Fruit detection with binary partition trees (İkili bölüntü ağaçları ile meyve tespiti)

In this study, binary partition trees are applied to the problem of fruit detection. The fact that binary partition trees are inherently unbiased and independent of flatzones is the main reason for this application. Using only circularity from the shape priors, this system is put to test with 39 images of three classes of fruits and the test results show an average of 0.669 precision and 0.851 recall

A Phylogenetic Analysis of the Genus Fragaria (Strawberry) Using Intron-Containing Sequence from the ADH-1 Gene

The genus Fragaria encompasses species at ploidy levels ranging from diploid to decaploid. The cultivated strawberry, Fragaria×ananassa, and its two immediate progenitors, F. chiloensis and F. virginiana, are octoploids. To elucidate the ancestries of these octoploid species, we performed a phylogenetic analysis using intron-containing sequences of the nuclear ADH-1 gene from 39 germplasm accessions representing nineteen Fragaria species and one outgroup species, Dasiphora fruticosa. All trees from Maximum Parsimony and Maximum Likelihood analyses showed two major clades, Clade A and Clade B. Each of the sampled octoploids contributed alleles to both major clades. All octoploid-derived alleles in Clade A clustered with alleles of diploid F. vesca, with the exception of one octoploid allele that clustered with the alleles of diploid F. mandshurica. All octoploid-derived alleles in clade B clustered with the alleles of only one diploid species, F. iinumae. When gaps encoded as binary characters were included in the Maximum Parsimony analysis, tree resolution was improved with the addition of six nodes, and the bootstrap support was generally higher, rising above the 50% threshold for an additional nine branches. These results, coupled with the congruence of the sequence data and the coded gap data, validate and encourage the employment of sequence sets containing gaps for phylogenetic analysis. Our phylogenetic conclusions, based upon sequence data from the ADH-1 gene located on F. vesca linkage group II, complement and generally agree with those obtained from analyses of protein-encoding genes GBSSI-2 and DHAR located on F. vesca linkage groups V and VII, respectively, but differ from a previous study that utilized rDNA sequences and did not detect the ancestral role of F. iinumae

Decision trees in epidemiological research

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

Partial least squares discriminant analysis: A dimensionality reduction method to classify hyperspectral data

The recent development of more sophisticated spectroscopic methods allows acquisition of high dimensional datasets from which valuable information may be extracted using multivariate statistical analyses, such as dimensionality reduction and automatic classification (supervised and unsupervised). In this work, a supervised classification through a partial least squares discriminant analysis (PLS-DA) is performed on the hy- perspectral data. The obtained results are compared with those obtained by the most commonly used classification approaches

Partial least squares discriminant analysis: A dimensionality reduction method to classify hyperspectral data

The recent development of more sophisticated spectroscopic methods allows acqui- sition of high dimensional datasets from which valuable information may be extracted using multivariate statistical analyses, such as dimensionality reduction and automatic classification (supervised and unsupervised). In this work, a supervised classification through a partial least squares discriminant analysis (PLS-DA) is performed on the hy- perspectral data. The obtained results are compared with those obtained by the most commonly used classification approaches

W(h)ither Fossils? Studying Morphological Character Evolution in the Age of Molecular Sequences

A major challenge in the post-genomics era will be to integrate molecular sequence data from extant organisms with morphological data from fossil and extant taxa into a single, coherent picture of phylogenetic relationships; only then will these phylogenetic hypotheses be effectively applied to the study of morphological character evolution. At least two analytical approaches to solving this problem have been utilized: (1) simultaneous analysis of molecular sequence and morphological data with fossil taxa included as terminals in the analysis, and (2) the molecular scaffold approach, in which morphological data are analyzed over a molecular backbone (with constraints that force extant taxa into positions suggested by sequence data). The perceived obstacles to including fossil taxa directly in simultaneous analyses of morphological and molecular sequence data with extant taxa include: (1) that fossil taxa are missing the molecular sequence portion of the character data; (2) that morphological characters might be misleading due to convergence; and (3) character weighting, specifically how and whether to weight characters in the morphological partition relative to characters in the molecular sequence data partition. The molecular scaffold has been put forward as a potential solution to at least some of these problems. Using examples of simultaneous analyses from the literature, as well as new analyses of previously published morphological and molecular sequence data matrices for extant and fossil Chiroptera (bats), we argue that the simultaneous analysis approach is superior to the molecular scaffold approach, specifically addressing the problems to which the molecular scaffold has been suggested as a solution. Finally, the application of phylogenetic hypotheses including fossil taxa (whatever their derivation) to the study of morphological character evolution is discussed, with special emphasis on scenarios in which fossil taxa are likely to be most enlightening: (1) in determining the sequence of character evolution; (2) in determining the timing of character evolution; and (3) in making inferences about the presence or absence of characteristics in fossil taxa that may not be directly observable in the fossil record. Published By: Missouri Botanical Garde

The topological complexity of pure graph braid groups is stably maximal

We prove Farber's conjecture on the stable topological complexity of configuration spaces of graphs. The conjecture follows from a general lower bound derived from recent insights into the topological complexity of aspherical spaces. Our arguments apply equally to higher topological complexity.Comment: 9 pages. Minor changes. To appear in Forum of Mathematics, Sigma. May differ slightly from published versio