Sample records for oblique decision trees

  1. Real-Time Speech/Music Classification With a Hierarchical Oblique Decision Tree

    DTIC Science & Technology

    2008-04-01

    REAL-TIME SPEECH/ MUSIC CLASSIFICATION WITH A HIERARCHICAL OBLIQUE DECISION TREE Jun Wang, Qiong Wu, Haojiang Deng, Qin Yan Institute of Acoustics...time speech/ music classification with a hierarchical oblique decision tree. A set of discrimination features in frequency domain are selected...handle signals without discrimination and can not work properly in the existence of multimedia signals. This paper proposes a real-time speech/ music

  2. Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

    DOEpatents

    Cantu-Paz, Erick [Oakland, CA; Kamath, Chandrika [Tracy, CA

    2006-06-13

    A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.

  3. Automated Decision Tree Classification of Corneal Shape

    PubMed Central

    Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

    2011-01-01

    Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification

  4. Decision trees in epidemiological research.

    PubMed

    Venkatasubramaniam, Ashwini; Wolfson, Julian; Mitchell, Nathan; Barnes, Timothy; JaKa, Meghan; French, Simone

    2017-01-01

    In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions. However, identifying relevant subgroups can be challenging with standard statistical methods. We review the literature on decision trees, a family of techniques for partitioning the population, on the basis of covariates, into distinct subgroups who share similar values of an outcome variable. We compare two decision tree methods, the popular Classification and Regression tree (CART) technique and the newer Conditional Inference tree (CTree) technique, assessing their performance in a simulation study and using data from the Box Lunch Study, a randomized controlled trial of a portion size intervention. Both CART and CTree identify homogeneous population subgroups and offer improved prediction accuracy relative to regression-based approaches when subgroups are truly present in the data. An important distinction between CART and CTree is that the latter uses a formal statistical hypothesis testing framework in building decision trees, which simplifies the process of identifying and interpreting the final tree model. We also introduce a novel way to visualize the subgroups defined by decision trees. Our novel graphical visualization provides a more scientifically meaningful characterization of the subgroups identified by decision trees. Decision trees are a useful tool for identifying homogeneous subgroups defined by combinations of individual characteristics. While all decision tree techniques generate subgroups, we advocate the use of the newer CTree technique due to its simplicity and ease of interpretation.

  5. Decision Tree Phytoremediation

    DTIC Science & Technology

    1999-12-01

    aromatic hydrocarbons, and landfill leachates . Phytoremediation has been used for point and nonpoint source hazardous waste control. 1.2 Types of... Phytoremediation Prepared by Interstate Technology and Regulatory Cooperation Work Group Phytoremediation Work Team December 1999 Decision Tree...1999 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Phytoremediation Decision Tree 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

  6. Objective consensus from decision trees.

    PubMed

    Putora, Paul Martin; Panje, Cedric M; Papachristofilou, Alexandros; Dal Pra, Alan; Hundsberger, Thomas; Plasswilm, Ludwig

    2014-12-05

    Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

  7. TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

    PubMed

    Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

    2018-01-01

    Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

  8. Two Trees: Migrating Fault Trees to Decision Trees for Real Time Fault Detection on International Space Station

    NASA Technical Reports Server (NTRS)

    Lee, Charles; Alena, Richard L.; Robinson, Peter

    2004-01-01

    We started from ISS fault trees example to migrate to decision trees, presented a method to convert fault trees to decision trees. The method shows that the visualizations of root cause of fault are easier and the tree manipulating becomes more programmatic via available decision tree programs. The visualization of decision trees for the diagnostic shows a format of straight forward and easy understands. For ISS real time fault diagnostic, the status of the systems could be shown by mining the signals through the trees and see where it stops at. The other advantage to use decision trees is that the trees can learn the fault patterns and predict the future fault from the historic data. The learning is not only on the static data sets but also can be online, through accumulating the real time data sets, the decision trees can gain and store faults patterns in the trees and recognize them when they come.

  9. VC-dimension of univariate decision trees.

    PubMed

    Yildiz, Olcay Taner

    2015-02-01

    In this paper, we give and prove the lower bounds of the Vapnik-Chervonenkis (VC)-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and the number of inputs. Via a search algorithm that calculates the VC-dimension of univariate decision trees exhaustively, we show that our VC-dimension bounds are tight for simple trees. To verify that the VC-dimension bounds are useful, we also use them to get VC-generalization bounds for complexity control using structural risk minimization in decision trees, i.e., pruning. Our simulation results show that structural risk minimization pruning using the VC-dimension bounds finds trees that are more accurate as those pruned using cross validation.

  10. Comprehensive decision tree models in bioinformatics.

    PubMed

    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

  11. Comprehensive Decision Tree Models in Bioinformatics

    PubMed Central

    Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

    2012-01-01

    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 with binary class

  12. Safety validation of decision trees for hepatocellular carcinoma.

    PubMed

    Wang, Xian-Qiang; Liu, Zhe; Lv, Wen-Ping; Luo, Ying; Yang, Guang-Yun; Li, Chong-Hui; Meng, Xiang-Fei; Liu, Yang; Xu, Ke-Sen; Dong, Jia-Hong

    2015-08-21

    To evaluate a different decision tree for safe liver resection and verify its efficiency. A total of 2457 patients underwent hepatic resection between January 2004 and December 2010 at the Chinese PLA General Hospital, and 634 hepatocellular carcinoma (HCC) patients were eligible for the final analyses. Post-hepatectomy liver failure (PHLF) was identified by the association of prothrombin time < 50% and serum bilirubin > 50 μmol/L (the "50-50" criteria), which were assessed at day 5 postoperatively or later. The Swiss-Clavien decision tree, Tokyo University-Makuuchi decision tree, and Chinese consensus decision tree were adopted to divide patients into two groups based on those decision trees in sequence, and the PHLF rates were recorded. The overall mortality and PHLF rate were 0.16% and 3.0%. A total of 19 patients experienced PHLF. The numbers of patients to whom the Swiss-Clavien, Tokyo University-Makuuchi, and Chinese consensus decision trees were applied were 581, 573, and 622, and the PHLF rates were 2.75%, 2.62%, and 2.73%, respectively. Significantly more cases satisfied the Chinese consensus decision tree than the Swiss-Clavien decision tree and Tokyo University-Makuuchi decision tree (P < 0.01,P < 0.01); nevertheless, the latter two shared no difference (P = 0.147). The PHLF rate exhibited no significant difference with respect to the three decision trees. The Chinese consensus decision tree expands the indications for hepatic resection for HCC patients and does not increase the PHLF rate compared to the Swiss-Clavien and Tokyo University-Makuuchi decision trees. It would be a safe and effective algorithm for hepatectomy in patients with hepatocellular carcinoma.

  13. Decision-Tree Formulation With Order-1 Lateral Execution

    NASA Technical Reports Server (NTRS)

    James, Mark

    2007-01-01

    A compact symbolic formulation enables mapping of an arbitrarily complex decision tree of a certain type into a highly computationally efficient multidimensional software object. The type of decision trees to which this formulation applies is that known in the art as the Boolean class of balanced decision trees. Parallel lateral slices of an object created by means of this formulation can be executed in constant time considerably less time than would otherwise be required. Decision trees of various forms are incorporated into almost all large software systems. A decision tree is a way of hierarchically solving a problem, proceeding through a set of true/false responses to a conclusion. By definition, a decision tree has a tree-like structure, wherein each internal node denotes a test on an attribute, each branch from an internal node represents an outcome of a test, and leaf nodes represent classes or class distributions that, in turn represent possible conclusions. The drawback of decision trees is that execution of them can be computationally expensive (and, hence, time-consuming) because each non-leaf node must be examined to determine whether to progress deeper into a tree structure or to examine an alternative. The present formulation was conceived as an efficient means of representing a decision tree and executing it in as little time as possible. The formulation involves the use of a set of symbolic algorithms to transform a decision tree into a multi-dimensional object, the rank of which equals the number of lateral non-leaf nodes. The tree can then be executed in constant time by means of an order-one table lookup. The sequence of operations performed by the algorithms is summarized as follows: 1. Determination of whether the tree under consideration can be encoded by means of this formulation. 2. Extraction of decision variables. 3. Symbolic optimization of the decision tree to minimize its form. 4. Expansion and transformation of all nested conjunctive

  14. Creating ensembles of decision trees through sampling

    DOEpatents

    Kamath, Chandrika; Cantu-Paz, Erick

    2005-08-30

    A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

  15. Uncertain decision tree inductive inference

    NASA Astrophysics Data System (ADS)

    Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

    2011-10-01

    Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

  16. The decision tree approach to classification

    NASA Technical Reports Server (NTRS)

    Wu, C.; Landgrebe, D. A.; Swain, P. H.

    1975-01-01

    A class of multistage decision tree classifiers is proposed and studied relative to the classification of multispectral remotely sensed data. The decision tree classifiers are shown to have the potential for improving both the classification accuracy and the computation efficiency. Dimensionality in pattern recognition is discussed and two theorems on the lower bound of logic computation for multiclass classification are derived. The automatic or optimization approach is emphasized. Experimental results on real data are reported, which clearly demonstrate the usefulness of decision tree classifiers.

  17. Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion

    NASA Astrophysics Data System (ADS)

    Jiang, San; Jiang, Wanshou

    2017-10-01

    The primary contribution of this paper is an efficient Structure from Motion (SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, an algorithm, considering spatial relationship constraints between image footprints, is designed for match pair selection with the assistance of UAV flight control data and oblique camera mounting angles. Second, a topological connection network (TCN), represented by an undirected weighted graph, is constructed from initial match pairs, which encodes the overlap areas and intersection angles into edge weights. Then, an algorithm, termed MST-Expansion, is proposed to extract the match graph from the TCN, where the TCN is first simplified by a maximum spanning tree (MST). By further analysis of the local structure in the MST, expansion operations are performed on the vertices of the MST for match graph enhancement, which is achieved by introducing critical connections in the expansion directions. Finally, guided by the match graph, an efficient SfM is proposed. Under extensive analysis and comparison, its performance is verified by using three oblique UAV datasets captured with different multi-camera systems. Experimental results demonstrate that the efficiency of image matching is improved, with speedup ratios ranging from 19 to 35, and competitive orientation accuracy is achieved from both relative bundle adjustment (BA) without GCPs (Ground Control Points) and absolute BA with GCPs. At the same time, images in the three datasets are successfully oriented. For the orientation of oblique UAV images, the proposed method can be a more efficient solution.

  18. Decision tree methods: applications for classification and prediction.

    PubMed

    Song, Yan-Yan; Lu, Ying

    2015-04-25

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

  19. Parallel object-oriented decision tree system

    DOEpatents

    Kamath,; Chandrika, Cantu-Paz [Dublin, CA; Erick, [Oakland, CA

    2006-02-28

    A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.

  20. Fast Image Texture Classification Using Decision Trees

    NASA Technical Reports Server (NTRS)

    Thompson, David R.

    2011-01-01

    Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

  1. The Decision Tree: A Tool for Achieving Behavioral Change.

    ERIC Educational Resources Information Center

    Saren, Dru

    1999-01-01

    Presents a "Decision Tree" process for structuring team decision making and problem solving about specific student behavioral goals. The Decision Tree involves a sequence of questions/decisions that can be answered in "yes/no" terms. Questions address reasonableness of the goal, time factors, importance of the goal, responsibilities, safety,…

  2. An automated approach to the design of decision tree classifiers

    NASA Technical Reports Server (NTRS)

    Argentiero, P.; Chin, R.; Beaudet, P.

    1982-01-01

    An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

  3. A survey of decision tree classifier methodology

    NASA Technical Reports Server (NTRS)

    Safavian, S. R.; Landgrebe, David

    1991-01-01

    Decision tree classifiers (DTCs) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps the most important feature of DTCs is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issues. After considering potential advantages of DTCs over single-state classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

  4. A survey of decision tree classifier methodology

    NASA Technical Reports Server (NTRS)

    Safavian, S. Rasoul; Landgrebe, David

    1990-01-01

    Decision Tree Classifiers (DTC's) are used successfully in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition. Perhaps, the most important feature of DTC's is their capability to break down a complex decision-making process into a collection of simpler decisions, thus providing a solution which is often easier to interpret. A survey of current methods is presented for DTC designs and the various existing issue. After considering potential advantages of DTC's over single stage classifiers, subjects of tree structure design, feature selection at each internal node, and decision and search strategies are discussed.

  5. Building of fuzzy decision trees using ID3 algorithm

    NASA Astrophysics Data System (ADS)

    Begenova, S. B.; Avdeenko, T. V.

    2018-05-01

    Decision trees are widely used in the field of machine learning and artificial intelligence. Such popularity is due to the fact that with the help of decision trees graphic models, text rules can be built and they are easily understood by the final user. Because of the inaccuracy of observations, uncertainties, the data, collected in the environment, often take an unclear form. Therefore, fuzzy decision trees becoming popular in the field of machine learning. This article presents a method that includes the features of the two above-mentioned approaches: a graphical representation of the rules system in the form of a tree and a fuzzy representation of the data. The approach uses such advantages as high comprehensibility of decision trees and the ability to cope with inaccurate and uncertain information in fuzzy representation. The received learning method is suitable for classifying problems with both numerical and symbolic features. In the article, solution illustrations and numerical results are given.

  6. Multivariate analysis of flow cytometric data using decision trees.

    PubMed

    Simon, Svenja; Guthke, Reinhard; Kamradt, Thomas; Frey, Oliver

    2012-01-01

    Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.

  7. Decision tree modeling using R.

    PubMed

    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.

  8. A framework for sensitivity analysis of decision trees.

    PubMed

    Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

    2018-01-01

    In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

  9. Decision Tree Approach for Soil Liquefaction Assessment

    PubMed Central

    Gandomi, Amir H.; Fridline, Mark M.; Roke, David A.

    2013-01-01

    In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view. PMID:24489498

  10. Decision tree approach for soil liquefaction assessment.

    PubMed

    Gandomi, Amir H; Fridline, Mark M; Roke, David A

    2013-01-01

    In the current study, the performances of some decision tree (DT) techniques are evaluated for postearthquake soil liquefaction assessment. A database containing 620 records of seismic parameters and soil properties is used in this study. Three decision tree techniques are used here in two different ways, considering statistical and engineering points of view, to develop decision rules. The DT results are compared to the logistic regression (LR) model. The results of this study indicate that the DTs not only successfully predict liquefaction but they can also outperform the LR model. The best DT models are interpreted and evaluated based on an engineering point of view.

  11. An Isometric Mapping Based Co-Location Decision Tree Algorithm

    NASA Astrophysics Data System (ADS)

    Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

    2018-05-01

    Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

  12. EEG feature selection method based on decision tree.

    PubMed

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

    2015-01-01

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

  13. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

    PubMed Central

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

  14. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

    PubMed

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

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

  15. Multi-test decision tree and its application to microarray data classification.

    PubMed

    Czajkowski, Marcin; Grześ, Marek; Kretowski, Marek

    2014-05-01

    The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the hierarchical process of human decision making. However, existing algorithms for learning decision trees have tendency to underfit gene expression data. The main aim of this work is to improve the performance and stability of decision trees with only a small increase in their complexity. We propose a multi-test decision tree (MTDT); our main contribution is the application of several univariate tests in each non-terminal node of the decision tree. We also search for alternative, lower-ranked features in order to obtain more stable and reliable predictions. Experimental validation was performed on several real-life gene expression datasets. Comparison results with eight classifiers show that MTDT has a statistically significantly higher accuracy than popular decision tree classifiers, and it was highly competitive with ensemble learning algorithms. The proposed solution managed to outperform its baseline algorithm on 14 datasets by an average 6%. A study performed on one of the datasets showed that the discovered genes used in the MTDT classification model are supported by biological evidence in the literature. This paper introduces a new type of decision tree which is more suitable for solving biological problems. MTDTs are relatively easy to analyze and much more powerful in modeling high dimensional microarray data than their popular counterparts. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. 15 CFR Supplement 1 to Part 732 - Decision Tree

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 15 Commerce and Foreign Trade 2 2010-01-01 2010-01-01 false Decision Tree 1 Supplement 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued) BUREAU... THE EAR Pt. 732, Supp. 1 Supplement 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6, 2004] ...

  17. 15 CFR Supplement 1 to Part 732 - Decision Tree

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 15 Commerce and Foreign Trade 2 2012-01-01 2012-01-01 false Decision Tree 1 Supplement 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued) BUREAU... THE EAR Pt. 732, Supp. 1 Supplement 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6, 2004] ...

  18. 15 CFR Supplement 1 to Part 732 - Decision Tree

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 15 Commerce and Foreign Trade 2 2011-01-01 2011-01-01 false Decision Tree 1 Supplement 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued) BUREAU... THE EAR Pt. 732, Supp. 1 Supplement 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6, 2004] ...

  19. Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior.

    PubMed

    Delgado-Gomez, D; Baca-Garcia, E; Aguado, D; Courtet, P; Lopez-Castroman, J

    2016-12-01

    Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Sequential decision tree using the analytic hierarchy process for decision support in rectal cancer.

    PubMed

    Suner, Aslı; Çelikoğlu, Can Cengiz; Dicle, Oğuz; Sökmen, Selman

    2012-09-01

    The aim of the study is to determine the most appropriate method for construction of a sequential decision tree in the management of rectal cancer, using various patient-specific criteria and treatments such as surgery, chemotherapy, and radiotherapy. An analytic hierarchy process (AHP) was used to determine the priorities of variables. Relevant criteria used in two decision steps and their relative priorities were established by a panel of five general surgeons. Data were collected via a web-based application and analyzed using the "Expert Choice" software specifically developed for the AHP. Consistency ratios in the AHP method were calculated for each set of judgments, and the priorities of sub-criteria were determined. A sequential decision tree was constructed for the best treatment decision process, using priorities determined by the AHP method. Consistency ratios in the AHP method were calculated for each decision step, and the judgments were considered consistent. The tumor-related criterion "presence of perforation" (0.331) and the patient-surgeon-related criterion "surgeon's experience" (0.630) had the highest priority in the first decision step. In the second decision step, the tumor-related criterion "the stage of the disease" (0.230) and the patient-surgeon-related criterion "surgeon's experience" (0.281) were the paramount criteria. The results showed some variation in the ranking of criteria between the decision steps. In the second decision step, for instance, the tumor-related criterion "presence of perforation" was just the fifth. The consistency of decision support systems largely depends on the quality of the underlying decision tree. When several choices and variables have to be considered in a decision, it is very important to determine priorities. The AHP method seems to be effective for this purpose. The decision algorithm developed by this method is more realistic and will improve the quality of the decision tree. Copyright © 2012 Elsevier

  1. Decision tree and ensemble learning algorithms with their applications in bioinformatics.

    PubMed

    Che, Dongsheng; Liu, Qi; Rasheed, Khaled; Tao, Xiuping

    2011-01-01

    Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.

  2. MRI-based decision tree model for diagnosis of biliary atresia.

    PubMed

    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.

  3. RE-Powering’s Electronic Decision Tree

    EPA Pesticide Factsheets

    Developed by US EPA's RE-Powering America's Land Initiative, the RE-Powering Decision Trees tool guides interested parties through a process to screen sites for their suitability for solar photovoltaics or wind installations

  4. A Decision Tree for Nonmetric Sex Assessment from the Skull.

    PubMed

    Langley, Natalie R; Dudzik, Beatrix; Cloutier, Alesia

    2018-01-01

    This study uses five well-documented cranial nonmetric traits (glabella, mastoid process, mental eminence, supraorbital margin, and nuchal crest) and one additional trait (zygomatic extension) to develop a validated decision tree for sex assessment. The decision tree was built and cross-validated on a sample of 293 U.S. White individuals from the William M. Bass Donated Skeletal Collection. Ordinal scores from the six traits were analyzed using the partition modeling option in JMP Pro 12. A holdout sample of 50 skulls was used to test the model. The most accurate decision tree includes three variables: glabella, zygomatic extension, and mastoid process. This decision tree yielded 93.5% accuracy on the training sample, 94% on the cross-validated sample, and 96% on a holdout validation sample. Linear weighted kappa statistics indicate acceptable agreement among observers for these variables. Mental eminence should be avoided, and definitions and figures should be referenced carefully to score nonmetric traits. © 2017 American Academy of Forensic Sciences.

  5. Learning accurate very fast decision trees from uncertain data streams

    NASA Astrophysics Data System (ADS)

    Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

    2015-12-01

    Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.

  6. PRIA 3 Fee Determination Decision Tree

    EPA Pesticide Factsheets

    The PRIA 3 decision tree will help applicants requesting a pesticide registration or certain tolerance action to accurately identify the category of their application and the amount of the required fee before they submit the application.

  7. The decision tree classifier - Design and potential. [for Landsat-1 data

    NASA Technical Reports Server (NTRS)

    Hauska, H.; Swain, P. H.

    1975-01-01

    A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

  8. A new approach to enhance the performance of decision tree for classifying gene expression data.

    PubMed

    Hassan, Md; Kotagiri, Ramamohanarao

    2013-12-20

    Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

  9. Learning in data-limited multimodal scenarios: Scandent decision forests and tree-based features.

    PubMed

    Hor, Soheil; Moradi, Mehdi

    2016-12-01

    Incomplete and inconsistent datasets often pose difficulties in multimodal studies. We introduce the concept of scandent decision trees to tackle these difficulties. Scandent trees are decision trees that optimally mimic the partitioning of the data determined by another decision tree, and crucially, use only a subset of the feature set. We show how scandent trees can be used to enhance the performance of decision forests trained on a small number of multimodal samples when we have access to larger datasets with vastly incomplete feature sets. Additionally, we introduce the concept of tree-based feature transforms in the decision forest paradigm. When combined with scandent trees, the tree-based feature transforms enable us to train a classifier on a rich multimodal dataset, and use it to classify samples with only a subset of features of the training data. Using this methodology, we build a model trained on MRI and PET images of the ADNI dataset, and then test it on cases with only MRI data. We show that this is significantly more effective in staging of cognitive impairments compared to a similar decision forest model trained and tested on MRI only, or one that uses other kinds of feature transform applied to the MRI data. Copyright © 2016. Published by Elsevier B.V.

  10. IND - THE IND DECISION TREE PACKAGE

    NASA Technical Reports Server (NTRS)

    Buntine, W.

    1994-01-01

    A common approach to supervised classification and prediction in artificial intelligence and statistical pattern recognition is the use of decision trees. A tree is "grown" from data using a recursive partitioning algorithm to create a tree which has good prediction of classes on new data. Standard algorithms are CART (by Breiman Friedman, Olshen and Stone) and ID3 and its successor C4 (by Quinlan). As well as reimplementing parts of these algorithms and offering experimental control suites, IND also introduces Bayesian and MML methods and more sophisticated search in growing trees. These produce more accurate class probability estimates that are important in applications like diagnosis. IND is applicable to most data sets consisting of independent instances, each described by a fixed length vector of attribute values. An attribute value may be a number, one of a set of attribute specific symbols, or it may be omitted. One of the attributes is delegated the "target" and IND grows trees to predict the target. Prediction can then be done on new data or the decision tree printed out for inspection. IND provides a range of features and styles with convenience for the casual user as well as fine-tuning for the advanced user or those interested in research. IND can be operated in a CART-like mode (but without regression trees, surrogate splits or multivariate splits), and in a mode like the early version of C4. Advanced features allow more extensive search, interactive control and display of tree growing, and Bayesian and MML algorithms for tree pruning and smoothing. These often produce more accurate class probability estimates at the leaves. IND also comes with a comprehensive experimental control suite. IND consists of four basic kinds of routines: data manipulation routines, tree generation routines, tree testing routines, and tree display routines. The data manipulation routines are used to partition a single large data set into smaller training and test sets. The

  11. Evaluation of Decision Trees for Cloud Detection from AVHRR Data

    NASA Technical Reports Server (NTRS)

    Shiffman, Smadar; Nemani, Ramakrishna

    2005-01-01

    Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

  12. 15 CFR Supplement No 1 to Part 732 - Decision Tree

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 15 Commerce and Foreign Trade 2 2013-01-01 2013-01-01 false Decision Tree No Supplement No 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... THE EAR Pt. 732, Supp. 1 Supplement No 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6...

  13. 15 CFR Supplement No 1 to Part 732 - Decision Tree

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 15 Commerce and Foreign Trade 2 2014-01-01 2014-01-01 false Decision Tree No Supplement No 1 to Part 732 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... THE EAR Pt. 732, Supp. 1 Supplement No 1 to Part 732—Decision Tree ER06FE04.000 [69 FR 5687, Feb. 6...

  14. An automated approach to the design of decision tree classifiers

    NASA Technical Reports Server (NTRS)

    Argentiero, P.; Chin, P.; Beaudet, P.

    1980-01-01

    The classification of large dimensional data sets arising from the merging of remote sensing data with more traditional forms of ancillary data is considered. Decision tree classification, a popular approach to the problem, is characterized by the property that samples are subjected to a sequence of decision rules before they are assigned to a unique class. An automated technique for effective decision tree design which relies only on apriori statistics is presented. This procedure utilizes a set of two dimensional canonical transforms and Bayes table look-up decision rules. An optimal design at each node is derived based on the associated decision table. A procedure for computing the global probability of correct classfication is also provided. An example is given in which class statistics obtained from an actual LANDSAT scene are used as input to the program. The resulting decision tree design has an associated probability of correct classification of .76 compared to the theoretically optimum .79 probability of correct classification associated with a full dimensional Bayes classifier. Recommendations for future research are included.

  15. The value of decision tree analysis in planning anaesthetic care in obstetrics.

    PubMed

    Bamber, J H; Evans, S A

    2016-08-01

    The use of decision tree analysis is discussed in the context of the anaesthetic and obstetric management of a young pregnant woman with joint hypermobility syndrome with a history of insensitivity to local anaesthesia and a previous difficult intubation due to a tongue tumour. The multidisciplinary clinical decision process resulted in the woman being delivered without complication by elective caesarean section under general anaesthesia after an awake fibreoptic intubation. The decision process used is reviewed and compared retrospectively to a decision tree analytical approach. The benefits and limitations of using decision tree analysis are reviewed and its application in obstetric anaesthesia is discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis.

    PubMed

    Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela

    2018-01-19

    OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for

  17. The Decision Tree for Teaching Management of Uncertainty

    ERIC Educational Resources Information Center

    Knaggs, Sara J.; And Others

    1974-01-01

    A 'decision tree' consists of an outline of the patient's symptoms and a logic for decision and action. It is felt that this approach to the decisionmaking process better facilitates each learner's application of his own level of knowledge and skills. (Author)

  18. A universal hybrid decision tree classifier design for human activity classification.

    PubMed

    Chien, Chieh; Pottie, Gregory J

    2012-01-01

    A system that reliably classifies daily life activities can contribute to more effective and economical treatments for patients with chronic conditions or undergoing rehabilitative therapy. We propose a universal hybrid decision tree classifier for this purpose. The tree classifier can flexibly implement different decision rules at its internal nodes, and can be adapted from a population-based model when supplemented by training data for individuals. The system was tested using seven subjects each monitored by 14 triaxial accelerometers. Each subject performed fourteen different activities typical of daily life. Using leave-one-out cross validation, our decision tree produced average classification accuracies of 89.9%. In contrast, the MATLAB personalized tree classifiers using Gini's diversity index as the split criterion followed by optimally tuning the thresholds for each subject yielded 69.2%.

  19. Improved Frame Mode Selection for AMR-WB+ Based on Decision Tree

    NASA Astrophysics Data System (ADS)

    Kim, Jong Kyu; Kim, Nam Soo

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

  20. Predicting metabolic syndrome using decision tree and support vector machine methods.

    PubMed

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

    2016-05-01

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

  1. Using histograms to introduce randomization in the generation of ensembles of decision trees

    DOEpatents

    Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

    2005-02-22

    A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

  2. A Decision Tree for Psychology Majors: Supplying Questions as Well as Answers.

    ERIC Educational Resources Information Center

    Poe, Retta E.

    1988-01-01

    Outlines the development of a psychology careers decision tree to help faculty advise students plan their program. States that students using the decision tree may benefit by learning more about their career options and by acquiring better question-asking skills. (GEA)

  3. Solar and Wind Site Screening Decision Trees

    EPA Pesticide Factsheets

    EPA and NREL created a decision tree to guide state and local governments and other stakeholders through a process for screening sites for their suitability for future redevelopment with solar photovoltaic (PV) energy and wind energy.

  4. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.

    PubMed

    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.

  5. The Utility of Decision Trees in Oncofertility Care in Japan.

    PubMed

    Ito, Yuki; Shiraishi, Eriko; Kato, Atsuko; Haino, Takayuki; Sugimoto, Kouhei; Okamoto, Aikou; Suzuki, Nao

    2017-03-01

    To identify the utility and issues associated with the use of decision trees in oncofertility patient care in Japan. A total of 35 women who had been diagnosed with cancer, but had not begun anticancer treatment, were enrolled. We applied the oncofertility decision tree for women published by Gardino et al. to counsel a consecutive series of women on fertility preservation (FP) options following cancer diagnosis. Percentage of women who decided to undergo oocyte retrieval for embryo cryopreservation and the expected live-birth rate for these patients were calculated using the following equation: expected live-birth rate = pregnancy rate at each age per embryo transfer × (1 - miscarriage rate) × No. of cryopreserved embryos. Oocyte retrieval was performed for 17 patients (48.6%; mean ± standard deviation [SD] age, 36.35 ± 3.82 years). The mean ± SD number of cryopreserved embryos was 5.29 ± 4.63. The expected live-birth rate was 0.66. The expected live-birth rate with FP indicated that one in three oncofertility patients would not expect to have a live birth following oocyte retrieval and embryo cryopreservation. While the decision trees were useful as decision-making tools for women contemplating FP, in the context of the current restrictions on oocyte donation and the extremely small number of adoptions in Japan, the remaining options for fertility after cancer are limited. In order for cancer survivors to feel secure in their decisions, the decision tree may need to be adapted simultaneously with improvements to the social environment, such as greater support for adoption.

  6. Learning from examples - Generation and evaluation of decision trees for software resource analysis

    NASA Technical Reports Server (NTRS)

    Selby, Richard W.; Porter, Adam A.

    1988-01-01

    A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

  7. New Splitting Criteria for Decision Trees in Stationary Data Streams.

    PubMed

    Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Rutkowski, Leszek; Duda, Piotr; Jaworski, Maciej

    2018-06-01

    The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality. Therefore, there is an urgent need to develop new algorithms, which are both mathematically justified and characterized by good performance. In this paper, we address this problem by developing a family of new splitting criteria for classification in stationary data streams and investigating their probabilistic properties. The new criteria, derived using appropriate statistical tools, are based on the misclassification error and the Gini index impurity measures. The general division of splitting criteria into two types is proposed. Attributes chosen based on type- splitting criteria guarantee, with high probability, the highest expected value of split measure. Type- criteria ensure that the chosen attribute is the same, with high probability, as it would be chosen based on the whole infinite data stream. Moreover, in this paper, two hybrid splitting criteria are proposed, which are the combinations of single criteria based on the misclassification error and Gini index.

  8. Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

    ERIC Educational Resources Information Center

    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…

  9. Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

    PubMed Central

    2012-01-01

    Background 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. Results 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. Conclusions 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. PMID:23171000

  10. Metric Sex Determination of the Human Coxal Bone on a Virtual Sample using Decision Trees.

    PubMed

    Savall, Frédéric; Faruch-Bilfeld, Marie; Dedouit, Fabrice; Sans, Nicolas; Rousseau, Hervé; Rougé, Daniel; Telmon, Norbert

    2015-11-01

    Decision trees provide an alternative to multivariate discriminant analysis, which is still the most commonly used in anthropometric studies. Our study analyzed the metric characterization of a recent virtual sample of 113 coxal bones using decision trees for sex determination. From 17 osteometric type I landmarks, a dataset was built with five classic distances traditionally reported in the literature and six new distances selected using the two-step ratio method. A ten-fold cross-validation was performed, and a decision tree was established on two subsamples (training and test sets). The decision tree established on the training set included three nodes and its application to the test set correctly classified 92% of individuals. This percentage was similar to the data of the literature. The usefulness of decision trees has been demonstrated in numerous fields. They have been already used in sex determination, body mass prediction, and ancestry estimation. This study shows another use of decision trees enabling simple and accurate sex determination. © 2015 American Academy of Forensic Sciences.

  11. Generation and Termination of Binary Decision Trees for Nonparametric Multiclass Classification.

    DTIC Science & Technology

    1984-10-01

    O M coF=F;; UMBER2. GOVT ACCE5SION NO.1 3 . REC,PINS :A7AL:,G NUMBER ( ’eneration and Terminat_,on :)f Binary D-ecision jC j ik; Trees for Nonnararetrc...1-I . v)IAMO 0~I4 EDvt" O F I 00 . 3 15I OR%.OL.ETL - S-S OCTOBER 1984 LIDS-P-1411 GENERATION AND TERMINATION OF BINARY DECISION TREES FOR...minimizes the Bayes risk. Tree generation and termination are based on the training and test samples, respectively. 0 0 0/ 6 0¢ A 3 I. Introduction We state

  12. Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis.

    PubMed

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

    2017-08-16

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

  13. Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

    PubMed

    Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

    2016-01-01

    Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P < 0.01). A clinically useful classification tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

  14. An Improved Decision Tree for Predicting a Major Product in Competing Reactions

    ERIC Educational Resources Information Center

    Graham, Kate J.

    2014-01-01

    When organic chemistry students encounter competing reactions, they are often overwhelmed by the task of evaluating multiple factors that affect the outcome of a reaction. The use of a decision tree is a useful tool to teach students to evaluate a complex situation and propose a likely outcome. Specifically, a decision tree can help students…

  15. Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

    NASA Astrophysics Data System (ADS)

    Wahyuni, Sri

    2018-03-01

    Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.

  16. Using decision tree models to depict primary care physicians CRC screening decision heuristics.

    PubMed

    Wackerbarth, Sarah B; Tarasenko, Yelena N; Curtis, Laurel A; Joyce, Jennifer M; Haist, Steven A

    2007-10-01

    The purpose of this study was to identify decision heuristics utilized by primary care physicians in formulating colorectal cancer screening recommendations. Qualitative research using in-depth semi-structured interviews. We interviewed 66 primary care internists and family physicians evenly drawn from academic and community practices. A majority of physicians were male, and almost all were white, non-Hispanic. Three researchers independently reviewed each transcript to determine the physician's decision criteria and developed decision trees. Final trees were developed by consensus. The constant comparative methodology was used to define the categories. Physicians were found to use 1 of 4 heuristics ("age 50," "age 50, if family history, then earlier," "age 50, if family history, then screen at age 40," or "age 50, if family history, then adjust relative to reference case") for the timing recommendation and 5 heuristics ["fecal occult blood test" (FOBT), "colonoscopy," "if not colonoscopy, then...," "FOBT and another test," and "a choice between options"] for the type decision. No connection was found between timing and screening type heuristics. We found evidence of heuristic use. Further research is needed to determine the potential impact on quality of care.

  17. [Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

    PubMed

    Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

    2017-08-15

    Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

  18. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    PubMed

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

  19. Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

    NASA Technical Reports Server (NTRS)

    Schwabacher, Mark A.; Aguilar, Robert; Figueroa, Fernando F.

    2009-01-01

    The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

  20. Application of preprocessing filtering on Decision Tree C4.5 and rough set theory

    NASA Astrophysics Data System (ADS)

    Chan, Joseph C. C.; Lin, Tsau Y.

    2001-03-01

    This paper compares two artificial intelligence methods: the Decision Tree C4.5 and Rough Set Theory on the stock market data. The Decision Tree C4.5 is reviewed with the Rough Set Theory. An enhanced window application is developed to facilitate the pre-processing filtering by introducing the feature (attribute) transformations, which allows users to input formulas and create new attributes. Also, the application produces three varieties of data set with delaying, averaging, and summation. The results prove the improvement of pre-processing by applying feature (attribute) transformations on Decision Tree C4.5. Moreover, the comparison between Decision Tree C4.5 and Rough Set Theory is based on the clarity, automation, accuracy, dimensionality, raw data, and speed, which is supported by the rules sets generated by both algorithms on three different sets of data.

  1. Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.

    PubMed

    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.

  2. Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

    NASA Technical Reports Server (NTRS)

    Lee, Hanbong

    2017-01-01

    In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

  3. Diagnostic classification scheme in Iranian breast cancer patients using a decision tree.

    PubMed

    Malehi, Amal Saki

    2014-01-01

    The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

  4. Contextual oblique view of north side and east rear, view ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Contextual oblique view of north side and east rear, view to southwest from Franklin Street showing partially cleared freeway right-of-way, and line of mature deodar cedar trees along North Fulton Avenue - Ira H. Brooks House, 350 North Fulton Avenue, Fresno, Fresno County, CA

  5. Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

    NASA Technical Reports Server (NTRS)

    Shiffman, Smadar

    2004-01-01

    Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

  6. Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

    PubMed

    Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

    2015-08-01

    Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

  7. Predicting the probability of mortality of gastric cancer patients using decision tree.

    PubMed

    Mohammadzadeh, F; Noorkojuri, H; Pourhoseingholi, M A; Saadat, S; Baghestani, A R

    2015-06-01

    Gastric cancer is the fourth most common cancer worldwide. This reason motivated us to investigate and introduce gastric cancer risk factors utilizing statistical methods. The aim of this study was to identify the most important factors influencing the mortality of patients who suffer from gastric cancer disease and to introduce a classification approach according to decision tree model for predicting the probability of mortality from this disease. Data on 216 patients with gastric cancer, who were registered in Taleghani hospital in Tehran,Iran, were analyzed. At first, patients were divided into two groups: the dead and alive. Then, to fit decision tree model to our data, we randomly selected 20% of dataset to the test sample and remaining dataset considered as the training sample. Finally, the validity of the model examined with sensitivity, specificity, diagnosis accuracy and the area under the receiver operating characteristic curve. The CART version 6.0 and SPSS version 19.0 softwares were used for the analysis of the data. Diabetes, ethnicity, tobacco, tumor size, surgery, pathologic stage, age at diagnosis, exposure to chemical weapons and alcohol consumption were determined as effective factors on mortality of gastric cancer. The sensitivity, specificity and accuracy of decision tree were 0.72, 0.75 and 0.74 respectively. The indices of sensitivity, specificity and accuracy represented that the decision tree model has acceptable accuracy to prediction the probability of mortality in gastric cancer patients. So a simple decision tree consisted of factors affecting on mortality of gastric cancer may help clinicians as a reliable and practical tool to predict the probability of mortality in these patients.

  8. Pruning a decision tree for selecting computer-related assistive devices for people with disabilities.

    PubMed

    Chi, Chia-Fen; Tseng, Li-Kai; Jang, Yuh

    2012-07-01

    Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson's decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients' individual needs in an efficient manner.

  9. Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

    PubMed

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

    2015-01-01

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

  10. Minimizing the cost of translocation failure with decision-tree models that predict species' behavioral response in translocation sites.

    PubMed

    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.

  11. Decision Trees Predicting Tumor Shrinkage for Head and Neck Cancer: Implications for Adaptive Radiotherapy.

    PubMed

    Surucu, Murat; Shah, Karan K; Mescioglu, Ibrahim; Roeske, John C; Small, William; Choi, Mehee; Emami, Bahman

    2016-02-01

    To develop decision trees predicting for tumor volume reduction in patients with head and neck (H&N) cancer using pretreatment clinical and pathological parameters. Forty-eight patients treated with definitive concurrent chemoradiotherapy for squamous cell carcinoma of the nasopharynx, oropharynx, oral cavity, or hypopharynx were retrospectively analyzed. These patients were rescanned at a median dose of 37.8 Gy and replanned to account for anatomical changes. The percentages of gross tumor volume (GTV) change from initial to rescan computed tomography (CT; %GTVΔ) were calculated. Two decision trees were generated to correlate %GTVΔ in primary and nodal volumes with 14 characteristics including age, gender, Karnofsky performance status (KPS), site, human papilloma virus (HPV) status, tumor grade, primary tumor growth pattern (endophytic/exophytic), tumor/nodal/group stages, chemotherapy regimen, and primary, nodal, and total GTV volumes in the initial CT scan. The C4.5 Decision Tree induction algorithm was implemented. The median %GTVΔ for primary, nodal, and total GTVs was 26.8%, 43.0%, and 31.2%, respectively. Type of chemotherapy, age, primary tumor growth pattern, site, KPS, and HPV status were the most predictive parameters for primary %GTVΔ decision tree, whereas for nodal %GTVΔ, KPS, site, age, primary tumor growth pattern, initial primary GTV, and total GTV volumes were predictive. Both decision trees had an accuracy of 88%. There can be significant changes in primary and nodal tumor volumes during the course of H&N chemoradiotherapy. Considering the proposed decision trees, radiation oncologists can select patients predicted to have high %GTVΔ, who would theoretically gain the most benefit from adaptive radiotherapy, in order to better use limited clinical resources. © The Author(s) 2015.

  12. Development of a New Decision Tree to Rapidly Screen Chemical Estrogenic Activities of Xenopus laevis.

    PubMed

    Wang, Ting; Li, Weiying; Zheng, Xiaofeng; Lin, Zhifen; Kong, Deyang

    2014-02-01

    During the last past decades, there is an increasing number of studies about estrogenic activities of the environmental pollutants on amphibians and many determination methods have been proposed. However, these determination methods are time-consuming and expensive, and a rapid and simple method to screen and test the chemicals for estrogenic activities to amphibians is therefore imperative. Herein is proposed a new decision tree formulated not only with physicochemical parameters but also a biological parameter that was successfully used to screen estrogenic activities of the chemicals on amphibians. The biological parameter, CDOCKER interaction energy (Ebinding ) between chemicals and the target proteins was calculated based on the method of molecular docking, and it was used to revise the decision tree formulated by Hong only with physicochemical parameters for screening estrogenic activity of chemicals in rat. According to the correlation between Ebinding of rat and Xenopus laevis, a new decision tree for estrogenic activities in Xenopus laevis is finally proposed. Then it was validated by using the randomly 8 chemicals which can be frequently exposed to Xenopus laevis, and the agreement between the results from the new decision tree and the ones from experiments is generally satisfactory. Consequently, the new decision tree can be used to screen the estrogenic activities of the chemicals, and combinational use of the Ebinding and classical physicochemical parameters can greatly improves Hong's decision tree. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Assessing School Readiness for a Practice Arrangement Using Decision Tree Methodology.

    ERIC Educational Resources Information Center

    Barger, Sara E.

    1998-01-01

    Questions in a decision-tree address mission, faculty interest, administrative support, and practice plan as a way of assessing arrangements for nursing faculty's clinical practice. Decisions should be based on congruence between the human resource allocation and the reward systems. (SK)

  14. Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology.

    ERIC Educational Resources Information Center

    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…

  15. Comparative Issues and Methods in Organizational Diagnosis. Report II. The Decision Tree Approach.

    DTIC Science & Technology

    organizational diagnosis . The advantages and disadvantages of the decision-tree approach generally, and in this study specifically, are examined. A pre-test, using a civilian sample of 174 work groups with Survey of Organizations data, was conducted to assess various decision-tree classification criteria, in terms of their similarity to the distance function used by Bowers and Hausser (1977). The results suggested the use of a large developmental sample, which should result in more distinctly defined boundary lines between classification profiles. Also, the decision matrix

  16. Decision tree and PCA-based fault diagnosis of rotating machinery

    NASA Astrophysics Data System (ADS)

    Sun, Weixiang; Chen, Jin; Li, Jiaqing

    2007-04-01

    After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

  17. Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process

    PubMed Central

    Masías, Víctor H.; Krause, Mariane; Valdés, Nelson; Pérez, J. C.; Laengle, Sigifredo

    2015-01-01

    Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice. PMID:25914657

  18. Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process.

    PubMed

    Masías, Víctor H; Krause, Mariane; Valdés, Nelson; Pérez, J C; Laengle, Sigifredo

    2015-01-01

    Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice.

  19. Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach.

    PubMed

    Batterham, Philip J; Christensen, Helen; Mackinnon, Andrew J

    2009-11-22

    Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk. The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves. The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors. The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.

  20. A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging.

    PubMed

    Nair, Shalini Rajandran; Tan, Li Kuo; Mohd Ramli, Norlisah; Lim, Shen Yang; Rahmat, Kartini; Mohd Nor, Hazman

    2013-06-01

    To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

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

    PubMed Central

    in ’t Veen, Johannes C.C.M.; Dekhuijzen, P.N. Richard; van Heijst, Ellen; Kocks, Janwillem W.H.; Muilwijk-Kroes, Jacqueline B.; Chavannes, Niels H.; van der Molen, Thys

    2016-01-01

    The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years) with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD) service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215). Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS) patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%). Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool. PMID:27730177

  2. Decision-Tree Program

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1994-01-01

    IND computer program introduces Bayesian and Markov/maximum-likelihood (MML) methods and more-sophisticated methods of searching in growing trees. Produces more-accurate class-probability estimates important in applications like diagnosis. Provides range of features and styles with convenience for casual user, fine-tuning for advanced user or for those interested in research. Consists of four basic kinds of routines: data-manipulation, tree-generation, tree-testing, and tree-display. Written in C language.

  3. PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

    NASA Astrophysics Data System (ADS)

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

    2018-03-01

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

  4. The application of a decision tree to establish the parameters associated with hypertension.

    PubMed

    Tayefi, Maryam; Esmaeili, Habibollah; Saberi Karimian, Maryam; Amirabadi Zadeh, Alireza; Ebrahimi, Mahmoud; Safarian, Mohammad; Nematy, Mohsen; Parizadeh, Seyed Mohammad Reza; Ferns, Gordon A; Ghayour-Mobarhan, Majid

    2017-02-01

    Hypertension is an important risk factor for cardiovascular disease (CVD). The goal of this study was to establish the factors associated with hypertension by using a decision-tree algorithm as a supervised classification method of data mining. Data from a cross-sectional study were used in this study. A total of 9078 subjects who met the inclusion criteria were recruited. 70% of these subjects (6358 cases) were randomly allocated to the training dataset for the constructing of the decision-tree. The remaining 30% (2720 cases) were used as the testing dataset to evaluate the performance of decision-tree. Two models were evaluated in this study. In model I, age, gender, body mass index, marital status, level of education, occupation status, depression and anxiety status, physical activity level, smoking status, LDL, TG, TC, FBG, uric acid and hs-CRP were considered as input variables and in model II, age, gender, WBC, RBC, HGB, HCT MCV, MCH, PLT, RDW and PDW were considered as input variables. The validation of the model was assessed by constructing a receiver operating characteristic (ROC) curve. The prevalence rates of hypertension were 32% in our population. For the decision-tree model I, the accuracy, sensitivity, specificity and area under the ROC curve (AUC) value for identifying the related risk factors of hypertension were 73%, 63%, 77% and 0.72, respectively. The corresponding values for model II were 70%, 61%, 74% and 0.68, respectively. We have developed a decision tree model to identify the risk factors associated with hypertension that maybe used to develop programs for hypertension management. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. Vlsi implementation of flexible architecture for decision tree classification in data mining

    NASA Astrophysics Data System (ADS)

    Sharma, K. Venkatesh; Shewandagn, Behailu; Bhukya, Shankar Nayak

    2017-07-01

    The Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a terrific raise in the size of the data being collected and analyzed. Classification is the main difficulty faced in data mining. In a number of the solutions developed for this problem, most accepted one is Decision Tree Classification (DTC) that gives high precision while handling very large amount of data. This paper presents VLSI implementation of flexible architecture for Decision Tree classification in data mining using c4.5 algorithm.

  6. FDT 2.0: Improving scalability of the fuzzy decision tree induction tool - integrating database storage.

    PubMed

    Durham, Erin-Elizabeth A; Yu, Xiaxia; Harrison, Robert W

    2014-12-01

    Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data science and data engineering: it combines a robust decisioning tool with data retention for future decisions, so that the tool does not need to be recalibrated from scratch every time a new decision is required. In this paper we briefly review the analytical capabilities of the freeware FDT tool and its major features and functionalities; examples of large biological datasets from HIV, microRNAs and sRNAs are included. This work shows how to integrate fuzzy decision algorithms with modern database technology. In addition, we show that integrating the fuzzy decision tree induction tool with database storage allows for optimal user satisfaction in today's Data Analytics world.

  7. A fuzzy decision tree for fault classification.

    PubMed

    Zio, Enrico; Baraldi, Piero; Popescu, Irina C

    2008-02-01

    In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.

  8. Development and acceptability testing of decision trees for self-management of prosthetic socket fit in adults with lower limb amputation.

    PubMed

    Lee, Daniel Joseph; Veneri, Diana A

    2018-05-01

    The most common complaint lower limb prosthesis users report is inadequacy of a proper socket fit. Adjustments to the residual limb-socket interface can be made by the prosthesis user without consultation of a clinician in many scenarios through skilled self-management. Decision trees guide prosthesis wearers through the self-management process, empowering them to rectify fit issues, or referring them to a clinician when necessary. This study examines the development and acceptability testing of patient-centered decision trees for lower limb prosthesis users. Decision trees underwent a four-stage process: literature review and expert consultation, designing, two-rounds of expert panel review and revisions, and target audience testing. Fifteen lower limb prosthesis users (average age 61 years) reviewed the decision trees and completed an acceptability questionnaire. Participants reported agreement of 80% or above in five of the eight questions related to acceptability of the decision trees. Disagreement was related to the level of experience of the respondent. Decision trees were found to be easy to use, illustrate correct solutions to common issues, and have terminology consistent with that of a new prosthesis user. Some users with greater than 1.5 years of experience would not use the decision trees based on their own self-management skills. Implications for Rehabilitation Discomfort of the residual limb-prosthetic socket interface is the most common reason for clinician visits. Prosthesis users can use decision trees to guide them through the process of obtaining a proper socket fit independently. Newer users may benefit from using the decision trees more than experienced users.

  9. Online adaptive decision trees: pattern classification and function approximation.

    PubMed

    Basak, Jayanta

    2006-09-01

    Recently we have shown that decision trees can be trained in the online adaptive (OADT) mode (Basak, 2004), leading to better generalization score. OADTs were bottlenecked by the fact that they are able to handle only two-class classification tasks with a given structure. In this article, we provide an architecture based on OADT, ExOADT, which can handle multiclass classification tasks and is able to perform function approximation. ExOADT is structurally similar to OADT extended with a regression layer. We also show that ExOADT is capable not only of adapting the local decision hyperplanes in the nonterminal nodes but also has the potential of smoothly changing the structure of the tree depending on the data samples. We provide the learning rules based on steepest gradient descent for the new model ExOADT. Experimentally we demonstrate the effectiveness of ExOADT in the pattern classification and function approximation tasks. Finally, we briefly discuss the relationship of ExOADT with other classification models.

  10. Circum-Arctic petroleum systems identified using decision-tree chemometrics

    USGS Publications Warehouse

    Peters, K.E.; Ramos, L.S.; Zumberge, J.E.; Valin, Z.C.; Scotese, C.R.; Gautier, D.L.

    2007-01-01

    Source- and age-related biomarker and isotopic data were measured for more than 1000 crude oil samples from wells and seeps collected above approximately 55??N latitude. A unique, multitiered chemometric (multivariate statistical) decision tree was created that allowed automated classification of 31 genetically distinct circumArctic oil families based on a training set of 622 oil samples. The method, which we call decision-tree chemometrics, uses principal components analysis and multiple tiers of K-nearest neighbor and SIMCA (soft independent modeling of class analogy) models to classify and assign confidence limits for newly acquired oil samples and source rock extracts. Geochemical data for each oil sample were also used to infer the age, lithology, organic matter input, depositional environment, and identity of its source rock. These results demonstrate the value of large petroleum databases where all samples were analyzed using the same procedures and instrumentation. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

  11. Improving ensemble decision tree performance using Adaboost and Bagging

    NASA Astrophysics Data System (ADS)

    Hasan, Md. Rajib; Siraj, Fadzilah; Sainin, Mohd Shamrie

    2015-12-01

    Ensemble classifier systems are considered as one of the most promising in medical data classification and the performance of deceision tree classifier can be increased by the ensemble method as it is proven to be better than single classifiers. However, in a ensemble settings the performance depends on the selection of suitable base classifier. This research employed two prominent esemble s namely Adaboost and Bagging with base classifiers such as Random Forest, Random Tree, j48, j48grafts and Logistic Model Regression (LMT) that have been selected independently. The empirical study shows that the performance varries when different base classifiers are selected and even some places overfitting issue also been noted. The evidence shows that ensemble decision tree classfiers using Adaboost and Bagging improves the performance of selected medical data sets.

