were drawn from the 2008 Korea National Health and Nutritional Examination Survey. The subjects were 3135 persons (1508 male and 2114 female) aged 19 years and older living in the community. The independent variables were age, sex, occupation, smoking, alcohol drinking, and self-reported voice problems. A decision tree analysis was done to identify risk factors for predicting a model of laryngeal pathology. The significant risk factors of laryngeal pathology were age, gender, occupation, smoking, and self-reported voice problem in decision tree model. Four significant paths were identified in the decision tree model for the prediction of laryngeal pathology. Those identified as high risk groups for laryngeal pathology included those who self-reported a voice problem, those who were males in their 50s who did not recognize a voice problem, those who were not economically active males in their 40s, and male workers aged 19 and over and under 50 or 60 and over who currently smoked. The results of this study suggest that individual risk factors, such as age, sex, occupation, health behavior, and self-reported voice problem, affect the onset of laryngeal pathology in a complex manner. Based on the results of this study, early management of the high-risk groups is needed for the prevention of laryngeal pathology. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Teolis, D.S.; Zarewczynski, S.A.; Detar, H.L.
2012-01-01
The reactor trip system (RTS) and engineered safety features actuation system (ESFAS) in nuclear power plants utilizes instrumentation and control (IC) to provide automatic protection against unsafe and improper reactor operation during steady-state and transient power operations. During normal operating conditions, various plant parameters are continuously monitored to assure that the plant is operating in a safe state. In response to deviations of these parameters from pre-determined set points, the protection system will initiate actions required to maintain the reactor in a safe state. These actions may include shutting down the reactor by opening the reactor trip breakers and actuation of safety equipment based on the situation. The RTS and ESFAS are represented in probabilistic risk assessments (PRAs) to reflect the impact of their contribution to core damage frequency (CDF). The reactor protection systems (RPS) in existing nuclear power plants are generally analog based and there is general consensus within the PRA community on fault tree modeling of these systems. In new plants, such as AP1000 plant, the RPS is based on digital technology. Digital systems are more complex combinations of hardware components and software. This combination of complex hardware and software can result in the presence of faults and failure modes unique to a digital RPS. The United States Nuclear Regulatory Commission (NRC) is currently performing research on the development of probabilistic models for digital systems for inclusion in PRAs; however, no consensus methodology exists at this time. Westinghouse is currently updating the AP1000 plant PRA to support initial operation of plants currently under construction in the United States. The digital RPS is modeled using fault tree methodology similar to that used for analog based systems. This paper presents high level descriptions of a typical analog based RPS and of the AP1000 plant digital RPS. Application of current fault
Modelling of the draining of a molten glass heated by induction
International Nuclear Information System (INIS)
Lima-Da-Silva, Marcio
2014-01-01
This thesis is part of the development of a new technology of oxides melting in a furnace heated by induction. The technology studied involves strong interactions between electromagnetic, thermal and hydrodynamic phenomena in a flow with physical properties strongly dependents of the temperature. The aim of the thesis is the modelling of the process by coupling closely the Joule heating, the mechanical stirring and the draining of the furnace. The modeling of the time evolution of the interface between glass and air during the emptying of the cold crucible was performed. Regarding the methodology, we chose to combine two scientific codes: Flux for the electromagnetic calculation and Fluent for thermal-hydraulics. The evolution of the free surface was treated by the multiphasic method 'Volume-Of-Fluid - VOF' and the mechanical stirring by the 'Moving Reference Frame' and the 'Sliding Mesh'. First of all, we considered the draining of a tank filled with a silicon oil of high-viscosity without mechanical stirring. This initial model took into account studies of hydraulic similarity between the silicon oil and the glass. Then we superimposed the forced flow creates by the mechanical stirrer, the thermal and the electromagnetic phenomena in order to model the flow of the molten glass. The final model can provide various parameters, including the time needed to drain the furnace, the heat transfer flux and the time evolution of the mass flow rate and of the temperature inside de furnace. (author) [fr
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 software is used to perform the stability analysis of the parallel connected induction motor drive under unbalanced load conditions. It is very simple compared with the methods discussed so far to study the performance of the drive under unbalanced load conditions. Control design and simulation toolkits...... are used to model the drive system and to study the stability analysis. Simulation is done for various operating conditions and the stability investigation is performed for different load conditions and difference in stator and rotor resistances among the two motors....
Removal of model proteins by means of low-pressure inductively coupled plasma discharge
Energy Technology Data Exchange (ETDEWEB)
Kylian, O; Rauscher, H; Gilliland, D; Bretagnol, F; Rossi, F [European Commission, Joint Research Centre, Institute for Health and Consumer Protection, Via E Fermi 2749, 21027 Ispra (Italy)], E-mail: francois.rossi@jrc.it
2008-05-07
Surgical instruments are intended to come into direct contact with the patients' tissues and thus interact with their first immune defence system. Therefore they have to be cleaned, sterilized and decontaminated, in order to prevent any kind of infections and inflammations or to exclude the possibility of transmission of diseases. From this perspective, the removal of protein residues from their surfaces constitutes new challenges, since certain proteins exhibit high resistance to commonly used sterilization and decontamination techniques and hence are difficult to remove without inducing major damages to the object treated. Therefore new approaches must be developed for that purpose and the application of non-equilibrium plasma discharges represents an interesting option. The possibility to effectively remove model proteins (bovine serum albumin, lysozyme and ubiquitin) from surfaces of different materials (Si wafer, glass, polystyrene and gold) by means of inductively coupled plasma discharges sustained in different argon containing mixtures is demonstrated and discussed in this paper.
