Search results for " Classification"
showing 10 items of 1043 documents
Site quality evaluation by classification tree: an application to cork quality in Sardinia
2005
Cork harvesting and stopper production represent a major forest industry in Sardinia (Italy). The target of the present investigation was to evaluate the ‘‘classification tree’’ as a tool to discover possible relationships between microsite characteristics and cork quality. Seven main cork oak (Quercus suber) producing areas have been identified in Sardinia, for a total of more than 122,000 ha. Sixty-three sample trees, distributed among different geographical locations and microsite conditions, were selected. A soil profile near each sample tree was described, soil samples were collected and analysed. After debarking, cork quality of each sample tree was graded by an independent panel of e…
Steppes of Southern Siberia - Experiences from the 6th EDGG Research Expedition to Khakassia, Russia (22 July – 1 August 2013)
2013
The 6th EDGG Research Expedition took place in summer 2013 in the Kuznetsky Alatau Mountains, part of the Altai-Sayanian mountain region (Republic of Khakassia, Russia). A group of 14 scientists from seven countries studied the variety of steppe vegetation in two regions of the "Khakassky" Reserve – Lake Itkul (Shira region) and Podzaploty (Ordzhenikidzevsky region). Standardised sampling procedures including nested-plot series and phytosociological relevés of 10-m2 plots were used to sample steppes of European-Siberian (Festuco-Brometea) and Central Asian (Cleistogenetea squarrosae) types. All terricolous plants present in the plots were sampled, including perennial and annual vascular pla…
Classification of stilbenoid compounds by entropy of artificial intelligence
2013
A set of 66 stilbenoid compounds is classified into a system of periodic properties by using a procedure based on artificial intelligence, information entropy theory. Eight characteristics in hierarchical order are used to classify structurally the stilbenoids. The former five features mark the group or column while the latter three are used to indicate the row or period in the table of periodic classification. Those stilbenoids in the same group are suggested to present similar properties. Furthermore, compounds also in the same period will show maximum resemblance. In this report, the stilbenoids in the table are related to experimental data of bioactivity and antioxidant properties avail…
Multiple Classifiers and Data Fusion for Robust Diagnosis of Gearbox Mixed Faults
2019
Detection and isolation of single and mixed faults in a gearbox are very important to enhance the system reliability, lifetime, and service availability. This paper proposes a hybrid learning algorithm, consisting of multilayer perceptron (MLP)- and convolutional neural network (CNN)-based classifiers, for diagnosis of gearbox mixed faults. Domain knowledge features are required to train the MLP classifier, while the CNN classifier can learn features itself, allowing to reduce the required knowledge features for the counterpart. Vibration data from an experimental setup with gearbox mixed faults is used to validate the effectiveness of the algorithms and compare them with conventional metho…
A one class classifier for Signal identification: a biological case study
2008
The paper describes an application of a one-class KNN to identify different signal patterns embedded in a noise structured background. The problem become harder whenever only one pattern is well represented in the signal, in such cases one class classifier techniques are more indicated. The classification phase is applied after a preprocessing phase based on a Multi Layer Model (MLM) that provides a preliminary signal segmentation in an interval feature space. The one-class KNN has been tested on synthetic data that simulate microarray data for the identification of nucleosomes and linker regions across DNA. Results have shown a good recognition rate on synthetic data for nucleosome and lin…
Automated quality control of next generation sequencing data using machine learning
2019
AbstractControlling quality of next generation sequencing (NGS) data files is a necessary but complex task. To address this problem, we statistically characterized common NGS quality features and developed a novel quality control procedure involving tree-based and deep learning classification algorithms. Predictive models, validated on internal data and external disease diagnostic datasets, are to some extent generalizable to data from unseen species. The derived statistical guidelines and predictive models represent a valuable resource for users of NGS data to better understand quality issues and perform automatic quality control. Our guidelines and software are available at the following …
Do Firms Share the Same Functional Form of Their Growth Rate Distribution? A New Statistical Test
2011
We propose a hypothesis testing procedure to investigate whether the same growth rate distribution is shared by all the firms in a balanced panel or, more generally, whether they share the same functional form for this distribution, without necessarily sharing the same parameters. We apply the test to panels of US and European Union publicly quoted manufacturing firms, both at the sectoral and at the subsectoral NAICS levels. We consider the following null hypotheses about the growth rate distribution of the individual firms: i) an unknown shape common to all firms, with all the firms sharing also the same parameters, or with the firm variance related to its firm size through a scaling rela…
Unsupervised clustering method for pattern recognition in IIF images
2017
Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns and fluorescence intensity. We propose here a method to automatically classify the centromere pattern based on the grouping of centromeres on the cells through a clustering K-means algorithm. The described method was tested on a public database (MIVIA). The results of the test showed an Accuracy…
Soil interpretation in the context of anthropedogenic transformations and pedotechniques application
2018
Abstract Following a long and vigorous study carried out by the International Committee on Anthropogenic Soils (ICOMANTH), the Soil Taxonomy (ST) classification system recently incorporated a number of changes to include Human-Altered and Human-Transported soils, generally called anthropogenic soils. These changes underwent careful scrutiny as they affect the current classification of existing soil series, and as the proposals and logics are as yet untested against existing data and descriptions. Particular attention was given to the diagnostic characteristics of the anthropogenic soils and to the Subgroups for Human-Altered and Human-Transported soils. In this study, we consider a frequent…
Modeling of 137Cs migration in soils using an 80-year soil archive: role of fertilizers and agricultural amendments
2008
An 80-year soil archive, the 42-plot experimental design at the INRA in Versailles (France), is used here to study long-term contamination by 137Cs atmospheric deposition and the fate of this radioisotope when associated with various agricultural practices: fallow land, KCl, NH4(NO3), superphosphate fertilizers, horse manure and lime amendments. The pertinence of a simple box model, where radiocaesium is supposed to move downward by convectional mechanisms, is checked using samples from control plots which had been neither amended, nor cultivated since 1928. This simple model presents the advantage of depending on only two parameters: α, a proportional factor allowing the historical atmosph…