  12. C-fuzzy variable-branch decision tree with storage and classification error rate constraints

    NASA Astrophysics Data System (ADS)

    Yang, Shiueng-Bien

    2009-10-01

    The C-fuzzy decision tree (CFDT), which is based on the fuzzy C-means algorithm, has recently been proposed. The CFDT is grown by selecting the nodes to be split according to its classification error rate. However, the CFDT design does not consider the classification time taken to classify the input vector. Thus, the CFDT can be improved. We propose a new C-fuzzy variable-branch decision tree (CFVBDT) with storage and classification error rate constraints. The design of the CFVBDT consists of two phases-growing and pruning. The CFVBDT is grown by selecting the nodes to be split according to the classification error rate and the classification time in the decision tree. Additionally, the pruning method selects the nodes to prune based on the storage requirement and the classification time of the CFVBDT. Furthermore, the number of branches of each internal node is variable in the CFVBDT. Experimental results indicate that the proposed CFVBDT outperforms the CFDT and other methods.

  13. Data mining for multiagent rules, strategies, and fuzzy decision tree structure

    NASA Astrophysics Data System (ADS)

    Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

    2002-03-01

    A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

  14. Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines.

    PubMed

    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.

  15. Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B.

    PubMed

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

    2013-01-01

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

  16. Ventriculogram segmentation using boosted decision trees

    NASA Astrophysics Data System (ADS)

    McDonald, John A.; Sheehan, Florence H.

    2004-05-01

    Left ventricular status, reflected in ejection fraction or end systolic volume, is a powerful prognostic indicator in heart disease. Quantitative analysis of these and other parameters from ventriculograms (cine xrays of the left ventricle) is infrequently performed due to the labor required for manual segmentation. None of the many methods developed for automated segmentation has achieved clinical acceptance. We present a method for semi-automatic segmentation of ventriculograms based on a very accurate two-stage boosted decision-tree pixel classifier. The classifier determines which pixels are inside the ventricle at key ED (end-diastole) and ES (end-systole) frames. The test misclassification rate is about 1%. The classifier is semi-automatic, requiring a user to select 3 points in each frame: the endpoints of the aortic valve and the apex. The first classifier stage is 2 boosted decision-trees, trained using features such as gray-level statistics (e.g. median brightness) and image geometry (e.g. coordinates relative to user supplied 3 points). Second stage classifiers are trained using the same features as the first, plus the output of the first stage. Border pixels are determined from the segmented images using dilation and erosion. A curve is then fit to the border pixels, minimizing a penalty function that trades off fidelity to the border pixels with smoothness. ED and ES volumes, and ejection fraction are estimated from border curves using standard area-length formulas. On independent test data, the differences between automatic and manual volumes (and ejection fractions) are similar in size to the differences between two human observers.

  17. [Analysis of the characteristics of the older adults with depression using data mining decision tree analysis].

    PubMed

    Park, Myonghwa; Choi, Sora; Shin, A Mi; Koo, Chul Hoi

    2013-02-01

    The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

  18. Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

    NASA Astrophysics Data System (ADS)

    Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

    Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

  19. Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

    PubMed

    Sankari, E Siva; Manimegalai, D

    2017-12-21

    Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Prediction of the compression ratio for municipal solid waste using decision tree.

    PubMed

    Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed

    2014-01-01

    The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.

  1. Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

    NASA Technical Reports Server (NTRS)

    Otterstatter, Matthew R.

    2005-01-01

    The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

  2. Three-dimensional object recognition using similar triangles and decision trees

    NASA Technical Reports Server (NTRS)

    Spirkovska, Lilly

    1993-01-01

    A system, TRIDEC, that is capable of distinguishing between a set of objects despite changes in the objects' positions in the input field, their size, or their rotational orientation in 3D space is described. TRIDEC combines very simple yet effective features with the classification capabilities of inductive decision tree methods. The feature vector is a list of all similar triangles defined by connecting all combinations of three pixels in a coarse coded 127 x 127 pixel input field. The classification is accomplished by building a decision tree using the information provided from a limited number of translated, scaled, and rotated samples. Simulation results are presented which show that TRIDEC achieves 94 percent recognition accuracy in the 2D invariant object recognition domain and 98 percent recognition accuracy in the 3D invariant object recognition domain after training on only a small sample of transformed views of the objects.

  3. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    NASA Technical Reports Server (NTRS)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  4. Office of Legacy Management Decision Tree for Solar Photovoltaic Projects - 13317

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Elmer, John; Butherus, Michael; Barr, Deborah L.

    2013-07-01

    To support consideration of renewable energy power development as a land reuse option, the DOE Office of Legacy Management (LM) and the National Renewable Energy Laboratory (NREL) established a partnership to conduct an assessment of wind and solar renewable energy resources on LM lands. From a solar capacity perspective, the larger sites in the western United States present opportunities for constructing solar photovoltaic (PV) projects. A detailed analysis and preliminary plan was developed for three large sites in New Mexico, assessing the costs, the conceptual layout of a PV system, and the electric utility interconnection process. As a result ofmore » the study, a 1,214-hectare (3,000-acre) site near Grants, New Mexico, was chosen for further study. The state incentives, utility connection process, and transmission line capacity were key factors in assessing the feasibility of the project. LM's Durango, Colorado, Disposal Site was also chosen for consideration because the uranium mill tailings disposal cell is on a hillside facing south, transmission lines cross the property, and the community was very supportive of the project. LM worked with the regulators to demonstrate that the disposal cell's long-term performance would not be impacted by the installation of a PV solar system. A number of LM-unique issues were resolved in making the site available for a private party to lease a portion of the site for a solar PV project. A lease was awarded in September 2012. Using a solar decision tree that was developed and launched by the EPA and NREL, LM has modified and expanded the decision tree structure to address the unique aspects and challenges faced by LM on its multiple sites. The LM solar decision tree covers factors such as land ownership, usable acreage, financial viability of the project, stakeholder involvement, and transmission line capacity. As additional sites are transferred to LM in the future, the decision tree will assist in determining whether

  5. Discovering Decision Knowledge from Web Log Portfolio for Managing Classroom Processes by Applying Decision Tree and Data Cube Technology.

    ERIC Educational Resources Information Center

    Chen, Gwo-Dong; Liu, Chen-Chung; Ou, Kuo-Liang; Liu, Baw-Jhiune

    2000-01-01

    Discusses the use of Web logs to record student behavior that can assist teachers in assessing performance and making curriculum decisions for distance learning students who are using Web-based learning systems. Adopts decision tree and data cube information processing methodologies for developing more effective pedagogical strategies. (LRW)

  6. Comparing wavefront-optimized, wavefront-guided and topography-guided laser vision correction: clinical outcomes using an objective decision tree.

    PubMed

    Stonecipher, Karl; Parrish, Joseph; Stonecipher, Megan

    2018-05-18

    This review is intended to update and educate the reader on the currently available options for laser vision correction, more specifically, laser-assisted in-situ keratomileusis (LASIK). In addition, some related clinical outcomes data from over 1000 cases performed over a 1-year are presented to highlight some differences between the various treatment profiles currently available including the rapidity of visual recovery. The cases in question were performed on the basis of a decision tree to segregate patients on the basis of anatomical, topographic and aberrometry findings; the decision tree was formulated based on the data available in some of the reviewed articles. Numerous recent studies reported in the literature provide data related to the risks and benefits of LASIK; alternatives to a laser refractive procedure are also discussed. The results from these studies have been used to prepare a decision tree to assist the surgeon in choosing the best option for the patient based on the data from several standard preoperative diagnostic tests. The data presented here should aid surgeons in understanding the effects of currently available LASIK treatment profiles. Surgeons should also be able to appreciate how the findings were used to create a decision tree to help choose the most appropriate treatment profile for patients. Finally, the retrospective evaluation of clinical outcomes based on the decision tree should provide surgeons with a realistic expectation for their own outcomes should they adopt such a decision tree in their own practice.

  7. A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

    PubMed Central

    Liu, Dong-sheng; Fan, Shu-jiang

    2014-01-01

    In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

  8. Peripheral Exophytic Oral Lesions: A Clinical Decision Tree

    PubMed Central

    Safi, Yaser; Jafari, Soudeh

    2017-01-01

    Diagnosis of peripheral oral exophytic lesions might be quite challenging. This review article aimed to introduce a decision tree for oral exophytic lesions according to their clinical features. General search engines and specialized databases including PubMed, PubMed Central, Medline Plus, EBSCO, Science Direct, Scopus, Embase, and authenticated textbooks were used to find relevant topics by means of keywords such as “oral soft tissue lesion,” “oral tumor like lesion,” “oral mucosal enlargement,” and “oral exophytic lesion.” Related English-language articles published since 1988 to 2016 in both medical and dental journals were appraised. Upon compilation of data, peripheral oral exophytic lesions were categorized into two major groups according to their surface texture: smooth (mesenchymal or nonsquamous epithelium-originated) and rough (squamous epithelium-originated). Lesions with smooth surface were also categorized into three subgroups according to their general frequency: reactive hyperplastic lesions/inflammatory hyperplasia, salivary gland lesions (nonneoplastic and neoplastic), and mesenchymal lesions (benign and malignant neoplasms). In addition, lesions with rough surface were summarized in six more common lesions. In total, 29 entities were organized in the form of a decision tree in order to help clinicians establish a logical diagnosis by a stepwise progression method. PMID:28757870

  9. Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

    PubMed

    Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

    2018-05-01

    Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

  10. Prognostic Factors and Decision Tree for Long-term Survival in Metastatic Uveal Melanoma.

    PubMed

    Lorenzo, Daniel; Ochoa, María; Piulats, Josep Maria; Gutiérrez, Cristina; Arias, Luis; Català, Jaum; Grau, María; Peñafiel, Judith; Cobos, Estefanía; Garcia-Bru, Pere; Rubio, Marcos Javier; Padrón-Pérez, Noel; Dias, Bruno; Pera, Joan; Caminal, Josep Maria

    2017-12-04

    The purpose of this study was to demonstrate the existence of a bimodal survival pattern in metastatic uveal melanoma. Secondary aims were to identify the characteristics and prognostic factors associated with long-term survival and to develop a clinical decision tree. The medical records of 99 metastatic uveal melanoma patients were retrospectively reviewed. Patients were classified as either short (≤ 12 months) or long-term survivors (> 12 months) based on a graphical interpretation of the survival curve after diagnosis of the first metastatic lesion. Ophthalmic and oncological characteristics were assessed in both groups. Of the 99 patients, 62 (62.6%) were classified as short-term survivors, and 37 (37.4%) as long-term survivors. The multivariate analysis identified the following predictors of long-term survival: age ≤ 65 years (p=0.012) and unaltered serum lactate dehydrogenase levels (p=0.018); additionally, the size (smaller vs. larger) of the largest liver metastasis showed a trend towards significance (p=0.063). Based on the variables significantly associated with long-term survival, we developed a decision tree to facilitate clinical decision-making. The findings of this study demonstrate the existence of a bimodal survival pattern in patients with metastatic uveal melanoma. The presence of certain clinical characteristics at diagnosis of distant disease is associated with long-term survival. A decision tree was developed to facilitate clinical decision-making and to counsel patients about the expected course of disease.

  11. Decision tree analysis of factors influencing rainfall-related building damage

    NASA Astrophysics Data System (ADS)

    Spekkers, M. H.; Kok, M.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.

    2014-04-01

    Flood damage prediction models are essential building blocks in flood risk assessments. Little research has been dedicated so far to damage of small-scale urban floods caused by heavy rainfall, while there is a need for reliable damage models for this flood type among insurers and water authorities. The aim of this paper is to investigate a wide range of damage-influencing factors and their relationships with rainfall-related damage, using decision tree analysis. For this, district-aggregated claim data from private property insurance companies in the Netherlands were analysed, for the period of 1998-2011. The databases include claims of water-related damage, for example, damages related to rainwater intrusion through roofs and pluvial flood water entering buildings at ground floor. Response variables being modelled are average claim size and claim frequency, per district per day. The set of predictors include rainfall-related variables derived from weather radar images, topographic variables from a digital terrain model, building-related variables and socioeconomic indicators of households. Analyses were made separately for property and content damage claim data. Results of decision tree analysis show that claim frequency is most strongly associated with maximum hourly rainfall intensity, followed by real estate value, ground floor area, household income, season (property data only), buildings age (property data only), ownership structure (content data only) and fraction of low-rise buildings (content data only). It was not possible to develop statistically acceptable trees for average claim size, which suggest that variability in average claim size is related to explanatory variables that cannot be defined at the district scale. Cross-validation results show that decision trees were able to predict 22-26% of variance in claim frequency, which is considerably better compared to results from global multiple regression models (11-18% of variance explained). Still, a

  12. Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features.

    PubMed

    Mudali, D; Teune, L K; Renken, R J; Leenders, K L; Roerdink, J B T M

    2015-01-01

    Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.

  13. Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

    PubMed

    Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

    2017-10-11

    Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

  14. Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed

    USGS Publications Warehouse

    Balk, Benjamin; Elder, Kelly

    2000-01-01

    We model the spatial distribution of snow across a mountain basin using an approach that combines binary decision tree and geostatistical techniques. In April 1997 and 1998, intensive snow surveys were conducted in the 6.9‐km2 Loch Vale watershed (LVWS), Rocky Mountain National Park, Colorado. Binary decision trees were used to model the large‐scale variations in snow depth, while the small‐scale variations were modeled through kriging interpolation methods. Binary decision trees related depth to the physically based independent variables of net solar radiation, elevation, slope, and vegetation cover type. These decision tree models explained 54–65% of the observed variance in the depth measurements. The tree‐based modeled depths were then subtracted from the measured depths, and the resulting residuals were spatially distributed across LVWS through kriging techniques. The kriged estimates of the residuals were added to the tree‐based modeled depths to produce a combined depth model. The combined depth estimates explained 60–85% of the variance in the measured depths. Snow densities were mapped across LVWS using regression analysis. Snow‐covered area was determined from high‐resolution aerial photographs. Combining the modeled depths and densities with a snow cover map produced estimates of the spatial distribution of snow water equivalence (SWE). This modeling approach offers improvement over previous methods of estimating SWE distribution in mountain basins.

  15. Extracting decision rules from police accident reports through decision trees.

    PubMed

    de Oña, Juan; López, Griselda; Abellán, Joaquín

    2013-01-01

    Given the current number of road accidents, the aim of many road safety analysts is to identify the main factors that contribute to crash severity. To pinpoint those factors, this paper shows an application that applies some of the methods most commonly used to build decision trees (DTs), which have not been applied to the road safety field before. An analysis of accidents on rural highways in the province of Granada (Spain) between 2003 and 2009 (both inclusive) showed that the methods used to build DTs serve our purpose and may even be complementary. Applying these methods has enabled potentially useful decision rules to be extracted that could be used by road safety analysts. For instance, some of the rules may indicate that women, contrary to men, increase their risk of severity under bad lighting conditions. The rules could be used in road safety campaigns to mitigate specific problems. This would enable managers to implement priority actions based on a classification of accidents by types (depending on their severity). However, the primary importance of this proposal is that other databases not used here (i.e. other infrastructure, roads and countries) could be used to identify unconventional problems in a manner easy for road safety managers to understand, as decision rules. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Using decision trees to understand structure in missing data

    PubMed Central

    Tierney, Nicholas J; Harden, Fiona A; Harden, Maurice J; Mengersen, Kerrie L

    2015-01-01

    Objectives Demonstrate the application of decision trees—classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs)—to understand structure in missing data. Setting Data taken from employees at 3 different industrial sites in Australia. Participants 7915 observations were included. Materials and methods The approach was evaluated using an occupational health data set comprising results of questionnaires, medical tests and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the type of data (medical or environmental), the site in which it was collected, the number of visits, and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured as compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusions Researchers are encouraged to use CART and BRT models to explore and understand missing data. PMID:26124509

  17. Fault trees for decision making in systems analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lambert, Howard E.

    1975-10-09

    The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut setsmore » according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure.« less

  18. Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis.

    PubMed

    Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji

    2015-07-01

    The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

  19. Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

    PubMed

    Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

    2014-12-01

    Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

  20. Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

    NASA Astrophysics Data System (ADS)

    Park, J.; Yoo, K.

    2013-12-01

    For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

  1. Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

    PubMed Central

    Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

    2015-01-01

    In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

  2. Using decision-tree classifier systems to extract knowledge from databases

    NASA Technical Reports Server (NTRS)

    St.clair, D. C.; Sabharwal, C. L.; Hacke, Keith; Bond, W. E.

    1990-01-01

    One difficulty in applying artificial intelligence techniques to the solution of real world problems is that the development and maintenance of many AI systems, such as those used in diagnostics, require large amounts of human resources. At the same time, databases frequently exist which contain information about the process(es) of interest. Recently, efforts to reduce development and maintenance costs of AI systems have focused on using machine learning techniques to extract knowledge from existing databases. Research is described in the area of knowledge extraction using a class of machine learning techniques called decision-tree classifier systems. Results of this research suggest ways of performing knowledge extraction which may be applied in numerous situations. In addition, a measurement called the concept strength metric (CSM) is described which can be used to determine how well the resulting decision tree can differentiate between the concepts it has learned. The CSM can be used to determine whether or not additional knowledge needs to be extracted from the database. An experiment involving real world data is presented to illustrate the concepts described.

  3. Exploratory Use of Decision Tree Analysis in Classification of Outcome in Hypoxic-Ischemic Brain Injury.

    PubMed

    Phan, Thanh G; Chen, Jian; Singhal, Shaloo; Ma, Henry; Clissold, Benjamin B; Ly, John; Beare, Richard

    2018-01-01

    Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data. The inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003-2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82-1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86-1.00). Our findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.

  4. Applying of Decision Tree Analysis to Risk Factors Associated with Pressure Ulcers in Long-Term Care Facilities.

    PubMed

    Moon, Mikyung; Lee, Soo-Kyoung

    2017-01-01

    The purpose of this study was to use decision tree analysis to explore the factors associated with pressure ulcers (PUs) among elderly people admitted to Korean long-term care facilities. The data were extracted from the 2014 National Inpatient Sample (NIS)-data of Health Insurance Review and Assessment Service (HIRA). A MapReduce-based program was implemented to join and filter 5 tables of the NIS. The outcome predicted by the decision tree model was the prevalence of PUs as defined by the Korean Standard Classification of Disease-7 (KCD-7; code L89 * ). Using R 3.3.1, a decision tree was generated with the finalized 15,856 cases and 830 variables. The decision tree displayed 15 subgroups with 8 variables showing 0.804 accuracy, 0.820 sensitivity, and 0.787 specificity. The most significant primary predictor of PUs was length of stay less than 0.5 day. Other predictors were the presence of an infectious wound dressing, followed by having diagnoses numbering less than 3.5 and the presence of a simple dressing. Among diagnoses, "injuries to the hip and thigh" was the top predictor ranking 5th overall. Total hospital cost exceeding 2,200,000 Korean won (US $2,000) rounded out the top 7. These results support previous studies that showed length of stay, comorbidity, and total hospital cost were associated with PUs. Moreover, wound dressings were commonly used to treat PUs. They also show that machine learning, such as a decision tree, could effectively predict PUs using big data.

  5. Decision tree analysis to stratify risk of de novo non-melanoma skin cancer following liver transplantation.

    PubMed

    Tanaka, Tomohiro; Voigt, Michael D

    2018-03-01

    Non-melanoma skin cancer (NMSC) is the most common de novo malignancy in liver transplant (LT) recipients; it behaves more aggressively and it increases mortality. We used decision tree analysis to develop a tool to stratify and quantify risk of NMSC in LT recipients. We performed Cox regression analysis to identify which predictive variables to enter into the decision tree analysis. Data were from the Organ Procurement Transplant Network (OPTN) STAR files of September 2016 (n = 102984). NMSC developed in 4556 of the 105984 recipients, a mean of 5.6 years after transplant. The 5/10/20-year rates of NMSC were 2.9/6.3/13.5%, respectively. Cox regression identified male gender, Caucasian race, age, body mass index (BMI) at LT, and sirolimus use as key predictive or protective factors for NMSC. These factors were entered into a decision tree analysis. The final tree stratified non-Caucasians as low risk (0.8%), and Caucasian males > 47 years, BMI < 40 who did not receive sirolimus, as high risk (7.3% cumulative incidence of NMSC). The predictions in the derivation set were almost identical to those in the validation set (r 2  = 0.971, p < 0.0001). Cumulative incidence of NMSC in low, moderate and high risk groups at 5/10/20 year was 0.5/1.2/3.3, 2.1/4.8/11.7 and 5.6/11.6/23.1% (p < 0.0001). The decision tree model accurately stratifies the risk of developing NMSC in the long-term after LT.

  6. Oblique Wing Flights

    NASA Image and Video Library

    2018-05-09

    Flown in the mid 70's, this Oblique Wing was a large-scale R/C experimental aircraft to demonstrate the ability to pivot its wing to an oblique angle, allowing for a reduced drag penalty at transonic speeds.

  7. Binary Decision Trees for Preoperative Periapical Cyst Screening Using Cone-beam Computed Tomography.

    PubMed

    Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa

    2017-03-01

    Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was <247 mm 3 and root displacement was present, cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.

  8. Toward the Decision Tree for Inferring Requirements Maturation Types

    NASA Astrophysics Data System (ADS)

    Nakatani, Takako; Kondo, Narihito; Shirogane, Junko; Kaiya, Haruhiko; Hori, Shozo; Katamine, Keiichi

    Requirements are elicited step by step during the requirements engineering (RE) process. However, some types of requirements are elicited completely after the scheduled requirements elicitation process is finished. Such a situation is regarded as problematic situation. In our study, the difficulties of eliciting various kinds of requirements is observed by components. We refer to the components as observation targets (OTs) and introduce the word “Requirements maturation.” It means when and how requirements are elicited completely in the project. The requirements maturation is discussed on physical and logical OTs. OTs Viewed from a logical viewpoint are called logical OTs, e.g. quality requirements. The requirements of physical OTs, e.g., modules, components, subsystems, etc., includes functional and non-functional requirements. They are influenced by their requesters' environmental changes, as well as developers' technical changes. In order to infer the requirements maturation period of each OT, we need to know how much these factors influence the OTs' requirements maturation. According to the observation of actual past projects, we defined the PRINCE (Pre Requirements Intelligence Net Consideration and Evaluation) model. It aims to guide developers in their observation of the requirements maturation of OTs. We quantitatively analyzed the actual cases with their requirements elicitation process and extracted essential factors that influence the requirements maturation. The results of interviews of project managers are analyzed by WEKA, a data mining system, from which the decision tree was derived. This paper introduces the PRINCE model and the category of logical OTs to be observed. The decision tree that helps developers infer the maturation type of an OT is also described. We evaluate the tree through real projects and discuss its ability to infer the requirements maturation types.

  9. Comparison of Naive Bayes and Decision Tree on Feature Selection Using Genetic Algorithm for Classification Problem

    NASA Astrophysics Data System (ADS)

    Rahmadani, S.; Dongoran, A.; Zarlis, M.; Zakarias

    2018-03-01

    This paper discusses the problem of feature selection using genetic algorithms on a dataset for classification problems. The classification model used is the decicion tree (DT), and Naive Bayes. In this paper we will discuss how the Naive Bayes and Decision Tree models to overcome the classification problem in the dataset, where the dataset feature is selectively selected using GA. Then both models compared their performance, whether there is an increase in accuracy or not. From the results obtained shows an increase in accuracy if the feature selection using GA. The proposed model is referred to as GADT (GA-Decision Tree) and GANB (GA-Naive Bayes). The data sets tested in this paper are taken from the UCI Machine Learning repository.

  10. Decision-Tree Analysis for Predicting First-Time Pass/Fail Rates for the NCLEX-RN® in Associate Degree Nursing Students.

    PubMed

    Chen, Hsiu-Chin; Bennett, Sean

    2016-08-01

    Little evidence shows the use of decision-tree algorithms in identifying predictors and analyzing their associations with pass rates for the NCLEX-RN(®) in associate degree nursing students. This longitudinal and retrospective cohort study investigated whether a decision-tree algorithm could be used to develop an accurate prediction model for the students' passing or failing the NCLEX-RN. This study used archived data from 453 associate degree nursing students in a selected program. The chi-squared automatic interaction detection analysis of the decision trees module was used to examine the effect of the collected predictors on passing/failing the NCLEX-RN. The actual percentage scores of Assessment Technologies Institute®'s RN Comprehensive Predictor(®) accurately identified students at risk of failing. The classification model correctly classified 92.7% of the students for passing. This study applied the decision-tree model to analyze a sequence database for developing a prediction model for early remediation in preparation for the NCLEXRN. [J Nurs Educ. 2016;55(8):454-457.]. Copyright 2016, SLACK Incorporated.

  11. Diagnostic Features of Common Oral Ulcerative Lesions: An Updated Decision Tree

    PubMed Central

    Safi, Yaser

    2016-01-01

    Diagnosis of oral ulcerative lesions might be quite challenging. This narrative review article aims to introduce an updated decision tree for diagnosing oral ulcerative lesions on the basis of their diagnostic features. Various general search engines and specialized databases including PubMed, PubMed Central, Medline Plus, EBSCO, Science Direct, Scopus, Embase, and authenticated textbooks were used to find relevant topics by means of MeSH keywords such as “oral ulcer,” “stomatitis,” and “mouth diseases.” Thereafter, English-language articles published since 1983 to 2015 in both medical and dental journals including reviews, meta-analyses, original papers, and case reports were appraised. Upon compilation of the relevant data, oral ulcerative lesions were categorized into three major groups: acute, chronic, and recurrent ulcers and into five subgroups: solitary acute, multiple acute, solitary chronic, multiple chronic, and solitary/multiple recurrent, based on the number and duration of lesions. In total, 29 entities were organized in the form of a decision tree in order to help clinicians establish a logical diagnosis by stepwise progression. PMID:27781066

  12. Evaluation with Decision Trees of Efficacy and Safety of Semirigid Ureteroscopy in the Treatment of Proximal Ureteral Calculi.

    PubMed

    Sancak, Eyup Burak; Kılınç, Muhammet Fatih; Yücebaş, Sait Can

    2017-01-01

    The decision on the choice of proximal ureteral stone therapy depends on many factors, and sometimes urologists have difficulty in choosing the treatment option. This study is aimed at evaluating the factors affecting the success of semirigid ureterorenoscopy (URS) using the "decision tree" method. From January 2005 to November 2015, the data of consecutive patients treated for proximal ureteral stone were retrospectively analyzed. A total of 920 patients with proximal ureteral stone treated with semirigid URS were included in the study. All statistically significant attributes were tested using the decision tree method. The model created using decision tree had a sensitivity of 0.993 and an accuracy of 0.857. While URS treatment was successful in 752 patients (81.7%), it was unsuccessful in 168 patients (18.3%). According to the decision tree method, the most important factor affecting the success of URS is whether the stone is impacted to the ureteral wall. The second most important factor affecting treatment was intramural stricture requiring dilatation if the stone is impacted, and the size of the stone if not impacted. Our study suggests that the impacted stone, intramural stricture requiring dilatation and stone size may have a significant effect on the success rate of semirigid URS for proximal ureteral stone. Further studies with population-based and longitudinal design should be conducted to confirm this finding. © 2017 S. Karger AG, Basel.

  13. Comparison of neurofuzzy logic and decision trees in discovering knowledge from experimental data of an immediate release tablet formulation.

    PubMed

    Shao, Q; Rowe, R C; York, P

    2007-06-01

    Understanding of the cause-effect relationships between formulation ingredients, process conditions and product properties is essential for developing a quality product. However, the formulation knowledge is often hidden in experimental data and not easily interpretable. This study compares neurofuzzy logic and decision tree approaches in discovering hidden knowledge from an immediate release tablet formulation database relating formulation ingredients (silica aerogel, magnesium stearate, microcrystalline cellulose and sodium carboxymethylcellulose) and process variables (dwell time and compression force) to tablet properties (tensile strength, disintegration time, friability, capping and drug dissolution at various time intervals). Both approaches successfully generated useful knowledge in the form of either "if then" rules or decision trees. Although different strategies are employed by the two approaches in generating rules/trees, similar knowledge was discovered in most cases. However, as decision trees are not able to deal with continuous dependent variables, data discretisation procedures are generally required.

  14. Determinants of farmers' tree-planting investment decisions as a degraded landscape management strategy in the central highlands of Ethiopia

    NASA Astrophysics Data System (ADS)

    Gessesse, Berhan; Bewket, Woldeamlak; Bräuning, Achim

    2016-04-01

    Land degradation due to lack of sustainable land management practices is one of the critical challenges in many developing countries including Ethiopia. This study explored the major determinants of farm-level tree-planting decisions as a land management strategy in a typical farming and degraded landscape of the Modjo watershed, Ethiopia. The main data were generated from household surveys and analysed using descriptive statistics and a binary logistic regression model. The model significantly predicted farmers' tree-planting decisions (χ2 = 37.29, df = 15, P < 0.001). Besides, the computed significant value of the model revealed that all the considered predictor variables jointly influenced the farmers' decisions to plant trees as a land management strategy. The findings of the study demonstrated that the adoption of tree-growing decisions by local land users was a function of a wide range of biophysical, institutional, socioeconomic and household-level factors. In this regard, the likelihood of household size, productive labour force availability, the disparity of schooling age, level of perception of the process of deforestation and the current land tenure system had a critical influence on tree-growing investment decisions in the study watershed. Eventually, the processes of land-use conversion and land degradation were serious, which in turn have had adverse effects on agricultural productivity, local food security and poverty trap nexus. Hence, the study recommended that devising and implementing sustainable land management policy options would enhance ecological restoration and livelihood sustainability in the study watershed.

  15. Determinants of farmers' tree planting investment decision as a degraded landscape management strategy in the central highlands of Ethiopia

    NASA Astrophysics Data System (ADS)

    Gessesse, B.; Bewket, W.; Bräuning, A.

    2015-11-01

    Land degradation due to lack of sustainable land management practices are one of the critical challenges in many developing countries including Ethiopia. This study explores the major determinants of farm level tree planting decision as a land management strategy in a typical framing and degraded landscape of the Modjo watershed, Ethiopia. The main data were generated from household surveys and analysed using descriptive statistics and binary logistic regression model. The model significantly predicted farmers' tree planting decision (Chi-square = 37.29, df = 15, P<0.001). Besides, the computed significant value of the model suggests that all the considered predictor variables jointly influenced the farmers' decision to plant trees as a land management strategy. In this regard, the finding of the study show that local land-users' willingness to adopt tree growing decision is a function of a wide range of biophysical, institutional, socioeconomic and household level factors, however, the likelihood of household size, productive labour force availability, the disparity of schooling age, level of perception of the process of deforestation and the current land tenure system have positively and significantly influence on tree growing investment decisions in the study watershed. Eventually, the processes of land use conversion and land degradation are serious which in turn have had adverse effects on agricultural productivity, local food security and poverty trap nexus. Hence, devising sustainable and integrated land management policy options and implementing them would enhance ecological restoration and livelihood sustainability in the study watershed.

  16. Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

    NASA Astrophysics Data System (ADS)

    Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

    2018-05-01

    Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.

  17. Validating a decision tree for serious infection: diagnostic accuracy in acutely ill children in ambulatory care.

    PubMed

    Verbakel, Jan Y; Lemiengre, Marieke B; De Burghgraeve, Tine; De Sutter, An; Aertgeerts, Bert; Bullens, Dominique M A; Shinkins, Bethany; Van den Bruel, Ann; Buntinx, Frank

    2015-08-07

    Acute infection is the most common presentation of children in primary care with only few having a serious infection (eg, sepsis, meningitis, pneumonia). To avoid complications or death, early recognition and adequate referral are essential. Clinical prediction rules have the potential to improve diagnostic decision-making for rare but serious conditions. In this study, we aimed to validate a recently developed decision tree in a new but similar population. Diagnostic accuracy study validating a clinical prediction rule. Acutely ill children presenting to ambulatory care in Flanders, Belgium, consisting of general practice and paediatric assessment in outpatient clinics or the emergency department. Physicians were asked to score the decision tree in every child. The outcome of interest was hospital admission for at least 24 h with a serious infection within 5 days after initial presentation. We report the diagnostic accuracy of the decision tree in sensitivity, specificity, likelihood ratios and predictive values. In total, 8962 acute illness episodes were included, of which 283 lead to admission to hospital with a serious infection. Sensitivity of the decision tree was 100% (95% CI 71.5% to 100%) at a specificity of 83.6% (95% CI 82.3% to 84.9%) in the general practitioner setting with 17% of children testing positive. In the paediatric outpatient and emergency department setting, sensitivities were below 92%, with specificities below 44.8%. In an independent validation cohort, this clinical prediction rule has shown to be extremely sensitive to identify children at risk of hospital admission for a serious infection in general practice, making it suitable for ruling out. NCT02024282. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  18. ON THE TIDAL DISSIPATION OF OBLIQUITY

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rogers, T. M.; Lin, D. N. C., E-mail: tami@lpl.arizona.edu, E-mail: lin@ucolick.org

    2013-05-20

    We investigate tidal dissipation of obliquity in hot Jupiters. Assuming an initial random orientation of obliquity and parameters relevant to the observed population, the obliquity of hot Jupiters does not evolve to purely aligned systems. In fact, the obliquity evolves to either prograde, retrograde, or 90 Degree-Sign orbits where the torque due to tidal perturbations vanishes. This distribution is incompatible with observations which show that hot Jupiters around cool stars are generally aligned. This calls into question the viability of tidal dissipation as the mechanism for obliquity alignment of hot Jupiters around cool stars.

  19. A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

    PubMed

    Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

    2018-01-01

    In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

  20. Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

    PubMed

    Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

    2018-05-12

    Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

  1. Identifying Risk and Protective Factors in Recidivist Juvenile Offenders: A Decision Tree Approach

    PubMed Central

    Ortega-Campos, Elena; García-García, Juan; Gil-Fenoy, Maria José; Zaldívar-Basurto, Flor

    2016-01-01

    Research on juvenile justice aims to identify profiles of risk and protective factors in juvenile offenders. This paper presents a study of profiles of risk factors that influence young offenders toward committing sanctionable antisocial behavior (S-ASB). Decision tree analysis is used as a multivariate approach to the phenomenon of repeated sanctionable antisocial behavior in juvenile offenders in Spain. The study sample was made up of the set of juveniles who were charged in a court case in the Juvenile Court of Almeria (Spain). The period of study of recidivism was two years from the baseline. The object of study is presented, through the implementation of a decision tree. Two profiles of risk and protective factors are found. Risk factors associated with higher rates of recidivism are antisocial peers, age at baseline S-ASB, problems in school and criminality in family members. PMID:27611313

  2. Which Types of Leadership Styles Do Followers Prefer? A Decision Tree Approach

    ERIC Educational Resources Information Center

    Salehzadeh, Reza

    2017-01-01

    Purpose: The purpose of this paper is to propose a new method to find the appropriate leadership styles based on the followers' preferences using the decision tree technique. Design/methodology/approach: Statistical population includes the students of the University of Isfahan. In total, 750 questionnaires were distributed; out of which, 680…

  3. The Americans with Disabilities Act: A Decision Tree for Social Services Administrators

    ERIC Educational Resources Information Center

    O'Brien, Gerald V.; Ellegood, Christina

    2005-01-01

    The 1990 Americans with Disabilities Act has had a profound influence on social workers and social services administrators in virtually all work settings. Because of the multiple elements of the act, however, assessing the validity of claims can be a somewhat arduous and complicated task. This article provides a "decision tree" for…

  4. A decision tree approach using silvics to guide planning for forest restoration

    Treesearch

    Sharon M. Hermann; John S. Kush; John C. Gilbert

    2013-01-01

    We created a decision tree based on silvics of longleaf pine (Pinus palustris) and historical descriptions to develop approaches for restoration management at Horseshoe Bend National Military Park located in central Alabama. A National Park Service goal is to promote structure and composition of a forest that likely surrounded the 1814 battlefield....

  5. What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis

    ERIC Educational Resources Information Center

    Thomas, Emily H.; Galambos, Nora

    2004-01-01

    To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…

  6. Classification of Liss IV Imagery Using Decision Tree Methods

    NASA Astrophysics Data System (ADS)

    Verma, Amit Kumar; Garg, P. K.; Prasad, K. S. Hari; Dadhwal, V. K.

    2016-06-01

    Image classification is a compulsory step in any remote sensing research. Classification uses the spectral information represented by the digital numbers in one or more spectral bands and attempts to classify each individual pixel based on this spectral information. Crop classification is the main concern of remote sensing applications for developing sustainable agriculture system. Vegetation indices computed from satellite images gives a good indication of the presence of vegetation. It is an indicator that describes the greenness, density and health of vegetation. Texture is also an important characteristics which is used to identifying objects or region of interest is an image. This paper illustrate the use of decision tree method to classify the land in to crop land and non-crop land and to classify different crops. In this paper we evaluate the possibility of crop classification using an integrated approach methods based on texture property with different vegetation indices for single date LISS IV sensor 5.8 meter high spatial resolution data. Eleven vegetation indices (NDVI, DVI, GEMI, GNDVI, MSAVI2, NDWI, NG, NR, NNIR, OSAVI and VI green) has been generated using green, red and NIR band and then image is classified using decision tree method. The other approach is used integration of texture feature (mean, variance, kurtosis and skewness) with these vegetation indices. A comparison has been done between these two methods. The results indicate that inclusion of textural feature with vegetation indices can be effectively implemented to produce classifiedmaps with 8.33% higher accuracy for Indian satellite IRS-P6, LISS IV sensor images.

  7. Re-Construction of Reference Population and Generating Weights by Decision Tree

    DTIC Science & Technology

    2017-07-21

    2017 Claflin University Orangeburg, SC 29115 DEFENSE EQUAL OPPORTUNITY MANAGEMENT INSTITUTE RESEARCH, DEVELOPMENT, AND STRATEGIC...Original Dataset 32 List of Figures in Appendix B Figure 1: Flow and Components of Project 20 Figure 2: Decision Tree 31 Figure 3: Effects of Weight...can compare the sample data. The dataset of this project has the reference population on unit level for group and gender, which is in red-dotted box

  8. The obturator oblique and iliac oblique/outlet views predict most accurately the adequate position of an anterior column acetabular screw.

    PubMed

    Guimarães, João Antonio Matheus; Martin, Murphy P; da Silva, Flávio Ribeiro; Duarte, Maria Eugenia Leite; Cavalcanti, Amanda Dos Santos; Machado, Jamila Alessandra Perini; Mauffrey, Cyril; Rojas, David

    2018-06-08

    Percutaneous fixation of the acetabulum is a treatment option for select acetabular fractures. Intra-operative fluoroscopy is required, and despite various described imaging strategies, it is debatable as to which combination of fluoroscopic views provides the most accurate and reliable assessment of screw position. Using five synthetic pelvic models, an experimental setup was created in which the anterior acetabular columns were instrumented with screws in five distinct trajectories. Five fluoroscopic images were obtained of each model (Pelvic Inlet, Obturator Oblique, Iliac Oblique, Obturator Oblique/Outlet, and Iliac Oblique/Outlet). The images were presented to 32 pelvic and acetabular orthopaedic surgeons, who were asked to draw two conclusions regarding screw position: (1) whether the screw was intra-articular and (2) whether the screw was intraosseous in its distal course through the bony corridor. In the assessment of screw position relative to the hip joint, accuracy of surgeon's response ranged from 52% (iliac oblique/outlet) to 88% (obturator oblique), with surgeon confidence in the interpretation ranging from 60% (pelvic inlet) to 93% (obturator oblique) (P < 0.0001). In the assessment of intraosseous position of the screw, accuracy of surgeon's response ranged from 40% (obturator oblique/outlet) to 79% (iliac oblique/outlet), with surgeon confidence in the interpretation ranging from 66% (iliac oblique) to 88% (pelvic inlet) (P < 0.0001). The obturator oblique and obturator oblique/outlet views afforded the most accurate and reliable assessment of penetration into the hip joint, and intraosseous position of the screw was most accurately assessed with pelvic inlet and iliac oblique/outlet views. Clinical Question.

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

    PubMed

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

    2016-07-07

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

  10. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  11. Computerization of guidelines: a knowledge specification method to convert text to detailed decision tree for electronic implementation.

    PubMed

    Aguirre-Junco, Angel-Ricardo; Colombet, Isabelle; Zunino, Sylvain; Jaulent, Marie-Christine; Leneveut, Laurence; Chatellier, Gilles

    2004-01-01

    The initial step for the computerization of guidelines is the knowledge specification from the prose text of guidelines. We describe a method of knowledge specification based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify and represent this algorithm, along with elementary messages of recommendation. Edition tools are also necessary to facilitate the process of validation and workflow between expert physicians who will validate the specified knowledge and computer scientist who will encode the specified knowledge in a guide-line model. Applied to eleven different guidelines issued by an official agency, the method allows a quick and valid computerization and integration in a larger decision support system called EsPeR (Personalized Estimate of Risks). The quality of the text guidelines is however still to be developed further. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

  12. Bayesian averaging over Decision Tree models for trauma severity scoring.

    PubMed

    Schetinin, V; Jakaite, L; Krzanowski, W

    2018-01-01

    Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. a Rough Set Decision Tree Based Mlp-Cnn for Very High Resolution Remotely Sensed Image Classification

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  14. Comparative study of unilateral versus bilateral inferior oblique recession/anteriorization in unilateral inferior oblique overaction.

    PubMed

    Mostafa, Attiat M; Kassem, Rehab R

    2018-05-01

    To compare the effect of, and the rate of subsequent development of iatrogenic antielevation syndrome after, unilateral versus bilateral inferior oblique graded recession-anteriorization to treat unilateral inferior oblique overaction. Thirty-four patients with unilateral inferior oblique overaction were included in a randomized prospective study. Patients were equally divided into 2 groups. Group UNI underwent unilateral, group BI bilateral, inferior oblique graded recession-anteriorization. A successful outcome was defined as orthotropia, or within 2 ∆ of a residual hypertropia, in the absence of signs of antielevation syndrome, residual inferior oblique overaction, V-pattern, dissociated vertical deviation, or ocular torticollis. A successful outcome was achieved in 11 (64.7%) and 13 (76.5%) patients in groups UNI and BI, respectively (p = 0.452). Antielevation syndrome was diagnosed as the cause of surgical failure in 6 (35.3%) and 2 (11.8%) patients, in groups UNI and BI, respectively (p = 0.106). The cause of surgical failure in the other 2 patients in group BI was due to persistence of ocular torticollis and hypertropia in a patient with superior oblique palsy and a residual V-pattern and hypertropia in the other patient. The differences between unilateral and bilateral inferior oblique graded recession-anteriorization are insignificant. Unilateral surgery has a higher tendency for the subsequent development of antielevation syndrome. Bilateral surgery may still become complicated by antielevation syndrome, although at a lower rate. In addition, bilateral surgery had a higher rate of undercorrection. Further studies on a larger sample are encouraged.

  15. Climates of Oblique Exoplanets

    NASA Astrophysics Data System (ADS)

    Dobrovolskis, A. R.

    2008-12-01

    A previous paper (Dobrovolskis 2007; Icarus 192, 1-23) showed that eccentricity can have profound effects on the climate, habitability, and detectability of extrasolar planets. This complementary study shows that obliquity can have comparable effects. The known exoplanets exhibit a wide range of orbital eccentricities, but those within several million km of their suns are generally in near-circular orbits. This fact is widely attributed to the dissipation of tides in the planets, which is particularly effective for solid/liquid bodies like "Super-Earths". Along with friction between a solid mantle and a liquid core, tides also are expected to despin a planet until it is captured in the synchronous resonance, so that its rotation period is identical to its orbital period. The canonical example of synchronous spin is the way that our Moon always keeps nearly the same hemisphere facing the Earth. Tides also tend to reduce the planet's obliquity (the angle between its spin and orbital angular velocities). However, orbit precession can cause the rotation to become locked in a "Cassini state", where it retains a nearly constant non-zero obliquity. For example, our Moon maintains an obliquity of about 6.7° with respect to its orbit about the Earth. For comparison, stable Cassini states can exist for practically any obliquity up to 180° for planets of binary stars, or in multi-planet systems with high mutual inclinations, such as are produced by scattering or by the Kozai mechanism. This work considers planets in synchronous rotation with circular orbits. For obliquities greater than 90°, the ground track of the sub-solar point wraps around all longitudes on the surface of such a planet. For smaller obliquities, the sub-solar track takes the figure-8 shape of an analemma. This can be visualized as the intersection of the planet's spherical surface with a right circular cylinder, parallel to the spin axis and tangent to the equator from the inside. The excursion of the

  16. Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

    NASA Astrophysics Data System (ADS)

    Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.

    2017-12-01

    Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. Since sub-daily streamflow information is unavailable for most small basins in China, one of the main challenges is finding appropriate parameter values for simulating flash floods in ungauged catchments. In this study, we use decision tree learning to explore parameter set transferability between different catchments. For this purpose, the physically-based, semi-distributed rainfall-runoff model PRMS-OMS is set up for 35 catchments in ten Chinese provinces. Hourly data from more than 800 storm runoff events are used to calibrate the model and evaluate the performance of parameter set transfers between catchments. For each catchment, 58 catchment attributes are extracted from several data sets available for whole China. We then use a data mining technique (decision tree learning) to identify catchment similarities that can be related to good transfer performance. Finally, we use the splitting rules of decision trees for finding suitable donor catchments for ungauged target catchments. We show that decision tree learning allows to optimally utilize the information content of available catchment descriptors and outperforms regionalization based on a conventional measure of physiographic-climatic similarity by 15%-20%. Similar performance can be achieved with a regionalization method based on spatial proximity, but decision trees offer flexible rules for selecting suitable donor catchments, not relying on the vicinity of gauged catchments. This flexibility makes the method particularly suitable for implementation in sparsely gauged environments. We evaluate the probability to detect flood events exceeding a given return period, considering measured discharge and PRMS-OMS simulated flows with regionalized parameters

  17. The risk of disabling, surgery and reoperation in Crohn's disease - A decision tree-based approach to prognosis.

    PubMed

    Dias, Cláudia Camila; Pereira Rodrigues, Pedro; Fernandes, Samuel; Portela, Francisco; Ministro, Paula; Martins, Diana; Sousa, Paula; Lago, Paula; Rosa, Isadora; Correia, Luis; Moura Santos, Paula; Magro, Fernando

    2017-01-01

    Crohn's disease (CD) is a chronic inflammatory bowel disease known to carry a high risk of disabling and many times requiring surgical interventions. This article describes a decision-tree based approach that defines the CD patients' risk or undergoing disabling events, surgical interventions and reoperations, based on clinical and demographic variables. This multicentric study involved 1547 CD patients retrospectively enrolled and divided into two cohorts: a derivation one (80%) and a validation one (20%). Decision trees were built upon applying the CHAIRT algorithm for the selection of variables. Three-level decision trees were built for the risk of disabling and reoperation, whereas the risk of surgery was described in a two-level one. A receiver operating characteristic (ROC) analysis was performed, and the area under the curves (AUC) Was higher than 70% for all outcomes. The defined risk cut-off values show usefulness for the assessed outcomes: risk levels above 75% for disabling had an odds test positivity of 4.06 [3.50-4.71], whereas risk levels below 34% and 19% excluded surgery and reoperation with an odds test negativity of 0.15 [0.09-0.25] and 0.50 [0.24-1.01], respectively. Overall, patients with B2 or B3 phenotype had a higher proportion of disabling disease and surgery, while patients with later introduction of pharmacological therapeutic (1 months after initial surgery) had a higher proportion of reoperation. The decision-tree based approach used in this study, with demographic and clinical variables, has shown to be a valid and useful approach to depict such risks of disabling, surgery and reoperation.

  18. Surface electromyography activity of the rectus abdominis, internal oblique, and external oblique muscles during forced expiration in healthy adults.

    PubMed

    Ito, Kenichi; Nonaka, Koji; Ogaya, Shinya; Ogi, Atsushi; Matsunaka, Chiaki; Horie, Jun

    2016-06-01

    We aimed to characterize rectus abdominis, internal oblique, and external oblique muscle activity in healthy adults under expiratory resistance using surface electromyography. We randomly assigned 42 healthy adult subjects to 3 groups: 30%, 20%, and 10% maximal expiratory intraoral pressure (PEmax). After measuring 100% PEmax and muscle activity during 100% PEmax, the activity and maximum voluntary contraction of each muscle during the assigned experimental condition were measured. At 100% PEmax, the external oblique (p<0.01) and internal oblique (p<0.01) showed significantly elevated activity compared with the rectus abdominis muscle. Furthermore, at 20% and 30% PEmax, the external oblique (p<0.05 and<0.01, respectively) and the internal oblique (p<0.05 and<0.01, respectively) showed significantly elevated activity compared with the rectus abdominis muscle. At 10% PEmax, no significant differences were observed in muscle activity. Although we observed no significant difference between 10% and 20% PEmax, activity during 30% PEmax was significantly greater than during 20% PEmax (external oblique: p<0.05; internal oblique: p<0.01). The abdominal oblique muscles are the most active during forced expiration. Moreover, 30% PEmax is the minimum intensity required to achieve significant, albeit very slight, muscle activity during expiratory resistance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. A multivariate decision tree analysis of biophysical factors in tropical forest fire occurrence

    Treesearch

    Rey S. Ofren; Edward Harvey

    2000-01-01

    A multivariate decision tree model was used to quantify the relative importance of complex hierarchical relationships between biophysical variables and the occurrence of tropical forest fires. The study site is the Huai Kha Kbaeng wildlife sanctuary, a World Heritage Site in northwestern Thailand where annual fires are common and particularly destructive. Thematic...

  20. The risk factors of laryngeal pathology in Korean adults using a decision tree model.

    PubMed

    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.

  1. Habitable planets with high obliquities

    NASA Technical Reports Server (NTRS)

    Williams, D. M.; Kasting, J. F.

    1997-01-01

    Earth's obliquity would vary chaotically from 0 degrees to 85 degrees were it not for the presence of the Moon (J. Laskar, F. Joutel, and P. Robutel, 1993, Nature 361, 615-617). The Moon itself is thought to be an accident of accretion, formed by a glancing blow from a Mars-sized planetesimal. Hence, planets with similar moons and stable obliquities may be extremely rare. This has lead Laskar and colleagues to suggest that the number of Earth-like planets with high obliquities and temperate, life-supporting climates may be small. To test this proposition, we have used an energy-balance climate model to simulate Earth's climate at obliquities up to 90 degrees. We show that Earth's climate would become regionally severe in such circumstances, with large seasonal cycles and accompanying temperature extremes on middle- and high-latitude continents which might be damaging to many forms of life. The response of other, hypothetical, Earth-like planets to large obliquity fluctuations depends on their land-sea distribution and on their position within the habitable zone (HZ) around their star. Planets with several modest-sized continents or equatorial supercontinents are more climatically stable than those with polar supercontinents. Planets farther out in the HZ are less affected by high obliquities because their atmospheres should accumulate CO2 in response to the carbonate-silicate cycle. Dense, CO2-rich atmospheres transport heat very effectively and therefore limit the magnitude of both seasonal cycles and latitudinal temperature gradients. We conclude that a significant fraction of extrasolar Earth-like planets may still be habitable, even if they are subject to large obliquity fluctuations.

  2. Identification of pests and diseases of Dalbergia hainanensis based on EVI time series and classification of decision tree

    NASA Astrophysics Data System (ADS)

    Luo, Qiu; Xin, Wu; Qiming, Xiong

    2017-06-01

    In the process of vegetation remote sensing information extraction, the problem of phenological features and low performance of remote sensing analysis algorithm is not considered. To solve this problem, the method of remote sensing vegetation information based on EVI time-series and the classification of decision-tree of multi-source branch similarity is promoted. Firstly, to improve the time-series stability of recognition accuracy, the seasonal feature of vegetation is extracted based on the fitting span range of time-series. Secondly, the decision-tree similarity is distinguished by adaptive selection path or probability parameter of component prediction. As an index, it is to evaluate the degree of task association, decide whether to perform migration of multi-source decision tree, and ensure the speed of migration. Finally, the accuracy of classification and recognition of pests and diseases can reach 87%--98% of commercial forest in Dalbergia hainanensis, which is significantly better than that of MODIS coverage accuracy of 80%--96% in this area. Therefore, the validity of the proposed method can be verified.

  3. Using Decision Trees for Estimating Mode Choice of Trips in Buca-Izmir

    NASA Astrophysics Data System (ADS)

    Oral, L. O.; Tecim, V.

    2013-05-01

    Decision makers develop transportation plans and models for providing sustainable transport systems in urban areas. Mode Choice is one of the stages in transportation modelling. Data mining techniques can discover factors affecting the mode choice. These techniques can be applied with knowledge process approach. In this study a data mining process model is applied to determine the factors affecting the mode choice with decision trees techniques by considering individual trip behaviours from household survey data collected within Izmir Transportation Master Plan. From this perspective transport mode choice problem is solved on a case in district of Buca-Izmir, Turkey with CRISP-DM knowledge process model.