Removal of model proteins by means of low-pressure inductively coupled plasma discharge
Kylián, O.; Rauscher, H.; Gilliland, D.; Brétagnol, F.; Rossi, F.
2008-05-01
Surgical instruments are intended to come into direct contact with the patients' tissues and thus interact with their first immune defence system. Therefore they have to be cleaned, sterilized and decontaminated, in order to prevent any kind of infections and inflammations or to exclude the possibility of transmission of diseases. From this perspective, the removal of protein residues from their surfaces constitutes new challenges, since certain proteins exhibit high resistance to commonly used sterilization and decontamination techniques and hence are difficult to remove without inducing major damages to the object treated. Therefore new approaches must be developed for that purpose and the application of non-equilibrium plasma discharges represents an interesting option. The possibility to effectively remove model proteins (bovine serum albumin, lysozyme and ubiquitin) from surfaces of different materials (Si wafer, glass, polystyrene and gold) by means of inductively coupled plasma discharges sustained in different argon containing mixtures is demonstrated and discussed in this paper.
Electrical vehicle drive control based on finite element induction motor model
Energy Technology Data Exchange (ETDEWEB)
Kandianis, T.; Kladas, A.G.; Manias, S.N.; Tegopoulos, J.A. [National Technical Univ., Athens (Greece)
1997-03-01
In electrical vehicle applications, AC drives have become attractive rivals of DC drives due to the evolution in semiconductor technology. A paramount concern in such applications is the overall efficiency of the motor and its PWM controller. In this paper, the methodology for determination of an induction motor model including parameter variations for different operating conditions is presented. The method is based on finite elements, and alternative techniques enabling to derive the equivalent circuit parameters from the field solution are described and discussed. The suitability of different techniques for the consideration of time variations in the application considered, such as complex variables and time stepping techniques, has been commented. The derived parameters are in good agreement with the low frequency response of the motor when supplied by a PWM inverter.
Shao, Q; Rowe, R C; York, P
2007-06-01
This study has investigated an artificial intelligence technology - model trees - as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been well established and widely applied in the pharmaceutical product formulation fields. The predictability of generated models was validated on unseen data and judged by correlation coefficient R(2). Output from the model tree analyses produced multivariate linear equations which predicted tablet tensile strength, disintegration time, and drug dissolution profiles of similar quality to neural network models. However, additional and valuable knowledge hidden in the formulation database was extracted from these equations. It is concluded that, as a transparent technology, model trees are useful tools to formulators.
Chemotherapy-Induced Apoptosis in a Transgenic Model of Neuroblastoma Proceeds Through p53 Induction
Directory of Open Access Journals (Sweden)
Louis Chesler
2008-11-01
Full Text Available Chemoresistance in neuroblastoma is a significant issue complicating treatment of this common pediatric solid tumor. MYCN-amplified neuroblastomas are infrequently mutated at p53 and are chemosensitive at diagnosis but acquire p53 mutations and chemoresistance with relapse. Paradoxically, Myc-driven transformation is thought to require apoptotic blockade. We used the TH-MYCN transgenic murine model to examine the role of p53-driven apoptosis on neuroblastoma tumorigenesis and the response to chemotherapy. Tumors formed with high penetrance and low latency in p53-haploinsufficient TH-MYCN mice. Cyclophosphamide (CPM induced a complete remission in p53 wild type TH-MYCN tumors, mirroring the sensitivity of childhood neuroblastoma to this agent. Treated tumors showed a prominent proliferation block, induction of p53 protein, and massive apoptosis proceeding through induction of the Bcl-2 homology domain-3-only proteins PUMA and Bim, leading to the activation of Bax and cleavage of caspase-3 and -9. Apoptosis induced by CPM was reduced in p53-haploinsufficient tumors. Treatment of MYCN-expressing human neuroblastoma cell lines with CPM induced apoptosis that was suppressible by siRNA to p53. Taken together, the results indicate that the p53 pathway plays a significant role in opposing MYCN-driven oncogenesis in a mouse model of neuroblastoma and that basal inactivation of the pathway is achieved in progressing tumors. This, in part, explains the striking sensitivity of such tumors to chemotoxic agents that induce p53-dependent apoptosis and is consistent with clinical observations that therapy-associated mutations in p53 are a likely contributor to the biology of tumors at relapse and secondarily mediate resistance to therapy.
Wildenberg, Manon E; Levin, Alon D; Ceroni, Alessandro; Guo, Zhen; Koelink, Pim J; Hakvoort, Theodorus B M; Westera, Liset; Bloemendaal, Felicia M; Brandse, Johannan F; Simmons, Alison; D'Haens, Geert R; Ebner, Daniel; van den Brink, Gijs R
2017-12-04
Regulatory macrophages play a critical role in tissue repair, and we have previously shown that anti-tumour necrosis factor [TNF] antibodies induce these macrophages in vitro and in vivo in IBD patients. The induction of regulatory macrophages can be potentiated using the combination of anti-TNF and thiopurines, consistent with the enhanced efficacy of this combination therapy described in clinical trials. As thiopurines are unfortunately associated with significant side effects, we here aimed to identify alternatives for combination therapy with anti-TNF, using the macrophage induction model as a screening tool. Mixed lymphocyte reactions were treated with anti-TNF and a library of 1600 drug compounds. Induction of CD14+CD206+ macrophages was analysed by flow cytometry. Positive hits were validated in vitro and in the T cell transfer model of colitis. Among the 98 compounds potentiating the induction of regulatory macrophages by anti-TNF were six benzimidazoles, including albendazole. Albendazole treatment in the presence of anti-TNF resulted in alterations in the tubulin skeleton and signalling though AMPK, which was required for the enhanced induction. Combination therapy also increased expression levels of the immunoregulatory cytokine IL-10. In vivo, albendazole plus anti-TNF combination therapy was superior to monotherapy in a model of colitis, in terms of both induction of regulatory macrophages and improvement of clinical symptoms. Albendazole enhances the induction of regulatory macrophages by anti-TNF and potentiates clinical efficacy in murine colitis. Given its favourable safety profile, these data indicate that the repurposing of albendazole may be a novel option for anti-TNF combination therapy in IBD.