  4. Defender-Attacker Decision Tree Analysis to Combat Terrorism.

    PubMed

    Garcia, Ryan J B; von Winterfeldt, Detlof

    2016-12-01

    We propose a methodology, called defender-attacker decision tree analysis, to evaluate defensive actions against terrorist attacks in a dynamic and hostile environment. Like most game-theoretic formulations of this problem, we assume that the defenders act rationally by maximizing their expected utility or minimizing their expected costs. However, we do not assume that attackers maximize their expected utilities. Instead, we encode the defender's limited knowledge about the attacker's motivations and capabilities as a conditional probability distribution over the attacker's decisions. We apply this methodology to the problem of defending against possible terrorist attacks on commercial airplanes, using one of three weapons: infrared-guided MANPADS (man-portable air defense systems), laser-guided MANPADS, or visually targeted RPGs (rocket propelled grenades). We also evaluate three countermeasures against these weapons: DIRCMs (directional infrared countermeasures), perimeter control around the airport, and hardening airplanes. The model includes deterrence effects, the effectiveness of the countermeasures, and the substitution of weapons and targets once a specific countermeasure is selected. It also includes a second stage of defensive decisions after an attack occurs. Key findings are: (1) due to the high cost of the countermeasures, not implementing countermeasures is the preferred defensive alternative for a large range of parameters; (2) if the probability of an attack and the associated consequences are large, a combination of DIRCMs and ground perimeter control are preferred over any single countermeasure. © 2016 Society for Risk Analysis.

  5. Using Boosting Decision Trees in Gravitational Wave Searches triggered by Gamma-ray Bursts

    NASA Astrophysics Data System (ADS)

    Zuraw, Sarah; LIGO Collaboration

    2015-04-01

    The search for gravitational wave bursts requires the ability to distinguish weak signals from background detector noise. Gravitational wave bursts are characterized by their transient nature, making them particularly difficult to detect as they are similar to non-Gaussian noise fluctuations in the detector. The Boosted Decision Tree method is a powerful machine learning algorithm which uses Multivariate Analysis techniques to explore high-dimensional data sets in order to distinguish between gravitational wave signal and background detector noise. It does so by training with known noise events and simulated gravitational wave events. The method is tested using waveform models and compared with the performance of the standard gravitational wave burst search pipeline for Gamma-ray Bursts. It is shown that the method is able to effectively distinguish between signal and background events under a variety of conditions and over multiple Gamma-ray Burst events. This example demonstrates the usefulness and robustness of the Boosted Decision Tree and Multivariate Analysis techniques as a detection method for gravitational wave bursts. LIGO, UMass, PREP, NEGAP.

  6. Lunar Obliquity History Revisited

    NASA Astrophysics Data System (ADS)

    Siegler, M.; Bills, B.; Paige, D.

    2007-12-01

    In preparation for a LRO (Lunar Reconnaissance Orbiter) related study of possible lunar polar volatiles, we re- examined the lunar orbital and rotational history, with primary focus on the obliquity history of the Moon. Though broad models have been made of lunar obliquity, a cohesive obliquity history was not found. We report on a new model of lunar obliquity including secular changes in inclination of the lunar orbit, tidal dissipation, lunar moments of inertia, and details for periods outside of the stable configurations known as Cassini states. For planets, the obliquity, or angle between the spin and orbit poles, is the dominant control on incident solar radiation. For planetary satellites, the radiation pattern can be more complex, as it depends on the mutual inclinations of three poles; the satellite spin and orbit poles, and the planetary heliocentric orbit pole. Presently, the lunar spin pole and orbit pole co-precess about the ecliptic pole, in a stable situation known as a Cassini state. As a result, permanently shadowed regions near the poles are expected to exist and act as cold traps, retaining water or other volatiles delivered to the surface by comets, solar wind, or via outgassing of the lunar interior. However, tidally driven secular changes in the lunar semimajor axis cause changes in precession rates of the spin and orbit poles, and thereby alter or destabilize the Cassini states. Only one prograde Cassini state exists at present (state 2). In the standard Cassini state model of Ward [1975], two other such states would have existed in the past (states 1 and 4) with the Moon starting in the low obliquity state 1, and remaining there until states 1 and 4 merged and disappear, at roughly half the present Earth-Moon distance. At that point, the Moon transitioned into the currently occupied state 2, and briefly attained very high obliquity values during the transition, and then stayed in state 2 until the present. If correct, this model implies that

  7. Type 2 Diabetes Mellitus Screening and Risk Factors Using Decision Tree: Results of Data Mining.

    PubMed

    Habibi, Shafi; Ahmadi, Maryam; Alizadeh, Somayeh

    2015-03-18

    The aim of this study was to examine a predictive model using features related to the diabetes type 2 risk factors. The data were obtained from a database in a diabetes control system in Tabriz, Iran. The data included all people referred for diabetes screening between 2009 and 2011. The features considered as "Inputs" were: age, sex, systolic and diastolic blood pressure, family history of diabetes, and body mass index (BMI). Moreover, we used diagnosis as "Class". We applied the "Decision Tree" technique and "J48" algorithm in the WEKA (3.6.10 version) software to develop the model. After data preprocessing and preparation, we used 22,398 records for data mining. The model precision to identify patients was 0.717. The age factor was placed in the root node of the tree as a result of higher information gain. The ROC curve indicates the model function in identification of patients and those individuals who are healthy. The curve indicates high capability of the model, especially in identification of the healthy persons. We developed a model using the decision tree for screening T2DM which did not require laboratory tests for T2DM diagnosis.

  8. Decision support for mitigating the risk of tree induced transmission line failure in utility rights-of-way.

    PubMed

    Poulos, H M; Camp, A E

    2010-02-01

    Vegetation management is a critical component of rights-of-way (ROW) maintenance for preventing electrical outages and safety hazards resulting from tree contact with conductors during storms. Northeast Utility's (NU) transmission lines are a critical element of the nation's power grid; NU is therefore under scrutiny from federal agencies charged with protecting the electrical transmission infrastructure of the United States. We developed a decision support system to focus right-of-way maintenance and minimize the potential for a tree fall episode that disables transmission capacity across the state of Connecticut. We used field data on tree characteristics to develop a system for identifying hazard trees (HTs) in the field using limited equipment to manage Connecticut power line ROW. Results from this study indicated that the tree height-to-diameter ratio, total tree height, and live crown ratio were the key characteristics that differentiated potential risk trees (danger trees) from trees with a high probability of tree fall (HTs). Products from this research can be transferred to adaptive right-of-way management, and the methods we used have great potential for future application to other regions of the United States and elsewhere where tree failure can disrupt electrical power.

  9. A Decision Tree to Identify Children Affected by Prenatal Alcohol Exposure

    PubMed Central

    Goh, Patrick K.; Doyle, Lauren R.; Glass, Leila; Jones, Kenneth L.; Riley, Edward P.; Coles, Claire D.; Hoyme, H. Eugene; Kable, Julie A.; May, Philip A.; Kalberg, Wendy O.; Elizabeth, R. Sowell; Wozniak, Jeffrey R.; Mattson, Sarah N.

    2017-01-01

    Objective To develop and validate a hierarchical decision tree model, combining neurobehavioral and physical measures, for identification of children affected by prenatal alcohol exposure even when facial dysmorphology is not present. Study design Data were collected as part of a multisite study across the United States. The model was developed after evaluating over 1000 neurobehavioral and dysmorphology variables collected from 434 children (8–16y) with prenatal alcohol exposure, with and without fetal alcohol syndrome (FAS), and non-exposed controls, with and without other clinically-relevant behavioral or cognitive concerns. The model was subsequently validated in an independent sample of 454 children in two age ranges (5–7y or 10–16y). In all analyses, the discriminatory ability of each model step was tested with logistic regression. Classification accuracies and positive and negative predictive values were calculated. Results The model consisted of variables from 4 measures (2 parent questionnaires, an IQ score, and a physical examination). Overall accuracy rates for both the development and validation samples met or exceeded our goal of 80% overall accuracy. Conclusions The decision tree model distinguished children affected by prenatal alcohol exposure from non-exposed controls, including those with other behavioral concerns or conditions. Improving identification of this population will streamline access to clinical services, including multidisciplinary evaluation and treatment. PMID:27476634

  10. Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

    PubMed Central

    Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

    2016-01-01

    Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

  11. Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

    PubMed

    Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

    2016-05-20

    In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

  12. Spatial distribution of block falls using volumetric GIS-decision-tree models

    NASA Astrophysics Data System (ADS)

    Abdallah, C.

    2010-10-01

    Block falls are considered a significant aspect of surficial instability contributing to losses in land and socio-economic aspects through their damaging effects to natural and human environments. This paper predicts and maps the geographic distribution and volumes of block falls in central Lebanon using remote sensing, geographic information systems (GIS) and decision-tree modeling (un-pruned and pruned trees). Eleven terrain parameters (lithology, proximity to fault line, karst type, soil type, distance to drainage line, elevation, slope gradient, slope aspect, slope curvature, land cover/use, and proximity to roads) were generated to statistically explain the occurrence of block falls. The latter were discriminated using SPOT4 satellite imageries, and their dimensions were determined during field surveys. The un-pruned tree model based on all considered parameters explained 86% of the variability in field block fall measurements. Once pruned, it classifies 50% in block falls' volumes by selecting just four parameters (lithology, slope gradient, soil type, and land cover/use). Both tree models (un-pruned and pruned) were converted to quantitative 1:50,000 block falls' maps with different classes; starting from Nil (no block falls) to more than 4000 m 3. These maps are fairly matching with coincidence value equal to 45%; however, both can be used to prioritize the choice of specific zones for further measurement and modeling, as well as for land-use management. The proposed tree models are relatively simple, and may also be applied to other areas (i.e. the choice of un-pruned or pruned model is related to the availability of terrain parameters in a given area).

  13. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

    PubMed

    Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

    2018-06-15

    Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Accuracy Potential and Applications of MIDAS Aerial Oblique Camera System

    NASA Astrophysics Data System (ADS)

    Madani, M.

    2012-07-01

    Airborne oblique cameras such as Fairchild T-3A were initially used for military reconnaissance in 30s. A modern professional digital oblique camera such as MIDAS (Multi-camera Integrated Digital Acquisition System) is used to generate lifelike three dimensional to the users for visualizations, GIS applications, architectural modeling, city modeling, games, simulators, etc. Oblique imagery provide the best vantage for accessing and reviewing changes to the local government tax base, property valuation assessment, buying & selling of residential/commercial for better decisions in a more timely manner. Oblique imagery is also used for infrastructure monitoring making sure safe operations of transportation, utilities, and facilities. Sanborn Mapping Company acquired one MIDAS from TrackAir in 2011. This system consists of four tilted (45 degrees) cameras and one vertical camera connected to a dedicated data acquisition computer system. The 5 digital cameras are based on the Canon EOS 1DS Mark3 with Zeiss lenses. The CCD size is 5,616 by 3,744 (21 MPixels) with the pixel size of 6.4 microns. Multiple flights using different camera configurations (nadir/oblique (28 mm/50 mm) and (50 mm/50 mm)) were flown over downtown Colorado Springs, Colorado. Boresight fights for 28 mm nadir camera were flown at 600 m and 1,200 m and for 50 mm nadir camera at 750 m and 1500 m. Cameras were calibrated by using a 3D cage and multiple convergent images utilizing Australis model. In this paper, the MIDAS system is described, a number of real data sets collected during the aforementioned flights are presented together with their associated flight configurations, data processing workflow, system calibration and quality control workflows are highlighted and the achievable accuracy is presented in some detail. This study revealed that the expected accuracy of about 1 to 1.5 GSD (Ground Sample Distance) for planimetry and about 2 to 2.5 GSD for vertical can be achieved. Remaining systematic

  15. Decision Tree Algorithm-Generated Single-Nucleotide Polymorphism Barcodes of rbcL Genes for 38 Brassicaceae Species Tagging.

    PubMed

    Yang, Cheng-Hong; Wu, Kuo-Chuan; Chuang, Li-Yeh; Chang, Hsueh-Wei

    2018-01-01

    DNA barcode sequences are accumulating in large data sets. A barcode is generally a sequence larger than 1000 base pairs and generates a computational burden. Although the DNA barcode was originally envisioned as straightforward species tags, the identification usage of barcode sequences is rarely emphasized currently. Single-nucleotide polymorphism (SNP) association studies provide us an idea that the SNPs may be the ideal target of feature selection to discriminate between different species. We hypothesize that SNP-based barcodes may be more effective than the full length of DNA barcode sequences for species discrimination. To address this issue, we tested a r ibulose diphosphate carboxylase ( rbcL ) S NP b arcoding (RSB) strategy using a decision tree algorithm. After alignment and trimming, 31 SNPs were discovered in the rbcL sequences from 38 Brassicaceae plant species. In the decision tree construction, these SNPs were computed to set up the decision rule to assign the sequences into 2 groups level by level. After algorithm processing, 37 nodes and 31 loci were required for discriminating 38 species. Finally, the sequence tags consisting of 31 rbcL SNP barcodes were identified for discriminating 38 Brassicaceae species based on the decision tree-selected SNP pattern using RSB method. Taken together, this study provides the rational that the SNP aspect of DNA barcode for rbcL gene is a useful and effective sequence for tagging 38 Brassicaceae species.

  16. Climate at high obliquity

    NASA Astrophysics Data System (ADS)

    Marshall, J.; Ferreira, D.; O'Gorman, P. A.; Seager, S.

    2011-12-01

    One method of studying earth-like exoplanets is to view earth as an exoplanet and consider how its climate might change if, for example, its obliquity were ranged from 0 to 90 degrees. High values of obliquity challenge our understanding of climate dynamics because if obliquity exceeds 54 degrees, then polar latitudes receive more energy per unit area than do equatorial latitudes. Thus the pole will become warmer than the equator and we are led to consider a world in which the meridional temperature gradients, and associated prevailing zonal wind, have the opposite sign to the present earth. The problem becomes even richer when one considers the dynamics of an ocean, should one exist below. A central question for the ocean circulation is: what is the pattern of surface winds at high obliquities?, for it is the winds that drive the ocean currents and thermohaline circulation. How do atmospheric weather systems growing in the easterly sheared middle latitude jets determine the surface wind pattern? Should one expect middle latitude easterly winds? Finally, a key aspect with regard to habitability is to understand how the atmosphere and ocean of this high obliquity planet work cooperatively together to transport energy meridionally, mediating the warmth of the poles and the coldness of the equator. How extreme are seasonal temperature fluctuations? Should one expect to find ice around the equator? Possible answers to some of these questions have been sought by experimentation with a coupled atmosphere, ocean and sea-ice General Circulation Model of an earth-like aquaplanet: i.e. a planet like our own but on which there is only an ocean but no land. The coupled climate is studied across a range of obliquities (23.5, 54 and 90). We present some of the descriptive climatology of our solutions and how they shed light on the deeper questions of coupled climate dynamics that motivate them. We also review what they tell us about habitability on such planets.

  17. Treatment of inferior oblique paresis with superior oblique silicone tendon expander.

    PubMed

    Greenberg, Marc F; Pollard, Zane F

    2005-08-01

    Patients with inferior oblique eye muscle paresis may show hypotropia and apparent superior oblique muscle overaction on the side of the presumed weak inferior oblique (IO) muscle. We report 8 such patients successfully treated using unilateral silicone superior oblique (SO) tendon expanders. Eight consecutive cases over the course of 6 years from the authors' private practice are described. None had a history of head trauma or a significant neurologic event. All patients showed IO paresis by 3-step test, with incyclotorsion and SO overacton of the hypotropic (paretic) eye. Forced ductions of the hypotropic eye were normal in all cases, and the vertical strabismus was treated with placement of a 7- mm silicone SO tendon expander in the hypotropic (paretic) eye. Mean preoperative primary position hypotropia was 6.5 prism diopters (PD); mean postoperative was 0.5 PD. Seven of 8 patients had resolution of primary position hypotropia, whereas the eighth was reduced. Mean preoperative SO overaction was 3+; all patients had postoperative resolution of SO overaction. Of 4 patients with preoperative ocular torticollis, mean preoperative head tilt was 9.3 degrees; mean postoperative tilt was 2.9 degrees. Two patients' head tilts had resolved, the other 2 showed improvement. All patients showed preoperative incylclotorsion of the hypotropic (paretic) eye; inclyclotorsion resolved in all patients after the placement of a SO tendon expander. The silicone SO tendon expander effectively restores ocular alignment in IO paresis with apparent SO overaction. Associated ocular torticollis can also be improved.

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

    PubMed

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

    2017-06-01

    Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p < 0.05). Identifying and training mothers at risk as well as improving prenatal care may reduce the PTB rate. We also recommend that statisticians utilize the logistic regression model for the classification of risk groups for PTB.

  19. Optimization of matrix tablets controlled drug release using Elman dynamic neural networks and decision trees.

    PubMed

    Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele; Đurić, Zorica

    2012-05-30

    The main objective of the study was to develop artificial intelligence methods for optimization of drug release from matrix tablets regardless of the matrix type. Static and dynamic artificial neural networks of the same topology were developed to model dissolution profiles of different matrix tablets types (hydrophilic/lipid) using formulation composition, compression force used for tableting and tablets porosity and tensile strength as input data. Potential application of decision trees in discovering knowledge from experimental data was also investigated. Polyethylene oxide polymer and glyceryl palmitostearate were used as matrix forming materials for hydrophilic and lipid matrix tablets, respectively whereas selected model drugs were diclofenac sodium and caffeine. Matrix tablets were prepared by direct compression method and tested for in vitro dissolution profiles. Optimization of static and dynamic neural networks used for modeling of drug release was performed using Monte Carlo simulations or genetic algorithms optimizer. Decision trees were constructed following discretization of data. Calculated difference (f(1)) and similarity (f(2)) factors for predicted and experimentally obtained dissolution profiles of test matrix tablets formulations indicate that Elman dynamic neural networks as well as decision trees are capable of accurate predictions of both hydrophilic and lipid matrix tablets dissolution profiles. Elman neural networks were compared to most frequently used static network, Multi-layered perceptron, and superiority of Elman networks have been demonstrated. Developed methods allow simple, yet very precise way of drug release predictions for both hydrophilic and lipid matrix tablets having controlled drug release. Copyright © 2012 Elsevier B.V. All rights reserved.

  20. Low-latitude glaciation and rapid changes in the Earth's obliquity explained by obliquity-oblateness feedback

    NASA Astrophysics Data System (ADS)

    Williams, Darren M.; Kasting, James F.; Frakes, Lawrence A.

    1998-12-01

    Palaeomagnetic data suggest that the Earth was glaciated at low latitudes during the Palaeoproterozoic, (about 2.4-2.2Gyr ago) and Neoproterozoic (about 820-550Myr ago) eras, although some of the Neoproterozoic data are disputed,. If the Earth's magnetic field was aligned more or less with its spin axis, as it is today, then either the polar ice caps must have extended well down into the tropics - the `snowball Earth' hypothesis - or the present zonation of climate with respect to latitude must have been reversed. Williams has suggested that the Earth's obliquity may have been greater than 54° during most of its history, which would have made the Equator the coldest part of the planet. But this would require a mechanism to bring the obliquity down to its present value of 23.5°. Here we propose that obliquity-oblateness feedback could have reduced the Earth's obliquity by tens of degrees in less than 100Myr if the continents were situated so as to promote the formation of large polar ice sheets. A high obliquity for the early Earth may also provide a natural explanation for the present inclination of the lunar orbit with respect to the ecliptic (5°), which is otherwise difficult to explain.

  1. Low-latitude glaciation and rapid changes in the Earth's obliquity explained by obliquity-oblateness feedback.

    PubMed

    Williams, D M; Kasting, J F; Frakes, L A

    1998-12-03

    Palaeomagnetic data suggest that the Earth was glaciated at low latitudes during the Palaeoproterozoic (about 2.4-2.2 Gyr ago) and Neoproterozoic (about 820-550 Myr ago) eras, although some of the Neoproterozoic data are disputed. If the Earth's magnetic field was aligned more or less with its spin axis, as it is today, then either the polar ice caps must have extended well down into the tropics-the 'snowball Earth' hypothesis-or the present zonation of climate with respect to latitude must have been reversed. Williams has suggested that the Earth's obliquity may have been greater than 54 degrees during most of its history, which would have made the Equator the coldest part of the planet. But this would require a mechanism to bring the obliquity down to its present value of 23.5 degrees. Here we propose that obliquity-oblateness feedback could have reduced the Earth's obliquity by tens of degrees in less than 100 Myr if the continents were situated so as to promote the formation of large polar ice sheets. A high obliquity for the early Earth may also provide a natural explanation for the present inclination of the lunar orbit with respect to the ecliptic (5 degrees), which is otherwise difficult to explain.

  2. Detection of clinical mastitis with sensor data from automatic milking systems is improved by using decision-tree induction.

    PubMed

    Kamphuis, C; Mollenhorst, H; Heesterbeek, J A P; Hogeveen, H

    2010-08-01

    The objective was to develop and validate a clinical mastitis (CM) detection model by means of decision-tree induction. For farmers milking with an automatic milking system (AMS), it is desirable that the detection model has a high level of sensitivity (Se), especially for more severe cases of CM, at a very high specificity (Sp). In addition, an alert for CM should be generated preferably at the quarter milking (QM) at which the CM infection is visible for the first time. Data were collected from 9 Dutch dairy herds milking automatically during a 2.5-yr period. Data included sensor data (electrical conductivity, color, and yield) at the QM level and visual observations of quarters with CM recorded by the farmers. Visual observations of quarters with CM were combined with sensor data of the most recent automatic milking recorded for that same quarter, within a 24-h time window before the visual assessment time. Sensor data of 3.5 million QM were collected, of which 348 QM were combined with a CM observation. Data were divided into a training set, including two-thirds of all data, and a test set. Cows in the training set were not included in the test set and vice versa. A decision-tree model was trained using only clear examples of healthy (n=24,717) or diseased (n=243) QM. The model was tested on 105 QM with CM and a random sample of 50,000 QM without CM. While keeping the Se at a level comparable to that of models currently used by AMS, the decision-tree model was able to decrease the number of false-positive alerts by more than 50%. At an Sp of 99%, 40% of the CM cases were detected. Sixty-four percent of the severe CM cases were detected and only 12.5% of the CM that were scored as watery milk. The Se increased considerably from 40% to 66.7% when the time window increased from less than 24h before the CM observation, to a time window from 24h before to 24h after the CM observation. Even at very wide time windows, however, it was impossible to reach an Se of 100

  3. Pollutant Concentrations in Street Canyons of Different Aspect Ratio with Avenues of Trees for Various Wind Directions

    NASA Astrophysics Data System (ADS)

    Gromke, Christof; Ruck, Bodo

    2012-07-01

    This study summarizes the effects of avenues of trees in urban street canyons on traffic pollutant dispersion. We describe various wind-tunnel experiments with different tree-avenue models in combination with variations in street-canyon aspect ratio W/ H (with W the street-canyon width and H the building height) and approaching wind direction. Compared to tree-free street canyons, in general, higher pollutant concentrations are found. Avenues of trees do not suppress canyon vortices, although the air ventilation in canyons is hindered significantly. For a perpendicular wind direction, increases in wall-average and wall-maximum concentrations at the leeward canyon wall and decreases in wall-average concentrations at the windward wall are found. For oblique and perpendicular wind directions, increases at both canyon walls are obtained. The strongest effects of avenues of trees on traffic pollutant dispersion are observed for oblique wind directions for which also the largest concentrations at the canyon walls are found. Thus, the prevailing assumption that attributes the most harmful dispersion conditions to a perpendicular wind direction does not hold for street canyons with avenues of trees. Furthermore, following dimensional analysis, an estimate of the normalized wall-maximum traffic pollutant concentration in street canyons with avenues of trees is derived.

  4. Digital Oblique Remote Ionospheric Sensing (DORIS) Program Development

    DTIC Science & Technology

    1992-04-01

    waveforms. A new with the ARTIST software (Reinisch and Iluang. autoscaling technique for oblique ionograms 1983, Gamache et al., 1985) which is...development and performance of a complete oblique ionogram autoscaling and inversion algorithm is presented. The inver.i-,n algorithm uses a three...OTIH radar. 14. SUBJECT TERMS 15. NUMBER OF PAGES Oblique Propagation; Oblique lonogram Autoscaling ; i Electron Density Profile Inversion; Simulated 16

  5. Large capacity oblique all-wing transport aircraft

    NASA Technical Reports Server (NTRS)

    Galloway, Thomas L.; Phillips, James A.; Kennelly, Robert A., Jr.; Waters, Mark H.

    1996-01-01

    Dr. R. T. Jones first developed the theory for oblique wing aircraft in 1952, and in subsequent years numerous analytical and experimental projects conducted at NASA Ames and elsewhere have established that the Jones' oblique wing theory is correct. Until the late 1980's all proposed oblique wing configurations were wing/body aircraft with the wing mounted on a pivot. With the emerging requirement for commercial transports with very large payloads, 450-800 passengers, Jones proposed a supersonic oblique flying wing in 1988. For such an aircraft all payload, fuel, and systems are carried within the wing, and the wing is designed with a variable sweep to maintain a fixed subsonic normal Mach number. Engines and vertical tails are mounted on pivots supported from the primary structure of the wing. The oblique flying wing transport has come to be known as the Oblique All-Wing (OAW) transport. This presentation gives the highlights of the OAW project that was to study the total concept of the OAW as a commercial transport.

  6. Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

    NASA Astrophysics Data System (ADS)

    Zhang, W.; Li, X.; Xiao, W.

    2018-05-01

    The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the

  7. Timing and pacing of the Late Devonian mass extinction event regulated by eccentricity and obliquity.

    PubMed

    De Vleeschouwer, David; Da Silva, Anne-Christine; Sinnesael, Matthias; Chen, Daizhao; Day, James E; Whalen, Michael T; Guo, Zenghui; Claeys, Philippe

    2017-12-22

    The Late Devonian envelops one of Earth's big five mass extinction events at the Frasnian-Famennian boundary (374 Ma). Environmental change across the extinction severely affected Devonian reef-builders, besides many other forms of marine life. Yet, cause-and-effect chains leading to the extinction remain poorly constrained as Late Devonian stratigraphy is poorly resolved, compared to younger cataclysmic intervals. In this study we present a global orbitally calibrated chronology across this momentous interval, applying cyclostratigraphic techniques. Our timescale stipulates that 600 kyr separate the lower and upper Kellwasser positive δ 13 C excursions. The latter excursion is paced by obliquity and is therein similar to Mesozoic intervals of environmental upheaval, like the Cretaceous Ocean-Anoxic-Event-2 (OAE-2). This obliquity signature implies coincidence with a minimum of the 2.4 Myr eccentricity cycle, during which obliquity prevails over precession, and highlights the decisive role of astronomically forced "Milankovitch" climate change in timing and pacing the Late Devonian mass extinction.

  8. Obliquity dependence of the tangential YORP

    NASA Astrophysics Data System (ADS)

    Ševeček, P.; Golubov, O.; Scheeres, D. J.; Krugly, Yu. N.

    2016-08-01

    Context. The tangential Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect is a thermophysical effect that can alter the rotation rate of asteroids and is distinct from the so-called normal YORP effect, but to date has only been studied for asteroids with zero obliquity. Aims: We aim to study the tangential YORP force produced by spherical boulders on the surface of an asteroid with an arbitrary obliquity. Methods: A finite element method is used to simulate heat conductivity inside a boulder, to find the recoil force experienced by it. Then an ellipsoidal asteroid uniformly covered by these types of boulders is considered and the torque is numerically integrated over its surface. Results: Tangential YORP is found to operate on non-zero obliquities and decreases by a factor of two for increasing obliquity.

  9. Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

    PubMed Central

    Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

    2016-01-01

    INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

  10. A Clinical Decision Tree to Predict Whether a Bacteremic Patient Is Infected With an Extended-Spectrum β-Lactamase-Producing Organism.

    PubMed

    Goodman, Katherine E; Lessler, Justin; Cosgrove, Sara E; Harris, Anthony D; Lautenbach, Ebbing; Han, Jennifer H; Milstone, Aaron M; Massey, Colin J; Tamma, Pranita D

    2016-10-01

    Timely identification of extended-spectrum β-lactamase (ESBL) bacteremia can improve clinical outcomes while minimizing unnecessary use of broad-spectrum antibiotics, including carbapenems. However, most clinical microbiology laboratories currently require at least 24 additional hours from the time of microbial genus and species identification to confirm ESBL production. Our objective was to develop a user-friendly decision tree to predict which organisms are ESBL producing, to guide appropriate antibiotic therapy. We included patients ≥18 years of age with bacteremia due to Escherichia coli or Klebsiella species from October 2008 to March 2015 at Johns Hopkins Hospital. Isolates with ceftriaxone minimum inhibitory concentrations ≥2 µg/mL underwent ESBL confirmatory testing. Recursive partitioning was used to generate a decision tree to determine the likelihood that a bacteremic patient was infected with an ESBL producer. Discrimination of the original and cross-validated models was evaluated using receiver operating characteristic curves and by calculation of C-statistics. A total of 1288 patients with bacteremia met eligibility criteria. For 194 patients (15%), bacteremia was due to a confirmed ESBL producer. The final classification tree for predicting ESBL-positive bacteremia included 5 predictors: history of ESBL colonization/infection, chronic indwelling vascular hardware, age ≥43 years, recent hospitalization in an ESBL high-burden region, and ≥6 days of antibiotic exposure in the prior 6 months. The decision tree's positive and negative predictive values were 90.8% and 91.9%, respectively. Our findings suggest that a clinical decision tree can be used to estimate a bacteremic patient's likelihood of infection with ESBL-producing bacteria. Recursive partitioning offers a practical, user-friendly approach for addressing important diagnostic questions. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of

  11. Secular obliquity variations for Ceres

    NASA Astrophysics Data System (ADS)

    Bills, Bruce; Scott, Bryan R.; Nimmo, Francis

    2016-10-01

    We have constructed secular variation models for the orbit and spin poles of the asteroid (1) Ceres, and used them to examine how the obliquity, or angular separation between spin and orbit poles, varies over a time span of several million years. The current obliquity is 4.3 degrees, which means that there are some regions near the poles which do not receive any direct Sunlight. The Dawn mission has provided an improved estimate of the spin pole orientation, and of the low degree gravity field. That allows us to estimate the rate at which the spin pole precesses about the instantaneous orbit pole.The orbit of Ceres is secularly perturbed by the planets, with Jupiter's influence dominating. The current inclination of the orbit plane, relative to the ecliptic, is 10.6 degrees. However, it varies between 7.27 and 11.78 degrees, with dominant periods of 22.1 and 39.6 kyr. The spin pole precession rate parameter has a period of 205 kyr, with current uncertainty of 3%, dominated by uncertainty in the mean moment of inertia of Ceres.The obliquity varies, with a dominant period of 24.5 kyr, with maximum values near 26 degrees, and minimum values somewhat less than the present value. Ceres is currently near to a minimum of its secular obliquity variations.The near-surface thermal environment thus has at least 3 important time scales: diurnal (9.07 hours), annual (4.60 years), and obliquity cycle (24.5 kyr). The annual thermal wave likely only penetrates a few meters, but the much long thermal wave associated with the obliquity cycle has a skin depth larger by a factor of 70 or so, depending upon thermal properties in the subsurface.

  12. hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm.

    PubMed

    Tayefi, Maryam; Tajfard, Mohammad; Saffar, Sara; Hanachi, Parichehr; Amirabadizadeh, Ali Reza; Esmaeily, Habibollah; Taghipour, Ali; Ferns, Gordon A; Moohebati, Mohsen; Ghayour-Mobarhan, Majid

    2017-04-01

    Coronary heart disease (CHD) is an important public health problem globally. Algorithms incorporating the assessment of clinical biomarkers together with several established traditional risk factors can help clinicians to predict CHD and support clinical decision making with respect to interventions. Decision tree (DT) is a data mining model for extracting hidden knowledge from large databases. We aimed to establish a predictive model for coronary heart disease using a decision tree algorithm. Here we used a dataset of 2346 individuals including 1159 healthy participants and 1187 participant who had undergone coronary angiography (405 participants with negative angiography and 782 participants with positive angiography). We entered 10 variables of a total 12 variables into the DT algorithm (including age, sex, FBG, TG, hs-CRP, TC, HDL, LDL, SBP and DBP). Our model could identify the associated risk factors of CHD with sensitivity, specificity, accuracy of 96%, 87%, 94% and respectively. Serum hs-CRP levels was at top of the tree in our model, following by FBG, gender and age. Our model appears to be an accurate, specific and sensitive model for identifying the presence of CHD, but will require validation in prospective studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes.

    PubMed

    Esmaily, Habibollah; Tayefi, Maryam; Doosti, Hassan; Ghayour-Mobarhan, Majid; Nezami, Hossein; Amirabadizadeh, Alireza

    2018-04-24

    We aimed to identify the associated risk factors of type 2 diabetes mellitus (T2DM) using data mining approach, decision tree and random forest techniques using the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) Study program. A cross-sectional study. The MASHAD study started in 2010 and will continue until 2020. Two data mining tools, namely decision trees, and random forests, are used for predicting T2DM when some other characteristics are observed on 9528 subjects recruited from MASHAD database. This paper makes a comparison between these two models in terms of accuracy, sensitivity, specificity and the area under ROC curve. The prevalence rate of T2DM was 14% among these subjects. The decision tree model has 64.9% accuracy, 64.5% sensitivity, 66.8% specificity, and area under the ROC curve measuring 68.6%, while the random forest model has 71.1% accuracy, 71.3% sensitivity, 69.9% specificity, and area under the ROC curve measuring 77.3% respectively. The random forest model, when used with demographic, clinical, and anthropometric and biochemical measurements, can provide a simple tool to identify associated risk factors for type 2 diabetes. Such identification can substantially use for managing the health policy to reduce the number of subjects with T2DM .

  14. Applying decision tree for identification of a low risk population for type 2 diabetes. Tehran Lipid and Glucose Study.

    PubMed

    Ramezankhani, Azra; Pournik, Omid; Shahrabi, Jamal; Khalili, Davood; Azizi, Fereidoun; Hadaegh, Farzad

    2014-09-01

    The aim of this study was to create a prediction model using data mining approach to identify low risk individuals for incidence of type 2 diabetes, using the Tehran Lipid and Glucose Study (TLGS) database. For a 6647 population without diabetes, aged ≥20 years, followed for 12 years, a prediction model was developed using classification by the decision tree technique. Seven hundred and twenty-nine (11%) diabetes cases occurred during the follow-up. Predictor variables were selected from demographic characteristics, smoking status, medical and drug history and laboratory measures. We developed the predictive models by decision tree using 60 input variables and one output variable. The overall classification accuracy was 90.5%, with 31.1% sensitivity, 97.9% specificity; and for the subjects without diabetes, precision and f-measure were 92% and 0.95, respectively. The identified variables included fasting plasma glucose, body mass index, triglycerides, mean arterial blood pressure, family history of diabetes, educational level and job status. In conclusion, decision tree analysis, using routine demographic, clinical, anthropometric and laboratory measurements, created a simple tool to predict individuals at low risk for type 2 diabetes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. Applications of urban tree canopy assessment and prioritization tools: supporting collaborative decision making to achieve urban sustainability goals

    Treesearch

    Dexter H. Locke; J. Morgan Grove; Michael Galvin; Jarlath P.M. ONeil-Dunne; Charles Murphy

    2013-01-01

    Urban Tree Canopy (UTC) Prioritizations can be both a set of geographic analysis tools and a planning process for collaborative decision-making. In this paper, we describe how UTC Prioritizations can be used as a planning process to provide decision support to multiple government agencies, civic groups and private businesses to aid in reaching a canopy target. Linkages...

  16. Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients.

    PubMed

    Chen, Weisheng; Sun, Cheng; Wei, Ru; Zhang, Yanlin; Ye, Heng; Chi, Ruibin; Zhang, Yichen; Hu, Bei; Lv, Bo; Chen, Lifang; Zhang, Xiunong; Lan, Huilan; Chen, Chunbo

    2016-08-31

    Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion. © 2016 American Society for Parenteral and Enteral Nutrition.

  17. Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients.

    PubMed

    Chen, Weisheng; Sun, Cheng; Wei, Ru; Zhang, Yanlin; Ye, Heng; Chi, Ruibin; Zhang, Yichen; Hu, Bei; Lv, Bo; Chen, Lifang; Zhang, Xiunong; Lan, Huilan; Chen, Chunbo

    2018-01-01

    Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion. © 2016 American Society for Parenteral and Enteral Nutrition.

  18. The effect of polar caps on obliquity

    NASA Technical Reports Server (NTRS)

    Lindner, B. L.

    1993-01-01

    Rubincam has shown that the Martian obliquity is dependent on the seasonal polar caps. In particular, Rubincam analytically derived this dependence and showed that the change in obliquity is directly proportional to the seasonal polar cap mass. Rubincam concludes that seasonal friction does not appear to have changed Mars' climate significantly. Using a computer model for the evolution of the Martian atmosphere, Haberle et al. have made a convincing case for the possibility of huge polar caps, about 10 times the mass of the current polar caps, that exist for a significant fraction of the planet's history. Since Rubincam showed that the effect of seasonal friction on obliquity is directly proportional to polar cap mass, a scenario with a ten-fold increase in polar cap mass over a significant fraction of the planet's history would result in a secular increase in Mars' obliquity of perhaps 10 degrees. Hence, the Rubincam conclusion of an insignificant contribution to Mars' climate by seasonal friction may be incorrect. Furthermore, if seasonal friction is an important consideration in the obliquity of Mars, this would significantly alter the predictions of past obliquity.

  19. Ceres' obliquity history: implications for permanently shadowed regions

    NASA Astrophysics Data System (ADS)

    Ermakov, A.; Mazarico, E.; Schroeder, S.; Carsenty, U.; Schorghofer, N.; Raymond, C. A.; Zuber, M. T.; Smith, D. E.; Russell, C. T.

    2016-12-01

    The Dawn spacecraft's Framing Camera (FC) images and radio-tracking data have allowed precise determination of Ceres' rotational pole and obliquity. Presently, the obliquity (ɛ) of Ceres is ≈4°. Because of the low obliquity, permanently shadowed regions (PSRs) can exist on Ceres, and have been identified using both images and shape models (Schorghofer et al., 2016). These observations make Ceres only the third body in the solar system with recognized PSRs after the Moon (Zuber et al., 1997) and Mercury (Chabot et al., 2012). Some craters in Ceres' polar regions possess bright crater floor deposits (BCFD). These crater floors are typically in shadow. However, they receive light scattered from the surrounding sunlit crater walls and therefore can be seen by FC. These bright deposits are hypothesized to be water ice accumulated in PSR cold traps, analogous to the Moon (Watson et al., 1961). The existence of the PSRs critically depends on the body's obliquity. The goal of this work is to study the history of Ceres' obliquity. Knowing past obliquity variations can shed light on the history of PSRs, and can help constrain the water-ice deposition time scales. We integrate the obliquity of Ceres over the last 3 My for the range of C/MR2vol constrained by the Dawn gravity measurements (Park et al., 2016, Ermakov et al., 2016) using methods described in Wisdom & Holman (1991) and Touma & Wisdom (1994). The obliquity history for C/MR2vol=0.392 is shown in Fig. 1. The integrations show that the obliquity of Ceres undergoes large oscillations with the main period of T=25 ky and a maximum of 19.7°. The obliquity oscillations are driven by the periodic change of Ceres' orbit inclination (T=22 ky) and the pole precession (T=210 ky). Ceres passed a local obliquity minimum 1327 years ago when (ɛmin=2.4°). The most recent maximum was 13895 years ago (ɛmax=18.5°). At such high obliquity, most of the present-day PSRs receive direct sunlight. We find a correlation between

  20. Oblique Wing Research Aircraft on ramp

    NASA Technical Reports Server (NTRS)

    1976-01-01

    This 1976 photograph of the Oblique Wing Research Aircraft was taken in front of the NASA Flight Research Center hangar, located at Edwards Air Force Base, California. In the photograph the noseboom, pitot-static probe, and angles-of-attack and sideslip flow vanes(covered-up) are attached to the front of the vehicle. The clear nose dome for the television camera, and the shrouded propellor for the 90 horsepower engine are clearly seen. The Oblique Wing Research Aircraft was a small, remotely piloted, research craft designed and flight tested to look at the aerodynamic characteristics of an oblique wing and the control laws necessary to achieve acceptable handling qualities. NASA Dryden Flight Research Center and the NASA Ames Research Center conducted research with this aircraft in the mid-1970s to investigate the feasibility of flying an oblique wing aircraft.

  1. A decision tree model for predicting mediastinal lymph node metastasis in non-small cell lung cancer with F-18 FDG PET/CT.

    PubMed

    Pak, Kyoungjune; Kim, Keunyoung; Kim, Mi-Hyun; Eom, Jung Seop; Lee, Min Ki; Cho, Jeong Su; Kim, Yun Seong; Kim, Bum Soo; Kim, Seong Jang; Kim, In Joo

    2018-01-01

    We aimed to develop a decision tree model to improve diagnostic performance of positron emission tomography/computed tomography (PET/CT) to detect metastatic lymph nodes (LN) in non-small cell lung cancer (NSCLC). 115 patients with NSCLC were included in this study. The training dataset included 66 patients. A decision tree model was developed with 9 variables, and validated with 49 patients: short and long diameters of LNs, ratio of short and long diameters, maximum standardized uptake value (SUVmax) of LN, mean hounsfield unit, ratio of LN SUVmax and ascending aorta SUVmax (LN/AA), and ratio of LN SUVmax and superior vena cava SUVmax. A total of 301 LNs of 115 patients were evaluated in this study. Nodular calcification was applied as the initial imaging parameter, and LN SUVmax (≥3.95) was assessed as the second. LN/AA (≥2.92) was required to high LN SUVmax. Sensitivity was 50% for training dataset, and 40% for validation dataset. However, specificity was 99.28% for training dataset, and 96.23% for validation dataset. In conclusion, we have developed a new decision tree model for interpreting mediastinal LNs. All LNs with nodular calcification were benign, and LNs with high LN SUVmax and high LN/AA were metastatic Further studies are needed to incorporate subjective parameters and pathologic evaluations into a decision tree model to improve the test performance of PET/CT.

  2. Application of Decision Tree on Collision Avoidance System Design and Verification for Quadcopter

    NASA Astrophysics Data System (ADS)

    Chen, C.-W.; Hsieh, P.-H.; Lai, W.-H.

    2017-08-01

    The purpose of the research is to build a collision avoidance system with decision tree algorithm used for quadcopters. While the ultrasonic range finder judges the distance is in collision avoidance interval, the access will be replaced from operator to the system to control the altitude of the UAV. According to the former experiences on operating quadcopters, we can obtain the appropriate pitch angle. The UAS implement the following three motions to avoid collisions. Case1: initial slow avoidance stage, Case2: slow avoidance stage and Case3: Rapid avoidance stage. Then the training data of collision avoidance test will be transmitted to the ground station via wireless transmission module to further analysis. The entire decision tree algorithm of collision avoidance system, transmission data, and ground station have been verified in some flight tests. In the flight test, the quadcopter can implement avoidance motion in real-time and move away from obstacles steadily. In the avoidance area, the authority of the collision avoidance system is higher than the operator and implements the avoidance process. The quadcopter can successfully fly away from the obstacles in 1.92 meter per second and the minimum distance between the quadcopter and the obstacle is 1.05 meters.

  3. Decision tree analysis of treatment strategies for mild and moderate cases of clinical mastitis occurring in early lactation.

    PubMed

    Pinzón-Sánchez, C; Cabrera, V E; Ruegg, P L

    2011-04-01

    The objective of this study was to develop a decision tree to evaluate the economic impact of different durations of intramammary treatment for the first case of mild or moderate clinical mastitis (CM) occurring in early lactation with various scenarios of pathogen distributions and use of on-farm culture. The tree included 2 decision and 3 probability events. The first decision evaluated use of on-farm culture (OFC; 2 programs using OFC and 1 not using OFC) and the second decision evaluated treatment strategies (no intramammary antimicrobials or antimicrobials administered for 2, 5, or 8 d). The tree included probabilities for the distribution of etiologies (gram-positive, gram-negative, or no growth), bacteriological cure, and recurrence. The economic consequences of mastitis included costs of diagnosis and initial treatment, additional treatments, labor, discarded milk, milk production losses due to clinical and subclinical mastitis, culling, and transmission of infection to other cows (only for CM caused by Staphylococcus aureus). Pathogen-specific estimates for bacteriological cure and milk losses were used. The economically optimal path for several scenarios was determined by comparison of expected monetary values. For most scenarios, the optimal economic strategy was to treat CM caused by gram-positive pathogens for 2 d and to avoid antimicrobials for CM cases caused by gram-negative pathogens or when no pathogen was recovered. Use of extended intramammary antimicrobial therapy (5 or 8 d) resulted in the least expected monetary values. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  4. Career Path Suggestion using String Matching and Decision Trees

    NASA Astrophysics Data System (ADS)

    Nagpal, Akshay; P. Panda, Supriya

    2015-05-01

    High school and college graduates seemingly are often battling for the courses they should major in order to achieve their target career. In this paper, we worked on suggesting a career path to a graduate to reach his/her dream career given the current educational status. Firstly, we collected the career data of professionals and academicians from various career fields and compiled the data set by using the necessary information from the data. Further, this was used as the basis to suggest the most appropriate career path for the person given his/her current educational status. Decision trees and string matching algorithms were employed to suggest the appropriate career path for a person. Finally, an analysis of the result has been done directing to further improvements in the model.

  5. Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images.

    PubMed

    Mane, Vijay Mahadeo; Jadhav, D V

    2017-05-24

    Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.

  6. Prediction of microRNA target genes using an efficient genetic algorithm-based decision tree.

    PubMed

    Rabiee-Ghahfarrokhi, Behzad; Rafiei, Fariba; Niknafs, Ali Akbar; Zamani, Behzad

    2015-01-01

    MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression in almost all plants and animals. They play an important role in key processes, such as proliferation, apoptosis, and pathogen-host interactions. Nevertheless, the mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. This step has shown to be quite challenging in animals primarily because of incomplete complementarities between miRNA and target mRNAs. In recent years, the use of machine-learning techniques has greatly increased the prediction of miRNA targets, avoiding the need for costly and time-consuming experiments to achieve miRNA targets experimentally. Among the most important machine-learning algorithms are decision trees, which classify data based on extracted rules. In the present work, we used a genetic algorithm in combination with C4.5 decision tree for prediction of miRNA targets. We applied our proposed method to a validated human datasets. We nearly achieved 93.9% accuracy of classification, which could be related to the selection of best rules.

  7. Prediction of microRNA target genes using an efficient genetic algorithm-based decision tree

    PubMed Central

    Rabiee-Ghahfarrokhi, Behzad; Rafiei, Fariba; Niknafs, Ali Akbar; Zamani, Behzad

    2015-01-01

    MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression in almost all plants and animals. They play an important role in key processes, such as proliferation, apoptosis, and pathogen–host interactions. Nevertheless, the mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. This step has shown to be quite challenging in animals primarily because of incomplete complementarities between miRNA and target mRNAs. In recent years, the use of machine-learning techniques has greatly increased the prediction of miRNA targets, avoiding the need for costly and time-consuming experiments to achieve miRNA targets experimentally. Among the most important machine-learning algorithms are decision trees, which classify data based on extracted rules. In the present work, we used a genetic algorithm in combination with C4.5 decision tree for prediction of miRNA targets. We applied our proposed method to a validated human datasets. We nearly achieved 93.9% accuracy of classification, which could be related to the selection of best rules. PMID:26649272

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

    PubMed

    Zhong, Taiyang; Chen, Dongmei; Zhang, Xiuying

    2016-11-09

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

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

    PubMed Central

    Zhong, Taiyang; Chen, Dongmei; Zhang, Xiuying

    2016-01-01

    Identification of the sources of soil mercury (Hg) on the provincial scale is helpful for enacting effective policies to prevent further contamination and take reclamation measurements. The natural and anthropogenic sources and their contributions of Hg in Chinese farmland soil were identified based on a decision tree method. The results showed that the concentrations of Hg in parent materials were most strongly associated with the general spatial distribution pattern of Hg concentration on a provincial scale. The decision tree analysis gained an 89.70% total accuracy in simulating the influence of human activities on the additions of Hg in farmland soil. Human activities—for example, the production of coke, application of fertilizers, discharge of wastewater, discharge of solid waste, and the production of non-ferrous metals—were the main external sources of a large amount of Hg in the farmland soil. PMID:27834884

  10. Cycle/Cocycle Oblique Projections on Oriented Graphs

    NASA Astrophysics Data System (ADS)

    Polettini, Matteo

    2015-01-01

    It is well known that the edge vector space of an oriented graph can be decomposed in terms of cycles and cocycles (alias cuts, or bonds), and that a basis for the cycle and the cocycle spaces can be generated by adding and removing edges to an arbitrarily chosen spanning tree. In this paper, we show that the edge vector space can also be decomposed in terms of cycles and the generating edges of cocycles (called cochords), or of cocycles and the generating edges of cycles (called chords). From this observation follows a construction in terms of oblique complementary projection operators. We employ this algebraic construction to prove several properties of unweighted Kirchhoff-Symanzik matrices, encoding the mutual superposition between cycles and cocycles. In particular, we prove that dual matrices of planar graphs have the same spectrum (up to multiplicities). We briefly comment on how this construction provides a refined formalization of Kirchhoff's mesh analysis of electrical circuits, which has lately been applied to generic thermodynamic networks.

  11. Test Reviews: Euler, B. L. (2007). "Emotional Disturbance Decision Tree". Lutz, FL: Psychological Assessment Resources

    ERIC Educational Resources Information Center

    Tansy, Michael

    2009-01-01

    The Emotional Disturbance Decision Tree (EDDT) is a teacher-completed norm-referenced rating scale published by Psychological Assessment Resources, Inc., in Lutz, Florida. The 156-item EDDT was developed for use as part of a broader assessment process to screen and assist in the identification of 5- to 18-year-old children for the special…

  12. Oblique nonlinear whistler wave

    NASA Astrophysics Data System (ADS)

    Yoon, Peter H.; Pandey, Vinay S.; Lee, Dong-Hun

    2014-03-01

    Motivated by satellite observation of large-amplitude whistler waves propagating in oblique directions with respect to the ambient magnetic field, a recent letter discusses the physics of large-amplitude whistler waves and relativistic electron acceleration. One of the conclusions of that letter is that oblique whistler waves will eventually undergo nonlinear steepening regardless of the amplitude. The present paper reexamines this claim and finds that the steepening associated with the density perturbation almost never occurs, unless whistler waves have sufficiently high amplitude and propagate sufficiently close to the resonance cone angle.

  13. Decision tree analysis to evaluate dry cow strategies under UK conditions.

    PubMed

    Berry, Elizabeth A; Hogeveen, Henk; Hillerton, J Eric

    2004-11-01

    Economic decisions on animal health strategies address the cost-benefit aspect along with animal welfare and public health concerns. Decision tree analysis at an individual cow level highlighted that there is little economic difference between the use of either dry cow antibiotic or an internal teat sealant in preventing a new intramammary infection in a cow free of infection in all quarters of the mammary gland at drying off. However, a potential net loss of over ł20 per cow might occur if the uninfected cow was left untreated. The only economically viable option, for a cow with one or more quarters infected at drying off, is antibiotic treatment, although a loss might still be incurred depending on the pathogen concerned and the cure rates achievable. There was a net loss for cows with quarters infected with Corynebacterium spp. at drying off, for both the teat sealant and untreated groups (ł22 and ł48, respectively) with only antibiotic-treated cows showing a gain.