T. Sghaier; M. Tome; J. Tome; M. Sanchez-Gonzalez; I. Cañellas; R. Calama
2013-01-01
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 f...
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.
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. Copyright © 2013 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Jacob, P.; Paretzke, H.G.; Roth, P.
2000-01-01
The Association Contract covers a range of research domains that are important to the Radiation Protection Research Action, especially in the areas 'Evaluation of Radiation Risks' and 'Understanding Radiation Mechanisms and Epidemiology'. Three research projects concentrate on radiation dosimetry research and two projects on the modelling of radiation carcinogenesis. The following list gives an overview on the topics and responsible scientific project leaders of the Association Contract: Study of radiation fields and dosimetry at aviation altitudes. Biokinetics and dosimetry of incorporated radionuclides. Dose reconstruction. Biophysical models for the induction of cancer by radiation. Experimental data for the induction of cancer by radiation of different qualities. (orig.)
DEFF Research Database (Denmark)
Svensson, Elin; Borraccino, Antoine; Meyer Forsting, Alexander Raul
configurations. The wind speeds were reconstructed using both a onedimensional and two-dimensional induction model to test the sensitivity towards the wind-induction model. In all cases, the sensitivity of the reconstructed wind speed was determined from the wind speed error and root mean square error (RMSE...... based on the NKE sensitivity analysis results. Based on these results, it is recommended to configure nacelle lidars to measure at approximately 3-5 ranges. The minimum distance should be configured to roughly 0.5 rotor diameters (Drot) while it is recommended that the maximum range lay within 1-1.5Drot...
Induction of T-cell memory by a dendritic cell vaccine: a computational model.
Pappalardo, Francesco; Pennisi, Marzio; Ricupito, Alessia; Topputo, Francesco; Bellone, Matteo
2014-07-01
Although results from phase III clinical trials substantially support the use of prophylactic and therapeutic vaccines against cancer, what has yet to be defined is how many and how frequent boosts are needed to sustain a long-lasting and protecting memory T-cell response against tumor antigens. Common experience is that such preclinical tests require the sacrifice of a relatively large number of animals, and are particularly time- and money-consuming. As a first step to overcome these hurdles, we have developed an ordinary differential equation model that includes all relevant entities (such as activated cytotoxic T lymphocytes and memory T cells), and investigated the induction of immunological memory in the context of wild-type mice injected with a dendritic cell-based vaccine. We have simulated the biological behavior both in the presence and in the absence of memory T cells. Comparing results of ex vivo and in silico experiments, we show that the model is able to envisage the expansion and persistence of antigen-specific memory T cells. The model might be applicable to more complex vaccination schedules and substantially in any biological condition of prime-boosting. The model is fully described in the article. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Ram P Sharma
Full Text Available Height to crown base (HCB of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L. Karst. and European beech (Fagus sylvatica L. on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM, basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure or Hegyi's competition index (HCI-spatially explicit measure, and basal area proportion of a species of interest (BAPOR, respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset. The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce, 0.85 (beech] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce, 0.83 (beech]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed
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
Comparison of universal kriging and regression tree modelling for soil property mapping
Kempen, Bas
2013-04-01
Geostatistical modelling approaches have been dominating the field of digital soil mapping (DSM) since its inception in the early 1980s. In recent years, however, machine learning methods such as classification and regression trees, random forests, and neural networks have quickly gained popularity among researchers in the DSM community. The increased use of these methods has largely gone at the cost of geostatistical approaches. Despite the apparent shift in the application of DSM methods from geostatistics to machine learning, quantitative comparisons of the prediction performance of these methods are largely lacking. The aims of this research, therefore, are: i) to map two soil properties (topsoil organic matter content and thickness of the peat layer in the soil profile) using regression tree (RT) modelling and universal kriging (UK), and ii) to compare the prediction performance of these methods with independent data obtained by probability sampling. Using such data for validation does not only yield a statistically valid and unbiased estimates of the map accuracy, but it also allows a statistical comparison of the accuracies of the maps generated by the two methods. The topsoil organic matter content and the thickness of the peat layer were mapped for a 14,000 ha area in the province of Drenthe, The Netherlands. The calibration dataset contained soil property observations at 1,715 sites. The covariates used include layers derived from soil and paleogeography maps, land cover, relative elevation, drainage class, land reclamation period, elevation change, and historic land use. The validation dataset contained 125 observations selected by stratified simple random sampling of the study area. The root mean squared error (RMSE) of the soil organic matter map obtained by RT modelling was 0.603 log(%), that of the map obtained by UK 0.595 log(%). The difference in map accuracy was not significant (p = 0.377). The RMSE of the peat thickness map obtained by RT
Kang, G.; Kim, J.