  14. A Novel Treatment Decision Tree and Literature Review of Retrograde Peri-Implantitis.

    PubMed

    Sarmast, Nima D; Wang, Howard H; Soldatos, Nikolaos K; Angelov, Nikola; Dorn, Samuel; Yukna, Raymond; Iacono, Vincent J

    2016-12-01

    Although retrograde peri-implantitis (RPI) is not a common sequela of dental implant surgery, its prevalence has been reported in the literature to be 0.26%. Incidence of RPI is reported to increase to 7.8% when teeth adjacent to the implant site have a previous history of root canal therapy, and it is correlated with distance between implant and adjacent tooth and/or with time from endodontic treatment of adjacent tooth to implant placement. Minimum 2 mm space between implant and adjacent tooth is needed to decrease incidence of apical RPI, with minimum 4 weeks between completion of endodontic treatment and actual implant placement. The purpose of this study is to compile all available treatment modalities and to provide a decision tree as a general guide for clinicians to aid in diagnosis and treatment of RPI. Literature search was performed for articles published in English on the topic of RPI. Articles selected were case reports with study populations ranging from 1 to 32 patients. Any case report or clinical trial that attempted to treat or rescue an implant diagnosed with RPI was included. Predominant diagnostic presentation of a lesion was presence of sinus tract at buccal or facial abscess of apical portion of implant, and subsequent periapical radiographs taken demonstrated a radiolucent lesion. On the basis of case reports analyzed, RPI was diagnosed between 1 week and 4 years after implant placement. Twelve of 20 studies reported that RPI lesions were diagnosed within 6 months after implant placement. A step-by-step decision tree is provided to allow clinicians to triage and properly manage cases of RPI on the basis of recommendations and successful treatments provided in analyzed case reports. It is divided between symptomatic and asymptomatic implants and adjacent teeth with vital and necrotic pulps. Most common etiology of apical RPI is endodontic infection from neighboring teeth, which was diagnosed within 6 months after implant placement. Most

  15. Centrifuge models simulating magma emplacement during oblique rifting

    NASA Astrophysics Data System (ADS)

    Corti, Giacomo; Bonini, Marco; Innocenti, Fabrizio; Manetti, Piero; Mulugeta, Genene

    2001-07-01

    A series of centrifuge analogue experiments have been performed to model the mechanics of continental oblique extension (in the range of 0° to 60°) in the presence of underplated magma at the base of the continental crust. The experiments reproduced the main characteristics of oblique rifting, such as (1) en-echelon arrangement of structures, (2) mean fault trends oblique to the extension vector, (3) strain partitioning between different sets of faults and (4) fault dips higher than in purely normal faults (e.g. Tron, V., Brun, J.-P., 1991. Experiments on oblique rifting in brittle-ductile systems. Tectonophysics 188, 71-84). The model results show that the pattern of deformation is strongly controlled by the angle of obliquity ( α), which determines the ratio between the shearing and stretching components of movement. For α⩽35°, the deformation is partitioned between oblique-slip and normal faults, whereas for α⩾45° a strain partitioning arises between oblique-slip and strike-slip faults. The experimental results show that for α⩽35°, there is a strong coupling between deformation and the underplated magma: the presence of magma determines a strain localisation and a reduced strain partitioning; deformation, in turn, focuses magma emplacement. Magmatic chambers form in the core of lower crust domes with an oblique trend to the initial magma reservoir and, in some cases, an en-echelon arrangement. Typically, intrusions show an elongated shape with a high length/width ratio. In nature, this pattern is expected to result in magmatic and volcanic belts oblique to the rift axis and arranged en-echelon, in agreement with some selected natural examples of continental rifts (i.e. Main Ethiopian Rift) and oceanic ridges (i.e. Mohns and Reykjanes Ridges).

  16. Application of a hybrid association rules/decision tree model for drought monitoring

    NASA Astrophysics Data System (ADS)

    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.

  17. Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

    PubMed Central

    2013-01-01

    Background Complex diseases are often difficult to diagnose, treat and study due to the multi-factorial nature of the underlying etiology. Large data sets are now widely available that can be used to define novel, mechanistically distinct disease subtypes (endotypes) in a completely data-driven manner. However, significant challenges exist with regard to how to segregate individuals into suitable subtypes of the disease and understand the distinct biological mechanisms of each when the goal is to maximize the discovery potential of these data sets. Results A multi-step decision tree-based method is described for defining endotypes based on gene expression, clinical covariates, and disease indicators using childhood asthma as a case study. We attempted to use alternative approaches such as the Student’s t-test, single data domain clustering and the Modk-prototypes algorithm, which incorporates multiple data domains into a single analysis and none performed as well as the novel multi-step decision tree method. This new method gave the best segregation of asthmatics and non-asthmatics, and it provides easy access to all genes and clinical covariates that distinguish the groups. Conclusions The multi-step decision tree method described here will lead to better understanding of complex disease in general by allowing purely data-driven disease endotypes to facilitate the discovery of new mechanisms underlying these diseases. This application should be considered a complement to ongoing efforts to better define and diagnose known endotypes. When coupled with existing methods developed to determine the genetics of gene expression, these methods provide a mechanism for linking genetics and exposomics data and thereby accounting for both major determinants of disease. PMID:24188919

  18. Bow and Oblique Shock Formation in Soap Film

    NASA Astrophysics Data System (ADS)

    Kim, Ildoo; Mandre, Shreyas; Sane, Aakash

    2015-11-01

    In recent years, soap films have been exploited primarily to approximate two-dimensional flows while their three-dimensional character is relatively unattended. An example of the three-dimensional character of the flow in a soap film is the observed Marangoni shock wave when the flow speed exceeds the wave speed. In this study, we investigated the formation of bow and oblique shocks in soap films generated by wedges with different deflection angles. When the wedge deflection angle is small and the film flows fast, oblique shocks are observed. When the oblique shock cannot exists, bow shock is formed upstream the wedge. We characterized the oblique shock angle as a function of the wedge deflection angle and the flow speed, and we also present the criteria for transition between bow and oblique Marangoni shocks in soap films.

  19. CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

    PubMed Central

    Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

    2015-01-01

    Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options

  20. CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

    PubMed

    Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

    2015-01-01

    The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

  1. Analytical and CASE study on Limited Search, ID3, CHAID, C4.5, Improved C4.5 and OVA Decision Tree Algorithms to design Decision Support System

    NASA Astrophysics Data System (ADS)

    Kaur, Parneet; Singh, Sukhwinder; Garg, Sushil; Harmanpreet

    2010-11-01

    In this paper we study about classification algorithms for farm DSS. By applying classification algorithms i.e. Limited search, ID3, CHAID, C4.5, Improved C4.5 and One VS all Decision Tree on common data set of crop with specified class, results are obtained. The tool used to derive results is SPINA. The graphical results obtained from tool are compared to suggest best technique to develop farm Decision Support System. This analysis would help to researchers to design effective and fast DSS for farmer to take decision for enhancing their yield.

  2. Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.

    PubMed

    Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

    2010-08-01

    Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this review was to assess machine learning alternatives to logistic regression, which may accomplish the same goals but with fewer assumptions or greater accuracy. We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (classification and regression trees [CART]), and meta-classifiers (in particular, boosting). Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  3. The scaling of oblique plasma double layers

    NASA Technical Reports Server (NTRS)

    Borovsky, J. E.

    1983-01-01

    Strong oblique plasma double layers are investigated using three methods, i.e., electrostatic particle-in-cell simulations, numerical solutions to the Poisson-Vlasov equations, and analytical approximations to the Poisson-Vlasov equations. The solutions to the Poisson-Vlasov equations and numerical simulations show that strong oblique double layers scale in terms of Debye lengths. For very large potential jumps, theory and numerical solutions indicate that all effects of the magnetic field vanish and the oblique double layers follow the same scaling relation as the field-aligned double layers.

  4. Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory

    EPA Science Inventory

    Efforts are increasingly being made to classify the world’s wetland resources, an important ecosystem and habitat that is diminishing in abundance. There are multiple remote sensing classification methods, including a suite of nonparametric classifiers such as decision-tree...

  5. Long-Term Obliquity Variations of a Moonless Earth

    NASA Astrophysics Data System (ADS)

    Barnes, Jason W.; Lissauer, J. J.; Chambers, J. E.

    2012-05-01

    Earth's present-day obliquity varies by +/-1.2 degrees over 100,000-year timescales. Without the Moon's gravity increasing the rotation axis precession rate, prior theory predicted that a moonless Earth's obliquity would be allowed to vary between 0 and 85 degrees -- moreso even than present-day Mars (0 - 60 degrees). We use a modified version of the symplectic orbital integrator `mercury' to numerically investigate the obliquity evolution of hypothetical moonless Earths. Contrary to the large theoretically allowed range, we find that moonless Earths more typically experience obliquity variations of just +/- 10 degrees over Gyr timescales. Some initial conditions for the moonless Earth's rotation rate and obliquity yield slightly greater variations, but the majority have smaller variations. In particular, retrograde rotators are quite stable and should constitute 50% of the population if initial terrestrial planet rotation is isotropic. Our results have important implications for the prospects of long-term habitability of moonless planets in extrasolar systems.

  6. Decision trees for the analysis of genes involved in Alzheimer's disease pathology.

    PubMed

    Mestizo Gutiérrez, Sonia L; Herrera Rivero, Marisol; Cruz Ramírez, Nicandro; Hernández, Elena; Aranda-Abreu, Gonzalo E

    2014-09-21

    Alzheimer's disease (AD) is characterized by a gradual loss of memory, orientation, judgement and language. There is still no cure for this disorder. AD pathogenesis remains fairly unknown and its underlying molecular mechanisms are not yet fully understood. Several studies have shown that the abnormal accumulation of beta-amyloid and tau proteins occurs 10 to 20 years before the onset of symptoms of the disease, so it is extremely important to identify changes in the brain before the first symptoms. We used decision trees to classify 31 individuals (9 healthy controls and 22 AD patients in three different stages of disease) according to the expression of 69 genes previously reported in a meta-analysis, plus the expression levels of APP, APOE, BACE1, NCSTN, PSEN1, PSEN2 and MAPT. We also included in our analysis the MMSE (Mini-Mental State Examination) scores and number of NFT (neurofibrillary tangles). Results allowed us to generate a model of classification values for different AD stages of severity, according to MMSE scores, and achieve the identification of the expression level of protein tau that may possibly determine the onset (incipient stage) of AD. We used decision trees to model the different stages of AD (severe, moderate, incipient and control) based on the meta-analysis of gene expression levels plus MMSE and NFT scores. Both classifiers reported the variable MMSE as most informative, however it we were found that the protein tau also an important role in the onset of AD. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Identifying controlling factors of ground-level ozone levels over southwestern Taiwan using a decision tree

    NASA Astrophysics Data System (ADS)

    Chu, Hone-Jay; Lin, Chuan-Yao; Liau, Churn-Jung; Kuo, Yi-Ming

    2012-12-01

    Kaohsiung City and the suburban region of southwestern Taiwan have suffered from severe air pollution since becoming the largest center of heavy industry in Taiwan. The complex process of ozone (O3) formation and its precursor compounds (the volatile organic compounds (VOCs) and nitrogen oxide (NOx) emissions), accompanied by meteorological conditions, make controlling ozone difficult. Using a decision tree is especially appropriate for analyzing time series data that contain ozone levels and meteorological and explanatory variables for ozone formation. Results show that dominant variables such as temperature, wind speed, VOCs, and NOx can play vital roles in describing ozone variations among observations. That temperature and wind speed are highly correlated with ozone levels indicates that these meteorological conditions largely affect ozone variability. The results also demonstrate that spatial heterogeneity of ozone patterns are in coastal and inland areas caused by sea-land breeze and pollutant sources during high ozone episodes over southwestern Taiwan. This study used a decision tree to obtain quantitative insight into spatial distributions of precursor compound emissions and effects of meteorological conditions on ozone levels that are useful for refining monitoring plans and developing management strategies.

  8. Evaluation of the oblique detonation wave ramjet

    NASA Technical Reports Server (NTRS)

    Morrison, R. B.

    1978-01-01

    The potential performance of oblique detonation wave ramjets is analyzed in terms of multishock diffusion, oblique detonation waves, and heat release. Results are presented in terms of thrust coefficients and specific impulses for a range of flight Mach numbers of 6 to 16.

  9. Abrupt plate acceleration through oblique rifting: Geodynamic aspects of Gulf of California evolution

    NASA Astrophysics Data System (ADS)

    Brune, S.

    2016-12-01

    The Gulf of California formed by oblique divergence across the Pacific-North America plate boundary. This presentation combines numerical forward modeling and plate tectonic reconstructions in order to address 2 important aspects of rift dynamics: (1) Plate motions during continental rifting are decisively controlled by the non-linear decay of rift strength. This conclusion is based on a recent plate-kinematic analysis of post-Pangea rift systems (Central Atlantic, South Atlantic, Iberia/Newfoundland, Australia/Antarctica, North Atlantic, South China Sea). In all cases, continental rifting starts with a slow phase followed by an abrupt acceleration within a few My introducing a fast rift phase. Numerical forward modeling with force boundary conditions shows that the two-phase velocity behavior and the rapid speed-up during rifting are intrinsic features of continental rupture that can be robustly inferred for different crust and mantle rheologies. (2) Rift strength depends on the obliquity of the rift system: the force required to maintain a given rift velocity can be computed from simple analytical and more realistic numerical models alike, and both modeling approaches demonstrate that less force is required to perpetuate oblique extension. The reason is that plastic yielding requires a smaller plate boundary force when extension is oblique to the rift trend. Comparing strike slip and pure extension end-member scenarios, it can be shown that about 50% less force is required to deform the lithosphere under strike-slip. This result implies that rift systems involving significant obliquity are mechanically preferred. These two aspects shed new light on the underlying geodynamic causes of Gulf of California rift history. Continental extension is thought to have started in Late Eocene/Oligocene times as part of the southern Basin and Range Province and evolved in a protracted history at low extension rate (≤15 mm/yr). However, with a direction change in Baja

  10. A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

    PubMed

    Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

    2014-01-01

    As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

  11. A novel decision tree approach based on transcranial Doppler sonography to screen for blunt cervical vascular injuries.

    PubMed

    Purvis, Dianna; Aldaghlas, Tayseer; Trickey, Amber W; Rizzo, Anne; Sikdar, Siddhartha

    2013-06-01

    Early detection and treatment of blunt cervical vascular injuries prevent adverse neurologic sequelae. Current screening criteria can miss up to 22% of these injuries. The study objective was to investigate bedside transcranial Doppler sonography for detecting blunt cervical vascular injuries in trauma patients using a novel decision tree approach. This prospective pilot study was conducted at a level I trauma center. Patients undergoing computed tomographic angiography for suspected blunt cervical vascular injuries were studied with transcranial Doppler sonography. Extracranial and intracranial vasculatures were examined with a portable power M-mode transcranial Doppler unit. The middle cerebral artery mean flow velocity, pulsatility index, and their asymmetries were used to quantify flow patterns and develop an injury decision tree screening protocol. Student t tests validated associations between injuries and transcranial Doppler predictive measures. We evaluated 27 trauma patients with 13 injuries. Single vertebral artery injuries were most common (38.5%), followed by single internal carotid artery injuries (30%). Compared to patients without injuries, mean flow velocity asymmetry was higher for single internal carotid artery (P = .003) and single vertebral artery (P = .004) injuries. Similarly, pulsatility index asymmetry was higher in single internal carotid artery (P = .015) and single vertebral artery (P = .042) injuries, whereas the lowest pulsatility index was elevated for bilateral vertebral artery injuries (P = .006). The decision tree yielded 92% specificity, 93% sensitivity, and 93% correct classifications. In this pilot feasibility study, transcranial Doppler measures were significantly associated with the blunt cervical vascular injury status, suggesting that transcranial Doppler sonography might be a viable bedside screening tool for trauma. Patient-specific hemodynamic information from transcranial Doppler assessment has the potential to alter

  12. Decision tree for accurate infection timing in individuals newly diagnosed with HIV-1 infection.

    PubMed

    Verhofstede, Chris; Fransen, Katrien; Van Den Heuvel, Annelies; Van Laethem, Kristel; Ruelle, Jean; Vancutsem, Ellen; Stoffels, Karolien; Van den Wijngaert, Sigi; Delforge, Marie-Luce; Vaira, Dolores; Hebberecht, Laura; Schauvliege, Marlies; Mortier, Virginie; Dauwe, Kenny; Callens, Steven

    2017-11-29

    There is today no gold standard method to accurately define the time passed since infection at HIV diagnosis. Infection timing and incidence measurement is however essential to better monitor the dynamics of local epidemics and the effect of prevention initiatives. Three methods for infection timing were evaluated using 237 serial samples from documented seroconversions and 566 cross sectional samples from newly diagnosed patients: identification of antibodies against the HIV p31 protein in INNO-LIA, SediaTM BED CEIA and SediaTM LAg-Avidity EIA. A multi-assay decision tree for infection timing was developed. Clear differences in recency window between BED CEIA, LAg-Avidity EIA and p31 antibody presence were observed with a switch from recent to long term infection a median of 169.5, 108.0 and 64.5 days after collection of the pre-seroconversion sample respectively. BED showed high reliability for identification of long term infections while LAg-Avidity is highly accurate for identification of recent infections. Using BED as initial assay to identify the long term infections and LAg-Avidity as a confirmatory assay for those classified as recent infection by BED, explores the strengths of both while reduces the workload. The short recency window of p31 antibodies allows to discriminate very early from early infections based on this marker. BED recent infection results not confirmed by LAg-Avidity are considered to reflect a period more distant from the infection time. False recency predictions in this group can be minimized by elimination of patients with a CD4 count of less than 100 cells/mm3 or without no p31 antibodies. For 566 cross sectional sample the outcome of the decision tree confirmed the infection timing based on the results of all 3 markers but reduced the overall cost from 13.2 USD to 5.2 USD per sample. A step-wise multi assay decision tree allows accurate timing of the HIV infection at diagnosis at affordable effort and cost and can be an important

  13. Oblique effect in visual area 2 of macaque monkeys

    PubMed Central

    Shen, Guofu; Tao, Xiaofeng; Zhang, Bin; Smith, Earl L.; Chino, Yuzo M.

    2014-01-01

    The neural basis of an oblique effect, a reduced visual sensitivity for obliquely oriented stimuli, has been a matter of considerable debate. We have analyzed the orientation tuning of a relatively large number of neurons in the primary visual cortex (V1) and visual area 2 (V2) of anesthetized and paralyzed macaque monkeys. Neurons in V2 but not V1 of macaque monkeys showed clear oblique effects. This orientation anisotropy in V2 was more robust for those neurons that preferred higher spatial frequencies. We also determined whether V1 and V2 neurons exhibit a similar orientation anisotropy soon after birth. The oblique effect was absent in V1 of 4- and 8-week-old infant monkeys, but their V2 neurons showed a significant oblique effect. This orientation anisotropy in infant V2 was milder than that in adults. The results suggest that the oblique effect emerges in V2 based on the pattern of the connections that are established before birth and enhanced by the prolonged experience-dependent modifications of the neural circuitry in V2. PMID:24511142

  14. The Obliquities of the Giant Planets

    NASA Astrophysics Data System (ADS)

    Hamilton, D. P.; Ward, Wm. R.

    2002-09-01

    Jupiter has by far the smallest obliquity ( ~ 3o) of the planets (not counting tidally de-spun Mercury and Venus) which may be reflective of its formation by hydrodynamic gas flow rather than stochastic impacts. Saturn's obliquity ( ~ 26o), however, seems to belie this simple formation picture. But since the spin angular momentum of any planet is much smaller than its orbital angular momentum, post-formation obliquity can be strongly modified by passing through secular spin-orbit resonances, i.e., when the spin axis precession rate of the planet matches one of the frequencies describing the precession of the orbit plane. Spin axis precession is due to the solar torque on both the oblate figure of the planet and any orbiting satellites. In the case of Jupiter, the torque on the Galilean satellites is the principal cause of its 4.5*105 year precession; Saturn's precession of 1.8*106 years is dominated by Titan. In the past, the planetary spin axis precession rates should have been much faster due to the massive circumplanetary disks from which the current satellites condensed. The regression of the orbital node of a planet is due to the gravitational perturbations of the other planets. Nodal regression is not uniform, but is instead a composite of the planetary system's normal modes. For Jupiter and Saturn, the principal frequency is the nu16, with a period of ~ 49,000 years; the amplitude of this term is I ~ 0o.36 for Jupiter and I ~ 0o.90 for Saturn. In spite of the small amplitudes, slow adiabatic passages through this resonance (due to circumplanetary disk dispersal) could increase planetary obliquities from near zero to ~ [tan1/3 I] ~ 10o. We will discuss scenarios in which giant planet obliquities are affected by this and other resonances, and will use Jupiter's low obliquity to constrain the mass and duration of a satellite precursor disk. DPH acknowledges support from NSF Career Grant AST 9733789 and WRW is grateful to the NASA OSS and PGG programs.

  15. What Satisfies Students? Mining Student-Opinion Data with Regression and Decision-Tree Analysis. AIR 2002 Forum Paper.

    ERIC Educational Resources Information Center

    Thomas, Emily H.; Galambos, Nora

    To investigate how students' characteristics and experiences affect satisfaction, this study used regression and decision-tree analysis with the CHAID algorithm to analyze student opinion data from a sample of 1,783 college students. A data-mining approach identifies the specific aspects of students' university experience that most influence three…

  16. Generation of 2D Land Cover Maps for Urban Areas Using Decision Tree Classification

    NASA Astrophysics Data System (ADS)

    Höhle, J.

    2014-09-01

    A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects like buildings, roads, grassland, trees, hedges, and walls from such an "intelligent" point cloud. The decision tree is derived from training areas which borders are digitized on top of a false-colour orthoimage. The produced 2D land cover map with six classes is then subsequently refined by using image analysis techniques. The proposed methodology is described step by step. The classification, assessment, and refinement is carried out by the open source software "R"; the generation of the dense and accurate digital surface model by the "Match-T DSM" program of the Trimble Company. A practical example of a 2D land cover map generation is carried out. Images of a multispectral medium-format aerial camera covering an urban area in Switzerland are used. The assessment of the produced land cover map is based on class-wise stratified sampling where reference values of samples are determined by means of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes "building" (99 %, 95 % CI: 95 %-100 %) and "road and parking lot" (90 %, 95 % CI: 83 %-95 %). Some other accuracy measures (overall accuracy, kappa value) and their 95 % confidence intervals are derived as well. The proposed methodology has a high potential for automation and fast processing and may be applied to other scenes and sensors.

  17. Lessons learned from Applications of a Decision Tree for Confronting Climate Change Uncertainty - the Short Term and the Long Term

    NASA Astrophysics Data System (ADS)

    Ray, P. A.; Wi, S.; Bonzanigo, L.; Taner, M. U.; Rodriguez, D.; Garcia, L.; Brown, C.

    2016-12-01

    The Decision Tree for Confronting Climate Change Uncertainty is a hierarchical, staged framework for accomplishing climate change risk management in water resources system investments. Since its development for the World Bank Water Group two years ago, the framework has been applied to pilot demonstration projects in Nepal (hydropower generation), Mexico (water supply), Kenya (multipurpose reservoir operation), and Indonesia (flood risks to dam infrastructure). An important finding of the Decision Tree demonstration projects has been the need to present the risks/opportunities of climate change to stakeholders and investors in proportion to risks/opportunities and hazards of other kinds. This presentation will provide an overview of tools and techniques used to quantify risks/opportunities to each of the project types listed above, with special attention to those found most useful for exploration of the risk space. Careful exploration of the risk/opportunity space shows that some interventions would be better taken now, whereas risks/opportunities of other types would be better instituted incrementally in order to maintain reversibility and flexibility. A number of factors contribute to the robustness/flexibility tradeoff: available capital, magnitude and imminence of potential risk/opportunity, modular (or not) character of investment, and risk aversion of the decision maker, among others. Finally, in each case, nuance was required in the translation of Decision Tree findings into actionable policy recommendations. Though the narrative of stakeholder solicitation, engagement, and ultimate partnership is unique to each case, summary lessons are available from the portfolio that can serve as a guideline to the community of climate change risk managers.

  18. Obliquity variation in a Mars climate evolution model

    NASA Technical Reports Server (NTRS)

    Tyler, D.; Haberle, Robert M.

    1993-01-01

    The existence of layered terrain in both polar regions of Mars is strong evidence supporting a cyclic variation in climate. It has been suggested that periods of net deposition have alternated with periods of net erosion in creating the layered structure that is seen today. The cause for this cyclic climatic behavior is variation in the annually averaged latitudinal distribution of solar insolation in response to obliquity cycles. For Mars, obliquity variation leads to major climatological excursion due to the condensation and sublimation of the major atmospheric constituent, CO2. The atmosphere will collapse into the polar caps, or existing caps will rapidly sublimate into the atmosphere, dependent upon the polar surface heat balance and the direction of the change in obliquity. It has been argued that variations in the obliquity of Mars cause substantial departures from the current climatological values of the surface pressure and the amount of CO2 stored in both the planetary regolith and polar caps. In this new work we have modified the Haberle et al. model to incorporate variable obliquity by allowing the polar and equatorial insolation to become functions of obliquity, which we assume to vary sinusoidally in time. As obliquity varies in the model, there can be discontinuities in the time evolution of the model equilibrium values for surface pressure, regolith, and polar cap storage. The time constant, tau r, for the regolith to find equilibrium with the climate is estimated--depending on the depth, thermal conductivity, and porosity of the regolith--between 10(exp 4) and 10(exp 6) yr. Thus, using 2000-yr timesteps to move smoothly through the 0.1250 m.y. obliquity cycles, we have an atmosphere/regolith system that cannot be assumed in equilibrium. We have dealt with this problem by limiting the rate at which CO2, can move between the atmosphere and regolith, mimicking the diffusive nature and effects of the temperature and pressure waves, by setting the time

  19. Motor mechanisms of vertical fusion in individuals with superior oblique paresis.

    PubMed

    Mudgil, Ananth V; Walker, Mark; Steffen, Heimo; Guyton, David L; Zee, David S

    2002-06-01

    We wanted to determine the mechanisms of motor vertical fusion in patients with superior oblique paresis and to correlate these mechanisms with surgical outcomes. Ten patients with superior oblique paresis underwent 3-axis, bilateral, scleral search coil eye movement recordings. Eye movements associated with fusion were analyzed. Six patients had decompensated congenital superior oblique paresis and 4 had acquired superior oblique paresis. All patients with acquired superior oblique paresis relied predominantly on the vertical rectus muscles for motor fusion. Patients with congenital superior oblique paresis were less uniform in their mechanisms for motor fusion: 2 patients used predominantly the oblique muscles, 2 patients used predominantly the vertical recti, and 2 patients used predominantly the superior oblique in the hyperdeviated eye and the superior rectus in the hypodeviated eye. The last 2 patients developed the largest changes in torsional eye alignment relative to changes in vertical eye alignment and were the only patients to develop symptomatic surgical overcorrections. There are 3 different mechanisms for vertical fusion in individuals with superior oblique paresis, with the predominant mechanism being the vertical recti. A subset of patients with superior oblique paresis uses predominantly the superior oblique muscle in the hyperdeviated paretic eye and the superior rectus muscle in the fellow eye for fusion. This results in intorsion of both eyes, causing a large change in torsional alignment. The consequent cyclodisparity, in addition to the existing vertical deviation, may make fusion difficult. The differing patterns of vertical fusional vergence may have implications for surgical treatment.

  20. A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

    PubMed Central

    Goo, Yeong-Jia James; Shen, Zone-De

    2014-01-01

    As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%. PMID:25302338

  1. Strike-Slip Fault Patterns on Europa: Obliquity or Polar Wander?

    NASA Technical Reports Server (NTRS)

    Rhoden, Alyssa Rose; Hurford, Terry A.; Manga, Michael

    2011-01-01

    Variations in diurnal tidal stress due to Europa's eccentric orbit have been considered as the driver of strike-slip motion along pre-existing faults, but obliquity and physical libration have not been taken into account. The first objective of this work is to examine the effects of obliquity on the predicted global pattern of fault slip directions based on a tidal-tectonic formation model. Our second objective is to test the hypothesis that incorporating obliquity can reconcile theory and observations without requiring polar wander, which was previously invoked to explain the mismatch found between the slip directions of 192 faults on Europa and the global pattern predicted using the eccentricity-only model. We compute predictions for individual, observed faults at their current latitude, longitude, and azimuth with four different tidal models: eccentricity only, eccentricity plus obliquity, eccentricity plus physical libration, and a combination of all three effects. We then determine whether longitude migration, presumably due to non-synchronous rotation, is indicated in observed faults by repeating the comparisons with and without obliquity, this time also allowing longitude translation. We find that a tidal model including an obliquity of 1.2?, along with longitude migration, can predict the slip directions of all observed features in the survey. However, all but four faults can be fit with only 1? of obliquity so the value we find may represent the maximum departure from a lower time-averaged obliquity value. Adding physical libration to the obliquity model improves the accuracy of predictions at the current locations of the faults, but fails to predict the slip directions of six faults and requires additional degrees of freedom. The obliquity model with longitude migration is therefore our preferred model. Although the polar wander interpretation cannot be ruled out from these results alone, the obliquity model accounts for all observations with a value

  2. A Decision-Tree-Oriented Guidance Mechanism for Conducting Nature Science Observation Activities in a Context-Aware Ubiquitous Learning

    ERIC Educational Resources Information Center

    Hwang, Gwo-Jen; Chu, Hui-Chun; Shih, Ju-Ling; Huang, Shu-Hsien; Tsai, Chin-Chung

    2010-01-01

    A context-aware ubiquitous learning environment is an authentic learning environment with personalized digital supports. While showing the potential of applying such a learning environment, researchers have also indicated the challenges of providing adaptive and dynamic support to individual students. In this paper, a decision-tree-oriented…

  3. Reaching to virtual targets: The oblique effect reloaded in 3-D.

    PubMed

    Kaspiris-Rousellis, Christos; Siettos, Constantinos I; Evdokimidis, Ioannis; Smyrnis, Nikolaos

    2017-02-20

    Perceiving and reproducing direction of visual stimuli in 2-D space produces the visual oblique effect, which manifests as increased precision in the reproduction of cardinal compared to oblique directions. A second cognitive oblique effect emerges when stimulus information is degraded (such as when reproducing stimuli from memory) and manifests as a systematic distortion where reproduced directions close to the cardinal axes deviate toward the oblique, leading to space expansion at cardinal and contraction at oblique axes. We studied the oblique effect in 3-D using a virtual reality system to present a large number of stimuli, covering the surface of an imaginary half sphere, to which subjects had to reach. We used two conditions, one with no delay (no-memory condition) and one where a three-second delay intervened between stimulus presentation and movement initiation (memory condition). A visual oblique effect was observed for the reproduction of cardinal directions compared to oblique, which did not differ with memory condition. A cognitive oblique effect also emerged, which was significantly larger in the memory compared to the no-memory condition, leading to distortion of directional space with expansion near the cardinal axes and compression near the oblique axes on the hemispherical surface. This effect provides evidence that existing models of 2-D directional space categorization could be extended in the natural 3-D space. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  4. Trees Are Terrific!

    ERIC Educational Resources Information Center

    Braus, Judy, Ed.

    1992-01-01

    Ranger Rick's NatureScope is a creative education series dedicated to inspiring in children an understanding and appreciation of the natural world while developing the skills they will need to make responsible decisions about the environment. Contents are organized into the following sections: (1) "What Makes a Tree a Tree?," including…

  5. Reduced Oblique Effect in Children with Autism Spectrum Disorders (ASD)

    PubMed Central

    Sysoeva, Olga V.; Davletshina, Maria A.; Orekhova, Elena V.; Galuta, Ilia A.; Stroganova, Tatiana A.

    2016-01-01

    People are very precise in the discrimination of a line orientation relative to the cardinal (vertical and horizontal) axes, while their orientation discrimination sensitivity along the oblique axes is less refined. This difference in discrimination sensitivity along cardinal and oblique axes is called the “oblique effect.” Given that the oblique effect is a basic feature of visual processing with an early developmental origin, its investigation in children with Autism Spectrum Disorder (ASD) may shed light on the nature of visual sensory abnormalities frequently reported in this population. We examined line orientation sensitivity along oblique and vertical axes in a sample of 26 boys with ASD (IQ > 68) and 38 typically developing (TD) boys aged 7–15 years, as well as in a subsample of carefully IQ-matched ASD and TD participants. Children were asked to detect the direction of tilt of a high-contrast black-and-white grating relative to vertical (90°) or oblique (45°) templates. The oblique effect was reduced in children with ASD as compared to TD participants, irrespective of their IQ. This reduction was due to poor orientation sensitivity along the vertical axis in ASD children, while their ability to discriminate line orientation along the oblique axis was unaffected. We speculate that this deficit in sensitivity to vertical orientation may reflect disrupted mechanisms of early experience-dependent learning that takes place during the critical period for orientation selectivity. PMID:26834540

  6. Modeling individual tree survial

    Treesearch

    Quang V. Cao

    2016-01-01

    Information provided by growth and yield models is the basis for forest managers to make decisions on how to manage their forests. Among different types of growth models, whole-stand models offer predictions at stand level, whereas individual-tree models give detailed information at tree level. The well-known logistic regression is commonly used to predict tree...

  7. A New Decision Tree to Solve the Puzzle of Alzheimer's Disease Pathogenesis Through Standard Diagnosis Scoring System.

    PubMed

    Kumar, Ashwani; Singh, Tiratha Raj

    2017-03-01

    Alzheimer's disease (AD) is a progressive, incurable and terminal neurodegenerative disorder of the brain and is associated with mutations in amyloid precursor protein, presenilin 1, presenilin 2 or apolipoprotein E, but its underlying mechanisms are still not fully understood. Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis and treatment of disease from the clinical dataset are therefore increasingly becoming necessary. The current study deals with the construction of classifiers that can be human readable as well as robust in performance for gene dataset of AD using a decision tree. Models of classification for different AD genes were generated according to Mini-Mental State Examination scores and all other vital parameters to achieve the identification of the expression level of different proteins of disorder that may possibly determine the involvement of genes in various AD pathogenesis pathways. The effectiveness of decision tree in AD diagnosis is determined by information gain with confidence value (0.96), specificity (92 %), sensitivity (98 %) and accuracy (77 %). Besides this functional gene classification using different parameters and enrichment analysis, our finding indicates that the measures of all the gene assess in single cohorts are sufficient to diagnose AD and will help in the prediction of important parameters for other relevant assessments.

  8. Three-dimensional frictional plastic strain partitioning during oblique rifting

    NASA Astrophysics Data System (ADS)

    Duclaux, Guillaume; Huismans, Ritske S.; May, Dave

    2017-04-01

    Throughout the Wilson cycle the obliquity between lithospheric plate motion direction and nascent or existing plate boundaries prompts the development of intricate three-dimensional tectonic systems. Where oblique divergence dominates, as in the vast majority of continental rift and incipient oceanic domains, deformation is typically transtensional and large stretching in the brittle upper crust is primarily achieved by the accumulation of displacement on fault networks of various complexity. In continental rift depressions such faults are initially distributed over tens to hundreds of kilometer-wide regions, which can ultimately stretch and evolve into passive margins. Here, we use high-resolution 3D thermo-mechanical finite element models to investigate the relative timing and distribution of localised frictional plastic deformation in the upper crust during oblique rift development in a simplified layered lithosphere. We vary the orientation of a wide oblique heterogeneous weak zone (representing a pre-existing geologic feature like a past orogenic domain), and test the sensitivity of the shear zones orientation to a range of noise distribution. These models allow us to assess the importance of material heterogeneities for controlling the spatio-temporal shear zones distribution in the upper crust during oblique rifting, and to discuss the underlying controls governing oblique continental breakup.

  9. Blood oxygen level dependent magnetic resonance imaging for detecting pathological patterns in lupus nephritis patients: a preliminary study using a decision tree model.

    PubMed

    Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng

    2018-02-09

    Precise renal histopathological diagnosis will guide therapy strategy in patients with lupus nephritis. Blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) has been applicable noninvasive technique in renal disease. This current study was performed to explore whether BOLD MRI could contribute to diagnose renal pathological pattern. Adult patients with lupus nephritis renal pathological diagnosis were recruited for this study. Renal biopsy tissues were assessed based on the lupus nephritis ISN/RPS 2003 classification. The Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) was used to obtain functional magnetic resonance parameter, R2* values. Several functions of R2* values were calculated and used to construct algorithmic models for renal pathological patterns. In addition, the algorithmic models were compared as to their diagnostic capability. Both Histopathology and BOLD MRI were used to examine a total of twelve patients. Renal pathological patterns included five classes III (including 3 as class III + V) and seven classes IV (including 4 as class IV + V). Three algorithmic models, including decision tree, line discriminant, and logistic regression, were constructed to distinguish the renal pathological pattern of class III and class IV. The sensitivity of the decision tree model was better than that of the line discriminant model (71.87% vs 59.48%, P < 0.001) and inferior to that of the Logistic regression model (71.87% vs 78.71%, P < 0.001). The specificity of decision tree model was equivalent to that of the line discriminant model (63.87% vs 63.73%, P = 0.939) and higher than that of the logistic regression model (63.87% vs 38.0%, P < 0.001). The Area under the ROC curve (AUROCC) of the decision tree model was greater than that of the line discriminant model (0.765 vs 0.629, P < 0.001) and logistic regression model (0.765 vs 0.662, P < 0.001). BOLD MRI is a useful non-invasive imaging technique

  10. Obliquity evolution of the minor satellites of Pluto and Charon

    NASA Astrophysics Data System (ADS)

    Quillen, Alice C.; Nichols-Fleming, Fiona; Chen, Yuan-Yuan; Noyelles, Benoît

    2017-09-01

    New Horizons mission observations show that the small satellites Styx, Nix, Kerberos and Hydra, of the Pluto-Charon system, have not tidally spun-down to near synchronous spin states and have high obliquities with respect to their orbit about the Pluto-Charon binary (Weaver, 2016). We use a damped mass-spring model within an N-body simulation to study spin and obliquity evolution for single spinning non-round bodies in circumbinary orbit. Simulations with tidal dissipation alone do not show strong obliquity variations from tidally induced spin-orbit resonance crossing and this we attribute to the high satellite spin rates and low orbital eccentricities. However, a tidally evolving Styx exhibits intermittent obliquity variations and episodes of tumbling. During a previous epoch where Charon migrated away from Pluto, the minor satellites could have been trapped in orbital mean motion inclination resonances. An outward migrating Charon induces large variations in Nix and Styx's obliquities. The cause is a commensurability between the mean motion resonance frequency and the spin precession rate of the spinning body. As the minor satellites are near mean motion resonances, this mechanism could have lifted the obliquities of all four minor satellites. The high obliquities need not be primordial if the minor satellites were at one time captured into mean motion resonances.

  11. Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

    NASA Astrophysics Data System (ADS)

    Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

    2017-03-01

    Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

  12. Constraints on the Obliquities of Kepler Planet-hosting Stars

    NASA Astrophysics Data System (ADS)

    Winn, Joshua N.; Petigura, Erik A.; Morton, Timothy D.; Weiss, Lauren M.; Dai, Fei; Schlaufman, Kevin C.; Howard, Andrew W.; Isaacson, Howard; Marcy, Geoffrey W.; Justesen, Anders Bo; Albrecht, Simon

    2017-12-01

    Stars with hot Jupiters have obliquities ranging from 0° to 180°, but relatively little is known about the obliquities of stars with smaller planets. Using data from the California-Kepler Survey, we investigate the obliquities of stars with planets spanning a wide range of sizes, most of which are smaller than Neptune. First, we identify 156 planet hosts for which measurements of the projected rotation velocity (v\\sin i) and rotation period are both available. By combining estimates of v and v\\sin i, we find nearly all the stars to be compatible with high inclination, and hence, low obliquity (≲20°). Second, we focus on a sample of 159 hot stars ({T}{eff}> 6000 K) for which v\\sin i is available but not necessarily the rotation period. We find six stars for which v\\sin i is anomalously low, an indicator of high obliquity. Half of these have hot Jupiters, even though only 3% of the stars that were searched have hot Jupiters. We also compare the v\\sin i distribution of the hot stars with planets to that of 83 control stars selected without prior knowledge of planets. The mean v\\sin i of the control stars is lower than that of the planet hosts by a factor of approximately π /4, as one would expect if the planet hosts have low obliquities. All these findings suggest that the Kepler planet-hosting stars generally have low obliquities, with the exception of hot stars with hot Jupiters.

  13. Inferring planetary obliquity using rotational and orbital photometry

    NASA Astrophysics Data System (ADS)

    Schwartz, J. C.; Sekowski, C.; Haggard, H. M.; Pallé, E.; Cowan, N. B.

    2016-03-01

    The obliquity of a terrestrial planet is an important clue about its formation and critical to its climate. Previous studies using simulated photometry of Earth show that continuous observations over most of a planet's orbit can be inverted to infer obliquity. However, few studies of more general planets with arbitrary albedo markings have been made and, in particular, a simple theoretical understanding of why it is possible to extract obliquity from light curves is missing. Reflected light seen by a distant observer is the product of a planet's albedo map, its host star's illumination, and the visibility of different regions. It is useful to treat the product of illumination and visibility as the kernel of a convolution. Time-resolved photometry constrains both the albedo map and the kernel, the latter of which sweeps over the planet due to rotational and orbital motion. The kernel's movement distinguishes prograde from retrograde rotation for planets with non-zero obliquity on inclined orbits. We demonstrate that the kernel's longitudinal width and mean latitude are distinct functions of obliquity and axial orientation. Notably, we find that a planet's spin axis affects the kernel - and hence time-resolved photometry - even if this planet is east-west uniform or spinning rapidly, or if it is north-south uniform. We find that perfect knowledge of the kernel at 2-4 orbital phases is usually sufficient to uniquely determine a planet's spin axis. Surprisingly, we predict that east-west albedo contrast is more useful for constraining obliquity than north-south contrast.

  14. Rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems in the presence of trees.

    PubMed

    Scholz, Miklas; Uzomah, Vincent C

    2013-08-01

    The retrofitting of sustainable drainage systems (SuDS) such as permeable pavements is currently undertaken ad hoc using expert experience supported by minimal guidance based predominantly on hard engineering variables. There is a lack of practical decision support tools useful for a rapid assessment of the potential of ecosystem services when retrofitting permeable pavements in urban areas that either feature existing trees or should be planted with trees in the near future. Thus the aim of this paper is to develop an innovative rapid decision support tool based on novel ecosystem service variables for retrofitting of permeable pavement systems close to trees. This unique tool proposes the retrofitting of permeable pavements that obtained the highest ecosystem service score for a specific urban site enhanced by the presence of trees. This approach is based on a novel ecosystem service philosophy adapted to permeable pavements rather than on traditional engineering judgement associated with variables based on quick community and environment assessments. For an example case study area such as Greater Manchester, which was dominated by Sycamore and Common Lime, a comparison with the traditional approach of determining community and environment variables indicates that permeable pavements are generally a preferred SuDS option. Permeable pavements combined with urban trees received relatively high scores, because of their great potential impact in terms of water and air quality improvement, and flood control, respectively. The outcomes of this paper are likely to lead to more combined permeable pavement and tree systems in the urban landscape, which are beneficial for humans and the environment. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Effects of Extreme Obliquity Variations on the Habitability of Exoplanets

    NASA Technical Reports Server (NTRS)

    Armstrong, J. C.; Barnes, R.; Domagal-Goldman, S.; Breiner, J.; Quinn, T. R.; Meadows, V. S.

    2014-01-01

    We explore the impact of obliquity variations on planetary habitability in hypothetical systems with high mutual inclination. We show that large-amplitude, high-frequency obliquity oscillations on Earth-like exoplanets can suppress the ice-albedo feedback, increasing the outer edge of the habitable zone. We restricted our exploration to hypothetical systems consisting of a solar-mass star, an Earth-mass planet at 1 AU, and 1 or 2 larger planets. We verified that these systems are stable for 108 years with N-body simulations and calculated the obliquity variations induced by the orbital evolution of the Earth-mass planet and a torque from the host star. We ran a simplified energy balance model on the terrestrial planet to assess surface temperature and ice coverage on the planet's surface, and we calculated differences in the outer edge of the habitable zone for planets with rapid obliquity variations. For each hypothetical system, we calculated the outer edge of habitability for two conditions: (1) the full evolution of the planetary spin and orbit and (2) the eccentricity and obliquity fixed at their average values. We recovered previous results that higher values of fixed obliquity and eccentricity expand the habitable zone, but we also found that obliquity oscillations further expand habitable orbits in all cases. Terrestrial planets near the outer edge of the habitable zone may be more likely to support life in systems that induce rapid obliquity oscillations as opposed to fixed-spin planets. Such planets may be the easiest to directly characterize with space-borne telescopes.

  16. Effects of extreme obliquity variations on the habitability of exoplanets.

    PubMed

    Armstrong, J C; Barnes, R; Domagal-Goldman, S; Breiner, J; Quinn, T R; Meadows, V S

    2014-04-01

    We explore the impact of obliquity variations on planetary habitability in hypothetical systems with high mutual inclination. We show that large-amplitude, high-frequency obliquity oscillations on Earth-like exoplanets can suppress the ice-albedo feedback, increasing the outer edge of the habitable zone. We restricted our exploration to hypothetical systems consisting of a solar-mass star, an Earth-mass planet at 1 AU, and 1 or 2 larger planets. We verified that these systems are stable for 10(8) years with N-body simulations and calculated the obliquity variations induced by the orbital evolution of the Earth-mass planet and a torque from the host star. We ran a simplified energy balance model on the terrestrial planet to assess surface temperature and ice coverage on the planet's surface, and we calculated differences in the outer edge of the habitable zone for planets with rapid obliquity variations. For each hypothetical system, we calculated the outer edge of habitability for two conditions: (1) the full evolution of the planetary spin and orbit and (2) the eccentricity and obliquity fixed at their average values. We recovered previous results that higher values of fixed obliquity and eccentricity expand the habitable zone, but we also found that obliquity oscillations further expand habitable orbits in all cases. Terrestrial planets near the outer edge of the habitable zone may be more likely to support life in systems that induce rapid obliquity oscillations as opposed to fixed-spin planets. Such planets may be the easiest to directly characterize with space-borne telescopes.

  17. Obliquity Modulation of the Incoming Solar Radiation

    NASA Technical Reports Server (NTRS)

    Liu, Han-Shou; Smith, David E. (Technical Monitor)

    2001-01-01

    Based on a basic principle of orbital resonance, we have identified a huge deficit of solar radiation induced by the combined amplitude and frequency modulation of the Earth's obliquity as possibly the causal mechanism for ice age glaciation. Including this modulation effect on solar radiation, we have performed model simulations of climate change for the past 2 million years. Simulation results show that: (1) For the past 1 million years, temperature fluctuation cycles were dominated by a 100-Kyr period due to amplitude-frequency resonance effect of the obliquity; (2) From 2 to 1 million years ago, the amplitude-frequency interactions. of the obliquity were so weak that they were not able to stimulate a resonance effect on solar radiation; (3) Amplitude and frequency modulation analysis on solar radiation provides a series of resonance in the incoming solar radiation which may shift the glaciation cycles from 41-Kyr to 100-Kyr about 0.9 million years ago. These results are in good agreement with the marine and continental paleoclimate records. Thus, the proposed climate response to the combined amplitude and frequency modulation of the Earth's obliquity may be the key to understanding the glaciation puzzles in paleoclimatology.

  18. Exploratory Bi-factor Analysis: The Oblique Case.

    PubMed

    Jennrich, Robert I; Bentler, Peter M

    2012-07-01

    Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.

  19. 33 CFR 118.90 - Bridges crossing channel obliquely.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Bridges crossing channel obliquely. 118.90 Section 118.90 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES BRIDGE LIGHTING AND OTHER SIGNALS § 118.90 Bridges crossing channel obliquely. Bridges...

  20. 33 CFR 118.90 - Bridges crossing channel obliquely.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Bridges crossing channel obliquely. 118.90 Section 118.90 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES BRIDGE LIGHTING AND OTHER SIGNALS § 118.90 Bridges crossing channel obliquely. Bridges...

  1. Compensation of Corneal Oblique Astigmatism by Internal Optics: a Theoretical Analysis

    PubMed Central

    Liu, Tao; Thibos, Larry N.

    2017-01-01

    Purpose Oblique astigmatism is a prominent optical aberration of peripheral vision caused by oblique incidence of rays striking the refracting surfaces of the cornea and crystalline lens. We inquired whether oblique astigmatism from these two sources should be expected, theoretically, to have the same or opposite signs across the visual field at various states of accommodation. Methods Oblique astigmatism was computed across the central visual field for a rotationally-symmetric schematic-eye using optical design software. Accommodative state was varied by altering the apical radius of curvature and separation of the biconvex lens’s two aspheric surfaces in a manner consistent with published biometry. Oblique astigmatism was evaluated separately for the whole eye, the cornea, and the isolated lens over a wide range of surface curvatures and asphericity values associated with the accommodating lens. We also computed internal oblique astigmatism by subtracting corneal oblique astigmatism from whole-eye oblique astigmatism. Results A visual field map of oblique astigmatism for the cornea in the Navarro model follows the classic, textbook description of radially-oriented axes everywhere in the field. Despite large changes in surface properties during accommodation, intrinsic astigmatism of the isolated human lens for collimated light is also radially oriented and nearly independent of accommodation both in theory and in real eyes. However, the magnitude of ocular oblique astigmatism is smaller than that of the cornea alone, indicating partial compensation by the internal optics. This implies internal oblique astigmatism (which includes wavefront propagation from the posterior surface of the cornea to the anterior surface of the lens and intrinsic lens astigmatism) must have tangentially-oriented axes. This non-classical pattern of tangential axes for internal astigmatism was traced to the influence of corneal power on the angles of incidence of rays striking the

  2. Compensation of corneal oblique astigmatism by internal optics: a theoretical analysis.

    PubMed

    Liu, Tao; Thibos, Larry N

    2017-05-01

    Oblique astigmatism is a prominent optical aberration of peripheral vision caused by oblique incidence of rays striking the refracting surfaces of the cornea and crystalline lens. We inquired whether oblique astigmatism from these two sources should be expected, theoretically, to have the same or opposite signs across the visual field at various states of accommodation. Oblique astigmatism was computed across the central visual field for a rotationally-symmetric schematic-eye using optical design software. Accommodative state was varied by altering the apical radius of curvature and separation of the biconvex lens's two aspheric surfaces in a manner consistent with published biometry. Oblique astigmatism was evaluated separately for the whole eye, the cornea, and the isolated lens over a wide range of surface curvatures and asphericity values associated with the accommodating lens. We also computed internal oblique astigmatism by subtracting corneal oblique astigmatism from whole-eye oblique astigmatism. A visual field map of oblique astigmatism for the cornea in the Navarro model follows the classic, textbook description of radially-oriented axes everywhere in the field. Despite large changes in surface properties during accommodation, intrinsic astigmatism of the isolated human lens for collimated light is also radially oriented and nearly independent of accommodation both in theory and in real eyes. However, the magnitude of ocular oblique astigmatism is smaller than that of the cornea alone, indicating partial compensation by the internal optics. This implies internal oblique astigmatism (which includes wavefront propagation from the posterior surface of the cornea to the anterior surface of the lens and intrinsic lens astigmatism) must have tangentially-oriented axes. This non-classical pattern of tangential axes for internal astigmatism was traced to the influence of corneal power on the angles of incidence of rays striking the internal lens. Partial

  3. Oblique Shot of Earth

    NASA Image and Video Library

    2008-09-05

    This highly oblique image shot over northwestern part of the African continent captures the curvature of the Earth and shows its atmosphere as seen by NASA EarthKAM. You can see clouds and even the occasional thunderhead.

  4. Prediction of adverse drug reactions using decision tree modeling.

    PubMed

    Hammann, F; Gutmann, H; Vogt, N; Helma, C; Drewe, J

    2010-07-01

    Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.

  5. Rotation, narrowing and preferential reactivation of brittle structures during oblique rifting

    NASA Astrophysics Data System (ADS)

    Huismans, R. S.; Duclaux, G.; May, D.

    2017-12-01

    Occurrence of multiple faults populations with contrasting orientations in oblique continental rifts and passive margins has long sparked debate about relative timing of deformation events and tectonic interpretations. Here, we use high-resolution three-dimensional thermo-mechanical numerical modeling to characterize the evolution of the structural style associated with moderately oblique rifting in the continental lithosphere. Automatic analysis of the distribution of active extensional shears at the surface of the model demonstrates a characteristic deformation sequence. We show that upon localization, Phase 1 wide oblique en-échelon grabens develop, limited by extensional shears oriented orthogonal to σ3. Subsequent widening of the grabens is accompanied by a progressive rotation of the Phase 1 extensional shears that become sub-orthogonal the plate motion direction. Phase 2 is marked by narrowing of active deformation resulting from thinning of the continental lithosphere and development of a second-generation of extensional shears. During Phase 2 deformation localizes both on plate motion direction-orthogonal structures that reactivate rotated Phase 1 shears, and on new oblique structures orthogonal to σ3. Finally, Phase 3 consists in the oblique rupture of the continental lithosphere and produces an oceanic domain where oblique ridge segments are linked with highly oblique accommodation zones. We conclude that while new structures form normal to σ3 in an oblique rift, progressive rotation and long-term reactivation of Phase 1 structures promotes orthorhombic fault systems, critical to accommodate upper crustal extension and control oblique passive margin architecture. The distribution, orientation, and evolution of frictional-plastic structures observed in our models is remarkably similar to documented fault populations in the Gulf of Aden conjugate passive margins, which developed in moderately oblique extensional settings.

  6. Application of Decision Tree in the Prediction of Periventricular Leukomalacia (PVL) Occurrence in Neonates After Neonatal Heart Surgery

    PubMed Central

    Jalali, Ali; Licht, Daniel J.; Nataraj, C.