2017-12-01
This study investigated the tree's effect on wind comfort at pedestrian height in an urban area using a computational fluid dynamics (CFD) model. We implemented the tree's drag parameterization scheme to the CFD model and validated the simulated results against the wind-tunnel measurement data as well as LES data via several statistical methods. The CFD model underestimated (overestimated) the concentrations on the leeward (windward) walls inside the street canyon in the presence of trees, because the CFD model can't resolve the latticed cage and can't reflect the concentration increase and decrease caused by the latticed cage in the simulations. However, the scalar pollutants' dispersion simulated by the CFD model was quite similar to that in the wind-tunnel measurement in pattern and magnitude, on the whole. The CFD model overall satisfied the statistical validation indices (root normalized mean square error, geometric mean variance, correlation coefficient, and FAC2) but failed to satisfy the fractional bias and geometric mean bias due to the underestimation on the leeward wall and overestimation on the windward wall, showing that its performance was comparable to the LES's performance. We applied the CFD model to evaluation of the trees' effect on the pedestrian's wind-comfort in an urban area. To investigate sensory levels for human activities, the wind-comfort criteria based on Beaufort wind-force scales (BWSs) were used. In the tree-free scenario, BWS 4 and 5 (unpleasant condition for sitting long and sitting short, respectively) appeared in the narrow spaces between buildings, in the upwind side of buildings, and the unobstructed areas. In the tree scenario, BWSs decreased by 1 3 grade inside the campus of Pukyong National University located in the target area, which indicated that trees planted in the campus effectively improved pedestrian's wind comfort.
Fuzzy virtual reference model sensorless tracking control for linear induction motors.
Hung, Cheng-Yao; Liu, Peter; Lian, Kuang-Yow
2013-06-01
This paper introduces a fuzzy virtual reference model (FVRM) synthesis method for linear induction motor (LIM) speed sensorless tracking control. First, we represent the LIM as a Takagi-Sugeno fuzzy model. Second, we estimate the immeasurable mover speed and secondary flux by a fuzzy observer. Third, to convert the speed tracking control into a stabilization problem, we define the internal desired states for state tracking via an FVRM. Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are threefold: 1) simplified approach--speed tracking problem converted into stabilization problem; 2) omit need of actual reference model--FVRM generates internal desired states; and 3) unification of controller and observer design--control objectives are formulated into an LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness.
Dynamic investigation of mode transition in inductively coupled plasma with a hybrid model
International Nuclear Information System (INIS)
Zhao Shuxia; Gao Fei; Wang Younian
2009-01-01
Industrial inductively coupled plasma (ICP) sources are always operated in low gas pressure 10-100 mTorr, therefore in order to accurately investigate the mode transition of ICP, we developed our pure fluid model (2009 J. Appl. Phys. 105 083306) into a hybrid fluid/Monte Carlo (MC) model, where the MC part is exploited to take in more dynamic characteristics of electrons and self-consistently calculate the rate coefficients and electron temperature used in the fluid module, and more crucially to study the electron energy distribution function (EEDF) evolution with mode transition. Due to the introduction of the nonlocal property of the electrons at relatively low pressures, the dependences of the plasma density on the coil current, including the mode transitions, are distinctly different at low and high pressures when simulated by this improved hybrid model (HM), while the trends for different pressures obtained from the original pure fluid model (PFM) are the same in all cases. Furthermore, the computed peaks of the electron density profile by the HM shift from the discharge centre in the E mode to the intense inductive field heating area (about half of the radius of the reaction chamber under the dielectric window) in H mode. In addition, the electron temperature profiles of two modes under different pressures simulated by HM are totally higher than the results of PFM. When the pressure is low, there is a minimum exhibited in the bulk plasma of the electron temperature profiles of the E mode, and along with the mode transition the distribution area of low temperature is substantially reduced. Moreover, this phenomenon disappears when the gas pressure is increased. Accompanied by this, the calculated EEDF of the E mode in the low pressure also demonstrates an absolutely dominant low energy electron fraction (about ≤5 eV); while transforming to the H discharge most of the electrons carry an energy of 1-10 eV. The tendencies of the calculated EEDF evolution with
Development of a parametric containment event tree model for a severe BWR accident
Energy Technology Data Exchange (ETDEWEB)
Okkonen, T. [OTO-Consulting Ay, Helsinki (Finland)
1995-04-01
A containment event tree (CET) is built for analysis of severe accidents at the TVO boiling water reactor (BWR) units. Parametric models of severe accident progression and fission product behaviour are developed and integrated in order to construct a compact and self-contained Level 2 PSA model. The model can be easily updated to correspond to new research results. The analyses of the study are limited to severe accidents starting from full-power operation and leading to core melting, and are focused mainly on the use and effects of the dedicated severe accident management (SAM) systems. Severe accident progression from eight plant damage states (PDS), involving different pre-core-damage accident evolution, is examined, but the inclusion of their relative or absolute probabilities, by integration with Level 1, is deferred to integral safety assessments. (33 refs., 5 figs., 7 tabs.).
Directory of Open Access Journals (Sweden)
Requeno José Ignacio
2014-12-01
Full Text Available Model checking is a generic verification technique that allows the phylogeneticist to focus on models and specifications instead of on implementation issues. Phylogenetic trees are considered as transition systems over which we interrogate phylogenetic questions written as formulas of temporal logic. Nonetheless, standard logics become insufficient for certain practices of phylogenetic analysis since they do not allow the inclusion of explicit time and probabilities. The aim of this paper is to extend the application of model checking techniques beyond qualitative phylogenetic properties and adapt the existing logical extensions and tools to the field of phylogeny. The introduction of time and probabilities in phylogenetic specifications is motivated by the study of a real example: the analysis of the ratio of lactose intolerance in some populations and the date of appearance of this phenotype.
Advanced Modeling of Cold Crucible Induction Melting for Process Control and Optimization
Energy Technology Data Exchange (ETDEWEB)
J. A. Roach; D. B. Lopukh; A. P. Martynov; B. S. Polevodov; S. I. Chepluk
2008-02-01
The Idaho National Laboratory (INL) and the St. Petersburg Electrotechnical University “LETI” (ETU) have collaborated on development and validation of an advanced numerical model of the cold crucible induction melting (CCIM) process. This work was conducted in support of the Department of Energy (DOE) Office of Environmental Management Technology and Engineering (EM-20) International Program. The model predicts quasi-steady state temperature distributions, convection cell configurations, and flow field velocities for a fully established melt of low conductivity non-magnetic materials at high frequency operations. The INL/ETU ANSYS© finite element model is unique in that it has been developed specifically for processing borosilicate glass (BSG) and other glass melts. Specifically, it accounts for the temperature dependency of key material properties, some of which change by orders of magnitude within the temperature ranges experienced (temperature differences of 500oC are common) in CCIM processing of glass, including density, viscosity, thermal conductivity, specific heat, and electrical resistivity. These values, and their responses to temperature changes, are keys to understanding the melt characteristics. Because the model has been validated, it provides the capability to conduct parametric studies to understand operational sensitivities and geometry effects. Additionally, the model can be used to indirectly determine difficult to measure material properties at higher temperatures such as resistivity, thermal conductivity and emissivity. The model can also be used to optimize system design and to predict operational behavior for specific materials and system configurations, allowing automated feedback control. This becomes particularly important when designing melter systems for full-scale industrial applications.
Anderson, Weston; Guikema, Seth; Zaitchik, Ben; Pan, William
2014-01-01
Obtaining accurate small area estimates of population is essential for policy and health planning but is often difficult in countries with limited data. In lieu of available population data, small area estimate models draw information from previous time periods or from similar areas. This study focuses on model-based methods for estimating population when no direct samples are available in the area of interest. To explore the efficacy of tree-based models for estimating population density, we compare six different model structures including Random Forest and Bayesian Additive Regression Trees. Results demonstrate that without information from prior time periods, non-parametric tree-based models produced more accurate predictions than did conventional regression methods. Improving estimates of population density in non-sampled areas is important for regions with incomplete census data and has implications for economic, health and development policies.
Bourdier, Thomas; Cordonnier, Thomas; Kunstler, Georges; Piedallu, Christian; Lagarrigues, Guillaume; Courbaud, Benoit
2016-01-01
Plant structural diversity is usually considered as beneficial for ecosystem functioning. For instance, numerous studies have reported positive species diversity-productivity relationships in plant communities. However, other aspects of structural diversity such as individual size inequality have been far less investigated. In forests, tree size inequality impacts directly tree growth and asymmetric competition, but consequences on forest productivity are still indeterminate. In addition, the effect of tree size inequality on productivity is likely to vary with species shade-tolerance, a key ecological characteristic controlling asymmetric competition and light resource acquisition. Using plot data from the French National Geographic Agency, we studied the response of stand productivity to size inequality for ten forest species differing in shade tolerance. We fitted a basal area stand production model that included abiotic factors, stand density, stand development stage and a tree size inequality index. Then, using a forest dynamics model we explored whether mechanisms of light interception and light use efficiency could explain the tree size inequality effect observed for three of the ten species studied. Size inequality negatively affected basal area increment for seven out of the ten species investigated. However, this effect was not related to the shade tolerance of these species. According to the model simulations, the negative tree size inequality effect could result both from reduced total stand light interception and reduced light use efficiency. Our results demonstrate that negative relationships between size inequality and productivity may be the rule in tree populations. The lack of effect of shade tolerance indicates compensatory mechanisms between effect on light availability and response to light availability. Such a pattern deserves further investigations for mixed forests where complementarity effects between species are involved. When studying the
Processing UAV data for Digital Terrain Model generation and tree detection
Plesioanu, Alin; Anca, Paula; Zavate, Lucian; Calugaru, Andreea; Vasile, Cristian; Sandric, Ionut
2017-04-01
This paper presents a method for processing point cloud data obtained from UAV flights in order to generate Digital Terrain Models (DTM) and to detect fine-scale objects (trees) in a complex sub-urban environment. The processing workflow is based on integrating tools from LAStools, SAGA GIS software and R into the ArcGIS Platform. The point cloud data is first obtained in Drone2Map by fotogrammetric processing. Further, by using the ground classification (lasground) module from LAStools software, an inital sample of ground points is classified. This step is improved by applying smoothing and thresholding spatial filters on the points in SAGA and R in order to enhance the classification of ground points. The final classified points are interpolated into a DTM surface with superior precision. A method for tree detection by combining circular and rectangular spatial filters is presented, that uses the obtained DTM surface as a basis for the Canopy Height Model (CHM) calculation. A case study is presented for a sub-urban area of Bucharest, the city of Mogosoaia
Application of a hybrid association rules/decision tree model for drought monitoring
Nourani, Vahid; Molajou, Amir
2017-12-01
The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.
A Skull Might Lie: Modeling Ancestral Ranges and Diet from Genes and Shape of Tree Squirrels.