    2013-01-01

    This paper is concerned with the prediction of the occurrence of Periventricular Leukomalacia (PVL) that occurs in neonates after heart surgery. The data which is collected over a period of 12 hours after the cardiac surgery contains vital measurements as well as blood gas measurements with different resolutions. The decision tree classification technique has been selected as a tool for prediction of the PVL because of its capacity for discovering rules and novel associations in the data. Vital data measured using near-inferred spectroscopy (NIRS) at the sampling rate of 0.25 Hz and blood gas measurement up to 12 times with irregular time intervals for 35 patients collected from Children's Hospital of Philadelphia (CHOP) are used for this study. Vital data contain heart rate (HR), mean arterial pressure (MAP), right atrium pressure (RAP), blood hemoglobin (Hb), hemoglobin oxygen content (HbO2), oxygen saturation (SpO2) and relative cerebral blood flow (rCBF). Features derived from the data include statistical moments (mean, variance, skewness and kurtosis), trend and min and max of the vital data and rate of change, time weighted mean and a custom defined out of range index (ORI) for the blood gas data. A decision tree is developed for the vital data in order to identify the most important vital measurements. In addition, a decision tree is developed for blood gas data to find important factors for the prediction of PVL occurrence. Results show that in blood gas data, maximum rate of change in the concentration of bicarbonate ions in blood (HCO3) and minimum rate of change in the partial pressure of dissolved CO2 in the blood (PaCO2) are the most important factors for prediction of the PVL. Among vital features the kurtosis of HR and Hb are the most important parameters. PMID:23367279

  7. Climate Dynamics and Hysteresis at Low and High Obliquity

    NASA Astrophysics Data System (ADS)

    Colose, C.; Del Genio, A. D.; Way, M.

    2017-12-01

    We explore the large-scale climate dynamics at low and high obliquity for an Earth-like planet using the ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics) 3-D General Circulation model being developed at NASA GISS as part of the Nexus for Exoplanet System Science (NExSS) initiative. We highlight the role of ocean heat storage and transport in determining the seasonal cycle at high obliquity, and describe the large-scale circulation and resulting regional climate patterns using both aquaplanet and Earth topographical boundary conditions. Finally, we contrast the hysteresis structure to varying CO2 concentration for a low and high obliquity planet near the outer edge of the habitable zone. We discuss the prospects for habitability for a high obliquity planet susceptible to global glaciation.

  8. Effects of Extreme Obliquity Variations on the Habitability of Exoplanets

    PubMed Central

    Barnes, R.; Domagal-Goldman, S.; Breiner, J.; Quinn, T.R.; Meadows, V.S.

    2014-01-01

    Abstract We explore the impact of obliquity variations on planetary habitability in hypothetical systems with high mutual inclination. We show that large-amplitude, high-frequency obliquity oscillations on Earth-like exoplanets can suppress the ice-albedo feedback, increasing the outer edge of the habitable zone. We restricted our exploration to hypothetical systems consisting of a solar-mass star, an Earth-mass planet at 1 AU, and 1 or 2 larger planets. We verified that these systems are stable for 108 years with N-body simulations and calculated the obliquity variations induced by the orbital evolution of the Earth-mass planet and a torque from the host star. We ran a simplified energy balance model on the terrestrial planet to assess surface temperature and ice coverage on the planet's surface, and we calculated differences in the outer edge of the habitable zone for planets with rapid obliquity variations. For each hypothetical system, we calculated the outer edge of habitability for two conditions: (1) the full evolution of the planetary spin and orbit and (2) the eccentricity and obliquity fixed at their average values. We recovered previous results that higher values of fixed obliquity and eccentricity expand the habitable zone, but we also found that obliquity oscillations further expand habitable orbits in all cases. Terrestrial planets near the outer edge of the habitable zone may be more likely to support life in systems that induce rapid obliquity oscillations as opposed to fixed-spin planets. Such planets may be the easiest to directly characterize with space-borne telescopes. Key Words: Exoplanets—Habitable zone—Energy balance models. Astrobiology 14, 277–291. PMID:24611714

  9. Behaviour change in overweight and obese pregnancy: a decision tree to support the development of antenatal lifestyle interventions.

    PubMed

    Ainscough, Kate M; Lindsay, Karen L; O'Sullivan, Elizabeth J; Gibney, Eileen R; McAuliffe, Fionnuala M

    2017-10-01

    Antenatal healthy lifestyle interventions are frequently implemented in overweight and obese pregnancy, yet there is inconsistent reporting of the behaviour-change methods and behavioural outcomes. This limits our understanding of how and why such interventions were successful or not. The current paper discusses the application of behaviour-change theories and techniques within complex lifestyle interventions in overweight and obese pregnancy. The authors propose a decision tree to help guide researchers through intervention design, implementation and evaluation. The implications for adopting behaviour-change theories and techniques, and using appropriate guidance when constructing and evaluating interventions in research and clinical practice are also discussed. To enhance the evidence base for successful behaviour-change interventions during pregnancy, adoption of behaviour-change theories and techniques, and use of published guidelines when designing lifestyle interventions are necessary. The proposed decision tree may be a useful guide for researchers working to develop effective behaviour-change interventions in clinical settings. This guide directs researchers towards key literature sources that will be important in each stage of study development.

  10. Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption.

    PubMed

    Newby, Danielle; Freitas, Alex A; Ghafourian, Taravat

    2015-01-27

    Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqueous solubility, melting point, and maximum dose for the same compounds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a solubility-related parameter such as experimental or predicted solubility, or the melting point based absorption potential (MPbAP), along with structural molecular descriptors were developed and validated to predict oral absorption class. The decision trees were able to determine the individual roles of permeability and solubility in oral absorption process. Poorly permeable compounds with high solubility show low intestinal absorption, whereas poorly water soluble compounds with high or low permeability may have high intestinal absorption provided that they have certain molecular characteristics such as a small polar surface or specific topology. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  11. The Oblique Orbit of WASP-107b from K2 Photometry

    NASA Astrophysics Data System (ADS)

    Dai, Fei; Winn, Joshua N.

    2017-05-01

    Observations of nine transits of WASP-107 during the K2 mission reveal three separate occasions when the planet crossed in front of a starspot. The data confirm the stellar rotation period to be 17 days—approximately three times the planet’s orbital period—and suggest that large spots persist for at least one full rotation. If the star had a low obliquity, at least two additional spot crossings should have been observed. They were not observed, giving evidence for a high obliquity. We use a simple geometric model to show that the obliquity is likely in the range 40°-140°, I.e., both spin-orbit alignment and anti-alignment can be ruled out. WASP-107 thereby joins the small collection of relatively low-mass stars with a high obliquity. Most such stars have been observed to have low obliquities; all of the exceptions, including WASP-107, involve planets with relatively wide orbits (“warm Jupiters,” with {a}{{\\min }}/{R}\\star ≳ 8). This demonstrates a connection between stellar obliquity and planet properties, in contradiction to some theories for obliquity excitation.

  12. Inferences from growing trees backwards

    Treesearch

    David W. Green; Kent A. McDonald

    1997-01-01

    The objective of this paper is to illustrate how longitudinal stress wave techniques can be useful in tracking the future quality of a growing tree. Monitoring the quality of selected trees in a plantation forest could provide early input to decisions on the effectiveness of management practices, or future utilization options, for trees in a plantation. There will...

  13. Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree.

    PubMed

    Erdoğan, Onur; Aydin Son, Yeşim

    2014-01-01

    Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations where only a single nucleotide differs between individuals. Individual SNPs and SNP profiles associated with diseases can be utilized as biological markers. But there is a need to determine the SNP subsets and patients' clinical data which is informative for the diagnosis. Data mining approaches have the highest potential for extracting the knowledge from genomic datasets and selecting the representative SNPs as well as most effective and informative clinical features for the clinical diagnosis of the diseases. In this study, we have applied one of the widely used data mining classification methodology: "decision tree" for associating the SNP biomarkers and significant clinical data with the Alzheimer's disease (AD), which is the most common form of "dementia". Different tree construction parameters have been compared for the optimization, and the most accurate tree for predicting the AD is presented.

  14. An analysis of penetration and ricochet phenomena in oblique hypervelocity impact

    NASA Technical Reports Server (NTRS)

    Schonberg, William P.; Taylor, Roy A.; Horn, Jennifer R.

    1988-01-01

    An experimental investigation of phenomena associated with the oblique hypervelocity impact of spherical projectiles on multisheet aluminum structures is described. A model that can be employed in the design of meteoroid and space debris protection systems for space structures is developed. The model consists of equations that relate crater and perforation damage of a multisheet structure to parameters such as projectile size, impact velocity, and trajectory obliquity. The equations are obtained through a regression analysis of oblique hypervelocity impact test data. This data shows that the response of a multisheet structure to oblique impact is significantly different from its response to normal hypervelocity impact. It was found that obliquely incident projectiles produce ricochet debris that can severely damage panels or instrumentation located on the exterior of a space structure. Obliquity effects of high-speed impact must, therefore, be considered in the design of any structure exposed to the meteoroid and space debris environment.

  15. Automatic interpretation of oblique ionograms

    NASA Astrophysics Data System (ADS)

    Ippolito, Alessandro; Scotto, Carlo; Francis, Matthew; Settimi, Alessandro; Cesaroni, Claudio

    2015-03-01

    We present an algorithm for the identification of trace characteristics of oblique ionograms allowing determination of the Maximum Usable Frequency (MUF) for communication between the transmitter and receiver. The algorithm automatically detects and rejects poor quality ionograms. We performed an exploratory test of the algorithm using data from a campaign of oblique soundings between Rome, Italy (41.90 N, 12.48 E) and Chania, Greece (35.51 N, 24.01 E) and also between Kalkarindji, Australia (17.43 S, 130.81 E) and Culgoora, Australia (30.30 S, 149.55 E). The success of these tests demonstrates the applicability of the method to ionograms recorded by different ionosondes in various helio and geophysical conditions.

  16. Multi-output decision trees for lesion segmentation in multiple sclerosis

    NASA Astrophysics Data System (ADS)

    Jog, Amod; Carass, Aaron; Pham, Dzung L.; Prince, Jerry L.

    2015-03-01

    Multiple Sclerosis (MS) is a disease of the central nervous system in which the protective myelin sheath of the neurons is damaged. MS leads to the formation of lesions, predominantly in the white matter of the brain and the spinal cord. The number and volume of lesions visible in magnetic resonance (MR) imaging (MRI) are important criteria for diagnosing and tracking the progression of MS. Locating and delineating lesions manually requires the tedious and expensive efforts of highly trained raters. In this paper, we propose an automated algorithm to segment lesions in MR images using multi-output decision trees. We evaluated our algorithm on the publicly available MICCAI 2008 MS Lesion Segmentation Challenge training dataset of 20 subjects, and showed improved results in comparison to state-of-the-art methods. We also evaluated our algorithm on an in-house dataset of 49 subjects with a true positive rate of 0.41 and a positive predictive value 0.36.

  17. Injury risk functions for frontal oblique collisions.

    PubMed

    Andricevic, Nino; Junge, Mirko; Krampe, Jonas

    2018-03-09

    The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set. Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes-a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured). IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18-64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes. The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.

  18. Inferior Oblique Overaction: Anterior Transposition Versus Myectomy.

    PubMed

    Rajavi, Zhale; Feizi, Mohadeseh; Behradfar, Narges; Yaseri, Mehdi; Sayanjali, Shima; Motevaseli, Tahmine; Sabbaghi, Hamideh; Faghihi, Mohammad

    2017-07-01

    To compare the efficacy of inferior oblique myectomy and anterior transposition for correcting inferior oblique overaction (IOOA). This retrospective study was conducted on 56 patients with IOOA who had either myectomy or anterior transposition of the inferior oblique muscle from 2010 to 2015. The authors compared preoperative and postoperative inferior oblique muscle function grading (-4 to +4) as the main outcome measure and vertical and horizontal deviation, dissociated vertical deviation (DVD), and A- and V-pattern between the two surgical groups as secondary outcomes. A total of 99 eyes of 56 patients with a mean age of 5.9 ± 6.5 years were included (47 eyes in the myectomy group and 52 eyes in the anterior transposition group). There were no differences in preoperative best corrected visual acuity, amblyopia, spherical equivalent, and primary versus secondary IOOA between the two groups. Both surgical procedures were effective in reducing IOOA and satisfactory results were similar between the two groups: 61.7% and 67.3% in the myectomy and anterior transposition groups, respectively (P = .56). After adjustment for the preoperative DVD, there was no statistically significant difference between the two groups postoperatively. The preoperative hypertropia was 6 to 14 and 6 to 18 prism diopters (PD) in the myectomy and anterior transposition groups, respectively. After surgery, no patient had a vertical deviation greater than 5 PD. Both the inferior oblique myectomy and anterior transposition procedures are effective in reducing IOOA with similar satisfactory results. DVD and hypertropia were also corrected similarly by these two surgical procedures. [J Pediatr Ophthalmol Strabismus. 2017;54(4):232-237.]. Copyright 2017, SLACK Incorporated.

  19. [Study on extraction method of Panax notoginseng plots in Wenshan of Yunnan province based on decision tree model].

    PubMed

    Shi, Ting-Ting; Zhang, Xiao-Bo; Guo, Lan-Ping; Huang, Lu-Qi

    2017-11-01

    The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level. Copyright© by the Chinese Pharmaceutical Association.

  20. Surface dose measurements for highly oblique electron beams.

    PubMed

    Ostwald, P M; Kron, T

    1996-08-01

    Clinical applications of electrons may involve oblique incidence of beams, and although dose variations for angles up to 60 degrees from normal incidence are well documented, no results are available for highly oblique beams. Surface dose measurements in highly oblique beams were made using parallel-plate ion chambers and both standard LiF:Mg, Ti and carbon-loaded LiF Thermoluminescent Dosimeters (TLD). Obliquity factors (OBF) or surface dose at an oblique angle divided by the surface dose at perpendicular incidence, were obtained for electron energies between 4 and 20 MeV. Measurements were performed on a flat solid water phantom without a collimator at 100 cm SSD. Comparisons were also made to collimated beams. The OBFs of surface doses plotted against the angle of incidence increased to a maximum dose followed by a rapid dropoff in dose. The increase in OBF was more rapid for higher energies. The maximum OBF occurred at larger angles for higher-energy beams and ranged from 73 degrees for 4 MeV to 84 degrees for 20 MeV. At the dose maximum, OBFs were between 130% and 160% of direct beam doses, yielding surface doses of up to 150% of Dmax for the 20 MeV beam. At 2 mm depth the dose ratio was found to increase initially with angle and then decrease as Dmax moved closer to the surface. A higher maximum dose was measured at 2 mm depth than at the surface. A comparison of ion chamber types showed that a chamber with a small electrode spacing and large guard ring is required for oblique dose measurement. A semiempirical equation was used to model the dose increase at the surface with different energy electron beams.

  1. Comparison of two data mining techniques in labeling diagnosis to Iranian pharmacy claim dataset: artificial neural network (ANN) versus decision tree model.

    PubMed

    Rezaei-Darzi, Ehsan; Farzadfar, Farshad; Hashemi-Meshkini, Amir; Navidi, Iman; Mahmoudi, Mahmoud; Varmaghani, Mehdi; Mehdipour, Parinaz; Soudi Alamdari, Mahsa; Tayefi, Batool; Naderimagham, Shohreh; Soleymani, Fatemeh; Mesdaghinia, Alireza; Delavari, Alireza; Mohammad, Kazem

    2014-12-01

    This study aimed to evaluate and compare the prediction accuracy of two data mining techniques, including decision tree and neural network models in labeling diagnosis to gastrointestinal prescriptions in Iran. This study was conducted in three phases: data preparation, training phase, and testing phase. A sample from a database consisting of 23 million pharmacy insurance claim records, from 2004 to 2011 was used, in which a total of 330 prescriptions were assessed and used to train and test the models simultaneously. In the training phase, the selected prescriptions were assessed by both a physician and a pharmacist separately and assigned a diagnosis. To test the performance of each model, a k-fold stratified cross validation was conducted in addition to measuring their sensitivity and specificity. Generally, two methods had very similar accuracies. Considering the weighted average of true positive rate (sensitivity) and true negative rate (specificity), the decision tree had slightly higher accuracy in its ability for correct classification (83.3% and 96% versus 80.3% and 95.1%, respectively). However, when the weighted average of ROC area (AUC between each class and all other classes) was measured, the ANN displayed higher accuracies in predicting the diagnosis (93.8% compared with 90.6%). According to the result of this study, artificial neural network and decision tree model represent similar accuracy in labeling diagnosis to GI prescription.

  2. Comparison of Chevron and Distal Oblique Osteotomy for Bunion Correction.

    PubMed

    Scharer, Brandon M; DeVries, J George

    2016-01-01

    The chevron osteotomy is a standard procedure by which bunions are corrected. One of us routinely performs a distal oblique osteotomy, which, to the best of our knowledge, has not been described for the correction of bunion deformities. The purpose of the present study was to compare the short- and medium-term results of the distal oblique and chevron osteotomies for bunion correction. We performed a retrospective clinical and radiographic comparison of patients who had undergone a distal oblique or chevron osteotomy for the correction of bunion deformity. In addition, a prospective patient satisfaction survey was undertaken. A total of 55 patients were included in the present study and were treated from January 2012 to November 2014. Of the 55 patients, 27 (49.2%) were in the chevron group and 28 (50.8%) in the distal oblique group. Radiographically, no statistically significant difference was found between the 2 groups with respect to postoperative first intermetatarsal angle (p < .0001) and hallux valgus angle (p < .0001), but a greater change was found in the intermetatarsal angle in the distal oblique group (p = .467). Prospective patient satisfaction scores were available for 33 patients (60%), 16 (29%) in the chevron group and 17 (31%) in the distal oblique group. When converting the satisfaction score to a numerical score, the chevron group scored 3.3 ± 1.1 and the distal oblique group scored 3.2 ± 0.8 (p = .812). We found that the distal oblique osteotomy used in the present study is simple and reliable and showed radiographic correction and patient satisfaction equivalent to those in the chevron osteotomy. Copyright © 2016 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

  3. Diagnostic assessment of intraoperative cytology for papillary thyroid carcinoma: using a decision tree analysis.

    PubMed

    Pyo, J-S; Sohn, J H; Kang, G

    2017-03-01

    The aim of this study was to elucidate the cytological characteristics and the diagnostic usefulness of intraoperative cytology (IOC) for papillary thyroid carcinoma (PTC). In addition, using decision tree analysis, effective features for accurate cytological diagnosis were sought. We investigated cellularity, cytological features and diagnosis based on the Bethesda System for Reporting Thyroid Cytopathology in IOC of 240 conventional PTCs. The cytological features were evaluated in terms of nuclear score with nuclear features, and additional figures such as presence of swirling sheets, psammoma bodies, and multinucleated giant cells. The nuclear score (range 0-7) was made via seven nuclear features, including (1) enlarged, (2) oval or irregularly shaped nuclei, (3) longitudinal nuclear grooves, (4) intranuclear cytoplasmic pseudoinclusion, (5) pale nuclei with powdery chromatin, (6) nuclear membrane thickening, and (7) marginally placed micronucleoli. Nuclear scores in PTC, suspicious for malignancy, and atypia of undetermined significance cases were 6.18 ± 0.80, 4.48 ± 0.82, and 3.15 ± 0.67, respectively. Additional figures more frequent in PTC than in other diagnostic categories were identified. Cellularity of IOC significantly correlated with tumor size, nuclear score, and presence of additional figures. Also, IOCs with higher nuclear scores (4-7) significantly correlated with larger tumor size and presence of additional figures. In decision tree analysis, IOCs with nuclear score >5 and swirling sheets could be considered diagnostic for PTCs. Our study suggests that IOCs using nuclear features and additional figures could be useful with decreasing the likelihood of inconclusive results.

  4. A Decision-Tree Approach to Cost Comparison of Newborn Screening Strategies for Cystic Fibrosis

    PubMed Central

    Wells, Janelle; Rosenberg, Marjorie; Hoffman, Gary; Anstead, Michael

    2012-01-01

    OBJECTIVE: Because cystic fibrosis can be difficult to diagnose and treat early, newborn screening programs have rapidly developed nationwide but methods vary widely. We therefore investigated the costs and consequences or specific outcomes of the 2 most commonly used methods. METHODS: With available data on screening and follow-up, we used a simulation approach with decision trees to compare immunoreactive trypsinogen (IRT) screening followed by a second IRT test against an IRT/DNA analysis. By using a Monte Carlo simulation program, variation in the model parameters for counts at various nodes of the decision trees, as well as for costs, are included and applied to fictional cohorts of 100 000 newborns. The outcome measures included the numbers of newborns given a diagnosis of cystic fibrosis and costs of screening strategy at each branch and cost per newborn. RESULTS: Simulations revealed a substantial number of potential missed diagnoses for the IRT/IRT system versus IRT/DNA. Although the IRT/IRT strategy with commonly used cutoff values offers an average overall cost savings of $2.30 per newborn, a breakdown of costs by societal segments demonstrated higher out-of-pocket costs for families. Two potential system failures causing delayed diagnoses were identified relating to the screening protocols and the follow-up system. CONCLUSIONS: The IRT/IRT screening algorithm reduces the costs to laboratories and insurance companies but has more system failures. IRT/DNA offers other advantages, including fewer delayed diagnoses and lower out-of-pocket costs to families. PMID:22291119

  5. Obliquity Variations of Habitable Zone Planets Kepler-62f and Kepler-186f

    NASA Astrophysics Data System (ADS)

    Shan, Yutong; Li, Gongjie

    2018-06-01

    Obliquity variability could play an important role in the climate and habitability of a planet. Orbital modulations caused by planetary companions and the planet’s spin axis precession due to the torque from the host star may lead to resonant interactions and cause large-amplitude obliquity variability. Here we consider the spin axis dynamics of Kepler-62f and Kepler-186f, both of which reside in the habitable zone around their host stars. Using N-body simulations and secular numerical integrations, we describe their obliquity evolution for particular realizations of the planetary systems. We then use a generalized analytic framework to characterize regions in parameter space where the obliquity is variable with large amplitude. We find that the locations of variability are fine-tuned over the planetary properties and system architecture in the lower-obliquity regimes (≲40°). As an example, assuming a rotation period of 24 hr, the obliquities of both Kepler-62f and Kepler-186f are stable below ∼40°, whereas the high-obliquity regions (60°–90°) allow moderate variabilities. However, for some other rotation periods of Kepler-62f or Kepler-186f, the lower-obliquity regions could become more variable owing to resonant interactions. Even small deviations from coplanarity (e.g., mutual inclinations ∼3°) could stir peak-to-peak obliquity variations up to ∼20°. Undetected planetary companions and/or the existence of a satellite could also destabilize the low-obliquity regions. In all cases, the high-obliquity region allows for moderate variations, and all obliquities corresponding to retrograde motion (i.e., >90°) are stable.

  6. Application of Decision Tree to Obtain Optimal Operation Rules for Reservoir Flood Control Considering Sediment Desilting-Case Study of Tseng Wen Reservoir

    NASA Astrophysics Data System (ADS)

    ShiouWei, L.

    2014-12-01

    Reservoirs are the most important water resources facilities in Taiwan.However,due to the steep slope and fragile geological conditions in the mountain area,storm events usually cause serious debris flow and flood,and the flood then will flush large amount of sediment into reservoirs.The sedimentation caused by flood has great impact on the reservoirs life.Hence,how to operate a reservoir during flood events to increase the efficiency of sediment desilting without risk the reservoir safety and impact the water supply afterward is a crucial issue in Taiwan.  Therefore,this study developed a novel optimization planning model for reservoir flood operation considering flood control and sediment desilting,and proposed easy to use operating rules represented by decision trees.The decision trees rules have considered flood mitigation,water supply and sediment desilting.The optimal planning model computes the optimal reservoir release for each flood event that minimum water supply impact and maximum sediment desilting without risk the reservoir safety.Beside the optimal flood operation planning model,this study also proposed decision tree based flood operating rules that were trained by the multiple optimal reservoir releases to synthesis flood scenarios.The synthesis flood scenarios consists of various synthesis storm events,reservoir's initial storage and target storages at the end of flood operating.  Comparing the results operated by the decision tree operation rules(DTOR) with that by historical operation for Krosa Typhoon in 2007,the DTOR removed sediment 15.4% more than that of historical operation with reservoir storage only8.38×106m3 less than that of historical operation.For Jangmi Typhoon in 2008,the DTOR removed sediment 24.4% more than that of historical operation with reservoir storage only 7.58×106m3 less than that of historical operation.The results show that the proposed DTOR model can increase the sediment desilting efficiency and extend the

  7. A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kupriyanov, M. S., E-mail: mikhail.kupriyanov@gmail.com; Shukeilo, E. Y., E-mail: eyshukeylo@gmail.com; Shichkina, J. A., E-mail: strange.y@mail.ru

    2015-11-17

    Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

  8. A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

    NASA Astrophysics Data System (ADS)

    Kupriyanov, M. S.; Shukeilo, E. Y.; Shichkina, J. A.

    2015-11-01

    Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient's health condition using data from a wearable device considers in this article.

  9. Structural Equation Model Trees

    ERIC Educational Resources Information Center

    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…

  10. Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

    PubMed

    Jin, Mingwu; Deng, Weishu

    2018-05-15

    There is a spectrum of the progression from healthy control (HC) to mild cognitive impairment (MCI) without conversion to Alzheimer's disease (AD), to MCI with conversion to AD (cMCI), and to AD. This study aims to predict the different disease stages using brain structural information provided by magnetic resonance imaging (MRI) data. The neighborhood component analysis (NCA) is applied to select most powerful features for prediction. The ensemble decision tree classifier is built to predict which group the subject belongs to. The best features and model parameters are determined by cross validation of the training data. Our results show that 16 out of a total of 429 features were selected by NCA using 240 training subjects, including MMSE score and structural measures in memory-related regions. The boosting tree model with NCA features can achieve prediction accuracy of 56.25% on 160 test subjects. Principal component analysis (PCA) and sequential feature selection (SFS) are used for feature selection, while support vector machine (SVM) is used for classification. The boosting tree model with NCA features outperforms all other combinations of feature selection and classification methods. The results suggest that NCA be a better feature selection strategy than PCA and SFS for the data used in this study. Ensemble tree classifier with boosting is more powerful than SVM to predict the subject group. However, more advanced feature selection and classification methods or additional measures besides structural MRI may be needed to improve the prediction performance. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Classification of Different Degrees of Disability Following Intracerebral Hemorrhage: A Decision Tree Analysis from VISTA-ICH Collaboration.

    PubMed

    Phan, Thanh G; Chen, Jian; Beare, Richard; Ma, Henry; Clissold, Benjamin; Van Ly, John; Srikanth, Velandai

    2017-01-01

    Prognostication following intracerebral hemorrhage (ICH) has focused on poor outcome at the expense of lumping together mild and moderate disability. We aimed to develop a novel approach at classifying a range of disability following ICH. The Virtual International Stroke Trial Archive collaboration database was searched for patients with ICH and known volume of ICH on baseline CT scans. Disability was partitioned into mild [modified Rankin Scale (mRS) at 90 days of 0-2], moderate (mRS = 3-4), and severe disabilities (mRS = 5-6). We used binary and trichotomy decision tree methodology. The data were randomly divided into training (2/3 of data) and validation (1/3 data) datasets. The area under the receiver operating characteristic curve (AUC) was used to calculate the accuracy of the decision tree model. We identified 957 patients, age 65.9 ± 12.3 years, 63.7% males, and ICH volume 22.6 ± 22.1 ml. The binary tree showed that lower ICH volume (<13.7 ml), age (<66.5 years), serum glucose (<8.95 mmol/l), and systolic blood pressure (<170 mm Hg) discriminate between mild versus moderate-to-severe disabilities with AUC of 0.79 (95% CI 0.73-0.85). Large ICH volume (>27.9 ml), older age (>69.5 years), and low Glasgow Coma Scale (<15) classify severe disability with AUC of 0.80 (95% CI 0.75-0.86). The trichotomy tree showed that ICH volume, age, and serum glucose can separate mild, moderate, and severe disability groups with AUC 0.79 (95% CI 0.71-0.87). Both the binary and trichotomy methods provide equivalent discrimination of disability outcome after ICH. The trichotomy method can classify three categories at once, whereas this action was not possible with the binary method. The trichotomy method may be of use to clinicians and trialists for classifying a range of disability in ICH.

  12. Repeatability and oblique flow response characteristics of current meters

    USGS Publications Warehouse

    Fulford, Janice M.; Thibodeaux, Kirk G.; Kaehrle, William R.; ,

    1993-01-01

    Laboratory investigation into the precision and accuracy of various mechanical-current meters are presented. Horizontal-axis and vertical-axis meters that are used for the measurement of point velocities in streams and rivers were tested. Meters were tested for repeatability and response to oblique flows. Both horizontal- and vertical-axis meters were found to under- and over-register oblique flows with errors generally increasing as the velocity and angle of flow increased. For the oblique flow tests, magnitude of errors were smallest for horizontal-axis meters. Repeatability of all meters tested was good, with the horizontal- and vertical-axis meters performing similarly.

  13. Modal control of an oblique wing aircraft

    NASA Technical Reports Server (NTRS)

    Phillips, James D.

    1989-01-01

    A linear modal control algorithm is applied to the NASA Oblique Wing Research Aircraft (OWRA). The control law is evaluated using a detailed nonlinear flight simulation. It is shown that the modal control law attenuates the coupling and nonlinear aerodynamics of the oblique wing and remains stable during control saturation caused by large command inputs or large external disturbances. The technique controls each natural mode independently allowing single-input/single-output techniques to be applied to multiple-input/multiple-output systems.

  14. Traditional Chinese medicine pharmacovigilance in signal detection: decision tree-based data classification.

    PubMed

    Wei, Jian-Xiang; Wang, Jing; Zhu, Yun-Xia; Sun, Jun; Xu, Hou-Ming; Li, Ming

    2018-03-09

    Traditional Chinese Medicine (TCM) is a style of traditional medicine informed by modern medicine but built on a foundation of more than 2500 years of Chinese medical practice. According to statistics, TCM accounts for approximately 14% of total adverse drug reaction (ADR) spontaneous reporting data in China. Because of the complexity of the components in TCM formula, which makes it essentially different from Western medicine, it is critical to determine whether ADR reports of TCM should be analyzed independently. Reports in the Chinese spontaneous reporting database between 2010 and 2011 were selected. The dataset was processed and divided into the total sample (all data) and the subsample (including TCM data only). Four different ADR signal detection methods-PRR, ROR, MHRA and IC- currently widely used in China, were applied for signal detection on the two samples. By comparison of experimental results, three of them-PRR, MHRA and IC-were chosen to do the experiment. We designed several indicators for performance evaluation such as R (recall ratio), P (precision ratio), and D (discrepancy ratio) based on the reference database and then constructed a decision tree for data classification based on such indicators. For PRR: R 1 -R 2  = 0.72%, P 1 -P 2  = 0.16% and D = 0.92%; For MHRA: R 1 -R 2  = 0.97%, P 1 -P 2  = 0.20% and D = 1.18%; For IC: R 1 -R 2  = 1.44%, P 2 -P 1  = 4.06% and D = 4.72%. The threshold of R,Pand Dis set as 2%, 2% and 3% respectively. Based on the decision tree, the results are "separation" for PRR, MHRA and IC. In order to improve the efficiency and accuracy of signal detection, we suggest that TCM data should be separated from the total sample when conducting analyses.

  15. The oblique effect is both allocentric and egocentric

    PubMed Central

    Mikellidou, Kyriaki; Cicchini, Guido Marco; Thompson, Peter G.; Burr, David C.

    2016-01-01

    Despite continuous movements of the head, humans maintain a stable representation of the visual world, which seems to remain always upright. The mechanisms behind this stability are largely unknown. To gain some insight on how head tilt affects visual perception, we investigate whether a well-known orientation-dependent visual phenomenon, the oblique effect—superior performance for stimuli at cardinal orientations (0° and 90°) compared with oblique orientations (45°)—is anchored in egocentric or allocentric coordinates. To this aim, we measured orientation discrimination thresholds at various orientations for different head positions both in body upright and in supine positions. We report that, in the body upright position, the oblique effect remains anchored in allocentric coordinates irrespective of head position. When lying supine, gravitational effects in the plane orthogonal to gravity are discounted. Under these conditions, the oblique effect was less marked than when upright, and anchored in egocentric coordinates. The results are well explained by a simple “compulsory fusion” model in which the head-based and the gravity-based signals are combined with different weightings (30% and 70%, respectively), even when this leads to reduced sensitivity in orientation discrimination. PMID:26129862

  16. Analyzing RCD30 Oblique Performance in a Production Environment

    NASA Astrophysics Data System (ADS)

    Soler, M. E.; Kornus, W.; Magariños, A.; Pla, M.

    2016-06-01

    In 2014 the Institut Cartogràfic i Geològic de Catalunya (ICGC) decided to incorporate digital oblique imagery in its portfolio in response to the growing demand for this product. The reason can be attributed to its useful applications in a wide variety of fields and, most recently, to an increasing interest in 3d modeling. The selection phase for a digital oblique camera led to the purchase of the Leica RCD30 Oblique system, an 80MPixel multispectral medium-format camera which consists of one Nadir camera and four oblique viewing cameras acquiring images at an off-Nadir angle of 35º. The system also has a multi-directional motion compensation on-board system to deliver the highest image quality. The emergence of airborne oblique cameras has run in parallel to the inclusion of computer vision algorithms into the traditional photogrammetric workflows. Such algorithms rely on having multiple views of the same area of interest and take advantage of the image redundancy for automatic feature extraction. The multiview capability is highly fostered by the use of oblique systems which capture simultaneously different points of view for each camera shot. Different companies and NMAs have started pilot projects to assess the capabilities of the 3D mesh that can be obtained using correlation techniques. Beyond a software prototyping phase, and taking into account the currently immature state of several components of the oblique imagery workflow, the ICGC has focused on deploying a real production environment with special interest on matching the performance and quality of the existing production lines based on classical Nadir images. This paper introduces different test scenarios and layouts to analyze the impact of different variables on the geometric and radiometric performance. Different variables such as flight altitude, side and forward overlap and ground control point measurements and location have been considered for the evaluation of aerial triangulation and

  17. Lessons Learned from Applications of a Climate Change Decision Tree toWater System Projects in Kenya and Nepal

    NASA Astrophysics Data System (ADS)

    Ray, P. A.; Bonzanigo, L.; Taner, M. U.; Wi, S.; Yang, Y. C. E.; Brown, C.

    2015-12-01

    The Decision Tree Framework developed for the World Bank's Water Partnership Program provides resource-limited project planners and program managers with a cost-effective and effort-efficient, scientifically defensible, repeatable, and clear method for demonstrating the robustness of a project to climate change. At the conclusion of this process, the project planner is empowered to confidently communicate the method by which the vulnerabilities of the project have been assessed, and how the adjustments that were made (if any were necessary) improved the project's feasibility and profitability. The framework adopts a "bottom-up" approach to risk assessment that aims at a thorough understanding of a project's vulnerabilities to climate change in the context of other nonclimate uncertainties (e.g., economic, environmental, demographic, political). It helps identify projects that perform well across a wide range of potential future climate conditions, as opposed to seeking solutions that are optimal in expected conditions but fragile to conditions deviating from the expected. Lessons learned through application of the Decision Tree to case studies in Kenya and Nepal will be presented, and aspects of the framework requiring further refinement will be described.

  18. Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

    PubMed

    Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

    2015-08-01

    In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

  19. Mapping potential carbon and timber losses from hurricanes using a decision tree and ecosystem services driver model.

    PubMed

    Delphin, S; Escobedo, F J; Abd-Elrahman, A; Cropper, W

    2013-11-15

    Information on the effect of direct drivers such as hurricanes on ecosystem services is relevant to landowners and policy makers due to predicted effects from climate change. We identified forest damage risk zones due to hurricanes and estimated the potential loss of 2 key ecosystem services: aboveground carbon storage and timber volume. Using land cover, plot-level forest inventory data, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and a decision tree-based framework; we determined potential damage to subtropical forests from hurricanes in the Lower Suwannee River (LS) and Pensacola Bay (PB) watersheds in Florida, US. We used biophysical factors identified in previous studies as being influential in forest damage in our decision tree and hurricane wind risk maps. Results show that 31% and 0.5% of the total aboveground carbon storage in the LS and PB, respectively was located in high forest damage risk (HR) zones. Overall 15% and 0.7% of the total timber net volume in the LS and PB, respectively, was in HR zones. This model can also be used for identifying timber salvage areas, developing ecosystem service provision and management scenarios, and assessing the effect of other drivers on ecosystem services and goods. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Learning classification trees

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1991-01-01

    Algorithms for learning classification trees have had successes in artificial intelligence and statistics over many years. How a tree learning algorithm can be derived from Bayesian decision theory is outlined. This introduces Bayesian techniques for splitting, smoothing, and tree averaging. The splitting rule turns out to be similar to Quinlan's information gain splitting rule, while smoothing and averaging replace pruning. Comparative experiments with reimplementations of a minimum encoding approach, Quinlan's C4 and Breiman et al. Cart show the full Bayesian algorithm is consistently as good, or more accurate than these other approaches though at a computational price.

  1. Implications of Anomalous Pectoralis Muscle in Reconstructive Breast Surgery: The Oblique Pectoralis Anterior

    PubMed Central

    Huber, Katherine Marie; Boyd, Travis Guthrie; Quillo, Amy R; Wilhelmi, Bradon J

    2012-01-01

    Introduction: Many case reports have described anatomical variants of the pectoralis muscles. However, there is a paucity of published literature on the consequence of such presentations in reconstructive breast surgery. Methods: A 45-year-old female patient with breast cancer presented for left mastectomy and immediate reconstruction with tissue expander. During mastectomy, she was noted to have an extra muscle anterior to her pectoralis major muscle. This variant had not previously been described in the literature and was therefore named the oblique pectoralis anterior. After inspection of the aberrant musculature, the decision was made to release the inferolateral insertion of the accessory muscle with the inferior edge of pectoralis major. An adequate pocket for the expander was created. Results: After routine expansion and implant exchange, muscular coverage of the implant from pectoralis major and the oblique pectoralis anterior muscle approximated 70%. The patient was left with good symmetry and a cosmetic result, despite the challenges presented by her anomalous chest wall musculature. Discussion: Prior knowledge of the various anatomic aberrations described in the literature can prepare a surgeon to properly incorporate and utilize the variant anatomy, should it be encountered, to benefit the outcome of the operation. PMID:22977679

  2. Use of Vertical Aerial Images for Semi-Oblique Mapping

    NASA Astrophysics Data System (ADS)

    Poli, D.; Moe, K.; Legat, K.; Toschi, I.; Lago, F.; Remondino, F.

    2017-05-01

    The paper proposes a methodology for the use of the oblique sections of images from large-format photogrammetric cameras, by exploiting the effect of the central perspective geometry in the lateral parts of the nadir images ("semi-oblique" images). The point of origin of the investigation was the execution of a photogrammetric flight over Norcia (Italy), which was seriously damaged after the earthquake of 30/10/2016. Contrary to the original plan of oblique acquisitions, the flight was executed on 15/11/2017 using an UltraCam Eagle camera with focal length 80 mm, and combining two flight plans, rotated by 90º ("crisscross" flight). The images (GSD 5 cm) were used to extract a 2.5D DSM cloud, sampled to a XY-grid size of 2 GSD, a 3D point clouds with a mean spatial resolution of 1 GSD and a 3D mesh model at a resolution of 10 cm of the historic centre of Norcia for a quantitative assessment of the damages. From the acquired nadir images the "semi-oblique" images (forward, backward, left and right views) could be extracted and processed in a modified version of GEOBLY software for measurements and restitution purposes. The potential of such semi-oblique image acquisitions from nadir-view cameras is hereafter shown and commented.

  3. Ureter Injury as a Complication of Oblique Lumbar Interbody Fusion.

    PubMed

    Lee, Hyeong-Jin; Kim, Jin-Sung; Ryu, Kyeong-Sik; Park, Choon Keun

    2017-06-01

    Oblique lumbar interbody fusion is a commonly used surgical method of achieving lumbar interbody fusion. There have been some reports about complications of oblique lumbar interbody fusion at the L2-L3 level. However, to our knowledge, there have been no reports about ureter injury during oblique lumbar interbody fusion. We report a case of ureter injury during oblique lumbar interbody fusion to share our experience. A 78-year-old male patient presented with a history of lower back pain and neurogenic intermittent claudication. He was diagnosed with spinal stenosis at L2-L3, L4-L5 level and spondylolisthesis at L4-L5 level. Symptoms were not improved after several months of medical treatments. Then, oblique lumbar interbody fusion was performed at L2-L3, L4-L5 level. During the surgery, anesthesiologist noticed hematuria. A retrourethrogram was performed immediately by urologist, and ureter injury was found. Ureteroureterostomy and double-J catheter insertion were performed. The patient was discharged 2 weeks after surgery without urologic or neurologic complications. At 2 months after surgery, an intravenous pyelogram was performed, which showed an intact ureter. Our study shows that a low threshold of suspicion of ureter injury and careful manipulation of retroperitoneal fat can be helpful to prevent ureter injury during oblique lumbar interbody fusion at the upper level. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. F-8 oblique wing structural feasibility study

    NASA Technical Reports Server (NTRS)

    Koltko, E.; Katz, A.; Bell, M. A.; Smith, W. D.; Lauridia, R.; Overstreet, C. T.; Klapprott, C.; Orr, T. F.; Jobe, C. L.; Wyatt, F. G.

    1975-01-01

    The feasibility of fitting a rotating oblique wing on an F-8 aircraft to produce a full scale manned prototype capable of operating in the transonic and supersonic speed range was investigated. The strength, aeroelasticity, and fatigue life of such a prototype are analyzed. Concepts are developed for a new wing, a pivot, a skewing mechanism, control systems that operate through the pivot, and a wing support assembly that attaches in the F-8 wing cavity. The modification of the two-place NTF-8A aircraft to the oblique wing configuration is discussed.

  5. Origins of oblique-slip faulting during caldera subsidence

    NASA Astrophysics Data System (ADS)

    Holohan, Eoghan P.; Walter, Thomas R.; Schöpfer, Martin P. J.; Walsh, John J.; van Wyk de Vries, Benjamin; Troll, Valentin R.

    2013-04-01

    Although conventionally described as purely dip-slip, faults at caldera volcanoes may have a strike-slip displacement component. Examples occur in the calderas of Olympus Mons (Mars), Miyakejima (Japan), and Dolomieu (La Reunion). To investigate this phenomenon, we use numerical and analog simulations of caldera subsidence caused by magma reservoir deflation. The numerical models constrain mechanical causes of oblique-slip faulting from the three-dimensional stress field in the initial elastic phase of subsidence. The analog experiments directly characterize the development of oblique-slip faulting, especially in the later, non-elastic phases of subsidence. The combined results of both approaches can account for the orientation, mode, and location of oblique-slip faulting at natural calderas. Kinematically, oblique-slip faulting originates to resolve the following: (1) horizontal components of displacement that are directed radially toward the caldera center and (2) horizontal translation arising from off-centered or "asymmetric" subsidence. We informally call these two origins the "camera iris" and "sliding trapdoor" effects, respectively. Our findings emphasize the fundamentally three-dimensional nature of deformation during caldera subsidence. They hence provide an improved basis for analyzing structural, geodetic, and geophysical data from calderas, as well as analogous systems, such as mines and producing hydrocarbon reservoirs.

  6. Uninjured trees - a meaningful guide to white-pine weevil control decisions

    Treesearch

    William E. Waters

    1962-01-01

    The white-pine weevil, Pissodes strobi, is a particularly insidious forest pest that can render a stand of host trees virtually worthless. It rarely, if ever, kills a tree; but the crooks, forks, and internal defects that develop in attacked trees over a period of years may reduce the merchantable volume and value of the tree at harvest age to zero. Dollar losses are...

  7. Vectorial point spread function and optical transfer function in oblique plane imaging.

    PubMed

    Kim, Jeongmin; Li, Tongcang; Wang, Yuan; Zhang, Xiang

    2014-05-05

    Oblique plane imaging, using remote focusing with a tilted mirror, enables direct two-dimensional (2D) imaging of any inclined plane of interest in three-dimensional (3D) specimens. It can image real-time dynamics of a living sample that changes rapidly or evolves its structure along arbitrary orientations. It also allows direct observations of any tilted target plane in an object of which orientational information is inaccessible during sample preparation. In this work, we study the optical resolution of this innovative wide-field imaging method. Using the vectorial diffraction theory, we formulate the vectorial point spread function (PSF) of direct oblique plane imaging. The anisotropic lateral resolving power caused by light clipping from the tilted mirror is theoretically analyzed for all oblique angles. We show that the 2D PSF in oblique plane imaging is conceptually different from the inclined 2D slice of the 3D PSF in conventional lateral imaging. Vectorial optical transfer function (OTF) of oblique plane imaging is also calculated by the fast Fourier transform (FFT) method to study effects of oblique angles on frequency responses.

  8. On the time-variable nature of Titan's obliquity

    NASA Astrophysics Data System (ADS)

    Noyelles, Benoit; Nimmo, Francis

    2014-05-01

    Titan presents an unexpectedly high obliquity (Stiles et al. 2008, Meriggiola & Iess 2012) while its topography and gravity suggest a non-hydrostatic ice shell (Hemingway et al. 2013). We here present a 6-dof model of the rotation of Titan simultaneously simulating the full orientation of the shell and the inner core, and considering a global subsurface ocean with a partially-compensated shell of spatially-variable thickness. Between 10 and 13% of our realistic interior models induce a resonance with the annual forcing, that dramatically raises the obliquity. The relevant model Titans are composed of a 130-140 km thick shell floating on a ~250 km thick ocean. The observed obliquity should not be considered as a mean one but as an instantaneous one, that should vary by ~7 arcmin over the duration of the Cassini mission.

  9. Evaluating the Effectiveness of Science for Decision-Making: Water Managers and Tree- Ring Data in the Western United States

    NASA Astrophysics Data System (ADS)

    Rice, J. L.; Woodhouse, C.; Lukas, J.

    2008-12-01

    Current climate variability, potential impacts of climate change, and limited resources in the face of growing demand are increasingly prompting water managers in the western United States to consider and use data from climate-related research in water resource planning. Much of these data are produced by stakeholder- driven science programs, such as NOAA's Regional Integrated Science Assessments (RISAs), but there have been few efforts to evaluate the effectiveness of these science-to-application efforts. Over the past several years, researchers with the Western Water Assessment (WWA) RISA have been providing tree-ring reconstructions of streamflow to water managers in Colorado and other western states, and presenting technical workshops explaining the applications of these tree-ring data for water management and planning. Using in-depth interviews and a survey questionnaire, we have assessed the effectiveness and outcomes of these engagements, addressing (1) the factors that have prompted water managers to seek out tree-ring data, (2) how paleoclimate data has been made relevant and accessible for water resource planning, and (3) how tree-ring data and information have been utilized by water managers and other workshop participants. We also provide an assessment of challenges and opportunities that exist in the translation of climate science for decision-making, including how tree-ring data are interpreted in the context of water planning paradigms, issues of credibility and acceptance of tree ring data, and what data needs exist in different planning environments. These findings have broader application in improving and evaluating science-policy interactions related to climate and climate change.

  10. Tree value system: users guide.

    Treesearch

    J.K. Ayer Sachet; D.G. Briggs; R.D. Fight

    1989-01-01

    This paper instructs resource analysts on use of the Tree Value System (TREEVAL). TREEVAL is a microcomputer system of programs for calculating tree or stand values and volumes based on predicted product recovery. Designed for analyzing silvicultural decisions, the system can also be used for appraisals and for evaluating log bucking. The system calculates results...

  11. The Evolution of Oblique Impact Flow Fields Using Maxwell's Z Model

    NASA Technical Reports Server (NTRS)

    Anderson, J. L. B.; Schultz, P. H.; Heineck, J. T.

    2003-01-01

    Oblique impacts are the norm rather than the exception for impact craters on planetary surfaces. This work focuses on the excavation of experimental oblique impact craters using the NASA Ames Vertical Gun Range (AVGR). Three-dimensional particle image velocimetry (3D PIV) is used to obtain quantitative data on ejection positions, three dimensional velocities and angles. These data are then used to constrain Maxwell's Z Model and follow the subsurface evolution of the excavation-stage flow-field center during oblique impacts.

  12. The use of decision trees and naïve Bayes algorithms and trace element patterns for controlling the authenticity of free-range-pastured hens' eggs.

    PubMed

    Barbosa, Rommel Melgaço; Nacano, Letícia Ramos; Freitas, Rodolfo; Batista, Bruno Lemos; Barbosa, Fernando

    2014-09-01

    This article aims to evaluate 2 machine learning algorithms, decision trees and naïve Bayes (NB), for egg classification (free-range eggs compared with battery eggs). The database used for the study consisted of 15 chemical elements (As, Ba, Cd, Co, Cs, Cu, Fe, Mg, Mn, Mo, Pb, Se, Sr, V, and Zn) determined in 52 eggs samples (20 free-range and 32 battery eggs) by inductively coupled plasma mass spectrometry. Our results demonstrated that decision trees and NB associated with the mineral contents of eggs provide a high level of accuracy (above 80% and 90%, respectively) for classification between free-range and battery eggs and can be used as an alternative method for adulteration evaluation. © 2014 Institute of Food Technologists®

  13. Acoustic plane waves incident on an oblique clamped panel in a rectangular duct

    NASA Technical Reports Server (NTRS)

    Unz, H.; Roskam, J.

    1980-01-01

    The theory of acoustic plane waves incident on an oblique clamped panel in a rectangular duct was developed from basic theoretical concepts. The coupling theory between the elastic vibrations of the panel (plate) and the oblique incident acoustic plane wave in infinite space was considered in detail, and was used for the oblique clamped panel in the rectangular duct. The partial differential equation which governs the vibrations of the clamped panel (plate) was modified by adding to it stiffness (spring) forces and damping forces. The Transmission Loss coefficient and the Noise Reduction coefficient for oblique incidence were defined and derived in detail. The resonance frequencies excited by the free vibrations of the oblique finite clamped panel (plate) were derived and calculated in detail for the present case.

  14. Oblique wing transonic transport configuration development

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Studies of transport aircraft designed for boom-free supersonic flight show the variable sweep oblique wing to be the most efficient configuration for flight at low supersonic speeds. Use of this concept leads to a configuration that is lighter, quieter, and more fuel efficient than symmetric aircraft designed for the same mission. Aerodynamic structural, weight, aeroelastic and flight control studies show the oblique wing concept to be technically feasible. Investigations are reported for wing planform and thickness, pivot design and weight estimation, engine cycle (bypass ratio), and climb, descent and reserve fuel. Results are incorporated into a final configuration. Performance, weight, and balance characteristics are evaluated. Flight control requirements are reviewed, and areas in which further research is needed are identified.

  15. Predictors of suicidal ideation in older people: a decision tree analysis.

    PubMed

    Handley, Tonelle E; Hiles, Sarah A; Inder, Kerry J; Kay-Lambkin, Frances J; Kelly, Brian J; Lewin, Terry J; McEvoy, Mark; Peel, Roseanne; Attia, John R

    2014-11-01

    Suicide among older adults is a major public health issue worldwide. Although studies have identified psychological, physical, and social contributors to suicidal thoughts in older adults, few have explored the specific interactions between these factors. This article used a novel statistical approach to explore predictors of suicidal ideation in a community-based sample of older adults. Prospective cohort study. Participants aged 55-85 years were randomly selected from the Hunter Region, a large regional center in New South Wales, Australia. Baseline psychological, physical, and social factors, including psychological distress, physical functioning, and social support, were used to predict suicidal ideation at the 5-year follow-up. Classification and regression tree modeling was used to determine specific risk profiles for participants depending on their individual well-being in each of these key areas. Psychological distress was the strongest predictor, with 25% of people with high distress reporting suicidal ideation. Within high psychological distress, lower physical functioning significantly increased the likelihood of suicidal ideation, with high distress and low functioning being associated with ideation in 50% of cases. A substantial subgroup reported suicidal ideation in the absence of psychological distress; dissatisfaction with social support was the most important predictor among this group. The performance of the model was high (area under the curve: 0.81). Decision tree modeling enabled individualized "risk" profiles for suicidal ideation to be determined. Although psychological factors are important for predicting suicidal ideation, both physical and social factors significantly improved the predictive ability of the model. Assessing these factors may enhance identification of older people at risk of suicidal ideation. Copyright © 2014. Published by Elsevier Inc.

  16. Planning effectiveness may grow on fault trees.

    PubMed

    Chow, C W; Haddad, K; Mannino, B

    1991-10-01

    The first step of a strategic planning process--identifying and analyzing threats and opportunities--requires subjective judgments. By using an analytical tool known as a fault tree, healthcare administrators can reduce the unreliability of subjective decision making by creating a logical structure for problem solving and decision making. A case study of 11 healthcare administrators showed that an analysis technique called prospective hindsight can add to a fault tree's ability to improve a strategic planning process.