Pečnerová, Patrícia; Moravec, Jiří C; Martínková, Natália
2015-11-01
Tropical forests of Central and South America represent hotspots of biological diversity. Tree squirrels of the tribe Sciurini are an excellent model system for the study of tropical biodiversity as these squirrels disperse exceptional distances, and after colonizing the tropics of the Central and South America, they have diversified rapidly. Here, we compare signals from DNA sequences with morphological signals using pictures of skulls and computational simulations. Phylogenetic analyses reveal step-wise geographic divergence across the Northern Hemisphere. In Central and South America, tree squirrels form two separate clades, which split from a common ancestor. Simulations of ancestral distributions show western Amazonia as the epicenter of speciation in South America. This finding suggests that wet tropical forests on the foothills of Andes possibly served as refugia of squirrel diversification during Pleistocene climatic oscillations. Comparison of phylogeny and morphology reveals one major discrepancy: Microsciurus species are a single clade morphologically but are polyphyletic genetically. Modeling of morphology-diet relationships shows that the only group of species with a direct link between skull shape and diet are the bark-gleaning insectivorous species of Microsciurus. This finding suggests that the current designation of Microsciurus as a genus is based on convergent ecologically driven changes in morphology. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Self-consistent multidimensional electron kinetic model for inductively coupled plasma sources
Dai, Fa Foster
Inductively coupled plasma (ICP) sources have received increasing interest in microelectronics fabrication and lighting industry. In 2-D configuration space (r, z) and 2-D velocity domain (νθ,νz), a self- consistent electron kinetic analytic model is developed for various ICP sources. The electromagnetic (EM) model is established based on modal analysis, while the kinetic analysis gives the perturbed Maxwellian distribution of electrons by solving Boltzmann-Vlasov equation. The self- consistent algorithm combines the EM model and the kinetic analysis by updating their results consistently until the solution converges. The closed-form solutions in the analytical model provide rigorous and fast computing for the EM fields and the electron kinetic behavior. The kinetic analysis shows that the RF energy in an ICP source is extracted by a collisionless dissipation mechanism, if the electron thermovelocity is close to the RF phase velocities. A criterion for collisionless damping is thus given based on the analytic solutions. To achieve uniformly distributed plasma for plasma processing, we propose a novel discharge structure with both planar and vertical coil excitations. The theoretical results demonstrate improved uniformity for the excited azimuthal E-field in the chamber. Non-monotonic spatial decay in electric field and space current distributions was recently observed in weakly- collisional plasmas. The anomalous skin effect is found to be responsible for this phenomenon. The proposed model successfully models the non-monotonic spatial decay effect and achieves good agreements with the measurements for different applied RF powers. The proposed analytical model is compared with other theoretical models and different experimental measurements. The developed model is also applied to two kinds of ICP discharges used for electrodeless light sources. One structure uses a vertical internal coil antenna to excite plasmas and another has a metal shield to prevent the
Estimating species trees from unrooted gene trees.
Liu, Liang; Yu, Lili
2011-10-01
In this study, we develop a distance method for inferring unrooted species trees from a collection of unrooted gene trees. The species tree is estimated by the neighbor joining (NJ) tree built from a distance matrix in which the distance between two species is defined as the average number of internodes between two species across gene trees, that is, average gene-tree internode distance. The distance method is named NJ(st) to distinguish it from the original NJ method. Under the coalescent model, we show that if gene trees are known or estimated correctly, the NJ(st) method is statistically consistent in estimating unrooted species trees. The simulation results suggest that NJ(st) and STAR (another coalescence-based method for inferring species trees) perform almost equally well in estimating topologies of species trees, whereas the Bayesian coalescence-based method, BEST, outperforms both NJ(st) and STAR. Unlike BEST and STAR, the NJ(st) method can take unrooted gene trees to infer species trees without using an outgroup. In addition, the NJ(st) method can handle missing data and is thus useful in phylogenomic studies in which data sets often contain missing loci for some individuals.
Directory of Open Access Journals (Sweden)
Andrzej Rusek
2008-01-01
Full Text Available The mathematical model of cylindrical linear induction motor (C-LIM fed via frequency converter is presented in the paper. The model was developed in order to analyze numerically the transient states. Problems concerning dynamics of ac-machines especially linear induction motor are presented in [1 – 7]. Development of C-LIM mathematical model is based on circuit method and analogy to rotary induction motor. The analogy between both: (a stator and rotor windings of rotary induction motor and (b winding of primary part of C-LIM (inductor and closed current circuits in external secondary part of C-LIM (race is taken into consideration. The equations of C-LIM mathematical model are presented as matrix together with equations expressing each vector separately. A computational analysis of selected transient states of C-LIM fed via frequency converter is presented in the paper. Two typical examples of C-LIM operation are considered for the analysis: (a starting the motor at various static loads and various synchronous velocities and (b reverse of the motor at the same operation conditions. Results of simulation are presented as transient responses including transient electromagnetic force, transient linear velocity and transient phase current.
Induction heating process of ferromagnetic filled carbon nanotubes based on 3-D model
Wiak, Sławomir; Firych-Nowacka, Anna; Smółka, Krzysztof; Pietrzak, Łukasz; Kołaciński, Zbigniew; Szymański, Łukasz
2017-12-01
Since their discovery by Iijima in 1991 [1], carbon nanotubes have sparked unwavering interest among researchers all over the world. This is due to the unique properties of carbon nanotubes (CNTs). Carbon nanotubes have excellent mechanical and electrical properties with high chemical and thermal stability. In addition, carbon nanotubes have a very large surface area and are hollow inside. This gives a very broad spectrum of nanotube applications, such as in combination with polymers as polymer composites in the automotive, aerospace or textile industries. At present, many methods of nanotube synthesis are known [2, 3, 4, 5, 6]. It is also possible to use carbon nanotubes in biomedical applications [7, 8, 9, 10, 11, 12, 13, 14], including the destruction of cancer cells using iron-filled carbon nanotubes in the hyperthermia process. Computer modelling results of Fe-CNTs induction heating process are presented in the paper. As an object used for computer model creation, Fe-CNTs were synthesized by the authors using CCVD technique.
Development of an experimental model of neutrophilic pulmonary response induction in mice
Directory of Open Access Journals (Sweden)
Leonardo Araújo Pinto
2003-08-01
Full Text Available BACKGROUND: Several lung diseases are characterized by a predominantly neutrophilic inflammation. A better understanding of the mechanisms of action of some drugs on the airway inflammation of such diseases may bring advances to the treatment. OBJECTIVE: To develop a method to induce pulmonary neutrophilic response in mice, without active infection. METHODS: Eight adult Swiss mice were used. The study group (n = 4 received an intranasal challenge with 1 x 10(12 CFU/ml of Pseudomonas aeruginosa (Psa, frozen to death. The control group (n = 4 received an intranasal challenge with saline solution. Two days after the intranasal challenge, a bronchoalveolar lavage (BAL was performed with total cell and differential cellularity counts. RESULTS: The total cell count was significantly higher in the group with Psa, as compared to the control group (median of 1.17 x 10(6 and 0.08 x 10(6, respectively, p = 0.029. In addition to this, an absolute predominance of neutrophils was found in the differential cellularity of the mice that had received the Psa challenge. CONCLUSIONS: The model of inducing a neutrophilic pulmonary disease using frost-dead bacteria was successfully developed. This neutrophilic inflammatory response induction model in Swiss mice lungs may be an important tool for testing the anti-inflammatory effect of some antimicrobial drugs on the inflammation of the lower airways.
Newman, Gregory A.
2014-01-01
Many geoscientific applications exploit electrostatic and electromagnetic fields to interrogate and map subsurface electrical resistivity—an important geophysical attribute for characterizing mineral, energy, and water resources. In complex three-dimensional geologies, where many of these resources remain to be found, resistivity mapping requires large-scale modeling and imaging capabilities, as well as the ability to treat significant data volumes, which can easily overwhelm single-core and modest multicore computing hardware. To treat such problems requires large-scale parallel computational resources, necessary for reducing the time to solution to a time frame acceptable to the exploration process. The recognition that significant parallel computing processes must be brought to bear on these problems gives rise to choices that must be made in parallel computing hardware and software. In this review, some of these choices are presented, along with the resulting trade-offs. We also discuss future trends in high-performance computing and the anticipated impact on electromagnetic (EM) geophysics. Topics discussed in this review article include a survey of parallel computing platforms, graphics processing units to multicore CPUs with a fast interconnect, along with effective parallel solvers and associated solver libraries effective for inductive EM modeling and imaging.
A multi-channel magnetic induction tomography measurement system for human brain model imaging
International Nuclear Information System (INIS)
Xu, Zheng; Luo, Haijun; He, Wei; He, Chuanhong; Song, Xiaodong; Zahng, Zhanglong
2009-01-01
This paper proposes a multi-channel magnetic induction tomography measurement system for biological conductivity imaging in a human brain model. A hemispherical glass bowl filled with a salt solution is used as the human brain model; meanwhile, agar blocks of different conductivity are placed in the solution to simulate the intracerebral hemorrhage. The excitation and detection coils are fixed co-axially, and the axial gradiometer is used as the detection coil in order to cancel the primary field. On the outer surface of the glass bowl, 15 sensor units are arrayed in two circles as measurement parts, and a single sensor unit for canceling the phase drift is placed beside the glass bowl. The phase sensitivity of our system is 0.204°/S m −1 with the excitation frequency of 120 kHz and the phase noise is in the range of −0.03° to +0.05°. Only the coaxial detection coil is available for each excitation coil; therefore, 15 phase data are collected in each measurement turn. Finally, the two-dimensional images of conductivity distribution are obtained using an interpolation algorithm. The frequency-varying experiment indicates that the imaging quality becomes better as the excitation frequency is increased
Moussu, Hélène; Van Overtvelt, Laurence; Horiot, Stéphane; Tourdot, Sophie; Airouche, Sabi; Zuercher, Adrian; Holvoet, Sébastien; Prioult, Guénolée; Nutten, Sophie; Mercenier, Annick; Mascarell, Laurent; Moingeon, Philippe
2012-01-01
Enhancing clinical efficacy remains a major goal in allergen-specific immunotherapy. In this study, we tested three strains of bifidobacteria as candidate adjuvants for sublingual allergy vaccines. Probiotic candidates were evaluated in human monocyte-derived dendritic cell (h-DC) maturation and CD4(+) T-cell polarization in vitro models and further tested in murine models of sublingual immunotherapy in BALB/c mice sensitized to either ovalbumin or birch pollen. Bifidobacterium adolescentis, B. bifidum and B. longum induced h-DC maturation and polarized naïve CD4(+) T cells toward interferon-γ and interleukin-10 production. B. bifidum increased CD25(high), Foxp3(+) cells within CD4(+) T lymphocytes and was the most potent inducer of interferon-γ in Th2-skewed peripheral blood mononuclear cells and h-DC T-cell cocultures. It also induced a significant decrease in airway hyperresponsiveness in BALB/c mice sensitized to ovalbumin. Sublingual administration of B. bifidum together with recombinant Bet v 1 enhanced tolerance induction in BALB/c mice sensitized to birch pollen, with a downregulation of both airway hyperresponsiveness, lung inflammation and Bet v 1-specific Th2 responses. Due to its capacity to reorient established Th2 responses toward Th1/regulatory T-cell profiles, B. bifidum represents a valid candidate adjuvant for specific immunotherapy of type I allergies. Copyright © 2011 S. Karger AG, Basel.