  17. Cosmic-ray shock acceleration in oblique MHD shocks

    NASA Technical Reports Server (NTRS)

    Webb, G. M.; Drury, L. OC.; Volk, H. J.

    1986-01-01

    A one-dimensional, steady-state hydrodynamical model of cosmic-ray acceleration at oblique MHD shocks is presented. Upstream of the shock the incoming thermal plasma is subject to the adverse pressure gradient of the accelerated particles, the J x B force, as well as the thermal gas pressure gradient. The efficiency of the acceleration of cosmic-rays at the shock as a function of the upstream magnetic field obliquity and upstream plasma beta is investigated. Astrophysical applications of the results are briefly discussed.

  18. A numerical study on the oblique focus in MR-guided transcranial focused ultrasound

    NASA Astrophysics Data System (ADS)

    Hughes, Alec; Huang, Yuexi; Pulkkinen, Aki; Schwartz, Michael L.; Lozano, Andres M.; Hynynen, Kullervo

    2016-11-01

    Recent clinical data showing thermal lesions from treatments of essential tremor using MR-guided transcranial focused ultrasound shows that in many cases the focus is oblique to the main axis of the phased array. The potential for this obliquity to extend the focus into lateral regions of the brain has led to speculation as to the cause of the oblique focus, and whether it is possible to realign the focus. Numerical simulations were performed on clinical export data to analyze the causes of the oblique focus and determine methods for its correction. It was found that the focal obliquity could be replicated with the numerical simulations to within 23.2+/- {{13.6}\\circ} of the clinical cases. It was then found that a major cause of the focal obliquity was the presence of sidelobes, caused by an unequal deposition of power from the different transducer elements in the array at the focus. In addition, it was found that a 65% reduction in focal obliquity was possible using phase and amplitude corrections. Potential drawbacks include the higher levels of skull heating required when modifying the distribution of power among the transducer elements, and the difficulty at present in obtaining ideal phase corrections from CT information alone. These techniques for the reduction of focal obliquity can be applied to other applications of transcranial focused ultrasound involving lower total energy deposition, such as blood-brain barrier opening, where the issue of skull heating is minimal.

  19. Comparison of rule induction, decision trees and formal concept analysis approaches for classification

    NASA Astrophysics Data System (ADS)

    Kotelnikov, E. V.; Milov, V. R.

    2018-05-01

    Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.

  20. Constraints on the near-Earth asteroid obliquity distribution from the Yarkovsky effect

    NASA Astrophysics Data System (ADS)

    Tardioli, C.; Farnocchia, D.; Rozitis, B.; Cotto-Figueroa, D.; Chesley, S. R.; Statler, T. S.; Vasile, M.

    2017-12-01

    Aims: From light curve and radar data we know the spin axis of only 43 near-Earth asteroids. In this paper we attempt to constrain the spin axis obliquity distribution of near-Earth asteroids by leveraging the Yarkovsky effect and its dependence on an asteroid's obliquity. Methods: By modeling the physical parameters driving the Yarkovsky effect, we solve an inverse problem where we test different simple parametric obliquity distributions. Each distribution results in a predicted Yarkovsky effect distribution that we compare with a χ2 test to a dataset of 125 Yarkovsky estimates. Results: We find different obliquity distributions that are statistically satisfactory. In particular, among the considered models, the best-fit solution is a quadratic function, which only depends on two parameters, favors extreme obliquities consistent with the expected outcomes from the YORP effect, has a 2:1 ratio between retrograde and direct rotators, which is in agreement with theoretical predictions, and is statistically consistent with the distribution of known spin axes of near-Earth asteroids.

  1. Pre-late heavy bombardment evolution of the Earth's obliquity

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Li, Gongjie; Batygin, Konstantin, E-mail: gli@cfa.harvard.edu

    2014-11-01

    The Earth's obliquity is stabilized by the Moon, which facilitates a rapid precession of the Earth's spin axis, detuning the system away from resonance with orbital modulation. It is, however, likely that the architecture of the solar system underwent a dynamical instability-driven transformation, where the primordial configuration was more compact. Hence, the characteristic frequencies associated with orbital perturbations were likely faster in the past, potentially allowing for secular resonant encounters. In this work, we examine if, at any point in the Earth's evolutionary history, the obliquity varied significantly. Our calculations suggest that even though the orbital perturbations were different, themore » system nevertheless avoided resonant encounters throughout its evolution. This indicates that the Earth obtained its current obliquity during the formation of the Moon.« less

  2. DYNAMICAL INSTABILITIES IN HIGH-OBLIQUITY SYSTEMS

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tamayo, D.; Nicholson, P. D.; Burns, J. A.

    2013-03-01

    High-inclination circumplanetary orbits that are gravitationally perturbed by the central star can undergo Kozai oscillations-large-amplitude, coupled variations in the orbital eccentricity and inclination. We first study how this effect is modified by incorporating perturbations from the planetary oblateness. Tremaine et al. found that, for planets with obliquities >68. Degree-Sign 875, orbits in the equilibrium local Laplace plane are unstable to eccentricity perturbations over a finite radial range and execute large-amplitude chaotic oscillations in eccentricity and inclination. In the hope of making that treatment more easily understandable, we analyze the problem using orbital elements, confirming this threshold obliquity. Furthermore, we findmore » that orbits inclined to the Laplace plane will be unstable over a broader radial range, and that such orbits can go unstable for obliquities less than 68. Degree-Sign 875. Finally, we analyze the added effects of radiation pressure, which are important for dust grains and provide a natural mechanism for particle semimajor axes to sweep via Poynting-Robertson drag through any unstable range. For low-eccentricity orbits in the equilibrium Laplace plane, we find that generally the effect persists; however, the unstable radial range is shifted and small retrograde particles can avoid the instability altogether. We argue that this occurs because radiation pressure modifies the equilibrium Laplace plane.« less

  3. Splashing Threshold of Oblique Droplet Impacts on Surfaces of Various Wettability.

    PubMed

    Aboud, Damon G K; Kietzig, Anne-Marie

    2015-09-15

    Oblique drop impacts were performed at high speeds (up to 27 m/s, We > 9000) with millimetric water droplets, and a linear model was applied to define the oblique splashing threshold. Six different sample surfaces were tested: two substrate materials of different inherent surface wettability (PTFE and aluminum), each prepared with three different surface finishes (smooth, rough, and textured to support superhydrophobicity). Our choice of surfaces has allowed us to make several novel comparisons. Considering the inherent surface wettability, we discovered that PTFE, as the more hydrophobic surface, exhibits lower splashing thresholds than the hydrophilic surface of aluminum of comparable roughness. Furthermore, comparing oblique impacts on smooth and textured surfaces, we found that asymmetrical spreading and splashing behaviors occurred under a wide range of experimental conditions on our smooth surfaces; however, impacts occurring on textured surfaces were much more symmetrical, and one-sided splashing occurred only under very specific conditions. We attribute this difference to the air-trapping nature of textured superhydrophobic surfaces, which lowers the drag between the spreading lamella and the surface. The reduced drag affects oblique drop impacts by diminishing the effect of the tangential component of the impact velocity, causing the impact behavior to be governed almost exclusively by the normal velocity. Finally, by comparing oblique impacts on superhydrophobic surfaces at different impact angles, we discovered that although the pinning transition between rebounding and partial rebounding is governed primarily by the normal impact velocity, there is also a weak dependence on the tangential velocity. As a result, pinning is inhibited in oblique impacts. This led to the observation of a new behavior in highly oblique impacts on our superhydrophobic surfaces, which we named the stretched rebound, where the droplet is extended into an elongated pancake shape

  4. The use of decision tree induction and artificial neural networks for recognizing the geochemical distribution patterns of LREE in the Choghart deposit, Central Iran

    NASA Astrophysics Data System (ADS)

    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

  5. The Evolution of Oblique Impact Flow Fields Using Maxwell's Z Model

    NASA Technical Reports Server (NTRS)

    Anderson, J. L. B.; Schultz, P. H.; Heineck, J. T.

    2003-01-01

    Oblique impacts are the norm rather than the exception for impact craters on planetary surfaces. This work focuses on the excavation of experimental oblique impact craters using the NASA Ames Vertical Gun Range (AVGR). Three-dimensional particle image velocimetry (3D PIV) is used to obtain quantitative data on ejection positions, three-dimensional velocities and angles. These data are then used to test the applicability and limitations of Maxwell's Z Model in representing the subsurface evolution of the excavation-stage flow-field center during vertical and oblique impacts.

  6. Structural Equation Model Trees

    PubMed Central

    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

  7. The utility of a classificatory decision tree approach to assist clinical differentiation of melancholic and non-melancholic depression.

    PubMed

    Parker, G; McCraw, S; Hadzi-Pavlovic, D

    2015-07-15

    Studies suggest that differentiating melancholic from non-melancholic depressive disorders is advanced by use of illness course as well as symptom variables but, in practice, potentially differentiating variables are generally positioned as having equal value. Judging that differentiating features are more likely to vary in their signal intensity, we sought to determine the number of features required to effect differentiation and their hierarchical order. The 24-item clinician-rated Sydney Melancholia Prototype Index (SMPI-CR) was completed for 364 unipolar depressed patients. The sample was divided into two cohorts according to the recruitment period. An RPART classification tree analysis identified the most discriminating SMPI items in the development sample of 197 patients, and examined the sensitivity and specificity of the diagnostic decisions, then sought to replicate findings in a validation sample of 169 patients. Independent analyses of putative SMPI items identified only seven items as required to discriminate those with clinically-diagnosed melancholic or non-melancholic depression when the conditions were examined separately. An RPART analysis considering differentiation of melancholic and non-melancholic depression in the total samples retained five of those items in the classification tree, three of which were non-symptom items, and with 92% sensitivity and 80% specificity in the development sample. This reduced item set showed 93% sensitivity and 82% specificity in the validation sample. Our clinical judgment of melancholic or non-melancholic depression may not correspond with the clinical logic employed by other clinicians. Only five SMPI items were required to derive a succinct and efficient decision tree, comprising high sensitivity and specificity in differentiating melancholic and non-melancholic depression. Current study findings provide an empirical model that could enrich clinicians׳ approach to differentiating melancholic and non

  8. Interactions between factors related to the decision of sex offenders to confess during police interrogation: a classification-tree approach.

    PubMed

    Beauregard, Eric; Deslauriers-Varin, Nadine; St-Yves, Michel

    2010-09-01

    Most studies of confessions have looked at the influence of individual factors, neglecting the potential interactions between these factors and their impact on the decision to confess or not during an interrogation. Classification and regression tree analyses conducted on a sample of 624 convicted sex offenders showed that certain factors related to the offenders (e.g., personality, criminal career), victims (e.g., sex, relationship to offender), and case (e.g., time of day of the crime) were related to the decision to confess or not during the police interrogation. Several interactions were also observed between these factors. Results will be discussed in light of previous findings and interrogation strategies for sex offenders.

  9. Modelling the spatial distribution of Fasciola hepatica in bovines using decision tree, logistic regression and GIS query approaches for Brazil.

    PubMed

    Bennema, S C; Molento, M B; Scholte, R G; Carvalho, O S; Pritsch, I

    2017-11-01

    Fascioliasis is a condition caused by the trematode Fasciola hepatica. In this paper, the spatial distribution of F. hepatica in bovines in Brazil was modelled using a decision tree approach and a logistic regression, combined with a geographic information system (GIS) query. In the decision tree and the logistic model, isothermality had the strongest influence on disease prevalence. Also, the 50-year average precipitation in the warmest quarter of the year was included as a risk factor, having a negative influence on the parasite prevalence. The risk maps developed using both techniques, showed a predicted higher prevalence mainly in the South of Brazil. The prediction performance seemed to be high, but both techniques failed to reach a high accuracy in predicting the medium and high prevalence classes to the entire country. The GIS query map, based on the range of isothermality, minimum temperature of coldest month, precipitation of warmest quarter of the year, altitude and the average dailyland surface temperature, showed a possibility of presence of F. hepatica in a very large area. The risk maps produced using these methods can be used to focus activities of animal and public health programmes, even on non-evaluated F. hepatica areas.

  10. Initiation structure of oblique detonation waves behind conical shocks

    NASA Astrophysics Data System (ADS)

    Yang, Pengfei; Ng, Hoi Dick; Teng, Honghui; Jiang, Zonglin

    2017-08-01

    The understanding of oblique detonation dynamics has both inherent basic research value for high-speed compressible reacting flow and propulsion application in hypersonic aerospace systems. In this study, the oblique detonation structures formed by semi-infinite cones are investigated numerically by solving the unsteady, two-dimensional axisymmetric Euler equations with a one-step irreversible Arrhenius reaction model. The present simulation results show that a novel wave structure, featured by two distinct points where there is close-coupling between the shock and combustion front, is depicted when either the cone angle or incident Mach number is reduced. This structure is analyzed by examining the variation of the reaction length scale and comparing the flow field with that of planar, wedge-induced oblique detonations. Further simulations are performed to study the effects of chemical length scale and activation energy, which are both found to influence the formation of this novel structure. The initiation mechanism behind the conical shock is discussed to investigate the interplay between the effect of the Taylor-Maccoll flow, front curvature, and energy releases from the chemical reaction in conical oblique detonations. The observed flow fields are interpreted by means of the energetic limit as in the critical regime for initiation of detonation.

  11. Chaotic obliquity and the nature of the Martian climate

    NASA Technical Reports Server (NTRS)

    Jakosky, Bruce M.; Henderson, Bradley G.; Mellon, Michael T.

    1995-01-01

    Recent calculations of the Martian obliquity suggests that it varies chaotically on timescales longer than about 10(exp 7) years and varies between about 0 and 60 deg. We examine the seasonal water behavior at obliquities between 40 and 60 deg. Up to several tens of centimeters of water may sublime from the polar caps each year, and possibly move to the equator, where it is more stable. The CO2 frost and CO2-H2O clathrate hydrate are stable in thepolar deposits below a few tens of meters depth, so that the polar cap could contain a significant CO2 reservoir. If CO2 is present, it could be left over from the early history of Mars; also, it could be released into the atmosphere during periods of high obliquity, causing occasional periods of more-clement climate.

  12. Use of CHAID Decision Trees to Formulate Pathways for the Early Detection of Metabolic Syndrome in Young Adults

    PubMed Central

    Liu, Pei-Yang

    2014-01-01

    Metabolic syndrome (MetS) in young adults (age 20–39) is often undiagnosed. A simple screening tool using a surrogate measure might be invaluable in the early detection of MetS. Methods. A chi-squared automatic interaction detection (CHAID) decision tree analysis with waist circumference user-specified as the first level was used to detect MetS in young adults using data from the National Health and Nutrition Examination Survey (NHANES) 2009-2010 Cohort as a representative sample of the United States population (n = 745). Results. Twenty percent of the sample met the National Cholesterol Education Program Adult Treatment Panel III (NCEP) classification criteria for MetS. The user-specified CHAID model was compared to both CHAID model with no user-specified first level and logistic regression based model. This analysis identified waist circumference as a strong predictor in the MetS diagnosis. The accuracy of the final model with waist circumference user-specified as the first level was 92.3% with its ability to detect MetS at 71.8% which outperformed comparison models. Conclusions. Preliminary findings suggest that young adults at risk for MetS could be identified for further followup based on their waist circumference. Decision tree methods show promise for the development of a preliminary detection algorithm for MetS. PMID:24817904

  13. Inferior oblique muscle paresis as a sign of myasthenia gravis.

    PubMed

    Almog, Yehoshua; Ben-David, Merav; Nemet, Arie Y

    2016-03-01

    Myasthenia gravis may affect any of the six extra-ocular muscles, masquerading as any type of ocular motor pathology. The frequency of involvement of each muscle is not well established in the medical literature. This study was designed to determine whether a specific muscle or combination of muscles tends to be predominantly affected. This retrospective review included 30 patients with a clinical diagnosis of myasthenia gravis who had extra-ocular muscle involvement with diplopia at presentation. The diagnosis was confirmed by at least one of the following tests: Tensilon test, acetylcholine receptor antibodies, thymoma on chest CT scan, or suggestive electromyography. Frequency of involvement of each muscle in this cohort was inferior oblique 19 (63.3%), lateral rectus nine (30%), superior rectus four (13.3%), inferior rectus six (20%), medial rectus four (13.3%), and superior oblique three (10%). The inferior oblique was involved more often than any other muscle (p<0.01). Eighteen (60%) patients had ptosis, six (20%) of whom had bilateral ptosis. Diagnosing myasthenia gravis can be difficult, because the disease may mimic every pupil-sparing pattern of ocular misalignment. In addition diplopia caused by paresis of the inferior oblique muscle is rarely encountered (other than as a part of oculomotor nerve palsy). Hence, when a patient presents with vertical diplopia resulting from an isolated inferior oblique palsy, myasthenic etiology should be highly suspected. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Independent sources of anisotropy in visual orientation representation: a visual and a cognitive oblique effect.

    PubMed

    Balikou, Panagiota; Gourtzelidis, Pavlos; Mantas, Asimakis; Moutoussis, Konstantinos; Evdokimidis, Ioannis; Smyrnis, Nikolaos

    2015-11-01

    The representation of visual orientation is more accurate for cardinal orientations compared to oblique, and this anisotropy has been hypothesized to reflect a low-level visual process (visual, "class 1" oblique effect). The reproduction of directional and orientation information also leads to a mean error away from cardinal orientations or directions. This anisotropy has been hypothesized to reflect a high-level cognitive process of space categorization (cognitive, "class 2," oblique effect). This space categorization process would be more prominent when the visual representation of orientation degrades such as in the case of working memory with increasing cognitive load, leading to increasing magnitude of the "class 2" oblique effect, while the "class 1" oblique effect would remain unchanged. Two experiments were performed in which an array of orientation stimuli (1-4 items) was presented and then subjects had to realign a probe stimulus within the previously presented array. In the first experiment, the delay between stimulus presentation and probe varied, while in the second experiment, the stimulus presentation time varied. The variable error was larger for oblique compared to cardinal orientations in both experiments reproducing the visual "class 1" oblique effect. The mean error also reproduced the tendency away from cardinal and toward the oblique orientations in both experiments (cognitive "class 2" oblique effect). The accuracy or the reproduced orientation degraded (increasing variable error) and the cognitive "class 2" oblique effect increased with increasing memory load (number of items) in both experiments and presentation time in the second experiment. In contrast, the visual "class 1" oblique effect was not significantly modulated by any one of these experimental factors. These results confirmed the theoretical predictions for the two anisotropies in visual orientation reproduction and provided support for models proposing the categorization of

  15. Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran.

    PubMed

    Ramezankhani, Roghieh; Sajjadi, Nooshin; Nezakati Esmaeilzadeh, Roya; Jozi, Seyed Ali; Shirzadi, Mohammad Reza

    2018-05-08

    Cutaneous Leishmaniasis (CL) is a neglected tropical disease that continues to be a health problem in Iran. Nearly 350 million people are thought to be at risk. We investigated the impact of the environmental factors on CL incidence during the period 2007- 2015 in a known endemic area for this disease in Isfahan Province, Iran. After collecting data with regard to the climatic, topographic, vegetation coverage and CL cases in the study area, a decision tree model was built using the classification and regression tree algorithm. CL data for the years 2007 until 2012 were used for model construction and the data for the years 2013 until 2015 were used for testing the model. The Root Mean Square error and the correlation factor were used to evaluate the predictive performance of the decision tree model. We found that wind speeds less than 14 m/s, altitudes between 1234 and 1810 m above the mean sea level, vegetation coverage according to the normalized difference vegetation index (NDVI) less than 0.12, rainfall less than 1.6 mm and air temperatures higher than 30°C would correspond to a seasonal incidence of 163.28 per 100,000 persons, while if wind speed is less than 14 m/s, altitude less than 1,810 m and NDVI higher than 0.12, then the mean seasonal incidence of the disease would be 2.27 per 100,000 persons. Environmental factors were found to be important predictive variables for CL incidence and should be considered in surveillance and prevention programmes for CL control.

  16. Integrating Decision Tree and Hidden Markov Model (HMM) for Subtype Prediction of Human Influenza A Virus

    NASA Astrophysics Data System (ADS)

    Attaluri, Pavan K.; Chen, Zhengxin; Weerakoon, Aruna M.; Lu, Guoqing

    Multiple criteria decision making (MCDM) has significant impact in bioinformatics. In the research reported here, we explore the integration of decision tree (DT) and Hidden Markov Model (HMM) for subtype prediction of human influenza A virus. Infection with influenza viruses continues to be an important public health problem. Viral strains of subtype H3N2 and H1N1 circulates in humans at least twice annually. The subtype detection depends mainly on the antigenic assay, which is time-consuming and not fully accurate. We have developed a Web system for accurate subtype detection of human influenza virus sequences. The preliminary experiment showed that this system is easy-to-use and powerful in identifying human influenza subtypes. Our next step is to examine the informative positions at the protein level and extend its current functionality to detect more subtypes. The web functions can be accessed at http://glee.ist.unomaha.edu/.

  17. Compensatory value of urban trees in the United States

    Treesearch

    David J. Nowak; Daniel E. Crane; John F. Dwyer

    2002-01-01

    Understanding the value of an urban forest can give decision makers a better foundation for urban tree namagement. Based on tree-valuation methods of the Council of Tree and Landscape Appraisers and field data from eight cities, total compensatory value of tree populations in U.S. cities ranges from $101 million in Jersey City, New Jersey, to $6.2 billion in New York,...

  18. Complete annular and partial oblique pulley release for pediatric locked trigger thumb

    PubMed Central

    Kuo, Meiying

    2010-01-01

    Purpose To report the surgical treatment outcome of pediatric locked trigger thumb by sequential release of the annular pulley and partial release of the oblique pulley. Materials and Methods A retrospective review was undertaken on 28 operative thumbs in 24 patients with an average follow-up of 79 months. Intraoperative observations focused on the pathology of the pulley system. Surgical technique involved complete release of the annular pulley, which alone was insufficient in relieving the deformity, along with release of the proximal 50% of the oblique pulley in all patients. Postoperative parameters of bowstringing, resolution of Notta's node, thumb interphalangeal motion, and patient/parent satisfaction were assessed. Results The oblique pulley appeared stenotic, whereas the annular pulley was observed to be membranous and nearly indistinguishable from the tendon sheath. No patients had recurrence of thumb locking or triggering. No bowstringing was detected, and Notta’s node resolved fully in 19 of 20 thumbs. Five thumbs had an average of 12o less active IP joint motion without flexion contracture (i.e., less flexion). All patients or families expressed overall satisfaction with the procedure. Conclusion The annular pulley was attenuated in the majority of cases and the proximal half of the oblique pulley was stenotic in all patients. Releasing 50% of the oblique pulley after complete annular pulley release was necessary in all thumbs to achieve full FPL excursion. Mistaking the constricted proximal oblique pulley for an annular pulley may encourage releasing the entire oblique pulley, leading to an adverse result. Satisfactory outcome was achieved after surgical treatment of pediatric locked trigger thumbs. Type of Study/Level of Evidence Therapeutic IV. PMID:22131924

  19. Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

    NASA Astrophysics Data System (ADS)

    Ragettli, S.; Zhou, J.; Wang, H.; Liu, C.; Guo, L.

    2017-12-01

    Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. One of the main challenges of setting up such a system is finding appropriate model parameter values for ungauged catchments. Previous studies have shown that the transfer of parameter sets from hydrologically similar gauged catchments is one of the best performing regionalization methods. However, a remaining key issue is the identification of suitable descriptors of similarity. In this study, we use decision tree learning to explore parameter set transferability in the full space of catchment descriptors. For this purpose, a semi-distributed rainfall-runoff model is set up for 35 catchments in ten Chinese provinces. Hourly runoff data from in total 858 storm events are used to calibrate the model and to evaluate the performance of parameter set transfers between catchments. We then present a novel technique that uses the splitting rules of classification and regression trees (CART) for finding suitable donor catchments for ungauged target catchments. The ability of the model to detect flood events in assumed ungauged catchments is evaluated in series of leave-one-out tests. We show that CART analysis increases the probability of detection of 10-year flood events in comparison to a conventional measure of physiographic-climatic similarity by up to 20%. Decision tree learning can outperform other regionalization approaches because it generates rules that optimally consider spatial proximity and physical similarity. Spatial proximity can be used as a selection criteria but is skipped in the case where no similar gauged catchments are in the vicinity. We conclude that the CART regionalization concept is particularly suitable for implementation in sparsely gauged and topographically complex environments where a proximity

  20. Slip re-orientation in the oblique Abiquiu embayment, northern Rio Grande rift

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Murphy, M. A.; Andrea, R. A.

    2015-12-01

    Traditional models of oblique rifting predict that an oblique fault accommodates both dip-slip and strike-slip kinematics. However, recent analog experiments suggest that slip can be re-oriented to almost pure dip-slip on oblique faults if a preexisting weak zone is present at the onset of oblique extension. In this study, we use fault slip data from the Abiquiu embayment in northern Rio Grande rift to test the new model. The Rio Grande rift is a Cenozoic oblique rift extending from southern Colorado to New Mexico. From north to south, it comprises three major half grabens (San Luis, Española, and Albuquerque). The Abiquiu embayment is a sub-basin of the San Luis basin in northern New Mexico. Rift-border faults are generally older and oblique to the trend of the rift, whereas internal faults are younger and approximately N-S striking, i.e. orthogonal to the regional extension direction. Rift-border faults are deep-seated in the basement rocks while the internal faults only cut shallow stratigraphic sections. It has been suggested by many that inherited structures may influence the Rio Grande rifting. Particularly, Laramide structures (and possibly the Ancestral Rockies as well) that bound the Abiquiu embayment strike N- to NW. Our data show that internal faults in the Abiquiu embayment exhibit almost pure dip-slip (rake of slickenlines = 90º ± 15º), independent of their orientations with respect to the regional extension direction. On the contrary, border faults show two sets of rakes: almost pure dip-slip (rake = 90º ± 15º) where the fault is sub-parallel to the foliation, and moderately-oblique (rake = 30º ± 15º) where the fault is high angle to the foliation. We conclude that slip re-orientation occurs on most internal faults and some oblique border faults under the influence of inherited structures. Regarding those border faults on which slip is not re-oriented, we hypothesize that it may be caused by the Jemez volcanism or small-scale mantle

  1. Bayesian Decision Tree for the Classification of the Mode of Motion in Single-Molecule Trajectories

    PubMed Central

    Türkcan, Silvan; Masson, Jean-Baptiste

    2013-01-01

    Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens -toxin (CPT) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CPT trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to

  2. Contributions to the Earth's Obliquity Rate, Precession, and Nutation

    NASA Technical Reports Server (NTRS)

    Williams, James G.

    1994-01-01

    The precession and nutation of the Earth's equator arise from solar, lunar, and planetary torques on the oblate Earth. The mean lunar orbit plane is nearly coincident with the ecliptic plane. A small tilt out of the ecliptic is caused by planetary perturbations and the Earth's gravitational harmonic J(sub 2). These planetary perturbations on the lunar orbit result in torques on the oblate Earth which contribute to precession, obliquity rate, and nutation while the J(sub 2) perturbations contribute to precession and nutation. Small additional contributions to the secular rates arise from tidal effects and planetary torques on the Earth's bulge. The total correction to the obliquity rate is -0.024 sec/century, it is an observable motion in space (the much larger conventional obliquity rate is wholly from the motion of the ecliptic, not the equator), and it is not present in the IAU-adopted expressions for the orientation of the Earth's equator. The effects have generally been allowed for in past nutation theories and some precession theories. For the planetary effect, the contributions to the 18.6 yr nutation are -0.03 mas (milliarcseconds) for the in-phase Delta(psi) plus out-of-phase contributions of 0.14 mas in Delta(psi) and -0.03 mas in Delta(sub epsilon). The latter terms demonstrate that out-of-phase contributions can arise by means other than dissipation. The sum of the contributions to the precession rate is considered and the inferred value of the moment of inertia combination (C-A)/C, which is used to scale the coefficients in the nutation series, is evaluated. Using an updated value for the precession rate, the rigid body (C-A)/C =0.003 273 763 4 which, in combination with a satellite-derived J(sub 2), gives a normalized polar moment of inertia C/MR(exp 2) = 0.330 700 7. The planetary contributions to the precession and obliquity rates are not constant for long times causing accelerations in both quantities. Acceleration in precession also arises from

  3. Ceres Obliquity History and Its Implications for the Permanently Shadowed Regions

    NASA Technical Reports Server (NTRS)

    Ermakov, A. I.; Mazarico, E.; Schroder, S. E.; Carsenty, U.; Schorghofer, N.; Preusker, F.; Raymond, C. A.; Russell, C. T.; Zuber, Maria T.

    2017-01-01

    Due to the small current obliquity of Ceres ( epsilon approximately equal to 4), permanently shadowed regions (PSRs) exist on the dwarf planets surface. Since the existence and persistence of the PSRs depend on the obliquity, we compute the obliquity history over the last 3 My and find that it undergoes large oscillations with a period of 24.5 ky and a maximum of max 19:5. During periods of large obliquity, most of the present-day PSRs receive direct sunlight. Some craters in Ceres polar regions possess bright crater floor deposits (BCFDs).We find an apparent correlation between BCFDs and the most persistent PSRs. In the north, only two PSRs remain at max and they both contain BCFDs. In the south, one of the two only craters that remain in shadow at max contains a BCFD. The location of BCFDs within persistent PSRs strongly suggests BCFDs consist of volatiles accumulated in PSR cold traps: either water molecules trapped from the exosphere or exposed ground ice.

  4. Mars Secular Obliquity Change Due to Water Ice Caps

    NASA Technical Reports Server (NTRS)

    Rubincam, David P.

    1998-01-01

    Mars may have substantially changed its average axial tilt over geologic time due to the waxing and waning of water ice caps. Depending upon Mars' climate and internal structure, the average obliquity could have increased or decreased through climate friction by tens of degrees. A decrease could account for the apparent youthfulness of the polar layered terrain. Alternatively, Mars' average obliquity may have changed until it became "stuck" at its present value of 24.4 deg.

  5. Oblique impact: Projectile richochet, concomitant ejecta and momentum transfer

    NASA Technical Reports Server (NTRS)

    Gault, Donald E.; Schultz, Peter H.

    1987-01-01

    Experimental studies of oblique impact indicate that projectile richochet occurs for trajectory angles less than 30 deg and that the richocheted projectile, accompanied by some target material, are ejected at velocities that are a large fraction of the impact velocity. Because the probability of occurrence of oblique impact less than 30 deg on a planetary body is about one out of every four impact events, oblique impacts would seem to be a potential mechanism to provide a source of meteorites from even the largest atmosphere-free planetary bodies. Because the amount of richocheted target material cannot be determined from previous results, additional experiments in the Ames Vertical Gun laboratory were undertaken toward that purpose using pendulums; one to measure momentum of the richocheted projectile and concomitant target ejecta, and a second to measure the momentum transferred from projectile to target. These experiments are briefly discussed.

  6. Oblique reconstructions in tomosynthesis. II. Super-resolution

    PubMed Central

    Acciavatti, Raymond J.; Maidment, Andrew D. A.

    2013-01-01

    Purpose: In tomosynthesis, super-resolution has been demonstrated using reconstruction planes parallel to the detector. Super-resolution allows for subpixel resolution relative to the detector. The purpose of this work is to develop an analytical model that generalizes super-resolution to oblique reconstruction planes. Methods: In a digital tomosynthesis system, a sinusoidal test object is modeled along oblique angles (i.e., “pitches”) relative to the plane of the detector in a 3D divergent-beam acquisition geometry. To investigate the potential for super-resolution, the input frequency is specified to be greater than the alias frequency of the detector. Reconstructions are evaluated in an oblique plane along the extent of the object using simple backprojection (SBP) and filtered backprojection (FBP). By comparing the amplitude of the reconstruction against the attenuation coefficient of the object at various frequencies, the modulation transfer function (MTF) is calculated to determine whether modulation is within detectable limits for super-resolution. For experimental validation of super-resolution, a goniometry stand was used to orient a bar pattern phantom along various pitches relative to the breast support in a commercial digital breast tomosynthesis system. Results: Using theoretical modeling, it is shown that a single projection image cannot resolve a sine input whose frequency exceeds the detector alias frequency. The high frequency input is correctly visualized in SBP or FBP reconstruction using a slice along the pitch of the object. The Fourier transform of this reconstructed slice is maximized at the input frequency as proof that the object is resolved. Consistent with the theoretical results, experimental images of a bar pattern phantom showed super-resolution in oblique reconstructions. At various pitches, the highest frequency with detectable modulation was determined by visual inspection of the bar patterns. The dependency of the highest

  7. Residual symptoms after surgery for unilateral congenital superior oblique palsy.

    PubMed

    Caca, Ihsan; Sahin, Alparslan; Cingu, Abdullah; Ari, Seyhmus; Akbas, Umut

    2012-01-01

    To establish the surgical results and residual symptoms in 48 cases with unilateral congenital superior oblique muscle palsy that had surgical intervention to the vertical muscles alone. Myectomy and concomitant disinsertion of the inferior oblique (IO) muscle was performed in 38 cases and myectomy and concomitant IO disinsertion and recession of the superior rectus muscle in the ipsilateral eye was performed in 10 cases. The preoperative and postoperative vertical deviation values and surgical results were compared. Of the patients who had myectomy and concomitant IO disinsertion, 74% achieved an "excellent" result, 21% a "good" result, and 5% a "poor" result postoperatively. The difference in deviation between preoperative and postoperative values was statistically significant (P < .001). Of the patients who had myectomy and concomitant inferior oblique disinsertion and ipsilateral superior rectus recession, 50% achieved an "excellent" result, 20% a "good" result, and 30% a "poor" result postoperatively. The difference in deviation between preoperative and postoperative values was statistically significant (P < .001). Both procedures are effective and successful in patients with superior oblique muscle palsy, but a secondary surgery may be required. Copyright 2012, SLACK Incorporated.

  8. Oblique Intrathecal Injection in Lumbar Spine Surgery: A Technical Note.

    PubMed

    Jewett, Gordon A E; Yavin, Daniel; Dhaliwal, Perry; Whittaker, Tara; Krupa, JoyAnne; Du Plessis, Stephan

    2017-09-01

    Intrathecal morphine (ITM) is an efficacious method of providing postoperative analgesia and reducing pain associated complications. Despite adoption in many surgical fields, ITM has yet to become a standard of care in lumbar spine surgery. Spine surgeons' reticence to make use of the technique may in part be attributed to concerns of precipitating a cerebrospinal fluid (CSF) leak. Herein we describe a method for oblique intrathecal injection during lumbar spine surgery to minimize risk of CSF leak. The dural sac is penetrated obliquely at a 30° angle to offset dural and arachnoid puncture sites. Oblique injection in instances of limited dural exposure is made possible by introducing a 60° bend to a standard 30-gauge needle. The technique was applied for injection of ITM or placebo in 104 cases of lumbar surgery in the setting of a randomized controlled trial. Injection was not performed in two cases (2/104, 1.9%) following preinjection dural tear. In the remaining 102 cases no instances of postoperative CSF leakage attributable to oblique intrathecal injection occurred. Three cases (3/102, 2.9%) of transient CSF leakage were observed immediately following intrathecal injection with no associated sequelae or requirement for postsurgical intervention. In two cases, the observed leak was repaired by sealing with fibrin glue, whereas in a single case the leak was self-limited requiring no intervention. Oblique dural puncture was not associated with increased incidence of postoperative CSF leakage. This safe and reliable method of delivery of ITM should therefore be routinely considered in lumbar spine surgery.

  9. An "oblique effect" in the visual evoked potential of the cat.

    PubMed

    Bonds, A B

    1982-01-01

    An oblique effect was observed in the amplitude of the VEP recorded from area 17 of the cat. The ratio of the responses to oblique gratings compared with responses to horizontal and vertical gratings averaged 0.77. Orientation dependence was strongest at low spatial frequencies, unlike the effect found in primates.

  10. Obliquity of the Ecliptic

    NASA Astrophysics Data System (ADS)

    Murdin, P.

    2000-11-01

    The angle between the planes of the ecliptic and the equator. On the celestial sphere, the angle at which the ecliptic intersects the celestial equator. The current (year 2000) value of the obliquity of ecliptic, which is denoted by the symbol ɛ, is 23° 26' 21''. Its value varies by ±9'' over a period of 18.6 years as a consequence of a phenomenon called nutation. Over a much longer period (abou...

  11. Generation and Micro-scale Effects of Electrostatic Waves in an Oblique Shock

    NASA Astrophysics Data System (ADS)

    Goodrich, K.; Ergun, R.; Schwartz, S. J.; Newman, D.; Johlander, A.; Argall, M. R.; Wilder, F. D.; Torbert, R. B.; Khotyaintsev, Y. V.; Lindqvist, P. A.; Strangeway, R. J.; Russell, C. T.; Giles, B. L.; Gershman, D. J.; Burch, J. L.

    2017-12-01

    We present an analysis of large amplitude (>100 mV/m), high frequency (≤1 kHz), electrostatic waves observed by MMS during an oblique bow shock crossing event. The observed waves primarily consist of electrostatic solitary waves (ESWs) and oblique ion plasma waves (IPWs). ESWs typically include nonlinear structures such as double layers, ion phase-space holes, and electron phase-space holes. Oblique IPWs are observed to be similar to ion acoustic waves, but can propagate up to 70° from the ambient magnetic field direction. Both wave-modes, particularly IPWs, are observed to have very short wavelengths ( 100 m) and are highly localized. While such wave-modes have been previously observed in the terrestrial bow shock, instrumental constraints have limited detailed insight into their generation and their effect on their plasma shock environment. Analysis of this oblique shock event shows evidence that ESWs and oblique IPWs can be generated through field-aligned currents associated with magnetic turbulence and through a counterstreaming ion instability respectively. We also present evidence that this wave activity can facilitate momentum exchange between ion populations, resulting in deceleration of incoming solar wind, and localized electron heating.

  12. Paediatric lateral humeral condyle fractures: internal oblique radiographs alter the course of conservative treatment.

    PubMed

    Kurtulmuş, Tuhan; Sağlam, Necdet; Saka, Gursel; Avcı, Cem Coşkun; Uğurlar, Meriç; Türker, Mehmet

    2014-10-01

    At first presentation of paediatric humeral lateral condyle fractures, radiological methods such as computerised tomography, ultrasonography, magnetic resonance imaging, arthrography, and internal oblique radiography are used to determine stability. Very few studies show which radiological method should be used to evaluate displacement at follow-up for conservatively treated patients. This study aimed to show that internal oblique radiography is a simple, effective method to determine the subsequent development of fracture displacement in patients with an initially non-displaced or minimally displaced fracture. In this retrospective study, 27 paediatric patients with non-displaced or minimally displaced (<2 mm) humerus lateral condyle fracture were evaluated by elbow anteroposterior radiograph. The degree of fracture displacement was evaluated by anteroposterior then by internal oblique radiographs. The first follow-up was made between the 5th and 8th day and thereafter at intervals of 7-10 days. Of the 27 patients identified with non-displaced or minimally displaced (<2 mm) fracture from the initial anteroposterior radiograph, 16 were accepted as displacement >2 mm as a result of the evaluation of the internal oblique radiography and underwent surgery. At follow-up, 2 of 11 patients were defined with displacement from anteroposterior and internal oblique radiographs and 4 from the internal oblique radiographs and underwent surgery. Conservative treatment was applied to 5 patients. Internal oblique radiography is the best imaging showing subsequent fracture displacement in initially non-displaced or minimally displaced humerus lateral condyle fractures. At the first week follow-up, anteroposterior and particularly internal oblique radiographs should be taken of conservatively treated patients.

  13. The saturation of monochromatic lights obliquely incident on the retina.

    PubMed Central

    Alpern, M; Tamaki, R

    1983-01-01

    Foveal dark-adaptation undertaken to test the hypothesis that the excitation of rods causes the desaturation of 'yellow' lights in a 1 degree field traversing the margin of the pupil, fails to exclude that possibility. The desaturation is largest for a 1 degree outside diameter annular test, is still measurable with a 0.5 degree circular disk, but disappears for a 0.29 degree disk. The supersaturation of obliquely incident 501.2 nm test light follows the opposite pattern; it disappears with an annulus and is largest for a 0.29 degree circular field. It is unlikely that rods replace short-wave sensitive cones in the trichromatic match of an obliquely incident test with normally incident primaries. If rods as well as all three cones species are involved, the matches might not be trichromatic in the strong sense. Grassmann's law of scalar multiplication was tested and shown not to hold for the match of an obliquely incident test with normally incident primaries, though it remains valid whenever, both primaries and test strike the retina at the same angle of incidence (independent of that angle). The result in section 3 (above) cannot be due to rod intrusion. It persists (and becomes more conspicuous) on backgrounds (4.0 log scotopic td) which saturate rods. Moreover obliquely incident 'yellow' lights remain desaturated in intervals in the dark after a full bleach, whilst the test field is below rod threshold. The amount of desaturation does not differ appreciably from that normally found. The assumption of the unified theory of Alpern, Kitahara & Tamaki (1983) that the outer segments of only a single set of three cone species (with acceptance angles wide enough to include the entire exit pupil) contain the visual pigments absorbing both the normally incident primaries and the obliquely incident test is disproved by these results. Failure of Grassmann's law is most conspicuous under the conditions for which the changes in saturation upon changing from normal to oblique

  14. Simulation of an oblique collision of a locomotive and an intermodal container

    DOT National Transportation Integrated Search

    1999-11-01

    This paper presents an approach to modeling an oblique collision of a locomotive and an intermodal container. Previous studies of offset and oblique train collisions have used one and two-dimensional models to determine the trajectories of the equipm...

  15. Finding structure in data using multivariate tree boosting

    PubMed Central

    Miller, Patrick J.; Lubke, Gitta H.; McArtor, Daniel B.; Bergeman, C. S.

    2016-01-01

    Technology and collaboration enable dramatic increases in the size of psychological and psychiatric data collections, but finding structure in these large data sets with many collected variables is challenging. Decision tree ensembles such as random forests (Strobl, Malley, & Tutz, 2009) are a useful tool for finding structure, but are difficult to interpret with multiple outcome variables which are often of interest in psychology. To find and interpret structure in data sets with multiple outcomes and many predictors (possibly exceeding the sample size), we introduce a multivariate extension to a decision tree ensemble method called gradient boosted regression trees (Friedman, 2001). Our extension, multivariate tree boosting, is a method for nonparametric regression that is useful for identifying important predictors, detecting predictors with nonlinear effects and interactions without specification of such effects, and for identifying predictors that cause two or more outcome variables to covary. We provide the R package ‘mvtboost’ to estimate, tune, and interpret the resulting model, which extends the implementation of univariate boosting in the R package ‘gbm’ (Ridgeway et al., 2015) to continuous, multivariate outcomes. To illustrate the approach, we analyze predictors of psychological well-being (Ryff & Keyes, 1995). Simulations verify that our approach identifies predictors with nonlinear effects and achieves high prediction accuracy, exceeding or matching the performance of (penalized) multivariate multiple regression and multivariate decision trees over a wide range of conditions. PMID:27918183

  16. Investigation of powder injection moulded oblique fin heat sinks

    NASA Astrophysics Data System (ADS)

    Sai, Vadri Siva

    The present work attempts to study the fluid flow and heat transfer characteristics of PIM oblique finned microchannel heat sink both numerically and experimentally. Experimental results such as thermal resistance and pressure drop have been well validated with ANSYS FLUENT simulations. Hot spots are observed at the most downstream location of the channel is due to the effect of flow migration. Finally, a novel technique has been proposed to reduce the pressure drop on creating additional channels by removing some material at the middle portion of oblique fins. It is found that the creation of oblique cuts incurred a reduction in both pressure drop and Nuavg up to 31.36 % and 16.66 % respectively at a flow rate of 500 ml/min. Nevertheless, for all the flowrates considered in this analysis. % reduction in pressure drop is almost double as compared with % reduction in Nuavg. Therefore, this analysis is beneflcial in reducing the additional cost incurs due to pressure drop penalty.

  17. An Analytical Study for Subsonic Oblique Wing Transport Concept

    NASA Technical Reports Server (NTRS)

    Bradley, E. S.; Honrath, J.; Tomlin, K. H.; Swift, G.; Shumpert, P.; Warnock, W.

    1976-01-01

    The oblique wing concept has been investigated for subsonic transport application for a cruise Mach number of 0.95. Three different mission applications were considered and the concept analyzed against the selected mission requirements. Configuration studies determined the best area of applicability to be a commercial passenger transport mission. The critical parameter for the oblique wing concept was found to be aspect ratio which was limited to a value of 6.0 due to aeroelastic divergence. Comparison of the concept final configuration was made with fixed winged configurations designed to cruise at Mach 0.85 and 0.95. The crossover Mach number for the oblique wing concept was found to be Mach 0.91 for takeoff gross weight and direct operating cost. Benefits include reduced takeoff distance, installed thrust and mission block fuel and improved community noise characteristics. The variable geometry feature enables the final configuration to increase range by 10% at Mach 0.712 and to increase endurance by as much as 44%.

  18. Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees

    NASA Astrophysics Data System (ADS)

    Khryashchev, V. V.; Lebedev, A. A.; Priorov, A. L.

    2017-05-01

    Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.

  19. Machine Learning Through Signature Trees. Applications to Human Speech.

    ERIC Educational Resources Information Center

    White, George M.

    A signature tree is a binary decision tree used to classify unknown patterns. An attempt was made to develop a computer program for manipulating signature trees as a general research tool for exploring machine learning and pattern recognition. The program was applied to the problem of speech recognition to test its effectiveness for a specific…

  20. A key for the Forest Service hardwood tree grades

    Treesearch

    Gary W. Miller; Leland F. Hanks; Harry V., Jr. Wiant

    1986-01-01

    A dichotomous key organizes the USDA Forest Service hardwood tree grade specifications into a stepwise procedure for those learning to grade hardwood sawtimber. The key addresses the major grade factors, tree size, surface characteristics, and allowable cull deductions in a series of paried choices that lead the user to a decision regarding tree grade.

  1. Assessing the safety of co-exposure to food packaging migrants in food and water using the maximum cumulative ratio and an established decision tree.

    PubMed

    Price, Paul; Zaleski, Rosemary; Hollnagel, Heli; Ketelslegers, Hans; Han, Xianglu

    2014-01-01

    Food contact materials can release low levels of multiple chemicals (migrants) into foods and beverages, to which individuals can be exposed through food consumption. This paper investigates the potential for non-carcinogenic effects from exposure to multiple migrants using the Cefic Mixtures Ad hoc Team (MIAT) decision tree. The purpose of the assessment is to demonstrate how the decision tree can be applied to concurrent exposures to multiple migrants using either hazard or structural data on the specific components, i.e. based on the acceptable daily intake (ADI) or the threshold of toxicological concern. The tree was used to assess risks from co-exposure to migrants reported in a study on non-intentionally added substances (NIAS) eluting from food contact-grade plastic and two studies of water bottles: one on organic compounds and the other on ionic forms of various elements. The MIAT decision tree assigns co-exposures to different risk management groups (I, II, IIIA and IIIB) based on the hazard index, and the maximum cumulative ratio (MCR). The predicted co-exposures for all examples fell into Group II (low toxicological concern) and had MCR values of 1.3 and 2.4 (indicating that one or two components drove the majority of the mixture's toxicity). MCR values from the study of inorganic ions (126 mixtures) ranged from 1.1 to 3.8 for glass and from 1.1 to 5.0 for plastic containers. The MCR values indicated that a single compound drove toxicity in 58% of the mixtures. MCR values also declined with increases in the hazard index for the screening assessments of exposure (suggesting fewer substances contributed as risk potential increased). Overall, it can be concluded that the data on co-exposure to migrants evaluated in these case studies are of low toxicological concern and the safety assessment approach described in this paper was shown to be a helpful screening tool.

  2. Personalized Modeling for Prediction with Decision-Path Models

    PubMed Central

    Visweswaran, Shyam; Ferreira, Antonio; Ribeiro, Guilherme A.; Oliveira, Alexandre C.; Cooper, Gregory F.

    2015-01-01

    Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach. PMID:26098570

  3. Crustal Rock: Recorder of Oblique Impactor Meteoroid Trajectories

    NASA Astrophysics Data System (ADS)

    Ahrens, Thomas J.

    2005-07-01

    Oblique impact experiments in which 2g lead bullets strike samples of San Marcos granite and Bedford limestone at 1.2 km/s induce zones of increased crack density (termed shocked damage) which result in local decreases in bulk and shear moduli that results in maximum decreases of 30-40% in compressional and shear wave velocity (Budianski and O'Connell). Initial computer simulation of oblique impacts of meteorites (Pierazzo and Melosh) demonstrate the congruence of peak shock stress trajectory with the pre-impact meteoroid trajectory. We measure (Ai and Ahrens) via multi-beam (˜ 300) tomographic inversion, the sub-impact surface distribution of damage from the decreases in compressional wave velocity in the 20 x 20 x 15 cm rock target. The damage profiles for oblique impacts are markedly asymmetric (in plane of pre-impact meteoroid pre-impact trajectory) beneath the nearly round excavated craters. Thus, meteorite trajectory information can be recorded in planetary surfaces. Asymmetric sub-surface seismic velocity profiles beneath the Manson (Iowa) and Ries (Germany) impact craters demonstrate that pre-impact meteoroid trajectories records remain accessible for at least ˜ 10 ^ 8 years.

  4. Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models.

    PubMed

    Liang, Shih-Hsiung; Walther, Bruno Andreas; Shieh, Bao-Sen

    2017-01-01

    Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Our

  5. Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models

    PubMed Central

    Liang, Shih-Hsiung; Walther, Bruno Andreas

    2017-01-01

    Background Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. Methods We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. Results The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables

  6. Tree-to-tree variation in seed size and its consequences for seed dispersal versus predation by rodents.

    PubMed

    Wang, Bo; Ives, Anthony R

    2017-03-01

    Individual variation in seed size and seed production is high in many plant species. How does this variation affect seed-dispersing animals and, in turn, the fitness of individual plants? In this study, we first surveyed intraspecific variation in seed mass and production in a population of a Chinese white pine, Pinus armandii. For 134 target trees investigated in 2012, there was very high variation in seed size, with mean seed mass varying among trees almost tenfold, from 0.038 to 0.361 g. Furthermore, 30 of the 134 trees produced seeds 2 years later, and for these individuals there was a correlation in seed mass of 0.59 between years, implying consistent differences among individuals. For a subset of 67 trees, we monitored the foraging preferences of scatter-hoarding rodents on a total of 15,301 seeds: 8380 were ignored, 3184 were eaten in situ, 2651 were eaten after being cached, and 395 were successfully dispersed (cached and left intact). At the scale of individual seeds, seed mass affected almost every decision that rodents made to eat, remove, and cache individual seeds. At the level of individual trees, larger seeds had increased probabilities of both predation and successful dispersal: the effects of mean seed size on costs (predation) and benefits (caching) balanced out. Thus, despite seed size affecting rodent decisions, variation among trees in dispersal success associated with mean seed size was small once seeds were harvested. This might explain, at least in part, the maintenance of high variation in mean seed mass among tree individuals.

  7. Contributions to the Earth's obliquity rate, precession, and nutation

    NASA Technical Reports Server (NTRS)

    Williams, James G.

    1994-01-01

    The precession and nutation of the Earth's equator arise from solar, lunar, and planetary torques on the oblate Earth. The mean lunar orbit plane is nearly coincident with the ecliptic plane. A small tilt out of the ecliptic is caused by planetary perturbations and the Earth's gravitational harmonic J(sub2). These planetary perturbations on the lunar orbit result in torques on the oblate Earth which contribute to precession, obliquity rate, and nutation while the J(sub 2) perturbations contribute to precession and nutation. Small additional contributions to the secular rates arise from tidal effects and planetary torques on the Earth's bulge. The total correction to the obliquity rate is -0.024sec/century, it is an observable motion in space (the much larger conventional obliquity rate is wholly from the motion of the ecliptic, not the equator), and it is not present in the IAU-adopted expressions for the orientation of the Earth's equator. The J(sub2) effects have generally been allowed for in past nutation theories and some procession theories. For the planetary effect, the contributions to the 18.6 yr nutation are -0.03 mas (milliarcseconds) for the in-phase Delta phi plus out-of-phase contributions of 0.14 mas in Delta phi and -0.03 mas in Delta epsilon. The latter terms demonstrate that out-of-phase contributions can arise by means other than dissipation. The sum of the contributions to the precession rate is considered and the inferred value of the moment of inertia combination (C-A)/C, which is used to scale the coefficients in the nutation series, is evaluated. Using an updated value for the precession rate, the rigid body (C-A)/C = 0.003 273 763 4 which, in combination with a satellite-derived J(sub2), gives a normalized polar moment of inertia C/MR(exp2) = 0.330 700 7. The planetary contributions to the precession and obliquity rates are not constant for long times causing accelerations in both quantities. Acceleration in precession also arises from tides

  8. Variation of axial and oblique astigmatism with accommodation across the visual field

    PubMed Central

    Liu, Tao; Thibos, Larry N.

    2017-01-01

    In this study we investigated the impact of accommodation on axial and oblique astigmatism along 12 meridians of the central 30° of visual field and explored the compensation of corneal first-surface astigmatism by the remainder of the eye's optical system. Our experimental evidence revealed no systematic effect of accommodation on either axial or oblique astigmatism for two adult populations (myopic and emmetropic eyes). Although a few subjects exhibited systematic changes in axial astigmatism during accommodation, the dioptric value of these changes was much smaller than the amount of accommodation. For most subjects, axial and oblique astigmatism of the whole eye are both less than for the cornea alone, which indicates a compensatory role for internal optics at all accommodative states in both central and peripheral vision. A new method for determining the eye's optical axis based on visual field maps of oblique astigmatism revealed that, on average, the optical axis is 4.8° temporal and 0.39° superior to the foveal line-of-sight in object space, which agrees with previous results obtained by different methodologies and implies that foveal astigmatism includes a small amount of oblique astigmatism (0.06 D on average). Customized optical models of each eye revealed that oblique astigmatism of the corneal first surface is negligible along the pupillary axis for emmetropic and myopic eyes. Individual variation in the eye's optical axis is due in part to misalignment of the corneal and internal components that is consistent with tilting of the crystalline lens relative to the pupillary axis. PMID:28362902

  9. Oblique muscle surgery for treatment of nystagmus with head tilt.

    PubMed

    Lueder, Gregg T; Galli, Marlo

    2012-08-01

    Patients with nystagmus may adopt an abnormal head posture if they have a null zone in eccentric gaze. These patients uncommonly present with torticollis due to a null zone when the head is tilted. We describe the results of surgery on the oblique muscles to improve the abnormal head posture in this condition. This was a retrospective review of patients who had head tilts due to null zones of nystagmus. Surgery consisted of an anterior 50% tenectomy of the superior oblique tendon on one side and recession of the inferior oblique muscle to a position 6 mm posterior to the insertion of the inferior rectus muscle on the contralateral side. The patients' clinical histories and outcomes were reviewed. Six patients underwent the procedure. Of these, four had infantile nystagmus syndrome and two were born prematurely and had histories of intraventricular hemorrhages. Five of the patients had previous Kestenbaum surgery that corrected the horizontal component of their abnormal head postures. Age at time of surgery for the head tilt ranged from 3 to 13 years. Postoperative follow-up ranged from 1.5 to 3 years. The preoperative head tilts ranged from 25° to 45° (mean, 39°). The postoperative improvement ranged from 20° to 40° (mean, 28°). One of the patients with a history of intraventricular hemorrhage required additional surgery for strabismus unrelated to nystagmus. Anterior tenectomy of the superior oblique tendon combined with contralateral recession of the inferior oblique muscle improved head tilts related to a null zone of nystagmus. Copyright © 2012 American Association for Pediatric Ophthalmology and Strabismus. Published by Mosby, Inc. All rights reserved.

  10. Analytic Theory for the Yarkovsky-O Effect on Obliquity

    NASA Astrophysics Data System (ADS)

    Nesvorný, David; Vokrouhlický, David

    2008-07-01

    The Yarkovsky-O'Keefe-Radzievski-Paddack (YORP) effect is a thermal radiation torque that causes small objects to speed up or slow down their rotation and modify their spin vector orientation. This effect has important implications for spin dynamics of diameter D lsim 50 km asteroids. In our previous work we developed an analytic theory for the component of the YORP torque that affects the spin rate. Here we extend these calculations to determine the effect of the YORP torque on obliquity. Our theory is limited to objects with near-spherical shapes. Two limiting cases are studied: (1) immediate emission of the thermal energy that occurs for surface thermal conductivity K = 0; (2) the effects of K ≠ 0 in the limit of small temporal variations of the surface temperature. We use the linearized heat transport equation to model (2). The results include explicit scaling of the YORP torque on obliquity with physical and dynamical parameters such as the thermal conductivity and spin rate. The dependence of torques on the obliquity is given as series of the Legendre polynomials. Comparisons show excellent agreement of the analytic results with the numerically calculated YORP torques for objects such as asteroids 1998 KY26 and (66391) 1999 KW4. We suggest that an important fraction of main belt asteroids may have specific obliquity values (generalized Slivan states) arising from the roots of the Legendre polynomials.

  11. Monte Carlo simulations of particle acceleration at oblique shocks

    NASA Technical Reports Server (NTRS)

    Baring, Matthew G.; Ellison, Donald C.; Jones, Frank C.

    1994-01-01

    The Fermi shock acceleration mechanism may be responsible for the production of high-energy cosmic rays in a wide variety of environments. Modeling of this phenomenon has largely focused on plane-parallel shocks, and one of the most promising techniques for its study is the Monte Carlo simulation of particle transport in shocked fluid flows. One of the principal problems in shock acceleration theory is the mechanism and efficiency of injection of particles from the thermal gas into the accelerated population. The Monte Carlo technique is ideally suited to addressing the injection problem directly, and previous applications of it to the quasi-parallel Earth bow shock led to very successful modeling of proton and heavy ion spectra, as well as other observed quantities. Recently this technique has been extended to oblique shock geometries, in which the upstream magnetic field makes a significant angle Theta(sub B1) to the shock normal. Spectral resutls from test particle Monte Carlo simulations of cosmic-ray acceleration at oblique, nonrelativistic shocks are presented. The results show that low Mach number shocks have injection efficiencies that are relatively insensitive to (though not independent of) the shock obliquity, but that there is a dramatic drop in efficiency for shocks of Mach number 30 or more as the obliquity increases above 15 deg. Cosmic-ray distributions just upstream of the shock reveal prominent bumps at energies below the thermal peak; these disappear far upstream but might be observable features close to astrophysical shocks.

  12. On the Obliquities of Planets in Close-in, Compact Systems

    NASA Astrophysics Data System (ADS)

    Millholland, Sarah; Laughlin, Gregory

    2018-04-01

    Secular spin-orbit resonances can be encountered when planets sweep through commensurabilities between nodal and spin-axis precession frequencies, for example, during disk-driven migration. These encounters can induce significant planetary spin-axis misalignment and capture into a “Cassini state”, a configuration involving synchronous precession of the planetary spin and orbital angular momentum vectors. We show that typical extrasolar systems – exemplified by the Kepler close-in, coplanar multiple-planet systems – frequently have nodal and spin-axis precession frequencies that are near-commensurable. This implies that obliquity-pumping should be common if the planets undergo any migration. We present analytic and numerical models of the spin evolution of typical Kepler-multi-type systems subject to the influences of disk migration, the quadrupole potential of an oblate young star, and tidal dissipation. Among other consequences of large obliquities, we find that the several orders of magnitude enhancement in tidal dissipation strength at non-zero obliquity may be able to generate the observed excess of planet pairs with period ratios just wide of 2:1 and 3:2. Though tidal origins of these excesses have previously been discussed, tidal dissipation is insufficient to reproduce the observations unless planets have non-negligible obliquities at some time in their history.

  13. Oblique view of Copernicus crater

    NASA Image and Video Library

    1972-12-13

    AS17-145-22287 (7-19 Dec. 1972) --- An oblique view of the large crater Copernicus on the lunar nearside, as photographed from the Apollo 17 spacecraft in lunar orbit. This view is looking generally southwest toward the crater on the horizon. The coordinates of the center of Copernicus are approximately 20 degrees west longitude and 9.5 degrees north latitude.

  14. Rectus Pulley Displacements without Abnormal Oblique Contractility Explain Strabismus in Superior Oblique Palsy.

    PubMed

    Suh, Soh Youn; Le, Alan; Clark, Robert A; Demer, Joseph L

    2016-06-01

    Using high-resolution magnetic resonance imaging (MRI), we investigated whether rectus pulleys are significantly displaced in superior oblique (SO) palsy and whether displacements account for strabismus patterns. Prospective case-control study. Twenty-four patients diagnosed with SO palsy based on atrophy of the SO muscle on MRI and 19 age-matched orthotropic control subjects. High-resolution, surface coil MRI scans were obtained in multiple, contiguous, quasicoronal planes during monocular central gaze fixation. Pulley locations in oculocentric coordinates in the following subgroups of patients with SO palsy were compared with normal results in subgroups of patients with SO palsy: unilateral versus bilateral, congenital versus acquired, and isotropic (round) versus anisotropic (elongated) SO atrophy. Expected effects of pulley displacements were modeled using Orbit 1.8 (Eidactics, San Francisco, CA) computational simulation. Rectus pulley positions and ocular torsion. Rectus pulleys typically were displaced in SO palsy. In unilateral SO palsy, on average the medial rectus (MR) pulley was displaced 1.1 mm superiorly, the superior rectus (SR) pulley was displaced 0.8 mm temporally, and the inferior rectus (IR) pulley was displaced 0.6 mm superiorly and 0.9 mm nasally from normal. Displacements were similar in bilateral SO palsy, with the SR pulley additionally displaced 0.9 mm superiorly. However, the lateral rectus pulley was not displaced in either unilateral or bilateral SO palsy. The SR and MR pulleys were displaced in congenital SO palsy, whereas the IR and MR pulleys were displaced in acquired palsy. Pulley positions did not differ between isotropic and anisotropic palsy or between patients with cyclotropia of less than 7° versus cyclotropia of 7° or more. Simulations predicted that the observed pulley displacements alone could cause patterns of incomitant strabismus typical of SO palsy, without requiring any abnormality of SO or inferior oblique strength

  15. Identification of Some Zeolite Group Minerals by Application of Artificial Neural Network and Decision Tree Algorithm Based on SEM-EDS Data

    NASA Astrophysics Data System (ADS)

    Akkaş, Efe; Evren Çubukçu, H.; Akin, Lutfiye; Erkut, Volkan; Yurdakul, Yasin; Karayigit, Ali Ihsan

    2016-04-01

    Identification of zeolite group minerals is complicated due to their similar chemical formulas and habits. Although the morphologies of various zeolite crystals can be recognized under Scanning Electron Microscope (SEM), it is relatively more challenging and problematic process to identify zeolites using their mineral chemical data. SEMs integrated with energy dispersive X-ray spectrometers (EDS) provide fast and reliable chemical data of minerals. However, considering elemental similarities of characteristic chemical formulae of zeolite species (e.g. Clinoptilolite ((Na,K,Ca)2 -3Al3(Al,Si)2Si13O3612H2O) and Erionite ((Na2,K2,Ca)2Al4Si14O36ṡ15H2O)) EDS data alone does not seem to be sufficient for correct identification. Furthermore, the physical properties of the specimen (e.g. roughness, electrical conductivity) and the applied analytical conditions (e.g. accelerating voltage, beam current, spot size) of the SEM-EDS should be uniform in order to obtain reliable elemental results of minerals having high alkali (Na, K) and H2O (approx. %14-18) contents. This study which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK Project No: 113Y439), aims to construct a database as large as possible for various zeolite minerals and to develop a general prediction model for the identification of zeolite minerals using SEM-EDS data. For this purpose, an artificial neural network and rule based decision tree algorithm were employed. Throughout the analyses, a total of 1850 chemical data were collected from four distinct zeolite species, (Clinoptilolite-Heulandite, Erionite, Analcime and Mordenite) observed in various rocks (e.g. coals, pyroclastics). In order to obtain a representative training data set for each minerals, a selection procedure for reference mineral analyses was applied. During the selection procedure, SEM based crystal morphology data, XRD spectra and re-calculated cationic distribution, obtained by EDS have been used for the

  16. Application Of Decision Tree Approach To Student Selection Model- A Case Study

    NASA Astrophysics Data System (ADS)

    Harwati; Sudiya, Amby

    2016-01-01

    The main purpose of the institution is to provide quality education to the students and to improve the quality of managerial decisions. One of the ways to improve the quality of students is to arrange the selection of new students with a more selective. This research takes the case in the selection of new students at Islamic University of Indonesia, Yogyakarta, Indonesia. One of the university's selection is through filtering administrative selection based on the records of prospective students at the high school without paper testing. Currently, that kind of selection does not yet has a standard model and criteria. Selection is only done by comparing candidate application file, so the subjectivity of assessment is very possible to happen because of the lack standard criteria that can differentiate the quality of students from one another. By applying data mining techniques classification, can be built a model selection for new students which includes criteria to certain standards such as the area of origin, the status of the school, the average value and so on. These criteria are determined by using rules that appear based on the classification of the academic achievement (GPA) of the students in previous years who entered the university through the same way. The decision tree method with C4.5 algorithm is used here. The results show that students are given priority for admission is that meet the following criteria: came from the island of Java, public school, majoring in science, an average value above 75, and have at least one achievement during their study in high school.

  17. Construction and validation of a decision tree for treating metabolic acidosis in calves with neonatal diarrhea.

    PubMed

    Trefz, Florian M; Lorch, Annette; Feist, Melanie; Sauter-Louis, Carola; Lorenz, Ingrid

    2012-12-06

    The aim of the present prospective study was to investigate whether a decision tree based on basic clinical signs could be used to determine the treatment of metabolic acidosis in calves successfully without expensive laboratory equipment. A total of 121 calves with a diagnosis of neonatal diarrhea admitted to a veterinary teaching hospital were included in the study. The dosages of sodium bicarbonate administered followed simple guidelines based on the results of a previous retrospective analysis. Calves that were neither dehydrated nor assumed to be acidemic received an oral electrolyte solution. In cases in which intravenous correction of acidosis and/or dehydration was deemed necessary, the provided amount of sodium bicarbonate ranged from 250 to 750 mmol (depending on alterations in posture) and infusion volumes from 1 to 6.25 liters (depending on the degree of dehydration). Individual body weights of calves were disregarded. During the 24 hour study period the investigator was blinded to all laboratory findings. After being lifted, many calves were able to stand despite base excess levels below -20 mmol/l. Especially in those calves, metabolic acidosis was undercorrected with the provided amount of 500 mmol sodium bicarbonate, which was intended for calves standing insecurely. In 13 calves metabolic acidosis was not treated successfully as defined by an expected treatment failure or a measured base excess value below -5 mmol/l. By contrast, 24 hours after the initiation of therapy, a metabolic alkalosis was present in 55 calves (base excess levels above +5 mmol/l). However, the clinical status was not affected significantly by the metabolic alkalosis. Assuming re-evaluation of the calf after 24 hours, the tested decision tree can be recommended for the use in field practice with minor modifications. Calves that stand insecurely and are not able to correct their position if pushed require higher doses of sodium bicarbonate, if there is clinical evidence of a

  18. Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree.

    PubMed

    Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang

    2016-07-12

    Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

  19. Can Classification Tree Analyses Help Improve Decision Making About Treatments for Depression and Anxiety Disorders? A Preliminary Investigation

    PubMed Central

    Rhodes, Louisa; Naumann, Ulrike M.

    2011-01-01

    Objective: To identify how decisions about treatment are being made in secondary services for anxiety disorders and depression and, specifically, whether it was possible to predict the decisions to refer for evidence-based treatments. Method: Post hoc classification tree analysis was performed using a sample from an audit on implementation of the National Institute for Health and Clinical Excellence Guidelines for Depression and Anxiety Disorders. The audit was of 5 teams offering secondary care services; they included psychiatrists, psychologists, community psychiatric nurses, social workers, dual-diagnosis workers, and vocational workers. The patient sample included all of those with a primary problem of depression (n = 56) or an anxiety disorder (n = 16) who were offered treatment from February 16 to April 3, 2009. The outcome variable was whether or not evidence-based treatments were offered, and the predictor variables were presenting problem, risk, comorbid problem, social problems, and previous psychiatric history. Results: Treatment decisions could be more accurately predicted for anxiety disorders (93% correct) than for depression (55%). For anxiety disorders, the presence or absence of social problems was a good predictor for whether evidence-based or non–evidence-based treatments were offered; 44% (4/9) of those with social problems vs 100% (6/6) of those without social problems were offered evidence-based treatments. For depression, patients’ risk rating had the largest impact on treatment decisions, although no one variable could be identified as individually predictive of all treatment decisions. Conclusions: Treatment decisions were generally consistent for anxiety disorders but more idiosyncratic for depression, making the development of a decision-making model very difficult for depression. The lack of clarity of some terms in the clinical guidelines and the more complex nature of depression could be factors contributing to this difficulty

  20. Comparing ensemble learning methods based on decision tree classifiers for protein fold recognition.

    PubMed

    Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi

    2014-01-01

    In this paper, some methods for ensemble learning of protein fold recognition based on a decision tree (DT) are compared and contrasted against each other over three datasets taken from the literature. According to previously reported studies, the features of the datasets are divided into some groups. Then, for each of these groups, three ensemble classifiers, namely, random forest, rotation forest and AdaBoost.M1 are employed. Also, some fusion methods are introduced for combining the ensemble classifiers obtained in the previous step. After this step, three classifiers are produced based on the combination of classifiers of types random forest, rotation forest and AdaBoost.M1. Finally, the three different classifiers achieved are combined to make an overall classifier. Experimental results show that the overall classifier obtained by the genetic algorithm (GA) weighting fusion method, is the best one in comparison to previously applied methods in terms of classification accuracy.

  1. Computation of Thermally Perfect Properties of Oblique Shock Waves

    NASA Technical Reports Server (NTRS)

    Tatum, Kenneth E.

    1996-01-01

    A set of compressible flow relations describing flow properties across oblique shock waves, derived for a thermally perfect, calorically imperfect gas, is applied within the existing thermally perfect gas (TPG) computer code. The relations are based upon a value of cp expressed as a polynomial function of temperature. The updated code produces tables of compressible flow properties of oblique shock waves, as well as the original properties of normal shock waves and basic isentropic flow, in a format similar to the tables for normal shock waves found in NACA Rep. 1135. The code results are validated in both the calorically perfect and the calorically imperfect, thermally perfect temperature regimes through comparisons with the theoretical methods of NACA Rep. 1135, and with a state-of-the-art computational fluid dynamics code. The advantages of the TPG code for oblique shock wave calculations, as well as for the properties of isentropic flow and normal shock waves, are its ease of use, and its applicability to any type of gas (monatomic, diatomic, triatomic, polyatomic, or any specified mixture thereof).

  2. Three-Dimensional Simulations of Oblique Asteroid Impacts into Water

    NASA Astrophysics Data System (ADS)

    Gisler, G. R.; Ferguson, J. M.; Heberling, T.; Plesko, C. S.; Weaver, R.

    2016-12-01

    Waves generated by impacts into oceans may represent the most significant danger from near-earth asteroids and comets. For impacts near populated shores, the crown splash and subsequent waves, accompanied by sediment lofting and high winds, could be more damaging than storm surges from the strongest hurricanes. For asteroids less than 500 m in diameter that impact into deep water far from shores, the waves produced will be detectable over large distances, but probably not significantly dangerous. We present new three-dimensional simulations of oblique impacts into deep water, with trajectory angles ranging from 20 degrees to 60 degrees (where 90 degrees is vertical). These simulations are performed with the Los Alamos Rage hydrocode, and include atmospheric effects including ablation and airbursts. These oblique impact simulations are specifically performed in order to help determine whether there are additional dangers from the obliquity of impact not covered by previous two-dimensional studies. Water surface elevation profiles, surface pressures, and depth-averaged mass fluxes within the water are prepared for use in propagation studies.

  3. Spatial evolution of Zagros collision zone in Kurdistan, NW Iran: constraints on Arabia-Eurasia oblique convergence

    NASA Astrophysics Data System (ADS)

    Sadeghi, Shahriar; Yassaghi, Ali

    2016-04-01

    Stratigraphy, detailed structural mapping and a crustal-scale cross section across the NW Zagros collision zone provide constraints on the spatial evolution of oblique convergence of the Arabian and Eurasian plates since the Late Cretaceous. The Zagros collision zone in NW Iran consists of the internal Sanandaj-Sirjan, Gaveh Rud and Ophiolite zones and the external Bisotoun, Radiolarite and High Zagros zones. The Main Zagros Thrust is the major structure of the Zagros suture zone. Two stages of oblique deformation are recognized in the external part of the NW Zagros in Iran. In the early stage, coexisting dextral strike-slip and reverse dominated domains in the Radiolarite zone developed in response to deformation partitioning due to oblique convergence. Dextral-reverse faults in the Bisotoun zone are also compatible with oblique convergence. In the late stage, deformation partitioning occurred during southeastward propagation of the Zagros orogeny towards its foreland resulting in synchronous development of orogen-parallel strike-slip and thrust faults. It is proposed that the first stage was related to Late Cretaceous oblique obduction, while the second stage resulted from Cenozoic collision. The Cenozoic orogen-parallel strike-slip component of Zagros oblique convergence is not confined to the Zagros suture zone (Main Recent Fault) but also occurred in the external part (Marekhil-Ravansar fault system). Thus, it is proposed that oblique convergence of Arabian and Eurasian plates in Zagros collision zone initiated with oblique obduction in the Late Cretaceous followed by oblique collision in the late Tertiary, consistent with global plate reconstructions.

  4. Red Shifts with Obliquely Approaching Light Sources.

    ERIC Educational Resources Information Center

    Head, C. E.; Moore-Head, M. E.

    1988-01-01

    Refutes the Doppler effect as the explanation of large red shifts in the spectra of distant galaxies and explains the relativistic effects in which the light sources approach the observer obliquely. Provides several diagrams and graphs. (YP)

  5. Atmospheric dynamics and habitability range in Earth-like aquaplanets obliquity simulations

    NASA Astrophysics Data System (ADS)

    Nowajewski, Priscilla; Rojas, M.; Rojo, P.; Kimeswenger, S.

    2018-05-01

    We present the evolution of the atmospheric variables that affect planetary climate by increasing the obliquity by using a general circulation model (PlaSim) coupled to a slab ocean with mixed layer flux correction. We increase the obliquity between 30° and 90° in 16 aquaplanets with liquid sea surface and perform the simulation allowing the sea ice cover formation to be a consequence of its atmospheric dynamics. Insolation is maintained constant in each experiment, but changing the obliquity affects the radiation budget and the large scale circulation. Earth-like atmospheric dynamics is observed for planets with obliquity under 54°. Above this value, the latitudinal temperature gradient is reversed giving place to a new regime of jet streams, affecting the shape of Hadley and Ferrel cells and changing the position of the InterTropical Convergence Zone. As humidity and high temperatures determine Earth's habitability, we introduce the wet bulb temperature as an atmospheric index of habitability for Earth-like aquaplanets with above freezing temperatures. The aquaplanets are habitable all year round at all latitudes for values under 54°; above this value habitability decreases toward the poles due to high temperatures.

  6. Experimental study on mean overtopping of sloping seawall under oblique irregular waves

    NASA Astrophysics Data System (ADS)

    Wang, Deng-ting; Ju, Lie-hong; Zhu, Jia-ling; Wang, Zhen; Sun, Tian-ting; Chen, Wei-qiu

    2017-06-01

    In this paper, domestic and abroad research progresses and related calculation formulae of the mean overtopping discharge are summarized. Through integral physical model experiments, the relation between the wave direction and the overtopping discharge on the top of the sloping dike is focused on and put into analysis and discussion; and a modified formula for mean overtopping discharges under oblique irregular waves is proposed. The study shows that the mean overtopping discharge generally goes down as the relative wave obliquity β increases for a fixed measurement point and the mean overtopping discharge generally increases as the wave steepness H/L decreases (the cycle increases) for a fixed relative wave obliquity.

  7. Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

    PubMed

    Lajnef, Tarek; Chaibi, Sahbi; Ruby, Perrine; Aguera, Pierre-Emmanuel; Eichenlaub, Jean-Baptiste; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

    2015-07-30

    Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k-fold cross-validation. The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts' scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. The DSVM framework outperforms classification with more standard multi-class "one-against-all" SVM and linear-discriminant analysis. The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

    NASA Astrophysics Data System (ADS)

    Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

    2018-04-01

    In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

  9. A Double Zone Dynamical Model For The Tidal Evolution Of The Obliquity

    NASA Astrophysics Data System (ADS)

    Damiani, Cilia

    2017-10-01

    It is debated wether close-in giants planets can form in-situ and if not, which mechanisms are responsible for their migration. One of the observable tests for migration theories is the current value of the obliquity. But after the main migration mechanism has ended, the combined effects of tidal dissipation and the magnetic braking of the star lead to the evolution of both the obliquity and the semi-major axis. The observed correlation between effective temperature and measured projected obliquity has been taken as evidence of such mechanisms being at play. Here I present an improved model for the tidal evolution of the obliquity. It includes all the components of the dynamical tide for circular misaligned systems. It uses an analytical formulation for the frequency-averaged dissipation for each mode, depending only on global stellar parameters, giving a measure of the dissipative properties of the convective zone of the host as it evolves in time. The model also includes the effect of magnetic braking in the framework of the double zone model. This results in the estimation of different tidal evolution timescales for the evolution of the planet's semi-major axis and obliquity depending on the properties of the stellar host. This model can be used to test migration theories, provided that a good determination of stellar radii, masses and ages can be obtained.

  10. Scale relativity and quantization of planet obliquities.

    NASA Astrophysics Data System (ADS)

    Nottale, L.

    1998-07-01

    The author applies the theory of scale relativity to the equations of rotational motion of solid bodies. He predicts in the new framework that the obliquities and inclinations of planets and satellites in the solar system must be quantized. Namely, one expects their distribution to be no longer uniform between 0 and π, but instead to display well-defined peaks of probability density at angles θk = kπ/n. The author shows in the present paper that the observational data agree very well with the prediction for n = 7, including the retrograde bodies and those which are heeled over the ecliptic plane. In particular, the value 23°27' of the obliquity of the Earth, which partly determines its climate, is not a random one, but lies in one of the main probability peaks at θ = π/7.

  11. Study on Practical Technologies of Aerial Triangulation for Real Scene 3d Moeling with Oblique Photography

    NASA Astrophysics Data System (ADS)

    Cai, Z.; Liu, W.; Luo, G.; Xiang, Z.

    2018-04-01

    The key technologies in the real scene 3D modeling of oblique photography mainly include the data acquisition of oblique photography, layout and surveying of photo control points, oblique camera calibration, aerial triangulation, dense matching of multi-angle image, building of triangulation irregular network (TIN) and TIN simplification and automatic texture mapping, among which aerial triangulation is the core and the results of aerial triangulation directly affect the later model effect and the corresponding data accuracy. Starting from this point of view, this paper aims to study the practical technologies of aerial triangulation for real scene 3D modeling with oblique photography and finally proposes a technical method of aerial triangulation with oblique photography which can be put into practice.

  12. Prescriptive models to support decision making in genetics.

    PubMed

    Pauker, S G; Pauker, S P

    1987-01-01

    Formal prescriptive models can help patients and clinicians better understand the risks and uncertainties they face and better formulate well-reasoned decisions. Using Bayes rule, the clinician can interpret pedigrees, historical data, physical findings and laboratory data, providing individualized probabilities of various diagnoses and outcomes of pregnancy. With the advent of screening programs for genetic disease, it becomes increasingly important to consider the prior probabilities of disease when interpreting an abnormal screening test result. Decision trees provide a convenient formalism for structuring diagnostic, therapeutic and reproductive decisions; such trees can also enhance communication between clinicians and patients. Utility theory provides a mechanism for patients to understand the choices they face and to communicate their attitudes about potential reproductive outcomes in a manner which encourages the integration of those attitudes into appropriate decisions. Using a decision tree, the relevant probabilities and the patients' utilities, physicians can estimate the relative worth of various medical and reproductive options by calculating the expected utility of each. By performing relevant sensitivity analyses, clinicians and patients can understand the impact of various soft data, including the patients' attitudes toward various health outcomes, on the decision making process. Formal clinical decision analytic models can provide deeper understanding and improved decision making in clinical genetics.

  13. Proposal of a Clinical Decision Tree Algorithm Using Factors Associated with Severe Dengue Infection.

    PubMed

    Tamibmaniam, Jayashamani; Hussin, Narwani; Cheah, Wee Kooi; Ng, Kee Sing; Muninathan, Prema

    2016-01-01

    WHO's new classification in 2009: dengue with or without warning signs and severe dengue, has necessitated large numbers of admissions to hospitals of dengue patients which in turn has been imposing a huge economical and physical burden on many hospitals around the globe, particularly South East Asia and Malaysia where the disease has seen a rapid surge in numbers in recent years. Lack of a simple tool to differentiate mild from life threatening infection has led to unnecessary hospitalization of dengue patients. We conducted a single-centre, retrospective study involving serologically confirmed dengue fever patients, admitted in a single ward, in Hospital Kuala Lumpur, Malaysia. Data was collected for 4 months from February to May 2014. Socio demography, co-morbidity, days of illness before admission, symptoms, warning signs, vital signs and laboratory result were all recorded. Descriptive statistics was tabulated and simple and multiple logistic regression analysis was done to determine significant risk factors associated with severe dengue. 657 patients with confirmed dengue were analysed, of which 59 (9.0%) had severe dengue. Overall, the commonest warning sign were vomiting (36.1%) and abdominal pain (32.1%). Previous co-morbid, vomiting, diarrhoea, pleural effusion, low systolic blood pressure, high haematocrit, low albumin and high urea were found as significant risk factors for severe dengue using simple logistic regression. However the significant risk factors for severe dengue with multiple logistic regressions were only vomiting, pleural effusion, and low systolic blood pressure. Using those 3 risk factors, we plotted an algorithm for predicting severe dengue. When compared to the classification of severe dengue based on the WHO criteria, the decision tree algorithm had a sensitivity of 0.81, specificity of 0.54, positive predictive value of 0.16 and negative predictive of 0.96. The decision tree algorithm proposed in this study showed high sensitivity

  14. Recent progress of obliquely deposited thin films for industrial applications

    NASA Astrophysics Data System (ADS)

    Suzuki, Motofumi; Itoh, Tadayoshi; Taga, Yasunori

    1999-06-01

    More than 10 years ago, birefringent films of metal oxides were formed by oblique vapor deposition and investigated with a view of their application to optical retardation plates. The retardation function of the films was explained in terms of the birefringence caused by the characteristic anisotropic nanostructure inside the films. These films are now classified in the genre of the so-called sculptured thin films. However, the birefringent films thus prepared are not yet industrialized even now due to the crucial lack of the durability and the yield of products. In this review paper, we describe the present status of application process of the retardation films to the information systems such as compact disc and digital versatile disc devices with a special emphasis on the uniformity of retardation properties in a large area and the stability of the optical properties of the obliquely deposited thin films. Finally, further challenges for wide application of the obliquely deposited thin films are also discussed.

  15. Coeval emplacement and orogen-parallel transport of gold in oblique convergent orogens

    NASA Astrophysics Data System (ADS)

    Upton, Phaedra; Craw, Dave

    2016-12-01

    Varying amounts of gold mineralisation is occurring in all young and active collisional mountain belts. Concurrently, these syn-orogenic hydrothermal deposits are being eroded and transported to form placer deposits. Local extension occurs in convergent orogens, especially oblique orogens, and facilitates emplacement of syn-orogenic gold-bearing deposits with or without associated magmatism. Numerical modelling has shown that extension results from directional variations in movement rates along the rock transport trajectory during convergence, and is most pronounced for highly oblique convergence with strong crustal rheology. On-going uplift during orogenesis exposes gold deposits to erosion, transport, and localised placer concentration. Drainage patterns in variably oblique convergent orogenic belts typically have an orogen-parallel or sub-parallel component; the details of which varies with convergence obliquity and the vagaries of underlying geological controls. This leads to lateral transport of eroded syn-orogenic gold on a range of scales, up to > 100 km. The presence of inherited crustal blocks with contrasting rheology in oblique orogenic collision zones can cause perturbations in drainage patterns, but numerical modelling suggests that orogen-parallel drainage is still a persistent and robust feature. The presence of an inherited block of weak crust enhances the orogen-parallel drainage by imposition of localised subsidence zones elongated along a plate boundary. Evolution and reorientation of orogen-parallel drainage can sever links between gold placer deposits and their syn-orogenic sources. Many of these modelled features of syn-orogenic gold emplacement and varying amounts of orogen-parallel detrital gold transport can be recognised in the Miocene to Recent New Zealand oblique convergent orogen. These processes contribute little gold to major placer goldfields, which require more long-term recycling and placer gold concentration. Most eroded syn

  16. Nearshore shore-oblique bars, gravel outcrops, and their correlation to shoreline change

    USGS Publications Warehouse

    Schupp, C.A.; McNinch, J.E.; List, J.H.

    2006-01-01

    This study demonstrates the physical concurrence of shore-oblique bars and gravel outcrops in the surf zone along the northern Outer Banks of North Carolina. These subaqueous features are spatially correlated with shoreline change at a range of temporal and spatial scales. Previous studies have noted the existence of beach-surf zone interactions, but in general, relationships between nearshore geological features and coastal change are poorly understood. These new findings should be considered when exploring coastal zone dynamics and developing predictive engineering models.The surf zone and nearshore region of the Outer Banks is predominantly planar and sandy, but there are several discrete regions with shore-oblique bars and interspersed gravel outcrops. These bar fields have relief up to 3 m, are several kilometers wide, and were relatively stationary over a 1.5 year survey period; however, the shoreward component of the bar field does exhibit change during this time frame. All gravel outcrops observed in the study region, a 40 km longshore length, were located adjacent to a shore-oblique bar, in a trough that had width and length similar to that of the associated bar. Seismic surveys show that the outcrops are part of a gravel stratum underlying the active surface sand layer.Cross-correlation analyses demonstrate high correlation of monthly and multi-decadal shoreline change rates with the adjacent surf-zone bathymetry and sediment distribution. Regionally, areas with shore-oblique bars and gravel outcrops are correlated with on-shore areas of high short-term shoreline variability and high long-term shoreline change rates. The major peaks in long-term shoreline erosion are onshore of shore-oblique bars, but not all areas with high rates of long-term shoreline change are associated with shore-oblique bars and troughs.

  17. Monte Carlo simulations of particle acceleration at oblique shocks: Including cross-field diffusion

    NASA Technical Reports Server (NTRS)

    Baring, M. G.; Ellison, D. C.; Jones, F. C.

    1995-01-01

    The Monte Carlo technique of simulating diffusive particle acceleration at shocks has made spectral predictions that compare extremely well with particle distributions observed at the quasi-parallel region of the earth's bow shock. The current extension of this work to compare simulation predictions with particle spectra at oblique interplanetary shocks has required the inclusion of significant cross-field diffusion (strong scattering) in the simulation technique, since oblique shocks are intrinsically inefficient in the limit of weak scattering. In this paper, we present results from the method we have developed for the inclusion of cross-field diffusion in our simulations, namely model predictions of particle spectra downstream of oblique subluminal shocks. While the high-energy spectral index is independent of the shock obliquity and the strength of the scattering, the latter is observed to profoundly influence the efficiency of injection of cosmic rays into the acceleration process.

  18. Transforming clinical practice guidelines and clinical pathways into fast-and-frugal decision trees to improve clinical care strategies.

    PubMed

    Djulbegovic, Benjamin; Hozo, Iztok; Dale, William

    2018-02-27

    Contemporary delivery of health care is inappropriate in many ways, largely due to suboptimal Q5 decision-making. A typical approach to improve practitioners' decision-making is to develop evidence-based clinical practice guidelines (CPG) by guidelines panels, who are instructed to use their judgments to derive practice recommendations. However, mechanisms for the formulation of guideline judgments remains a "black-box" operation-a process with defined inputs and outputs but without sufficient knowledge of its internal workings. Increased explicitness and transparency in the process can be achieved by implementing CPG as clinical pathways (CPs) (also known as clinical algorithms or flow-charts). However, clinical recommendations thus derived are typically ad hoc and developed by experts in a theory-free environment. As any recommendation can be right (true positive or negative), or wrong (false positive or negative), the lack of theoretical structure precludes the quantitative assessment of the management strategies recommended by CPGs/CPs. To realize the full potential of CPGs/CPs, they need to be placed on more solid theoretical grounds. We believe this potential can be best realized by converting CPGs/CPs within the heuristic theory of decision-making, often implemented as fast-and-frugal (FFT) decision trees. This is possible because FFT heuristic strategy of decision-making can be linked to signal detection theory, evidence accumulation theory, and a threshold model of decision-making, which, in turn, allows quantitative analysis of the accuracy of clinical management strategies. Fast-and-frugal provides a simple and transparent, yet solid and robust, methodological framework connecting decision science to clinical care, a sorely needed missing link between CPGs/CPs and patient outcomes. We therefore advocate that all guidelines panels express their recommendations as CPs, which in turn should be converted into FFTs to guide clinical care. © 2018 John Wiley

  19. Graphic Representations as Tools for Decision Making.

    ERIC Educational Resources Information Center

    Howard, Judith

    2001-01-01

    Focuses on the use of graphic representations to enable students to improve their decision making skills in the social studies. Explores three visual aids used in assisting students with decision making: (1) the force field; (2) the decision tree; and (3) the decision making grid. (CMK)

  20. Accuracy Analysis for Automatic Orientation of a Tumbling Oblique Viewing Sensor System

    NASA Astrophysics Data System (ADS)

    Stebner, K.; Wieden, A.

    2014-03-01

    Dynamic camera systems with moving parts are difficult to handle in photogrammetric workflow, because it is not ensured that the dynamics are constant over the recording period. Minimum changes of the camera's orientation greatly influence the projection of oblique images. In this publication these effects - originating from the kinematic chain of a dynamic camera system - are analysed and validated. A member of the Modular Airborne Camera System family - MACS-TumbleCam - consisting of a vertical viewing and a tumbling oblique camera was used for this investigation. Focus is on dynamic geometric modeling and the stability of the kinematic chain. To validate the experimental findings, the determined parameters are applied to the exterior orientation of an actual aerial image acquisition campaign using MACS-TumbleCam. The quality of the parameters is sufficient for direct georeferencing of oblique image data from the orientation information of a synchronously captured vertical image dataset. Relative accuracy for the oblique data set ranges from 1.5 pixels when using all images of the image block to 0.3 pixels when using only adjacent images.

  1. Effects of excimer laser illumination on microdrilling into an oblique polymer surface

    NASA Astrophysics Data System (ADS)

    Wu, Chih-Yang; Shu, Chun-Wei; Yeh, Zhi-Chang

    2006-08-01

    In this work, we present the experimental results of micromachining into polymethy-methacrylate exposed to oblique KrF excimer laser beams. The results of low-aspect-ratio ablations show that the ablation rate decreases monotonously with the increase of incident angle for various fluences. The ablation rate of high-aspect-ratio drilling with opening center on the focal plane is almost independent of incident angles and is less than that of low-aspect-ratio ablation. The results of high-aspect-ratio ablations show that the openings of the holes at a distance from the focal plane are enlarged and their edges are blurred. Besides, the depth of a hole in the samples oblique to the laser beam at a distance from the focal plane decreases with the increase of the distance from the focal plane. The number of deep holes generated by oblique laser beams through a matrix of apertures decreases with the increase of incident angle. Those phenomena reveal the influence of the local light intensity on microdrilling into an oblique surface.

  2. Flexibility and fatigue evaluation of oblique as compared with anterior lumbar interbody cages with integrated endplate fixation.

    PubMed

    Freeman, Andrew L; Camisa, William J; Buttermann, Glenn R; Malcolm, James R

    2016-01-01

    This study was undertaken to quantify the in vitro range of motion (ROM) of oblique as compared with anterior lumbar interbody devices, pullout resistance, and subsidence in fatigue. Anterior and oblique cages with integrated plate fixation (IPF) were tested using lumbar motion segments. Flexibility tests were conducted on the intact segments, cage, cage + IPF, and cage + IPF + pedicle screws (6 anterior, 7 oblique). Pullout tests were then performed on the cage + IPF. Fatigue testing was conducted on the cage + IPF specimens for 30,000 cycles. No ROM differences were observed in any test group between anterior and oblique cage constructs. The greatest reduction in ROM was with supplemental pedicle screw fixation. Peak pullout forces were 637 ± 192 N and 651 ± 127 N for the anterior and oblique implants, respectively. The median cage subsidence was 0.8 mm and 1.4 mm for the anterior and oblique cages, respectively. Anterior and oblique cages similarly reduced ROM in flexibility testing, and the integrated fixation prevented device displacement. Subsidence was minimal during fatigue testing, most of which occurred in the first 2500 cycles.

  3. Including public-health benefits of trees in urban-forestry decision making

    Treesearch

    Geoffrey H. Donovan

    2017-01-01

    Research demonstrating the biophysical benefits of urban trees are often used to justify investments in urban forestry. Far less emphasis, however, is placed on the non-bio-physical benefits such as improvements in public health. Indeed, the public-health benefits of trees may be significantly larger than the biophysical benefits, and, therefore, failure to account for...

  4. Oblique collision of dust acoustic solitons in a strongly coupled dusty plasma

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Boruah, A.; Sharma, S. K., E-mail: sumita-sharma82@yahoo.com; Bailung, H.

    2015-09-15

    The oblique collision between two equal amplitude dust acoustic solitons is observed in a strongly coupled dusty plasma. The solitons are subjected to oblique interaction at different colliding angles. We observe a resonance structure during oblique collision at a critical colliding angle which is described by the idea of three wave resonance interaction modeled by Kadomtsev-Petviashvili equation. After collision, the solitons preserve their identity. The amplitude of the resultant wave formed during interaction is measured for different collision angles as well as for different colliding soliton amplitudes. At resonance, the maximum amplitude of the new soliton formed is nearly 3.7more » times the initial soliton amplitude.« less

  5. The conceptual design of a Mach 2 Oblique Flying Wing supersonic transport

    NASA Technical Reports Server (NTRS)

    Vandervelden, Alexander J. M.

    1989-01-01

    This paper is based on a performance and economics study of a Mach two oblique flying wing transport aircraft that is to replace the B747B. In order to fairly compare our configuration with the B747B an equal structural technology level is assumed. It will be shown that the oblique flying wing configuration will equal or outperform the B747 in speed, economy and comfort while a modern stability and control system will balance the aircraft and smooth out gusts. The aircraft is designed to comply with the FAR25 airworthiness requirements and FAR36 stage 3 noise regulations. Geometry, aerodynamics, stability and control parameters of the oblique flying wing transport are discussed.

  6. Migration of the Cratering Flow-Field Center with Implications for Scaling Oblique Impacts

    NASA Technical Reports Server (NTRS)

    Anderson, J. L. B.; Schultz, P. H.; Heineck, J. T.

    2004-01-01

    Crater-scaling relationships are used to predict many cratering phenomena such as final crater diameter and ejection speeds. Such nondimensional relationships are commonly determined from experimental impact and explosion data. Almost without exception, these crater-scaling relationships have used data from vertical impacts (90 deg. to the horizontal). The majority of impact craters, however, form by impacts at angles near 45 deg. to the horizontal. While even low impact angles result in relatively circular craters in sand targets, the effects of impact angle have been shown to extend well into the excavation stage of crater growth. Thus, the scaling of oblique impacts needs to be investigated more thoroughly in order to quantify fully how impact angle affects ejection speed and angle. In this study, ejection parameters from vertical (90 deg.) and 30 deg. oblique impacts are measured using three-dimensional particle image velocimetry (3D PIV) at the NASA Ames Vertical Gun Range (AVGR). The primary goal is to determine the horizontal migration of the cratering flow-field center (FFC). The location of the FFC at the time of ejection controls the scaling of oblique impacts. For vertical impacts the FFC coincides with the impact point (IP) and the crater center (CC). Oblique impacts reflect a more complex, horizontally migrating flow-field. A single, stationary point-source model cannot be used accurately to describe the evolution of the ejection angles from oblique impacts. The ejection speeds for oblique impacts also do not follow standard scaling relationships. The migration of the FFC needs to be understood and incorporated into any revised scaling relationships.

  7. Classification tree for the assessment of sedentary lifestyle among hypertensive.

    PubMed

    Castelo Guedes Martins, Larissa; Venícios de Oliveira Lopes, Marcos; Gomes Guedes, Nirla; Paixão de Menezes, Angélica; de Oliveira Farias, Odaleia; Alves Dos Santos, Naftale

    2016-04-01

    To develop a classification tree of clinical indicators for the correct prediction of the nursing diagnosis "Sedentary lifestyle" (SL) in people with high blood pressure (HTN). A cross-sectional study conducted in an outpatient care center specializing in high blood pressure and Mellitus diabetes located in northeastern Brazil. The sample consisted of 285 people between 19 and 59 years old diagnosed with high blood pressure and was applied an interview and physical examination, obtaining socio-demographic information, related factors and signs and symptoms that made the defining characteristics for the diagnosis under study. The tree was generated using the CHAID algorithm (Chi-square Automatic Interaction Detection). The construction of the decision tree allowed establishing the interactions between clinical indicators that facilitate a probabilistic analysis of multiple situations allowing quantify the probability of an individual presenting a sedentary lifestyle. The tree included the clinical indicator Choose daily routine without exercise as the first node. People with this indicator showed a probability of 0.88 of presenting the SL. The second node was composed of the indicator Does not perform physical activity during leisure, with 0.99 probability of presenting the SL with these two indicators. The predictive capacity of the tree was established at 69.5%. Decision trees help nurses who care HTN people in decision-making in assessing the characteristics that increase the probability of SL nursing diagnosis, optimizing the time for diagnostic inference.

  8. A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Soner Yorgun, M.; Rood, Richard B.

    An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

  9. A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

    DOE PAGES

    Soner Yorgun, M.; Rood, Richard B.

    2016-11-11

    An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

  10. Evolving optimised decision rules for intrusion detection using particle swarm paradigm

    NASA Astrophysics Data System (ADS)

    Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

    2012-12-01

    The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

  11. Activities of the Vastus Lateralis and Vastus Medialis Oblique Muscles during Squats on Different Surfaces.

    PubMed

    Hyong, In Hyouk; Kang, Jong Ho

    2013-08-01

    [Purpose] The purpose of the present study was to examine the effects of squat exercises performed on different surfaces on the activity of the quadriceps femoris muscle in order to provide information on support surfaces for effective squat exercises. [Subjects and Method] Fourteen healthy subjects performed squat exercises for five seconds each on three different support surfaces: hard plates, foam, and rubber air discs. Their performance was measured using electromyography. As the subjects performed the squat exercises on each surface, data on the activity of the vastus medialis oblique and the vastus lateralis, and the vastus medials oblique/vastus lateralis ratio, were collected. [Results] The activity of the vastus medialis oblique and the vastus medialis oblique/vastus lateralis ratio were found to be statistically significantly higher on rubber air discs than when the squats were performed on hard plates or foam. [Conclusion] To activate the vastus medialis obilique, and to enhance the vastus medialis oblique/vastus lateralis ratio, unstable surfaces that are highly unstable should be selected.

  12. An oblique muscle hematoma as a rare cause of severe abdominal pain: a case report.

    PubMed

    Shimodaira, Masanori; Kitano, Tomohiro; Kibata, Minoru; Shirahata, Kumiko

    2013-01-18

    Abdominal wall hematomas are an uncommon cause of acute abdominal pain and are often misdiagnosed. They are more common in elderly individuals, particularly in those under anticoagulant therapy. Most abdominal wall hematomas occur in the rectus sheath, and hematomas within the oblique muscle are very rare and are poorly described in the literature. Here we report the case of an oblique muscle hematoma in a middle-aged patient who was not under anticoagulant therapy. A 42-year-old Japanese man presented with a painful, enlarging, lateral abdominal wall mass, which appeared after playing baseball. Abdominal computed tomography and ultrasonography showed a large soft tissue mass located in the patient's left internal oblique muscle. A diagnosis of a lateral oblique muscle hematoma was made and the patient was treated conservatively. Physicians should consider an oblique muscle hematoma during the initial differential diagnosis of pain in the lateral abdominal wall even in the absence of anticoagulant therapy or trauma.

  13. Oblique contractional reactivation of inherited heterogeneities: Cause for arcuate orogens

    PubMed Central

    Sokoutis, D.; Willingshofer, E.; Brun, J.‐P.; Gueydan, F.; Cloetingh, S.

    2017-01-01

    Abstract We use lithospheric‐scale analog models to study the reactivation of pre‐existing heterogeneities under oblique shortening and its relation to the origin of arcuate orogens. Reactivation of inherited rheological heterogeneities is an important mechanism for localization of deformation in compressional settings and consequent initiation of contractional structures during orogenesis. However, the presence of an inherited heterogeneity in the lithosphere is in itself not sufficient for its reactivation once the continental lithosphere is shortened. The heterogeneity orientation is important in determining if reactivation occurs and to which extent. This study aims at giving insights on this process by means of analog experiments in which a linear lithospheric heterogeneity trends with various angles to the shortening direction. In particular, the key parameter investigated is the orientation (angle α) of a strong domain (SD) with respect to the shortening direction. Experimental results show that angles α ≥ 75° (high obliquity) allow for reactivation along the entire SD and the development of a linear orogen. For α ≤ 60° (low obliquity) the models are characterized by the development of an arcuate orogen, with the SD remaining partially non‐reactivated. These results provide a new mechanism for the origin of some arcuate orogens, in which orocline formation was not driven by indentation or subduction processes, but by oblique shortening of inherited heterogeneities, as exemplified by the Ouachita orogen of the southern U.S. PMID:28670046

  14. Decision tree analysis as a supplementary tool to enhance histomorphological differentiation when distinguishing human from non-human cranial bone in both burnt and unburnt states: A feasibility study.

    PubMed

    Simmons, T; Goodburn, B; Singhrao, S K

    2016-01-01

    This feasibility study was undertaken to describe and record the histological characteristics of burnt and unburnt cranial bone fragments from human and non-human bones. Reference series of fully mineralized, transverse sections of cranial bone, from all variables and specimen states, were prepared by manual cutting and semi-automated grinding and polishing methods. A photomicrograph catalogue reflecting differences in burnt and unburnt bone from human and non-humans was recorded and qualitative analysis was performed using an established classification system based on primary bone characteristics. The histomorphology associated with human and non-human samples was, for the main part, preserved following burning at high temperature. Clearly, fibro-lamellar complex tissue subtypes, such as plexiform or laminar primary bone, were only present in non-human bones. A decision tree analysis based on histological features provided a definitive identification key for distinguishing human from non-human bone, with an accuracy of 100%. The decision tree for samples where burning was unknown was 96% accurate, and multi-step classification to taxon was possible with 100% accuracy. The results of this feasibility study strongly suggest that histology remains a viable alternative technique if fragments of cranial bone require forensic examination in both burnt and unburnt states. The decision tree analysis may provide an additional but vital tool to enhance data interpretation. Further studies are needed to assess variation in histomorphology taking into account other cranial bones, ontogeny, species and burning conditions. © The Author(s) 2015.

  15. Reverse design of a bull's eye structure for oblique incidence and wider angular transmission efficiency.

    PubMed

    Yamada, Akira; Terakawa, Mitsuhiro

    2015-04-10

    We present a design method of a bull's eye structure with asymmetric grooves for focusing oblique incident light. The design method is capable of designing transmission peaks to a desired oblique angle with capability of collecting light from a wider range of angles. The bull's eye groove geometry for oblique incidence is designed based on the electric field intensity pattern around an isolated subwavelength aperture on a thin gold film at oblique incidence, calculated by the finite difference time domain method. Wide angular transmission efficiency is successfully achieved by overlapping two different bull's eye groove patterns designed with different peak angles. Our novel design method would overcome the angular limitations of the conventional methods.

  16. Effect of oblique channel on discharge characteristics of 200-W Hall thruster

    NASA Astrophysics Data System (ADS)

    Ding, Yongjie; Peng, Wuji; Sun, Hezhi; Xu, Yu; Wei, Liqiu; Li, Hong; Zeng, Ming; Wang, Fufeng; Yu, Daren

    2017-02-01

    In an experiment involving a 200-W Hall thruster, partial ionization occurs in the plume area because of the extrapolation of the magnetic field. To improve the thruster performance, the concept of an oblique channel is proposed for improving the ionization degree in the plume area. Calculations performed using a Particle-in-cell (PIC) simulator and the experimental results both show that an oblique channel structure can reduce the wall loss. Compared with a straight channel under similar conditions of the discharge voltage and current, the ionization degree in the plume area, thrust, specific impulse, propellant utilization, and anode efficiency are improved by ˜20%. The oblique channel is an important design consideration for improving the partial ionization of the plume area in the thruster.