Fan, Yang; Qi, Yang; Bing, Gao; Rong, Xia; Yanjie, Le; Iroegbu, Paul Ikechukwu
2018-03-01
Water tree is the predominant defect in high-voltage crosslinked polyethylene cables. The microscopic mechanism in the discharge process is not fully understood; hence, a drawback is created towards an effective method to evaluate the insulation status. In order to investigate the growth of water tree, a plasma-chemical model is developed. The dynamic characteristics of the discharge process including voltage waveform, current waveform, electron density, electric potential, and electric field intensity are analyzed. Our results show that the distorted electric field is the predominant contributing factor of electron avalanche formation, which inevitably leads to the formation of pulse current. In addition, it is found that characteristic parameters such as the pulse width and pulse number have a great relevance to the length of water tree. Accordingly, the growth of water tree can be divided into the initial stage, development stage, and pre-breakdown stage, which provides a reference for evaluating the deteriorated stages of crosslinked polyethylene cables.
Directory of Open Access Journals (Sweden)
Margaret Penner
2015-11-01
Full Text Available Airborne Laser Scanning (ALS metrics have been used to develop area-based forest inventories; these metrics generally include estimates of stand-level, per hectare values and mean tree attributes. Tree-based ALS inventories contain desirable information on individual tree dimensions and how much they vary within a stand. Adding size class distribution information to area-based inventories helps to bridge the gap between area- and tree-based inventories. This study examines the potential of ALS and stereo-imagery point clouds to predict size class distributions in a boreal forest. With an accurate digital terrain model, both ALS and imagery point clouds can be used to estimate size class distributions with comparable accuracy. Nonparametric imputations were generally superior to parametric imputations; this may be related to the limitation of using a unimodal Weibull function on a relatively small prediction unit (e.g., 400 m2.
Nóbrega, Cristina; Pereira, Fernando L.; Valente, Fernanda
2015-04-01
Water losses associated to the rainfall interception process by trees can be an important component of the local hydrologic balance and must be accounted for when implementing any sustainable water management programme. In many dry areas of the Mediterranean region where agro-forestry systems are common, those programmes are crucial to foster adequate water conservation measures. Recent studies have shown that the evaluation of interception loss in sparse forests or tree plantations should be made for individual trees, being the total value determined as the sum of the individual contributions. Following this approach, rainfall interception was measured and modelled over two years, in an isolated Olea europeaea L. tree, in a traditional low-density olive grove in Castelo Branco, central Portugal. Total interception loss over the experimental period was 243.5 mm, on a tree crown projected area basis, corresponding to 18.0% of gross rainfall (Pg). Modelling made for each rainfall event using the sparse version of the Gash model, slightly underestimated interception loss with a value of 240.5 mm, i.e., 17.8 % ofPg. Modelling quality, evaluated according to a number of criteria, was good, allowing the conclusion that the methodology used was adequate. Modelling was also made on a daily basis, i.e., assuming a single storm per rainday. In this case, interception loss was overestimated by 12%, mostly because 72% of all rainfall events lasted for more than a day.
Effect of tree roots on a shear zone: modeling reinforced shear stress.
Kazutoki Abe; Robert R. Ziemer
1991-01-01
Tree roots provide important soil reinforcement that impoves the stability of hillslopes. After trees are cut and roots begin to decay, the frequency of slope failures can increase. To more fully understand the mechanics of how tree roots reinforce soil, fine sandy soil containing pine roots was placed in a large shear box in horizontal layers and sheared across a...
Weiss, C. J.
2014-12-01
At the macroscopic scale, where the e-folding distance of low-frequency electromagnetic fields in conductive geomaterials is much larger than the size of organized heterogeneities such as fracture sets or laminations that constitute the geologic texture therein, electrical properties can be conveniently approximated by a generalized 3x3 tensor σ. Less convenient, however, are the algorithmic consequences of this approximation in electromagnetic modeling of 3D induction methods for geophysical exploration. Previous efforts at modelling generalized anisotropy with finite differences on a staggered Cartesian grid (e.g. Weiss and Newman, 2002; Wang and Fang, 2001) are posed in terms of the electric field with its governing "curl-curl" equation and well-documented null-space issues at low induction numbers. In contrast, Weiss (2013) proposed an alternate full-physics formulation in terms of Lorenz-gauged magentic vector A and electric scalar Φ potentials (Project APhiD) that eliminates the troublesome curl-curl operator, with ultrabroadband examples drawn from geologies with scalar, isotropic conductivity over the frequency range 10-2-1010 Hz. Here, the anisotropic theory presented in Weiss (2013) is implemented with finite differences on a Cartesian grid. Briefly stated, in this theoretical approach the conductivity tensor σ is split in terms of a rotationally-invariant isotropic conductivity σ* = ⅓ Tr(σ) and the residual σ - σ*I. This splitting decomposes the resulting finite difference coefficient matrix K into the sum Kiso + Kaniso, where the Kiso term is the coefficient matrix for the isotropic medium σ*, thus enabling reuse of the various routines previously developed for computing matrix coefficients in the isotropic case. Treatment of anisotropy is algorithmically therefore restricted to computing the coefficients in the sparse matrix Kaniso consisting of simple inner products of (σ - σ*I) · (A-∇Φ) and their divergence. In keeping with the