  17. Can activity within the external abdominal oblique be measured using real-time ultrasound imaging?

    PubMed

    John, E K; Beith, I D

    2007-11-01

    Differences in the function of the anterolateral abdominal muscles have been the subject of much investigation, but primarily using electromyography. Recently changes in thickness of transversus abdominis and internal oblique measured from real-time ultrasound images have been shown to represent activity within these muscles. However it is still unclear if such a change in thickness in external oblique similarly represents activity within that muscle. The purpose of this study was to investigate the relationship between change in thickness and muscle activity in the external oblique using real-time ultrasound and surface electromyography. Simultaneous measurements of electromyography and real-time ultrasound images of external oblique were studied in up to 24 subjects during two tasks compared to the muscle at rest (1) isometric trunk rotation and (2) drawing in the lower abdomen. Changes in muscle thickness correlated significantly with electromyography during isometric trunk rotation in the majority of subjects but with a significant difference between subjects. In contrast, the relationship between change in thickness and electrical activity in the muscle when drawing in the lower abdomen was significant in less than 50% of subjects and the muscle often got thinner. Thickness changes of external oblique can be used as a valid indicator of electromyography activity during isometric trunk rotation, though the relationship is not as good as previously published data for transversus abdominis. Thickness changes of external oblique measured during lower abdominal drawing in cannot be used to detect activity within this muscle.

  18. Construction and validation of a decision tree for treating metabolic acidosis in calves with neonatal diarrhea

    PubMed Central

    2012-01-01

    Background The aim of the present prospective study was to investigate whether a decision tree based on basic clinical signs could be used to determine the treatment of metabolic acidosis in calves successfully without expensive laboratory equipment. A total of 121 calves with a diagnosis of neonatal diarrhea admitted to a veterinary teaching hospital were included in the study. The dosages of sodium bicarbonate administered followed simple guidelines based on the results of a previous retrospective analysis. Calves that were neither dehydrated nor assumed to be acidemic received an oral electrolyte solution. In cases in which intravenous correction of acidosis and/or dehydration was deemed necessary, the provided amount of sodium bicarbonate ranged from 250 to 750 mmol (depending on alterations in posture) and infusion volumes from 1 to 6.25 liters (depending on the degree of dehydration). Individual body weights of calves were disregarded. During the 24 hour study period the investigator was blinded to all laboratory findings. Results After being lifted, many calves were able to stand despite base excess levels below −20 mmol/l. Especially in those calves, metabolic acidosis was undercorrected with the provided amount of 500 mmol sodium bicarbonate, which was intended for calves standing insecurely. In 13 calves metabolic acidosis was not treated successfully as defined by an expected treatment failure or a measured base excess value below −5 mmol/l. By contrast, 24 hours after the initiation of therapy, a metabolic alkalosis was present in 55 calves (base excess levels above +5 mmol/l). However, the clinical status was not affected significantly by the metabolic alkalosis. Conclusions Assuming re-evaluation of the calf after 24 hours, the tested decision tree can be recommended for the use in field practice with minor modifications. Calves that stand insecurely and are not able to correct their position if pushed require higher doses of

  19. A decision tree-based on-line preventive control strategy for power system transient instability prevention

    NASA Astrophysics Data System (ADS)

    Xu, Yan; Dong, Zhao Yang; Zhang, Rui; Wong, Kit Po

    2014-02-01

    Maintaining transient stability is a basic requirement for secure power system operations. Preventive control deals with modifying the system operating point to withstand probable contingencies. In this article, a decision tree (DT)-based on-line preventive control strategy is proposed for transient instability prevention of power systems. Given a stability database, a distance-based feature estimation algorithm is first applied to identify the critical generators, which are then used as features to develop a DT. By interpreting the splitting rules of DT, preventive control is realised by formulating the rules in a standard optimal power flow model and solving it. The proposed method is transparent in control mechanism, on-line computation compatible and convenient to deal with multi-contingency. The effectiveness and efficiency of the method has been verified on New England 10-machine 39-bus test system.

  20. Subduction obliquity as a prime indicator for geotherm in subduction zone

    NASA Astrophysics Data System (ADS)

    Plunder, Alexis; Thieulot, Cédric; van Hinsbergen, Douwe

    2016-04-01

    The geotherm of a subduction zone is thought to vary as a function of subduction rate and the age of the subducting lithosphere. Along a single subduction zone the rate of subduction can strongly vary due to changes in the angle between the trench and the plate convergence vector, namely the subduction obliquity. This phenomenon is observed all around the Pacific (i.e., Marianna, South America, Aleutian…). However due to observed differences in subducting lithosphere age or lateral convergence rate in nature, the quantification of temperature variation due to obliquity is not obvious. In order to investigate this effect, 3D generic numerical models were carried out using the finite element code ELEFANT. We designed a simplified setup to avoid interaction with other parameters. An ocean/ocean subduction setting was chosen and the domain is represented by a 800 × 300 × 200 km Cartesian box. The trench geometry is prescribed by means of a simple arc-tangent function. Velocity of the subducting lithosphere is prescribed using the analytical solution for corner flow and only the energy conservation equation is solved in the domain. Results are analysed after steady state is reached. First results show that the effect of the trench curvature on the geotherm with respect to the convergence direction is not negligible. A small obliquity yields isotherms which are very slightly deflected upwards where the obliquity is maximum. With an angle of ˜30°, the isotherms are deflected upwards of about 10 kilometres. Strong obliquity (i.e., angles from 60° to almost 90°) reveal extreme effects of the position of the isotherms. Further model will include other parameter as the dip of the slab and convergence rate to highlight their relative influence on the geotherm of subduction zone.

  1. A dynamic fault tree model of a propulsion system

    NASA Technical Reports Server (NTRS)

    Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila

    2006-01-01

    We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.

  2. Prediction of heart disease using apache spark analysing decision trees and gradient boosting algorithm

    NASA Astrophysics Data System (ADS)

    Chugh, Saryu; Arivu Selvan, K.; Nadesh, RK

    2017-11-01

    Numerous destructive things influence the working arrangement of human body as hypertension, smoking, obesity, inappropriate medication taking which causes many contrasting diseases as diabetes, thyroid, strokes and coronary diseases. The impermanence and horribleness of the environment situation is also the reason for the coronary disease. The structure of Apache start relies on the evolution which requires gathering of the data. To break down the significance of use programming focused on data structure the Apache stop ought to be utilized and it gives various central focuses as it is fast in light as it uses memory worked in preparing. Apache Spark continues running on dispersed environment and chops down the data in bunches giving a high profitability rate. Utilizing mining procedure as a part of the determination of coronary disease has been exhaustively examined indicating worthy levels of precision. Decision trees, Neural Network, Gradient Boosting Algorithm are the various apache spark proficiencies which help in collecting the information.

  3. Activities of the Vastus Lateralis and Vastus Medialis Oblique Muscles during Squats on Different Surfaces

    PubMed Central

    Hyong, In Hyouk; Kang, Jong Ho

    2013-01-01

    [Purpose] The purpose of the present study was to examine the effects of squat exercises performed on different surfaces on the activity of the quadriceps femoris muscle in order to provide information on support surfaces for effective squat exercises. [Subjects and Method] Fourteen healthy subjects performed squat exercises for five seconds each on three different support surfaces: hard plates, foam, and rubber air discs. Their performance was measured using electromyography. As the subjects performed the squat exercises on each surface, data on the activity of the vastus medialis oblique and the vastus lateralis, and the vastus medials oblique/vastus lateralis ratio, were collected. [Results] The activity of the vastus medialis oblique and the vastus medialis oblique/vastus lateralis ratio were found to be statistically significantly higher on rubber air discs than when the squats were performed on hard plates or foam. [Conclusion] To activate the vastus medialis obilique, and to enhance the vastus medialis oblique/vastus lateralis ratio, unstable surfaces that are highly unstable should be selected. PMID:24259884

  4. Decision Tree Analysis of Traditional Risk Factors of Carotid Atherosclerosis and a Cutpoint-Based Prevention Strategy

    PubMed Central

    Lv, Lihong; Xiao, Yufei; Tu, Jiangfeng; Tao, Lisha; Wu, Jiaqi; Tang, Xiaoxiao; Pan, Wensheng

    2014-01-01

    Background Reducing the exposure to risk factors for the prevention of cardio-cerebral vascular disease is a crucial issue. Few reports have described practical interventions for preventing cardiovascular disease in different genders and age groups, particularly detailed and specific cutpoint-based prevention strategies. Methods We collected the health examination data of 5822 subjects between 20 and 80 years of age. The administration of medical questionnaires and physical examinations and the measurement of blood pressure, fasting plasma glucose (FPG) and blood lipids [total cholesterol (TC), triglycerides (TG), high density lipoprotein–cholesterol (HDL-C), and low density lipoprotein-cholesterol (LDL-C)] were performed by physicians. Carotid ultrasound was performed to examine the carotid intima-media thickness (CIMT), which was defined as carotid atherosclerosis when CIMT ≥0.9 mm. Decision tree analysis was used to screen for the most important risk factors for carotid atherosclerosis and to identify the relevant cutpoints. Results In the study population, the incidence of carotid atherosclerosis was 12.20% (men: 14.10%, women: 9.20%). The statistical analysis showed significant differences in carotid atherosclerosis incidence between different genders (P<0.0001) and age groups (P<0.001). The decision tree analysis showed that in men, the most important traditional risk factors for carotid atherosclerosis were TC (cutpoint [CP]: 6.31 mmol/L) between the ages of 20–40 and FPG (CP: 5.79 mmol/L) between the ages of 41–59. By comparison, LDL-C (CP: 4.27 mmol/L) became the major risk factor when FPG ≤5.79 mmol/L. FPG (CP: 5.52 mmol/L) and TG (CP: 1.51 mmol/L) were the most important traditional risk factors for women between 20–40 and 41–59 years of age, respectively. Conclusion Traditional risk factors and relevant cutpoints were not identical in different genders and age groups. A specific gender and age group-based cutpoint strategy might contribute

  5. Reduced magnetohydrodynamic theory of oblique plasmoid instabilities

    NASA Astrophysics Data System (ADS)

    Baalrud, S. D.; Bhattacharjee, A.; Huang, Y.-M.

    2012-02-01

    The three-dimensional nature of plasmoid instabilities is studied using the reduced magnetohydrodynamic equations. For a Harris equilibrium with guide field, represented by Bo=Bpotanh(x /λ)ŷ+Bzoẑ, a spectrum of modes are unstable at multiple resonant surfaces in the current sheet, rather than just the null surface of the poloidal field Byo(x)=Bpotanh(x /λ), which is the only resonant surface in 2D or in the absence of a guide field. Here, Bpo is the asymptotic value of the equilibrium poloidal field, Bzo is the constant equilibrium guide field, and λ is the current sheet width. Plasmoids on each resonant surface have a unique angle of obliquity θ ≡arctan(kz/ky). The resonant surface location for angle θ is xs=λarctanh(μ), where μ =tanθBzo/Bpo and the existence of a resonant surface requires |θ |oblique, i.e., θ ≠0 and xs≠0, in the constant-ψ regime, but parallel, i.e., θ =0 and xs=0, in the nonconstant-ψ regime. For a fixed angle of obliquity, the most unstable wavenumber lies at the intersection of the constant-ψ and nonconstant-ψ regimes. The growth rate of this mode is γmax/Γo≃SL1/4(1-μ4)1/2, in which Γo=VA/L, VA is the Alfvén speed, L is the current sheet length, and SL is the Lundquist number. The number of plasmoids scales as N ~SL3/8(1-μ2)-1/4(1+μ2)3/4.

  6. Histologic consequences of inferior oblique anastomosis to denervated lateral rectus muscle.

    PubMed

    Christiansen, S; Madhat, M; Baker, R S

    1987-01-01

    Secondary muscular neurotization has been proposed as a means of restoring contractility to paretic extraocular muscle. We studied this technique by anastomosing healthy inferior oblique muscle to lateral rectus muscle that had been denervated either orbitally or intracranially in 20 dogs. Nerve and muscle fiber growth from the inferior oblique to the lateral rectus was demonstrated but no new neuromuscular junctions were formed. Regeneration of the lesioned sixth nerve occurred frequently and may explain the restoration of function claimed after this procedure.

  7. SouthWest view; Station Building north elevation, oblique North ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    South-West view; Station Building - north elevation, oblique - North Philadelphia Station, 2900 North Broad Street, on northwest corner of Broad Street & Glenwood Avenue, Philadelphia, Philadelphia County, PA

  8. SouthEast view; Station Building north elevation, oblique North ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    South-East view; Station Building - north elevation, oblique - North Philadelphia Station, 2900 North Broad Street, on northwest corner of Broad Street & Glenwood Avenue, Philadelphia, Philadelphia County, PA

  9. OBLIQUE VIEW, REAR ELEVATION, LOOKING NORTHEAST Mountain Home Air ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    OBLIQUE VIEW, REAR ELEVATION, LOOKING NORTHEAST - Mountain Home Air Force Base 1958 Senior Officers' Housing, General's Residence, Rabeni Street (originally Ivy Street), Mountain Home, Elmore County, ID

  10. The Resilience of Kepler Multi-systems to Stellar Obliquity

    NASA Astrophysics Data System (ADS)

    Spalding, Christopher; Marx, Noah W.; Batygin, Konstantin

    2018-04-01

    The Kepler mission and its successor K2 have brought forth a cascade of transiting planets. Many of these planetary systems exhibit multiple transiting members. However, a large fraction possesses only a single transiting planet. This high abundance of singles, dubbed the "Kepler Dichotomy," has been hypothesized to arise from significant mutual inclinations between orbits in multi-planet systems. Alternatively, the single-transiting population truly possesses no other planets in the system, but the true origin of the overabundance of single systems remains unresolved. In this work, we propose that planetary systems typically form with a coplanar, multiple-planetary architecture, but that quadrupolar gravitational perturbations from their rapidly-rotating host star subsequently disrupt this primordial coplanarity. We demonstrate that, given sufficient stellar obliquity, even systems beginning with 2 planetary constituents are susceptible to dynamical instability soon after planet formation, as a result of the stellar quadrupole moment. This mechanism stands as a widespread, yet poorly explored pathway toward planetary system instability. Moreover, by requiring that observed multi-systems remain coplanar on Gyr timescales, we are able to place upper limits on the stellar obliquity in systems such as K2-38 (obliquity < 20 degrees), where other methods of measuring spin-orbit misalignment are not currently available.

  11. Oblique sounding using the DPS-4D stations in Europe

    NASA Astrophysics Data System (ADS)

    Mosna, Zbysek; Kouba, Daniel; Koucka Knizova, Petra; Arikan, Feza; Arikan, Orhan; Gok, Gokhan; Rejfek, Lubos

    2016-07-01

    The DPS-4D Digisondes are capable of detection of echoes from neighbouring European stations. Currently, a campaign with high-temporal resolution of 5 min is being run. Further, ionograms from regular vertical sounding with 15 min resolution provide us with oblique reflections together with vertical reflections. We analyzed profiles of electron concentration and basic ionospheric parameters derived from the ionograms. We compared results derived from reflections from the ionosphere above the stations (vertical sounding) with information derived from oblique reflections between the stations. This study is supported by the Joint TUBITAK 114E092 and AS CR 14/001 projects.

  12. Teetering Stars: Resonant Excitation of Stellar Obliquities by Hot and Warm Jupiters with External Companions

    NASA Astrophysics Data System (ADS)

    Anderson, Kassandra; Lai, Dong

    2018-04-01

    Stellar spin-orbit misalignments (obliquities) in hot Jupiter systems have been extensively probed in recent years thanks to Rossiter-McLaughlin observations. Such obliquities may reveal clues about hot Jupiter dynamical and migration histories. Common explanations for generating stellar obliquities include high-eccentricity migration, or primordial disk misalignment. This talk investigates another mechanism for producing stellar spin-orbit misalignments in systems hosting a close-in giant planet with an external, inclined planetary companion. Spin-orbit misalignment may be excited due to a secular resonance, occurring when the precession rate of the stellar spin axis (due to the inner orbit) becomes comparable to the precession rate of the inner orbital axis (due to the outer companion). Due to the spin-down of the host star via magnetic braking, this resonance may be achieved at some point during the star's main sequence lifetime for a wide range of giant planet masses and orbital architectures. We focus on both hot Jupiters (with orbital periods less than ten days) and warm Jupiters (with orbital periods around tens of days), and identify the outer perburber properties needed to generate substantial obliquities via resonant excitation, in terms of mass, separation, and inclination. For hot Jupiters, the stellar spin axis is strongly coupled to the orbital axis, and resonant excitation of obliquity requires a close perturber, located within 1-2 AU. For warm Jupiters, the spin and orbital axes are more weakly coupled, and the resonance may be achieved for more distant perturbers (at several to tens of AU). Resonant excitation of the stellar obliquity is accompanied by a decrease in the planets' mutual orbital inclination, and can thus erase high mutual inclinations in two-planet systems. Since many warm Jupiters are known to have outer planetary companions at several AU or beyond, stellar obliquities in warm Jupiter systems may be common, regardless of the

  13. NorthWest view; Station Building south (front) elevation, oblique ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    North-West view; Station Building - south (front) elevation, oblique - North Philadelphia Station, 2900 North Broad Street, on northwest corner of Broad Street & Glenwood Avenue, Philadelphia, Philadelphia County, PA

  14. NorthEast view; Station Building south (front) elevation, oblique ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    North-East view; Station Building - south (front) elevation, oblique - North Philadelphia Station, 2900 North Broad Street, on northwest corner of Broad Street & Glenwood Avenue, Philadelphia, Philadelphia County, PA

  15. OBLIQUE VIEW, REAR ELEVATION, LOOKING SOUTHSOUTHWEST Mountain Home Air ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    OBLIQUE VIEW, REAR ELEVATION, LOOKING SOUTH-SOUTHWEST - Mountain Home Air Force Base 1958 Senior Officers' Housing, General's Residence, Rabeni Street (originally Ivy Street), Mountain Home, Elmore County, ID

  16. OBLIQUE VIEW, FRONT ELEVATION, LOOKING WESTSOUTHWEST Mountain Home Air ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    OBLIQUE VIEW, FRONT ELEVATION, LOOKING WEST-SOUTHWEST - Mountain Home Air Force Base 1958 Senior Officers' Housing, General's Residence, Rabeni Street (originally Ivy Street), Mountain Home, Elmore County, ID

  17. Oblique view of southeast corner; camera facing northwest. Mare ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Oblique view of southeast corner; camera facing northwest. - Mare Island Naval Shipyard, Defense Electronics Equipment Operating Center, I Street, terminus west of Cedar Avenue, Vallejo, Solano County, CA

  18. Oblique Sagittal Images Prevent Underestimation of the Neuroforaminal Stenosis Grade Caused by Disc Herniation in Cervical Spine MRI.

    PubMed

    Kintzelé, Laurent; Rehnitz, Christoph; Kauczor, Hans-Ulrich; Weber, Marc-André

    2018-06-06

     To identify whether standard sagittal MRI images result in underestimation of the neuroforaminal stenosis grade compared to oblique sagittal MRI images in patients with cervical spine disc herniation.  74 patients with a total of 104 cervical disc herniations compromising the corresponding nerve root were evaluated. Neuroforaminal stenosis grades were evaluated in standard and oblique sagittal images by one senior and one resident radiologist experienced in musculoskeletal imaging. Oblique images were angled 30° towards the standard sagittal plane. Neuroforaminal stenosis grades were classified from 0 (no stenosis) to 3 (high grade stenosis).  Average neuroforaminal stenosis grades of both readers were significantly lower in standard compared to oblique sagittal images (p < 0.001). For 47.1 % of the cases, one or both readers reported a stenosis grade, which was at least 1 grade lower in standard compared to oblique sagittal images. There was also a significant difference when looking at patients who had neurological symptoms (p = 0.002) or underwent cervical spine surgery subsequently (p = 0.004). Interreader reliability, as measured by kappa value, and accordance rates were better for oblique sagittal images (0.94 vs. 0.88 and 99 % vs. 93 %).  Standard sagittal images tend to underestimate neuroforaminal stenosis grades compared to oblique sagittal images and are less reliable in the evaluation of disc herniations within the cervical spine MRI. In order to assess the potential therapeutic consequence, oblique images should therefore be considered as a valuable adjunct to the standard MRI protocol for patients with a radiculopathy.   · Neuroforaminal stenosis grades are underestimated in standard compared to oblique sagittal images. · Interreader reliability is higher for oblique sagittal images. · Oblique sagittal images should be performed in patients with a cervical radiculopathy. · Kintzele L, Rehnitz C, Kauczor H et

  19. Analytical and experimental validation of the Oblique Detonation Wave Engine concept

    NASA Technical Reports Server (NTRS)

    Adelman, Henry G.; Cambier, Jean-Luc; Menees, Gene P.; Balboni, John A.

    1988-01-01

    The Oblique Detonation Wave Engine (ODWE) for hypersonic flight has been analytically studied by NASA using the CFD codes which fully couple finite rate chemistry with fluid dynamics. Fuel injector designs investigated included wall and strut injectors, and the in-stream strut injectors were chosen to provide good mixing with minimal stagnation pressure losses. Plans for experimentally validating the ODWE concept in an arc-jet hypersonic wind tunnel are discussed. Measurements of the flow field properties behind the oblique wave will be compared to analytical predictions.

  20. Oblique rotaton in canonical correlation analysis reformulated as maximizing the generalized coefficient of determination.

    PubMed

    Satomura, Hironori; Adachi, Kohei

    2013-07-01

    To facilitate the interpretation of canonical correlation analysis (CCA) solutions, procedures have been proposed in which CCA solutions are orthogonally rotated to a simple structure. In this paper, we consider oblique rotation for CCA to provide solutions that are much easier to interpret, though only orthogonal rotation is allowed in the existing formulations of CCA. Our task is thus to reformulate CCA so that its solutions have the freedom of oblique rotation. Such a task can be achieved using Yanai's (Jpn. J. Behaviormetrics 1:46-54, 1974; J. Jpn. Stat. Soc. 11:43-53, 1981) generalized coefficient of determination for the objective function to be maximized in CCA. The resulting solutions are proved to include the existing orthogonal ones as special cases and to be rotated obliquely without affecting the objective function value, where ten Berge's (Psychometrika 48:519-523, 1983) theorems on suborthonormal matrices are used. A real data example demonstrates that the proposed oblique rotation can provide simple, easily interpreted CCA solutions.

  1. Constrained Least Squares Estimators of Oblique Common Factors.

    ERIC Educational Resources Information Center

    McDonald, Roderick P.

    1981-01-01

    An expression is given for weighted least squares estimators of oblique common factors of factor analyses, constrained to have the same covariance matrix as the factors they estimate. A proof of the uniqueness of the solution is given. (Author/JKS)

  2. Binary Classification using Decision Tree based Genetic Programming and Its Application to Analysis of Bio-mass Data

    NASA Astrophysics Data System (ADS)

    To, Cuong; Pham, Tuan D.

    2010-01-01

    In machine learning, pattern recognition may be the most popular task. "Similar" patterns identification is also very important in biology because first, it is useful for prediction of patterns associated with disease, for example cancer tissue (normal or tumor); second, similarity or dissimilarity of the kinetic patterns is used to identify coordinately controlled genes or proteins involved in the same regulatory process. Third, similar genes (proteins) share similar functions. In this paper, we present an algorithm which uses genetic programming to create decision tree for binary classification problem. The application of the algorithm was implemented on five real biological databases. Base on the results of comparisons with well-known methods, we see that the algorithm is outstanding in most of cases.

  3. Oblique view of arches and ironwork on south breezeway ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Oblique view of arches and ironwork on south breezeway - National Home for Disabled Volunteer Soldiers, Pacific Branch, Mental Health Buildings, 11301 Wilshire Boulevard, West Los Angeles, Los Angeles County, CA

  4. Design of orbital debris shields for oblique hypervelocity impact

    NASA Technical Reports Server (NTRS)

    Fahrenthold, Eric P.

    1994-01-01

    A new impact debris propagation code was written to link CTH simulations of space debris shield perforation to the Lagrangian finite element code DYNA3D, for space structure wall impact simulations. This software (DC3D) simulates debris cloud evolution using a nonlinear elastic-plastic deformable particle dynamics model, and renders computationally tractable the supercomputer simulation of oblique impacts on Whipple shield protected structures. Comparison of three dimensional, oblique impact simulations with experimental data shows good agreement over a range of velocities of interest in the design of orbital debris shielding. Source code developed during this research is provided on the enclosed floppy disk. An abstract based on the work described was submitted to the 1994 Hypervelocity Impact Symposium.

  5. Investigations of ionospheric sporadic Es layer using oblique sounding method

    NASA Astrophysics Data System (ADS)

    Minullin, R.

    The characteristics of Es layer have been studied using oblique sounding at 28 radiolines at the frequencies of 34 -- 73 MHz at the transmission paths 400 -- 1600 km long during 30 years. Reflections from Es layer with a few hours duration were observed. The amplitude of the reflected signal reached 1000 μ V with the registration threshold 0,1 μ V. The borderlines between reflected and scattered signals were observed as sharp curves in 60 -- 100 s range on the distributions of duration of reflected signals for decameter waves. The duration of continuous Es reflections were decreased upon amplification of oblique sounding frequency. The distributions of duration of reflected signals for meter waves showed sharp curves in the range 200 -- 300 s, representing borderlines between signals reflected from meteoric traces and from Es layer. The filling coefficient for the oblique sounding as well as the Es layer emersion probability for the vertical sounding were shown to undergo daily, seasonal and periodic variations. The daily variations of the filling coefficient of Es signals showed clear-cut maximums at 10 -- 12 and 18 -- 20 hours and minimum at 4 -- 6 hours at all paths in summer time and the maximum at 12 -- 14 hours in winter time. The values of the filling coefficient for Es layer declined with the increase of oblique sounding frequency. The minimal values of the filling coefficient were observed in winter and early spring, while the maximal values were observed from May to August. Provided that the averaged filling coefficient is equal to one in summer, it reaches the level 0,25 in equinox and does not exceed the level 0,12 in winter as evident by the of oblique sounding. The filling coefficient relation to the value of the voltage detection threshold was approximated by power-mode law. The filling coefficients for summer period showed exponential relation with equivalent sounding frequencies. The experimental evidence was generalized in an analytical model

  6. Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

    NASA Astrophysics Data System (ADS)

    Smith, R.; Kasprzyk, J. R.; Balaji, R.

    2017-12-01

    In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

  7. Building 1204, oblique view to east, 90 mm lens. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Building 1204, oblique view to east, 90 mm lens. - Travis Air Force Base, Squadron Operations & Readiness Crew Facility, W Street, Armed Forces Special Weapons Project Q Area, Fairfield, Solano County, CA

  8. Building 1204, oblique view to west, 135 mm lens. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Building 1204, oblique view to west, 135 mm lens. - Travis Air Force Base, Squadron Operations & Readiness Crew Facility, W Street, Armed Forces Special Weapons Project Q Area, Fairfield, Solano County, CA

  9. Oblique Photogrammetry and Usage on Land Administration

    NASA Astrophysics Data System (ADS)

    Kisa, A.; Ozmus, L.; Erkek, B.; Ates, H. B.; Bakici, S.

    2013-08-01

    Projects based on Geographic Information Systems (GIS) have started within the body of the General Directorate of Land Registry and Cadastre (GDLRC) by the Land Registry and Cadastre Information System (LRCIS) in the beginning of 2000s. LRCIS was followed by other projects which are Turkish National Geographic Information System (TNGIS), Continuously Operating GPS Reference Stations (CORS-TR), Geo Metadata Portal (GMP), Orthophoto Web Services, Completion of Initial Cadastre, Cadastre Renovation Project (CRP), 2B and Land Registry Achieve Information System (LRAIS). When examining the projects generated by GDLRC, it is realized that they include basic functions of land administration required for sustainable development. Sustainable development is obtained through effective land administration as is known. Nowadays, land use becomes more intense as a result of rapid population increase. The importance of land ownership has increased accordingly. At this point, the necessity of cadastre appears. In Turkey, cadastral registration is carried out by the detection of parcels. In other words, it is obtained through the division of land surface into 2D boundaries and mapping of them. However, existing land administration systems have begun to lose their efficiency while coping with rights, restrictions and responsibilities (RRRs) belonging to land which become more complicated day by day. Overlapping and interlocking constructions appear particularly in urban areas with dense housing and consequently, the problem of how to project these structures onto the surface in 2D cadastral systems has arisen. Herein, the necessity of 3D cadastre concept and 3D property data is confronted. In recent years, oblique photogrammetry, whose applications are gradually spreading, is used as an effective method for producing 3D data. In this study, applications of oblique photogrammetry and usability of oblique images as base for 3D Cadastre and Land Administration projects are examined.

  10. Mean flow characteristics for the oblique impingement of an axisymmetric jet

    NASA Technical Reports Server (NTRS)

    Foss, J. F.; Kleis, S. J.

    1975-01-01

    The oblique impingement of an axisymmetric jet has been investigated. A summary of the data and the analytical interpretations of the dominant mechanisms which influence the flow are reported. The major characteristics of the shallow angle oblique jet impingement flow field are: (1) minimal dynamic spreading as revealed by the surface pressure field, (2) pronounced kinematic spreading as revealed by the jet flow velocity field, (3) a pronounced upstream shift of the stagnation point from the maximum pressure point, (4) the production of streamwise vorticity by the impingement process.

  11. Predicting skin sensitisation using a decision tree integrated testing strategy with an in silico model and in chemico/in vitro assays.

    PubMed

    Macmillan, Donna S; Canipa, Steven J; Chilton, Martyn L; Williams, Richard V; Barber, Christopher G

    2016-04-01

    There is a pressing need for non-animal methods to predict skin sensitisation potential and a number of in chemico and in vitro assays have been designed with this in mind. However, some compounds can fall outside the applicability domain of these in chemico/in vitro assays and may not be predicted accurately. Rule-based in silico models such as Derek Nexus are expert-derived from animal and/or human data and the mechanism-based alert domain can take a number of factors into account (e.g. abiotic/biotic activation). Therefore, Derek Nexus may be able to predict for compounds outside the applicability domain of in chemico/in vitro assays. To this end, an integrated testing strategy (ITS) decision tree using Derek Nexus and a maximum of two assays (from DPRA, KeratinoSens, LuSens, h-CLAT and U-SENS) was developed. Generally, the decision tree improved upon other ITS evaluated in this study with positive and negative predictivity calculated as 86% and 81%, respectively. Our results demonstrate that an ITS using an in silico model such as Derek Nexus with a maximum of two in chemico/in vitro assays can predict the sensitising potential of a number of chemicals, including those outside the applicability domain of existing non-animal assays. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Obliquity Driven Climate Change in Mars' Recent Past

    NASA Technical Reports Server (NTRS)

    Haberle, R. M.; Montmessin, F.; Forget, F.; Spiga, A.; Colaprete, A.

    2003-01-01

    Mars has a natural mechanism for experiencing significant climate change and redistributing surface ice. Obliquity changes alone are quite capable of moving ice into low latitudes and may provide an explanation for the many geological landforms that strongly indicate recent climate change.

  13. The Computation of Orthogonal Independent Cluster Solutions and Their Oblique Analogs in Factor Analysis.

    ERIC Educational Resources Information Center

    Hofmann, Richard J.

    A very general model for the computation of independent cluster solutions in factor analysis is presented. The model is discussed as being either orthogonal or oblique. Furthermore, it is demonstrated that for every orthogonal independent cluster solution there is an oblique analog. Using three illustrative examples, certain generalities are made…

  14. Collisionless kinetic theory of oblique tearing instabilities

    NASA Astrophysics Data System (ADS)

    Baalrud, S. D.; Bhattacharjee, A.; Daughton, W.

    2018-02-01

    The linear dispersion relation for collisionless kinetic tearing instabilities is calculated for the Harris equilibrium. In contrast to the conventional 2D geometry, which considers only modes at the center of the current sheet, modes can span the current sheet in 3D. Modes at each resonant surface have a unique angle with respect to the guide field direction. Both kinetic simulations and numerical eigenmode solutions of the linearized Vlasov-Maxwell equations have recently revealed that standard analytic theories vastly overestimate the growth rate of oblique modes. We find that this stabilization is associated with the density-gradient-driven diamagnetic drift. The analytic theories miss this drift stabilization because the inner tearing layer broadens at oblique angles sufficiently far that the assumption of scale separation between the inner and outer regions of boundary-layer theory breaks down. The dispersion relation obtained by numerically solving a single second order differential equation is found to approximately capture the drift stabilization predicted by solutions of the full integro-differential eigenvalue problem. A simple analytic estimate for the stability criterion is provided.

  15. Comments on the Parameters and Processes that Affect the Preservation Potential and Style of Oblique-Divergent Plate Boundaries

    NASA Astrophysics Data System (ADS)

    Umhoefer, P. J.

    2014-12-01

    Oblique-divergent or transtensional zones present particular challenges in ancient belts because of the poor preservation potential of the thinned continental crust and young oceanic crust. Many oblique belts will preferentially preserve their boundary zones that lie within continents rather than the main plate boundary zone, which will be at a much lower elevation and composed of denser crust. Zones of tectonic escape or strike-slip overprinting of arcs or plateaus deform continental crust and may be better preserved. Here I highlight parameters and processes that have major effects on oblique divergent belts. Strain partitioning is common, but not ubiquitous, along and across oblique boundaries; the causes of partitioning are not always clear and make this especially vexing for work in ancient belts. Partitioning causes complexity in the patterns of structures at all scales. Inherited structures commonly determine the orientation and style of structures along oblique boundaries and can control the pattern of faults across transtensional belts. Regionally, inherited trends of arcs or other 1000-km-scale features can control boundary structures. Experiments and natural examples suggest that oblique boundary zones contain less of a record of strike-slip faulting and more extensional structures. The obliquity of divergence produces predictable families of structures that typify (i) strike-slip dominated zones (obliquity <~20°), (ii) mixed zones (~20° - ~35°), and (iii) extension dominated zones (>~35°). The combination of partitioning and mixed structures in oblique zones means that the boundaries of belts with large-magnitude strike-slip faulting will commonly preserve little of no record of that faulting history. Plate boundaries localize strain onto the main plate boundary structures from the broader plate boundary and therefore the boundary zones commonly preserve the earlier structures more than later structures, a major problem in interpreting ancient belts

  16. Building 931, oblique view to northwest, 210 mm lens. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Building 931, oblique view to northwest, 210 mm lens. - Travis Air Force Base, Central Battery Charging Building, North of W Street, Armed Forces Special Weapons Project Q Area, Fairfield, Solano County, CA

  17. Building 931, oblique view to southeast, 135 mm lens. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Building 931, oblique view to southeast, 135 mm lens. - Travis Air Force Base, Central Battery Charging Building, North of W Street, Armed Forces Special Weapons Project Q Area, Fairfield, Solano County, CA

  18. The Resilience of Kepler Systems to Stellar Obliquity

    NASA Astrophysics Data System (ADS)

    Spalding, Christopher; Marx, Noah W.; Batygin, Konstantin

    2018-04-01

    The Kepler mission and its successor K2 have brought forth a cascade of transiting planets. Many of these planetary systems exhibit multiple members, but a large fraction possess only a single transiting example. This overabundance of singles has led to the suggestion that up to half of Kepler systems might possess significant mutual inclinations between orbits, reducing the transiting number (the so-called “Kepler Dichotomy”). In a recent paper, Spalding & Batygin demonstrated that the quadrupole moment arising from a young, oblate star is capable of misaligning the constituent orbits of a close-in planetary system enough to reduce their transit number, provided that the stellar spin axis is sufficiently misaligned with respect to the planetary orbital plane. Moreover, tightly packed planetary systems were shown to be susceptible to becoming destabilized during this process. Here, we investigate the ubiquity of the stellar obliquity-driven instability within systems with a range of multiplicities. We find that most planetary systems analyzed, including those possessing only two planets, underwent instability for stellar spin periods below ∼3 days and stellar tilts of order 30°. Moreover, we are able to place upper limits on the stellar obliquity in systems such as K2-38 (obliquity ≲20°), where other methods of measuring the spin–orbit misalignment are not currently available. Given the known parameters of T-Tauri stars, we predict that up to one-half of super-Earth-mass systems may encounter the instability, in general agreement with the fraction typically proposed to explain the observed abundance of single-transiting systems.

  19. Building 904, oblique view to southeast, 135 mm lens. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Building 904, oblique view to southeast, 135 mm lens. - Travis Air Force Base, Base Spares Warehouse No. 1, Dixon Avenue & W Street, Armed Forces Special Weapons Project Q Area, Fairfield, Solano County, CA

  20. Building 904, oblique view to northwest, 135 mm lens ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Building 904, oblique view to northwest, 135 mm lens - Travis Air Force Base, Base Spares Warehouse No. 1, Dixon Avenue & W Street, Armed Forces Special Weapons Project Q Area, Fairfield, Solano County, CA

  1. Oblique patterned etching of vertical silicon sidewalls

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Burckel, D. Bruce; Finnegan, Patrick S.; Henry, M. David

    A method for patterning on vertical silicon surfaces in high aspect ratio silicontopography is presented. A Faraday cage is used to direct energetic reactive ions obliquely through a patterned suspended membrane positioned over the topography. The technique is capable of forming high-fidelity pattern (100 nm) features, adding an additional fabrication capability to standard top-down fabrication approaches.

  2. Oblique patterned etching of vertical silicon sidewalls

    NASA Astrophysics Data System (ADS)

    Bruce Burckel, D.; Finnegan, Patrick S.; David Henry, M.; Resnick, Paul J.; Jarecki, Robert L.

    2016-04-01

    A method for patterning on vertical silicon surfaces in high aspect ratio silicon topography is presented. A Faraday cage is used to direct energetic reactive ions obliquely through a patterned suspended membrane positioned over the topography. The technique is capable of forming high-fidelity pattern (100 nm) features, adding an additional fabrication capability to standard top-down fabrication approaches.

  3. Oblique patterned etching of vertical silicon sidewalls

    DOE PAGES

    Burckel, D. Bruce; Finnegan, Patrick S.; Henry, M. David; ...

    2016-04-05

    A method for patterning on vertical silicon surfaces in high aspect ratio silicontopography is presented. A Faraday cage is used to direct energetic reactive ions obliquely through a patterned suspended membrane positioned over the topography. The technique is capable of forming high-fidelity pattern (100 nm) features, adding an additional fabrication capability to standard top-down fabrication approaches.

  4. A parallel decision tree-based method for user authentication based on keystroke patterns.

    PubMed

    Sheng, Yong; Phoha, Vir V; Rovnyak, Steven M

    2005-08-01

    We propose a Monte Carlo approach to attain sufficient training data, a splitting method to improve effectiveness, and a system composed of parallel decision trees (DTs) to authenticate users based on keystroke patterns. For each user, approximately 19 times as much simulated data was generated to complement the 387 vectors of raw data. The training set, including raw and simulated data, is split into four subsets. For each subset, wavelet transforms are performed to obtain a total of eight training subsets for each user. Eight DTs are thus trained using the eight subsets. A parallel DT is constructed for each user, which contains all eight DTs with a criterion for its output that it authenticates the user if at least three DTs do so; otherwise it rejects the user. Training and testing data were collected from 43 users who typed the exact same string of length 37 nine consecutive times to provide data for training purposes. The users typed the same string at various times over a period from November through December 2002 to provide test data. The average false reject rate was 9.62% and the average false accept rate was 0.88%.

  5. A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization

    PubMed Central

    Sánchez-Rodríguez, David; Hernández-Morera, Pablo; Quinteiro, José Ma.; Alonso-González, Itziar

    2015-01-01

    Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have. PMID:26110413

  6. Integrated Aerodynamic and Control System Design of Oblique Wing Aircraft. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Morris, Stephen James

    1990-01-01

    An efficient high speed aircraft design must achieve a high lift to drag ratio at transonic and supersonic speeds. In 1952 Dr. R. T. Jones proved that for any flight Mach number minimum drag at a fixed lift is achieved by an elliptic wing planform with an appropriate oblique sweep angle. Since then, wind tunnel tests and numerical flow models have confirmed that the compressibility drag of oblique wing aircraft is lower than similar symmetrical sweep designs. At oblique sweep angles above thirty degrees the highly asymmetric planform gives rise to aerodynamic and inertia couplings which affect stability and degrade the aircraft's handling qualities. In the case of the NASA-Rockwell Oblique Wing Research Aircraft, attempts to improve the handling qualities by implementing a stability augmentation system have produced unsatisfactory results because of an inherent lack of controllability in the proposed design. The present work focuses on improving the handling qualities of oblique wing aircraft by including aerodynamic configuration parameters as variables in the control system synthesis to provide additional degrees of freedom with which to further decouple the aircraft's response. Handling qualities are measured using a quadratic cost function identical to that considered in optimal control problems, but the controller architecture is not restricted to full state feedback. An optimization procedure is used to simultaneously solve for the aircraft configuration and control gains which maximize a handling qualities measure, while meeting imposed constraints on trim. In some designs wing flexibility is also modeled and reduced order controllers are implemented. Oblique wing aircraft synthesized by this integrated design method show significant improvement in handling qualities when compared to the originally proposed closed loop aircraft. The integrated design synthesis method is then extended to show how handling qualities may be traded for other types of mission

  7. Voxel-based plaque classification in coronary intravascular optical coherence tomography images using decision trees

    NASA Astrophysics Data System (ADS)

    Kolluru, Chaitanya; Prabhu, David; Gharaibeh, Yazan; Wu, Hao; Wilson, David L.

    2018-02-01

    Intravascular Optical Coherence Tomography (IVOCT) is a high contrast, 3D microscopic imaging technique that can be used to assess atherosclerosis and guide stent interventions. Despite its advantages, IVOCT image interpretation is challenging and time consuming with over 500 image frames generated in a single pullback volume. We have developed a method to classify voxel plaque types in IVOCT images using machine learning. To train and test the classifier, we have used our unique database of labeled cadaver vessel IVOCT images accurately registered to gold standard cryoimages. This database currently contains 300 images and is growing. Each voxel is labeled as fibrotic, lipid-rich, calcified or other. Optical attenuation, intensity and texture features were extracted for each voxel and were used to build a decision tree classifier for multi-class classification. Five-fold cross-validation across images gave accuracies of 96 % +/- 0.01 %, 90 +/- 0.02% and 90 % +/- 0.01 % for fibrotic, lipid-rich and calcified classes respectively. To rectify performance degradation seen in left out vessel specimens as opposed to left out images, we are adding data and reducing features to limit overfitting. Following spatial noise cleaning, important vascular regions were unambiguous in display. We developed displays that enable physicians to make rapid determination of calcified and lipid regions. This will inform treatment decisions such as the need for devices (e.g., atherectomy or scoring balloon in the case of calcifications) or extended stent lengths to ensure coverage of lipid regions prone to injury at the edge of a stent.

  8. Comparative analysis of tree classification models for detecting fusarium oxysporum f. sp cubense (TR4) based on multi soil sensor parameters

    NASA Astrophysics Data System (ADS)

    Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica

    2017-09-01

    Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.

  9. A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

    NASA Astrophysics Data System (ADS)

    Khader, A.; Rosenberg, D.; McKee, M.

    2012-12-01

    Nitrate pollution poses a health risk for infants whose freshwater drinking source is groundwater. This risk creates a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision maker and the expected outcomes from these alternatives. The alternatives include: (i) ignore the health risk of nitrate contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, pollution transport processes, and climate (Khader and McKee, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine where methemoglobinemia is the main health problem associated with the principal pollutant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not-use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs include healthcare for methemoglobinemia, purchase of bottled water, and installation and maintenance of the groundwater monitoring system. At current

  10. Document segmentation via oblique cuts

    NASA Astrophysics Data System (ADS)

    Svendsen, Jeremy; Branzan-Albu, Alexandra

    2013-01-01

    This paper presents a novel solution for the layout segmentation of graphical elements in Business Intelligence documents. We propose a generalization of the recursive X-Y cut algorithm, which allows for cutting along arbitrary oblique directions. An intermediate processing step consisting of line and solid region removal is also necessary due to presence of decorative elements. The output of the proposed segmentation is a hierarchical structure which allows for the identification of primitives in pie and bar charts. The algorithm was tested on a database composed of charts from business documents. Results are very promising.

  11. Analytical and experimental investigations of the oblique detonation wave engine concept

    NASA Technical Reports Server (NTRS)

    Menees, Gene P.; Adelman, Henry G.; Cambier, Jean-Luc

    1990-01-01

    Wave combustors, which include the oblique detonation wave engine (ODWE), are attractive propulsion concepts for hypersonic flight. These engines utilize oblique shock or detonation waves to rapidly mix, ignite, and combust the air-fuel mixture in thin zones in the combustion chamber. Benefits of these combustion systems include shorter and lighter engines which require less cooling and can provide thrust at higher Mach numbers than conventional scramjets. The wave combustor's ability to operate at lower combustor inlet pressures may allow the vehicle to operate at lower dynamic pressures which could lessen the heating loads on the airframe. The research program at NASA-Ames includes analytical studies of the ODWE combustor using Computational Fluid Dynamics (CFD) codes which fully couple finite rate chemistry with fluid dynamics. In addition, experimental proof-of-concept studies are being performed in an arc heated hypersonic wind tunnel. Several fuel injection design were studied analytically and experimentally. In-stream strut fuel injectors were chosen to provide good mixing with minimal stagnation pressure losses. Measurements of flow field properties behind the oblique wave are compared to analytical predictions.

  12. Analytical and experimental investigations of the oblique detonation wave engine concept

    NASA Technical Reports Server (NTRS)

    Menees, Gene P.; Adelman, Henry G.; Cambier, Jean-Luc

    1991-01-01

    Wave combustors, which include the Oblique Detonation Wave Engine (ODWE), are attractive propulsion concepts for hypersonic flight. These engines utilize oblique shock or detonation waves to rapidly mix, ignite, and combust the air-fuel mixture in thin zones in the combustion chamber. Benefits of these combustion systems include shorter and lighter engines which will require less cooling and can provide thrust at higher Mach numbers than conventional scramjets. The wave combustor's ability to operate at lower combustor inlet pressures may allow the vehicle to operate at lower dynamic pressures which could lessen the heating loads on the airframe. The research program at NASA-Ames includes analytical studies of the ODWE combustor using CFD codes which fully couple finite rate chemistry with fluid dynamics. In addition, experimental proof-of-concept studies are being carried out in an arc heated hypersonic wind tunnel. Several fuel injection designs were studied analytically and experimentally. In-stream strut fuel injectors were chosen to provide good mixing with minimal stagnation pressure losses. Measurements of flow field properties behind the oblique wave are compared to analytical predictions.

  13. 3D dynamics of crustal deformation driven by oblique subduction: Northern and Central Andes

    NASA Astrophysics Data System (ADS)

    Schütt, Jorina M.; Whipp, David M., Jr.

    2017-04-01

    The geometry and relative motion of colliding plates will affect how and where they deform. In oblique subduction systems, factors such as the dip angle of the subducting plate and the convergence obliquity, as well as the presence of weak zones in the overriding plate, all influence how oblique convergence is partitioned onto various fault systems in the overriding plate. The partitioning of strain into margin-normal slip on the plate-bounding fault and horizontal shearing on a strike-slip system parallel to the margin is mainly controlled by the margin-parallel shear forces acting on the plate interface and the strength of the continental crust. While these plate interface forces are influenced by the dip angle of the subducting plate (i.e., the length of plate interface in the frictional domain) and the obliquity angle between the normal to the plate margin and the plate convergence vector, the strength of the continental crust in the upper plate is strongly affected by the presence or absence of weak zones such as regions of arc volcanism, pre-existing fault systems, or boundaries of stronger crustal blocks. In order to investigate which of these factors are most important in controlling how the overriding continental plate deforms, we compare results of lithospheric-scale 3D numerical geodynamic experiments from two regions in the north-central Andes: the Northern Volcanic Zone (NVZ; 5°N - 3°S) and adjacent Peruvian Flat Slab Segment (PFSS; 3°S -14°S). The NVZ is characterized by a 35° subduction dip angle with an obliquity angle of about 40°, extensive volcanism and significant strain partitioning in the continental crust. In contrast, the PFSS is characterized by flat subduction (the slab flattens beneath the continent at around 100 km depth for several hundred kilometers), an obliquity angle of about 20°, no volcanism and minimal strain partitioning. The plate geometry and convergence obliquity for these regions are incorporated in 3D (1600 x 1600 x

  14. Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty.

    PubMed

    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.

  15. Design of Human-Machine Interface and altering of pelvic obliquity with RGR Trainer.

    PubMed

    Pietrusinski, Maciej; Unluhisarcikli, Ozer; Mavroidis, Constantinos; Cajigas, Iahn; Bonato, Paolo

    2011-01-01

    The Robotic Gait Rehabilitation (RGR) Trainer targets secondary gait deviations in stroke survivors undergoing rehabilitation. Using an impedance control strategy and a linear electromagnetic actuator, the device generates a force field to control pelvic obliquity through a Human-Machine Interface (i.e. a lower body exoskeleton). Herein we describe the design of the RGR Trainer Human-Machine Interface (HMI) and we demonstrate the system's ability to alter the pattern of movement of the pelvis during gait in a healthy subject. Results are shown for experiments during which we induced hip-hiking - in healthy subjects. Our findings indicate that the RGR Trainer has the ability of affecting pelvic obliquity during gait. Furthermore, we provide preliminary evidence of short-term retention of the modified pelvic obliquity pattern induced by the RGR Trainer. © 2011 IEEE

  16. Effects of varying obliquity on Martian sublimation thermokarst landforms

    USGS Publications Warehouse

    Dundas, Colin M.

    2017-01-01

    Scalloped depressions in the Martian mid-latitudes are likely formed by sublimation of ice-rich ground. The stability of subsurface ice changes with the planetary obliquity, generally becoming less stable at lower axial tilt. As a result, the relative rates of sublimation and creep change over time. A landscape evolution model shows that these variations produce internal structure in scalloped depressions, commonly in the form of arcuate ridges, which emerge as depressions resume growth after pausing or slowing. In other scenarios, the formation of internal structure is minimal. Significant uncertainties in past climate and model parameters permit a range of scenarios. Ridges observed in some Martian scalloped depressions could date from obliquity lows or periods of low ice stability occurring <5 Ma, suggesting that the pits are young features and may be actively evolving.

  17. A two-fluid study of oblique tearing modes in a force-free current sheet

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Akçay, Cihan, E-mail: akcay@lanl.gov; Daughton, William; Lukin, Vyacheslav S.

    2016-01-15

    Kinetic simulations have demonstrated that three-dimensional reconnection in collisionless regimes proceeds through the formation and interaction of magnetic flux ropes, which are generated due to the growth of tearing instabilities at multiple resonance surfaces. Since kinetic simulations are intrinsically expensive, it is desirable to explore the feasibility of reduced two-fluid models to capture this complex evolution, particularly, in the strong guide field regime, where two-fluid models are better justified. With this goal in mind, this paper compares the evolution of the collisionless tearing instability in a force-free current sheet with a two-fluid model and fully kinetic simulations. Our results indicatemore » that the most unstable modes are oblique for guide fields larger than the reconnecting field, in agreement with the kinetic results. The standard two-fluid tearing theory is extended to address the tearing instability at oblique angles. The resulting theory yields a flat oblique spectrum and underestimates the growth of oblique modes in a similar manner to kinetic theory relative to kinetic simulations.« less

  18. A two-fluid study of oblique tearing modes in a force-free current sheet

    DOE PAGES

    Akçay, Cihan; Daughton, William; Lukin, Vyacheslav S.; ...

    2016-01-01

    Kinetic simulations have demonstrated that three-dimensional reconnection in collisionless regimes proceeds through the formation and interaction of magnetic flux ropes, which are generated due to the growth of tearing instabilities at multiple resonance surfaces. Because kinetic simulations are intrinsically expensive, it is desirable to explore the feasibility of reduced two-fluid models to capture this complex evolution, particularly, in the strong guide field regime, where two-fluid models are better justified. With this goal in mind, this paper compares the evolution of the collisionless tearing instability in a force-free current sheet with a two-fluid model and fully kinetic simulations. Our results indicatemore » that the most unstable modes are oblique for guide fields larger than the reconnecting field, in agreement with the kinetic results. The standard two-fluid tearing theory is extended to address the tearing instability at oblique angles. As a results this theory yields a flat oblique spectrum and underestimates the growth of oblique modes in a similar manner to kinetic theory relative to kinetic simulations.« less

  19. Oblique Wing Research Aircraft on ramp

    NASA Image and Video Library

    1976-08-02

    This 1976 photograph of the Oblique Wing Research Aircraft was taken in front of the NASA Flight Research Center hangar, located at Edwards Air Force Base, California. In the photograph the noseboom, pitot-static probe, and angles-of-attack and sideslip flow vanes(covered-up) are attached to the front of the vehicle. The clear nose dome for the television camera, and the shrouded propellor for the 90 horsepower engine are clearly seen.

  20. Goal Programming: A New Tool for the Christmas Tree Industry

    Treesearch

    Bruce G. Hansen

    1977-01-01

    Goal programing (GP) can be useful for decision making in the natural Christmas tree industry. Its usefulness is demonstrated through an analysis of a hypothetical problem in which two potential growers decide how to use 10 acres in growing Christmas trees. Though the physical settings are identical, distinct differences between their goals significantly influence the...